You searched for subject:(Data assimilation).
Showing records 1 – 30 of
458 total matches.
◁ [1] [2] [3] [4] [5] … [16] ▶
1.
Luo, Yawei.
A Data Assimilating Model of the Microbial Ecosystem in the
Open Ocean.
Degree: PhD, Division of Biology and Medicine. Ecological and
Evolutionary Biology, 2009, Brown University
URL: https://repository.library.brown.edu/studio/item/bdr:192/ 
► Prokaryotic microbes, commonly termed bacteria, are essential components of the ecosystem in the open ocean. They are major primary producers, major diazotrophs that fix dinitrogen…
(more)
▼ Prokaryotic microbes, commonly termed bacteria, are
essential components of the ecosystem in the open ocean. They are
major primary producers, major diazotrophs that fix dinitrogen (N2)
into new bio-available nitrogen, and are major consumers of
dissolved organic matter (DOM). An ocean ecosystem model was
constructed for the open ocean focusing on bacterial dynamics. A
data assimilation technology was adapted to integrate the model
with observations by objectively optimizing model parameters and
minimizing the differences between the model results and
observations. As up to 17 types of major biogeochemical
observations, usually in seasonal or monthly profiles, were
assimilated, the model was constrained and tested rigorously to fit
different aspects of the ecosystem simultaneously. The
1-dimensional model was applied to three open ocean sites: the
Arabian Sea, Equatorial Pacific and Hawaii Ocean Time-series (HOT).
Good fitness to most of the observations supported the robustness
of the model and reliability of the results. The results indicated
the importance of heterotrophic bacteria in carbon cycling and
nutrient regeneration in all the three sites. Semilabile DOM was
identified as a stabilizing resource for heterotrophic bacteria.
The model also indicated refractory DOM could be an important form
of export from the upper ocean. Heterotrophic bacterial production
(BP) observations improved the model by strengthening constraints
on the model parameters. Despite uncertainties related to
estimating BP, the model supported current estimates of BP as 5 ?
25% of primary production and the commonly-used conversion factors
for BP measurements as 0.7 ? 3.1 kg C/mol leucine incorporation. A
15-year modeling experiment at HOT successfully simulated the
observed interannual increase of primary production. The model
suggested three mechanisms for this increase: (1) the deepening
mixed layer and increased physical nitrate supply from the deep
ocean, (2) enhanced nitrogen recycling as part of N2 fixation was
replaced with physical nitrate supply, and (3) new nitrogen supply
from semilabile DOM. The last two mechanisms only applied to the
surface 20 m.
Advisors/Committee Members: Ducklow, Hugh (director), Friedrichs, Marjorie (reader), Prell, Warren (reader), Vallino, Joseph (reader).
Subjects/Keywords: Data assimilation
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Luo, Y. (2009). A Data Assimilating Model of the Microbial Ecosystem in the
Open Ocean. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:192/
Chicago Manual of Style (16th Edition):
Luo, Yawei. “A Data Assimilating Model of the Microbial Ecosystem in the
Open Ocean.” 2009. Doctoral Dissertation, Brown University. Accessed February 26, 2021.
https://repository.library.brown.edu/studio/item/bdr:192/.
MLA Handbook (7th Edition):
Luo, Yawei. “A Data Assimilating Model of the Microbial Ecosystem in the
Open Ocean.” 2009. Web. 26 Feb 2021.
Vancouver:
Luo Y. A Data Assimilating Model of the Microbial Ecosystem in the
Open Ocean. [Internet] [Doctoral dissertation]. Brown University; 2009. [cited 2021 Feb 26].
Available from: https://repository.library.brown.edu/studio/item/bdr:192/.
Council of Science Editors:
Luo Y. A Data Assimilating Model of the Microbial Ecosystem in the
Open Ocean. [Doctoral Dissertation]. Brown University; 2009. Available from: https://repository.library.brown.edu/studio/item/bdr:192/
2.
Slivinski, Laura C.
Lagrangian Data Assimilation and its Applications to
Geophysical Fluid Flows.
Degree: PhD, Applied Mathematics, 2014, Brown University
URL: https://repository.library.brown.edu/studio/item/bdr:386205/
► Lagrangian data assimilation is the process of estimating a velocity flow field, given observations of the locations of passive drifters whose trajectories are determined by…
(more)
▼ Lagrangian
data assimilation is the process of
estimating a velocity flow field, given observations of the
locations of passive drifters whose trajectories are determined by
the flow. This problem often poses difficulties for traditional
data assimilation algorithms, as it involves variables which may be
high-dimensional and highly nonlinear. This thesis discusses the
design and implementation of a hybrid particle - ensemble Kalman
filter for Lagrangian
data assimilation, which avoids the
disadvantages of each filter individually while exploiting their
strengths. This filter applies the ensemble Kalman filter (EnKF)
update to the potentially high-dimensional flow state, and the
particle filter (PF) to the highly nonlinear drifter state. As a
proof of concept, this filter is tested on the linear shallow water
equations, for which the flow field can be parameterized to a
low-dimensional variable. Results show that the hybrid filter
outperforms the EnKF in highly non-Gaussian situations, and in
particular when the time between observations is long, both by
better capturing the Bayesian posterior distribution and by better
tracking the truth. The hybrid filter and the EnKF are then applied
to the nonlinear shallow water equations, to compare their results
with different drifter deployment strategies. Results suggest that
the velocity field is better estimated when the drifters target
energetic regions of the flow, both inside and outside vortices; on
the other hand, the height field is best approximated when the
drifters are spread evenly across the domain. Finally, we
investigate the general application of particle filters to
high-dimensional nonlinear systems, and find that the so-called
"optimal proposal" implementation can afford greater performance
than the standard proposal implementation.
Advisors/Committee Members: Sandstede, Bjorn (Director), Maxey, Martin (Reader), Spiller, Elaine (Reader).
Subjects/Keywords: data assimilation
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Slivinski, L. C. (2014). Lagrangian Data Assimilation and its Applications to
Geophysical Fluid Flows. (Doctoral Dissertation). Brown University. Retrieved from https://repository.library.brown.edu/studio/item/bdr:386205/
Chicago Manual of Style (16th Edition):
Slivinski, Laura C. “Lagrangian Data Assimilation and its Applications to
Geophysical Fluid Flows.” 2014. Doctoral Dissertation, Brown University. Accessed February 26, 2021.
https://repository.library.brown.edu/studio/item/bdr:386205/.
MLA Handbook (7th Edition):
Slivinski, Laura C. “Lagrangian Data Assimilation and its Applications to
Geophysical Fluid Flows.” 2014. Web. 26 Feb 2021.
Vancouver:
Slivinski LC. Lagrangian Data Assimilation and its Applications to
Geophysical Fluid Flows. [Internet] [Doctoral dissertation]. Brown University; 2014. [cited 2021 Feb 26].
Available from: https://repository.library.brown.edu/studio/item/bdr:386205/.
Council of Science Editors:
Slivinski LC. Lagrangian Data Assimilation and its Applications to
Geophysical Fluid Flows. [Doctoral Dissertation]. Brown University; 2014. Available from: https://repository.library.brown.edu/studio/item/bdr:386205/
NSYSU
3.
Lin, Ken-Dei.
Data Assimilation Technique Applied to Tidal Prediction Model.
Degree: Master, Marine Environment and Engineering, 2012, NSYSU
URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1106112-143704
► Computer technology is growing fast in recent years. Modeling technique is used in predicting or in planning engineering works and even in preventing disaster. Modeling…
(more)
▼ Computer technology is growing fast in recent years. Modeling technique is used in predicting or in planning engineering works and even in preventing disaster. Modeling is widely used in many domains and unmanned Real-time online operation modeling systems on prediction become popular. Model may become inaccurate due to a number of uncertainties in the approximation and by numerical reasons.
Data Assimilation technique is developed to solve this problem. Measured
data is used to improve the model results. In this research, the Cressman scheme was chosen as the
data assimilation scheme and used for correcting the modeling system.
An idealized model was constructed first as Taiwan Strait. In order to test the stability if
data assimilation system several geographical variations and
data availability cases were designed, eg adding varying bottom topography, an island added in the domain, different measurement
data locations. In order to test the model sensibilities an error was inserted to the boundaries. Model results were first corrected with
data assimilation system for a period of time, a Harmonic Analysis was, then, used for reanalysis the corrected time series on the boundaries. The new boundary condition is used in the new model run for making predictions. A true topography and island system as Taiwan Strait was tested with the true astronomical tide as the boundary input.
The
data assimilation system using the Cressman scheme could reduce the RMSE effectively. The factor that affects the efficiency of the
data assimilation system is the number and the location of the measurement
data.
Advisors/Committee Members: Yang-Chi Chang (chair), Jason C.S. Yu (committee member), Wen-Juinn Chen (chair).
Subjects/Keywords: Cressman; Data Assimilation; Tidal Model
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Lin, K. (2012). Data Assimilation Technique Applied to Tidal Prediction Model. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1106112-143704
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Lin, Ken-Dei. “Data Assimilation Technique Applied to Tidal Prediction Model.” 2012. Thesis, NSYSU. Accessed February 26, 2021.
http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1106112-143704.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Lin, Ken-Dei. “Data Assimilation Technique Applied to Tidal Prediction Model.” 2012. Web. 26 Feb 2021.
Vancouver:
Lin K. Data Assimilation Technique Applied to Tidal Prediction Model. [Internet] [Thesis]. NSYSU; 2012. [cited 2021 Feb 26].
Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1106112-143704.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Lin K. Data Assimilation Technique Applied to Tidal Prediction Model. [Thesis]. NSYSU; 2012. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-1106112-143704
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Texas A&M University
4.
Benoit, Mark David.
Sensitivity of High-resolution WRF Forecasts to a Single Radiosonde in a Data Sparse Region.
Degree: MS, Atmospheric Sciences, 2016, Texas A&M University
URL: http://hdl.handle.net/1969.1/159055
► Radiosonde observations (RAOBs) are relatively sparse over central Texas. The closest RAOB launch site to College Station, Texas is in Fort Worth, Texas, about 250…
(more)
▼ Radiosonde observations (RAOBs) are relatively sparse over central Texas. The closest RAOB launch site to College Station, Texas is in Fort Worth, Texas, about 250 km away. On-demand soundings were launched by Texas A&M University students in high-impact situations. Both the local NWS offices and the SPC requested RAOBs. These observations had value to forecasters in convective and winter weather situations.
The purpose of this research was to find the value of on-demand RAOBs on a high-resolution NWP forecast for College Station. DA was done with 29 RAOBs using WRF, but also incorporated other observations from MADIS. In total, there were 116 simulations since four simulations were done for each RAOB. Using weather model analyses and observations from the EOL, MADIS, and NOAA, the simulations were evaluated. DTC-MET and SPoRT-MET tools utilized the datasets to provide verification.
In some cases, DA of a single RAOB produced modest, positive impacts on the WRF forecast. Precipitation characterization and high precipitation amounts were improved in convective cases, while surface and low-level temperature forecast improvements were seen in short-range forecasts for winter cases. Benefit was spatially limited to areas near College Station, and was further limited when MADIS observations were assimilated. Future work supports RAOB launches in high-impact situations; however, real-time DA of these RAOBs is not a high priority.
Advisors/Committee Members: Nowotarski, Chris (advisor), Conlee, Don T (advisor), Szunyogh, Istvan (committee member), Gao, Huilin (committee member).
Subjects/Keywords: WRF; Data Assimilation; NWP; RAOB
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Benoit, M. D. (2016). Sensitivity of High-resolution WRF Forecasts to a Single Radiosonde in a Data Sparse Region. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/159055
Chicago Manual of Style (16th Edition):
Benoit, Mark David. “Sensitivity of High-resolution WRF Forecasts to a Single Radiosonde in a Data Sparse Region.” 2016. Masters Thesis, Texas A&M University. Accessed February 26, 2021.
http://hdl.handle.net/1969.1/159055.
MLA Handbook (7th Edition):
Benoit, Mark David. “Sensitivity of High-resolution WRF Forecasts to a Single Radiosonde in a Data Sparse Region.” 2016. Web. 26 Feb 2021.
Vancouver:
Benoit MD. Sensitivity of High-resolution WRF Forecasts to a Single Radiosonde in a Data Sparse Region. [Internet] [Masters thesis]. Texas A&M University; 2016. [cited 2021 Feb 26].
Available from: http://hdl.handle.net/1969.1/159055.
Council of Science Editors:
Benoit MD. Sensitivity of High-resolution WRF Forecasts to a Single Radiosonde in a Data Sparse Region. [Masters Thesis]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/159055
Oregon State University
5.
Landon, Kyle C.
Ensemble-based data assimilation and depth inversion on the Kootenai River, ID, USA.
