Satellite wind vector data is integral to atmospheric models and forecasts. Currently, the limited refresh rate of global wind vector measurement systems makes it difficult to observe diurnal variation of mesoscale processes. Using advancements in the underlying subsystem technologies, new satellite wind scatterometers may be possible that increase temporal resolution, among other performance metrics. I propose a method for parametrically modeling the extreme performance range of a complex system. I use this method to develop a model of the space of possible satellite wind scatterometer designs. I validate the model using point designs of heritage scatterometers. Finally, I present two example concepts for constellations of cooperative satellite wind scatterometers capable of measuring global ocean surface vector winds every hour for the same total cost as a single heritage scatterometer.

In recent years, the scientific community has expressed interest in the ability to observe global climate indicators such as polar sea ice. Advances in microwave remote sensing technology have allowed a large-scale and detailed study of sea ice characteristics. This thesis provides the analysis and development of sea ice mapping algorithms for the SeaWinds scatterometer. First, an in-depth analysis of the Remund Long (RL) algorithm for SeaWinds is performed. From this study, several improvements are made to the RL algorithm which enhance its performance. In addition, a new method for automated polar sea ice mapping is developed for the SeaWinds instrument. This method is rooted in Bayes decision theory, and incorporates an adaptive model for seasonally fluctuating sea ice and ocean microwave signatures. The new approach is compared to the RL algorithm, to passive microwave data, and to high-resolution SAR imagery for validation.

Ku-band dual-polarization radar backscatter measurements from the SeaWinds on QuikScat scatterometer and microwave radiometer measurements from the Special Sensor Microwave/Imager (SSM/I) are used to determine periods of surface melt and freeze in the Antarctic ice-shelves. The normalized radar backscatter (sigma-0) and backscatter polarization ratio (PR) are used in the maximum likelihood estimation of the ice-state. This method is used to infer the daily ice-surface conditions for 25 selected study points located on the Ronne, Ross, Larsen, Fimbul, Amery, and Shackleton Ice-shelves. The temporal and spatial variations of the radar response are also observed for various neighborhood sizes surrounding each given point during the study period. Criteria for determining the dates of melt-onset and freeze-up for each Austral summer are also presented. Validation of the ice-state and melt-onset date estimates is performed by analyzing corresponding brightness temperature (Tb) measurements from radiometers. QuikScat sigma-0 measurements from 1999 through 2003 are analyzed and it is shown that Ku-band scatterometers are very useful for determining periods of melt in Antarctic ice-sheets and provide high temporal and spatial resolution ice-state estimates. These estimates can be important for long-term studies of the climatic effects of the seasonal and inter-annual melting of the Antarctic ice-sheets. The SeaWinds on QuikScat (QuikScat) and SeaWinds on ADEOS-2 (SeaWinds) scatterometers are identical radar sensors on different spaceborne platforms traversing similar orbits. QuikSCAT and SeaWinds data are used to infer near-surface wind vectors, polar sea-ice extent, polar-ice melt events, among others. In order to verify the relative calibration of these two sensors a simple cross-calibration method is implemented based on land measurements. A first-order polynomial model for the incidence angle dependence of sigma-0 is used to account for biases in the sigma-0 measurements. This model is applied to selected regions of the Amazon rainforest and the Sahara desert. It is shown that the two sensors are well calibrated. Additionally, evidence of a previously presumed diurnal cycle in the Amazon rainforest backscatter is given.

Ku-band dual-polarization radar backscatter measurements from the SeaWinds on QuikScat (QuikScat) and SeaWinds on ADEOS-2 (SeaWinds) scatterometers are used to classify the melt state and estimate melt severity in Greenland. Backscatter measurements are organized into high temporal and high spatial resolution images created using the Scatterometer Image Reconstruction (SIR) algorithm and a new temporal data segmentation technique. Melt detection is performed using a layered electromagnetic model combined with a Markov chain model. The new melt detection method allows classification of the snow-pack into three states: melt, refreeze, and frozen. Melt severity and refreeze severity indexes are also developed. The melt detection methods developed in this thesis are verified by using a one-dimensional geophysical/electromagnetic model simulation of the snow-pack under melting conditions and by comparison with in situ weather station data at the ETH Camp in western Greenland. The diurnal cycle of backscatter measurements is also analyzed at this location. The melt detection and estimation method is applied to the entire Greenland ice-sheet. The resulting melt classifications and melt severity indexes are used to generate a number of maps outlining the features of the 2003 melt season. Good agreement of the melt severity and a 1978 SASS Greenland ice facies map is observed.

