Regional Atmospheric Modeling System Research Articles

Forest Breeze - Cold Pool Interactions Drive Convective Organization over Heterogeneous Vegetation

Abstract Heterogeneous landscapes can influence the development of convection through the generation of thermally-driven mesoscale circulations. To assess the impacts of these circulations and their interaction with sea breezes, we simulated convection in an idealized coastal environment using the Regional Atmospheric Modeling System (RAMS). We compared simulations with striped patterns of surface vegetation to those of uniform vegetation to identify the importance of vegetation heterogeneity in impacting convective development. Under dry soil conditions representative of those during the TRACER and ESCAPE campaigns in June 2022, we found that these vegetation-induced circulations, referred to in literature as “forest breezes,” are more important than the sea breeze in determining the location of convection initiation. Convection and precipitation are also found to be favored over forests and suppressed over pasture and suburban landscapes as a result of greater surface sensible heat flux over the forest. Our findings also indicate that forest breezes are important for initiating convection along the boundaries of the forest, but that cold pools may play a key role in propagating the forest breezes toward the center of the forest stripe. In our simulations, the collisions of these breezes in the center of the forest stripe leads to uplift and strong convection there; however, a different width of the forest stripe would alter when the forest breezes collide, or whether they collide at all. The presence of these cold pools may therefore impact the “ideal stripe width”, the width of each vegetation stripe which maximizes domain-wide precipitation.

Dynamic and Thermodynamic Environmental Modulation of Tropical Congestus and Cumulonimbus in Maritime Tropical Regions

Abstract We have quantified the impacts of varying thermodynamic environments on tropical congestus and cumulonimbus clouds (CCCs) within maritime tropical regions. To elucidate this relationship, we employed the Regional Atmospheric Modeling System (RAMS) to conduct high-resolution (1 km) simulations of convection over the Philippine Archipelago for a month-long period in 2019. We subsequently performed a cloud-object-based analysis, identifying and tracking hundreds of thousands of individual CCCs using the Tracking and Object-Based Analysis of Clouds (tobac) tracking library. Using this object-oriented dataset of tracked cells, we examined differences in individual storm strength, organization, and morphology due to the storm’s initial environment. We found that storm strength, defined here as maximum midlevel updraft velocity, was controlled primarily by convective available potential energy (CAPE) and precipitable water (PW); high CAPE (>2500 J kg−1) and high (approximately 63 mm) PW were both required for midlevel CCC updraft velocities to reach at least 10 m s−1. Of the CCCs with the most vigorous updrafts, 80.9% were also in the upper tercile of precipitation rates, with the strongest precipitation rates requiring even higher PW. Further, we found that vertical wind shear was the primary differentiator between organized and isolated convective storms. Within the set of organized storms, linearly oriented CCC systems have significantly weaker vertical wind shear than nonlinear CCCs in low- (0–1, 0–3 km) and midlevels (0–5, 2–7 km). Overall, these results provide new insights into the environmental conditions determining the CCC properties in maritime tropical regions.

Bulk cloud microphysical properties as seen from numerical simulation and remote sensing products: case study of a hailstorm event over the La Plata Basin

Hailstorms develop over the La Plata Basin, in south-eastern South America, more often during later winter and early austral spring, between September and October. These systems have significant socioeconomic impacts over the region. Thus, a better understanding of how atmospheric drivers modulate the formation of hailstorms is important to improve the forecast of such phenomena. In this study, we selected a hailstorm event observed over the eastern La Plata Basin during 14–15 July 2016 to evaluate the performance of the Brazilian developments on the Regional Atmospheric Modelling System (BRAMS) model. The ability of the model in simulating cloud microphysical properties was evaluated by comparing simulations driven by different global forcings against in situ and remote sensing observations. The model results showed good skill in capturing the basic characteristics of the thunderstorm, particularly in terms of the spatial distribution of hydrometeors. The simulated spatial distribution of hail covers locations where hail fall was reported. The BRAMS simulations suggest that, despite relatively low values of the convective available potential energy (CAPE) (700–1000 J kg−1), environments with strong 0–8-km bulk shear (60–70 kt, ~30.9–36.0 m s–1) can promote the formation of ice clouds and hail fall over the eastern La Plata Basin. To be more conclusive, however, further research is needed to understand how different combinations of CAPE and shear affect hail formation over the region.

