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Performance evaluation of reanalysis precipitation products in Egypt using fuzzy entropy time series similarity analysis
International Journal of Climatology ( IF 3.5 ) Pub Date : 2021-07-04 , DOI: 10.1002/joc.7286
Mohammed Magdy Hamed 1, 2 , Mohamed Salem Nashwan 1 , Shamsuddin Shahid 2
Affiliation  

Selection of suitable gridded precipitation data is deemed for hydroclimatic assessment and climate change impact analysis, especially in regions where long-term reliable precipitation data is unavailable. A novel approach based on fuzzy entropy similarity analysis (FESA) is proposed to evaluate the performance of four reanalysis gridded precipitation datasets (GPDs) for Egypt, namely European Reanalysis v.5. (ERA5), TerraClimate, Global Land Data Assimilation System (GLDAS)—Noah Land Surface Model L4 v.2 and Climatologies at high resolution for the Earth's land surface areas (CHELSA), against gauge records. The proposed method was verified using conventional statistics. Besides, the relative performance of different GPDs was verified according to their response to the influence of North Atlantic Oscillation (NAO) and Mediterranean Oscillation (MO) on winter precipitation. The performance of the best reanalysis GPD was also compared with the gauge-based global precipitation climatology centre (GPCC) dataset to show its reliability. The FESA revealed CHELSA as the best reanalysis GPD for Egypt. The performance assessment of GDPs based on conventional statistical metrics and visual presentation confirms the results obtained using FESA. CHELSA showed significant correlations with NAO (r = 0.3627) and MO (r = 0.624) like that obtained for gauge records. CHELSA also showed a better representation of precipitation in Egypt than GPCC at nearly half of the gauge locations. As CHELSA has a much higher spatial resolution than GPCC, it can be recommended as the proxy of gauge records in Egypt. The FESA can be used for performance analysis of gridded climate data by avoiding the complexities of using multiple statistical metrics.

中文翻译:

基于模糊熵时间序列相似性分析的埃及再分析降水产品性能评价

选择合适的网格降水数据被认为是水文气候评估和气候变化影响分析,尤其是在长期可靠降水数据不可用的地区。提出了一种基于模糊熵相似性分析 (FESA) 的新方法来评估埃及的四个再分析网格降水数据集 (GPD) 的性能,即欧洲再分析 v.5。(ERA5)、TerraClimate、全球陆地数据同化系统 (GLDAS) - 诺亚陆地表面模型 L4 v.2 和地球陆地表面区域的高分辨率气候学 (CHELSA),对照仪表记录。所提出的方法使用常规统计进行了验证。除了,根据对北大西洋涛动 (NAO) 和地中海涛动 (MO) 对冬季降水影响的响应,验证了不同 GPD 的相对性能。最佳再分析 GPD 的性能也与基于测量仪的全球降水气候学中心 (GPCC) 数据集进行了比较,以显示其可靠性。FESA 显示 CHELSA 是埃及最好的再分析 GPD。基于传统统计指标和视觉呈现的 GDP 绩效评估证实了使用 FESA 获得的结果。CHELSA 与 NAO 显着相关(FESA 显示 CHELSA 是埃及最好的再分析 GPD。基于传统统计指标和视觉呈现的 GDP 绩效评估证实了使用 FESA 获得的结果。CHELSA 与 NAO 显着相关(FESA 显示 CHELSA 是埃及最好的再分析 GPD。基于传统统计指标和视觉呈现的 GDP 绩效评估证实了使用 FESA 获得的结果。CHELSA 与 NAO 显着相关(r  = 0.3627) 和 MO ( r  = 0.624) 就像从规范记录中获得的那样。CHELSA 在将近一半的测量位置显示出比 GPCC 更好地代表埃及的降水。由于 CHELSA 具有比 GPCC 高得多的空间分辨率,因此可以推荐它作为埃及仪表记录的代理。通过避免使用多个统计指标的复杂性,FESA 可用于网格气候数据的性能分析。
更新日期:2021-09-09
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