Assessment of the Performance of a Dual-Frequency Surface Reference Technique

The high correlation of the rain-free surface cross sections at two frequencies implies that the estimate of differential path integrated attenuation (PIA) caused by precipitation along the radar beam can be obtained to a higher degree of accuracy than the path-attenuation at either frequency. We explore this finding first analytically and then by examining data from the JPL dual-frequency airborne radar using measurements from the TC4 experiment obtained during July-August 2007. Despite this improvement in the accuracy of the differential path attenuation, solving the constrained dual-wavelength radar equations for parameters of the particle size distribution requires not only this quantity but the single-wavelength path attenuation as well. We investigate a simple method of estimating the single-frequency path attenuation from the differential attenuation and compare this with the estimate derived directly from the surface return

Vertical Characteristics of Raindrops Size Distribution over Sumatra Region from Global Precipitation Measurement Observation

The climatology of the vertical profile of raindrops size distribution (DSD) over Sumatra Region (10° S – 10° N, 90° E – 110° E) has been investigated using Global Precipitation Measurement (GPM) level 2 data from January 2015 to June 2018. DSD's vertical profile was observed through a vertical profile of corrected radar reflectivity (Ze) and two parameters of normalized gamma DSD, i.e., mass-weight mean diameter (Dm) and total drops concentration (Nw). Land-ocean contrast and rain type dependence of DSD over Sumatra were clearly observed. The values of Dm and Nw were larger in the land than in the ocean. Negative and positive gradients of Dm toward the surface were dominant during stratiform and convective rains, respectively, consistent with the Z gradient. Moreover, the negative gradient of stratiform rain in the ocean is larger than in land. Thus, the depletion of large drops is dominant over the ocean, which is due to the break-up process that can be observed from the increase of Nw. Raindrop growth of convective rains is more robust over the ocean than land that can be seen from a larger value of Dmgradient. The BB strength is slightly larger over land and coastal region than over the ocean, indicating that the riming process is more dominant over land and coastal regions than the ocean. Doi: 10.28991/esj-2021-01274 Full Text: PD

A Dual-Wavelength Radar Technique to Detect Hydrometeor Phases

This study is aimed at investigating the feasibility of a Ku- and Ka-band space/air-borne dual wavelength radar algorithm to discriminate various phase states of precipitating hydrometeors. A phase-state classification algorithm has been developed from the radar measurements of snow, mixed-phase and rain obtained from stratiform storms. The algorithm, presented in the form of the look-up table that links the Ku-band radar reflectivities and dual-frequency ratio (DFR) to the phase states of hydrometeors, is checked by applying it to the measurements of the Jet Propulsion Laboratory, California Institute of Technology, Airborne Precipitation Radar Second Generation (APR-2). In creating the statistically-based phase look-up table, the attenuation corrected (or true) radar reflectivity factors are employed, leading to better accuracy in determining the hydrometeor phase. In practice, however, the true radar reflectivities are not always available before the phase states of the hydrometeors are determined. Therefore, it is desirable to make use of the measured radar reflectivities in classifying the phase states. To do this, a phase-identification procedure is proposed that uses only measured radar reflectivities. The procedure is then tested using APR-2 airborne radar data. Analysis of the classification results in stratiform rain indicates that the regions of snow, mixed-phase and rain derived from the phase-identification algorithm coincide reasonably well with those determined from the measured radar reflectivities and linear depolarization ratio (LDR)

Satellite-based remote sensing of rainfall in areas with sparse gauge networks and complex topography

