Baseline Surface Radiation Network Stations Research Articles

Interdecadal Changes of the MERRA-2 Incoming Surface Solar Radiation (SSR) and Evaluation against GEBA & BSRN Stations

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.

Impact of tropical convective conditions on solar irradiance forecasting based on cloud motion vectors

Intra-day forecasts of global horizontal solar irradiance (GHI) are widely produced by displacing existing clouds on a geo-stationary satellite image to their future locations with cloud motion vectors (CMVs) derived from preceding images. The CMV estimation methods assume rigid cloud bodies with advective motion, which performs reasonably well in mid-latitudes but can be strained for tropical and sub-tropical climatic zones during prolonged periods of seasonal convection. We study the impact of the South Asian monsoon time convection on the accuracy of CMV based forecasts by analysing 2 years of forecasts from three commonly used CMV methods—Block-match, Farnebäck (Optical flow) and TV-L1 (Optical flow). Forecasted cloud index (CI) maps of the entire image section are validated against analysis CI maps for the period 2018–2019 for forecast lead times from 0 to 5.5 h. Site-level GHI forecasts are validated against ground measured data from two Baseline Surface Radiation Network stations—Gurgaon (GUR) and Tiruvallur (TIR), located in hot semi-arid and tropical savanna climatic zones respectively. The inter-seasonal variation of forecast accuracy is prominent and a clear link is found between the increase in convection, represented by a decrease in outgoing longwave radiation (OLR), and the decrease in forecast accuracy. The GUR site shows the highest forecast error in the southwest monsoon period and exhibits a steep rise of forecast error with the increase in convection. The highest forecast error occurs in the northeast monsoon period of December in TIR. The impact of convection on the number of erroneous time blocks of predicted photovoltaic production is also studied. Our results provide insights into the contribution of convection to errors in CMV based forecasts and shows that OLR can be used as a feature in future forecasting methods to consider the impact of convection on forecast accuracy.

An Improved Algorithm for Estimating Surface Shortwave Radiation: Preliminary Evaluation With MODIS Products

Cloud parameters, as key inputs in radiative transfer algorithms, have a critical impact on surface shortwave radiation (SSR) computation. By introducing a parameterization of cloud transmittance and reflectance, based on radiative transfer simulations, this study improves the accuracy of an existing physically based model which severely underestimates SSR under thick cloud conditions. The cloud parameterization adopts the single-layer cloud model and simulates cloud transmittances and reflectances by varying cloud optical thickness, cloud particle size, and solar zenith angle. The revised model is applied to estimate instantaneous SSR using Moderate-resolution Imaging Spectroradiometer (MODIS) atmospheric and land products. The retrieved SSR is evaluated against observation data from 41 Baseline Surface Radiation Network (BSRN) stations and is also compared with the MODIS official SSR product. The root mean square error (RMSE) of the estimated instantaneous radiation is approximately 52 and 98 W m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−2</sup> under clear-sky and all-sky conditions, respectively. The accuracy of the improved parameterization is higher than that of the original model, and there is no obvious underestimation of SSR in the case of high cloud optical thickness. Therefore, the new algorithm improves the accuracy of SSR estimates in the presence of thick clouds. Retrievals with the improved model also achieve higher accuracy than the MODIS official SSR product (MCD18A1). Finally, the reliable performance of the scheme at most BSRN stations illustrates that the improved model can be used to map SSR on a global scale.

Effects of the meteorological data resolution and aggregation on the optimal design of photovoltaic power plants

The accuracy of the simulation and optimization of ground-mounted photovoltaic plants depends on the reliability of the meteorological datasets, which is affected by their source, length, and resolution. Quantifying the effect of the irradiance data temporal resolution on the optimal design parameters and the expected profitability is important to improve the credibility of photovoltaic design simulations. The optimal values of nine important design parameters, the annual energy yield, and the levelized cost of electricity are calculated for 50 Baseline Surface Radiation Network stations by an automatic photovoltaic optimization method based on datasets with six different resolutions created by two aggregation methods. The aggregation by averaging suppresses the high irradiance values resulting from the transient cloud enhancement effect, while the aggregation by sampling a single value from the middle of each aggregation interval can retain the original distribution of minute-resolution data. The optimization based on averaged hourly data underestimates the levelized cost of electricity by up to 3%, overestimates the inverter sizing ratio by 0.05 on average, and the tilt angle by up to 5° compared to the high-resolution datasets. The datasets aggregated by sampling provide more reliable results even at lower resolutions; therefore, it can be an effective technique for accurate photovoltaic optimization without the long calculation time of the minute-resolution simulation.

