MHW_Forecasts

Code used to create forecasts in Jacox et al. (2022), Global Seasonal Forecasts of Marine Heatwaves, Nature, doi:10.1038/s41586-022-04573-9.

MHW forecasts are calculated using monthly sea surface temperature output from the North American Multimodel Ensemble. Steps in the workflow, with associated matlab scripts, are:

1. Download NMME forecasts

Download SST forecasts from the North American Multimodel Ensemble using OPeNDAP. Saves file organized by lead time for use in subsequent analyses.

Script called:
download_nmme_forecasts.m

Data generated:
Hindcast and forecast SST organized by lead time

2. Concatenate hindcasts and forecasts

Join hindcasts and forecasts to a single dataset for each model Keeps same number of forecast ensemble members as used for hindcast Applies hindcast land mask to forecasts Converts units from K to C where needed

Script called:
concatenate_nmme_forecasts.m

Data generated:
Concatenated forecasts organized by lead time

3. Calculate model ensemble means

Calculate ensemble means for each model from concatenated hindcast/forecast output

Script called:
calc_nmme_ensemble_means.m

Data generated:
Ensemble means for each model

4. Calculate model ensemble mean climatologies

Calculate climatologies from ensemble means of concatenated hindcast/forecast output

Script called:
calc_nmme_climatology.m

Data generated:
Climatologies for each model

5. Calculate forecast anomalies

Calculate SST anomalies from SST forecasts and lead-dependent monthly climatologies

Script called:
calc_nmme_anomalies.m

Data generated:
Concatenated forecast anomalies organized by lead time for each model

6. Detrend forecast anomalies

Remove linear trends from forecast anomalies. Subsequent steps are performed using forecast with trends removed as well as with trends retained.

Script called:
detrend_nmme_anomalies.m

Data generated:
Detrended forecast anomalies organized by lead time for each model

7. Calculate MHW thresholds and identify MHWs

Calculate seasonally-varying 90th percentile SST anomaly thresholds and use them to define forecast MHWs

Script called:
calc_nmme_mhw.m

Data generated:
Forecast MHWs organized by lead time for each model, with and without detrending

8. Create multimodel ensemble MHW forecasts

Combine MHW forecasts from individual models into a multimodel ensemble

Scripts called:
nmme_ensemble_mhw.m

Data generated:
Multimodel ensemble forecast MHWs organized by lead time, with and without detrending