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DOI | 10.1002/2017JD026648 |
Performance of Optimally Merged Multisatellite Precipitation Products Using the Dynamic Bayesian Model Averaging Scheme Over the Tibetan Plateau | |
Ma, Yingzhao1,2; Hong, Yang1,3; Chen, Yang4; Yang, Yuan1; Tang, Guoqiang1; Yao, Yunjun5; Long, Di1; Li, Changmin1; Han, Zhongying1; Liu, Ronghua6 | |
2018-01-27 | |
发表期刊 | JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES |
ISSN | 2169-897X |
EISSN | 2169-8996 |
出版年 | 2018 |
卷号 | 123期号:2页码:814-834 |
文章类型 | Article |
语种 | 英语 |
国家 | Peoples R China; USA |
英文摘要 | Accurate estimation of precipitation from satellites at high spatiotemporal scales over the Tibetan Plateau (TP) remains a challenge. In this study, we proposed a general framework for blending multiple satellite precipitation data using the dynamic Bayesian model averaging (BMA) algorithm. The blended experiment was performed at a daily 0.25 degrees grid scale for 2007-2012 among Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42RT and 3B42V7, Climate Prediction Center MORPHing technique (CMORPH), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR). First, the BMA weights were optimized using the expectation-maximization (EM) method for each member on each day at 200 calibrated sites and then interpolated to the entire plateau using the ordinary kriging (OK) approach. Thus, the merging data were produced by weighted sums of the individuals over the plateau. The dynamic BMA approach showed better performance with a smaller root-mean-square error (RMSE) of 6.77mm/day, higher correlation coefficient of 0.592, and closer Euclid value of 0.833, compared to the individuals at 15 validated sites. Moreover, BMA has proven to be more robust in terms of seasonality, topography, and other parameters than traditional ensemble methods including simple model averaging (SMA) and one-outlier removed (OOR). Error analysis between BMA and the state-of-the-art IMERG in the summer of 2014 further proved that the performance of BMA was superior with respect to multisatellite precipitation data merging. This study demonstrates that BMA provides a new solution for blending multiple satellite data in regions with limited gauges. |
英文关键词 | dynamic Bayesian model averaging satellite precipitation Tibetan Plateau data merging |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000425520200012 |
WOS关键词 | SURFACE-TEMPERATURE FORECASTS ; GAUGE OBSERVATIONS ; ERROR ANALYSIS ; UNCERTAINTY ; TMPA ; TRMM ; SET |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/32402 |
专题 | 气候变化 |
作者单位 | 1.Tsinghua Univ, Dept Hydraul Engn, State Key Lab Hydrosci & Engn, Beijing, Peoples R China; 2.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing, Peoples R China; 3.Univ Oklahoma, Sch Civil Engn & Environm Sci, Norman, OK 73019 USA; 4.Tianjin Normal Univ, Tianjin Key Lab Water Resources & Environm, Tianjin, Peoples R China; 5.Beijing Normal Univ, Fac Geog Sci, State Key Lab Remote Sensing Sci, Beijing, Peoples R China; 6.China Inst Water Resources & Hydropower Res, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Ma, Yingzhao,Hong, Yang,Chen, Yang,et al. Performance of Optimally Merged Multisatellite Precipitation Products Using the Dynamic Bayesian Model Averaging Scheme Over the Tibetan Plateau[J]. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,2018,123(2):814-834. |
APA | Ma, Yingzhao.,Hong, Yang.,Chen, Yang.,Yang, Yuan.,Tang, Guoqiang.,...&Liu, Ronghua.(2018).Performance of Optimally Merged Multisatellite Precipitation Products Using the Dynamic Bayesian Model Averaging Scheme Over the Tibetan Plateau.JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES,123(2),814-834. |
MLA | Ma, Yingzhao,et al."Performance of Optimally Merged Multisatellite Precipitation Products Using the Dynamic Bayesian Model Averaging Scheme Over the Tibetan Plateau".JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 123.2(2018):814-834. |
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