Defining regions with similar characteristics for extreme precipitation is crucial for understanding the impacts of climate change, planning and managing water resources, and designing hydraulic structures. However, studies on the regionalization of extreme precipitation for Türkiye are limited, and regional extreme precipitation characteristics are not well defined. In this study, motivated by the need to contribute to this field, homogenous regions for extreme precipitation across Türkiye were determined using the latest version (V07) of Integrated Multi-satellitE Retrievals for GPM (IMERG). We initially validated IMERG V07 estimates using data from 214 ground-based stations and compared the results with its predecessor V06. The results revealed that IMERG showed some notable improvements from V06 to V07 for all seasons, especially in winter. During this season, the correlation coefficient increased from 0.57 to 0.64, the mean absolute bias decreased from 78.22 % to 69.27 %, and the RMSE decreased from 11.10 mm/day to 9.70 mm/day. In V07, while the trend of decreasing accuracy with increasing elevation observed in V06 continues, it has been shown that some notable improvements were achieved in continuous and categorical metrics. We then applied widely used non-hierarchical (K-means) and hierarchical (Ward's method) clustering techniques. To perform this, we first applied Principal Component Analysis (PCA) to reduce the number of variables related to extreme precipitation (e.g. amount, frequency, standard deviation, and seasonality) and geographic characteristics to identify the most significant variables for analysis. The K-means method delineated Türkiye into eight extreme precipitation regions, while the Ward's method resulted in six distinct extreme precipitation regions. We evaluated the results based on the existing extreme precipitation climatology literature for Türkiye and by associating them to known precipitation dynamics, and as a result, we recommended eight precipitation regions determined by the K-means. The identified precipitation regions are expected to contribute to future studies analyzing the effects of climate change and to regional studies on natural disasters resulting from extreme precipitation.

中文翻译：

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GPM IMERG V07 与其前身 V06 的性能比较及其在土耳其极端降水集群中的应用


定义具有相似极端降水特征的区域对于了解气候变化的影响、规划和管理水资源以及设计水力结构至关重要。然而，关于土耳其极端降水区域化的研究有限，区域极端降水特征没有得到明确定义。在这项研究中，出于对该领域做出贡献的需要，使用最新版本 （V07） 的 GPM 综合多卫星检索 （IMERG） 确定了土耳其极端降水的均匀区域。我们最初使用来自 214 个地面站的数据验证了 IMERG V07 估计值，并将结果与其前身 V06 进行了比较。结果显示，IMERG 在所有季节从 V06 到 V07 都显示出一些显着的改善，尤其是在冬季。在这个季节，相关系数从 0.57 增加到 0.64，平均绝对偏差从 78.22 % 下降到 69.27 %，RMSE 从 11.10 mm/d 下降到 9.70 mm/d。在 V07 中，虽然在 V06 中观察到的准确率随着海拔增加而降低的趋势仍在继续，但已经表明在连续和分类指标方面取得了一些显着的改进。然后，我们应用了广泛使用的非分层 （K-means） 和分层 （Ward 方法） 聚类技术。为此，我们首先应用主成分分析 （PCA） 来减少与极端降水相关的变量数量（例如数量、频率、标准差和季节性）和地理特征，以确定最重要的分析变量。 K-means 方法将 Türkiye （土耳其） 划分为 8 个极端降水区域，而 Ward 方法则产生了 6 个不同的极端降水区域。我们根据土耳其现有的极端降水气候学文献评估了结果，并将它们与已知的降水动力学相关联，因此，我们推荐了由 K-means 确定的八个降水区域。已确定的降水区域有望为未来分析气候变化影响的研究以及极端降水导致的自然灾害的区域研究做出贡献。