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Recent advances in ray tracing hardware bring real-time path tracing into reach, and ray traced soft shadows, glossy reflections, and diffuse global illumination are now common features in games. Nonetheless, ray budgets are still limited. This results in undersampling, which manifests as aliasing and noise. Prior work addresses these issues separately. While temporal supersampling methods based on neural networks have gained a wide use in modern games due to their better robustness, neural denoising remains challenging because of its higher computational cost. We introduce a novel neural network architecture for real-time rendering that combines supersampling and denoising, thus lowering the cost compared to two separate networks. This is achieved by sharing a single low-precision feature extractor with multiple higher-precision filter stages. To reduce cost further, our network takes low-resolution inputs and reconstructs a high-resolution denoised supersampled output. Our technique produces temporally stable high-fidelity results that significantly outperform state-of-the-art real-time statistical or analytical denoisers combined with TAA or neural upsampling to the target resolution.

As the third most important greenhouse gas (GHG) after carbon dioxide (CO2) and methane (CH4), tropospheric ozone (O3) is also an air pollutant causing damage to human health and ecosystems. This study brings together recent research on observations and modeling of tropospheric O3 in the Arctic, a rapidly warming and sensitive environment. At different locations in the Arctic, the observed surface O3 seasonal cycles are quite different. Coastal Arctic locations, for example, have a minimum in the springtime due to O3 depletion events resulting from surface bromine chemistry. In contrast, other Arctic locations have a maximum in the spring. The 12 state-of-the-art models used in this study lack the surface halogen chemistry needed to simulate coastal Arctic surface O3 depletion in the springtime; however, the multi-model median (MMM) has accurate seasonal cycles at non-coastal Arctic locations. There is a large amount of variability among models, which has been previously reported, and we show that there continues to be no convergence among models or improved accuracy in simulating tropospheric O3 and its precursor species. The MMM underestimates Arctic surface O3 by 5 % to 15 % depending on the location. The vertical distribution of tropospheric O3 is studied from recent ozonesonde measurements and the models. The models are highly variable, simulating free-tropospheric O3 within a range of ±50 % depending on the model and the altitude. The MMM performs best, within ±8 % for most locations and seasons. However, nearly all models overestimate O3 near the tropopause (∼300 hPa or ∼8 km), likely due to ongoing issues with underestimating the altitude of the tropopause and excessive downward transport of stratospheric O3 at high latitudes. For example, the MMM is biased high by about 20 % at Eureka. Observed and simulated O3 precursors (CO, NOx, and reservoir PAN) are evaluated throughout the troposphere. Models underestimate wintertime CO everywhere, likely due to a combination of underestimating CO emissions and possibly overestimating OH. Throughout the vertical profile (compared to aircraft measurements), the MMM underestimates both CO and NOx but overestimates PAN. Perhaps as a result of competing deficiencies, the MMM O3 matches the observed O3 reasonably well. Our findings suggest that despite model updates over the last decade, model results are as highly variable as ever and have not increased in accuracy for representing Arctic tropospheric O3.

As the third most important greenhouse gas (GHG) after CO2 and methane, tropospheric ozone (O3) is also an air pollutant causing damage to human health and ecosystems. This study brings together recent research on observations and modeling of tropospheric O3 in the Arctic, a rapidly warming and sensitive environment. At different locations in the Arctic, the observed surface O3 seasonal cycles are quite different. Coastal Arctic locations, for example, have a minimum in the springtime due to O3 depletion events resulting from surface bromine chemistry. In contrast, other Arctic locations have a maximum in the spring. The 12 state-of-the-art models used in this study lack the surface halogen chemistry needed to simulate coastal Arctic surface O3 depletion in the springtime, however, the multi-model median (MMM) has accurate seasonal cycles at non-coastal Arctic locations. There is a large amount of variability among models, which has been reported previously, and we show that there continues to be no convergence among models, nor improved accuracy in simulating tropospheric O3 and its precursor species. The MMM underestimates Arctic surface O3 by 5 % to 15 % depending on the location. The vertical distribution of tropospheric O3 is studied from recent ozonesonde measurements and the models. The models are highly variable, simulating free-tropospheric O3 within a range of +/- 50 % depending on the model and the altitude. The MMM performs best, within +/- 8 % at most locations and seasons. However, nearly all models overestimate O3 near the tropopause (~300 hPa or ~8 km), likely due to ongoing issues with underestimating the altitude of the tropopause and excessive downward transport of stratospheric O3 at high latitudes. For example, the MMM is biased high by about 20 % at Eureka. Observed and simulated O3 precursors (CO, NOx and reservoir PAN) are evaluated throughout the troposphere. Models underestimate wintertime CO everywhere, likely due to a combination of underestimating CO emissions and possibly overestimating OH. Throughout the vertical profile (compared to aircraft measurements), the MMM underestimates both CO and NOx but overestimates PAN. Perhaps as a result of competing deficiencies, the MMM O3 matches the observed O3 reasonably well. Our findings suggest that despite model updates over the last decade , model results are as highly variable as ever, and have not increased in accuracy for representing Arctic tropospheric.

Neural networks are often quantized to use reduced-precision arithmetic, as it greatly improves their storage and computational costs. This approach is commonly used in image classification and natural language processing applications. However, using a quantized network for the reconstruction of HDR images can lead to a significant loss in image quality. In this paper, we introduce QW-Net , a neural network for image reconstruction, in which close to 95% of the computations can be implemented with 4-bit integers. This is achieved using a combination of two U-shaped networks that are specialized for different tasks, a feature extraction network based on the U-Net architecture, coupled to a filtering network that reconstructs the output image. The feature extraction network has more computational complexity but is more resilient to quantization errors. The filtering network, on the other hand, has significantly fewer computations but requires higher precision. Our network recurrently warps and accumulates previous frames using motion vectors, producing temporally stable results with significantly better quality than TAA, a widely used technique in current games.