The De-Icing Comparison Experiment (D-ICE): a study of broadband radiometric measurements under icing conditions in the Arctic

Abstract. Surface-based measurements of broadband shortwave (solar) and longwave (infrared) radiative fluxes using thermopile radiometers are made regularly around the globe for scientific and operational environmental monitoring. The occurrence of ice on sensor windows in cold environments – whether snow, rime, or frost – is a common problem that is difficult to prevent as well as difficult to correct in post-processing. The Baseline Surface Radiation Network (BSRN) community recognizes radiometer icing as a major outstanding measurement uncertainty. Towards constraining this uncertainty, the De-Icing Comparison Experiment (D-ICE) was carried out at the NOAA Atmospheric Baseline Observatory in Utqiaġvik (formerly Barrow), Alaska, from August 2017 to July 2018. The purpose of D-ICE was to evaluate existing ventilation and heating technologies developed to mitigate radiometer icing. D-ICE consisted of 20 pyranometers and 5 pyrgeometers operating in various ventilator housings alongside operational systems that are part of NOAA's Barrow BSRN station and the US Department of Energy Atmospheric Radiation Measurement (ARM) program North Slope of Alaska and Oliktok Point observatories. To detect icing, radiometers were monitored continuously using cameras, with a total of more than 1 million images of radiometer domes archived. Ventilator and ventilator–heater performance overall was skillful with the average of the systems mitigating ice formation 77 % (many &gt;90 %) of the time during which icing conditions were present. Ventilators without heating elements were also effective and capable of providing heat through roughly equal contributions of waste energy from the ventilator fan and adiabatic heating downstream of the fan. This provided ∼0.6 ∘C of warming, enough to subsaturate the air up to a relative humidity (with respect to ice) of ∼105 %. Because the mitigation technologies performed well, a near complete record of verified ice-free radiometric fluxes was assembled for the duration of the campaign. This well-characterized data set is suitable for model evaluation, in particular for the Year of Polar Prediction (YOPP) first Special Observing Period (SOP1). We used the data set to calculate short- and long-term biases in iced sensors, finding that biases can be up to +60 W m−2 (longwave) and −211 to +188 W m−2 (shortwave). However, because of the frequency of icing, mitigation of ice by ventilators, cloud conditions, and the timing of icing relative to available sunlight, the biases in the monthly means were generally less than the aggregate uncertainty attributed to other conventional sources in both the shortwave and longwave.

Constructing a gridded direct normal irradiance dataset in China during 1981–2014

High-quality direct normal irradiance (DNI) observations are of vital importance for the optimal design, installation and profitability of CST plants. Numerous models have been developed for estimating DNI at regional or global scales. The goal of this study is to generate a gridded DNI dataset for all-sky conditions over mainland China during 1981–2014, based on a broadband DNI estimates for clear-sky conditions (obtained with the REST2_v9.1 model) and cloud transmittance estimates using sunshine observations. The results indicate that the REST2_v9.1 model can be used to estimate DNI with high accuracy and consistency, owing to its robust two-band parameterization of the radiation transfer processes. Comparing daily DNI modeled predictions to measurements at 6 BSRN (Baseline Surface Radiation Network) stations in East Asia results in relatively low errors statistics: RMSE, MAE, RMSER, MAER and R of 1.436 MJm−2, 0.900 MJm−2, 22.26%, 13.95% and 0.972. Somewhat lessened agreement is found at the 17 CMA (China meteorological administrations) stations: 4.064 MJm−2, 2.864 MJm−2, 34.41%, 24.26% and 0.914, respectively. A gridded DNI dataset is constructed using sunshine duration measurements at 2474 CMA meteorological stations and the MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, version 2) reanalysis products. The spatial and temporal variations of DNI in different climate zones throughout China are also investigated. The gridded DNI datasets generated in this study would assist in numerous solar resource studies and solar energy applications.

