Contributors: J. Haas, E. Boergens, A. Güntner

GFZ Helmholtz Centre for Geosciences

Issued by: GFZ / J.Haas

Date: 10/06/2026

Ref: C3S2_313c_EODC_WP3-DDP-GWSC-v1_202602_PUGS

Official reference number service contract: ECMWF/COPERNICUS/2024/C3S2_313c_EODC

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History of modifications

List of datasets covered by this document

Acronyms

General definitions

Equivalent Water Height: Equivalent Water Height represents the mass change per unit area as if it were entirely due to a uniform layer of water. It is derived from changes in gravity and surface deformation and is typically expressed in millimetres or centimetres.

GCOS Product Target Requirements: For each ECV, measurable requirements of the product performance are defined by expert panels within GCOS. These requirements encompass quantitative criteria along several dimensions, including spatial resolution, temporal resolution, measurement uncertainty, stability over time (bias drift), and timeliness (latency of data availability). For each target requirement, a threshold and a goal value are defined. Threshold is the minimum acceptable requirement. If a product fails this, it is presumably not useful for climate monitoring. The goal is the ideal level. Once this is met, further improvements in that criterion are not strictly necessary for most applications. 

Glacial Isostatic Adjustment (GIA): Glacial isostatic adjustment describes the deformational behaviour of the solid Earth in response to glacial loading processes, particularly resulting in surface displacements due to stress, gravity, and sea level changes.

Glacier Mass Change: Glacier Mass Change refers to the gain or loss of ice mass in a glacier over a given time period expressed in terms of water equivalent. It reflects the balance between accumulation (e.g., snowfall) and ablation (e.g., melting, sublimation), indicating whether a glacier is growing or shrinking.

Gravity Recovery and Climate Experiment (GRACE): Twin satellite mission observing the time variable gravity field of the Earth from which water mass redistribution can be inferred. The mission was active between 2002 and 2017 and was a joint US-German project. 

GRACE Follow-On (GRACE-FO): Identically constructed successor satellite mission of GRACE, launched in 2018. The mission is again a joint US-German project.

Groundwater Storage Change (GWSC): the deviation or anomaly of groundwater storage in a certain epoch (e.g., a month) from the long-term mean groundwater storage. Groundwater is here defined as water stored underground in the saturated zone of soil and rock.

Leakage: Leakage refers to the inability to precisely localise signals in the GRACE-derived data sets, due to factors such as the band-limited resolution of GRACE and filtering. Leakage leads to apparent signal loss (leakage out) or gain (leakage in) inside a given integration region.

Level-0 data: Raw instrument data received from the satellites. 

Level-1 data: Level-0 data converted to engineering units (Level-1A). Time-tagging of the data of all different instruments, filtering, and downsampling results in Level-1B data. Level-1B data includes range rate data, Global Positioning System (GPS) positions, and accelerometer data.

Level-2 data: Time-variable, usually monthly, gravity fields given in Spherical Harmonic (SH) coefficients (Level-2A). Within the C3S TWSA production system further processing steps, including several corrections, are implemented (Level-2B, see section 3.1 of the TWSA ATBD).

Level-3 data: Time-variable, usually monthly, gravity fields given in the spatial domain as gridded data, based on Level-2B data. TWSA data is a Level-3 data set. 

Level-4 data: Targeted compartment mass-change products derived from Level-2B spherical harmonic or Level-3 gridded gravity data using additional signal isolation methods, model integration, or removal of non-target water storage contributions. This GWSC product is a Level-4 data set.

Root Zone Soil Moisture (RZSM): RZSM refers to the amount of water stored in the soil within the plant root zone. In this product the root zone is fixed to a depth of 2 meters.

Snow Water Equivalent (SWE): SWE is the amount of liquid water that would result if a given volume of snow were completely melted. It quantifies the water content of a snowpack.

