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At least 379 records · Page 21

Radiative feedbacks of dust in snow over eastern Asia in CAM4-BAM

Dust in snow on the Tibetan Plateau (TP) could reduce the visible snow albedo by changing surface optical properties and removing the snow cover through increased snowmelt, which leads to a significant positive radiative forcing and remarkably alters the regional energy balance and the eastern Asian climate system. This work extends our previous investigation in dust–radiation interactions to investigate the dust-in-snow radiative forcing (SRF) and its feedbacks on the regional climate and the dust cycle over eastern Asia through the use of the Community Atmosphere Model version 4 with a Bulk Aerosol Model parameterizations of the dust size distribution (CAM4-BAM). Our results show that SRF increases the eastern Asian dust emissions significantly by 13.7% in the spring, countering a 7.6% decrease in the regional emissions by the dust direct radiative forcing (DRF). SRF also remarkably affects the whole dust cycle, including transport and deposition of dust aerosols over eastern Asia. The simulations indicate an increase in dust emissions of 5.1%, due to the combined effect of DRF and SRF. Further analysis reveals that these results are mainly due to the regional climatic feedbacks induced by SRF over eastern Asia. By reducing the snow albedo over the TP, the dust in snow mainly warms the TP and influences its thermal effects by increasing the surface sensible and latent heat flux, which in turn increases the aridity and westerly winds over northwestern China and affects the regional dust cycle. Additionally, the dust in snow also accelerates the snow-melting process, reduces the snow cover and then expands the eastern Asian dust source region, which results in increasing the regional dust emissions. Hence, a significant feature of SRF on the TP is the creation of a positive feedback loop that affects the dust cycle over eastern Asia.

54 ENVIRONMENTAL SCIENCES↗

Modulation of springtime surface sensible heating over the Tibetan Plateau on the interannual variability of East Asian dust cycle

Previous observational evidence and numerical simulations have revealed that the surface sensible heating in spring (March–April–May, MAM) over the Tibetan Plateau (TPSH) can affect the Asian regional hydrological cycle, surface energy balance, and climate through altering atmospheric heat source of the Tibetan Plateau (TP). This study aims to investigate the impacts of MAM TPSH on the interannual variability of East Asian dust cycle by using CAM4-BAM (version 4 of the Community Atmosphere Model coupled to a bulk aerosol model), MERRA-2 (version 2 of the Modern-Era Retrospective analysis for Research and Applications) surface dust concentration, and TPSH measurements. Our simulations show that the surface dust concentrations over the East Asian (EA) dust source region and over the northwestern Pacific (NP) in MAM are significantly positively correlated with TPSH, with regionally averaged correlation coefficients of 0.49 for EA and 0.44 for NP. Similar positive correlations are also shown between the MAM TPSH measurements averaged over the 73 observation sites and the surface dust concentration from MERRA-2. Simulation-based comparisons between strongest and weakest TPSH years reveal that, the MAM surface dust concentration in the strongest TPSH years increases with relative differences of 13.1 % over EA and 36.9 % over NP. These corresponding differences are found in MERRA-2 with 22.9 % and 13.3 % over EA and NP, respectively. Further simulated results show that the processes of whole dust cycles (e.g., dust loading, emission, and transport, as well as dust deposition) are also significantly enhanced during the strongest TPSH years over EA and NP. Through enhancing the TP heat source, stronger TPSH in MAM generates an anticyclonic anomaly in middle and upper troposphere over the TP and over the downstream Pacific region, respectively. These atmospheric circulation anomalies induced by the increased TPSH result in increasing the westerly winds over both EA and NP, which in turn increases dust emissions over the dust source, and dust transport over these two regions, as well as the regional dust cycles. These results suggest that addressing the East Asian dust changes in the future climates requires considering not only increasing greenhouse gas emissions but also the variations of the TP's heat source under global warming.

