Photo caption (above): Antarctica - abandoned Wilkes Base and Observing Station (Photo: Sue Barrell)
WMO has adopted a unified Earth system approach to ensure weather, water and climate decisions are better informed by an integrated monitoring and prediction of all relevant Earth system components. This includes extending its reach to the furthest and most frigid parts of the globe, the Arctic, Antarctica (Figure 1) and the high-mountain regions, where the cryosphere is a prominent feature (IPCC, 2019).
CryosphereThe word "cryosphere" comes from the Greek word for cold, "kryos." The cryosphere is the part of the Earth's climate system that includes solid precipitation, snow, sea ice, lake and river ice, icebergs, glaciers and ice caps, ice sheets and ice shelves, and permafrost and seasonally frozen ground. The cryosphere extends globally. It exists seasonally or perennially at most latitudes, not just in the Arctic, Antarctic and mountain regions, and in nearly 100 countries. It influences the climate of the entire planet. Approximately 70% of the Earth’s freshwater exists as snow or ice. The Second International Meteorological Congress, held in 1879, drew the attention of meteorologists to the importance of measuring the variations Pin length and thickness of the glaciers. It recommended to institute continued glacier observations and to publish the results. |
An integrated Earth system approach allows for a better representation of the complex interactions between different components of the system– atmosphere, oceans, hydrosphere and cryosphere. It strongly relies on coupled assimilation to ensure consistency and to enhance the exploitation of interface observations that depend on more than one component, for the benefit of numerical Earth system prediction models.
Data assimilation is a critical component of both uncoupled and coupled Earth system prediction models. As the spatial and temporal resolution of these models steadily increase, improved in situ and remote-sensing observations are required to provide the most consistent representation of the Earth system components. Improvements in the spatial and temporal resolution of observations, as well as extending the number of variables that are observed, are necessary to further improve the performance of numerical prediction systems.
In cryosphere regions – whether polar or mountainous – producing accurate and reliable predictions is more difficult at all timescales than it is for other regions. Our understanding of and ability to model some of the processes unique to these regions is limited, for example, for small-scale processes occurring during sea-ice formation, snowfall, solid precipitation and within mixed-phase clouds and stable boundary layers. The limiting factors currently include (i) the limited availability of in situ observations, in particular those on snow and ice, (ii) the sub-optimal assimilation over snow and ice-covered surfaces of satellite observations in polar regions, (iii) the limited availability of adequate remote-sensing and satellite observations over polar and mountain regions (snow cover, glaciers, etc.), and (iv) the limited reliable data exchanges and near-real-time access to the available data.
Cryosphere data for hydrometeorological and climatological information and services
Many applications and services within the mandate of WMO Members, as well as those across the wider scientific community, increasingly require sustained access to cryosphere data. Such data complements meteorological, hydrological and ocean data as well as data used in the modelling and reanalysis fields. Climate-related changes in regions with snow, sea ice, glaciers and permafrost could trigger feedback processes and changes in precipitation and freshwater regulation regimes over large regions – up to the continental and hemispheric scale.
Cryosphere data for data assimilation into Earth system models
Snow and ice observations are increasingly used for data assimilation in Numerical Weather Prediction (NWP) models and have substantial impact on the performance of these models. Data on snow, glaciers, sea ice and permafrost are also increasingly used for numerical climate prediction, seasonal forecasting, operational analyses, climate reanalyses and for model verification.
In the context of large-scale coupled models, and in particular for cryosphere data, the exchange of snow and ice data across institutional, sectoral and political boundaries is essential to advancing the development of hydro-meteorological and climate services (Helmert et al., 2018). Insufficient prediction capacity in remote mountain regions may seem irrelevant, but the impacts travel downstream via rivers and the socioeconomic consequences are felt by communities living downstream and in lowlands.