Rainfall is an essential parameter in the analysis and research of water resource management. However, the complexity of rainfall combined with the uneven distribution of ground-based gauges and radar in developing countries’ mountainous and semi-arid areas limits its investigation. In this context, satellite-based rainfall products provide area-wide precipitation observations with a high spatio-temporal resolution, engaging them in hydrological management in ungauged basins. Therefore, in this study, I investigated method to establish a satellite-based rainfall algorithm for ungauged basins. The algorithm combines the new Integrated Multi-SatEllite Retrieval for the Global Precipitation Measurement (GPM) (IMERG) rainfall products and second-generation geostationary orbit (GEO) systems developing rainfall retrieval techniques with the high spatio-temporal resolution using machine learning algorithms. For the first step, microwave satellite and Meteosat Second Generation Spinning Enhanced Visible and Infrared Imager (MSG SEVIRI) data for Iran were collected to develop a regionally based new rainfall retrieval technique. The method used geostationary multispectral infrared (IR) data to train Random forest (RF) models. I employed the microwave (MW) rainfall information from the IMERG as a reference for RF training. The rainfall area was delineated in the first step, followed by rainfall rate assignment. The validation results showed the new technique’s reliable performance in both rain area delineation and rain estimate, particularly when compared to IR-only IMERG. Multispectral IR data improves rainfall retrieval compared with one single band. In the next step, I investigated the applicability of the developed algorithm in Ecuador with different orography and rainfall regimes compared to Iran. For this aim, I used the Geostationary Operational Environmental Satellite-16 (GOES-16) as the GEO satellite, which covers Ecuador at a suitable angle. The feature selection and algorithm tuning were performed to regionalize the models for Ecuador. The validation results show the reliable performance of the method in both rain area delineation and rain estimation in Ecuador. The results proved the suitability of the developed algorithm with different GEO systems and in different regions. Some inaccuracies at the Andes’ high elevation were evident after the spatial analysis of the validation indices. Evaluating the validation results against a high spatio-temporal radar network showed that the developed algorithm has difficulty capturing drizzles and extreme events dominant in the Andes’ high elevations and needs improvement. In summary, this research presents a new satellite-based technique for rainfall retrieval in a high spatio-temporal resolution for ungauged regions, which can be applied in parts of the world with different rainfall regimes. This findings could be used by planners and water managers regardless of the availability of rain gauges at ground. Furthermore, the research showed, for the very first time, the advantage of using the new generation of GEO satellite combined with microwave satellites integrated in GPM IMERG for estimating rainfall.Der Niederschlag ist ein wesentlicher Parameter bei der Analyse und Erforschung der Bewirtschaftung von Wasserressourcen. Die Komplexität des Niederschlags in Verbindung mit der ungleichmäßigen Verteilung von bodengestützten Messgeräten und Radar in den gebirgigen und halbtrockenen Gebieten von Entwicklungsländern schränkt