The scope of this work was to evaluate simulated carbon monoxide (CO) and aerosol optical depth (AOD) from the CAM-chem model against observed satellite data and additionally explore the empirical relationship of CO, AOD and fire radiative power (FRP). The simulated seasonal global concentrations of CO and AOD were compared, respectively, with the Measurements of Pollution in the Troposphere (MOPITT) and the Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite products for the period 2010–2014. The CAM-chem simulations were performed with two configurations: (A) tropospheric-only; and (B) tropospheric with stratospheric chemistry. Our results show that the spatial and seasonal distributions of CO and AOD were reasonably reproduced in both model configurations, except over central China, central Africa and equatorial regions of the Atlantic and Western Pacific, where CO was overestimated by 10–50 ppb. In configuration B, the positive CO bias was significantly reduced due to the inclusion of dry deposition, which was not present in the model configuration A. There was greater CO loss due to the chemical reactions, and shorter lifetime of the species with stratospheric chemistry. In summary, the model has difficulty in capturing the exact location of the maxima of the seasonal AOD distributions in both configurations. The AOD was overestimated by 0.1 to 0.25 over desert regions of Africa, the Middle East and Asia in both configurations, but the positive bias was even higher in the version with added stratospheric chemistry. By contrast, the AOD was underestimated over regions associated with anthropogenic activity, such as eastern China and northern India. Concerning the correlations between CO, AOD and FRP, high CO is found during March–April–May (MAM) in the Northern Hemisphere, mainly in China. In the Southern Hemisphere, high CO, AOD, and FRP values were found during August–September–October (ASO) due to fires, mostly in South America and South Africa. In South America, high AOD levels were observed over subtropical Brazil, Paraguay and Bolivia. Sparsely urbanized regions showed higher correlations between CO and FRP (0.7–0.9), particularly in tropical areas, such as the western Amazon region. There was a high correlation between CO and aerosols from biomass burning at the transition between the forest and savanna environments over eastern and central Africa. It was also possible to observe the transport of these pollutants from the African continent to the Brazilian coast. High correlations between CO and AOD were found over southeastern Asian countries, and correlations between FRP and AOD (0.5–0.8) were found over higher latitude regions such as Canada and Siberia as well as in tropical areas. Higher correlations between CO and FRP are observed in Savanna and Tropical forests (South America, Central America, Africa, Australia, and Southeast Asia) than FRP x AOD. In contrast, boreal forests in Russia, particularly in Siberia, show a higher FRP x AOD correlation than FRP x CO. In tropical forests, CO production is likely favored over aerosol, while in temperate forests, aerosol production is more than CO compared to tropical forests. On the east coast of the United States, the eastern border of the USA with Canada, eastern China, on the border between China, Russia, and Mongolia, and the border between North India and China, there is a high correlation of CO x AOD and a low correlation between FRP with both CO and AOD. Therefore, such emissions in these regions are not generated by forest fires but by industries and vehicular emissions since these are densely populated regions.

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.

This study aims to evaluate the synoptic conditions responsible for two extreme precipitation events development that occurred in the same region on the east coast of Northeast Brazil (NEB) in two different years, on July 1, 2022 (185 mm/24h), and July 7, 2023 (213 mm/24h). These events are becoming increasingly frequent in all regions of Brazil, especially in areas with high population density, associated with significant material and human losses, emphasizing the significance of a deeper comprehension of these events. ERA5 global reanalysis data have been used for synoptic and vertical structure evaluation as a first analysis step. Infrared GOES-16 satellite images have been used to monitor the cloudiness development. Pluviometric stations were used to document accumulated precipitation caused by these events. The following step will consist of conducting very high-resolution simulations using the Model for Prediction Across Scales (MPAS) to assess its ability to represent the circulation patterns associated with the analyzed extreme precipitation events. Both analyzed cases occurred along the eastern coast of the NEB, specifically over the Alagoas state, and were triggered by the same synoptic-scale system, the Easterly Wave Disturbances (EWDs). The trough axis penetrating the study area was observed on both examined dates, with a very characteristic relative vorticity of this tropical disturbance. Despite satellite images in the IR channel indicating lower cloud top temperatures in the first case, thermodynamic diagram data showed a greater vertical development of cloudiness in the second case. Distinct situations were observed when analyzing moisture transport convergence fields. In the first event, moisture convergence intensified over 12 hours, while in the second event, moisture convergence over Alagoas was evident throughout the entire day. This variation can be attributed to the intensification of the subtropical anticyclone during the extreme precipitation event in July 2023, which intensified moisture transport in the region. In general, moisture convergence resulted from the high flow of moisture prevailing over the region combined with upward movements caused by the trough present at low levels, which combined with local factors in the region such as topography, contributed to the increase in rainfall over the study area in both analyzed cases.