Cryosphere data for hydrology
As all major rivers originate in mountains, these are often referred to as the “water towers of the world” (Immerzeel et al., 2020). The mountain cryosphere – glaciers, snow, permafrost and seasonally frozen ground – plays a fundamental role in providing and regulating freshwater resources for around half of the world’s population (Egan and Price, 2017). This notably includes those living in densely populated lowland areas, such as the Ganges–Brahmaputra Delta.
Snow, glaciers, permafrost and seasonably frozen ground act as reservoirs of freshwater. Data on melting snow and ice are essential for understanding the variability of water resources. The short-term cryosphere monitoring is critical for spring melt and flash flood forecasting, for hydropower production planning, for water availability in arid regions (e.g. Andes – Schoolmeester et al., 2018), and for irrigation, while the glacier melt is a key predictor for long-term water scarcity.
Figure 2 - Contribution of the cryosphere to the water availability in the basins of major rivers in Asia, as estimated based on data from 1998 to 2012 as published by Huss et al., 2017 (Illustration by Nora Krebs, WMO) |
Many countries rely on snowmelt forecasts (one to several months in advance) to predict river run-off, flood potential and to provide flood alerts (Figure 2) . A rise in the frequency of rain on snow events increases the exposure to avalanche and flood risks. Whereas augmented river discharge into the Arctic brings huge quantities of freshwater to the Arctic Ocean and surrounding seas, thereby influencing the oceanic circulation.
Further improvements to understanding and modelling the hydrological cycle for cold regions, are necessary. Access to observations is critical, for instance to better model the relationship between precipitation and run-off, including the contributions from permafrost and seasonally frozen ground.
Cryosphere data for ice forecasting and services
Reliable estimates of sea-ice extent and volume in the Arctic Ocean and in the Southern Ocean around Antarctica are needed for understanding climate change, for initializing numerical weather forecasts, for sea-ice prediction and in operational ocean–sea-ice reanalyses (Zuo et al., 2019).
Monthly and seasonal outlooks of sea-ice presence and dynamics are in great demand by the maritime industry for safe navigation and operation in polar waters (Figures 3 and 4).
|
|
|
Figure 3 - 30-day Ice Extent Change in the Arctic, produced by the 
Figure 4 - 30-day Ice Extent Change Antarctica - produced by Persistent reductions in Arctic sea-ice thickness and in multi-year sea-ice area lead to greater mobility of sea-ice cover and increased variability of sea-ice conditions. These changes necessitate a different approach to timeliness and horizontal resolution of ice charting and weather forecasting for marine transportation in high-latitude areas.
Figure 5 - Fig: September Arctic sea ice area in 106 km2 based on satellite-based observations and CMIP6 model simulations. Very likely ranges are shown for SSP1-2.6 and SSP3-7.0. The Arctic is projected to be practically ice-free near mid-century under mid and high GHG emission scenarios. The figure is adapted from Figure SMP.8 in IPCC (2021). (Observations added by Prf Ed Hawkins (http://www.climate-lab-book.ac.uk/2021/adding-observations/) – Courtesy Thomas Lavergne) |
Improvements in sea-ice (and coupled ocean–sea-ice) modelling, both for the Arctic and the Southern Ocean, are needed to overcome current limitations (Figure 5). These limitations are due partly to a general under-sampling of the polar oceans, especially for a wide swath of the Antarctic sea-ice zone, and partly to difficulties in deriving accurate sea-ice products from currently available remotely-sensed data. As younger first-year ice is becoming more dominant – resulting in a seasonal ice regime in the Polar regions – it is critical that operational ice services incorporate more timely and accurate ice data in their monitoring activities.
Cryosphere and the changing climate
Data on the changing ice sheets of Antarctica and Greenland (Figure 6) and on mountain glaciers are essential to understanding and modelling sea-level rise. More than a billion people – as well ecosystems – whether on small-island communities in the Atlantic, Indian and Pacific Oceans or in the large coastal cities of the world, are concerned. Systematic climate datasets on snow and ice also are necessary for reliable engineering design of infrastructure in cold climates, for example, for transportation, buildings, water supply, etc. They are also essential for addressing the effects of coastal erosion and subsequent changes in coastlines. Data on ground-ice conditions are emerging as critical for land-use planning and for assessing the potential release of greenhouse gases.
