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开发印度尼西亚爪哇岛 1985-2014 年的网格化气象数据集。

Development of a gridded meteorological dataset over Java island, Indonesia 1985-2014.

机构信息

Civil Engineering Department, Jenderal Soedirman University, Purwokerto 53371, Indonesia.

Department of Civil Environmental and Architectural Engineering, University of Colorado, Boulder, Colorado 80309, USA.

出版信息

Sci Data. 2017 May 23;4:170072. doi: 10.1038/sdata.2017.72.

Abstract

We describe a gridded daily meteorology dataset consisting of precipitation, minimum and maximum temperature over Java Island, Indonesia at 0.125°×0.125° (14 km) resolution spanning 30 years from 1985-2014. Importantly, this data set represents a marked improvement from existing gridded data sets over Java with higher spatial resolution, derived exclusively from ground-based observations unlike existing satellite or reanalysis-based products. Gap-infilling and gridding were performed via the Inverse Distance Weighting (IDW) interpolation method (radius, r, of 25 km and power of influence, α, of 3 as optimal parameters) restricted to only those stations including at least 3,650 days (10 years) of valid data. We employed MSWEP and CHIRPS rainfall products in the cross-validation. It shows that the gridded rainfall presented here produces the most reasonable performance. Visual inspection reveals an increasing performance of gridded precipitation from grid, watershed to island scale. The data set, stored in a network common data form (NetCDF), is intended to support watershed-scale and island-scale studies of short-term and long-term climate, hydrology and ecology.

摘要

我们描述了一个网格化的每日气象数据集,该数据集包含印度尼西亚爪哇岛的降水、最低和最高温度,分辨率为 0.125°×0.125°(约 14 公里),时间跨度为 30 年,从 1985 年到 2014 年。重要的是,与现有的基于卫星或再分析的产品不同,该数据集是通过地面观测获得的,代表了爪哇岛现有网格化数据的显著改进,具有更高的空间分辨率。通过反距离加权(IDW)插值方法(最优半径 r 为 25 公里,影响幂 α 为 3)进行填补和网格化,仅对那些包含至少 3650 天(约 10 年)有效数据的站点进行限制。我们在交叉验证中使用了 MSWEP 和 CHIRPS 降雨产品。结果表明,网格化的降雨表现最为合理。目视检查显示,从网格、流域到岛屿尺度,网格化降水的性能不断提高。该数据集以网络通用数据格式(NetCDF)存储,旨在支持流域尺度和岛屿尺度的短期和长期气候、水文和生态研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2918/5441288/4e5107ab460a/sdata201772-f1.jpg

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