Bin Guo

Dr. Bin Guo

Shandong University of Science and Technology
orcid

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 November 2012 in Journal of Hydrology
Verified
Journal Article
Closed access
XHXing-Ming Hao
Xing-Ming Hao
CLCong Li
Cong Li
BGBin Guo
Bin Guo
JMJian-Xin Ma
Jian-Xin Ma
MAMubarek Ayup
Mubarek Ayup
Zhongsheng ChenZhongsheng Chen
Zhongsheng Chen

1 February 2019 in Science of The Total Environment
Verified
Journal Article
Closed access
Hongbo LingHongbo Ling
Hongbo Ling
BGBin Guo
Bin Guo
GZGuangpeng Zhang
Guangpeng Zhang
HXHailiang Xu
Hailiang Xu
XDXiaoya Deng
Xiaoya Deng

22 March 2019 in Remote Sensing
Verified
Journal Article
Open access
PDF file
FXfenglin xu
fenglin xu
BGBin Guo
Bin Guo
BYBei Ye
Bei Ye
QYQia Ye
Qia Ye
HCHuining Chen
Huining Chen
ZWZhong-Liang Wang
Zhong-Liang Wang
Accurate estimation of high-resolution satellite precipitation products like Global Precipitation Measurement (GPM) and Tropical Rainfall Measuring Mission (TRMM) is critical for hydrological and meteorological research, providing a benchmark for the continued development and future improvement of these products. This study aims to comprehensively evaluate the Integrated Multi-Satellite Retrievals for GPM (IMERG) and TRMM 3B42V7 products at multiple temporal scales from 1 January 2015 to 31 December 2017 over the Huang-Huai-Hai Plain in China, using daily precipitation data from 59 meteorological stations. Three commonly used statistical metrics (CC, RB, and RMSE) are adopted to quantitatively verify the accuracy of two satellite precipitation products. The assessment also takes into account the precipitation detection capability (POD, FAR, CSI, and ACC) and frequency of different precipitation intensities. The results show that the IMERG and 3B42V7 present strong correlation with meteorological stations observations at annual and monthly scales (CC > 0.90), whereas moderate at the daily scale (CC = 0.76 and 0.69 for IMERG and 3B42V7, respectively). The spatial variability of the annual and seasonal precipitation is well captured by these two satellite products. And spatial patterns of precipitation gradually decrease from south to north over the Huang-Huai-Hai Plain. Both IMERG and 3B42V7 products overestimate precipitation compared with the station observations, of which 3B42V7 has a lower degree of overestimation. Relative to the IMERG, annual precipitation estimates from 3B42V7 show lower RMSE (118.96 mm and 142.67 mm, respectively), but opposite at the daily, monthly, and seasonal scales. IMERG has a better precipitation detection capability than 3B42V7 (POD = 0.83 and 0.67, respectively), especially when detecting trace and solid precipitation. The two precipitation products tend to overestimate moderate (2–10 mm/d) and heavy (10–50 mm/d) precipitation events, but underestimate violent (>50 mm/d) precipitation events. The IMERG is not found capable to detecting precipitation events of different frequencies more precisely. In general, the accuracy of IMERG is better than 3B42V7 product in the Huang-Huai-Hai Plain. The IMERG satellite precipitation product with higher temporal and spatial resolutions can be regarded a reliable data sources in studying hydrological and climatic research.

1 November 2014 in Global and Planetary Change
Verified
Journal Article
Closed access
HLHongbo Ling
Hongbo Ling
BGBin Guo
Bin Guo
HXHailiang Xu
Hailiang Xu
JFJinyi Fu
Jinyi Fu

1 April 2019 in Science of The Total Environment
Verified
Journal Article
Closed access
Hongbo LingHongbo Ling
Hongbo Ling
JYJunjie Yan
Junjie Yan
HXHailiang Xu
Hailiang Xu
BGBin Guo
Bin Guo
QZQingqing Zhang
Qingqing Zhang

1 May 2019 in Journal of Hydrology
Verified
Journal Article
Closed access
HLHongbo Ling
Hongbo Ling
HXHailiang Xu
Hailiang Xu
BGBin Guo
Bin Guo
XDXiaoya Deng
Xiaoya Deng
PZPei Zhang
Pei Zhang
XWXiyi Wang
Xiyi Wang