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 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>

Global and Regional Satellite-based Surface Solar Radiation data sets provided by the CM SAF

2021 ◽  
Author(s):  
Jörg Trentmann ◽  
Uwe Pfeifroth ◽  
Jaqueline Drücke ◽  
Roswitha Cremer
Keyword(s):  
Solar Radiation ◽  
Global Climate ◽  
Surface Radiation ◽  
Data Sets ◽  
Climate Data ◽  
Surface Solar Radiation ◽  
Climate Monitoring ◽  
Data Record ◽  
Irradiance Data ◽  
Climate Data Record

<p>The incoming surface solar radiation has been defined as an essential climate variable by GCOS. Long term monitoring of this part of the earth’s energy budget is required to gain insights on the state and variability of the climate system. In addition, climate data sets of surface solar radiation have received increased attention over the recent years as an important source of information for solar energy assessments, for crop modeling, and for the validation of climate and weather models.</p><p>The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) is deriving climate data records (CDRs) from geostationary and polar-orbiting satellite instruments. Within the CM SAF these CDRs are accompanied by operational data at a short time latency to be used for climate monitoring. All data from the CM SAF are freely available via www.cmsaf.eu.</p><p>Here we present the regional and global climate data records of surface solar radiation from the CM SAF. The regional SARAH-2.1 climate data record (Surface Solar Radiation Dataset – Heliosat, doi: 10.5676/EUM_SAF_CM/SARAH/V002_01) is based on observations from the series of Meteosat satellites. SARAH-2.1 provides high resolution data (temporal and spatial) of the surface solar radiation (global and direct) and the sunshine duration from 1983 to 2017 for the full view of the Meteosat satellite (i.e, Europe, Africa, parts of South America, and the Atlantic ocean). The global climate data record CLARA (CM SAF Clouds, Albedo and Radiation dataset from AVHRR data, doi: 10.5676/EUM_SAF_CM/CLARA_AVHRR/V002_01) is based on observations from the series of AVHRR instruments onboard polar-orbiting satellites. CLARA provides daily- and monthly-averaged global data of the solar irradiance (SIS) from January 1982 to June 2019 with a spatial resolution of 0.25°. In addition to the solar surface radiation, also the longwave surface radiation as well as surface albedo and numerous cloud properties are provided in CLARA. The high accuracy and stability of these data record allows the assessment of the spatial and temporal variability and trends as well as a number of other applications that require high-resolution surface irradiance data.</p><p>Both Thematic Climate Data Records (TCDR) are accompanied and temporally-extended by consistent data records, so-called Interim Climate Data Records (ICDR), which are provided with a latency of 5 days to support applications that require more recent surface irradiance data, e.g., operational climate monitoring.</p><p>In late 2021 / early 2022 new versions of both data records, SARAH and CLARA, will be provided by the CM SAF. The quality of these data records will be improved, e.g, by a better treatment of snow-covered surfaces, and temporally extended to cover the WMO climate reference period 1991 to 2020. Here, first results of the updated data records and their improvements will be presented.</p>

scholarly journals Satellite-derived sunshine duration data in the CM SAF SARAH-3 climate data record 

2021 ◽  
Author(s):  
Jaqueline Drücke ◽  
Uwe Pfeifroth ◽  
Jörg Trentmann ◽  
Rainer Hollmann
Keyword(s):  
Sunshine Duration ◽  
Climate Data ◽  
Surface Solar Radiation ◽  
Data Set ◽  
Climate Assessment ◽  
Climate Monitoring ◽  
Direct Normal Irradiance ◽  
Data Record ◽  
Definition Of ◽  
Climate Data Record

<p>Sunshine Duration (SDU) is an important parameter in climate monitoring (e.g., due to the availability of long term measurements) and weather application. The exceptional sunny years in Europe since 2018 have raised also the attention of the general public towards this parameter.</p><p>The definition of SDU by WMO via the threshold of 120 W/m<sup>2</sup> for the Direct Normal Irradiance (DNI) allows the estimation of sunshine duration from satellite-derived surface irradiance data. Sunshine duration is part of the climate data record (CDR) “Surface Solar Radiation data set – Heliosat” (SARAH-2.1, doi: 10.5676/EUM_SAF_CM/SARAH/V002_01) by EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF), which is based on observations from the series of Meteosat satellites. The provided temporal resolutions are daily and monthly sums with a grid space of 0.05°; the data are available from 1983 to 2017 at www.cmsaf.eu. This climate data record is temporally extended by the so-called SARAH-ICDR (Interim Climate Data record) with an average timeliness of 3 days to allow climate monitoring. An updated, improved, and extended version of the SARAH-2.1 CDR is currently being developed and will be made available in early 2022. The SARAH-3 CDR of sunshine duration, covering 1983 to 2020, will be improved compared to the current version, in particular during situations with snow-covered surfaces.</p><p>Here, the algorithm, improvements compared to SARAH-2.1 and a first validation will be presented for sunshine duration, especially for Germany and Europe. The validation is based on station data from Climate Data Center (CDC) for Germany and European Climate Assessment & Dataset (ECA&D) for Europe.</p>