The NASA SeaWinds scatterometer is a radar remote sensor which operates on two satellites; NASA's QuikSCAT launched in June 1999 and on Japan's ADEOS-II satellite launched in December 2002. The purpose of SeaWinds is to provide global measurements of the ocean surface wind vector. On QuikSCAT, a ground data processing algorithm was developed, which allowed the instrument to function as a QuikSCAT Radiometer (QRad) and measure the ocean microwave emissions (brightness temperature, Tb) simultaneously with the backscattered power. When SeaWinds on ADEOS was launched, this same algorithm was applied, but the results were anomalous. The initial SRad brightness temperatures exhibited significant, unexpected, ascending/descending orbit Tb biases. This thesis presents an empirical correction algorithm to correct the anomalous SeaWinds Radiometer (SRad) ocean brightness temperature measurements. I use the Advanced Microwave Scanning Radiometer (AMSR) as a brightness temperature standard to calibrate and then, with independent measurements, validate the corrected SRad Tb measurements. AMSR is a well-calibrated multi-frequency, dual-polarized microwave radiometer that also operates on ADEOS-II. These results demonstrate that, after tuning the Tb algorithm, good quality SRad brightness temperature measurements are obtained over the oceans.

Ocean surface wind vectors over the ocean present vital information for scientists and forecasters in their attempt to understand the Earth's global weather and climate. As the demand for global wind velocity information has increased, the number of satellite missions that carry wind-measuring sensors has also increased; however, there are still not sufficient numbers of instruments in orbit today to fulfill the need for operational meteorological and scientific wind vector data. Over the last three decades operational measurements of global ocean wind speeds have been obtained from passive microwave radiometers. Also, vector ocean surface wind data were primarily obtained from several scatterometry missions that have flown since the early 1990's. However, other than SeaSat-A in 1978, there has not been combined active and passive wind measurements on the same satellite until the launch of the second Advanced Earth Observing Satellite (ADEOS-II) in 2002. This mission has provided a unique data set of coincident measurements between the SeaWinds scatterometer and the Advanced Microwave Scanning Radiometer (AMSR). AMSR observes the vertical and horizontal brightness temperature (TB) at six frequency bands between 6.9 GHz and 89.0 GHz. Although these measurements contain some wind direction information, the overlying atmospheric influence can easily obscure this signal and make wind direction retrieval from passive microwave measurements very difficult. However, at radiometer frequencies between 10 and 37 GHz, a certain linear combination of vertical and horizontal brightness temperatures causes the atmospheric dependence to be nearly cancelled and surface parameters such as wind speed, wind direction and sea surface temperature to dominate the resulting signal. This brightness temperature combination may be expressed as ATBV-TBH, where A is a constant to be determined and the TBV and TBH are the brightness temperatures for the vertical and horizontal polarization respectively. In this dissertation, an empirical relationship between the AMSR's ATBV-TBH and SeaWinds' surface wind vector retrievals was established for three microwave frequencies: 10, 18 and 37 GHz. This newly developed model function for a passive microwave radiometer could provide the basis for wind vector retrievals either separately or in combination with scatterometer measurements.

