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| 基于TRMM 3B43产品的1998—2016年黄淮海平原降水时空特征研究 | |
| 引用本文： | 郭斌,邢文雪,李云,赵佳琪,冯凯月,黄壮壮.基于TRMM 3B43产品的1998—2016年黄淮海平原降水时空特征研究[J].地理科学,2021,41(7):1285-1294. |
| 作者姓名： | 郭斌 邢文雪 李云 赵佳琪 冯凯月 黄壮壮 |
| 作者单位： | 1.山东科技大学测绘与空间信息学院，山东 青岛 266590 2.北京师范大学全球变化与地球系统科学研究院，北京 100875 3.北京师范大学地理科学学部减灾与应急管理研究院，北京 100875 4.中国科学院南京土壤研究所土壤与农业可持续发展国家重点实验室，江苏 南京 210008 5.中国科学院地理科学与资源研究所，北京 100101 |
| 基金项目： | 国家自然科学基金项目(41807170);山东省重大科技创新工程项目(2019JZZY020103);山东省高等学校青创人才引育计划（卫星定位导航研究创新团队） |
| 摘 要： | 以黄淮海平原为研究区，基于59个气象站点的逐月降水数据，采用相关系数（R）、相对误差（BIAS）和均方根误差（RMSE）对TRMM 3B43降水产品的精度进行系统评估，揭示黄淮海平原降水的时空变化规律。研究表明：① TRMM 3B43产品对研究区内大部分气象站点存在轻微高估现象，总体上TRMM产品和站点数据在黄淮海平原的拟合效果较好，且月尺度的精度较年尺度高；② 1998—2016年黄淮海平原年降水和秋季降水增加明显，其余季节降水呈不同程度的减少趋势；③ 研究区降水在空间上呈从南到北递减的趋势，且南北降水差距较大。研究结果为卫星降水产品在中纬度地区水资源评估、农业生产和洪旱灾害等研究提供一定的参考。 |
| 关 键 词： | 黄淮海平原 TRMM 3B43 精度验证 降水 |
| 收稿时间： | 2021-02-26 |
| 修稿时间： | 2021-04-01 |
Temporal and Spatial Characteristics of Precipitation Based on TRMM 3B43 Product in the Huang-Huai-Hai Plain During 1998-2016 |
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| Guo Bin,Xing Wenxue,Li Yun,Zhao Jiaqi,Feng Kaiyue,Huang Zhuangzhuang.Temporal and Spatial Characteristics of Precipitation Based on TRMM 3B43 Product in the Huang-Huai-Hai Plain During 1998-2016[J].Scientia Geographica Sinica,2021,41(7):1285-1294. | |
| Authors: | Guo Bin Xing Wenxue Li Yun Zhao Jiaqi Feng Kaiyue Huang Zhuangzhuang |
| Abstract: | Accurate precipitation data are crucial for flood forecasting, drought monitoring and related emergency management. Therefore, how to obtain accurate precipitation data with good spatial and temporal resolution is one of the great challenges in the world. The Tropical Rainfall Measurement Satellite (TRMM) is the first satellite to measure precipitation. TRMM can well estimate the temporal and spatial distribution of precipitation; however, its accuracy and applicability in the mid-latitude area are worth studying. Therefore, this study aims to evaluate the accuracy of TRMM 3B43 product and analyze the temporal and spatial characteristics of precipitation in the Huang-Huai-Hai Plain during 1998-2016, using monthly precipitation data from 59 meteorological stations. And TRMM 3B43 product is validated adopting correlation coefficient (R), relative error (BIAS) and root mean square error (RMSE). The results show that: 1) On the annual and monthly scales, TRMM 3B43 product fits well with the meteorological station data, with R of 0.926 and 0.930 (P<0.01), respectively. 2) TRMM 3B43 overestimates the precipitation for 88% of the stations; the relative error is between -7% and 10% for 66% of the stations. The error of spatial distribution is uneven, and it is higher in the southeast than that in the central and northern regions. 3) During 1998 to 2016, the average annual precipitation shows an increasing trend in the Huang-Huai-Hai Plain. In addition, the precipitation shows an increasing trend in autumn, presenting decreasing trend in other seasons. Moreover, the precipitation presents the most obvious decreasing trend in summer. The annual precipitation is mainly concentrated in the warm season (April-October), accounting for about 86% of the total year. The precipitation accounts for about 1/4 of the year in July. 4) Dependented on latitude, precipitation gradually decreases from the south to the north. Among them, abundant precipitation is occurred in southern Henan, Anhui, and Jiangsu, while with less average annual precipitation in Hebei, Beijing, and Tianjin. The precipitation in summer presents the same spatial distribution characteristics with annual average precipitation. The study area shows obvious characteristics of dry and wet seasons. There is a dry period from January to May, and it is humid and rainy from June to September. Moreover, it enters a dry period again from October to December. Overall, this study will be valuable for both algorithm developers and users, as well as for associated products, and it will also better support disaster risk reduction and hydrological applications, especially in areas with a sparse rain gauge network. |
| Keywords: | the Huang-Huai-Hai Plain TRMM 3B43 accuracy verification precipitation |
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