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The dust aerosols are a major type of aerosol over the Tibetan Plateau (TP) and influence climate at local to regional scales through their effects on thermal radiation and snow-albedo feedback. Ba...

This study investigates anthropogenic aerosol effects on East Asian winter monsoon (EAWM) with Community Atmospheric Model version 5. In winter, the anthropogenic aerosol optical depth is the largest over southern East Asia and adjacent oceans. The associated EAWM change, however, is the most significant in northern East Asia, which is characterized by a significant surface cooling in northern East Asia and an acceleration of the jet stream around 40°N, indicating an intensification of the EAWM northern mode. Such an intensification is attributed to anthropogenic black carbon (BC) induced Tibetan Plateau (TP) warming. The BC is mostly transported from northern South Asia by wintertime westerly and southwesterly, and then deposited on snow, giving rise to a reduction of surface albedo and an increase of surface air temperature via the snow-albedo feedback. The TP warming increases meridional temperature gradient and lower-tropospheric baroclinicity over northern East Asia, leading to the jet stream acceleration around 40°N and the westward shift of East Asian major trough via the transient eddy-mean flow feedback. Such upper-tropospheric pattern favors more cold air outbreak, leading to a large surface cooling in northern East Asia. In southern East Asia, the effect of non-absorbing aerosols is dominant. The solar flux at surface is significantly reduced directly by scattering of non-absorbing aerosols, and indirectly by intensification of short wave cloud forcing. Accordingly, the surface air temperature in southern East Asia is reduced. The precipitation is also significantly reduced in South China and Indo-China Peninsula, where the aerosol indirect effect is the largest.

Occurrence frequency and dynamical conditions of ice supersaturation (ISS, where relative humidity with respect to ice (RHi) greater than 100%) are examined in the upper troposphere around convective activity. Comparisons are conducted between in situ airborne observations and the Weather Research and Forecasting model simulations using four double-moment microphysical schemes at temperatures less than or or equal to -40degdegC. All four schemes capture both clear-sky and in-cloud ISS conditions. However, the clear-sky (in-cloud) ISS conditions are completely (significantly) limited to the RHi thresholds of the Cooper parameterization. In all of the simulations, ISS occurrence frequencies are higher by approximately 3-4 orders of magnitude at higher updraft speeds (greater than 1 m s(exp -1) than those at the lower updraft speeds when ice water content (IWC) greater than 0.01 gm(exp -3), while observations show smaller differences up to approximately 1-2 orders of magnitude. The simulated ISS also occurs less frequently at weaker updrafts and downdrafts than observed. These results indicate that the simulations have a greater dependence on stronger updrafts to maintain/generate ISS at higher IWC. At lower IWC (less than or equal or 0.01 gm(exp -3), simulations unexpectedly show lower ISS frequencies at stronger updrafts. Overall, the Thompson aerosol-aware scheme has the closest magnitudes and frequencies of ISS greater than 20% to the observations, and the modified Morrison has the closest correlations between ISS frequencies and vertical velocity at higher IWC and number density. The Cooper parameterization often generates excessive ice crystals and therefore suppresses the frequency and magnitude of ISS, indicating that it should be initiated at higher ISS (e.g.,lees than or equal to 25%).

The ability of 11 models in simulating the aerosol vertical distribution from regional to global scales, as part of the second phase of the AeroCom model intercomparison initiative (AeroCom II), is assessed and compared to results of the first phase. The evaluation is performed using a global monthly gridded data set of aerosol extinction profiles built for this purpose from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) Layer Product 3.01. Results over 12 subcontinental regions show that five models improved, whereas three degraded in reproducing the interregional variability in Zα0–6 km, the mean extinction height diagnostic, as computed from the CALIOP aerosol profiles over the 0–6 km altitude range for each studied region and season. While the models' performance remains highly variable, the simulation of the timing of the Zα0–6 km peak season has also improved for all but two models from AeroCom Phase I to Phase II. The biases in Zα0–6 km are smaller in all regions except Central Atlantic, East Asia, and North and South Africa. Most of the models now underestimate Zα0–6 km over land, notably in the dust and biomass burning regions in Asia and Africa. At global scale, the AeroCom II models better reproduce the Zα0–6 km latitudinal variability over ocean than over land. Hypotheses for the performance and evolution of the individual models and for the intermodel diversity are discussed. We also provide an analysis of the CALIOP limitations and uncertainties contributing to the differences between the simulations and observations.

