Performance ranking of global precipitation estimates over data scarce Western Himalayan Region of India

IF 2.8 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES Theoretical and Applied Climatology Pub Date : 2024-06-29 DOI:10.1007/s00704-024-05069-4
Deepak Singh Bisht, Bratati Chowdhury, Soban Singh Rawat, Jose George Pottakkal
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Abstract

With the advent of numerous global precipitation estimates (GPEs) in the recent decades, dependability of hydrologists has lessened on the station data as the GPEs can be readily availed and utilized. Since the skills of GPEs may differ from region-to-region, it is vital to analyse their ability in resolving the regional precipitation climatology using appropriate statistical methods. In this study, a total of five GPEs, viz., APHRODITE, PERSIANN-CDR, CHIRPS, CMORPH, and IMERG were evaluated for their abilities in resolving regional precipitation climatology of WHR with respect to gridded precipitation product of India Meteorological Department (IMD). Different performance indicators i.e., Probability of Detection (POD), False Alarm Ratio (FAR), Normalised Root Mean Square Deviation (NRMSD), Pearson Correlation Coefficient (CC) and Skill Score (SS) were used for evaluating the GPEs. Multicriterion Decision Making (MCDM)approaches i.e., Compromise Programming (CP), Cooperative Game Theory (CGT), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Weighted Average Technique (WAT), and Fuzzy TOPSIS were used for ranking the GPEs across different grids in WHR. Entropy based weight assignment to NRMSD, CC, and SS were performed while applying them in MCDM methods. Group Decision Making (GDM) approach utilizing spearman correlation coefficient and additive ranking rule was employed to obtain the final ranking of GPEs from multiple rankings assigned through different MCDM methods. Across 115 grids, APHRODITE exhibits superior performance compared to other GPEs in 89 grids. Conversely, CHIRPS and CMORPH emerge as the least favorable products among the five GPEs across more than 70 grids, being consistently ranked either 4th or 5th. Notably, IMERG was identified as the best-performing product in 14 grids and as the second-best product in 63 grids, positioning it as the second most suitable option after APHRODITE for monthly rainfall time series analysis. Similar results, as detailed in the paper, were also obtained for month-wise rainfall time series analysis.

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对印度西喜马拉雅地区数据稀缺的全球降水量估算进行性能排序
近几十年来,随着大量全球降水估算(GPEs)的出现,水文学家对测站数据的依赖性降低了,因为 GPEs 可以随时获得和使用。由于各地区 GPE 的技能可能不同,因此使用适当的统计方法分析其解析地区降水气候学的能力至关重要。本研究评估了 APHRODITE、PERSIANN-CDR、CHIRPS、CMORPH 和 IMERG 这五个 GPEs 在解析世界降水资源区域降水气候学方面的能力,以及与印度气象局 (IMD) 的网格降水产品相比的能力。评估 GPE 时使用了不同的性能指标,即检测概率 (POD)、误报率 (FAR)、归一化均方根偏差 (NRMSD)、皮尔逊相关系数 (CC) 和技能分数 (SS)。多标准决策(MCDM)方法,即折中方案规划(CP)、合作博弈论(CGT)、与理想解相似度排序技术(TOPSIS)、加权平均技术(WAT)和模糊 TOPSIS,用于对 WHR 中不同网格的 GPE 进行排序。在将 NRMSD、CC 和 SS 应用于 MCDM 方法时,对它们进行了基于熵的权重分配。利用矛曼相关系数和加法排序规则的群体决策(GDM)方法,从通过不同 MCDM 方法分配的多个排名中获得 GPE 的最终排名。在 115 个网格中,APHRODITE 在 89 个网格中表现出优于其他 GPE 的性能。相反,在 70 多个网格中,CHIRPS 和 CMORPH 是五个 GPE 中表现最差的产品,一直排名第四或第五。值得注意的是,IMERG 在 14 个网格中表现最佳,在 63 个网格中排名第二,是继 APHRODITE 之后最适合月降雨时间序列分析的产品。在月降雨时间序列分析中也获得了类似的结果,详见本文。
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来源期刊
Theoretical and Applied Climatology
Theoretical and Applied Climatology 地学-气象与大气科学
CiteScore
6.00
自引率
11.80%
发文量
376
审稿时长
4.3 months
期刊介绍: Theoretical and Applied Climatology covers the following topics: - climate modeling, climatic changes and climate forecasting, micro- to mesoclimate, applied meteorology as in agro- and forestmeteorology, biometeorology, building meteorology and atmospheric radiation problems as they relate to the biosphere - effects of anthropogenic and natural aerosols or gaseous trace constituents - hardware and software elements of meteorological measurements, including techniques of remote sensing
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