气候变化领域集成服务门户(CCPortal): Satellite Sea Surface Salinity Observations Impact on El Niño/Southern Oscillation Predictions: Case Studies From the NASA GEOS Seasonal Forecast System

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DOI	10.1029/2019JC015788
	Satellite Sea Surface Salinity Observations Impact on El Niño/Southern Oscillation Predictions: Case Studies From the NASA GEOS Seasonal Forecast System
	Hackert E.; Kovach R.M.; Molod A.; Vernieres G.; Borovikov A.; Marshak J.; Chang Y.
发表日期	2020
ISSN	21699275
卷号	125 期号:4
英文摘要	El Niño/Southern Oscillation (ENSO) has far reaching global climatic impacts and so extending useful ENSO forecasts would have great societal benefit. However, one key variable that has yet to be fully exploited within coupled forecast systems is accurate estimation of near-surface ocean salinity. Satellite sea surface salinity (SSS), combined with temperature, help to improve the estimates of ocean density changes and associated near-surface mixing. For the first time, we assess the impact of satellite SSS observations for improving near-surface dynamics within ocean reanalyses and how these initializations impact dynamical ENSO forecasts using NASA's coupled forecast system (GEOS-S2S-2). For all initialization experiments, all available sea level and in situ temperature and salinity observations are assimilated. Separate observing system experiments additionally assimilate Aquarius, SMAP, SMOS, and these data sets combined. We highlight the impact of satellite SSS on ocean reanalyses by comparing experiments with and without the application of SSS assimilation. Next, we compare case studies of coupled forecasts for the big 2015 El Niño, the 2017 La Niña, and the weak El Niño in 2018 that are initialized from GEOS-S2S-2 spring reanalyses that assimilate and withhold along-track SSS. For each of these ENSO-event case studies, assimilation of satellite SSS improves the forecast validation with respect to observed NINO3.4 anomalies (or at least reduces the forecast uncertainty). Satellite SSS assimilation improved characterization of the mixed layer depth leading to more accurate coupled air/sea interaction and better forecasts. These results further underline the value of satellite SSS assimilation into operational forecast systems. ©2020. American Geophysical Union. All Rights Reserved.
英文关键词	data assimilation; ENSO forecasts; GEOS seasonal forecast system; Kelvin wave; mixed layer depth; satellite sea surface salinity
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/186903
作者单位	Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD, United States; Science Systems and Applications, Inc., Lanham, MD, United States; University Corporation for Atmospheric Research, Boulder, CO, United States; Division of Research and Economic Development, NOAA, Boulder, CO, United States; Morgan State University, Baltimore, MD, United States
推荐引用方式 GB/T 7714	Hackert E.,Kovach R.M.,Molod A.,et al. Satellite Sea Surface Salinity Observations Impact on El Niño/Southern Oscillation Predictions: Case Studies From the NASA GEOS Seasonal Forecast System[J],2020,125(4).
APA	Hackert E..,Kovach R.M..,Molod A..,Vernieres G..,Borovikov A..,...&Chang Y..(2020).Satellite Sea Surface Salinity Observations Impact on El Niño/Southern Oscillation Predictions: Case Studies From the NASA GEOS Seasonal Forecast System.Journal of Geophysical Research: Oceans,125(4).
MLA	Hackert E.,et al."Satellite Sea Surface Salinity Observations Impact on El Niño/Southern Oscillation Predictions: Case Studies From the NASA GEOS Seasonal Forecast System".Journal of Geophysical Research: Oceans 125.4(2020).