Abstract
We present a simple algorithm that calculates the cloud occurrence frequency at an altitude site using automatic camera image analysis. This algorithm was applied at the puy de Dôme station (PUY, 1465 m. a.s.l., France) over 2013–2018. Cloud detection thresholds were determined by direct comparison with simultaneous in situ cloud probe measurements (particulate volume monitor (PVM) Gerber). The cloud occurrence frequency has a seasonal cycle, with higher values in winter (60%) compared to summer (24%). A cloud diurnal cycle is observed only in summer. Comparisons with the larger scale products from satellites and global model reanalysis are also presented. The NASA cloud-aerosol transport system (CATS) cloud fraction shows the same seasonal and diurnal variations and is, on average, 11% higher. Monthly variations of the ECMWF ERA-5 fraction of cloud cover are also highly correlated with the camera cloud occurrence frequency, but the values are 19% lower and up to 40% for some winter months. The METEOSAT-SEVIRI cloud occurrence frequency also follows the same seasonal cycle but with a much smaller decrease in summer. The all-sky imager cloud fraction (CF) presents larger variability than the camera cloud occurrence but also follows similar seasonal variations (67% in winter and 44% in summer). This automatic low-cost detection of cloud occurrence is of interest in characterizing altitude observation sites, especially those that are not yet equipped with microphysical instruments and can be deployed to other high-altitude sites equipped with cameras.
Highlights
Clouds can act as a greenhouse ingredient to warm the Earth by trapping outgoing longwave radiation and can cool the earth by reflecting shortwave solar radiation [1]
We found that the closest cloud-aerosol transport system (CATS) cloud fraction (CF) values to the camera COF are those of the 1–2 km layer, which is consistent with the altitude of the puy de Dôme station (PUY) roughly in the middle of this altitude range
The objective of this work was to show the feasibility of the detection of cloud occurrence on an altitude site from a simple, low-cost, and automatic algorithm based on an analysis of camera images
Summary
Clouds can act as a greenhouse ingredient to warm the Earth by trapping outgoing longwave radiation and can cool the earth by reflecting shortwave solar radiation [1]. The net effect of these two competing processes depends on the height, type, and optical properties of the clouds. Cloud microphysical properties are an important characteristic of clouds, as their ability to produce rain and snow, generate lightning, and contribute to the radiation balance of the earth depends on local air motions and on their individual microphysical properties [5]. The chemical and biological transformations occurring in clouds perturb both the gas phase chemical composition and the microphysical and chemical properties of aerosols acting as cloud condensation nuclei (CCN). These transformations could, impact air quality and cloud formation. A recent study showed that cloud microorganisms isolated at the puy de Dôme station (PUY)
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