Detection and attribution of aerosol-cloud interactions in large-domain large-eddy simulations with the ICOsahedral Non-hydrostatic model

Clouds and aerosols contribute the largest uncertainty to current estimates and interpretations of the Earth’s changing energy budget. Here we use a new-generation large-domain large-eddy model, ICON-LEM (ICOsahedral Non-hydrostatic Large Eddy Model), to simulate the response of clouds to realistic anthropogenic perturbations in aerosols serving as cloud condensation nuclei (CCN). The novelty compared to previous studies is that (i) the LEM is run in weather prediction mode and with fully interactive land surface over a large domain and (ii) a large range of data from various sources are used for the detection and attribution. The aerosol perturbation was chosen as peak-aerosol conditions over Europe in 1985, with more than fivefold more sulfate than in 2013. Observational data from various satellite and ground-based remote sensing instruments are used, aiming at the detection and attribution of this response. The simulation was run for a selected day (2 May 2013) in which a large variety of cloud regimes was present over the selected domain of central Europe. It is first demonstrated that the aerosol fields used in the model are consistent with corresponding satellite aerosol optical depth retrievals for both 1985 (perturbed) and 2013 (reference) conditions. In comparison to retrievals from ground-based lidar for 2013, CCN profiles for the reference conditions were consistent with the observations, while the ones for the 1985 conditions were not. Similarly, the detection and attribution process was successful for droplet number concentrations: the ones simulated for the 2013 conditions were consistent with satellite as well as new ground-based lidar retrievals, while the ones for the 1985 conditions were outside the observational range. For other cloud quantities, including cloud fraction, liquid water path, cloud base altitude and cloud lifetime, the aerosol response was small compared to their natural variability. Also, large uncertainties in satellite and ground-based observations make the detection and attribution difficult for these quantities. An exception to this is the fact that at a large liquid water path value (LWP > 200 g m−2), the control simulation matches the observations, while the perturbed one shows an LWP which is too large. The model simulations allowed for quantifying the radiative forcing due to aerosol–cloud interactions, as well as the adjustments to this forcing. The latter were small compared to the variability and showed overall a small positive radiative effect. The overall effective radiative forcing (ERF) due to aerosol–cloud interactions (ERFaci) in the simulation was dominated thus by the Twomey effect and yielded for this day, region and aerosol perturbation −2.6 W m$^{-2}$. Using general circulation models to scale this to a global-mean present-day vs. pre-industrial ERFaci yields a global ERFaci of −0.8 W m$^{-2}$

Lung cancer in HIV patients and their parents: A Danish cohort study

<p>Abstract</p> <p>Background</p> <p>HIV patients are known to be at increased risk of lung cancer but the risk factors behind this are unclear.</p> <p>Methods</p> <p>We estimated the cumulative incidence and relative risk of lung cancer in 1) a population of all Danish HIV patients identified from the Danish HIV Cohort Study (n = 5,053) and a cohort of population controls matched on age and gender (n = 50,530) (study period; 1995 - 2009) and 2) their parents (study period; 1969 - 2009). Mortality and relative risk of death after a diagnosis of lung cancer was estimated in both populations.</p> <p>Results</p> <p>29 (0.6%) HIV patients vs. 183 (0.4%) population controls were diagnosed with lung cancer in the observation period. HIV patients had an increased risk of lung cancer (adjusted incidence rate ratio (IRR); 2.38 (95% CI; 1.61 - 3.53)). The IRR was considerably increased in HIV patients who were smokers or former smokers (adjusted IRR; 4.06 (95% CI; 2.66 - 6.21)), male HIV patients with heterosexual route of infection (adjusted IRR; 4.19 (2.20 - 7.96)) and HIV patients with immunosuppression (adjusted IRR; 3.25 (2.01 - 5.24)). Both fathers and mothers of HIV patients had an increased risk of lung cancer (adjusted IRR for fathers; 1.31 (95% CI: 1.09 - 1.58), adjusted IRR for mothers 1.35 (95% CI: 1.07 - 1.70)). Mortality after lung cancer diagnose was increased in HIV patients (adjusted mortality rate ratio 2.33 (95%CI; 1.51 - 3.61), but not in the parents. All HIV patients diagnosed with lung cancer were smokers or former smokers.</p> <p>Conclusion</p> <p>The risk was especially increased in HIV patients who were smokers or former smokers, heterosexually infected men or immunosuppressed. HIV appears to be a marker of behavioural or family related risk factors that affect the incidence of lung cancer in HIV patients.</p