Analysis of the temporal–spatial changes in surface radiation budget over the Antarctic sea ice region

The surface radiation budget (SRB) of the Antarctic sea ice region (ASIR) is important for the climate change in Antarctica, which partly explains the global warming. Long-term (1982–2015) satellite-derived (EUMETSAT Satellite Application Facility on Climate Monitoring, CLARA-A2) and reanalysis (European Centre for Medium-Range Weather Forecasts, ERA-Interim) datasets provided high quality and global coverage surface radiation products, which enabled us to quantify the SRB of the ASIR and widen our understanding of the polar climate. The downwelling longwave (LW) and shortwave (SW) radiation from the two datasets were validated at two Baseline Surface Radiation Network Stations (i.e., Neumayer and Syowa). Cloud LW emission dominated over cloud SW reflection and absorption due to high-albedo over the sea ice surface, thereby leading to a positive all-wave cloud radiative forcing (CRF) within 0–100 W m−2. This result indicated a warming effect on the surface of the ASIR, except during the austral summer. Compared with the all sky, substantial solar radiation was absorbed by the surface which under the clear sky will result in the increasing of temperature and sea ice melting during the austral summer; hence, the SW CRF had a major influence on all-wave CRF and caused more than −150 W m−2 of cooling near the edge of the sea ice. The summer averages of all-wave CRF over the ASIR surface were − 43.02 and − 35.74 W m−2 for the ERA-Interim and CLARA-A2 datasets, respectively. Contrary to the effect of CRF, the surface net LW radiation (LWnet) exhibited a cooling effect over the ASIR surface throughout the year and peaks at −47.21 W m−2 for CLARA-A2 dataset in December. Meanwhile, a warming effect was caused by the surface net SW radiation (SWnet) peaks at 101.52 and 104.09 W m−2 for the ERA-Interim and CLARA-A2 datasets, respectively. In summer, the warming effect caused by the surface net all-wave radiation in East Antarctica was deeper than that in West Antarctica. The time series and trend analysis showed that the surface net radiation and CRF over the entire ASIR basically exhibited a decreasing trend. The descending speed of SWnet (−3.652 W m−2 decade−1) about five times faster than that of LWnet (−0.722 W m−2 decade−1). Although a significant trough appeared in 1993/1994 of the time series curves of All-wave CRF, it had a deeply negative trend with about −3.443 W m−2 decade−1. Detailed analysis on the five longitudinal sectors around Antarctica (the Weddell Sea, the Indian Ocean, the Pacific Ocean, the Ross Sea, and the Bellingshausen-Amundsen Sea) can further help us understand the SRB of the ASIR.

Description of the Baseline Surface Radiation Network (BSRN) station at the Izaña Observatory (2009–2017): measurements and quality control/assurance procedures

Abstract. The Baseline Surface Radiation Network (BSRN) was implemented by the World Climate Research Programme (WCRP) starting observations with nine stations in 1992, under the auspices of the World Meteorological Organization (WMO). Currently, 59 BSRN stations submit their data to the WCRP. One of these stations is the Izaña station (station IZA, no. 61) that enrolled in this network in 2009. This is a high-mountain station located in Tenerife (Canary Islands, Spain, at 28.3∘ N, 16.5∘ W; 2373 m a.s.l.) and is a representative site of the subtropical North Atlantic free troposphere. It contributes with basic-BSRN radiation measurements, such as global shortwave radiation (SWD), direct radiation (DIR), diffuse radiation (DIF) and longwave downward radiation (LWD), and extended-BSRN measurements, including ultraviolet ranges (UV-A and UV-B), shortwave upward radiation (SWU) and longwave upward radiation (LWU), and other ancillary measurements, such as vertical profiles of temperature, humidity and wind obtained from radiosonde profiles (WMO station no. 60018) and total column ozone from the Brewer spectrophotometer. The IZA measurements present high-quality standards since more than 98 % of the data are within the limits recommended by the BSRN. There is an excellent agreement in the comparison between SWD, DIR and DIF (instantaneous and daily) measurements with simulations obtained with the LibRadtran radiative transfer model. The root mean square error (RMSE) for SWD is 2.28 % for instantaneous values and 1.58 % for daily values, while the RMSE for DIR is 2.00 % for instantaneous values and 2.07 % for daily values. IZA is a unique station that provides very accurate solar radiation data in very contrasting scenarios: most of the time under pristine sky conditions and periodically under the effects of the Saharan air layer characterized by a high content of mineral dust. A detailed description of the BSRN program at IZA, including quality control and quality assurance activities, is given in this work.

