The Arctic is experiencing unprecedented moistening, which is expected to have far-reaching impact on global climate and weather patterns. However, it remains unclear whether this newly-sourced moisture originates locally from ice-free ocean regions or is advected from lower latitudes. In this study, we use water vapour isotope measurements in combination with trajectory-based diagnostics and an isotope-enabled AGCM, to assess seasonal shifts in moisture sources and transport pathways in the Arctic. Continuous measurements of near-surface vapour, δ18O, and δD were performed onboard RV Polarstern during the MOSAiC expedition from October 2019 to September 2020. Combining this isotope dataset with meteorological observations reveals that the spatiotemporal evolution of δ18O mimics changes in local temperature and humidity at synoptic to seasonal time scales, while corresponding d-excess changes suggest a seasonal shift in the origin of moisture. Simulation results from the particle dispersion model FLEXPART support these findings, indicating that summer moisture originates from nearby open ocean, while winter moisture comes from more remote sources with longer residence time over sea-ice. Results from a nudged ECHAM6-wiso simulation also indicate that evaporative processes from the ocean surface reproduce summer sotope values, but are insufficient to explain measured winter isotope values. Our study provides the first isotopic characterization of Central Arctic moisture over the course of an entire year, helping to differentiate the influence of local processes versus large-scale vapour transport on Arctic moistening. Future process-based investigations should focus on assessing the non-equilibrium isotopic fractionation during airmass transformation over sea-ice.

A document by Carmen González Hernández. Click on the document to view its contents.

Estimating the unresolved geophysical processes from resolved geophysical fluid dynamics is the key for improving numerical weather-climate predictions. While data-driven parameterization for unresolved geophysical processes shows potential, most practices fail to capture the diversity of unresolved geophysical processes that agree with resolved geophysical fluid state. This pitfall undermines the likelihood or severity of simulated weather extremes, and erodes the fidelity of climate projections. We propose the criteria of READS (Realism, Efficiency, Adaptability, Diversity, Sharpness) for generative models to yield reasonable stochastic parameterization. We introduce probabilistic diffusion model, a non-equilibrium thermodynamics inspired deep generative modeling approach, to better meet these criteria. Using a case example of numerical precipitation estimation, we demonstrate the advantage of the proposed methodology in quickly delivering diverse and faithful estimates for the target unresolved process, as compared to other popular data-driven deterministic and stochastic methods (UNet, variational autoencoder, generative adversarial net), as well as dynamical downscaling method (WRF). We conclude that generative models, in particular, probabilistic diffusion model, can significantly enhance the representation of unresolved geophysical processes in numerical weather-climate predictions.

Aerosol particles play a critical role in the tropical tropopause layer (TTL) through cloud formation and heterogeneous chemistry, influencing the radiative and chemical balance of the stratosphere. However, aerosol measurements in the TTL are sparse, resulting in poor knowledge of aerosol abundance and distribution in this important region. Here, we present in situ aircraft measurements over the western tropical Pacific, revealing a persistent and altitude-dependent enhancement of aerosol mass in the TTL compared to the convectively influenced troposphere below. Notably, our data demonstrate a striking positive correlation between aerosol mass and ozone. Model simulations suggest that organic materials constitute a substantial fraction of the total aerosol mass within the TTL. We further derived an empirical parameterization of TTL aerosol mass as a function of ozone. Given the relative ease of ozone measurements and modeling, the parameterization provides a promising framework for estimating TTL aerosol abundance and its effects on climate.

