Search

We investigate potential reasons for decadal-scale internal variability of surface solar radiation (SSR) using model data from the Coupled Model Intercomparison Project - Phase 6. We compare unforced coupled atmosphere-ocean (piControl) to atmosphere-only (piClim) simulations with prescribed climatological sea surface temperatures (SSTs) to access the relevance of SSTs for unforced SSR inter-annual variability. Further, the connection between SSTs and known climate modes of variability is exploited. We focus on coupled and ocean-only modes of variability such as El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO). Using the climate indices which describe these modes, we relate the SST field to SSR trends in different regions and we find a relationship between periods with strongly changing SSTs and decadal SSR depending on the regions. Unforced clear-sky SSR trends appear to mimic the SST trend pattern, while all-sky trends show a complex spatial structure with trends opposite in sign in different regions. These results are based only on pre-industrial control simulations (CMIP6 piControl) and can be used to infer in which direction internal variability has affected SSR in the historical period and whether it has enhanced or suppressed the anthropogenic signal from aerosols.

Simple climate models or climate emulators (CEs) are indispensable in the context of climate economics, where the lion share of compute resources is bound to the economic part of the problem. Associated applications traditionally focused on scenarios with strongly increasing carbon emissions. Here we ask to what degree CEs developed with such applications in mind are fit for purpose when it comes to strong reduction or negative emission scenarios, as in the context of the Paris agreement.To this end, we present and discuss an augmented version of the CE used in the seminal DICE model. Augmentation consists of additional carbon reservoirs, notably a land biosphere and / or a middle ocean reservoir, on top of the three standard carbon reservoirs representing atmosphere, upper ocean, and lower ocean. The different CEs are calibrated and tested against output of large-scale Earth System Models from the Coupled Model Intercomparison Project, run on pre-defined emissions scenarios. For the calibration of the CE, we use the same strategy as in our previous work, i.e., two highly idealized test cases to separately calibrate the CE's carbon cycle and temperature response. In contrast to previous work, we strongly augment the set of test cases to which we expose the calibrated CE. Additional test cases address, in particular, strong mitigation as well as negative emission scenarios. As in our previous work, we demand that all test cases are well documented in the climate literature and can be easily implemented based on that literature. Based on these test cases, we discuss what added value the additional carbon reservoirs may offer with regard to the CE and associated econ studies.

Sea Surface Temperature (SST) plays a major role in the unforced variability of the climate system on decadal scales via the interplay between ocean and atmosphere, and associated changes in cloud cover and water vapor. The ocean modes, such as El Nino Southern Oscillation (ENSO) and Interdecadal Pacific Oscillation (IPO), are major coherent manifestations of SST variability. This means that the impacts of the ocean modes might be reflected in several components of the climate system, such as the energy budget. At the surface, this can be observed in the decadal trends in surface solar radiation (SSR). In this study we investigated the impacts of IPO and ENSO and associated cloud cover and water vapor variability on the decadal trends in SSR at 6 island stations scattered in the western Pacific (two stations in Fiji, one in New Caledonia, Nauru, Papua New Guinea and Marshall Islands). We combined between 15 and 40 years of daily SSR observations (depending on the station) with cloud cover from ERA5 reanalysis, aerosol optical depth (AOD) from CAMS reanalysis, and time series of IPO and ENSO. The comparison between clear-sky and all-sky SSR trends show that the all-sky trends strongly dominate in 5 out of the 6 stations. The exception is New Caledonia, where the clear-sky seems to also play an important role in the overall trend. This is the least cloudy station, and also the closest station to eastern Australia, an important source of aerosols in the region. Maps of cloud cover trends show two distinct regions which can be approximately separated by the average climatological position of the South Pacific Convergence Zone (SPCZ): one where cloud cover trends follow the phase of the IPO (positive IPO phase = positive cloud cover trend; N-NE of the SPCZ) and one where the opposite happens (positive IPO phase = negative cloud cover trend; S-SW of the SPCZ). The direct comparison between annual time series of all-sky SSR and IPO shows correlations stronger than 0.5 at two stations in Fiji and the one in New Caledonia (SW of the SPCZ). At the station in Nauru (North of the SPCZ) there is a negative correlation stronger than -0.5. When comparing annual all-sky SSR to the ENSO index, significant negative correlations are found at Momote-Papua New Guinea (-0.41) and at Nauru (-0.96), both located in the Western Pacific Warm Pool, near the Equator. In all cases strong negative correlations (

Solar energy generation is highly volatile during the day due to the strong dependence on cloud dynamics, which limits its integration into the power grid (Smith et al., 2022). On the other hand, higher utilization of renewable energy is essential to tackle climate change. To increase the share of photovoltaic energy in the grid without jeopardizing grid stability, accurate forecasts are essential to ascertain the balance between energy demand and supply (David et al., 2021).Photovoltaic energy production mainly depends on downwelling surface solar radiation (). SSR is accurately measured by pyranometers, but their spatial representativeness is limited to a few kilometers. By estimating the SSR from geostationary satellites, we can cover larger areas with high spatial and temporal resolutions, allowing us to track cloud motion.Previous studies on probabilistic cloud motion focused on optical-flow methods without considering the temporal evolution of clouds as such. We address this issue by presenting a scale-dependent approach to forecast. Our approach is inspired by the works of Bowler et al., 2006 and Pulkkinen et al., 2019 on precipitation nowcasting. The novelty of our study is the utilization of different autoregressive models to forecast the temporal evolution of cloudiness of different spatial scales. Our work is motivated by the scale-dependent predictability of cloud growth and decay. By exploiting more than one autoregressive model, we can predict the noisy evolution of small scales independently of the more deterministic evolution of larger spatial scales.Our preliminary results over Switzerland indicate that our model outperforms the probabilistic advection model based on Carriere et al., 2021 noise generation by reducing the continuously ranked probability score (CRPS) on the test set by 14%. Moreover, we demonstrate the advantage of cloudiness scale decomposition by comparing our model with the same approach without decomposition. We can reduce the CRPS by 6% and the RMSE by 5% by decomposing the images into multiple cascadesReferencesBowler, N., C. Pierce, A. Seed, 2006, “STEPS: A probabilistic precipitation forecasting scheme which merges an extrapolation nowcast with downscaled NWP”, Quarterly Journal of the Royal Meteorological Society, 132, 620, pp. 2127–2155, doi:10.1256/qj.04.100.Carriere, T., R. Amaro e Silva, F. Zhuang, Y. Saint-Drenan, P. Blanc, 2021, “A New Approach for Satellite-Based Probabilistic Solar Forecasting with Cloud Motion Vectors”, Energies, 14, doi:10.3390/en14164951.David, M., M. Luis, P. Lauret, 2018, “Comparison of intraday probabilistic forecasting of solar irradiance using only endogenous data”, International Journal of Forecasting, 34, doi:10.1016/j.ijforecast.2018.02.003.Pulkkinen, S., D. Nerini, A. Perez Hortal, C. Velasco-Forero, A. Seed, U. Germann, L. Foresti, 2019, “Systems: an open-source Python library for probabilistic precipitation nowcasting (v1.0)”, Geoscientific Model Development, 12, 10, pp. 4185–4219, doi:10.5194/gmd-12-4185-2019.Smith, O., O. Cattell, E. Farcot, R. D. O’Dea, K. I. Hopcraft, 2022, “The effect of renewable energy incorporation on power grid stability and resilience”, Science Advances, https://www.science.org/doi/abs/10.1126/sciadv.abj6734.

