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Development Towards a Global Operational Aerosol Consensus: Basic Climatological Characteristics of the International Cooperative for Aerosol Prediction Multi-model Ensemble (Icap-mme) : Volume 14, Issue 10 (06/06/2014)

By Sessions, W. R.

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Book Id: WPLBN0003996920
Format Type: PDF Article :
File Size: Pages 66
Reproduction Date: 2015

Title: Development Towards a Global Operational Aerosol Consensus: Basic Climatological Characteristics of the International Cooperative for Aerosol Prediction Multi-model Ensemble (Icap-mme) : Volume 14, Issue 10 (06/06/2014)  
Author: Sessions, W. R.
Volume: Vol. 14, Issue 10
Language: English
Subject: Science, Atmospheric, Chemistry
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Silva, A. D., Colarco, P. R., Sekiyama, T., Jorba, O. C., Hansen, J. A., Lu, S.,...Reid, J. S. (2014). Development Towards a Global Operational Aerosol Consensus: Basic Climatological Characteristics of the International Cooperative for Aerosol Prediction Multi-model Ensemble (Icap-mme) : Volume 14, Issue 10 (06/06/2014). Retrieved from

Description: CSC Inc., Monterey, CA, USA. Over the past several years, there has been a rapid development in the number and quality of global aerosol models intended for operational forecasting use. Indeed, most centers with global numerical weather prediction (NWP) capabilities have some program for aerosol prediction. These aerosol models typically have differences in their underlying meteorology as well as aerosol sources, sinks, microphysics and transformations. However, like similar diversity in aerosol climate models, the aerosol forecast models have fairly similar overall bulk error statistics for aerosol optical thickness (AOT)-one of the few aerosol metrics that is globally available. Experience in climate and weather prediction has shown that in situations such as this where there are several independent models, a multi-model ensemble or consensus will be top performing in many key error metrics. Further, multi-model ensembles provide a highly valuable tool for forecasters attempting to predict severe aerosol events. 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, five day AOT forecasts are analyzed for December 2011 through November 2012 from four institutions: ECMWF, JMA, NASA GSFC, and NRL/FNMOC. For dust, we also include the NOAA NGAC product in our analysis. The Barcelona Supercomputing Centre (NMMC) and UK Met office dust product have also recent become available with 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 0Z 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 oceans, though low in AOT, nevertheless also have high diversity. In regard to root mean square error, 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; as more global operational aerosol models come on line, we expect their inclusion in a robust operational multi-model ensemble will provide valuable aerosol forecasting guidance.

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

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