Last modified on Apr 17, 2024 13:16

Contributors:  M. Zemp (University of Zurich), I. Dussaillant (University of Zurich), J. Bannwart (University of Zurich), F. Paul (University of Zurich)

Issued by: UZH / Michael Zemp, Inés Dussaillant

Date: 23/10/2023

Ref: C3S2_312a_Lot4.WP3-TRGAD-GL-v2_202304_MC_TR_GA_i1.1

Official reference number service contract: 2021/C3S2_312a_Lot4_EODC/SC1

History of modifications

Related documents 

Acronyms

General definitions

Glacier mass balance definitions and related terms as from the "Glossary of Mass Balance and Related Terms" (Cogley et al., 2011).
Altimetry
A remote-sensing technique in which surface altitudes (elevations) are estimated as a function of the travel time of a pulse

Digital elevation model (DEM)
An array of numbers representing the elevation of part or all of the Earth's surface as samples or averages at fixed spacing in two horizontal coordinate directions. Digital elevation models are now the preferred means of representing the elevation changes on which mass-balance measurements by geodetic methods are based. The elevation change is calculated by subtracting an earlier DEM from a later DEM.

Elevation change
Vertical change in glacier surface elevation (altitude), typically derived from two elevation measurements, adjusted if necessary for the difference of their respective datum surfaces, at the same (or nearly the same) horizontal coordinates.
Geodetic method
Any method for determining mass balance by repeated mapping of glacier surface elevations to estimate the volume balance; cartographic method and topographic method are synonyms. The conversion of elevation change to mass balance requires information on the density of the mass lost or gained, or an assumption about the time variations in density.

Glaciological method
A method of determining mass balance in-situ on the glacier surface by measurements of accumulation and ablation, generally including measurements at stakes and in snow pits; direct method has long been a synonym. The measurements may also rely on depth probing and density sampling of the snow and firn, and coring. They are made at single points, the results from a number of points being extrapolated and integrated to yield the surface mass balance over a larger area such as an elevation band or the entire glacier.

Gravimetric method
A technique in which glacier mass variations are calculated from direct measurements of Earth's gravity field. Satellite gravimetry is at present the most feasible method for determining glacier mass balance from changes in gravity. The Gravity Recovery and Climate Experiment (GRACE) consists of two polar-orbiting satellites separated by about 200 km along-track, and is the primary mission for this work to date.

Interferometry
Measurement of the interference of waves, particularly electromagnetic waves, from a common source such as a radar, with the aim of obtaining information about the topography, velocity field and other characteristics of the glacier surface.

Scope of the document

This report corresponds to the Target Requirements and Gap Analysis Document (TRGAD) for the glacier essential climate variable (ECV) within the Land Hydrology and Cryosphere (LHC) service. We here provide users with the relevant information on the C3S global gridded annual glacier mass change product requirements and existing gaps on the current product version. A related document for the glacier area product is also available (Target Requirements and Gap Analysis Document, RD3).

The scope of this document is threefold: First, it defines the evolving target requirements for the glacier change Climate Data Record (CDR) and the associated data products based on Global Climate Observing System (GCOS) requirements and Copernicus Climate Change Service (C3S) user needs. Secondly, it describes gaps and limitations to the data fitness-for-purpose according to the specific target requirements, identifying opportunities and needs to improve the glacier change dataset. Thirdly, it addresses limitations in the existing coverage, processing algorithms and methods for estimating uncertainties, identifying scientific research needs and opportunities for exploiting the new glacier change observations. 

This document refers to the current gridded glacier change product (version WGMS-FoG-2022-09) as provided in the Climate Data Store, which is based on the observations from the Fluctuations of Glaciers (FoG) database of the World Glacier Monitoring Service (WGMS, 2022).

Executive summary

This document provides an overview on the C3S global gridded annual glacier mass change product for the ECV Glacier, explains user requirements that force the evolution of the datasets and describes the gap analysis or existing limitations of the product and the opportunities for improvement.

The C3S glacier change service provides a global gridded product of annual glacier mass changes covering the hydrological years 1975/76 to 2020/21. The product is made available as annual NetCDF files with annual mass changes provided in the unit gigatonnes (Gt) at a spatial resolution of 0.5° × 0.5°. It was computed by combining the temporal variability from glaciological in-situ observations with long-term trends from spaceborne geodetic surveys, both available from the World Glacier Monitoring Service (WGMS). The production of this gridded product has become feasible thanks to geodetic glacier surveys recently reaching almost global coverage.

User requirements for observations of glacier mass changes and of glacier elevation changes are found in the Integrated Global Observing Strategy (IGOS) Cryosphere Theme Report 2007 (IGOS, 2007) as well as in the GCOS Implementation Plan (GCOS, 2022, and earlier issues).

The global gridded annual glacier mass change product integrates nicely into the family of the gridded ECV products provided by the C3S Climate Data Store. It provides new insights into regional to global glacier mass changes and, hence, has a great potential for contributing to the various statement of the climate report as well as to assessments of the global sea-level budget, the global energy cycle or the global water cycle.

Continuation and expansion of the glaciological in-situ observation network is essential for our understanding of the process and provides the temporal variability of the glacier mass change product. Ensuring the continuation of open source spaceborne datasets with extensive acquisitions tasking planned over glaciated regions is crucial for ensuring the good quality of future glacier products, and one of the greatest gaps in the quality and continuation of the glacier services delivered to C3S. 

Product description

This section aims at providing users with the relevant information about the C3S global gridded annual glacier mass change product as well as about related input data, retrieval algorithms, and related uncertainties. More details about the product are available in the Algorithm Theoretical Basis Document of the C3S glacier mass-change product (RD1).