In this study, we adopt a parametric sensitivity analysis framework that integrates the quasi-Monte Carlo parameter sampling approach and a surrogate model to examine aerosol effects on the East Asian Monsoon climate simulated in the Community Atmosphere Model (CAM5). A total number of 256 CAM5 simulations are conducted to quantify the model responses to the uncertain parameters associated with cloud microphysics parameterizations and aerosol (e.g., sulfate, black carbon (BC), and dust) emission factors and their interactions. Results show that the interaction terms among parameters are important for quantifying the sensitivity of fields of interest, especially precipitation, to the parameters. The relative importance of cloud microphysics parameters and emission factors (strength) depends on evaluation metrics or the model fields we focused on, and the presence of uncertainty in cloud microphysics imposes an additional challenge in quantifying the impact of aerosols on cloud and climate. Due to their different optical and microphysical properties and spatial distributions, sulfate, BC, and dust aerosols have very different impacts on East Asian Monsoon through aerosol-cloud-radiation interactions. The climatic effects of aerosol do not always have a monotonic response to the change of emission factors. The spatial patterns of both sign and magnitude of aerosol-induced changes in radiative fluxes, cloud, and precipitation could be different, depending on the aerosol types, when parameters are sampled in different ranges of values. We also identify the different cloud microphysical parameters that show the most significant impact on climatic effect induced by sulfate, BC, and dust, respectively, in East Asia.

Changes in the ice nucleation characteristics of atmospherically relevant mineral dust particles caused by a coating of nitric acid are not well understood. Further, the atmospheric implications of dust coatings on ice-cloud properties under different assumptions of primary ice nucleation mechanisms are unknown. We investigated the ice nucleation ability of Arizona Test Dust, illite, K-feldspar, and quartz as a function of temperature (−25°C to −30°C) and relative humidity with respect to water (75% to 110%). The particles (bare or nitric acid coated) were size selected at 250 nm, and the fraction of particles nucleating ice at various temperature and saturation conditions was determined. All of the dust species nucleated ice at subsaturated conditions, although the coated particles (except quartz) showed a reduction in their ice nucleation ability relative to bare particles. However, at supersaturated conditions, bare and coated particles had nearly equivalent ice nucleation characteristics. The results of a single-column model showed that simulated ice crystal number concentrations are mostly dependent upon the coated particle fraction, primary ice nucleation mechanisms, and competition among ice nucleation mechanisms to nucleate ice. In general, coatings were observed to modify ice-cloud properties, and the complexity of ice-cloud and mixed-phase-cloud evolution when different primary ice nucleation mechanisms compete for fixed water vapor budgets was supported.

Central Asian droughts have drastically and significantly affected agriculture and water resource management in these arid and semiarid areas. Based on tree ring δ18O from native, dominant Schrenk spruce (Picea schrenkiana Fisch. et Mey.), we developed a 300 year (1710–2010) standard precipitation-evaporation index (SPEI) reconstruction from January to August for China's western Tianshan Mountains. The regression model explained 37.6% of the variation in the SPEI reconstruction during the calibration period from 1950 to 2010. Comparison with previous drought reconstructions confirmed the robustness of our reconstruction. The 20th century has been a relatively wet period during the past 300 years. The SPEI showed quasi 2, 5, and 10 year cycles. Several pluvials and droughts with covariability over large areas were revealed clearly in the reconstruction. The two longest pluvials (lasting for 12 years), separated by 50 years, appeared in the 1900s and the 1960s. The most severe drought occurred from 1739 to 1761 and from 1886 to 1911 was the wettest period since 1710. Compared to previous investigations of hydroclimatic changes in the western Tianshan Mountains, our reconstruction revealed more low-frequency variability and indicated that climate in the western Tianshan Mountains shifted from dry to wet in 1886. This regime shift was generally consistent with other moisture reconstructions for the northeastern Tibetan Plateau and northern Pakistan and may have resulted from a strengthened westerly circulation. The opposite hydrological trends in the western Tianshan Mountains and southeastern Tibetan Plateau reveal a substantial influence of strengthened westerlies and weakening of the Indian summer monsoon.

