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At least 199 records · Page 11

Effective radiative forcing and adjustments in CMIP6 models

Abstract. The effective radiative forcing, which includes the instantaneous forcing plus adjustments from the atmosphere and surface, has emerged as the key metric of evaluating human and natural influence on the climate. We evaluate effective radiative forcing and adjustments in 17 contemporary climate models that are participating in the Coupled Model Intercomparison Project (CMIP6) and have contributed to the Radiative Forcing Model Intercomparison Project (RFMIP). Present-day (2014) global-mean anthropogenic forcing relative to pre-industrial (1850) levels from climate models stands at 2.00 (±0.23) W m−2, comprised of 1.81 (±0.09) W m−2 from CO2, 1.08 (± 0.21) W m−2 from other well-mixed greenhouse gases, −1.01 (± 0.23) W m−2 from aerosols and −0.09 (±0.13) W m−2 from land use change. Quoted uncertainties are 1 standard deviation across model best estimates, and 90 % confidence in the reported forcings, due to internal variability, is typically within 0.1 W m−2. The majority of the remaining 0.21 W m−2 is likely to be from ozone. In most cases, the largest contributors to the spread in effective radiative forcing (ERF) is from the instantaneous radiative forcing (IRF) and from cloud responses, particularly aerosol–cloud interactions to aerosol forcing. As determined in previous studies, cancellation of tropospheric and surface adjustments means that the stratospherically adjusted radiative forcing is approximately equal to ERF for greenhouse gas forcing but not for aerosols, and consequentially, not for the anthropogenic total. The spread of aerosol forcing ranges from −0.63 to −1.37 W m−2, exhibiting a less negative mean and narrower range compared to 10 CMIP5 models. The spread in 4×CO2 forcing has also narrowed in CMIP6 compared to 13 CMIP5 models. Aerosol forcing is uncorrelated with climate sensitivity. Therefore, there is no evidence to suggest that the increasing spread in climate sensitivity in CMIP6 models, particularly related to high-sensitivity models, is a consequence of a stronger negative present-day aerosol forcing and little evidence that modelling groups are systematically tuning climate sensitivity or aerosol forcing to recreate observed historical warming.

54 ENVIRONMENTAL SCIENCES↗

Viewing Atmospheric Aerosols from the MODIS Satellite Sensor

The MODerate resolution Imaging Spectroradiometer (MODIS) currently aboard both the Terra and Aqua satellites produces a suite of products designed to characterize global aerosol distribution, optical thickness and particle size. Never before has a space-borne instrument been able to provide such detailed information, complementing field and modeling efforts to produce a comprehensive picture of aerosol characteristics. The three years of Terra-MODIS data have been validated by comparing with co-located AERONET observations of aerosol optical thickness and derivations of aerosol size parameters. Some 8000 comparison points located at 133 AERONET sites around the globe show that the MODIS aerosol optical thickness retrievals are accurate to within the pre-launch expectations, on a global basis. The global statistics, however, can hide local biases in the product. Some of these biases will be discussed. Nevertheless, the products can be used and are currently being used to answer some pressing questions concerning aerosol radiative forcing, aerosol-cloud interaction, estimating aerosol sources and height of transport, and Air Quality forecasting. A survey of current applications of MODIS aerosol products will be presented.