1.1. Input and auxiliary data

The input data for C3S global gridded glacier mass change product are glacier mass changes from the glaciological method and glacier elevation changes from the geodetic method. Observational time series of annual glaciological mass changes and of multi-annual geodetic elevation changes are used from the Fluctuations of Glaciers database of the World Glacier Monitoring Service. Both time series are provided as glacier-wide observations. The glaciological data are in the unit meter water equivalent (m w.e.). The geodetic data come in the unit meter and, hence, require a conversion to m w.e. For more detail on these time series, we refer to previous versions of the C3S glacier product (RD2) as well as to WGMS (2021) and to Zemp et al. (2015).

For the computation of the distributed glacier mass change product, we used glacier outlines from the Randolph Glacier Inventory (RGI) version 6.0 (RGI Consortium, 2017) as available from the glacier distribution service (RD3) to spatially locate glaciers and measure their area, and glacier regions (GTN-G, 2017) to spatially constrain climatic regions as auxiliary data.

1.2. Retrieval Algorithms and uncertainty estimation of the Global gridded annual glacier mass change product

For C3S, we developed an algorithm following Zemp et al. (2019, 2020) to produce a global gridded product in four processing steps, summarized in Figure 1. First, we estimate, for each glacier of the RGI 6.0, its temporal mass-change variability, calculated as mean annual anomaly (with respect to a given reference period) from nearby glaciological time series. Second, we calibrate this time series with all geodetic observations (after density conversion) available for the given glacier. For each glacier, this results in multiple time series that all come with the temporal variability from the glaciological sample but are calibrated to the long-term trend from the different geodetic surveys. Third, we produce one time series for each glacier calculated as a weighted mean, considering the uncertainty as well as the temporal coverage of the geodetic surveys. Fourth, we aggregate the time series of all glaciers as area-weighted mean for each grid cell. Uncertainty estimations combine the reported observational uncertainties from both the glaciological and the geodetic input data with uncertainties from the product computation, including the variability between multiple time series, density conversion, and glacier areas.

Following these steps, the glacier change service provides an annual glacier mass change product (in Gigatonnes per year; 1 Gt = 10¹² kg) at global scale with a spatial resolution of 0.5° × 0.5° covering the hydrological years from 1975/76 to 2020/21. For more details in the algorithm and product description, we refer the reader to the related product documentation (RD1, RD2 and RD4).

Figure 1: Summary illustration of the four main processing steps to produce the C3S global gridded annual glacier mass changes since 1975/76.

2. User Requirements

Several requirements for glacier elevation and mass changes of the ECV Glaciers have already been listed and described in previous documents from international organizations, foremost in the Integrated Global Observing Strategy Cryosphere Theme Report (IGOS, 2007) and the Global Climate Observing System implementation plans (GCOS, 2011, 2016, 2022). These requirements represent international community needs for glacier products and usually refer to observation at glacier scale. We note that the C3S global gridded glacier mass change product combines glacier mass changes from in-situ observations with glacier elevation changes from airborne and spaceborne geodetic surveys, and provides the resulting glacier-wide mass changes at 0.5° × 0.5° spatial resolution. As such, the requirements from IGOS and GCOS reports mainly refer to the input data at local to glacier scale, while the spatially aggregated C3S product comes at lower spatial resolution.

2.1. Integrated Global Observing Strategy Cryosphere Theme Report 2007

A detailed overview of technical requirements for glacier observations is provided in the Appendix of the IGOS Cryosphere Report (IGOS, 2007). The relevant entries for the elevation (i.e. topography) and mass balance products are shown in Table 1.

Table 1: Target requirements for glaciers according to the IGOS Cryosphere Report 2007.



C: Current Capability, T: Threshold Requirement (Minimum necessary), O: Objective Requirement (Target), L: Low end of measurement range, U: Unit, H: High end of measurement range, V: Value, mo: month, yr: year.

The values listed for measurement range and accuracy still reflect the current target requirements. The topography parameter refers to the quality requirements of DEMs used to determine glacier volume and mass changes with the geodetic method (DEM differencing). Given the current vertical DEM accuracies ranging between 2 and 8 m, an accuracy of 0.1 m can only be achieved with DEMs acquired 20-80 years apart. This is still unrealistic for optical stereoscopic and interferometric radar sensors but will be possible soon. Altimetry sensors such as the one onboard Ice, Cloud and Elevation Satellite (ICESat), can reach accuracies of 0.2 m/year for cross-over points (Moholdt et al., 2010) but observations are spatially limited, as only points are measured and spatial extrapolation introduces other uncertainties. 
Glacier mass balance measurements require in situ measurements. Determining mass balance from space is not (yet) possible as the evolution of the density of the snowpack cannot be determined remotely. The combination of a process model with Synthetic Aperture Radar (SAR)-based measurements is a theoretical possibility to determine snow water equivalent but has so far not materialized as the required sensors have not been launched.
Hence, for the time being the strategy is to:

1. Ensure the continuity of annual/seasonal in-situ mass balance measurements on selected glaciers.
2. Ensure good representativity of mass balance measurements in all glaciated regions
3. Validate and calibrate these carefully with the geodetic methods on a decadal time scale.
4. Determine the representativeness of the measured glaciers for the entire mountain range from DEM differencing to improve spatial up-scaling.

The two parameters stated in IGOS (2007) refer to i) mass balance, representing annual and seasonal variability of glacier changes and (ii) topography, representing the quality of the DEMs that allow to calculate glacier elevation changes, and remain key in any glacier change related exercise and therefore still apply for the glaciers ECV within the Copernicus glacier service.

