In this paper the prediction of the spatial correlation coefficient and the time correlation coefficient of the atmospheric disturbances has been discussed in connection with the distribution function of the fluctuations in pressure patterns. In the case of wind-tunnel turbulence, the spatial correlation coefficients are easily trans-formed to the time correlation coefficients, since the time coordinate t is transformed to the space coordinate x, multiplying the general flow U by t. In the case of atmospheric disturbances, however, the transformation is not uniquely determined and hence there occurs an apparent difference between the spatial and time correlation coefficients.
Crimes such as fraud, bicycle theft and larceny are partly due to the carelessness of victims. So the number of occurrence of these crimes may provide a good information of the people's carelessness. In order to study the psychological effect of weather factors, as precipitation, wind velocity, humidity, temperature, pressure, etc., we analysed the variance of the number of occurrence of the above crimes according to police records, getting rid of physical influences of weather.
Several statistical quantities such as the intensity and correlation coefficients of temperature fluctuations in the atmosphere and oceans are theoretically derived from thermal similarity hypotheses of two different kinds which give the -7/3 and the -5/3 power law of fluctuation spectrum, respectively. Relations between statistical quantities and the averaging procedures in observation are given in two different forms following either hypothesis. Some observational results seem supporting the -7/3 power law rather than the -5/3 power law.
Since the accurate height of high cloud is measured by balloon tracking, we can know the meteorological elements there from radiosonde data. High cloud exists in the transitional layer between two air flows. This transitional layer has the temperature lapse rate of about 0.2_??_0.4°C/100m. From the fact that the balloon disappears at the top, inside, and base of the layer, the thickness of the layer seems to denote the thickness of high cloud but it follows, the thickness of the layer is not in so good proportion to the thickness by sight, and we must consider not only the thickness but also the density of the cloud particles. We have no reliable data of, humidity at higher level. Hair hygrometer doesn't work enough there, and in this paper the value is decided from temperature and humidity. Temperature range of high cloud extends -10_??_-50°C. This has a certain connection with the experiments on the growth of ice crystals. By analysis of transitonal, layer on time-isopleth, we can analyse the states of high cloud, and make it use for weather forecast. Here we show two cases, that is, developing and dissipating of high cloud. Relation between temperature lapse rate and state of the sky (CH) is given as one of the general results.