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The Copernicus Atmospheric Monitoring Service (CAMS) offers Solar radiation services (CRS) providing information on surface solar irradiance (SSI). The service is currently derived from Meteosat Second Generation (MSG) and the service evolution includes its extension to other parts of the globe. CRS provides clear and all sky time series combining satellite data products with numerical model output from CAMS on aerosols, water vapour and ozone. These products are available from 2004 until yesterday. A regular quality control of input parameters, quarterly benchmarking against ground measurements and automatic consistency checks ensure the service quality. Variability of solar surface irradiances in the 1-minute range is of interest especially for solar energy applications. The variability classes can be defined based on ground as well as satellite-based measurements. This study will present the evaluation of the CAMS CRS based on the eight variability classes derived from ground observations of direct normal irradiation (DNI) (Schroedter-Homscheidt et al., 2018). Such an analysis will help assess the impact of recent improvements in the derivation of all sky irradiance under different cloudy conditions. References: Schroedter-Homscheidt, M., S. Jung, M. Kosmale, 2018: Classifying ground-measured 1 minute temporal variability within hourly intervals for direct normal irradiances. – Meteorol. Z. 27, 2, 160–179. DOI:10.1127/metz/2018/0875.

The Copernicus Atmospheric Monitoring Service (CAMS) provides a surface solar irradiance service which is currently derived from Meteosat Second Generation (MSG). The service combines satellite data products with numerical model output from CAMS on aerosols, water vapour and ozone in order to provide both clear-sky and all-sky radiation time series with availability from 2004 until yesterday. A regular quality control of input parameters, quarterly benchmarking against ground measurements and automatic consistency checks ensures the data quality. To anticipate the increase in resolution that will occur with the commissioning of MTG, it is necessary to enhance methods currently used in CAMS.The recent development focuses on the assessment and improvement of cloud retrieval products from APOLLO_NG in irradiance retrieval schemes. Such a validation against ground-based surface solar irradiances provides insight into the use of probabilistic cloud masking, specific results for pixels with small COD values below 5, as well as in partly cloudy pixel conditions. Such conditions are often neglected in existing cloud retrieval validation studies due to the expected large uncertainties of cloud properties. But they cannot be omitted in irradiance retrieval schemes for solar energy sector users as complete temporal coverage is required.Such cloud situations may additionally be better characterized in future with the help of spatially higher resolved channels. Using e.g. SEVIRI’s HRV channel is known to be beneficial in cloud index based irradiance retrieval schemes, but has not been evaluated yet for cloud physical retrieval based irradiance schemes. Results from such a method development for the HRV channel in preparation for MTG, Himawari-8, and GOES-R channels will be presented.

A growing number of studies has suggested potential impacts of meteorological variables on the spread of the COVID-19 pandemic. These impacts are supported by data from similar viral contagions, such as SARS and the 1918 Flu Pandemic, and corroborated by US influenza data relative to the last decade. However, there is still limited understanding about the extent to which meteorology affects COVID-19 transmission rates and how meteorology can be a relevant element to anticipate social and politic measures. This study demonstrates that such an understanding is attainable through the development of regression models that verify the contribution of meteorology to the modeling of COVID-19 transmission, and the use of feature importance techniques assessing the relative weight of meteorological variables compared to epidemiological, socioeconomic, environmental, and global health indicator factors. The study results show that meteorological factors play an important role in regression models of COVID-19 transmission that have low error rates (R2 0.964). These results are corroborated by a panel data fixed-effect model showing that meteorological coefficients are often significantly correlated with COVID-19 transmission rates (R2 0.691-0.746, p

The present work deals with the spatial consistency of two well-known databases of solar radiation received at ground level: the CAMS Radiation Service database version 3.2, abbreviated as CAMS-Rad and the HelioClim-3 database version 5, abbreviated as HC3v5. Both databases are derived from satellite images. They are validated against 10 min means of irradiance for the period 2010–2018 recorded in a network of 26 ground stations in Germany operated by the Deutscher Wetterdienst (DWD). For the CAMS-Rad database, the correlation coefficient between ground measurements and estimates ranges between 0.83 and 0.92 for all sky conditions. The bias ranges from −41 and 32 W m−2 (−11 % and 10 % of the mean irradiance). The standard deviation ranges between 89 and 129 W m−2 (25 % and 39 %). For the HC3v5 database, the correlation coefficient ranges between 0.90 and 0.95. The bias and the standard deviation are comprised between −22 and 16 W m−2 (−6 % and 5 %), and between respectively 70 and 104 W m−2 (20 % and 31 %). For the CAMS Rad database, overestimation is observed in the South, and underestimation in the North with a faint tendency of the bias to increase from East to West. For the HC3v5 database, the bias is fairly homogeneous across Germany. For both databases, there is no noticeable spatial trend in the standard deviation.

