本文已被:浏览 507次 下载 1962次
投稿时间:2022-02-08 修订日期:2022-02-28
投稿时间:2022-02-08 修订日期:2022-02-28
中文摘要: 高质量的水文气象观测数据是开展气象和水文灾害监测、预报预警及长期气候变化趋势分析的基本支撑。以降水等水分循环基本要素为重点,简要概述部分单源的观测数据集、二维/三维的融合分析产品和多维的再分析产品的研发进展,及其在水文气象监测预报中的应用。分析表明:气象和水文数据是地球系统中水分循环的最重要体现,二者的有效汇聚和协同质量控制,能更有效地促进其在地球系统模式各分量中的应用;经过多源数据融合分析和同化分析形成的多尺度、高精度、高时效、时空连续的格点化分析场,是智能网格天气预报和气候预测的“零时刻”起点,已经成为无缝隙预报业务的组成部分;经过历史数据同化分析产出的长序列大气、陆面等再分析产品,是气候变化演变评估和监测的重要保障,其应用价值远超观测数据本身。
中文关键词: 水文气象观测,质量控制,数据融合分析,再分析
Abstract:High-quality hydrometeorological observation data are the base for the monitoring, forecasting, prediction of hydrometeorological hazards, and also the basic support for long-term climate trend analysis. Focusing on the fundamental elements such as precipitation of water cycle, this paper summarizes the great progress in developing hydrometeorological observation datasets, two and three dimensional fusion analysis products, and multi-dimensional reanalysis products as well as their application in hydrological and climate monitoring and forecasting. The analysis shows that meteorological and hydrological data are two most important embodiments of water cycle in the earth system. Their effective integration and collaborative quality control can effectively promote their application in various components of the earth system model. Produced through intensive data processing such as data fusion analysis and assimilation analysis of multi-source earth observation data, the gridded analysis products with multi spatiotemporal scale, high precision, high timeliness and continuous space-time are used to be the initial points of intelligent grid forecasting and climate prediction, having become an integral part of seamless fine gridded forecasting operation. The global long-series atmospheric and land surface reanalysis products produced by assimilation of historical observational data play important roles in the assessment and monitoring of long-term evolution of climate change, and their application values are far beyond the observation data itself.
文章编号: 中图分类号: 文献标志码:
基金项目:国家自然科学基金重大项目(42090033)资助
作者 | 单位 |
周自江 | 国家气象信息中心,北京 100081 |
曹丽娟 | 国家气象信息中心,北京 100081 |
廖捷 | 国家气象信息中心,北京 100081 |
谷军霞 | 国家气象信息中心,北京 100081 |
张涛 | 国家气象信息中心,北京 100081 |
潘旸 | 国家气象信息中心,北京 100081 |
引用文本:
周自江,曹丽娟,廖捷,谷军霞,张涛,潘旸,2022.水文气象信息概述:观测、融合与再分析[J].气象,48(3):272-283.
ZHOU Zijiang,CAO Lijuan,LIAO Jie,GU Junxia,ZHANG Tao,PAN Yang,2022.Overview of Hydrometeorological Information:Obeservation, Data Fusion and Reanalysis[J].Meteor Mon,48(3):272-283.
周自江,曹丽娟,廖捷,谷军霞,张涛,潘旸,2022.水文气象信息概述:观测、融合与再分析[J].气象,48(3):272-283.
ZHOU Zijiang,CAO Lijuan,LIAO Jie,GU Junxia,ZHANG Tao,PAN Yang,2022.Overview of Hydrometeorological Information:Obeservation, Data Fusion and Reanalysis[J].Meteor Mon,48(3):272-283.
![](/uploadfile/pub_images/20220302/周自江.png)