The Arctic atmosphere is warming rapidly and its relatively pristine environment is sensitive to the long-range transport of atmospheric pollutants. While carbon dioxide is the main cause for global warming, short-lived climate forcers (SLCFs) such as methane, ozone, and particles also play a role in Arctic climate on near-term time scales. Atmospheric modelling is critical for understanding the abundance and distribution of SLCFs throughout the Arctic atmosphere, and is used as a tool towards determining SLCF impacts on climate and health in the present and in future emissions scenarios. In this study, we evaluate 18 state-of-the-art atmospheric and Earth system models, assessing their representation of Arctic and Northern Hemisphere atmospheric SLCF distributions, considering a wide range of different chemical species (methane, tropospheric ozone and its precursors, black carbon, sulfate, organic aerosol, and particulate matter) and multiple observational datasets. Model simulations over four years (2008–2009 and 2014–2015) conducted for the 2021 Arctic Monitoring and Assessment Programme (AMAP) SLCF assessment report are thoroughly evaluated against satellite, ground, ship and aircraft-based observations. The results show a large range in model performance, with no one particular model or model type performing well for all regions and all SLCF species. The multi-model mean was able to represent the general features of SLCFs in the Arctic, though vertical mixing, long-range transport, deposition, and wildfire emissions remain highly uncertain processes. These need better representation within atmospheric models to improve their simulation of SLCFs in the Arctic environment.

Given the vast expanse of oceans on our planet, marine aerosols (and sea salt in particular) play an important role in the climate system via multitude of direct and indirect effects. The efficacy of their net impact, however, depends strongly on the local meteorological conditions that influence their physical, optical and chemical properties. Understanding the coupling between aerosol properties and meteorological conditions is therefore important. It has been historically difficult to statistically quantify this coupling over larger oceanic areas due to the lack of suitable observations, leading to large uncertainties in the representation of aerosol processes in climate models. Perhaps no other region shows higher uncertainties in the representation of marine aerosols and their effects than the Southern Ocean. During winter the Southern Ocean boundary layer is dominated by sea salt emissions. Here, using 10 years of austral winter period (June, July and August, 2007–2016) space-based aerosol profiling by CALIOP-CALIPSO in combination with meteorological reanalysis data, we investigated the sensitivity of marine aerosol properties over the Southern Ocean (40–65∘ S) to various meteorological parameters, such as vertical relative humidity (RH), surface wind speed and sea surface temperature (SST) in terms of joint histograms. The sensitivity study is done for the climatological conditions and for the enhanced cyclonic and anticyclonic conditions in order to understand the impact of large-scale atmospheric circulation on the aerosol properties. We find a clear demarcation in the 532 nm aerosol backscatter and extinction at RH around 60 %, irrespective of the state of the atmosphere. The backscatter and extinction increase at higher relative humidity as a function of surface wind speed. This is mainly because of the water uptake by the wind-driven sea salt aerosols at high RH near the ocean surface resulting in an increase in size, which is confirmed by the decreased depolarization for the wet aerosols. An increase in aerosol backscatter and extinction is observed during the anticyclonic conditions compared to cyclonic conditions for the higher wind speeds and relative humidity, mainly due to aerosols being confined to the boundary layer, and their proximity to the ocean surface facilitates the growth of the particles. We further find a very weak dependency of aerosol backscatter on SSTs at lower wind speeds. However, when the winds are stronger than about 12 m s−1, the backscattering coefficient generally increases with SST. When aerosol properties are investigated in terms of aerosol verticality and in relation to meteorological parameters, it is seen that the aerosol backscatter values in the free troposphere (pressure hPa) are much lower than in the boundary layer, irrespective of the RH and the three weather states. This indicates that the local emissions from the ocean surface make the dominant contribution to aerosol loads over the Southern Ocean. A clear separation of particulate depolarization is observed in the free and lower troposphere, more prominent in the climatological mean and the cyclonic states. For RH > 60 %, low depolarization values are noticeable in the lower troposphere, which is an indication of the dominance of water-coated and mostly spherical sea salt particles. For RH < 60 %, there are instances when the aerosol depolarization increases in the boundary layer; this is more prominent in the mean and anticyclonic cases, which can be associated with the presence of drier aerosol particles. Based on the joint histograms investigated here, we provide third-degree polynomials to obtain aerosol extinction and backscatter as a function of wind speed and relative humidity. Additionally, backscattering coefficient is also expressed jointly in terms of wind speed and sea surface temperature. Furthermore, depolarization is expressed as a function of relative humidity. These fitting functions would be useful to test and improve the parameterizations of sea salt aerosols in the climate models. We also note some limitations of our study. For example, interpreting the verticality of aerosol properties (especially depolarization) in relation to the meteorological conditions in the free and upper troposphere (pressure hPa) was challenging. Furthermore, we do not see any direct evidence of sudden crystallization (efflorescence), deliquescence or hysteresis effects of the aerosols. Observing such effects will likely require a targeted investigation of individual cases considering tracer transport, rather than the statistical sensitivity study that entails temporally and geographically averaged large data sets.

The transport and distribution of short-lived climate forcers in the Arctic are influenced by the prevailing atmospheric circulation patterns. Understanding the coupling between pollutant distribution and dominant atmospheric circulation types is therefore important, not least to understand the processes governing the local processing of pollutants in the Arctic, but also to test the fidelity of chemistry transport models to simulate the transport from the southerly latitudes. Here, we use a combination of satellite-based and reanalysis datasets spanning over 12 years (2007–2018) and investigate the concentrations of NO2, O3, CO and aerosols and their co-variability during eight different atmospheric circulation types in the spring season (March, April and May) over the Arctic. We carried out a self-organizing map analysis of mean sea level pressure to derive these circulation types. Although almost all pollutants investigated here show statistically significant sensitivity to the circulation types, NO2 exhibits the strongest sensitivity among them. The circulation types with low-pressure systems located over the northeast Atlantic show a clear enhancement of NO2 and aerosol optical depths (AODs) in the European Arctic. The O3 concentrations are, however, decreased. The free tropospheric CO is increased over the Arctic during such events. The circulation types with atmospheric blocking over Greenland and northern Scandinavia show the opposite signal in which the NO2 concentrations are decreased and AODs are smaller than the climatological values. The O3 concentrations are, however, increased, and the free tropospheric CO is decreased during such events. The study provides the most comprehensive assessment so far of the sensitivity of springtime pollutant distribution to the atmospheric circulation types in the Arctic and also provides an observational basis for the evaluation of chemistry transport models.

