Application of the Multi-Scale Infrastructure for Chemistry and Aerosols version 0 (MUSICAv0) for air quality research in Africa

Abstract

Abstract. The Multi-Scale Infrastructure for Chemistry and Aerosols Version 0 (MUSICAv0) is a new community modeling infrastructure that enables the study of atmospheric composition and chemistry across all relevant scales. We develop a MUSICAv0 grid with Africa refinement (∼ 28 km × 28 km over Africa). We evaluate the MUSICAv0 simulation for 2017 with in situ observations and compare the model results to satellite products over Africa. A simulation from the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), a regional model that is widely used in Africa studies, is also included in the analyses as a reference. Overall, the performance of MUSICAv0 is comparable to WRF-Chem. Both models underestimate carbon monoxide (CO) compared to in situ observations and satellite CO column retrievals from the Measurements of Pollution in the Troposphere (MOPITT) satellite instrument. MUSICAv0 tends to overestimate ozone (O3), likely due to overestimated stratosphere-to-troposphere flux of ozone. Both models significantly underestimate fine particulate matter (PM2.5) at two surface sites in East Africa. The MUSICAv0 simulation agrees better with aerosol optical depth (AOD) retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) and tropospheric nitrogen dioxide (NO2) column retrievals from the Ozone Monitoring Instrument (OMI) than WRF-Chem. MUSICAv0 has a consistently lower tropospheric formaldehyde (HCHO) column than OMI retrievals. Based on model–satellite discrepancies between MUSICAv0 and WRF-Chem and MOPITT CO, MODIS AOD, and OMI tropospheric NO2, we find that future field campaign(s) and more in situ observations in the East African region (5∘ S–5∘ N, 30–45∘ E) could substantially improve the predictive skill of atmospheric chemistry model(s). This suggested focus region exhibits the largest model–in situ observation discrepancies, as well as targets for high population density, land cover variability, and anthropogenic pollution sources.

Evaluating the Model Representation of Asian Summer Monsoon Upper Troposphere and Lower Stratosphere Transport and Composition Using Airborne In Situ Observations

“…On the other hand, MUSICA and WACCM show a high bias in ozone spanning between the free troposphere and lower stratosphere (Figure 3, right panels). A similar high bias has been noted in previous work when compared to observations (Dubé et al., 2022; Froidevaux et al., 2019; Tang et al., 2023). Ozone mixing ratios observed by FOZAN‐II are further supported by ozonesonde observations over Nepal during StratoClim which show ∼30–50 ppbv ozone throughout the free troposphere (Brunamonti et al., 2018), as well as by ozonesonde observations from the neighboring regions (Bian et al., 2012; Ma et al., 2022).…”

Multiscale CO Budget Estimates Across South America: Quantifying Local Sources and Long Range Transport

“…We use MUSICAv0, which is part of the Community Earth System Model (Danabasoglu et al., 2020) version 2.2 (CESM2.2), an open source Earth System Model maintained by the National Center for Atmospheric Research (NCAR). MUSICAv0 is a configuration of the Community Atmosphere Model with Chemistry (CAM‐chem) (Emmons et al., 2020; Tilmes et al., 2019) with a spectral element (SE) dynamical core that allows for regional refinement (Lauritzen et al., 2018; Schwantes et al., 2022; Tang et al., 2022, 2023). The model is run coupled to the Community Land Model (CLM) v5.0 (Lawrence et al., 2019) to interactively simulate land processes, the deposition of gases and aerosols and biogenic emissions.…”

“…We use MUSICAv0, which is part of the Community Earth System Model (Danabasoglu et al, 2020) (Emmons et al, 2020;Tilmes et al, 2019) with a spectral element (SE) dynamical core that allows for regional refinement (Lauritzen et al, 2018;Schwantes et al, 2022;Tang et al, 2022Tang et al, , 2023. The model is run coupled to the Community Land Model (CLM) v5.0 (Lawrence et al, 2019) to interactively simulate land processes, the deposition of gases and aerosols and biogenic emissions.…”