The aim of this paper is to present a research of seasonal forecasting on a scientific basis. There is no difference between the stochastic formulation for short-range forecasting and that for long-range. For the latter, however, it is far more difficult to follow the physical relation than for the former, and it is inevitable to rely mainly on empirical or statistical relationships in the procedure of framing a forecasting scheme. Our method of stochastic numerical prediction may be summarized as follows: (1) The predictors should be empirically researchful by taking meteorological experiences into consideration. Significance of meteorological hypotheses must be statistically tested. Out of the factors considered and tested, we select some effective ones in the course of framing a stochastic prediction scheme. It is important to use the data of the recent stationary period. (2) The predictors should be synthesized into a stochastic prediction formula in which periodicities, multiple correlation and similarity methods are combined. In the case of the Gaussian process, into which we can transform the original series if it is not accepted as the Gaussian, the linear prediction has an optimum property. (3) Prediction should be probability-theoretically represented; in the case of the Gaussian process it may be expressed by the conditional mean value and conditional variance of the predictand. (4) When the conditional variance is smaller, the prediction scheme is better. Thus we can construct a stochastic prediction formula which may be best relative to an ‘extent of the consideration’ in the research for predictors. But the applicability of the prediction is of course dependent on the stationarity of the process ranging from the past to the future in question. According to the principle stated above, we practiced a seasonal prediction, as a trial, under the following conditions: Predictands: Monthly mean temperature for July and August 1953 in the region represented by Miyako, and monthly total amount of precipitation for June and July in the northern parts of the Kanto district including Maebashi, Kumagaya and Utsunomiya; the division of forecasting regions was performed by a stochastic criterion. Data and deadline time: Data before March 31, 1953 were used. The extent of consideration for each predictand is described in detail as much as possible in the present paper. Predictors adopted by the authors are as follows: July temperature: long period variation, periodic fluctuation with 13.0-year period, Pontadelgade-Malye Karmakouly pressure difference for January of the year and Malye Karmakouly-Stykkisholm pressure difference for January of the year. August temperature: long-period variation, periodic fluctuation with 7.4, 13.0 and 11.4-year periods, autoregressive periodicities, change in Chichizima-Shikka pressure difference for February of the year and of the last year, and Chichizima pressure for February of the year. June precipitation: total amount of precipitation for January and February of the year, total amount of precipitation for June 6 years before and that for the same month 10 years before. July precipitation: periodic fluctuation with 7/3-year period, Barrow-Dutchharbour pressure difference for January of the year, Naha-Chichizima pressure difference for January of the year and that for March of the year. If we adopt too many predictors the precision of forecasting may be reduced owing to the reduction of degrees of freedom. The large sample prediction formula is adopted here throughout; an example of exact sampling method of prediction is published in the Journal of Meteorological Research, Vol. 6 (1954), pp. 172-183.
Many researches regarding the relationship between the solar activity and weather have been undertaken by many authors such as H. H. Clayton, S. Fujiwhara and others. But, most of them discussed mainly the relationship between the solar activity and the temperature or pressure at a single station, and their results often contradicted each other. This is due partly to the fact that most of them failed to take physical laws into account and partly to the failure of analysis from the global stand-point. Presented in this paper are the existence and mode of the 5-month oscillatory temperature change in the Northern Hemisphere and a definite relationship between the solar activity and the oscillation. The thermal budget in the earth's atmosphere is discussed for a simple model in relation to the oscillation. Obtained results are as follows: (1) The 5-month periodicity is found in the monthly course of the sunspot number as well as in the temperature-and pressure-change, the latter undergoing the same change as the former, as far as the amplitude is concerned. The phase difference of the 5-month periodicity between the solar activity and the pressure in the Northern Hemisphere may be divided into the two groups: the one with the same mode as the solar activity, the other not so. The zone of in-phase with the solar activity mentioned above is found near action centers of the atmosphere such as Siberian and North American anticyclone, the zone of out of-phase is encircling the lower latitude area. The location of the nodal line is oscillating following the change of the sunspot number. (2) The thermal budget in the earth's atmosphere is discussed by making use of the idea of the great turbulence after Ångstrom, and our conclusion is: The periodic changes of the atmospheric temperature with a period of 5-month may be attributed to the periodic change of the austausch coefficient in the atmosphere, as far as the order of magnitude is concerned, but not to the variation of the solar constant.
The distribution of ash-fall in case of the explosion of hydrogen bomb at Bikini atoll was investigated by using the wind data aloft at Kwajalein and Eniwetok. How atomic dust is diffused in the free atmosphere with time was roughly estimated from the distribution of the ash-fall of Mt. Asama.