Secondary organic aerosols (SOA) are large contributors to fine-particle loadings and radiative forcing but are often represented crudely in global models. We have implemented three new detailed SOA treatments within the Community Atmosphere Model version 5 (CAM5) that allow us to compare the semivolatile versus nonvolatile SOA treatments (based on some of the latest experimental findings) and to investigate the effects of gas-phase fragmentation reactions. The new treatments also track SOA from biomass burning and biofuel, fossil fuel, and biogenic sources. For semivolatile SOA treatments, fragmentation reactions decrease the simulated annual global SOA burden from 7.5 Tg to 1.8 Tg. For the nonvolatile SOA treatment with fragmentation, the burden is 3.1 Tg. Larger differences between nonvolatile and semivolatile SOA (up to a factor of 5) exist in areas of continental outflow over the oceans. According to comparisons with observations from global surface Aerosol Mass Spectrometer measurements and the U.S. Interagency Monitoring of Protected Visual Environments (IMPROVE) network measurements, the FragNVSOA treatment, which treats SOA as nonvolatile and includes gas-phase fragmentation reactions, agrees best at rural locations. Urban SOA is underpredicted, but this may be due to the coarse model resolution. All three revised treatments show much better agreement with aircraft measurements of organic aerosols (OA) over the North American Arctic and sub-Arctic in spring and summer, compared to the standard CAM5 formulation. This is mainly due to the oxidation of SOA precursor gases from biomass burning, not included in standard CAM5, and long-range transport of biomass burning OA at high altitudes. The revised model configurations that include fragmentation (both semivolatile and nonvolatile SOA) show much better agreement with MODerate resolution Imaging Spectrometers (MODIS) aerosol optical depth data over regions dominated by biomass burning during the summer compared to standard CAM5, and predict biomass burning and biofuel as the largest global source of OA, followed by biogenic and fossil fuel sources. The large contribution of biomass burning OA in the revised treatments is supported by these measurements, but the emissions and aging of SOA precursors and POA are uncertain, and need further investigation. The nonvolatile and semivolatile configurations with fragmentation predict the direct radiative forcing of SOA as −0.5 W m−2 and −0.26 W m−2 respectively, at top of the atmosphere, which are higher than previously estimated by most models, but in reasonable agreement with a recent constrained modeling study. This study highlights the importance of improving process-level representation of SOA in global models.

We present the adjoint of a cirrus formation parameterization that computes the sensitivity of ice crystal number concentration to updraft velocity, aerosol, and ice deposition coefficient. The adjoint is driven by simulations from the National Center for Atmospheric Research Community Atmosphere Model version 5.1 CAM 5.1 to understand the sensitivity of formed ice crystal number concentration to 13 variables and quantify which contribute to its variability. Sensitivities of formed ice crystal number concentration to updraft velocity, sulfate number, and is sufficient but sulfate number concentration is low, indicating a sulfate-limited regime. Outside of the tropics, competition between homogeneous and heterogeneous nucleation may shift annually averaged sensitivities to higher magnitudes, when infrequent strong updrafts shift crystal production away from purely heterogeneous nucleation. Outside the tropics, updraft velocity is responsible for approximately 52.70% of the ice crystal number variability. In the tropics, sulfate number concentration and updraft jointly control variability in formed crystal number concentration. Insoluble aerosol species play a secondary, but still important, role in influencing the variability in crystal concentrations, with coarse-mode dust being the largest contributor at nearly 50% in certain regions. On a global scale, more than 95% of the temporal variability in crystal number concentration can be described by temperature, updraft velocity, sulfate number, and coarse-mode dust number concentration.

