Analysis of 14 years of broadband ground‐based solar <scp>UV</scp> index observations in Barcelona

Bech, Joan; Solá, Yolanda; Ossó, Albert; Lorente, J.

doi:10.1002/joc.3961

Cited by 5 publications

(7 citation statements)

References 48 publications

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“…The relative frequency diagrams of the higher elevation sites, such as Schauinsland and Zugspitze, show a higher frequency of the UVI categories high and very high compared to a site at a lower elevation, such as Munich. The results for Rome are similar to the categories published for the comparable situated site of Barcelona (41.2°N, 12 m) [53].…”

Section: Discussionsupporting

confidence: 86%

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UV-Index Climatology for Europe Based on Satellite Data

et al. 2020

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The UV-Index (UVI) is aimed at the prevention of skin cancer as well as other negative implications of ultraviolet radiation exposure. In order to support health related applications, assessments and planning that rely on long term data in high spatial resolution and as there exist only limited ground-based measurements, satellite products from reliable atmospheric monitoring services are used as sustainable data sources to create a climatology of the UVI at the local noon. In this study, the (all-sky) UVI as well as the hypothetically clear-sky UVI were analysed for the European region from 30° North to 65° North and from 25° West to 35° East in a spatial resolution of 0.05° for the time period 1983 to 2015. Maps of the monthly mean UVI provide an overview of the distribution of UVI for Europe as well as the spatial and temporal differences and regional variability at local solar noon. Additionally, eight selected locations provide insight into the effects of latitude and altitude on UVI in Europe. Monthly boxplots for each location provide information about regional differences in the variability of UVI, showing maximum variability in Northern and Central Europe in summer, where in Southern Europe this basically occurs in spring. The frequency of the World Health Organization exposure categories moderate, high and very high UVI is provided based on ten-day means for each month. The maximum difference between mean values per decade of 2006–2015 compared to 1983–1992 ranges from −1.2 to +1.2 for UVI and from −0.4 to +0.6 for UVI c l e a r − s k y . All locations, except the Northern European site, show an increase of UVI during spring and early summer months. A statistically significant increase in the annual mean all-sky UVI has been found for four sites, which ranges from +1.2% to +3.6% per decade. The latest eleven-year period of the UVI climatology (2005–2015) has been validated with UVI measured in five sites. The sites that are located north of the Alps show an underestimation of the UVI, likely due to the cloud modification. In the south, the UVI climatology provides values that are on average overestimated, possibly related to the use of climatological aerosol information. For the site within the Alps, a switch between underestimation and overestimation during the course of the year has been found. 7% to 9% of the UVI values of the climatology differ from the measured UVI by more than one unit.

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Section: Discussionsupporting

confidence: 86%

“…These regional differences in the variability of UVIs are mainly a result of the regional differences in cloudiness. This has also been found for ground based UVI observations in Barcelona 1999-2012 [53].…”

Section: Discussionsupporting

confidence: 79%

UV-Index Climatology for Europe Based on Satellite Data

et al. 2020

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“…The sky conditions associated with each spectral measurement were described with the simultaneous 10-min clearness index. Following the same criteria for skycondition classification used in previous studies [23,25], a clearness index higher than 0.65 was associated with clear-sky conditions. In this study we are interested in determining cloud-free conditions to show the highest UV irradiances at each SZA.…”

Section: Datamentioning

confidence: 97%

“…The annual maximum value was measured in February (425 DU) and the minimum one in December (233 DU). Some previous studies have analyzed the TOC in Barcelona from satellite-based observations [22,23].…”

Section: Datamentioning

confidence: 99%

Contribution of UVA irradiance to the erythema and photoaging effects in solar and sunbed exposures

Solá

Lorente

2015

Journal of Photochemistry and Photobiology B: Biology

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“…Among the available algorithms, it is worth mentioning the Heliosat-2 method (Raschke et al, 1987;Rigollier et al, 2004;Blanc et al, 2011), the State University of New York (SUNY) model (Perez et al, 2002), the Surface Insolation under Clear and Cloudy skies model (SICCS; Greuell et al, 2013), and more sophisticated radiative transfer models (e.g., Pinker and Laszlo, 1992) and algorithms based on neural network models (e.g., Takenaka et al, 2011;Taylor et al, 2016). Because of its unprecedented temporal resolution (up to 2.5 min), the new Japanese geostationary meteorological satellite Himawari-8 is expected shortly to attain a key position within this framework, drastically improving atmospheric research (Bessho et al, 2016) and forecasts of photovoltaic power generation (e.g., Ohtake et al, 2013Ohtake et al, , 2015.…”

Section: Introductionmentioning

confidence: 99%

Reply to Referee #2

Damiani¹

2018

Preprint

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Observations from the new Japanese geostationary satellite Himawari-8 permit quasi-real-time estimation of global shortwave radiation at an unprecedented temporal resolution. However, accurate comparisons with groundtruthing observations are essential to assess their uncertainty. In this study, we evaluated the Himawari-8 global radiation product AMATERASS using observations recorded at four SKYNET stations in Japan and, for certain analyses, from the surface network of the Japanese Meteorological Agency in 2016. We found that the spatiotemporal variability of the satellite estimates was smaller than that of the ground observations; variability decreased with increases in the time step and spatial domain. Cloud variability was the main source of uncertainty in the satellite radiation estimates, followed by direct effects caused by aerosols and bright albedo. Under all-sky conditions, good agreement was found between satellite and ground-based data, with a mean bias in the range of 20-30 W m −2 (i.e., AMATERASS overestimated ground observations) and a root mean square error (RMSE) of approximately 70-80 W m −2. However, results depended on the time step used in the validation exercise, on the spatial domain, and on the different climatological regions. In particular, the validation performed at 2.5 min showed largest deviations and RMSE values ranging from about 110 W m −2 for the mainland to a maximum of 150 W m −2 in the subtropical region. We also detected a limited overestimation in the number of clear-sky episodes, particularly at the pixel level. Overall, satellite-based estimates were higher under overcast conditions, whereas frequent episodes of cloud-induced enhanced surface radiation (i.e., measured radiation was greater than expected clear-sky radiation) tended to reduce this difference. Finally, the total mean bias was approximately 10-15 W m −2 under clear-sky conditions, mainly because of overall instantaneous direct aerosol forcing efficiency in the range of 120-150 W m −2 per unit of aerosol optical depth (AOD). A seasonal anticorrelation between AOD and global radiation differences was evident at all stations and was also observed within the diurnal cycle.

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Analysis of 14 years of broadband ground‐based solar UV index observations in Barcelona

Cited by 5 publications

References 48 publications

UV-Index Climatology for Europe Based on Satellite Data

UV-Index Climatology for Europe Based on Satellite Data

Contribution of UVA irradiance to the erythema and photoaging effects in solar and sunbed exposures

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