Elevation changes of High Mountain Asia from 2000 to 2016, links to GeoTIFFs
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| Format: | Dataset Open Access |
| Langue: | en |
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2017
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| _version_ | 1867172336393781248 |
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| author | Brun, Fanny Berthier, Etienne Wagnon, Patrick Kääb, Andreas Treichler, Désirée |
| author_facet | Brun, Fanny Berthier, Etienne Wagnon, Patrick Kääb, Andreas Treichler, Désirée |
| collection | Datos científicos de ciencias marinas y ambientales |
| contents | High Mountain Asia hosts the largest glacier concentration outside the polar regions. These glaciers are important contributors to streamflow in one of the most populated areas of the world. Past studies have used methods that can provide only regionally averaged glacier mass balances to assess the glacier contribution to rivers and sea level rise. Here we compute the mass balance for about 92% of the glacierized area of High Mountain Asia using time series of digital elevation models derived from satellite stereo-imagery. We calculate a total mass change of -16.3 ± 3.5Gt/yr (-0.18 ± 0.04 m w.e./yr) between 2000 and 2016, which is less negative than most previous estimates. Region-wide mass balances vary from -4.0 ± 1.5 Gt/yr (-0.62 ± 0.23 m w.e./yr) in Nyainqentanglha to +1.4 ± 0.8 Gt/yr (+0.14 ± 0.08 m w.e./yr) in Kunlun, with large intra-regional variability of individual glacier mass balances (standard deviation within a region ~0.20 m w.e./yr). Specifically, our results shed light on the Nyainqentanglha and Pamir glacier mass changes, for which contradictory estimates exist in the literature. They provide crucial information for the calibration of the models used for projecting glacier response to climatic change, as these models do not capture the pattern, magnitude and intra-regional variability of glacier changes at present. |
| format | Dataset Open Access |
| id | pangaea_https___doi_org_10_1594_PANGAEA_876545 |
| institution | PANGAEA |
| language | en |
| publishDate | 2017 |
| publisher | PANGAEA |
| record_format | pangaea |
| spellingShingle | Elevation changes of High Mountain Asia from 2000 to 2016, links to GeoTIFFs Brun, Fanny Berthier, Etienne Wagnon, Patrick Kääb, Andreas Treichler, Désirée ASTER_n27_e086; ASTER_n27_e087; ASTER_n27_e088; ASTER_n27_e092; ASTER_n28_e083; ASTER_n28_e084; ASTER_n28_e085; ASTER_n28_e086; ASTER_n28_e087; ASTER_n28_e089; ASTER_n28_e090; ASTER_n28_e091; ASTER_n28_e092; ASTER_n28_e097; ASTER_n28_e098; ASTER_n29_e081; ASTER_n29_e082; ASTER_n29_e083; ASTER_n29_e094; ASTER_n29_e095; ASTER_n29_e096; ASTER_n29_e097; ASTER_n29_e101; ASTER_n30_e078; ASTER_n30_e079; ASTER_n30_e080; ASTER_n30_e081; ASTER_n30_e082; ASTER_n30_e083; ASTER_n30_e090; ASTER_n30_e093; ASTER_n30_e094; ASTER_n30_e095; ASTER_n31_e077; ASTER_n31_e078; ASTER_n31_e079; ASTER_n31_e083; ASTER_n31_e094; ASTER_n32_e076; ASTER_n32_e077; ASTER_n32_e078; ASTER_n32_e092; ASTER_n33_e075; ASTER_n33_e076; ASTER_n33_e077; ASTER_n33_e078; ASTER_n33_e079; ASTER_n33_e082; ASTER_n33_e089; ASTER_n33_e090; ASTER_n33_e091; ASTER_n33_e094; ASTER_n34_e075; ASTER_n34_e076; ASTER_n34_e077; ASTER_n34_e078; ASTER_n34_e079; ASTER_n34_e080; ASTER_n34_e081; ASTER_n34_e082; ASTER_n34_e085; ASTER_n35_e070; ASTER_n35_e072; ASTER_n35_e073; ASTER_n35_e074; ASTER_n35_e075; ASTER_n35_e076; ASTER_n35_e077; ASTER_n35_e078; ASTER_n35_e079; ASTER_n35_e080; ASTER_n35_e081; ASTER_n35_e082; ASTER_n35_e089; ASTER_n35_e090; ASTER_n36_e070; ASTER_n36_e071; ASTER_n36_e072; ASTER_n36_e073; ASTER_n36_e074; ASTER_n36_e075; ASTER_n36_e076; ASTER_n36_e077; ASTER_n36_e078; ASTER_n36_e079; ASTER_n36_e082; ASTER_n36_e084; ASTER_n36_e087; ASTER_n36_e090; ASTER_n36_e091; ASTER_n37_e071; ASTER_n37_e072; ASTER_n37_e073; ASTER_n37_e074; ASTER_n37_e075; ASTER_n37_e087; ASTER_n38_e071; ASTER_n38_e072; ASTER_n38_e073; ASTER_n38_e075; ASTER_n38_e096; ASTER_n38_e097; ASTER_n39_e069; ASTER_n39_e070; ASTER_n39_e071; ASTER_n39_e072; ASTER_n39_e073; ASTER_n39_e074; ASTER_n39_e098; ASTER_n40_e074; ASTER_n41_e076; ASTER_n41_e077; ASTER_n41_e078; ASTER_n41_e079; ASTER_n41_e080; ASTER_n42_e074; ASTER_n42_e077; ASTER_n42_e078; ASTER_n42_e079; ASTER_n42_e080; ASTER_n42_e081; ASTER_n42_e082; ASTER_n42_e085; ASTER_n43_e077; ASTER_n43_e083; ASTER_n43_e084; ASTER_n43_e085; ASTER_n43_e086; ASTER_n44_e079; ASTER_n44_e080; ASTER_n44_e083; ASTER_n45_e080; DATE/TIME; Event