Remer, L.↗

Effective radiative forcing and adjustments in CMIP6 models

The effective radiative forcing, which includes the instantaneous forcing plus adjustments from the atmosphere and surface, has emerged as the key metric of evaluating human and natural influence on the climate. We evaluate effective radiative forcing and adjustments in 17 contemporary climate models that are participating in the Coupled Model Intercomparison Project (CMIP6) and have contributed to the Radiative Forcing Model Intercomparison Project (RFMIP). Present-day (2014) global-mean anthropogenic forcing relative to pre-industrial (1850) levels from climate models stands at 2.00 (±0.23) W/sq. m, comprised of 1.81 (±0.09) W/sq. m from CO2, 1.08 (± 0.21) W/sq. m from other well-mixed greenhouse gases, −1.01 (± 0.23) W/sq. m from aerosols and −0.09 (±0.13) W/sq. m from land use change. Quoted uncertainties are 1 standard deviation across model best estimates, and 90 % confidence in the reported forcings, due to internal variability, is typically within 0.1 W/sq. m. The majority of the remaining 0.21 W/sq. m is likely to be from ozone. In most cases, the largest contributors to the spread in effective radiative forcing (ERF) is from the instantaneous radiative forcing (IRF) and from cloud responses, particularly aerosol–cloud interactions to aerosol forcing. As determined in previous studies, cancellation of tropospheric and surface adjustments means that the stratospherically adjusted radiative forcing is approximately equal to ERF for greenhouse gas forcing but not for aerosols, and consequentially, not for the anthropogenic total. The spread of aerosol forcing ranges from −0.63 to −1.37 W/sq. m, exhibiting a less negative mean and narrower range compared to 10 CMIP5 models. The spread in 4×CO2 forcing has also narrowed in CMIP6 compared to 13 CMIP5 models. Aerosol forcing is uncorrelated with climate sensitivity. Therefore, there is no evidence to suggest that the increasing spread in climate sensitivity in CMIP6 models, particularly related to high-sensitivity models, is a consequence of a stronger negative present-day aerosol forcing and little evidence that modelling groups are systematically tuning climate sensitivity or aerosol forcing to recreate observed historical warming.

effective radiative forcing↗

An Automatic Light Rain Detection Algorithm on NASA MPLNET Lidar Observations in the Frame of WMO GALION Project

The water cycle strongly influences life on Earth. In particular, the precipitation modifies the atmospheric column thermodynamics through the process of evaporation and serves as a proxy for latent heat modulation. For this reason, a correct precipitation parameterization (especially low-intensity precipitation) at global scale, bedsides improving our understanding of the hydrological cycle, it is crucial to reduce the associated uncertainty of the global climate models to correctly forecast future scenarios, i.e. to apply fast mitigation strategies. In this study we developed an algorithm to automatically detect precipitation from lidar measurements obtained by the National and Aeronautics Space Administration (NASA) Micropulse lidar network (MPLNET) permanent observational site in Goddard. The algorithm, once full operational, will deliver in Near Real Time (latency 1.5h) a new rain mask product that will be publicly available on MPLNET website as part of the new Version 3 Level 1.5 data. The methodology, based on an image processing technique, can detect only light precipitation events (defined by intensity and duration) as the morphological filters used through the detection process are applied on the lidar volume depolarization ratio range corrected composite images, i.e. heavy rain events are unusable as the lidar signal is completely extinguished after few meters in the precipitation or no signal detected because of the water accumulated on the receiver optics. Results from the algorithm, besides filling a gap in precipitation and virga detection by radars, are of particular interest for the scientific community because will help to better understand long-term aerosol-cloud interactions and aerosol atmospheric removal (scavenging effect) by rain as multi-year database being available for several MPLNET permanent observational sites across the globe. Moreover, we developed the automatic algorithm at Universitat Politecnica de Catalunya (UPC) Barcelona, the unique permanent observation station member of MPLNET and the European Aerosol Lidar Network (EARLINET) In the future the algorithm can be then easily applied to any other lidar and/or ceilometer network infrastructure in the frame of World Meteorological Organization (WMO) Global Aerosol Watch (GAW) aerosol lidar observation network (GALION)