Figure 6 - Climate change significantly changes the infrastructure design conditions in the regions where snow and ice are present, and adaptive strategies are needed (Ittoqqortoormiit Village - Eastern Greenland), (Photo: Sue Barrell) |
Cryosphere changes and natural hazards
 Figure 7 - The Palcacocha Glacier lake (Peru) is drained using siphons to avoid Glacier Lake Outburst Floods (GLOF) (Photo: Christian Huggel) |
Integrated approaches to monitoring hydrometeorological changes that include cryosphere information are essential for developing early warning systems to warn of impending related risks and extreme events. These range from avalanches, catastrophic snowmelt floods (Rössler et al., 2014), glacial lake outburst floods (GLOFs or jökulhlaups), ice jams on rivers and lakes, river damming from surging glaciers, coastal decay, landslides and slope failure to the increased presence of icebergs on navigation routes, and other cryosphere related hazards. Glacial lakes have caused some of the world’s most devastating floods, for example, in the Andes (Huggel et al., 2020) and the Hindu Kush Himalayas. In a rapidly changing climate, access to accurate inventories and descriptions of past events and to robust climate datasets are critical to underpin hazard assessments (GAPHAZ, 2017) and prepare adaptation strategies (Figure 7).
Extending data exchange into polar and mountain regions
With its development of the Unified Data Policy, WMO is recognizing and responding to the need to broaden access to cryosphere data at a global level to further improve and sustain critical hydrometeorological and climate services provided by its Members. The Policy will help realize the WMO vision and strategy for an integrated Earth system approach to monitoring, modelling and prediction. The end goal is to further inform and enable WMO Members to provide services critical to protecting the safety and well-being of their citizens.
The new Policy recognizes that, unlike long-standing weather, climate, and hydrological monitoring infrastructure and systems, the systematic monitoring of cryosphere has emerged only in recent decades, driven by climate system research, and mostly through a bottom-up approach.
However, despite the increased interest, many mountain and polar regions remain insufficiently monitored due to high costs, difficult access (Figure 8), extreme operating conditions, insufficient local capacity, multi-state jurisdictions, and weak or absent institutional mandates. Even meteorological stations are sparse in these regions. This shortfall negatively impacts model performance, leading, for example, to an altitudinal bias in precipitation forecasting in high mountains.
Figure 8 - High Mountain Observations - Station Mueller Hut, 1818 m elevation, New Zealand - accessible only by helicopter and experiencing annual snow accumulations of over 4 metres. Image courtesy of Christian Zammit; contribution to the WMO Solid Precipitation Intercomparison Experiment (SPICE), WMO Report No. 131 (Nitu et al., 2018) |
Progress has been made on addressing the cryosphere observing needs with space-based systems, mostly for polar regions, less so for mountain regions. Many gaps remain in what is observed as well as in the access to and the assimilation of cryosphere space observations.
In many countries, cryosphere observing systems continue to be operated by multiple institutions with diverse mandates – from research, academia, hydropower production agencies, naval and ice services to space agencies, National Meteorological and Hydrological Services (NMHSs) and others – with research entities continuing to play a key role. In many developing countries, cryosphere observations and research continue to be part of internationally funded projects with limited or no links to national institutions, including the NMHS.
Cryosphere data in the WMO Unified Data Policy
Data sharing is important for research organizations (Pan et al., 2021) in their quest to increase our understanding of the interactions among the atmosphere, cryosphere, hydrosphere and biosphere. This is especially so as they seek to provide answers to increasingly complex questions on the socioeconomic and environmental impacts of unprecedented changes in the climate.
The international scientific community is actively taking steps to facilitate broader access to research data. The FAIR (Wilkinson et al., 2016) data principles, with four pillars – Findable, Accessible, Interoperable, and Reusable – provide a set of high-level guidelines for research data holders. FAIR places emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting reuse by individuals, while attributing ownership and protecting intellectual property, for example, through licenses.
