Global Land Ice Measurements from Space (GLIMS), an initiative to build and distribute a database of global glacier data, has recently begun to track glaciers that have recently disappeared. GLIMS provides a definition of "extinct" glaciers for our community, and the final determination of extinction is left to local experts. There are currently 181 glaciers in the GLIMS Glacier Database that are marked as "extinct", though we recognize that there have been many more reported in the literature. GLIMS welcomes more submissions to make the list more complete.

AbstractGlacier monitoring has been internationally coordinated for more than 125 years. Despite this long history, there is no authoritative answer to the popular question: ‘Which glaciers are the largest in the world?’ Here, we present the first systematic assessment of this question and identify the largest glaciers in the world – distinct from the two ice sheets in Greenland and Antarctica but including the glaciers on the Antarctic Peninsula. We identify the largest glaciers in two domains: on each of the seven geographical continents and in the 19 first-order glacier regions defined by the Global Terrestrial Network for Glaciers. Ranking glaciers by area is non-trivial. It depends on how a glacier is defined and mapped and also requires differentiating between a glacier and a glacier complex, i.e. glaciers that meet at ice divides such as ice caps and icefields. It also depends on the availability of a homogenized global glacier inventory. Using separate rankings for glaciers and glacier complexes, we find that the largest glacier complexes have areas on the order of tens of thousands of square kilometers whereas the largest glaciers are several thousands of square kilometers. The world's largest glaciers and glacier complexes are located in the Antarctic, Arctic and Patagonia.

Glacier monitoring has been internationally coordinated since the late 19th century. For the last 25 years (i.e., 1998-2023), the compilation and dissemination of global glacier datasets has been coordinated by the Global Terrestrial Network for Glaciers (GTN-G, https://gtn-g.org). Authorized under the Global Climate Observing System (GCOS) and supported by an international Advisory Board, GTN-G is jointly run by the science officers from the World Glacier Monitoring Service (WGMS, https://wgms.ch), the US National Snow and Ice Data Center (NSIDC, https://nsidc.org), and the Global Land Ice Measurements from Space initiative (GLIMS, https://glims.org), in collaboration with related working groups of the International Association of Cryospheric Sciences (IACS, https://cryosphericsciences.org/).We present an updated overview of the various observational glacier datasets (https://www.gtn-g.ch/data_catalogue/), including world regions for regional glacier assessments (GTN-G Glacier Regions), glacier attributes (WGI: World Glacier Inventory), centerlines, and outlines (GLIMS, RGI: Randolph Glacier Inventory), ice velocities (ITS_LIVE), ice thickness (GlaThiDa: Glacier Thickness Database), glacier photographs (GPC: Glacier Photograph Collection), and glacier maps (GMC: Glacier Map Collection). For each dataset, we provide insights into the increased amount and richness of available data. We also demonstrate the value of these datasets by presenting selected findings from our own analyses as well as from user applications.

Glaciers in the Hindu Kush-Karakoram-Himalayas (HKH) are a major source of freshwater in the agriculture-dependent economy of Pakistan. In recent decades, mountain glaciers have been threatened by global warming. In this study, we estimated the Equilibrium Line Altitude (ELA) and geodetic mass balance of fifteen representative glaciers from Hunza (Karakoram), Chitral (Hindu Kush), and Astore (Himalaya) using Landsat satellite images and Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) DEMs between 2000 and 2018. The climatic trends (temperature and precipitation) in the 19 years (1995–2013) time series of the three regions were assessed using the non-parametric Mann-Kendall test and Sen’s Slope. The ELA of the observed glaciers except for two Atrak (Chitral) and Gulkin (Hunza) is shifted upward, while the mass balance indicates a heterogeneous pattern ranging from −0.23 ± 0.05 to −0.01 ± 0.015 m w.e a−1, −0.13 ± 0.05 to+0.17 ± 0.11 m w.e a−1 and −0.03 ± 0.02 to+0.23 ± 0.09 m w.e a−1 in Chitral, Hunza, and Astore basin, respectively. A significant or slight increasing or decreasing trend was found in the mean annual temperature, mean total precipitation, and mean discharge of the studied basins. This study will be a good contribution to understanding snow and glacier dynamics in HKH, the factors that influence them, and their interaction with the environment.

The Randolph Glacier Inventory (RGI) is a globally complete collection of digital glacier outlines, excluding the two ice sheets. It has become a pillar of glaciological research at global and regional scales for estimates of recent and future glacier changes, glacier mass balance, glacier contribution to sea-level rise, among others. The latest RGI version (V6) was released in July 2017. Here, we present a new version of the RGI (version 7.0), which is our best estimate of global glacier outlines around the year 2000. Unlike previous versions which were compiled by an ad-hoc manual process using different sources, RGI7.0 is generated directly from the Global Land Ice Measurements from Space (GLIMS) glacier database, ensuring full traceability of single outlines to their original authors. The dataset is generated automatically with Python scripts parsing the GLIMS database and selecting outlines according to community decisions (based on data availability, quality and closeness to the year 2000). Prior to its release, the dataset was available for open review from the scientific community, and further refined as necessary. About 70% of the outlines (30% of the total area) in RGI7.0 are obtained from new inventories that were submitted to GLIMS since the last release of RGI6.0 by different groups around the world. This led to considerable quality improvements especially in High Mountain Asia, Northern Canada, northern Greenland, Caucasus and Middle East, South America and New Zealand. RGI7.0 includes updated topographical and geometrical glacier attributes generated with a new community software. The new RGI generation process is open-source, fully reproducible and easily adaptable, making future updates straightforward to generate.