An attempt has been made to quantitatively analyze different degrees of environmental drought events, given the limited scientific understanding of environmental droughts, which hinders practical assessment efforts. This study thus aims to rigorously develop and assess the applicability of a novel heuristic method in conjunction with creating an Environmental Drought Index \cite{Srivastava_2023}. The heuristic method evaluates the combined influences of drought duration and water shortage levels, providing crucial insights into the environmental flow requirements amidst climate change. The Minimum in-stream Flow Requirements (MFR) is first defined as the threshold value essential for sustaining the river basin's ecological functions, aligning with Tennant’s environmental flow concept. Establishing MFR enables a balance between water resource utilization and ecological preservation, fostering sustainable water management. To comprehensively assess the eco-status, the study defined the High Flow Season (HFS) and the Low Flow Season (LFS). Drought status is then determined by comparing MFR with observed streamflow rate, quantifying negative differences as environmental droughts. Drought Duration Length (DDL) and Water Shortage Level (WSL) are introduced as functions of environmental drought. DDL categorizes consecutive months into four classes: DDL 1 (1-3 months), DDL 2 (4-6 months), DDL 3 (7-12 months), and DDL 4 (>12 months). WSL is determined by the most significant water deficit observed during DDL, classified into four categories: WSL 1 (<40%), WSL 2 (40-60%), WSL 3 (60-80%), and WSL 4 (>80%). Integrating DDL and WSL yields an index classifying environmental drought events into slight, moderate, severe, and extreme levels. The index value is obtained by comparing DDL and WSL values and selecting the maximum. The study enhances the scientific rigor of environmental drought identification and analysis, contributing to understanding drought impacts and effective mitigation strategies.  

The geostationary Himawari-8 satellite offers a unique opportunity to monitor sub-daily thermal dynamics over Asia and Oceania, and several operational land surface temperature (LST) retrieval algorithms have been developed for this purpose. However, studies have reported inconsistency between LST data obtained from geostationary and polar-orbiting platforms, particularly for daytime LST, which usually shows directional artefacts and can be strongly impacted by viewing and illumination geometries and shadowing effects. To overcome this challenge, Solar Zenith Angle (SZA) serves as an ideal physical variable to quantify systematic differences between platforms. Here we presented an SZA-based Calibration (SZAC) method to operationally calibrate the daytime component of a split-window retrieved Himawari-8 LST (referred to here as the baseline). SZAC describes the spatial heterogeneity and magnitude of diurnal LST discrepancies from different products. The SZAC coefficient was spatiotemporally optimised against highest-quality assured (error < 1 K) pixels from the MODerate-resolution Imaging Spectroradiometer (MODIS) daytime LST between 01/Jan/2016 and 31/Dec/2020. We evaluated the calibrated LST data, referred to as the Australian National University LST with SZAC (ANUSZAC), against MODIS LST and the Visible Infrared Imaging Radiometer Suite (VIIRS) LST, as well as in-situ LST from the OzFlux network. Two peer Himawari-8 LST products from Chiba University and the Copernicus Global Land Service were also collected for comparisons. The median daytime bias of ANUSZAC LST against Terra-MODIS LST, Aqua-MODIS LST and VIIRS LST was 1.52 K, 0.98 K and -0.63 K, respectively, which demonstrated improved performance compared to baseline (5.37 K, 4.85 K and 3.02 K, respectively) and Chiba LST (3.71 K, 2.90 K and 1.07 K, respectively). All four Himawari-8 LST products showed comparable performance of unbiased root mean squared error (ubRMSE), ranging from 2.47 to 3.07 K, compared to LST from polar-orbiting platforms. In the evaluation against in-situ LST, the overall mean values of bias (ubRMSE) of baseline, Chiba, Copernicus and ANUSZAC LST during daytime were 4.23 K (3.74 K), 2.16 K (3.62 K), 1.73 K (3.31 K) and 1.41 K (3.24 K), respectively, based on 171,289 hourly samples from 20 OzFlux sites across Australia between 01/Jan/2016 and 31/Dec/2020. In summary, the SZAC method offers a promising approach to enhance the reliability of geostationary LST retrievals by incorporating the spatiotemporal characteristics observed by accurate polar-orbiting LST data. Furthermore, it is possible to extend SZAC for LST estimation by using data acquired by geostationary satellites in other regions, e.g., Europe, Africa and Americas, as this could improve our understanding of the error characteristics of overlapped geostationary imageries, allowing for targeted refinements and calibrations to further enhance applicability.KeywordsLand surface temperature; Geostationary; Himawari-8; Diurnal temperature cycle; Calibration; Solar zenith angle; MODIS; VIIRS

ANCHOR is a novel assimilative model developed at the U.S. Naval Research Laboratory. It extracts ionospheric parameters from RO and ionosonde data and assimilates them as point measurements into the maps of the background parameters using Kalman Filter approach. This paper introduces the ANCHOR algorithm, discusses its coordinate system and background, explains the background covariance formation, discusses the extraction of the ionospheric parameters from the data and the assimilation process, and, finally, shows the results of the observing system simulation experiment.

