Global Assimilation of Multiangle and Multipolarization SMOS Brightness Temperature Observations into the GEOS-5 Catchment Land Surface Model for Soil Moisture Estimation

AbstractMultiangle and multipolarization L-band microwave observations from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated into the Goddard Earth Observing System Model, version 5 (GEOS-5), using a spatially distributed ensemble Kalman filter. A variant of this system is also used for the Soil Moisture Active Passive (SMAP) Level 4 soil moisture product. The assimilation involves a forward simulation of brightness temperatures (Tb) for various incidence angles and polarizations and an inversion of the differences between Tb forecasts and observations into updates to modeled surface and root-zone soil moisture, as well as surface soil temperature. With SMOS Tb assimilation, the unbiased root-mean-square difference between simulations and gridcell-scale in situ measurements in a few U.S. watersheds during the period from 1 July 2010 to 1 July 2014 is 0.034 m3 m−3 for both surface and root-zone soil moisture. A validation against gridcell-scale measurements and point-scale measurements from ...

[1]  Bruce H. Raup,et al.  Correction: Brodzik, M.J., et al. EASE-Grid 2.0: Incremental but Significant Improvements for Earth-Gridded Data Sets. ISPRS International Journal of Geo-Information 2012, 1, 32-45 , 2014, ISPRS Int. J. Geo Inf..

[2]  Praveen Kumar,et al.  A catchment‐based approach to modeling land surface processes in a general circulation model: 1. Model structure , 2000 .

[3]  Jasper A. Vrugt,et al.  Uncertainty quantification of GEOS-5 L-band radiative transfer model parameters using Bayesian inference and SMOS observations , 2014 .

[4]  Yudong Tian,et al.  Estimating evapotranspiration with land data assimilation systems , 2011 .

[5]  Gabrielle J. M. De Lannoy,et al.  Converting Between SMOS and SMAP Level-1 Brightness Temperature Observations Over Nonfrozen Land , 2015, IEEE Geoscience and Remote Sensing Letters.

[6]  Rolf H. Reichle,et al.  Connecting Satellite Observations with Water Cycle Variables Through Land Data Assimilation: Examples Using the NASA GEOS-5 LDAS , 2013, Surveys in Geophysics.

[7]  Randal D. Koster,et al.  Land Boundary Conditions for the Goddard Earth Observing System Model Version 5 (GEOS-5) Climate Modeling System: Recent Updates and Data File Descriptions , 2015 .

[8]  Mike Schwank,et al.  Assimilation of an L-Band Microwave Soil Moisture Proxy to Compensate for Uncertainties in Precipitation Data , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[9]  Joanna Joiner,et al.  An error analysis of radiance and suboptimal retrieval assimilation , 2000 .

[10]  G. Evensen,et al.  Analysis Scheme in the Ensemble Kalman Filter , 1998 .

[11]  Xiangjun Tian,et al.  Assimilation of microwave brightness temperature in a land data assimilation system with multi-observation operators , 2012 .

[12]  Ahmad Al Bitar,et al.  SMOS soil moisture assimilation for improved hydrologic simulation in the Murray Darling Basin, Australia , 2015 .

[13]  Jiancheng Shi,et al.  A soil moisture assimilation scheme based on the microwave Land Emissivity Model and the Community Land Model , 2012 .

[14]  Yann Kerr,et al.  The SMOS Mission: New Tool for Monitoring Key Elements ofthe Global Water Cycle , 2010, Proceedings of the IEEE.

[15]  J. MacQueen.  Some methods for classification and analysis of multivariate observations , 1967 .

[16]  Ahmad Al Bitar,et al.  An Initial Assessment of SMOS Derived Soil Moisture over the Continental United States , 2012, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[17]  G. Lannoy,et al.  Global Calibration of the GEOS-5 L-Band Microwave Radiative Transfer Model over Nonfrozen Land Using SMOS Observations , 2013 .

[18]  Randal D. Koster,et al.  Assimilation of Satellite-Derived Skin Temperature Observations into Land Surface Models , 2010 .

