Investigation on potential and limitations of ERA5 Reanalysis downscaled on Italy by a convection-permitting model

被引:16
作者
Adinolfi, Marianna [1 ]
Raffa, Mario [1 ]
Reder, Alfredo [1 ]
Mercogliano, Paola [1 ]
机构
[1] Fdn Ctr Euro Mediterraneo Cambiamenti Climat, I-81100 Caserta, Italy
关键词
Regional climate models; ERA5; reanalysis; Kilometer-scale resolution; Model evaluation; Urban parameterisation; Climate indicators; MOISTURE-PRECIPITATION FEEDBACK; NUMERICAL WEATHER PREDICTION; SOIL-MOISTURE; COSMO-CLM; DATA ASSIMILATION; SIMULATIONS; EVENTS; SCALE; TEMPERATURE; PERFORMANCE;
D O I
10.1007/s00382-023-06803-w
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
This study presents a comprehensive assessment of a dynamical downscaling of ERA5 Reanalysis recently performed over Italy through the COSMO-CLM model at a convection-permitting scale (0.02 degrees) over the period 1989-2020. Results are analysed against several independent observational datasets and reanalysis products. The capability of the downscaling to realistically represent the climatology for 2 m temperature and precipitation is analysed over the whole peninsula and subdomains. Hourly precipitation patterns, orography effects, and urban climate dynamics are also investigated, highlighting the weaknesses and strengths of the convection-permitting model. In particular, gains in performances are achieved in mountainous areas where the climate characteristics are correctly represented, as are the hourly precipitation characteristics. Losses in performances occur in coastal and flat areas of the Italian peninsula, where the convection-permitting model performance does not seem to be satisfactory, as opposed to complex orographic areas. The adopted urban parameterisation is demonstrated to simulate heat detection for two Italian cities: Rome and Milan. Finally, a subset of extreme climate indicators is evaluated, finding: (i) a region-dependent response, (ii) a notable performance of the convection-permitting model over mountainous areas and (iii) discrepancies in the South, Central and Insular subdomains. Climate indicators detect extreme events at a detailed scale, becoming an important tool for turning climate data into information.
引用
收藏
页码:4319 / 4342
页数:24
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