多源卫星臭氧观测的高效全球四维变分同化技术研究

项目名称： 多源卫星臭氧观测的高效全球四维变分同化技术研究

项目编号： No.41475094

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 天文学、地球科学

项目作者： 曹小群

作者单位： 中国人民解放军国防科技大学

项目金额： 85万元

中文摘要： 近年来在轨运行的卫星臭氧遥感仪不断增加，丰富的臭氧观测不但能有效弥补平流层等区域观测信息的不足，而且对提高数值天气预报质量具有巨大潜力。虽然许多业务预报中心已成功实现臭氧资料同化，并取得一定正效果；但是仍存在一系列急需解决的科学难题。本项目将开展多源卫星臭氧资料全球四维变分同化的关键技术研究，主要包括：大气成分资料同化新方法、臭氧不同尺度背景误差特征刻画、基于混合范数的观测质量控制、自适应偏差订正、臭氧化学输送模式、平流层物理和化学参数化方案以及卫星观测算子的切线性/伴随模式等。目标是实现不同类型卫星(包括风云三号)臭氧观测的最优融合和高效同化，提高高分辨率全球数值天气预报系统的分析场质量和中期天气预报能力，重点挖掘臭氧同化在改进中高层风场和对流层台风等高影响天气预报上的潜力。本项目的研究是对卫星资料同化方法的进一步探索，对资料同化理论完善和业务同化系统研制都有重要实用价值。

中文关键词： 四维变分资料同化；卫星臭氧资料；化学输送模式；质量控制；偏移误差订正

英文摘要： In recent years,the number of ozone instruments onboard satellite increases continuously. They can not only provide abundant information in many areas，such as the stratosphere and ocean， where the conventional observation is usually scarce, but also have huge potential for improving the accuracy of numerical weather predtiction (NWP). Although many operational NWP centers have been successful in satellite ozone data assimilation and achieved some positive results，but it is still in face of a great deal of scientific challenges in the ozone data assimilation community. This study will focus on the key tecnologies for global four-dimensional variational data assimilation (4DVAR) of multi-source satellite ozone observations, mainly including the innovative method of atmospheric constituent data assimilation, exact description of background error characteristic for different scale, the new observation quality control method based on L1/L2 mixed norms, self-adaptive variational bias correction method, chemistry transport model for ozone,the tangent and adjoint programs of stratospheric physical and chemistry parameterization schemes, the new radiative transfer models for ozone instruments, and so on. The target is to improve the analysis quality and medium-range forecasting ability of high-resolution global NWP system by optimal combination and high-efficient assimilation of multi-source satellite ozone data (includes two FY-3 ozone instruments), and especially to discover the potential to improve the accuracy of typhoon forecasts and wind predictions in the middle and upper atmosphere. Therefore, this study is of importance for further developments of satellite data assmilation method, and has great practical values for both the completeness of data assmilation theory and construction of operational 4DVAR systems.

英文关键词： four-dimensional variational data assimilation;satellite ozone data;chemistry transport model;quality control;displacement error correction