2.2. GCOS Implementation Plans

Similar to IGOS (2007), the GCOS Implementation Plans (GCOS, 2011, 2016, 2022) periodically provide an updated overview of the technical requirements that have been adopted for glacier change related products. In the latest GCOS Implementation Plan (GCOS, 2022), the requirements for the glacier mass and elevation changes have been updated to overcome the potential confusion of glacier elevation changes with glacier topography (Table 2). 

It is assumed here that measurement uncertainties for annual field observations of mass changes are two times better (10 cm/year) than for satellite derived elevation changes (20 cm/year).  

It is important to state that the user requirements listed in the IGOS and GCOS documents are critical in ensuring the evolution towards better quality glacier change related estimations, both at the spatial (better resolved and complete dataset and related products) and temporal resolution (annual and seasonal), allowing to produce final products in line with the evolving user needs. Some of the direct benefits are listed below. 

• Support for the instrumental data record of climate by providing climate-related information, further back in time, in remote areas and at higher altitude than meteorological stations.
• Input to regional climate models and the validation of impact assessment and climate scenarios on a regional scale.
• Computation of glacier melt contribution to regional hydrology and global sea-level rise; and
• Support for the in-situ mass-balance measurements to assess their representativeness for entire mountain ranges as well as to extend data coverage in space and time.

Table 2: Target requirements for glacier elevation changes from geodetic methods and for glacier mass changes from glaciological method, according to GCOS (2022). Values are defined at three levels: goal (G) – ideal requirement above which improvements are not necessary, breakthrough (B) – intermediate level at which specific uses within climate monitoring become possible, and threshold (T) – minimum requirement to be met to ensure that data are useful. For notes related to each value, please check original tables in GCOS (2022).

3. Gap Analysis

3.1. Description of past, current and future glacier change observations

3.1.1. Historic development of glacier change observations

For more than a century, the WGMS and its predecessor organizations have been compiling and disseminating standardized data on glacier fluctuations. The historical development of this service as well as of the related datasets and science are summarized in Haeberli (2008) and in Zemp et al. (2014). The main variables currently observed in standardized formats are changes in glacier mass, elevation and volume, area, and length (front variations). Glacier changes are observed using in-situ and remote sensing methods. The glaciological mass balance is obtained from ablation stake and snow pit measurements and provides seasonal to annual information on glacier contribution to runoff. Geodetic methods from in-situ, airborne and space borne platforms provide multi-annual to decadal information on glacier elevation changes. Based on the assumptions on the density of snow, ice and firn, the observed geodetic elevation changes can be converted to mass balance and runoff contribution (Huss, 2013). Glacier elevation change and mass balance are a relatively direct reaction to the atmospheric conditions. They are thus relatively easy to interpret but comparably difficult to measure. Glacier front variations on the other hand, are an indirect and delayed reaction to climate change that are thus more difficult to interpret but easy to measure (from both in-situ and remotely sensed observations). Their much longer time series allow the extension of the observational series back into the Little Ice Age period. Standardised observations of glacier changes are actively compiled by the WGMS in annual calls-for-data, are regularly published bi-annual reports (WGMS, 2021, and earlier issues), and are made available open access thought the Fluctuations of Glaciers database (WGMS, 2022).

3.1.2. Present coverage of glacier elevation and mass change observations

Zemp et al. (2015) provide a detailed overview of the available datasets and discuss their potential and shortcomings for scientific assessments. The Global Glacier Change Bulletin (WGMS, 2021¹) and WGMS Fluctuations of Glaciers browser² provide a periodically updated overview and access to all data products, respectively. Figure 2 provides a visual representation of the global distribution of glacier change observations from the glaciological and geodetic (elevation change) samples available from the WGMS.

Glaciological in-situ observations have a long tradition, with pioneer measurements reaching back into the 19^th century, but have only been carried out at a few hundred glaciers worldwide. Geodetic coverage of glaciers in past periods (i.e. before the boom of the satellite era in the 2000s) is generally to, partly because historical national elevation data (i.e. derived from airborne imagery) is only commercially distributed and its sharing is prohibited. Only in some exceptional cases national DEMs are freely available (e.g. DEMs from 1960s to 1980s for the United States and Canada) and have been used in related studies to derive elevation and mass changes (Berthier et al., 2010; Larsen et al., 2007). As the quality of the national DEMs differ (in general, the older ones have lower accuracy), also the quality of the derived elevation changes differs. The lower quality is, to some extend, compensated by the longer time period of observation, i.e. a DEM from 1960 with an elevation uncertainty of 8 m is as good as a DEM from 1990 with a 2 m uncertainty (0.2 m/yr) when both are subtracted from a year 2000 DEM (such as Shuttle Radar Topography Mission (SRTM)). Spy satellites (such as Corona and Hexagon) have only been declassified recently and efforts to use them to estimate past glacier changes are still ongoing (Belart et al., 2020; Dehecq et al., 2020).

Figure 2: Global distribution of glaciological mass change and geodetic elevation change observations as available from the WGMS Fluctuations of Glaciers database (version WGMS-FoG-2022-09). While the glaciological sample covers a few hundred glaciers only, the geodetic sample covers more than 200,000 glaciers and more than 96% of the glacier surface area mapped in RGI 6.0. Country boundaries are from Natural Earth.

It is only during the last decades that the increased efforts on the exploitation of remote sensing data have allowed us to picture the distribution of glacier changes over increasingly larger regions with improved precision and homogeneity of the estimates. Since the year 2000, DEMs from numerous satellite missions are being used increasingly (e.g., Satellites Pour l’Observation de la Terre (SPOT) Stereoscopic survey of Polar Ice: Reference Images & Topographies (SPIRIT), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), ArcticDEM, Reference Elevation Model of Antarctica (REMA), Advanced Land Observing Satellite (ALOS) World 3D-30m (AW3D30) or TanDEM-X) to determine elevation changes at the mountain range and continental scales (Braun et al., 2019; Brun et al., 2017; Dussaillant et al., 2019; Shean, 2017). The study by Hugonnet et al. (2021) was the first to provide glacier elevation changes at global scale, covering the time period from 2000 to 2020. The integration of these results allowed the WGMS to boost the geodetic sample to almost global coverage, i.e. >96% with respect to the glacier area as mapped around the year 2000 (RGI Consortium, 2017).

