engleski

Statistical correlation between satellite data and various meteorological parameters

The work presents the results of a statistical comparison of the grey shade values in satellite imagery with the values of various meteorological parameters. The main aim of the work was to combine these two types of synoptica material objectively. Instead of comparing the location and the intensity of the parameter maxima with the cloud structures in the image, the exact pixel values from the satellite image have been compared with the parameter values at each point. The pixel values from the satellite images were extracted twice daily, for six months, in the region approximately from 35° to 60°N and from 15°W to 35°E. The parameter values were extracted from the ECMWF analysis fields of vertical velocity, divergence, vorticity advection, temperature advection, Q-vector normal component, thermal front parameter, Showalter index and relative humidity. The results are shown as correlation coefficients and absolute and relative frequency tables. For the interpretation of the results relative frequency diagrams are used. In the first part the images are compared to parameters connected to vertical motion and therefore to cloud development. The results show that vertical velocity is connected to cloud formation, regardless of the synoptic situation. The correlation of w and water-vapour (WV) pixel values has also been investigated and it shows that the positive values of vertical velocity are correlated with the small pixel values in WV imagery, meaning that subsidence causes drying of the mid- and upper- tropospheric air. Compared to w, the correlation of divergence and satellite imagery is not so good. Therefore, since these two parameters are related to each other, the analysis of the w field is much more useful. Vorticity advction should be combined with temperature advection, because they act together as forcing functions for the ascending motion. Cloud development can be expected in regions with positive upper-level vorticity advection and positive temperature advection. Separate analyses show that vorticity advection is a very useful parameter in cases of comma-shaped cloud structures, enhanced cumuli clouds and frontal intensifications. This has also been proven by analysing 16 cases in which those cloud strustures occured. In case one of the mentioned cloud structures is found in the image, the path and changes of the maximum of vorticity advection can be used to follow the clouds and their development, but the forecast is then based on subjective methods, since cloud structure recognition is required. Temperature advection showed better correlation with WV then with the infra-red (IR) image, especially in the regions of low IR and low WV pixel values. However, temperature advection cannot be used as a prognostic parameter alone because strong cold air advection is not necessarily connected to low WV signals, and especcially not to low IR signals. The fact is that the regions with very low WV pixel values in the image are also characterised by cold air advection. But there are also regions with cold air advection, in which WV signals are not very low, therefore one cannot forecast low satellite signals in all regions with cold advection. The thermal front parameter and Q-vector normal component should be used only in frontal cases, because the general correlation of those parameters with pixel values in the IR satellite image is not satisfactory. The thermal front parameter shows the location of the front with vera good accuracy and the Q-vector normal component can be used for predicting frontogenesis and frontolysis in frontal regions. The combination of those two parameters seems to be a very promising tool for forecasting fronts, their intensity and development. In the analysis, threshold pixel values for IR satellite signals as well as for all the investigated parameters have been found. Those values can find their application in automatic satellite image analysis.

satellite data; meteorological parameters; correlation

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