Spatial Correlation Analysis: Spatial Correlation Analysis is a statistical method used to quantify the degree to which a variable is correlated with itself or another variable across geographic space. It assesses patterns of similarity or dependence between observations as a function of their spatial proximity or arrangement.

Spherical Harmonics (SH): Mathematical functions defined on the surface of a sphere, commonly used to express potential fields such as the Earth's gravity field by solving Laplace's equation.

Spherical Harmonic Coefficients: Commonly used representation of a global gravity field model based on the Spherical Harmonics basis functions. They are jointly estimated by least-squares adjustment, together with other parameters (instrument and orbit), using satellite observations provided by GRACE and GRACE-FO.

Subtraction Approach: The Subtraction Approach (or Residual Approach) refers to the method in which a target water storage compartment (here: Groundwater Storage Change) is estimated by subtracting other independently quantified storage compartments (here: Snow Water Equivalent, Root Zone Soil Moisture, Glacier Mass, and Surface Water Storage) from TWSA.

Terrestrial Water Storage Anomaly (TWSA): TWSA represents the deviation or anomaly of terrestrial water storage (TWS) in a certain epoch (e.g., a month) from the long-term (2003-01 - 2022-12) mean. TWS comprises allhydrological water storage compartments: groundwater storage, soil moisture, surface water storage, snow storage, and glaciers. Globally, TWSA can only be observed with GRACE and GRACE-FO. 

Uncertainty: Uncertainty measures jointly the precision and accuracy of the GWSC data, expressed as a standard deviation. The uncertainties of the GWSC grids are propagated from the uncertainties of the input datasets.

Water Storage Compartment (WSC): A WSC refers to a distinct component of the terrestrial water cycle in which water is stored, such as groundwater, soil moisture, surface water, snow, or glaciers. In the context of GWSC, the individual WSCs, i.e. glacier mass change (GM), snow water equivalent (SWE), root zone soil moisture (RZSM), and surface water storage (SWS), are subtracted from the TWSA signal to isolate the groundwater storage change signal.

Executive summary

This Product User Guide and Specifications (PUGS) is a self-contained document that gathers all necessary information for using and applying the Groundwater Storage Change (GWSC) dataset, as delivered within the Copernicus Climate Change Service (C3S).

The C3S Terrestrial Water Storage and Groundwater service provides the operational service to generate datasets of the Essential Climate Variables (ECV) quantities Terrestrial Water Storage Anomaly (TWSA) and Groundwater Storage Change (GWSC) for a wide variety of users, such as climate scientists, hydrologists, water resource managers, and policymakers. This document covers the GWSC data product.

The GWSC dataset is a Level-4 product derived by subtracting observation- and model-based estimates of the anomalies of glacier mass, snow water equivalent, root zone soil moisture, and surface water storage from the C3S TWSA data. The resulting product provides users with ready-to-use, gridded monthly estimates of groundwater storage change without the need for further processing.

This document provides a brief summary of the data processing involved in generating the GWSC dataset in Section 1.1. A more extensive description of the data processing algorithm can be found in the GWSC Algorithm Theoretical Basis Document (ATBD). This section also includes details on the spatial and temporal characteristics of the product. Section 1.2 then details the Global Climate Observing System (GCOS) user requirements and their fulfilment with the dataset. This is followed by an example visualisation of key variables in Section 1.3. Section 1.4 collects data usage information, including the known issues and limitations of the GWSC dataset in Section 1.4.4, which are especially relevant for users unfamiliar with gravity-based groundwater products. This document concludes with Section 2, which provides information on data access.

Product Description

Groundwater Storage Change (GWSC) description

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Groundwater storage change (GWSC) refers to variations in the amount of water stored in aquifers and subsurface reservoirs. Groundwater is the largest liquid freshwater reservoir on Earth and plays a central role in sustaining ecosystems, agriculture, and fresh water supply, and, as such, has been designated as an Essential Climate Variable (ECV) by the World Meteorological Organization (WMO). GWSC is a key indicator of long-term changes in water availability, particularly in regions where surface water resources are limited or seasonally variable.