Through its Unified Data Policy, WMO recognizes the wealth of cryosphere data that exist across this broader scientific community and the contribution that these can make to the WMO Earth system strategic focus. The policy therefore emphasizes the need for strengthened two-way engagements and data exchange between operational and research agencies, and it seeks to articulate clearly its principles and the benefits it confers to all stakeholders. In particular, the unified data policy calls for priority Earth system data (i.e. both ‘core’ and ‘recommended’ data) to be freely exchanged by WMO Members, including for the purposes of public research, without conditions. This reflects the importance of research outcomes and insights on driving ongoing advances in capability across all aspects of WMO’s mandate.
The policy also calls on Members to honor requests for attribution of data ownership whenever possible, as a means to provide recognition and protect the intellectual property rights of the owner of the data as feasible. Where appropriate, Digital Object Identifiers (DOI) may be used for scientific data access, tracking, and citation. Recognition of ownership is mutually beneficial for owners and users of data, and citation allows the scientific community to show to document to their funding agencies how their data are used.
WMO Global Cryosphere Watch (GCW) - facilitating access to cryosphere observations and data
The WMO Global Cryosphere Watch (GCW) acts as a convener for developing coordinated approaches across operational and research communities in support of key cryospheric in situ and remote-sensing observations as well as the access to data and information on the state of the cryosphere. The observing component of GCW is an integral part of the WMO Integrated Global Observing System (WIGOS). The GCW Data Portal is hosted by the Norwegian Meteorological Institute and supported by the WSL Institute for Snow and Avalanche Research (Switzerland). Through its Data Portal, GCW strives to provide access (Bavay et al., 2020) to cryospheric and ancillary data, both real-time and archived (in the form of climate consistent time series), via cost-efficient mechanisms within the framework of the WMO Information System (WIS), by building on existing data exchange within and external to WMO. Complementary to WIS, GCW fosters the inclusion of cryosphere specific functions as part of the WMO Global Data Processing and Forecasting System (GDPFS), supporting specialized services for polar and high mountain regions.
|
|
Figure 9 - Field work and installation of new sensors at the permafrost monitoring station at Janssonhaugen (78° N) on Svalbard on a cold day in mid-February. (Photo: Ketil Isaksen)Cryosphere data are sourced from NMHSs and from other operational and scientific entities (Figure 9), with the latter using a range of different data management approaches, often quite different from those used in the WMO community. GCW is using the tools and procedures available through WIGOS and WIS to establish links between the cryosphere scientific communities and WMO data providers and users. These include (1) allocation of WIGOS station identifiers for observing facilities, (2) the use of WIGOS metadata to document observing facilities, (3) standardization and registration of cryosphere observing facilities alongside meteorological, climate and other observing facilities, in the WMO OSCAR/Surface database, (4) the documentation of cryosphere observing requirements and capabilities in the OSCAR/Requirements database, (5) standardization and interoperability supporting the discoverability of cryosphere datasets within WIS, (6) exchange of the cryosphere data for operational purposes through WIS, and (7) providing access to the free and unrestricted WMO data to the non-NMHS community.
The implementation of the WMO Unified Data Policy offers incentives to improve connectivity between providers of cryosphere data and NMHSs. While the adoption of tools brokered by GCW may come at a cost for many data providers, the aspiration is that they would benefit, in return, by gaining access to data for multiple providers and to capabilities to monitor what data are exchanged, the use and reuse of shared data as well as being able to influence further developments of tools relevant to them. The ability to report on the data available will also help to identify observational gaps and capabilities. For example, mutual benefits are anticipated if snow data collected at the regional level would be shared by default with agencies at the national level and NHMSs (Vionnet et al., 2021).
At the practical level, GCW supports and enables contributions from data providers with limited resources and capabilities for data management, by making a software package for transforming data from unstructured to structured NetCDF/CF (FAIR compliant) available through the GCW Data Portal (Bavay, Fiddes and Godøy, , 2020).