A plausible simulation of the global energy balance is a first-order requirement for a credible climate model. Therefore we investigate the representation of the global energy balance in the latest generation of global climate models (CMIP6). In the multi-model global mean, the magnitudes of the energy balance components of the CMIP6 models are often in better agreement with our reference estimates (Wild et al. 2015, 2019 Clim Dyn) as well as those from CERES/EBAF and NASA/NEWS than in earlier model generations (Wild 2020). However, the inter-model spread in the representation of many of the components remains substantial, often on the order of 10-20 Wm-2 globally, except for the shortwave clear-sky budgets, which are now more consistently simulated by the CMIP6 models. The substantial inter-model spread in the simulated global mean latent heat fluxes in the CMIP6 models, exceeding 20% (18 Wm-2), further implies also large discrepancies in their representation of the global water balance. From a historic perspective of model development over the past decades, the largest adjustments in the magnitudes of the simulated present-day global mean energy balance components occurred in the shortwave atmospheric clear-sky absorption and the surface downward longwave radiation. Both components were gradually adjusted upwards over several model generations, on the order of 10 Wm-2, to reach 73 and 344 Wm-2, respectively in the CMIP6 multi-model means. Thereby, CMIP6 has become the first model generation that largely remediates long-standing model deficiencies related to an overestimation in surface downward shortwave and compensational underestimation in downward longwave radiation in its global multi-model mean. There are also indications for an overall improvement in the representation of the energy budgets in the CMIP6 models compared to CMIP5 on regional scales (regions considered here as defined by the NASA/NEWS project). Still substantial spreads between the energy balance components of individual CMIP6 models appear also on regional scales (Li et al. 2022). Related references:Wild, M., 2020: The global energy balance as represented in CMIP6 climate models. Clim Dyn., 55, 553–577Li, D., Folini D., Wild, M., 2022: Assessment of regional energy budgets in CMIP6 models, submitted

Decadal-scale unforced climate variability associated with low-frequency ocean (or coupled) modes can be identified within the time-evolving sea surface temperature (SST) pattern. We seek to find a relationship between 12 well-known climate modes of variability (El Niño–Southern Oscillation, Pacific Decadal Oscillation, Atlantic Multidecadal Oscillation, etc.), which are reflected in the SST pattern, and decadal trends in downwelling shortwave radiation at Earth's surface (surface solar radiation, surface shortwave radiation [SSR]). The analysis is performed using the pre-industrial control runs (piControl) of 57 models from the Coupled Model Intercomparison Project—Phase 6. We find that regional SSR trends occur during periods when a climate mode is transitioning and show a mirroring pattern (opposite sign SSR trends) when the mode transitions in the opposite direction. Unforced trends in clear-sky SSR are mostly driven by SST-induced water vapor changes, while all-sky SSR trends show a complex spatial structure with trends of different signs in different regions. Unforced SSR trends are generally weaker in simulations with climatological SSTs. The role of natural aerosols as another potentially relevant factor for SSR variability is briefly addressed and we find that constantly higher aerosol loads result in increased variability for clear-sky conditions, but not for all-sky conditions. The results from this study suggest that all-sky dimming and brightening in different parts of the world are enhanced rather than suppressed by internal variability related to an SST-pattern with the exception of India and China, where both effects are present. A practical application can be the planning of photovoltaic energy facilities given areas where internal variability is generally smaller or affects SSR in opposite directions., Journal of Geophysical Research: Atmospheres, 128 (12), ISSN:0148-0227, ISSN:2169-897X

Accurate intraday forecasts of surface solar radiation (SSR) are essential for utility companies and electricity grid operators. However, satellite SSR estimates can suffer from surprisingly low accuracies on short observation time scales and from significant spatial and temporal biases when compared to ground-based SSR measurements.We present a bias assessment of two high-resolution satellite SSR products for intra-day application time scales. The satellite SSRs are retrieved with the Heliosat SARAH-2 and the HelioMont algorithms (Müller et al., 2015; Stöckli, 2013). We investigate intra-day and intra-hour estimates for altitudes from 200 to 3570 m a.s.l. We make use of 133 ground stations of the high-precision monitoring network SwissMetNet for the bias analysis. For solar zenith angle (SZA) lower than 90 degrees, we find that Heliosat SARAH-2 underestimates SSR at high altitudes (over 1000m) with an instantaneous root mean squared deviation (RMSD) of 179 W/m2and a mean bias deviation (MBD) of -68 W/m2 in the winter half year. The bias magnitude is approximately the double w.r.t. low altitude stations, due to difficulties in distinguishing snow-covered surfaces from clouds.We also present an intra-hour bias correction approach: a deep neural network exploiting time-encoding features to model the bias in the time dimension. Our model achieves up to 30% RMSE reduction in the case of Heliosat SARAH-2, especially in mountainous regions. Moreover, we highlight the importance of the clear-sky index for bias correcting the Heliosat SSR estimates. Including a clear-sky index as a regressor in the bias correction improves the bias correction on average from 15.5% to 21.9% RMSE reduction. We also discuss the relevance of bias correcting satellite-derived SSR maps for short-term forecasting applications of SSR. References Müller, R., U. Pfeifroth, C. Träger-Chatterjee, J. Trentmann, and R. Cremer (2015), Digging the METEOSAT Treasure-3 Decades of Solar Surface Radiation, Remote Sensing, 7(6), 8067-8101, doi:10.3390/rs70608067. Stöckli (2013). The HelioMont Surface Solar Radiation Processing. Scientific Report 93, MeteoSwiss, 122 pp.

Internal variability, a natural source of uncertainty in climate projections, is important when one wants to distinguish between the forced signal and the random noise in the climate system. The downwelling surface solar radiation, a key climate variable, has been shown to exhibit unforced trends (i.e. trends exclusively due to internal variability) even on decadal timescales. These long-term unforced trends interfere with the forced signal and contribute to the decadal variations of SSR, known as global dimming and brightening. A common technique in observation analysis, which serves to reduce the contribution of internal variability and therefore give a better estimate of the forced signal, is the use of composite time series of multiple locations (averaging in space). We use annual mean data of 49 models from the pre-industrial control experiment of the Coupled Model Intercomparison Project – Phase 6 (CMIP6) to give a quantitative estimate of how much the system noise is reduced upon spatial averaging. We find that globally the standard deviation σ (which is proportional to the magnitudes of random trends) is reduced almost linearly with the horizontal grid increment Δx in the range 2 – 15 degrees. On coarser resolutions, deviations from a linear fit are observed, possibly because the patterns of ocean oscillations are not concentrated in compact forms in space. Comparing the rate of reduction of the noise with grid resolution (dσ/dΔx), we find that the noise in all-sky SSR is averaged out ~10 times faster (with increasing Δx) than the noise in clear-sky SSR. Numerical values estimated from the CMIP6 multi-model median and uncertainties estimated from the inter-model spread are dσ/dΔx = -0.11 ± 0.03 Wm-2/deg for all-sky SSR and dσ/dΔx = -0.01 ± 0.004 Wm-2/deg for clear-sky SSR. The all-sky SSR global mean σ for a 0.5 deg grid is 4.79Wm-2, while for clear-sky it is 0.66 Wm-2. Furthermore, dσ/dΔx is strongly dependent on the geographical location, being more than twice as large in China, compared to Europe for both all-sky and clear-sky SSR.

