How feasible is it to predict Arctic climate at seasonal-to-interannual timescales? As part of the APPOSITE project a multi-model ensemble prediction experiment was conducted in order to answer this question.
The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial condition predictability experiments with seven general circulation models was conducted. This was the first intercomparison project designed to quantify the predictability of Arctic climate on seasonal to interannual timescales.
Several different coupled climate models performed simulations for APPOSITE (see Doc below for Details of simulations submitted to the APPOSITE database). Six of these models followed the same experimental protocol (see Doc below for Control Simulations details and for Ensemble Predictions). One model, CanCM4 followed a slightly different protocol.
The Model data output from the APPOSITE project are now archived at CEDA. The collection of model outputs (control and prediction) include data from:
- Canadian Centre for Climate Modelling and Analysis (CanCM4)
- ECHAM6-FESOM (E6F), run and developed by the Alfred Wegener Institute.
- EC-Earth consortium (ec-earth_v2_3)
- Geophysical Fluid Dynamics Laboratory (gfdlcm3)
- Met Office (hadgem1-2)
- Model for Interdisciplinary Research on Climate (MIROC5-2)
- Max-Planck-Institut for Meteorologie (mpiesm)
Although designed to address Arctic predictability, this data set could also be used to assess the predictability of other regions and modes of climate variability on these timescales, such as the El Nino Southern Oscillation.
A paper describing the simulations for APPOSITE is in preparation to be submitted to the Geoscientific Model Development Journal.
Note: These data do not correspond to a particular time period since the studies are all conducted in the model world. They are not predictions or attempts to simulate a particular period of time. So the dates in the files are completely arbitrary.