3.1.3. Overview of past, current, and future satellite missions

An overview of past and current satellite missions used in glacier mass balance studies is given in Figure 3. One decade ago, only a handful satellite missions were available that allowed for assessing local to regional glacier elevation and mass change assessments from space. We now have entered a new era where multiple regional, or even global, comprehensive estimates have become possible (Berthier et al., 2023). Space-borne sources can be categorized into laser (e.g. IceSat-2) and radar (e.g. Cryosat-2) altimetry, gravimetry (GRACE, GRACE-FO), and methods providing DEM differencing from optical (e.g., ASTER, Pléiades, Corona, Hexagon) and radar (e.g., SRTM, TanDEM-X) sensors. While all sources are used for regional mass change assessments, only DEM differencing and radar altimetry have the spatial resolution to provide results at local to glacier scale.

The future of satellite missions able to measure glacier elevation changes is uncertain. ASTER-Terra satellite, providing an extensive archive of stereoscopic images over glaciated regions with free availability - thanks to the efforts from the Global Land Ice Measurements from Space initiative (Raup et al., 2000) - has already exceeded its predicted lifespan and is expected to be decommissioned soon. Most of the alternative spaceborne datasets are commercially distributed and allow free exclusive use only to some national parties (e.g. Pleiades and SPOT by French National Centre for Space Studies and Airbus, TanDEM-X in German Aerospace Center). Future planned missions are scarce, with uncertain launching dates and most of them planned for commercial use. Ensuring the continuation of open source spaceborne datasets with extensive acquisitions tasking planned over glaciated regions is crucial for ensuring the good quality of future glacier product, and represents one of the greatest gaps in the quality and continuation of the glacier services delivered to C3S.
For further reading, we refer to the review on measuring glacier mass changes from space by Berthier et al. (2023).

Figure 3. Overview of the lifetime of the main satellite missions used in glacier mass balance studies (as of October 2022). The colours distinguish different types of satellite sensors. The '?' is used when the decommission date is not known and '∞' for long term (i.e. operational) monitoring without a specific end date. A distinction is also made between missions that provide systematic 'global' coverage and others that make 'local' acquisitions on demand. 'Open access' missions are those for which the data are fully open access to all users. Conversely, 'proprietary' is used for commercial missions or missions for which the access is limited to certain users, for example upon acceptance of a research proposal. The list of future missions is not exhaustive but aims at illustrating a potential gaps for certain categories of data (notably, laser altimetry and 'open access' stereo-images with global coverage). Source: Berthier et al. (2023).

3.2. Development of processing algorithms

The current version of the processing algorithm for the C3S global gridded glacier mass change product is summarized above (section 1.2) and full details are available in the Algorithm Theoretical Basis Document of the C3S glacier change service (RD1). The basic approach to combine the temporal variability from glaciological observations with the long-term trend from geodetic observations originates from Zemp et al. (2019, 2020). It was originally developed for glacier change assessments at regional scale. Within the EU-project Global Gravity-based Groundwater Products (G3P)³, the approach was refined and further developed for the application to all glaciers in the RGI 6.0 and for spatial aggregation to a global grids, as now implemented for C3S. A related publication by Dussaillant et al. is in work and a corresponding reference will be provided here after publication.

3.3. Methods for estimating uncertainties

3.3.1. Glaciological method uncertainty estimation

The uncertainties of the glaciological method lie mostly on the problems of sampling: i) the use of a limited number of point measurements, which are not necessarily able to capture the spatial variability of surface mass balances along the glacier. (ii) The difficulties in measuring certain zones of the glacier like highly steep slopes or strongly cracked zones. And (iii) the errors on every specific measure. Therefore, glacier-wide mass balance estimations by the glaciological method can be biased and need to be calibrated with other methodologies. Total uncertainties on the annual glaciological mass balance lie between 0.2 and 0.4 m w.e. per year (Sicart et al., 2007; Thibert et al., 2008; Zemp et al., 2013). Geodetic measurements are usually preferred for calibration (Huss et al., 2009; Thibert and Vincent, 2009; Zemp et al., 2013), but attention must be taken, as both methods measure different quantities: the geodetic method integrates the subaerial part of frontal ablation. In glaciers where frontal ablation is not a negligible part of the mass loss (Truffer and Motyka, 2016), large discrepancies can be observed between the surface mass balance measured by the glaciological method and the geodetic mass balance.

3.3.2. Geodetic method uncertainty estimation

DEMs from various sources can be used for glacier elevation changes assessment and their characteristics (e.g. time stamp, spatial sampling, optical/radar) have to be considered to obtain meaningful uncertainties. In some mountain regions, appropriate data might not be available and a more qualitative description of DEM uncertainties might have to be used.

Table 3 provides an overview on the measures for uncertainty assessment that can be applied to the elevation change product (DEM differencing). The table does not consider uncertainties introduced during post-processing, e.g. the method selected to fill data voids and reduce artefacts. The mandatory step to be performed in any case is the image co-registration (Nuth and Kääb, 2011), horizontally as well as vertically if this is sensible and both datasets have the same geodetic datum. As a further minimum requirement and first quantitative descriptor of product accuracy, the elevation differences over stable ground should be given. "Stable" means outside of glaciers, water bodies and forests.