Decadal trends in Surface solar radiation (SSR) have gained attention in the last few decades after several studies identified the non stable behaviour of such measurements. Also referred to as Global Dimming and Global Brightening, these decadal trends are known to be spatially heterogeneous, meaning that different regions might experience different trends, associated with different causes. While measurements have allowed the identification of trends around the world, the understanding of the causes of those trends is limited to a few regional studies mostly focusing on developed countries. The lack of data in developing countries leads to an underrepresentation of those regions in what regards to global dimming and brightening research. In this work, we use around 39 years (1967-2005) of daily SSR measurements of two stations in Zimbabwe, and apply a new method for clear-sky derivation, using satellite cloud fraction to identify optimal daily transmittance thresholds for clear-sky identification. The all-sky and clear-sky time series of SSR are then compared to cloud fraction and water vapor data from ERA5 reanalysis and to aerosol emissions from the EDGAR database. The SSR time series show a persistent dimming of similar magnitude both in all-sky and clear-sky. The cloud fraction does not show any significant trends, reinforcing the hypothesis that the dimming was caused by cloud-free radiative processes in the atmosphere. The water vapour time series also does not show any significant trend which could justify the negative trends in SSR. However, the monthly interannual variability show that the dimming is stronger between July and September, months with higher emission of biomass burning aerosols in that region. This might also indicate an anthropogenic related cause of the dimming observed in southern Africa. This study intends to contribute to the understanding of the global dimming and brightening phenomena in southern Africa, but also to highlight the importance of studies focusing in underrepresented regions of the world.

Accurate maps of surface incoming solar (SIS) radiation are a crucial prerequisite for producing precise solar radiation and photovoltaic power (PV) nowcasts useful to utility companies, grid operators and energy traders. We present a new bias correction approach for satellite-retrieved SIS measurements using deep neural networks with time encoding features, achieving significantly reduced biases on high time resolution data. Moreover, we demonstrate the necessity and the benefits of automated bias correction prior to performing surface radiation and PV nowcasts.We make use of SIS retrieved from the SEVIRI spectrometer onboard the geostationary Meteosat MSG satellite with the HelioMont (Stöckli, 2013) and HelioSat (Müller et al., 2015) algorithms by the CM SAF team. HelioMont comes at a spatial resolution of 0.02x0.02 degrees, while HelioSat provides a resolution of 0.05x0.05 degrees. For the bias correction, we employ high-quality long-term pyranometer measurements from 113 ground stations of one of the densest meteorological networks around the world, the SwissMetNet. The SIS radiations are retrieved at 30-minutes, 15-minutes and 10-minutes resolutions (HelioSat, HelioMont, and SwissMetNet, respectively) for the entire year 2018. We use 46 weeks as training set and 6 weeks as test set, wherein the latter consists of the 3 sunniest and 3 cloudiest weeks of 2018.Our approach involves a multilayer perceptron (MLP) trained to correct the satellite SIS bias by exploiting the predictor variables (time encoding, location features and satellite SIS) and fitting them to predict the ground station SIS. By doing so, we demonstrate that our novel bias correction method can reduce the SIS mean absolute bias (MAB) of both HelioMont and HelioSat by more than 10%. Comparing our results with a standard linear regression (LR) model, we find that the MLP outperforms the LR approach on 112 and 111 SwissMetNet stations for HelioMont and HelioSat, respectively. Moreover, we found that the bias magnitude is significantly correlated with the altitude of the considered location and with the time of year. The biases are largest in mountainous regions that tend to have a higher albedo due snow and ice. In fact, the Pearson correlation between the altitude and the average MAB is 0.76 and 0.80 for HelioMont and HelioSat, respectively. ReferencesR. Stöckli (2013). The HelioMont Surface Solar Radiation Processing. Scientific Report 93, MeteoSwiss, 122 pp. Müller, R., U. Pfeifroth, C. Träger-Chatterjee, J. Trentmann, and R. Cremer (2015), Digging the METEOSAT Treasure-3 Decades of Solar Surface Radiation, Remote Sensing, 7(6), 8067-8101, doi:10.3390/rs70608067.

Near-surface winds affect many processes on planet Earth, ranging from fundamental biological mechanisms such as pollination to man-made infrastructure that is designed to resist or harness wind. The observed systematic wind speed decline up to around 2010 (stilling) and its subsequent recovery have therefore attracted much attention. While this sequence of downward and upwards trends and good connections to well-established modes of climate variability suggest that stilling could be a manifestation of multidecadal climate variability, a systematic investigation is currently lacking. Here, we use the Max Planck Institute Grand Ensemble (MPI-GE) to decompose internal variability from forced changes in wind speeds. We report that wind speed changes resembling observed stilling and its recovery are well in line with internal climate variability, both under current and future climate conditions. Moreover, internal climate variability outweighs forced changes in wind speeds on 20-year timescales by 1 order of magnitude, despite the fact that smaller, forced changes become relevant in the long run as they represent alterations of mean states. In this regard, we reveal that land use change plays a pivotal role in explaining MPI-GE ensemble-mean wind changes in the representative concentration pathways 2.6, 4.5, and 8.5. Our results demonstrate that multidecadal wind speed variability is of greater relevance than forced changes over the 21st century, in particular for wind-related infrastructure like wind energy., Earth System Dynamics, 12 (4), ISSN:2190-4987, ISSN:2190-4979

We use the best currently available in situ and satellite-derived surface and top-of-the-atmosphere (TOA) shortwave radiation observations to explore climatological annual cycles of fractional (i.e., normalized by incoming radiation at the TOA) atmospheric shortwave absorption [Formula: see text] on a global scale. The analysis reveals that [Formula: see text] is a rather regional feature where the reported nonexisting [Formula: see text] in Europe is an exception rather than the rule. In several regions, large and distinctively different [Formula: see text] are apparent. The magnitudes of [Formula: see text] reach values up to 10% in some regions, which is substantial given that the long-term global mean atmospheric shortwave absorption is roughly 23%. Water vapor and aerosols are identified as major drivers for [Formula: see text] while clouds seem to play only a minor role for [Formula: see text]. Regions with large annual cycles in aerosol emissions from biomass burning also show the largest [Formula: see text]. As biomass burning is generally related to human activities, [Formula: see text] is likely also anthropogenically intensified or forced in the respective regions. We also test if climate models are able to simulate the observed pattern of [Formula: see text]. In regions where [Formula: see text] is driven by the annual cycle of natural aerosols or water vapor, the models perform well. In regions with large [Formula: see text] induced by biomass-burning aerosols, the models’ performance is very limited.

Using projections of surface solar radiation and temperature from 23 CMIP5 global climate models for two climate change scenarios (RCP4.5 & 8.5) we quantify the average change in PV electricity production expected in the years 2060–2080 compared to the present (2007–2027). We upsample daily radiation data to hourly resolution with a sinusoidal diurnal cycle model and split it into direct and diffuse radiation with the semi-empirical BRL model as input to a PV electricity generation model. Locally, changes in PV potential from −6% to +3% in annual and −25% to +10% in monthly means are shown. These projections are combined with a PV deployment scenario and show countries benefitting from increased PV yields include Spain, France, Italy and Germany. We also calculate uncertainties when calculating PV yield with input data at daily or lower resolution, demonstrating that our method to derive synthetic hourly profiles should be of use for other researchers using input data with low temporal resolution. We conclude that PV is an attractive and no-regrets investment in Europe irrespective of future climate change, and can continue to play a key role in energy system decarbonisation.