A realistic representation of snowfall in general circulation models (GCMs) of global climate is important to accurately simulate snow cover, surface albedo, high-latitude precipitation and thus the surface radiation budget. Hence, in this study, we evaluate snowfall in a range of climate models run at two different resolutions by comparing to the latest estimates of snowfall from the CloudSat Cloud Profiling Radar over the northern latitudes. We also evaluate whether the finer-resolution versions of the GCMs simulate the accumulated snowfall better than their coarse-resolution counterparts. As the Arctic Oscillation (AO) is the prominent mode of natural variability in the polar latitudes, the snowfall variability associated with the different phases of the AO is examined in both models and in our observational reference. We report that the statistical distributions of snowfall differ considerably between the models and CloudSat observations. While CloudSat shows an exponential distribution of snowfall, the models show a Gaussian distribution that is heavily positively skewed. As a result, the 10th and 50th percentiles, representing the light and median snowfall, are overestimated by up to factors of 3 and 1.5, respectively, in the models investigated here. The overestimations are strongest during the winter months compared to autumn and spring. The extreme snowfall represented by the 90th percentiles, on the other hand, is positively skewed, underestimating the snowfall estimates by up to a factor of 2 in the models in winter compared to the CloudSat estimates. Though some regional improvements can be seen with increased spatial resolution within a particular model, it is not easy to identify a specific pattern that holds across all models. The characteristic snowfall variability associated with the positive phase of AO over Greenland Sea and central Eurasian Arctic is well captured by the models.

This study evaluates the impact of atmospheric horizontal resolution on the representation of cloud radiative effects (CREs) in an ensemble of global climate model simulations following the protocols of the High Resolution Model Intercomparison Project (HighResMIP). We compare results from four European modelling centres, each of which provides data from “standard”- and “high”-resolution model configurations. Simulated radiative fluxes are compared with observation-based estimates derived from the Clouds and Earth's Radiant Energy System (CERES) dataset. Model CRE biases are evaluated using both conventional statistics (e.g. time and spatial averages) and after conditioning on the phase of two modes of internal climate variability, namely the El Niño–Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO). Simulated top-of-atmosphere (TOA) and surface CREs show large biases over the polar regions, particularly over regions where seasonal sea-ice variability is strongest. Increasing atmospheric resolution does not significantly improve these biases. The spatial structure of the cloud radiative response to ENSO and NAO variability is simulated reasonably well by all model configurations considered in this study. However, it is difficult to identify a systematic impact of atmospheric resolution on the associated CRE errors. Mean absolute CRE errors conditioned on the ENSO phase are relatively large (5–10 W m−2) and show differences between models. We suggest this is a consequence of differences in the parameterization of SW radiative transfer and the treatment of cloud optical properties rather than a result of differences in resolution. In contrast, mean absolute CRE errors conditioned on the NAO phase are generally smaller (0–2 W m−2) and more similar across models. Although the regional details of CRE biases show some sensitivity to atmospheric resolution within a particular model, it is difficult to identify patterns that hold across all models. This apparent insensitivity to increased atmospheric horizontal resolution indicates that physical parameterizations play a dominant role in determining the behaviour of cloud–radiation feedbacks. However, we note that these results are obtained from atmosphere-only simulations and the impact of changes in atmospheric resolution may be different in the presence of coupled climate feedbacks.

Air quality implications of volcanic eruptions have gained increased attention recently in association with the 2010 Icelandic eruption that resulted in the shut-down of European air space. The emission amount, injection height and prevailing weather conditions determine the extent of the impact through the spatio-temporal distribution of pollutants. It is often argued that in the case of a major eruption in Iceland, like Laki in 1783–1784, that pollutants injected high into the atmosphere lead to substantially increased concentrations of sulfur compounds over continental Europe via long-range transport in the jet stream and eventual large-scale subsidence in a high-pressure system. Using state-of-the-art simulations, we show that the air quality impact of Icelandic volcanoes is highly sensitive to the injection height. In particular, it is the infinitesimal injections into the lower half of the troposphere, rather than the substantial injections into the upper troposphere/lower stratosphere that contribute most to increased pollutant concentrations, resulting in atmospheric haze over mainland Europe/Scandinavia. Besides, the persistent high pressure system over continental Europe/Scandinavia traps the pollutants from dispersing, thereby prolonging the haze.

We introduce TempoCave, a novel visualization application for analyzing dynamic brain networks, or connectomes. TempoCave provides a range of functionality to explore metrics related to the activity patterns and modular affiliations of different regions in the brain. These patterns are calculated by processing raw data retrieved functional magnetic resonance imaging (fMRI) scans, which creates a network of weighted edges between each brain region, where the weight indicates how likely these regions are to activate synchronously. In particular, we support the analysis needs of clinical psychologists, who examine these modular affiliations and weighted edges and their temporal dynamics, utilizing them to understand relationships between neurological disorders and brain activity, which could have a significant impact on the way in which patients are diagnosed and treated. We summarize the core functionality of TempoCave, which supports a range of comparative tasks, and runs both in a desktop mode and in an immersive mode. Furthermore, we present a real-world use case that analyzes pre- and post-treatment connectome datasets from 27 subjects in a clinical study investigating the use of cognitive behavior therapy to treat major depression disorder, indicating that TempoCave can provide new insight into the dynamic behavior of the human brain.

Animation studios render 3D scenes using a technique called path tracing which enables them to create high quality photorealistic frames. Path tracing involves shooting 1000’s of rays into a pixel randomly (Monte Carlo) which will then hit the objects in the scene and, based on the reflective property of the object, these rays reflect or refract or get absorbed. The colors returned by these rays are averaged to determine the color of the pixel. This process is repeated for all the pixels. Due to the computational complexity it might take 8–16 hours to render a single frame. We implemented a neural network-based solution to reduce the time it takes to render a frame to less than a second using a generative adversarial network (GAN), once the network is trained. The main idea behind this proposed method is to render the image using a much smaller number of samples per pixel than is normal for path tracing (e.g., 1, 4, or 8 samples instead of, say, 32,000 samples) and then pass the noisy, incompletely rendered image to our network, which is capable of generating a high-quality photorealistic image.