A Statistical Framework for Evaluating Rain Microphysics in Model Simulations and Disdrometer Observations

AbstractStatistical analyses of a large disdrometer data set and a diverse set of model simulations for convection using the Regional Atmospheric Modeling System were conducted, with the mutual goal of providing insights into precipitation formation and microphysical processes. We demonstrate that a two‐moment bulk microphysical model successfully captures the dominant observed modes of variability in rainfall related to rainfall intensity and raindrop size distributions. The model reproduced the general distribution of observed precipitation groups (PGs) derived from Principal Component Analysis. The multi‐variable analysis also uncovered some shortcomings in the model as well as limitations of the disdrometer data. The model solutions were constrained in their predicted drop size distributions (DSDs) due to the fixed DSD parameters assumed in a two‐moment microphysics scheme. A case study from the Mid‐latitude Continental Clouds and Convection Experiment field project demonstrated how model results can be used to contextualize the disdrometer observations which are limited in sample size, spatial coherence, and detection of small drops and low drop concentrations. The case study also showed that the spatial patterns of the statistically derived PGs revealed by the model are consistent with the hypothesized microphysical processes that determine surface rain DSDs. This work demonstrates how leveraging the strengths of observations and models together can improve our understanding and representation of rain microphysical processes.

Identifying Important Microphysical Properties and Processes for Marine Fog Forecasts

Abstract In this study, a marine fog event that occurred from 0000 to 1800 UTC 7 September 2018 near Canada’s Grand Banks is used to investigate the sensitivity of simulated fog properties to six model parameters found primarily in the microphysics scheme. To do so, we ran a large suite of regional simulations that spanned the life cycle of the fog event using the Regional Atmospheric Modeling System (RAMS). We randomly selected parameter combinations for the simulation suite and used Gaussian process regression to emulate the response of a variety of simulated fog properties to the parameters. We find that the microphysics shape parameter, which controls the relative width of the droplet size distribution, and the aerosol number concentration have the greatest impact on fog in terms of spatial extent, duration, and surface visibility. In general, parameters that reduce mean fall speed of droplets and/or suppress drizzle formation lead to reduced visibility in fog but also delayed onset, shorter lifetimes, and reduced spatial extent. The importance of the distribution width suggests a need for better characterization of this property for fog droplet distributions and better treatment of this property in microphysics schemes.

Nocturnal Turbulence at Jezero Crater as Determined From MEDA Measurements and Modeling

AbstractMars 2020 Mars Environmental Dynamics Analyzer (MEDA) instrument data acquired during half of a Martian year (Ls 13°–180°), and modeling efforts with the Mars Regional Atmospheric Modeling System (MRAMS) and the Mars Climate Database (MCD) enable the study of the seasonal evolution and variability of nocturnal atmospheric turbulence at Jezero crater. Nighttime conditions in Mars's Planetary Boundary Layer are highly stable because of strong radiative cooling that efficiently inhibits convection. However, MEDA nighttime observations of simultaneous rapid fluctuations in horizontal wind speed and air temperatures suggest the development of nighttime turbulence in Jezero crater. Mesoscale modeling with MRAMS also shows a similar pattern and enables us to investigate the origins of this turbulence and the mechanisms at play. As opposed to Gale crater, less evidence of turbulence from breaking mountain wave activity was found in Jezero during the period studied with MRAMS. On the contrary, the model suggests that nighttime turbulence at Jezero crater is explained by increasingly strong wind shear produced by the development of an atmospheric bore‐like disturbance at the nocturnal inversion interface. These atmospheric bores are produced by downslope winds from the west rim undercutting a strong low‐level jet aloft from ∼19:00 to 01:00 LTST and from ∼01:00 LTST to dawn when undercutting weak winds aloft. The enhanced wind shear leads to a reduction in the Richardson number and an onset of mechanical turbulence. Once the critical Richardson Number is reached (Ri ∼ <0.25), shear instabilities can mix warmer air aloft down to the surface.

