A spatially distributed rainfall dataset for West Java, Indonesia

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief Pub Date : 2025-08-12 DOI:10.1016/j.dib.2025.111974

Dwi Yoga Primartono , Rahmat Hidayat , Supari , Rakhmat Prasetia , Muh Taufik

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Abstract

Rainfall data availability is a basis of climate analysis and application, but its spatial distribution based on observed rainfall at local scale remains a research challenge. A spatially distributed rainfall at a finer resolution is the foundation for coping uncertain climate change and water resource planning and management. Here, we established a daily grid dataset for observed rainfall of West Java, Indonesia. The data were from 1991-2020 at daily resolution from 162 rain gauges covering various terrains and climate zone, which were monitored by the Indonesian Agency for Meteorology Climatology and Geophysics (BMKG). We used the inverse distance weighting (IDW) approach to spatially interpolate rainfall at 0.05⁰ grid resolution. In addition, timeseries of monthly and annual rainfall were generated from the daily dataset. Further, the spatial rainfall data is useful for identifying local climate, adaptation strategy for hydro-meteorological hazard, and water resource planning.

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印度尼西亚西爪哇的空间分布降雨数据集

降雨资料的可得性是气候分析和应用的基础，但基于局地尺度降水观测的降雨资料空间分布仍然是一个研究难题。更精细分辨率的降雨空间分布是应对不确定性气候变化和水资源规划管理的基础。在这里，我们建立了印度尼西亚西爪哇观测降雨量的日网格数据集。这些数据是由印度尼西亚气象、气候和地球物理机构（BMKG）监测的162个雨量器从1991年到2020年的日分辨率数据。这些雨量器覆盖了不同的地形和气候区。我们使用逆距离加权（IDW）方法在0.050网格分辨率下对降雨进行空间插值。此外，从每日数据集生成月降雨量和年降雨量时间序列。此外，空间降雨数据还可用于识别当地气候、水文气象灾害适应策略和水资源规划。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Data in Brief MULTIDISCIPLINARY SCIENCES-

CiteScore

3.10

自引率

0.00%

发文量

996

审稿时长

70 days

期刊介绍： Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.