Table 3: List of measures to determine uncertainty of glacier elevation changes from DEM differencing.

 At the next level, DEM elevations can be compared to ICESat (L1a) and ICESat data can be integrated in the co-registration process to determine the vector sum of the residuals (L1b). If a high-quality DEM or ground control points are available (L2), elevation differences over stable terrain for the DEMs used can be calculated. Finally (L3), it is also possible that change rates are directly compared to an independent dataset that, at best, should have been available for the same period. If not, differences due to timely variable change rates might occur. As a note of caution: it is required to adjust all datasets compared to the same geodetic datum before they are compared, as this is not always WGS84 (e.g. for ICESat and national DEMs, or different SRTM products).

3.3.3. Global gridded glacier mass change product uncertainty estimation

The uncertainty estimation for the C3S global gridded glacier mass change product is summarized above (section 1.2) and full details are available in the Algorithm Theoretical Basis Document of the C3S glacier change service (RD1). The error bars for the gridded product combine the observational uncertainties from both the glaciological and the geodetic surveys as reported by the principal investigators to the WGMS. These uncertainties are propagated to the aggregated grid values, taking into account other error sources, such as the variability between multiple time series, density conversion, and glacier areas. Uncertainties are provided at 95% confidence interval.
For the Product Quality Assessment Report (RD4), we used mass-change time series from WGMS reference glaciers, which were validated and (if needed) calibrated with air-borne geodetic surveys, for a leave-one-out cross validation. This validation experiment indicated that the error bars of our approach are rather too large. For a next product version, we aim to adjust our uncertainty estimation approach to produce less conservative error bars.

3.4. Opportunities to improve quality and fitness-for-purpose of the CDRs

The quality of the C3S global gridded glacier mass change product strongly depends on the input data. As such, the glacier in-situ network – providing the temporal variability and annual updates of glacier mass changes – needs to be maintained, extended into under-sampled regions, and the timeliness of data availability needs to be shortened. Long-term glaciological time series are recommended to be homogenized as well as validated and – if required – calibrated with airborne geodetic surveys (Zemp et al., 2013). The geodetic sample – providing the long-term trends of glacier mass changes, currently mainly from 2000 to 2020 – needs to be extended back in time (unlocking archival data) and continued into the future. Also in the auxiliary data, there is room for improvement. As such, a new improved version of the glacier inventory (i.e., RGI version 7) is pending release and will improve the quality of the glacier outlines for the reference year 2000. In parallel to the new inventory, updated glacier regions are expected to come out.

In order to profit from improvements in the input data, we provide an annually reprocessed CDRs (instead of annual updates through Interim CDRs (ICDRs)) to C3S. Both temporal coverage and temporal resolution of our product depend mainly on the glaciological sample. As such, the annual updates of our C3S product depends on the near-time reporting of the worldwide observation network to the WGMS. Extension of the annual time series into the past requires rescuing historical observation series from yet unknown literature and archives. Thanks to the integration of the geodetic sample from Hugonnet et al. (2021), our product profits from worldwide glacier-specific calibration to long-term geodetic change rates for the period from 2000 to 2020. Improving the long-term trends before the year 2000 requires unlocking archives and processing of stereo images from aerial surveys as well as from declassified spy satellites (e.g., Corona, Hexagon).

The fitness-for-purpose of the C3S global gridded glacier mass change product can be improved by providing glacier mass changes not only as total mass change (in the unit Gt) but also as specific mass change (in the unit m w.e.), and corresponding glacier areas. In addition, the spatial and temporal resolution of the glacier product can be optimized in view of cross-ECV consistency (e.g. Ice Sheet) and applications (e.g., sea-level budget).

3.5. Scientific research needs

The C3S global gridded glacier mass change product would benefit from scientific improvement in the following themes:

• Development and implementation of real-time measurements of ablation and accumulation processes for improving the temporal resolution (from annual or seasonal to monthly or daily observations) and reducing the periodicity of ingestion of the glaciological observations from the monitoring network to the FoG database (currently once a year). We note that only with monthly resolution, mass balances from different hydrological regimes (northern vs southern hemispheres; maritime vs continental regimes) can be correctly compared combined.
• Development of common good practices in the processing of DEMs (e.g., co-registration, void filling, filtering), bias corrections (e.g., radar penetration), as well as in the assessment and reporting of uncertainties within and across geodetic methods.
• Development of improved methods for density conversion (Huss, 2013).
• Improved estimates for regional area change rates over time.

In addition, we see a great opportunity to compare the results from the C3S glacier mass-change product – combining glaciological and geodetic (DEM differencing) methods – with estimates from other sources (i.e., altimetry, gravimetry) in internationally coordinated intercomparison exercises (ESA GlaMBIE⁴). Results from peripheral glaciers in Greenland and Antarctica may contribute to Ice Sheet intercomparison exercises (ESA/NASA IMBIE⁵). Furthermore, the new gridded product can provide improved insights into the current state of the climate (e.g., C3S, 2022) as well as into regional to global assessments of the energy cycle (von Schuckmann et al., 2020), the water cycle (Dorigo et al., 2021), and the sea-level budget (Slater et al., 2021). Last but not least, the C3S glacier mass change product can contribute to multi-ECV products, such as demonstrated for the Global Gravity-based Ground Water product (G3P⁶).

3.6. Opportunities from exploiting the Sentinels and any other relevant satellite

The current Sentinels provide excellent input for the mapping of global glacier distribution using optical images (cf., RD3) and allow for the assessment of glacier velocities from both optical and synthetic aperture radar data (e.g., Paul et al., 2022). However, there are currently no Sentinels available with high-resolution stereo images required for DEM production (cf., Figure 3).

