globalchange  > 影响、适应和脆弱性
DOI: 10.1002/2017MS001129
Scopus记录号: 2-s2.0-85043275047
论文题名:
Role of Ocean Initial Conditions to Diminish Dry Bias in the Seasonal Prediction of Indian Summer Monsoon Rainfall: A Case Study Using Climate Forecast System
作者: Koul V; , Parekh A; , Srinivas G; , Kakatkar R; , Chowdary J; S; , Gnanaseelan C
刊名: Journal of Advances in Modeling Earth Systems
ISSN: 19422466
出版年: 2018
卷: 10, 期:3
起始页码: 603
结束页码: 616
语种: 英语
英文关键词: Atmospheric temperature ; Atmospheric thermodynamics ; Feedback ; Forecasting ; Hydrographic surveys ; Moisture ; Oceanography ; Troposphere ; Coupled models ; Data assimilation ; Indian summer monsoon ; Initial conditions ; Seasonal forecasts ; Rain ; air-sea interaction ; Argo ; atmospheric forcing ; climate modeling ; climate prediction ; data assimilation ; environmental conditions ; hindcasting ; moisture ; monsoon ; rainfall ; salinity ; seasonal variation ; summer ; temperature ; temperature gradient ; thermal structure ; weather forecasting ; India
英文摘要: Coupled models tend to underestimate Indian summer monsoon (ISM) rainfall over most of the Indian subcontinent. Present study demonstrates that a part of dry bias is arising from the discrepancies in Oceanic Initial Conditions (OICs). Two hindcast experiments are carried out using Climate Forecast System (CFSv2) for summer monsoons of 2012–2014 in which two different OICs are utilized. With respect to first experiment (CTRL), second experiment (AcSAL) differs by two aspects: usage of high-resolution atmospheric forcing and assimilation of only ARGO observed temperature and salinity profiles for OICs. Assessment of OICs indicates that the quality of OICs is enhanced due to assimilation of actual salinity profiles. Analysis reveals that AcSAL experiment showed 10% reduction in the dry bias over the Indian land region during the ISM compared to CTRL. This improvement is consistently apparent in each month and is highest for June. The better representation of upper ocean thermal structure of tropical oceans at initial stage supports realistic upper ocean stability and mixing. Which in fact reduced the dominant cold bias over the ocean, feedback to air-sea interactions and land sea thermal contrast resulting better representation of monsoon circulation and moisture transport. This reduced bias of tropospheric moisture and temperature over the Indian land mass and also produced better tropospheric temperature gradient over land as well as ocean. These feedback processes reduced the dry bias in the ISM rainfall. Study concludes that initializing the coupled models with realistic OICs can reduce the underestimation of ISM rainfall prediction. © 2018. The Authors.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/75634
Appears in Collections:影响、适应和脆弱性
气候变化与战略

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作者单位: Climate Variability and Data Assimilation Research, Indian Institute of Tropical Meteorology, Pune, India; Department of Atmospheric and Space Sciences, Savitribai Phule Pune University, Pune, India; Climate Modelling, Institute of Oceanography, Universität Hamburg, Hamburg, Germany; International Max Planck Research School on Earth System Modelling, Max Planck Institute for Meteorology, Hamburg, Germany

Recommended Citation:
Koul V,, Parekh A,, Srinivas G,et al. Role of Ocean Initial Conditions to Diminish Dry Bias in the Seasonal Prediction of Indian Summer Monsoon Rainfall: A Case Study Using Climate Forecast System[J]. Journal of Advances in Modeling Earth Systems,2018-01-01,10(3)
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