We analyze the evolution of inter-hemispheric asymmetries in the energy budgets (EBs) and near-surface temperature anomalies during the 20th century, as given in Coupled Model Inter-comparison Project, phase 5 (CMIP5) simulations. We also consider the cross-equatorial energy transports (CET) in the atmosphere and in the oceans, in order to evidence how EB asymmetries affect the redistribution of energy between the two hemispheres. Two different experimental settings have been considered, one including only the spatially homogeneous evolving greenhouse gas forcing (GHG), and another one a realistic superposition of all known evolving forcings (ALL), such as aerosols and volcanic eruptions. This study shows that, according to the CMIP5 models, the response of the climate system to the ongoing forcing during the 20th century has differed substantially from what would have resulted from an increase in GHG concentration alone. In the GHG ensemble the Northern Hemisphere (NH) warms more than the Southern Hemisphere (SH), while both hemispheres exhibit similar and positive EB anomalies at the TOA, mainly due to increasing shortwave absorption and with no significant variations of cross-equatorial energy transports. On the contrary, in the ALL ensemble the two hemispheres warm similarly, while the SH exhibits a positive EB anomaly twice as large as in the NH, due to a reduced LW emission (Outgoing Longwave Radiation, OLR) in the SH, with oceanic CET anomalies directed towards the NH. The EB asymmetry in ALL is ascribed to the asymmetry in OLR changes, which is explained by the different role of clouds in the two hemispheres. The ocean heat content (OHC) tendency per unit surface area is similar in the two hemispheres, so that the asymmetries in ALL EB determine CET changes. We evidence that CET changes in the ALL ensemble are associated with the inter-hemispheric asymmetry in the aerosol forcing, which is stronger in the NH than in the SH. We find no significant relation between CETs and inter-hemispheric near-surface temperature asymmetries in GHG, partly due to the large model spread. Generally, deficits in modeled CET for present-day conditions are not ascribed to forcings and feedbacks, rather they are intrinsic to the models.

Solar radiation is the primary source of energy for the climate system and a variety of biological processes on the planet. In that sense, understanding the radiative processes in the atmosphere and identifying the governing factors of these processes is key for climate diagnosis and prognosis. In this work, we use daily in-situ observations from 528 stations over Europe from the World Radiation Data Centre (WRDC) database, to analyze Surface Solar Radiation (SSR) trends from 1964 until 2018 in all regions of the continent. Statistical methods were applied to quality-control the dataset: detecting and removing outliers, homogenization and gap-filling of the time series. Two different statistical approaches for identification of clear-sky conditions were applied and compared. Observations in most of the regions on the European continent agree with previously observed negative trends (diming) until the 80’s, followed by positive SSR trends (brightening) from then on, continuing until recent years. However, the regime shifts and the intensity of the trends are not homogeneous within the continent, indicating that regional aspects have non-negligible impacts on the SSR behavior. The comparison between all-sky and clear-sky SSR observations helps to identify to what extent the clouds were a relevant factor in the observed trends in every part of the continent. With this type of analysis we intend to not only present the SSR trends over Europe, but also to expand the comprehension of their spatial heterogeneity across the continent, as well as their causes.

Quantifying trends in surface solar radiation (SSR) of unforced simulations is of substantial importance when one tries to quantify the anthropogenic effect in forced trends, as the net effect may be dampened or amplified by the internal variability of the system. In our analysis, we consider trends on different temporal scales (10, 30, 50 and 100 years) from 58 global climate models, participating in the Coupled Model Intercomparison Project - Phase 6 (CMIP6). We calculate the trends at the grid-box level for all-sky and clear-sky SSR using annual mean data of the multi-century pre-industrial control (piControl) experiments. The trends from both variables are found to depend strongly on the geographical region, as the most pronounced trends of the all-sky variable are observed in the Tropical Pacific, while the largest clear-sky trends are found in the large desert regions. Inspecting for each grid cell the statistical distribution of occurring N-year trends shows that they are normally distributed in the majority of grid cells for both all-sky and clear-sky SSR. The 75-th percentile taken from these distributions (i.e. a positive trend with a 25 % chance of occurrence) varies with geographical region, taking values in the ranges 0.79 - 12.03 Wm-2/decade for 10-year trends, 0.15 - 2.05 Wm-2/decade for 30-year trends, 0.07 - 0.92 Wm-2/decade for 50-year trends and 0.02 - 0.29 Wm-2/decade for 100-year trends for all-sky SSR. The unforced trends become less significant on longer timescales – the trend medians, corresponding to the above ranges, are 3.18 Wm-2/decade, 0.62 Wm-2/decade, 0.29 Wm-2/decade, 0.10 Wm-2/decade respectively. The trends for clear-sky SSR are found to differ from the all-sky SSR by a factor of 0.16 on average, independent of the trend length. The model spread becomes greater at longer trend timescales, the differences being more substantial between large model families rather than between individual models. To elucidate the dominant causes of variability in different regions, we examine the correlations of the SSR variables with ambient aerosol optical thickness at 550 nm, atmosphere mass content of water vapour, cloud area fraction and albedo.

We develop a generic and transparent calibration strategy for climate models used in economics. The key idea is to choose the free model parameters to match the output of large-scale Earth System Models, which are run on pre-defined future emissions scenarios and collected in the Coupled Model Intercomparison Project, Phase 5 (CMIP5). We propose to jointly use four different test cases that are considered pivotal in the climate science literature. Two of these tests are highly idealized to allow for the separate quantitative examination of the carbon cycle and the temperature response. Another two tests are closer to the scenarios that arise from economic models. They test the climate module as a whole, that is, they incorporate gradual changes in CO2 emissions, exogenous forcing, and ultimately the temperature response. To illustrate the applicability of our method, we re-calibrate the free parameters of the climate part of the seminal DICE-2016 model for three different CMIP5 model responses: the multi-model mean as well as two other CMIP5 models that exhibit extreme but still permissible equilibrium climate sensitivities. As an additional novelty, our calibrations of DICE-2016 allow for an arbitrary time step in the model explicitly. By applying our comprehensive suite of tests, we show that i) both the temperature equations and the carbon cycle in DICE-2016 are miscalibrated and that ii) by re-calibrating their coefficients, we can match all CMIP5 targets we consider. Finally, we apply the economic model from DICE-2016 in combination with the newly calibrated climate model to compute the social cost of carbon and the optimal warming. We find that in our updated model, the social cost of carbon is similar to DICE-2016. However, the optimal long-run temperature in our calibration lies almost one degree below that obtained by DICE-2016. Moreover, the social cost of carbon turns out to be much less sensitive to the discount rate than in DICE-2016. We explain how the model's climate part relates to these differences and also show that under the optimal mitigation scenario, the temperature predictions of DICE-2016 (in contrast to our proposed calibration) fall outside of the CMIP5 scenarios, suggesting that one might want to be skeptical about policy predictions derived from DICE-2016.

We develop a generic and transparent calibration strategy for simple climate models used in economics. The goal is to choose the free model parameters such as to best match the output of large-scale Earth System Models from the Coupled Model Intercomparison Project, run on pre-defined emissions scenarios. We propose to jointly use four different test cases that are considered pivotal in the climate science literature: two highly idealized tests to separately examine the carbon cycle and the temperature response, and two tests closer to real scenarios, incorporating gradual changes in CO2 emissions and exogenous forcings.To illustrate the applicability of our method, we re-calibrate the free parameters of the climate part of the seminal DICE-2016 model for three different CMIP5 model responses: the multi-model mean as well as two CMIP5 models that exhibit extreme but still permissible equilibrium climate sensitivities. As an additional novelty, our calibrations of DICE-2016 allow for an arbitrary time step in the model explicitly. By applying our comprehensive suite of tests, we i) confirm that both the temperature equations and the carbon cycle in DICE-2016 are miscalibrated and ii) we show that by re-calibrating coefficients all CMIP5 targets considered can be well matched.Finally, we apply the economic model from DICE-2016 in combination with the newly calibrated climate model to compute the social cost of carbon and optimal warming. We find the social cost of carbon to be similar to DICE-2016, while the optimal long-run temperature is almost one degree lower. The social cost of carbon turns out to be much less sensitive to the discount rate than in DICE-2016. We explain how the model's climate part relates to these differences. As the temperature in DICE-2016 under optimal mitigation falls outside the range of CMIP5 projections, we caution that one might want to be skeptical about policy advice based on DICE-2016.

