Downscaled climate variables from the MIROC5 GCM

URL: http://data.southcentralclimate.org/RedRiver/Downscaled/MIROC5/

Statistically downscaled daily maximum and minimum temperature, and daily precipitation over the Red River Basin. The predictors used to downscale were obtained from the MIROC5 Global Climate Model (realization 1).

MIROC5: HWatanabe M, Suzuki T, O’ishi R, Komuro Y, Watanabe S, Emori S, Takemura T, Chikira M, Ogura T, Sekiguchi M, Takata K, Yamazaki D, Yokohata T, Nozawa T, Hasumi H, Tatebe H, Kimoto M (2010) Improved Climate Simulation by MIROC5: Mean States, Variability, and Climate Sensitivity. Journal of Climate 23 (23):6312-6335. doi:10.1175/2010jcli3679.1

The folder contains historical and future (RCP 2.6, RCP 4.5 and RCP 8.5) simulations. The downscaled time series were generated using three statistical downscaling methods: EDQM, CDFt and BCQM. Every statistically downscaled variable has its corresponding quality control mask (qc_mask). The masks mark as NAs, in the case of precipitation, negative values, and in the case of the temperatures, the points that are +/- 6 C from what it would expected after applying a simple bias correction.

Please go to the main directory: http://data.cybercommons.org/dataset/downscaling-red-river-basin for a detailed description of the datasets in this collection (spatial and temporal resolution, observations used for training, and climate variables in the dataset).

The datasets can be downloaded as NetCDF or .zip files (Browse and Download tabs, respectively).

NetCDF files can be opened and visualized using open source software like R, Python, Panoply and Ferret. The NetCDF files contain additional metadata and can be used to geo-reference the time series. This functionality allows the users to open the NetCDF files using GIS software. For more information "Mapping and Modeling Weather and Climate with GIS", a book from Esri Press, offers a wealth of information for atmospheric research methods.

NOTE: We do not recommend the use of the BCQM method, as the CDFt method is considered an improvement of it. The datasets created using the BCQM method are published as a demonstration of the risks of using flawed methods.

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Field Value
Data last updated February 12, 2016
Metadata last updated February 12, 2016
Created February 12, 2016
Format NetCDF
License Creative Commons Attribution
createdover 3 years ago
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