Evaluating Bias‐Corrected AMSR‐E Soil Moisture using in situ Observations and Model Estimates

Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) soil moisture data products are proven to be useful across various regions around the world. However, numerous studies have suggested that validation and bias-correction at the local scale is important to use them with confidence for numerical weather prediction, land surface energy, and water balance assessment, including infiltration and drainage. Here we investigate the cumulative distribution function (CDF) to correct AMSR-E surface soil moisture data using field observations of soil moisture for 37 sites from Nebraska’s Automated Weather Data Network (AWDN) and model-simulated soil moisture from southwestern Idaho. We explore the scaling of AMSR-E data using simulated soil moisture from three hydrological models, Variable Infiltration Capacity (VIC), Noah Land Surface Model (Noah LSM) and Robinson Hubbard 1-D (RH1D) models. We hypothesize that these calibrated hydrological models can substitute for field observations to represent continuous surface of soil moisture fields over space and time when used in conjunction with daily AMSR-E data. Our results suggest that it is necessary to have the AMSR-E data bias-corrected based on either field observations or model estimates. The magnitude of values for corrected AMSR-E soil moisture and observed soil moisture showed better correlation for the growing seasons between 2003 and 2005. It is also shown that well-calibrated hydrological models can be useful to provide correction for the AMSR-E product thereby adding value to the AMSR-E soil moisture datasets.

[1]  R. Mahmood,et al.  Quality Control of Soil Water Data in Applied Climate Information System—Case Study in Nebraska , 2010 .

[2]  D. Lettenmaier,et al.  Streamflow simulation for continental‐scale river basins , 1997 .

[3]  E. Njoku,et al.  Vegetation and surface roughness effects on AMSR-E land observations , 2006 .

[4]  Y. Kerr,et al.  Operational readiness of microwave remote sensing of soil moisture for hydrologic applications , 2007 .

[6]  T. Koike,et al.  Modification and Application of the Satellite-Based Land Data Assimilation Scheme for Very Dry Soil Regions Using AMSR-E Images : Model Validation for Mongolia-a CEOP data platform , 2007 .

[7]  Wade T. Crow,et al.  An observation system simulation experiment for the impact of land surface heterogeneity on AMSR-E soil moisture retrieval , 2001, IEEE Trans. Geosci. Remote. Sens..

[8]  M. Khanal,et al.  Evaluation of the Complementary Relationship Using Noah Land Surface Model and North American Regional Reanalysis (NARR) Data to Estimate Evapotranspiration in Semiarid Ecosystems , 2013 .

[9]  Randal D. Koster,et al.  Bias reduction in short records of satellite soil moisture , 2004 .

[10]  Dennis P. Lettenmaier,et al.  Application of regional parameter estimation schemes to simulate the water balance of a large continental river , 1997 .

[11]  Matthew F. McCabe,et al.  Copula-Derived Observation Operators for Assimilating TMI and AMSR-E Retrieved Soil Moisture into Land Surface Models , 2007 .

[12]  Thomas R. H. Holmes,et al.  An evaluation of AMSR–E derived soil moisture over Australia , 2009 .

[13]  Y. Kerr.  Soil moisture from space: Where are we? , 2007 .

[14]  K. Hubbard,et al.  Soil Water Assessment Model for Several Crops in the High Plains , 1990 .

[15]  T. J. Schmugge,et al.  Surface soil moisture measurement with microwave radiometry , 1995 .

[16]  Jennifer M. Jacobs,et al.  Temporal Variability Corrections for Advanced Microwave Scanning Radiometer E (AMSR-E) Surface Soil Moisture: Case Study in Little River Region, Georgia, U.S. , 2008, Sensors.

[17]  Philippe Richaume,et al.  Evaluation of AMSR‐E soil moisture product based on ground measurements over temperate and semi‐arid regions , 2008 .

[18]  R. Koster,et al.  Comparison and assimilation of global soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR‐E) and the Scanning Multichannel Microwave Radiometer (SMMR) , 2007 .

[19]  Jennifer C. Adam,et al.  Implications of global climate change for snowmelt hydrology in the twenty‐first century , 2009 .

