对喀拉拉邦基丹古尔子流域中原和高原地区平均的卫星 CHIRPS 降水量数据进行统计评估

IF 0.7 4区 地球科学 Q4 METEOROLOGY & ATMOSPHERIC SCIENCES
MAUSAM Pub Date : 2024-03-24 DOI:10.54302/mausam.v75i2.6189
D. VARGHESE G. S., M. Chadaga, L. U A, S. Salim, Roopali Shantha Pai
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引用次数: 0

摘要

喀拉拉邦东起西高止山脉,西至沙滩,地形陡峭,需要使用时空分辨率极高的降水数据进行一系列水文和水文气象研究。现有的雨量计网络数据在反映该州各地貌分区季风降雨量的变化方面存在局限性,使用分辨率更高的卫星降雨量数据集可以克服这一局限性。 本文通过与站点降雨数据和 IMD 网格数据集进行比较,对卫星得出的基丹古尔子流域 CHIRPS(气候灾害组红外降水与站点)降水数据进行了统计评估。在 95% 的置信度下进行的同质性检验将站点数据归入 "有用 "类别。此外,统计性能矩阵表明,CHIRPS 数据略微低估了观测站降雨量数据。不过,月序列的判定系数 R2 值(0.95-0.97)和年序列的判定系数 R2 值(0.37-0.64)表明,数据集之间存在较强至中等程度的正相关性。总之,在研究区域首次评估的定量统计性能矩阵表明,CHIRPS 雨量估计值可以很好地再现地面月降雨量数据集,也可以很好地替代 IMD 网格数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Statistical evaluation of satellite-based CHIRPS precipitation data averaged over the midland and highland regions of Kidangoor sub-catchment, Kerala
The steep topographical setting of Kerala, traversing from Western Ghats in the east to the sandy beaches on the west, demands the use of precipitation data at a very fine spatio-temporal resolution for a range of hydrological and hydrometeorological studies. The limitation of the existing rain gauge network data in representing the variability in the monsoon showers received, across the physiographic divisions of the state, could be overcome using satellite rainfall dataset offered at a finer resolution.  In this paper, a statistical evaluation of the satellite derived CHIRPS (Climate Hazards Group Infrared Precipitation with Stations) precipitation data for the Kidangoor sub-catchment was performed by comparing it with station rainfall data and IMD gridded data sets. The homogeneity test at 95 % confidence level classified the station data under ‘useful’ category. Additionally, the statistical performance matrices suggested that the CHIRPS data slightly underestimated the observed station rainfall data. However, the coefficient of determination R2 values (0.95-0.97) in the monthly series and (0.37 - 0.64) in the annual series demonstrated a strong to moderate positive correlation between the datasets. To summarize, the quantitative statistical performance matrices, evaluated for the first time in the study area, proposed that the CHIRPS rainfall estimates could very well reproduce the ground-based monthly rainfall datasets and could also serve as a good replacement for IMD gridded data.
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来源期刊
MAUSAM
MAUSAM 地学-气象与大气科学
CiteScore
1.20
自引率
0.00%
发文量
1298
审稿时长
6-12 weeks
期刊介绍: MAUSAM (Formerly Indian Journal of Meteorology, Hydrology & Geophysics), established in January 1950, is the quarterly research journal brought out by the India Meteorological Department (IMD). MAUSAM is a medium for publication of original scientific research work. MAUSAM is a premier scientific research journal published in this part of the world in the fields of Meteorology, Hydrology & Geophysics. The four issues appear in January, April, July & October.
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