Simone Lolli↗

Scattering and Absorbing Aerosols in the Climate System

Tropospheric anthropogenic aerosols contribute the second-largest forcing to climate change, but with high uncertainty owing to their spatio-temporal variability and complicated optical properties. In this Review, we synthesize understanding of aerosol observations and their radiative and climate effects. Aerosols offset about one-third of the warming effect by anthropogenic greenhouse gases. Yet, in regions and seasons where the absorbing aerosol fraction is high — such as South America and East and South Asia — substantial atmospheric warming can occur. The internal mixing and the vertical distribution of aerosols, which alters both the direct effect and aerosol–cloud interactions, might further enhance this warming. Despite extensive research in aerosol–cloud interactions, there is still at least a 50% spread in total aerosol forcing estimates. This ongoing uncertainty is linked, in part, to the poor measurement of anthropogenic and natural aerosol absorption, as well as the little-understood effects of aerosols on clouds. Next-generation, space-borne, multi-angle polarization and active remote sensing, combined with in situ observations, offer opportunities to better constrain aerosol scattering, absorption and size distribution, thus, improving models to refine estimates of aerosol forcing and climate effects.

Tropospheric anthropogenic aerosols↗

A Model Intercomparison Study of Aerosol‐Cloud‐Turbulence Interactions in a Cloud Chamber: 1. Model Results

This study presents the first model intercomparison of aerosol‐cloud‐turbulence interactions in a controlled cloudy Rayleigh‐Bénard Convection chamber environment, utilizing the Pi Chamber at Michigan Technological University. We analyzed simulated cloud chamber‐averaged statistics of microphysics and thermodynamics in a warm‐phase, cloudy environment under steady‐state conditions at varying aerosol injection rates. Simulation results from seven distinct models (DNS, LES, and a 1D turbulence model) were compared. Our findings demonstrate that while all models qualitatively capture observed trends in droplet number concentration, mean radius, and droplet size distributions at both high and low aerosol injection rates, significant quantitative differences were observed. Notably, droplet number concentrations varied by over two orders of magnitude between models for the same injection rates, indicating sensitivities to the model treatments in droplet activation and removal and wall fluxes. Furthermore, inconsistencies in vertical relative humidity profiles and in achieving steady‐state liquid water content suggest the need for further investigation into the mechanisms driving these variations. Despite these discrepancies, the models generally reproduced consistent power‐law relationships between the microphysical variables. This model intercomparison underscores the importance of controlled cloud chamber experiments for validating and improving cloud microphysical parameterizations. Recommendations for future modeling studies are also highlighted, including constraining wall conditions and processes, investigating droplet/aerosol removal (including sidewall losses), and conducting simplified experiments to isolate specific processes contributing to model divergence and reduce model uncertainties.

54 ENVIRONMENTAL SCIENCES↗

Aerosol-Radiation-Cloud Interactions in the South-East Atlantic: Model-Relevant Observations and the Beneficiary Modeling Efforts in the Realm of the EVS-2 Project ORACLES

Globally, aerosols remain a major contributor to uncertainties in assessments of anthropogenically-induced changes to the Earth climate system, despite concerted efforts using satellite and suborbital observations and increasingly sophisticated models. The quantification of direct and indirect aerosol radiative effects, as well as cloud adjustments thereto, even at regional scales, continues to elude our capabilities. Some of our limitations are due to insufficient sampling and accuracy of the relevant observables, under an appropriate range of conditions to provide useful constraints for modeling efforts at various climate scales. In this talk, I will describe (1) the efforts of our group at NASA Ames to develop new airborne instrumentation to address some of the data insufficiencies mentioned above; (2) the efforts by the EVS-2 ORACLES project to address aerosol-cloud-climate interactions in the SE Atlantic and (3) time permitting, recent results from a synergistic use of A-Train aerosol data to test climate model simulations of present-day direct radiative effects in some of the AEROCOM phase II global climate models.