Aerosol–cloud impacts on aerosol detrainment and rainout in shallow maritime tropical clouds

Abstract. This study investigates how aerosol-induced changes to cloud properties subsequently influence the overall aerosol budget through changes to detrainment and rainout. We simulated an idealized field of shallow maritime tropical clouds using the Regional Atmospheric Modeling System (RAMS) and varied the aerosol loading and type between 16 simulations. The full aerosol budget was tracked over the course of the 48 h simulation, showing that increasing the aerosol loading leads to an increase in aerosol regeneration and detrainment aloft at the expense of aerosol removal via rainout. Under increased aerosol loadings, cloud droplets are smaller and more likely to evaporate before they form precipitation-sized hydrometeors. As a result, the aerosol particles contained inside these droplets are released into the environment rather than being removed to the surface via rainout. However, the few raindrops which do happen to form under increased aerosol loadings tend to be larger, since the cloud water available for collection is divided among fewer raindrops, and thus raindrops experience less evaporation. Thus, in contrast to previous work, we find that increases in aerosol loading lead to decreases in aerosol rainout efficiency, even without a decrease in the overall precipitation efficiency. We further used tobac, a package for tracking and identifying cloud objects, to identify shifts in the overall cloud population as a function of aerosol loading and type, and we found contrasting aerosol effects in shallow cumulus and congestus clouds. Shallow cumulus clouds are more sensitive to the increase in cloud edge and/or top evaporation with increased aerosol loading and thereby tend to rain less and remove fewer aerosols via rainout. On the other hand, larger congestus clouds are more protected from evaporation and are thereby able to benefit from warm-phase invigoration. This leads to an increase in rain rates but not in domain-wide aerosol rainout, as the domain total rainfall becomes concentrated over a smaller horizontal area. Trends as a function of aerosol loading were remarkably consistent between the different aerosol types tested. These results represent a pathway by which a polluted environment not only has higher aerosol loadings than a pristine one but is also less able to regulate those loadings by removal processes, instead transporting aerosols to the free troposphere where they remain available for reactivation and further aerosol–cloud interactions.

Establishment of an analytical model for remote sensing of typical stratocumulus cloud profiles under various precipitation and entrainment conditions

Abstract. Structural patterns of cloud effective radius (ER) and liquid water content (LWC) profiles are essential variables of cloud lifecycle and precipitation processes, while observing cloud profiles from passive remote-sensing sensors remains highly challenging. Understanding whether there are typical structural patterns of ER and LWC profiles in liquid clouds and how they are linked to cloud entrainment or precipitating status is critical in developing algorithms to derive cloud profiles from passive satellite sensors. This study aims to address these questions and provide a preliminary foundation for the development of liquid cloud profile retrievals for the Multi-viewing, Multi-channel and Multi-polarization Imaging (3MI) sensor aboard the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Polar System-Second Generation (EPS-SG) satellite, which is scheduled to be launched in 2025. Firstly, we simulate a large ensemble of stratocumulus cloud profiles using the Colorado State University (CSU) Regional Atmospheric Modeling System (RAMS). The empirical orthogonal function (EOF) analysis is adopted to describe the shape of simulated profiles with a limited number of elemental profile variations. Our results indicate that the first three EOFs of LWC and ER profiles can explain >90 % of LWC and ER profiles. The profiles are divided into four prominent patterns and all of these patterns can be simplified as triangle-shaped polylines. The frequency of these four patterns is found to relate to intensities of the cloud-top entrainment and precipitation. Based on these analyses, we propose a simplified triangle-shaped cloud profile parameterization scheme allowing us to represent these main patterns of LWC and ER. This simple yet physically realistic analytical model of cloud profiles is expected to facilitate the representation of cloud properties in advanced retrieval algorithms such as those developed for the 3MI/EPS-SG.

