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You searched for subject:(Microphysical retrieval). Showing records 1 – 3 of 3 total matches.

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Colorado State University

1. Hardin, Joseph C. Integrated retrieval framework for multiple polarization, multiple frequency radar networks, An.

Degree: PhD, Electrical and Computer Engineering, 2015, Colorado State University

Radar networks form the backbone of severe weather and remote sensing in throughout most of the world. These networks provide diverse measurements of weather phenomenon, but ultimately are measuring indirect parameters rather than detecting the physics of the situation. One of the long standing goals of weather remote sensing is to relate the measurements from the various instruments to the physics that give rise to the measurements. Weather radar networks give both a better spatial coverage than single radars, as well as providing multiple looks at the environment. Newly developed radar networks have started to incorporate multiple frequencies and multiple polarizations to take advantage of attributes of different radar frequencies. Raindrops occupy different scattering regimes based on the frequency of the radar being used. Based on this, multiple radars at different wavelengths provide unique information about the microphysical characteristics of the atmosphere. Nonetheless, very little work has been conducted on fusing multiple radar measurements at heterogeneous frequencies to improve microphysical retrievals. This work presents a forward variational algorithm for multiple radar fusion that retrieves microphysical parameters from the atmosphere. The single radar case and the multiple radar case will both be addressed. Ground instrumentation will be used for verification, and the spatial and temporal variability of precipitation microphysics will be discussed. Advisors/Committee Members: Chandrasekar, V. (advisor), Jayasumana, Anura P. (committee member), Mielke, Paul (committee member), Cheney, Margaret (committee member).

Subjects/Keywords: inverse problems; weather radar; Microphysical retrieval; disdrometer; spatial variability; Remote sensing

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APA (6th Edition):

Hardin, J. C. (2015). Integrated retrieval framework for multiple polarization, multiple frequency radar networks, An. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/167246

Chicago Manual of Style (16th Edition):

Hardin, Joseph C. “Integrated retrieval framework for multiple polarization, multiple frequency radar networks, An.” 2015. Doctoral Dissertation, Colorado State University. Accessed March 07, 2021. http://hdl.handle.net/10217/167246.

MLA Handbook (7th Edition):

Hardin, Joseph C. “Integrated retrieval framework for multiple polarization, multiple frequency radar networks, An.” 2015. Web. 07 Mar 2021.

Vancouver:

Hardin JC. Integrated retrieval framework for multiple polarization, multiple frequency radar networks, An. [Internet] [Doctoral dissertation]. Colorado State University; 2015. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/10217/167246.

Council of Science Editors:

Hardin JC. Integrated retrieval framework for multiple polarization, multiple frequency radar networks, An. [Doctoral Dissertation]. Colorado State University; 2015. Available from: http://hdl.handle.net/10217/167246

2. Lafrique, Pierre. Lidar multispectral pour la caractérisation des aérosols : Multiwavelength lidar for aerosol characterization.

Degree: Docteur es, Photonique et systèmes optoélectroniques, 2015, Toulouse, ISAE

Cette thèse vise à montrer rapport d'un lidar multispectral, en particulier en ajoutant des longueurs d'onde dans le proche infrarouge proche, pour la caractérisation des aérosols. En effet par rapport à un lidar mono-longueur d'onde, l'information contenue dans les profils multispectraux permet de remonter aux propriétés microphysiques des aérosols (distribution en aille et composition). Pour cela un simulateur de signaux lidar multispectraux a été adapté à notre étude afin de pouvoir développer et tester deux méthodes permettant de retrouver les propriétés microphysiques des aérosols le long de la ligne e visée à partir de signaux lidar synthétiques. La première méthode, basée sur l'inversion des signaux lidar, permet de retrouver la répartition en taille des aérosols et donc d'en déduire notamment leur concentration et leur rayon modal. Cette méthode nécessite des informations a priori sur les aérosols. Un bilan d'erreur a été réalisé en introduisant des incertitudes sur ces paramètres a priori et montre que les résultats obtenus sur la concentration et le rayon modal sont précis (respectivement 16% et 17% d'erreur). Cette méthode présente l'avantage de ne pas nécessiter d'étalonnage absolu de l'instrument. La deuxième méthode est basée sur la minimisation de l'écart entre des signaux simulés et les signaux que l'on étudie. Même si la précision obtenue sur la répartition en taille retrouvée est plus faible (35% et 40 % d'erreur sur la concentration t le rayon modal) et que la constante d'étalonnage de l'instrument doit être connue, cette méthode a l'avantage de retrouver la composition des aérosols dans 74 % des cas.

The purpose of this thesis is to show the contribution of a multispectral Iidar for the characterisation of aerosols, in particular hen wavelengths in near infrared are added. Indeed, compared with a mono-wavelength Iidar, the information contained in multispectral profiles allow to retrieve the microphysical properties of aerosols (particule size distribution and composition). To this end, we adapted a multispectral Iidar signal simulator to our study in order to develop and test two methods which objective is to obtain the microphysical properties of aerosol along the line-of-sight from synthetic lidar signals. The first method, based on the inversion of lidar signals, enables to find the length distribution of aerosols and therefore to educe their concentration and their modal radius. This method requires a priori information about the aerosols. An error budget was made by introducing uncertainties on the a priori parameters. It shows that the results obtained regarding the concentration and modal radius are accurate (respectively 16% and 17% uncertainty). The advantage of this method is that it does not require absolute calibration of the instrument. The principle of the second method is to minimize the difference between the studied and the simulated signals. Even if the accuracy on the size distribution is lower (35% and 40% on the concentration and modal radius) and the calibration constant…

Advisors/Committee Members: Briottet, Xavier (thesis director), Dabas, Alain (thesis director).

