Articles | Volume 12, issue 5
https://doi.org/10.5194/tc-12-1579-2018
https://doi.org/10.5194/tc-12-1579-2018
Research article
 | 
03 May 2018
Research article |  | 03 May 2018

Using machine learning for real-time estimates of snow water equivalent in the watersheds of Afghanistan

Edward H. Bair, Andre Abreu Calfa, Karl Rittger, and Jeff Dozier

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Short summary
In Afghanistan, almost no snow measurements exist. Operational estimates use measurements from satellites, but all have limitations. We have developed a satellite-based technique called reconstruction that accurately estimates the snowpack retrospectively. To solve the problem of estimating today's snowpack, we used machine learning, trained on our reconstructed snow estimates, using predictors that are available today. Our results show low errors, demonstrating the utility of this approach.