jedoch seine Untersuchung ein. In diesem Zusammenhang liefern satellitengestützte Produkte flächendeckende Niederschlagsbeobachtungen mit einer hohen räumlich-zeitlichen Auflösung, die für das hydrologische Management in nicht beprobten Einzugsgebieten eingesetzt werden können. Daher konzentriert sich die vorliegende Untersuchung auf die Erstellung eines satellitengestützten Niederschlagsalgorithmus für nicht beprobte Einzugsgebiete. Die neuen IMERG (Integrated Multi-SatEllite Retrieval for Global Precipitation Measurement (GPM)) Satellitenprodukte werden mit geostationären Orbit-Systemen (GEO) der zweiten Generation mittels Algorithmen des maschinellen Lernens zur Niederschlagsermittlung mit hoher räumlicher und zeitlicher Auflösung kombiniert. In einem ersten Schritt wurden Mikrowellensatelliten- und Meteosat-Daten der zweiten Generation des Spinning Enhanced Visible and Infrared Imager (MSG SEVIRI) für den Iran gesammelt, um eine neue, regional basierte Methode zur Niederschlagsermittlung zu entwickeln. Die Methode verwendete geostationäre multispektrale Infrarotdaten (IR), um Random-Forest-Modelle (RF) zu trainieren. Als Referenz für das RF-Training wurden Mikrowellen-Niederschlagsdaten (MW) des IMERG verwendet. Im ersten Schritt wurde das Niederschlagsgebiet abgegrenzt, gefolgt von der Zuordnung der Niederschlagsmenge. Die Validierungsergebnisse zeigen, dass die neue Technik sowohl bei der Abgrenzung des Niederschlagsgebiets als auch bei der Niederschlagsschätzung zuverlässig funktioniert, insbesondere im Vergleich zum IR-only IMERG. Multispektrale IR-Daten verbessern die Niederschlagsermittlung im Vergleich zu einem einzelnen Band. Im nächsten Schritt wurde die Anwendbarkeit des entwickelten Algorithmus in Ecuador untersucht, das sich in Bezug auf die Orographie und das Niederschlagssystem vom Iran unterscheidet. Zu diesem Zweck wurde der Geostationary Operational Environmental Satellite-16 (GOES-16) als GEO-Satellit verwendet, der Ecuador in einem geeigneten Winkel abdeckt. Die Auswahl der Features und das Tuning des Algorithmus wurden durchgeführt, um die Modelle für Ecuador zu regionalisieren. Die Validierungsergebnisse zeigen die zuverlässige Leistung der Methode sowohl bei der Abgrenzung von Regengebieten als auch bei der Schätzung der Niederschlagsmenge in Ecuador. Die Ergebnisse belegen die Eignung des entwickelten Algorithmus für verschiedene GEO-Systeme und verschiedene Regionen. Nach der räumlichen Analyse der Validierungsindizes wurden einige Ungenauigkeiten in denhohen Lagen der Anden deutlich. Die Auswertung der Validierungsergebnisse anhand eines räumlich-zeitlichen Radarnetzes zeigt, dass der entwickelte Algorithmus Schwierigkeiten bei der Erfassung von Nieselregen und extremen Wetterereignissen hat, die in den hohen Lagen der Anden vorherrschen, und dahingehend verbessert werden muss. Diese Forschungsarbeit stellt ein neues satellitengestütztes Verfahren zur Niederschlagsermittlung mit hoher räumlicher und zeitlicher Auflösung vor, das auf Regionen ohne Bodenstationsmessungen und unterschiedliche Niederschlagsregime angewendet werden kann. Dieser Algorithmuskann von Planungs- und Wasserwirtschaftsämtern oder anderen einschlägigen Einrichtungen unabhängig von der Verfügbarkeit von Regenmessern am Boden genutzt werden. Darüber hinaus zeigte die Untersuchung zum ersten Mal den Vorteil der Nutzung der neuen Generation von GEO-Satelliten in Kombination mit den in IMERG integrierten Mikrowellensatelliten für die Bewertung der Niederschlagsmenge

