Abstract. At Uccle, Belgium, a long time series of simultaneous measurements of erythemal ultraviolet (UV) dose (S ery ), global solar radiation (S g ), total ozone column (Q O 3 ) and aerosol optical depth (τ aer ) (at 320.1 nm) is available, which allows for an extensive study of the changes in the variables over time. Linear trends were determined for the different monthly anomalies time series. S ery , S g and Q O 3 all increase by respectively 7, 4 and 3 % per decade. τ aer shows an insignificant negative trend of −8 % per decade. These trends agree with results found in the literature for sites with comparable latitudes. A change-point analysis, which determines whether there is a significant change in the mean of the time series, is applied to the monthly anomalies time series of the variables. Only for S ery and Q O 3 , was a significant change point present in the time series around February 1998 and March 1998, respectively. The change point in Q O 3 corresponds with results found in the literature, where the change in ozone levels around 1997 is attributed to the recovery of ozone. A multiple linear regression (MLR) analysis is applied to the data in order to study the influence of S g , Q O 3 and τ aer on S ery . Together these parameters are able to explain 94 % of the variation in S ery . Most of the variation (56 %) in S ery is explained by S g . The regression model performs well, with a slight tendency to underestimate the measured S ery values and with a mean absolute bias error (MABE) of 18 %. However, in winter, negative S ery are modeled. Applying the MLR to the individual seasons solves this issue. The seasonal models have an adjusted R 2 value higher than 0.8 and the correlation between modeled and measured S ery values is higher than 0.9 for each season. The summer model gives the best performance, with an absolute mean error of only 6 %. However, the seasonal regression models do not always represent reality, where an increase in S ery is accompanied with an increase in Q O 3 and a decrease in τ aer . In all seasonal models, S g is the factor that contributes the most to the variation in S ery , so there is no doubt about the necessity to include this factor in the regression models. The individual contribution of τ aer to S ery is very low, and for this reason it seems unnecessary to include τ aer in the MLR analysis. Including Q O 3 , however, is justified to increase the adjusted R 2 and to decrease the MABE of the model.
Abstract. We present a cloud-screening method based on differential optical absorption spectroscopy (DOAS) measurements, more specifically using intensity measurements and O4 differential slant-column densities (DSCDs). Using the colour index (CI), i.e. the ratio of the radiance at two wavelengths, we define different sky conditions including clear, thin clouds/polluted, fully-cloudy, and heavily polluted. We also flag the presence of broken and scattered clouds. The O4 absorption is a good tracer for cloud-induced light-path changes and is used to detect clouds and discriminate between instances of high aerosol optical depth (AOD) and high cloud optical depth (COD). We apply our cloud screening to MAX-DOAS (multi-axis DOAS) retrievals at three different sites with different typical meteorological conditions, more specifically suburban Beijing (39.75° N, 116.96° E), Brussels (50.78° N, 4.35° E) and Jungfraujoch (46.55° N, 7.98° E). We find that our cloud screening performs well characterizing the different sky conditions. The flags based on the colour index are able to detect changes in visibility due to aerosols and/or (scattered) clouds. The O4-based multiple-scattering flag is able to detect optically thick clouds, and is needed to correctly identify clouds for sites with extreme aerosol pollution. Removing data taken under cloudy conditions results in a better agreement, in both correlation and slope, between the MAX-DOAS AOD retrievals and measurements from other co-located instruments.
