NCA-LDAS Land Analysis: Development and Performance of a Multisensor, Multivariate Land Data Assimilation System for the National Climate Assessment

This article describes one of the first successful examples of multisensor, multivariate land data assimilation, encompassing a large suite of soil moisture, snow depth, snow cover, and irrigation intensity environmental data records (EDRs) from the Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave Imager (SSM/I), Advanced Scatterometer (ASCAT), Moderate-Resolution Imaging Spectroradiometer (MODIS), Advanced Microwave Scanning Radiometer (AMSR-E and AMSR2), Soil Moisture Ocean Salinity (SMOS) mission, and Soil Moisture Active Passive (SMAP) mission. The analysis is performed using the NASA Land Information System (LIS) as an enabling tool for the U.S. National Climate Assessment (NCA). The performance of the NCA Land Data Assimilation System (NCA-LDAS) is evaluated by comparing it to a number of hydrological reference data products. Results indicate that multivariate assimilation provides systematic improvements in simulated soil moisture and snow depth, with marginal effects on the accuracy of simulated streamflow and evapotranspiration. An important conclusion is that across all evaluated variables, assimilation of data from increasingly more modern sensors (e.g., SMOS, SMAP, AMSR2, ASCAT) produces more skillful results than assimilation of data from older sensors (e.g., SMMR, SSM/I, AMSR-E). The evaluation also indicates the high skill of NCA-LDAS when compared with other LSM products. Further, drought indicators based on NCA-LDAS output suggest a trend of longer and more severe droughts over parts of the western United States during 1979–2015, particularly in the southwestern United States, consistent with the trends from the U.S. Drought Monitor, albeit for a shorter 2000–15 time period.

[1]  David Mocko,et al.  Quantifying the Added Value of Snow Cover Area Observations in Passive Microwave Snow Depth Data Assimilation , 2015 .

[2]  J. D. Tarpley,et al.  The multi‐institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system , 2004 .

[3]  Jeffrey P. Walker,et al.  THE GLOBAL LAND DATA ASSIMILATION SYSTEM , 2004 .

[4]  M. Rodell,et al.  Assimilation of gridded terrestrial water storage observations from GRACE into a land surface model , 2016 .

[5]  R. Koster,et al.  Assimilation of GRACE terrestrial water storage into a land surface model: Evaluation and potential value for drought monitoring in western and central Europe , 2012 .

[6]  Zong-Liang Yang,et al.  Multisensor snow data assimilation at the continental scale: The value of Gravity Recovery and Climate Experiment terrestrial water storage information , 2010 .

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

[8]  Anthony C. Janetos,et al.  Building an integrated U.S. National Climate Indicators System , 2016, Climatic Change.

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

[10]  Benjamin F. Zaitchik,et al.  Forward-Looking Assimilation of MODIS-Derived Snow-Covered Area into a Land Surface Model , 2009 .

[11]  K. Mo,et al.  Model-Based Drought Indices over the United States , 2008 .

[12]  Yann Kerr,et al.  An RFI Index to Quantify the Contamination of SMOS Data by Radio-Frequency Interference , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[13]  Wade T. Crow,et al.  Benchmarking a Soil Moisture Data Assimilation System for Agricultural Drought Monitoring , 2014 .

[14]  C. Daly,et al.  A Statistical-Topographic Model for Mapping Climatological Precipitation over Mountainous Terrain , 1994 .

[15]  Randal D. Koster,et al.  On the Nature of Soil Moisture in Land Surface Models , 2009 .

[16]  Martha C. Anderson,et al.  A climatological study of evapotranspiration and moisture stress across the continental United States based on thermal remote sensing: 1. Model formulation , 2007 .

[17]  R. Jeu,et al.  Multisensor historical climatology of satellite‐derived global land surface moisture , 2008 .

[18]  Richard Kelly,et al.  The AMSR-E Snow Depth Algorithm: Description and Initial Results , 2009 .