Optical Absorption Properties in Pentacene/Tetracene Solid Solutions

Modifying the optical and electronic properties of crystalline organic thin films is of great interest for improving the performance of modern organic semiconductor devices. Therein, the statistical mixing of molecules to form a solid solution provides an opportunity to fine-tune optical and electronic properties. Unfortunately, the diversity of intermolecular interactions renders mixed organic crystals highly complex, and a holistic picture is still lacking. Here, we report a study of the optical absorption properties in solid solutions of pentacene and tetracene, two prototypical organic semiconductors. In the mixtures, the optical properties can be continuously modified by statistical mixing at the molecular level. Comparison with time-dependent density functional theory calculations on occupationally disordered clusters unravels the electronic origin of the low energy optical transitions. The disorder partially relaxes the selection rules, leading to additional optical transitions that manifest as optical broadening. Furthermore, the contribution of diabatic charge-transfer states is modified in the mixtures, reducing the observed splitting in the 0-0 vibronic transition. Additional comparisons with other blended systems generalize our results and indicate that changes in the polarizability of the molecular environment in organic thin-film blends induce shifts in the absorption spectrum.</p

Detection and attribution of aerosol&amp;#8211;cloud interactions in large-domain large-eddy simulations with the ICOsahedral Non-hydrostatic model

Clouds and aerosols contribute the largest uncertainty to current estimates and interpretations of the Earth’s changing energy budget. Here we use a new-generation large-domain large-eddy model, ICON-LEM (ICOsahedral Non-hydrostatic Large Eddy Model), to simulate the response of clouds to realistic anthropogenic perturbations in aerosols serving as cloud condensation nuclei (CCN). The novelty compared to previous studies is that (i) the LEM is run in weather prediction mode and with fully interactive land surface over a large domain and (ii) a large range of data from various sources are used for the detection and attribution. The aerosol perturbation was chosen as peak-aerosol conditions over Europe in 1985, with more than fivefold more sulfate than in 2013. Observational data from various satellite and ground-based remote sensing instruments are used, aiming at the detection and attribution of this response. The simulation was run for a selected day (2 May 2013) in which a large variety of cloud regimes was present over the selected domain of central Europe.It is first demonstrated that the aerosol fields used in the model are consistent with corresponding satellite aerosol optical depth retrievals for both 1985 (perturbed) and 2013 (reference) conditions. In comparison to retrievals from ground-based lidar for 2013, CCN profiles for the reference conditions were consistent with the observations, while the ones for the 1985 conditions were not.Similarly, the detection and attribution process was successful for droplet number concentrations: the ones simulated for the 2013 conditions were consistent with satellite as well as new ground-based lidar retrievals, while the ones for the 1985 conditions were outside the observational range.For other cloud quantities, including cloud fraction, liquid water path, cloud base altitude and cloud lifetime, the aerosol response was small compared to their natural variability. Also, large uncertainties in satellite and ground-based observations make the detection and attribution difficult for these quantities. An exception to this is the fact that at a large liquid water path value (LWP > 200 g m-²), the control simulation matches the observations, while the perturbed one shows an LWP which is too large.The model simulations allowed for quantifying the radiative forcing due to aerosol–cloud interactions, as well as the adjustments to this forcing. The latter were small compared to the variability and showed overall a small positive radiative effect. The overall effective radiative forcing (ERF) due to aerosol–cloud interactions (ERFaci) in the simulation was dominated thus by the Twomey effect and yielded for this day, region and aerosol perturbation −2.6 W m-². Using general circulation models to scale this to a global-mean present-day vs. pre-industrial ERFaci yields a global ERFaci of −0.8 W m-²

Detection and attribution of aerosol-cloud interactions in large-domain large-eddy simulations with the ICOsahedral Non-hydrostatic model

Clouds and aerosols contribute the largest uncertainty to current estimates and interpretations of the Earth's changing energy budget. Here we use a new-generation large-domain large-eddy model, ICON-LEM (ICOsahedral Non-hydrostatic Large Eddy Model), to simulate the response of clouds to realistic anthropogenic perturbations in aerosols serving as cloud condensation nuclei (CCN). The novelty compared to previous studies is that (i) the LEM is run in weather prediction mode and with fully interactive land surface over a large domain and (ii) a large range of data from various sources are used for the detection and attribution. The aerosol perturbation was chosen as peak-aerosol conditions over Europe in 1985, with more than fivefold more sulfate than in 2013. Observational data from various satellite and ground-based remote sensing instruments are used, aiming at the detection and attribution of this response. The simulation was run for a selected day (2 May 2013) in which a large variety of cloud regimes was present over the selected domain of central Europe. It is first demonstrated that the aerosol fields used in the model are consistent with corresponding satellite aerosol optical depth retrievals for both 1985 (perturbed) and 2013 (reference) conditions. In comparison to retrievals from groundbased lidar for 2013, CCN profiles for the reference conditions were consistent with the observations, while the ones for the 1985 conditions were not. Similarly, the detection and attribution process was successful for droplet number concentrations: the ones simulated for the 2013 conditions were consistent with satellite as well as new ground-based lidar retrievals, while the ones for the 1985 conditions were outside the observational range. For other cloud quantities, including cloud fraction, liquid water path, cloud base altitude and cloud lifetime, the aerosol response was small compared to their natural vari ability. Also, large uncertainties in satellite and ground-based observations make the detection and attribution difficult for these quantities. An exception to this is the fact that at a large liquid water path value (LWP > 200 g m-2), the control simulation matches the observations, while the perturbed one shows an LWP which is too large. The model simulations allowed for quantifying the radiative forcing due to aerosol-cloud interactions, as well as the adjustments to this forcing. The latter were small compared to the variability and showed overall a small positive radiative effect. The overall effective radiative forcing (ERF) due to aerosol-cloud interactions (ERFaci) in the simulation was dominated thus by the Twomey effect and yielded for this day, region and aerosol perturbation-2:6 W m-2. Using general circulation models to scale this to a global-mean present-day vs. pre-industrial ERFaci yields a global ERFaci of-0:8 W m-2 © 2020 Author(s)

