East Asia Reanalysis System (EARS)

Reanalysis data plays a vital role in weather and climate study, as well as meteorological resource development and application. In this work, the East Asia Reanalysis System (EARS) was developed using the Weather Research and Forecasting (WRF) model and the Gridpoint Statistical Interpolations (GSI) data assimilation system. The regional reanalysis system is forced by the European Centre of Medium-Range Weather Forecasts (ECMWF) global reanalysis EAR-Interim data at 6-h intervals; and hourly surface observations are assimilated by the WRF Four-Dimension Data Assimilation (FDDA) scheme during the model integration; upper observations are assimilated in 3D-VAR mode at analysis moment. The reanalysis runs from 1980 to 2018, producing a regional reanalysis dataset covering East Asia and surrounding areas at 12-km horizontal resolution, 74 sigma levels, and 3-hour intervals. Compared to the global reanalysis data of the EAR-Interim, EARS are closer to the observations in both near-surface and upper-level fields. The present study provides evidence for substantial improvements seen in EARS compared to the ERA-Interim reanalysis fields over East Asia. Domain: covering a large domain of an area of 10,800 km x 9,120 km (with 900 x 760 grid points). (left bottom corner 61.6E, 10.3S, right bottom 138.3E, 10.3S, right top 138.3E, 10.3S, and left top 2.51E, 50.8N) The database format is GRIB version 1 and the total volume of the data files is 54.6 TB. The GRIB files are hosted at http://data.cma.cn/ as their total volume exceeds the volume that could be provided by Zenodo. Required files can therefore be downloaded from this location.

再分析数据（Reanalysis data）在天气与气候研究以及气象资源开发应用中发挥着至关重要的作用。本研究依托天气研究与预报模型（Weather Research and Forecasting, WRF）与格点统计插值（Gridpoint Statistical Interpolations, GSI）数据同化系统，开发了东亚再分析系统（East Asia Reanalysis System, EARS）。该区域再分析系统以欧洲中期天气预报中心（European Centre of Medium-Range Weather Forecasts, ECMWF）每6小时输出一次的全球再分析ERA-Interim数据作为强迫场；在模式积分过程中，通过WRF四维数据同化（Four-Dimension Data Assimilation, FDDA）方案同化地面逐小时观测资料；在分析时刻，则采用三维变分（3D-VAR）方式同化高空观测资料。该再分析数据集的时间覆盖范围为1980年至2018年，生成了覆盖东亚及周边区域的区域再分析数据，其水平分辨率为12千米，垂直包含74个西格玛层次，时间分辨率为3小时。相较于ERA-Interim全球再分析数据，EARS在近地面与高空场中均更贴近观测实况。本研究证实，相较于ERA-Interim再分析场，EARS在东亚区域的表现实现了显著提升。
数据集覆盖范围：包含一块总面积为10800 km × 9120 km的大区域（对应900 × 760个网格点），其左下角坐标为61.6°E、10.3°S，右下角坐标为138.3°E、10.3°S，右上角坐标为138.3°E、50.8°N，左上角坐标为2.51°E、50.8°N。
数据集格式为GRIB版本1，数据文件总容量达54.6 TB。因数据总容量超出Zenodo可支持的存储上限，相关GRIB文件托管于http://data.cma.cn/，用户可从此地址下载所需文件。

搜集汇总

背景与挑战

背景概述

East Asia Reanalysis System (EARS)是一个高分辨率的区域再分析数据集，覆盖东亚及周边地区，时间跨度为1980年至2018年，空间分辨率为12公里，时间分辨率为3小时。该数据集通过同化多种观测数据，提供了比全球再分析数据更准确的近地面和高空场数据，适用于天气和气候研究以及气象资源开发和应用。