气候变化领域集成服务门户(CCPortal): Improving australian rainfall prediction using sea surface salinity

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DOI	10.1175/JCLI-D-20-0625.1
	Improving australian rainfall prediction using sea surface salinity
	Rathore S.; Bindoff N.L.; Ummenhofer C.C.; Phillips H.E.; Feng M.; Mishra M.
发表日期	2021
ISSN	08948755
起始页码	2473
结束页码	2490
卷号	34 期号:7
英文摘要	This study uses sea surface salinity (SSS) as an additional precursor for improving the prediction of summer [December-February (DJF)] rainfall over northeastern Australia. From a singular value decomposition between SSS of prior seasons and DJF rainfall, we note that SSS of the Indo-Pacific warm pool region [SSSP (150°E-165° W and 10°S-10°N) and SSSI (50°-95°E and 10°S-10°N)] covaries with Australian rainfall, particularly in the northeast region. Composite analysis that is based on high or low SSS events in the SSSP and SSSI regions is performed to understand the physical links between the SSS and the atmospheric moisture originating from the regions of anomalously high or low, respectively, SSS and precipitation over Australia. The composites show the signature of co-occurring La Niña and negative Indian Ocean dipole with anomalously wet conditions over Australia and conversely show the signature of co-occurring El Niño and positive Indian Ocean dipole with anomalously dry conditions there. During the high SSS events of the SSSP and SSSI regions, the convergence of incoming moisture flux results in anomalously wet conditions over Australia with a positive soil moisture anomaly. Conversely, during the low SSS events of the SSSP and SSSI regions, the divergence of incoming moisture flux results in anomalously dry conditions over Australia with a negative soil moisture anomaly. We show from the random-forest regression analysis that the local soil moisture, El Niño-Southern Oscillation (ENSO), and SSSP are the most important precursors for the northeast Australian rainfall whereas for the Brisbane region ENSO, SSSP, and the Indian Ocean dipole are the most important. The prediction of Australian rainfall using random-forest regression shows an improvement by including SSS from the prior season. This evidence suggests that sustained observations of SSS can improve the monitoring of the Australian regional hydrological cycle. © 2021 American Meteorological Society.
英文关键词	ENSO; Flood events; Hydrologic cycle; Machine learning; Rainfall; Salinity; Seasonal forecasting; Soil moisture
语种	英语
scopus关键词	Atmospheric pressure; Climatology; Decision trees; Forecasting; Random forests; Singular value decomposition; Soil moisture; Surface waters; Atmospheric moisture; Australian rainfall; Composite analysis; Hydrological cycles; Indian Ocean dipole; Pacific warm pool regions; Sea surface salinity; Southern oscillation; Rain; atmospheric moisture; climate prediction; covariance analysis; El Nino; El Nino-Southern Oscillation; flood; hydrological cycle; Indian Ocean Dipole; machine learning; rainfall; sea surface salinity; seasonal variation; singular value decomposition; soil moisture; summer; Australia; Brisbane; Indian Ocean; Queensland
来源期刊	Journal of Climate
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/178666
作者单位	Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, TAS, Australia; ARC Centre of Excellence for Climate System Science, Hobart, TAS, Australia; ARC Centre of Excellence for Climate Extremes, Sydney, NSW, Australia; CSIRO Oceans and Atmosphere, Hobart, TAS, Australia; Australian Antarctic Program Partnership, Hobart, TAS, Australia; Woods Hole Oceanographic Institution, Woods Hole, MA, United States; CSIRO Oceans and Atmosphere, Indian Ocean Marine Research Centre, Crawley, WA, Australia; Centre for Southern Hemisphere Oceans Research, CSIRO, Hobart, TAS, Australia; Centre for Oceans, Rivers, Atmosphere and Land Sciences, Indian Institute of Technology Kharagpur, Kharagpur, India
推荐引用方式 GB/T 7714	Rathore S.,Bindoff N.L.,Ummenhofer C.C.,et al. Improving australian rainfall prediction using sea surface salinity[J],2021,34(7).
APA	Rathore S.,Bindoff N.L.,Ummenhofer C.C.,Phillips H.E.,Feng M.,&Mishra M..(2021).Improving australian rainfall prediction using sea surface salinity.Journal of Climate,34(7).
MLA	Rathore S.,et al."Improving australian rainfall prediction using sea surface salinity".Journal of Climate 34.7(2021).