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Abstract In much of western-central Europe, summer temperatures have surged three times faster than the global mean warming since 1980, yet this is not captured by most climate model simulations. Here we disentangle this warming into thermodynamic and circulation-induced contributions, and show that the latter is the main reason why numerically simulated warming is weaker than observed. Crucially, regional climate models from the Coordinated Regional Downscaling Experiment with constant aerosol forcings systematically show the strongest discrepancies from observations: in these simulations, the regional brightening and associated thermodynamic warming due to aerosol reductions is not represented. We estimate an effect of ~0.5 °C over western-central Europe for our model ensemble, and the discrepancy to climate models with evolving aerosols increases in future projections. To better reap the benefits of regional high-resolution simulations, it is thus imperative to represent the relevant external forcings and associated responses across the entire climate model chain.

Surface solar radiation (SSR) serves as the primary energy source on Earth. However, a relative lack of research systematically quantifies long-term SSR variations and their driving factors based on complete and reliable baseline data. This paper presents a new assessment of the Northern Hemisphere/regional SSR variations and the influence of total cloud cover (TCC) on these variations, based on the latest reconstructed SSR gridded dataset. We also address multicollinearity among multiple aerosol types and quantify the effects of multiple aerosol/precursors on SSR variability using a partial least squares regression model. The results indicate that TCC is not the predominant driver of longer-term SSR variations, known as ‘dimming’ and ‘brightening’. The variations of NH _3 and SO _2 primarily drive inter-decadal SSR variations in North America, while the variations of SO _2 and NO _X mainly influence inter-decadal SSR variations in Europe.

An international team of researchers finds high potential for improving climate projections by a more comprehensive treatment of largely ignored Arctic vegetation types, underscoring the importance of Arctic energy exchange measuring stations.

Abstract We examine top of atmosphere (TOA), atmospheric, and surface energy budget components of 53 CMIP6 models for the period 2000–2009 on regional scales with respect to two reference data sets: the NASA Energy and Water cycle Study (NEWS), from which we adopt the regional decomposition, and the Clouds and the Earth's Radiant Energy System (CERES) Energy Balanced and Filled (EBAF). Focusing on regional scale, CMIP6 models tend to have more energy entering or less energy leaving the climate systems at TOA over the Northern Hemisphere land, Southern Hemisphere ocean and the polar regions compared to CERES EBAF, while the contrary applies in other regions. Atmospheric net shortwave and longwave fluxes both tend to be underestimated in CMIP6 models as compared to EBAF, with substantial regional differences. Regional surface radiative fluxes as reported by NEWS and EBAF can differ substantially. Nevertheless, robust regional biases exist in CMIP6. Surface upward shortwave radiation is overestimated by 43 (81%) models over Eurasia. For almost all surface radiative flux components over the North Atlantic and Indian Ocean, there are at least 21 (40%) models which fall outside the NEWS uncertainty range. Latent heat flux is overestimated over most of the land and ocean regions while firm conclusions for sensible heat flux remain elusive due to discrepancies between different reference data sets. Compared to CMIP5, there is an overall improvement in CMIP6 on regional scale. Still, substantial deficiencies and spreads on regional scale remain, which are potentially translated into an inadequate simulation of atmospheric dynamics or hydrological cycle.

