青藏高原陆气相互作用高分辨率资料同化数据集（2000-2022）

利用WRF（4.2.2）模式和三维变分（3DVAR）模块，同化了全球电信系统（GTS）的无线电探空仪、地面观测站、飞机报告和卫星云迹风数据，包括气压、位势高度、气温、露点温度、风向和风速（NCEP_ADP资料）。生成了2000~2022年青藏高原高时空分辨率（5×5 km, 1小时）陆地-大气同化数据集（QTP-HRAD）。该同化数据始于2000年1月1日00:00（UTC），止于2022年12月31日23:00（UTC），经纬度范围为72.3°E ~ 103.2°E，25.9°N ~ 40.3°N。数据包括2m温度（K）、地表温度（K）、相对湿度（%）、地表气压（Pa）、2米水汽混合比（kg/kg）、10米U和V风成分（m/s）、10米风速（m/s）、风向（°）、降水（mm）、露点温度（℃）、地表能量通量（W/m-2）和高空三维风场、温湿度场等共35个变量。我们挑选了高原周边10个站点的观测资料与QTP-HRAD作对比分析，QTP-HRAD的日平均值与观测值基本吻合，在年变化趋势上也较为一致，能够较好地反映出温度、湿度、降水、蒸发量、气压、风速等气象要素的年际变化特征，但在地形条件复杂的站点，统计误差较大。对比QTP-HRAD和ERA-5数据的区域分布，发现5×5 km空间分辨率得到的气象要素的区域分布比0.25×0.25的ERA-5数据更精确，可以明显看出由地形高度差异引起的气温、湿度、风速和降水的分布差异。本资料同化数据集可以用于研究青藏高原地区陆地-大气相互作用、能量水分循环以及极端天气过程，为高原生态环境、极端天气气候综合评价提供基础数据。

This study utilized the Weather Research and Forecasting (WRF, version 4.2.2) model and its Three-Dimensional Variational (3DVAR) assimilation module to assimilate data from the Global Telecommunications System (GTS), including radiosonde observations, surface station measurements, aircraft reports, and satellite cloud-motion wind data. The assimilated data cover variables such as air pressure, geopotential height, air temperature, dew point temperature, wind direction, and wind speed (NCEP_ADP data). A high spatiotemporal resolution (5 × 5 km, 1-hour temporal interval) land-atmosphere assimilation dataset over the Qinghai-Tibet Plateau (QTP), designated as QTP-HRAD, was generated for the period 2000–2022. The dataset runs from 00:00 UTC on January 1, 2000 to 23:00 UTC on December 31, 2022, with a spatial coverage of 72.3°E – 103.2°E and 25.9°N – 40.3°N. In total, the dataset contains 35 variables, including 2-meter temperature (K), surface temperature (K), relative humidity (%), surface air pressure (Pa), 2-meter water vapor mixing ratio (kg/kg), 10-meter U and V wind components (m/s), 10-meter wind speed (m/s), wind direction (°), precipitation (mm), dew point temperature (°C), surface energy flux (W/m²), as well as three-dimensional upper-air wind, temperature and humidity fields. We conducted a comparative analysis between QTP-HRAD and in-situ observations from 10 stations surrounding the QTP. The daily mean values of QTP-HRAD generally agree with the observed data, and their annual variation trends are consistent. The dataset can well reflect the interannual variation characteristics of meteorological elements such as temperature, humidity, precipitation, evaporation, air pressure, and wind speed, but exhibits relatively large statistical errors at stations with complex terrain. By comparing the spatial distributions of meteorological variables between QTP-HRAD and ERA5 reanalysis data, it is found that the distributions derived from the 5 × 5 km resolution are more accurate than those from the 0.25° × 0.25° ERA5 data. The distribution differences of temperature, humidity, wind speed, and precipitation caused by topographic height variations can be clearly observed. This land-atmosphere assimilation dataset can be used to study land-atmosphere interactions, energy and water cycles, and extreme weather processes over the Qinghai-Tibet Plateau, providing fundamental data for comprehensive evaluations of the plateau’s ecological environment, extreme weather and climate.

搜集汇总

背景与挑战

背景概述

该数据集为2000-2022年青藏高原高时空分辨率（5×5 km, 1小时）陆地-大气同化数据集，包含35个气象变量，适用于研究陆地-大气相互作用和极端天气过程。数据通过WRF模式和三维变分模块同化多种观测数据生成，具有较高的区域分布精度。