Redemann, Jens↗

Tracking Aerosol Convection Interactions Experiment (TRACER) Field Campaign Report

Convective clouds serve a critical role in the Earth’s energy and water cycles through their transport of heat, moisture, momentum, and chemical species through the troposphere driving the global circulation (e.g., Hartmann et al. 1984, Del Genio et al. 2012, Su et al. 2014). On more local scales, convective clouds impact the atmospheric heating profile through diabatic heating effects, removal of water from the atmospheric column through precipitation, and conditioning of the local environment impacting further development of clouds (e.g., Sullivan and Voigt 2021). These critical roles underscore the importance of realistic representation of convective processes across scales of models from large-eddy simulation (LES), to convection-permitting models (CPM; e.g., Kendon et al. 2020, Marinescu et al. 2021), to numerical weather prediction (NWP) models used for operational weather forecasting, to Earth system models used to predict climate sensitivity (Sanderson et al. 2011, Sherwood et al. 2014, Tomassini et al. 2014, Zhao et al. 2016, Cronin et al. 2017). A key component of improving model representation of convective clouds is better quantification and parameterization of updraft microphysics and dynamics, including their interactions with the surrounding environment and storm organization (Bony et al. 2015, Hagos and Houze 2016, Donner et al. 2016, Morrison et al. 2020). Aerosol is an important environmental factor that could affect convective clouds and precipitation since cloud droplet and ice formation processes are initiated by it. Andrae et al. (2004) hypothesized that aerosols associated with increased biomass burning particles acting as cloud condensation nuclei (CCN) result in smaller and more monodisperse cloud droplets leading to suppression of warm rain formation, ultimately leading to more cloud water being lofted above the freezing level based on observations in the Amazon region. The subsequent increase in latent heat release increases the buoyancy of rising convective parcels invigorating the deep convection. This work was followed by a description of the theoretical basis for this “cold-phase invigoration” by Rosenfeld et al. (2008), who argued that it could have a significant effect for deep convective clouds with warm cloud-bases. Several modeling studies (e.g., Khain et al. 2005, 2009, van den Heever et al. 2006, Fan et al. 2007, 2009, 2012, Lee et al. 2008, Storer et al. 2010, Lebo et al. 2012, Storer and van den Heever 2013, Chen et al. 2020, Dagan et al. 2022) have investigated these aerosol-convection interactions and the environmental factors that influence their relative importance and magnitude. More recently, several studies have indicated that “warm-phase invigoration”, the enhancement of convection through condensational heating, also appears to play a role in enhancing both shallow cumuli (Seiki and Nakajima 2014, Saleeby et al 2015) and deeper tropical convection (Lebo and Seinfeld 2011, Khain et al. 2012, Sheffield et al 2015, Fan et al. 2018, Igel and van den Heever 2021), as well as Houston thunderstorms (Fan et al. 2007, 2020). However, still other studies have provided additional evidence of systematic biases in simulated convective outflow ice size distribution properties, which are consistent with a lack of poorly understood secondary ice production within convective updrafts (e.g., Fridlind et al. 2017). To help address these critical gaps in our understanding of cloud processes, aerosol processes and aerosol-cloud interactions, the Tracking Aerosol Convection Interactions Experiment was designed building upon efforts by the Aerosol, Cloud, Precipitation and Climate (ACPC) Initiative (http://acpcintiative.org/), a joint effort of the International Geosphere-Biosphere Programme (IGBP) and the World Climate Research Program (WCRP) that focused on resolving uncertainties in the interactions between aerosol and clouds towards better understanding the role that these interactions play in the climate system. The TRACER campaign was motivated by recommendations from a number of pilot studies undertaken by ACPC (van den Heever et al. 2017, Fridlind et al. 2019, Hu et al. 2019, Fan et al. 2020, Marinescu et al. 2021, Hernandez-Deckers et al. 2022) that pointed towards the southeastern Texas region as a locale where aerosol-convection interactions could be studied owing to the copious occurrence of isolated convection during the summer months accompanied by diverse and significant sources of aerosols from both anthropogenic and natural sources. The TRACER campaign began on 01 October 2021 and extended through 30 September 2022 with an intensive operational period (IOP) during June-September 2022. Three main sites (Table 1) were managed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility.

