气候变化异常和空气污染双重胁迫下的淮河流域稻麦轮作区能量平衡、水分循环和碳收支研究

The dual effects of climate change anomalies and air pollution increase the complexity of the land surface process in the rice wheat rotation region of the Huaihe basin. This project aims to study the energy balance, the water cycle, and the carbon budget of the Huaihe River Basin by conducting the intensified observations. On this basis, we will establish a high quality four-dimensional database by integration and assimilation with data quality control technology and a variety of mathematical statistics methods. We will investigate the impact of climate anomalies and air pollution on energy balance, water cycle and carbon budget under the rice wheat cropping system in Huaihe River Basin and explore water use efficiency and the key parameters required by numerical simulation of land surface process and (surface albedo, surface roughness, thermal aerodynamic roughness, soil thermal conductivity, thermal diffusivity and volumetric heat capacity). The purpose of this project is to better understand the current characteristics of energy balance, water cycle, carbon budget and water use efficiency in Huaihe basin, and to provide scientific basis and data support for weather prediction, climate assessment and carbon emissions assessment.

气候变化异常事件和空气污染的双重影响增加了淮河流域稻麦轮作区陆面过程的复杂性。本项目拟以淮河流域能量平衡、水分循坏和碳收支过程为研究对象，实施强化观测试验。在此基础上，运用数据质量控制技术和各种数学统计方法对观测数据进行融合和同化，建立一个高质量的四维数据集；研究气候异常事件和空气污染双重胁迫下的淮河流域稻麦轮作区能量平衡、水分循环及碳收支特征；探究水利用率以及陆面过程数值模拟必需的关键参数（地表反照率、地表空气动力粗糙度、热力粗糙度、土壤热传导率、热扩散率和体积热容量）。本项目旨在进一步认识当前淮河流域能量分配、水分循环、碳收支过程和水利用率特征，为天气预报和气候评估以及碳排放评估提供科学依据和数据支撑。

气候变化异常事件和空气污染的双重影响增加了淮河流域稻麦轮作区陆面过程的复杂性。本项目通过在淮河流域开展外场观测试验，运用数据质量控制技术和各种数学统计方法对观测数据进行融合和同化，建立一个高质量的四维数据集。基于此数据集，本项目利用机器人工智能的区域升尺度方法，构建农业CO2通量虚拟站点和评估方法并用其来校正MODIS产品，探究农业碳通量时空分布及其与气象条件的关系；研究了气候异常事件和空气污染双重胁迫下的淮河流域稻麦轮作区能量平衡、水分循环及碳收支特征；定量描述水利用率以及陆面过程数值模拟必需的关键参数（地表反照率、地表空气动力粗糙度、热力粗糙度、土壤热传导率、热扩散率和体积热容量）。本项目加深了对于淮河流域能量分配、水分循环、碳收支过程和水利用率特征的理解，为天气预报和气候评估以及碳排放评估提供科学依据和数据支撑。