Remote Sensing of Precipitation: Part II

Precipitation is a well-recognized pillar in the global water and energy balances. The accurate and timely understanding of its characteristics at the global, regional and local scales is indispensable for a clearer insight on the mechanisms underlying the Earth’s atmosphere-ocean complex system. Precipitation is one of the elements that is documented to be greatly affected by climate change. In its various forms, precipitation comprises the primary source of freshwater, which is vital for the sustainability of almost all human activities. Its socio-economic significance is fundamental in managing this natural resource effectively, in applications ranging from irrigation to industrial and household usage. Remote sensing of precipitation is pursued through a broad spectrum of continuously enriched and upgraded instrumentation, embracing sensors which can be ground-based (e.g., weather radars), satellite-borne (e.g., passive or active space-borne sensors), underwater (e.g., hydrophones), aerial, or ship-borne. This volume hosts original research contributions on several aspects of remote sensing of precipitation, including applications which embrace the use of remote sensing in tackling issues such as precipitation estimation, seasonal characteristics of precipitation and frequency analysis, assessment of satellite precipitation products, storm prediction, rain microphysics and microstructure, and the comparison of satellite and numerical weather prediction precipitation products

Polarimetric weather radar:from signal processing to microphysical retrievals

Accurate modelling of liquid, solid and mixed-phase precipitation requires a thorough understanding of phenomena occurring at various spatial and temporal scales. At the smallest scales, precipitation microphysics defines all the processes occurring at the level where precipitation is a discrete process. The knowledge of these microphysical processes originates from the interpretation of snowfall and rainfall measurements collected with various sensors. Direct sampling, performed with in-situ instruments, provides data of superior quality. However, the development of remote sensing (and dual-polarization radar in particular) offers a noteworthy alternative: large domains can in fact be sampled in real time and with a single instrument. The drawback is obviously the fact that radars measure precipitation indirectly. Only through appropriate interpretation radar data can be translated into physical mechanisms of precipitation. This thesis contributes to the effort to decode polarimetric radar measurements into microphysical processes or microphysical quantities that characterize precipitation. The first part of the work is devoted to radar data processing. In particular, it focuses on how to obtain high resolution estimates of the specific differential phase shift, a very important polarimetric variable with significant meteorological importance. Then, hydrometeor classification, i.e. the first qualitative microphysical aspect that may come to mind, is tackled and two hydrometeor classification methods are proposed. One is designed for polarimetric radars and one for an in-situ instrument: the two-dimensional video disdrometer. These methods illustrate the potential that supervised and unsupervised techniques can have for the interpretation of meteorological measurements. The combination of in-situ measurements and polarimetric data (including hydrometeor classification) is exploited in the last part of the thesis, devoted to the microphysics of snowfall and in particular of rimed precipitation. Riming is shown to be an important factor leading to significant accumulation of snowfall in the alpine environment. Additionally, the vertical structure of rimed precipitation is examined and interpreted

Raindrop Size Distribution variability from high resolution disdrometer networks

The characteristics of the raindrop size distribution (DSD) have been widely studied since Marshall and Palmer (1948) introduced specific version of exponential distribution for the observed size spectra, based on measurements of raindrops records on dyed filter papers. Across the decades, interest in measuring and studying rain DSD has grown due to applications in cloud physics studies, in calibration of space-borne and ground-based microwave active precipitation sensors and in soil science and agriculture. The study of DSD and of the processes that determine it, are always been challenging from both theoretical and experimental point of view. Moreover, the study of DSD in natural rain is hindered by the difficulties (logistic and economic) in the management of dense disdrometer networks. Based on the unprecedented datasets available, this Thesis aims to contribute in characterizing, from a microphysical point of view, the precipitation structure and the processes that generate it. In particular, the vertical and horizontal DSD variability is analyzed, starting from the study of collisional break-up mechanism in natural rain. The signature of collisional break-up, first evidenced in a particular shape of Doppler power spectrum of a microwave disdrometer, is then searched and characterized in DSD spectrum, assessing its variability with altitude. The horizontal variability of DSD is studied both analyzing the occurrence of equilibrium DSD among the