Ocean and marine heatwaves responses to multiple net-zero worlds - datasets and scripts for Figures 1 to 10

Files and code in data_and_script_FINAL.tar.gz provide the required information to create Figure 1 to 10 of the paper. Before using the data you need to uncompress it. Scripts are coded in Python. You can find hereafter a few information on their organization.

1] In the compressed folder you will find datasets and scripts organized as follows:

data_and_script_FINAL/

_____DATA/

__________dataframe/

_______________dataframe_02Kpd_timeseries_yearly_co2s.csv

_______________dataframe_02Kpd_timeseries_yearly_hfds.csv

_______________dataframe_02Kpd_timeseries_yearly_msftyz.csv

_______________dataframe_02Kpd_timeseries_yearly_tas.csv

_______________dataframe_02Kpd_timeseries_yearly_thetao_lev1.csv

_______________dataframe_02Kpd_timeseries_yearly_thetao_lev2.csv

_______________dataframe_02Kpd_timeseries_yearly_tos.csv

__________netcdf/

_______________FDR_KS_all/

_______________net_zero_MHW_frequency/

_______________net_zero_MHW_intensity/

_______________net_zero_mean/

_______________net_zero_std/

_______________tos_Omon/

_______________transient_MHW_frequency/

_______________transient_MHW_intensity/

_______________transient_mean/

_______________transient_std/

_____script/

__________f01_script.py

__________f02_script.py

__________f03_script.py

__________f04_script.py

__________f05_script.py

__________f06_script.py

__________f07_script.py

__________f08_script.py

__________f09_script.py

__________f10_script.py

2] Scipts are stored in the script folder. They are named "fXX_script.py" with XX being th Figure number. For example, when f02_script.py is run it plots Figure 2 of the paper. It searches for data in the DATA folder.

3] Data are stored in the netcdf or dataframe folder according to their type (.nc or .csv). They can be direct model outputs such as those in the tos_Omon folder or they can be processed data. Not all model outputs where given since it would be too heavy.

4] Global mean yearly timeseries are stored in the dataframe folder. We give their units hereafter: 

dataframe_02Kpd_timeseries_yearly_co2s.csv: ppm

dataframe_02Kpd_timeseries_yearly_hfds.csv: W/m2

dataframe_02Kpd_timeseries_yearly_msftyz.csv: Sv

dataframe_02Kpd_timeseries_yearly_tas.csv: °C

dataframe_02Kpd_timeseries_yearly_thetao_lev1.csv: °C

dataframe_02Kpd_timeseries_yearly_thetao_lev2.csv: °C

dataframe_02Kpd_timeseries_yearly_tos.csv: °C

5] We review hereafter information on the netcdf folder. File name that contain "02Kpd" or "02Kpd-XX" refer to the ramp-up or net-zero runs 

FDR_KS_all/: contains netcdf showing the results of the False Discovery Rate (FRD) on the Kolmogorov-Smirnov test applied to the whole net-zero runs.

net_zero_MHW_frequency/: contains day-of-year mean frequency of MHW over periods stated in filename. This is for each net-zero run. Unit: dimensionless

net_zero_MHW_intensity/: contains day-of-year mean intensity of MHW over periods stated in filename. This is for each net-zero run. Unit: °C

net_zero_mean/: Mean of the SST anomaly distribution over the whole net-zero runs. Unit: °C

net_zero_std/: Standard-deviation of the SST anomaly distribution over the whole net-zero runs. Unit: °C

tos_Omon/: contains grided monthly sea surface temperature in °C for the ramp-up and all net-zero runs.

transient_MHW_frequency/: contains day-of-year mean frequency of MHW over periods stated in filename (baseline periods). This is for the ramp-up. Unit: dimensionless

transient_MHW_intensity/: contains day-of-year mean intensity of MHW over periods stated in filename (baseline periods). This is for the ramp-up. Unit: °C

transient_mean/: Mean of the SST anomaly distribution over transient baseline periods indicated in filename. Unit: °C

transient_std/: Standard-deviation of the SST anomaly distribution over transient baseline periods indicated in filename. Unit: °C