Determining and analysing solar irradiation based on freely available data: A case study from Croatia

The aim of this research was to determine the global horizontal irradiation (GHI) for the Republic of Croatia with the GRASS GIS r.sun module and to compare it with the values of solar irradiation obtained from satellite images, ground measurements and commercial providers. Since the results obtained from the r.sun module have no quality control, the accuracy assessment was made on ground solar irradiation measurements obtained from Baseline Surface Radiation Network stations (BSRN) and stations from the Meteorological and Hydrological Institute of Croatia (DHMZ). The differences in accuracy obtained by comparison with BSRN stations indicate a 3% higher accuracy of r.sun data compared to SoDa (Solar radiation data). The trend was also observed in the differences obtained by calculating the deviations from DHMZ stations (0.5%). Compared to the r.sun and SoDa data, MSG (Meteosat Second Generation) data have 24% (BSRN) and 26% (DHMZ) higher accuracy. The reason why r.sun and SoDa data have an advantage over MSG is the higher spatial resolution. Another important aspect of using solar energy compared to other renewable resources is that Croatia experiences an increase in electricity consumption due to tourism and imports approximately 200 GWh in the summer months when the GHI value is up to 5 times higher compared to in the winter period. It can be concluded that using solar energy can significantly reduce the need for electricity imports in Croatia and ensure sustainable environmental development.

Optimal solar tracking strategy to increase irradiance in the plane of array under cloudy conditions: A study across Europe

In this study, we have performed an analysis of potential irradiation increase across Europe, derived from moving photovoltaic (PV) modules to a horizontal position during cloudy and overcast situations. The motivation of research is that PV technology has expanded outside countries endowed with high solar irradiation and it is nowadays present in high-latitude regions and areas with frequent cloud cover. Unlike concentrating solar technologies, PV panels can make use of both beam and diffuse irradiance. During cloudy or overcast situations, most of solar irradiance comes from the diffuse component, which approaches an isotropic behavior under those circumstances. Then, a PV panel facing the zenith would receive more irradiation than a PV panel following the Sun’s path.In our approach, we have used data from several Baseline Surface Radiation Network stations. Results showed a yearly potential irradiation increase of 3.01% with respect to a reference single-axis tracking system (SATS) in the northern-most station. Values for other stations were correlated to climate. Thus, the sunniest station would increase its annual irradiation by 0.16% compared to a reference SATS. Daily irradiation increases of up to 19.91% were registered.Two predictive models were created to develop a SATS, which could determine in advance the optimum position of PV panels. Model 1, which was based on the persistence of irradiance, was designed to work real time in order to increase production. Yearly gains of up to 2.51% of irradiation were registered. However, Model 2 was developed to update production forecasts in the intra-day electricity markets so that PV plant owners can maximize their revenues. It is based on irradiance predictions from a numerical weather prediction service and underperformed current SATS.

Modification of the SUNFLUX solar radiation scheme with a new aerosol parameterization and its validation using observation network data

SUNFLUX is a fast parameterization scheme for determination of the solar radiation at the Earth’s surface. In this paper, SUNFLUX is further modified in the treatment of aerosols. A new aerosol parameterization scheme is developed for five aerosol species. Observational data from Baseline Surface Radiation Network (BSRN), Surface Radiation Budget Network (SURFRAD) and Aerosol Robotic Network (AERONET) stations are used to evaluate the accuracy of the original and modified SUNFLUX schemes. General meteorological data are available at SURFRAD stations, but not at BSRN stations. Therefore, the total precipitable water content and aerosol data are obtained from AERONET stations. Fourteen stations are selected from both BSRN and AERONET. Cloud fraction data from MODIS are further used to screen the cloud. Ten-year average aerosol mixing ratios simulated by the CAM-chem system are used to calculate the fractions of aerosol optical depth for each aerosol species, and these fractions are further used to convert the observed total aerosol optical depth into the components of individual species for use in the evaluations. The proper treatment of multiple aerosol types in the model is discussed. The evaluation results using SUNFLUX with the new aerosol scheme, in terms of the BSRN dataset, are better than those using the original aerosol scheme under clear-sky conditions. However, the results using the SURFRAD dataset are slightly worse, attributable to the differences in the input water vapor and aerosol optical depth. Sensitivity tests are conducted to investigate the error response of the SUNFLUX scheme to the errors in the input variables.

