This study focuses on the validation of high-resolution regional reanalyses to understand their effectiveness in reproducing precipitation patterns over Italy, a climate change hotspot characterized by coastal sea-land interaction and complex orography. Nine reanalysis products were evaluated, with the ECMWF global reanalysis ERA5 serving as a benchmark. These included both European (COSMO-REA6, CERRA) and Italy-specific (BOLAM, MERIDA, MERIDA-HRES, MOLOCH, SPHERA, VHR-REA_IT) datasets, using different models and parametrizations. The inter-comparison involved determining the effective resolution of daily precipitation fields using wavelet techniques and assessing intense precipitation statistics through frequency distributions. In-situ observations and observational gridded datasets were used to independently validate reanalysis precipitation fields. The capability of reanalyses to depict daily precipitation patterns was assessed, highlighting a maximum radius of precipitation misplacement of about 15 km, with notably lower skills during summer. An overall overestimation of precipitation was identified in the reanalysis climatological fields over the Po Valley and the Alps, whereas multiple products showed an underestimation of precipitations across the North-West coast, the Apennines, and Southern Italy. Finally, a comparison with a time-consistent observational dataset (UniMi/ISAC-CNR) revealed a non-stable deviation from observations in the annual precipitation cumulate of the reanalysis products analyzed. This should be taken into account when interpreting precipitation trends over Italy.

中文翻译：

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意大利高分辨率再分析降水场的多尺度评估


本研究的重点是验证高分辨率区域再分析，以了解它们在意大利重现降水模式的有效性，意大利是一个以沿海海陆相互作用和复杂地形为特征的气候变化热点地区。评估了 9 种再分析产品，以 ECMWF 全局再分析 ERA5 为基准。其中包括欧洲 （COSMO-REA6， CERRA） 和意大利特定的 （BOLAM， MERIDA， MERIDA-HRES， MOLOCH， SPHERA， VHR-REA_IT） 数据集，使用不同的模型和参数化。相互比较包括使用小波技术确定日降水场的有效分辨率，并通过频率分布评估强降水统计数据。原位观测和观测网格化数据集用于独立验证再分析降水场。评估了再分析描绘日降水模式的能力，突出了降水错位的最大半径约为 15 公里，夏季的技能明显较低。在波河谷和阿尔卑斯山的再分析气候田中发现了对降水的总体高估，而多个产品显示对西北海岸、亚平宁山脉和意大利南部的降水进行了低估。最后，与时间一致的观测数据集 （UniMi/ISAC-CNR） 的比较显示，所分析的再分析产品的年降水累积量与观测值存在不稳定的偏差。在解释意大利的降水趋势时，应考虑到这一点。