GLIMS, Global Land Ice Measurements from Space, is an initiative that involves ~250 analysts from 34 countries and has the purpose of mapping all glaciers in the world (excluding the Greenland and Antarctic ice sheets) on a periodic basis. The GLIMS Glacier Database, which became an official product of the NASA NSIDC DAAC (Distributed Active Archive Center) in 2019, contains time series of glacier outlines from different data sources. Various parts or facies of glaciers are mapped, including the full glacier extent, debris-covered parts, internal rock outcrops, and glacial lakes. The Randolph Glacier Inventory (RGI) is a snapshot map of glaciers, with one outline per glacier, as close as possible to a target date. In the last year, GLIMS and the RGI working group have been working closely together to ingest new data into GLIMS and to improve GLIMS and RGI software tools. The goal is to improve data completeness and quality and to make the creation of the RGI smoother and more transparent (Maussion et al., EGU22-4484). New data include approximately 60,000 outlines from 14 regions in all parts of the Earth, with times ranging from the Little Ice Age to 2018. Software improvements include more quality-control checks and constraints, such as separating multi-polygons into individual ones. The presentation will provide an overview on the latest data additions and software developments in GLIMS and the synergy with RGI production.

The creation and curation of environmental data present numerous challenges and rewards. In this study, we reflect on the increasing amount of freely available glacier data (inventories and changes), as well as on related demands by data providers, data users, and data repositories in-between. The amount of glacier data has increased significantly over the last two decades as remote sensing techniques have improved and free data access is much more common. The portfolio of observed parameters has increased as well, which presents new challenges for international data centers, and fosters new expectations from users. We focus here on the service of the Global Terrestrial Network for Glaciers (GTN-G) as the central organization for standardized data on glacier distribution and change. Within GTN-G, different glacier datasets are consolidated under one umbrella, and the glaciological community supports this service by actively contributing their datasets and by providing strategic guidance via an Advisory Board. To assess each GTN-G dataset, we present a maturity matrix and summarize achievements, challenges, and ambitions. The challenges and ambitions in the democratization of glacier data are discussed in more detail, as they are key to providing an even better service for glacier data in the future. Most challenges can only be overcome in a financially secure setting for data services and with the help of international standardization as, for example, provided by the CoreTrustSeal. Therefore, dedicated financial support for and organizational long-term commitment to certified data repositories build the basis for the successful democratization of data. In the field of glacier data, this balancing act has so far been successfully achieved through joint collaboration between data repository institutions, data providers, and data users. However, we also note an unequal allotment of funds for data creation and projects using the data, and data curation. Considering the importance of glacier data to answering numerous key societal questions (from local and regional water availability to global sea-level rise), this imbalance needs to be adjusted. In order to guarantee the continuation and success of GTN-G in the future, regular evaluations are required and adaptation measures have to be implemented.

Glacier monitoring has been internationally coordinated for more than 125 years. Despite this long history there is no unambiguous answer to the popular question: which are the world’s largest glaciers? In this study, we present a first scientific assessment of the largest glaciers in the world – distinct from the two ice sheets in Greenland and Antarctica – and in the 19 regions used for the current Randolph Glacier Inventory. Ranking glaciers by size is non-trivial since it depends on how an individual glacier is defined and mapped. It is also important to differentiate between individual glaciers and glacier complexes, which are contiguous glaciers that meet at ice divides and might form an ice cap or ice field. We find that the largest glacier complexes cover areas larger than ten thousand square kilometres, whereas the largest individual glaciers cover up to several thousand square kilometres. The world’s largest glaciers and glacier complexes are located on the Antarctic Peninsula, on sub-Antarctic Islands, in the Arctic, and in Patagonia. As such, the largest glacier complexes cover areas the size of smaller countries (e.g., Switzerland or Austria) or of smaller US states (e.g. New Jersey or South Carolina), but are still orders of magnitudes smaller than the Greenland and Antarctic Ice Sheets. In addition, we show that the ranking of glaciers requires not only clear definitions but depends on the availability, quality, and consistency of digital glacier outlines at global scale. Corresponding additional metadata are required in the available inventories to fully automate a glacier ranking by area, and to extend such a study to rankings by length, volume/mass, and other parameters.