[19]  A. Bondeau,et al.  Towards global empirical upscaling of FLUXNET eddy covariance observations: validation of a model tree ensemble approach using a biosphere model , 2009 .

[20]  Alina Barbu,et al.  The effect of satellite-derived surface soil moisture and leaf area index land data assimilation on streamflow simulations over France , 2017 .

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

[22]  Kristie J. Franz,et al.  Assimilation of AMSR-E snow water equivalent data in a spatially-lumped snow model , 2015 .

[23]  Zong-Liang Yang,et al.  Assimilation of MODIS snow cover through the Data Assimilation Research Testbed and the Community Land Model version 4 , 2014 .

[24]  Arlindo da Silva,et al.  Data assimilation in the presence of forecast bias , 1998 .

[25]  Sujay V. Kumar,et al.  Multiscale assimilation of Advanced Microwave Scanning Radiometer–EOS snow water equivalent and Moderate Resolution Imaging Spectroradiometer snow cover fraction observations in northern Colorado , 2012 .

[26]  R. Houborg,et al.  Drought indicators based on model‐assimilated Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage observations , 2012 .

[27]  Steven D. Miller,et al.  Assimilating MODIS and AMSR-E Snow Observations in a Snow Evolution Model , 2012 .

[28]  J. Famiglietti,et al.  A GRACE‐based water storage deficit approach for hydrological drought characterization , 2014 .

[29]  Aaron Boone,et al.  The Hydrological Modeling and Analysis Platform (HyMAP): Evaluation in the Amazon Basin , 2012 .

[30]  Randal D. Koster,et al.  Assessment of MERRA-2 Land Surface Hydrology Estimates , 2017 .

[31]  J. D. Tarpley,et al.  Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model , 2003 .

[32]  Michael G. Bosilovich,et al.  Atmospheric Water Balance and Variability in the MERRA-2 Reanalysis , 2017 .

[33]  D. Toll,et al.  Simulating the Effects of Irrigation over the United States in a Land Surface Model Based on Satellite-Derived Agricultural Data , 2010 .

[34]  G. P. Cressman.  AN OPERATIONAL OBJECTIVE ANALYSIS SYSTEM , 1959 .

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

[36]  R. Heim.  A Review of Twentieth-Century Drought Indices Used in the United States , 2002 .

[37]  Lifeng Luo,et al.  Streamflow and water balance intercomparisons of four land surface models in the North American Land Data Assimilation System Project , 2004 .

[38]  R. Reynolds,et al.  The NCEP/NCAR 40-Year Reanalysis Project , 1996, Renewable Energy.

[39]  Toshio Koike,et al.  Progress and Prospects for Reanalysis for Weather and Climate , 2008 .

[40]  K. Mo,et al.  Continental-scale water and energy flux analysis and validation for the North American Land Data Assimilation System project phase 2 (NLDAS-2): 1. Intercomparison and application of model products , 2012 .

[41]  Yi Y. Liu,et al.  ESA CCI Soil Moisture for improved Earth system understanding : State-of-the art and future directions , 2017 .

[42]  Martha C. Anderson,et al.  Assimilation of Gridded GRACE Terrestrial Water Storage Estimates in the North American Land Data Assimilation System , 2016 .

[43]  Michael H. Cosh,et al.  Assimilation of Remotely Sensed Soil Moisture and Snow Depth Retrievals for Drought Estimation , 2014 .

[44]  Dorothy K. Hall,et al.  Nimbus-7 SMMR derived global snow cover parameters , 1987 .

[45]  M. Ek,et al.  Continental‐scale water and energy flux analysis and validation for North American Land Data Assimilation System project phase 2 (NLDAS‐2): 2. Validation of model‐simulated streamflow , 2012 .

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

[47]  Henrik Madsen,et al.  On the definition and modelling of streamflow drought duration and deficit volume , 1997 .

[48]  David D. Parrish,et al.  NORTH AMERICAN REGIONAL REANALYSIS , 2006 .

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

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

[51]  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 .