Partnerships for access to data from polar and high-mountain regions
Significant steps have been taken by GCW as a broker of data for polar and high mountain regions. For polar regions, the existing engagements between GCW and the joint Arctic Data Committee (ADC) of the Sustaining Arctic Observing Network (SAON) and the International Arctic Science Committee (IASC), as well as the Scientific Committee for Antarctic Data Management (SCADM) of the Scientific Committee for Antarctic Research (SCAR) provide opportunities for enhancing the collaboration, leading to increased access to available data. It is notable that SCAR, as the scientific committee of the Antarctic Treaty System, is mandated to facilitate free and unrestricted access to Antarctic scientific data and information. As documented by ADC, data on the Arctic exist and flow independently within a complex Arctic Information Ecosystem (AIE – Pulsifer et al., 2020) of institutions and data centres, but it aims to build capacity to support relevant applications and link to the global data needs to meet regional needs and enhance disaster resilience in the Arctic.
For high mountain regions, the data landscape is much more fragmented (Thornton et al., 2021, Shahgedanova et al., 2021). Collective efforts are being made (Adler, Pomeroy and Nitu, 2020) to address barriers through mechanisms such as those facilitated by the Mountain Research Initiative and its flagship activity, such as GEO Mountains, and the International Network for Alpine Research Catchment Hydrology (INARCH). In 2019, GCW signed a 5-year Memorandum of Understanding with the Third Pole Environment program, with a dedicated focus on establishing interoperability with the Third Pole Environment Data Center (Xin Li et all, 2021, also # 10). Similar engagements are being pursued with other research data centres to further facilitate the access to critical streams of cryosphere and ancillary data.
These partners recognize that WMO is well-positioned to play a key role regarding data policies and practices by fostering greater integration beyond specific regions and domains. To this end, if enacted, the Unified Data Policy will translate into practice the principles of engagement between partners holding cryosphere data who are willing to share and exchange their data internationally. The Policy will once again set an example for partner communities, just as was the case for the International Polar Year (IPY) 2007–2008 when WMO, jointly with the International Council for Science, established an innovative data management framework to underpin the goals of the stakeholder communities. Since IPY, the WMO-partner communities have made significant progress in data and information management, with the notable increased relevance of the FAIR guiding principles.
These areas of progress offer potential benefits for WMO Members, as the Unified Data Policy is designed to be fit for its current purposes and to adapt to future needs.
|
|
Figure 10 - Sept 2021 installation of a new high mountain observation site in the Western Pamir, Tajikistan as part of the "Cryosphere Observations and Modelling for improved Adaptation in Central Asia" (CROMO-ADAPT) funded by the Swiss Development Corporation and co-led by University of Fribourg and WSL Institute of Snow and Avalanche Research SLF (Switzerland) (Photo: Joel Fiddes)Conclusions
The focus of WMO on Earth system monitoring, modelling and prediction is increasing the need to integrate cryosphere data in support of all weather and climate-related service delivery. The Unified Data Policy paves the way for a more systematic approach to the exchange and use of cryosphere data in conjunction with data from the more traditional domains of WMO. It is anticipated that the implementation of the Policy will be instrumental in enhancing data access and in fulfilling the spatio-temporal resolution required by users. At the same time, the current holders of those data, including cryosphere data, that reside outside the domain of NMHSs, will receive tangible benefits.
Mutual benefits to WMO, research and other communities are expected as a result of the improved data exchange triggered by the Unified Data Policy. Access to descriptive inventories of past events and to robust climatic data that is the underpinning of hazard assessments will allow scientists and NMHSs to better help the global community with some of major challenges posed by a rapidly changing climate (Figure 10).
Strengthening of partnerships in support of effective cryosphere data exchange in the framework of WIGOS, WIS and GDPFS is essential for meeting the ambitious goals of the WMO Earth system approach. The benefits will be tangible and substantial, but success will critically depend on our ability to establish mutually beneficial engagements across the diverse community and data holders in the cryosphere domain.