The reliability of climate simulations and projections, particularly in the regions with complex terrains, is greatly limited by the model resolution. In this study we evaluate the variable-resolution Community Earth System Model (VR-CESM) with a high-resolution (0.125°) refinement over the Rocky Mountain region. The VR-CESM results are compared with observations, as well as CESM simulation at a quasi-uniform 1° resolution (UNIF) and Canadian Regional Climate Model version 5 (CRCM5) simulation at a 0.11° resolution. We find that VR-CESM is effective at capturing the observed spatial patterns of temperature, precipitation, and snowpack in the Rocky Mountains with the performance comparable to CRCM5, while UNIF is unable to do so. VR-CESM and CRCM5 simulate better the seasonal variations of precipitation than UNIF, although VR-CESM still overestimates winter precipitation whereas CRCM5 and UNIF underestimate it. All simulations distribute more winter precipitation along the windward (west) flanks of mountain ridges with the greatest overestimation in VR-CESM. VR-CESM simulates much greater snow water equivalent peaks than CRCM5 and UNIF, although the peaks are still 10–40% less than observations. Moreover, the frequency of heavy precipitation events (daily precipitation ≥ 25 mm) in VR-CESM and CRCM5 is comparable to observations, whereas the same events in UNIF are an order of magnitude less frequent. In addition, VR-CESM captures the observed occurrence frequency and seasonal variation of rain-on-snow days and performs better than UNIF and CRCM5. These results demonstrate the VR-CESM's capability in regional climate modeling over the mountainous regions and its promising applications for climate change studies.

Mixed-phase clouds (clouds that consist of both cloud droplets and ice crystals) are frequently present in the Earth’s atmosphere and influence the Earth’s energy budget through their radiative properties, which are highly dependent on the cloud water phase. In this study, the phase partitioning of cloud water is compared among six global climate models (GCMs) and with Cloud and Aerosol Lidar with Orthogonal Polarization retrievals. It is found that the GCMs predict vastly different distributions of cloud phase for a given temperature, and none of them are capable of reproducing the spatial distribution or magnitude of the observed phase partitioning. While some GCMs produced liquid water paths comparable to satellite observations, they all failed to preserve sufficient liquid water at mixed-phase cloud temperatures. Our results suggest that validating GCMs using only the vertically integrated water contents could lead to amplified differences in cloud radiative feedback. The sensitivity of the simulated cloud phase in GCMs to the choice of heterogeneous ice nucleation parameterization is also investigated. The response to a change in ice nucleation is quite different for each GCM, and the implementation of the same ice nucleation parameterization in all models does not reduce the spread in simulated phase amongmore » GCMs. The results suggest that processes subsequent to ice nucleation are at least as important in determining phase and should be the focus of future studies aimed at understanding and reducing differences among the models.« less

Single-column models (SCM) are useful test beds for investigating the parameterization schemes of numerical weather prediction and climate models. The usefulness of SCM simulations are limited, however, by the accuracy of the best estimate large-scale observations prescribed. Errors estimating the observations will result in uncertainty in modeled simulations. One method to address the modeled uncertainty is to simulate an ensemble where the ensemble members span observational uncertainty. This study first derives an ensemble of large-scale data for the Tropical Warm Pool International Cloud Experiment (TWP-ICE) based on an estimate of a possible source of error in the best estimate product. These data are then used to carry out simulations with 11 SCM and two cloud-resolving models (CRM). Best estimate simulations are also performed. All models show that moisture-related variables are close to observations and there are limited differences between the best estimate and ensemble mean values. The models, however, show different sensitivities to changes in the forcing particularly when weakly forced. The ensemble simulations highlight important differences in the surface evaporation term of the moisture budget between the SCM and CRM. Differences are also apparent between the models in the ensemble mean vertical structure of cloud variables, while for each model, cloud properties are relatively insensitive to forcing. The ensemble is further used to investigate cloud variables and precipitation and identifies differences between CRM and SCM particularly for relationships involving ice. This study highlights the additional analysis that can be performed using ensemble simulations and hence enables a more complete model investigation compared to using the more traditional single best estimate simulation only.

[1] Current climate models generally underpredict the surface concentration of black carbon (BC) in the Arctic due to the uncertainties associated with emissions, transport, and removal. This bias is also present in the Community Atmosphere Model version 5.1 (CAM5). In this study, we investigate the uncertainty of Arctic BC due to transport processes simulated by CAM5 by configuring the model to run in an “off-line mode” in which the large-scale circulation features are prescribed. We compare the simulated BC transport when the off-line model is driven by the meteorology predicted by the standard free-running CAM5 with simulations where the meteorology is constrained to agree with reanalysis products. Some circulation biases are apparent: the free-running CAM5 produces about 50% less transient eddy transport of BC than the reanalysis-driven simulations, which may be attributed to the coarse model resolution insufficient to represent eddies. Our analysis shows that the free-running CAM5 reasonably captures the essence of the Arctic Oscillation (AO), but some discernable differences in the spatial pattern of the AO between the free-running CAM5 and the reanalysis-driven simulations result in significantly different AO modulation of BC transport over northeast Asia and eastern Europe. Nevertheless, we find that the overall climatological circulation patterns simulated by the free-running CAM5 generally resemble those from the reanalysis products, and BC transport is very similar in both simulation sets. Therefore, the simulated circulation features regulating the long-range BC transport are unlikely the most important cause of the large underprediction of surface BC concentration in the Arctic.