Global validation of satellite-based and reanalysis surface solar radiation data sets

2020 ◽  
Author(s):  
Jörg Trentmann ◽  
Uwe Pfeifroth ◽  
Roswitha Cremer ◽  
Martin Stengel
Keyword(s):  
Solar Radiation ◽  
Current Knowledge ◽  
Global Scale ◽  
Reanalysis Data ◽  
Surface Radiation ◽  
Data Sets ◽  
Surface Solar Radiation ◽  
Radiation Data ◽  
Surface Measurements ◽  
Reference Measurements

<p>The solar radiation reaching the Earth’s surface determines our climate and is therefore important to be monitored as consistent and complete as possible. Even though surface reference measurements of surface solar radiation are available (e.g. from the Baseline Surface Radiation Network (BSRN)), their density remains low and large areas, like the oceans, remain poorly covered. To fill the gaps in space and time, satellite-based data records (like CLARA-A2 and SARAH-2.1 from the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF)) or model-based reanalysis data records (like ERA-5) are used. They provide surface solar radiation data with regional and global coverage, which are needed to understand its distribution and variability from the regional to the global scale.</p><p>Here we present a validation and analysis of monthly mean surface solar irradiance from multiple satellite-based and reanalysis data sets on the regional and global scale with reference to a data base of hundreds of surface measurements over land and ocean, collected from different sources (incl. BSRN, GEBA, WRDC, and buoy networks). This study provides new insights about the quality and uncertainty of available state-of-the-art satellite-based and reanalysis data records for climate studies. Regions of agreement as well as areas where the gridded data records exhibit larger differences are identified, providing important information on our current knowledge of the surface solar radiation climatology and possible improvements for future developments.</p>

SARAH-3 – a new satellite-based Climate Data Record of Surface Solar Radiation parameters

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

<p class="western"><span lang="en-US">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.</span></p> <p class="western"><span lang="en-US">In 2022, 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.</span></p> <p class="western" align="left"><span lang="en-US">In this presentation, an overview of the SARAH climate data record and their applications will be given. A focus will be on the SARAH-3 developments and validation with surface reference observations. Further, SARAH-3 will be used for a first analysis of the climate variability and potential trends of global radiation in Europe during the last decades. </span><span lang="en-US">The data record reveals that there is an increasing trend of surface solar radiation in Europe during the last decades, which is superimposed by decadal and regional variability.</span></p>

scholarly journals CLARA-A2: the second edition of the CM SAF cloud and radiation data record from 34 years of global AVHRR data

2017 ◽  
Vol 17 (9) ◽  
pp. 5809-5828 ◽  
Author(s):  
Karl-Göran Karlsson ◽  
Kati Anttila ◽  
Jörg Trentmann ◽  
Martin Stengel ◽  
Jan Fokke Meirink ◽  
...  
Keyword(s):  
Surface Albedo ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Climate Data ◽  
Ground Segment ◽  
Surface Radiation Budget ◽  
Avhrr Data ◽  
Data Record ◽  
Development And Validation ◽  
Climate Data Record

Abstract. The second edition of the satellite-derived climate data record CLARA (The CM SAF Cloud, Albedo And Surface Radiation dataset from AVHRR data – second edition denoted as CLARA-A2) is described. The data record covers the 34-year period from 1982 until 2015 and consists of cloud, surface albedo and surface radiation budget products derived from the AVHRR (Advanced Very High Resolution Radiometer) sensor carried by polar-orbiting, operational meteorological satellites. The data record is produced by the EUMETSAT Climate Monitoring Satellite Application Facility (CM SAF) project as part of the operational ground segment. Its upgraded content and methodology improvements since edition 1 are described in detail, as are some major validation results. Some of the main improvements to the data record come from a major effort in cleaning and homogenizing the basic AVHRR level-1 radiance record and a systematic use of CALIPSO-CALIOP cloud information for development and validation purposes. Examples of applications studying decadal changes in Arctic summer surface albedo and cloud conditions are provided.

