Evaluation of Subseasonal Drought Forecast Skill over the Coastal Western United States

Author:

Su Lu1,Cao Qian2,Shukla Shraddhanand3,Pan Ming2,Lettenmaier Dennis P.1

Affiliation:

1. a Department of Geography, University of California, Los Angeles, Los Angeles, California

2. b Center for Western Weather and Water Extremes, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California

3. c University of California, Santa Barbara, Santa Barbara, California

Abstract

Abstract Predictions of drought onset and termination at subseasonal (from 2 weeks to 1 month) lead times could provide a foundation for more effective and proactive drought management. We used reforecasts archived in NOAA’s Subseasonal Experiment (SubX) to force the Noah Multiparameterization (Noah-MP), which produced forecasts of soil moisture from which we identified drought levels D0–D4. We evaluated forecast skill of major and more modest droughts, with leads from 1 to 4 weeks, and with particular attention to drought termination and onset. We find usable drought termination and onset forecast skill at leads 1 and 2 weeks for major D0–D2 droughts and limited skill at week 3 for major D0–D1 droughts, with essentially no skill at week 4 regardless of drought severity. Furthermore, for both major and more modest droughts, we find limited skill or no skill for D3–D4 droughts. We find that skill is generally higher for drought termination than for onset for all drought events. We also find that drought prediction skill generally decreases from north to south for all drought events.

Publisher

American Meteorological Society

Subject

Atmospheric Science

Reference84 articles.

1. Soil moisture conditions determine land–atmosphere coupling and drought risk in the northeastern United States;Alessi, M. J.,2022

2. An efficient approach for estimating streamflow forecast skill elasticity;Arnal, L.,2017

3. The NASA hydrological forecast system for food and water security applications;Arsenault, K. R.,2020

4. Developing subseasonal to seasonal climate forecast products for hydrology and water management;Baker, S. A.,2019

5. MetSim: A Python package for estimation and disaggregation of meteorological data;Bennett, A. R.,2020

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3