scholarly journals Satellite-based trends of solar radiation and cloud parameters in Europe

2018 ◽  
Vol 15 ◽  
pp. 31-37 ◽  
Author(s):  
Uwe Pfeifroth ◽  
Jedrzej S. Bojanowski ◽  
Nicolas Clerbaux ◽  
Veronica Manara ◽  
Arturo Sanchez-Lorenzo ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Water Cycle ◽  
Parameter Analysis ◽  
Positive Trend ◽  
Climate Data ◽  
High Quality ◽  
Surface Solar Radiation ◽  
Cloud Parameters ◽  
Common Framework ◽  
Spatio Temporal

Abstract. Solar radiation is the main driver of the Earth's climate. Measuring solar radiation and analysing its interaction with clouds are essential for the understanding of the climate system. The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) generates satellite-based, high-quality climate data records, with a focus on the energy balance and water cycle. Here, multiple of these data records are analyzed in a common framework to assess the consistency in trends and spatio-temporal variability of surface solar radiation, top-of-atmosphere reflected solar radiation and cloud fraction. This multi-parameter analysis focuses on Europe and covers the time period from 1992 to 2015. A high correlation between these three variables has been found over Europe. An overall consistency of the climate data records reveals an increase of surface solar radiation and a decrease in top-of-atmosphere reflected radiation. In addition, those trends are confirmed by negative trends in cloud cover. This consistency documents the high quality and stability of the CM SAF climate data records, which are mostly derived independently from each other. The results of this study indicate that one of the main reasons for the positive trend in surface solar radiation since the 1990's is a decrease in cloud coverage even if an aerosol contribution cannot be completely ruled out.

scholarly journals Effects of Aerosols and Clouds on the Levels of Surface Solar Radiation and Solar Energy in Cyprus

2021 ◽  
Author(s):  
Ilias Fountoulakis ◽  
Panagiotis Kosmopoulos ◽  
Kyriakoula Papachristopoulou ◽  
Panagiotis-Ioannis Raptis ◽  
Rodanthi-Elisavet Mamouri ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Renewable Energy Sources ◽  
Financial Loss ◽  
Low Latitude ◽  
High Quality ◽  
Surface Solar Radiation ◽  
Satellite Retrievals ◽  
Different Types ◽  
Fine Resolution

Cyprus plans to drastically increase the share of renewable energy sources from 13.9% in 2020 to 22.9% in 2030. Solar energy can play a key role in the effort to fulfil this goal. The potential for production of solar energy over the island is much higher than most of European territory because of the low latitude of the island and the nearly cloudless summers. In this study, high quality and fine resolution satellite retrievals of aerosols and dust, from the newly developed MIDAS climatology, as well as information for clouds from CMSAF are used in order to quantify the effects of aerosols, dust, and clouds on the levels of surface solar radiation (SSR) and the corresponding financial loss for different types of installations for production of solar energy. An SSR climatology has been also developed based on the above information. Ground-based measurements were also incorporated to study the contribution of different species to the aerosol mixture and the effects of day-to-day variability of aerosols on SSR. Aerosols attenuate 5 – 10% of annual GHI and 15 – 35% of annual DNI, while clouds attenuate ~25 – 30% and 35 – 50% respectively. Dust is responsible for 30 – 50% of the overall attenuation by aerosols.

Variability and Trends of Surface Solar Radiation in Europe based on satellite- and surface-based data

2020 ◽  
Author(s):  
Uwe Pfeifroth ◽  
Jörg Trentmann
Keyword(s):  
Data Center ◽  
Water Cycle ◽  
Surface Radiation ◽  
Climate Data ◽  
Surface Solar Radiation ◽  
Global Energy ◽  
Radiation Data ◽  
Climate Monitoring ◽  
Data Record ◽  
Surface Measurements

<p>The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) generates satellite-based  high-quality climate data records, with a focus on the global energy and water cycle. The new concept of Interim Climate Data Records (ICDRs) that extent the fixed-length Climate Data Records (CDRs) into 'near-realtime' in a consistent way, enables climate monitoring at a higher level of accuracy.</p><p>It has been found in recent studies based on surface and satellite data that on average SSR has been increasing in the last 3 decades in Europe (e.g. Sanchez-Lorenzo et al. 2017, Pfeifroth et al. 2018) - especially in spring and summer. Here we use the latest SARAH-2.1 TCDR (1983-2017), potentially together with its corresponding ICDR (2018 onwards), to analyze if the found positve trends in SSR are about to continue. In this respect, the satellite-based data record will be compared and validated with surface measurements given by the Baseline Surface Radiation Network (BSRN), the  World Radiation Data Center (WRDC) and the Global Energy Balance Archive (GEBA). A reasonable line of potential reasons for the found spring and summertime brightening in Europe is discussed.</p>

scholarly journals Evaluating the spatio-temporal performance of sky-imager-based solar irradiance analysis and forecasts

