中国近地表日气温数据集（1979-2018）

近地表气温是反映气候变化的重要物理参数。为了获得中国地区高时空分辨率的日数据(Tmax、Tmin和Tavg)，我们充分分析了各种现有数据(再分析数据、遥感数据和原位数据)的优缺点。针对不同的天气条件建立了不同的Ta重建模型，并通过建立不同区域的修正方程进一步提高数据精度。最后，获得了1979 - 2018年中国逐日气温数据集(Tmax、Tmin和Tavg)，空间分辨率为0.1°。
对于Tmax，使用原位数据的验证表明，均方根误差(RMSE)范围为0.86°C至1.78°C，平均绝对误差(MAE)范围为0.63°C至1.40°C，皮尔逊系数(R2)范围为0.96至0.99。Tmin的RMSE为0.78°C ~ 2.09°C, MAE为0.58°C ~ 1.61°C, R2为0.95 ~ 0.99。对于Tavg, RMSE范围为0.35°C ~ 1.00°C, MAE范围为0.27°C ~ 0.68°C, R2范围为0.99 ~ 1.00。此外，利用多种评价指标分析Ta的时空变化趋势，Tavg增加幅度大于0.0°C/a，与全球变暖的总体趋势一致。
综上所述，该数据集具有较高的空间分辨率和可靠的精度，弥补了之前在高空间分辨率下缺失的温度值(Tmax、Tmin和Tavg)。该数据集也为研究气候变化，特别是高温干旱和低温冷害提供了关键参数。

Near-surface air temperature is an important physical parameter reflecting climate change. To obtain daily high-spatiotemporal resolution temperature data (Tmax, Tmin, and Tavg) over China, we thoroughly analyzed the advantages and disadvantages of various existing datasets, including reanalysis data, remote sensing data, and in-situ observation data. We developed distinct air temperature reconstruction models tailored to different weather conditions, and further improved the data accuracy by establishing correction equations for different regions. Finally, we constructed a daily air temperature dataset (Tmax, Tmin, and Tavg) over China spanning from 1979 to 2018, with a spatial resolution of 0.1°.

For Tmax, validation using in-situ observation data shows that the root mean square error (RMSE) ranges from 0.86 °C to 1.78 °C, the mean absolute error (MAE) ranges from 0.63 °C to 1.40 °C, and the coefficient of determination (R²) ranges from 0.96 to 0.99. For Tmin, the RMSE is 0.78 °C – 2.09 °C, MAE is 0.58 °C – 1.61 °C, and R² is 0.95 – 0.99. For Tavg, the RMSE ranges from 0.35 °C to 1.00 °C, MAE ranges from 0.27 °C to 0.68 °C, and R² ranges from 0.99 to 1.00. In addition, we analyzed the spatiotemporal variation trends of near-surface air temperature using multiple evaluation indicators, and found that the increasing rate of Tavg is greater than 0.0 °C/a, which is consistent with the overall trend of global warming.

In summary, this dataset features high spatial resolution and reliable accuracy, filling the gap of missing high-spatial-resolution temperature values (Tmax, Tmin, and Tavg) in previous studies. It also provides key parameters for research on climate change, particularly high-temperature droughts and low-temperature chilling damages.

搜集汇总

背景与挑战

背景概述

该数据集是中国地区1979年至2018年的近地表日气温数据，包含日最高、最低和平均气温，空间分辨率为0.1°，时间分辨率为日。数据集通过融合再分析、遥感和原位数据，并建立修正模型，确保了高精度（如RMSE和R2指标验证），适用于气候变化分析，如全球变暖趋势研究。数据以栅格TIF格式提供，开放获取，但使用需遵循CC BY-NC-SA 4.0许可协议并引用相关文献。