The current pandemic of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is having negative health, social and economic consequences worldwide. In Europe, the pandemic started to develop strongly at the end of February and beginning of March 2020. Subsequently, it spread over the continent, with special virulence in northern Italy and inland Spain. In this study we show that an unusual persistent anticyclonic situation prevailing in southwestern Europe during February 2020 (i.e. anomalously strong positive phase of the North Atlantic and Arctic Oscillations) could have resulted in favorable conditions, e.g., in terms of air temperature and humidity among other factors, in Italy and Spain for a quicker spread of the virus compared with the rest of the European countries. It seems plausible that the strong atmospheric stability and associated dry conditions that dominated in these regions may have favored the virus propagation, both outdoors and especially indoors, by short-range droplet and aerosol (airborne) transmission, or/and by changing social contact patterns. Later recent atmospheric circulation conditions in Europe (July 2020) and the U.S. (October 2020) seem to support our hypothesis, although further research is needed in order to evaluate other confounding variables. Interestingly, the atmospheric conditions during the Spanish flu pandemic in 1918 seem to have resembled at some stage with the current COVID-19 pandemic., Highlights • First study to explore the effects of large-scale atmospheric patterns on COVID-19. • Anticyclonic conditions could have favored early spread of COVID-19 over Europe. • Transmission by droplets and/or aerosols, and social contact could be enhanced. • Resemblances with spatial and atmospheric conditions during the 1918 Spanish flu.

We explore the ability of general circulation models in the Coupled Model Intercomparison Project (CMIP5) to recreate observed seasonal variability in top‐of‐the‐atmosphere and surface radiation fluxes over West Africa. This tests CMIP5 models' ability to describe the radiative energy partitioning, which is fundamental to our understanding of the current climate and its future changes. We use 15 years of the monthly Clouds and the Earth's Radiant Energy System Energy Balanced and Filled (EBAF) product, alongside other satellite, reanalysis, and surface station products. We find that the CMIP5 multimodel mean is generally within the reference product range, with annual mean CMIP5 multimodel mean—EBAF of −0.5 W m−2 for top‐of‐the‐atmosphere reflected shortwave radiation, and 4.6 W m−2 in outgoing longwave radiation over West Africa. However, the range in annual mean of the model seasonal cycles is large (37.2 and 34.0 W m−2 for reflected shortwave radiation and outgoing longwave radiation, respectively). We use seasonal and regional contrasts in all‐sky fluxes to infer that the representation of the West African monsoon in numerical models affects radiative energy partitioning. Using clear‐sky surface fluxes, we find that the models tend to have more downwelling shortwave and less downwelling longwave radiation than EBAF, consistent with past research. We find models that are drier and have lower aerosol loading tend to show the largest differences. We find evidence that aerosol variability has a larger effect in modulating downwelling shortwave radiation than water vapor in EBAF, while the opposite effect is seen in the majority of CMIP5 models., Earth and Space Science, 7 (5), ISSN:2333-5084

The current pandemic caused by the coronavirus SARS-CoV-2 is having negative health, social and economic consequences worldwide. In Europe, the pandemic started to develop strongly at the end of February and beginning of March 2020. It has subsequently spread over the continent, with special virulence in northern Italy and inland Spain. In this study we show that an unusual persistent anticyclonic situation prevailing in southwestern Europe during February 2020 (i.e. anomalously strong positive phase of the North Atlantic and Arctic Oscillations) could have resulted in favorable conditions, in terms of air temperature and humidity, in Italy and Spain for a quicker spread of the virus compared with the rest of the European countries. It seems plausible that the strong atmospheric stability and associated dry conditions that dominated in these regions may have favored the virus's propagation, by short-range droplet transmission as well as likely by long-range aerosol (airborne) transmission., 22 pages, 4 figures, Supplementary Information with 8 figures

Results on the statistical properties of internal variability of annual mean surface solar radiation (SSR) and associated decadal scale trends are presented, following in part Folini et al. 2017 (doi:10.1002/2016JD025869). Estimates are based on 43 pre-industrial control (piControl) experiments of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Trends are shown to depend strongly on geographical region and on whether they are quantified in absolute units or relative to the long term mean SSR. Providing one map for absolute and one map for relative trends is sufficient, as approximate analytical relations are shown to hold between trends of different length and likelihood and the standard deviation of the underlying SSR time series. Comparison with present-day observations and inter-model spread suggest an average uncertainty of these estimates of about 30%. Intermodel spread suggests that regional uncertainties can be up to about three times larger or smaller. Using the model by Crook et al. 2011 (doi:10.1039/C1EE01495A) to translate SSR into PV production, associated internal variability of photo voltaic (PV) energy production is inferred. Results suggest that it is plausible for PV production to change by several per cent over a decade just because of internal variability.

There is growing evidence that the amount of solar radiation at the Earth’s surface is not stable over time but undergoes substantial multidecadal variations. Particularly, a decrease in surface solar radiation has been noted from the 1950s to the 1980s at widespread observation sites, a phenomenon popularly known as “global (solar) dimming”, followed by a partial recovery known as “brightening”. An interesting hotspot in this context is China, where surface solar radiation (SSR) underwent particularly large changes over the past decades.Here we discuss our latest studies, which shed new light on the magnitude, causes and implications of this phenomenon in China. The focus is on recent developments, which indicate, that after decades of decline in surface solar radiation, some recovery can be noted since the mid-2000s in the SSR records observed by the Chinese Meteorological Agency. This recovery is not seen in satellite derived records, which assume a constant aerosol climatology in their retrieval algorithm, suggesting the necessity for a decrease in aerosol to reconcile the diverging trends (Wang et al., 2019). This is independently supported by an analysis of SSR trends specifically in the cloud-free atmosphere, which show a turn into increase since around 2006, also suggesting a reduction of aerosol over China in recent years (Yang et al., 2019).In a further study, the combination of the Chinese SSR observations with collocated space-based measurements of the net solar exchanges at the Top of Atmosphere from CERES enabled the determination of changes in solar absorption within the atmospheric column as a residual over recent decades. The results suggest that the recent brightening in China is predominately caused by a weakening of the solar absorption within the atmosphere. This indicates that a reduction of particularly the absorbing aerosol must have taken place in recent years (Schwarz et al., 2020).In summary, all these studies provide independent evidence that air pollution mitigation efforts in China have successfully induced a trend reversal in the amount of solar radiation reaching the Earth’s surface, with some recovery in recent years after decades of dimming.We further estimated that, if such a recovery could persist and air pollution levels could eventually be reduced down to the pristine 1960s levels in China, this would have major benefits for Chinese photovoltaic (PV) solar power production, which could be enhanced by as much as 13 %. With the PV capacity currently installed in China, and as projected for the year 2030, this would correspond to a yearly economic benefit of 2 and 6 billion US dollars, respectively, assuming current electricity prices (Sweerts et al., 2019).ReferencesYang, S., Wang, X.L., Wild, M. (2018) J. Climate 31, 4529-4541.Yang, S., Wang, X.L., Wild, M. (2019) J. Climate 32, 5901-5913.Sweerts, B., Pfenninger, S., Yang, S., Folini, D., vanderZwaan, B., Wild, M. (2019) Nature Energy 4, 657-663.Wang, Y., Trentmann, Y., Pfeifroth, U., Yuan, W., Wild, M. (2019) Remote Sens. 11, 2910.Schwarz, M., Folini, D., Yang, S., Allan, R.P., and Wild, M. (2020) Nature Geoscience (in press)

