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，是南亚的农业中心地带。人口和经济的快速增长导致了土地利用、土地覆盖的显著变化、气溶胶负荷和温室气体排放。区域水文气候表现出大量的（有时是不稳定的）多年代际趋势：例如，自20世纪50年代以来，恒河平原的夏季降雨量减少了10-15%。此外，季节性降雨很少得到准确预测；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步，但预测技能仍然保持适度和停滞不前。本项目有以下目标：(A)调查1950年代以后降雨量的急剧下降是来自人为影响、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干扰的本质，这种归因分析将有助于估计未来几十年降雨量更急剧下降或干旱有所缓解的可能性。模拟分析将揭示多年代际海洋变率影响南亚季风降雨的机制。(B)通过对20 -21世纪海温和降雨观测的清晰时空分析，以及从同期和海温领先的独立时期降水回归中重建的降水，确定南亚季节性夏季降水的潜在可预测性，从而对不同季节领先的基于海温的季风降水可预测性进行定量评估。通过对比海温-季候风在自然和历史模拟中的关键环节，将进一步推进两个耦合气候模式（社区地球系统模式（CESM）和美国国家海洋和大气管理局地球物理流体动力学实验室（NOAA GFDL）模式）对季风水文气候变率的模拟。