DocumentCode
22292
Title
Characterizing Snowpack and the Freeze–Thaw State of Underlying Soil via Assimilation of Multifrequency Passive/Active Microwave Data: A Case Study (NASA CLPX 2003)
Author
Bateni, S. Mohyddin ; Margulis, Steven A. ; Podest, Erika ; McDonald, Kyle C.
Author_Institution
Dept. of Civil & Environ. Eng., Univ. of Hawaii at Manoa, Honolulu, HI, USA
Volume
53
Issue
1
fYear
2015
fDate
Jan. 2015
Firstpage
173
Lastpage
189
Abstract
Ground-based passive microwave observations at 18.7- and 36.5-GHz frequencies and active microwave observations in L- [1.4 GHz] and Ku- [15.5 GHz] bands are used within an ensemble-based data assimilation (DA) framework to characterize the snow water equivalent (SWE) and the underlying soil freeze-thaw state (including soil surface temperature and both soil ice/liquid water content). The proposed framework is tested at the local-scale observation site of the National Aeronautics and Space Administration (NASA) Cold Land Processes Experiment field campaign during the third intensive observation period (February 18-26, 2003) for which the best set of collocated ground-based passive/active microwave observations, SWE, soil surface temperature, and moisture measurements are available. The DA approach effectively merges an a priori estimate of the soil freeze-thaw state and SWE generated by a land surface model (LSM) with information contained in passive/active microwave observations in order to overcome errors in the forcing data of LSM. Results indicate that the root-mean-square errors of SWE, soil surface temperature, and soil ice+liquid water content after the assimilation of passive (active) observations respectively decrease to 25.4 mm (22.8 mm), 0.61 K (0.52 K), and 0.063 (0.057) from 90.55 mm, 2.17 K, and 0.13 before assimilation, resulting in improvements of 75% (77%), 72% (76%), and 51% (56%). Also, it is found that the simultaneous assimilation of passive and active measurements further improves the estimates of SWE and soil temperature as well as soil ice/liquid water content, suggesting that there is an advantage offered by the synergistic use of passive and active measurements. Overall, the findings show that future studies can take advantage of remotely sensed microwave passive and active measurements from present and upcoming satellites such as Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E), Soil Moisture Active Passive, and COld - Egion Hydrology High-resolution Observatory (CoReH2O) for monitoring SWE and the underlying soil freeze-thaw state.
Keywords
data assimilation; freezing; ice; land surface temperature; melting; moisture; remote sensing; snow; AD 2003 02 18 to 26; Advanced Microwave Scanning Radiometer-Earth Observing System; COld REgion Hydrology High-resolution Observatory; Ku-band; L-band; NASA CLPX 2003; National Aeronautics and Space Administration Cold Land Processes Experiment field campaign; Soil Moisture Active Passive; collocated ground-based active microwave observations; collocated ground-based passive microwave observations; ensemble-based data assimilation framework; frequency 1.4 GHz; frequency 15.5 GHz; frequency 18.7 GHz; frequency 36.5 GHz; ground-based passive microwave observations; land surface model; local-scale observation site; moisture measurements; multifrequency active microwave data assimilation; multifrequency passive microwave data assimilation; remotely sensed microwave active measurements; remotely sensed microwave passive measurements; root-mean-square errors; snow water equivalent; snowpack; soil freeze-thaw state; soil ice+liquid water content; soil surface temperature; Microwave FET integrated circuits; Microwave integrated circuits; Microwave measurement; Microwave theory and techniques; Snow; Soil; Temperature measurement; Active microwave data; data assimilation (DA); national aeronautics and space administration (NASA) Cold Land Processes Experiment (CLPX) 2003; passive microwave data; snow water equivalent (SWE); soil freeze–thaw; soil freeze???thaw;
fLanguage
English
Journal_Title
Geoscience and Remote Sensing, IEEE Transactions on
Publisher
ieee
ISSN
0196-2892
Type
jour
DOI
10.1109/TGRS.2014.2320264
Filename
6822506
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