Development and evaluation of an advanced microwave radiance data assimilation system for estimating snow water storage at the continental scale

Snow cover modulates the Earth's surface energy and water fluxes, and snowmelt runoff is the principal source of water for humans and ecosystems in many of the middle to high latitudes in the Northern Hemisphere. Understanding spatial and temporal variation in snowpack is crucial for climate studies and water resource management and thus the climate and hydrological research communities have invested in improving large-scale snow estimates. This dissertation aims to develop an advanced snow radiance assimilation (RA) system to improve continental-scale snow water storage estimates. The RA system is comprised of the Community Land Model version 4 (CLM4) (for snow energy and mass balance modeling), radiative transfer models (RTMs) (for brightness temperature estimates), and the Data Assimilation Research Testbed (DART) (for ensemble-based data assimilation). Two snowpack RTMs, the Microwave Emission Model for Layered Snowpacks (MEMLS) and the Dense Media Radiative Transfer--Multi Layers model (DMRT-ML), are used to simulate T[subscript B] of a multi-layered snowpack. Through an error characterization study, this dissertation presents that the correlations between snow water equivalent (SWE) error and brightness temperature (T[subscript B]) error and subsequent RA performance in estimating snow are significantly affected by all physical properties of soil and snow involved in estimating T[subscript B]. Based on the error characterization results, it is hypothesized that the continental-scale RA performance in estimating snow water storage can be improved by simultaneously updating all model physical states and parameters determining T[subscript B] based on a rule, in which prior estimates are updated depending on their correlations with a prior T[subscript B]. The results of a series of RA experiments show that the improved continental-scale snow estimates are obtained by applying the hypothesis. This dissertation also shows that further improvement of the performance of the RA system can be achieved, especially for vegetated areas, by assimilating the best-performing frequency channels (i.e., 18.7 and 23.8 GHz) and by considering the vegetation single scattering albedo to represent the vegetation effect on T[subscript B] at the top of the atmosphere.Geological Science

Exploring scaling issues by using NASA Cold Land Processes Experiment(CLPX-1, IOP3) radiometric data

The NASA Cold-land Processes Field Experiment-1 (CLPX-1) involved several instruments in order to acquire data at different spatial resolutions. Indeed, one of the main tasks of CLPX-1 was to explore scaling issues associated with microwave remote sensing of snowpacks. To achieve this task, microwave brightness temperatures collected at 18.7, 36.5, and 89 GHz at LSOS test site by means of the University of Tokyo s Ground Based Microwave Radiometer-7 (GBMR-7) were compared with brightness temperatures recorded by the NOAA Polarimetric Scanning Radiometer (PSR/A) and by SSM/I and AMSR-E radiometers. Differences between different scales observations were observed and they may be due to the topography of the terrain and to observed footprints. In the case of satellite and airborne data, indeed, it is necessary to consider the heterogeneity of the terrain and the presence of trees inside the observed scene becomes a very important factor. Also when comparing data acquired only by the two satellites, differences were found. Different acquisition times and footprint positions, together with different calibration and validation procedures, can be responsible for the observed differences