Degree: M.Oc.E., Civil Engineering, 2012, Oregon State University
URL: http://hdl.handle.net/1957/33794
► Velocity measurements from drifter GPS records are assimilated and used in an ensemble-based inversion technique to extract the river bathymetry. The method is tested on…
(more)
▼ Velocity measurements from drifter GPS records are assimilated and used in an ensemble-based inversion technique to extract the river bathymetry. The method is tested on a deep meandering reach and a shallow braided reach of the Kootenai River in Idaho, USA. The Regional Ocean Modeling System (ROMS) is used to model numerous statistically varied bathymetries to create an ensemble of hydrodynamic states. These states, the drifter observations, and the uncertainty of each are combined to form a cost function which is minimized to produce an estimated velocity field. State augmentation is then used to relate the velocity field to bathymetry. Our goals are to assess whether ROMS can accurately reproduce the Kootenai River flow to an extent that depth inversion is feasible, investigate if drifter paths are sensitive enough to bottom topography to make depth inversion possible, and to establish practical limitations of the present methodology. At both test sites, the depth inversion method produced an estimate of bathymetry that was more accurate and more skillful than the prior estimate.
Advisors/Committee Members: Ozkan-Haller, Tuba (advisor), Hill, David (committee member).
Subjects/Keywords: Data Assimilation; Streamflow – Kootenai River
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Landon, K. C. (2012). Ensemble-based data assimilation and depth inversion on the Kootenai River, ID, USA. (Masters Thesis). Oregon State University. Retrieved from http://hdl.handle.net/1957/33794
Chicago Manual of Style (16th Edition):
Landon, Kyle C. “Ensemble-based data assimilation and depth inversion on the Kootenai River, ID, USA.” 2012. Masters Thesis, Oregon State University. Accessed February 26, 2021.
http://hdl.handle.net/1957/33794.
MLA Handbook (7th Edition):
Landon, Kyle C. “Ensemble-based data assimilation and depth inversion on the Kootenai River, ID, USA.” 2012. Web. 26 Feb 2021.
Vancouver:
Landon KC. Ensemble-based data assimilation and depth inversion on the Kootenai River, ID, USA. [Internet] [Masters thesis]. Oregon State University; 2012. [cited 2021 Feb 26].
Available from: http://hdl.handle.net/1957/33794.
Council of Science Editors:
Landon KC. Ensemble-based data assimilation and depth inversion on the Kootenai River, ID, USA. [Masters Thesis]. Oregon State University; 2012. Available from: http://hdl.handle.net/1957/33794
University of Oklahoma
6.
Carlin, Jacob.
The Use of Polarimetric Radar Data for Informing Numerical Weather Prediction Models.
Degree: PhD, 2018, University of Oklahoma
URL: http://hdl.handle.net/11244/299801
► The explicit prediction of convective storms using storm-scale models has recently become a reality. Radar data is a crucial source of information about the microphysical…
(more)
▼ The explicit prediction of convective storms using storm-scale models has recently become a reality. Radar
data is a crucial source of information about the microphysical and kinematic properties of convection at the storm-scale. Whereas
assimilation studies have primarily focused on radial velocity and reflectivity, much less has been done to investigate how dual-polarization radar
data, and the enhanced microphysical information it offers, may inform storm-scale models.
This study employs a suite of microphysical and numerical weather prediction models, coupled to a polarimetric radar operator, to study how dual-polarization radar
data may be used in conjunction with storm-scale models. The commonly-used polarimetric variables are defined, and a review of existing microphysical, wind, moisture, and thermodynamic retrieval and radar
data assimilation techniques is presented for reflectivity, radial velocity, and dual-polarization
data. Using a one-dimensional spectral bin model, the efficacy of reflectivity-based retrievals of hydrometeor mixing ratios in rain/hail mixtures, and the potential benefits of dual-polarization
data, is assessed. A one-dimensional model of the melting layer is presented and used to study the impact of
the environment on polarimetric brightband characteristics, the potential for polarimetric thermodynamic retrievals in the melting layer, and the potential microphysical causes of “sagging” brightband signatures. Predicated on a connection between ZDR column characteristics and the latent heating rate within convective updrafts, a novel method for assimilating ZDR columns using a cloud analysis is developed, with results indicating positive impacts compared to reflectivity-based cloud analysis techniques. Future work ideas and an outlook for the near future is presented.
Advisors/Committee Members: Ryzhkov, Alexander (advisor), Gao, Jidong (advisor), Zhang, Guifu (advisor), Wang, Xuguang (committee member), Bluestein, Howard (committee member), Goodman, Nathan (committee member).
Subjects/Keywords: Atmospheric Sciences.; Radar; Data assimilation
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Carlin, J. (2018). The Use of Polarimetric Radar Data for Informing Numerical Weather Prediction Models. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/299801
Chicago Manual of Style (16th Edition):
Carlin, Jacob. “The Use of Polarimetric Radar Data for Informing Numerical Weather Prediction Models.” 2018. Doctoral Dissertation, University of Oklahoma. Accessed February 26, 2021.
http://hdl.handle.net/11244/299801.
MLA Handbook (7th Edition):
Carlin, Jacob. “The Use of Polarimetric Radar Data for Informing Numerical Weather Prediction Models.” 2018. Web. 26 Feb 2021.
Vancouver:
Carlin J. The Use of Polarimetric Radar Data for Informing Numerical Weather Prediction Models. [Internet] [Doctoral dissertation]. University of Oklahoma; 2018. [cited 2021 Feb 26].
Available from: http://hdl.handle.net/11244/299801.
Council of Science Editors:
Carlin J. The Use of Polarimetric Radar Data for Informing Numerical Weather Prediction Models. [Doctoral Dissertation]. University of Oklahoma; 2018. Available from: http://hdl.handle.net/11244/299801
University of Oklahoma
7.
Sobash, Ryan.
Assimilation of radar and surface observations of a developing convective system: Observing system simulation and real-data experiments.
Degree: PhD, 2013, University of Oklahoma
URL: http://hdl.handle.net/11244/7912
► Convective-scale observing system simulation experiments (OSSEs) and real-data experiments were performed to study the impact of radar and surface observations on analyses and forecasts of…
(more)
▼ Convective-scale observing system simulation experiments (OSSEs) and real-
data experiments were performed to study the impact of radar and surface observations on analyses and forecasts of convective systems using the Weather Research and Forecasting (WRF) model with an ensemble Kalman filter (EnKF). The OSSEs were performed to assess the impact of covariance localization of radar
data on the analyses of a developing convective system. Increasing the horizontal localization and decreasing the vertical localization produced analyses with the smallest RMSE for most of the state variables. The convective mode of the analyzed system also had an impact on the localization results. During cell mergers, larger horizontal localization improved the results. Prior state correlations between the observations and state variables were used to construct reverse cumulative density functions (RCDFs) to identify the correlation length scales for various observation-state pairs. The OSSE with the smallest RMSE employed localization cutoff values that were similar to the horizontal and vertical length scales of the prior state correlations, especially for observation-state correlations above 0.6. Vertical correlations were restricted to state points closer to the observations than in the horizontal, as determined by the RCDFs. Further, the microphysical state variables were correlated with the reflectivity observations on smaller scales than the three-dimensional wind field and radial velocity observations.
As a complement to the OSSEs, the WRF model and the EnKF were again employed to produce analyses and forecasts for the 29 May 2012 convective episode. This event produced very large hail (> 4” diameter), 80 mph wind gusts, and a brief tornado, near and within the OKC metropolitan area, with estimated losses totaling 500 million dollars. Surface
data, including
data from surface mesoscale networks (i.e. mesonets), were assimilated at 5-minute intervals between 18 UTC and 21 UTC. Both surface and WSR-88D
data were assimilated at 5-minute intervals between 21 UTC and 23 UTC, following convection initiation (CI). Several 50-member, 6-hour, ensemble forecasts were produced between 18 UTC and 23 UTC.
The frequent
assimilation of surface
data, especially the use of mesonet
data, improved the forecast of CI timing and placement within the domain, especially for convection developing along a surface dry line. Surface
data assimilation reduced a surface moisture bias that was present due to model error. Experiments where mesonet
data were withheld, or where surface
data were assimilated less frequently, produced less accurate forecasts of CI and possessed larger surface moisture errors. The improved surface state at 21 UTC also led to changes in the forecast convective mode after 00 UTC. The ability of sub-hourly
assimilation of mesonet
data to improve forecasts of CI has not been previously documented.
After two hours of both radar and surface
data assimilation, the 23 UTC ensemble forecast was able to capture much of the observed…
Advisors/Committee Members: Stensrud, David (advisor), Xue, Ming (committee member), Carr, Frederick (committee member), Wang, Xuguang (committee member), Wicker, Louis (committee member), Lakshmivarahan, S (committee member).
Subjects/Keywords: Data assimilation; meteorology; severe storms
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Sobash, R. (2013). Assimilation of radar and surface observations of a developing convective system: Observing system simulation and real-data experiments. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/7912
Chicago Manual of Style (16th Edition):
Sobash, Ryan. “Assimilation of radar and surface observations of a developing convective system: Observing system simulation and real-data experiments.” 2013. Doctoral Dissertation, University of Oklahoma. Accessed February 26, 2021.
http://hdl.handle.net/11244/7912.
MLA Handbook (7th Edition):
Sobash, Ryan. “Assimilation of radar and surface observations of a developing convective system: Observing system simulation and real-data experiments.” 2013. Web. 26 Feb 2021.
Vancouver:
Sobash R. Assimilation of radar and surface observations of a developing convective system: Observing system simulation and real-data experiments. [Internet] [Doctoral dissertation]. University of Oklahoma; 2013. [cited 2021 Feb 26].
Available from: http://hdl.handle.net/11244/7912.
Council of Science Editors:
Sobash R. Assimilation of radar and surface observations of a developing convective system: Observing system simulation and real-data experiments. [Doctoral Dissertation]. University of Oklahoma; 2013. Available from: http://hdl.handle.net/11244/7912
University of Oklahoma
8.
Kong, Rong.
HYBRID EN3DVAR RADAR DATA ASSIMILATION AND COMPARISONS WITH 3DVAR AND ENKF WITH OSSES AND A REAL CASE.
Degree: PhD, 2017, University of Oklahoma
URL: http://hdl.handle.net/11244/52910
► Studies have shown advantages of the hybrid ensemble-variational data assimilation (DA) algorithms over pure ensemble or variational algorithms, although such advantages at the convective scale,…
(more)
▼ Studies have shown advantages of the hybrid ensemble-variational
data assimilation (DA) algorithms over pure ensemble or variational algorithms, although such advantages at the convective scale, in the presence of complex ice microphysics and for radar
data assimilation, have not yet been clearly demonstrated, if the advantages do exist. A hybrid ensemble-3DVar (En3DVar) system is developed recently based on the ARPS 3DVar and EnKF systems at the Center for Analysis and Prediction of Storms (CAPS). In this dissertation, hybrid En3DVar is compared with 3DVar, EnKF, and pure En3DVar for radar DA through observing system simulation experiments (OSSEs) under both perfect and imperfect model assumptions. It is also applied to a real case including multiple tornadic supercells. For the real case, radar radial velocity and reflectivity
data are assimilated every 5 minutes for 1 hour that is followed by short-term forecasts. DfEnKF that updates a single deterministic background forecast using the EnKF updating algorithm is introduced to have an algorithm-wise parallel comparison between EnKF and pure En3DVar.
In the perfect-model OSSEs, DfEnKF and pure En3DVar are compared and are found to perform differently when using the same localization radii. The serial (EnKF) versus global (pure En3DVar) nature of the algorithms, and direct filter update (EnKF) versus variational minimization (En3DVar) are the major reasons for the differences. Hybrid En3DVar for radar DA is also compared with 3DVar, EnKF, DfEnKF, and pure En3DVar. Experiments are conducted first to obtain the optimal configurations for different algorithms before they are compared; the optimal configurations include the optimal background decorrelation scales for 3DVar, optimal localization radii for EnKF, DfEnKF, and pure En3DVar, as well as the optimal hybrid weights for hybrid En3DVar. When the algorithms are tuned optimally, hybrid En3DVar does not outperform EnKF or pure En3DVar, although their analyses are all much better than 3DVar. When ensemble background error covariance is a good estimation of the true error distribution, pure ensemble-based DA methods can do a good job, and the advantage of including static background error covariance B in hybrid DA is not obvious.
In the imperfect-model OSSEs, model errors are introduced by using different microphysical schemes in the truth run (Lin scheme) and in the ensemble forecasts (WSM6 scheme). Experiments are conducted to obtain the optimal configurations for different algorithms, similar to those in perfect-model OSSEs. Hybrid En3DVar is then found to outperform EnKF and pure En3DVar (3DVar) for better capturing the hail analyses below the freezing level (intensity of the storm). The advantage of hybrid En3DVar over pure ensemble-based methods is most obvious when ensemble background errors are systematically underestimated. In addition, the impact of adding a mass continuity constraint in 3DVar, pure and hybrid En3DVar is also examined. Overall, adding the mass continuity constraint improving the analyses by…
Advisors/Committee Members: Xue, Ming (advisor), Shapiro, Alan (committee member), Parsons, David (committee member), Kong, Fanyou (committee member), Brewster, Keith (committee member), Xiao, Xiangming (committee member).
Subjects/Keywords: meteorology; radar data assimilation
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Kong, R. (2017). HYBRID EN3DVAR RADAR DATA ASSIMILATION AND COMPARISONS WITH 3DVAR AND ENKF WITH OSSES AND A REAL CASE. (Doctoral Dissertation). University of Oklahoma. Retrieved from http://hdl.handle.net/11244/52910
Chicago Manual of Style (16th Edition):
Kong, Rong. “HYBRID EN3DVAR RADAR DATA ASSIMILATION AND COMPARISONS WITH 3DVAR AND ENKF WITH OSSES AND A REAL CASE.” 2017. Doctoral Dissertation, University of Oklahoma. Accessed February 26, 2021.
http://hdl.handle.net/11244/52910.