54 ENVIRONMENTAL SCIENCES↗

Trends and source apportionment of aerosols in Europe during 1980-2018

Aerosols have significantly affected health, environment, and climate in Europe. Aerosol concentrations have been declining since the 1980s in Europe,mainly owing to a reduction of local aerosol and precursor emissions.Emissions from other source regions of the world, which have been changing rapidly as well, may also perturb the historical and future trends of aerosols and change their radiative impact in Europe. This study examines trends of aerosols in Europe during 1980–2018 and quantifies contributions from 16 source regions using the Community Atmosphere Model version 5 with Explicit Aerosol Source Tagging (CAM5-EAST). The simulated near-surface total mass concentration of sulfate, black carbon, and primary organic carbon had a 62 % decrease during 1980–2018. The majority of which was contributed to reductions of local emissions in Europe, and 8 %–9 % was induced by a decrease in emissions from Russia–Belarus–Ukraine. With the decreases in the fractional contribution of local emissions, aerosols transported from other source regions are increasingly important for air quality in Europe. During 1980–2018, the decrease in sulfate loading led to a warming effect of 2.0 W m –2 in Europe, with 12 % coming from changes in non-European sources, especially from North America and Russia–Belarus–Ukraine. According to the Shared Socioeconomic Pathways (SSP) scenarios, contributions to the sulfate radiative forcing over Europe from both local European emissions and non-European emissions should decrease at a comparable rate in the next 3 decades, suggesting that future changes in non-European emissions are as important as European emissions for causing possible regional climate change associated with aerosols in Europe.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Aerosol transport pathways and source attribution in China during the COVID-19 outbreak

Abstract. Due to the coronavirus disease 2019 (COVID-19) pandemic, human activities and industrial productions were strictly restricted during January–March 2020 in China. Despite the fact that anthropogenic aerosol emissions largely decreased, haze events still occurred. Characterization of aerosol transport pathways and attribution of aerosol sources from specific regions are beneficial to air quality and pandemic control strategies. This study establishes source–receptor relationships in various regions covering all of China during the COVID-19 outbreak based on the Community Atmosphere Model version 5 with Explicit Aerosol Source Tagging (CAM5-EAST). Our analysis shows that PM2.5 burden over the North China Plain between 30 January and 19 February is mostly contributed by local emissions (40 %–66 %). For other regions in China, PM2.5 burden is largely contributed from nonlocal sources. During the most polluted days of the COVID-19 outbreak, local emissions within the North China Plain and eastern China contributed 66 % and 87 % to the increase in surface PM2.5 concentrations, respectively. This is associated with the anomalous mid-tropospheric high pressure at the location of the climatological East Asia trough and the consequently weakened winds in the lower troposphere, leading to the local aerosol accumulation. The emissions outside China, especially those from South Asia and Southeast Asia, contribute over 50 % to the increase in PM2.5 concentration in southwestern China through transboundary transport during the most polluted day. As the reduction in emissions in the near future is desirable, aerosols from long-range transport and unfavorable meteorological conditions are increasingly important to regional air quality and need to be taken into account in clean-air plans.

54 ENVIRONMENTAL SCIENCES↗

Exploring dimethyl sulfide (DMS) oxidation and implications for global aerosol radiative forcing

Abstract. Aerosol indirect radiative forcing (IRF), which characterizes how aerosols alter cloud formation and properties, is very sensitive to the preindustrial (PI) aerosol burden. Dimethyl sulfide (DMS), emitted from the ocean, is a dominant natural precursor of non-sea-salt sulfate in the PI and pristine present-day (PD) atmospheres. Here we revisit the atmospheric oxidation chemistry of DMS, particularly under pristine conditions, and its impact on aerosol IRF. Based on previous laboratory studies, we expand the simplified DMS oxidation scheme used in the Community Atmospheric Model version 6 with chemistry (CAM6-chem) to capture the OH-addition pathway and the H-abstraction pathway and the associated isomerization branch. These additional oxidation channels of DMS produce several stable intermediate compounds, e.g., methanesulfonic acid (MSA) and hydroperoxymethyl thioformate (HPMTF), delay the formation of sulfate, and, hence, alter the spatial distribution of sulfate aerosol and radiative impacts. The expanded scheme improves the agreement between modeled and observed concentrations of DMS, MSA, HPMTF, and sulfate over most marine regions, based on the NASA Atmospheric Tomography (ATom), the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA), and the Variability of the American Monsoon Systems (VAMOS) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) measurements. We find that the global HPMTF burden and the burden of sulfate produced from DMS oxidation are relatively insensitive to the assumed isomerization rate, but the burden of HPMTF is very sensitive to a potential additional cloud loss. We find that global sulfate burden under PI and PD emissions increase to 412 Gg S (+29 %) and 582 Gg S (+8.8 %), respectively, compared to the standard simplified DMS oxidation scheme. The resulting annual mean global PD direct radiative effect of DMS-derived sulfate alone is −0.11 W m−2. The enhanced PI sulfate produced via the gas-phase chemistry updates alone dampens the aerosol IRF as anticipated (−2.2 W m−2 in standard versus −1.7 W m−2, with updated gas-phase chemistry). However, high clouds in the tropics and low clouds in the Southern Ocean appear particularly sensitive to the additional aqueous-phase pathways, counteracting this change (−2.3 W m−2). This study confirms the sensitivity of aerosol IRF to the PI aerosol loading and the need to better understand the processes controlling aerosol formation in the PI atmosphere and the cloud response to these changes.