This paper assesses several methods for the retrieval of Photosynthetically Active Radiation (PAR) from satellite imagery. The results of five different methods are compared to coincident in-situ measurements collected at three sites in southern UK. PAR retrieval methods are separated into two distinct groups. The first group comprises three methods that compute PAR by multiplying the satellite-retrieved solar broadband irradiance at the surface (SSI) by a constant coefficient. The two methods in the second group are based on more sophisticated modelling of the radiative transfer in the atmosphere involving advanced global aerosol property analyses and physically consistent total column water vapour and ozone produced by the Copernicus Atmosphere Monitoring Service (CAMS). Both methods compute a cloud modification factor from satellite-retrieved SSI. The five methods have been applied to two satellite-retrieved SSI datasets: HelioClim-3 version 5 (HC3v5) and CAMS Radiation Service (CAMS-Rad). Except at the seashore site, Group 2 methods combined with the cloud extinction from the HC3v5 dataset deliver the best results with small biases of −5 to 0 µmol m−2 s−1 (−1 % to 0 % relative to the mean of the measurements), root mean square errors of 130 µmol m−2 s−1 (28 %) and correlation coefficients exceeding 0.945. For all methods, best results are attained with the HC3v5 data set. These results demonstrate that all methods capture the temporal and spatial variability of the PAR irradiation field well, although several methods require a posteriori bias adjustments for reliable results. Combined with such an adjustment, the Udo et Aro method is a good compromise for this geographical area in terms of reliability, tractability and its ability to run in real-time. Overall, the method performing a spectral discretization in cloud-free conditions, combined with the HC3v5 dataset, outperforms other methods and has great potential for supporting an operational system.

The present work deals with two well-known databases of hourly mean of solar irradiance that are derived from satellite imagery: the CAMS Radiation Service version 3.2, abbreviated as CAMS-Rad and part of the Copernicus Atmosphere Monitoring Service version 3.2 (CAMS), and the HelioClim-3 version 5, abbreviated as HC3v5. It adds up to the continuous documentation of these two databases that demonstrates that both databases capture the temporal and spatial variability of the solar radiation and are reliable sources of data. The spatial consistency of the uncertainties of these databases is verified against measurements performed within a dense network of ground stations in the Netherlands from the Royal Meteorological Institute KNMI for the period 2014–2017. For the CAMS-Rad database, the correlation coefficients between ground measurements and estimates are around 0.94–0.97 for irradiance E and 0.85–0.89 for clearness index KT. The bias ranges between −12 and 27 W m−2 (−4 % and 10 %). The standard deviation for E is almost constant at all stations and around 67 W m−2 (24 %) except at Valkenburg (57 W m−2, 20 %) and De Bilt (73 W m−2, 27 %). For this database, the statistical indicators are constant at inland stations showing the spatial consistency of the performances of CAMS-Rad dataset. At seashore stations, statistical indicators are more variable. The sea proximity influences CAMS-Rad performances and a weak spatial consistency is observed near seashore. For the HC3v5 database, the correlation coefficients are around 0.96–0.98 for E and 0.86–0.91 for KT. The bias ranges between −3 and 15 W m−2 (−1 % and 5 %). The standard deviation ranges between 48 (17 %) and 60 W m−2 (22 %). It is constant at inland stations and around 54 W m−2 (20 %) with peaks at Ell (59 W m−2, 21 %) and De Bilt (60 W m−2, 22 %). For this database, statistical indicators are constant at all stations as a whole, showing a strong spatial consistency of uncertainties. An exception is the standard deviation which tends to decrease at the seashore stations and is close to 50 W m−2 (17 %); this could be related to the general trend of decreasing standard deviation with increasing KT already reported in the scientific literature. As a whole, it is found that both databases are reliable sources on solar radiation in the Netherlands.

Meteosat Second Generation (MSG) satellite images acquired every 15 min during daytime are currently processed by the Heliosat-2 method every night to generate the HelioClim-3 (HC3) database of the surface solar irradiation for the day before. A new service is proposed based on version 4 of HC3 (HC3v4) that offers real-time and forecasted irradiation for horizons up to a few hours. The service is based on a local persistence of the clear-sky index. Its results were compared to coincident high quality 15 min global irradiations measured in fourteen stations belonging to the Baseline Surface Radiation Network (BSRN). For forecasts for a temporal horizon of 15 min ahead, the relative bias and root mean square error (RMSE) range respectively from 0 to 2 %, and 20 to 23 % for most stations. The correlation coefficient ranges from 0.94 to 0.95. These performances are similar to HC3v4 for the same stations. Expectedly, the quality of the forecasts degrades as the temporal horizon increases. For 1 h ahead forecasts of 15 min irradiation, the relative bias, root mean square error (RMSE) and correlation coefficient range respectively from −3 to 1 %, 30 to 37 %, and 0.90 to 0.91.