[52]  A. Sterl,et al.  The ERA‐40 re‐analysis , 2005 .

[53]  T. Ose,et al.  JRA‐25: Japanese 25‐year re‐analysis project—progress and status , 2005 .

[54]  J. Dracup,et al.  The Quantification of Drought: An Evaluation of Drought Indices , 2002 .

[55]  R. Vose,et al.  An Overview of the Global Historical Climatology Network-Daily Database , 2012 .

[56]  Lars Isaksen,et al.  Initialisation of Land Surface Variables for Numerical Weather Prediction , 2014, Surveys in Geophysics.

[57]  Yi Y. Liu,et al.  Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals , 2011 .

[58]  D. Lettenmaier,et al.  Satellite‐based near‐real‐time estimation of irrigated crop water consumption , 2009 .

[59]  D. Wilhite,et al.  Objective Quantification of Drought Severity and Duration , 1999 .

[60]  Kenneth W. Harrison,et al.  A comparison of methods for a priori bias correction in soil moisture data assimilation , 2012 .

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

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

[63]  Sujay V. Kumar,et al.  A land data assimilation system for sub-Saharan Africa food and water security applications , 2017, Scientific Data.

[64]  S. Shukla,et al.  Use of a standardized runoff index for characterizing hydrologic drought , 2008 .

[65]  Sujay V. Kumar,et al.  High-performance Earth system modeling with NASA/GSFC’s Land Information System , 2007, Innovations in Systems and Software Engineering.

[66]  M. Palecki,et al.  THE DROUGHT MONITOR , 2002 .

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

[68]  Kenneth W. Harrison,et al.  Land surface Verification Toolkit (LVT) – a generalized framework for land surface model evaluation , 2012 .

[69]  Leung Tsang,et al.  A prototype AMSR-E global snow area and snow depth algorithm , 2003, IEEE Trans. Geosci. Remote. Sens..

[70]  A. Weerts,et al.  Data assimilation of GRACE terrestrial water storage estimates into a regional hydrological model of the Rhine River basin , 2014 .

[71]  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 .

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

[73]  B. Ramsay,et al.  The interactive multisensor snow and ice mapping system , 1998 .

[74]  R. Moss,et al.  Building a sustained climate assessment process , 2016, Climatic Change.

[75]  Craig Anderson,et al.  Analysis of Radio Frequency Interference in Metop ASCAT Backscatter Measurements , 2017, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[76]  M. Rodell,et al.  Evaluation of a Model-Based Groundwater Drought Indicator in the Conterminous U.S. , 2015 .

[77]  Uang,et al.  The NCEP Climate Forecast System Reanalysis , 2010 .

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

[79]  Mutlu Ozdogan,et al.  A new methodology to map irrigated areas using multi-temporal MODIS and ancillary data: An application example in the continental US , 2008 .

[80]  Bryan A. Tolson,et al.  Comparison of X-Band and L-Band Soil Moisture Retrievals for Land Data Assimilation , 2017, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[81]  F. Pappenberger,et al.  ERA-Interim/Land: a global land surface reanalysis data set , 2015 .

[82]  Wade T. Crow,et al.  A land surface data assimilation framework using the land information system : Description and applications , 2008 .

[83]  Alina Barbu,et al.  Integrating ASCAT surface soil moisture and GEOV1 leaf area index into the SURFEX modelling platform: a land data assimilation application over France , 2013 .

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

[85]  Sujay V. Kumar,et al.  Land information system: An interoperable framework for high resolution land surface modeling , 2006, Environ. Model. Softw..

[86]  J. D. Tarpley,et al.  Surface radiation budgets in support of the GEWEX Continental‐Scale International Project (GCIP) and the GEWEX Americas Prediction Project (GAPP), including the North American Land Data Assimilation System (NLDAS) project , 2003 .

[87]  Eric F. Wood,et al.  Uncertainties, Correlations, and Optimal Blends of Drought Indices from the NLDAS Multiple Land Surface Model Ensemble , 2014 .