Using Satellite Gravimetry for Validating the Water Cycle in Global and Regional Atmospheric Reanalyses 1

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1 Using Satellite Gravimetry for Validating the Water Cycle in Global and Regional Atmospheric Reanalyses 1 Anne Springer, Jürgen Kusche, Annette Eicker Institute of Geodesy and Geoinformation, Bonn University, Germany Christian Ohlwein, Christoph Bollmeyer, Jan Keller Meteorological Institute, Bonn University, Germany Laurent Longuevergne CNRS Géosciences Rennes, France Susanne Crewell Institute for Geophysics and Meteorology, Cologne University, Cologne, Germany

2 The water budget equation ΔS=P-E-R Precipitation P 2 Evapotranspiration E Storage S Discharge R

3 The water budget equation ΔS+R=P-E 3 P - E represents: an important boundary condition for hydrological studies and climate modeling. an indicator for the intensification of the water cycle. the coupling of the Earth s water and energy cycles.

4 Data sets ΔS+R=P-E GFZ GRACE Release 05a 4 GRDC BfG Regional Analysis Regional Reanalysis Global Reanalyses Observations COSMO-EU COSMO-REA6 ERA-Interim MERRA MERRA-Land MPI (E) GPCC (P) E-OBS (P)

5 GRACE & Water budget studies Evapotranspiration, Mississippi Discharge, Global Rodell et al., 2004 Syed et al., P-E, Danube Springer et al., 2014

6 Availability of discharge Availability of monthly discharge data from GRDC and BfG for

7 COSMO-REA6: a regional reanalysis Data assimilation: Continuous nudging scheme wind, temperature, humidity, pressure Surface analysis: Snow depth, sea surface temperature, soil moisture 7 Boundary data: ECMWF ERA-Interim Bollmeyer et al. (2015): Towards a high-resolution regional reanalysis for the European CORDEX domain

8 Study area 8 Region SIze [km 2 ] Meuse Rhine Ems Weser Elbe Oder Danube

9 Processing strategy Aim: consistent time series of ΔS & P-E Careful processing of GRACE data: Degree 1 coefficients replaced c 20 coefficient replaced GIA model applied 9 DDK4 filter Central differences Time-variable rescaling factor Springer, et al. (2014) New Estimates of Variations in Water Flux and Storage over Europe Based on Regional (Re)Analyses and Multisensor Observations.

10 P-E = ΔS+R 10

11 P-E = ΔS+R: detrended, deseasoned ρ= ρ= ρ= Anne Springer Earth Observation for Water Cycle Science 21/10/2015

12 Consistency: ΔS+R-(P-E)=0 12

13 Power Spectrum Density 13

14 Consistency: ΔS+R-(P-E)=0 14 𝜀 = 𝑎 + 𝑏 sin(2𝜋𝑡) + 𝑐 cos(2𝜋𝑡) + 𝑑 sin(4𝜋𝑡) + 𝑒 cos(4𝜋𝑡) Anne Springer Earth Observation for Water Cycle Science 21/10/2015

15 Bias COSMO-REA6 COSMO-EU GPCC+MPI 15 ERA-Interim MERRA MERRA-Land

16 TWSC Total water storage from fluxes: Danube ΔS = P-E-R 16 TWS S = P E R

17 TWSC Total water storage from fluxes: Danube ΔS = P-E-R 17 TWS ε = a + b sin(2πt) + c cos(2πt) + d sin(4πt) + e cos(4πt) S = P E R

18 TWSC Total water storage from fluxes: Danube ΔS = P-E-R 18 TWS S = P E R

19 Total water storage from fluxes 19

20 Take Home Messages Short-term variability: GRACE and models agree notably well even in very small basins. Constant biases, differences in annual amplitude and phase: regional models perform better than global models. Reconstructed storage from fluxes: Time-variable biases lead to trends in storage. 20 Further steps: Extend study to the whole European area Develop more sophisticated error models Understand flux-derived storage

21 Literatur Bollmeyer, C., J. D. Keller, C. Ohlwein, S. Wahl, S. Crewell, P. Friederichs, A. Hense, J. Keune, S. Kneifel, I. Pscheidt, S. Redl and S. Steinke (2015) Towards a high-resolution regional reanalysis for the European CORDEX domain. Q. J. R. Meteorol. Soc. 141: Jung, M., M. Reichstein and A. Bondeau (2009) Towards global empirical upscaling of FLUXNET eddy covariance observations: validation of a model tree ensemble approach using a biosphere model. Biogeosciences, 6: Klees, R., E.A. Zapreeva, H.C. Winsemius and H.H.G. Savenije (2007) The bias in GRACE estimates of continental water storage variations. Hydrol. Earth Syst. Sci., 11: Kusche, J. (2007) Approximate decorrelation and non-isotropic smoothing of time-variable GRACE-type gravity field models. J. Geodesy, 81: Lorenz, C. and H. Kunstmann (2012) The Hydrological Cycle in Three State-of-the-art Reanalyses: Intercomparison and Performance Analysis. J. Hydrometeor., 13: M. Rodell, J. S. Famiglietti, J. Chen, S. I. Seneviratne, P. Viterbo, S. Holl and C. R. Wilson (2004) Basin scale estimates of evapotranspiration using GRACE and other observations. Geophy. Res. Lett., 31. T. H. Syed, J. S. Famiglietti (2009) GRACE-Based Estimates of Terrestrial Freshwater Discharge from Basin to Continental Scales. J. Hydrometeor., 10: Springer, Anne, J. Kusche, K. Hartung, C. Ohlwein and L. Longuevergne (2014) New Estimates of Variations in Water Flux and Storage over Europe Based on Regional (Re)Analyses and Multisensor Observations. J. Hydrometeor., 15: Wahr, J., M. Molenaar and F. Bryan (1998) Time variability of the Earth s gravity field: hydrological and oceanic effects and their possible detection using GRACE. J. Geophys. Res.-Solid, 103:

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