Abstract 080

Abstract ID: 080

The impact of biomass burning emissions on seasonal prediction: a study using the ECMWF’s coupled Ensemble Prediction System

Lead Author: Angela Benedetti
ECMWF, United Kingdom

Keywords: aerosol radiative impacts, fire emissions, predictability due to aerosol processes

Abstract: In the context of the EU-funded CONsistent representation of temporal variations of boundary Forcings in reanalysES and Seasonal forecasts (CONFESS, https://confess-h2020.eu/) project, ECMWF has investigated the impact of biomass burning emissions on predictability at the seasonal scales. In previous studies, it has been shown that aerosols can impact the prediction through their interaction with the radiation. Sensitivity studies performed with the ECMWF’s coupled Ensemble Prediction System have shown that biomass burning aerosols play an important part. In particular for areas where extensive seasonal biomass burning takes place such as central Africa and Indonesia, the effect of this type of aerosols can be very important.

The impact of aerosols for average conditions is taken into account with a climatological distribution which is operationally used at ECMWF. However, for exceptional years, it is only with prognostic interactive aerosols that the impact of biomass burning events can be properly accounted for.

This study presents new simulations using the ECMWF’s coupled system with fully prognostic and interactive aerosols and prescribed fire emission based on MODIS Fire Radiative Power from the Global Fire Assimilation System database. The simulations are compared with a control run using the current operational set-up which includes an up-to-date climatology for all aerosols as well as with a run with interactive prognostic aerosols which uses climatological biomass burning emissions (also derived from GFAS) instead of observed emissions. It is shown that including the interannual variations of fire emissions improves the S2S forecasts of large scale atmospheric circulation, especially in the Tropics. These results illustrate the potential for improving the S2S prediction systems by including prognostic aerosols and models for fire emissions.

Fréderic Vitart (ECMWF)
Magdalena Alonso Balmaseda (ECMWF)
Mark Parrington (ECMWF)
Roberto Bilbao (BSC)
Etienne Tourigny (BSC)
Pablo Ortega (BSC)
Elisabet Sorribes (BSC)