A global reconstruction of climate‐driven subdecadal water storage variability

Since 2002, the Gravity Recovery and Climate Experiment (GRACE) mission has provided unprecedented observations of global mass redistribution caused by hydrological processes. However, there are still few sources on pre-2002 global terrestrial water storage (TWS). Classical approaches to retrieve past TWS rely on either land surface models (LSMs) or basin-scale water balance calculations. Here we propose a new approach which statistically relates anomalies in atmospheric drivers to monthly GRACE anomalies. Gridded subdecadal TWS changes and time-dependent uncertainty intervals are reconstructed for the period 1985–2015. Comparisons with model results demonstrate the performance and robustness of the derived data set, which represents a new and valuable source for studying subdecadal TWS variability, closing the ocean/land water budgets and assessing GRACE uncertainties. At midpoint between GRACE observations and LSM simulations, the statistical approach provides TWS estimates (doi:10.5905/ethz-1007-85) that are essentially derived from observations and are based on a limited number of transparent model assumptions.

[1]  A. Güntner,et al.  Calibration analysis for water storage variability of the global hydrological model WGHM , 2009 .

[2]  Anny Cazenave,et al.  Evaluation of the Global Mean Sea Level Budget between 1993 and 2014 , 2016, Surveys in Geophysics.

[3]  Matthew Rodell,et al.  Groundwater Storage Changes: Present Status from GRACE Observations , 2016, Surveys in Geophysics.

[4]  J. Famiglietti.  The global groundwater crisis , 2014 .

[5]  P. Sen.  Estimates of the Regression Coefficient Based on Kendall's Tau , 1968 .

[6]  Anne Springer,et al.  Does GRACE see the terrestrial water cycle “intensifying”? , 2016 .

[7]  Anny Cazenave,et al.  Past terrestrial water storage (1980–2008) in the Amazon Basin reconstructed from GRACE and in situ river gauging data , 2010 .

[8]  J. Kusche,et al.  A systematic impact assessment of GRACE error correlation on data assimilation in hydrological models , 2016, Journal of Geodesy.

[9]  J. Kusche,et al.  Calibration/Data Assimilation Approach for Integrating GRACE Data into the WaterGAP Global Hydrology Model (WGHM) Using an Ensemble Kalman Filter: First Results , 2013, Surveys in Geophysics.

[10]  Franz Barthelmes,et al.  Determination of dominant periodic components of water storage changes from GRACE and global hydrology models , 2007 .

[11]  J. Nash,et al.  River flow forecasting through conceptual models part I — A discussion of principles☆ , 1970 .

[12]  Sonia I. Seneviratne,et al.  Basin‐scale water‐balance estimates of terrestrial water storage variations from ECMWF operational forecast analysis , 2006 .

[13]  D. Lawrence,et al.  Parameterization improvements and functional and structural advances in Version 4 of the Community Land Model , 2011 .

[14]  T. Meyers,et al.  Sensitivity of Land Surface Simulations to Model Physics, Land Characteristics, and Forcings, at Four CEOP Sites , 2007 .

[15]  Irma J. Terpenning,et al.  STL : A Seasonal-Trend Decomposition Procedure Based on Loess , 1990 .

[16]  W. Tad Pfeffer,et al.  Recent contributions of glaciers and ice caps to sea level rise , 2012, Nature.

[17]  F. Bryan,et al.  Time variability of the Earth's gravity field: Hydrological and oceanic effects and their possible detection using GRACE , 1998 .

[18]  J. Famiglietti,et al.  Satellite-based estimates of groundwater depletion in India , 2009, Nature.

[19]  B. Scanlon,et al.  Global evaluation of new GRACE mascon products for hydrologic applications , 2016 .

[20]  S. Swenson,et al.  Accuracy of GRACE mass estimates , 2006 .

[21]  Victor Zlotnicki,et al.  Time‐variable gravity from GRACE: First results , 2004 .