[20]  P. Dirmeyer,et al.  Evaluation of AMSR-E soil moisture results using the in-situ data over the Little River Experimental Watershed, Georgia , 2008 .

[21]  Venkat Lakshmi,et al.  Soil moisture as an indicator of weather extremes , 2004 .

[22]  M. S. Moran,et al.  Estimating soil moisture at the watershed scale with satellite-based radar and land surface models , 2004 .

[23]  J. Dudhia,et al.  Coupling an Advanced Land Surface–Hydrology Model with the Penn State–NCAR MM5 Modeling System. Part I: Model Implementation and Sensitivity , 2001 .

[24]  Matthew F. McCabe,et al.  Initial soil moisture retrievals from AMSR‐E: Multiscale comparison using in situ data and rainfall patterns over Iowa , 2005 .

[25]  H. Mao,et al.  Melting behavior of H2O at high pressures and temperatures , 2005 .

[26]  J. Shukla,et al.  Influence of Land-Surface Evapotranspiration on the Earth's Climate , 1982, Science.

[27]  Thomas J. Jackson,et al.  Soil moisture retrieval from AMSR-E , 2003, IEEE Trans. Geosci. Remote. Sens..

[28]  Jianguang Wen,et al.  Surface soil moisture estimates from AMSR-E observations over an arid area, Northwest China , 2009 .

[29]  Luca Brocca,et al.  Assimilation of Surface- and Root-Zone ASCAT Soil Moisture Products Into Rainfall–Runoff Modeling , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[30]  R. Mahmood,et al.  Simulating sensitivity of soil moisture and evapotranspiration under heterogeneous soils and land uses , 2003 .

[31]  V. Lakshmi,et al.  Characterizing subpixel variability of low resolution radiometer derived soil moisture using high resolution radar data , 2008 .

[32]  D. Lettenmaier,et al.  A Long-Term Hydrologically Based Dataset of Land Surface Fluxes and States for the Conterminous United States* , 2002 .

[33]  D. Lettenmaier,et al.  Surface soil moisture parameterization of the VIC-2L model: Evaluation and modification , 1996 .

[34]  Robain De Keyser,et al.  Can ASCAT-derived soil wetness indices reduce predictive uncertainty in well-gauged areas? A comparison with in situ observed soil moisture in an assimilation application , 2012 .

[35]  F. Aires,et al.  Sensitivity of satellite microwave and infrared observations to soil moisture at a global scale: Relationship of satellite observations to in situ soil moisture measurements , 2005 .

[36]  W. Wagner,et al.  Improving runoff prediction through the assimilation of the ASCAT soil moisture product , 2010 .

[37]  Philippe Richaume,et al.  Sunglint observations over land from ground and airborne L-band radiometer data , 2008 .

[38]  Frank Veroustraete,et al.  Assessment of Evapotranspiration and Soil Moisture Content Across Different Scales of Observation , 2008, Sensors.

[39]  H. Pan,et al.  Interaction between soil hydrology and boundary-layer development , 1987 .

[40]  D. Lettenmaier,et al.  A simple hydrologically based model of land surface water and energy fluxes for general circulation models , 1994 .

[41]  Wade T. Crow,et al.  Improving hydrologic predictions of a catchment model via assimilation of surface soil moisture , 2011 .

[42]  V. Sridhar,et al.  Assessment of Soil Moisture Dynamics of the Nebraska Sandhills Using Long-Term Measurements and a Hydrology Model , 2006 .

[43]  Matthias Drusch,et al.  Observation operators for the direct assimilation of TRMM microwave imager retrieved soil moisture , 2005 .

[44]  Peter Moczo,et al.  On the rheological models used for time‐domain methods of seismic wave propagation , 2005 .

[45]  Yi Y. Liu,et al.  Error characterisation of global active and passive microwave soil moisture datasets. , 2010 .

[46]  V. Sridhar,et al.  Development of the Soil Moisture Index to Quantify Agricultural Drought and Its “User Friendliness” in Severity-Area-Duration Assessment , 2008 .