Figure 1 provides a schematic illustration of the global hydrological cycle, highlighting the water storage compartments making up Terrestrial Water Storage (TWS) and the role of groundwater in it. 

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Figure 1: Scheme of the hydrological cycle and of the different water storage compartments that make up Terrestrial Water Storage (TWS).

Currently, no satellite mission or in-situ technique is capable of observing groundwater storage directly. Instead, GWSC is derived indirectly from observations made by the GRACE (Gravity Recovery and Climate Experiment, 2002–2017) and GRACE-FO (GRACE Follow-On, since 2018) satellite missions. These missions measure temporal and spatial variations in the Earth's gravity field which, over land, are primarily caused by the redistribution of water masses across all storage compartments combined. The resulting Terrestrial Water Storage Anomaly (TWSA) therefore integrates signals from groundwater, soil moisture, snow and ice, and surface water bodies.

The groundwater signal is derived by subtracting observation- and model-based estimates of the anomalies A of other Water Storage Compartments (WSCs), i.e. glacier mass (GM), snow water equivalent (SWE), root zone soil moisture (RZSM), and surface water storage (SWS), from the TWSA, following the water budget equation (1):

The global availability of GWSC data as presented with this product will enable a wide range of hydrological and hydrogeological applications, e.g. the assessments of long-term groundwater depletion in heavily irrigated regions such as Northern India, the Middle East, and the High Plains Aquifer in North America. GWSC could also provide insight into groundwater recharge dynamics in response to extreme precipitation events or prolonged droughts, and support the monitoring of aquifer recovery following periods of intensive extraction.

It should be noted that Greenland and Antarctica are excluded from the GWSC product. In these regions, the TWSA signal is dominated by changes in glacier and ice sheet mass, which are very large in magnitude and carry substantial uncertainties. As a result, reliably isolating the groundwater signal through the subtraction approach is not currently feasible for these regions.

Data processing algorithm 

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The GWSC product is derived from five input data streams: the C3S TWSA and the four WSC datasets covering glacier mass change (GM), snow water equivalent (SWE), root zone soil moisture (RZSM), and surface water storage (SWS). Figure 2 provides an overview of the processing steps required to produce the GWSC data. Comprehensive details of the algorithm are available in the GWSC ATBD. The current version of the algorithm is GWSC v1.0.

All input data streams are first converted to anomalies relative to the reference period January 2003 to December 2022, and units are harmonised to millimetres of equivalent water height. The WSC datasets are then resampled to a common 0.5° grid, with a consistent land-ocean mask applied throughout. To make the WSC data spatially compatible with the TWSA data, which carries the characteristic spatial smoothing of GRACE and GRACE-FO gravity field solutions, the aggregated WSCs are filtered using a 250 km Gaussian filter, whose width was determined through a spatial correlation analysis (Sharifi et al., 2025a). Finally, the filtered and aggregated WSC anomalies are subtracted from TWSA to yield the GWSC product. Uncertainties from all input data streams are propagated through the same processing chain and delivered alongside the GWSC estimates.

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Figure 2: Overview of the processing steps in the GWSC production system. Input WSC data streams (TWSA, SWS, SWE, RZSM, GM) and their uncertainties are converted to anomalies, resampled to a common 0.5° grid under a consistent land-ocean mask, filtered with a 250 km Gaussian filter, whose width is informed by a spatial correlation analysis, and finally combined through the subtraction approach. Uncertainties are propagated throughout the chain to the final GWSC product.

Product characteristics

Processing level

The processing level of the GWSC product is Level-4 according to the definition by NASA EarthDATA¹ .

