Thesis (Ph. D.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2005. / Dr. Waymond R. Scott, Committee Member ; Dr. Aaron Lanterman, Committee Member ; Dr. Paul G. Steffes, Committee Chair ; Dr. Andrew F. Peterson, Committee Member ; Dr. Judith A. Curry, Committee Member. Vita. Includes bibliographical references.

Thesis (Ph. D.)--Brigham Young University. Dept. of Electrical and Computer Engineering, 2004. / Includes bibliographical references (p. 161-167).

Thesis (M.S.)--Brigham Young University. Dept. of Electrical and Computer Engineering, 2004. / Includes bibliographical references (p. 111-113).

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The molecular compositions of the atmospheres of the giant planets (Jupiter, Saturn, Uranus and Neptune) are fundamental to understanding the processes which formed these planets and the solar system as a whole. Microwave observations of these planets probe regions in their atmospheres from approximately 0.1 to several bars, a process otherwise unachievable by visible and infrared means. Many gases and various cloud layers influence the millimeter wave spectra of the outer planets; however phosphine and ammonia are the main microwave absorbers at Saturn at pressures less than two bars. Understanding the pressure induced absorption of both constituents at observational frequencies is therefore vital to the analysis of any observational data. Laboratory measurements have been conducted to measure the microwave absorptivity and refractivity of phosphine and ammonia at Ka-band (32-40 GHz) and W-band (94 GHz), under conditions characteristic of the atmosphere of Saturn. The results were used to verify the accuracy of the phosphine formalism created by Hoffman et. al (2001) for use at millimeter wavelengths. Based on the laboratory measurements conducted, new formalisms were also created to express the opacity of ammonia at the measured frequencies. An important method for the study of planetary atmospheres is the radio occultation experiment ??method that uses radio links between Earth, and the spacecraft which passes behind the planet. The Cassini mission to Saturn, which will be conducting such experiments at Ka-band as well as S (2.3 GHz) and X (8.4 GHz) bands, has prompted the development of a radio occultation simulator used to calculate excess Doppler shifts and attenuation profiles for Saturn, utilizing the newest formalisms for phosphine and ammonia. The results indicate that there will be unambiguous detection and profiling of phosphine and ammonia, and predictions are made for the pressures at which loss of signal is anticipated.

Résumé: La mesure de l’équivalent en eau de la neige (EEN) sur le terrain permet de prédire la quantité d’eau libérée par la fonte de la neige. La télédétection dans les micro-ondes passives offre le potentiel d’estimer I’EEN et peut complémenter ces observations de façon synoptique pour l’ensemble du territoire. Un produit de cartographie de I’EEN couvrant l’ensemble du globe a été élaboré par le NSIDC basé sur le capteur AMSR-E. Cet instrument, lancé en 2002, a une résolution améliorée par rapport aux capteurs antérieurs. L’estimation de I’EEN se base sur la différence entre un canal peu affecté (19 GHz) et un canal affecté (37 GHz) par la diffusion de volume de la neige. La précision de ce produit a été évaluée pour la province de Québec à l’hiver 2003 et à l’hiver 2004 qui ont un EEN moyen de 170 mm. Des sous-estimations importantes ont été révélées et une certaine difficulté à détecter la présence de neige. Des modèles régionaux de régressions linéaires ont été développés pour le Québec. Des corrections pour la fraction d’eau et de forêt ont été appliquées à la combinaison T19v.37v et ont permis d’améliorer les résultats. Ces corrections sont basées sur la température de l’air du modèle GEM. Les meilleurs résultats sont pour la classe de neige taïga à l’hiver 2003 avec une erreur relative de 24 % tandis que l’erreur relative est d’environ 40 % pour la région maritime. Les erreurs élevées dans la classe taïga ont été attribuées à des couverts de neige plus épais que la capacité de pénétration des micro-ondes tandis que les erreurs de la classe maritime a des fractions forêt élevées et à la neige mouillée. La présence d’importante quantité de neige et la forêt dense de la province de Québec compliquent l’estimation de I’EEN au Québec avec un modèle de régression. || Abstract: Snow water equivalent (SWE) measurements in the field allow estimation of the quantity of released water from the melting of snow. This is useful to predict the water reserve available for production of hydro-electricity. Remote sensing with microwave can estimate SWE and complement those observations synoptically for whole territories. A SWE mapping products was developed by NSIDC based on the AMSR-E sensor launched in 2002 with an improved resolution compared to previous sensors. SWE estimation is based on difference between a channel weakly affected (19 GHz) and a channel strongly affected by volume scattering. The precision of this product was evaluated for the province of Quebec in winter 2003 and winter 2004 with a mean SWE of 170 mm. Important underestimation and some difficulty of detecting the snow was revealed. Regional linear regression models were developed for the province of Quebec. Corrections for forest and water fraction were applied on T19V-37V combination and permit to improve the results. Those corrections were based on air temperature from the GEM model. Best results were found for taiga snow class in winter 2003 with a relative error of 28% and approximately 40% for maritime snow class. High errors in the taiga region were attributed to snow depth higher than the penetration depth of the microwave and errors in the maritime region to high forest density and wet snow. The important snow amount and high density forest of the province of Quebec hampers the estimation of SWE with a regression model.

