Surface elevation changes of the tropical glaciers throughout Peru between 2000 and 2016

Abstract

Glaciers in tropical regions are very sensitive to climatic variations and thus strongly affected by climate change. The majority of the tropical glaciers worldwide are located in the Peruvian Andes, which have shown significant ice loss in the last century. Here, we present the first multi-temporal, region-wide survey of geodetic mass balances throughout Peru covering the period 2000-2016. Using interferometric satellite SAR acquisitions, bi-temporal geodetic mass balances are derived. An average specific mass balance of -296±41 kg m-2 a-1 is found throughout Peru for the period 2000-2016. However, there are strong regional and temporal differences in the mass budgets ranging from 45±97 kg m-2 a-1 to -752±452 kg m-2 a-1. The ice loss increased towards the end of the observation period. Between 2013 and 2016, the average mass budget amounts to -660±178 kg m-2 a-1. The glacier changes revealed can be attributed to changes in the climatic settings in the study region, derived from ERA-Interim reanalysis data and the Oceanic Niño Index. The intense El Niño activities in 2015/16 are most likely the trigger for the increased change rates in the time interval 2013-2016. Our observations provide fundamental information on the current dramatic glacier changes for local authorities and for the calibration and validation of glacier change projections. The data set consists of elevation change maps for each subregion (R1, R2, R3; see associated article) for the periods 2000-2013, 2000-2016 and 2013-2016. The glacier outlines used to delineate the glacier areas are available via the Global Land Ice Measurements from Space (GLIMS) database. Each elevation change map is a mosaic of several dh/dt GeoTiff data sets. The product is derived from differencing of TanDEM-X and SRTM Digital Elevation Models. See the associated article for further information regarding the generation of the data sets. Please note: The here provided elevation change maps are unfiltered (i.e. no outliers were removed). The "date_merge....." data sets provide information on the observation period (measured in years relative to the date of the start of the observation period). Data sets with observation periods starting in 2000: The mean data of the SRTM mission (2000-02-16) is used as the data reference. Data sets with observation periods starting in 2013: The date of the individual TanDEM-X DEM tiles is used as data reference (date of TanDEM-X tiles in 2013 can be derived from the data sets covering the period 2000-2013; "SRTM mean date" + "date_merge_......2000-2013...."

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