Revising shortwave and longwave radiation archives in view of possible revisions of the WSG and WISG reference scales: methods and implications

Abstract. A large number of radiometers are traceable to the World Standard Group (WSG) for shortwave radiation and the interim World Infrared Standard Group (WISG) for longwave radiation, hosted by the Physikalisch-Meteorologisches Observatorium Davos/World Radiation Centre (PMOD/WRC, Davos, Switzerland). The WSG and WISG have recently been found to over- and underestimate radiation values, respectively (Fehlmann et al., 2012; Gröbner et al., 2014), although research is still ongoing. In view of a possible revision of the reference scales of both standard groups, this study discusses the methods involved and the implications on existing archives of radiation time series, such as the Baseline Surface Radiation Network (BSRN). Based on PMOD/WRC calibration archives and BSRN data archives, the downward longwave radiation (DLR) time series over the 2006–2015 period were analysed at four stations (polar and mid-latitude locations). DLR was found to increase by up to 3.5 and 5.4 W m−2 for all-sky and clear-sky conditions, respectively, after applying a WISG reference scale correction and a minor correction for the dependence of pyrgeometer sensitivity on atmospheric integrated water vapour content. Similar increases in DLR may be expected at other BSRN stations. Based on our analysis, a number of recommendations are made for future studies.

Global Performance of a Fast Parameterization Scheme for Estimating Surface Solar Radiation From MODIS Data

A fast parameterization scheme named SUNFLUX is first used in this paper to estimate instantaneous surface solar radiation (SSR) based on products from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard both Terra and Aqua platforms. The scheme mainly takes into account the absorption and scattering processes due to clouds, aerosols, and gas in the atmosphere. The estimated instantaneous SSR is evaluated against surface observations obtained from seven stations of the surface radiation budget network (SURFRAD), four stations in the North China Plain (NCP) and 40 stations of the baseline surface radiation network (BSRN). The statistical results for evaluation against these three data sets show that the relative root-mean-square error (RMSE) values of SUNFLUX are less than 15%, 16%, and 17%, respectively. Daily SSR is derived through temporal upscaling from the MODIS-based instantaneous SSR estimates, and is validated against surface observations. The relative RMSE values for daily SSR estimates are about 16% at the seven SURFRAD stations, four NCP stations, 40 BSRN stations, and 90 China Meteorological Administration (CMA) radiation stations. The accuracy of the scheme is generally higher than those of previous algorithms, and thus can be potentially applied on geostationary satellites for mapping high-resolution SSR data in the future.

Validation of the new HelioClim-3 version 4 real-time and short-term forecast service using 14 BSRN stations

Abstract. 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.

Validation of HelioClim-3 Version 4, HelioClim-3 Version 5 and MACC-RAD Using 14 BSRN Stations

