Comparing satellite- to ground-based automated and manual cloud coverage observations – a case study

In this case study we compare cloud fractional cover measured by radiometers on polar satellites (AVHRR) and on one geostationary satellite (SEVIRI) to ground-based manual (SYNOP) and automated observations by a cloud camera (Hemispherical Sky Imager, HSI). These observations took place in Hannover, Germany, and in Lauder, New Zealand, over time frames of 3 and 2 months, respectively. Daily mean comparisons between satellite derivations and the ground-based HSI found the deviation to be 6 14% for AVHRR and 8 16% for SEVIRI, which can be considered satisfactory. AVHRR’s instantaneous differences are smaller (2 22 %) than instantaneous SEVIRI cloud fraction estimates (8 29 %) when compared to HSI due to resolution and scenery effect issues. All spaceborne observations show a very good skill in detecting completely overcast skies (cloud cover 6 oktas) with probabilities between 92 and 94% and false alarm rates between 21 and 29% for AVHRR and SEVIRI in Hannover, Germany. In the case of a clear sky (cloud cover lower than 3 oktas) we find good skill with detection probabilities between 72 and 76 %. We find poor skill, however, whenever broken clouds occur (probability of detection is 32% for AVHRR and 12% for SEVIRI in Hannover, Germany). In order to better understand these discrepancies we analyze the influence of algorithm features on the satellite-based data. We find that the differences between SEVIRI and HSI cloud fractional cover (CFC) decrease (from a bias of 8 to almost 0 %) with decreasing number of spatially averaged pixels and decreasing index which determines the cloud coverage in each “cloud-contaminated” pixel of the binary map. We conclude that window size and index need to be adjusted in order to improve instantaneous SEVIRI and AVHRR estimates. Due to its automated operation and its spatial, temporal and spectral resolution, we recommend as well that more automated ground-based instruments in the form of cloud cameras should be installed as they cover larger areas of the sky than other automated ground-based instruments. These cameras could be an essential supplement to SYNOP observation as they cover the same spectral wavelengths as the human eye.DF

Remote sensing of lunar aureole with a sky camera: Adding information in the nocturnal retrieval of aerosol properties with GRASP code

The use of sky cameras for nocturnal aerosol characterization is discussed in this study. Two sky cameras are configured to take High Dynamic Range (HDR) images at Granada and Valladolid (Spain). Some properties of the cameras, like effective wavelengths, sky coordinates of each pixel and pixel sensitivity, are characterized. After that, normalized camera radiances at lunar almucantar points (up to 20° in azimuth from the Moon) are obtained at three effective wavelengths from the HDR images. These normalized radiances are compared in different case studies to simulations fed with AERONET aerosol information, giving satisfactory results. The obtained uncertainty of normalized camera radiances is around 10% at 533 nm and 608 nm and 14% for 469 nm. Normalized camera radiances and six spectral aerosol optical depth values (obtained from lunar photometry) are used as input in GRASP code (Generalized Retrieval of Aerosol and Surface Properties) to retrieve aerosol properties for a dust episode over Valladolid. The retrieved aerosol properties (refractive indices, fraction of spherical particles and size distribution parameters) are in agreement with the nearest diurnal AERONET products. The calculated GRASP retrieval at night time shows an increase in coarse mode concentration along the night, while fine mode properties remained constant.This work was supported by the Andalusia Regional Government (project P12-RNM-2409) and by the “Consejería de Educación, Junta de Castilla y León” (project VA100U14).Spanish Ministry of Economy and Competitiveness and FEDER funds under the projects CGL2013-45410-R, CMT2015-66742-R, CGL2016-81092-R.“Juan de la Cierva-Formación” program (FJCI-2014-22052).European Union's Horizon 2020 research and innovation programme through project ACTRIS-2 (grant agreement No 654109)

Derivation of sky luminance and spectral sky radiance from images taken with a CCD camera

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Improving lighting quality by practical measurements of the luminance distribution

\u3cp\u3eLight is one of the important aspects for a comfortable office environment. Too often high quality lighting is not achieved. Lighting quality can be defined by different aspects that are relevant such as the quantity, distribution, glare, spectral power distribution, daylight, directionality, and dynamics of light. The luminance distribution seems to be a suitable measure to achieve high quality lighting. The luminance distribution can be measured, with a practical accuracy, by commercially available cameras and fisheye lenses. All these aspects spectral power distribution can be measured using a camera-based luminance distribution measurement device. So, a luminance distribution measurement device is an excellent tool to measure or indicate lighting quality. It can be used to achieve a better understanding of lighting quality and potentially it can be implemented in automated building control systems.\u3c/p\u3