54 ENVIRONMENTAL SCIENCES↗

Biomass-burning smoke's properties and its interactions with marine stratocumulus clouds in WRF-CAM5 and southeastern Atlantic field campaigns

Abstract. A large part of the uncertainty in climate projections comes from uncertain aerosol properties and aerosol–cloud interactions as well as the difficulty in remotely sensing them. The southeastern Atlantic functions as a natural laboratory to study biomass-burning smoke and to constrain this uncertainty. We address these gaps by comparing the Weather Research and Forecasting with Chemistry Community Atmosphere Model (WRF-CAM5) to the multi-campaign observations ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS), CLARIFY (CLoud–Aerosol–Radiation Interaction and Forcing), and LASIC (Layered Atlantic Smoke Interactions with Clouds) in the southeastern Atlantic in August 2017 to evaluate a large range of the model's aerosol chemical properties, size distributions, processes, and transport, as well as aerosol–cloud interactions. Overall, while WRF-CAM5 is able to represent smoke properties and transport, some key discrepancies highlight the need for further analysis. Observations of smoke composition show an overall decrease in aerosol mean diameter as smoke ages over 4–12 d, while the model lacks this trend. A decrease in the mass ratio of organic aerosol (OA) to black carbon (BC), OA:BC, and the OA mass to carbon monoxide (CO) mixing ratio, OA:CO, suggests that the model is missing processes that selectively remove OA from the particle phase, such as photolysis and heterogeneous aerosol chemistry. A large (factor of ∼2.5) enhancement in sulfate from the free troposphere (FT) to the boundary layer (BL) in observations is not present in the model, pointing to the importance of properly representing secondary sulfate aerosol formation from marine dimethyl sulfide and gaseous SO2 smoke emissions. The model shows a persistent overprediction of aerosols in the marine boundary layer (MBL), especially for clean conditions, which multiple pieces of evidence link to weaker aerosol removal in the modeled MBL than reality. This evidence includes several model features, such as not representing observed shifts towards smaller aerosol diameters, inaccurate concentration ratios of carbon monoxide and black carbon, underprediction of heavy rain events, and little evidence of persistent biases in modeled entrainment. The average below-cloud aerosol activation fraction (NCLD/NAER) remains relatively constant in WRF-CAM5 between field campaigns (∼0.65), while it decreases substantially in observations from ORACLES (∼0.78) to CLARIFY (∼0.5), which could be due to the model misrepresentation of clean aerosol conditions. WRF-CAM5 also overshoots an observed upper limit on liquid cloud droplet concentration around NCLD= 400–500 cm−3 and overpredicts the spread in NCLD. This could be related to the model often drastically overestimating the strength of boundary layer vertical turbulence by up to a factor of 10. We expect these results to motivate similar evaluations of other modeling systems and promote model development to reduce critical uncertainties in climate simulations.

54 ENVIRONMENTAL SCIENCES↗

Aircraft in-situ measurements from SOCRATES constrain the anthropogenic perturbations of cloud droplet number

Aerosol-cloud interactions (ACI) in warm clouds alter reflected shortwave radiation by influencing cloud microphysical and macrophysical properties. The variable of state controlling ACI is the cloud droplet number concentration (N d ). Here, we examine the perturbations in N d due to anthropogenic aerosols (ΔN d, PD-PI ) using a perturbed parameter ensemble (PPE) hosted in the sixth Community Atmosphere Model (CAM6). Surrogate models are created for the CAM6 PPE outputs and are used to generate 1 million model variants of CAM6 by sampling 45 sources of parameter uncertainty. The range of uncertain physical parameters related to ACI are constrained with observations of aerosol and cloud properties from SOCRATES. The likely range of uncertain parameters and the associated range of ΔN d, PD-PI are more strongly constrained with observations of N d relative to observations of cloud condensation nuclei. We conduct sensitivity tests of how constraints on ΔN d, PD-PI are affected by systematic uncertainties in observations and our limitations in our surrogate models created for CAM6 PPE outputs. Based on this, we provide guidance on the impact of reducing systematic uncertainty in airborne microphysical observations and in surrogate models.

