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GRACE-REC: A reconstruction of climate-driven water storage changes over the last century
Version 3 2019-10-14, 00:04
Version 2 2019-05-31, 01:43
Version 1 2019-02-05, 23:48
dataset
posted on 2019-10-14, 00:04 authored by Vincent HumphreyVincent Humphrey, Lukas GudmundssonNotes for the 13.10.2019 update
- The months of January 2019 to July 2019 were added to the ERA5 reconstructions
- The robustness of the ERA5 reconstruction was improved for a few Greenland and Antarctica mascons by better handling a special case occuring when air temperature is always lower than 0°C during the calibration period.
- The updated ERA5 time series might differ from the previous version (especially individual ensemble members). With the exception of the special case mentioned above, these differences are not significant.
List of all files
Readme file
00_readme.txt
Monthly grids - ensemble means
01_monthly_grids_ensemble_means_allmodels.zip
The dataset contains reconstructed time series of daily and monthly anomalies of terrestrial water storage (TWS) based on two different GRACE solutions and three different meteorological forcing datasets. There is a total of 6 different models:
JPL_MSWEP - trained with GRACE JPL mascons, forced with MSWEP forcing (1979-2016)
JPL_GSWP3 - trained with GRACE JPL mascons, forced with GSWP3 forcing (1901-2014)
JPL_ERA5 - trained with GRACE JPL mascons, forced with ERA5 forcing (1979-present)
GSFC_MSWEP - trained with GRACE GSFC mascons, forced with MSWEP forcing (1979-2016)
GSFC_GSWP3 - trained with GRACE GSFC mascons, forced with GSWP3 forcing (1901-2014)
GSFC_ERA5 - trained with GRACE GSFC mascons, forced with ERA5 forcing (1979-present)
The reconstruction aims at reproducing the sub-decadal climate-driven variability observed in the GRACE data. Seasonal cycle and human impacts on TWS are not reconstructed. A GRACE-based seasonal cycle is provided for convenience. Long-term signals (trends over a period >15 years) are removed during the model calibration procedure but are still present in the final dataset and mainly represent precipitation-driven trends. The interpretation of the reconstructed long-term trends should be done with the awareness that there can be some uncertainty in the reconstructed trends.
For most applications, uncertainty ranges can be derived from the 100 ensemble members available for each model.
The grids are stored in NetCDFv4 files in units of mm (kg m^-2). Although the data is provided on a 0.5 degrees grid, the effective spatial resolution should be considered to be 3 degrees, similar to the original resolution of the GRACE datasets. This might need to be taken into account when comparing this dataset against other sources.
The global means are stored as csv files in units of Gt of water. To convert back to mm of water, use the land area values given in the reference paper below.
When using this dataset, please cite:
Vincent Humphrey, October 2019
California Institute of Technology
Your feedback is always welcome:
vincent.humphrey[-a-t-]caltech.edu (vincent.humphrey[-a-t-]bluewin.ch)
Monthly grids - ensembles, model 1 to 6
02_monthly_grids_ensemble_JPL_MSWEP_1979_2016.zip
02_monthly_grids_ensemble_JPL_GSWP3_1901_2014.zip
02_monthly_grids_ensemble_JPL_ERA5_1979_201907.zip
02_monthly_grids_ensemble_GSFC_MSWEP_1979_2016.zip
02_monthly_grids_ensemble_GSFC_GSWP3_1901_2014.zip
02_monthly_grids_ensemble_GSFC_ERA5_1979_201907.zip
Daily grids - ensemble means, model 1 to 6
03_daily_grids_ensemble_means_JPL_MSWEP_1979_2016.zip
03_daily_grids_ensemble_means_JPL_GSWP3_1901_2014.zip
03_daily_grids_ensemble_means_JPL_ERA5_1979_201907.zip
03_daily_grids_ensemble_means_GSFC_MSWEP_1979_2016.zip
03_daily_grids_ensemble_means_GSFC_GSWP3_1901_2014.zip
03_daily_grids_ensemble_means_GSFC_ERA5_1979_201907.zip
Global averages - daily and monthly time series
04_global_averages_allmodels.zip
Content of readme
GRACE TWS Reconstruction (GRACE_REC_v03)The dataset contains reconstructed time series of daily and monthly anomalies of terrestrial water storage (TWS) based on two different GRACE solutions and three different meteorological forcing datasets. There is a total of 6 different models:
JPL_MSWEP - trained with GRACE JPL mascons, forced with MSWEP forcing (1979-2016)
JPL_GSWP3 - trained with GRACE JPL mascons, forced with GSWP3 forcing (1901-2014)
JPL_ERA5 - trained with GRACE JPL mascons, forced with ERA5 forcing (1979-present)
GSFC_MSWEP - trained with GRACE GSFC mascons, forced with MSWEP forcing (1979-2016)
GSFC_GSWP3 - trained with GRACE GSFC mascons, forced with GSWP3 forcing (1901-2014)
GSFC_ERA5 - trained with GRACE GSFC mascons, forced with ERA5 forcing (1979-present)
The reconstruction aims at reproducing the sub-decadal climate-driven variability observed in the GRACE data. Seasonal cycle and human impacts on TWS are not reconstructed. A GRACE-based seasonal cycle is provided for convenience. Long-term signals (trends over a period >15 years) are removed during the model calibration procedure but are still present in the final dataset and mainly represent precipitation-driven trends. The interpretation of the reconstructed long-term trends should be done with the awareness that there can be some uncertainty in the reconstructed trends.
