Locally Downscaled and Spatially Customizable Climate Data for Historical and Future Periods for North America.
Large volumes of gridded climate data have become available in recent years including interpolated historical data from weather stations and future predictions from general circulation models. These datasets, however, are at various spatial resolutions that need to be converted to scales meaningful...
Main Authors: | Tongli Wang, Andreas Hamann, Dave Spittlehouse, Carlos Carroll |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2016-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC4898765?pdf=render |
Similar Items
-
ClimateAP: an application for dynamic local downscaling of historical and future climate data in Asia Pacific
by: Tongli WANG, Guangyu WANG, John L. INNES, Brad SEELY, Baozhang CHEN
Published: (2017-12-01) -
Future Climate of Colombo Downscaled with SDSM-Neural Network
by: Singay Dorji, et al.
Published: (2017-03-01) -
Using statistical downscaling to project the future climate of Hong Kong
by: Cheung, Chi-shing, Calvin, et al.
Published: (2015) -
Weather-Type Statistical Downscaling and Future Projection for Wave Climate in Taiwan
by: Chi-HsiangTseng, et al.
Published: (2018) -
Downscaling of climate extremes over South America – Part I: Model evaluation in the reference climate
by: Claudine Dereczynski, et al.
Published: (2020-09-01)