different datasets available and evaluating the correlation of integral and non-integral DSD parameters at small scale. In the first part of the Thesis, an overview on past and recent studies on different aspects of DSD is given. The main mechanisms that govern the rain development are firstly summarized, then the DSD parameterization and the DSD variability in natural rain are discussed. Finally, the description of the characteristics of instruments and of the field campaigns considered in this work are presented. The vertical variability of DSD has been studied thanks to the development of specific algorithms able to detect and characterize both the collisional break-up and the equilibrium DSD. I analyzed the signature of collisional break-up both on the Pludix Doppler power spectrum and on DSD spectrum. The analysis is carried out developing two algorithms that detect the collisional break-up as well as estimate the break-up diameter as function of altitude. The results show a decrease of break-up diameter with altitude, due to the reduction of air density, that plays a critical role in the energetic balance of the collision between two raindrops. The analysis also indicates that, regardless the altitude, the collisional break-up occurs if the kinetic energy of the collision exceeds 12.2 μJ. The results, together with the detailed analysis of some case study at high altitude (over the Tibetan Plateau), show also that the dominance of the break-up process is required to reach the equilibr ium DSD. The study of the DSD variability was deepened focusing the analysis on the 2DVD DSD properties to evaluate the occurrence of equilibrium DSD in natural rain. Another algorithm, based on 2DVD characteristics, is set up to automatically detect the equilibrium DSD by using the great amount of high quality disdrometric data available from the datasets of Ground Validation program of NASAGlobal Precipitation Measurement mission. The results shows a good agreement between the experimental equilibrium DSD and the equilibrium DSD obtained by theoretical models. The analysis shows also that the equilibrium DSD is mainly reached during convective rain and its dependence on season and latitude (no equilibrium DSD is observed at high latitude - 60°N). The occurrence of equilibrium DSD is a rare event in natural rain (maximum 8% of selected minutes), while an increase is observed if transition situations are considered. The results are also analyzed to estimate the goodness of fitting the equilibrium DSD by a three parameter gamma distribution, that is widely used to parameterize the DSD. The low correlation between the experimental DSDs and the gamma distribution evidences that the gamma is not the best parametric form to fit the experimental equilibrium DSD. The behavior of the rain and DSD parameters is studied as function of break-up occurrence and shows that they can be considered an additional indicators to screen out the situations that are not expected to reach the equilibrium DSD. The data collected from two high-resolution disdrometric dataset are used to study the horizonta l DSD spatial variability at small scale. The size of the measuring fields are different but comparable with a ground radar pixel or satellite footprint and this makes the analysis of the particular interest . The rainfall rate and other DSD parameters are analyzed using a three parameter exponential function to estimate their correlation at small scale. The estimated correlation distance shows that the most of the rain and DSD parameters are correlated within a radar pixel or satellite footprint (generally, the integral DSD parameters – rainfall rate, radar reflectivity, liquid water content, etc. – are less correlated than the non integral DSD parameters – maximum diameter, mean mass diameter, etc.). The root mean square error evidences a very good fit of the function used with respect the experimental data, indicating a good reliability of data. The results presented in this Thesis, first, increase the knowledge of break-up phenomenon and its effect on the DSD up to reach the equilibrium DSD, and can be used to improve the parameterizat ion form for break-up and equilibrium DSD occurrence and the modeling of cloud and precipitat ion mechanisms. Secondly, they give reliable indications about the spatial variability of the structure of precipitation within a radar pixel and/or a satellite footprint, with an immediate application to the interpretation of remote sensing measurements to improve precipitation retrieval from radar/satellite measurements, especially after the launch of Dual-frequency Polarization Radar in the frame of Global Precipitation Measurement mission. The results obtained in this Thesis lead to the study of many other aspects that can be investigated to better characterize the precipitation. The time evolution of the precipitation with particular emphasis to the time necessary to the break-up to modify the DSD to reach equilibrium DSD can be investigated by using the algorithms proposed here. A new parameterization of DSD affected by break-up and of equilibrium DSD is necessary to improve the remote sensing of precipitation. Finally, a deeper study of DSD spatial variability is needed to have more information about rain structures at small/medium spatial scales, by different techniques and datasets in different season/location