54 ENVIRONMENTAL SCIENCES↗

Arctic Radiation-Cloud-Aerosol-Surface Interaction eXperiment (ARCSIX)

The Arctic climate system is amidst a transition. Over the last 40 years, the Arctic sea ice pack has transformed from a predominantly thick, multi-year sea ice to a predominantly thin, seasonal sea ice, termed the “New Arctic”. The observed rapid changes in the Arctic sea ice pack are an integral part of the Arctic Amplification phenomenon and represent a response to and a feedback on global climate change. As a result, the role of the Arctic within the global climate system is changing. Substantial uncertainty exists in our understanding of the atmosphere-surface interactions within the Arctic system, limiting our knowledge of the Arctic’s role in the future climate. Advancing our understanding of the Arctic climate system requires (1) measurements of the coupling between radiative processes and sea ice surface properties during summer sea ice melt; (2) measurements of the processes controlling the predominant Arctic cloud regimes and their properties (Fig. 1); and (3) improvements in the ability to monitor Arctic cloud, radiation, and sea ice processes from space. A key challenge is that thin, low clouds that are radiatively important to the Arctic surface energy budget can go undetected (Fig. 1). The Arctic Radiation-Cloud-Aerosol-Surface-Interaction eXperiment (ARCSIX) is an airborne campaign based at the Pituffik Space Base in Greenland from May-August 2024 sponsored by the National Aeronautics and Space Administration (NASA) to address these needs. ARCSIX consists of two airborne measurement campaigns taking place in two 3-week intervals during the early and late sea ice melt season: late May through early June and late July through early August, respectively. ARCSIX science is guided by three broad science questions that encapsulate the key influences of radiation-cloud-aerosol-sea ice coupling and a remote sensing and modeling objective: Science Question 1 (Radiation): What is the impact of the predominant summer Arctic cloud types on the radiative surface energy budget? Science Question 2 (Cloud Life Cycle): What processes control the evolution and maintenance of the predominant cloud regimes in the summertime Arctic? Science Question 3 (Sea Ice): How do the two-way interactions between surface properties and atmospheric forcings affect the sea ice evolution? Remote Sensing and Modeling Objective: Enhance our long-term space-based monitoring and predictive capabilities of Arctic sea ice, clouds, and aerosols.

Patrick Taylor↗

Overview of the HI-SCALE Field Campaign: A New Perspective on Shallow Convective Clouds

Shallow convective clouds are common, occurring over many areas of the world, and are an important component in the atmospheric radiation budget. In addition to synoptic and mesoscale meteorological conditions, land-atmosphere interactions and aerosol-radiation-cloud interactions can influence the formation of shallow clouds and their properties. However, these processes exhibit large spatial and temporal variability and occur at the sub-grid scale for all climate and operational forecast models and must be represented by parameterizations. Uncertainties in shallow cloud parameterization predictions arise from many sources, including insufficient coincident data needed to adequately represent the coupling of cloud macrophysical and microphysical properties with inhomogeneity in the surface layer, boundary layer, and aerosol properties. Predictions in the transition of shallow to deep convection and the onset of precipitation are also affected by errors in simulated shallow clouds. Coincident data is a key factor needed to achieve a more complete understanding of the lifecycle of shallow convective clouds and to develop improved model parameterizations. To address these issues, the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) campaign was conducted near the Atmospheric Radiation and Measurement (ARM) Southern Great Plains site in north-central Oklahoma during 2016. We describe the scientific objectives of HI-SCALE as well as the experimental approach, the overall weather conditions during the campaign, and preliminary findings from the measurements. Finally, we discuss the remaining scientific gaps in our understanding of shallow clouds that can be addressed by analysis and modeling studies that use HI-SCALE data including: the effects of heterogeneous land-use, vegetation, and soil moisture conditions on boundary layer mixing and consequently cloud formation; factors that contribute to the transition of shallow to deep convection; the role of cloud population on

Fast, Jerome D.↗

Machine-Learning Reveals Climate Forcing From Aerosols is Dominated by Increased Cloud Cover