The creation and curation of environmental data present numerous challenges and rewards. In this study, we reflect on the maturity of freely available glacier data sets (inventories and changes), as well as on related demands by data providers, data users, and data repositories in-between. The amount of glacier data has increased significantly over the last two decades, especially as remote-sensing techniques have developed quickly. The portfolio of observed parameters has increased as well, which presents new challenges for international data centers, and fosters new expectations from users. We assess the services of the Global Terrestrial Network for Glaciers (GTN-G) as the central organization for standardized data on glacier distribution and changes. Within GTN-G, different glacier data sets are consolidated under one umbrella, and the glaciological community supports this service by actively contributing their data sets and by providing strategic guidance via an Advisory Board. To assess each GTN-G data set, we present a maturity matrix and summarize achievements, challenges, and future ambitions. Most challenges can only be overcome in a financially secure setting for data services and with the help of international standardization. Therefore, dedicated support and long-term commitment for certified data repositories build the basis for the successful democratization of data. In the field of glacier data, this balancing act has so far been successfully achieved through joint collaboration between data repositories, data providers, and data users. However, we also note an unequal allotment of funds for data creation and projects using the data, and data curation. Considering the importance of glacier data to answering numerous key societal questions (from water availability to global sea-level rise), this imbalance needs to be adjusted. In order to guarantee the continuation and success of GTN-G in the future, basic funding schemes, flexible adaptation measures, and regular evaluations are required.

The Randolph Glacier Inventory (RGI) is a globally complete collection of digital glacier outlines, excluding the two polar ice sheets. It has become a pillar of glaciological research at global and regional scales, among others for estimates of recent and future glacier changes, glacier mass balance, and glacier contribution to sea-level rise. After its creation in 2012, the dataset’s further development has been coordinated by an IACS Working Group (WG) until 2019. This new WG (2020 - 2023) expands the scope of the previous one with new and updated objectives.The latest RGI version (V6) was released in July 2017, and several new glacier outline datasets have been generated by the community since then. In the past, the RGI was updated by an ad-hoc manual process, which was effective but labor-intensive. One of the main objectives of the WG is to automate this process as much as possible by incorporating RGI generation tools into the Global Land Ice Measurements from Space (GLIMS) glacier database. Furthermore, the RGI (as of version 6) needs further improvements to remain useful to the wider scientific community. Examples include data quality (wrong/outdated outlines, ice divides) but also the quality and availability of glacier attributes (hypsometry, glacier type, ...). Additionally, there is a demand for consistent historic glacier outlines (e.g. from the mid-1980s or earlier) to facilitate validation of glacier evolution models or transient mass balance calculations. With this WG, we strive to continuously improve and update the RGI, as well as to lay out a long-term plan for sustainable continuation of the RGI beyond the end of this WG.In this presentation, we will discuss the current status and future of the RGI, and will engage with the community to encourage participation and feedback.

Across High Asia, the amount, timing, and spatial patterns of snow and ice melt play key roles in providing water for downstream irrigation, hydropower generation, and general consumption. The goal of this paper is to distinguish the specific contribution of seasonal snow versus glacier ice melt in the major basins of High Mountain Asia: Ganges, Brahmaputra, Indus, Amu Darya, and Syr Darya. Our methodology involves the application of MODIS-derived remote sensing products to separately calculate daily melt outputs from snow and glacier ice. Using an automated partitioning method, we generate daily maps of (1) snow over glacier ice, (2) exposed glacier ice, and (3) snow over land. These are inputs to a temperature index model that yields melt water volumes contributing to river flow. Results for the five major High Mountain Asia basins show that the western regions are heavily reliant on snow and ice melt sources for summer dry season flow when demand is at a peak, whereas monsoon rainfall dominates runoff during the summer period in the east. While uncertainty remains in the temperature index model applied here, our approach to partitioning melt from seasonal snow and glacier ice is both innovative and systematic and more constrained than previous efforts with similar goals.

Two pairs of small stagnant ice bodies on the Hazen Plateau of northeastern Ellesmere Island, the St. Patrick Bay ice caps and the Murray and Simmons ice caps, are rapidly shrinking, and the remnants of the St. Patrick Bay ice caps are likely to disappear entirely within the next 5 years. Vertical aerial photographs of these Little Ice Age relics taken during August of 1959 show that the larger of the St. Patrick Bay ice caps had an area of 7.48 km2 and the smaller one 2.93 km2; the Murray and Simmons ice caps covered 4.37 and 7.45 km2 respectively. Outlines determined from ASTER satellite data for July 2016 show that, compared to 1959, the larger and the smaller of the St. Patrick Bay ice caps had both been reduced to only 5 % of their former area, with the Murray and Simmons ice caps faring better at 39 and 25 %, likely reflecting their higher elevation. Consistent with findings from other glaciological studies in the Queen Elizabeth Islands, ASTER imagery in conjunction with past GPS surveys documents a strikingly rapid wastage of the St. Patrick Bay ice caps over the last 15 years. These two ice caps shrank noticeably even between 2014 and 2015, apparently in direct response to the especially warm summer of 2015 over northeastern Ellesmere Island. The well-documented recession patterns of the Hazen Plateau ice caps over the last 55+ years offer an opportunity to examine the processes of plant recolonization of polar landscapes.