ColdBlobMIP

ColdBlobMIP is an ad hoc atmospheric model intercomparison project (AMIP) wherein a numer of models (9 base models plus some variations in configuration) simulated the atmospheric response to the observed North Atlantic Warming Hole (NAWH). This collection of model outputs includes the variables analyzed in Kramer et al. (2025, in revision): sea level pressure, surface wind speed and total cloud cover. The files are in MATLAB v7.0 format. Python users can open the files with one line of code after importing SciPy (https://stackoverflow.com/questions/874461/read-mat-files-in-python). import scipy.iomat = scipy.io.loadmat('file.mat') The files ColdBlobMIP_SLP_DJF.mat, ColdBlobMIP_Wind_DJF.mat and ColdBlobMIP_Clouds_JJA.mat contain the seasonal mean variables needed to reproduce the results of Kramer et al. (2025, in revision). They were regridded to a common 1° lat/lon grid, and the first three years were discarded as spinup. In each .mat file, there is one array per model (1-15) and simulation (1 for control, 2 for cold blob). For example, in the file ColdBlobMIP_SLP_DJF.mat, the array p2_3 is SLP from the cold blob run of the 3rd model (see Table 1 of Kramer et al., 2025 for identification and other information on the 15 models). The first (time) dimension of each array has a different length due to the different number of years simulated by each model. Each file also includes coordinate vectors (lat and lon), and arrays with the time means from each model stored (e.g., p1 and p2 have dimensions 15 models x 181 latitudes x 361 longitudes). The control simulation was run with an unaltered, perpetually-repeating, seasonally-varying climatological SST forcing prescribed. The cold blob simulation was run as in control, but with the cold blob SST anomaly added to the control SST climatology. The file ColdBlobMIP_SSTA.mat provides the cold blob SST anomaly from model 1 on the native grid of model 1, from which all others derived their SST anomaly via interpolation.