MLA Handbook (7th Edition):
Kong, Rong. “HYBRID EN3DVAR RADAR DATA ASSIMILATION AND COMPARISONS WITH 3DVAR AND ENKF WITH OSSES AND A REAL CASE.” 2017. Web. 26 Feb 2021.
Vancouver:
Kong R. HYBRID EN3DVAR RADAR DATA ASSIMILATION AND COMPARISONS WITH 3DVAR AND ENKF WITH OSSES AND A REAL CASE. [Internet] [Doctoral dissertation]. University of Oklahoma; 2017. [cited 2021 Feb 26].
Available from: http://hdl.handle.net/11244/52910.
Council of Science Editors:
Kong R. HYBRID EN3DVAR RADAR DATA ASSIMILATION AND COMPARISONS WITH 3DVAR AND ENKF WITH OSSES AND A REAL CASE. [Doctoral Dissertation]. University of Oklahoma; 2017. Available from: http://hdl.handle.net/11244/52910
University of Utah
9.
Tyndall, Daniel Paul.
Sensitivity of surface meteorological analyses to observation networks.
Degree: PhD, Atmospheric Sciences, 2011, University of Utah
URL: http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/314/rec/2163
► A computationally efficient variational analysis system for two-dimensional meteorological fields is developed and described. This analysis approach is most efficient when the number of analysis…
(more)
▼ A computationally efficient variational analysis system for two-dimensional meteorological fields is developed and described. This analysis approach is most efficient when the number of analysis grid points is much larger than the number of available observations, such as for large domain mesoscale analyses. The analysis system is developed using MATLAB software and can take advantage of multiple processors or processor cores. A version of the analysis system has been exported as a platform independent application (i.e., can be run on Windows, Linux, or Macintosh OS X desktop computers without a MATLAB license) with input/output operations handled by commonly available internet software combined with data archives at the University of Utah. The impact of observation networks on the meteorological analyses is assessed by utilizing a percentile ranking of individual observation sensitivity and impact, which is computed by using the adjoint of the variational surface assimilation system. This methodology is demonstrated using a case study of the analysis from 1400 UTC 27 October 2010 over the entire contiguous United States domain. The sensitivity of this approach to the dependence of the background error covariance on observation density is examined. Observation sensitivity and impact provide insight on the influence of observations from heterogeneous observing networks as well as serve as objective metrics for quality control procedures that may help to identify stations with significant siting, reporting, or representativeness issues.
Subjects/Keywords: Data assimilation; Mesonet; Mesoscale analysis; Meteorology; Surface analysis; Variational assimilation methods
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Tyndall, D. P. (2011). Sensitivity of surface meteorological analyses to observation networks. (Doctoral Dissertation). University of Utah. Retrieved from http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/314/rec/2163
Chicago Manual of Style (16th Edition):
Tyndall, Daniel Paul. “Sensitivity of surface meteorological analyses to observation networks.” 2011. Doctoral Dissertation, University of Utah. Accessed February 26, 2021.
http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/314/rec/2163.
MLA Handbook (7th Edition):
Tyndall, Daniel Paul. “Sensitivity of surface meteorological analyses to observation networks.” 2011. Web. 26 Feb 2021.
Vancouver:
Tyndall DP. Sensitivity of surface meteorological analyses to observation networks. [Internet] [Doctoral dissertation]. University of Utah; 2011. [cited 2021 Feb 26].
Available from: http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/314/rec/2163.
Council of Science Editors:
Tyndall DP. Sensitivity of surface meteorological analyses to observation networks. [Doctoral Dissertation]. University of Utah; 2011. Available from: http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/314/rec/2163
INP Toulouse
10.
Vandamme, Thibaud.
Simulation-inversion des diagraphies : Simulation-inversion of logs.
Degree: Docteur es, Mathematiques Appliquées, 2018, INP Toulouse
URL: http://www.theses.fr/2018INPT0125
► L’évaluation des formations géologiques consiste en l’analyse et la synthèse de données de différentes sources, de différentes échelles (microscopique à kilométrique) et acquises à des…
(more)
▼ L’évaluation des formations géologiques consiste en l’analyse et la synthèse de données de différentes sources, de différentes échelles (microscopique à kilométrique) et acquises à des dates très variables. Le processus conventionnel de caractérisation des formations relève alors de l’interprétation physique spécialisée de chacune de ces sources de données et leur mise en cohérence par des processus de synthèse essentiellement d’ordre statistique (corrélation, apprentissage, up-scaling…). Il s’avère cependant qu’une source de données présente un caractère central : les diagraphies. Ces mesures physiques de différentes natures (nucléaires, acoustiques, électromagnétiques…) sont réalisées le long de la paroi d’un puits à l’aide de différentes sondes. Elles sont sensibles aux propriétés in situ des roches, et ce, sur une gamme d’échelle centimétrique à métrique intermédiaire aux carottes et données de test de production. De par leur profondeur d’investigation, les données diagraphiques sont particulièrement sensibles au phénomène d’invasion de boue se produisant lors du forage dans l’abord puits. Traditionnellement, l’invasion est modélisée de façon frustre au moment de l’interprétation diagraphiques par un simple effet piston. Ce modèle simple permet d’honorer le bilan de volume mais ne prend aucunement en compte la physique réelle d’invasion et prive, de fait, les diagraphies de toute portée dynamique. Des essais de modélisation de l’historique d’invasion couplés aux données diagraphiques ont déjà été élaborés par différents laboratoires et une abondante littérature sur le sujet est disponible. Les limitations majeures de ces approches résident dans le caractère sous déterminé des problèmes inverses issus de ces modèles physiques et dans le fait que la donnée diagraphique est réalisée en général sur un intervalle de temps inadaptée au regard du développement de l’invasion. Nous proposons une approche différente qui s’attèle non pas à décrire la physique de l’écoulement mais celle de l’équilibre radial des fluides dans le domaine envahi lorsque les diagraphies sont acquises. Nous montrons qu’en introduisant quelques contraintes pétrophysiques supplémentaires, il est possible d’inverser efficacement la distribution des propriétés dynamiques pour chaque faciès géologique. L’inversion prend en compte le phénomène d’invasion radial dans la zone à eau ainsi que l’équilibre capillaire vertical caractérisant le profil de saturation dans le réservoir pour chaque facies. A chaque profondeur du puits, sont ainsi obtenues perméabilités, pressions capillaires et facteurs de cimentation avec leurs incertitudes ainsi que les lois pétrophysiques propres à chaque faciès. Cette méthode a été appliquée à deux puits réels. En guise de validation, les résultats d’inversion ont été comparés aux mesures laboratoire faites sur carotte. De plus, les perméabilités inversées ont été comparées aux transitoires de pression de mini-tests. La cohérence des résultats montre que, d’une part, les hypothèses de base du modèle sont validées et que,…
Advisors/Committee Members: Gratton, Serge (thesis director).
Subjects/Keywords: Diagraphies; Assimilation de données; Problèmes inverses; Logs; Data assimilation; Inverse problem
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Vandamme, T. (2018). Simulation-inversion des diagraphies : Simulation-inversion of logs. (Doctoral Dissertation). INP Toulouse. Retrieved from http://www.theses.fr/2018INPT0125
Chicago Manual of Style (16th Edition):
Vandamme, Thibaud. “Simulation-inversion des diagraphies : Simulation-inversion of logs.” 2018. Doctoral Dissertation, INP Toulouse. Accessed February 26, 2021.
http://www.theses.fr/2018INPT0125.
MLA Handbook (7th Edition):
Vandamme, Thibaud. “Simulation-inversion des diagraphies : Simulation-inversion of logs.” 2018. Web. 26 Feb 2021.
Vancouver:
Vandamme T. Simulation-inversion des diagraphies : Simulation-inversion of logs. [Internet] [Doctoral dissertation]. INP Toulouse; 2018. [cited 2021 Feb 26].
Available from: http://www.theses.fr/2018INPT0125.
Council of Science Editors:
Vandamme T. Simulation-inversion des diagraphies : Simulation-inversion of logs. [Doctoral Dissertation]. INP Toulouse; 2018. Available from: http://www.theses.fr/2018INPT0125
Universidade do Rio Grande do Sul
11.
Macedo, Luana Ribeiro.
O impacto do uso da técnica de assimilação de dados 3DVAR nos prognósticos do modelo WRF.
Degree: 2014, Universidade do Rio Grande do Sul
URL: http://hdl.handle.net/10183/111855
► O uso da técnica de assimilação de dados meteorológicos é extremamente importante para a correção de imprecisões nos dados que compõem as condições iniciais e…
(more)
▼ O uso da técnica de assimilação de dados meteorológicos é extremamente importante para a correção de imprecisões nos dados que compõem as condições iniciais e de fronteira dos modelos de previsão do tempo. Neste trabalho, faz-se uso da técnica de assimilação de dados 3DVAR contida no modelo de mesoescala WRF (Weather Research and Forecasting), o objetivo principal do trabalho é analisar o impacto da assimilação de dados meteorológicos de diversas fontes de dados (GTS – Sistema Global de Telecomunicações, estações automáticas, dados radar) no modelo WRF. Para analisar a consistência da assimilação de dados no WRF verificou-se a diferença entre a análise com e sem assimilação de dados. Confirmando a consistência da mesma, foram realizados os procedimentos necessários para gerar os prognósticos com assimilação de dados para cada caso individualmente. Os experimentos com assimilação de dados foram realizados para cada tipo de dado e em conjunto, possibilitando assim fazer uma análise do impacto que cada dado tem na previsão. Os resultados foram comparados entre si espacialmente utilizando dados do modelo global GFS (Global Forecast System) e satélite da Missão de Medida da Chuva Tropical (TRMM). A variável da precipitação acumulada foi comparada e validada espacialmente com os dados do TRMM, constatou-se para o caso do mês de janeiro uma superestimação dos valores acumulados para algumas regiões e para o caso do mês de abril uma subestimação, isso se deve ao fato da frequência temporal dos dados do satélite TRMM, pois provavelmente elas não foram compatíveis com o horário das precipitações. Quando comparado com o volume de chuva pontual com os dados da estação automática a maioria dos processamentos mostrou-se eficaz. Também no estudo de caso ocorrido no mês de janeiro a inserção de dados assimilados possibilitou uma melhora na intensidade e localização da célula convectiva. As variáveis da temperatura e do vento foram comparadas espacialmente com as análises do modelo GFS. A variável da temperatura ora apresentou valores superiores, ora inferiores ao modelo GFS, mesmo assim os resultados foram satisfatórios, uma vez que, foi possível simular temperaturas superiores antes da passagem do sistema e inferiores após a passagem do mesmo. Para o campo de vento houve uma pequena discrepância em todas as simulações em relação a magnitude, porém a direção do vento foi plotada de forma coerente, simulando até o ciclone presente no caso do mês de abril. Para o perfil vertical da temperatura e temperatura do ponto de orvalho o impacto da assimilação de dados foi pequeno, porém ambas as simulações representaram de forma coesa os perfis quando comparados com o perfil observado. Em suma, o estudo comprova que, embora se tenha algumas incoerências assimilação 3DVAR contribui de modo significativo nas previsões do tempo do modelo WRF.
The use of meteorological data assimilation technique is extremely important for the correction of the imprecisions of observational data for the initial and boundary conditions of weather forecasting…
Advisors/Committee Members: Alves, Rita de Cássia Marques.
Subjects/Keywords: Data assimilation; Sensoriamento remoto; 3DVAR; WRF; TRMM
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Macedo, L. R. (2014). O impacto do uso da técnica de assimilação de dados 3DVAR nos prognósticos do modelo WRF. (Thesis). Universidade do Rio Grande do Sul. Retrieved from http://hdl.handle.net/10183/111855
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Macedo, Luana Ribeiro. “O impacto do uso da técnica de assimilação de dados 3DVAR nos prognósticos do modelo WRF.” 2014. Thesis, Universidade do Rio Grande do Sul. Accessed February 26, 2021.
http://hdl.handle.net/10183/111855.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Macedo, Luana Ribeiro. “O impacto do uso da técnica de assimilação de dados 3DVAR nos prognósticos do modelo WRF.” 2014. Web. 26 Feb 2021.
Vancouver:
Macedo LR. O impacto do uso da técnica de assimilação de dados 3DVAR nos prognósticos do modelo WRF. [Internet] [Thesis]. Universidade do Rio Grande do Sul; 2014. [cited 2021 Feb 26].
Available from: http://hdl.handle.net/10183/111855.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Macedo LR. O impacto do uso da técnica de assimilação de dados 3DVAR nos prognósticos do modelo WRF. [Thesis]. Universidade do Rio Grande do Sul; 2014. Available from: http://hdl.handle.net/10183/111855
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Universiteit Utrecht
12.
Terwisscha van Scheltinga, A.D.
Data assimilation with implicit ocean models.
