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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.

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

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.

This paper presents trends in downward surface shortwave radiation (SSR) over Europe, which are based on the 56 longest series available from the Global Energy Balance Archive that are mainly concentrated in central Europe. Special emphasis has been placed on both ensuring the temporal homogeneity and including the most recent years in the data set. We have generated, for the first time, composite time series for Europe covering the period 1939–2012, which have been studied by means of running trend analysis. The mean annual SSR series shows an increase from the late 1930s to the early 1950s (i.e., early brightening), followed by a reduction until mid-1980s (i.e., global dimming) and a subsequent increase up to the early 2000s (i.e., global brightening). The series ends with a tendency of stabilization since the early 21st century, but the short time period is insufficient with regard to establishing whether a change in the trend is actually emerging over Europe. Seasonal and regional variations are also presented, which highlight that similar variations are obtained for most of the seasons and regions across Europe. In fact, due to the strong spatial correlation in the SSR series, few series are enough to capture almost the same interannual and decadal variability as using a dense network of stations. Decadal variations of the SSR are expected to have an impact on the modulation of the temperatures and other processes over Europe linked with changes in the hydrological cycle, agriculture production, or natural ecosystems. For a better dissemination of the time series developed in this study, the data set is freely available for scientific purposes., Global solar radiation series in Europe

The Global Energy Balance Archive (GEBA) is a database for the worldwide measured energy fluxes at the Earth’s surface. GEBA is maintained at ETH Zurich (Switzerland) and has been founded in the 1980s by Prof. Atsumu Ohmura. It has continuously been updated and currently contains around 2500 stations with 500‘000 monthly mean entries of various surface energy balance components. Many of the records extend over several decades. The most widely measured quantity available in GEBA is the solar radiation incident at the Earth’s surface (“global radiation”). The data sources include, in addition to the World Radiation Data Centre (WRDC) in St. Petersburg, data reports from National Weather Services, data from different research networks (BSRN, ARM, SURFRAD), data published in peer-reviewed publications and data obtained through personal communications. Different quality checks are applied to check for gross errors in the dataset. GEBA is used in various research applications, such as for the quantification of ...

In previous studies1, 2 we derived new estimates for the magnitude of the components of the global mean energy budget using to the extent possible the information contained in direct observations from surface and space. Here we establish complementary estimates for the global mean energy budget specifically under cloud-free conditions. The energy fluxes under cloud-free conditions at the Top of Atmosphere (TOA) can be determined with high accuracy from satellite measurements (CERES-EBAF). For the estimation of their counterparts at the Earth’s surface we follow the approach presented in our recent studies, based on an analysis of 39 state of the art global climate models from CMIP5 and their bias structure compared to a comprehensive set of high quality surface observations from the Baseline Surface Radiation Network (BSRN). Thereby we infer a best estimate of 249 Wm−2 for the global mean clear-sky downward shortwave radiation at the surface, and a corresponding clear-sky surface shortwave absorption of 2...

[1] The validation of gridded surface solar radiation (SSR) data often relies on the comparison with ground-based in situ measurements. This poses the question on how representative a point measurement is for a larger-scale surrounding. We use high-resolution (0.03°) SSR data from the Satellite Application Facility on Climate Monitoring (CM SAF) to study the subgrid spatial variability in all-sky SSR over Europe and the spatial representativeness of 143 surface sites with homogeneous records for their site-centered larger surroundings varying in size from 0.25° to 3°, as well as with respect to a given standard grid of 1° resolution. These analyses are done on a climatological annual and monthly mean basis over the period 2001–2005. The spatial variability of the CM SAF data set itself agrees very well with surface measurements in Europe, justifying its use for the present study. The annual mean subgrid variability in the 1° standard grid over European land is on average 1.6% (2.4 W m−2), with maximum of up to 10% in Northern Spain. The annual mean representation error of point values at 143 surface sites with respect to their 1° surrounding is on average 2% (3 W m−2). For larger surroundings of 3°, the representation error increases to 3% (4.8 W m−2). The monthly mean representation error at the surface sites with respect to the 1° standard grid is on average 3.7% (4 W m−2). This error is reduced when site-specific correction factors are applied or when multiple sites are available in the same grid cell, i.e., three more sites reduce the error by 50%.

