Abstract.A Microtops II "ozone monitor" with UV channels centered at 305.5, 312.5, and 320 nm has been used routinely in six experimental campaigns carried out in several geographic locations and seasons, covering latitudes from 35 to 68 • N during the last ten years (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011). The total ozone content is retrieved by Microtops II by using different combinations (Channel I, 305.5/312.5 nm; Channel II, 312.5/320 nm; and Channel III, 305.5/312.5/320 nm) of the signals at the three ultraviolet wavelengths. The long-term performance of the total ozone content determination has been studied taking into account the sensitivities to the calibration, airmass, temperature and aerosols. When a calibration was used and the airmass limit was fixed to 3, the root mean square deviations of the relative differences produced by Microtops II with respect to several Brewers are 0.9, 2, and 2 % respectively for the Channel I, Channel II, and Channel III retrieval. The performance of the Microtops retrieval has been stable during the last ten years. Channel I represents the best option to determine the instantaneous total ozone content. Channels II and III values appear weakly sensitive to temperature, ozone content, and aerosols. Channel II is more stable than Channel I for airmasses larger than 2.6. The conclusions do not show any dependence on latitude and season.

Atmospheric aerosols have an uncertain effect on climate and serious impacts on human health. The uncertainty in the aerosols' role on climate has several sources. First, aerosols have great spatial and temporal variability. The spatial variability arises from the fact that aerosols emitted in a certain place can travel thousands of kilometers, swept by the winds to modify the destination region's climate. The spatial variability also means that aerosols are inhomogeneously distributed in the vertical direction, which can lead to a differential effect on the energy balance depending on the aerosols' altitude. On the other hand, aerosols experience physical and chemical transformations in the time they spend in the atmosphere, commonly known as aging, which modifies its optical properties. These factors make necessary the use of two approaches for the study of the aerosol impact on climate: global aerosol models and satellite- and ground-based measurements. The disagreement between the estimates of the two approaches is the main cause of the climate uncertainty. One way to reduce climate uncertainty is to create new tools to simulate more realistic aerosol scenarios. We present a graphical user interface to obtain aerosol optical properties: extinction, scattering, and absorption coefficients; single-scattering albedo; asymmetry parameter; and aerosol optical depth. The tool can be used to obtain the optical properties of the external and internal mixture of several aerosol components. Interface outputs have successfully been compared to a black carbon plume and to aging mineral dust.

The daily values of UVB irradiation (290–315 nm), IUVB, and the broadband total irradiation (300–2800 nm), IT, measured on a horizontal plane have been correlated for the period 2000–2008 at 16 measurement sites in Spain. The results have been compared with the daily experimental values registered at the same sites during the period 2009–2011. The coefficients of determination R2 obtained by applying a linear regression are higher than 0.88 for all sites and increase to 0.94 when using a quadratic regression. When all data are considered together, the values of R2 are 0.91 and 0.97 for the linear and quadratic regressions, respectively. Three different clearness indices, which are dimensionless parameters, have been also used in order to reduce the uncertainties of the estimations and to reduce the local nature of the coefficients: (1) the UVB clearness index, kTUVB = IUVB/I0UVB; (2) the modified UVB clearness index, k′TUVB and (3) the estimated UVB clearness index, k*TUVB. The results show a strong dependence on the solar zenith angle. The bi‐dimensional regression of kTUVB as a function of the solar zenith angle and the clearness index, kT, substantially improves the correlation, with R2 values higher than 0.81 for all sites. Finally, a formula relating kTUVB and kT, valid for latitudes between 36°N and 44°N, has been obtained: kTUVB = 0.064 kT – 0.0011 θz – 1.24 E‐05 ϕ + 7.6 E‐05 λ + 0.063, where θz represents the solar zenith angle (in degrees), ϕ is the latitude (in degrees) of the site and λ is the distance to the sea (in km). We have compared the experimental values for the period 2009–2011 with those estimated using this expression. For this, the coefficient of determination (R2) is 0.87, with a MBD of –3.4%, a RMSE of 21% and a NRMSE of 8.7%.

ResumenLas cópulas se han convertido en una herramienta popular para la construcción de modelos multivariados en campos donde la dependencia multivariada es de gran interés. El propósito de este trabajo es presentar las cópulas tanto en su concepto teórico, como en su implementación en el software estadístico R y profundizar en la construcción de distribuciones multivariadas con marginales dependientes, usando la clase mvdc del paquete copula, la cual permite utilizar varias y diferentes marginales ya implementadas. Además, se trabajará con métodos para dibujar representaciones de perspectiva y contorno para las funciones de distribución y densidad.Palabras clave: Análisis Multivariado, Cópulas en R, Paquete copula, Software R. AbstractThe copula has become a popular tool to build the multivariate models, in many fields where the multivariate dependence is of a great interest. This paper purpose is to present the copula both in their theoretical concept and its implementation in the R statistical software, and to deepen into the multivariate distributions? construction with the dependent marginal, by using the copula package's mvdc class, which allows to use the marginal in several and different types, that have been implemented already. In addition, to work with the methods for drawing the perspective and the contour representations for the distribution and the density functions.

No abstract