Current eddy-permitting and eddy-resolving ocean models require dissipation to prevent a spurious accumulation of enstrophy at the grid scale. We introduce a new numerical scheme for momentum advection in large-scale ocean models that involves upwinding through a weighted essentially non-oscillatory (WENO) reconstruction. The new scheme provides implicit dissipation and thereby avoids the need for an additional explicit dissipation that may require calibration of unknown parameters. This approach uses the rotational, "vector invariant" formulation of the momentum advection operator that is widely employed by global general circulation models. A novel formulation of the WENO "smoothness indicators" is key for avoiding excessive numerical dissipation of kinetic energy and enstrophy at grid-resolved scales. We test the new advection scheme against a standard approach that combines explicit dissipation with a dispersive discretization of the rotational advection operator in two scenarios: (i) two-dimensional turbulence and (ii) three-dimensional baroclinic equilibration. In both cases, the solutions are stable, free from dispersive artifacts, and achieve increased "effective" resolution compared to other approaches commonly used in ocean models.

The Chinese Loess Plateau (CLP) in northern China serves one of the most prominent loess records in the world. The CLP is an extensive record of changes in past aeolian dust activity in East Asia; however, the interpretation of the loess records is hampered by ambiguity regarding the origin of loess-forming dust and an incomplete understanding of the circulation forcing dust accumulation. In this study, we used a novel modeling approach combining a dust emission model FLEXDUST with simulated back trajectories from FLEXPART to trace the dust back to where it was emitted. Over 21 years (1999-2019), we modeled back trajectories for fine (~ 2mu) and super-coarse (~ 20mu) dust particles at six CLP sites during the peak dust storm season from March to May. The source receptor relationship from FLEXPART is combined with the dust emission inventory from FLEXDUST to create site-dependent high-resolution maps of the source contribution of deposited dust. The nearby dust-emission areas dominate the source contribution at all sites. Wet deposition is important for dust deposition at all sites, regardless of dust size. Non-negligible amounts of dust from distant emission regions could be wet deposited on the CLP following high-level tropospheric transport, with the super-coarse dust preferentially from emission areas upwind of sloping topography. On an interannual scale, the phase of the Arctic Oscillation (AO) in winter was found to have a strong impact on the deposition rate on the CLP, while the strength of the East Asian Winter Monsoon was less influential.

The paper presents a new method for the decomposition of the horizontal wind divergence among the linear wave solutions on the sphere: inertia-gravity (IG), mixed Rossby-gravity (MRG), Kelvin and Rossby waves. The work is motivated by the need to quantify the vertical velocity and momentum fluxes in the tropics where the distinction between the Rossby and gravity regime, present in the extratropics, becomes obliterated. The new method decomposes divergence and its power spectra as a function of latitude and pressure level. Its application on ERA5 data in August 2018 reveals that the Kelvin and MRG waves made about 6% of the total divergence power in the upper troposphere within 10S-10N, that is about 25% of divergence. Their contribution at individual zonal wavenumbers k can be much larger; for example, Kelvin waves made up to 24% of divergence power at synoptic k in August 2018. The relatively small roles of the Kelvin and MRG waves in tropical divergence power are explained by decomposing their kinetic energies into rotational and divergent parts. The Rossby wave divergence power is 0.3-0.4% at most, implying up to 6% of global divergence due to the beta effect. The remaining divergence is about equipartitioned between the eastward- and westward-propagating IG modes in the upper troposphere, whereas the stratospheric partitioning depends on the background zonal flow. This work is a step towards a unified decomposition of the momentum fluxes that supports the coexistence of different wave species in the tropics in the same frequency and wavenumber bands. 