2016 ◽  
Vol 16 (5) ◽  
pp. 3399-3412 ◽  
Author(s):  
Thomas Schmidt ◽  
John Kalisch ◽  
Elke Lorenz ◽  
Detlev Heinemann
Keyword(s):  
Solar Radiation ◽  
Forecast Error ◽  
Forecast Skill ◽  
Small Scale ◽  
Surface Solar Radiation ◽  
Data Set ◽  
Forecast Performance ◽  
Electric Power Supply ◽  
Sky Imager ◽  
Spatio Temporal

Abstract. Clouds are the dominant source of small-scale variability in surface solar radiation and uncertainty in its prediction. However, the increasing share of solar energy in the worldwide electric power supply increases the need for accurate solar radiation forecasts. In this work, we present results of a very short term global horizontal irradiance (GHI) forecast experiment based on hemispheric sky images. A 2-month data set with images from one sky imager and high-resolution GHI measurements from 99 pyranometers distributed over 10 km by 12 km is used for validation. We developed a multi-step model and processed GHI forecasts up to 25 min with an update interval of 15 s. A cloud type classification is used to separate the time series into different cloud scenarios. Overall, the sky-imager-based forecasts do not outperform the reference persistence forecasts. Nevertheless, we find that analysis and forecast performance depends strongly on the predominant cloud conditions. Especially convective type clouds lead to high temporal and spatial GHI variability. For cumulus cloud conditions, the analysis error is found to be lower than that introduced by a single pyranometer if it is used representatively for the whole area in distances from the camera larger than 1–2 km. Moreover, forecast skill is much higher for these conditions compared to overcast or clear sky situations causing low GHI variability, which is easier to predict by persistence. In order to generalize the cloud-induced forecast error, we identify a variability threshold indicating conditions with positive forecast skill.

scholarly journals A New Long-Term Downward Surface Solar Radiation Dataset over China from 1958 to 2015

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6167
Author(s):  
Ning Hou ◽  
Xiaotong Zhang ◽  
Weiyu Zhang ◽  
Jiawen Xu ◽  
Chunjie Feng ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Dominant Role ◽  
Northern China ◽  
Climate Data ◽  
Surface Solar Radiation ◽  
Term Variation ◽  
Meteorological Observations ◽  
Increasing Demand ◽  
Variation Trends

Downward surface solar radiation (Rs) plays a dominant role in determining the climate and environment on the Earth. However, the densely distributed ground observations of Rs are usually insufficient to meet the increasing demand of the climate diagnosis and analysis well, so it is essential to build a long-term accurate Rs dataset. The extremely randomized trees (ERT) algorithm was used to generate Rs using routine meteorological observations (2000–2015) from the Climate Data Center of the Chinese Meteorological Administration (CDC/CMA). The estimated Rs values were validated against ground measurements at the national scale with an overall correlation coefficient value of 0.97, a mean bias of 0.04 Wm−2, a root-mean-square-error value of 23.12 Wm−2, and a mean relative error of 9.81%. It indicates that the estimated Rs from the ERT-based model is reasonably accurate. Moreover, the ERT-based model was used to generate a new daily Rs dataset at 756 CDC/CMA stations from 1958 to 2015. The long-term variation trends of Rs at 454 stations covering 46 consecutive years (1970–2015) were also analyzed. The Rs in China showed a significant decline trend (−1.1 Wm−2 per decade) during 1970–2015. A decreasing trend (−2.8 Wm−2 per decade) in Rs during 1970–1992 was observed, followed by a recovery trend (0.23 Wm−2 per decade) during 1992–2015. The recovery trends at individual stations were found at 233 out of 454 stations during 1970–2015, which were mainly located in southern and northern China. The new Rs dataset would substantially provide basic data for the related studies in agriculture, ecology, and meteorology.

scholarly journals Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data

2016 ◽  
Vol 16 (4) ◽  
pp. 2543-2557 ◽  
Author(s):  
Wenjun Tang ◽  
Jun Qin ◽  
Kun Yang ◽  
Shaomin Liu ◽  
Ning Lu ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Temporal Resolution ◽  
Surface Radiation ◽  
Mean Bias Error ◽  
Haihe River Basin ◽  
High Temporal Resolution ◽  
Spatiotemporal Resolution ◽  
Surface Solar Radiation ◽  
Radiation Data ◽  
Cloud Parameters