The interdecadal changes of the incident solar radiation at the Earth’s surface (SSR) are mainly driven by changes in clouds and aerosols. In order to investigate their contribution to the SSR changes (global dimming and brightening or GDB), the FORTH radiative transfer model (RTM) is used to compute the SSR fluxes. The cloud input data were taken from satellite observations of ISCCP-H, while aerosols and meteorological data were taken from the MERRA-2 reanalysis dataset. The RTM operates on a monthly basis and in 0.5° × 0.625° latitude-longitude spatial resolution. The GDB was also computed keeping constant at their initial 1984 values, each input parameter that was examined, resulting in a GDB with the ‘frozen’ parameter. The contribution of each parameter to the GDB is defined as the subtraction of the frozen GDB from the base-run GDB, and the positive/negative values of the contribution indicate that the interdecadal variability of the examined parameter increased/decreased the SSR. The aerosol optical depth (AOD) produced a dimming in India, Amazonia, and S. China, whereas it induced a brightening in Europe and Mexico. On the other hand, the total cloud cover (TCC) changes caused a dimming over the Arctic, Australia, and the South Ocean against a brightening in Europe, Mexico, the Middle East, and South America. The global mean contribution of changing AOD is 0.37 W/m2, and for TCC, it is 4.7 W/m2, indicating that globally, the counteraction of cloud cover to the overall global dimming is larger. Opposite contributions to GDB from AOD and TCC may occur over specific regions, highlighting the complexity of the causes of the GDB phenomenon.

In this study, an assessment of the FORTH radiative transfer model (RTM) surface solar radiation (SSR) as well as its interdecadal changes (Δ(SSR)), namely global dimming and brightening (GDB), is performed during the 35-year period of 1984–2018. Furthermore, a thorough evaluation of SSR and (Δ(SSR)) is conducted against high-quality reference surface measurements from 1193 Global Energy Balance Archive (GEBA) and 66 Baseline Surface Radiation Network (BSRN) stations. For the first time, the FORTH-RTM Δ(SSR) was evaluated over an extended period of 35 years and with a spatial resolution of 0.5° × 0.625°. The RTM uses state-of-the-art input products such as MERRA-2 and ISCCP-H and computes 35-year-long monthly SSR and GDB, which are compared to a comprehensive dataset of reference measurements from GEBA and BSRN. Overall, the FORTH-RTM deseasonalized SSR anomalies correlate satisfactorily with either GEBA (R equal to 0.72) or BSRN (R equal to 0.80). The percentage of agreement between the sign of computed GEBA and FORTH-RTM Δ(SSR) is equal to 63.5% and the corresponding percentage for FORTH-RTM and BSRN is 54.5%. The obtained results indicate that a considerable and statistically significant increase in SSR (Brightening) took place over Europe, Mexico, Brazil, Argentina, Central and NW African areas, and some parts of the tropical oceans from the early 1980s to the late 2010s. On the other hand, during the same 35-year period, a strong and statistically significant decrease in SSR (Dimming) occurred over the western Tropical Pacific, India, Australia, Southern East China, Northern South America, and some parts of oceans. A statistically significant dimming at the 95% confidence level, equal to −0.063 Wm−2 year−1 (or −2.22 Wm−2) from 1984 to 2018 is found over the entire globe, which was more prevalent over oceanic than over continental regions (−0.07 Wm−2 year−1 and −0.03 Wm−2 year−1, statistically significant dimming at the 95% confidence level, respectively) in both hemispheres. Yet, this overall 35-year dimming arose from alternating decadal-scale changes, consisting of dimming during 1984–1989, brightening in the 1990s, turning into dimming over 2000–2009, and brightening during 2010–2018.

Abstract Time series of clear‐sky irradiance are fundamental for the understanding of changes in the Earth Radiation budget, since they allow to examine radiative processes in the cloud‐free atmosphere. Clear‐sky data is usually derived from all‐sky irradiances using one of several clear‐sky methods proposed in the literature. However, most of the available clear‐sky methods require additional in situ measurements and/or high temporal resolution (sub‐daily), which restricts the derivation of clear‐sky time series to a few well equipped stations. Here we propose a new clear‐sky identification method that aims to overcome this problem, with the ultimate goal of deriving multidecadal clear‐sky trends for many sites globally. The method uses site specific monthly transmittance thresholds to derive long term clear‐sky time series for any station worldwide that has daily mean irradiance data. We exemplify the method for 24 stations. Transmittance thresholds are derived by combining 29 years (1990–2018) of satellite cloud cover data with in situ irradiance measurements. The thresholds are then applied to the whole time series (independent of satellite data availability) to screen out cloudy days. Comparison of our results with reference data derived using Long and Ackerman's (2000, https://doi.org/10.1029/2000jd900077) method shows good agreement after bias correction, especially for decadal trends. While limitations of the method, such as anomalies representation, are highlighted and discussed, validation results encourage its use to derive long term clear‐sky time series and associated decadal‐scale trends around the globe.

