The 2-m temperature data is a significant indicator for studying the weather extremes and the exchange of water and energy fluxes between the surface and atmosphere. This study compared three reanalysis datasets, i.e., ERA5, ERA5-Land, and MERRA-2, with observations from in-situ sources from 1990 to 2022 using various statistical error metrics and extreme temperature indices over the Arabian Peninsula (AP) region. We selected these reanalysis datasets due to the continuous improvements and higher spatiotemporal output better capturing the temperature variability. The spatiotemporal climatology shows lower temperatures in winter (<15 °C) and maximum in summer (>35 °C); however, the reanalysis data show more deviations in temperature during the cold season than in the warm season. The reanalysis data underestimated the frequency of the cold (<10 °C) and hot (>30 °C) days across the four regions, except ERA5-Land, which closely followed observed data. The strength of the correlation shows better performance (>0.90) in the cold extremes (cold nights and cold days) frequency than the hot extremes. On an interannual scale, reanalysis products exhibit strong correlations (>0.90) with in-situ data across most regions, particularly in winter and autumn, moderate in spring, and weaker in summer. The reanalysis data shows negative biases in the inland regions and positive biases in the coastal areas with consistent root mean square differences (RMSD) spatiotemporally. The differences in performance are due to the topography and poor representation of the energy fluxes, especially in MERRA-2 as well as missing data in observations. This study recommends ERA5-Land as the first choice for extreme weather simulations in the region, followed by MERRA-2 and ERA5 on the same scale, but proper attention is needed when using reanalysis data for cold and hot extremes.

中文翻译：

---

阿拉伯半岛 2 m 地表温度再分析数据与观测数据对比


2 m 温度数据是研究极端天气以及地表和大气之间水和能量通量交换的重要指标。本研究将三个再分析数据集，即 ERA5、ERA5-Land 和 MERRA-2，与 1990 年至 2022 年使用各种统计误差指标和阿拉伯半岛 （AP） 地区极端温度指数的原位来源的观测结果进行了比较。我们选择这些再分析数据集是因为持续改进和更高的时空输出更好地捕捉了温度变化。时空气候显示冬季气温较低 （<15 °C），夏季最高气温 （>35 °C）;然而，再分析数据显示，寒冷季节的温度偏差比温暖季节多。再分析数据低估了四个地区寒冷 （<10 °C） 和炎热 （>30 °C） 日的频率，但 ERA5-Land 除外，它紧随观测数据。相关性强度显示，在极端寒冷（寒冷的夜晚和寒冷的白天）频率下，性能优于极端高温（3E0.90）。在年际尺度上，再分析产品与大多数地区的原位数据表现出很强的相关性 （>0.90），特别是在冬季和秋季，春季中等，夏季较弱。再分析数据显示内陆地区存在负偏差，沿海地区存在正偏差，时空均方根差 （RMSD） 一致。性能的差异是由于地形和能量通量的表示不佳，尤其是在 MERRA-2 中以及观测中数据的缺失。 本研究推荐 ERA5-Land 作为该地区极端天气模拟的首选，其次是相同尺度的 MERRA-2 和 ERA5，但在使用冷热极端事件的再分析数据时需要适当注意。