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    Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: implementation and examples
    (Katlenburg-Lindau : European Geosciences Union, 2021) Deneke, Hartwig; Barrientos-Velasco, Carola; Bley, Sebastian; Hünerbein, Anja; Lenk, Stephan; Macke, Andreas; Meirink, Jan Fokke; Schroedter-Homscheidt, Marion; Senf, Fabian; Wang, Ping; Werner, Frank; Witthuhn, Jonas
    The modification of an existing cloud property retrieval scheme for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the geostationary Meteosat satellites is described to utilize its high-resolution visible (HRV) channel for increasing the spatial resolution of its physical outputs. This results in products with a nadir spatial resolution of 1×1ĝ€¯km2 compared to the standard 3×3ĝ€¯km2 resolution offered by the narrowband channels. This improvement thus greatly reduces the resolution gap between current geostationary and polar-orbiting meteorological satellite imagers. In the first processing step, cloudiness is determined from the HRV observations by a threshold-based cloud masking algorithm. Subsequently, a linear model that links the 0.6ĝ€¯μm, 0.8ĝ€¯μm, and HRV reflectances provides a physical constraint to incorporate the spatial high-frequency component of the HRV observations into the retrieval of cloud optical depth. The implementation of the method is described, including the ancillary datasets used. It is demonstrated that the omission of high-frequency variations in the cloud-absorbing 1.6ĝ€¯μm channel results in comparatively large uncertainties in the retrieved cloud effective radius, likely due to the mismatch in channel resolutions. A newly developed downscaling scheme for the 1.6ĝ€¯μm reflectance is therefore applied to mitigate the effects of this scale mismatch. Benefits of the increased spatial resolution of the resulting SEVIRI products are demonstrated for three example applications: (i) for a convective cloud field, it is shown that significantly better agreement between the distributions of cloud optical depth retrieved from SEVIRI and from collocated MODIS observations is achieved. (ii) The temporal evolution of cloud properties for a growing convective storm at standard and HRV spatial resolutions are compared, illustrating an improved contrast in growth signatures resulting from the use of the HRV channel. (iii) An example of surface solar irradiance, determined from the retrieved cloud properties, is shown, for which the HRV channel helps to better capture the large spatiotemporal variability induced by convective clouds. These results suggest that incorporating the HRV channel into the retrieval has potential for improving Meteosat-based cloud products for several application domains.
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    Absorption instruments inter-comparison campaign at the Arctic Pallas station
    (Katlenburg-Lindau : European Geosciences Union, 2021) Asmi, Eija; Backman, John; Servomaa, Henri; Virkkula, Aki; Gini, Maria I.; Eleftheriadis, Konstantinos; Müller, Thomas; Ohata, Sho; Kondo, Yutaka; Hyvärinen, Antti
    Aerosol light absorption was measured during a 1-month field campaign in June-July 2019 at the Pallas Global Atmospheric Watch (GAW) station in northern Finland. Very low aerosol concentrations prevailed during the campaign, which posed a challenge for the instruments' detection capabilities. The campaign provided a real-world test for different absorption measurement techniques supporting the goals of the European Metrology Programme for Innovation and Research (EMPIR) Black Carbon (BC) project in developing aerosol absorption standard and reference methods. In this study we compare the results from five filter-based absorption techniques - aethalometer models AE31 and AE33, a particle soot absorption photometer (PSAP), a multi-angle absorption photometer (MAAP), and a continuous soot monitoring system (COSMOS) - and from one indirect technique called extinction minus scattering (EMS). The ability of the filter-based techniques was shown to be adequate to measure aerosol light absorption coefficients down to around 0.01g¯Mm-1 levels when data were averaged to 1-2g¯h. The hourly averaged atmospheric absorption measured by the reference MAAP was 0.09g¯Mm-1 (at a wavelength of 637g¯nm). When data were averaged for >1g¯h, the filter-based methods agreed to around 40g¯%. COSMOS systematically measured the lowest absorption coefficient values, which was expected due to the sample pre-treatment in the COSMOS inlet. PSAP showed the best linear correlation with MAAP (slopeCombining double low line0.95, R2Combining double low line0.78), followed by AE31 (slopeCombining double low line0.93). A scattering correction applied to PSAP data improved the data accuracy despite the added noise. However, at very high scattering values the correction led to an underestimation of the absorption. The AE31 data had the highest noise and the correlation with MAAP was the lowest (R2Combining double low line0.65). Statistically the best linear correlations with MAAP were obtained for AE33 and COSMOS (R2 close to 1), but the biases at around the zero values led to slopes clearly below 1. The sample pre-treatment in the COSMOS instrument resulted in the lowest fitted slope. In contrast to the filter-based techniques, the indirect EMS method was not adequate to measure the low absorption values found at the Pallas site. The lowest absorption at which the EMS signal could be distinguished from the noise was >0.1g¯Mm-1 at 1-2g¯h averaging times. The mass absorption cross section (MAC) value measured at a range 0-0.3g¯Mm-1 was calculated using the MAAP and a single particle soot photometer (SP2), resulting in a MAC value of 16.0±5.7g¯m2g-1. Overall, our results demonstrate the challenges encountered in the aerosol absorption measurements in pristine environments and provide some useful guidelines for instrument selection and measurement practices. We highlight the need for a calibrated transfer standard for better inter-comparability of the absorption results. © Author(s) 2021.