Participate in ForceSMIP

1. Register: Register as a ForceSMIP contributor to get access to the data. Register here. Registration is simply to help us keep track of contributors, and ForceSMIP is open to anyone. 

2. Download the training and evaluation data: After registering, you will receive a link to a repository containing the training and evalution data. The training data consists of 9 variables (tos, tas, pr, psl, siconc, zmta, monmaxtasmax, monmintasmin, monmaxpr; see definitions below) for 5 large ensembles (CanESM2, 25 members; CESM2, 50 members; MIROC6,  50 members; MIROC-ES2L, 30 members; MPI-ESM1-2-LR, 30 members) over the period 1880-2100. The evaluation data consists of 10 ensemble members chosen from 9 different earth system models and from observations/reanalysis. The evaluation data includes different variables for different time periods (tiers): 

• Tier 1 (1950-2022): tos, tas, pr, psl, zmta, monmaxtasmax, monmintasmin, monmaxpr

• Tier 2 (1900-2022): tos, tas, pr (land only), psl

• Tier 3 (1979-2022): tos, tas, pr, psl, siconc

The metadata for the evaluation data is edited so that it doesn't show which model or observational dataset it came from. Please don't try to figure this out (there is no reason to cheat, and it will be clear if you do). 

3. Develop code that estimates the forced component: Codes will be judged on their ability to estimate the forced response (see definition below) for each member and each variable of the evaluation data. In other words, you will estimate the forced response based on individual ensemble members, and the estimate will be judged based on how well it agrees with the ensemble mean of the corresponding large ensemble. You should make 10 forced response estimates - one for each evaluation member - for each variable and time period. You can develop the code in whichever programming language you choose. We encourage you to make use of the training data to train/tune your method. 

4. Submit your contribution by March 1, 2024: Once you have estimated the forced response for all variables in the Tier 1 evaluation data [Note: due to the different spatial dimensions of zmta, this variable is not required], please fill out the submission form (will be made available to registered participants). This will give you access to space on a Google Drive to upload your forced response estimate (netCDF preferred; please ask the organizers before submitting another data type) and a zip folder with your code. We encourage you to also use the same method to estimate the forced response in the Tier 2 and Tier 3 evaluation data. More than one submission per participant is allowed, but please ask the organizers before making more than 5 submissions. Each submission will need a unique name, which will be entered into the submission form and then used to label the forced response estimate and associated code in the Google Drive.

See the full protocol here.

Please email Robb Jnglin Wills (r.jnglinwills@usys.ethz.ch) or one of the other organizers if you have any questions about the process. 

Forced response: Spatiotemporal evolution of anomalies in a climate quantity (either a monthly average or a monthly max or min) in response to external forcing (GHG, aerosols, volcanoes, land-use change, solar, etc.) once internal variability in that climate quantity has been removed. In the case of large ensemble data, the forced response will be defined by the ensemble mean. 

Variables:

tos: monthly-mean sea-surface temperature 

tas: monthly-mean surface air temperature 

pr: monthly-mean precipitation

psl: monthly-mean sea-level pressure

siconc: monthly-mean sea-ice concentration

zmta: monthly-mean zonal-mean air temperature

monmaxtasmax: monthly maximum of daily maximum surface air temperature 

monmintasmin: monthly minimum of daily minimum surface air temperature 

monmaxpr: monthly maximum of daily total precipitation