Tamanna Subba

Aerosol particles larger than roughly 50–100 nm in diameter are climatically important because they can act as cloud condensation nuclei (CCN), making their global number concentrations essential for understanding aerosol–cloud interactions. However, observationally constrained, long-term global datasets of particle number concentrations in this size range remain scarce. In this investigation, we present a global dataset of ground-level particle number concentrations for the period 2003–2024, produced by combining in situ observations with a machine-learning approach. The dataset includes two variables: the number concentrations for particles larger than 100 nm (N100) and larger than 50 nm (N50), provided at 0.75° × 0.75° spatial resolution and daily temporal resolution. To generate this dataset, we trained an eXtreme Gradient Boosting (XGB) model using measurements from 62 in situ stations as targets and reanalysis variables as predictors, enabling a data-driven representation of particle number concentrations at the global scale. We evaluated the dataset against independent observations from 12 additional stations. At 2/3 of these stations, the dataset shows good performance, capturing the median concentrations within a factor of 1.5 from the observations. Furthermore, we describe the main characteristics of the dataset in terms of global spatial patterns, temporal variability, and seasonal cycles, and demonstrate its ability to capture long-term trends in particle number concentrations, including both increasing and decreasing tendencies reported in the literature. This work provides the first observation-constrained, machine-learning-based global dataset of N50 and N100 at daily resolution over two decades, bridging the gap between sparse measurements and computationally expensive process-based models. The dataset, publicly available at https://doi.org/10.5281/zenodo.20202080, offers a valuable resource for evaluating model simulations, improving CCN-related parameterizations, and supporting weather and climate studies without the need for explicit knowledge of the aerosol particle microphysics.

In cumulus clouds, aerosol concentrations control cloud droplet concentrations, modifying cloud radiative properties, precipitation processes, and cloud electrification. However, mechanisms of aerosol-deep convection interactions are not well understood due to complex cloud dynamics and microphysics. We investigate the interaction of aerosols with isolated deep convection using Large Eddy Simulations of two cases during the TRacking Aerosol Convection interactions ExpeRiment (TRACER) near Houston, Texas, using a joint cell-thermal tracking algorithm. Cumulus thermals are droplet generators, since supersaturation and droplet nucleation coincide with thermal centers, where the strongest updrafts occur. Primary ice crystal formation does not take place inside thermals, but at layers where previous thermals detrained moisture. As subsequent thermals containing supercooled droplets penetrate these layers, hail and graupel form at or near these thermals. Higher aerosol concentrations result in higher droplet concentrations that suppress drizzle, delay warm rain processes, and transport more moisture aloft. This increases snow and ice amount, as well as graupel and hail, leading to more lightning. Polluted thermals initiate at slightly higher altitudes, and are slightly larger and faster, suggesting a weak invigoration. We also find more thermals per cell, but fewer isolated cells, since convection is more aggregated and intense, especially near the end of the 24 h simulation. Non-linear mesoscale feedback likely triggered by temperature and moisture responses to aerosol-thermal interactions causes the aggregation. Time-lagged aerosol-reinitialization experiments show that the mesoscale response is the predominant forcing for the invigoration. These changes happen within one day, on a smaller scale than previously suggested.

Quantifying parametric uncertainty using observations from individual sites provides a critical foundation for Earth system modeling, serving as a necessary first step before scaling up to regional or global applications. This study introduces a novel computational framework designed to enhance model predictability by reducing parametric uncertainty and assessing site and observable generalizability using various observational constraints. The framework integrates five components: Model Simulation, Statistical Emulation, Global Sensitivity Analysis (GSA), Model Calibration, and Model Prediction. Using the E3SM land model, we simulated site‐level land‐atmosphere carbon and energy fluxes from 2003 to 2007 across five evergreen needleleaf FLUXNET sites, perturbing 26 vegetation‐related model parameters. Gaussian process emulators were employed to expedite GSA and model calibration. Four critical parameters that strongly influence selected land‐atmosphere fluxes were identified by GSA. Bayesian approaches were used to infer parameter probability distributions leveraging synthetic data and FLUXNET observations. The results reveal that posterior parameter distributions vary significantly across different sites and observables within the same plant functional type. Probabilistic predictions indicate that parameters calibrated at one site can enhance predictive accuracy at other sites, although site heterogeneity may sometimes outweigh parametric uncertainty. Additionally, the probabilistic predictions demonstrate that calibration for one variable can also improve predictability for other variables, thereby maximizing predictive capabilities with limited observations. This framework provides a powerful approach for reducing parametric uncertainty in Earth system models and deepening our understanding of carbon dynamics and energy cycles. Its adaptability makes it a valuable tool for broader applications in Earth system modeling.