This study evaluates the impact of atmospheric horizontal resolution on the representation of cloud radiative effects (CREs) in an ensemble of global climate model simulations following the protocols of the High Resolution Model Intercomparison Project (HighResMIP). We compare results from four European modelling centres, each of which provides data from "standard" and "high" resolution model configurations. Simulated radiative fluxes are compared with observation-based estimates derived from the Clouds and Earth's Radiant Energy System (CERES) dataset. Model CRE biases are evaluated using both conventional statistics (e.g. time and spatial averages) and after conditioning on the phase of two modes of internal climate variability, namely the El Niño and Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO). Simulated top-of-atmosphere (TOA) and surface CREs show large biases over the polar regions, particularly over regions where seasonal sea-ice variability is strongest. Increasing atmospheric resolution does not significantly improve these biases. The spatial structure of the cloud radiative response to ENSO and NAO variability is simulated reasonably well by all model configurations considered in this study. However, it is difficult to identify a systematic impact of atmospheric resolution on the associated CRE errors. Mean absolute CRE errors conditioned on ENSO phase are relatively large (5–10 W/m2) and show differences between models. We suggest this is a consequence of differences in the parameterization of SW radiative transfer and the treatment of cloud optical properties rather than a result of differences in resolution. In contrast, mean absolute CRE errors conditioned on NAO phase are generally smaller (0–2 W/m2) and more similar across models. Although the regional details of CRE biases show some sensitivity to atmospheric resolution within a particular model, it is difficult to identify patterns that hold across all models. This apparent insensitivity to increased atmospheric horizontal resolution indicates that physical parameterizations play a dominant role in determining the behaviour of cloud-radiation feedbacks. However, we note that these results are obtained from atmosphere-only simulations and the impact of changes in atmospheric resolution may be different in the presence of coupled climate feedbacks.

To reduce uncertainties and hence to obtain a better estimate of aerosol (direct and indirect) radiative forcing, next generation climate models aim for a tighter coupling between chemistry transport models and regional climate models and a better representation of aerosol–cloud interactions. In this study, this coupling is done by first forcing the Rossby Center regional climate model (RCA4) with ERA-Interim lateral boundaries and sea surface temperature (SST) using the standard cloud droplet number concentration (CDNC) formulation (hereafter, referred to as the "stand-alone RCA4 version" or "CTRL" simulation). In the stand-alone RCA4 version, CDNCs are constants distinguishing only between land and ocean surface. The meteorology from this simulation is then used to drive the chemistry transport model, Multiple-scale Atmospheric Transport and Chemistry (MATCH), which is coupled online with the aerosol dynamics model, Sectional Aerosol module for Large Scale Applications (SALSA). CDNC fields obtained from MATCH–SALSA are then fed back into a new RCA4 simulation. In this new simulation (referred to as "MOD" simulation), all parameters remain the same as in the first run except for the CDNCs provided by MATCH–SALSA. Simulations are carried out with this model setup for the period 2005–2012 over Europe, and the differences in cloud microphysical properties and radiative fluxes as a result of local CDNC changes and possible model responses are analysed. Our study shows substantial improvements in cloud microphysical properties with the input of the MATCH–SALSA derived 3-D CDNCs compared to the stand-alone RCA4 version. This model setup improves the spatial, seasonal and vertical distribution of CDNCs with a higher concentration observed over central Europe during boreal summer (JJA) and over eastern Europe and Russia during winter (DJF). Realistic cloud droplet radii (CD radii) values have been simulated with the maxima reaching 13 μm, whereas in the stand-alone version the values reached only 5 μm. A substantial improvement in the distribution of the cloud liquid-water paths (CLWP) was observed when compared to the satellite retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) for the boreal summer months. The median and standard deviation values from the "MOD" simulation are closer to observations than those obtained using the stand-alone RCA4 version. These changes resulted in a significant decrease in the total annual mean net fluxes at the top of the atmosphere (TOA) by −5 W m−2 over the domain selected in the study. The TOA net fluxes from the "MOD" simulation show a better agreement with the retrievals from the Clouds and the Earth's Radiant Energy System (CERES) instrument. The aerosol indirect effects are estimated in the "MOD" simulation in comparison to the pre-industrial aerosol emissions (1900). Our simulations estimated the domain averaged annual mean total radiative forcing of −0.64 W m−2 with a larger contribution from the first indirect aerosol effect (−0.57 W m−2) than from the second indirect aerosol effect (−0.14 W m−2).

Mini Challenge 2 of the VAST Challenge 2017 focused on a small industrial area south of the fictional Mistford preserve, specifically around four manufacturing factories. Our main goal was to develop a visual analytics tool to explore the spatio-temporal chemical readings and wind data. Specifically, we wanted to determine which factories were responsible for emitting which chemicals and to determine the performance of the nine sensors in the area. In order to help achieve this goal, we developed a web-based application that utilizes interactive visualizations and path line analysis for revealing sensor errors and chemical reading spikes, along with pinpointing the possible sources of chemical reading spikes.

Characterizing typical meteorological conditions associated with extreme pollution events helps in the better understanding of the role of local meteorology in governing the transport and distribution of pollutants in the atmosphere. The knowledge of their co-variability could further help to evaluate and constrain chemistry transport models (CTMs). Hence, in this study, we investigate the statistical linkages between extreme nitrogen dioxide (NO2) pollution events and meteorology over Scandinavia using observational and reanalysis data. It is observed that the south-westerly winds dominated during extreme events, accounting for 50–65 % of the total events depending on the season, while the second largest annual occurrence was from south-easterly winds, accounting for 17 % of total events. The specific humidity anomalies showed an influx of warmer and moisture-laden air masses over Scandinavia in the free troposphere. Two distinct modes in the persistency of circulation patterns are observed. The first mode lasts for 1–2 days, dominated by south-easterly winds that prevailed during 78 % of total extreme events in that mode, while the second mode lasted for 3–5 days, dominated by south-westerly winds that prevailed during 86 % of the events. The combined analysis of circulation patterns, their persistency, and associated changes in humidity and clouds suggests that NO2 extreme events over Scandinavia occur mainly due to the long-range transport from the southern latitudes.

We compare four different model geometries for particles with small-scale surface roughness. The geometries are based on regular and stochastic surface perturbations, as well as on 2D- and 3D-roughness models. We further compare T-matrix and discrete dipole computations. Particle size parameters of 5 and 50 are considered, as well as refractive indices of 1.6+0.0005i and 3+0.1i. The effect of small-scale surface roughness on the intensity and polarisation of the scattered light strongly depends on the size parameter and refractive index. In general, 2D surface roughness models predict stronger effects than 3D models. Stochastic surface roughness models tend to predict the strongest depolarising effects, while regular surface roughness models can have a stronger effect on the angular distribution of the scattered intensity. Computations with the discrete dipole approximation only cover a limited range of size parameters. T-matrix computations allow us to significantly extend that range, but at the price of restricting the model particles to symmetric surface perturbations with small amplitudes.