[22]  Sonia I. Seneviratne,et al.  New diagnostic estimates of variations in terrestrial water storage based on ERA‐Interim data , 2011 .

[23]  V. M. Tiwari,et al.  Dwindling groundwater resources in northern India, from satellite gravity observations , 2009 .

[24]  M. Watkins,et al.  Quantifying and reducing leakage errors in the JPL RL05M GRACE mascon solution , 2016 .

[25]  D. S. Wilks,et al.  Chapter 8 - Forecast Verification , 2011 .

[26]  P. R. Bevington,et al.  Data Reduction and Error Analysis for the Physical Sciences , 1969 .

[27]  M. Rodell,et al.  Assimilation of GRACE Terrestrial Water Storage Data into a Land Surface Model: Results for the Mississippi River Basin , 2008 .

[28]  J. Kusche,et al.  Multivariate Prediction of Total Water Storage Changes Over West Africa from Multi-Satellite Data , 2014, Surveys in Geophysics.

[29]  Zizhan Zhang,et al.  Long-Term Groundwater Variations in Northwest India From Satellite Gravity Measurements , 2014 .

[30]  Isabella Velicogna,et al.  Regional acceleration in ice mass loss from Greenland and Antarctica using GRACE time‐variable gravity data , 2014 .

[31]  Vincent Humphrey,et al.  Assessing Global Water Storage Variability from GRACE: Trends, Seasonal Cycle, Subseasonal Anomalies and Extremes , 2016, Surveys in Geophysics.

[32]  B. Hurk,et al.  A Revised Hydrology for the ECMWF Model: Verification from Field Site to Terrestrial Water Storage and Impact in the Integrated Forecast System , 2009 .

[33]  Lukas Gudmundsson,et al.  Towards observation-based gridded runoff estimates for Europe , 2014 .

[34]  Dick Dee,et al.  Low‐frequency variations in surface atmospheric humidity, temperature, and precipitation: Inferences from reanalyses and monthly gridded observational data sets , 2010 .

[35]  S. Swenson,et al.  Climate model biases in seasonality of continental water storage revealed by satellite gravimetry , 2006 .

[36]  Anny Cazenave,et al.  The rate of sea-level rise , 2014 .

[37]  R. Steven Nerem,et al.  The 2011 La Niña: So strong, the oceans fell , 2012 .

[38]  M. Watkins,et al.  Improved methods for observing Earth's time variable mass distribution with GRACE using spherical cap mascons , 2015 .

[39]  J. Famiglietti,et al.  Characteristic mega-basin water storage behavior using GRACE , 2013, Water resources research.

[40]  Heikki Haario,et al.  DRAM: Efficient adaptive MCMC , 2006, Stat. Comput..

[41]  William H. Farrand,et al.  Hydrothermal origin of halogens at Home Plate, Gusev Crater , 2008 .

[42]  J. Famiglietti,et al.  A decade of sea level rise slowed by climate-driven hydrology , 2016, Science.

[43]  J. Thepaut,et al.  The ERA‐Interim reanalysis: configuration and performance of the data assimilation system , 2011 .

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

[45]  Andreas Güntner,et al.  Improvement of Global Hydrological Models Using GRACE Data , 2008 .

[46]  E. Wood,et al.  Little change in global drought over the past 60 years , 2012, Nature.

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

[48]  David M. Lawrence,et al.  A GRACE‐based assessment of interannual groundwater dynamics in the Community Land Model , 2015 .

[49]  A. Cazenave,et al.  Total land water storage change over 2003–2013 estimated from a global mass budget approach , 2015 .

[50]  J. Famiglietti,et al.  Improving parameter estimation and water table depth simulation in a land surface model using GRACE water storage and estimated base flow data , 2010 .

[51]  P. Döll,et al.  Global‐scale assessment of groundwater depletion and related groundwater abstractions: Combining hydrological modeling with information from well observations and GRACE satellites , 2014 .

[52]  M. Watkins,et al.  GRACE Measurements of Mass Variability in the Earth System , 2004, Science.

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