Simulation and forecasting of atmospheric CO2 using RAMS

Concentration of carbon dioxide as the main greenhouse gas has been increasing, which has serious impacts on climate change, ecosystem, and human health. This study uses the Regional Atmospheric Modeling System (RAMS V6.2) with the Simple Biosphere (SiB-2) sub-model to simulate and forecast the concentration of carbon dioxide over the Daintree Rainforest in Australia. To evaluate the performance of the model, results are compared with the satellite product (MultiInstrumentFusedXCO2). This work evaluates the impact of various grid sizes, different combinations of diffusion parameters, and boundary conditions on CO2 simulations. Results reveal that RAMS can remarkably improve the statistical measures of the simulations particularly compared with the previous modeling analysis. The maximum mean bias error and RMSE in this study for all simulations are smaller than 1.85 and 2.07 ppm, respectively. The most proper simulation type (type III) leads to the average bias error and RMSE of 0.34 and 0.94 ppm, respectively. Furthermore, results show that the fuzzy algorithm is a proper method to provide initial CO2 in forecasting. This study shows that RAMS can be efficiently used in CO2 simulation and forecasting, which is valuable for CO2 monitoring, climate, environment, and management applications.

Assessing Raindrop Breakup Parameterizations Using Disdrometer Observations

Abstract An intercomparison of raindrop mean diameter frequency distribution (RDFD) is performed for numerical simulations of precipitating cloud systems using an array of models and microphysics schemes. This includes results from the Regional Atmospheric Modeling System (RAMS) double-moment microphysics, the Hebrew University Cloud Model bin microphysics (HUCM) interfaced to the RAMS parent model, and the Weather Research and Forecasting (WRF) Model with the Thompson, Morrison, double-moment 6-class (WDM6), and National Severe Storms Laboratory (NSSL) double-moment schemes. Simulations are examined with respect to the raindrop size distribution (DSD) volume-number mean diameter (Dm) and intercept parameter (Nw). When compared to a suite of disdrometer observations, the RDFD resulting from each microphysics scheme exhibits varying degrees of mean drop size constraints and peaks in the frequency distribution of Dm. A more detailed investigation of the peaked RDFD from the RAMS simulations suggests that the parameterization of raindrop collisional breakup can impose strong limitations on the evolution of simulated drop growth. As such, a summary and comparison of the drop breakup parameterizations among the aforementioned microphysics schemes is presented. While some drop breakup parameterizations are adjusted toward the observations by modifying the threshold diameter for the onset of breakup, this study explores the use of a modified maximum breakup efficiency. This method permits the parameterization to retain its threshold breakup diameter, while limiting the strength of drop breakup and permitting a broader range of drop sizes. As a result, the simulated mean drop sizes are in better agreement with observations.

Investigating the Role of Amazonian Mesoscale Wind Patterns and Strength on the Spatial Distribution of Martian Bedrock Exposures.

The Martian highlands contain Noachian-aged areally-extensive (>225km2) bedrock exposures that have been mapped using thermal and visible imaging datasets. Given their age, crater density and impact gardening should have led to the formation of decameter scale layers of regolith that would overlie and bury these outcrops if composed of competent materials like basaltic lavas. However, many of these regions lack thick regolith layers and show clear exposures of bedrock materials with elevated thermal inertia values compared to the global average. Hypothesized reasons for the lack of regolith include: (a) relatively weaker material properties than lavas, where friable materials are comminuted and deflated during wind erosion, (b) long-term protection from regolith development through burial and later exhumation through one or more surface processes, and (c) spatially concentrated aeolian erosion and wind energetics on well-lithified basaltic substrates. To test the third hypothesis, we used the Mars Regional Atmospheric Modeling System to calculate wind erosive strength at 10 regions throughout the Martian highlands and compared it to their thermophysical properties by using thermal infrared data derived from the Thermal Emission Spectrometer to understand the effect that Amazonian mesoscale wind patterns may have on the exposure of bedrock. We also investigated the effect of planet obliquity, Ls of perihelion, and atmospheric mean pressure on wind erosion potential. We found no evidence for increased aeolian activity over bedrock-containing regions relative to surrounding terrains, including at the mafic floor unit at Jezero crater (Máaz formation), supporting the first or second hypotheses for these regions.