International audience; The well-know and widely cited Heliosat-2 method has been successfully applied at Transvalor and MINES Paris-Tech for more than twelve years to derive solar irradiance received at ground level from satellite imagery. It has been applied on a reduced dataset extracted from Meteosat First Generation imagery to generate the GEOSS-core service HelioClim-1, spanning from 1985 to 2005, and is routinely used to provide archives, real time and short-term forecasts of HelioClim-3, starting from 2004. Several drawbacks have been identified in Heliosat-2; the method presented here, called Heliosat-5 Interim, intends to correct several of them. This is the first steps of an ambitious project to produce the Heliosat-5 method that may process various satellites to achieve a worldwide solar radiation database. This communication provides an overview of the Heliosat-5 Interim method and the preliminary results of its validation against measurements collected at terrestrial stations. Heliosat-2 computes the ground albedo in cloud-free conditions at a given pixel by selecting one of the minima in a time series of satellite observations. This algorithm may at times select wrong values in specific cases. It has also an operational drawback as it requires a long enough archive of satellite images to build a relevant time series. This prevents from the immediate real-time processing of images from a recently launched satellite. This limitation is overcome in Heliosat-5 Interim by exploiting two runs of McClear clear-sky model, one in the downward direction from the sun towards the earth surface, and a second one upward from the surface towards the satellite. McClear is a service of the European-funded Copernicus Atmosphere Monitoring Service (CAMS). It produces estimates of the solar irradiance that should be observed if the sky were cloud-free at any time and any site in the world since 2004. Part of its inputs is the properties of the cloud-free atmosphere such as ozone, water vapour and aerosols, which are updated every three hours, provided by CAMS. McClear has already demonstrated its reliability and its performance as it is exploited in our most performant version of HelioClim-3 version 5 (HC3v5) for more than four years now. It is consequently sound and safe to base a new operational service on this resource. Heliosat-5 Interim is based on the same concept that Heliosat-2. The other elements of the model are so far similar to those available in Heliosat-2, except that they are now computed at satellite level instead of at ground level. The preliminary results of validation against the measurements of fourteen stations located in the geographical coverage of the Meteosat Second Generation satellite are presented together with a reminder of those obtained for HC3v5. Limits of Heliosat-5 Interim are discussed and ways of improvements are proposed.

International audience; The new Heliosat-4 method estimates the downwelling shortwave irradiance received at ground level in all sky conditions. It provides the global irradiance and its direct and diffuse components on a horizontal plane and the direct irradiance for a plane normal to sun rays. It is a fully physical model using a fast, but still accurate approximation of radiative transfer modelling and is therefore well suited for geostationary satellite retrievals. It can also be used as a fast radiative transfer model in numerical weather prediction models. It is composed of two models based on abaci, also called look-up tables: the already-published McClear model calculating the irradiance under cloud-free conditions and the new McCloud model calculating the extinction of irradiance due to clouds. Both have been realized by using the libRadtran radiative transfer model. The main inputs to Heliosat-4 are aerosol properties, total column water vapour and ozone content as provided by the Copernicus Atmosphere Monitoring Service (CAMS) every 3 h. Cloud properties are derived from images of the Meteosat Second Generation (MSG) satellites in their 15 min temporal resolution using an adapted APOLLO (AVHRR Processing scheme Over cLouds, Land and Ocean) scheme. The 15 min means of irradiance estimated by Heliosat-4 are compared to corresponding measurements made at 13 stations within the Baseline Surface Radiation Network and being located in the field of view of MSG and in various climates. The bias for global irradiance is comprised between 2 and 32 W m −2. The root mean square error (RMSE) ranges between 74 and 94 W m −2. Relative RMSE values range between 15 % and 20 % of the mean observed irradiance for stations in desert and Mediterranean climates, and between 26 % and 43 % for rainy climates with mild winters. Correlation coefficients between 0.91 and 0.97 are found. The bias for the direct irradiance at normal incidence is comprised between −163 and +50 W m −2. The RMSE ranges from 160 W m −2 (29 % of the mean observed irradiance) to 288 W m −2 (63 %). The correlation coefficient ranges between 0.67 and 0.87.