Raindrop Size Distribution variability from high resolution\ud disdrometer networks

The characteristics of the raindrop size distribution (DSD) have been widely studied since Marshall and Palmer (1948) introduced specific version of exponential distribution for the observed size spectra, based on measurements of raindrops records on dyed filter papers. Across the decades, interest in measuring and studying rain DSD has grown due to applications in cloud physics studies, in calibration of space-borne and ground-based microwave active precipitation sensors and in soil science and agriculture. The study of DSD and of the processes that determine it, are always been challenging from both theoretical and experimental point of view. Moreover, the study of DSD in natural rain is hindered by the difficulties (logistic and economic) in the management of dense disdrometer networks. Based on the unprecedented datasets available, this Thesis aims to contribute in characterizing, from a microphysical point of view, the precipitation structure and the processes that generate it. In particular, the vertical and horizontal DSD variability is analyzed, starting from the study of collisional break-up mechanism in natural rain. The signature of collisional break-up, first evidenced in a particular shape of Doppler power spectrum of a microwave disdrometer, is then searched and characterized in DSD spectrum, assessing its variability with altitude. The horizontal variability of DSD is studied both analyzing the occurrence of equilibrium DSD among the different datasets available and evaluating the correlation of integral and non-integral DSD parameters at small scale. In the first part of the Thesis, an overview on past and recent studies on different aspects of DSD is given. The main mechanisms that govern the rain development are firstly summarized, then the DSD parameterization and the DSD variability in natural rain are discussed. Finally, the description of the characteristics of instruments and of the field campaigns considered in this work are presented. The vertical variability of DSD has been studied thanks to the development of specific algorithms able to detect and characterize both the collisional break-up and the equilibrium DSD. I analyzed the signature of collisional break-up both on the Pludix Doppler power spectrum and on DSD spectrum. The analysis is carried out developing two algorithms that detect the collisional break-up as well as estimate the break-up diameter as function of altitude. The results show a decrease of break-up diameter with altitude, due to the reduction of air density, that plays a critical role in the energetic balance of the collision between two raindrops. The analysis also indicates that, regardless the altitude, the collisional break-up occurs if the kinetic energy of the collision exceeds 12.2 μJ. The results, together with the detailed analysis of some case study at high altitude (over the Tibetan Plateau), show also that the dominance of the break-up process is required to reach the equilibr ium DSD. The study of the DSD variability was deepened focusing the analysis on the 2DVD DSD properties to evaluate the occurrence of equilibrium DSD in natural rain. Another algorithm, based on 2DVD characteristics, is set up to automatically detect the equilibrium DSD by using the great amount of high quality disdrometric data available from the datasets of Ground Validation program of NASAGlobal Precipitation Measurement mission. The results shows a good agreement between the experimental equilibrium DSD and the equilibrium DSD obtained by theoretical models. The analysis shows also that the equilibrium DSD is mainly reached during convective rain and its dependence on season and latitude (no equilibrium DSD is observed at high latitude - 60°N). The occurrence of equilibrium DSD is a rare event in natural rain (maximum 8% of selected minutes), while an increase is observed if transition situations are considered. The results are also analyzed to estimate the goodness of fitting the equilibrium DSD by a three parameter gamma distribution, that is widely used to parameterize the DSD. The low correlation between the experimental DSDs and the gamma distribution evidences that the gamma is not the best parametric form to fit the experimental equilibrium DSD. The behavior of the rain and DSD parameters is studied as function of break-up occurrence and shows that they can be considered an additional indicators to screen out the situations that are not expected to reach the equilibrium DSD. The data collected from two high-resolution disdrometric dataset are used to study the horizonta l DSD spatial variability at small scale. The size of the measuring fields are different but comparable with a ground radar pixel or satellite footprint and this makes the analysis of the particular interest . The rainfall rate and other DSD parameters are analyzed using a three parameter exponential function to estimate their correlation at small scale. The estimated correlation distance shows that the most of the rain and DSD parameters are correlated within a radar pixel or satellite footprint (generally, the integral DSD parameters – rainfall rate, radar reflectivity, liquid water content, etc. – are less correlated than the non integral DSD parameters – maximum diameter, mean mass diameter, etc.). The root mean square error evidences a very good fit of the function used with respect the experimental data, indicating a good reliability of data. The results presented in this Thesis, first, increase the knowledge of break-up phenomenon and its effect on the DSD up to reach the equilibrium DSD, and can be used to improve the parameterizat ion form for break-up and equilibrium DSD occurrence and the modeling of cloud and precipitat ion mechanisms. Secondly, they give reliable indications about the spatial variability of the structure of precipitation within a radar pixel and/or a satellite footprint, with an immediate application to the interpretation of remote sensing measurements to improve precipitation retrieval from radar/satellite measurements, especially after the launch of Dual-frequency Polarization Radar in the frame of Global Precipitation Measurement mission. The results obtained in this Thesis lead to the study of many other aspects that can be investigated to better characterize the precipitation. The time evolution of the precipitation with particular emphasis to the time necessary to the break-up to modify the DSD to reach equilibrium DSD can be investigated by using the algorithms proposed here. A new parameterization of DSD affected by break-up and of equilibrium DSD is necessary to improve the remote sensing of precipitation. Finally, a deeper study of DSD spatial variability is needed to have more information about rain structures at small/medium spatial scales, by different techniques and datasets in different season/location

Polarimetric X-band weather radar measurements in the tropics: radome and rain attenuation correction