For most applications, uncertainty ranges can be derived from the 100 ensemble members available for each model.
The grids are stored in NetCDFv4 files in units of mm (kg m^-2). Although the data is provided on a 0.5 degrees grid, the effective spatial resolution should be considered to be 3 degrees, similar to the original resolution of the GRACE datasets. This might need to be taken into account when comparing this dataset against other sources.
The global means are stored as csv files in units of Gt of water. To convert back to mm of water, use the land area values given in the reference paper below.
When using this dataset, please cite:
Humphrey, V., & Gudmundsson, L.
(2019). GRACE-REC: a reconstruction of climate-driven water storage
changes over the last century. Earth System Science Data, 11(3), 1153-1170.
Vincent Humphrey, October 2019
California Institute of Technology
Your feedback is always welcome:
vincent.humphrey[-a-t-]caltech.edu (vincent.humphrey[-a-t-]bluewin.ch)
Abstract
The
amount of water stored on continents is an important constraint for water mass
and energy exchanges in the Earth system and exhibits large inter-annual
variability at both local and continental scales. From 2002 to 2017, the
satellites of the Gravity Recovery and Climate Experiment mission (GRACE) have
observed changes in terrestrial water storage (TWS) with an unprecedented level
of accuracy. In this paper, we use a statistical model trained with GRACE
observations to reconstruct past climate-driven changes in TWS from historical and
near real time meteorological datasets at daily and monthly scales. Unlike most
hydrological models which represent water reservoirs individually (e.g. snow,
soil moisture, etc.) and usually provide a single model run, the presented
approach directly reconstructs total TWS changes and includes hundreds of
ensemble members which can be used to quantify predictive uncertainty. We
compare these data-driven TWS estimates with other independent evaluation
datasets such as the sea level budget, large-scale water balance from
atmospheric reanalysis and in-situ streamflow measurements. We find that the
presented approach performs overall as well or better than a set of
state-of-the-art global hydrological models (Water Resources Reanalysis version
2). We provide reconstructed TWS anomalies at a spatial resolution of 0.5°, at both
daily and monthly scales over the period 1901 to present, based on two
different GRACE products and three different meteorological forcing datasets,
resulting in 6 reconstructed TWS datasets of 100 ensemble members each. Possible
user groups and applications include hydrological modelling and model
benchmarking, sea level budget studies, assessments of long-term changes in the
frequency of droughts, the analysis of climate signals in geodetic time series
and the interpretation of the data gap between the GRACE and the GRACE
Follow-On mission.
Check reference for additional details and caveats.
Reference
Humphrey, V., & Gudmundsson, L.
(2019). GRACE-REC: a reconstruction of climate-driven water storage
changes over the last century. Earth System Science Data, 11(3), 1153-1170.
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terrestrial water storageGRACEgravityclimate dataclimate changehydrologymodelland surface modelhydrological modelsoil moisturegroundwaterspatial auto-regressive processuncertaintyfreshwater resourcesstatistical modelreconstructionhistorical dataHydrologySurfacewater HydrologyClimatology (excl. Climate Change Processes)Climate Change ProcessesPhotogrammetry and Remote SensingGeodesyOceanographySimulation and Modelling
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