Synergetic retrieval of altitude-dependent cloud cover from ceilometers and infrared camera

Total and altitude-dependent cloud cover are important characteristics of the present weather and used in nowcasting, numerical weather prediction and climate applications as well as for scientific studies. While cloud cover is still widely observed by humans, MeteoSwiss is in the process to automate the procedure using a variety of sensors. In this effort, the estimation of the cloud amount per cloud layer appeared to be particularly challenging as algorithms based exclusively on ceilometers could not satisfy all quality requirements. The main shortcomings are limitations in the representativity and the long integration time of 15 minutes, which prevents the delivery of timely and accurate values for the present weather.

In this context, we investigate how a well-calibrated hemispheric infrared camera combined with the ceilometer cloud base measurements can improve the cloud information. In the different investigated synergetic algorithms the ceilometer is the predominant source of cloud height information whereas the infrared camera provides information on the cloud amount. The more basic algorithm uses a threshold on the infrared brightness temperatures to distinguish cloudy from clear-sky pixels. A more elaborate algorithm matches cloud-base hits of the ceilometers with infrared camera pixels to produce cloud cover estimates for each cloud layer. This approach does not require a clear sky reference and is to a large extent insensitive to calibration inaccuracies. It further allows us to exploit the infrared image at high airmasses, i.e. far down towards the horizon, what in turn further improves spatial representativity. In this work, we evaluate both algorithms with respect to human observations and the reference algorithm based on ceilometers only.