Abstract. Cloud parameters (cloud mask, effective particle radius, and liquid/ice water path) are the important inputs in estimating surface solar radiation (SSR). These parameters can be derived from MODIS with high accuracy, but their temporal resolution is too low to obtain high-temporal-resolution SSR retrievals. In order to obtain hourly cloud parameters, an artificial neural network (ANN) is applied in this study to directly construct a functional relationship between MODIS cloud products and Multifunctional Transport Satellite (MTSAT) geostationary satellite signals. In addition, an efficient parameterization model for SSR retrieval is introduced and, when driven with MODIS atmospheric and land products, its root mean square error (RMSE) is about 100 W m−2 for 44 Baseline Surface Radiation Network (BSRN) stations. Once the estimated cloud parameters and other information (such as aerosol, precipitable water, ozone) are input to the model, we can derive SSR at high spatiotemporal resolution. The retrieved SSR is first evaluated against hourly radiation data at three experimental stations in the Haihe River basin of China. The mean bias error (MBE) and RMSE in hourly SSR estimate are 12.0 W m−2 (or 3.5 %) and 98.5 W m−2 (or 28.9 %), respectively. The retrieved SSR is also evaluated against daily radiation data at 90 China Meteorological Administration (CMA) stations. The MBEs are 9.8 W m−2 (or 5.4 %); the RMSEs in daily and monthly mean SSR estimates are 34.2 W m−2 (or 19.1 %) and 22.1 W m−2 (or 12.3 %), respectively. The accuracy is comparable to or even higher than two other radiation products (GLASS and ISCCP-FD), and the present method is more computationally efficient and can produce hourly SSR data at a spatial resolution of 5 km.

scholarly journals SARAH-3 - a new satellite-based Cimate Data Record for surface radiation parameters from the CM SAF

2021 ◽  
Author(s):  
Uwe Pfeifroth ◽  
Jaqueline Drücke ◽  
Jörg Trentmann ◽  
Rainer Hollmann
Keyword(s):  
Water Cycle ◽  
Sunshine Duration ◽  
Global Radiation ◽  
Surface Radiation ◽  
Climate Data ◽  
Surface Solar Radiation ◽  
Data Set ◽  
Time Period ◽  
Data Record ◽  
Climate Data Record

<p>The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) generates and distributes high quality long-term climate data records (CDR) of energy and water cycle parameters, which are freely available.</p><p>In fall 2021, a new version of the “Surface Solar Radiation data set – Heliosat” will be released: SARAH-3. As the previous editions, the SARAH-3 climate data record is based on satellite observations from the first and second METEOSAT generations and provides various surface radiation parameters, including global radiation, direct radiation, sunshine duration, photosynthetic active radiation and others. SARAH-3 covers the time period 1983 to 2020 and offers 30-minute instantaneous data as well as daily and monthly means on a regular 0.05° x 0.05° lon/lat grid.</p><p>In this presentation, an overview of the SARAH climate data record and their applications will be provided. A focus will be on the SARAH-3 developments and improvements (i.e. improved consideration of snow-covered surfaces). First validation results of the new Climate Data Record using surface reference observations will be presented. Further, SARAH-3 will be used for the analysis of the climate variability in Europe during the last decades.</p><p>. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .</p>

scholarly journals Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data

2015 ◽  
Vol 15 (23) ◽  
pp. 35201-35236
Author(s):  
W. Tang ◽  
J. Qin ◽  
K. Yang ◽  
S. Liu ◽  
N. Lu ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Temporal Resolution ◽  
Surface Radiation ◽  
Mean Bias Error ◽  
Haihe River Basin ◽  
Bias Error ◽  
High Temporal Resolution ◽  
Surface Solar Radiation ◽  
Radiation Data ◽  
Cloud Parameters