Attribution of data ownership wherever requested, as called for in the Policy, ensures the recognition and the protection of the individual intellectual property rights and is an important aspect for improving the effectiveness and the longevity of partnerships.
WMO has a long-standing and innovative collaboration with the research community, and the success of the data policy of the International Polar Year 2007–2008 is a testament to this. The Unified Data Policy will set an example for the partner communities. It demonstrates a clear aim to ensure continued successful collaboration with the cryosphere community in the future.
References
Adler, C., Pomeroy, J., Nitu, R., 2020. High Mountain Summit: Outcomes and Outlook, WMO Bulletin, 69(1), pp. 34-37.
Bavay, M., Fiddes, J. and Godøy, Ø., 2020. Automatic Data Standardization for the Global Cryosphere Watch Data Portal. Data Science Journal, 19(6), pp.1-8, http://doi.org/10.5334/dsj-2020-006
Egan, P.A. and Price, M.F., 2017. Mountain Ecosystem Services and Climate Change A Global Overview of Potential Threats and Strategies for Adaptation. Paris, France, UNESCO.
GAPHAZ 2017: Assessment of Glacier and Permafrost Hazards in Mountain Regions – Technical Guidance Document. [Allen, S., Frey, H., Huggel, C., Bründl, M., Chiarle, M., Clague, J.J., Cochachin, A., Cook, S., Deline, P., Geertsema, M., Giardino, M., Haeberli, W., Kääb, A., Kargel, J., Klimes, J., Krautblatter, M., McArdell, B., Mergili, M., Petrakov, D., Portocarrero, C., Reynolds, J., Schneider, D. Standing Group on Glacier and Permafrost Hazards in Mountains (GAPHAZ) of the International Association of Cryospheric Sciences (IACS) and the International Permafrost Association (IPA). Zurich, Switzerland / Lima, Peru, GAPHAZ, pp.72.
Helmert, J., Şensoy Şorman, A., Alvarado Montero, R., De Michele, C., De Rosnay, P., Dumont, M., Finger, D.C., Lange, M., Picard, G., Potopová, V. and Pullen, S., 2018. Review of snow data assimilation methods for hydrological, land surface, meteorological and climate models: Results from a COST HarmoSnow survey. Geosciences, 8(12), p.489, https://doi.org/10.1038/s41586-019-1822-y
Huggel, C., Cochachin, A., Drenkhan, F., Fluixá-Sanmartín, J., Frey, H., García Hernández, J., Jurt, C., Muñoz, R., Price, K. and Vicuña, L., 2020. Glacier Lake 513, Peru: lessons for early warning service development. WMO Bulletin, 69(1), pp.45-52.
Huss, M., Bookhagen, B., Huggel, C., Jacobsen, D., Bradley, R.S., Clague, J.J., Vuille, M., Buytaert, W., Cayan, D.R., Greenwood, G. and Mark, B.G., 2017. Toward mountains without permanent snow and ice. Earth's Future, 5(5), pp.418-435.
Immerzeel, W.W., Lutz, A.F., Andrade, M., Bahl, A., Biemans, H., Bolch, T., Hyde, S., Brumby, S., Davies, B.J., Elmore, A.C. and Emmer, A., 2020. Importance and vulnerability of the world’s water towers. Nature, 577(7790), pp.364-369.
IPCC, 2019: Summary for Policymakers. In: IPCC Special Report on the Ocean and Cryosphere in a Changing Climate [Pörtner, H.-O., Roberts, D.C., Masson-Delmotte, V., Zhai, P., Tignor, M., Poloczanska, E., Mintenbeck, K., Alegría, A., Nicolai, M., Okem, A., Petzold, J., Rama, B., Weyer, N.M. (eds.)]. In press.
IPCC, 2021: Summary for Policymakers. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson Delmotte, V., Zhai, P., Pirani, A., Connors, S.L., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M.I., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J.B.R., Maycock, T.K., Waterfield, T., Yelekçi, O., Yu, R. and Zhou, B., (eds.)]. Cambridge University Press. In Press.