The ICON-A model for direct QBO simulations on GPUs (version icon-cscs:baf28a514)

Classical numerical models for the global atmosphere, as used for numerical weather forecasting or climate research, have been developed for conventional central processing unit (CPU) architectures. This hinders the employment of such models on current top-performing supercomputers, which achieve their computing power with hybrid architectures, mostly using graphics processing units (GPUs). Thus also scientific applications of such models are restricted to the lesser computer power of CPUs. Here we present the development of a GPU-enabled version of the ICON atmosphere model (ICON-A), motivated by a research project on the quasi-biennial oscillation (QBO), a global-scale wind oscillation in the equatorial stratosphere that depends on a broad spectrum of atmospheric waves, which originates from tropical deep convection. Resolving the relevant scales, from a few kilometers to the size of the globe, is a formidable computational problem, which can only be realized now on top-performing supercomputers. This motivated porting ICON-A, in the specific configuration needed for the research project, in a first step to the GPU architecture of the Piz Daint computer at the Swiss National Supercomputing Centre and in a second step to the JUWELS Booster computer at the Forschungszentrum Julich. On Piz Daint, the ported code achieves a single-node GPU vs. CPU speedup factor of 6.4 and allows for global experiments at a horizontal resolution of 5 km on 1024 computing nodes with 1 GPU per node with a turnover of 48 simulated days per day. On JUWELS Booster, the more modern hardware in combination with an upgraded code base allows for simulations at the same resolution on 128 computing nodes with 4 GPUs per node and a turnover of 133 simulated days per day. Additionally, the code still remains functional on CPUs, as is demonstrated by additional experiments on the Levante compute system at the German Climate Computing Center. While the application shows good weak scaling over the tested 16-fold increase in grid size and node count, making also higher resolved global simulations possible, the strong scaling on GPUs is relatively poor, which limits the options to increase turnover with more nodes. Initial experiments demonstrate that the ICON-A model can simulate downward-propagating QBO jets, which are driven by wave-mean flow interaction.ISSN:1991-9603ISSN:1991-959

Detection and attribution of aerosol-cloud interactions in large-domain large-eddy simulations with ICON

Abstract. Clouds and aerosols contribute the largest uncertainty to current estimates and interpretations of the Earth&#8217;s changing energy budget. Here we use a new-generation large-domain large-eddy model, ICON-LEM, to simulate the response of clouds to realistic anthropogenic perturbations in aerosols serving as cloud condensation nuclei (CCN). The novelty compared to previous studies is that (i) the LEM is run in weather prediction mode and with fully interactive land surface over a large domain, and (ii) a large range of data from various sources are used for the detection and attribution. The aerosol perturbation was chosen as peak-aerosol conditions over Europe in 1985, with more than five-fold more sulfate than in 2013. Observational data from various satellite and ground-based remote sensing instruments are used aiming at a detection and attribution of this response. The simulation was run for a selected day (2 May 2013) in which over the selected domain of central Europe a large variety of cloud regimes was present. It first is demonstrated, using satellite aerosol optical depth retrievals available for both 1985 and 2013, that the aerosol fields for the reference conditions and also for the perturbed ones, as well as the difference between the two, were consistent in the model and the satellite retrievals. In comparison to retrievals from ground-based lidar for 2013, CCN profiles for the reference conditions were consistent with the observations, while the ones for the 1985 conditions were not. Similarly, detection-and-attribution was successful for droplet number concentrations: the ones simulated for the 2013 conditions were consistent with satellite as well as new ground-based lidar retrievals, while the ones for the 1985 conditions were outside the observational range. For other cloud quantities, including cloud fraction, liquid water path, cloud-base altitude, and cloud lifetime, the aerosol response was small compared to their natural variability. Also, large uncertainties in satellite and ground-based observations make the detection-attribution difficult for these quantities. An exception to this is the fact that at large liquid water path, the control simulation matches the observations, while the perturbed one shows too large LWP. The model simulations allowed to quantify the radiative forcing due to aerosol-cloud interactions, as well as the adjustments to this forcing. The latter were small compared to the variability and showed overall a small positive radiative effect. The overall effective radiative forcing (ERF) due to aerosol-cloud interactions (ERFaci) in the simulation was dominated thus by the Twomey effect and yielded for this day, region, and aerosol perturbation &#8722;2.6 W&#8201;m-2. Using general circulation models to scale this to a global-mean present-day vs. pre-industrial ERFaci yields a global ERFaci of &#8722;0.8&#8201;W&#8201;m-2.</p

Biodiversity

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