TEMPERATURE DISTRIBUTION AND ITS MESO-CLIMATOLOGICAL ANALYSIS IN THE KANTO PLAIN

Abstract

A method of meso-climatological analysis using temperature data available in a great number is presented in this paper. The changing rate of temperature variation at a given place may be expressed by the following equation. _??_ where the first term on the right denotes horizontal advection and the second is the changing rate due to the heat transfer from the ground. When an area with a meso-scale horizontal extention of the order of 104-105m and also a uniform surface condition is entirely included in a macro-scale disturbance such as an anticyclonic cell, the areal differences of temperature changing rate due to the first term may be negligible. In this case temperature differences within this area are considered to appear in connection with advection by meso-scale disturbance. On the assumption mentioned above, the author prepared 183 daily maximum temperature distribution patterns of summer half year in 1958 using about 170 climatological stations in and around the Kanto Plain (dots in Figure 11 show their locations). During this season the advection effect by meso-scale sea. breezes was predominant. Three typical distribution patterns, diurnal temperature records, and wind data at the three-hour interval are shown in Figures 1, 2, and Table 1 respectively. According to these, it is possible to recognize clearly that the lower temperatures along the coasts on May 31 st are the result of the sea breeze invasion and on the other two days its effect is not conspicuous because of the general wind. Similiar tendncies appear on almost all the fine days, but on rainy or cloudy days no marked pat-terns develop. Temperature distribution patterns were classified into five groups, i. e., sea breeze-, SSW-, S-, ESE-, and E-type, according to the conditions of general wind. Then ten typical patterns were selected for each of the five groups, Table 2 shows the dates and the wind conditions for these selected 50 days.In order to clarify the above-mentioned advection effects quantitatively, the author constructed a chart showing the mean temperature gradients ∇ T using the data from the above-mentioned ten patterns, and the same procedure was employed for all other four groups, resulting in five charts. The calculated mini-mum value of the temperature gradient was 1/20°C/km, and its direction was counted on a 16-point scale. The results obtained are shown in Figures 4, 5, 6, 8, and 9, where the width of arrows is proportional to the magnitude of vectors and the direction of arrows is towards higher temperature. The vectors were calculated at 308 points as shown in Figure 3. The pattern of these 308 points was. made by a following special method. Then lines were first drawn all parallel to the coast lines at the interval of 7km. except for the first line nearest to the coasts. The 308 points were then plotted on these lines at the same interval, This interval 7km, was determined empirically. Figure 10 is the simplified and comparative presentation of Figures 4, 5.6.8. and 9. It may be possible to recognize the influence of the sea for representative general wind conditions respectively. In case of sea breeze-type, i.e., on fine and calm days, the sea breeze effect is marked until 10-15km. inland from the coasts. The effect of Tokyo Bay is clear in the case of prevailing Sor SSW-general wind, In fur. they detail, topographical effects on temperature distribution also can be found. As a result of a precise examination of the two maps in Figure 11, standard deviation of daily maximum temperature may be proposed as an appropriate parameter for expressing well the meso-climatological characteristics.