In this study, we applied an uncertainty quantification (UQ) technique to improve convective precipitation in the global climate model, the Community Atmosphere Model version 5 (CAM5), in which the convective and stratiform precipitation partitioning is very different from observational estimates. We examined the sensitivity of precipitation and circulation to several key parameters in the Zhang-McFarlane deep convection scheme in CAM5, using a stochastic importance-sampling algorithm that can progressively converge to optimal parameter values. The impact of improved deep convection on the global circulation and climate was subsequently evaluated. Our results show that the simulated convective precipitation is most sensitive to the parameters of the convective available potential energy consumption time scale, parcel fractional mass entrainment rate, and maximum downdraft mass flux fraction. Using the optimal parameters constrained by the observed Tropical Rainfall Measuring Mission, convective precipitation improves the simulation of convective to stratiform precipitation ratio and rain-rate spectrum remarkably. When convection is suppressed, precipitation tends to be more confined to the regions with strong atmospheric convergence. As the optimal parameters are used, positive impacts on some aspects of the atmospheric circulation and climate, including reduction of the double Intertropical Convergence Zone, improved East Asian monsoon precipitation, and improved annual cyclesmore » of the cross-equatorial jets, are found as a result of the vertical and horizontal redistribution of latent heat release from the revised parameterization. Positive impacts of the optimal parameters derived from the 2 simulations are found to transfer to the 1 simulations to some extent.« less

The production of sulfuric acid vapor and new particle formation are studied over the northwest Atlantic for two synoptic cases: a wet case in April with a large amount of cloud and precipitation in the simulation domain and a relatively dry one in March. The Fifth-Generation Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model (MM5) is utilized coupled on-line with a simple sulfur chemistry mechanism. Our numerical simulations show that there are three regions where significant binary homogeneous nucleation occurs. One region is in convective outflow where high anthropogenic SO 2 concentration transported upward and low air temperature in the free troposphere (FT) favor the binary homogeneous nucleation of sulfuric acid gas and water vapor. The second region is near the top of marine boundary layer (MBL) clouds. The third region is in the clear FT at 500-600 hPa. In the three regions, significant nucleation events are all connected with relative humidity (RH) higher than 60%. For the northwest Atlantic we found that homogeneous nucleation generally occurs from the late morning through the afternoon on the northwest side of our simulation domain where anthropogenic SO 2 concentration is high enough to produce sufficient sulfuric acid gas through the oxidation by OH radical. Significant nucleation does not necessarily happen in regions with very low preexisting particle surface area in our simulated cases. Our simulated total aerosol number concentrations in regions with significant new particle formation are generally consistent with field measurements. Nucleation rates are enhanced by NH 3 especially in the MBL. Sensitivity tests show that a grid of 10 km (and time step of 30 s) yielded significantly higher nucleation as compared with a grid size of 30 km (and time step of 90 s). The latter grid may be too coarse to resolve the concentration gradients, which likely strongly impact the highly nonlinear homogeneous nucleation system.

This study investigates the seasonality in anthropogenic aerosol optical depth (AOD) distributions and their effects on clouds and precipitation in East Asia with the Community Atmospheric Model version 5. The differences between the model experiments with and without anthropogenic emissions exhibit a northward shift of the maximal AOD change in East Asia from March to July and then a southward withdrawal from September to November, which are induced by East Asian monsoon circulation. Associated with the shift, the direct and semi-direct effects of the anthropogenic aerosols are the most pronounced in spring and summer, with a maximum center in North China during summer and a secondary center in South China during spring. The cloud liquid water path and shortwave cloud forcing changes, however, are the weakest in North China during summer. The indirect effect is the strongest in South China during spring, which is related to the large amount of middle-low level clouds in cold seasons in East China. A positive feedback between aerosol induced surface cooling and low-level cloud increase is identified in East China, which acts to enforce the aerosol indirect effect in spring. Accordingly, the climate response to the anthropogenic aerosols is also characterized by a northward shift of reduced precipitation from spring to summer, leading to a spring drought in South China and a summer drought in North China. The spring drought is attributed to both direct and indirect effects of the anthropogenic aerosols, while the summer drought is primarily determined by the aerosols' direct effect.