[19]  Stéphane Bélair,et al.  A Global Root-Zone Soil Moisture Analysis Using Simulated L-band Brightness Temperature in Preparation for the Hydros Satellite Mission , 2006 .

[20]  Jesse,et al.  U.S. Climate Reference Network after One Decade of Operations: Status and Assessment , 2013 .

[21]  A. B. Smith,et al.  The Murrumbidgee soil moisture monitoring network data set , 2012 .

[22]  D. McLaughlin,et al.  Hydrologic Data Assimilation with the Ensemble Kalman Filter , 2002 .

[23]  G. Lannoy,et al.  Simultaneous estimation of model state variables and observation and forecast biases using a two-stage hybrid Kalman filter , 2012 .

[24]  N. Verhoest,et al.  Correcting for forecast bias in soil moisture assimilation with the ensemble Kalman filter , 2007 .

[25]  Chunlin Huang,et al.  Experiments of one-dimensional soil moisture assimilation system based on ensemble Kalman filter , 2008 .

[26]  Paul Poli,et al.  Diagnosis of observation, background and analysis‐error statistics in observation space , 2005 .

[27]  S. Schubert,et al.  MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications , 2011 .

[28]  Benjamin Scarino,et al.  A Dynamic Approach to Addressing Observation-Minus-Forecast Bias in a Land Surface Skin Temperature Data Assimilation System , 2015 .

[29]  W. Crow,et al.  The assimilation of remotely sensed soil brightness temperature imagery into a land surface model using Ensemble Kalman filtering: a case study based on ESTAR measurements during SGP97 , 2003 .

[30]  Witold F. Krajewski,et al.  Analyses of a long‐term, high‐resolution radar rainfall data set for the Baltimore metropolitan region , 2012 .

[31]  T. Jackson,et al.  III. Measuring surface soil moisture using passive microwave remote sensing , 1993 .

[32]  Arnaud Mialon,et al.  The SMOS Soil Moisture Retrieval Algorithm , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[33]  Randal D. Koster,et al.  An updated treatment of soil texture and associated hydraulic properties in a global land modeling system , 2014 .

[34]  Venkat Lakshmi,et al.  Advances in downscaling soil moisture for use in drought and flood assessments: Implications for data from the Soil Moisture Active and Passive (SMAP) Mission , 2015 .

[35]  Wade T. Crow,et al.  The Contributions of Precipitation and Soil Moisture Observations to the Skill of Soil Moisture Estimates in a Land Data Assimilation System , 2011 .

[36]  P. Houser,et al.  Soil Moisture Data Assimilation , 2017 .

[37]  Wade T. Crow,et al.  Performance Metrics for Soil Moisture Retrievals and Application Requirements , 2009 .

[38]  C. Albergel,et al.  From near-surface to root-zone soil moisture using an exponential filter: an assessment of the method based on in-situ observations and model simulations , 2008 .

[39]  Christian Heipke,et al.  MULTIPLE-MODEL BASED VERIFICATION OF JAPANESE ROAD DATA , 2010 .

[40]  Bruce H. Raup,et al.  EASE-Grid 2.0: Incremental but Significant Improvements for Earth-Gridded Data Sets , 2012, ISPRS Int. J. Geo Inf..

[41]  Rolf Reichle,et al.  Variational data assimilation of microwave radiobrightness observations for land surface hydrology applications , 2001, IEEE Trans. Geosci. Remote. Sens..

[42]  John Kochendorfer,et al.  U.S. Climate Reference Network Soil Moisture and Temperature Observations , 2013 .

[43]  Wade T. Crow,et al.  Role of Subsurface Physics in the Assimilation of Surface Soil Moisture Observations , 2009 .

[44]  R. Koster,et al.  Assessing the Impact of Horizontal Error Correlations in Background Fields on Soil Moisture Estimation , 2003 .

[45]  S. Cohn,et al.  Ooce Note Series on Global Modeling and Data Assimilation Construction of Correlation Functions in Two and Three Dimensions and Convolution Covariance Functions , 2022 .