Aerosol-cloud interactions have a potentially large impact on climate, but are poorly quantified and thus contribute a significant and long-standing uncertainty in climate projections. The impacts derived from climate models are poorly constrained by observations, because retrieving robust large-scale signals of aerosol-cloud interactions are frequently hampered by the considerable noise associated with meteorological co-variability. The Iceland-Holuhraun effusive eruption in 2014 resulted in a massive aerosol plume in an otherwise near-pristine environment and thus provided an ideal natural experiment to quantify cloud responses to aerosol perturbations. Here we disentangle significant signals from the noise of meteorological co-variability using a satellite-based machine-learning approach. Our analysis shows that aerosols from the eruption increased cloud cover by approximately 10%, and this appears to be the leading cause of climate forcing, rather than cloud brightening as previously thought. We find that volcanic aerosols do brighten clouds by reducing droplet size, but this has a significantly smaller radiative impact than changes in cloud fraction. These results add substantial observational constraints on the cooling impact of aerosols. Such constraints are critical for improving climate models, which still inadequately represent the complex macro-physical and micro-physical impacts of aerosol-cloud interactions.

Aerosols↗

Vertical Gradient of Size-Resolved Aerosol Compositions over the Arctic Reveals Cloud Processed Aerosol in-Cloud and above Cloud

Arctic aerosols play a significant role in the aerosol-radiation and aerosol-cloud interactions, but ground-based measurements are insufficient to explain the interaction of aerosols and clouds in a vertically stratified Arctic atmosphere. This study shows the vertical variability of aerosol particle composition via tethered balloon system at Oliktok Point, Alaska, in August 2019, at different cloud layers for two case studies (background aerosol condition and polluted condition). Multi-modal micro-spectroscopy analysis of samples during the background case reveals a broadening of chemically specific size distribution above cloud top with a high abundance of sulfate and core-shell morphology, suggesting possible cloud processing of aerosols. The pollution case also indicates a broadening of size distribution at the upper cloud layer with the dominance of carbonaceous aerosol, which suggests the potential of carbonaceous aerosols for Arctic cloud formation. Here this study provides insights into the vertical profile of Arctic aerosols on cloud formation.

54 ENVIRONMENTAL SCIENCES↗

Effect of volcanic emissions on clouds during the 2008 and 2018 Kilauea degassing events

Volcanic eruptions in otherwise clean environments are “natural experiments” wherein the effects of aerosol emissions on clouds and climate can be partitioned from meteorological variability and anthropogenic activities. In this work, we combined satellite retrievals, reanalysis products, and atmospheric modeling to analyze the mechanisms of aerosol–cloud interactions during two degassing events at the Kilauea volcano in 2008 and 2018. The eruptive nature of the 2008 and 2018 degassing events was distinct from long-term volcanic activity for Kilauea. Although previous studies assessed the modulation of cloud properties from the 2008 event, this is the first time such an analysis has been reported for the 2018 event and that multiple degassing events have been analyzed and compared at this location. Both events resulted in significant changes in cloud effective radius and cloud droplet number concentration that were decoupled from local meteorology and in line with an enhanced cloud albedo. However, it is likely that the effects of volcanic emissions on liquid water path and cloud fraction were largely offset by meteorological variability. Comparison of cloud anomalies between the two events suggested a threshold response of aerosol–cloud interactions to overcome meteorological effects, largely controlled by aerosol loading. In both events, the ingestion of aerosols within convective parcels enhanced the detrainment of condensate in the upper troposphere, resulting in deeper clouds than observed under pristine conditions. Accounting for ice nucleation on ash particles led to enhanced ice crystal concentrations at cirrus levels and a slight decrease in ice water content, improving the correlation of the model results with the satellite retrievals. Overall, aerosol loading, plume characteristics, and meteorology contributed to changes in cloud properties during the Kilauea degassing events.