Based upon the measurements of vertical profiles of gaseous SO2, H2,O2, O3, and meteorological parameters from aircraft and of the aerosol chemical composition and gaseous NH3, HNO3, and SO2 at the surface in southeastern Germany (Melpitz) during the Sanitation of the Atmosphere (SANA) 2 campaign, realistic modeling of cloud, droplet nucleation and in-cloud sulfate production was performed with an explicit microphysical cloud model with size-resolved chemistry and cloud top entrainment. For the fair weather cumulus observed during the measurements, the calculated cloud droplet number concentrations could be as high as 2000 cm(- 3) (and precloud aerosol sulfate up to 9.1 my g m(-3)), indicating strong sulfur pollution at Melpitz during the campaign. The in-cloud sulfate production is within 1.5-5.0 my g m(-3) depending on the initial gaseous NH3 concentration in the parcel. This result shows the necessity of gaseous NH3 vertical profile measurements. Entrainment can reduce the cloud dro plet number concentration and cause the distribution of in-cloud produced sulfate to shift toward larger particle sizes. Under the cases we studied, we do not find a significant effect of cloud top gaseous H2O2 entrainment on the in-cloud sulfate production. For the adiabatic cases the departure of bulk water H2O2 from the Henry's law equilibrium is very small. When entrainment included, however, bulk water H2O2 concentrations could be clearly less than the equilibrium values, and the deficiencies are higher (>20 per cent) for droplets larger than 10 mu m radius. Our results suggest that entrainment could be one of the important factors to account for the measured H2O2 deficiency in cloud water.

Several different ice nucleation parameterizations in two different General Circulation Models (GCMs) are used to understand the effects of ice nucleation on the mean climate state, and the Aerosol Indirect Effects (AIE) of cirrus clouds on climate. Simulations have a range of ice microphysical states that are consistent with the spread of observations, but many simulations have higher present-day ice crystal number concentrations than in-situ observations. These different states result from different parameterizations of ice cloud nucleation processes, and feature different balances of homogeneous and heterogeneous nucleation. Black carbon aerosols have a small (0.06 Wm(exp-2) and not statistically significant AIE when included as ice nuclei, for nucleation efficiencies within the range of laboratory measurements. Indirect effects of anthropogenic aerosols on cirrus clouds occur as a consequence of increasing anthropogenic sulfur emissions with different mechanisms important in different models. In one model this is due to increases in homogeneous nucleation fraction, and in the other due to increases in heterogeneous nucleation with coated dust. The magnitude of the effect is the same however. The resulting ice AIE does not seem strongly dependent on the balance between homogeneous and heterogeneous ice nucleation. Regional effects can reach several Wm2. Indirect effects are slightly larger for those states with less homogeneous nucleation and lower ice number concentration in the base state. The total ice AIE is estimated at 0.27 +/- 0.10 Wm(exp-2) (1 sigma uncertainty). This represents a 20% offset of the simulated total shortwave AIE for ice and liquid clouds of 1.6 Wm(sup-2).