Degree: 2007, Universiteit Utrecht
URL: http://dspace.library.uu.nl:8080/handle/1874/23459
► The ocean is an important part of the climate system, controlling the climate variability on many time-scales. Climate change, for example, has been linked to…
(more)
▼ The ocean is an important part of the climate system, controlling the climate variability on many time-scales. Climate change, for example, has been linked to changes in the thermohaline circulation. This thesis is motivated by theoretical results on the stability of this circulation, especially the Atlantic Meridional Overturning circulation (AMOC). These results indentify a scalar whose sign is an indicator for the stability of the AMOC. This indicator measures the net advective freshwater transport in the Atlantic. The central problem adressed in this thesis is the determination of a time-mean value for this indicator from observational records. Since the observational records is sparse and short, one needs a data assimilation methods in combination with a models of the AMOC. The main focus is: (i) to determine best values of the freshwater transports of the present ocean circulation in the Atlantic basin rom available observations; (ii) to determine values for the indicator; and (iii) to assess which processes contribute to the uncertain values for this indicator. The approach suggested here is: (i) develop fully implicit ocean models with which it is possible to calculate equillibrium solutions efficiently because large time-steps can be taken; (ii) adapt a variational data-assimilation method for use in these implicit models; and (iii) develop a data-handling technique such that the effect of temporal variability on the time-mean state can be computed relatively efficient. This approach requires the development of several pieces of new numerical methodology. In this thesis these pieces are developed systematically and tested with idealized models. The foces therefore is on the developement and testing of the new methodology and not on the application in realistic situations with realistic observations. For a wide range of test problems the new methodology performed well and better than traditional data-assimilation schemes using explicit ocean models.
Subjects/Keywords: Natuur- en Sterrenkunde; data-assimilation; oceanography; modelling
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Terwisscha van Scheltinga, A. D. (2007). Data assimilation with implicit ocean models. (Doctoral Dissertation). Universiteit Utrecht. Retrieved from http://dspace.library.uu.nl:8080/handle/1874/23459
Chicago Manual of Style (16th Edition):
Terwisscha van Scheltinga, A D. “Data assimilation with implicit ocean models.” 2007. Doctoral Dissertation, Universiteit Utrecht. Accessed February 26, 2021.
http://dspace.library.uu.nl:8080/handle/1874/23459.
MLA Handbook (7th Edition):
Terwisscha van Scheltinga, A D. “Data assimilation with implicit ocean models.” 2007. Web. 26 Feb 2021.
Vancouver:
Terwisscha van Scheltinga AD. Data assimilation with implicit ocean models. [Internet] [Doctoral dissertation]. Universiteit Utrecht; 2007. [cited 2021 Feb 26].
Available from: http://dspace.library.uu.nl:8080/handle/1874/23459.
Council of Science Editors:
Terwisscha van Scheltinga AD. Data assimilation with implicit ocean models. [Doctoral Dissertation]. Universiteit Utrecht; 2007. Available from: http://dspace.library.uu.nl:8080/handle/1874/23459
University of California – Berkeley
13.
Jeong, Seongeun.
Understanding Snow Process Uncertainties and Their Impacts.
Degree: Civil and Environmental Engineering, 2009, University of California – Berkeley
URL: http://www.escholarship.org/uc/item/4zv592q2
► Prediction of snow in regional and global hydrological models has been a difficult task due to errors in the forcing data, subgrid-scale variability in the…
(more)
▼ Prediction of snow in regional and global hydrological models has been a difficult task due to errors in the forcing data, subgrid-scale variability in the snowpack, and uncertain model physics. This dissertation conducts thorough studies of uncertainties that are concerned with snow modeling, in particular for high mountain areas. First, an in-depth analysis of uncertainties associated with meteorological forcing data in the Sierra Nevada was performed. The use of ensemble forcing data with a reasonable degree of uncertainty and model parameter adjustments did not overcome the low-bias in simulating snow states using a simple two-layer (2-L) snow model in the Variable Capacity Infiltration (VIC) land surface model (LSM). To reveal the uncertainty related to model parameterization, a multi-layer (M-L) soil-snow model with more complexity has been developed. This dissertation examines the impact of model complexity on snow simulations in high mountains by comparing the M-L model and the 2-L model. While the current VIC LSM solves state variables for soil and snow separately, the new M-L model solves state variables for the integrated soil-snow system simultaneously. This dissertation has found that the complex M-L model performs better than the 2-L model overall, in particular during the melting season, but the added complexity did not significantly remove the uncertainty, which is similar to some other researchers' findings. This conclusion has led this dissertation research to data assimilation work to investigate the uncertainty problem from a different angle.The data assimilation approach was taken to discover the hidden facets of uncertain land surface processes that could not be explained by the complex M-L soil-snow model. This research uses a multiscale data assimilation scheme that allows for incorporation of data with different scales. As an extension of the traditional state space model (e.g., Kalman filtering), the multiscale data assimilation incorporates data at different scales by computing their conditional probabilities in a scale-recursive way. The multiscale assimilation scheme has been embedded into the M-L soil-snow model of the VIC LSM. This dissertation applies the new assimilation system to the West Coast region to examine the impact of snow data assimilation at the regional scale as well as at the local scale. The assimilation at the local and regional scales showed promise by reducing biases in simulating snow states in the region. In addition, this research shows the impact of snow data assimilation on energy flux and streamflow simulations.
Subjects/Keywords: Engineering, Civil; data assimilation; modeling; snow; uncertainty
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Jeong, S. (2009). Understanding Snow Process Uncertainties and Their Impacts. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/4zv592q2
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Jeong, Seongeun. “Understanding Snow Process Uncertainties and Their Impacts.” 2009. Thesis, University of California – Berkeley. Accessed February 26, 2021.
http://www.escholarship.org/uc/item/4zv592q2.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Jeong, Seongeun. “Understanding Snow Process Uncertainties and Their Impacts.” 2009. Web. 26 Feb 2021.
Vancouver:
Jeong S. Understanding Snow Process Uncertainties and Their Impacts. [Internet] [Thesis]. University of California – Berkeley; 2009. [cited 2021 Feb 26].
Available from: http://www.escholarship.org/uc/item/4zv592q2.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Jeong S. Understanding Snow Process Uncertainties and Their Impacts. [Thesis]. University of California – Berkeley; 2009. Available from: http://www.escholarship.org/uc/item/4zv592q2
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
University of Utah
14.
Li, Zhan.
Studying the genesis of typhoon Nuri (2008) with numerical simulations and data assimilation.
Degree: PhD, Atmospheric Sciences, 2013, University of Utah
URL: http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/3482/rec/2297
► Forecasting tropical cyclone (TC) genesis is a challenging problem. Thisdissertation attempts to understand the following questions through studying the genesisof Typhoon Nuri (2008) with numerical…
(more)
▼ Forecasting tropical cyclone (TC) genesis is a challenging problem. Thisdissertation attempts to understand the following questions through studying the genesisof Typhoon Nuri (2008) with numerical simulations and data assimilation: 1) What arethe atmospheric conditions and processes that contribute to Nuri’s genesis and early rapidintensification? 2) To what extent can data assimilation improve the forecasts of Nuri’sgenesis?To address the first question, numerical simulations of Nuri’s genesis areconducted using an advanced research version of the Weather Research and Forecasting(WRF) model. First, initial and boundary conditions derived from two global analyses arefound to lead to remarkably different simulations of Nuri’s genesis in developing andnondeveloping cases. It is also found that the convective development into the pre-Nuricore region is a critical process for Nuri’s genesis. A strong midlevel vortex and a moistenvironment provide the favorable conditions for the convective development. Inducedby the persistent deep convection, diabatic heating at upper levels is produced from latentheat release. This substantial warming at upper levels results in the drop in Nuri’sminimum central sea level pressure.Next, the sensitivity of numerical simulations of Nuri’s genesis to the modelhorizontal resolution is examined. Results show that the simulation at a coarse-resolution(e.g., 12 km) better predicts Nuri’s rapid intensification than that at a higher resolution(e.g., 4 km). Specifically, the simulation at the coarser resolution produces strongconvective bursts and diabatic heating in the inner core region and also stronger warmingin the upper atmosphere, thus leading to a lower minimum sea level pressure (MSLP).Further experiments suggest that an appropriate microphysics scheme (e.g., the twomomentMorrison scheme) and a later initialization time (after Nuri’s early development)could help the high-resolution simulation better capture Nuri’s rapid intensification.Finally, numerical experiments are conducted to examine the impact of radar dataassimilation on numerical simulations of Nuri’s genesis using a four-dimensionalvariational data assimilation (4D-VAR) method. The radar data assimilation results insignificant improvements in the numerical simulation of Nuri’s genesis. Severalconfigurations of data assimilation are evaluated. Specifically, assimilation of radialvelocity leads to more improvement in intensity forecasts, whereas track forecasts arebetter simulated by the assimilation of radar-retrieved wind components. Improvedanalysis and forecasts are obtained when both radial velocity and retrieved winds areassimilated. In addition, 4D-VAR performs better than three-dimensional variational dataassimilation (3D-VAR) in radar data assimilation. The positive impact of radar dataassimilation can be attributed to the improved simulations of convective evolution andthe enhanced midlevel vortex and moisture conditions.
Subjects/Keywords: Data assimilation; Numerical simulation; Tropical cyclone genesis
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Li, Z. (2013). Studying the genesis of typhoon Nuri (2008) with numerical simulations and data assimilation. (Doctoral Dissertation). University of Utah. Retrieved from http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/3482/rec/2297
Chicago Manual of Style (16th Edition):
Li, Zhan. “Studying the genesis of typhoon Nuri (2008) with numerical simulations and data assimilation.” 2013. Doctoral Dissertation, University of Utah. Accessed February 26, 2021.
http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/3482/rec/2297.
MLA Handbook (7th Edition):
Li, Zhan. “Studying the genesis of typhoon Nuri (2008) with numerical simulations and data assimilation.” 2013. Web. 26 Feb 2021.
Vancouver:
Li Z. Studying the genesis of typhoon Nuri (2008) with numerical simulations and data assimilation. [Internet] [Doctoral dissertation]. University of Utah; 2013. [cited 2021 Feb 26].
Available from: http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/3482/rec/2297.
Council of Science Editors:
Li Z. Studying the genesis of typhoon Nuri (2008) with numerical simulations and data assimilation. [Doctoral Dissertation]. University of Utah; 2013. Available from: http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/3482/rec/2297
Texas A&M University
15.
Brainard, Adam R.
Regionally Enhanced Global Data Assimilation (REG DA): An Evaluation of the Limited Area Model Performance.
Degree: MS, Atmospheric Sciences, 2017, Texas A&M University
URL: http://hdl.handle.net/1969.1/161291
► Regionally Enhanced Global (REG) Data Assimilation (DA) is a method of global data assimilation in which high-resolution information from a single or multiple Limited Area…
(more)
▼ Regionally Enhanced Global (REG)
Data Assimilation (DA) is a method of global
data assimilation in which high-resolution information from a single or multiple Limited Area Model (LAM) domains is blended with the global model information to create a regionally enhanced analysis of the global atmospheric state. This approach has been demonstrated to benefit both local and global model forecasts in idealized studies but has never been tested on operational numerical weather prediction models. This study investigates the limited area model forecast performance of an implementation of the REG DA approach on the operational 4D-Var
data assimilation system, global model, and limited area model of the U.S. Navy. This implementation is called REG 4D-Var. The results of analysis-forecast experiments with the system show that the approach leads to small, but statistically significant overall forecast improvements and large and significant forecast improvements for Hurricane Sandy.
Advisors/Committee Members: Szunyogh, Istvan (advisor), Nowotarski, Christopher (committee member), Chang, Ping (committee member).
Subjects/Keywords: REG DA; Data Assimilation; blending; COAMPS; NAVGEM
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Brainard, A. R. (2017). Regionally Enhanced Global Data Assimilation (REG DA): An Evaluation of the Limited Area Model Performance. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/161291
Chicago Manual of Style (16th Edition):
Brainard, Adam R. “Regionally Enhanced Global Data Assimilation (REG DA): An Evaluation of the Limited Area Model Performance.” 2017. Masters Thesis, Texas A&M University. Accessed February 26, 2021.
http://hdl.handle.net/1969.1/161291.
MLA Handbook (7th Edition):
Brainard, Adam R. “Regionally Enhanced Global Data Assimilation (REG DA): An Evaluation of the Limited Area Model Performance.” 2017. Web. 26 Feb 2021.
Vancouver:
Brainard AR. Regionally Enhanced Global Data Assimilation (REG DA): An Evaluation of the Limited Area Model Performance. [Internet] [Masters thesis]. Texas A&M University; 2017. [cited 2021 Feb 26].
Available from: http://hdl.handle.net/1969.1/161291.
Council of Science Editors:
Brainard AR. Regionally Enhanced Global Data Assimilation (REG DA): An Evaluation of the Limited Area Model Performance. [Masters Thesis]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/161291
Penn State University
16.
Poterjoy, Jonathan.
Ensemble and hybrid four-dimensional data assimilation for tropical cyclone analysis and prediction.
Degree: 2014, Penn State University
URL: https://submit-etda.libraries.psu.edu/catalog/22698
► Numerical models and observations contain critical information regarding the earth-atmosphere system: they present a means of quantifying the system dynamics and provide evidence of the…
(more)
▼ Numerical models and observations contain critical information regarding the earth-atmosphere system: they present a means of quantifying the system dynamics and provide evidence of the true system state, respectively. These two sources of information, however, are more valuable when combined into a single, dynamically consistent dataset. The objective of
data assimilation in geosciences is to find an estimate of the model state that is statistically optimal, given all information known about the system, while preserving physical balances in the system dynamics. Another objective is to quantify the uncertainty in the resulting state estimate, which can be used for designing future observing networks, examining predictability limits, and initializing probabilistic model forecasts.