Abstract Renewable generation variability over multiple days is a key challenge in decarbonizing the European power system. Weather regimes are one way to quantify this variability, but so far, their applications to energy research have focused on wind power generation in winter. However, the projected growth of solar photovoltaic (PV) capacity implies that its absolute variability across the continent will grow substantially. Here we combine weather regimes based on ERA5 reanalysis data with country‐specific capacity factors to investigate multiday PV generation variability in Europe. With current installed capacity (131 GW), total PV production in Europe (52.3 GW) varies by 0.9 GW on average, with a maximum change of 3.0 GW, upon transition from one weather regime to another. Using projected PV capacity for 2050 (1.94 TW), variability would rise to 13.9 and 43.8 GW. We present optimized spatial distributions of capacity additions in three scenarios that substantially reduce variability by up to 40%. One of them ascertains a large local PV production, thereby minimizing the need for long‐range power transmission while still reducing variability by about 30%, highlighting that optimized siting and local generation can be reconciled. Our results emphasize the value of leveraging climate information in decarbonizing power systems.

Claire Patterson et al. present the design and development of AZD0466, a drug-dendrimer conjugate, and use preclinical and mathematical models to determine the optimal release rate of the drug from the dendrimer carrier for maximal therapeutic index in terms of anti-tumour efficacy and cardiovascular tolerability. This study identifies this promising dual Bcl-2/Bcl-xL inhibitor for progression to clinical development.

Solar shortwave and terrestrial thermal longwave irradiance are measured at radiation sites at the Earth's surface and on satellite platforms high up in space, since many years. Radiation profiles through the Earth's atmosphere, however, have only sporadically been measured from enhanced upper-air radiosondes. Here we show profiles of solar and terrestrial radiation measured with balloon-borne radiometers through cloud-free and cloudy atmospheres, which reveal radiative effects of temperature, water vapor, ozone and clouds on downward and upward radiation. Shortwave radiation profiles show solar absorption in the free atmosphere and strong reflection in clouds and albedo effects on the ground and the atmosphere above. Longwave upward radiation profiles visualize terrestrial radiation emitted from the Earth's surface, which is partly absorbed and reemitted in the boundary layer and in the atmosphere by water vapor and other greenhouse gases. Longwave downward radiation profiles show the absorbed terrestrial radiation in the atmosphere and reveal the warming effect of increasing greenhouse gases, and by this visualize and demonstrate radiative forcing and a changing greenhouse effect by water vapor in the Earth's atmosphere. Longwave net radiation profiles show terrestrial emission into space to be reduced by water vapor and clouds. Measured radiation profiles are compared to numerically calculated radiation profiles.

This study assesses and evaluates the 40-year (1980–2019) Modern-Era Retrospective Analysis for Research and Applications v.2 (MERRA-2) surface solar radiation (SSR) as well as its interdecadal changes (Δ(SSR)) against high quality reference surface measurements from 1397 Global Energy Balance Archive (GEBA) and 73 Baseline Surface Radiation Network (BSRN) stations. The study is innovative since MERRA-2 (Δ(SSR)) has never been evaluated in the past, while the MERRA-2 SSR fluxes themselves have not been evaluated in such large spatial scale, which is global here, and temporal basis, which counts 40-years. Other novelties of the study are the use of the highest quality BSRN stations, done for the first time in such an evaluation, as well as the use of a greater number of reference-GEBA stations than in other studies. Moreover, the assessment and evaluation in this study are largely based on SSR anomalies, while being done in depth, at spatial scales ranging from the local to global/hemispherical, and separately for land and ocean areas, and at temporal scales spanning intervals from decadal sub-periods to 40 years. Overall, the MERRA-2 deseasonalized SSR anomalies correlate well with either GEBA (R equal to 0.61) and BSRN (R equal to 0.62). The percentage of agreement between the sign of computed GEBA and MERRA-2 Δ(SSR) is equal to 63.4% and the corresponding percentage for MERRA-2 and BSRN is 50%. According to MERRA-2, strong and statistically significant positive Δ(SSR) (Brightening) is found over Europe, Central Africa, Mongolia, Mexico, Brazil, Argentina and some parts of the tropical oceans. In contrast, large and statistically significant negative Δ(SSR) (Dimming) occurs over the western Tropical Warm Pool, India, Southern East China, Amazonia, stratocumulus covered areas and some parts of oceans. MERRA-2 yields a dimming equal to −0.158 ± 0.005 W/m2/year over the globe from 1980 to 2019. This 40-year dimming, which occurred in both hemispheres, more over ocean than continental areas (−0.195 ± 0.006 and −0.064 ± 0.006 W/m2/year, respectively), underwent decadal scale variations.