Subjects/Keywords: Lidar; Aérosols; Inversion multispectral; Propriétés microphysiques; Lidar; Aerosols; Multi-Wavelength retrieval algorithm; Microphysical properties; 530

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APA (6th Edition):

Lafrique, P. (2015). Lidar multispectral pour la caractérisation des aérosols : Multiwavelength lidar for aerosol characterization. (Doctoral Dissertation). Toulouse, ISAE. Retrieved from http://www.theses.fr/2015ESAE0033

Chicago Manual of Style (16th Edition):

Lafrique, Pierre. “Lidar multispectral pour la caractérisation des aérosols : Multiwavelength lidar for aerosol characterization.” 2015. Doctoral Dissertation, Toulouse, ISAE. Accessed March 07, 2021. http://www.theses.fr/2015ESAE0033.

MLA Handbook (7th Edition):

Lafrique, Pierre. “Lidar multispectral pour la caractérisation des aérosols : Multiwavelength lidar for aerosol characterization.” 2015. Web. 07 Mar 2021.

Vancouver:

Lafrique P. Lidar multispectral pour la caractérisation des aérosols : Multiwavelength lidar for aerosol characterization. [Internet] [Doctoral dissertation]. Toulouse, ISAE; 2015. [cited 2021 Mar 07]. Available from: http://www.theses.fr/2015ESAE0033.

Council of Science Editors:

Lafrique P. Lidar multispectral pour la caractérisation des aérosols : Multiwavelength lidar for aerosol characterization. [Doctoral Dissertation]. Toulouse, ISAE; 2015. Available from: http://www.theses.fr/2015ESAE0033


Texas A&M University

3. Wang, Chenxi. Investigation of Thin Cirrus Cloud Optical and Microphysical Properties on the Basis of Satellite Observations and Fast Radiative Transfer Models.

Degree: PhD, Atmospheric Sciences, 2013, Texas A&M University

This dissertation focuses on the global investigation of optically thin cirrus cloud optical thickness (tau) and microphysical properties, such as, effective particle size (D_(eff)) and ice crystal habits (shapes), based on the global satellite observations and fast radiative transfer models (RTMs). In the first part, we develop two computationally efficient RTMs simulating satellite observations under cloudy-sky conditions in the visible/shortwave infrared (VIS/SWIR) and thermal inferred (IR) spectral regions, respectively. To mitigate the computational burden associated with absorption, thermal emission and multiple scattering, we generate pre-computed lookup tables (LUTs) using two rigorous models, i.e., the line-by-line radiative transfer model (LBLRTM) and the discrete ordinates radiative transfer model (DISORT). The second part introduces two methods (i.e., VIS/SWIR- and IR-based methods) to retrieve tau and D_(eff) from satellite observations in corresponding spectral regions of the two RTMs. We discuss the advantages and weakness of the two methods by estimating the impacts from different error sources on the retrievals through sensitivity studies. Finally, we develop a new method to infer the scattering phase functions of optically thin cirrus clouds in a water vapor absorption channel (1.38-µm). We estimate the ice crystal habits and surface structures by comparing the inferred scattering phase functions and numerically simulated phase functions calculated using idealized habits. We find two critical features of the two retrieval methods: (1) the IR-based method is more sensitive to optically thin cirrus cloud, and (2) the VIS/SWIR-based method is more sensitive to the pre-assumed ice cloud microphysical parameterization schemes. We derive the optically thin cirrus cloud phase functions based on the two methods. We find that small column-like particles (e.g., solid columns and columnaggregates) and droxtals with rough surfaces are likely to reside in optically thin cirrus clouds. Advisors/Committee Members: Yang, Ping (advisor), Kattawar, George (committee member), Nasiri, Shaima (committee member), North, Gerald (committee member).

Subjects/Keywords: Radiative transfer model; Cloud retrieval; Cloud optical and microphysical properties; Optically thin cirrus cloud; Cloud phase function

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Wang, C. (2013). Investigation of Thin Cirrus Cloud Optical and Microphysical Properties on the Basis of Satellite Observations and Fast Radiative Transfer Models. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/151213

Chicago Manual of Style (16th Edition):

Wang, Chenxi. “Investigation of Thin Cirrus Cloud Optical and Microphysical Properties on the Basis of Satellite Observations and Fast Radiative Transfer Models.” 2013. Doctoral Dissertation, Texas A&M University. Accessed March 07, 2021. http://hdl.handle.net/1969.1/151213.

MLA Handbook (7th Edition):

Wang, Chenxi. “Investigation of Thin Cirrus Cloud Optical and Microphysical Properties on the Basis of Satellite Observations and Fast Radiative Transfer Models.” 2013. Web. 07 Mar 2021.

Vancouver:

Wang C. Investigation of Thin Cirrus Cloud Optical and Microphysical Properties on the Basis of Satellite Observations and Fast Radiative Transfer Models. [Internet] [Doctoral dissertation]. Texas A&M University; 2013. [cited 2021 Mar 07]. Available from: http://hdl.handle.net/1969.1/151213.

Council of Science Editors:

Wang C. Investigation of Thin Cirrus Cloud Optical and Microphysical Properties on the Basis of Satellite Observations and Fast Radiative Transfer Models. [Doctoral Dissertation]. Texas A&M University; 2013. Available from: http://hdl.handle.net/1969.1/151213

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