CLM4.5模式多源卫星遥感土壤湿度数据同化及其对亚洲陆地水循环模拟的影响研究

Water resources play an important role in the development of human society, economic, and ecological sustainability. However, climate change and anthropogenic activities exert great impact on the global or regional hydrological cycle. This project aims to investigate the terrestrial hydrological cycle system over Asia. The CESM1.2 (Community Earth System Model, Version 1.2) offline land surface model, CLM4.5 (Community Land Model, Version 4.5) is adopted to construct the terrestrial hydrological cycling system over Asia based on the optimum selection of rainfall-runoff parameterization scheme and atmospheric forcing data. To improve the performance of CLM4.5 modeling, multi-sources of remote sensing soil moisture data are used to develop the CLM4.5 soil moisture data assimilation system with optimum data assimilation techniques. The impact of CLM4.5 model data assimilation on the monitoring of terrestrial hydrological cycle is evaluated with the in-situ observed hydroclimatological data, reanalysis data, remote sensing data products and related research. The hydroclimatological variables from the atmospheric forcing data and simulation of the optimum CLM4.5 model with remote sensing data assimilation are selected to evaluate the impact of climate change and anthropogenic activities on terrestrial hydrological cycle over Asia. According to the overviews of land-atmosphere water and energy exchange mechanisms, multi-variable inspection and attribution analysis methods are adopted to analyze the temporal and spatial characteristics of terrestrial hydrological cycle change and their response to the changes of climate variables, diagnose the land-atmosphere coupling strength, and evaluate the influence of climate change and anthropogenic activities on the terrestrial hydrological cycle and water resources.This project may improve the recognition of spatial and temporal distribution of water resources under environmental changes, and therefore scientifically contribute to the achievement of sustainable development strategy of water resources.

水资源对人类社会、经济和生态可持续性发展影响深远。然而，气候变化和人类活动对全球及区域水循环产生重大影响。本项目以亚洲陆地水循环系统为研究对象，采用CESM1.2离线陆面过程模式CLM4.5，通过产汇流方案优选，大气驱动数据改进，构建适应于亚洲陆地水循环模拟的陆面水文模式。融合多源卫星遥感数据，优选数据同化方案，发展陆面水文模式多源卫星遥感土壤湿度数据同化系统。结合观测数据、再分析数据、卫星遥感数据和现有研究成果，对比分析模式数据同化对亚洲陆地水循环模拟的影响。基于模式数据同化输入输出水文气象要素数据序列，通过多要素检测与归因分析，从陆-气水量能量交换的观点，检测亚洲水循环时空演变特征及其对气候变化的响应，诊断陆气耦合强度，评估气候变化和人类活动对亚洲水循环和水文水资源的影响。该研究旨在提高对变化环境下水资源时空分布的认知，为科学制定变化环境下水资源可持续发展战略提供理论依据。

水资源对人类社会、经济和生态可持续性发展影响深远。然而，气候变化和人类活动对全球及区域水循环产生重大影响。本项目以亚洲陆地水循环系统为研究对象，采用CESM1.2离线陆面过程模式CLM4.5，通过产汇流方案优选，大气驱动数据改进，构建了适应于亚洲陆地水循环模拟的陆面水文模式CLM4.5-VIC模式。融合AMSR-E土壤湿度卫星遥感数据，选用集合卡尔曼滤波技术，构建陆面过程模式CLM4.5-VIC-DA数据同化系统，发展陆面水文模式多源卫星遥感土壤湿度数据同化系统。结合观测数据、再分析数据、卫星遥感数据和现有研究成果，对比分析模式数据同化对亚洲陆地水循环模拟的影响。CLM4.5-VIC-DA模式可有效改进模式在亚洲区域的模拟准确性，其中显著改善区域主要位于中高纬度和印度等气候过渡带上。在项目执行中，将数据同化技术拓展应用至短期农业干旱监测预报预警及作物产量模式数值模拟中，研究表明数据同化技术具有普适性，可有效提高农业干旱监测预报预警的准确性及作物产量的预报精度。该项目中构建的陆面水文模式多源卫星遥感数据同化系统适应于不同尺度陆面水文循环模拟，有效提高对变化环境下水资源时空分布的认知，为科学制定变化环境下水资源可持续发展战略提供理论依据。此外，构建的农业干旱监测预报预警同化系统及作物产量模式数据同化系统可为应对变化环境下粮食产量危机提供风险决策依据，服务社会经济可持续发展。