In birds the auditory system plays a key role in providing the sensory input used to discriminate between conspecific and heterospecific vocal signals. In those species that are known to learn their vocalizations, for example, songbirds, it is generally considered that this ability arises and is manifest in the forebrain, although there is no a priori reason why brainstem components of the auditory system could not also play an important part. To test this assumption, we used groups of normal reared and cross-fostered zebra finches that had previously been shown in behavioural experiments to reduce their preference for conspecific songs subsequent to cross fostering experience with Bengalese finches, a related species with a distinctly different song. The question we asked, therefore, is whether this experiential change also changes the bias in favour of conspecific song displayed by auditory midbrain units of normally raised zebra finches. By recording the responses of single units in MLd to a variety of zebra finch and Bengalese finch songs in both normally reared and cross-fostered zebra finches, we provide a positive answer to this question. That is, the difference in response to conspecific and heterospecific songs seen in normal reared zebra finches is reduced following cross-fostering. In birds the virtual absence of mammalian-like cortical projections upon auditory brainstem nuclei argues against the interpretation that MLd units change, as observed in the present experiments, as a result of top-down influences on sensory processing. Instead, it appears that MLd units can be influenced significantly by sensory inputs arising directly from a change in auditory experience during development.

Abstract 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.

Extreme weather events in the mid-latitudes are often associated with weather systems, such as extratropical cyclones or blocks. However little is known about the decadal variation in the frequency of blocks and the activity of storm tracks and their relation to the two most important low-frequency oceanic modes of variability, the Atlantic multidecadal oscillation (AMO) and the Pacific decadal oscillation (PDO). To address this question, first the representation of blocks, storm tracks and Alpine circulation types is assessed in recently released centennial reanalyses during the 20th century. While interannual variability is represented similarly in all centennial reanalyses, the trends in particular for storm track activity before 1950 differ substantially between the NOAA 20th century reanalyses (20CR and 20CRv2c) and ECMWF centennial reanalyses (ERA-20C and CERA-20C). Therefore, the analysis of the connection between the AMO and PDO and the mid-latitudinal circulation is restricted to the period 1950–2010. All centennial reanalyses agree on the anomaly patterns associated with the different AMO/PDO phases. We find no significant connections except a southward (northward) shift of the storm track over the North Pacific as well as the North Atlantic during the positive (negative) PDO phase. The ERA-20CM atmosphere-only model ensemble captures this relationship, indicating that the ocean forces the atmosphere in the North Pacific. For studies investigating periods earlier than 1950, we recommend using several reanalysis products to ensure the robustness of results.

