基于卫星数据的偏差校正和空间分类,用于检测降雨季节性指数
Winifred Ayinpogbilla Atiah1, Robert Johnson1, Francis Kamau Muthoni2
1Kwame Nkrumah University of Science and Technology (KNUST), Department of Physics, Meteorology and Climate Science Unit, Kumasi, Ghana.
Heliyon
|July 14, 2023
概括
这里是加拿大加拿大加拿大加拿大.
科学领域:
- 水文学和气候科学 气象学和气候科学
- 环境监测中的遥感应用.
背景情况:
- 加纳面临着雨量测量网络恶化的挑战,影响实时降雨数据.
- 卫星降水产品 (SPP) 具有潜力,但需要对水文应用进行偏差校正.
研究的目的:
- 在加纳,使用偏差校正和空间分类 (BCSD) 方法对基于卫星的每日降雨估计进行偏差校正 (CHIRPS-v2).
- 评估偏差校正对确定降雨季节性和极端指数的影响.
主要方法:
- 将偏差校正和空间分类 (BCSD) 方法应用于CHIRPS-v2每日降雨数据.
- 在偏差校正之前和之后分析了季节性和极端降雨指数的变化.
主要成果:
- 偏差校正改善了季节性和年度降雨模式的表示.
- 校正后的停止日期与标尺数据保持一致,特别是在西南部和中上部地区.
结论:
- BCSD方法有效地纠正了加纳卫星降雨估计中的偏差.
- 偏差纠正的CHIRPS-v2数据增强了降雨季节性和极端指数的识别,这对于水文应用至关重要.
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