When using time series of ground based surface solar radiation (SSR) measurements in combination with gridded data the spatial and temporal representativeness of the point observations must be considered. We use SSR data from surface observations and high resolution (0.05∘) satellite derived data to infer the spatiotemporal representativeness of observations for monthly and longer time scales in Europe. The correlation analysis shows that the squared correlation coefficients (R2) between SSR times series decrease linearly with increasing distance between the surface observations. For deseasonalized monthly mean time series R2 ranges from 0.85 for distances up to 25km between the stations, to 0.25 at distances of 500km. A decorrelation length (i.e. the e-folding distance of R2) in the order of 400km (with spread of 100-600km) was found. R2 from correlations between point observations and colocated grid box area means determined from satellite data were found to be 0.80 for a 1∘ grid. To quantify the error which arises when using a point observation as a surrogate for the area mean SSR of a larger surrounding we calculated a spatial sampling error (SSE) for a 1∘ grid of 8(3)W/m2 for monthly (annual) time series. The SSE based on a 1∘ grid, therefore, is of the same magnitude as the measurement uncertainty. The analysis generally reveals that monthly mean (or longer temporally aggregated) point observations of SSR capture the larger scale variability well. This finding shows that comparing time series of SSR measurements with gridded data is feasible for that timescales.

The spatial representativeness of a point measurement of surface solar radiation (SSR) of its larger-scale surrounding, e.g., collocated grid cell, is a potential source of uncertainty in the validation of climate models and satellite products. Here we expand our previous study over Europe to the entire Meteosat disk, covering additional climate zones in Africa, the Middle east, and South America between −70° to 70° East and −70° to 70° North. Using a high-resolution (0.03°) satellite-based SSR data set (2001–2005), we quantify the spatial subgrid variability in grids of 1° and 3° resolution and the spatial representativeness of 887 surface sites with respect to site-centered surroundings of variable size. In the multiannual mean the subgrid variability is the largest in some mountainous and coastal regions but varies seasonally due to changes in the Intertropical Convergence Zone location. The absolute mean representation errors at the surface sites with respect to surroundings of 1° and 3° are on average 1–2% (3 W m−2) and 2–3% (4 W m−2), respectively. The majority of sites are found to be representative within the in situ measurement accuracy. We show that their site-specific representativeness can be reliably approximated by the subgrid variability in a fixed grid (1°). The subgrid variability in turn is only moderately reduced when computed from coarser grid data, typically the only data available in areas not covered by the 0.03° resolved Meteosat disk. Together, this paves the way to a fully global assessment of site-specific spatial representativeness.

The energy budgets over land and oceans are still afflicted with considerable uncertainties, despite their key importance for terrestrial and maritime climates. We evaluate these budgets as represented in 43 CMIP5 climate models with direct observations from both surface and space and identify substantial biases, particularly in the surface fluxes of downward solar and thermal radiation. These flux biases in the various models are then linearly related to their respective land and ocean means to infer best estimates for present day downward solar and thermal radiation over land and oceans. Over land, where most direct observations are available to constrain the surface fluxes, we obtain 184 and 306 Wm−2 for solar and thermal downward radiation, respectively. Over oceans, with weaker observational constraints, corresponding estimates are around 185 and 356 Wm−2. Considering additionally surface albedo and emissivity, we infer a surface absorbed solar and net thermal radiation of 136 and −66 Wm−2 over land, and 170 and −53 Wm−2 over oceans, respectively. The surface net radiation is thus estimated at 70 Wm−2 over land and 117 Wm−2 over oceans, which may impose additional constraints on the poorly known sensible/latent heat flux magnitudes, estimated here near 32/38 Wm−2 over land, and 16/100 Wm−2 over oceans. Estimated uncertainties are on the order of 10 and 5 Wm−2 for most surface and TOA fluxes, respectively. By combining these surface budgets with satellite-determined TOA budgets we quantify the atmospheric energy budgets as residuals (including ocean to land transports), and revisit the global mean energy balance., Climate Dynamics, 44 (11-12), ISSN:0930-7575, ISSN:1432-0894