International audience; The HelioClim-1 database contains daily values of the solar radiation reaching the ground. This GEOSS (Global Earth Observation System of Systems) Data Collection of Open Resources for Everyone (Data-CORE) covers Europe, Africa and the Atlantic Ocean, from 1985 to 2005. It is freely accessible at no cost through the SoDa Service (www.soda-is.com). Several assessments of the HelioClim-1 data against measurements made in meteorological networks reveal that the HelioClim-1 database offers a reliable and accurate knowledge of the solar radiation and its daily, seasonal and annual variations over recent years. The HelioClim-1 data may help in qualifying in situ measurements and may supplement them, thus offering 21 years of accurate daily means of surface solar irradiance. Several published works benefited from openness, availability and accuracy of the HelioClim-1 database in various domains: oceanography, climate, energy production, life cycle analysis, agriculture, forestry, architecture, health and air quality. This demonstration of the benefit of the HelioClim-1 database draws attention to resources open to everyone such as those labeled GEOSS Data-CORE.

International audience; HelioClim-3 is a database containing surface solar irradiance assessed every 15 min from images taken by the Meteosat series of satellites since 2004. It covers Europe, Africa and Atlantic Ocean. In average, comparison with hourly measurements made in meteorological stations yields a correlation coefficient greater than 0.9, a relative root mean square error (rRMSE) around 20% of the mean measured irradiance and a relative mean bias error (rMBE) below 2%. HelioClim-3 can be accessed via the SoDa Service (www.soda- is.org). The availability and quality of HelioClim-3 data should help in performing steps towards a better knowledge of the surface solar irradiance and its variations over recent years.

International audience; Satellite-derived databases of the surface solar irradiance (SSI) are common tools in solar energy and assessing their performance by comparison with in situ measurements is a common activity. The present work focuses on two databases: the CAMS Radiation Service version 3 (abbreviated as CAMS-Rad) and the HelioClim-3 version 5 (abbreviated as HC3v5) that are well used by academics and practitioners. It adds up to the continuous documentation of these databases already available in detailed manner for Europe, Brazil, Egypt, Arabic Peninsula, and Morocco. It has been found that these two databases capture the temporal and spatial variability of the solar radiation and that they are reliable sources of solar radiation. The present communication focuses on 12 stations located in The Netherlands operated by the met-office KNMI. They are close to each other, thus allowing the study of the spatial consistency of the performance of a database. Ground measurements of hourly means of global irradiance by pyranometers were collected from the KNMI web-site. The twelve sites are: Leeuwarden, Marknesse, Deelen, Volkel, Ell, Maastricht, Twenthe, Hupsel, De Bilt, Cabauw, Valkenburg, Voorschoten. Measurements were quality-checked using recognized procedures. Estimates were collected from the SoDa web site (www.soda-pro.com) for the same locations and same instants of measurements for both databases. CAMS-Rad uses the Heliosat-4 method with inputs from the Copernicus Atmosphere Monitoring Service (CAMS) of gaseous and aerosols content in the atmosphere, and cloud optical properties deduced every 15 min from Meteosat imagery. Part of this service is the McClear service that provides estimates of the irradiance that should be observed if the sky were cloud-free. The second database is the HelioClim-3v5 that is derived from Meteosat images using the Heliosat-2 method, McClear and CAMS products. Expectations for performance are to be the same at all stations for a given database. This is what is observed as a whole for both databases. The relative bias is approximatively 9 % of the mean of the measurements for CAMS-Rad and 3 % for HC3v5. The relative standard deviation ranges between 19 and 25 % for CAMS-Rad and between 16 and 19 % for HC3v5. The correlation coefficient is greater than 0.95 for both databases. The two stations Valkenburg and Voorschoten are close to the seashore and their results are slightly different. Assuming that the quality of measurements is the same at both stations, this discrepancy in performance may be related to the difference in cloud coverage as these two stations experience more frequent cloud-free conditions than the others. It is speculated that the performance depends on the clearness index. This point will be deepened in a further study.