This dissertation provides an introduction to atmospheric
data assimilation in the context of tropical cyclone modeling efforts at Penn State University using the Weather Research and Forecasting (WRF) model. The first chapter focuses on the role of forecast error covariance, and the necessity of using flow-dependent statistics from ensembles to initialize tropical cyclones with consistent inner-core structure. Chapter two presents an investigation on sampling errors in ensemble
data assimilation systems, and discusses some of the major challenges for applying the Ensemble Kalman filter (EnKF) for mesoscale applications. An EnKF is applied in chapter three to explore the predictability and genesis of Hurricane Karl (2010), and study the impact of field observations in forecasting its track and intensity. The Hurricane Karl case study is revisited in chapter four to examine the impact of applying four-dimensional variational (4DVar) and hybrid ensemble-4DVar (E4DVar)
data assimilation methods for analyzing and forecasting genesis. The last chapter provides a more theoretical perspective on hybrid four-dimensional
data assimilation. It compares the E4DVar approach used for the WRF model in chapter 4, with an alternative method that is being considered for operational use at several national forecast centers. This comparison is performed using a low-dimensional dynamical system to investigate several aspects of these methods in detail.
Advisors/Committee Members: Fuqing Zhang, Dissertation Advisor/Co-Advisor, Fuqing Zhang, Committee Chair/Co-Chair, Eugene Edmund Clothiaux, Committee Member, Jenni Evans, Committee Member, Runze Li, Committee Member, Xiang Yu Huang, Special Member.
Subjects/Keywords: Data assimilation; Kalman filtering; tropical cyclones
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Poterjoy, J. (2014). Ensemble and hybrid four-dimensional data assimilation for tropical cyclone analysis and prediction. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/22698
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Poterjoy, Jonathan. “Ensemble and hybrid four-dimensional data assimilation for tropical cyclone analysis and prediction.” 2014. Thesis, Penn State University. Accessed February 26, 2021.
https://submit-etda.libraries.psu.edu/catalog/22698.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Poterjoy, Jonathan. “Ensemble and hybrid four-dimensional data assimilation for tropical cyclone analysis and prediction.” 2014. Web. 26 Feb 2021.
Vancouver:
Poterjoy J. Ensemble and hybrid four-dimensional data assimilation for tropical cyclone analysis and prediction. [Internet] [Thesis]. Penn State University; 2014. [cited 2021 Feb 26].
Available from: https://submit-etda.libraries.psu.edu/catalog/22698.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Poterjoy J. Ensemble and hybrid four-dimensional data assimilation for tropical cyclone analysis and prediction. [Thesis]. Penn State University; 2014. Available from: https://submit-etda.libraries.psu.edu/catalog/22698
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Penn State University
17.
Kalogeras, Petros.
Evaluating radiance and retrieval assimilation of Mars Thermal Emission Spectrometer Spacecraft observations.
Degree: 2015, Penn State University
URL: https://submit-etda.libraries.psu.edu/catalog/26390
► In the current study two types of data assimilation approaches for updating atmospheric temperature profiles on Mars are explored. Namely, we investigate a retrieval and…
(more)
▼ In the current study two types of
data assimilation approaches for updating atmospheric temperature profiles on Mars are explored. Namely, we investigate a retrieval and a radiance
data assimilation, where in each case the assimilated observations are atmospheric temperature profiles and satellite spectra respectively. Temperature profiles alongside pressure distributions are simulated by utilizing the Mars Global Climate Model (MGCM). In particular, these temperature profiles serve as the prior to the applied filtering technique, an ensemble Kalman filter (EnKF). Direct satellite measurements in the form of Thermal Emission Spectrometer (TES) spectra of radiance available from the Planetary
Data System (PDS), as well as Optimal Spectral Sampling (OSS) temperature retrievals deduced from PDS TES radiance spectra, are considered as the observations to be assimilated. Temperature retrievals, which are not direct observations, depend upon their respective acquisition procedures and in this sense are not unique. On the other hand, observed spectra cannot be compared directly with a weather model. Nevertheless, both geophysical quantities can be considered as observations and in this lies the focus of the current project.
The findings suggest that both types of observations can yield physically sensible Kalman filtering analysis results. However, the quality of the results depends profoundly on how the filtering approach is carried out, with vertical and spectral localizations having the greatest impact.
Comparing retrieval and radiance assimilations for the Martian atmosphere is also relevant to NWP on Earth; the Martian observations network is limited to satellite observations, whereas the terrestrial observations include satellite measurements, atmospheric soundings, and
data procured from ground weather stations. Considering the paucity of
data directly usable in a Martian weather model, the Martian case may then serve as suitable test bed being in the position to highlight viable
assimilation procedures, in the context of operating only with such observed spectra.
Advisors/Committee Members: Steven J Greybush, Thesis Advisor/Co-Advisor, Eugene Edmund Clothiaux, Thesis Advisor/Co-Advisor, Fuqing Zhang, Thesis Advisor/Co-Advisor.
Subjects/Keywords: Data assimilation; Mars; NWP; Retrieval; Radiance; TES
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Kalogeras, P. (2015). Evaluating radiance and retrieval assimilation of Mars Thermal Emission Spectrometer Spacecraft observations. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/26390
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Kalogeras, Petros. “Evaluating radiance and retrieval assimilation of Mars Thermal Emission Spectrometer Spacecraft observations.” 2015. Thesis, Penn State University. Accessed February 26, 2021.
https://submit-etda.libraries.psu.edu/catalog/26390.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Kalogeras, Petros. “Evaluating radiance and retrieval assimilation of Mars Thermal Emission Spectrometer Spacecraft observations.” 2015. Web. 26 Feb 2021.
Vancouver:
Kalogeras P. Evaluating radiance and retrieval assimilation of Mars Thermal Emission Spectrometer Spacecraft observations. [Internet] [Thesis]. Penn State University; 2015. [cited 2021 Feb 26].
Available from: https://submit-etda.libraries.psu.edu/catalog/26390.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Kalogeras P. Evaluating radiance and retrieval assimilation of Mars Thermal Emission Spectrometer Spacecraft observations. [Thesis]. Penn State University; 2015. Available from: https://submit-etda.libraries.psu.edu/catalog/26390
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Penn State University
18.
Lei, Lili.
A Hybrid Nudging-Ensemble Kalman Filter Approach to Data Assimilation
.
Degree: 2011, Penn State University
URL: https://submit-etda.libraries.psu.edu/catalog/12441
► A hybrid nudging-ensemble Kalman filter (HNEnKF) data assimilation approach that effectively combines the advantages of nudging and the EnKF is proposed and explored in this…
(more)
▼ A hybrid nudging-ensemble Kalman filter (HNEnKF)
data assimilation approach that effectively combines the advantages of nudging and the EnKF is proposed and explored in this dissertation. It is first developed and tested in simplified models, the Lorenz three-variable system and a more realistic 2D shallow water model, with simulated observations, and then in a full-physics 3D mesoscale model, the Weather Research and Forecasting (WRF) model, using real observations.
The HNEnKF uses the EnKF to obtain a flow-dependent / time-dependent background error covariance matrix that can be used to compute a flow-dependent / time-varying nudging coefficient matrix. It also extends the nudging magnitude matrix to include the inter-variable influences of innovations via nonzero off-diagonal elements of the EnKF gain matrix. This additional coupling between the observations and the multivariate state may lead to a faster and more accurate adjustment of the background to observations than does traditional nudging. By use of nudging-type terms, the HNEnKF applies the EnKF gradually in time to achieve a more gradual
data assimilation that greatly reduces the insertion noise common with intermittent methods such as the EnKF. Thus it combines the strengths of nudging and the EnKF while avoiding their individual weaknesses.
In the Lorenz three-variable system, the HNEnKF promotes a better fit of an analysis to
data compared to that produced by nudging. When model error is introduced, it produces similar or better RMS errors compared to the EnKF while minimizing the error spikes / discontinuities created by the intermittent EnKF. It provides a continuous
data assimilation with better inter-variable consistency and improved temporal smoothness than that of the EnKF. Compared to the ensemble Kalman smoother (EnKS), considered to be a “gold standard” in statistical
data assimilation methods, the HNEnKF has similar or better temporal smoothness with much smaller CPU time and
data storage requirements.
In the 2D shallow water model, a quasi-stationary wave case and a moving vortex case are used to investigate the
data assimilation methods. The HNEnKF generally produces smaller RMS errors in both the height and wind fields than the nudging and EnKF applied separately. The HNEnKF also has better temporal smoothness than the EnKF and the more practical and computationally efficient lagged EnKS used in the shallow water model. The HNEnKF takes advantage of the EnKF by effectively reducing the RMS errors through the flow-dependent background error covariances, and also retains the benefits of the continuous nudging by reducing the RMS errors gradually over time. Moreover, the HNEnKF produces a smoother evolution of the ageostrophic wind without any strong discontinuities / dynamic imbalances around the observation time, while the EnKF exhibits large bursts in the ageostrophic wind after the observations are assimilated.
The HNEnKF is further tested in the 3D WRF model with real observations using a Cross Appalachian Tracer…
Advisors/Committee Members: David R Stauffer, Dissertation Advisor/Co-Advisor, David R Stauffer, Committee Chair/Co-Chair, George Spencer Young, Committee Member, Sue Ellen Haupt, Committee Member, Qiang Du, Committee Member.
Subjects/Keywords: nudging; EnKF; insertion noise; hybrid data assimilation
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Lei, L. (2011). A Hybrid Nudging-Ensemble Kalman Filter Approach to Data Assimilation
. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/12441
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Lei, Lili. “A Hybrid Nudging-Ensemble Kalman Filter Approach to Data Assimilation
.” 2011. Thesis, Penn State University. Accessed February 26, 2021.
https://submit-etda.libraries.psu.edu/catalog/12441.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Lei, Lili. “A Hybrid Nudging-Ensemble Kalman Filter Approach to Data Assimilation
.” 2011. Web. 26 Feb 2021.
Vancouver:
Lei L. A Hybrid Nudging-Ensemble Kalman Filter Approach to Data Assimilation
. [Internet] [Thesis]. Penn State University; 2011. [cited 2021 Feb 26].
Available from: https://submit-etda.libraries.psu.edu/catalog/12441.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Lei L. A Hybrid Nudging-Ensemble Kalman Filter Approach to Data Assimilation
. [Thesis]. Penn State University; 2011. Available from: https://submit-etda.libraries.psu.edu/catalog/12441
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Penn State University
19.
Hanson, Glen Steven.
Impact of Assimilating Surface Pressure Observations from Smartphones on a Regional, High Resolution Ensemble Forecast: Observing System Simulation Experiments.
Degree: 2016, Penn State University
URL: https://submit-etda.libraries.psu.edu/catalog/28709
► Smartphones equipped with barometers represent an untapped, and incredibly dense source of surface pressure observations that could be used to improve numerical weather prediction (NWP)…
(more)
▼ Smartphones equipped with barometers represent an untapped, and incredibly dense source of surface pressure observations that could be used to improve numerical weather prediction (NWP) forecasts. To explore their potential value, a series of observing system simulation experiments (OSSEs) were performed using WRF-ARW and the PSU WRF-EnKF
Data Assimilation System at convective allowing scales to assimilate synthetic smartphone observations of a severe weather event from 20 April 2015. The experiments assessed the analysis and ensemble forecast performances for a variety of
assimilation set-ups, testing the effect of observation error, horizontal radius of influence (HROI), and
assimilation frequency. Additionally, neighborhood-based fractions skill scores (FSS) and relative operating characteristic (ROC) curves showed that the rapid
assimilation of smartphone
data can produce forecasts with more skill than forecasts that only rely on traditional surface observations (METARs). These findings can be used to guide further research using real smartphone
data to supplement conventional observations or as a stand-alone observation network in otherwise
data-sparse regions.
Advisors/Committee Members: Steven J Greybush, Thesis Advisor/Co-Advisor.
Subjects/Keywords: data assimilation; EnKF; smartphone; surface pressure
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Hanson, G. S. (2016). Impact of Assimilating Surface Pressure Observations from Smartphones on a Regional, High Resolution Ensemble Forecast: Observing System Simulation Experiments. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/28709
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Hanson, Glen Steven. “Impact of Assimilating Surface Pressure Observations from Smartphones on a Regional, High Resolution Ensemble Forecast: Observing System Simulation Experiments.” 2016. Thesis, Penn State University. Accessed February 26, 2021.
https://submit-etda.libraries.psu.edu/catalog/28709.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Hanson, Glen Steven. “Impact of Assimilating Surface Pressure Observations from Smartphones on a Regional, High Resolution Ensemble Forecast: Observing System Simulation Experiments.” 2016. Web. 26 Feb 2021.
Vancouver:
Hanson GS. Impact of Assimilating Surface Pressure Observations from Smartphones on a Regional, High Resolution Ensemble Forecast: Observing System Simulation Experiments. [Internet] [Thesis]. Penn State University; 2016. [cited 2021 Feb 26].