label; File name; File size; High Mountain Asia; SAT; Satellite remote sensing; Uniform resource locator/link to file High Mountain Asia hosts the largest glacier concentration outside the polar regions. These glaciers are important contributors to streamflow in one of the most populated areas of the world. Past studies have used methods that can provide only regionally averaged glacier mass balances to assess the glacier contribution to rivers and sea level rise. Here we compute the mass balance for about 92% of the glacierized area of High Mountain Asia using time series of digital elevation models derived from satellite stereo-imagery. We calculate a total mass change of -16.3 ± 3.5Gt/yr (-0.18 ± 0.04 m w.e./yr) between 2000 and 2016, which is less negative than most previous estimates. Region-wide mass balances vary from -4.0 ± 1.5 Gt/yr (-0.62 ± 0.23 m w.e./yr) in Nyainqentanglha to +1.4 ± 0.8 Gt/yr (+0.14 ± 0.08 m w.e./yr) in Kunlun, with large intra-regional variability of individual glacier mass balances (standard deviation within a region ~0.20 m w.e./yr). Specifically, our results shed light on the Nyainqentanglha and Pamir glacier mass changes, for which contradictory estimates exist in the literature. They provide crucial information for the calibration of the models used for projecting glacier response to climatic change, as these models do not capture the pattern, magnitude and intra-regional variability of glacier changes at present. |
| title | Elevation changes of High Mountain Asia from 2000 to 2016, links to GeoTIFFs |
| topic | ASTER_n27_e086; ASTER_n27_e087; ASTER_n27_e088; ASTER_n27_e092; ASTER_n28_e083; ASTER_n28_e084; ASTER_n28_e085; ASTER_n28_e086; ASTER_n28_e087; ASTER_n28_e089; ASTER_n28_e090; ASTER_n28_e091; ASTER_n28_e092; ASTER_n28_e097; ASTER_n28_e098; ASTER_n29_e081; ASTER_n29_e082; ASTER_n29_e083; ASTER_n29_e094; ASTER_n29_e095; ASTER_n29_e096; ASTER_n29_e097; ASTER_n29_e101; ASTER_n30_e078; ASTER_n30_e079; ASTER_n30_e080; ASTER_n30_e081; ASTER_n30_e082; ASTER_n30_e083; ASTER_n30_e090; ASTER_n30_e093; ASTER_n30_e094; ASTER_n30_e095; ASTER_n31_e077; ASTER_n31_e078; ASTER_n31_e079; ASTER_n31_e083; ASTER_n31_e094; ASTER_n32_e076; ASTER_n32_e077; ASTER_n32_e078; ASTER_n32_e092; ASTER_n33_e075; ASTER_n33_e076; ASTER_n33_e077; ASTER_n33_e078; ASTER_n33_e079; ASTER_n33_e082; ASTER_n33_e089; ASTER_n33_e090; ASTER_n33_e091; ASTER_n33_e094; ASTER_n34_e075; ASTER_n34_e076; ASTER_n34_e077; ASTER_n34_e078; ASTER_n34_e079; ASTER_n34_e080; ASTER_n34_e081; ASTER_n34_e082; ASTER_n34_e085; ASTER_n35_e070; ASTER_n35_e072; ASTER_n35_e073; ASTER_n35_e074; ASTER_n35_e075; ASTER_n35_e076; ASTER_n35_e077; ASTER_n35_e078; ASTER_n35_e079; ASTER_n35_e080; ASTER_n35_e081; ASTER_n35_e082; ASTER_n35_e089; ASTER_n35_e090; ASTER_n36_e070; ASTER_n36_e071; ASTER_n36_e072; ASTER_n36_e073; ASTER_n36_e074; ASTER_n36_e075; ASTER_n36_e076; ASTER_n36_e077; ASTER_n36_e078; ASTER_n36_e079; ASTER_n36_e082; ASTER_n36_e084; ASTER_n36_e087; ASTER_n36_e090; ASTER_n36_e091; ASTER_n37_e071; ASTER_n37_e072; ASTER_n37_e073; ASTER_n37_e074; ASTER_n37_e075; ASTER_n37_e087; ASTER_n38_e071; ASTER_n38_e072; ASTER_n38_e073; ASTER_n38_e075; ASTER_n38_e096; ASTER_n38_e097; ASTER_n39_e069; ASTER_n39_e070; ASTER_n39_e071; ASTER_n39_e072; ASTER_n39_e073; ASTER_n39_e074; ASTER_n39_e098; ASTER_n40_e074; ASTER_n41_e076; ASTER_n41_e077; ASTER_n41_e078; ASTER_n41_e079; ASTER_n41_e080; ASTER_n42_e074; ASTER_n42_e077; ASTER_n42_e078; ASTER_n42_e079; ASTER_n42_e080; ASTER_n42_e081; ASTER_n42_e082; ASTER_n42_e085; ASTER_n43_e077; ASTER_n43_e083; ASTER_n43_e084; ASTER_n43_e085; ASTER_n43_e086; ASTER_n44_e079; ASTER_n44_e080; ASTER_n44_e083; ASTER_n45_e080; DATE/TIME; Event label; File name; File size; High Mountain Asia; SAT; Satellite remote sensing; Uniform resource locator/link to file |
| url | https://doi.org/10.1594/PANGAEA.876545 |