Spatial information

The Level-4 data are provided on a regular 0.5° x 0.5° latitude-longitude grid. This results in a dimension of 720 grid cells in longitude and 360 in latitude for the data fields. Of these 259200 grid cells in total, 59018 are considered land cells according to the applied land-ocean mask and contain numeric values, whereas the remaining cells contain NaN (Not a Number) values. The mask is based on the European Space Agency (ESA) Climate Change Initiative (CCI) global map of open water bodies v4.0 (CCI WB v4.0) and are freely available in different resolutions (Sharifi et al., 2025b).

Longitude and latitude values are expressed with respect to the WGS84 ellipsoid. The given coordinates describe the central point of each grid cell.

Temporal information 

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Typically, the GWSC product has a monthly temporal resolution. The time variable of the product is based on the time variable of the TWSA product. In TWSA it represents the mean day of the data collection period used for each monthly value. Therefore, the time stamp in the TWSA product corresponds to the 15th or 16th of the respective month. In the GWSC product the timestamp is set to the 1st of the respective month for user friendliness.

It has to be noted that, due to GRACE and GRACE-FO mission operations or instrument issues, some months are unavailable, or of lower data quality, or based on data collection periods that deviate from full monthly coverage. Additionally, owing to the gap between the two missions GRACE and GRACE-FO no data are available between July 2017 and May 2018. Since the GWSC product is based on the GRACE-based TWSA product, the corresponding months are also missing in the GWSC product. Figure 3 shows all available monthly solutions. For more details on the deviations from the monthly solutions, including missing data, monthly solutions with poorer data quality, and solutions where the data collection deviated from the monthly time frame, please refer to section 1.1.2.3 of the TWSA PUGS.

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Figure 3: Overview of the available monthly GWSC fields for Climate Data Record (CDR) v1.0. 

Timeliness and update frequency

The GWSC data processing chain is mainly dominated by a) the production schedule of the TWSA dataset, and b) the delivery of the Glacier Mass product. The former requires approximately three months from data collection of the satellites to the generation of Level-3 TWSA data. For the latter case, however, a full global product can only be produced once a year. This is due to the fact that manual measurements of the changes of glacier heights, which are crucial to the production, are usually only done once a year, around the same dates. As soon as both these datasets are available, the GWSC processing chain takes only a couple of days to run on GFZ's HPC cluster. Accordingly, the last entry of the dataset dates back to the latest month that both datasets cover.

CDR v1.0 covers the period from April 2002 to September 2023. CDR v2.0 will be published in early 2027 and extend this period until September 2026. An ICDR will be published in early 2028 and, again, extend the period until September 2027.

Overview of Product Target Requirements 

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The product target requirements have been defined by the GCOS (WMO, 2025). Table 1 summarises the requirements and characteristics of the C3S GWSC product.

For each requirement, a threshold and a goal value, for some also a breakthrough value, are defined as listed in Table 1. The goal is the ideal level. Once this is met, further improvements in that criterion are not strictly necessary for most applications. Breakthrough is the level considered a major step towards operational provision. Threshold is the minimum acceptable requirement. Further details on product accuracy and stability are provided in the Product Quality Assessment Report (PQAR).

Table 1: GCOS goal, breakthrough and threshold requirements for the ECV GWSC. Colours: green - within goal, yellow - within breakthrough or threshold, red - does not meet threshold, grey - not applicable

Example visualisation of key variables 

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Figure 4 shows, as an example, (a) GWSC and (b) GWSC uncertainty for March 2008.

Figure 4: Fields of the final data product. (a) shows GWSC from the final data product for the example month of March 2008 stored in the gwsc variable in the netcdf file; (b) shows the uncertainty of GWSC for the same month, stored in the gwsc_uncertainty variable of the netcdf file.

Data usage information 

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Data format and file naming 

The data file is in "NetCDF-4" format and is CF-Convention v1.8 compliant. The data are delivered as a zip archive containing the NetCDF file.

File naming convention:

The data set file name for both CDRs and ICDRs follows the following naming convention, with the tokens of the filename provided in Table 2:

GGG_HHH_III_KKK_LLLMMM_NNNOOO_PPP.nc

Table 2: Tokens of the filename

Example:

C3S_GWSC_GLOBAL_MONTHLY_200204_202309_v1.0.nc

Contains the global grid of monthly GWSC data, version 1.0. The temporal coverage spans from April 2002 to September 2023.