Available from: https://submit-etda.libraries.psu.edu/catalog/28709.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Hanson GS. Impact of Assimilating Surface Pressure Observations from Smartphones on a Regional, High Resolution Ensemble Forecast: Observing System Simulation Experiments. [Thesis]. Penn State University; 2016. Available from: https://submit-etda.libraries.psu.edu/catalog/28709
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Penn State University
20.
Ying, Yue.
Ensemble Data Assimilation for the Analysis and Prediction of Multiscale Tropical Weather Systems.
Degree: 2018, Penn State University
URL: https://submit-etda.libraries.psu.edu/catalog/15110yxy159
► Tropical weather systems are important components of the global circulation that span a wide range of spatial and temporal scales. On the large-scale end of…
(more)
▼ Tropical weather systems are important components of the global circulation that span a wide range of spatial and temporal scales. On the large-scale end of the spectrum, the Madden-Julian Oscillation (MJO) is found to be the dominant mode. Atmospheric wave motion due to Earth’s rotation and gravity fills the spectrum from weeks to hours and from tens of thousands of kilometers to a few tens of kilometers. The thermally driven convective processes at smaller scales are chaotic in nature, which poses an intrinsic limit on the long-term predictability of tropical weather through coupling and scale interaction. This dissertation seeks to identify the predictability limits for tropical atmosphere, establishing an upper bound in expected prediction skill of these weather systems. Other scientific questions this dissertation answered are how much future satellite observations can improve the prediction skill, and how to design adaptive multiscale
data assimilation methods that make better use of the available observations.
Using a convection-permitting numerical model, Weather Research and Forecasting (WRF), an MJO active phase during October 2011 is simulated. The practical predictability limit is estimated from an ensemble forecast with realistic initial and boundary condition uncertainties sampled from the operational global model forecasts. Predictability limit is reached when the ensemble spread is indistinguishable from random climatological draws. Results indicate predictability is scale dependent. There is a sharp transition from slow to fast error growth at the intermediate scales (~500 km), separating the more predictable large-scale components (~2 weeks) from the less predictable small-scale components (<1 day). The intrinsic predictability limits, estimated by reducing the uncertainties to 1%, are >2 weeks for larger scales and <3 days for small scales. An Observing System Simulation Experiment (OSSE) is conducted using the Ensemble Kalman Filter (EnKF) to evaluate the potential improvements in the prediction skill through assimilating current and future satellite observations. Results show that the currently available temperature, humidity profiles and wind vectors retrieved from infrared and microwave satellite sounder
data can extend the skillful forecast lead time by as much as 4 days for the larger scales. With prospective improvement in resolution and complementary sampling strategies, the prediction skill can be further improved, especially for the smaller scales. These results shed lights on the need, design and cost-benefit analysis of future observing systems for better tropical weather prediction.
For ensemble filtering, covariance localization and inflation methods are required to account for sampling errors due to limited ensemble size and unrepresented model errors. Tuning the localization and inflation to achieve optimal filter performance is a laborious process, thus adaptive algorithms are much favored. In this dissertation, an adaptive covariance relaxation (ACR) method is proposed and tested…
Advisors/Committee Members: Fuqing Zhang, Dissertation Advisor/Co-Advisor, Fuqing Zhang, Committee Chair/Co-Chair, Steven J Greybush, Committee Member, David Jonathan Stensrud, Committee Member, Xiaofeng Liu, Outside Member, Jeffrey L Anderson, Special Member.
Subjects/Keywords: tropical weather; multiscale; predictability; data assimilation
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Ying, Y. (2018). Ensemble Data Assimilation for the Analysis and Prediction of Multiscale Tropical Weather Systems. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/15110yxy159
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Ying, Yue. “Ensemble Data Assimilation for the Analysis and Prediction of Multiscale Tropical Weather Systems.” 2018. Thesis, Penn State University. Accessed February 26, 2021.
https://submit-etda.libraries.psu.edu/catalog/15110yxy159.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Ying, Yue. “Ensemble Data Assimilation for the Analysis and Prediction of Multiscale Tropical Weather Systems.” 2018. Web. 26 Feb 2021.
Vancouver:
Ying Y. Ensemble Data Assimilation for the Analysis and Prediction of Multiscale Tropical Weather Systems. [Internet] [Thesis]. Penn State University; 2018. [cited 2021 Feb 26].
Available from: https://submit-etda.libraries.psu.edu/catalog/15110yxy159.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Ying Y. Ensemble Data Assimilation for the Analysis and Prediction of Multiscale Tropical Weather Systems. [Thesis]. Penn State University; 2018. Available from: https://submit-etda.libraries.psu.edu/catalog/15110yxy159
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Victoria University of Wellington
21.
Maxwell, Deborah.
A Rainfall - Runoff Model for the Highly Regulated Lake Taupo Catchment, Using a Constrained Ensemble Kalman Filter to Improve the Accuracy and Reliability of Model Output.
Degree: 2013, Victoria University of Wellington
URL: http://hdl.handle.net/10063/2703
► Lake Taupo is the effective source of the Waikato River. The Waikato Power Scheme relies on the outflow from the lake for moderated flows throughout…
(more)
▼ Lake Taupo is the effective source of the Waikato River. The Waikato Power Scheme relies on the outflow from the lake for moderated flows throughout the year. As the lake is maintained between a 1.4m operating range, it is the inflows to the lake that determine the amount of water available to the scheme for electricity generation. These inflows have not been modelled in any detail prior to this dissertation.
This dissertation aims to develop a predictive rainfall-runoff model that can provide accurate and reliable inflow and lake level forecasts for the Lake Taupo catchment. Model formulation is guided by a fundamental understanding of catchment hydrologic principles and an in-depth assessment of catchment hydrologic behaviour. The model is a semi-distributed physically-consistent conceptual model which aims to provide a parsimonious representation of different storages and flow pathways through a catchment. It has three linear sub-surface stores. Drainage to these stores is related to the size of the saturation zone, utilising the concept of a variable source area. This model is used to simulate inflows from gauged unregulated sub-catchments. It is also used to estimate the inflow from ungauged areas through regionalisation. For regulated sub-catchments, the model is modified to incorporate available
data and information relating to the relevant scheme‟s operation, resource consent conditions and other physical and legislative constraints. The output from such models is
subject to considerable uncertainty due to simplifications in the model structure, estimated parameter values and imperfect driving
data. For robust decision making, it is important this uncertainty is reduced to within acceptable levels. In this study, a constrained Ensemble Kalman Filter (EnKF) is applied to the four unregulated gauged catchments to deal with model structure and
data uncertainties. Used in conjunction with Monte Carlo simulations, all three sources of uncertainty are addressed. Simple mass and flux constraints are applied to the four (soil storage, baseflow, interflow and fastflow) model states. Without these constraints states can be adjusted beyond what is physically possible, compromising the integrity of model output. It is demonstrated that the application of a constrained EnKF improves the accuracy and reliability of model output.Due to the complexity of the Tongariro Power Scheme (TPS) and the limited
data available to model it, the conceptual model is not suitable. Rather, a statistical probability analysis is used to estimate the discharge from this scheme given the month of the year, day of the week and hour of the day.
Model output is combined and converted into a corresponding change in lake level. The model is evaluated over a wide range of hydrological and meteorological conditions. An in-depth critical evaluation is undertaken on eight events chosen a priori as representation of both extreme and „usual‟ conditions. The model provides reasonable predictions of lake level given the uncertainty with the TPS, complexity…
Advisors/Committee Members: McGregor, James, Jackson, Bethanna.
Subjects/Keywords: Rainfall - runoff model; Data assimilation; Taupo catchment
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Maxwell, D. (2013). A Rainfall - Runoff Model for the Highly Regulated Lake Taupo Catchment, Using a Constrained Ensemble Kalman Filter to Improve the Accuracy and Reliability of Model Output. (Doctoral Dissertation). Victoria University of Wellington. Retrieved from http://hdl.handle.net/10063/2703
Chicago Manual of Style (16th Edition):
Maxwell, Deborah. “A Rainfall - Runoff Model for the Highly Regulated Lake Taupo Catchment, Using a Constrained Ensemble Kalman Filter to Improve the Accuracy and Reliability of Model Output.” 2013. Doctoral Dissertation, Victoria University of Wellington. Accessed February 26, 2021.
http://hdl.handle.net/10063/2703.
MLA Handbook (7th Edition):
Maxwell, Deborah. “A Rainfall - Runoff Model for the Highly Regulated Lake Taupo Catchment, Using a Constrained Ensemble Kalman Filter to Improve the Accuracy and Reliability of Model Output.” 2013. Web. 26 Feb 2021.
Vancouver:
Maxwell D. A Rainfall - Runoff Model for the Highly Regulated Lake Taupo Catchment, Using a Constrained Ensemble Kalman Filter to Improve the Accuracy and Reliability of Model Output. [Internet] [Doctoral dissertation]. Victoria University of Wellington; 2013. [cited 2021 Feb 26].
Available from: http://hdl.handle.net/10063/2703.
Council of Science Editors:
Maxwell D. A Rainfall - Runoff Model for the Highly Regulated Lake Taupo Catchment, Using a Constrained Ensemble Kalman Filter to Improve the Accuracy and Reliability of Model Output. [Doctoral Dissertation]. Victoria University of Wellington; 2013. Available from: http://hdl.handle.net/10063/2703
Oregon State University
22.
Javaheri, Amir.
Assimilation of Multi-Sensor Data into Numerical Hydrodynamic Models of Inland Water Bodies.
Degree: PhD, Civil Engineering, 2016, Oregon State University
URL: http://hdl.handle.net/1957/60000
► Numerical models are effective tools for simulating complex physical processes such as hydrodynamic and water quality processes in aquatic systems. The accuracy of the model…
(more)
▼ Numerical models are effective tools for simulating complex physical processes such as hydrodynamic and water quality processes in aquatic systems. The accuracy of the model is dependent on multiple model parameters and variables that need to be calibrated and regularly updated to reproduce changing aquatic conditions accurately. Multi-sensor water temperature observations, such as remote sensing
data and in situ monitoring technologies, can improve model accuracy by providing benefits of individual monitoring technology to the model updating process. In contrast to in-situ temperature sensors, remote sensing technologies (e.g., satellites) provide the benefit of collecting measurements with better X-Y spatial coverage. However, the temporal resolution of satellite
data is limited comparing to in-situ measurements. Numerical models and all source of observations have large uncertainty coming from different sources such as errors of approximation and truncation, uncertain model inputs, error in measuring devices and etc.
Data assimilation (DA) is able to sequentially update the model state variables by considering the uncertainty in model and observations and estimate the model states and outputs more accurately.
Data Assimilation has been proposed for multiple water resources studies that require rapid employment of incoming observations to update and improve accuracy of operational prediction models. The usefulness of DA approaches in assimilating water temperature observations from different types of monitoring technologies (e.g., remote sensing and
in-situ sensors) into numerical models of in-land water bodies (e.g., reservoirs, lakes, and rivers) has, however, received limited attention. Assimilating of water temperature measurements from satellites can introduce biases in the updated numerical model of water bodies because the physical region represented by these measurements do not directly correspond with the numerical model's representation of the water column. The main research objective of this study is to efficiently assimilate multi-sensor water temperature
data into the hydrodynamic model of water bodies in order to improve the model accuracy. Four specific objectives were addressed in this work to accomplish the overall goal:
* Objective 1: Propose a novel approach to address the representation challenge of model and measurements by coupling a skin temperature adjustment technique based on available air and in-situ water temperature observations, with an ensemble Kalman filter (EnKF) based
data assimilation technique for reservoirs and lakes.
* Objective 2: Investigate whether
assimilation of remotely sensed temperature observations using the proposed
data fusion approach can improve model accuracy with respect to in-situ temperature observations as well as remote sensing
data.
* Objective 3: Investigate a global sensitivity analysis tool that combines Latin-hypercube and one-factor-at-a-time sampling to investigate the most sensitive model inputs and parameters in calculating the water age and…
Advisors/Committee Members: Babbar-Sebens, Meghna (advisor), Miller, Robert N. (committee member).
Subjects/Keywords: Data assimilation; Bodies of water – Mathematical models
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Javaheri, A. (2016). Assimilation of Multi-Sensor Data into Numerical Hydrodynamic Models of Inland Water Bodies. (Doctoral Dissertation). Oregon State University. Retrieved from http://hdl.handle.net/1957/60000
Chicago Manual of Style (16th Edition):
Javaheri, Amir. “Assimilation of Multi-Sensor Data into Numerical Hydrodynamic Models of Inland Water Bodies.” 2016. Doctoral Dissertation, Oregon State University. Accessed February 26, 2021.
http://hdl.handle.net/1957/60000.
MLA Handbook (7th Edition):
Javaheri, Amir. “Assimilation of Multi-Sensor Data into Numerical Hydrodynamic Models of Inland Water Bodies.” 2016. Web. 26 Feb 2021.
Vancouver:
Javaheri A. Assimilation of Multi-Sensor Data into Numerical Hydrodynamic Models of Inland Water Bodies. [Internet] [Doctoral dissertation]. Oregon State University; 2016. [cited 2021 Feb 26].
Available from: http://hdl.handle.net/1957/60000.