Repeat DEMs from the same sensor and with global coverage as already implemented for ASTER (Hugonnet et al., 2021) and currently planned for the extended TerraSAR-X / TanDEM-X mission will substantially increase the possibility to determine glacier elevation and mass changes regularly. In combination with sensors such as ICESat-2 to determine residual effects of radar penetration, uncertainties of the related products can be calculated. With the now available automated processing lines for optical stereo images, future high-resolution sensors (along-track or across-track) will allow the calculation of elevation changes more frequently and robustly (e.g. elevation trends derived from many rather than only two DEMs).

In regions with large glacier covers, the present estimates can be complemented with estimates from spaceborne gravimetry and altimetry observations. Spaceborne altimetry determines the surface elevation by measuring the two-way travel time of pulses between glacier and sensor using radar (Jakob et al., 2021) or laser (Treichler et al., 2019) technology. Spaceborne gravimetry is used to detect changes in the Earth’s gravimetric force by measuring the distance between two satellites on the same orbit (e.g., Gravity Recovery and Climate Experiment (GRACE)). From the observed variations in the gravity fields, numerical modelling is used to estimate related changes in the terrestrial water storage and related components, such as glacier mass changes (Ciracì et al., 2020; Wouters et al., 2019).

The variety of methods now available opens up new opportunities for regional evaluation of results from different methods as well as for reconciled global assessments of glacier mass changes and related contributions to sea-level rise. The strong community determination to reconcile the measurements from all methods is clear given the recently started ESA GlaMBIE project. At the same time, the glacier research and monitoring community is facing new challenges related to data size, formats, and availability as well as new questions with regard to best practises for data processing chains and for related uncertainty assessments. These questions are currently addressed by the working group on Regional Assessments of Glacier Mass Change (RAGMAC) of the International Association of Cryospheric Sciences (IACS)⁷.

References

Belart, J. M. C., Magnússon, E., Berthier, E., Gunnlaugsson, Á. Þ., Pálsson, F., Aðalgeirsdóttir, G., Jóhannesson, T., Thorsteinsson, T. and Björnsson, H.: Mass Balance of 14 Icelandic Glaciers, 1945–2017: Spatial Variations and Links With Climate, Front. Earth Sci., 8, doi:10.3389/feart.2020.00163, 2020.

Berthier, E., Schiefer, E., Clarke, G. K. C., Menounos, B. and Rémy, F.: Contribution of Alaskan glaciers to sea-level rise derived from satellite imagery, Nat. Geosci., 3(2), 92–95, doi:10.1038/ngeo737, 2010.

Berthier, E., Floriciou, D., Gardner, A. S., Gourmelen, N., Jakob, L., Paul, F., Treichler, D., Wouters, B., Belart, J. M. C., Dehecq, A., Dussaillant, I., Hugonnet, R., Kääb, A., Krieger, L., Pálsson, F. and Zemp, M.: Measuring glacier mass changes from space—a review, Reports Prog. Phys., 86(3), 036801, doi:10.1088/1361-6633/acaf8e, 2023.

Braun, M. H., Malz, P., Sommer, C., Farías-Barahona, D., Sauter, T., Casassa, G., Soruco, A., Skvarca, P. and Seehaus, T. C.: Constraining glacier elevation and mass changes in South America, Nat. Clim. Chang., 9(2), 130–136, doi:10.1038/s41558-018-0375-7, 2019.

Brun, F., Berthier, E., Wagnon, P., Kääb, A. and Treichler, D.: A spatially resolved estimate of High Mountain Asia glacier mass balances from 2000 to 2016, Nat. Geosci., 10(9), 668–673, doi:10.1038/ngeo2999, 2017.

C3S: European State of the Climate 2021, Reading, UK. [online] Available from: https://climate.copernicus.eu/esotc/2021, 2022.

Ciracì, E., Velicogna, I. and Swenson, S.: Continuity of the Mass Loss of the World’s Glaciers and Ice Caps From the GRACE and GRACE Follow‐On Missions, Geophys. Res. Lett., 47(9), doi:10.1029/2019GL086926, 2020.

Cogley, J. G., Hock, R., Rasmussen, L. A., Arendt, A. A., Bauder, A., Braithwaite, R. J., Jansson, P., Kaser, G., Möller, M., Nicholson, L. and Zemp, M.: Glossary of glacier mass balance and related terms. IHP-VII Technical Documents in Hydrology No. 86, IACS Contribution No. 2, UNESCO-IHP, Paris, France. [online] Available from: unesdoc.unesco.org/images/0019/001925/192525e.pdf, 2011.

Dehecq, A., Gardner, A. S., Alexandrov, O., McMichael, S., Hugonnet, R., Shean, D. and Marty, M.: Automated Processing of Declassified KH-9 Hexagon Satellite Images for Global Elevation Change Analysis Since the 1970s, Front. Earth Sci., 8, doi:10.3389/feart.2020.566802, 2020.

Dorigo, W., Dietrich, S., Aires, F., Brocca, L., Carter, S., Cretaux, J.-F., Dunkerley, D., Enomoto, H., Forsberg, R., Güntner, A., Hegglin, M. I., Hollmann, R., Hurst, D. F., Johannessen, J. A., Kummerow, C., Lee, T., Luojus, K., Looser, U., Miralles, D. G., Pellet, V., Recknagel, T., Ruz Vargas, C., Schneider, U., Schoeneich, P., Schröder, M., Tapper, N., Vuglinsky, V., Wagner, W., Yu, L., Zappa, L., Zemp, M. and Aich, V.: Closing the water cycle from observations across scales: Where do we stand?, Bull. Am. Meteorol. Soc., 1–95, doi:10.1175/BAMS-D-19-0316.1, 2021.