Katherine H. Breen↗

Constraining the instantaneous aerosol influence on cloud albedo

Much of the uncertainty in estimates of the anthropogenic forcing of climate change comes from uncertainties in the instantaneous effect of aerosols on cloud albedo, known as the Twomey effect or the radiative forcing from aerosol–cloud interactions (RFaci), a component of the total or effective radiative forcing. Because aerosols serving as cloud condensation nuclei can have a strong influence on the cloud droplet number concentration ( N d ), previous studies have used the sensitivity of the N d to aerosol properties as a constraint on the strength of the RFaci. However, recent studies have suggested that relationships between aerosol and cloud properties in the present-day climate may not be suitable for determining the sensitivity of the N d to anthropogenic aerosol perturbations. Using an ensemble of global aerosol–climate models, this study demonstrates how joint histograms between N d and aerosol properties can account for many of the issues raised by previous studies. It shows that if the anthropogenic contribution to the aerosol is known, the RFaci can be diagnosed to within 20% of its actual value. Furthermore, the accuracy of different aerosol proxies for diagnosing the RFaci is investigated, confirming that using the aerosol optical depth significantly underestimates the strength of the aerosol–cloud interactions in satellite data.

54 ENVIRONMENTAL SCIENCES↗

Enhanced mid-latitude warming due to poleward shift of sea salt aerosols in a warmer future

Natural aerosols provide large uncertainties regarding the quantification of the climate effects of aerosols, especially those related to aerosol-cloud interactions. Advancing research on the interaction of natural aerosols and climate can provide a better assessment of the climate impacts of anthropogenic activities. Furthermore, as one of the most dominant natural aerosols, sea salt has the highest proportion of mass in natural aerosols. Sea salt can be regarded as a purely scattering aerosol, causing a negative radiative effect by scattering shortwave solar radiation and acting as cloud condensation nuclei (CCN) through aerosol-cloud interactions. Future climate change will influence sea salt distribution, thus modifying the radiative effects of sea salt, which will further affect the climate. However, few previous studies have explored the interactions between sea salt changes under warming scenarios and climate change.

Yang, Yang [Nanjing Univ. of Information Science a↗

Atmospheric Research Over the Extended Western North Atlantic Ocean Region and North American East Coast: A Review of Past Work and Challenges Ahead

Decades of atmospheric research have focused on the extended Western North Atlantic Ocean (WNAO) region, including the East Coast of North America and the island of Bermuda, because of its unique location that offers accessibility, gradients in important atmospheric parameters, and a range of meteorological regimes leading to diverse conditions that are poorly understood. This work reviews decades of scientific investigations for the extended WNAO region. Approximately 40 combined field campaigns and long-term monitoring programs, in addition to 563 peer-reviewed publications between 1950 and 2019 have provided a firm foundation of knowledge for the extended WNAO region. Of particular importance in this region has been extensive work at the island of Bermuda that is host to important time series records of oceanic and atmospheric variables. Our review categorizes WNAO research into eight major categories, with some studies fitting into multiple categories (relative %): Aerosols (26%), Gases (23%), Development/Validation of Techniques, Models, and Retrievals (17%), Meteorology and Transport (10%), Air-Sea Interactions (9%), Wet Deposition (6%), Clouds/Storms (6%), and Aerosol-Cloud Interactions (3%). These extensive works have revealed a series of major knowledge gaps. For instance, a disproportionately low number of studies have been devoted to aerosol-cloud interactions, which is identified here as one of the most pressing research needs for the extended WNAO region. Recommendations for future research are provided in the categories highlighted above. Part 2 of this paper series will summarize major spatial and temporal features for the extended WNAO region.

