South Asian Summer Monsoon Rainfall: Origin of Multidecadal Variability/Trends and Investigation of Seasonal Predictability

南亚夏季季风降雨：多年代变率/趋势的起源和季节可预测性的研究

• 批准号: 1439940
• 负责人: Sumant Nigam
• 金额: $ 71.46万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2019-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1439940&HistoricalAwards=false
• 关键词: South; Asian; Summer; Monsoon; Rainfall

The Indo-Gangetic Plain is home to a billion people and is the agricultural heartland of South Asia. Rapid population and economic growth have led to significant land-use land-cover change, aerosol loadings, and greenhouse gas emissions. Regional hydroclimate exhibits substantial - at times, precarious - multidecadal trends: For example, summer rainfall over the Gangetic Plain has declined by 10-15% since the 1950s. The seasonal rainfall is moreover seldom predicted accurately; prediction skill has remained modest and stagnant despite advances in the representation of physical processes, numerical model resolution, and data assimilation.This project has the following goals:(A) To investigate if the steep decline in post-1950s rainfall is from anthropogenic effects, multidecadal natural variability, or both. By revealing the nature of interference between secular change and natural variability, this attribution analysis will help estimate the likelihood of even steeper rainfall decline or some reprieve from drying in future decades. The modeling analysis will uncover the mechanisms through which multidecadal ocean variability influences the South Asian monsoon rainfall. (B) To determine the potential predictability of seasonal summer rainfall over South Asia from a discerning spatiotemporal analysis of 20th-21st century SST and rainfall observations, and rainfall reconstruction from contemporaneous and SST-leading rainfall regressions in an independent period - yielding a quantitative assessment of the SST-based predictability of monsoon rainfall at various seasonal leads. Intercomparison of the key SST-monsoon rainfall links in nature and historical simulations will advance the modeling of monsoon hydroclimate variability in two coupled climate models, viz. the Community Earth System Model(CESM) and the National Oceanic and Atmospheric Administration Geophysical Fluid Dynamics Lab (NOAA GFDL) model.

印度-恒河平原是10亿人口的家园，也是南亚的农业中心地带。快速的人口和经济增长导致了显著的土地利用土地覆盖变化、气溶胶负荷和温室气体排放。区域水文气候表现出实质性的-有时，不稳定的-几十年的趋势：例如，自20世纪50年代以来，恒河平原的夏季降雨量下降了10-15%。此外，季节性降雨很少被准确预测;尽管在物理过程的表示、数值模式分辨率和数据同化方面取得了进展，但预测技术仍然有限和停滞不前。本项目有以下目标：（A）调查20世纪50年代后降雨量的急剧下降是由于人为影响，多年自然变率，还是两者兼而有之。通过揭示长期变化和自然变率之间的干扰性质，这种归因分析将有助于估计未来几十年降雨量下降幅度更大或干旱缓解的可能性。模拟分析将揭示多年海洋变化影响南亚季风降水的机制。(B)通过对20 - 21世纪世纪SST和降雨观测的识别性时空分析，确定南亚地区夏季季节性降雨的潜在可预测性，并通过同期和SST主导的降雨回归在一个独立的时期内重建降雨-对基于SST的季风降雨可预测性进行定量评估。在自然界和历史模拟的关键SST季风降雨联系的相互比较将推进季风水文气候变率在两个耦合的气候模型，即社区地球系统模型（CESM）和国家海洋和大气管理局地球物理流体动力学实验室（NOAA GFDL）模型的建模。