Accurately representing aerosol-cloud interactions in global climate models is challenging. As parameterizations evolve, it is important to evaluate their performance with appropriate use of observations. In this investigation we compare aerosols, clouds, and their interactions in three global climate models (Geophysical Fluid Dynamics Laboratory-Atmosphere Model 3 (AM3), National Center for Atmospheric Research-Community Atmosphere Model 5 (CAM5), and Goddard Institute for Space Studies-ModelE2) to Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations. Modeled cloud properties are diagnosed using a MODIS simulator. Cloud droplet number concentrations (N) are computed identically from satellite-simulated and MODIS-observed values of liquid cloud optical depth and droplet effective radius. We find that aerosol optical depth (τa) simulated by models is similar to observations in many regions around the globe. For N, AM3 and CAM5 capture the observed spatial pattern of higher values in coastal marine stratocumulus versus remote ocean regions, though modeled values, in general, are higher than observed. Aerosol-cloud interactions were computed as the sensitivity of ln(N) to ln(τa) for coastal marine liquid clouds near South Africa (SAF) and Southeast Asia where τa varies in time. AM3 and CAM5 are more sensitive than observations, while the sensitivity for ModelE2 is statistically insignificant. This widely used sensitivity could be subject to misinterpretation due to the confounding influence of meteorology on both aerosols and clouds. A simple framework for assessing the sensitivity of ln(N) to ln(τa) at constant meteorology illustrates that observed sensitivity can change from positive to statistically insignificant when including the confounding influence of relative humidity. Satellite-simulated versus standard model values of N are compared; for CAM5 in SAF, standard model values are significantly lower than satellite-simulated values with a bias of 83 cm−3.

[1] Different schemes have been used to represent the vertical coherence of clouds for radiation and cloud microphysics in general circulation models and for photolysis in photochemical transport models. Here, we examine the maximum-random overlap scheme, the random overlap scheme, and a linear scheme (linear scaling of the cloud optical depth in a grid box with cloud fraction) and evaluate their effects on averaged photolysis frequencies and OH concentrations in a global photochemical model. Photolysis frequencies are increased in the upper tropical troposphere and decreased in the lower troposphere if clouds are assumed to be randomly overlapped or if a linear assumption is followed rather than the maximum-random overlap assumption. The underestimate is of order 50% and 20–30% at the surface in the tropics and over some continental midlatitude regions for the linear and the random assumptions, respectively, relative to the maximum-random assumption. The global average CH4 + OH reaction rate-weighted OH concentration calculated with the random overlap assumption is within a few percent of that calculated with the maximum-random overlap assumption but is underestimated with the nonphysically based linear assumption, by 4 to 6% relative to the maximum-random overlap assumption and by 6 to 7% relative to the random overlap assumption. An underestimate of rate-weighted OH concentration implies that the tropospheric lifetime for CH4 and other greenhouse gases that react with OH is too long in models that use this scheme.

[1] The Second Aerosol Characterization Experiment (ACE-2) data set along with ECMWF reanalysis meteorological fields provided the basis for the single column model (SCM) simulations, performed as part of the PACE (Parameterization of the Aerosol Indirect Climatic Effect) project. Six different SCMs were used to simulate ACE-2 case studies of clean and polluted cloudy boundary layers, with the objective being to identify limitations of the aerosol/cloud/radiation interaction schemes within the range of uncertainty in in situ, reanalysis and satellite retrieved data. The exercise proceeds in three steps. First, SCMs are configured with the same fine vertical resolution as the ACE-2 in situ data base to evaluate the numerical schemes for prediction of aerosol activation, radiative transfer and precipitation formation. Second, the same test is performed at the coarser vertical resolution of GCMs to evaluate its impact on the performance of the parameterizations. Finally, SCMs are run for a 24–48 hr period to examine predictions of boundary layer clouds when initialized with large-scale meteorological fields. Several schemes were tested for the prediction of cloud droplet number concentration (N). Physically based activation schemes using vertical velocity show noticeable discrepancies compared to empirical schemes due to biases in the diagnosed cloud base vertical velocity. Prognostic schemes exhibit a larger variability than the diagnostic ones, due to a coupling between aerosol activation and drizzle scavenging in the calculation of N. When SCMs are initialized at a fine vertical resolution with locally observed vertical profiles of liquid water, predicted optical properties are comparable to observations. Predictions however degrade at coarser vertical resolution and are more sensitive to the mean liquid water path than to its spatial heterogeneity. Predicted precipitation fluxes are severely underestimated and improve when accounting for sub-grid liquid water variability. Results from the 24–48 hr runs suggest that most models have problems in simulating boundary layer cloud morphology, since the large-scale initialization fields do not accurately reproduce observed meteorological conditions. As a result, models significantly overestimate optical properties. Improved cloud morphologies were obtained for models with subgrid inversions and subgrid cloud thickness schemes. This may be a result of representing subgrid scale effects though we do not rule out the possibility that better large-forcing data may also improve cloud morphology predictions.