Abstract. Cloud parameters (cloud mask, effective particle radius and liquid/ice water path) are the important inputs in determining surface solar radiation (SSR). These parameters can be derived from MODIS with high accuracy but their temporal resolution is too low to obtain high temporal resolution SSR retrievals. In order to obtain hourly cloud parameters, the Artificial Neural Network (ANN) is applied in this study to directly construct a functional relationship between MODIS cloud products and Multi-functional Transport Satellite (MTSAT) geostationary satellite signals. Meanwhile, an efficient parameterization model for SSR retrieval is introduced and, when driven with MODIS atmospheric and land products, its root mean square error (RMSE) is about 100 W m-2 for 44 Baseline Surface Radiation Network (BSRN) stations. Once the estimated cloud parameters and other information (such as aerosol, precipitable water, ozone and so on) are input to the model, we can derive SSR at high spatio-temporal resolution. The retrieved SSR is first evaluated against hourly radiation data at three experimental stations in the Haihe River Basin of China. The mean bias error (MBE) and RMSE in hourly SSR estimate are 12.0 W m-2 (or 3.5 %) and 98.5 W m-2 (or 28.9 %), respectively. The retrieved SSR is also evaluated against daily radiation data at 90 China Meteorological Administration (CMA) stations. The MBEs are 9.8 W m-2 (5.4 %); the RMSEs in daily and monthly-mean SSR estimates are 34.2 W m-2 (19.1 %) and 22.1 W m-2 (12.3 %), respectively. The accuracy is comparable or even higher than other two radiation products (GLASS and ISCCP-FD), and the present method is more computationally efficient and can produce hourly SSR data at a spatial resolution of 5 km.

scholarly journals Yearly changes in surface solar radiation in New Caledonia

2015 ◽  
Vol 12 (1) ◽  
pp. 1-4 ◽  
Author(s):  
P. Blanc ◽  
C. Coulaud ◽  
L. Wald
Keyword(s):  
Solar Radiation ◽  
New Caledonia ◽  
Solar Irradiation ◽  
Data Sets ◽  
Climate Data ◽  
Surface Solar Radiation ◽  
Data Set ◽  
The Mean ◽  
Energy Plants

Abstract. New Caledonia experiences a decrease in surface solar irradiation since 2004. It is of order of 4% of the mean yearly irradiation over the 10 years period: 2004–2013, and amounts to −9 W m−2. The preeminent roles of the changes in cloud cover and to a lesser extent, those in aerosol optical depth on the decrease in yearly irradiation are evidenced. The study highlights the role of data sets offering a worldwide coverage in understanding changes in solar radiation and planning large solar energy plants such as the ICOADS (International Comprehensive Ocean-Atmosphere Data Set) of the NOAA and MACC (Monitoring Atmosphere Composition and Climate) data sets combined with the McClear model.

scholarly journals Validation of CM SAF CLARA-A2 and SARAH-E Surface Solar Radiation Datasets over China

2018 ◽  
Vol 10 (12) ◽  
pp. 1977 ◽  
Author(s):  
Yawen Wang ◽  
Jörg Trentmann ◽  
Wenping Yuan ◽  
Martin Wild
Keyword(s):  
Solar Radiation ◽  
High Elevation ◽  
Anthropogenic Aerosols ◽  
High Quality ◽  
Urbanization Effect ◽  
Surface Solar Radiation ◽  
Climate Monitoring ◽  
Spatial Performance ◽  
Quality Surface ◽  
High Quality Surface

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.

scholarly journals Inter-Comparison and Evaluation of the Four Longest Satellite-Derived Cloud Climate Data Records: CLARA-A2, ESA Cloud CCI V3, ISCCP-HGM, and PATMOS-x

2018 ◽  
Vol 10 (10) ◽  
pp. 1567 ◽  
Author(s):  
Karl-Göran Karlsson ◽  
Abhay Devasthale
Keyword(s):  
Cloud Cover ◽  
Cloud Fraction ◽  
Seasonal Cycles ◽  
Climate Data ◽  
High Quality ◽  
Cloud Parameters ◽  
Latitude Region ◽  
Cloud Top Pressure ◽  
Global Mean ◽  
Good Agreement

Results from four global cloud climate data records (ISCCP-HGM, ESA Cloud CCI V3, CLARA-A2 and PATMOS-x) have been inter-compared in global time series plots, in global maps and in zonal region plots covering the period in common, 1984–2009. The investigated cloud parameters were total cloud fraction and cloud top pressure. Averaged seasonal cycles of cloud cover, as observed by the CALIPSO-CALIOP sensor over the 2007–2015 period, were also used as an additional independent and high-quality reference for the study of global cloud cover. All CDRs show good agreement on global cloud amounts (~65%) and also a weak negative trend (0.5–1.9% per decade) over the period of investigation. Deviations between the CDRs are seen especially over the southern mid-latitude region and over the poles. Particularly good results are shown by PATMOS-x and by ESA Cloud CCI V3 when compared to the CALIPSO-CALIOP reference. Results for cloud top pressure show large differences (~60 hPa) between ISCCP-HGM and the other CDRs for the global mean. The two CDR groups show also opposite signs in the trend over the period.

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