Song, Ci [Univ. of Wyoming, Laramie, WY (United St↗

Constraining aerosol–cloud adjustments by uniting surface observations with a perturbed parameter ensemble

Abstract. Aerosol–cloud interactions (ACIs) are the largest source of uncertainty in inferring the magnitude of future warming consistent with the observational record. The effective radiative forcing due to ACI (ERFaci) is dominated by liquid clouds and is composed of two terms: the change in cloud albedo due to redistributing liquid over a larger number of cloud droplets (Nd) and the change in cloud macrophysical properties due to changes in cloud microphysics. These terms are, respectively, referred to as the radiative forcing due to ACI (RFaci) and aerosol–cloud adjustments. While the magnitude of RFaci is uncertain, its sign is confidently negative and results in a cooling in the historical record. In contrast, the adjustment of cloud liquid water path (LWP) to enhanced Nd and associated radiative forcing is uncertain in sign. Increased LWP in response to increased Nd is consistent with precipitation suppression, while decreased LWP in response to increased Nd is consistent with enhanced evaporation from cloud top. Observational constraints of these processes are poor in part because of causal ambiguity in the relationship between Nd and LWP. To better understand this relationship, precipitation (P), Nd, and LWP surface observations from the Eastern North Atlantic (ENA) atmospheric observatory are combined with the output from a perturbed parameter ensemble (PPE) hosted in the Community Atmosphere Model version 6 (CAM6). This allows for causal interpretation of observed covariability. Observations of precipitation and cloud from ENA constrain the range of possible LWP aerosol–cloud adjustments relative to the prior from the PPE by 15 %, resulting in a global value that is confidently positive (a historical cooling) ranging from 2.1 to 6.9 g m−2. It is found that observed covariability between Nd and LWP is dominated by coalescence scavenging and that this observed covariability is not strongly related to aerosol–cloud adjustments.

54 ENVIRONMENTAL SCIENCES↗

The path to CAM6: coupled simulations with CAM5.4 and CAM5.5

This paper documents coupled simulations of two developmental versions of the Community Atmosphere Model (CAM) towards CAM6. The configuration called CAM5.4 introduces new microphysics, aerosol, and ice nucleation changes, among others to CAM. The CAM5.5 configuration represents a more radical departure, as it uses an assumed probability density function (PDF)-based unified cloud parameterization to replace the turbulence, shallow convection, and warm cloud macrophysics in CAM. This assumed PDF method has been widely used in the last decade in atmosphere-only climate simulations but has never been documented in coupled mode. Here, we compare the simulated coupled climates of CAM5.4 and CAM5.5 and compare them to the control coupled simulation produced by CAM5.3. We find that CAM5.5 has lower cloud forcing biases when compared to the control simulations. Improvements are also seen in the simulated amplitude of the Niño-3.4 index, an improved representation of the diurnal cycle of precipitation, subtropical surface wind stresses, and double Intertropical Convergence Zone biases. Degradations are seen in Amazon precipitation as well as slightly colder sea surface temperatures and thinner Arctic sea ice. Simulation of the 20th century results in a credible simulation that ends slightly colder than the control coupled simulation. The authors find this is due to aerosol indirect effects that are slightly stronger in the new version of the model and propose a solution to ameliorate this. Altogether, in these early coupled simulations, CAM5.5 produces a credible climate that is appropriate for science applications and is ready for integration into the National Center for Atmospheric Research's (NCAR's) next-generation climate model.

54 ENVIRONMENTAL SCIENCES↗

Topological data analysis and machine learning for recognizing atmospheric river patterns in large climate datasets

Identifying weather patterns that frequently lead to extreme weather events is a crucial first step in understanding how they may vary under different climate change scenarios. Here, we propose an automated method for recognizing atmospheric rivers (ARs) in climate data using topological data analysis and machine learning. The method provides useful information about topological features (shape characteristics) and statistics of ARs. We illustrate this method by applying it to outputs of version 5.1 of the Community Atmosphere Model version 5.1 (CAM5.1) and the reanalysis product of the second Modern-Era Retrospective Analysis for Research and Applications (MERRA-2). An advantage of the proposed method is that it is threshold-free – there is no need to determine any threshold criteria for the detection method – when the spatial resolution of the climate model changes. Hence, this method may be useful in evaluating model biases in calculating AR statistics. Further, the method can be applied to different climate scenarios without tuning since it does not rely on threshold conditions. We show that the method is suitable for rapidly analyzing large amounts of climate model and reanalysis output data.