Understanding the dynamics of sulfur dioxide (SO2) degassing is of primary importance to track temporal variations of volcanic activity. We develop here an algorithm to automatically estimate daily SO2 masses flux from space-borne hyperspectral images (such as those provided by Sentinel-5P/TROPOMI) without requiring prior knowledge of plume direction or speed. The method computes a linear regression, as a function of distance, of SO2 mass integrated in a series of nested circular domains centered on the volcano. An additional term proportional to the square of the distance, depending solely on a cutoff on the minimum reliable pixel column amount, allows for estimating pixel noise and posterior uncertainty. A statistical test is introduced to automatically detect occurrences of volcanic degassing, by comparing estimated flux and its associated uncertainty. After inversion, a single multiplication by plume speed suffices to deduce the SO2 mass flux, without requiring to re-run the inversion. This way, a range of plume speed scenarios can be easily explored. The method is suited for weakly degassing sources or high-latitude volcanoes. It is applied to two case-studies, where temporal correlation between degassing and seismic energy is highlighted: (a) a one-year-long period of intense degassing at Etna, Italy (2021), and (b) a two-years-long period including three eruptions at Piton de la Fournaise, La Réunion (2021–2023). The method is open-source, and is implemented as an interactive tool within the VolcPlume web portal, facilitating near-real-time exploitation of the TROPOMI archive for both volcano monitoring and assessment of volcanogenic atmospheric hazards.

Understanding the formation of the solar system can provide a simplified look at the universe at large. This is because we have a lot of evidence about the formation of our solar system, and because the universe is homogeneous on a large scale. In this paper, we propose a new way for investigating the formation of the Earth and other Solar System objects. Our approach offers insights into details of the formation of the multiple layers within Earth, the existence of water and oil, the variation in mass distribution within Earth, and the origin of mountains, erratic boulders, and moons. According to our proposed approach, Roche Radius can explain the origin of moons, rings and mountains on planets. We have listed and use critical conditions that are required to form celestial objects.

Large-scale dynamical and thermodynamical processes are common environmental drivers of extreme weather events. However, such large-scale environmental conditions often display systematic biases in climate simulations, posing challenges to evaluating extreme weather events and associated risks in current and future climate. In this paper, a machine learning (ML) approach was employed to bias correct the large-scale wind, temperature, and humidity simulated by the E3SM atmosphere model at $\sim 1^\circ$ resolution. The usefulness of the proposed ML approach for extreme weather analysis was demonstrated with a focus on three extreme weather events, including tropical cyclones (TCs), extratropical cyclones (ETCs), and atmospheric rivers (ARs). We show that the ML model can effectively reduce climate bias in large-scale wind, temperature, and humidity while preserving their responses to imposed climate change perturbations. The bias correction is found to directly improve the water vapor transport associated with ARs, and the representations of thermodynamical flows associated with ETCs. When the bias-corrected large-scale winds are used to drive a synthetic TC track forecast model over the Atlantic basin, the resulting TC track density agrees better with that of the TC track model driven by observed winds. In addition, the ML model insignificantly interferes with the mean climate change signals of large-scale storm environments as well as the occurrence and intensity of three extreme events. This study suggests that the proposed ML approach can be used to improve the downscaling of extreme weather events by providing more realistic large-scale storm environments simulated by low-resolution climate models.

Heterogeneous chemical cycles of pyrogenic nitrogen and halides influence tropospheric ozone and affect the stratosphere during extreme pyrocumulonimbus (PyroCB) events. We report field-derived N2O5 uptake coefficients, γ(N2O5), and ClNO2 yields, φ(ClNO2), from two aircraft campaigns observing fresh smoke in the lower and mid troposphere and processed/aged smoke in the upper troposphere and lower stratosphere (UTLS). Derived φ(ClNO2) varied across the full 0–1 range but was typically < 0.5 and smallest in a PyroCB (< 0.05). Derived γ(N2O5) was low in agricultural smoke (0.2–3.6 ×10-3), extremely low in mid-tropospheric wildfire smoke (0.1 × 10-3), but larger in PyroCB processed smoke (0.7–5.0 × 10–3). Aged BB aerosol in the UTLS had a higher median γ(N2O5) of 17 × 10–3 that increased with sulfate and liquid water, but that was nevertheless 1–2 orders of magnitude lower than values for aqueous sulfuric aerosol used in stratospheric models.