Quality flags and data masks

The dataset does not come with quality flags. However, some of the input datastreams do provide such information. TWSA provides a flag for the filter used in individual months, described in section 1.4.2 of the TWSA PUGS. SWE provides a flag describing reasons for missing data, like over mountains or open water, described in section 1.4.2 of the SWE PUGS. RZSM comes with a variety of quality flags. See section 1.7 of the RZSM PUGS for a summary. GM and SWS do not provide such information.

For information on masking see section 1.1.1 of this document and sections 2.6.1 and 3. of the GWSC ATBD.

File contents

The data is provided as a single netCDF file of the size of 187.8 MB for the entire time series.

File dimensions

The file dimensions are detailed in Table 3 below.

Table 3: File dimensions

File variables

The variables in the netCDF file are summarised in Table 4, and more details are provided below.

Table 4: Variables in the GWSC product.

time

Data type: double

Dimensions: (time)

Description: The first day of the observed month

lon

Data type: float

Dimensions: (lon)

Description: Central longitude of each grid cell

lat

Data type: float

Dimensions: (lat)

Description: Central latitude of each grid cell

gwsc

Data type: double

Dimensions: (time, lat, lon)

Description: Gravity-based groundwater storage change given as equivalent water height

gwsc_uncertainty

Data type: double

Dimensions: (time, lat, lon)

Description: Uncertainty of the groundwater storage change propagated from uncertainties of the input datastreams

File metadata

The netCDF file contains descriptive metadata as global attributes (Table 5 for all attributes and their values). 

Table 5: Global attributes included in the product files: Values set in italic are valid for the CDR v1.0 data version but will change with future CDR and ICDR publications.

Examples of known climate applications and best practices

As a new C3S dataset, the C3S GWSC product has not yet been used in climate applications. However, the preceding dataset of the Global Gravity-based Groundwater Project (G3P) has been used in validation studies, such as Sayyadi et al. (2025) or Güntner et al. (2026), and in climate-related studies, such as Ongdas et al. (2025).

Additionally, the value of the G3P dataset has been demonstrated on  https://www.globalwaterstorage.info/en/ (last accessed April 21, 2026), an information portal dedicated to the GRACE and GRACE-FO satellite missions, their applications and derived products. Application examples are showcased through blog articles written by scientists from the community, as well as a regularly featured “picture of the month".

Known Issues and Limitations 

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Some principal limitations of GWSC stem from the input TWSA product and the nature of GRACE-based observations. Those are the limited spatial resolution of approximately 250–300 km, the coarse temporal resolution of one month, the missing months, and the phenomenon known as leakage. For more details on this please refer to section 1.4.5 of the TWSA PUGS.

As a consequence of the coarse spatial resolution it is advisable to assess groundwater storage variations by area averages of at least 100,000 km², e.g. over an aquifer.

A further set of limitations relates to the shallow integration depth of the soil moisture data used to separate unsaturated zone storage variations from the TWSA signal. With an integration depth of only 2 m, storage variations occurring in deeper unsaturated zones are incorrectly attributed to groundwater as a residual. The magnitude and frequency of this error varies regionally depending on climatic, soil physical, and hydrogeological conditions. Please see section 4 of Güntner et al. (2026) for further details on this.

Surface water storage, as used in the GWSC processing chain, is fully derived from hydrological model simulations rather than observations, with the exception of the Caspian Sea. Besides the fact itself, this means that it lacks the uncertainty characterisation that is propagated from instrument noise and processing uncertainties in the observation-based input datasets. The uncertainty value is derived from comparisons of the SWS product with a model ensemble. Future observation-based products hold potential to address this limitation, though integrating such sources will require careful data merging to preserve a closed mass balance.

