کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8912339 | 1639333 | 2018 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Validation of satellite-based rainfall in Kalahari
ترجمه فارسی عنوان
اعتبار بارش باران ماهواره ای در کالاهاری
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کلمات کلیدی
تصحیح تقاطع، حوضه کلاهاری مرکزی، باران سنج، تغییرات بارش، بارش باران ماهواره ای،
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
ژئوشیمی و پترولوژی
چکیده انگلیسی
Water resources management in arid and semi-arid areas is hampered by insufficient rainfall data, typically obtained from sparsely distributed rain gauges. Satellite-based rainfall estimates (SREs) are alternative sources of such data in these areas. In this study, daily rainfall estimates from FEWS-RFEâ¼11â¯km, TRMM-3B42â¼27â¯km, CMOPRHâ¼27â¯km and CMORPHâ¼8â¯km were evaluated against nine, daily rain gauge records in Central Kalahari Basin (CKB), over a five-year period, 01/01/2001-31/12/2005. The aims were to evaluate the daily rainfall detection capabilities of the four SRE algorithms, analyze the spatio-temporal variability of rainfall in the CKB and perform bias-correction of the four SREs. Evaluation methods included scatter plot analysis, descriptive statistics, categorical statistics and bias decomposition. The spatio-temporal variability of rainfall, was assessed using the SREs' mean annual rainfall, standard deviation, coefficient of variation and spatial correlation functions. Bias correction of the four SREs was conducted using a Time-Varying Space-Fixed bias-correction scheme. The results underlined the importance of validating daily SREs, as they had different rainfall detection capabilities in the CKB. The FEWS-RFEâ¼11â¯km performed best, providing better results of descriptive and categorical statistics than the other three SREs, although bias decomposition showed that all SREs underestimated rainfall. The analysis showed that the most reliable SREs performance analysis indicator were the frequency of “miss” rainfall events and the “miss-bias”, as they directly indicated SREs' sensitivity and bias of rainfall detection, respectively. The Time Varying and Space Fixed (TVSF) bias-correction scheme, improved some error measures but resulted in the reduction of the spatial correlation distance, thus increased, already high, spatial rainfall variability of all the four SREs. This study highlighted SREs as valuable source of daily rainfall data providing good spatio-temporal data coverage especially suitable for areas with limited rain gauges, such as the CKB, but also emphasized SREs' drawbacks, creating avenue for follow up research.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Physics and Chemistry of the Earth, Parts A/B/C - Volume 105, June 2018, Pages 84-97
Journal: Physics and Chemistry of the Earth, Parts A/B/C - Volume 105, June 2018, Pages 84-97
نویسندگان
Moiteela Lekula, Maciek W. Lubczynski, Elisha M. Shemang, Wouter Verhoef,