This communication presents the results of a comparison of three satellite-derived databases covering Africa, Europe, Middle East and part of South America, against corresponding 15min irradiations of very high quality measured by fourteen Baseline Surface Radiation Network (BSRN) stations. The three databases are accessible via the SoDa Service website, and are the two latest versions of HelioClim-3: versions 4 (HC3v4) and 5 (HC3v5), and the MACC-RAD database. The comparison was performed for durations of 15min, 1h, 1 day and 1 month for both the global irradiation received on a horizontal surface (GHI) and the direct irradiation received on a plane normal to sun rays (DNI).It is found that the three satellite-derived radiation databases exhibit satisfactory performances. For most of the fourteen locations, HC3v5 surpasses HC3v4 and MACC-RAD, with a bias ranging from -4 to 5% for the GHI and for all tested duration. The correlation coefficient is large for all databases and most often greater than 0.92 for 15min and 0.98 for daily irradiation for GHI. The RMSE is fairly constant for all locations for 15min and is approximately 20 kWh m-2 –slightly greater for MACC-RAD. -For daily irradiation, it ranges between 300 and 400 kWh m-2 for HC3v5, 300 and 500 kWh m-2 for HC3v4, and 400 and 550 kWh m-2 for MACC-RAD. Bias for the DNI is larger in absolute values than for GHI for all databases: -12 to 10% for HC3v5. The correlation coefficient is most often greater than 0.68 for 15min and 0.84 for daily irradiation. The RMSE for 15min ranges between 46 and 60 kWh m-2 for HC3v5, 46 and 63 kWh m-2 for HC3v4, and 48 and 66 kWh m-2 for MACC-RAD. For daily irradiation, it ranges between 1100 and 1600 kWh m-2 for HC3v5, between 1300 and 1700 kWh m-2 for HC3v4, and between 1000 and 1850 kWh m-2 for MACC-RAD. The MACC-RAD resource show promises provided the model for cloud properties is improved.

A Combination of Heliosat-1 and Heliosat-2 Methods for Deriving Solar Radiation from Satellite Images

Solar radiation estimation from geostationary satellite images is accepted by the international scientific community, especially where no previous ground radiometric measurements are available. The most accepted methodology is Heliosat. In this work, a combination of the existing methods Heliosat-1 and Heliosat-2 has been implemented for this purpose, and the obtained results are presented.To analyze the results provided by the implemented methodology a validation against measurements has been made. Firstly, solar Global Horizontal Irradiance (GHI) has been estimated from satellite images using data of the Meteosat Second Generation (MSG) satellite corresponding to the period from 2009 to 2011. Secondly, measurements recorded during the same period of time at the Cener station which belongs to the Baseline Surface Radiation Network (BSRN) have been obtained. Both estimated and measured data have been integrated into hourly values for the validation process.The obtained values for Cener BSRN station are a MBE of 2% and a RMSE of 113W/m2, which are smaller than the recommended values for hourly GHI data (MBE smaller than 5% and RMSE smaller than 160W/m2). During the months of summer the errors in terms of W/m2 are bigger than during the months of winter. However, since the irradiance is higher during the months of summer, the errors are smaller in terms of % during the months of summer. Although the methodology can be applied to locations where no ground measurements are available, it is preferable to analyze locations with available measured data.

Retrieval and validation of global, direct, and diffuse irradiance derived from SEVIRI satellite observations

AbstractThis paper discusses Surface Insolation under Clear and Cloudy skies derived from SEVIRI imagery (SICCS), a physics‐based, empirically adjusted algorithm developed for estimation of surface solar irradiance from satellite data. Its most important input are a cloud mask product and cloud properties derived from Meteosat/Spinning Enhanced Visible and Infrared Imager (SEVIRI) observations. These observations set the characteristics of the output, namely, a temporal resolution of 15 min, a nadir spatial resolution of 3 × 3 km2, the period from January 2004 until at least November 2012, and the domain equal to most of the Meteosat disc. SICCS computes global, direct, and diffuse irradiance separately. Direct irradiance for cloudy skies is estimated with an empirical method. Hourly means retrieved with SICCS were validated with data from eight Baseline Surface Radiation Network stations for the year 2006. We found median values of the station biases of +6 W/m2 (+5%) for direct irradiance, +1 W/m2 (+1%) for diffuse irradiance, and +7 W/m2 (+2%) for global irradiance. Replacing the three‐hourly aerosol optical thickness input by monthly means introduces considerable additional biases in the clear‐sky direct (−6%) and diffuse (+26%) irradiances. The performance of SICCS does not degrade when snow covers the surface. Biases do not vary with cloud optical thickness and cloud particle radius. However, the bias in global transmissivity tends to decrease with increasing cloud heterogeneity, and the bias in direct transmissivity is a function of the solar zenith angle. We discuss why satellite retrieval of surface solar irradiance is relatively successful.