54 ENVIRONMENTAL SCIENCES↗

The spectral element method (SEM) on variable-resolution grids: evaluating grid sensitivity and resolution-aware numerical viscosity

We evaluate the performance of the Community Atmosphere Model's (CAM) spectral element method on variable-resolution grids using the shallow-water equations in spherical geometry. We configure the method as it is used in CAM, with dissipation of grid scale variance, implemented using hyperviscosity. Hyperviscosity is highly scale selective and grid independent, but does require a resolution-dependent coefficient. For the spectral element method with variable-resolution grids and highly distorted elements, we obtain the best results if we introduce a tensor-based hyperviscosity with tensor coefficients tied to the eigenvalues of the local element metric tensor. The tensor hyperviscosity is constructed so that, for regions of uniform resolution, it matches the traditional constant-coefficient hyperviscosity. With the tensor hyperviscosity, the large-scale solution is almost completely unaffected by the presence of grid refinement. This later point is important for climate applications in which long term climatological averages can be imprinted by stationary inhomogeneities in the truncation error. We also evaluate the robustness of the approach with respect to grid quality by considering unstructured conforming quadrilateral grids generated with a well-known grid-generating toolkit and grids generated by SQuadGen, a new open source alternative which produces lower valence nodes.

Guba, O.↗

Quantifying the impact of sub-grid surface wind variability on sea salt and dust emissions in CAM5

This paper evaluates the impact of sub-grid variability of surface wind on sea salt and dust emissions in the Community Atmosphere Model version 5 (CAM5). The basic strategy is to calculate emission fluxes multiple times, using different wind speed samples of a Weibull probability distribution derived from model-predicted grid-box mean quantities. In order to derive the Weibull distribution, the sub-grid standard deviation of surface wind speed is estimated by taking into account four mechanisms: turbulence under neutral and stable conditions, dry convective eddies, moist convective eddies over the ocean, and air motions induced by mesoscale systems and fine-scale topography over land. The contributions of turbulence and dry convective eddy are parameterized using schemes from the literature. Wind variabilities caused by moist convective eddies and fine-scale topography are estimated using empirical relationships derived from an operational weather analysis data set at 15 km resolution. The estimated sub-grid standard deviations of surface wind speed agree well with reference results derived from 1 year of global weather analysis at 15 km resolution and from two regional model simulations with 3 km grid spacing. The wind-distribution-based emission calculations are implemented in CAM5. In terms of computational cost, the increase in total simulation time turns out to be less than 3 %. Simulations at 2° resolution indicate that sub-grid wind variability has relatively small impacts (about 7 % increase) on the global annual mean emission of sea salt aerosols, but considerable influence on the emission of dust. Among the considered mechanisms, dry convective eddies and mesoscale flows associated with topography are major causes of dust emission enhancement. With all the four mechanisms included and without additional adjustment of uncertain parameters in the model, the simulated global and annual mean dust emission increase by about 50 % compared to the default model. By tuning the globally constant dust emission scale factor, the global annual mean dust emission, aerosol optical depth, and top-of-atmosphere radiative fluxes can be adjusted to the level of the default model, but the frequency distribution of dust emission changes, with more contribution from weaker wind events and less contribution from stronger wind events. Lastly, in Africa and Asia, the overall frequencies of occurrence of dust emissions increase, and the seasonal variations are enhanced, while the geographical patterns of the emission frequency show little change.

58 GEOSCIENCES↗

ENSO Tropical Cloud and TOA radiative signatures from the CERES observation

The Clouds and the Earth's Radiant Energy System (CERES) project now has over 15 years accurately observed top-of-the-atmosphere (TOA) flux record for climate monitoring and diagnostic studies. The CERES flux-by-cloud-type dataset, which contains cloud properties and radiative fluxes for 42 cloud types sorted by cloud top pressure and cloud optical depth, is used to investigate the clouds and their associated TOA (top-of-the-atmosphere) fluxes changes over the tropical area during ENSO events during the observed period. Unlike past studies, this study shows the impact of ENSO on cloud properties like optical depth, cloud top effective pressure and temperature and TOA LW and SW fluxes for each sub cloud type. The study reveals the detailed contributions from different cloud types for radiative characteristics during different phases of ENSO. This is especially important for very small net TOA radiative balance due to the cancellation of the fluxes from different cloud types. To further demonstrate the usefulness of this dataset, NCAR Community Atmosphere Model (CAM) is used to simulate the cloud and radiative changes during the period. The model cloud properties are converted to MODIS like cloud properties using modified MODIS simulator. The dataset serves as a more stringent validation of the model for cloud properties and radiative fluxes.