A resposta oceânica a perturbações com períodos e comprimentos significativamente maiores que o período inercial e que o raio de deformação de Rossby se dá na forma de ondas de Rossby planetárias. Geralmente, as perturbações são atribuídas a variações no rotacional do vento via bombeamento de Ekman. A passagem dessas ondas causa deformação das isopicnais, podendo resultar em anomalias da temperatura da superfície do mar (TSM) por advecção vertical. Dependendo de como ocorre a interação ar-mar, anomalias de TSM podem alterar o campo de ventos ou serem alteradas por ele através de fluxo de calor. Este trabalho utiliza dez anos de dados de temperatura da superfície do mar, velocidade e direção dos ventos e anomalia da altura do mar obtidos por satélites para identificar regiões do oceano onde há forçamento direto do vento na geração de ondas planetárias que se propagam linearmente. Mapas de correlação cruzada entre essas variáveis permitiram identificar onde a interação entre o oceano e a atmosfera é linear. Um modelo simples de uma camada e meia forçado apenas pelo bombeamento de Ekman foi utilizado para testar se, nestas regiões, a variabilidade atmosférica seria suficiente para explicar a variabilidade das ondas de Rossby estimadas pelos dados altimétricos. A interação entre a TSM e a intensidade do vento no Atlântico sul tropical é distinta das demais bacias oceânicas. Das correlações entre a TSM e o rotacional da tensão de cisalhamento do vento, observou-se que a dinâmica de Ekman não é marcante no Índico. Nas regiões tropicais do Atlântico e do Pacífico, as previsões do modelo foram similares às observações. Por fim, foram obtidas evidências de geração e retroalimentação de ondas planetárias nas bordas leste do Atlântico e do Pacífico. / Rossby waves are the ocean response to perturbations whose temporal and spatial scales are significantly longer than both the inertial period and the Rossby radius of deformation. These perturbations are, more often than not, attributed to variations in the wind stress curl {\\em via} Ekman pumping. The waves cause isopycnal displacement which due to vertical advection may result in sea surface temperature (SST) anomalies. Depending on the ocean--atmosphere interaction, SST anomalies can either change the wind field or be changed by it due to the heat flux. This study makes use of ten years of satellite derived SST, wind vector, and sea surface height anomaly data to identify regions where there is direct wind forcing of linear Rossby waves. Cross-correlation maps between these variables show where linear interactions occur. A simple 1½ layer model forced by Ekman pumping was used to check if, in those regions, atmospheric variability alone can explain the observed Rossby wave variability as estimated from radar altimeter data. The interaction between SST and wind magnitude in the South Atlantic is distinct from all other ocean basins. SST and wind stress curl correlations show that the Ekman dynamics is not dominant in the Indian Ocean. In the tropical Atlantic and Pacific the model predictions are similar to the observations. Finally, evidence of genesis and feedback of planetary waves is presented for the eastern boundaries of the Atlantic and Pacific oceans.

A resposta oceânica a perturbações com períodos e comprimentos significativamente maiores que o período inercial e que o raio de deformação de Rossby se dá na forma de ondas de Rossby planetárias. Geralmente, as perturbações são atribuídas a variações no rotacional do vento via bombeamento de Ekman. A passagem dessas ondas causa deformação das isopicnais, podendo resultar em anomalias da temperatura da superfície do mar (TSM) por advecção vertical. Dependendo de como ocorre a interação ar-mar, anomalias de TSM podem alterar o campo de ventos ou serem alteradas por ele através de fluxo de calor. Este trabalho utiliza dez anos de dados de temperatura da superfície do mar, velocidade e direção dos ventos e anomalia da altura do mar obtidos por satélites para identificar regiões do oceano onde há forçamento direto do vento na geração de ondas planetárias que se propagam linearmente. Mapas de correlação cruzada entre essas variáveis permitiram identificar onde a interação entre o oceano e a atmosfera é linear. Um modelo simples de uma camada e meia forçado apenas pelo bombeamento de Ekman foi utilizado para testar se, nestas regiões, a variabilidade atmosférica seria suficiente para explicar a variabilidade das ondas de Rossby estimadas pelos dados altimétricos. A interação entre a TSM e a intensidade do vento no Atlântico sul tropical é distinta das demais bacias oceânicas. Das correlações entre a TSM e o rotacional da tensão de cisalhamento do vento, observou-se que a dinâmica de Ekman não é marcante no Índico. Nas regiões tropicais do Atlântico e do Pacífico, as previsões do modelo foram similares às observações. Por fim, foram obtidas evidências de geração e retroalimentação de ondas planetárias nas bordas leste do Atlântico e do Pacífico. / Rossby waves are the ocean response to perturbations whose temporal and spatial scales are significantly longer than both the inertial period and the Rossby radius of deformation. These perturbations are, more often than not, attributed to variations in the wind stress curl {\\em via} Ekman pumping. The waves cause isopycnal displacement which due to vertical advection may result in sea surface temperature (SST) anomalies. Depending on the ocean--atmosphere interaction, SST anomalies can either change the wind field or be changed by it due to the heat flux. This study makes use of ten years of satellite derived SST, wind vector, and sea surface height anomaly data to identify regions where there is direct wind forcing of linear Rossby waves. Cross-correlation maps between these variables show where linear interactions occur. A simple 1½ layer model forced by Ekman pumping was used to check if, in those regions, atmospheric variability alone can explain the observed Rossby wave variability as estimated from radar altimeter data. The interaction between SST and wind magnitude in the South Atlantic is distinct from all other ocean basins. SST and wind stress curl correlations show that the Ekman dynamics is not dominant in the Indian Ocean. In the tropical Atlantic and Pacific the model predictions are similar to the observations. Finally, evidence of genesis and feedback of planetary waves is presented for the eastern boundaries of the Atlantic and Pacific oceans.

