کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8864517 | 1620469 | 2018 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Comparison of two long-term and high-resolution satellite precipitation datasets in Xinjiang, China
ترجمه فارسی عنوان
مقایسه دو مجموعه داده ماهواره ای با طول عمر با وضوح بالا در سین کیانگ، چین
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
علم هواشناسی
چکیده انگلیسی
To investigate the long-term characteristics of precipitation in Xinjiang, China, two long-term monthly satellite precipitation datasets called CHIRPS (Climate Hazards Group Infrared Precipitation with Stations data) and PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks - Climate Data Record) are evaluated and compared with in situ measurements from 105 meteorological stations for the period 1983-2014. The evaluation is performed at multiple temporal and spatial scales. Results based on comparisons with in situ measurements show that PERSIANN-CDR and CHIRPS have similar correlations. However, both of the BIAS and RMSE, CHIRPS outperformed PERSIANN-CDR with the smaller errors and bias. In terms of the long time-series comparison at temporal scale, CHIRPS is more accurate with gauge observations at monthly and annual scales while PERSIANN-CDR tends to overestimate the precipitation in the rain season (from May to September). Furthermore, compared with PERSIANN-CDR, results show that CHIRPS is more accurate in reflecting the spatial distribution of average monthly and annual precipitation. In summary, the study shows that CHIRPS is a valuable complement to gauge precipitation data and provides useful guidance when choosing satellite precipitation product for hydrometeorological applications in Xinjiang.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Atmospheric Research - Volume 212, 1 November 2018, Pages 150-157
Journal: Atmospheric Research - Volume 212, 1 November 2018, Pages 150-157
نویسندگان
Feng Gao, Yuhu Zhang, Qiuhua Chen, Peng Wang, Huirong Yang, Yunjun Yao, Wanyuan Cai,