[46]  Toshio Koike,et al.  A simplified land data assimilation scheme and its application to soil moisture experiments in 2002 (SMEX02) , 2003 .

[47]  Misako Kachi,et al.  INSTRUMENT PERFORMANCE AND CALIBRATION OF AMSR-E AND AMSR2 , 2010 .

[48]  Dara Entekhabi,et al.  Tests of sequential data assimilation for retrieving profile soil moisture and temperature from observed L-band radiobrightness , 1999, IEEE Trans. Geosci. Remote. Sens..

[49]  Xin Li,et al.  Joint Assimilation of Surface Temperature and L‐Band Microwave Brightness Temperature in Land Data Assimilation , 2013 .

[50]  Clemens Simmer,et al.  Effects of the Near-Surface Soil Moisture Profile on the Assimilation of L-band Microwave Brightness Temperature , 2006 .

[51]  Rita Castro,et al.  SMOS instrument performance and calibration , 2012, 2012 IEEE International Geoscience and Remote Sensing Symposium.

[52]  Rolf H. Reichle,et al.  Observation-Corrected Precipitation Estimates in GEOS-5 , 2014 .

[53]  Sujay V. Kumar,et al.  Assessing the Impact of L-Band Observations on Drought and Flood Risk Estimation: A Decision-Theoretic Approach in an OSSE Environment , 2014 .

[54]  Jiancheng Shi,et al.  The Soil Moisture Active Passive (SMAP) Mission , 2010, Proceedings of the IEEE.

[55]  R. Koster,et al.  Global Soil Moisture from Satellite Observations, Land Surface Models, and Ground Data: Implications for Data Assimilation , 2004 .

[56]  Randal D. Koster,et al.  Global assimilation of satellite surface soil moisture retrievals into the NASA Catchment land surface model , 2005 .

[57]  Y. Kerr,et al.  L-band Microwave Emission of the Biosphere (L-MEB) Model: Description and calibration against experimental data sets over crop fields , 2007 .

[58]  Niko E. C. Verhoest,et al.  Satellite-Scale Snow Water Equivalent Assimilation into a High-Resolution Land Surface Model , 2010 .

[59]  Marco L. Carrera,et al.  The Canadian Land Data Assimilation System (CaLDAS): Description and Synthetic Evaluation Study , 2015 .

[60]  D. Entekhabi,et al.  Land data assimilation and estimation of soil moisture using measurements from the Southern Great Plains 1997 Field Experiment , 2001 .

[61]  Thomas J. Jackson,et al.  Validation of Advanced Microwave Scanning Radiometer Soil Moisture Products , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[62]  Rolf H. Reichle,et al.  Assimilation of passive and active microwave soil moisture retrievals , 2012 .

[63]  R. Koster,et al.  Assessment and Enhancement of MERRA Land Surface Hydrology Estimates , 2011 .

[64]  Jun Qin,et al.  Optimal Exploitation of AMSR-E Signals for Improving Soil Moisture Estimation Through Land Data Assimilation , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[65]  T. Jackson,et al.  The USDA Natural Resources Conservation Service Soil Climate Analysis Network (SCAN) , 2007 .

[66]  P. Houser,et al.  Assimilation and downscaling of satellite observed soil moisture over the Little River Experimental Watershed in Georgia, USA , 2013 .

[67]  David M. Le Vine,et al.  Aquarius: An Instrument to Monitor Sea Surface Salinity From Space , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[68]  D. McLaughlin,et al.  Downscaling of radio brightness measurements for soil moisture estimation: A four‐dimensional variational data assimilation approach , 2001 .

[69]  T. Jackson,et al.  Temporal persistence and stability of surface soil moisture in a semi-arid watershed , 2008 .

[70]  A. Robock,et al.  The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements , 2011 .

[71]  Dara Entekhabi,et al.  Solving the inverse problem for soil moisture and temperature profiles by sequential assimilation of multifrequency remotely sensed observations , 1994, IEEE Trans. Geosci. Remote. Sens..