Urban ventilation assessment with improved vertical wind profile in high-density cities – Comparisons between LiDAR and conventional methods

The vertical wind speed profile is crucial to urban ventilation assessment and urban planning/design. This study uses Light Detection and Ranging (LiDAR) observation as benchmark to evaluate accuracy of wind profiles estimated by conventional methods. The conventional methods include Boundary Layer Wind Tunnel (BLWT), Regional Atmospheric Modeling System (RAMS), Power Law (PL), and Weather Research and Forecasting (WRF). The evaluation involves two typical urban sites with different densities under summer weak-wind conditions. Large Eddie Simulations (LES) are conducted to further investigate the sensitivity of urban ventilation assessment results to the deviations of wind profiles. The results indicate significant deviations in LES caused by conventional methods. The largest deviations of wind velocity ratio are found in mesoscale meteorological models (RAMS and WRF (>65%)). Deviations caused by physical and empirical models are smaller but still significant (BLWT (>25%) and PL (>40%)). Consequently, large deviations (>100%) of wind-relevant criterion for outdoor thermal comfort are observed. Finally, to balance accuracy and data availability, we recommend power law method as the optimal method to provide inflow boundary condition for numerical simulations when LiDAR observation is not available. We provide new and valuable understandings to improve urban ventilation assessment in high-density cities.

Precipitation extremes over the tropical Americas under RCP4.5 and RCP8.5 climate change scenarios: Results from dynamical downscaling simulations

AbstractThe Regional Atmospheric Modelling System (RAMS) driven by data from the CMIP5 Earth System Model HadGEM2‐ES was used to simulate daily precipitation over the tropical Americas for both current and future climate, including distinct scenarios (representative concentration pathways 4.5 and 8.5) and different time horizons (short‐term, mid‐term and long‐term changes). The major objective was to evaluate possible future changes in extreme events, with emphasis on the intensity of precipitation events and the duration of wet and dry spells. According to RAMS, longer dry spells are expected over most regions of the tropical Americas in the future, with indications for Northeast Brazil, Caribbean, Northern Amazon, and shorter wet spells over Central America and Amazon. With the exception of the Caribbean, there is a general tendency towards the increased frequency of intense precipitation in the tropical Americas.

Assessing the contribution of dynamical downscaling to austral autumn Northeast Brazil seasonal precipitation prediction performance

This study aims to assess the contribution to prediction performance of dynamically downscaling seasonal precipitation for the Brazilian Northeast region (NEB) produced in February with a global climate model for the austral autumn (March-April-May). This season includes the peak precipitation period of a large portion of this region. To achieve this aim, 32 years of hindcasts for the period 1979–2010 were produced with a regional model known as the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS) run at 30 km spatial resolution, which was unidirectional nested to a global model run at approximately 200 km spatial resolution. The used global model was the Atmospheric General Circulation Models of the Brazilian Center for Weather Forecast and Climate Studies (CPTEC/AGCM), which provided initial and lateral boundary conditions for BRAMS. Hindcast ensembles of 10 members were produced with both the global and the regional models, simulating an operational prediction environment using persisted sea surface temperature (SST) anomalies observed in the previous January of each of the 32 hindcast years as oceanic boundary conditions. A comparative deterministic and probabilistic performance assessment of the two models was conducted. The deterministic assessment included the investigation of the mean error (bias) of the produced seasonal precipitation hindcasts, the degree of linear association between the observed and predicted precipitation anomalies measuring phase error through the correlation of the ensemble means with the corresponding observations, and amplitude error investigated through the ratio between the hindcast ensemble mean and observed variances. The probabilistic assessment was performed investigation the reliability, resolution, and discrimination characteristics of tercile probability predictions for the above normal and below normal categories, and also for probabilistic predictions for the occurrence of the symmetric event positive (or negative) precipitation anomaly. The two investigated modeling approaches showed similar performance, with an indication for dynamically downscaled predictions to have reduced amplitude error and slightly improved reliability and resolution compared to the predictions produced with the global model.

Simulation of an orographic gravity wave above the Amazon rainforest and its influence on gases transport near the surface

The influence of the topography at the ATTO site (Amazon Tall Tower Observatory) in the formation of Gravity Waves (GW) was investigated in this work. The role of these waves in gas transport on different heights in the nocturnal boundary layer, was also investigated. For this, were analyzed: experimental data of wind speed, temperature, humidity and CO2 to identify the GW. Furthermore satellite images, ECMWF ERA5 (European Center for Medium-Range Weather Forecasts) reanalysis, and numerical simulations from the mesoscale JULES-CCATT-BRAMS model (Brazilian Regional Atmospheric Modeling System) version 5.3 were used to perform GW simulations. The simulations involved two configurations (Control-With Topography and No Topography). The sattelite images made it clear that the GW was not associated with convective activities. The simulations showed clear ondulatory signs in air temperature, vertical component of the wind, and gases like CO and O3. Moreover, they also reveal that the wave originated by the presence of the local topography and this orograph gravity wave had and important role in the transport of gases above the ATTO site.

