Dataset DOI: 10.5061/dryad.c59zw3rkq

Description of the data and file structure

This is the relevant model data from MITgcm simulations for the paper “Understanding ENSO Weakening in Warmer Climates” (https://doi.org/10.1029/2024GL113124). The code is available here: “verification_other/cpl_gray+swamp+ocn at master · MITgcm/verification_other · GitHub”. The goal of the simulations and data included here was to understand how ENSO events differ in warmer climates. The simulations were warmed by changing the longwave absorption efficiency of CO_2 (ir_tau_co2) in the code, and run for at least 750 years so they would come to a quasi-steady-state. The data stored here is from after this equilibriation period.

Directory structure and variables

All data is stored in one zip file, which contains data for all five simulations studied. Below is a description of the relevant folders and variables.

File: 20240826ENSOWarmingSummaries.7z

Description: This is a zip file with summaries of each simulation

Folder: C2IRT3ENSO

Description: Data for the “cold” simulation (discussed in the paper), with mean equatorial temperature of 295.8 K and longwave absorption efficiency of CO_2 of 0.87.

Folder: C2IRT4ENSO

Description: Data for the “cool” simulation, with mean equatorial temperature of 299.5 K and longwave absorption efficiency of CO_2 of 1.15.

Folder: C2IRT5ENSO

Description: Data for the “Temperate” simulation, with mean equatorial temperature of 302.8 K and longwave absorption efficiency of CO_2 of 1.45.

Folder: C2IRT6ENSO

Description: Data for the “Warm” simulation, with mean equatorial temperature of 305.6 K and longwave absorption efficiency of CO_2 of 1.74.

Folder: C2IRT7ENSO

Description: Data for the “Hot” simulation, with mean equatorial temperature of 308.4 K and longwave absorption efficiency of CO_2 of 2.02.

Files and Variables:

Description: Each folder listed above contains the following five .mat files, with relevant variables:

• AllPrecipAndSST.mat
  • Grid – A structure with the relevant information about the MITgcm cubed sphere grid.
  • Time – A time vector (1x12000) in units of seconds for each datapoint in the other variables. Covers 200 years with 60 data points per year
  • YearShapedPrecip – Precipitation data (192x32x1x60x200), where the first two dimensions are spatial dependencies at stored in Grid.XC and Grid.YC, while the fourth dimension is time of year, and the fifth dimension is the year
  • YearShapedSST – SST data with the same shape as the Precip data.
• AtmosphereFields.mat
  • Grid
  • Time
  • ClimatologicalMeanTheta – Potential temperature data in the atmosphere (192x32x26x60) as a function of X, Y, pressure (coordinates in Grid.XC, Grid.YC, and Grid.RC), and time of year (fourth dimension). Data is averaged over the 200 years indicated in the Time dimension.
  • ClimatologicalMeanq – Specific humidity data, same shape as the potential temperature data.
  • ClimatologicalMeanPhiHyd – Geopotential data (units of J/kg), same shape as the potential temperature data.
  • ClimatologicalMeanUVel – Wind velocity in the x-direction, same shape as the potential temperature data with one additional point in the x-direction. Note that this is not the same as Eastward wind. In order to convert to East wind run [EastVel,NorthVel]=rotate_uv2uv_EN(UVel,VVel,Grid.AngleCS,Grid.AngleSN) from the MITgcm/Utils available on the MITgcm github. The data is located on the -X edge of each cell.
  • ClimatologicalMeanVVel – Wind velocity in the y-direction (not North), same shape is the potential temperature data with one additional point in the y-direction. Data is located on the -Y edge of each cell.
  • ClimatologicalMeanWVel – Wind velocity in the z-direction, units of Pa/s. Same shape as the potential temperature data.
  • ClimatologicalMeanUTheta – Same as ClimatologicalMeanUVel, but transport of potential temperature instead of wind.
  • ClimatologicalMeanVTheta – Same as ClimatologicalMeanVVel, but transport of potential temperature instead of wind.
  • ClimatologicalMeanUq – Same as ClimatologicalMeanUTheta, but transport of specific humidity instead of potential temperature.
  • ClimatologicalMeanVq – Same as ClimatologicalMeanVTheta, but transport of specific humidity instead of potential temperature.
  • ClimatologicalMeanUPhi – Same as ClimatologicalMeanUTheta, but transport of geopotential instead of potential temperature.
  • ClimatologicalMeanVPhi – Same as ClimatologicalMeanVTheta, but transport of geopotential instead of potential temperature.
  • ClimatologicalMeanEFP – Climatological mean energy flux potential, defined such that its gradients indicate negative transport of moist static energy. For further information, see Boos and Korty, 2016 (https://doi.org/10.1038/ngeo2833), or Tuckman et al., 2024 (https://doi.org/10.1175/JCLI-D-23-0125.1).
• AtmosphereSurface.mat
  • Grid
  • Time
  • ClimatologicalMeanPrecip – Precipitation data, same as the fields described in the file AtmosphereFields.mat, but no vertical dependence (shape: 192x32x1x60).
  • ClimatologicalMeanSST – SST data, similar to precipitation data.
  • ClimatologicalMeanEvap – Evaporation data, similar to precipitation data.
  • ClimatologicalMeanSensible – Surface sensible heat data, similar to precipitation data.
  • ClimatologicalMeanSurfaceOLR – Surface net longwave radiation (units of W/m^2), similar to precipitation data.
  • ClimatologicalMeanSurfaceUpwardOLR – Surface upward longwave radiation (units of W/m^2), similar to precipitation data.
  • ClimatologicalMeanTOAOLR – Top-of-atmosphere net longwave radiation (units of W/m^2), similar to precipitation data.
  • ClimatologicalMeanTOANSR – Top-of-atmosphere net shortwave radiation (units of W/m^2), similar to precipitation data.
• OceanFields.mat
  • Grid – Same as grid described above, but for the ocean instead of atmosphere. The horizontal grid is the same but the vertical grid is different.
  • ClimatologicalMeanTheta – Potential temperature data, same as described in AtmosphereFields.mat, but for the ocean.
  • ClimatologicalMeanUVel – Current in the x-direction, same as described in AtmosphereFields.mat, but for the ocean.
  • ClimatologicalMeanVVel – Current in the y-direction, same as described in AtmosphereFields.mat, but for the ocean.
  • ClimatologicalMeanWVel – Current in the z-direction, same as described in AtmosphereFields.mat, but for the ocean and with units of m/s.
  • ClimatologicalMeanUTheta – Potential temperature transport in the x-direction, same as described in AtmosphereFields.mat, but for the ocean.
  • ClimatologicalMeanVTheta – Potential temperature transport in the y-direction, same as described in AtmosphereFields.mat, but for the ocean.
  • ClimatologicalMeanWTheta – Potential temperature transport in the z-direction, same as described in AtmosphereFields.mat, but for the ocean.
• TwoHundredYearData.mat
  • AtmosphereDSLR – Downward surface longwave radiation, with coordinates indicating X, Y, 1 (no vertical dependence), time of year, and year.
  • AtmosphereEvaporation – Evaporative data, same shape as AtmosphereDSLR.
  • AtmosphereGrid – As described from the Grid in the atmosphere files above
  • AtmosphereNSSR – Net surface solar radiation, same shape as AtmosphereDSLR.
  • AtmosphereSensible – Surface sensible heat flux, same shape as AtmosphereDSLR.
  • AtmosphereSurfaceUVel – Lowest level x-direction wind, same shape as AtmosphereDSLR with one additional point in the x-direction.
  • AtmosphereSurfaceVVel – Lowest level y-direction wind, same shape as AtmosphereDSLR with one additional point in the y-direction.
  • AtmosphereTauX – Wind stress on the ocean exerted by the atmosphere in the x-direction, same shape as AtmosphereDSLR.
  • AtmosphereTauY – Wind stress on the ocean exerted by the atmosphere in the y-direction, same shape as AtmosphereDSLR.
  • AtmosphereUSLR – Upward surface longwave radiation, same shape as AtmosphereDSLR.
  • OceanGrid – As described from the Grid in the ocean files above
  • SurfaceTheta – The top 8 levels of potential temperature data from the ocean, with a shape of 192x32x8x60x200. Eight levels are chosen as that is the relevant portion of the ocean for ENSO events, and saving the entire ocean’s worth of data as a function of depth and year would be prohibitively expensive.
  • SurfaceUTh – X-direction transport of potential temperature, same shape as SurfaceTheta with one additional point in the x-direction.
  • SurfaceUVel – X-direction current, same shape as SurfaceTheta with one additional point in the x-direction.
  • SurfaceVTh – Y-direction transport of potential temperature, same shape as SurfaceTheta with one additional point in the y-direction.
  • SurfaceVVel – X-direction current, same shape as SurfaceTheta with one additional point in the y-direction.
  • SurfaceWTh – Z-direction transport of potential temperature, same shape as SurfaceTheta.
  • SurfaceWVel – Z-direction current, same shape as SurfaceTheta.
• TwoHundredYearDataOceanOnly.mat – The final two folders (C2IRT6ENSO and C2IRT7ENSO) also have this file, with the ocean variables from TwoHundredYearData.mat. The existence of this smaller file makes it easier to load just the ocean variables if that is desired.

Code/software

The data is in .mat files, so can be read in matlab with “load(FILENAME.mat)”. Many helpful manipulations of the data can be done with the Utils folder in the MITgcm github.