Sorooshian, Armin↗

Using aircraft measurements to characterize subgrid-scale variability of aerosol properties near the Atmospheric Radiation Measurement Southern Great Plains site

Abstract. Complex distributions of aerosol properties evolve in space and time as a function of emissions, new particle formation, coagulation, condensational growth, chemical transformation, phase changes, turbulent mixing and transport, removal processes, and ambient meteorological conditions. The ability of chemical transport models to represent the multi-scale processes affecting the life cycle of aerosols depends on their spatial resolution since aerosol properties are assumed to be constant within a grid cell. Subgrid-scale-dependent processes that affect aerosol populations could have a significant impact on the formation of particles, their growth to cloud condensation nuclei (CCN) sizes, aerosol–cloud interactions, dry deposition and rainout and hence their burdens, lifetimes, and radiative forcing. To address this issue, we characterize subgrid-scale variability in terms of measured aerosol number, size, composition, hygroscopicity, and CCN concentrations made by repeated aircraft flight paths over the Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site during the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystem (HI-SCALE) campaign. Subgrid variability is quantified in terms of both normalized frequency distributions and percentage difference percentiles using grid spacings of 3, 9, 27, and 81 km that represent those typically used by cloud-system-resolving models as well as the current and next-generation climate models. Even though the SGP site is a rural location, surprisingly large horizontal gradients in aerosol properties were frequently observed. For example, 90 % of the 3, 9, and 27 km cell mean organic matter concentrations differed from the 81 km cell around the SGP site by as much as ∼ 46 %, large spatial variability in aerosol number concentrations and size distributions were found during new particle formation events, and consequently 90 % of the 3, 9, and 27 km cell mean CCN number concentrations differed from the 81 km cell mean by as much as ∼ 38 %. The spatial variability varied seasonally for some aerosol properties, with some having larger spatial variability during the spring and others having larger variability during the late summer. While measurements at a single surface site cannot reflect the surrounding variability of aerosol properties at a given time, aircraft measurements that are averaged within an 81 km cell were found to be similar to many, but not all, aerosol properties measured at the ground SGP site. This analysis suggests that it is reasonable to directly compare most ground SGP site aerosol measurements with coarse global climate model predictions. In addition, the variability quantified by the aircraft can be used as an uncertainty range when comparing the surface point measurements with model predictions that use coarse grid spacings.

54 ENVIRONMENTAL SCIENCES↗

Comparing the interactions between particulate matter and cloud properties over two populated cities in Texas using WRF-Chem fine-resolution modeling

Accurate modeling of aerosol-cloud interactions is essential for reliable weather and air quality simulations, given their significant impact on precipitation patterns, cloud dynamics, and aerosol distributions. This study employed the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to examine the impact of enhanced meteorological simulations, achieved through advanced microphysics parameterization supported by data assimilation techniques, on air quality across Texas on August 19 and 20, 2022. We tested four distinct configurations: (1) the Morrison two-moment bulk microphysics scheme, (2) Morrison's with observation nudging, (3) the Spectral Bin Microphysics (SBM), and (4) SBM with observation nudging. While the SBM scheme is known for its detailed representation of aerosol-cloud interactions, our focus was on how improvements in meteorological accuracy translate to more precise air quality simulations. Our findings demonstrated a progressive improvement in simulation accuracy, starting with the Morrison's scheme and further enhanced by adopting the SBM scheme, complemented by incorporating observation nudging. Specifically, the combination of the SBM scheme and the nudging substantially enhanced the model's ability to capture convective precipitation events, as shown by better alignment with NEXRAD radar reflectivity, with R increasing from –0.21 to 0.82, IOA from 0.10 to 0.87, and NMB decreasing from 99% to 34% in Houston. The enhanced meteorology translated into more accurate PM 2.5 concentration simulations, particularly through the more accurate representation of aerosol washout during precipitation events. In Houston, the SBM scheme with nudging improved the model's PM 2.5 simulations significantly, with NMB decreasing from –20% to 5% and IOA improving from 0.43 to 0.61. In San Antonio, improvements were also notable, with NMB improved from –27% to –22%, R increased from 0.48 to 0.82, and IOA increased from 0.66 to 0.86. Furthermore, our results underscore the crucial role of accurate meteorological simulations in refining our understanding of aerosol behaviors in relation to precipitation patterns, directly enhancing the reliability and effectiveness of air quality modeling.

54 ENVIRONMENTAL SCIENCES↗