Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1073/pnas.1716760115 |
Potential for western US seasonal snowpack prediction | |
Kapnick, Sarah B.1; Yang, Xiaosong1,2; Vecchi, Gabriel A.3,4; Delworth, Thomas L.1; Gudgel, Rich1; Malyshev, Sergey1,5; Milly, P. C. D.6; Shevliakova, Elena1,4; Underwood, Seth1; Margulis, Steven A.7 | |
2018-02-06 | |
发表期刊 | PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA |
ISSN | 0027-8424 |
出版年 | 2018 |
卷号 | 115期号:6页码:1180-1185 |
文章类型 | Article |
语种 | 英语 |
国家 | USA |
英文摘要 | 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 Nino 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. |
英文关键词 | cryosphere seasonal prediction climate water snowpack |
领域 | 地球科学 ; 气候变化 ; 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000424191300041 |
WOS关键词 | DECLINING MOUNTAIN SNOWPACK ; UNITED-STATES ; NORTH-AMERICA ; CLIMATE MODEL ; DATA ASSIMILATION ; FORECAST SKILL ; EL-NINO ; PRECIPITATION ; VARIABILITY ; CALIFORNIA |
WOS类目 | Multidisciplinary Sciences |
WOS研究方向 | Science & Technology - Other Topics |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/205043 |
专题 | 地球科学 资源环境科学 气候变化 |
作者单位 | 1.NOAA, Geophys Fluid Dynam Lab, Princeton, NJ 08540 USA; 2.Univ Corp Atmospher Res, Cooperat Programs Adv Earth Syst Sci, Boulder, CO 80307 USA; 3.Princeton Univ, Geosci, Princeton, NJ 08544 USA; 4.Princeton Univ, Princeton Environm Inst, Princeton, NJ 08544 USA; 5.Princeton Univ, Ecol & Evolutionary Biol, Princeton, NJ 08540 USA; 6.US Geol Survey, Integrated Modeling & Predict Div, Water Mission Area, Princeton, NJ 08540 USA; 7.Univ Calif Los Angeles, Civil & Environm Engn, Los Angeles, CA 90095 USA |
推荐引用方式 GB/T 7714 | Kapnick, Sarah B.,Yang, Xiaosong,Vecchi, Gabriel A.,et al. Potential for western US seasonal snowpack prediction[J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA,2018,115(6):1180-1185. |
APA | Kapnick, Sarah B..,Yang, Xiaosong.,Vecchi, Gabriel A..,Delworth, Thomas L..,Gudgel, Rich.,...&Margulis, Steven A..(2018).Potential for western US seasonal snowpack prediction.PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA,115(6),1180-1185. |
MLA | Kapnick, Sarah B.,et al."Potential for western US seasonal snowpack prediction".PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 115.6(2018):1180-1185. |
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