ALBERT

Description: The Arosa site is well known in the ozone community for its continuous total ozone column observations that have been recorded since 1926. Originally based on Dobson sun spectrophotometers, the site has been gradually complemented by three automatic Brewer instruments, in operation since 1998. To secure the long-term ozone monitoring in this Alpine region and to benefit from synergies with the World Radiation Center, the feasibility of moving this activity to the nearby site at Davos (aerial distance of 13 km) has been explored. Concerns about a possible rupture of the 90-year-long record has motivated a careful comparison of the two sites, since great attention to the data continuity and quality has always been central to the operations of the observatory at Arosa. To this end, one element of the Arosa Brewer triad has been set up at the Davos site since November 2011 to realize a campaign of parallel measurements and to study the deviations between the three Brewer instruments. The analysis of the coincident measurement shows that the differences between Arosa and Davos remain within the range of the long-term stability of the Brewer instruments. A nonsignificant seasonal cycle is observed, which could possibly be induced by a stray-light bias and the altitude difference between the two sites. These differences are shown to be lower than the short-term variability of the time series and the overall uncertainty from individual Brewer instruments and therefore are not statistically significant. It is therefore concluded that the world's longest time series of the total ozone column obtained at Arosa site could be safely extended and continued with measurements taken from instruments located at the nearby Davos site without introducing a bias to this unique record.

Description: The current study analyses the cloud radiative effect during the daytime depending on cloud fraction and cloud type at two stations in Switzerland over a time period of 3 to 5 years. Information on fractional cloud coverage and cloud type is retrieved from images taken by visible all-sky cameras. Cloud-base height (CBH) data are retrieved from a ceilometer and integrated water vapour (IWV) data from GPS measurements. The longwave cloud radiative effect (LCE) for low-level clouds and a cloud coverage of 8 oktas has a median value between 59 and 72 Wm−2. For mid- and high-level clouds the LCE is significantly lower. It is shown that the fractional cloud coverage, the CBH and IWV all have an influence on the magnitude of the LCE. These observed dependences have also been modelled with the radiative transfer model MODTRAN5. The relative values of the shortwave cloud radiative effect (SCErel) for low-level clouds and a cloud coverage of 8 oktas are between −90 and −62 %. Also here the higher the cloud is, the less negative the SCErel values are. In cases in which the measured direct radiation value is below the threshold of 120 Wm−2 (occulted sun) the SCErel decreases substantially, while cases in which the measured direct radiation value is larger than 120 Wm−2 (visible sun) lead to a SCErel of around 0 %. In 14 and 10 % of the cases in Davos and Payerne respectively a cloud enhancement has been observed with a maximum in the cloud class cirrocumulus–altocumulus at both stations. The calculated median total cloud radiative effect (TCE) values are negative for almost all cloud classes and cloud coverages.

Description: We have used a method based on ground-based solar radiation measurements and radiative transfer models (RTMs) in order to estimate the following cloud optical properties: cloud optical thickness (COT), cloud single scattering albedo (SSAc) and effective droplet radius (reff). The method is based on the minimisation of the difference between modelled and measured downward shortwave radiation (DSR). The optical properties are estimated for more than 3000 stratus–altostratus (St–As) and 206 cirrus–cirrostratus (Ci–Cs) measurements during 2013–2017, at the Baseline Surface Radiation Network (BSRN) station in Payerne, Switzerland. The RTM libRadtran is used to simulate the total DSR as well as its direct and diffuse components. The model inputs of additional atmospheric parameters are either ground- or satellite-based measurements. The cloud cases are identified by the use of an all-sky cloud camera. For the low- to mid-level cloud class St–As, 95 % of the estimated cloud optical thickness values using total DSR measurements in combination with a RTM, herein abbreviated as COTDSR, are between 12 and 92 with a geometric mean and standard deviation of 33.8 and 1.7, respectively. The comparison of these COTDSR values with COTBarnard values retrieved from an independent empirical equation results in a mean difference of -1.2±2.7 and is thus within the method uncertainty. However, there is a larger mean difference of around 18 between COTDSR and COT values derived from MODIS level-2 (L2), Collection 6.1 (C6.1) data (COTMODIS). The estimated reff (from liquid water path and COTDSR) for St–As are between 2 and 20 µm. For the high-level cloud class Ci–Cs, COTDSR is derived considering the direct radiation, and 95 % of the COTDSR values are between 0.32 and 1.40. For Ci–Cs, 95 % of the SSAc values are estimated to be between 0.84 and 0.99 using the diffuse radiation. The COT for Ci–Cs is also estimated from data from precision filter radiometers (PFRs) at various wavelengths (COTPFR). The herein presented method could be applied and validated at other stations with direct and diffuse radiation measurements.

Description: The Mann–Kendall test associated with the Sen's slope is a very widely used non-parametric method for trend analysis. It requires serially uncorrelated time series, yet most of the atmospheric processes exhibit positive autocorrelation. Several prewhitening methods have therefore been designed to overcome the presence of lag-1 autocorrelation. These include a prewhitening, a detrending and/or a correction of the detrended slope and the original variance of the time series. The choice of which prewhitening method and temporal segmentation to apply has consequences for the statistical significance, the value of the slope and of the confidence limits. Here, the effects of various prewhitening methods are analyzed for seven time series comprising in situ aerosol measurements (scattering coefficient, absorption coefficient, number concentration and aerosol optical depth), Raman lidar water vapor mixing ratio, as well as tropopause and zero-degree temperature levels measured by radio-sounding. These time series are characterized by a broad variety of distributions, ranges and lag-1 autocorrelation values and vary in length between 10 and 60 years. A common way to work around the autocorrelation problem is to decrease it by averaging the data over longer time intervals than in the original time series. Thus, the second focus of this study evaluates the effect of time granularity on long-term trend analysis. Finally, a new algorithm involving three prewhitening methods is proposed in order to maximize the power of the test, to minimize the number of erroneous detected trends in the absence of a real trend and to ensure the best slope estimate for the considered length of the time series.