The Sea Breeze Circulation (SBC) influences atmospheric processes at multiple scales in coastal regions. Understanding how SBCs impact the aerosol number budget and aerosol–cloud interaction processes is essential. This study investigates sea breeze–aerosol interactions (SAIs) during 46 summertime SBC events using data from the TRacking Aerosol Convection Interactions Experiment (TRACER) field campaign across urban (main) and rural (supplemental) coastal sites in southern Texas. Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) simulations complement observations to explore spatio-temporal meteorological controls on boundary layer aerosols. During the summertime, Sea Breeze Fronts (SBF) penetrating inland transported cool, moist air over the land, introducing air masses with distinct properties compared to the preexisting continental air. These SAIs cause variability in number concentrations of up to a factor of two, with events typically lasting ∼ 5 h before returning to background conditions. SAI impact on aerosols varies with site proximity to water and the preceding sea breeze (SB) history, primarily affecting the marine-influenced accumulation mode. The main site, influenced by both Galveston Bay and the Gulf of Mexico, reflects a stronger marine influence. In contrast, a supplemental site, at a similar shoreline distance but exposed only to the Gulf of Mexico and typically upstream of the urban core, samples SB air that has traversed land and partially regained continental characteristics. Simulations show that the regional SAIs extend ∼ 50 km inland and reach up to the boundary layer height. SAIs further decrease cloud condensation nuclei relevant aerosol number concentrations in ∼ 20 % of events during SBF passage.

In cumulus clouds, aerosol concentrations control cloud droplet concentrations, modifying cloud radiative properties, precipitation processes, and cloud electrification. However, mechanisms of aerosol-deep convection interactions are not well understood due to complex cloud dynamics and microphysics. We investigate the interaction of aerosols with isolated deep convection using Large Eddy Simulations during the TRacking Aerosol Convection interactions ExpeRiment (TRACER) in the Houston area, using a joint cell-thermal tracking algorithm. Cumulus thermals are droplet generators, since supersaturation and droplet nucleation coincide with thermal centers, where the strongest updrafts occur. Primary ice crystal formation does not take place inside thermals, but at layers where previous thermals detrained moisture. As subsequent thermals containing supercooled droplets penetrate these layers, hail and graupel form at or near these thermals. Higher aerosol concentrations result in higher droplet concentrations that suppress drizzle, delay warm rain processes, and transport more moisture aloft. This increases snow and ice amount, as well as graupel and hail, also associated with more lightning. Also, thermals initiate slightly higher, are slightly larger and faster, suggesting a weak invigoration. We also find more thermals per cell, albeit fewer isolated cells. Convection aggregates more, explaining the lower isolated cell count, and enhancing convection, especially near the end of the 24-hour integration. This non-linear mesoscale feedback is likely triggered by temperature and moisture responses due to aerosol-thermal interactions. Additional time-lagged aerosol-reinialization experiments show that the mesoscale response is the predominant forcing for the invigoration. These changes happen within one day, on a smaller scale than previously suggested.

In cumulus clouds, aerosol concentrations control cloud droplet concentrations, modifying cloud radiative properties, precipitation processes, and cloud electrification. However, mechanisms of aerosol-deep convection interactions are not well understood due to complex cloud dynamics and microphysics. We investigate the interaction of aerosols with isolated deep convection using Large Eddy Simulations during the TRacking Aerosol Convection interactions ExpeRiment (TRACER) in the Houston area, using a joint cell-thermal tracking algorithm. Cumulus thermals are droplet generators, since supersaturation and droplet nucleation coincide with thermal centers, where the strongest updrafts occur. Primary ice crystal formation does not take place inside thermals, but at layers where previous thermals detrained moisture. As subsequent thermals containing supercooled droplets penetrate these layers, hail and graupel form at or near these thermals. Higher aerosol concentrations result in higher droplet concentrations that suppress drizzle, delay warm rain processes, and transport more moisture aloft. This increases snow and ice amount, as well as graupel and hail, also associated with more lightning. Also, thermals initiate slightly higher, are slightly larger and faster, suggesting a weak invigoration. We also find more thermals per cell, albeit fewer isolated cells. Convection aggregates more, explaining the lower isolated cell count, and enhancing convection, especially near the end of the 24-hour integration. This non-linear mesoscale feedback is likely triggered by temperature and moisture responses due to aerosol-thermal interactions. Additional time-lagged aerosol-reinialization experiments show that the mesoscale response is the predominant forcing for the invigoration. These changes happen within one day, on a smaller scale than previously suggested.