Temperature inversions influence the local air quality at smaller scales and the pollution transport at larger spatio-temporal scales and are one of the most commonly observed meteorological phenomena over Scandinavia (54°N–70°N, 0–30°E) during winter. Here, apart from presenting key statistics on temperature inversions, a large-scale co-variation of inversion strength and carbon monoxide (CO), an ideal pollution tracer, is further quantified at six vertical levels in the free troposphere during three distinct meteorological regimes that are identified based on inversion strength. Collocated temperature and CO profiles from Atmospheric Infrared Sounder (AIRS) are used for this purpose. Higher values of CO (up to 15%) are observed over Scandinavia during weakly stable regimes at all vertical levels studied, whereas lower CO values (up to 10%) are observed when inversions become stronger and elevated. The observed systematic co-variation between CO and inversion strength in three meteorological regimes is most likely explained by the efficacy of long-range transport to influence tropospheric composition over Scandinavia. We argue that this large-scale co-variation of temperature inversions and CO would be a robust metric to test coupling of large-scale meteorology and chemistry in transport models.

The main purpose of this study is to underline the sensitivity of cloud liquid water content (LWC) estimates purely to 1) the shape of computationally simplified temperature-dependent thermodynamic phase and 2) the range of subzero temperatures covered to partition total cloud condensate into liquid and ice fractions. Linear, quadratic, or sigmoid-shaped functions for subfreezing temperatures (down to −20° or −40°C) are often used in climate models and reanalysis datasets for partitioning total condensate. The global vertical profiles of clouds obtained from CloudSat for the 4-yr period June 2006–May 2010 are used for sensitivity analysis and the quantitative estimates of sensitivities based on these realistic cloud profiles are provided. It is found that three cloud regimes in particular—convective clouds in the tropics, low-level clouds in the northern high latitudes, and middle-level clouds over the midlatitudes and Southern Ocean—are most sensitive to assumptions on thermodynamic phase. In these clouds, the LWC estimates based purely on quadratic or sigmoid-shaped functions with a temperature range down to −20°C can differ by up to 20%–40% over the tropics (in seasonal means), 10%–30% over the midlatitudes, and up to 50% over high latitudes compared to a linear assumption. When the temperature range is extended down to −40°C, LWC estimates in the sigmoid case can be much higher than the above values over high-latitude regions compared to the commonly used case with quadratic dependency down to −20°C. This sensitivity study emphasizes the need to critically investigate radiative impacts of cloud thermodynamic phase assumptions in simplified climate models and reanalysis datasets.

Generalized Laplacian distribution is considered. A new distribution called geometric generalized Laplacian distribution is introduced and its properties are studied. First- and higher-order autoregressive processes with these stationary marginal distributions are developed and studied. Simulation studies are conducted and trajectories of the process are obtained for selected values of the parameters. Various areas of application of these models are discussed.

The degree of non-linearity in DMS-cloud-climate interactions is assessed using the ECHAM5-HAMMOZ model by taking into account end-to-end aerosol chemistry-cloud microphysics link. The evaluation is made over the Southern oceans in austral summer, a region of minimal anthropogenic influence. In this study, we compare the DMS-derived changes in the aerosol and cloud microphysical properties between a baseline simulation with the ocean DMS emissions from a prescribed climatology, and a scenario where the DMS emissions are doubled. Our results show that doubling the DMS emissions in the current climate results in a non-linear response in atmospheric DMS burden and subsequently, in SO2 and H2SO4 burdens due to inadequate OH oxidation. The aerosol optical depth increases by only ~20 % in the 30° S–75° S belt in the SH summer months. This increases the vertically integrated cloud droplet number concentrations (CDNC) by 25 %. Since the vertically integrated liquid water vapor is constant in our model simulations, an increase in CDNC leads to a reduction in cloud droplet radius of 3.4 % over the Southern oceans in summer. The equivalent increase in cloud liquid water path is 10.7 %. The above changes in cloud microphysical properties result in a change in global annual mean radiative forcing at the TOA of −1.4 W m−2. The results suggest that the DMS-cloud microphysics link is highly non-linear. This has implications for future studies investigating the DMS-cloud climate feedbacks in a warming world and for studies evaluating geoengineering options to counteract warming by modulating low level marine clouds.

The sensitivity of the climate impact of Mt. Pinatubo eruption in the tropics and extratropics to different QBO phases is investigated. Mt. Pinatubo erupted in June 1991 during the easterly phase of the QBO at 30 hPa and the phase change to westerly took place in August 1992. Here, the consequences are analyzed if the QBO phase had been in the opposite phase during the eruption of Mt. Pinatubo. Hence, in this study, simulations are carried out using the middle atmosphere configuration of ECHAM5 general circulation model for two cases – one with the observed QBO phase and the other with the opposite QBO phase. The response of temperature and geopotential height in the lower stratosphere is evaluated for the following cases – (1) when only the effects of the QBO are included and (2) when the effects of aerosols, QBO and SSTs (combined response) are included. The tropical QBO signature in the lower stratospheric temperature is well captured in the pure QBO responses and in the combined (aerosol + ocean + QBO) responses. The response of the extratropical atmosphere to the QBO during the second winter after the eruption is captured realistically in the case of the combined forcing showing a strengthening of the polar vortex when the QBO is in its westerly phase and a warm, weak polar vortex in the easterly QBO phase. The vortex is disturbed during the first winter irrespective of the QBO phases in the combined responses and this may be due to the strong influences of El Niño during the first winters after eruption. However, the pure QBO experiments do not realistically reproduce a strengthening of the polar vortex in the westerly QBO phase, even though below normal temperatures in the high latitudes are seen in October-November-December months when the opposite QBO phase is prescribed instead of the December-January-February winter months used here for averaging.

13 pages, 5 figures, supporting information http://dx.doi.org/10.1002/2014JD022687, One of the critical parameters in assessing the global impacts of dimethyl sulfide (DMS) on cloud properties and the radiation budget is the estimation of phytoplankton-induced ocean emissions, which are derived from prescribed, climatological surface seawater DMS concentrations. The most widely used global ocean DMS climatology was published 15 years ago and has recently been updated using a much larger database of observations. The updated climatology displays significant differences in terms of the global distribution and regional monthly averages of sea surface DMS. In this study, we use the ECHAM5-HAMMOZ aerosol-chemistry-climate general circulation model to quantify the influence of the updated DMS climatology in computed atmospheric properties, namely, the spatial and temporal distributions of atmospheric DMS concentration, sulfuric acid concentration, sulfate aerosols, number of activated aerosols, cloud droplet number concentration, and the aerosol radiative forcing at the top of the atmosphere. Significant differences are observed for all the modeled variables. Comparison with observations of atmospheric DMS and total sulfate also shows that in places with large DMS emissions, the updated climatology shows a better match with the observations. This highlights the importance of using the updated climatology for projecting future impacts of oceanic DMS emissions, especially considering that the relative importance of the natural sulfur fluxes is likely to increase due to legislation to “clean up” anthropogenic emissions. The largest estimated differences are in the Southern Ocean, Indian Ocean, and parts of the Pacific Ocean, where the climatologies differ in seasonal concentrations over large geographical areas. The model results also indicate that the former DMS climatology underestimated the effect of DMS on the globally averaged annual aerosol radiative forcing at the top of the atmosphere by about 20%, The Indian Institute of Tropical Meteorology is supported by the Ministry of Earth Sciences, Government of India. S.-J.R. and R.S. acknowledge support from the former Spanish Ministry of Science and Innovation through projects PRISMA and Malaspina 2010

