World Glacier Monitoring Service

A parameterization scheme using simple algorithms for unmeasured glaciers is being applied to glacier inventory data to estimate the basic glaciological characteristics of the inventoried ice bodies and simulate potential climate-change effects on mountain glaciers. For past and potential climate scenarios, glacier changes for assumed mass-balance changes are calculated as step functions between steady-state conditions for time intervals that approximately correspond to the characteristic dynamic response time (a few decades) of the glaciers. In order to test the procedure, a pilot study was carried out in the European Alps where detailed glacier inventories had been compiled around the mid-1970s. Total glacier volume in the Alps is estimated at about 130 km 3 for the mid-1970s; strongly negative mass balances are likely to have caused a loss of about 10–20% of this total volume during the decade 1980–90. Backward calculation of glacier-length changes using a mean annual mass balance of 0.25m w.e.a −1 since the end of the “Little Ice Age” around 1850 AD gives considerable scatter but satisfactory overall results as compared with long-term observations. The total loss of Alpine surface ice mass since 1850 can be estimated at about half the original value. An acceleration of this development, with annual mass losses of around 1 m a −1 or more as anticipated from IPCC scenario A for the coming century, could eliminate major parts of the presently existing Alpine ice volume within decades.

A parameterization scheme using simple algorithms for unmeasured glaciers is being applied to glacier inventory data to estimate the basic glaciological characteristics of the inventoried ice bodies and simulate potential climate-change effects on mountain glaciers. For past and potential climate scenarios, glacier changes for assumed mass-balance changes are calculated as step functions between steady-state conditions for time intervals that approximately correspond to the characteristic dynamic response time (a few decades) of the glaciers. In order to test the procedure, a pilot study was carried out in the European Alps where detailed glacier inventories had been compiled around the mid-1970s. Total glacier volume in the Alps is estimated at about 130 km 3 for the mid-1970s; strongly negative mass balances are likely to have caused a loss of about 10–20% of this total volume during the decade 1980–90. Backward calculation of glacier-length changes using a mean annual mass balance of 0.25m w.e.a −1 since the end of the “Little Ice Age” around 1850 AD gives considerable scatter but satisfactory overall results as compared with long-term observations. The total loss of Alpine surface ice mass since 1850 can be estimated at about half the original value. An acceleration of this development, with annual mass losses of around 1 m a −1 or more as anticipated from IPCC scenario A for the coming century, could eliminate major parts of the presently existing Alpine ice volume within decades.

Tree trunks and wood fragments in minerotrophic fen peat that accumulated as the result of a jökulhlaup in the outwash plain of Unteraarglacier were radiocarbon-dated using conventional ß-counting. Different pretreatment methods were tested on two wood samples to determine the reliability of our dates. We dated the wood compounds after extended acid-alkali-acid treatment, as well as extraction of cellulose and lignin. The results of the samples Picea (B-6687) and Pinus cent-bra (B-6699) show insignificant differences of < 1σ. The 14 C dates represent retreat of Unteraarglacier due to warmer and/or drier phases in the Holocene compared to modern climate conditions. The glacier was at least several hundred meters smaller in extent than today ca. 8100–7670 bp, 6175–5780 bp, 4580–4300 bp, 4100–3600 bp and 3380–3200 bp. The 14 C dates suggest a ca. 2000-yr cyclicity of tree growth in the area covered by the present Unteraarglacier. The most intense warm and dry period occurred between 4100 bp (probably extending back to 4580 bp) and 3600 bp, with growth of fen peat between 3800 and 3600 bp attributed to wetter conditions.

Abstract The Desert Andes contain >4500 ice masses, but only a handful are currently being monitored. We present the mass changes of the small mountain glacier Agua Negra (1 km 2 ) and of the rest of glaciers in the Jáchal river basin. Remote-sensing data show Agua Negra glacier lost 23% of its area during 1959–2019. Glaciological measurements during 2014–2021 indicate an average annual mass balance of −0.52 m w.e. a −1 , with mean winter and summer balances of 0.80 and −1.33 m w.e. a −1 , respectively. The Equilibrium Line Altitude (ELA) is estimated to be 5100 ± 100 m a.s.l., which corresponds to an Accumulation Area Ratio (AAR) of 0.28 ± 0.21. Geodetic data from SRTM X and Pléiades show a doubling of the loss rate from −0.32 ± 0.03 m w.e. a −1 in 2000–2013, to −0.66 ± 0.06 m w.e. a −1 in 2013–2019. Comparatively, the ice losses for the entire Jáchal river basin (25 500 km 2 ) derived from ASTER show less negative values, −0.11 ± 16 m w.e. a −1 for 2000–2012 and −0.23 ± 14 m w.e. a −1 for 2012–2018. The regional warming trend since 1979 and a recent decline in snow accumulation are probably driving the observed glacier mass balance.

<p>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.</p><p><br>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.</p><p><br>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.</p>

Abstract. Measurements of englacial temperatures have been collected since the earliest years of glaciology, with the first measurements dating back to the mid-19th century. Although temperature is a defining characteristic of any glacier – and is notoriously laborious to collect – no effort had yet been made to gather all existing measurements. In an attempt to make existing ice temperature data more accessible, we present glenglat, a global database of englacial temperature measurements, compiled from 241 literature sources and nine data submissions and composed of 1142163 measurements of depth and temperature from 690 boreholes located on 186 glaciers outside of the ice sheets. Alongside recent compilations for the ice sheets (Løkkegaard et al., 2023; Vandecrux et al., 2023), most published englacial temperature measurements are now readily available to the research community. Here, we review the variety of glacier thermal regimes that have been measured and summarize the spatial, temporal, and climatic coverage of measurements relative to global glacierized area. Measurements of cold and polythermal glacier ice greatly outnumber those of temperate ice. Overall, temperature has been measured in fewer than 1 ‰ of all glaciers, and only 20 % of borehole locations have been measured more than once, highlighting the large potential to investigate changing temperature conditions by repeating past measurements. The database is developed on GitHub (www.github.com/mjacqu/glenglat) and published to Zenodo (https://doi.org/10.5281/zenodo.13334175; Jacquemart and Welty, 2024). It consists of four relational tables and detailed machine-actionable and human-readable metadata. The GitHub repository also provides submission instructions (including a spreadsheet template and validation tools), in the hopes that investigators can help us keep glenglat complete and current going forward. We hope that glenglat can help improve our understanding of glacier thermal regimes, help refine glacier thermo-dynamic models, or shed insight into hazardous glacier instabilities in a warming world.

<p>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.</p><p>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.</p><p>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.</p>