scholarly journals A Climate Data Record (CDR) for the global terrestrial water budget: 1984–2010

2018 ◽  
Vol 22 (1) ◽  
pp. 241-263 ◽  
Author(s):  
Yu Zhang ◽  
Ming Pan ◽  
Justin Sheffield ◽  
Amanda L. Siemann ◽  
Colby K. Fisher ◽  
...  
Keyword(s):  
Water Budget ◽  
Water Cycle ◽  
Data Sources ◽  
Climate Data ◽  
Data Set ◽  
Data Record ◽  
Terrestrial Water ◽  
In Situ Observations ◽  
Climate Data Record

Abstract. Closing the terrestrial water budget is necessary to provide consistent estimates of budget components for understanding water resources and changes over time. Given the lack of in situ observations of budget components at anything but local scale, merging information from multiple data sources (e.g., in situ observation, satellite remote sensing, land surface model, and reanalysis) through data assimilation techniques that optimize the estimation of fluxes is a promising approach. Conditioned on the current limited data availability, a systematic method is developed to optimally combine multiple available data sources for precipitation (P), evapotranspiration (ET), runoff (R), and the total water storage change (TWSC) at 0.5∘ spatial resolution globally and to obtain water budget closure (i.e., to enforce P-ET-R-TWSC= 0) through a constrained Kalman filter (CKF) data assimilation technique under the assumption that the deviation from the ensemble mean of all data sources for the same budget variable is used as a proxy of the uncertainty in individual water budget variables. The resulting long-term (1984–2010), monthly 0.5∘ resolution global terrestrial water cycle Climate Data Record (CDR) data set is developed under the auspices of the National Aeronautics and Space Administration (NASA) Earth System Data Records (ESDRs) program. This data set serves to bridge the gap between sparsely gauged regions and the regions with sufficient in situ observations in investigating the temporal and spatial variability in the terrestrial hydrology at multiple scales. The CDR created in this study is validated against in situ measurements like river discharge from the Global Runoff Data Centre (GRDC) and the United States Geological Survey (USGS), and ET from FLUXNET. The data set is shown to be reliable and can serve the scientific community in understanding historical climate variability in water cycle fluxes and stores, benchmarking the current climate, and validating models.

scholarly journals Quality Control of Solar Radiation Data within the South African Weather Service Solar Radiometric Network

2018 ◽  
Author(s):  
Lucky Ntsangwane ◽  
Venkataraman Sivakumar ◽  
Brighton Mabasa ◽  
Nosipho Zwane ◽  
Katlego Ncongwane ◽  
...  
Keyword(s):  
Quality Control ◽  
Solar Radiation ◽  
South African ◽  
Surface Radiation ◽  
The South ◽  
Absolute Deviation ◽  
Surface Solar Radiation ◽  
Practical Applications ◽  
Radiation Data ◽  
Weather Service

Quality control (QC) may be a lengthy and tedious process. As a result, most data users use data from meteorological services without performing data quality checks. The South African Weather Service (SAWS) re-established the national solar radiometric network comprising of 13 new stations within the six climatic zones of the country. This study reports on the performance results of the Baseline Surface Radiation Network (BSRN) QC procedures applied to the solar radiation data within the SAWS radiometric network. The overall percentage performance of the SAWS solar radiation network based on BSRN QC methodology is 97.79%, 93.64%, 91.6% and 92.23% for Long Wave Downward Irradiance (LWD), Global Horizontal Irradiance (GHI), Diffuse Horizontal Irradiance (DHI) and Direct Normal Irradiance (DNI) respectively with operational problems largely dominating the percentage of bad data. The overall average performance of the Surface Solar Radiation Dataset – Heliosat (SARAH) data records for the GHI estimation for all the stations showed a Mean Bias Deviation (MBD) of -8.28 Wm-2, a Mean Absolute Deviation (MAD) of 9.06 Wm-2 and the Root Mean Square Deviation (RMSD) of 11.02 Wm-2. The correlation (quantified by R2) between ground-based and SARAH-derived GHI time series was ~ 0.98. The established network has the potential of providing high quality minute solar radiation data sets (GHI, DHI, DNI and LWD) and auxiliary hourly meteorological parameters vital for scientific and practical applications in renewable energy technologies in South Africa.

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.

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