title: Temporal Variability Corrections for Advanced Microwave Scanning Radiometer E (AMSR-E) Surface Soil Moisture: Case Study in Little River Region, Georgia, U.S.
abstract: Statistical correction methods, the Cumulative Distribution Function (CDF) matching technique and Regional Statistics Method (RSM) are applied to adjust the limited temporal variability of Advanced Microwave Scanning Radiometer E (AMSR-E) data using the Common Land Model (CLM). The temporal variability adjustment between CLM and AMSR-E data was conducted for annual and seasonal periods for 2003 in the Little River region, GA. The results showed that the statistical correction techniques improved AMSR-E's limited temporal variability as compared to ground-based measurements. The regression slope and intercept improved from 0.210 and 0.112 up to 0.971 and -0.005 for the non-growing season. The R² values also modestly improved. The Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf Area Index (LAI) products were able to identify periods having an attenuated microwave brightness signal that are not likely to benefit from these statistical correction techniques.
authors.affiliation: Research Physical Scientist, USDA-ARS Hydrology & Remote Sensing Lab., Beltsville, MD 20705, U.S.A.. minha.choi@ars.usda.gov.
authors.forename: Minha
authors.initials: M
authors.lastname: Choi
authors.affiliation: Associate Professor of Civil Engineering, University of New Hampshire, Durham, NH 03824, U.S.A. jennifer.jacobs@unh.edu.
authors.forename: Jennifer M
authors.initials: JM
authors.lastname: Jacobs
keywords: Advanced Microwave Scanning Radiometer E (AMSR-E); Common Land Model (CLM); Leaf Area Index (LAI); Statistical correction; Temporal variability