The annual mean surface solar radiation (SSR) trends under all-sky, clear-sky, all-sky-no-aerosol, and clear-sky-no-aerosol conditions as well as their possible causes are analyzed during 2005–2018 across China based on different satellite-retrieved datasets to determine the major drivers of the trends. The results confirm clouds and aerosols as the major contributors to such all-sky SSR trends over China but play differing roles over sub-regions. Aerosol variations during this period result in a widespread brightening, while cloud effects show opposite trends from south to north. Moreover, aerosols contribute more to the increasing all-sky SSR trends over northern China, while clouds dominate the SSR decline over southern China. A radiative transfer model is used to explore the relative contributions of cloud cover from different cloud types to the all-types-of-cloud-cover-induced (ACC-induced) SSR trends during this period in four typical sub-regions over China. The simulations point out that the decreases in low-cloud-cover (LCC) over the North China Plain are the largest positive contributor of all cloud types to the marked annual and seasonal ACC-induced SSR increases, and the positive contributions from both high-cloud-cover (HCC) and LCC declines in summer and winter greatly contribute to the ACC-induced SSR increases over East China. The contributions from medium-low-cloud-cover (mid-LCC) and LCC variations dominate the ACC-caused SSR trends over southwestern and South China all year round, except for the larger HCC contribution in summer.

There was a dramatic increase in aerosol loading in China after the 1960s due to rapid industrialization, followed by a gradual reduction due to improvements in air quality since the early 2000s. They are deemed to be the main cause of ‘dimming’ and ‘brightening’ in China, respectively. China, therefore, provides an ideal testbed to investigate the multi-decadal evolution of clouds under a background of large variations in the amount of atmospheric aerosols. We used a unique combination of long-term in-situ observational records combined with a radiative transfer model to investigate the changes in clouds and aerosols over the last 60 years (1958–2018) over China. We found during the dimming period, the clouds over China shrunk in area steadily, gradually thinned in terms of optical depth, and thereby blocked less and less solar radiation. This situation reversed during the brightening period. The clouds over China showed a quick expansion in extent and thickening in terms of optical depth, and accordingly the amounts of solar radiation blocked by clouds recovered rapidly. It is observationally demonstrated that high levels of pollution and the associated amount of aerosols cause a suppression of cloud growth and a reduction of optical depth.

Downward surface solar radiation (SSR) trends for the first decade of the 2000s were computed using a radiative transfer model and satellite and reanalysis input data and were validated against measurements from the reference global station networks Global Energy Balance Archive (GEBA) and Baseline Surface Radiation Network (BSRN). Under all-sky conditions, in spite of a somewhat patchy structure of global dimming and brightening (GDB), an overall dimming was found that is weaker in the Northern than in the Southern Hemisphere (−2.2 and −3.1 W m−2, respectively, over the 2001−2009 period). Dimming is observed over both land and ocean in the two hemispheres, but it is more remarkable over land areas of the Southern Hemisphere. The post-2000 dimming is found to have been primarily caused by clouds, and secondarily by aerosols, with total cloud cover contributing −1.4 W m−2 and aerosol optical thickness −0.7 W m−2 to the global average dimming of −2.65 W m−2. The evaluation of the model-computed GDB against BSRN and GEBA measurements indicates a good agreement, with the same trends for 65% and 64% of the examined stations, respectively. The obtained model results are in line with other studies for specific world regions and confirm the occurrence of an overall solar dimming over the globe during the first decade of 21st century. This post-2000 dimming has succeeded the global brightening observed in the 1990s and points to possible impacts on the ongoing global warming and climate change.

Long-term historic climate datasets are valuable tools to investigate climate variability, validate climate models and contextualize anticipated climate change. Surface solar radiation is one particularly relevant variable, with implications on policy decisions (e.g. performance of solar panels) and fundamental questions in climate science (e.g. regarding the energy budget). While all current twentieth century reanalyses provide surface solar radiation, we demonstrate that most of them fail to capture multidecadal surface radiation variability in Europe. To this end, we systematically compare the reanalyses 20CRv2c, 20CRv3, ERA20C and CERA20C and the free model run ERA20CM. We show that only CERA20C captures dimming (1949–1979) and brightening (1979–2009) in line with station observations, satellite-era reanalyses and established theory. The lack of multidecadal surface radiation variability in 20CRv2c/v3 is plausible given the use of constant aerosols. In contrast, ERA20CM, ERA20C and CERA20C are forced with time-varying aerosols. Despite this common forcing, ERA20CM and ERA20C surprisingly show no trends in clear-sky fluxes over the dimming and brightening periods while CERA20C shows significant trends. We discuss different potential explanations for this discrepancy (model versions, ocean coupling and ensemble size) and conclude that none of them provides a convincing explanation. Our results therefore imply that only CERA20C is suitable for assessments of surface solar radiation variability on multi-decadal timescales. This particularly applies to impact studies, for example, on long-term potentials of solar power generation.