Moguo Sun↗

Testing cloud microphysics parameterizations in NCAR CAM5 with ISDAC and M-PACE observations

Arctic clouds simulated by the National Center for Atmospheric Research (NCAR) Community Atmospheric Model version 5 (CAM5) are evaluated with observations from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Indirect and Semi-Direct Aerosol Campaign (ISDAC) and Mixed-Phase Arctic Cloud Experiment (M-PACE), which were conducted at its North Slope of Alaska site in April 2008 and October 2004, respectively. Model forecasts for the Arctic spring and fall seasons performed under the Cloud-Associated Parameterizations Testbed framework generally reproduce the spatial distributions of cloud fraction for single-layer boundary-layer mixed-phase stratocumulus and multilayer or deep frontal clouds. However, for low-level stratocumulus, the model significantly underestimates the observed cloud liquid water content in both seasons. As a result, CAM5 significantly underestimates the surface downward longwave radiative fluxes by 20-40 W m{sup -2}. Introducing a new ice nucleation parameterization slightly improves the model performance for low-level mixed-phase clouds by increasing cloud liquid water content through the reduction of the conversion rate from cloud liquid to ice by the Wegener-Bergeron-Findeisen process. The CAM5 single-column model testing shows that changing the instantaneous freezing temperature of rain to form snow from -5 C to -40 C causes a large increase in modeled cloud liquid water content through the slowing down of cloud liquid and rain-related processes (e.g., autoconversion of cloud liquid to rain). The underestimation of aerosol concentrations in CAM5 in the Arctic also plays an important role in the low bias of cloud liquid water in the single-layer mixed-phase clouds. In addition, numerical issues related to the coupling of model physics and time stepping in CAM5 are responsible for the model biases and will be explored in future studies.

54 ENVIRONMENTAL SCIENCES↗

Inter-annual Tropospheric Aerosol Variability in Late Twentieth Century and its Impact on Tropical Atlantic and West African Climate by Direct and Semi-direct Effects

A new high-resolution (0.9$^{\circ}$x1.25$^{\circ}$ in the horizontal) global tropospheric aerosol dataset with monthly resolution is generated using the finite-volume configuration of Community Atmosphere Model (CAM4) coupled to a bulk aerosol model and forced with recent estimates of surface emissions for the latter part of twentieth century. The surface emissions dataset is constructed from Coupled Model Inter-comparison Project (CMIP5) decadal-resolution surface emissions dataset to include REanalysis of TROpospheric chemical composition (RETRO) wildfire monthly emissions dataset. Experiments forced with the new tropospheric aerosol dataset and conducted using the spectral configuration of CAM4 with a T85 truncation (1.4$^{\circ}$x1.4$^{\circ}$) with prescribed twentieth century observed sea surface temperature, sea-ice and greenhouse gases reveal that variations in tropospheric aerosol levels can induce significant regional climate variability on the inter-annual timescales. Regression analyses over tropical Atlantic and Africa reveal that increasing dust aerosols can cool the North African landmass and shift convection southwards from West Africa into the Gulf of Guinea in the spring season in the simulations. Further, we find that increasing carbonaceous aerosols emanating from the southwestern African savannas can cool the region significantly and increase the marine stratocumulus cloud cover over the southeast tropical Atlantic ocean by aerosol-induced diabatic heating of the free troposphere above the low clouds. Experiments conducted with CAM4 coupled to a slab ocean model suggest that present day aerosols can shift the ITCZ southwards over the tropical Atlantic and can reduce the ocean mixed layer temperature beneath the increased marine stratocumulus clouds in the southeastern tropical Atlantic.