Article, We have implemented the sectional aerosol dynamics model SALSA (Sectional Aerosol module for Large Scale Applications) in the European-scale chemistry-transport model MATCH (Multi-scale Atmospheric Transport and Chemistry). The new model is called MATCH-SALSA. It includes aerosol microphysics, with several formulations for nucleation, wet scavenging and condensation. The model reproduces observed higher particle number concentration (PNC) in central Europe and lower concentrations in remote regions. The modeled PNC size distribution peak occurs at the same or smaller particle size as the observed peak at four measurement sites spread across Europe. Total PNC is underestimated at northern and central European sites and accumulation-mode PNC is underestimated at all investigated sites. The low nucleation rate coefficient used in this study is an important reason for the underestimation. On the other hand, the model performs well for particle mass (including secondary inorganic aerosol components), while elemental and organic carbon concentrations are underestimated at many of the sites. Further development is needed, primarily for treatment of secondary organic aerosol, in terms of biogenic emissions and chemical transformation. Updating the biogenic secondary organic aerosol (SOA) scheme will likely have a large impact on modeled PM2.5 and also affect the model performance for PNC through impacts on nucleation and condensation., published version, http://purl.org/eprint/status/PeerReviewed

This paper describes the pre-operational analysis and forecasting system developed during MACC (Monitoring Atmospheric Composition and Climate) and continued in the MACC-II (Monitoring Atmospheric Composition and Climate: Interim Implementation) European projects to provide air quality services for the European continent. This system is based on seven state-of-the art models developed and run in Europe (CHIMERE, EMEP, EURAD-IM, LOTOS-EUROS, MATCH, MOCAGE and SILAM). These models are used to calculate multi-model ensemble products. The paper gives an overall picture of its status at the end of MACC-II (summer 2014) and analyses the performance of the multi-model ensemble. The MACC-II system provides daily 96 h forecasts with hourly outputs of 10 chemical species/aerosols (O3, NO2, SO2, CO, PM10, PM2.5, NO, NH3, total NMVOCs (non-methane volatile organic compounds) and PAN+PAN precursors) over eight vertical levels from the surface to 5 km height. The hourly analysis at the surface is done a posteriori for the past day using a selection of representative air quality data from European monitoring stations. The performance of the system is assessed daily, weekly and every 3 months (seasonally) through statistical indicators calculated using the available representative air quality data from European monitoring stations. Results for a case study show the ability of the ensemble median to forecast regional ozone pollution events. The seasonal performances of the individual models and of the multi-model ensemble have been monitored since September 2009 for ozone, NO2 and PM10. The statistical indicators for ozone in summer 2014 show that the ensemble median gives on average the best performances compared to the seven models. There is very little degradation of the scores with the forecast day but there is a marked diurnal cycle, similarly to the individual models, that can be related partly to the prescribed diurnal variations of anthropogenic emissions in the models. During summer 2014, the diurnal ozone maximum is underestimated by the ensemble median by about 4 μg m−3 on average. Locally, during the studied ozone episodes, the maxima from the ensemble median are often lower than observations by 30–50 μg m−3. Overall, ozone scores are generally good with average values for the normalised indicators of 0.14 for the modified normalised mean bias and of 0.30 for the fractional gross error. Tests have also shown that the ensemble median is robust to reduction of ensemble size by one, that is, if predictions are unavailable from one model. Scores are also discussed for PM10 for winter 2013–1014. There is an underestimation of most models leading the ensemble median to a mean bias of −4.5 μg m−3. The ensemble median fractional gross error is larger for PM10 (~ 0.52) than for ozone and the correlation is lower (~ 0.35 for PM10 and ~ 0.54 for ozone). This is related to a larger spread of the seven model scores for PM10 than for ozone linked to different levels of complexity of aerosol representation in the individual models. In parallel, a scientific analysis of the results of the seven models and of the ensemble is also done over the Mediterranean area because of the specificity of its meteorology and emissions. The system is robust in terms of the production availability. Major efforts have been done in MACC-II towards the operationalisation of all its components. Foreseen developments and research for improving its performances are discussed in the conclusion.

The present study is based on the observations carried out over the IndianOcean from the Indian research vessel ORV Sagar Kanya during the intensive field phase of the Indian Ocean Experiment in January–March 1999. The study area spanned from 15°N to 20°S in the central Indian Ocean. Near surface variations and surface fluxes along the cruise track are presented. A comparison of near surface characteristics over the Indian Ocean and tropical west Pacific has been made. It is observed that the average difference between the sea surface temperature and air temperature at 10 m height was 0.7 °C over the study area, nearly half of that observed over the tropical west Pacific. A comparison between observed and NCEP reanalysissurface data has been made. We find good agreement between ship measured andNCEP reanalysis surface pressure, specific humidity and wind fields.On the other hand, surface air temperature in the reanalysis tends to be lowcompared to observations. The components of the net surface heat flux comparebetter in the north Indian Ocean than in the southern Indian Ocean.