Mars Exploration Using Sailplanes

We present the preliminary design of sailplanes, used for Mars exploration. The sailplanes mitigate the weight and energy storage limitations traditionally associated with powered flight by instead exploiting atmospheric wind gradients for dynamic soaring, and slope/thermal updrafts for static soaring. Equations of motion for the sailplanes were combined with wind profiles from the Mars Regional Atmospheric Modeling System (MRAMS) for two representative sites: Jezero crater, Perseverance’s landing site, and over a section of the Valles Marineris canyon. Optimal flight trajectories were obtained from the constrained optimization problem, using the lift coefficient and the roll angle as control parameters. Numerical results for complete dynamic soaring cycles demonstrated that the total sailplane energy at the end of a soaring cycle increases by 6.8–11%. The absence of a propulsion system, allowing for a compact form factor, means the sailplanes can be packaged into CubeSats and deployed as secondary payloads at a relatively low cost; providing scientific data over locations inaccessible by current landers and rovers. Various sailplane deployment methods are considered, including rapid deployment during Entry, Descent, and Landing (EDL) of a Mars Science Laboratory-class (MSL) vehicle and slow deployment using a blimp.

The Application of a Genetic Algorithm to the Optimization of a Mesoscale Model for Emergency Response

Abstract Besides solving the equations of momentum, heat, and moisture transport on the model grid, mesoscale weather models must account for subgrid-scale processes that affect the resolved model variables. These are simulated with model parameterizations, which often rely on values preset by the user. Such “free” model parameters, along with others set to initialize the model, are often poorly constrained, requiring that a user select each from a range of plausible values. Finding the values to optimize any forecasting tool can be accomplished with a search algorithm, and one such process—the genetic algorithm (GA)—has become especially popular. As applied to modeling, GAs represent a Darwinian process: an ensemble of simulations is run with a different set of parameter values for each member, and the members subsequently judged to be most accurate are selected as “parents” who pass their parameters onto a new generation. At the U.S. Department of Energy’s Savannah River Site in South Carolina, we are applying a GA to the Regional Atmospheric Modeling System (RAMS) mesoscale weather model, which supplies input to a model to simulate the dispersion of an airborne contaminant as part of the site’s emergency response preparations. An ensemble of forecasts is run each day, weather data are used to “score” the individual members of the ensemble, and the parameters from the best members are used for the next day’s forecasts. As meteorological conditions change, the parameters change as well, maintaining a model configuration that is best adapted to atmospheric conditions. Significance Statement We wanted to develop a forecasting system by which a weather model is run over the Savannah River Site each day and repeatedly adjusted according to how well it performed the previous day. To run the model, a series of values (parameters) must be set to control how the model will calculate winds, temperatures, and other desired variables. Each day the model was run several times using different combinations of these parameters and later compared with observed meteorological conditions. Parameters that produced the most accurate forecasts were preferentially reused to create the forecasts for the next day. The process was tested for the summer of 2020 and exhibited lower errors than forecasts produced by the model using default values of the parameters.

Model analysis of vertical exchange of boundary layer ozone and its impact on surface air quality over the North China Plain