Canonical understanding based on general circulation models (GCMs) is that the atmospheric circulation response to midlatitude sea-surface temperature (SST) anomalies is weak compared to the larger influence of tropical SST anomalies. However, the horizontal resolution of modern GCMs, ranging from roughly 300 km to 25 km, is too coarse to fully resolve mesoscale atmospheric processes such as weather fronts. Here, we investigate the large-scale atmospheric circulation response to idealized Gulf Stream SST anomalies in Community Atmosphere Model (CAM6) simulations with 14-km regional grid refinement over the North Atlantic, and compare it to the response in simulations with 28-km regional refinement and uniform 111-km resolution. The highest resolution simulations show a large positive response of the wintertime North Atlantic Oscillation (NAO) to positive SST anomalies in the Gulf Stream, a 0.8-standard-deviation anomaly in the seasonal-mean NAO for 2°C SST anomalies. The lower-resolution simulations show a weaker response with a different spatial structure. The enhanced large-scale circulation response results from an increase in resolved vertical motions with resolution and an associated increase in the influence of SST anomalies on transient-eddy heat and momentum fluxes in the free troposphere. In response to positive SST anomalies, these processes lead to a stronger North Atlantic jet that varies less in latitude, as is characteristic of positive NAO anomalies. Our results suggest that the atmosphere responds differently to midlatitude SST anomalies in higher-resolution models and that regional refinement in key regions offers a potential pathway to improve multi-year regional climate predictions based on midlatitude SSTs.

Numerous satellite operators are building megaconstellations in Low Earth Orbit (LEO) with hundreds of satellites, placing new satellites and spent rocket stages in orbit. Once these objects fail, they are often removed from LEO via atmospheric reentry, producing metallic particles that can interact with ozone chemistry and Earth’s radiative balance. The extent of these interactions remains poorly understood despite their importance to current space governance and policymaking. Helping to address this gap, this paper estimates the distribution, lifetime and direct radiative forcing of reentry-ablated alumina using an Earth system model. We consider a future scenario where all megaconstellations publicly filed at the Federal Communications Commission as of 2022 are operating, amounting to 2.52 Gg/yr of reentry-ablated alumina emissions. As a conservative approximation, we find that reentry-ablated alumina particles have an atmospheric lifetime between one and two years, leading to a cooling radiative forcing of approximately -0.378mW/m2. Simulations with fine alumina particles produce between 14% and 36% larger radiative forcings and have lifetimes 1.54 times longer than simulations with coarse alumina emissions. Alumina emitted only in the South Pacific produces an asymmetrical radiative forcing. Furthermore, modeling alumina with time-averaged, constant emissions rather than in discrete reentry plumes in results in 21% to 24% overestimation of alumina’s radiative forcing. These results are sensitive to numerous assumptions on initial particle size, radiative indices and coagulation characteristics of the aerosol. In-situ observation and a sophisticated understanding of reentry-ablated alumina particles are necessary to better predict the atmospheric consequences of reentry-ablated alumina.

