气候变化领域集成服务门户(CCPortal): Seasonal Forecasting Skill of Sea-Level Anomalies in a Multi-Model Prediction Framework

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DOI	10.1029/2020JC017060
	Seasonal Forecasting Skill of Sea-Level Anomalies in a Multi-Model Prediction Framework
	Long X.; Widlansky M.J.; Spillman C.M.; Kumar A.; Balmaseda M.; Thompson P.R.; Chikamoto Y.; Smith G.A.; Huang B.; Shin C.-S.; Merrifield M.A.; Sweet W.V.; Leuliette E.; Annamalai H.S.; Marra J.J.; Mitchum G.
发表日期	2021
ISSN	21699275
卷号	126 期号:6
英文摘要	Coastal high water level events are increasing in frequency and severity as global sea-levels rise, and are exposing coastlines to risks of flooding. Yet, operational seasonal forecasts of sea-level anomalies are not made for most coastal regions. Advancements in forecasting climate variability using coupled ocean-atmosphere global models provide the opportunity to predict the likelihood of future high water events several months in advance. However, the skill of these models to forecast seasonal sea-level anomalies has not been fully assessed, especially in a multi-model framework. Here, we construct a 10-model ensemble of retrospective forecasts with future lead times of up to 11 months. We compare predicted sea levels from bias-corrected forecasts with 20 years of observations from satellite-based altimetry and shore-based tide gauges. Forecast skill, as measured by anomaly correlation, tends to be highest in the tropical and subtropical open oceans, whereas the skill is lower in the higher latitudes and along some continental coasts. For most locations, multi-model averaging produces forecast skill that is comparable to or better than the best performing individual model. We find that the most skillful predictions typically come from forecast systems with more accurate initializations of sea level, which is generally achieved by assimilating altimetry data. Having relatively higher horizontal resolution in the ocean is also beneficial, as such models seem to better capture dynamical processes necessary for successful forecasts. The multi-model assessment suggests that skillful seasonal sea-level forecasts are possible in many, though not all, parts of the global ocean. © 2021. American Geophysical Union. All Rights Reserved.
英文关键词	ensemble forecast; forecast skill; sea level; seasonal forecast
语种	英语
来源期刊	Journal of Geophysical Research: Oceans
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/186270
作者单位	Joint Institute for Marine and Atmospheric Research, School of Ocean and Earth Science and Technology, University of Hawai'i at Mānoa, Honolulu, HI, United States; Bureau of Meteorology, Melbourne, VIC, Australia; Climate Prediction Center, NCEP/NWS/NOAA, College Park, MD, United States; European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom; Department of Oceanography, University of Hawai'i at Mānoa, Honolulu, HI, United States; Department of Plants, Soils and Climate, Utah State University, Logan, UT, United States; Department of Atmospheric, Oceanic, and Earth Sciences, College of Science, George Mason University, Fairfax, VA, United States; Scripps Institution of Oceanography, University of California, San Diego, CA, United States; NOAA/National Ocean Service, Silver Spring, MD, United States; NOAA/NWS NCWCP Laboratory for Satellite Altimetry, College Park, MD, United States; International Pacific Research Center, University of Hawai'i at Mānoa, Honolulu, HI, United States; NOAA/N...
推荐引用方式 GB/T 7714	Long X.,Widlansky M.J.,Spillman C.M.,et al. Seasonal Forecasting Skill of Sea-Level Anomalies in a Multi-Model Prediction Framework[J],2021,126(6).
APA	Long X..,Widlansky M.J..,Spillman C.M..,Kumar A..,Balmaseda M..,...&Mitchum G..(2021).Seasonal Forecasting Skill of Sea-Level Anomalies in a Multi-Model Prediction Framework.Journal of Geophysical Research: Oceans,126(6).
MLA	Long X.,et al."Seasonal Forecasting Skill of Sea-Level Anomalies in a Multi-Model Prediction Framework".Journal of Geophysical Research: Oceans 126.6(2021).