Council of Science Editors:
Javaheri A. Assimilation of Multi-Sensor Data into Numerical Hydrodynamic Models of Inland Water Bodies. [Doctoral Dissertation]. Oregon State University; 2016. Available from: http://hdl.handle.net/1957/60000
23.
Shi, Yingxi.
Critical Evaluations Of Modis And Misr Satellite Aerosol Products For Aerosol Modeling Applications.
Degree: PhD, Atmospheric Sciences, 2015, University of North Dakota
URL: https://commons.und.edu/theses/1963
► The study of uncertainties in satellite aerosol products is essential to aerosol data assimilation and modeling efforts. In this study, with the assistance of…
(more)
▼ The study of uncertainties in satellite aerosol products is essential to aerosol
data assimilation and modeling efforts. In this study, with the assistance of ground- based observations, uncertainties in Moderate Resolution Imaging Spectroradiometer (MODIS) collection 5 Deep Blue (DB), Multi-Angle Imaging Spectroradiometer (MISR) version 22 aerosol products, and the newly released collection 6 Dark Target over-ocean and DB products were evaluated. For each product, systematic biases were analyzed against observing conditions. Empirical correction procedures and
data filtering steps were generated to develop noise and bias reduced DA-quality aerosol products for modeling related applications.
Special attention was also directed at the potential low bias in satellite aerosol optical depth (AOD) climatology due to misclassification of aerosols as clouds over Asia. A heavy aerosol identifying system (HAIS) was developed through the combined use of the Ozone Monitoring Instrument (OMI) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) products for detecting heavy smoke aerosol plumes. Upon extensive evaluation, HAIS was applied to one year of collocated OMI, CALIOP, and MODIS
data to study the misclassifications related low bias. This study suggests that the misclassification of heavy smoke aerosol plumes by MODIS is rather infrequent and thus introduces an insignificant low bias to its AOD climatology. Still, this study confirms that misclassification happens in both active- and passive- based satellite aerosol products and needs to be studied for forecasting these events.
Advisors/Committee Members: Jianglong Zhang.
Subjects/Keywords: Aerosols; Data assimilation; Satellite retrievals; Uncertainty evaluations
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Shi, Y. (2015). Critical Evaluations Of Modis And Misr Satellite Aerosol Products For Aerosol Modeling Applications. (Doctoral Dissertation). University of North Dakota. Retrieved from https://commons.und.edu/theses/1963
Chicago Manual of Style (16th Edition):
Shi, Yingxi. “Critical Evaluations Of Modis And Misr Satellite Aerosol Products For Aerosol Modeling Applications.” 2015. Doctoral Dissertation, University of North Dakota. Accessed February 26, 2021.
https://commons.und.edu/theses/1963.
MLA Handbook (7th Edition):
Shi, Yingxi. “Critical Evaluations Of Modis And Misr Satellite Aerosol Products For Aerosol Modeling Applications.” 2015. Web. 26 Feb 2021.
Vancouver:
Shi Y. Critical Evaluations Of Modis And Misr Satellite Aerosol Products For Aerosol Modeling Applications. [Internet] [Doctoral dissertation]. University of North Dakota; 2015. [cited 2021 Feb 26].
Available from: https://commons.und.edu/theses/1963.
Council of Science Editors:
Shi Y. Critical Evaluations Of Modis And Misr Satellite Aerosol Products For Aerosol Modeling Applications. [Doctoral Dissertation]. University of North Dakota; 2015. Available from: https://commons.und.edu/theses/1963
Université Catholique de Louvain
24.
Massonnet, François.
Evaluation and improvement of climate simulations of sea ice.
Degree: 2014, Université Catholique de Louvain
URL: http://hdl.handle.net/2078.1/146359
► At high latitudes, a significant part of the oceans is covered by sea ice that forms when seawater freezes. Sea ice is a major player…
(more)
▼ At high latitudes, a significant part of the oceans is covered by sea ice that forms when seawater freezes. Sea ice is a major player in the global climate system. It is also a primary indicator of climate change, as it responds rapidly to variations in surface air temperatures and wind regimes. Since years now, scientists have developed numerical models to assist them in better understanding the sea ice system. These models simulate the evolution of the main sea ice characteristics at high spatial resolution and temporal frequency, which makes them valuable tools to enlarge the picture given by incomplete observations. In addition, models are used for their predictive skills, from seasonal to centennial horizons. However, in spite of their increasing complexity, substantial uncertainties still persist in model reconstructions and predictions of Arctic and Antarctic sea ice. In this doctoral thesis, we have developed the tools to properly identify the possible sources of these uncertainties. We have highlighted the important role of model physics and initial conditions for the climate simulations of Arctic sea ice. We have also implemented statistical methods to optimally constrain the models given measurements, a field of research known as data assimilation. In the framework of sea ice data assimilation, we have been able to propose a multi-decadal reconstruction of Antarctic sea ice thickness, which is not possible from observational data only. Sea ice models become more comprehensive. At the same time, more and more observations are available to evaluate, constrain and improve them. To address the sensible questions about the future of sea ice and of climate in general, an optimal use of these two sources of information will be required. This thesis illustrates some steps to move forward in this direction.
(SC - Sciences) – UCL, 2014
Advisors/Committee Members: UCL - SST/ELI/ELIC - Earth & Climate, UCL - Faculté des Sciences, Fichefet, Thierry, Goosse, Hugues, Crucifix, Michel, Legat, Vincent, De Keersmaecker, Marie-Laurence, Vancoppenolle, Martin, Bertino, Laurent, Notz, Dirk.
Subjects/Keywords: Sea ice modeling; Data assimilation; Climate change
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Massonnet, F. (2014). Evaluation and improvement of climate simulations of sea ice. (Thesis). Université Catholique de Louvain. Retrieved from http://hdl.handle.net/2078.1/146359
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Massonnet, François. “Evaluation and improvement of climate simulations of sea ice.” 2014. Thesis, Université Catholique de Louvain. Accessed February 26, 2021.
http://hdl.handle.net/2078.1/146359.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Massonnet, François. “Evaluation and improvement of climate simulations of sea ice.” 2014. Web. 26 Feb 2021.
Vancouver:
Massonnet F. Evaluation and improvement of climate simulations of sea ice. [Internet] [Thesis]. Université Catholique de Louvain; 2014. [cited 2021 Feb 26].
Available from: http://hdl.handle.net/2078.1/146359.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Massonnet F. Evaluation and improvement of climate simulations of sea ice. [Thesis]. Université Catholique de Louvain; 2014. Available from: http://hdl.handle.net/2078.1/146359
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Delft University of Technology
25.
Arkesteijn, E.C.M.M. (author).
Uncertainty assessment of the geometry of an aquitard using an EnKF and EnKF-GMM.
Degree: 2014, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:1672b38e-fcf6-4f9f-9299-e23e241f710f
► Hydraulic head data is frequently used for the calibration of groundwater flow models, usually with the main objective to improve the model performance. The hydraulic…
(more)
▼ Hydraulic head data is frequently used for the calibration of groundwater flow models, usually with the main objective to improve the model performance. The hydraulic parameters in a groundwater flow model depend on the underlying geometry of the subsurface and the permeability of the soil. In the current calibration routines, the geometry is considered known, such that all uncertainties of the hydraulic parameters are ascribed to the permeabilities. After calibration these permeabilities may have physically unreasonable values, indicating that the estimate of the geometry is likely to be wrong. In this thesis the roles are reversed. A calibration procedure that focuses on the uncertainty of the geometry is performed. This shift introduces a dependency between the hydraulic parameters that is not considered in the current calibration method. An EnKF and EnKF-GMM are applied to a synthetic test case where only the geometry of one aquitard is considered uncertain. The filters are performed with the objectives to 1) localise the extent of the aquitard, and 2) find a probability distribution function for the thickness of the aquitard. In a series of experiments it is shown that the EnKF is only suitable in situations where the exact extent of the aquitard is known. In other cases, the probability distribution function of the thickness is bimodal, resulting in an EnKF that performs poorly and produces physically unrealistic outputs. As a solution, the EnKF-GMM is proposed. This extension of the regular EnKF can be used in more general scenarios as it allows a multimodal distribution as posterior distribution. Roughly speaking, the EnKF-GMM is an application of two EnKFs simultaneously. For two separate populations (modes) an EnKF is performed, and after each iteration the inhabitants of the population have the possibility to cross over to the other population. The cross-over probabilities are based on the likelihood of each population. The results of the experiments show that the EnKF-GMM is able to define probabilities on the extent of the aquitard. However, it fails to find a proper probability distribution function of the thickness. Filter divergence occurs as a result of the insufficient amount of information that hydraulic head data contains.
Applied mathematics
Electrical Engineering, Mathematics and Computer Science
Advisors/Committee Members: Heemink, A.W. (mentor), Van Geer, F.C. (mentor), Lourens, A. (mentor).
Subjects/Keywords: data assimilation; EnKF; EnKF-GMM; uncertainty assessment
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Arkesteijn, E. C. M. M. (. (2014). Uncertainty assessment of the geometry of an aquitard using an EnKF and EnKF-GMM. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:1672b38e-fcf6-4f9f-9299-e23e241f710f
Chicago Manual of Style (16th Edition):
Arkesteijn, E C M M (author). “Uncertainty assessment of the geometry of an aquitard using an EnKF and EnKF-GMM.” 2014. Masters Thesis, Delft University of Technology. Accessed February 26, 2021.
http://resolver.tudelft.nl/uuid:1672b38e-fcf6-4f9f-9299-e23e241f710f.
MLA Handbook (7th Edition):
Arkesteijn, E C M M (author). “Uncertainty assessment of the geometry of an aquitard using an EnKF and EnKF-GMM.” 2014. Web. 26 Feb 2021.
Vancouver:
Arkesteijn ECMM(. Uncertainty assessment of the geometry of an aquitard using an EnKF and EnKF-GMM. [Internet] [Masters thesis]. Delft University of Technology; 2014. [cited 2021 Feb 26].
Available from: http://resolver.tudelft.nl/uuid:1672b38e-fcf6-4f9f-9299-e23e241f710f.
Council of Science Editors:
Arkesteijn ECMM(. Uncertainty assessment of the geometry of an aquitard using an EnKF and EnKF-GMM. [Masters Thesis]. Delft University of Technology; 2014. Available from: http://resolver.tudelft.nl/uuid:1672b38e-fcf6-4f9f-9299-e23e241f710f
Delft University of Technology
26.
Beers, Karlijn (author).
Data assimilation, Geomechanical parameter estimation in the Groningen hydrocarbon reservoir from PS-InSAR measurements with a particle filter.
Degree: 2018, Delft University of Technology
URL: http://resolver.tudelft.nl/uuid:6db5ad75-8b34-4fce-a570-070c7b6bf6b3
► This thesis explores the usage of the particle filter as a data assimilation technique to estimate subsurface processes, such as reservoir volume change from space-geodetic…
(more)
▼ This thesis explores the usage of the particle filter as a
data assimilation technique to estimate subsurface processes, such as reservoir volume change from space-geodetic PS-InSAR surface measurements. The specific research area is Groningen, where subsidence is induced by hydrocarbon and salt production. The satellite radar PS-InSAR technique is used for observing subsidence values in the line-of-sight for a Radarsat-2 descending and a TerraSAR ascending set of measurements. A geomechanical model, the Mogi point source, translates subsurface volume changes to surface deformation. The geomechanical model parameters are estimated by the
data assimilation technique particle filter from the observed surface measurements. The particle filter is tested on synthetic
data in a couple of test situations with an identical twin experiment. In addition the knowledge of the synthetic
data experiments is used in the particle filter application on the PS-InSAR measurements of the Groningen gas field. A workflow is created in how to apply the steps of the particle filter on the PS-InSAR measurements in Groningen. Several solutions are developed for improving the fit between measurements and model.
Advisors/Committee Members: Hanssen, Ramon (mentor), Vossepoel, Femke (mentor), Delft University of Technology (degree granting institution).
Subjects/Keywords: Data assimilation; Particle Filter; InSAR; Groningen
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Beers, K. (. (2018). Data assimilation, Geomechanical parameter estimation in the Groningen hydrocarbon reservoir from PS-InSAR measurements with a particle filter. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:6db5ad75-8b34-4fce-a570-070c7b6bf6b3
Chicago Manual of Style (16th Edition):
Beers, Karlijn (author). “Data assimilation, Geomechanical parameter estimation in the Groningen hydrocarbon reservoir from PS-InSAR measurements with a particle filter.” 2018. Masters Thesis, Delft University of Technology. Accessed February 26, 2021.
http://resolver.tudelft.nl/uuid:6db5ad75-8b34-4fce-a570-070c7b6bf6b3.
MLA Handbook (7th Edition):
Beers, Karlijn (author). “Data assimilation, Geomechanical parameter estimation in the Groningen hydrocarbon reservoir from PS-InSAR measurements with a particle filter.” 2018. Web. 26 Feb 2021.
Vancouver:
Beers K(. Data assimilation, Geomechanical parameter estimation in the Groningen hydrocarbon reservoir from PS-InSAR measurements with a particle filter. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Feb 26].
Available from: http://resolver.tudelft.nl/uuid:6db5ad75-8b34-4fce-a570-070c7b6bf6b3.