Canada’s first and only F5/EF5 tornado associated with a supercell touched down near Elie, Manitoba in the late afternoon of 22 June 2007. An observational and numerical simulation analysis with the Weather Research and Forecasting (WRF) model was undertaken to characterize the pre-storm environment and processes leading to storm initiation. WRF sufficiently reproduced the synoptic and mesoscale features, including a supercell-like storm in the region of interest, and supplemented available observations. Synthesis of observational and simulation data suggests that the environment near Elie immediately before storm initiation was primed for tornadic supercells, with large most-unstable and mixed-layer convective available potential energy (4000 J kg^-1) and sufficient vertical shear (effective bulk wind shear 40 kt; effective storm-relative helicity >200 m2 s^-2). Despite enhancement owing to a cold pool left behind by passing early-afternoon convection, shear remained weaker than those typically found in other North American significant tornadic supercell events. The interaction between a surface trough and convective boundary-layer thermals was the primary triggering mechanism of the Elie supercell. The former appeared to be associated with a low pressure arising from the juxtaposition of lower-troposphere cyclonic differential vorticity advection and lee troughing over the western Red River Valley. More observational analysis and numerical sensitivity experiments are required to better diagnose Manitoba terrain’s contribution to the Elie supercell initiation.

Zonal extensions of the Western Pacific subtropical high (WPSH) strongly modulate extreme rainfall activity and tropical cyclone (TC) landfall over the Western North Pacific (WNP) region. On seasonal timescales, these zonal extensions are forced primarily by inter-basin zonal sea surface temperature (SST) gradients. However, despite the presence of large-scale zonal SST gradients, the WPSH’s response to SSTs varies from year to year. In this study, we force the atmosphere-only NCAR Community Earth System Model version 2 simulations with two real-world SST patterns, both featuring the large-scale zonal SST gradient characteristic of decaying El Niño/developing La Niña summers. For each of these patterns, we perform four experimental sets that test the relative contributions of the tropical Indian Ocean, Pacific, and Atlantic basin SSTs to simulated westward extensions over the WNP during June-August. Our results indicate that the subtle differences between the two SST anomaly patterns belie two different mechanisms forcing the WPSH’s westward extensions. In one SST pattern, the extratropical North Pacific SST forcing suppresses the tropical Pacific zonal SST gradient forcing, resulting in tropical Atlantic and Indian Ocean SST warming being the main drivers of the Walker Circulation. With an adjacent SST pattern, subsidence over the WNP is driven predominantly by intra-basin Pacific SST forcing. The results of this study have implications for understanding and predicting the impact of the WPSH’s zonal variability on tropical cyclones and extreme rainfall over the WNP.

Comprehending the intricate interplay between atmospheric aerosols and water vapour in subsaturated regions is vital for accurate modelling of aerosol–cloud–radiation–climate dynamics. But the microphysical mechanisms governing these interactions with ambient aerosols remain inadequately understood. Here we report results from high-altitude, relatively pristine site in Western-Ghats of India during monsoon, serving as a baseline for climate processes in one of the world’s most polluted regions. Utilizing a novel quartz crystal microbalance (QCM) approach, we conducted size-resolved sampling to analyse humidity-dependent growth factors, hygroscopicity, deliquescence behaviour, and aerosol liquid water content (ALWC). Fine-mode aerosols (≤2.5 μm) exhibited size-dependent interactions with water vapour, contributing significantly to ALWC. Deliquescence was observed in larger aerosols (>180 nm), influenced by organic species, with deliquescence relative humidity (DRH) lower than that of pure inorganic salts. This research highlights the significance of understanding ambient aerosol-water interactions and hygroscopicity for refining climate models in subsaturated conditions.

Due to their potential role in organizing tropical mesoscale convective systems, a better understanding of cold pool (CP) dynamics in such regions is critical, particularly over land where the diurnal cycle further concentrates convective activity. Numerical models help disentangle the processes involved but often lack observational benchmark studies. To close this gap, we analyze nearly 43 years of five-minute resolution near-surface timeseries records from twelve automatic weather stations across equatorial Africa. We identify 4289 CPs based on criteria for temperature and wind. The identified CP gust fronts, which exhibit respective median temperature and specific humidity decreases of 5.2 K and 2.8 g/kg, closely correlate with satellite-observed brightness temperature discontinuities. Despite weak diurnal variation in precipitation, observed CP occurrence shows a pronounced diurnal cycle with an afternoon peak — a finding we attribute to low-level moisture conditions. Our findings can serve as observational benchmark to improve simulations of CP organization.