The amount of solar (shortwave) radiation that reaches the Earth’s surface underwent substantial variations over recent decades. Since the 1950s, surface shortwave radiation gradually decreased at widespread locations. In Europe, this so-called surface dimming continued until the late 1980s, when surface brightening set in and surface shortwave radiation increased again. In China, the dimming levelled off in the 1980s, but did not turn into brightening until 2005. Changes in clouds and aerosol are the prime potential causes for the phenomenon, but the scientific community has not yet reached a consensus about the relative role of the different potential forcing agents. Here we bring together co-located long-term observational data from surface and space to study decadal changes of the shortwave energy balance in Europe and China from 1985 to 2015. Within this observation-based framework, we show that an increasing net shortwave radiation at the top of the atmosphere and a decreasing atmospheric shortwave absorption each contribute roughly half of the observed brightening trends in Europe. For China, we find that the continued dimming until 2005 and the subsequent brightening occurred despite opposing trends in the top-of-the-atmosphere net shortwave radiation. This shows that changes in atmospheric shortwave absorption are a major driver of European brightening and the dominant cause for the Chinese surface trends. Although the observed variations cannot be attributed unambiguously, we discuss potential causes for the observed changes. Changes in the atmospheric absorption of shortwave radiation, probably through cloud and aerosol effects, is the main reason for the dimming and brightening over China and Europe in past decades, according to co-located surface and space observations.

Context. Relativistic jets are ubiquitous in astrophysics. High Mass Microquasars (HMMQs) are useful labs to study such jets, as they are relatively close and evolve over observable time scales. The ambient medium into which the jet propagates is, however, far from homogeneous. Corresponding simulation studies to date consider various forms of a wind-shaped ambient medium but typically neglect radiative cooling and relativistic effects. Aims. We investigate the dynamical and structural effects of radiative losses and system parameters on relativistic jets in HMMQs, from the jet launch to its propagation over several tens of orbital separations. Methods. We use 3D relativistic hydrodynamical simulations including parameterized radiative cooling derived from relativistic thermal plasma distribution to carry out parameter studies around two fiducial cases inspired by Cygnus X-1 and Cygnus X-3. Results. Radiative losses are found to be more relevant in Cygnus X-3 than Cygnus X-1. Varying jet power, jet temperature, or the wind of the donor star tends to have a larger impact at early times, when the jet forms and instabilities initially develop, than at later times when the jet has reached a turbulent state. Conclusions. Radiative losses may be dynamically and structurally relevant at least in Cygnus X-3 case, and thus should be examined in more detail., Comment: 28 pages, 25 figures, 8 tables. Accepted for publication in A&A

The Global Energy Balance Archive (GEBA) is a database for the central storage of the worldwide measured energy fluxes at the Earth's surface, maintained at ETH Zurich (Switzerland). This paper documents the status of the GEBA version 2017 dataset, presents the new web interface and user access, and reviews the scientific impact that GEBA data had in various applications. GEBA has continuously been expanded and updated and contains in its 2017 version around 500 000 monthly mean entries of various surface energy balance components measured at 2500 locations. The database contains observations from 15 surface energy flux components, with the most widely measured quantity available in GEBA being the shortwave radiation incident at the Earth's surface (global radiation). Many of the historic records extend over several decades. GEBA contains monthly data from a variety of sources, namely from the World Radiation Data Centre (WRDC) in St. Petersburg, from national weather services, from different research networks (BSRN, ARM, SURFRAD), from peer-reviewed publications, project and data reports, and from personal communications. Quality checks are applied to test for gross errors in the dataset. GEBA has played a key role in various research applications, such as in the quantification of the global energy balance, in the discussion of the anomalous atmospheric shortwave absorption, and in the detection of multi-decadal variations in global radiation, known as global dimming and brightening. GEBA is further extensively used for the evaluation of climate models and satellite-derived surface flux products. On a more applied level, GEBA provides the basis for engineering applications in the context of solar power generation, water management, agricultural production and tourism. GEBA is publicly accessible through the internet via http://www.geba.ethz.ch. Supplementary data are available at https://doi.org/10.1594/PANGAEA.873078.

The process of parameter estimation targeting a chosen set of observations is an essential aspect of numerical modeling. This process is usually named tuning in the climate modeling community. In climate models, the variety and complexity of physical processes involved, and their interplay through a wide range of spatial and temporal scales, must be summarized in a series of approximate submodels. Most submodels depend on uncertain parameters. Tuning consists of adjusting the values of these parameters to bring the solution as a whole into line with aspects of the observed climate. Tuning is an essential aspect of climate modeling with its own scientific issues, which is probably not advertised enough outside the community of model developers. Optimization of climate models raises important questions about whether tuning methods a priori constrain the model results in unintended ways that would affect our confidence in climate projections. Here, we present the definition and rationale behind model tuning, review specific methodological aspects, and survey the diversity of tuning approaches used in current climate models. We also discuss the challenges and opportunities in applying so-called objective methods in climate model tuning. We discuss how tuning methodologies may affect fundamental results of climate models, such as climate sensitivity. The article concludes with a series of recommendations to make the process of climate model tuning more transparent.

We consider decadal scale trends of annual mean all sky surface solar radiation (SSR) that occur solely because of internal variability of the climate system. We give statistical estimates of their magnitude and probability of occurrence. The estimates are based on 43 pre-industrial control (piControl) experiments of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Trends are found to depend strongly on geographical region and on whether they are quantified in absolute units or relative to the long term mean SSR. We find it to be sufficient to provide one map for absolute and one for relative trends, as approximate analytical relations are shown to hold between trends of different length and likelihood and the standard deviation of the underlying SSR time series. We estimate that a positive trend over 30 years and with 25% chance of occurrence (75th percentile of all possible trends) has a magnitude between 0.15 and 1.7 W/m2/decade or 0.11 and 1.4 percent of long term mean SSR per decade, depending on geographical location. Comparison with present-day observations and inter-model spread suggest an average uncertainty of these estimates of about 30%. Intermodel spread suggests that regional uncertainties can be up to about three times larger or smaller. We give examples of how these results may be used to obtain statistical estimates of how (un-)likely it is that observed SSR trends or part thereof are due to internal variability alone.

China is the largest worldwide consumer of solar photovoltaic (PV) electricity, with 130 GW of installed capacity as of 2017. China’s PV capacity is expected to reach at least 400 GW by 2030, to provide 10% of its primary energy. However, anthropogenic aerosol emissions and changes in cloud cover affect solar radiation in China. Here, we use observational radiation data from 119 stations across China to show that the PV potential decreased on average by 11–15% between 1960 and 2015. The relationship between observed surface radiation and emissions of sulfur dioxide and black carbon suggests that strict air pollution control measures, combined with reduced fossil fuel consumption, would allow surface radiation to increase. We find that reverting back to 1960s radiation levels in China could yield a 12–13% increase in electricity generation, equivalent to an additional 14 TWh produced with 2016 PV capacities, and 51–74 TWh with the expected 2030 capacities. The corresponding economic benefits could amount to US$1.9 billion in 2016 and US$4.6–6.7 billion in 2030.