Spaceborne microwave sensors are capable of estimating various properties of many geophysical phenomena, including the age and extent of Arctic sea ice and the relative soil moisture over land. The measurement and classification of such geophysical phenomena are used to refine climate models, localize and predict drought, and better understand the water cycle. Data from the active Ku-band scatterometers, the Quick Scatterometer (QuikSCAT), and the Oceansat-2 Scatterometer (OSCAT), are here used to classify areas of first-year and multiyear Arctic sea ice using a temporally adaptive threshold on reported radar backscatter values. The result is a 15-year data record of daily ice classification images. An additional ice age data record is produced using the C-band Advanced Scatterometer (ASCAT) and the Special Sensor Microwave Imager Sounder (SSMIS) with an alternate classification methodology based on Bayesian decision theory. The ASCAT/SSMIS classification methodology results in a record which is generally consistent with the QuikSCAT and OSCAT classifications, which conclude in 2014. With multiple ASCAT and SSMIS sensors still operational, the ASCAT/SSMIS ice classifications can continue to be produced into the future. In addition to ice classification, ASCAT is used to estimate the relative surface soil moisture at high-resolution (4.45 — 4.45 km per pixel). The soil moisture estimates are obtained using enhanced resolution image reconstruction techniques and an altered version of the Water Retrieval Package (WARP) algorithm. The high-resolution soil moisture estimates are shown to agree well with the existing lower resolution WARP products while also revealing finer details.

The assimilation process to produce daily Snow Water Equivalent (SWE) maps is modified by using Helsinki University of Technology (HUT) snow emission model and AMSR-E passive microwave data. The characteristics of HUT emission model is analyzed in-depth and discussed with respects to the extinction coefficient function. A new extinction coefficient function for the HUT model is proposed for snow over mountainous areas. Performance of the modified model is checked against original and other modified cases against ground truth data covering 2003-2007 winter periods. A new approach to calculate grain size and density is integrated inside the developed data assimilation process. An extensive validation is successfully carried out by means of snow data measured at ground stations during 2008-2010 winter periods. Validation results were less satisfactory for SWE smaller than 75.0 mm and greater than 200.0 mm. Overestimation is especially observed for stations located below 1750.0 m elevation where SWE is less than 75.0 mm. Applied methodology is fine tuned to improve its performance for shallow snow depths observed below 1750 m elevation using a relationship that integrates 10.7 GHz channel data. But an underestimation for SWE greater than 150 mm could not beresolved due to microwave signal saturation that is expected in dense snowpack.

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