全球25公里日分辨率大气温度廓线数据集（2010-2020）

1. 数据内容
大气温度是大气和环境的重要参数，获得连续的大气温度廓线数据对认识各种尺度的天气演变过程和做好临近天气预报具有重要意义。本数据根据科技部重点研发项目“全球能量循环和水循环关键参数的立体观测与遥感反演”的课题1“能量循环关键参数反演算法和产品研制”的研发任务要求，基于ERA5再分析数据和RAOB探空数据，采用机器学习和多项式拟合方法，生产了全球2010-2020年25km/日分辨率，气压0-1000hpa共16层的大气温度廓线产品。

2. 数据来源及加工方法
数据来源：欧洲中期天气预报中心最新的ERA5再分析数据+RAOB探空数据
加工方法：机器学习+多项式拟合。

3. 数据质量描述
利用匹配好的RAOB温度廓线验证产品精度，RMSE为3.5k。

4. 数据应用成果及前景
温度廓线是指在不同高度的温度值，是大气重要的气象参数，也是其他大气痕量气体精确反演的基础，可以用来表示大气的热力状况，其分布及变化监测对研究温室效应等气候现象有着重要的意义。

1. Data Content
Atmospheric temperature is a critical parameter for the atmosphere and the environment. Acquiring continuous atmospheric temperature profile data is of great significance for understanding weather evolution processes at all scales and enhancing short-term nowcasting. This dataset was developed in compliance with the research task requirements of Task 1 "Development of Key Parameter Retrieval Algorithms and Products for Energy Cycles" under the Key R&D Program of the Ministry of Science and Technology of China titled "Stereoscopic Observation and Remote Sensing Retrieval of Key Parameters of Global Energy and Water Cycles". Based on ERA5 reanalysis data and RAOB radiosonde data, we generated global atmospheric temperature profile products with a resolution of 25 km/day, covering 16 atmospheric layers from 0 to 1000 hPa, spanning the period from 2010 to 2020, using machine learning and polynomial fitting methods.

2. Data Source and Processing Method
Data Source: The latest ERA5 reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) plus RAOB radiosonde data.
Processing Method: Machine learning + polynomial fitting.

3. Data Quality Description
The accuracy of the product was validated using matched RAOB temperature profiles, with a root-mean-square error (RMSE) of 3.5 K.

4. Data Application Achievements and Prospects
Temperature profiles represent temperature values at different altitudes, which are important meteorological parameters of the atmosphere and the foundation for the accurate retrieval of other atmospheric trace gases. They can be used to characterize the thermal state of the atmosphere, and monitoring their distribution and variation is of great significance for researching climatic phenomena such as the greenhouse effect.

搜集汇总

背景与挑战

背景概述

该数据集是一个全球范围、高时空分辨率的大气温度廓线产品，覆盖2010年至2020年，每日更新，空间分辨率约25公里（0.25度），包含气压0-1000hpa的16个垂直层次，数据总量为428.55 GB。它基于ERA5再分析数据和RAOB探空数据，采用机器学习和多项式拟合方法生成，并通过验证显示RMSE为3.5K，精度可靠，适用于天气演变研究、临近天气预报和温室效应等气候分析。