Downscaled climate variables from the ...
Statistically downscaled daily maximum and minimum temperature, and daily precipitation over the Red River Basin. The predictors used to downscale were obtained from the MPI-ESM-LR Global Climate Model (realization 1).
MPI-ESM-LR: Giorgetta MA, Jungclaus J, Reick CH, Legutke S, Bader J, Böttinger M, Brovkin V, Crueger T, Esch M, Fieg K, Glushak K, Gayler V, Haak H, Hollweg H-D, Ilyina T, Kinne S, Kornblueh L, Matei D, Mauritsen T, Mikolajewicz U, Mueller W, Notz D, Pithan F, Raddatz T, Rast S, Redler R, Roeckner E, Schmidt H, Schnur R, Segschneider J, Six KD, Stockhause M, Timmreck C, Wegner J, Widmann H, Wieners K-H, Claussen M, Marotzke J, Stevens B (2013) Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the Coupled Model Intercomparison Project phase 5. Journal of Advances in Modeling Earth Systems 5 (3):572-597. doi:10.1002/jame.20038
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.
|Data last updated||February 16, 2016|
|Metadata last updated||February 16, 2016|
|Created||February 16, 2016|
|License||Creative Commons Attribution|
|created||over 3 years ago|