Geoscientific Instrumentation, Methods and Data Systems | |
Potential soil moisture products from the aquarius radiometer and scatterometer using an observing system simulation experiment | |
G.De Lannoy1  X.Fan1  X.Feng1  L.Dabbiru1  P.Houser1  V.Anantharaj1  X.Zhan1  Y.Luo1  | |
DOI : 10.5194/gi-2-113-2013 | |
学科分类:天文学(综合) | |
来源: Copernicus Publications | |
【 摘 要 】
Using an observing system simulation experiment (OSSE), we investigate thepotential soil moisture retrieval capability of the National Aeronautics andSpace Administration (NASA) Aquarius radiometer (L-band 1.413 GHz) andscatterometer (L-band, 1.260 GHz). We estimate potential errors in soilmoisture retrievals and identify the sources that could cause those errors.The OSSE system includes (i) a land surface model in the NASA LandInformation System, (ii) a radiative transfer and backscatter model, (iii) arealistic orbital sampling model, and (iv) an inverse soil moisture retrievalmodel.
We execute the OSSE over a 1000 × 2200 km2 region in thecentral United States, including the Red and Arkansas river basins. Spatialdistributions of soil moisture retrieved from the radiometer andscatterometer are close to the synthetic truth. High root mean square errors(RMSEs) of radiometer retrievals are found over the heavily vegetatedregions, while large RMSEs of scatterometer retrievals are scattered over theentire domain. The temporal variations of soil moisture are realisticallycaptured over a sparely vegetated region with correlations 0.98 and 0.63, andRMSEs 1.28% and 8.23% vol/vol for radiometer and scatterometer,respectively. Over the densely vegetated region, soil moisture exhibitslarger temporal variation than the truth, leading to correlation 0.70 and0.67, respectively, and RMSEs 9.49% and 6.09% vol/vol respectively. Thedomain-averaged correlations and RMSEs suggest that radiometer is moreaccurate than scatterometer in retrieving soil moisture. The analysis alsodemonstrates that the accuracy of the retrieved soil moisture is affected byvegetation coverage andspatial aggregation.
【 授权许可】
Unknown
【 预 览 】
Files | Size | Format | View |
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RO201912130860147ZK.pdf | 1251KB | download |