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Using passive microwave data to understand spatio-temporal trends and dynamics in snow-water storage in High Mountain Asia

  • High Mountain Asia provides water for more than a billion downstream users. Many catchments receive the majority of their yearly water budget in the form of snow - the vast majority of which is not monitored by sparse weather networks. We leverage passive microwave data from the SSMI series of satellites (SSMI, SSMI/S, 1987-2016), reprocessed to 3.125 km resolution, to examine trends in the volume and spatial distribution of snow-water equivalent (SWE) in the Indus Basin. We find that the majority of the Indus has seen an increase in snow-water storage. There exists a strong elevation-trend relationship, where high-elevation zones have more positive SWE trends. Negative trends are confined to the Himalayan foreland and deeply-incised valleys which run into the Upper Indus. This implies a temperature-dependent cutoff below which precipitation increases are not translated into increased SWE. Earlier snowmelt or a higher percentage of liquid precipitation could both explain this cutoff.(1) Earlier work 2 found a negative snow-waterHigh Mountain Asia provides water for more than a billion downstream users. Many catchments receive the majority of their yearly water budget in the form of snow - the vast majority of which is not monitored by sparse weather networks. We leverage passive microwave data from the SSMI series of satellites (SSMI, SSMI/S, 1987-2016), reprocessed to 3.125 km resolution, to examine trends in the volume and spatial distribution of snow-water equivalent (SWE) in the Indus Basin. We find that the majority of the Indus has seen an increase in snow-water storage. There exists a strong elevation-trend relationship, where high-elevation zones have more positive SWE trends. Negative trends are confined to the Himalayan foreland and deeply-incised valleys which run into the Upper Indus. This implies a temperature-dependent cutoff below which precipitation increases are not translated into increased SWE. Earlier snowmelt or a higher percentage of liquid precipitation could both explain this cutoff.(1) Earlier work 2 found a negative snow-water storage trend for the entire Indus catchment over the time period 1987-2009 (-4 x 10(-3) mm/yr). In this study based on an additional seven years of data, the average trend reverses to 1.4 x 10(-3). This implies that the decade since the mid-2000s was likely wetter, and positively impacted long-term SWE trends. This conclusion is supported by an analysis of snowmelt onset and end dates which found that while long-term trends are negative, more recent (since 2005) trends are positive (moving later in the year).(3)zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Taylor SmithORCiDGND, Bodo BookhagenORCiDGND
DOI:https://doi.org/10.1117/12.2323827
ISBN:978-1-5106-2160-2
ISSN:0277-786X
ISSN:1996-756X
Titel des übergeordneten Werks (Englisch):active and passive microwave remote sensing for environmental monitoring II
Verlag:SPIE-INT Soc Optical Engineering
Verlagsort:Bellingham
Publikationstyp:Sonstiges
Sprache:Englisch
Jahr der Erstveröffentlichung:2018
Erscheinungsjahr:2018
Datum der Freischaltung:07.03.2022
Freies Schlagwort / Tag:Climate Change; High Mountain Asia; Passive Microwave; Snow
Band:10788
Seitenanzahl:8
Fördernde Institution:State of Brandenburg (Germany) through the Ministry of Science and Education; StRATEGy program (DFG IRTG2018)
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften
DDC-Klassifikation:5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften
Peer Review:Referiert
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