ANN-based statistical downscaling of climatic parameters using decision tree predictor screening method
作者： Vahid Nourani , Zahra Razzaghzadeh , Aida Hosseini Baghanam , Amir Molajou
DOI: 10.1007/S00704-018-2686-Z
关键词:
摘要: In this paper, artificial neural network (ANN) was used for statistically downscale the outputs of general circulation models (GCMs) to assess future changes precipitation and mean temperature in Tabriz synoptic station at north-west Iran. Since one significant subjects statistical downscaling GCMs is select most dominant large scale climate variables (predictors) among huge number potential predictors, predictors screening methods including decision tree, mutual information (MI) correlation coefficient (CC) were monthly temperature. Three used, Can-ESM2 BNU-ESM from IPCC AR5 CGCM3 AR4 models. The results base period (1951–2000) indicated that feature extraction tree had superiority MI CC techniques. Therefore, projection during 2020–2060 implemented using ANN-based simulation according efficient model (i.e., tree-based calibration). Different different scenarios obtained projection. way, under RCP8.5 showed 29.78% decrease annual B1 1.06% increase precipitation. Temperature outcomes denoted will over region determined by RCP8.5.
springer.com
harvard.edu
sci-hub.se 参考文章(66)
Riccardo Taormina, Kwok-Wing Chau, Bellie Sivakumar, Neural network river forecasting through baseflow separation and binary-coded swarm optimization Journal of Hydrology. ,vol. 529, pp. 1788- 1797 ,(2015) , 10.1016/J.JHYDROL.2015.08.008
P. R. Tiwari, S. C. Kar, U. C. Mohanty, S. Kumari, P. Sinha, A. Nair, S. Dey, Skill of precipitation prediction with GCMs over north India during winter season International Journal of Climatology. ,vol. 34, pp. 3440- 3455 ,(2014) , 10.1002/JOC.3921
S. Galelli, A. Castelletti, Tree‐based iterative input variable selection for hydrological modeling Water Resources Research. ,vol. 49, pp. 4295- 4310 ,(2013) , 10.1002/WRCR.20339
Casey Brown, William Werick, Wendy Leger, David Fay, A Decision‐Analytic Approach to Managing Climate Risks: Application to the Upper Great Lakes1 Journal of The American Water Resources Association. ,vol. 47, pp. 524- 534 ,(2011) , 10.1111/J.1752-1688.2011.00552.X
Thomas F Stocker, Dahe Qin, G-K Plattner, Melinda MB Tignor, Simon K Allen, Judith Boschung, Alexander Nauels, Yu Xia, Vincent Bex, Pauline M Midgley, Climate change 2007 : the physical science basis : contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change Published in <b>2007</b> in Cambridge by Cambridge university press. ,(2007) , 10.1017/CBO9781107415324
Nachiketa Acharya, Surajit Chattopadhyay, U. C. Mohanty, S. K. Dash, L. N. Sahoo, On the bias correction of general circulation model output for Indian summer monsoon Meteorological Applications. ,vol. 20, pp. 349- 356 ,(2013) , 10.1002/MET.1294
Y.B. Dibike, P. Coulibaly, Temporal neural networks for downscaling climate variability and extremes international joint conference on neural network. ,vol. 3, pp. 1636- 1641 ,(2005) , 10.1109/IJCNN.2005.1556124
Mark A. Hall, Ian H. Witten, Eibe Frank, Data Mining: Practical Machine Learning Tools and Techniques ,(1999)
B. Timbal, A. Dufour, B. McAvaney, An estimate of future climate change for western France using a statistical downscaling technique Climate Dynamics. ,vol. 20, pp. 807- 823 ,(2003) , 10.1007/S00382-002-0298-9
Zhiyong Gao, Bin Gu, Jiarui Lin, Monomodal image registration using mutual information based methods Image and Vision Computing. ,vol. 26, pp. 164- 173 ,(2008) , 10.1016/J.IMAVIS.2006.08.002