The Izaña BSRN station

The BSRN (Baseline Surface Radiation Network) is a project of the Radiation Panel from the Global Energy and Water Cycle Experiment (GEWEX) under the umbrella of the World Climate Research Programme (WCRP). Since March 2009 the Izana Atmospheric Observatory belongs to the BSRN network. The Izana Observatory is a Global Atmospheric Watch station. It is a high mountain station, located at Tenerife Island (2.367 m. above sea level). The measurements recorded in this station are sent on a monthly basic to the BSRN database are: global, direct, diffuse, longwave downward, net, UV-A, UV-B radiation and the data obtained with rawinsondes launched daily from the Santa Cruz de Tenerife station, located 30 km from the Izana station. In this work we focused on the study of the global, direct and diffuse radiation measurements, performed at the Izana Observatory during 2009. The results show a high quality of BSRN measurements. Although Izana is a high mountain station there are 357 days with valid measurements for 2009. A 99% of the measurements are within the limits recommended by the BSRN. Furthermore there is a very good agreement between the measurements and the simulated values with the radiative transfer model LibRadtran using a sample set of 129 days with cloud free sky conditions. The daily values of the global and direct radiation show a RMSE lower than 2%, while the diffuse radiation shows a RMSE of about 10%.

Arctic and Antarctic diurnal and seasonal variations of snow albedo from multiyear Baseline Surface Radiation Network measurements

This study analyzes diurnal and seasonal variations of snow albedo at four Baseline Surface Radiation Network stations in the Arctic and Antarctica from 2003 to 2008 to elucidate similarities and differences in snow albedo diurnal cycles across geographic zones and to assess how diurnal changes in snow albedo affect the surface energy budget. At the seasonal scale, the daily albedo for the perennial snow at stations South Pole and Georg von Neumayer in Antarctica has a similar symmetric variation with solar zenith angle (SZA) around the austral summer; whereas the daily albedo for the seasonal snow at stations Barrow, Alaska, and Ny-Alesund, Spitsbergen, in the Arctic tends to decrease with SZA decrease from winter to spring before snow starts melting. At the hourly scale, each station shows unique diurnal cycles due to different processes that affect snow albedo such as cloud cover, snow metamorphism, surface hoar formation, SZA, solar azimuth angle, and surface features. Cloud escalates the snow albedo at all four stations by shifting solar radiation to visible wavelengths and diminishes the diurnal variation by diffusing incident solar radiation. The 24 h mean snow albedo is higher on cloudy than clear days by 0.02 at the South Pole (December) and Barrow (May), 0.05 at Neumayer (December), and 0.07 at Ny-Alesund (April). Snow surface structures, for example, wind-channeled sastrugi, appear to be a controlling factor in the diurnal variation of clear-sky snow albedo at the South Pole and Ny-Alesund. The surface hoar formation cycles and snow metamorphism are consistent with the asymmetric diurnal variation of snow albedo at Neumayer and Barrow. Near the melting point temperature, melt-freeze cycles exceed cloud and surface structure impacts and dominate the diurnal variation of snow albedo at stations Barrow and Ny-Alesund. The satellite-measured clear-sky snow albedo usually underestimates the average all-sky snow albedo at these stations. These results illustrate the potential biases in daily and monthly albedo products constructed from sun-synchronous satellite daily instantaneous observations which inevitably undersample the diurnal variation of snow albedo.

Observing snowmelt dynamics on fast ice in Kongsfjorden, Svalbard, with NOAA/AVHRR data and field measurements

Temporal snowmelt dynamics on fast ice in Kongsfjorden/Svalbard are studied for the period 1990–2003, using visible and near-infrared channels of the Advanced Very High Resolution Radiometer (AVHRR). Long-term radiation data from an adjacent Baseline Surface Radiation Network station, as well as extensive glaciological and meteorological field measurements on the melting ice in 2002 and 2003, are used to validate a snowmelt index derived from the satellite data. This study shows that the remote sensing data are in good agreement with the field observations. However, the temporal variability of atmospheric water vapour has an impact on the snowmelt index, and must be accounted for through atmospheric correction. The analysis of long-term satellite data provides valuable insight into the strength and rate of the snowvolume decay, and reveals a strong interannual variability of the snowmelt intensity. However, a precise date for determining melt onset requires clear-sky AVHRR data throughout the onset period.