Abstract. The Langley Plot Method (LPM) is adapted for the retrieval of Aerosol Optical Depth (AOD) values at 340 nm from Brewer#178 sun scan measurements between 335 and 345 nm (convoluted with the band pass function of the Cimel sunphotometer filter at 340 nm) performed in Uccle, Belgium. The use of sun scans instead of direct sun measurements simplifies the comparison of the AOD values with quasi-simultaneous Cimel sunphotometer values. Also, the irradiance at 340 nm is larger than the one at 320.1 nm due to lower ozone absorption, thus improving the signal to noise ratio. For the selection of the cloudless days (from now on referred to as calibration quality clear days), a new set of criteria is proposed. With the adapted method, individual clear sky AOD values, for which the selection criteria are also presented in this article, are calculated for a period from September 2006 until the end of August 2010. These values are then compared to quasi-simultaneous Cimel sunphotometer measurements, showing a very good agreement (the correlation coefficient, the slope and the intercept of the regression line are respectively 0.974, 0.968 and 0.011), which proves that good quality observations can be obtained from Brewer sun scan measurements at 340 nm. The analysis of the monthly and seasonal Brewer AODs at Uccle is consistent with studies at other sites reporting on the seasonal variation of AODs in Europe. The highest values can be observed in summer and spring, whereas more than 50% of the winter AODs are lower than 0.3. On a monthly scale, the lowest AOD are observed in December and the highest values occur in June and April. No clear weekly cycle is observed for Uccle. The current cloud-screening algorithm is still an issue, Correspondence to: V. De Bock (veerle.debock@meteo.be) which means that some AOD values can still be influenced by scattered clouds. This effect can be seen when comparing the calculated monthly mean values of the Brewer with the AERONET measurements.
Review of the existing bibliography shows that the direction and magnitude of the long-term trends of UV irradiance, and their main drivers, vary significantly throughout Europe. Analysis of total ozone and spectral UV data recorded at four European stations during 1996–2017 reveals that long-term changes in UV are mainly driven by changes in aerosols, cloudiness, and surface albedo, while changes in total ozone play a less significant role. The variability of UV irradiance is large throughout Italy due to the complex topography and large latitudinal extension of the country. Analysis of the spectral UV records of the urban site of Rome, and the alpine site of Aosta reveals that differences between the two sites follow the annual cycle of the differences in cloudiness and surface albedo. Comparisons between the noon UV index measured at the ground at the same stations and the corresponding estimates from the Deutscher Wetterdienst (DWD) forecast model and the ozone monitoring instrument (OMI)/Aura observations reveal differences of up to 6 units between individual measurements, which are likely due to the different spatial resolution of the different datasets, and average differences of 0.5–1 unit, possibly related to the use of climatological surface albedo and aerosol optical properties in the retrieval algorithms.
Abstract. This study examines the adequacy of the existing Brewer network to supplement other networks from the ground and space to detect SO2 plumes of volcanic origin. It was found that large volcanic eruptions of the last decade in the Northern Hemisphere have a positive columnar SO2 signal seen by the Brewer instruments located under the plume. It is shown that a few days after the eruption the Brewer instrument is capable of detecting significant columnar SO2 increases, exceeding on average 2 DU relative to an unperturbed pre-volcanic 10-day baseline, with a mean close to 0 and σ = 0.46, as calculated from the 32 Brewer stations under study. Intercomparisons with independent measurements from the ground and space as well as theoretical calculations corroborate the capability of the Brewer network to detect volcanic plumes. For instance, the comparison with OMI (Ozone Monitoring Instrument) and GOME-2 (Global Ozone Monitoring Experiment-2) SO2 space-borne retrievals shows statistically significant agreement between the Brewer network data and the collocated satellite overpasses in the case of the Kasatochi eruption. Unfortunately, due to sparsity of satellite data, the significant positive departures seen in the Brewer and other ground networks following the Eyjafjallajökull, Bárðarbunga and Nabro eruptions could not be statistically confirmed by the data from satellite overpasses. A model exercise from the MACC (Monitoring Atmospheric Composition and Climate) project shows that the large increases in SO2 over Europe following the Bárðarbunga eruption in Iceland were not caused by local pollution sources or ship emissions but were clearly linked to the volcanic eruption. Sulfur dioxide positive departures in Europe following Bárðarbunga could be traced by other networks from the free troposphere down to the surface (AirBase (European air quality database) and EARLINET (European Aerosol Research Lidar Network)). We propose that by combining Brewer data with that from other networks and satellites, a useful tool aided by trajectory analyses and modelling could be created which can also be used to forecast high SO2 values both at ground level and in air flight corridors following future eruptions.
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