Nitu, R., Roulet, Y.A., Wolff, M., Earle, M., Reverdin, A., Smith, C., Kochendorfer, J., Morin, S., Rasmussen, R., Wong, K. and Alastrué, J., 2018. WMO Solid Precipitation Intercomparison Experiment (SPICE) (2012-2015), World Meteorological Organization, IOM Report, 131.
Pan, X., Guo, X., Li, X., Niu, X., Yang, X., Feng, M., Che, T., Jin, R., Ran, Y., Guo, J. and Hu, X., 2021. National Tibetan Plateau Data Center: Promoting Earth System Science on the Third Pole. Bulletin of the American Meteorological Society, pp.1-43, https://doi.org/10.1175/BAMS-D-21-0004.1
Pulsifer, P.L., Kontar, Y., Berkman, P.A. and Taylor, D.F., 2020. Information ecology to map the Arctic information ecosystem. Governing Arctic Seas: Regional Lessons from the Bering Strait and Barents Sea, Springer, Cham., pp.269-291.
Rössler, O., Froidevaux, P., Börst, U., Rickli, R., Martius, O. and Weingartner, R., 2014. Retrospective analysis of a nonforecasted rain-on-snow flood in the Alps–a matter of model limitations or unpredictable nature?. Hydrology and Earth System Sciences, 18(6), pp.2265-2285.
Schoolmeester, T., Johansen, K.S., Alfthan, B., Baker, E., Hesping, M. and Verbist, K., 2018. The Andean glacier and water atlas: the impact of glacier retreat on water resources. UNESCO and GRID-Arendal Publishing.
Shahgedanova, M., Adler, C., Gebrekirstos, A., Grau, H.R., Huggel, C., Marchant, R., Pepin, N., Vanacker, V., Viviroli, D. and Vuille, M., 2021. Mountain Observatories: Status and Prospects for Enhancing and Connecting a Global Community. Mountain Research and Development, 41(2), p.A1, https://doi.org/10.1659/MRD-JOURNAL-D-20-00054.1
Thornton, J.M., Palazzi, E., Pepin, N.C., Cristofanelli, P., Essery, R., Kotlarski, S., Giuliani, G., Guigoz, Y., Kulonen, A., Pritchard, D., Li, X., Fowler, H.J., Randin, C.F., Shahgedanova, M., Steinbacher, M., Zebisch, M., and Adler, C., 2021. Toward a definition of Essential Mountain Climate Variables. One earth 4(6), https://doi.org/10.1016/j.oneear.2021.05.005
Vionnet, V., Mortimer, C., Brady, M., Arnal, L., Brown, R., 2021. Canadian historical Snow Water Equivalent dataset (CanSWE, 1928–2020). Earth System Science Data Discussions, pp.1-22, https://doi.org/10.5194/essd-2021-160
Wilkinson, M.D., Dumontier, M., Aalbersberg, I.J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J.W., da Silva Santos, L.B., Bourne, P.E. and Bouwman, J., 2016. The FAIR Guiding Principles for scientific data management and stewardship. Scientific data, 3(1), pp.1-9, https://doi.org/10.1038/sdata.2016.18
Zuo, H., Balmaseda, M.A., Tietsche, S., Mogensen, K. and Mayer, M., 2019. The ECMWF operational ensemble reanalysis–analysis system for ocean and sea ice: a description of the system and assessment. Ocean science, 15(3), pp.779-808, https://doi.org/10.5194/os-15-779-2019
Authors
Árni Snorrason, Director General, Icelandic Meteorological Office and Chair of the Global Cryosphere Watch Advisory Group (GCW-AG)
Øystein Godøy, Senior Scientist, Norwegian Meteorological Institute and Chair of the Cryosphere and Data Interoperability – Global Cryosphere Watch
Sue Barrell, Chair, Study Group on Data Issues and Policies, co-chair of the EC Panel on Polar and High Mountain Observations, Research and Services (EC-PHORS)
Rodica Nitu, WMO Secretariat (Global Cryosphere Watch)
