Towards Unified Online-Coupled Aerosol Parameterization for the Brazilian Global Atmospheric Model (BAM): Aerosol–Cloud Microphysical–Radiation Interactions

Author:

Pendharkar Jayant,Figueroa Silvio NiloORCID,Vara-Vela AngelORCID,Krishna R. Phani MuraliORCID,Schuch Daniel,Kubota Paulo Yoshio,Alvim Débora Souza,Vendrasco Eder Paulo,Gomes Helber BarrosORCID,Nobre Paulo,Herdies Dirceu LuísORCID

Abstract

In this work, we report the ongoing implementation of online-coupled aerosol–cloud microphysical–radiation interactions in the Brazilian global atmospheric model (BAM) and evaluate the initial results, using remote-sensing data for JFM 2014 and JAS 2019. Rather than developing a new aerosol model, which incurs significant overheads in terms of fundamental research and workforce, a simplified aerosol module from a preexisting global aerosol–chemistry–climate model is adopted. The aerosol module is based on a modal representation and comprises a suite of aerosol microphysical processes. Mass and number mixing ratios, along with dry and wet radii, are predicted for black carbon, particulate organic matter, secondary organic aerosols, sulfate, dust, and sea salt aerosols. The module is extended further to include physically based parameterization for aerosol activation, vertical mixing, ice nucleation, and radiative optical properties computations. The simulated spatial patterns of surface mass and number concentrations are similar to those of other studies. The global means of simulated shortwave and longwave cloud radiative forcing are comparable with observations with normalized mean biases ≤11% and ≤30%, respectively. Large positive bias in BAM control simulation is enhanced with the inclusion of aerosols, resulting in strong overprediction of cloud optical properties. Simulated aerosol optical depths over biomass burning regions are moderately comparable. A case study simulating an intense biomass burning episode in the Amazon is able to reproduce the transport of smoke plumes towards the southeast, thus showing a potential for improved forecasts subject to using near-real-time remote-sensing fire products and a fire emission model. Here, we rely completely on remote-sensing data for the present evaluation and restrain from comparing our results with previous results until a complete representation of the aerosol lifecycle is implemented. A further step is to incorporate dry deposition, in-cloud and below-cloud scavenging, sedimentation, the sulfur cycle, and the treatment of fires.

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

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