Dussaillant, I., Berthier, E., Brun, F., Masiokas, M., Hugonnet, R., Favier, V., Rabatel, A., Pitte, P. and Ruiz, L.: Two decades of glacier mass loss along the Andes, Nat. Geosci., 12(10), 802–808, doi:10.1038/s41561-019-0432-5, 2019.

GCOS: Systematic observation requirements for satellite-based data products for climate. Supplement details to the satellite-based component of the “Implementation Plan for the Global Observing System for Climate in Support of the UNFCCC (2010 Update)”. GCOS Re., 2011.

GCOS: The Global Observing System for Climate: Implementation Needs., 2016.

GCOS: GCOS 2022 Implementation Plan. [online] Available from: https://library.wmo.int/index.php?lvl=notice_display&id=22134, 2022.

GTN-G: GTN-G Glacier Regions, , doi:10.5904/gtng-glacreg-2017-07, 2017.

Haeberli, W.: Changing views of changing glaciers, in The darkening peaks: Glacial retreat in scientific and social context, edited by B. Orlove, E. Wiegandt, and B. H. Luckman, pp. 23–32, University of California Press., 2008.

Hugonnet, R., McNabb, R., Berthier, E., Menounos, B., Nuth, C., Girod, L., Farinotti, D., Huss, M., Dussaillant, I., Brun, F. and Kääb, A.: Accelerated global glacier mass loss in the early twenty-first century, Nature, 592(7856), 726–731, doi:10.1038/s41586-021-03436-z, 2021.

Huss, M.: Density assumptions for converting geodetic glacier volume change to mass change, Cryosph., 7(3), 877–887, doi:10.5194/tc-7-877-2013, 2013.

Huss, M., Bauder, A. and Funk, M.: Homogenization of long-term mass-balance time series, Ann. Glaciol., 50(50), 198–206, 2009.

IGOS: Integrated Global Observing Strategy Cryosphere Theme Report - For the monitoring of our environment from space and from Earth, Geneva, Switzerland., 2007.

Jakob, L., Gourmelen, N., Ewart, M. and Plummer, S.: Spatially and temporally resolved ice loss in High Mountain Asia and the Gulf of Alaska observed by CryoSat-2 swath altimetry between 2010 and 2019, Cryosph., 15(4), 1845–1862, doi:10.5194/tc-15-1845-2021, 2021.

Joerg, P. C. and Zemp, M.: Evaluating Volumetric Glacier Change Methods Using Airborne Laser Scanning Data, Geogr. Ann. Ser. A, Phys. Geogr., 96(2), 135–145, doi:10.1111/geoa.12036, 2014.

Larsen, C. F., Motyka, R. J., Arendt, A. A., Echelmeyer, K. A. and Geissler, P. E.: Glacier changes in southeast Alaska and northwest British Columbia and contribution to sea level rise, J. Geophys. Res. Earth Surf., 112(1), 1–11, doi:10.1029/2006JF000586, 2007.

Moholdt, G., Nuth, C., Hagen, J. O. and Kohler, J.: Recent elevation changes of Svalbard glaciers derived from ICESat laser altimetry, Remote Sens. Environ., 114(11), 2756–2767, doi:10.1016/j.rse.2010.06.008, 2010.

Nuth, C. and Kääb, A.: Co-registration and bias corrections of satellite elevation data sets for quantifying glacier thickness change, Cryosphere, 5(1), 271–290, doi:10.5194/tc-5-271-2011, 2011.

Paul, F., Piermattei, L., Treichler, D., Gilbert, L., Girod, L., Kääb, A., Libert, L., Nagler, T., Strozzi, T. and Wuite, J.: Three different glacier surges at a spot: what satellites observe and what not, Cryosph., 16(6), 2505–2526, doi:10.5194/tc-16-2505-2022, 2022.

Raup, B. H., Kieffer, H. H., Hare, T. M. and Kargel, J. S.: Generation of data acquisition requests for the ASTER satellite instrument for monitoring a globally distributed target: glaciers, IEEE Trans. Geosci. Remote Sens., 38(2), 1–10, 2000.

RGI Consortium: Randolph Glacier Inventory - a dataset of global glacier outlines: version 6.0, technical report., 2017.

von Schuckmann, K., Cheng, L., Palmer, M. D., Hansen, J., Tassone, C., Aich, V., Adusumilli, S., Beltrami, H., Boyer, T., Cuesta-Valero, F. J., Desbruyères, D., Domingues, C., García-García, A., Gentine, P., Gilson, J., Gorfer, M., Haimberger, L., Ishii, M., Johnson, G. C., Killick, R., King, B. A., Kirchengast, G., Kolodziejczyk, N., Lyman, J., Marzeion, B., Mayer, M., Monier, M., Monselesan, D. P., Purkey, S., Roemmich, D., Schweiger, A., Seneviratne, S. I., Shepherd, A., Slater, D. A., Steiner, A. K., Straneo, F., Timmermans, M.-L. and Wijffels, S. E.: Heat stored in the Earth system: where does the energy go?, Earth Syst. Sci. Data, 12(3), 2013–2041, doi:10.5194/essd-12-2013-2020, 2020.

Shean, D.: High Mountain Asia 8-meter DEMs Derived from Along-track Optical Imagery, Version 1, , doi:http://dx.doi.org/10.5067/GSACB044M4PK, 2017.

Sicart, J. E., Ribstein, P., Francou, B., Pouyaud, B. and Condom, T.: Glacier mass balance of tropical Zongo glacier, Bolivia, comparing hydrological and glaciological methods, Glob. Planet. Change, 59(1–4), 27–36, doi:10.1016/j.gloplacha.2006.11.024, 2007.

