Anming Bao

Prof. Dr. Anming Bao

Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China

Research Focus & Metrics

Academic Career Length

21Years (2006-Present)

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

Representative Publications

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1 December 2017 in Science of The Total Environment
Verified
Journal Article
Closed access
LJLiangliang Jiang
Liangliang Jiang
GUGuli·jiapaer
Guli·jiapaer
ABAnming Bao
Anming Bao
Hao GuoHao Guo
Hao Guo
FNFelix Ndayisaba
Felix Ndayisaba

6 May 2021 in Nature Climate Change
Verified
Journal Article
Closed access
PDF file
Guoxiong ZhengGuoxiong Zheng
Guoxiong Zheng
SASimon Keith Allen
Simon Keith Allen
ABAnming Bao
Anming Bao
JCJuan Antonio Ballesteros Canovas
Juan Antonio Ballesteros Canovas
MHMatthias Huss
Matthias Huss
MSMarkus Stoffel
Markus Stoffel

1 May 2018 in Science of The Total Environment
Verified
Journal Article
Closed access
Hao GuoHao Guo
Hao Guo
ABAnming Bao
Anming Bao
TLTie Liu
Tie Liu
GJGuli Jiapaer
Guli Jiapaer
FNFelix Ndayisaba
Felix Ndayisaba
Philippe De MaeyerPhilippe De Maeyer
Philippe De Maeyer

1 February 2019 in Science of The Total Environment
Verified
Journal Article
Closed access
CTChen Tao
Chen Tao
ABAnming Bao
Anming Bao
GJGuli Jiapaer
Guli Jiapaer
Hao GuoHao Guo
Hao Guo
Guoxiong ZhengGuoxiong Zheng
Guoxiong Zheng
LTLatipa Tuerhanjiang
Latipa Tuerhanjiang

7 August 2018 in Water
Verified
Journal Article
Open access
PDF file
MLMin Luo
Min Luo
TLTie Liu
Tie Liu
FMFanhao Meng
Fanhao Meng
YDYongchao Duan
Yongchao Duan
AFAmaury Frankl
Amaury Frankl
Philippe De MaeyerPhilippe De Maeyer
Philippe De Maeyer
The systemic biases of Regional Climate Models (RCMs) impede their application in regional hydrological climate-change effects analysis and lead to errors. As a consequence, bias correction has become a necessary prerequisite for the study of climate change. This paper compares the performance of available bias correction methods that focus on the performance of precipitation and temperature projections. The hydrological effects of these correction methods are evaluated by the modelled discharges of the Kaidu River Basin. The results show that all used methods improve the performance of the original RCM precipitation and temperature simulations across a number of levels. The corrected results obtained by precipitation correction methods demonstrate larger diversities than those produced by the temperature correction methods. The performance of hydrological modelling is highly influenced by the choice of precipitation correction methods. Furthermore, no substantial differences can be identified from the results of the temperature-corrected methods. The biases from input data are often greater from the works of hydrological modelling. The suitability of these approaches depends upon the regional context and the RCM model, while their application procedure and a number of results can be adapted from region to region.

1 September 2018 in Journal of Hydrology
Verified
Journal Article
Closed access
Hao GuoHao Guo
Hao Guo
ABAnming Bao
Anming Bao
FNFelix Ndayisaba
Felix Ndayisaba
TLTie Liu
Tie Liu
GJGuli Jiapaer
Guli Jiapaer
PMPhilippe De Maeyer
Philippe De Maeyer