Evans, Katherine J↗

Hemispheric Differences in Tropical Lower Stratospheric Transport and Tracers Annual Cycle

Transport of long-lived tracers (such as O, CO, and N O) in the lower stratosphere largely determines the composition of the entire stratosphere. Stratospheric transport includes the mean residual circulation (with air rising in the tropics and sinking in the polar and middle latitudes), plus two-way isentropic (quasi-horizontal) mixing by eddies. However, the relative importance of two transport components remains uncertain. Previous studies quantified the relative role of these processes based on tropics-wide average characteristics under common assumption of well-mixed tropics. However, multiple instruments provide us with evidence that show significant differences in the seasonal cycle of ozone between the Northern (0-20N) and Southern (0-20S) tropical (NT and ST respectively) lower stratosphere. In this study we investigate these differences in tracer seasonality and quantify transport processes affecting tracers annual cycle amplitude using simulations from Goddard Earth Observing System Chemistry Climate Model (GEOSCCM) and Whole Atmosphere Community Climate Model (WACCM) and compare them to observations from the Microwave Limb Sounder (MLS) on the Aura satellite. We detect the observed contrast between the ST and NT in GEOSCCM and WACCM: annual cycle in ozone and other chemical tracers is larger in the NT than in the ST but opposite is true for the annual cycle in vertical advection. Ozone budgets in the models, analyzed based on the Transformed Eulerian Mean (TEM) framework, demonstrate a major role of quasi-horizontal mixing vertical advection in determining the NTST ozone distribution and behavior. Analysis of zonal variations in the NT and ST ozone annual cycles further suggests important role of North American and Asian Summer Monsoons (associated with strong isentropic mixing) on the lower stratospheric ozone in the NT. Furthermore, multi model comparison shows that most CCMs reproduce the observed characteristic of ozone annual cycle quite well. Thus, latitudinal variations within the tropics have to be considered in order to understand the balance between upwelling and quasi- horizontal mixing in the tropical lower stratosphere and the paradigm of well mixed tropics has to be reconsidered.

Chemistry-Climate Models↗

WACCM6 Projections of Polar Mesospheric Cloud Abundance Over the 21st Century

Polar mesospheric clouds (PMC), or noctilucent clouds, can be observed over high latitudes with the naked eye from the ground or from space near the summer solstice. PMC are considered a direct and sensitive indicator of climate change and have been reported to appear more frequently in recent decades. How PMC will change in the future under the influence of natural variability and anthropogenic forcing is uncertain. In this study, we utilize model output from the Whole Atmosphere Community Climate Model under several shared socioeconomic pathway (SSP) scenarios and input the water vapor, temperature, and pressure information into a 0-d PMC model to project the trend and variation of PMC over the 21st century, and their relationship to future changes of temperature, water vapor, and the solar cycle. The 0-d model calculations indicate that PMC ice water content (IWC) will increase and PMC will extend to lower latitudes under high SSP scenarios. Under these scenarios, more mesospheric water vapor leads to an increased IWC of PMC over the polar region, and colder mesopause temperature leads to more PMC over the mid-latitudes. There is a significant anti-correlation between the solar cycle and PMC IWC over the 21st century, but the anti-correlation is not always significant on the decadal scale. Finally, methane oxidation in the stratosphere and water vapor entering from the troposphere are both responsible for future changes in mesospheric water vapor and thus PMC.

54 ENVIRONMENTAL SCIENCES↗

WACCM6 Projections of Polar Mesospheric Cloud Abundance Over the 21st Century

Polar mesospheric clouds (PMC), or noctilucent clouds, can be observed over high latitudes with the naked eye from the ground or from space near the summer solstice. PMC are considered a direct and sensitive indicator of climate change and have been reported to appear more frequently in recent decades. How PMC will change in the future under the influence of natural variability and anthropogenic forcing is uncertain. In this study, we utilize model output from the Whole Atmosphere Community Climate Model under several shared socioeconomic pathway (SSP) scenarios and input the water vapor, temperature, and pressure information into a 0-d PMC model to project the trend and variation of PMC over the 21st century, and their relationship to future changes of temperature, water vapor, and the solar cycle. The 0-d model calculations indicate that PMC ice water content (IWC) will increase and PMC will extend to lower latitudes under high SSP scenarios. Under these scenarios, more mesospheric water vapor leads to an increased IWC of PMC over the polar region, and colder mesopause temperature leads to more PMC over the mid-latitudes. There is a significant anti-correlation between the solar cycle and PMC IWC over the 21st century, but the anti-correlation is not always significant on the decadal scale. Finally, methane oxidation in the stratosphere and water vapor entering from the troposphere are both responsible for future changes in mesospheric water vapor and thus PMC.

Polar Mesospheric Clouds↗