International audience; This communication deals with the assessment of the Photosynthetically Active Radiation (PAR) from satellite images. Five different methods are applied onto Meteosat images over Europe and their results are compared to PAR measurements performed at terrestrial stations. This co-designed precursor of an operational application focuses on the delivery of time series and maps of PAR for the monitoring of raspberry cultures in plastic tunnels in the Southern United-Kingdom. An accurate knowledge of PAR radiation is necessary as it represents the portion of the solar spectrum responsible for the growth of plants, algae, and of certain microorganisms. The scarcity of in-situ PAR measurements motivated scientists to find alternatives to derive PAR from measurements of the broadband solar radiation. As the broadband solar radiation can be accurately estimated at any place from satellite images, several empirical methods applying coefficients on broadband estimates have been proposed and validated. The advantage of such approaches is to meet the constraint of a real-time operational service. A few publications have also demonstrated the limitation of these approaches due to their dependence on the sky conditions and the atmospheric properties. To overcome this limitation, other approaches better describe the spectral content of the atmosphere in cloud-free conditions by using sophisticated Radiative Transfer Models (RTM), aiming at providing higher quality estimates of the spectral radiation. As RTMs are computationally expensive, a recent method has been built to reduce the amount of calculations by working on a reduced number of spectral bands. This method proposes a resampling technique of the outputs of the Copernicus Atmosphere Monitoring Service McClear service. The latter provides radiation components in cloud-free conditions in the thirty-two spectral bands described by Kato et al. (1999) using updates of ozone, aerosol and water vapour contents as inputs. A version of this service in all-sky conditions is obtained by extracting a cloud index from the satellite-derived database HelioClim-3 version 5 with the underlying assumption that the extinction of clouds is independent on the spectral range. The validation results of three empirical methods together with two implementations of the proposed approach are presented, both in photosynthetic photon flux density (expressed in µmol.m-2.s-1) and in irradiance (in W.m-2). The specifications, versions and performances, of the service are driven by a collaboration with an end-user requesting long-term archive and real-time PAR estimations for the monitoring of more than sixty farms producing raspberries in plastic tunnels. The use of plastic tunnels enable farmers to control and consequently postpone the raspberry harvest to maximize their profit. This work belongs to a wider project which aims at providing irradiances in any spectral range to meet the numerous requirements from users in various applications for instance in solar energy, human health, agro-meteorology, e-cosmetic.

International audience; Meteosat images are routinely processed at Transvalor / MINES ParisTech for assessing the solar radiation at ground by the means of the Heliosat-2 method. So far, Heliosat-2 was launched every night to update the HelioClim-3 (HC3) database with the images collected during the day. HC3 data were thus available so far at d-1. Several requirements were made by customers of HC3 for a real-time and forecast capability for horizons up to 2 h. It would help in managing the PV plants or intelligent buildings, and eventually increasing the financial gains. The major challenges to develop such a capability were pertaining to the scientific domain in order to find an accurate method, and to operational constraints. The constraints are on both sides: provider and customer. The method should be fast enough to enable the processing of large areas such as Europe, and its outputs should be such as they can be directly ingested in the own processes of the customers. The selected model is based on a local persistence and has been validated against in situ measurements. A prototype has been set up and tested for several weeks by 15 customers. The customers used the outputs of this prototype as inputs to their own processes and made their own validation by comparing the results against measurements of, e.g. PV yield. The feedback gathered from testers was overall positive and a new operational service was set up based on the prototype (http://www.soda-pro.com/soda-products/real-time-and-forecast). Further validation campaigns are planned during the second semester of 2015, either by comparing to ground measurements or performed by users with their own criteria.

International audience; The atmosphere service of Copernicus combines state-of-the-art atmospheric modeling on aerosols with Earth observation data to provide information services covering European air quality, global atmospheric composition, climate, and UV and solar energy. Besides the radiation service, it provides information on – among others – ultraviolet radiation and aerosol concentration on a global scale as parameters being of interest for the solar energy sector. Within the radiation service, existing historical databases HelioClim-3 and SOLEMI for monitoring incoming surface solar irradiance have been further developed. The new service is jointly provided by DLR, Armines, and Transvalor. The Monitoring Atmospheric Composition and Climate (MACC) project series has been preparing for the service provision, which is now operational as part of the Copernicus programme. Data are made available both via the Copernicus portal and the SODA portal. The radiation service consists of an all-sky radiation time series service taking satellite-based cloud parameters into account and a clear-sky radiation time series service for cloud-free skies. Quality of the service is ensured by regular input quality control, regular quarterly benchmarking against ground stations, and regular monitoring of the consistency in order to detect possible trends. The fast clear-sky model called Copernicus McClear implements a fully physical modeling replacing empirical relations or simpler models used before. It exploits the recent results on aerosol properties and total column content in water vapor and ozone produced by the Copernicus service. Details of the clear-sky radiation service are the same as the all-sky service, but the spatial coverage is global and any point of interest can be interpolated. Data elements provided are clear sky (i.e. cloud free) global, direct, diffuse and direct at normal incidence irradiances, and a verbose mode with all atmospheric input parameters used for clouds, aerosols, ozone, water vapor and the surface reflective properties. The paper will summarize the new service capabilities and illustrate quality control and validation results.