Only water bodies that are considered oceans are masked out of the product (i.e., set to NaN). Naturally, this does not include the Caspian Sea, the Great Lakes or any other very large lake. However, the GWSC signals given at these locations are no reliable representation of the reality below such large water bodies. It is hence recommended to consider masking out these water bodies before further analyses.

Greenland and Antarctica are excluded from the GWSC product. In these regions, the input TWSA signal is dominated by changes in glacier and ice sheet mass, which are very large in magnitude and carry substantial uncertainties. As a result, reliably isolating the groundwater signal through the subtraction approach is currently not feasible for these regions.

Data access information 

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GWSC data

The GWSC data is available through the Copernicus Climate Data Store (CDS) web-based service (https://cds.climate.copernicus.eu/). To access the CDS and all its toolbox software, a free-of-charge registration is required. Data can be directly downloaded from the portal and used under the License to Use Copernicus Products (also included on the download page). All requests for user support shall be directed via the ECMWF Support Portal.

Input and auxiliary data

The TWSA input data is available from the TWSA CDS page (URL last accessed on 21.04.2026).

For all other input and auxiliary datasets please refer to the GWSC ATBD.

Data citation requirements

Same as landing page once this is agreed with ECMWF/CDS

User Support

A dedicated support portal (https://confluence.ecmwf.int/site/support) has been set up by the Copernicus User Support (CUS) team, which provides support to users of the Copernicus Atmosphere Monitoring Service (CAMS) and C3S services at ECMWF. All enquiries about the GWSC dataset can be submitted through the service desk where appropriate agents will deal with it. Once submitted, the user may add comments or further information to the issue, including responding to questions / requests for additional information from the support team.

References

• Güntner, A., Sharifi, E., Haas, J., Boergens, E., Cao, F., Dahle, C., Darbeheshti, N., Dobslaw, H., Dussaillant, I., Dorigo, W., Flechtner, F., Jäggi, A., Kosmale, M., Lasser, M., Luojus, K., Meyer, U., Pasik, A., Preimersberger, W., Ruz Vargas, C., and Zemp, M., 2026. The Global Gravity-based Groundwater Product (G3P), Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2025-797 (URL last accessed 29/04/2026), in review.
• Ongdas, N., Yapiyev, V., Catalin, S., Mehan, S., Muzdybaev, M., Hartmann, A., 2025. Lowland transboundary river in a cold, semi-arid steppe: review of the Yesil River basin. nviron Earth Sci 84, 496. https://doi.org/10.1007/s12665-025-12500-0 (URL last accessed 29/04/2026)
• Sayyadi, S., Nguyen, V., Apel, H., Haas, J., Dang, T. T., Than, V. D., Nguyen, N. H., Güntner, A., 2025. Observation-based analysis of groundwater storage in Vietnam’s Central Highlands: influence of hydro-climatic variability. Hydrological Sciences Journal, 70, 16, 2993-3012. https://doi.org/10.1080/02626667.2025.2568558 (URL last accessed 29/04/2026)
• Sharifi, E., Haas, J., Boergens, E., Dobslaw, H., and Güntner, A., 2025a. Technical note: GRACE-compatible filtering of water storage data sets via spatial autocorrelation analysis, Hydrol. Earth Syst. Sci., 29, 6985–6998, https://doi.org/10.5194/hess-29-6985-2025 (URL last accessed 29/04/2026)
• Sharifi, Ehsan; Haas, Julian; Boergens, Eva; Güntner, Andreas, 2025b. Global Multi-Resolution Land Fraction and Land–Ocean Masks Derived from ESA CCI Water Bodies v4.0 (Version 1.0). GFZ Data Services. https://doi.org/10.5880/G3P.2023.001 (URL last accessed 29/04/2026)
• WMO, 2025. The 2022 GCOS ECVs Requirements, 2022 edition - Updated in 2025, https://library.wmo.int/idurl/4/58111 (URL last accessed 29/04/2026)

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