The Randolph Glacier Inventory (RGI) is a globally complete collection of digital outlines of glaciers, excluding the ice sheets, developed to meet the needs of the Fifth Assessment of the Intergovernmental Panel on Climate Change for estimates of past and future mass balance. The RGI was created with limited resources in a short period. Priority was given to completeness of coverage, but a limited, uniform set of attributes is attached to each of the ~198 000 glaciers in its latest version, 3.2. Satellite imagery from 1999–2010 provided most of the outlines. Their total extent is estimated as 726 800 ± 34 000 km2. The uncertainty, about ±5%, is derived from careful single-glacier and basin-scale uncertainty estimates and comparisons with inventories that were not sources for the RGI. The main contributors to uncertainty are probably misinterpretation of seasonal snow cover and debris cover. These errors appear not to be normally distributed, and quantifying them reliably is an unsolved problem. Combined with digital elevation models, the RGI glacier outlines yield hypsometries that can be combined with atmospheric data or model outputs for analysis of the impacts of climatic change on glaciers. The RGI has already proved its value in the generation of significantly improved aggregate estimates of glacier mass changes and total volume, and thus actual and potential contributions to sea-level rise.

ABSTRACT. Deriving glacier outlines from satellite data has become increasingly popular in the past decade. In particular when glacier outlines are used as a base for change assessment, it is important to know how accurate they are. Calculating the accuracy correctly is challenging, as appropriate reference data (e.g. from higher-resolution sensors) are seldom available. Moreover, after the required manual correction of the raw outlines (e.g. for debris cover), such a comparison would only reveal the accuracy of the analyst rather than of the algorithm applied. Here we compare outlines for clean and debriscovered glaciers, as derived from single and multiple digitizing by different or the same analysts on very high-(1 m) and medium-resolution (30 m) remote-sensing data, against each other and to glacier outlines derived from automated classification of Landsat Thematic Mapper data. Results show a high variability in the interpretation of debris-covered glacier parts, largely independent of the spatial resolution (area differences were up to 30%), and an overall good agreement for clean ice with sufficient contrast to the surrounding terrain (differences $5%). The differences of the automatically derived outlines from a reference value are as small as the standard deviation of the manual digitizations from several analysts. Based on these results, we conclude that automated mapping of clean ice is preferable to manual digitization and recommend using the latter method only for required corrections of incorrectly mapped glacier parts (e.g. debris cover, shadow).

Glacier inventories provide essential baseline information for the determination of water resources, glacier-specific changes in area and volume, climate change impacts as well as past, potential and future contribution of glaciers to sea-level rise. Although Greenland is heavily glacierised and thus highly relevant for all of the above points, a complete inventory of its glaciers was not available so far. Here we present the results and details of a new and complete inventory that has been compiled from more than 70 Landsat scenes (mostly acquired between 1999 and 2002) using semi-automated glacier mapping techniques. A digital elevation model (DEM) was used to derive drainage divides from watershed analysis and topographic attributes for each glacier entity. To serve the needs of different user communities, we assigned to each glacier one of three connectivity levels with the ice sheet (CL0, CL1, CL2; i.e. no, weak, and strong connection) to clearly, but still flexibly, distinguish the local glaciers and ice caps (GIC) from the ice sheet and its outlet glaciers. In total, we mapped ~ 20 300 glaciers larger than 0.05 km² (of which ~ 900 are marine terminating), covering an area of 130 076 ± 4032 km², or 89 720 ± 2781 km² without the CL2 GIC. The latter value is about 50% higher than the mean value of more recent previous estimates. Glaciers smaller than 0.5 km² contribute only 1.5% to the total area but more than 50% (11 000) to the total number. In contrast, the 25 largest GIC (> 500 km²) contribute 28% to the total area, but only 0.1% to the total number. The mean elevation of the GIC is 1700 m in the eastern sector and around 1000 m otherwise. The median elevation increases with distance from the coast, but has only a weak dependence on mean glacier aspect

The recently finalized inventory of Greenland's glaciers and ice caps (GIC) allows for the first time to determine the mass changes of the GIC separately from the ice sheet using space‐borne laser altimetry data. Corrections for firn compaction and density that are based on climatic conditions are applied for the conversion from volume to mass changes. The GIC which are clearly separable from the icesheet (i.e., have a distinct ice divide or no connection) lost 27.9 ± 10.7 Gt a−1 or 0.08 ± 0.03 mm a−1 sea‐level equivalent (SLE) between October 2003 and March 2008. All GIC (including those with strong but hydrologically separable connections) lost 40.9 ± 16.5 Gt a−1 (0.12 ± 0.05 mm a−1 SLE). This is a significant fraction (~14 or 20%) of the reported overall mass loss of Greenland and up to 10% of the estimated contribution from the world's GIC to sea level rise. The loss was highest in southeastern and lowest in northern Greenland.

Abstract. Knowledge about the coverage and characteristics of glaciers in High Mountain Asia (HMA) is still incomplete and heterogeneous. However, several applications, such as modelling of past or future glacier development, run-off, or glacier volume, rely on the existence and accessibility of complete datasets. In particular, precise outlines of glacier extent are required to spatially constrain glacier-specific calculations such as length, area, and volume changes or flow velocities. As a contribution to the Randolph Glacier Inventory (RGI) and the Global Land Ice Measurements from Space (GLIMS) glacier database, we have produced a homogeneous inventory of the Pamir and the Karakoram mountain ranges using 28 Landsat TM and ETM+ scenes acquired around the year 2000. We applied a standardized method of automated digital glacier mapping and manual correction using coherence images from the Advanced Land Observing Satellite 1 (ALOS-1) Phased Array type L-band Synthetic Aperture Radar 1 (PALSAR-1) as an additional source of information; we then (i) separated the glacier complexes into individual glaciers using drainage divides derived by watershed analysis from the ASTER global digital elevation model version 2 (GDEM2) and (ii) separately delineated all debris-covered areas. Assessment of uncertainties was performed for debris-covered and clean-ice glacier parts using the buffer method and independent multiple digitizing of three glaciers representing key challenges such as shadows and debris cover. Indeed, along with seasonal snow at high elevations, shadow and debris cover represent the largest uncertainties in our final dataset. In total, we mapped more than 27 800 glaciers >0.02 km2 covering an area of 35 520±1948 km2 and an elevation range from 2260 to 8600 m. Regional median glacier elevations vary from 4150 m (Pamir Alai) to almost 5400 m (Karakoram), which is largely due to differences in temperature and precipitation. Supraglacial debris covers an area of 3587±662 km2, i.e. 10 % of the total glacierized area. Larger glaciers have a higher share in debris-covered area (up to >20 %), making it an important factor to be considered in subsequent applications (https://doi.org/10.1594/PANGAEA.894707).