A polarimetric X-band radar has been deployed during one month (April 2011) for a field campaign in Fortaleza, Brazil, together with three additional laser disdrometers. The disdrometers are capable of measuring the raindrop size distributions (DSDs), hence making it possible to forward-model theoretical polarimetric X-band radar observables at the point where the instruments are located. This setup allows to thoroughly test the accuracy of the X-band radar measurements as well as the algorithms that are used to correct the radar data for radome and rain attenuation. For the campaign in Fortaleza it was found that radome attenuation dominantly affects the measurements. With an algorithm that is based on the self-consistency of the polarimetric observables, the radome induced reflectivity offset was estimated. Offset corrected measurements were then further corrected for rain attenuation with two different schemes. The performance of the post-processing steps was analyzed by comparing the data with disdrometer-inferred polarimetric variables that were measured at a distance of 20 km from the radar. Radome attenuation reached values up to 14 dB which was found to be consistent with an empirical radome attenuation vs. rain intensity relation that was previously developed for the same radar type. In contrast to previous work, our results suggest that radome attenuation should be estimated individually for every view direction of the radar in order to obtain homogenous reflectivity fields.FAPESP [2009/15235-8

Fast 3D Inhomogeneous Radiative Transfer Model Incorporating Aspherical Frozen Hydrometeors with Application to Precipitation Locking

A horizontally inhomogeneous unified microwave radiative transfer (HI-UMRT) model incorporating aspherical frozen hydrometeors based on the NASA/GSFC OpenSSP database is presented to study 3-dimensional (3D) effects of horizontal inhomogeneous clouds on computed microwave radiances and facilitate satellite radiance assimilation over horizontally inhomogeneous weather conditions. HI-UMRT provides a coupled two-Stokes parameter numerical radiance solution of the 3D radiative transfer equation by embedding the existing 1D UMRT algorithm into an iterative perturbation scheme. The horizontal derivatives in radiances of lower perturbation order are treated as the source functions of the azimuthal harmonic perturbation radiative transfer equations that are readily solved by the planar-stratified 1D UMRT algorithm.The 1D UMRT algorithm requires symmetry of the transition matrix for the discretized planar-stratified radiative transfer equation to realize numerically stable and accurate matrix operations as required by the discrete-ordinate eigenanalysis method. In this thesis, the necessary block-diagonal structure of the full Stokes matrix for randomly oriented OpenSSP aspherical hydrometeors is shown to be maintained, albeit with small asymmetric deviations which introduce small asymmetric components into the transition matrix that are negligible for most passive microwave remote sensing applications. An upper bound of the brightness temperature error calculated by neglecting the asymmetric components of the transition matrix under even extreme atmospheric conditions is shown to be small. Hence the OpenSSP hydrometeor database can be reliably used within the UMRT model.Block-diagonal Stokes matrix elements along with other single-scattering parameters of OpenSSP hydrometeors were subsequently used in radiative simulations of multi-stream dual-polarization radiances for a simulated hurricane event to demonstrate the inherent numerical stability and utility of the extended 1D UMRT algorithm. An intercomparison of computed upwelling radiances for a multiphase distribution of aspherical OpenSSP hydrometeors versus a mass-equivalent Mie hydrometeor polydispersion for key sensing frequencies from 10 to 874 GHz shows the considerable impact of complex (versus simple spherical) hydrometeors on predicted microwave radiances.Further, a numerical performance assessment shows that the increase in computing time for the 3D HI-UMRT model relative to the 1D UMRT model is moderate since (i) the computationally efficient UMRT engine is applied only to the perturbation equations with non-trivial solutions, and (ii) the layer parameters for the 1D solution are reused for all higher perturbation orders. Numerical simulations using HI-UMRT based on 3D cloud profiles simulated by the WRF numerical weather model illustrate the convergence of the iterative perturbation series. An intercomparison of top-of-atmosphere brightness temperature images for HI-UMRT versus the planar-stratified UMRT model illustrates the considerable impact of cloud horizontal inhomogeneities on computed upwelling microwave radiances.The microwave radiances simulated using UMRT at 118 and 183 GHz based on the Orbital Micro Systems Inc. Global Earth Monitoring System (GEMS) CubeSat constellation concept have been used in an all-weather microwave data assimilation scheme to facilitate precipitation locking of hydrometeor state variables in severe weather. The capability of first frame precipitation locking can be achieved based on constrained extended Kalman filtering (XKF), statistical estimation of a flow-dependent background error covariance matrix, and appropriate update of state variables using nonlinear iterative method. Preliminary simulation results demonstrate the potential for assimilating both thermodynamic and hydrometeor variables in first-frame locking iterations