We present the results from a particle-in-cell (PIC) simulation that models the interaction between a spatially localized electron-positron cloud and an electron-ion plasma. The latter is permeated by a magnetic field that is initially spatially uniform and aligned with the mean velocity vector of the pair cloud. The pair cloud expels the magnetic field and piles it up into an electromagnetic piston. Its electromagnetic field is strong enough to separate the pair cloud from the ambient plasma in the direction that is perpendicular to the cloud propagation direction. The piston propagates away from the spine of the injected pair cloud and it accelerates the protons to a high nonrelativistic speed. The accelerated protons form an outer cocoon that will eventually become separated from the unperturbed ambient plasma by a fast magnetosonic shock. No electromagnetic piston forms at the front of the cloud and a shock is mediated here by the filamentation instability. The final plasma distribution resembles that of a hydrodynamic jet. Collisionless plasma jets may form in the coronal plasma of accreting black holes and the interaction between the strong magnetic field of the piston and the hot pair cloud may contribute to radio emissions by such objects., Comment: Accepted for publication by the Proceedings of Science. 10 pages, 4 figures

In recent studies we quantified the global mean Earth energy balance based on direct observations from surface and space. Here we infer complementary reference estimates for its components specifically under cloud-free conditions. While the clear-sky fluxes at the top of atmosphere (TOA) are accurately known from satellite measurements, the corresponding fluxes at the Earth’s surface are not equally well established, as they cannot be directly measured from space. This is also evident in 38 global climate models from CMIP5, which are shown to greatly vary in their clear-sky surface radiation budgets. To better constrain the latter, we established new clear-sky reference climatologies of surface downward shortwave and longwave radiative fluxes from worldwide distributed Baseline Surface Radiation Network sites. 33 out of the 38 CMIP5 models overestimate the clear-sky downward shortwave reference climatologies, whereas both substantial overestimations and underestimations are found in the longwave counterparts in some of the models. From the bias structure of the CMIP5 models we infer best estimates for the global mean surface downward clear-sky shortwave and longwave radiation, at 247 and 314 Wm−2, respectively. With a global mean surface albedo of 13.5% and net shortwave clear-sky flux of 287 Wm−2 at the TOA this results in a global mean clear-sky surface and atmospheric shortwave absorption of 214 and 73 Wm−2, respectively. From the newly-established diagrams of the global energy balance under clear-sky and all-sky conditions, we quantify the cloud radiative effects not only at the TOA, but also within the atmosphere and at the surface. ISSN:0930-7575 ISSN:1432-0894

We study the effect a guiding magnetic field has on the formation and structure of a pair jet that propagates through a collisionless electron-proton plasma at rest. We model with a PIC simulation a pair cloud with the temperature 400 keV and mean speed 0.9c. The cloud propagates through a spatially uniform, magnetized and cool ambient electron-proton plasma that is at rest. Its mean velocity vector is aligned with the background magnetic field. A jet forms in time. Its outer cocoon consists of jet-accelerated ambient plasma and is separated from the inner cocoon by an electromagnetic piston with a thickness that is comparable to the thermal gyroradius of jet particles. A supercritical fast magnetosonic shock will form between the pristine ambient plasma and the jet-accelerated one on a time scale that exceeds our simulation time by an order of magnitude. The inner cocoon is pair plasma that lost its directed flow energy while it swept out the background magnetic field. A beam of electrons and positrons moves along the jet spine at its initial speed. Its electrons are slowed down and some positrons are accelerated as they cross the jet's head. The latter escape upstream along the magnetic field, which yields an excess of MeV positrons ahead of the jet. Some of the protons, which were located behind the electromagnetic piston at the time it formed, are accelerated to MeV energies, 12 pages, 15 figures, accepted for publication by Astronomy and Astrophysics

International audience; We study with a 1D particle-in-cell (PIC) simulation the evolution of a subcritical perpendicular fast magnetosonic shock. The shock propagates at 1.5 times the fast magnetosonic speed. Some upstream protons are reflected by the shock's electric potential. They form a beam which carries less energy than those that are reflected magnetically by super-critical shocks. The beam triggers the growth of a fast magnetosonic solitary wave upstream of the shock, which reflects the beam protons back to the shock. Extracting the momentum and energy of this beam allows the solitary wave to grow into a proto-shock that is trailed by a short downstream region. Protons from the shock-reflected proton beam increase the density of the plasma between the shock and the proto-shock reducing its potential difference relative to both surrounding structures. Bulk protons, which cross the proto-shock, react to the decreased potential jump. The plasma behind the proto-shock accelerates and so does the shock. The trailing end of the proto-shock speeds up in order to continue reflecting the beam protons and eventually it catches up with its front; the proto-shock collapses and the self-reformation fails. A more energetic proton beam could decrease the potential jump across the shock, let it collapse and replace it with the proto-shock.

Characterizing stellar convection in multiple dimensions is a topic at the forefront of stellar astrophysics. Numerical simulations are an essential tool for this task. We present an extension of the existing numerical tool-kit A-MaZe that enables such simulations of stratified flows in a gravitational field. The finite-volume based, cell-centered, and time-explicit hydrodynamics solver of A-MaZe was extended such that the scheme is now well-balanced in both momentum and energy. The algorithm maintains an initially static balance between gravity and pressure to machine precision. Quasi-stationary convection in slab-geometry preserves gas energy (internal plus kinetic) on average, despite strong local up- and down-drafts. By contrast, a more standard numerical scheme is demonstrated to result in substantial gains of energy within a short time on purely numerical grounds. The test is further used to point out the role of dimensionality, viscosity, and Rayleigh number for compressible convection. Applications to a young sun in 2D and 3D, covering a part of the inner radiative zone, as well as the outer convective zone, demonstrate that the scheme meets its initial design goal. Comparison with results obtained for a physically identical setup with a time-implicit code show qualitative agreement., Astronomy & Astrophysics, 630, ISSN:0004-6361, ISSN:1432-0746

Over Europe, a recent study found the fractional all-sky atmospheric solar absorption to be largely unaffected by variations in latitude, remaining nearly constant at its regional mean of 23% ± 1%, relative to the respective top-of-atmosphere insolation. The satellite-based CERES EBAF dataset (2000–10) confirms the weak latitude dependence within 23% ± 2%, representative of the near-global scale between 60°S and 60°N. Under clear-sky conditions, the fractional absorption follows the spatial imprint of the water vapor path, peaking in the tropics and decreasing toward the poles, accompanied by a slight hemispheric asymmetry. In the northern extratropics, the clear-sky absorption attains zonal near-constancy due to combined water vapor, surface albedo, and aerosol effects that are largely amiss in the Southern Hemisphere. In line with earlier studies, the CERES EBAF suggests an increase in atmospheric solar absorption due to clouds by on average 1.5% (5 W m−2) from 21.5% (78 W m−2) under clear-sky conditions to 23% (83 W m−2) under all-sky conditions (60°S–60°N). The low-level clouds in the extratropics act to enhance the absorption, whereas the high clouds in the tropics exhibit a near-zero effect. Consequently, clouds reduce the latitude dependence of fractional atmospheric solar absorption and yield a near-constant zonal mean pattern under all-sky conditions. In the GEWEX-SRB satellite product and the historical simulations from phase 5 of CMIP (CMIP5; 1996–2005, multimodel mean) the amount of insolation absorbed by the atmosphere is reduced by around −1.3% (5 W m−2) with respect to the CERES EBAF mean. The zonal variability and magnitude of the atmospheric cloud effect are, however, largely in line.