To achieve high-quality surface solar radiation (SSR) data for climate monitoring and analysis, the two satellite-derived monthly SSR datasets of CM SAF CLARA-A2 and SARAH-E have been validated against a homogenized ground-based dataset covering 59 stations across China for 1993⁻2015 and 1999⁻2015, respectively. The satellite products overestimate surface solar irradiance by 10.0 W m−2 in CLARA-A2 and 7.5 W m−2 in SARAH-E on average. A strong urbanization effect has been noted behind the large positive bias in China. The bias decreased after 2004, possibly linked to a weakened attenuating effect of aerosols on radiation in China. Both satellite datasets can reproduce the monthly anomalies of SSR, indicated by a significant correlation around 0.8. Due to the neglection of temporal aerosol variability in the satellite algorithms, the discrepancy between the satellite-estimated and ground-observed SSR trends slightly increases in 1999⁻2015 as compared to 1993⁻2015. The seasonal performance of the satellite products shows a better accuracy during warm than cold seasons. With respect to the spatial performance, the effects from anthropogenic aerosols, dust aerosols and high elevation and snow-covered surfaces should be well considered in the satellite SSR retrievals to further improve the performance in the eastern, northwestern and southwestern parts of China, respectively.

The use of regional climate models (RCMs) can partly reduce the biases in global radiative flux (Eg↓) that are found in reanalysis products and global models, as they allow for a finer spatial resolution and a finer parametrisation of surface and atmospheric processes. In this study, we assess the ability of the MAR («Modèle Atmosphérique Régional») RCM to reproduce observed changes in Eg↓, and we investigate the added value of MAR with respect to reanalyses. Simulations were performed at a horizontal resolution of 5 km for the period 1959–2010 by forcing MAR with different reanalysis products: ERA40/ERA-interim, NCEP/NCAR-v1, ERA-20C, and 20CRV2C. Measurements of Eg↓ from the Global Energy Balance Archive (GEBA) and from the Royal Meteorological Institute of Belgium (RMIB), as well as cloud cover observations from Belgocontrol and RMIB, were used for the evaluation of the MAR model and the forcing reanalyses. Results show that MAR enables largely reducing the mean biases that are present in the reanalyses. The trend analysis shows that only MAR forced by ERA40/ERA-interim shows historical trends, which is probably because the ERA40/ERA-interim has a better horizontal resolution and assimilates more observations than the other reanalyses that are used in this study. The results suggest that the solar brightening observed since the 1980s in Belgium has mainly been due to decreasing cloud cover.

In many hydrological models, the amount of evapotranspired water is calculated using the potential evapotranspiration (PET) approach. The main driver of several PET approaches is net radiation, whose downward components are usually obtained from meteorological input data, whereas the upward components are calculated by the model itself. Thus, uncertainties can be large due to both the input data and model assumptions. In this study, we compare the radiation components of the WaterGAP Global Hydrology Model, driven by two meteorological input datasets and two radiation setups from ERA-Interim reanalysis. We assess the performance with respect to monthly observations provided by the Baseline Surface Radiation Network (BSRN) and the Global Energy Balance Archive (GEBA). The assessment is done for the global land area and specifically for energy/water limited regions. The results indicate that there is no optimal radiation input throughout the model variants, but standard meteorological input datasets perform better than those directly obtained by ERA-Interim reanalysis for the key variable net radiation. The low number of observations for some radiation components, as well as the scale mismatch between station observations and 0.5° × 0.5° grid cell size, limits the assessment.