Slater, T., Lawrence, I. R., Otosaka, I. N., Shepherd, A., Gourmelen, N., Jakob, L., Tepes, P., Gilbert, L. and Nienow, P.: Review article: Earth’s ice imbalance, Cryosph., 15(1), 233–246, doi:10.5194/tc-15-233-2021, 2021.

Thibert, E. and Vincent, C.: Best possible estimation of mass balance combining glaciological and geodetic methods, Ann. Glaciol., 50(50), 112–118, 2009.

Thibert, E., Blanc, R., Vincent, C. and Eckert, N.: Glaciological and Volumetric Mass Balance Measurements: Error Analysis over 51 years for the Sarennes glacier, French Alps, J. Glaciol., 54(54186), 522–532, doi:10.3189/002214308785837093, 2008.

Treichler, D., Kääb, A., Salzmann, N. and Xu, C.-Y.: Recent glacier and lake changes in High Mountain Asia and their relation to precipitation changes, Cryosph., 13(11), 2977–3005, doi:10.5194/tc-13-2977-2019, 2019.

Truffer, M. and Motyka, R. J.: Where glaciers meet water: Subaqueous melt and its relevance to glaciers in various settings, Rev. Geophys., 54(1), 220–239, doi:10.1002/2015RG000494, 2016.

WGMS: Global Glacier Change Bulletin No. 4 (2018-2019), edited by M. Zemp, S. U. Nussbaumer, I. Gärtner-Roer, J. Bannwart, F. Paul, and M. Hoelzle, ISC(WDS)/IUGG(IACS)/UNEP/UNESCO/WMO, World Glacier Monitoring Service, Zurich, Switzerland., 2021.

WGMS: Fluctuations of Glaciers Database, , doi:10.5804/wgms-fog-2022-09, 2022.

Wouters, B., Gardner, A. S. and Moholdt, G.: Global Glacier Mass Loss During the GRACE Satellite Mission (2002-2016), Front. Earth Sci., 7, doi:10.3389/feart.2019.00096, 2019.

Xu, C., Li, Z., Li, H., Wang, F. and Zhou, P.: Long-range terrestrial laser scanning measurements of annual and intra-annual mass balances for Urumqi Glacier No. 1, eastern Tien Shan, China, Cryosph., 13(9), 2361–2383, doi:10.5194/tc-13-2361-2019, 2019.

Zemp, M., Thibert, E., Huss, M., Stumm, D., Rolstad Denby, C., Nuth, C., Nussbaumer, S. U., Moholdt, G., Mercer, A., Mayer, C., Joerg, P. C., Jansson, P., Hynek, B., Fischer, A., Escher-Vetter, H., Elvehøy, H. and Andreassen, L. M.: Reanalysing glacier mass balance measurement series, Cryosph., 7(4), 1227–1245, doi:10.5194/tc-7-1227-2013, 2013.

Zemp, M., Armstrong, R., Gärtner-Roer, I., Haeberli, W., Hoelzle, M., Kääb, A., Kargel, J. S., Khalsa, S. J. S., Leonard, G. J., Paul, F. and Raup, B. H.: Global glacier monitoring - a long-term task integrating in situ observations and remote sensing, in Global Land Ice Measurements from Space, edited by J. S. Kargel, G. J. Leonard, M. P. Bishop, A. Kääb, and B. H. Raup, pp. 1–21, Springer Berlin Heidelberg, Berlin, Heidelberg., 2014.

Zemp, M., Frey, H., Gärtner-Roer, I., Nussbaumer, S. U., Hoelzle, M., Paul, F., Haeberli, W., Denzinger, F., Ahlstrøm, A. P., Anderson, B., Bajracharya, S. R., Baroni, C., Braun, L. N., Cáceres, B. E., Casassa, G., Cobos, G., Dávila, L. R., Delgado Granados, H., Demuth, M. N., Espizua, L., Fischer, A., Fujita, K., Gadek, B., Ghazanfar, A., Hagen, J.-O., Holmlund, P., Karimi, N., Li, Z., Pelto, M. S., Pitte, P., Popovnin, V. V., Portocarrero, C., Prinz, R., Sangewar, C. V., Severskiy, I., Sigurðsson, O., Soruco, A., Usubaliev, R. and Vincent, C.: Historically unprecedented global glacier decline in the early 21st century, J. Glaciol., 61(228), 745–762, doi:10.3189/2015JoG15J017, 2015.

Zemp, M., Huss, M., Thibert, E., Eckert, N., McNabb, R., Huber, J., Barandun, M., Machguth, H., Nussbaumer, S. U., Gärtner-Roer, I., Thomson, L., Paul, F., Maussion, F., Kutuzov, S. and Cogley, J. G.: Global and regional glacier mass changes from 1961 to 2016. (Version 1.1.0), , doi:10.5281/zenodo.3557199, 2019.

Zemp, M., Huss, M., Eckert, N., Thibert, E., Paul, F., Nussbaumer, S. U. and Gärtner-Roer, I.: Brief communication: Ad hoc estimation of glacier contributions to sea-level rise from the latest glaciological observations, Cryosph., 14(3), 1043–1050, doi:10.5194/tc-14-1043-2020, 2020.

Related articles

• Page:
  Glacier Area document version 2024: Product Quality Assessment Report (PQAR)
• Page:
  Glacier Area document version 2023: Target Requirements and Gap Analysis Document (TRGAD)
• Page:
  Glacier Area data version 7.0: System Quality Assurance Document (SQAD)
• Page:
  Glacier Area data version 7.0: Product Quality Assurance Document (PQAD)
• Page:
  Glacier Area data version 7.0: Algorithm Theoretical Basis Document (ATBD)