皖江中东部雾的客观预报自动化业务系统

介绍了一种雾的客观预报方法，并研制了一个与ＳＴＹＳ接口的雾的客观预报自动化业务系统，对雾有一定的预报能力。     

多源信息方法在殷庄矿开采水文地质预测分区中的应用

根据对殷庄矿地质、水文地质、开采条件与矿井涌水之间关系的研究，提出了煤矿开采水文地质条件预测分区的方法——多源信息方法。该方法借助于地理信息系统技术实现了矿井涌水因素间的有机处理。经过将模型与实际情况反复拟合，最终得出了分区预测模型。     

The reserves of extracted resources: Historical data

The available data on known reserves of extracted resources have not previously been tabulated and graphed. In this article we compile the reserves data in one place for the first time. This serves to (1) show the trends in the reserves series, (2) make the series available to others, and (3) place the reserves data in the context of price data for which longer series have been available, and with which they can now be seen to be consistent in both showing increasing availability rather than increasing scarcity.     

A comparison of state space and multiple regression for monthly forecasts: U.S. Fuel consumption

Monthly consumption forecasts for U.S. oil, natural gas, and coal are made using state space and multiple regression applied to the same data. These forecasts are compared with actual consumption for a test period. The forecasts made using state space are preferred to those made using multiple regression models for both expost and exante cases. The state space forecasts track data cycles better than do the regression forecasts. Average absolute forecast errors are less for the state space models than they are for the multiple regression models.     

船舶气象导航随船验证

通过横流太平洋往返两个航次随船调查，研究了采用气象导航对减少燃油消耗和保证船舶安全、班期等，不但有定的经济效益，而且是一种非常有效的航运管理方法。     

用时间序列模拟和预报天山乌鲁木齐河源1号冰川年径流总量

本文把1958—1984年天山乌鲁木齐河源1号冰川的融水径流总量的时间序列X(t),分解为趋势项L(t)、周期项P(t)、平稳项S(t)、随机项ε(t),使该时间序列表示为X(t)=L(t)+P(t)+S(t)+ε(t)。采用非线性回归提取L(t),用谱分析和Fourier级数提取P(t),余差用自回归方程建模,用上述项的叠加作出预报,按相关指数公式计算R=0.90,效果良好。     

A univariate model for long-term streamflow forecasting

This paper, the first in a series of two, employs the principle of maximum entropy (POME) via maximum entropy spectral analysis (MESA) to develop a univariate model for long-term streamflow forecasting. Three cases of streamflow forecasting are investigated: forward forecasting, backward forecasting (or reconstruction) and intermittent forecasting (or filling in missing records). Application of the model is discussed in the second paper.     

PRELIMINARY STUDY OF BAROTROPIC STOCHASTIC DIFFERENCE MODEL APPLIED TO WEATHER PREDICTION

In order to consider both the deterministic and the stochastic property of atmospheric motion simul-taneously,in this paper,the weather prediction is proposed as the problem of the evolution of meteorologicalfield.The historical viewpoint of atmospheric motion is emphasized here.Based on time series analysis te-chnique,a stochastic-dynamical model with multiple initial fields is derived.Thus,weather forecasting is sum-meal up as a problem of solving a set of stochastic difference equations.For the barotropic atmosphere,thenumerical solutions of the equations are obtained by using the method of empirical orthogonal functions(EOF),and examples of medium-range weather prediction are given here.Meanwhile,selecting the order oftime series,i.e.,determining the number of initial fields properly,is also discussed.