In the spring of 1999 NASA will launch the scatterometer SeaWinds, beginning a 3 year mission to measure the ocean winds. SeaWinds is different from previous spaceborne scatterometers in that it employs a rotating pencil-beam antenna as opposed to fixed fan-beam antennas. The scanning beam provides greater coverage but causes the wind retrieval accuracy to vary across the swath. This thesis develops a filed-wise wind retrieval algorithm to improve the overall wind retrieval accuracy for use with SeaWinds data. In order to test the field-wise wind retrieval algorithm, methods for simulating wind fields are developed. A realistic approach interpolates the NASA Scatterometer (NSCAT) estimates to fill a SeaWinds swath using optimal interpolation along with linear wind filed models. The two stages of the field-wise wind retrieval algorithm are filed-wise estimation and field-wise ambiguity selection. Field-wise estimation is implemented using a 22 parameter Karhunen-Loeve (KL) wind field model in conjunction with a maximum likelihood objective function. An augmented multi-start global optimization is developed which uses information from the point-wise estimates to aid in a global search of the objective function. The local minima in the objective function are located using the augmented multi-start search techniques and are stored as field-wise ambiguities. The ambiguity selection algorithm uses a field-wise median filter to select the field-wise ambiguity closest to the true wind in each region. Point-wise nudging is used to further improve the filed-wise estimate using information from the point-wise estimates. Combined, these two techniques select a good estimate of the wind 95% of the time. The overall performance of the field-wise wind retrieval algorithm is compared with the performance of the current point-wise techniques. Field-wise estimation techniques are shown to be potentially better than point-wise techniques. The field-wise estimates are also shown to be very useful tools in point-wise ambiguity selection since 95.8%-96.6% of the point-wise estimates closest to the field-wise estimates are the correct aliases.

Oceanic microwave remote sensing provides the data necessary for the estimation of significant geophysical parameters such as the near-surface vector wind. To obtain accurate estimates, a precise understanding of the measurements is critical. This work clarifies and quantifies specific uncertainties in the scattered power measured by an active radar instrument. While there are many sources of uncertainty in remote sensing measurements, this work concentrates on three significant, yet largely unstudied effects. With a theoretical derivation of the backscatter from an ocean-like surface, results from this dissertation demonstrate that the backscatter decays with surface roughness with two distinct modes of behavior, affected by the size of the footprint. A technique is developed and scatterometer data analyzed to quantify the variability of spaceborne backscatter measurements for given wind conditions; the impact on wind retrieval is described in terms of bias and the Cramer-Rao lower bound. The probability density function of modified periodogram averages (a spectral estimation technique) is derived in generality and for the specific case of power estimates made by the NASA scatterometer. The impact on wind retrieval is quantified.