Paper Info
Title
Feasibility of Characterizing Snowpack and the Freeze–Thaw State of Underlying Soil Using Multifrequency Active/Passive Microwave Data
Abstract
An ensemble-based data assimilation approach is developed to characterize the snow water equivalent (SWE) and underlying soil freeze-thaw state (including the soil surface temperature and both soil ice and liquid water content) using multifrequency passive and active microwave remote-sensing measurements. Its feasibility was examined using a synthetic test where passive microwave (1.4, 18.7, and 36.5 GHz) and active microwave [L-band (1.4 GHz), C-band (5.4 GHz), and Ku-band (12 GHz)] measurements at the point scale were individually and simultaneously assimilated to estimate the SWE and soil freeze-thaw state using an Ensemble Batch Smoother framework. The contribution of each channel in retrieving the true SWE, soil surface temperature, soil liquid water and ice content was investigated at the local-scale observation site of the National Aeronautics and Space Administration Cold Land Processes Experiments Field Campaign in northern Colorado during both the snow accumulation (Fall 2002-Winter 2003) and melt (Spring 2003) periods. All of the utilized passive and active measurements were found to contain valuable and complementary information for characterizing the SWE and freeze-thaw state of the underlying soil. L-band measurements were most effective for soil freeze-thaw state estimation, whereas higher frequencies were more effective at SWE characterization. In addition, results from the simultaneous assimilation of passive and active microwave data were compared to those from a modeling approach without assimilating microwave data (open loop). It was found that assimilating both passive and active microwave data decreased the errors that are associated with the open-loop approach. Finally, passive and active measurements were undersampled as expected from the overpasses of current and future satellite platforms. It was observed that the developed method can reliably estimate the soil freeze-thaw state and SWE, even with measurement sequences anticipated from the- temporal frequency of existing and future satellites such as the Special Sensor Microwave/Imager, Soil Moisture Active Passive Mission, and Cold Regions Hydrology High-Resolution Observatory.
Year
DOI
Venue
2013
10.1109/TGRS.2012.2229466
Geoscience and Remote Sensing, IEEE Transactions
Keywords
Field
DocType
data assimilation,hydrological techniques,ice,land surface temperature,melting,radiometry,remote sensing,snow,soil,AD 2002 to 2003,C-band measurements,Cold Regions Hydrology High-Resolution Observatory,Ku-band measurements,L-band measurements,National Aeronautics and Space Administration Cold Land Processes Experiments Field Campaign,SWE characterization,Soil Moisture Active Passive Mission,Special Sensor Microwave/Imager,USA,active microwave data,ensemble batch smoother framework,ensemble-based data assimilation approach,frequency 1.4 GHz,frequency 12 GHz,frequency 18.7 GHz,frequency 36.5 GHz,frequency 5.4 GHz,future satellite platforms,local-scale observation,measurement sequences,modeling approach,multifrequency active microwave remote-sensing measurements,multifrequency passive microwave remote-sensing measurements,northern Colorado,open-loop approach,passive microwave data,point scale,snow accumulation period,snow melt period,snow water equivalent,snowpack,soil freeze-thaw state estimation,soil ice content,soil liquid water content,soil surface temperature,synthetic test,temporal frequency,Active microwave data,data assimilation (DA),passive microwave data,snow cover,snow water equivalent (SWE),soil freeze–thaw
Microwave,Satellite,Liquid water content,Remote sensing,Radiometry,Water content,Data assimilation,Mathematics,Snow,Snowpack
Journal
Volume
Issue
ISSN
51
7
0196-2892
Citations 
PageRank 
References 
3
0.53
17
Authors
5
Name
Order
Citations
PageRank
S. Mohyeddin Bateni1183.14
Chunlin Huang2367.22
Steven A. Margulis3153.17
Erika Podest4133.19
Kyle McDonald5365.09