Quantitative Cloud Analysis Using Meteorological Satellites

This thesis is about observations of clouds from satellite and ground based instruments. The aim is to reconstruct the three dimensional cloud distributions. This information is used both in climate research and operational meteorological applications. In climate research, cloud observations provide a reference to atmospheric models, which enables optimization of cloud parameterizations. For operational meteorologists clouds are symptoms of atmospheric conditions. Cloud observations therefore are helpful in understanding the current weather (nowcasting) and improve the estimate of how of the atmospheric conditions will evolve (forecasting).

In order to obtain cloud field characteristics, analysis environments were developed for the interpretation of meteorological satellite measurements in terms of cloud properties. A large effort was put in the evaluation of the results with synoptic observations and measurements from two measurement campaigns. As a result this thesis comprises three major research topics: Meteosat analysis, AVHRR analysis and combined analysis of ground and satellite observations.
Meteosat analysis

A new cloud detection scheme was developed that includes the use of the surface temperature fields of a Numerical Weather Prediction (NWP) model as a threshold value to distinguish cloudy and cloud free areas. It is shown that also for cloud free conditions, the equivalent black body temperature as measured from satellite is different from the model surface temperature. An innovative part of the scheme is the quantification of this temperature difference, which is used to improve the skill of the cloud detection method. The improvement of the detection efficiency was quantified over land and ocean for 1997 on a 3 hourly basis in a semi-operational setting. As the method optimizes the use of the infrared information it is relatively insensitive to changes of insolation conditions with time of day, location, or season.
AVHRR analysis

The NWP model surface temperatures are also used in the AVHRR analysis environment. For the interpretation of the 0.6 microm channel reflectivities, extensive radiative transfer calculations were done with the Doubling-Adding KNMI (DAK) radiative transfer code. The results were put in Look-up tables (LUT). The LUTs are used to obtain the following cloud field properties: cloud cover fraction, cloud top temperature, optical thickness and liquid water path. In order to assess the quality, the retrieved properties were compared to measurements from two campaigns: the Tropospheric Budget Experiment, TEBEX, and the Clouds and Radiation intensive measurement campaigns, CLARA. The comparison shows that the retrieval algorithms yield results that agree with independent ground based measurements for the cases studied.
Combined analysis of satellite and ground observations

Combined analysis of satellite and ground based observations from the TEBEX and CLARA data sets yields information on the quality of the satellite retrieval, but also on the merits of the ground based remote sensing instruments. The study shows that both observational sets have strong points, but a combination is preferred to obtain a good definition of the cloud field. In all comparisons the problem of collocation occurs. The ground based instruments measure continuous in time at one location, while satellites measure a spatial distribution at one moment in time. When comparing ground and satellite derived cloud products it is always questionable which part of the time series corresponds to which part of the spatial distribution. This correlation is studied by comparing variance spectra of time series and spatial distributions of liquid water path derived from microwave radiometer and AVHRR data respectively. It is shown that for two cases with different scaling properties the variance spectrum is similar for a part of the time-series and for a part of the AVHRR image.

This thesis contributes to quantitative use of meteorological satellite data in meteorology and climate research. Furthermore, it advances combined analysis of space born and ground based remote sensing measurements of clouds for routine applications.