In addition to photochemical production and horizontal regional transport, surface O3 concentration can also likely be affected by vertical transport, which is not well known so far. The process analysis was conducted by using the Regional Atmospheric Modeling System Community Multiscale Air Quality (RAMS-CMAQ) model to investigate photochemical production and the vertical transport mechanism of boundary-layer O3 during a typical O3 pollution episode in the North China Plain (NCP), and further quantify the contribution of vertical transport to surface O3. The diurnal variations of vertical budgets of O3 and NO2 in the boundary layer at multiple sites showed that there were substantial differences in the vertical distribution of O3 production and transport between urban and suburban/rural areas. In urban areas, surface O3 is consumed by titration reaction to generate NO2, which is then transported to the upper boundary layer and produces O3 by photochemical reaction. With the development of the boundary layer, the upper-layer O3 stored in the residual layer at nighttime can be transported vertically to the surface as the turbulent diffusion intensifies the next morning. While in suburban and rural areas, the vertical transport is relatively weaker because the photochemical formation of O3 occurs in the whole boundary layer, although it decreases slightly with the altitude. Model simulation showed that 20.6–27.9% of urban surface O3 changes in the morning (09:00–10:00 LST) was attributable to the downward transport from the residual layer, while it is 15.0–22.1% at suburban site. The vertical transport from above the boundary layer contributed 24.0–63.6% to daytime urban surface O3 changes, which was weak in suburban areas. Differences and similarities in O3 formation and transport mechanism in urban and suburban regions revealed here highlight the importance of earlier control and regional collaboration.

Improving the south America wildfires smoke estimates: Integration of polar-orbiting and geostationary satellite fire products in the Brazilian biomass burning emission model (3BEM)

Large land extensions are subjected to environmental degradation and land-use changes by fires annually. In tropical regions, such as South America, the global demand for commodities leads to the conversion of natural vegetation into agricultural land-uses. With the new orbital fire products that have improved in spatial and temporal resolution, it is now possible to better understand fire properties at large scales, such as fire radiative power (FRP), fire spread, heat flux, and fire life cycle. This study aims to integrate polar-orbit and geostationary satellites’ fire-related products to estimate biomass burning (BB) emissions on a continental-scale to better monitor smoke plumes in near-real-time (NRT) while using the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS). The total aerosol optical depth at 550 nm channel from the model during the South American 2020 fire season (September–November) showed a good agreement with Modern-Era Retrospective analysis for Research and Applications (MERRA-2) and Copernicus Atmosphere Monitoring Service (CAMS) Global Near-Real-Time reanalyzes (R = 0.97, p < 0.05, student t-test). Moreover, the new improvements made in the Brazilian Biomass Burning Emission Model with fire radiative power (3BEM-FRP) better represent smoke emissions of large fire events, such as the Pantanal 2020 fires.

On the cross-tropopause transport of water by tropical convective overshoots: a mesoscale modelling study constrained by in situ observations during the TRO-Pico field campaign in Brazil

Abstract. Deep convection overshooting the lowermost stratosphere is well known for its role in the local stratospheric water vapour (WV) budget. While it is seldom the case, local enhancement of WV associated with stratospheric overshoots is often published. Nevertheless, one debatable topic persists regarding the global impact of this event with respect to the temperature-driven dehydration of air parcels entering the stratosphere. As a first step, it is critical to quantify their role at a cloud-resolving scale before assessing their impact on a large scale in a climate model. It would lead to a nudging scheme for large-scale simulation of overshoots. This paper reports on the local enhancements of WV linked to stratospheric overshoots, observed during the TRO-Pico campaign conducted in March 2012 in Bauru, Brazil, using the BRAMS (Brazilian version of the Regional Atmospheric Modeling System; RAMS) mesoscale model. Since numerical simulations depend on the choice of several preferred parameters, each having its uncertainties, we vary the microphysics or the vertical resolution while simulating the overshoots. Thus, we produce a set of simulations illustrating the possible variations in representing the stratospheric overshoots. To better resolve the stratospheric hydration, we opt for simulations with the 800 m horizontal-grid-point presentation. Next, we validate these simulations against the Bauru S-band radar echo tops and the TRO-Pico balloon-borne observations of WV and particles. Two of the three simulations' setups yield results compatible with the TRO-Pico observations. From these two simulations, we determine approximately 333–2000 t of WV mass prevailing in the stratosphere due to an overshooting plume depending on the simulation setup. About 70 % of the ice mass remains between the 380 and 385 K isentropic levels. The overshooting top comprises pristine ice and snow, while aggregates only play a role just above the tropopause. Interestingly, the horizontal cross section of the overshooting top is about 450 km2 at the 380 K isentrope, which is similar to the horizontal-grid-point resolution of a simulation that cannot compute overshoots explicitly. In a large-scale simulation, these findings could provide guidance for a nudging scheme of overshooting hydration or dehydration.