Spatial and temporal UV irradiance and aerosol variability within the area of an OMI satellite pixel

Abstract

Abstract.Results of an experimental campaign that took place in the greater Thessaloniki area were used to investigate temporal and spatial UV variability within an OMI satellite pixel. UV irradiance and aerosol optical depth measurements were performed for a one month period at three sites characterized as urban, rural and industrial, depending on their location and possible local aerosol sources. OMI showed a general UV irradiance overestimation compared to all three sites and for all atmospheric conditions. During the campaign the standard deviation calculated from the three sites for UV irradiance at 324 nm was of the order of 26%. For cloudless days with high spatial aerosol variability, UV differences reached ±20% within the OMI pixel. For cloudy days UV differences up to 100% were found at the three sites, a percentage that depends on the ground-based data integration time used for the comparison. Here we tried to focus on the limitations when trying to interpret results of UV irradiance comparisons between OMI satellite and ground based stations, taking into account the UV variability within an OMI pixel, due to such small scale spatial cloud and aerosol inhomogeneities.

Validation of satellite-based noontime UVI with NDACC ground-based instruments: influence of topography, environment and satellite overpass time

“…Thus, part of the observed positive biases between SB and GB UVI for cloud-free and cloudy conditions can be explained by OMTO3 and GOME-2 TOC underestimation. At this site also, cloud cover variability within the satellite pixel (Kazadzis et al, 2009b), aerosol climatology (Kinne et al, 2013) and surface albedo climatology (Tanskanen, 2004) might explain part of the biases.…”

“…Of course part of the bias might come from differences between the two RT models used and also between the other input parameters. Kazadzis et al (2009b) concluded also with an overestimation due to aerosol variability (in time and space). Of course, we have to keep in mind that modelling computations are affected by uncertainties.…”

“…Indeed, these aerosol climatologies rely on AERONET data that show an interannual variability, and the gridding is 1 • × 1 • in latitude-longitude. Cloud cover variability within the satellite pixel (Kazadzis et al, 2009b) is expected to contribute to the biases as well as the surface albedo climatology from Tanskanen (2004).…”

“…Surface albedo climatology (Tanskanen, 2004) might contribute. According to Kazadzis et al (2009b), due to the particular situation of SDR (coastal site on a small mountainous island) the cloud cover spatial variability in the satellite pixel should be the main contributor to the SB-GB UVI bias.…”

GARRLiC and LIRIC: strengths and limitations for the characterization of dust and marine particles along with their mixtures

“…So far, various studies have tried to characterize the aerosol radiative properties in the Mediterranean with satellite or ground-based AOD measurements (e.g. di Sarra et al, 2008;Kazadzis et al, 2009;Papadimas et al, 2012). Unfortunately, they fail to overcome their limitations, such as the non-realistic assumptions about the aerosol absorption properties and the lack of information on the real vertical aerosol structure (Mishra et al, 2014).…”