In cumulus clouds, aerosol concentrations control cloud droplet concentrations, modifying cloud radiative properties, precipitation processes, and cloud electrification. However, mechanisms of aerosol-deep convection interactions are not well understood due to complex cloud dynamics and microphysics. We investigate the interaction of aerosols with isolated deep convection using Large Eddy Simulations during the TRacking Aerosol Convection interactions ExpeRiment (TRACER) in the Houston area, using a joint cell-thermal tracking algorithm. Cumulus thermals are droplet generators, since supersaturation and droplet nucleation coincide with thermal centers, where the strongest updrafts occur. Primary ice crystal formation does not take place inside thermals, but at layers where previous thermals detrained moisture. As subsequent thermals containing supercooled droplets penetrate these layers, hail and graupel form at or near these thermals. Higher aerosol concentrations result in higher droplet concentrations that suppress drizzle, delay warm rain processes, and transport more moisture aloft. This increases snow and ice amount, as well as graupel and hail, also associated with more lightning. Also, thermals initiate slightly higher, are slightly larger and faster, suggesting a weak invigoration. We also find more thermals per cell, albeit fewer isolated cells. Convection aggregates more, explaining the lower isolated cell count, and enhancing convection, especially near the end of the 24-hour integration. This non-linear mesoscale feedback is likely triggered by temperature and moisture responses due to aerosol-thermal interactions. Additional time-lagged aerosol-reinialization experiments show that the mesoscale response is the predominant forcing for the invigoration. These changes happen within one day, on a smaller scale than previously suggested.

In cumulus clouds, aerosol concentrations control cloud droplet concentrations, modifying cloud radiative properties, precipitation processes, and cloud electrification. However, mechanisms of aerosol-deep convection interactions are not well understood due to complex cloud dynamics and microphysics. We investigate the interaction of aerosols with isolated deep convection using Large Eddy Simulations during the TRacking Aerosol Convection interactions ExpeRiment (TRACER) in the Houston area, using a joint cell-thermal tracking algorithm. Cumulus thermals are droplet generators, since supersaturation and droplet nucleation coincide with thermal centers, where the strongest updrafts occur. Primary ice crystal formation does not take place inside thermals, but at layers where previous thermals detrained moisture. As subsequent thermals containing supercooled droplets penetrate these layers, hail and graupel form at or near these thermals. Higher aerosol concentrations result in higher droplet concentrations that suppress drizzle, delay warm rain processes, and transport more moisture aloft. This increases snow and ice amount, as well as graupel and hail, also associated with more lightning. Also, thermals initiate slightly higher, are slightly larger and faster, suggesting a weak invigoration. We also find more thermals per cell, albeit fewer isolated cells. Convection aggregates more, explaining the lower isolated cell count, and enhancing convection, especially near the end of the 24-hour integration. This non-linear mesoscale feedback is likely triggered by temperature and moisture responses due to aerosol-thermal interactions. Additional time-lagged aerosol-reinialization experiments show that the mesoscale response is the predominant forcing for the invigoration. These changes happen within one day, on a smaller scale than previously suggested.

The Sea Breeze Circulation (SBC) influences atmospheric processes at multiple scales in coastal regions. Understanding how SBCs impact the aerosol number budget and aerosol impact on perturbation of incoming solar radiation is essential. This study investigates sea breeze-aerosol interactions (SAIs) during 46 summertime SBC events using data from the TRacking Aerosol Convection Interactions Experiment (TRACER) field campaign across rural and urban sites in southern Texas. Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) simulations complement observations to explore spatio-temporal meteorological controls on boundary layer aerosols. During the campaign, Sea Breeze Fronts (SBF) penetrating inland transported cool, moist air over the land, introducing air masses with distinct properties compared to the preexisting continental air. These SAIs cause variability in number concentrations of up to a factor of two, with events typically lasting ~5 hrs before returning to background conditions. SAI’s impact on aerosols varies with site’s proximity to the sea and the preceding sea breeze (SB) history, primarily affecting the marine-influenced accumulation mode. The coastal site reflects stronger marine influence, while the inland site reflects SB air masses that regain continental characteristics. Model outputs show that the regional SAIs extend ~50 km inland and reach up to the boundary layer height. SBC further influences the local aerosol radiative impacts by changing the aerosol number budget. SAIs modify cloud condensation nuclei in ~20 % of events during SBF passage. For the typical TRACER SBF passage, the local aerosol radiative forcing was also found to change by up to 40 %.