Among various factors that influence the long-range transport of pollutants in the free troposphere (FT), the prevailing atmospheric weather states probably play the most important role in governing characteristics and efficacy of such transport. The weather states, such as a particular wind pattern, cyclonic or anticyclonic conditions, and their degree of persistency determine the spatio-temporal distribution and the final fate of the pollutants. This is especially true in the case of Nordic countries, where baroclinic disturbances and associated weather fronts primarily regulate local meteorology, in contrast to the lower latitudes where a convective paradigm plays a similarly important role. Furthermore, the long-range transport of pollutants in the FT has significant contribution to the total column burden over the Nordic countries. However, there is insufficient knowledge on the large-scale co-variability of pollutants in the FT and atmospheric weather states based solely on observational data over this region. The present study attempts to quantify and understand this statistical co-variability while providing relevant meteorological background. To that end, we select eight weather states that predominantly occur over the Nordic countries and three periods of their persistency (3 days, 5 days, and 7 days), thus providing in total 24 cases to investigate sensitivity of free tropospheric carbon monoxide, an ideal tracer for studying pollutant transport, to these selected weather states. The eight states include four dominant wind directions (namely, NW, NE, SE and SW), cyclonic and anticyclonic conditions, and the enhanced positive and negative phases of the North Atlantic Oscillation (NAO). For our sensitivity analysis, we use recently released Version 6 retrievals of CO at 500 hPa from the Atmospheric Infrared Sounder (AIRS) onboard Aqua satellite covering the 11-year period from September 2002 through August 2013 and winds from the ECMWF's ERA-Interim project to classify weather states for the same 11-year period. We show that, among the various weather states studied here, southeasterly winds lead to highest observed CO anomalies (up to +8%) over the Nordic countries while transporting pollution from the central and eastern parts of Europe. The second (up to +4%) and third highest (up to +2.5%) CO anomalies are observed when winds are northwesterly (facilitating inter-continental transport from polluted North American regions) and during the enhanced positive phase of the NAO respectively. Higher than normal CO anomalies are observed during anticyclonic conditions (up to +1%) compared to cyclonic conditions. The cleanest conditions are observed when winds are northeasterly and during the enhanced negative phases of the NAO, when relatively clean Arctic air masses are transported over the Nordic regions in the both cases. In the case of nearly all weather states, the CO anomalies consistently continue to increase or decrease as the degree of persistency of a weather state is increased. The results of this sensitivity study further provide an observational basis for the process-oriented evaluation of chemistry transport models, especially with regard to the representation of large-scale coupling of chemistry and local weather states and its role in the long-range transport of pollutants in such models.

The normal-Laplace distribution is considered and its properties are discussed. A multivariate normal-Laplace distribution is introduced and its properties are studied. First order autoregressive processes with these stationary marginal distributions are developed and studied. A generalized multivariate normal-Laplace distribution is introduced. Multivariate geometric normal-Laplace distribution and multivariate geometric generalized normal-Laplace distributions are introduced and their properties are studied. Estimation of parameters and some applications are also discussed., Statistica, Vol 74, No 1 (2014)

Preliminary estimate of divergent Hadley and Walker circulation associated with inter-decadal variations in the tropics is made with 50-year reanalysis data and compared with their inter-annual counterparts. Interdecadal and inter-annual components are separated using harmonic analysis and meridional and zonal mass flux stream functions are used to calculate the strength of Hadley and Walker circulations. The magnitude of inter-decadal Hadley and Walker circulation anomalies are shown to be comparable to those associated with dominant inter-annual variations. How superposition of inter-decadal and inter-annual divergent circulations may influence regional climate is discussed.

One of the key knowledge gaps when estimating aerosol forcing and their role in air quality is our limited understanding of their vertical distribution. As an active lidar in space, the CALIOP-CALIPSO is helping to close this gap. The descending orbital track of CALIPSO follows elongated semi-major axis of Sweden, slicing its atmosphere every 2–3 d, thus providing a unique opportunity to characterise aerosols and their verticality in all seasons irrespective of solar conditions. This favourable orbital configuration of CALIPSO over Sweden is exploited in the present study. Using five years of night-time aerosol observations (2006–2011), we investigated the vertical distribution of aerosols. The role of temperature inversions and winds in governing this distribution is additionally investigated using collocated AIRS-Aqua and ERA-Interim Reanalysis data. It is found that the majority of aerosols (up to 70%) are located within 1 km above the surface in the lowermost troposphere, irrespective of the season. In summer, convection and stronger mixing lift aerosols to slightly higher levels, but their noticeable presence in the upper free troposphere is observed in the winter half of the year, when the boundary layer is decoupled due to strong temperature inversions separating local sources from the transport component. When southerly winds prevail, two or more aerosol layers are most frequent over southern Sweden and the polluted air masses have higher AOD values. The depolarisation ratio and integrated attenuated backscatter of these aerosol layers are also higher. About 30–50% of all aerosol layers are located below the level where temperature inversions peak. On the other hand, relatively cleaner conditions are observed when the winds have a northerly component.Keywords: aerosols, CALIPSO, vertical distribution, air quality(Published: 11 October 2013)Citation: Tellus B 2013, 65, 21155, http://dx.doi.org/10.3402/tellusb.v65i0.21155

The main purpose of this study is to investigate the influence of the Arctic Oscillation (AO), the dominant mode of natural variability over the northerly high latitudes, on the spatial (horizontal and vertical) distribution of clouds in the Arctic. To that end, we use a suite of sensors onboard NASA's A-Train satellites that provide accurate observations of the distribution of clouds along with information on atmospheric thermodynamics. Data from three independent sensors are used (AQUA-AIRS, CALIOP-CALIPSO and CPR-CloudSat) covering two time periods (winter half years, November through March, of 2002–2011 and 2006–2011, respectively) along with data from the ERA-Interim reanalysis. We show that the zonal vertical distribution of cloud fraction anomalies averaged over 67–82° N to a first approximation follows a dipole structure (referred to as "Greenland cloud dipole anomaly", GCDA), such that during the positive phase of the AO, positive and negative cloud anomalies are observed eastwards and westward of Greenland respectively, while the opposite is true for the negative phase of AO. By investigating the concurrent meteorological conditions (temperature, humidity and winds), we show that differences in the meridional energy and moisture transport during the positive and negative phases of the AO and the associated thermodynamics are responsible for the conditions that are conducive for the formation of this dipole structure. All three satellite sensors broadly observe this large-scale GCDA despite differences in their sensitivities, spatio-temporal and vertical resolutions, and the available lengths of data records, indicating the robustness of the results. The present study also provides a compelling case to carry out process-based evaluation of global and regional climate models.

