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Title: Potential for western US seasonal snowpack prediction

Abstract

Western US snowpack—snow that accumulates on the ground in the mountains—plays a critical role in regional hydroclimate and water supply, with 80% of snowmelt runoff being used for agriculture. While climate projections provide estimates of snowpack loss by the end of the century and weather forecasts provide predictions of weather conditions out to 2 weeks, less progress has been made for snow predictions at seasonal timescales (months to 2 years), crucial for regional agricultural decisions (e.g., plant choice and quantity). Seasonal predictions with climate models first took the form of El Niño predictions 3 decades ago, with hydroclimate predictions emerging more recently. While the field has been focused on single-season predictions (3 months or less), we are now poised to advance our predictions beyond this timeframe. Utilizing observations, climate indices, and a suite of global climate models, we demonstrate the feasibility of seasonal snowpack predictions and quantify the limits of predictive skill 8 months in advance. This physically based dynamic system outperforms observation-based statistical predictions made on July 1 for March snowpack everywhere except the southern Sierra Nevada, a region where prediction skill is nonexistent for every predictor presently tested. Additionally, in the absence of externally forced negative trends inmore » snowpack, narrow maritime mountain ranges with high hydroclimate variability pose a challenge for seasonal prediction in our present system; natural snowpack variability may inherently be unpredictable at this timescale. This work highlights present prediction system successes and gives cause for optimism for developing seasonal predictions for societal needs.« less

Authors:
ORCiD logo; ORCiD logo; ; ; ; ; ; ; ORCiD logo;
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1417723
Grant/Contract Number:  
CERC-WET/CEC 300-15-006
Resource Type:
Published Article
Journal Name:
Proceedings of the National Academy of Sciences of the United States of America
Additional Journal Information:
Journal Name: Proceedings of the National Academy of Sciences of the United States of America Journal Volume: 115 Journal Issue: 6; Journal ID: ISSN 0027-8424
Publisher:
Proceedings of the National Academy of Sciences
Country of Publication:
United States
Language:
English

Citation Formats

Kapnick, Sarah B., Yang, Xiaosong, Vecchi, Gabriel A., Delworth, Thomas L., Gudgel, Rich, Malyshev, Sergey, Milly, P. C. D., Shevliakova, Elena, Underwood, Seth, and Margulis, Steven A. Potential for western US seasonal snowpack prediction. United States: N. p., 2018. Web. doi:10.1073/pnas.1716760115.
Kapnick, Sarah B., Yang, Xiaosong, Vecchi, Gabriel A., Delworth, Thomas L., Gudgel, Rich, Malyshev, Sergey, Milly, P. C. D., Shevliakova, Elena, Underwood, Seth, & Margulis, Steven A. Potential for western US seasonal snowpack prediction. United States. doi:10.1073/pnas.1716760115.
Kapnick, Sarah B., Yang, Xiaosong, Vecchi, Gabriel A., Delworth, Thomas L., Gudgel, Rich, Malyshev, Sergey, Milly, P. C. D., Shevliakova, Elena, Underwood, Seth, and Margulis, Steven A. Mon . "Potential for western US seasonal snowpack prediction". United States. doi:10.1073/pnas.1716760115.
@article{osti_1417723,
title = {Potential for western US seasonal snowpack prediction},
author = {Kapnick, Sarah B. and Yang, Xiaosong and Vecchi, Gabriel A. and Delworth, Thomas L. and Gudgel, Rich and Malyshev, Sergey and Milly, P. C. D. and Shevliakova, Elena and Underwood, Seth and Margulis, Steven A.},
abstractNote = {Western US snowpack—snow that accumulates on the ground in the mountains—plays a critical role in regional hydroclimate and water supply, with 80% of snowmelt runoff being used for agriculture. While climate projections provide estimates of snowpack loss by the end of the century and weather forecasts provide predictions of weather conditions out to 2 weeks, less progress has been made for snow predictions at seasonal timescales (months to 2 years), crucial for regional agricultural decisions (e.g., plant choice and quantity). Seasonal predictions with climate models first took the form of El Niño predictions 3 decades ago, with hydroclimate predictions emerging more recently. While the field has been focused on single-season predictions (3 months or less), we are now poised to advance our predictions beyond this timeframe. Utilizing observations, climate indices, and a suite of global climate models, we demonstrate the feasibility of seasonal snowpack predictions and quantify the limits of predictive skill 8 months in advance. This physically based dynamic system outperforms observation-based statistical predictions made on July 1 for March snowpack everywhere except the southern Sierra Nevada, a region where prediction skill is nonexistent for every predictor presently tested. Additionally, in the absence of externally forced negative trends in snowpack, narrow maritime mountain ranges with high hydroclimate variability pose a challenge for seasonal prediction in our present system; natural snowpack variability may inherently be unpredictable at this timescale. This work highlights present prediction system successes and gives cause for optimism for developing seasonal predictions for societal needs.},
doi = {10.1073/pnas.1716760115},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
number = 6,
volume = 115,
place = {United States},
year = {2018},
month = {1}
}

Journal Article:
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DOI: 10.1073/pnas.1716760115

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