The future increase of methane concentration leads to a raise in water vapor abundance in the middle atmosphere. This will enhance the brightness of noctilucent clouds (NLC). We use an atmospheric background model and a microphysical model to study the associated absorption of solar radiation in the period 1950 to 2100. At 69°N mean absorptions at λ=126nm will increase from ~3% to ~7% from 1950 to 2100, respectively. Locally, the absorption can increase to ~30% in the year 2100. In the visible we find an increase from 0.0030% (1950) to 0,020% (2100), i.e., by a factor of ~7, and local maxima up to 0.35% in 2100. The results are similar for polar latitudes (79°N) but are smaller at middle latitudes (58°N). Future mean absorptions are comparable to solar cycle variations, but much larger locally. The ice mass bound in NLC increases from 677 to 1871 tons in 1950 and 2100.

A key uncertainty in Aerosol-cloud interactions is the cloud liquid water path (LWP) response to increased aerosols (λ). LWP can either increase due to precipitation suppression or decrease due to entrainment-drying. Previous research suggests that precipitation suppression dominates in thick clouds, while entrainment-drying prevails in thin clouds. The time scales of the two competing effects are vastly different, requiring temporally resolved observations. We analyze 3-day Lagrangian trajectories of stratocumulus clouds over the southeast Pacific using geostationary data. We find that clouds with a LWP exceeding 200 g m-2 exhibit a positive response, while clouds with lower LWP show a negative response. We observe a significant diurnal cycle in λ, indicating a more strongly negative daytime adjustment driven by entrainment-drying. In contrast, at night, precipitation suppression can occasionally fully counteract the entrainment-drying mechanism. The time-integrated adjustment appears weaker than previously suggested in studies that do not account for the diurnal cycle.

Marine regulations aim to reduce sulfur and nitrogen exhaust emissions from maritime shipping. Here, two compliance pathways for reducing sulfur dioxide emissions, fuel sulfur content reduction and exhaust wet scrubbing, are studied for their effects on physicochemical properties and cloud forming abilities of engine exhaust particles. A test-bed diesel engine was utilized to study fresh exhaust emissions from combustion of non-compliant, high sulfur content fuel with (WS) and without (HiS) the usage of a wet scrubber as well as a regulatory compliant, low sulfur content fuel (LoS). Particle number emissions are decreased by ≈ 99% when switching to LoS due to absence of 20-30 nm sulfate particles. While number emissions for WS are also decreased, a shift in the sulfate mode towards larger sizes was found to increase particle mass emission factors by at least 31%. Changes in the mixing state induced by the compliance measures are reflected in the hygroscopicity of the exhaust particles. Fuel sulfur reduction decreased cloud condensation nuclei emissions by at least 97% due to emissions of primarily hydrophobic soot particles. Wet scrubbing increased those emissions, mainly driven by changes in particle size distributions. Our results indicate that both compliance alternatives have no obvious impact on the ice forming abilities of 200 nm exhaust particles. These detailed results are relevant for atmospheric processes and might be useful input parameters for cloud-resolving models to investigate ship aerosol cloud interactions and to quantify the impact of shipping on the radiative budget.

South America is a large continent situated mostly in the Southern Hemisphere (SH) with complex topography and diverse emissions sources. However, the atmospheric chemistry of this region has been historically understudied. Here, we employ the Multi-Scale Infrastructure for Chemistry and Aerosols, a novel global circulation model with regional refinement capabilities and full chemistry, to explore the sources and distribution of the carbon monoxide (CO) tropospheric column in South America during 2019, and also to assess the effect that South American primary emissions have over the rest of the world. Most of the CO over South America can be explained either by NMVOC secondary chemical production or by biomass burning emissions, with biomass burning as the main explanation for the variability in CO. Biomass burning in Central Africa is a relevant contributor to CO in all of the continent, including the southern tip. Biogenic emissions play a dual role in CO concentrations: they provide volatile organic compounds that contribute to the secondary CO production, but they also destroy OH, which limits the chemical production and destruction of CO. As a net effect, the lifetime of CO is extended to ~120 days on average over the Amazon, while still being in the range of 30-60 days in the rest of South America.