Development towards a global operational aerosol consensus: basic climatological characteristics of the International Cooperative for Aerosol Prediction Multi-Model Ensemble (ICAP-MME)

Here we present the first steps in developing a global multi-model aerosol forecasting ensemble intended for eventual operational and basic research use. Drawing from members of the International Cooperative for Aerosol Prediction (ICAP) latest generation of quasi-operational aerosol models, 5-day aerosol optical thickness (AOT) forecasts are analyzed for December 2011 through November 2012 from four institutions: European Centre for Medium-Range Weather Forecasts (ECMWF), Japan Meteorological Agency (JMA), NASA Goddard Space Flight Center (GSFC), and Naval Research Lab/Fleet Numerical Meteorology and Oceanography Center (NRL/FNMOC). For dust, we also include the National Oceanic and Atmospheric Administration-National Geospatial Advisory Committee (NOAA NGAC) product in our analysis. The Barcelona Supercomputing Centre and UK Met Office dust products have also recently become members of ICAP, but have insufficient data to be included in this analysis period. A simple consensus ensemble of member and mean AOT fields for modal species (e.g., fine and coarse mode, and a separate dust ensemble) is used to create the ICAP Multi-Model Ensemble (ICAP-MME). The ICAP-MME is run daily at 00:00 UTC for 6-hourly forecasts out to 120 h. Basing metrics on comparisons to 21 regionally representative Aerosol Robotic Network (AERONET) sites, all models generally captured the basic aerosol features of the globe. However, there is an overall AOT low bias among models, particularly for high AOT events. Biomass burning regions have the most diversity in seasonal average AOT. The Southern Ocean, though low in AOT, nevertheless also has high diversity. With regard to root mean square error (RMSE), as expected the ICAP-MME placed first over all models worldwide, and was typically first or second in ranking against all models at individual sites. These results are encouraging; furthermore, as more global operational aerosol models come online, we expect their inclusion in a robust operational multi-model ensemble will provide valuable aerosol forecasting guidance.