Council of Science Editors:
Beers K(. Data assimilation, Geomechanical parameter estimation in the Groningen hydrocarbon reservoir from PS-InSAR measurements with a particle filter. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:6db5ad75-8b34-4fce-a570-070c7b6bf6b3
27.
Hofman Radek.
APPLICATION OF ADVANCED DATA ASSIMILATION METHODS IN OFF-SITE CONSEQUENCE ASSESSMENT
.
Degree: 2011, Czech University of Technology
URL: http://hdl.handle.net/10467/8017
APPLICATION OF ADVANCED DATA ASSIMILATION METHODS IN OFF-SITE CONSEQUENCE ASSESSMENT; APPLICATION OF ADVANCED DATA ASSIMILATION METHODS IN OFF-SITE CONSEQUENCE ASSESSMENT
Advisors/Committee Members: Pecha Petr (advisor).Subjects/Keywords: data assimilation; particle filtering; dispersion modelling
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Radek, H. (2011). APPLICATION OF ADVANCED DATA ASSIMILATION METHODS IN OFF-SITE CONSEQUENCE ASSESSMENT
. (Thesis). Czech University of Technology. Retrieved from http://hdl.handle.net/10467/8017
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Radek, Hofman. “APPLICATION OF ADVANCED DATA ASSIMILATION METHODS IN OFF-SITE CONSEQUENCE ASSESSMENT
.” 2011. Thesis, Czech University of Technology. Accessed February 26, 2021.
http://hdl.handle.net/10467/8017.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Radek, Hofman. “APPLICATION OF ADVANCED DATA ASSIMILATION METHODS IN OFF-SITE CONSEQUENCE ASSESSMENT
.” 2011. Web. 26 Feb 2021.
Vancouver:
Radek H. APPLICATION OF ADVANCED DATA ASSIMILATION METHODS IN OFF-SITE CONSEQUENCE ASSESSMENT
. [Internet] [Thesis]. Czech University of Technology; 2011. [cited 2021 Feb 26].
Available from: http://hdl.handle.net/10467/8017.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Radek H. APPLICATION OF ADVANCED DATA ASSIMILATION METHODS IN OFF-SITE CONSEQUENCE ASSESSMENT
. [Thesis]. Czech University of Technology; 2011. Available from: http://hdl.handle.net/10467/8017
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
28.
Lorenzo, Antonio Tomas.
Short-Term Irradiance Forecasting Using an Irradiance Monitoring Network, Satellite Imagery, and Data Assimilation
.
Degree: 2017, University of Arizona
URL: http://hdl.handle.net/10150/624494
► Solar and other renewable power sources are becoming an integral part of the electrical grid in the United States. In the Southwest US, solar and…
(more)
▼ Solar and other renewable power sources are becoming an integral part of the electrical grid in the United States. In the Southwest US, solar and wind power plants already serve over 20% of the electrical load during the daytime on sunny days in the Spring. While solar power produces fewer emissions and has a lower carbon footprint than burning fossil fuels, solar power is only generated during the daytime and it is variable due to clouds blocking the sun. Electric utilities that are required to maintain a reliable electricity supply benefit from anticipating the schedule of power output from solar power plants. Forecasting the irradiance reaching the ground, the primary input to a solar power forecast, can help utilities understand and respond to the variability. This dissertation will explore techniques to forecast irradiance that make use of
data from a network of sensors deployed throughout Tucson, AZ. The design and deployment of inexpensive sensors used in the network will be described. We will present a forecasting technique that uses
data from the sensor network and outperforms a reference persistence forecast for one minute to two hours in the future. We will analyze the errors of this technique in depth and suggest ways to interpret these errors. Then, we will describe a
data assimilation technique, optimal interpolation, that combines estimates of irradiance derived from satellite images with
data from the sensor network to improve the satellite estimates. These improved satellite estimates form the base of future work that will explore generating forecasts while continuously assimilating new
data.
Advisors/Committee Members: Cronin, Alexander D (advisor), Morzfeld, Matthias (advisor), Cronin, Alexander D. (committeemember), Morzfeld, Matthias (committeemember), Potter, Barrett G. (committeemember).
Subjects/Keywords: data assimilation;
forecasting;
sensor network;
solar power
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Lorenzo, A. T. (2017). Short-Term Irradiance Forecasting Using an Irradiance Monitoring Network, Satellite Imagery, and Data Assimilation
. (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/624494
Chicago Manual of Style (16th Edition):
Lorenzo, Antonio Tomas. “Short-Term Irradiance Forecasting Using an Irradiance Monitoring Network, Satellite Imagery, and Data Assimilation
.” 2017. Doctoral Dissertation, University of Arizona. Accessed February 26, 2021.
http://hdl.handle.net/10150/624494.
MLA Handbook (7th Edition):
Lorenzo, Antonio Tomas. “Short-Term Irradiance Forecasting Using an Irradiance Monitoring Network, Satellite Imagery, and Data Assimilation
.” 2017. Web. 26 Feb 2021.
Vancouver:
Lorenzo AT. Short-Term Irradiance Forecasting Using an Irradiance Monitoring Network, Satellite Imagery, and Data Assimilation
. [Internet] [Doctoral dissertation]. University of Arizona; 2017. [cited 2021 Feb 26].
Available from: http://hdl.handle.net/10150/624494.
Council of Science Editors:
Lorenzo AT. Short-Term Irradiance Forecasting Using an Irradiance Monitoring Network, Satellite Imagery, and Data Assimilation
. [Doctoral Dissertation]. University of Arizona; 2017. Available from: http://hdl.handle.net/10150/624494
Virginia Tech
29.
Hebbur Venkata Subba Rao, Vishwas.
Adjoint based solution and uncertainty quantification techniques for variational inverse problems.
Degree: PhD, Computer Science and Applications, 2015, Virginia Tech
URL: http://hdl.handle.net/10919/76665
► Variational inverse problems integrate computational simulations of physical phenomena with physical measurements in an informational feedback control system. Control parameters of the computational model are…
(more)
▼ Variational inverse problems integrate computational simulations of physical phenomena with physical measurements in an informational feedback control system. Control parameters of the computational model are optimized such that the simulation results fit the physical measurements.The solution procedure is computationally expensive since it involves running the simulation computer model (the emph{forward model}) and the associated emph {adjoint model} multiple times. In practice, our knowledge of the underlying physics is incomplete and hence the associated computer model is laden with emph {model errors}. Similarly, it is not possible to measure the physical quantities exactly and hence the measurements are associated with emph {
data errors}. The errors in
data and model adversely affect the inference solutions. This work develops methods to address the challenges posed by the computational costs and by the impact of
data and model errors in solving variational inverse problems.
Variational inverse problems of interest here are formulated as optimization problems constrained by partial differential equations (PDEs). The solution process requires multiple evaluations of the constraints, therefore multiple solutions of the associated PDE. To alleviate the computational costs we develop a parallel in time discretization algorithm based on a nonlinear optimization approach. Like in the emph{parareal} approach, the time interval is partitioned into subintervals, and local time integrations are carried out in parallel. Solution continuity equations across interval boundaries are added as constraints. All the computational steps - forward solutions, gradients, and Hessian-vector products - involve only ideally parallel computations and therefore are highly scalable.
This work develops a systematic mathematical framework to compute the impact of
data and model errors on the solution to the variational inverse problems. The computational algorithm makes use of first and second order adjoints and provides an a-posteriori error estimate for a quantity of interest defined on the inverse solution (i.e., an aspect of the inverse solution). We illustrate the estimation algorithm on a shallow water model and on the Weather Research and Forecast model.
Presence of outliers in measurement
data is common, and this negatively impacts the solution to variational inverse problems. The traditional approach, where the inverse problem is formulated as a minimization problem in L
2 norm, is especially sensitive to large
data errors. To alleviate the impact of
data outliers we propose to use robust norms such as the L
1 and Huber norm in
data assimilation. This work develops a systematic mathematical framework to perform three and four dimensional variational
data assimilation using L
1 and Huber norms. The power of this approach is demonstrated by solving
data assimilation problems where measurements contain outliers.
Advisors/Committee Members: Sandu, Adrian (committeechair), Ribbens, Calvin J. (committee member), Constantinescu, Emil Mihai (committee member), De Sturler, Eric (committee member), Cao, Yang (committee member).
Subjects/Keywords: Data assimilation; Inverse problems; sensitivity analysis
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Hebbur Venkata Subba Rao, V. (2015). Adjoint based solution and uncertainty quantification techniques for variational inverse problems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/76665
Chicago Manual of Style (16th Edition):
Hebbur Venkata Subba Rao, Vishwas. “Adjoint based solution and uncertainty quantification techniques for variational inverse problems.” 2015. Doctoral Dissertation, Virginia Tech. Accessed February 26, 2021.
http://hdl.handle.net/10919/76665.
MLA Handbook (7th Edition):
Hebbur Venkata Subba Rao, Vishwas. “Adjoint based solution and uncertainty quantification techniques for variational inverse problems.” 2015. Web. 26 Feb 2021.
Vancouver:
Hebbur Venkata Subba Rao V. Adjoint based solution and uncertainty quantification techniques for variational inverse problems. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2021 Feb 26].
Available from: http://hdl.handle.net/10919/76665.
Council of Science Editors:
Hebbur Venkata Subba Rao V. Adjoint based solution and uncertainty quantification techniques for variational inverse problems. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/76665
University of New South Wales
30.
Pathiraja, Sahani.
Improving Data Assimilation Algorithms for Enhanced Environmental Predictions.
Degree: Civil & Environmental Engineering, 2018, University of New South Wales
URL: http://handle.unsw.edu.au/1959.4/59579
;
https://unsworks.unsw.edu.au/fapi/datastream/unsworks:49002/SOURCE02?view=true
► Data Assimilation (DA) methods provide a means of combining model output with observations based on their respective uncertainties. They are considered an invaluable tool in…
(more)
▼ Data Assimilation (DA) methods provide a means of combining model output with observations based on their respective uncertainties. They are considered an invaluable tool in a wide variety of disciplines, particularly in hydrologic and meteorological forecasting. There is significant potential to improve existing DA methods, which have predominantly been developed in an ad-hoc manner to enhance their applicability to complex real world problems. In particular, relatively little attention has been devoted to one of the most fundamental aspects of DA: Model uncertainty quantification. This thesis aims to develop improved DA based methods for highly non-Gaussian/non-linear systems, with a particular focus on hydrologic and atmospheric systems. It also examines how DA methods can be enhanced to solve problems outside of their traditional application domain. Specifically, two overarching aims are investigated: 1) the development of DA based methods for estimating time varying model parameters, with the ultimate goal of improving hydrologic predictions in dynamic catchments; and 2) the development of objective model uncertainty quantification techniques for use in state-estimation DA. Firstly, a DA based method for sequentially estimating time varying model parameters is investigated. Two new methods for proposing prior parameter distributions are developed, which can be utilised depending on the amount of a priori information available regarding the form of temporal variations in model parameters. The methods are verified against synthetic
data and applied to a number of real catchments with land use change, without relying on prior information of such changes. This approach represents a promising modelling paradigm for hydrologists faced with providing predictions in rapidly changing catchments. In addressing the second objective, two model uncertainty quantification methods are developed for DA in partially observed systems with highly non-Gaussian uncertainties. The methods proposed in this thesis address some of the major shortcomings in existing methods related to objectivity and ability to characterise non-Gaussian errors. Their efficacy is demonstrated through application to flood forecasting problems, and also for state estimation in a partially observed multi-scale atmospheric toy model. In all cases, the proposed methods are shown to provide improved forecasts and updates compared to standard approaches.
Advisors/Committee Members: Sharma, Ashish, Civil & Environmental Engineering, Faculty of Engineering, UNSW, Marshall, Lucy, Civil & Environmental Engineering, Faculty of Engineering, UNSW.
Subjects/Keywords: Uncertainty quantification; Data assimilation; Forecasting; Hydrology; Meteorology
Record Details
Similar Records
Cite
Share »
Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Pathiraja, S. (2018). Improving Data Assimilation Algorithms for Enhanced Environmental Predictions. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/59579 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:49002/SOURCE02?view=true
Chicago Manual of Style (16th Edition):
Pathiraja, Sahani. “Improving Data Assimilation Algorithms for Enhanced Environmental Predictions.” 2018. Doctoral Dissertation, University of New South Wales. Accessed February 26, 2021.
http://handle.unsw.edu.au/1959.4/59579 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:49002/SOURCE02?view=true.
MLA Handbook (7th Edition):
Pathiraja, Sahani. “Improving Data Assimilation Algorithms for Enhanced Environmental Predictions.” 2018. Web. 26 Feb 2021.
Vancouver:
Pathiraja S. Improving Data Assimilation Algorithms for Enhanced Environmental Predictions. [Internet] [Doctoral dissertation]. University of New South Wales; 2018. [cited 2021 Feb 26].
Available from: http://handle.unsw.edu.au/1959.4/59579 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:49002/SOURCE02?view=true.
Council of Science Editors:
Pathiraja S. Improving Data Assimilation Algorithms for Enhanced Environmental Predictions. [Doctoral Dissertation]. University of New South Wales; 2018. Available from: http://handle.unsw.edu.au/1959.4/59579 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:49002/SOURCE02?view=true
◁ [1] [2] [3] [4] [5] … [16] ▶
. 
Open Access Theses and Dissertations
