Data source
glUV was generated using UV-B data from the 
Ozone Monitoring Instrument (OMI) onboard the NASA EOS Aura spacecraft. OMI is a contribution of the Netherlands’ Agency for Aerospace Programs (NIVR) in collaboration with the Finnish Meteorological Institute (FMI) to the EOS Aura mission of NASA. Since October 2004, OMI continues the Total Ozone Mapping Spectrometer (TOMS) record for total ozone and other atmospheric parameters with improved sensitivity and higher spatial resolution (Schoeberl et al. 2006). The Aura spacecraft orbits at 705 km in a sun-synchronous orbit with a 1:45 PM ±15 minute equator crossing time. OMI is a nadir-viewing instrument with a 2,600 km wide viewing swath and provides daily global coverage of the sunlit portion of the atmosphere. The spatial resolution of the instrument is 13x24 km in nadir and larger toward the edges of the swath (Tanskanen et al. 2006). OMI contains two spectrometers and measures reflected solar radiation in a selected range of the visible (350-500nm) and UV spectrum (two bands at 270-314nm and 306-380nm, Levelt et al. 2006). The OMI measurements are used to calculate clear-sky surface UV irradiance, which is subsequently corrected for clouds and aerosols to obtain the OMI surface UV irradiance products (OMUVB, Tanskanen et al. 2006). The accuracy of the OMUVB products, assessed with ground-reference data, ranges from 70% to 93%, depending on atmospheric and location-specific conditions (Tanskanen et al. 2006).
Data acquisition and processing
The Spectral Surface UV-B Irradiance and Erythemal Dose Level-2G data product (OMUVBG, V003) were acquired at 15 arc-minute spatial resolution from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) by employing the Mirador interface. The Erythemal Dose is an erythemally weighted estimate of daily UV-B radiation over the wavelengths measured by the OMI instrument given in J/m² (for reasons of simplicity we use J/m²/day for all derived data). We used all available data from October 1st 2004 to January 26th 2013 and converted them from the HDF5 format into ASCII files using the hd5dump tool provided by the HDF Group at the University of Illinois. Daily measurements were summarized into monthly mean UV-B Erythemal Daily Dose values and averaged them across all years in the study period to account for inter-annual variability.
UV-B variables
Six biologically meaningful UV-B variables were derived from the monthly mean layers, following methods similar to those used for the WorldClim (Hijmans et al. 2005) and CliMond (Kriticos et al. 2012) datasets. The variables represent Annual Mean UV-B (UVB1), UV-B Seasonality (UVB2), Mean UV-B of Highest Month (UVB3), Mean UV-B of Lowest Month (UVB4), Sum of Monthly Mean UV-B during Highest Quarter (UVB5) and Sum of Monthly Mean UV-B during Lowest Quarter (UVB6). UV-B Seasonality is calculated as standard deviation of mean monthly values. The calculations of Sum of Mean UV-B during Highest/Lowest Quarter (UVB3 and UVB4) are based on the same algorithm used for computing the bioclimatic variables BIO16 and BIO17 (Precipitation of Wettest/Driest Quarter) in WorldClim ('biovars' method in the R package dismo, Hijmans et al. 2012). This algorithm computes all possible 12 combinations of quarterly sums including the ones around the turn of the year and identifies the highest/lowest among these. For UVB3 to UVB6, the respective point in time (month or quarter, respectively) to which these variables refer is therefore spatially heterogeneous and may be different among adjacent cells. For reasons of consistency the same units (J/m²/day) were used for all UV-B surfaces including UVB5 and UVB6.
References
- Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G. & Jarvis, A. (2005). Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25, 1965–1978.
- Hijmans, R.J., Phillips, S., Leathwick, J. & Elith, J. (2012). dismo: Species distribution modeling. Retrieved from http://CRAN.R-project.org/package=dismo
- Kriticos, D.J., Webber, B.L., Leriche, A., Ota, N., Macadam, I., Bathols, J. & Scott, J.K. (2012). CliMond: global high-resolution historical and future scenario climate surfaces for bioclimatic modelling. Methods in Ecology and Evolution, 3, 53–64.
- Levelt, P.F., van den Oord, G.H., Dobber, M.R., Malkki, A., Visser, H., de Vries, J., Stammes, P., Lundell, J.O. & Saari, H. (2006). The ozone monitoring instrument. Geoscience and Remote Sensing, IEEE Transactions on, 44, 1093–1101.
- Schoeberl, M.R., Douglass, A.R., Hilsenrath, E., Bhartia, P.K., Beer, R., Waters, J.W., Gunson, M.R., Froidevaux, L., Gille, J.C. & Barnett, J.J. (2006). Overview of the EOS Aura mission. Geoscience and Remote Sensing, IEEE Transactions on, 44, 1066–1074.
- Tanskanen, A., Krotkov, N.A., Herman, J.R. & Arola, A. (2006). Surface ultraviolet irradiance from OMI. Geoscience and Remote Sensing, IEEE Transactions on, 44, 1267–1271.