@misc{SmithBookhagen2018,
  author    = {Smith, Taylor and Bookhagen, Bodo},
  title     = {Using passive microwave data to understand spatio-temporal trends and dynamics in snow-water storage in High Mountain Asia},
  series = {active and passive microwave remote sensing for environmental monitoring II},
  volume    = {10788},
  journal   = {active and passive microwave remote sensing for environmental monitoring II},
  publisher = {SPIE-INT Soc Optical Engineering},
  address   = {Bellingham},
  isbn      = {978-1-5106-2160-2},
  issn      = {0277-786X},
  doi       = {10.1117/12.2323827},
  pages     = {8},
  year      = {2018},
  abstract  = {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-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)},
  language  = {en}
}