The Ku-band SeaWinds-on-QuikSCAT scatterometer (QuikSCAT) operated continuously from 1999 to 2009. Though its primary mission was to estimate global ocean winds, QuikSCAT has proven useful in a variety of geophysical studies using land backscatter measurements. The end of the primary QuikSCAT mission in 2009 has prompted interest for continuing the QuikSCAT land dataset with other scatterometers. The Oceansat-2 scatterometer (OSCAT), launched in 2009, is a viable candidate for continuing the QuikSCAT time series because of the similarities of both sensors in function and design. An important difference in the sensors is that they operate at slightly different incidence angles. Continuing the time series requires careful cross-calibration of the two sensors. Because the sensor datasets overlapped by only a few weeks in late 2009, the amount of simultaneous data is insufficient to describe temporal and locational variations in the relative calibration, or difference between QuikSCAT and OSCAT measurements. To overcome this limitation, we perform direct and model-based comparisons of temporally-disjoint QuikSCAT and OSCAT global land measurements to describe the relative calibration. Using homogeneous rainforest targets, we also identify drift and azimuthal biases in the OSCAT dataset and present suggestions for removing them. The relative calibration is found to vary locationally by several tenths of a decibel over certain regions. Evidence is presented that suggests the relative calibration is dependent on environmental factors such as vegetation density and freeze-thaw status and results from the different incidence angles of the measurements.

Polar sea ice measurements are an important contribution to global climate models. Passive and active microwave remote sensing instruments are used to track global trends in polar sea ice growth and retreat from day to day. A scatterometer sea ice extent data set is valuable for comparison with other radiometer data sets and ground based measurements. This scatterometer sea ice record began with the NASA Scatterometer (NSCAT) and continued with the Quick Scatterometer (QuikSCAT) data set. The Ku-band Oceansat-2 scatterometer (OSCAT) is very similar to the Quick Scatterometer, which operated from 1999 to 2009. OSCAT continues the Ku-band scatterometer data record through 2014 with an overlap of eighteen days with QuikSCATs mission in 2009. This thesis discusses a particular climate application of the time series for sea ice extent observation. In this thesis, a QuikSCAT sea ice extent algorithm is modified for OSCAT. Gaps in OSCAT data are accounted for using a reverse time processing approach. The data gaps are filled in to support sea ice extent mapping. The data set is validated with overlapping data from QuikSCAT as well as the sea ice extent data set calculated from Special Sensor Microwave Imager data by the NASA Team algorithm.Data from the Advanced Scatterometer (ASCAT), which operates at C-band, are processed using a Bayesian classification algorithm for a stand-alone C-band sea ice extent product to continue scatterometer sea ice extent observation past 2014. ASCAT azimuth dependence data is developed for use as a parameter in the ASCAT sea ice extent algorithm. Image dilation and erosion techniques are employed to smooth the sea ice edge and correct misclassifications. ASCAT sea ice extent data is validated to overlapping OSCAT data.

In this thesis, the development and methodology of a new, consolidated BYU/NIC Antarctic Iceberg Tracking Database is presented. The new database combines data from the original BYU daily iceberg tracking database derived from scatterometers, and the National Ice Center's weekly Antarctic iceberg tracking database derived from mostly optical and infrared sensors. Using this data, interpolation methods and statistical analyses of iceberg locations are discussed. The intent of this database is to consolidate iceberg location data in order to increase accessibility to users.Active microwave remote sensing instruments are used to track tabular icebergs and provide a daily estimate of their positions and sizes. A consolidated data set of these positions from several different instruments is valuable to ensure accurate positional data. The scatterometer iceberg positional record began with the Seasat-A Satellite Scatterometer (SASS) and is continued with the Quick Scatterometer (QuikSCAT) and Advanced Scatterometer (ASCAT) data sets.A reliable method of automatically estimating Antarctic iceberg contours and sizes from satellite data is desirable to help better understand patterns in iceberg formation and behavior. Starting from scatterometer images, this thesis develops a method of using the relatively constant backscatter values across the surface of an iceberg to derive a contour of its shape. Contours are then used to find an angle of rotation between images taken on successive days. This method produces size estimates that are within 10% of the area given by the National Ice Center (NIC). The size estimates and rotation angles are included in the new consolidated database.

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.

Originally designed for wind velocity estimation over the ocean, scatterometers have since been applied to climate studies of the Earth's cryosphere and bioshere. As an integral part of climatological studies of the planet, the NASA Scatterometer Climate Record Pathfinder (SCP) supplies scatterometer-based products designed to aid researchers in climatological studies of the planet. In this thesis, necessary steps are taken to facilitate data from the Oceansat-2 Ku-band scatterometer (OSCAT) to be used in extending the Ku-band SCP dataset of conically scanning pencil-beam scatterometers begun by the Seawinds scatterometer flown on the QuikSCAT mission 1999-2009. As a standard SCP product, a temporal resolution enhancement technique for the scatterometer image reconstruction (SIR) algorithm is applied to OSCAT data. A relative cross-calibration method is developed to ensure consistency amongst datasets of conically scanning pencil-beam scatterometers in the SCP data time series. By application of the method, both raw data and SIR image data of OSCAT is cross-calibrated with QuikSCAT. To enable creation of SCP products requiring knowledge of the spatial response function (SRF) with OSCAT data, a method of estimating the SRF of pencil-beam scatterometers is developed. The estimation method employs rank-reduced least-squares to invert the radar equation using measurements over islands. A simulation is performed to validate the efficacy of the method and provide optimum choice of island size and number of singular values used in rank-reduced least-squares. The utility of the SRF estimates is demonstrated by applying an estimate of the OSCAT SRF to SIR image construction with OSCAT data.