Influx of aerosols from the mid-latitudes has a wide range of impacts on the Arctic atmosphere. In this study, the capability of the CALIPSO-CALIOP instrument to provide accurate observations of aerosol layers is exploited to characterize their vertical distribution, probability density functions (PDFs) of aerosol layer thickness, base and top heights, and optical depths over the Arctic for the 4-yr period from June 2006 to May 2010. It is shown that the bulk of aerosols, from about 65% in winter to 45% in summer, are confined below the lowermost kilometer of the troposphere. In the middle troposphere (3-5 km), spring and autumn seasons show slightly higher aerosol amounts compared to other two seasons. The relative vertical distribution of aerosols shows that clean continental aerosol is the largest contributor in all seasons except in summer, when layers of polluted continental aerosols are almost as large. In winter and spring, polluted continental aerosols are the second largest contributor to the total number of observed aerosol layers, whereas clean marine aerosol is the second largest contributor in summer and autumn. The PDFs of the geometrical thickness of the observed aerosol layers peak about 400-700 m. Polluted continental and smoke aerosols, which are associated with the intrusions from mid-latitudes, have much broader distributions of optical and geometrical thicknesses, suggesting that they appear more often optically thicker and higher up in the troposphere.

The presence of aerosols over highly reflective liquid water cloud tops poses a big challenge in simulating their radiative impacts. Particularly, absorbing aerosols, such as smoke, may have significant impact in such situations and even change the sign of net radiative forcing. Until now, it was not possible to obtain information on such overlap events realistically from the existing passive satellite sensors. However, the CALIOP instrument onboard NASA's CALIPSO satellite allows us to examine these events with an unprecedented accuracy. Using four years of collocated CALIPSO 5 km Aerosol and Cloud Layer Version 3 Products (June 2006–May 2010), we quantify, for the first time, the macrophysical characteristics of overlapping aerosol and water cloud layers globally. We investigate seasonal variability in these characteristics over six latitude bands to understand the hemispheric differences. We compute a) the percentage cases when such overlap is seen globally and seasonally when all aerosol types are included (AAO case) in the analysis, b) the joint histograms of aerosol layer base height and cloud layer top height, and c) the joint histograms of aerosol and cloud geometrical thicknesses in such overlap cases. We also investigate frequency of smoke aerosol-cloud overlap (SAO case). The results show a distinct seasonality in overlap frequency in both AAO and SAO cases. Globally, the frequency is highest during JJA months in AAO case, while for the SAO case, it is highest in SON months. The seasonal mean overlap frequency can regionally exceed 20% in AAO case and 10% in SAO case. There is a tendency that the vertical separation between aerosol and cloud layers increases from high to low latitude regions in the both hemispheres. In about 5–10% cases the vertical distance between aerosol and cloud layers is less than 100 m, while about in 45–60% cases it less than a kilometer in the annual means for different latitudinal bands. The frequency of occurrence of thicker aerosol layers gradually increases from poles to tropics. In about 70–80% cases, aerosol layers are less than a kilometer thick, while in about 18–22% cases they are 1–2 km thick. The frequency of aerosol layers 2–3 km thick is about 4–5% in the tropical belts during overlap events. The results further highlight spatial and temporal variations in aerosol-liquid water cloud overlap and suggest that the frequency of occurrence of such overlap events is far from being negligible globally.

The contribution of ocean dimethyl sulfide (DMS) emissions to changes in cloud microphysical properties is quantified seasonally and globally for present day climate conditions using an aerosol-chemistry-climate general circulation model, ECHAM5-HAMMOZ, coupled to a cloud microphysics scheme. We evaluate DMS aerosol-cloud-climate linkages over the southern oceans where anthropogenic influence is minimal. The changes in the number of activated particles, cloud droplet number concentration (CDNC), cloud droplet effective radius, cloud cover and the radiative forcing are examined by analyzing two simulations: a baseline simulation with ocean DMS emissions derived from a prescribed climatology and one in which the ocean DMS emissions are switched off. Our simulations show that the model realistically simulates the seasonality in the number of activated particles and CDNC, peaking during Southern Hemisphere (SH) summer coincident with increased phytoplankton blooms and gradually declining with a minimum in SH winter. In comparison to a simulation with no DMS, the CDNC level over the southern oceans is 128% larger in the baseline simulation averaged over the austral summer months. Our results also show an increased number of smaller sized cloud droplets during this period. We estimate a maximum decrease of up to 15–18% in the droplet radius and a mean increase in cloud cover by around 2.5% over the southern oceans during SH summer in the simulation with ocean DMS compared to when the DMS emissions are switched off. The global annual mean top of the atmosphere DMS aerosol all sky radiative forcing is −2.03 W/m2, whereas, over the southern oceans during SH summer, the mean DMS aerosol radiative forcing reaches −9.32 W/m2.

[1] The large AD 1258 eruption had a stratospheric sulfate load approximately ten times greater than the 1991 Pinatubo eruption. Yet surface cooling was not substantially larger than for Pinatubo (∼0.4 K). We apply a comprehensive Earth System Model to demonstrate that the size of the aerosol particles needs to be included in simulations, especially to explain the climate response to large eruptions. The temperature response weakens because increased density of particles increases collision rate and therefore aerosol growth. Only aerosol particle sizes substantially larger than observed after the Pinatubo eruption yield temperature changes consistent with terrestrial Northern Hemisphere summer temperature reconstructions. These results challenge an oft-held assumption of volcanic impacts not only with respect to the immediate or longer-term temperature response, but also any ecosystem response, including extinctions.

Large volcanic eruptions and their subsequent climate responses are relatively short-lived perturbations to the climate system. They provide an excellent opportunity to understand the response of the climate system to a global radiative forcing and to assess the ability of our climate models to simulate such large perturbations. The eruption of Mt. Pinatubo in Philippines in June 1991 was one of the strongest volcanic eruptions in the 20th century and this well observed eruption can serve as an important case study to understand the subsequent weather and climate changes. In this paper, the most comprehensive simulations to date of the climate impact of Mt. Pinatubo eruption are carried out with prescribed volcanic aerosols including observed SSTs, QBO and volcanically induced ozone anomalies. This is also the first attempt to include all the known factors for the simulation of such an experiment. Here, the climate response is evaluated under different boundary conditions including one at a time, thereby, investigating the radiative and dynamical responses to individual and combined forcings by observed SSTs, QBO and volcanic effects. Two ensembles of ten members each, for unperturbed and volcanically perturbed conditions were carried out using the middle atmosphere configuration of ECHAM5 model. Our results show that the pure aerosol response in lower stratospheric temperature is insensitive to the boundary conditions in the tropics and does not show some observed features which results from the boundary conditions. To simulate realistically the lower stratospheric temperature response, one must include all the known factors. The pure QBO and ocean responses are simulated consistent with earlier studies. The dynamical response manifested as the winter warming pattern is not simulated in the ensemble mean of the experiments. Our analysis also shows that the response to El Niño conditions is very strong in the model and that it partially masks the effects due to volcanic forcing.