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Title: Non-stationary bias correction of monthly CMIP5 temperature projections over China using a residual-based bagging tree model: Non-stationary Bias Correction of GCMs Ensemble

Abstract

Not provided.

Authors:
 [1]; ORCiD logo [1];  [1];  [2];  [3];  [4]
  1. Department of Civil and Environmental Engineering, University of California, Irvine CA USA
  2. State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, China
  3. China's Agenda21, The Administrative Center, Beijing China
  4. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China, Institute of Water Resources and Hydropower Research, Beijing China
Publication Date:
Research Org.:
Univ. of California, Oakland, CA (United States)
Sponsoring Org.:
USDOE Office of International Affairs (IA)
OSTI Identifier:
1537578
DOE Contract Number:  
IA0000018
Resource Type:
Journal Article
Journal Name:
International Journal of Climatology
Additional Journal Information:
Journal Volume: 38; Journal Issue: 1; Journal ID: ISSN 0899-8418
Publisher:
Royal Meteorological Society
Country of Publication:
United States
Language:
English
Subject:
Meteorology & Atmospheric Sciences

Citation Formats

Tao, Yumeng, Yang, Tiantian, Faridzad, Mohammad, Jiang, Lin, He, Xiaojia, and Zhang, Xiaoming. Non-stationary bias correction of monthly CMIP5 temperature projections over China using a residual-based bagging tree model: Non-stationary Bias Correction of GCMs Ensemble. United States: N. p., 2017. Web. doi:10.1002/joc.5188.
Tao, Yumeng, Yang, Tiantian, Faridzad, Mohammad, Jiang, Lin, He, Xiaojia, & Zhang, Xiaoming. Non-stationary bias correction of monthly CMIP5 temperature projections over China using a residual-based bagging tree model: Non-stationary Bias Correction of GCMs Ensemble. United States. https://doi.org/10.1002/joc.5188
Tao, Yumeng, Yang, Tiantian, Faridzad, Mohammad, Jiang, Lin, He, Xiaojia, and Zhang, Xiaoming. 2017. "Non-stationary bias correction of monthly CMIP5 temperature projections over China using a residual-based bagging tree model: Non-stationary Bias Correction of GCMs Ensemble". United States. https://doi.org/10.1002/joc.5188.
@article{osti_1537578,
title = {Non-stationary bias correction of monthly CMIP5 temperature projections over China using a residual-based bagging tree model: Non-stationary Bias Correction of GCMs Ensemble},
author = {Tao, Yumeng and Yang, Tiantian and Faridzad, Mohammad and Jiang, Lin and He, Xiaojia and Zhang, Xiaoming},
abstractNote = {Not provided.},
doi = {10.1002/joc.5188},
url = {https://www.osti.gov/biblio/1537578}, journal = {International Journal of Climatology},
issn = {0899-8418},
number = 1,
volume = 38,
place = {United States},
year = {2017},
month = {8}
}

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