Tropical land mean surface air temperature and precipitation responses to the eruptions of El Chichón in 1982 and Pinatubo in 1991, as simulated by the atmosphere-only GCMs (AMIP) in phase 5 of the Coupled Model Intercomparison Project (CMIP5), are examined and compared to three observational datasets. The El Niño–Southern Oscillation (ENSO) signal was statistically separated from the volcanic signal in all time series. Focusing on the ENSO signal, it was found that the 17 investigated AMIP models successfully simulate the observed 4-month delay in the temperature responses to the ENSO phase but simulate somewhat too-fast precipitation responses during the El Niño onset stage. The observed correlation between temperature and ENSO phase (correlation coefficient of 0.75) is generally captured well by the models (simulated correlation of 0.71 and ensemble means of 0.61–0.83). For precipitation, mean correlations with the ENSO phase are −0.59 for observations and −0.53 for the models, with individual ensemble members having correlations as low as −0.26. Observed, ENSO-removed tropical land temperature and precipitation decrease by about 0.35 K and 0.25 mm day−1 after the Pinatubo eruption, while no significant decrease in either variable was observed after El Chichón. The AMIP models generally capture this behavior despite a tendency to overestimate the precipitation response to El Chichón. Scatter is substantial, both across models and across ensemble members of individual models. Natural variability thus may still play a prominent role despite the strong volcanic forcing.

It is debated to what extent surface solar radiation (SSR) changes through varying anthropogenic aerosol emissions since industrialization affected surface temperatures (tsurf). We use mixed-layer ocean experiments with the general circulation model ECHAM6.1 and explicit aerosols (HAM2.2) to identify regions where this effect is discernible. For each decade from 1870 to 2000 we derive three equilibria: anthropogenic aerosol emissions and greenhouse gas concentrations at the respective decade's levels (ALL), either aerosols or greenhouse gases fixed at year 1850 levels (GHG and AERO). We duplicated parts of the experiments with different prescribed divergence of ocean heat transport (Q_ALL, Q_AERO, and Q_GHG). Comparing year 2000 with year 1870 equilibria, we find global average cooling of −1.4 K for AERO and warming of 1.4 K for GHG. ALL and Q_ALL warm by 0.6 K and 0.4 K, respectively. The way divergence of ocean heat transport is prescribed thus matters. Pattern correlations of year 2000 tsurf responses in ALL with the sum of AERO and GHG are higher (0.88) than with Q_ALL (0.71) confirming additivity of global patterns, but not of global means. The imprint of anthropogenic aerosols on tsurf response patterns in ALL is distinct, thus potentially detectable. Over the decades, ocean fractions affected by either changing aerosol optical depth or all-sky SSR vary in concert, supporting linkage between anthropogenic aerosols and all-sky SSR. SSR changes and tsurf responses are marginally collocated. Oceanic regions with strongest tsurf response to aerosol-induced SSR changes are the northern midlatitudes and North Pacific with tsurf sensitivities up to −0.7 K W m−2 SSR change.

We study with a two-dimensional particle-in-cell simulation the stability of a discontinuity or piston, which separates an electron-positron cloud from a cooler electron-proton plasma. Such a piston might be present in the relativistic jets of accreting black holes separating the jet material from the surrounding ambient plasma and when pair clouds form during an X-ray flare and expand into the plasma of the accretion disk corona. We inject a pair plasma at a simulation boundary with a mildly relativistic temperature and mean speed. It flows across a spatially uniform electron-proton plasma, which is permeated by a background magnetic field. The magnetic field is aligned with one simulation direction and oriented orthogonally to the mean velocity vector of the pair cloud. The expanding pair cloud expels the magnetic field and piles it up at its front. It is amplified to a value large enough to trap ambient electrons. The current of the trapped electrons, which are carried with the expanding cloud front, drives an electric field that accelerates protons. A solitary wave grows and changes into a piston after it saturated. Our simulations show that this piston undergoes a collision-less instability similar to a Rayleigh-Taylor instability. The undular mode grows and we observe fingers in the proton density distribution. The effect of the instability is to deform the piston but it cannot destroy it., 13 pages, 11 figures, accepted for publication in Physics of Plasmas

Context. A 1D description of stellar dynamics is at the basis of stellar evolution modeling. Designed to investigate open problems in stellar evolution, the MUltidimensional Stellar Implicit Code expands a realistic 1D profile of a star’s internal structure to examine the interior dynamics of a specific star through either 2D or 3D hydrodynamic simulations. Aims. Extending our recent studies of 2D stellar convection to 3D stellar convection, we aim to compare 3D hydrodynamic simulations to identically set-up 2D simulations, for a realistic pre-main sequence star. Methods. We compare statistical quantities related to convective flows including: average velocity, vorticity, local enstrophy, and penetration depth beneath a convection zone. These statistics were produced during stationary, steady-state compressible convection in the star’s convection zone. Results. Our simulations confirm the common result that 2D simulations of stellar convection have a higher magnitude of velocity on average than 3D simulations. Boundary conditions and the extent of the spherical shell can affect the magnitude and variability of convective velocities. The difference between 2D and 3D velocities is dependent on these background points; in our simulations this can have an effect as large as the difference resulting from the dimensionality of the simulation. Nevertheless, radial velocities near the convective boundary are comparable in our 2D and 3D simulations. The average local enstrophy of the flow is lower for 2D simulations than for 3D simulations, indicating a different shape and structuring of 3D stellar convection. We performed a statistical analysis of the depth of convective penetration below the convection zone using the model proposed in our recent study (Pratt et al. 2017, A&A, 604, A125). That statistical model was developed based on 2D simulations, which allowed us to examine longer times and higher radial resolution than are possible in 3D. Here, we analyze the convective penetration in 3D simulations, and compare the results to identically set-up 2D simulations. In 3D simulations, the penetration depth is as large as the penetration depth calculated from 2D simulations.

We study with 1D PIC simulations the expansion of a dense plasma into a dilute one for density ratios 2.5 ≤ α ≤ 20. Both are unmagnetized and consist of electrons and protons. Shocks form in all ca ...

In the framework of the global energy balance, the radiative energy exchanges between Sun, Earth and space are now accurately quantified from new satellite missions. Much less is known about the magnitude of the energy flows within the climate system and at the Earth surface, which cannot be directly measured by satellites. In addition to satellite observations, here we make extensive use of the growing number of surface observations to constrain the global energy balance not only from space, but also from the surface. We combine these observations with the latest modeling efforts performed for the 5th IPCC assessment report to infer best estimates for the global mean surface radiative components. Our analyses favor global mean downward surface solar and thermal radiation values near 185 and 342 Wm−2, respectively, which are most compatible with surface observations. Combined with an estimated surface absorbed solar radiation and thermal emission of 161 and 397 Wm−2, respectively, this leaves 106 Wm−2 of surface net radiation available globally for distribution amongst the non-radiative surface energy balance components. The climate models overestimate the downward solar and underestimate the downward thermal radiation, thereby simulating nevertheless an adequate global mean surface net radiation by error compensation. This also suggests that, globally, the simulated surface sensible and latent heat fluxes, around 20 and 85 Wm−2 on average, state realistic values. The findings of this study are compiled into a new global energy balance diagram, which may be able to reconcile currently disputed inconsistencies between energy and water cycle estimates., Climate Dynamics, 40, ISSN:0930-7575, ISSN:1432-0894

Clouds play a major role in the climate system, but large uncertainties remain about their decadal variations. Here we report a widespread decrease in cloud cover since the 1970 s over the Mediterranean region, in particular during the 1970 s–1980 s, especially in the central and eastern areas and during springtime. Confidence in these findings is high due to the good agreement between the interannual variations of cloud cover provided by surface observations and several satellite-derived and reanalysis products, although some discrepancies exist in their trends. Climate model simulations of the historical experiment from the Coupled Model Intercomparison Project Phase 5 (CMIP5) also exhibit a decrease in cloud cover over the Mediterranean since the 1970 s, in agreement with surface observations, although the rate of decrease is slightly lower. The observed northward expansion of the Hadley cell is discussed as a possible cause of detected trends., Scientific Reports, 7, ISSN:2045-2322