The purposes of this research were to study organizationaL climate work motivation and work efficiency of employee at Rajamangala Universit of Technology Phra Nakhon. This is a quantitative research which samples were collected from 304 Rajamangala University of Technology Phra Nakhon employees by using proportional stratified random sampling. Data were collected through questionnaire and analyzed by frequency percentage mean standard deviation Pearson Product Moment Correlation Coefficient and multiple regression analysis. Results of this study found that : 1) organizational climate work motivation and work efficiency of Rajamangala University of Technology Phra Nakhon employees is in the high level in overall image and in individual aspect; 2) four aspects of organizational climate including the attachment and faith aspect the organization structure aspect the acceptance aspect and the work standard aspect.had an effect on work efficiency of employees at Rajamangala University of Technology Phra Nakhon. These factors couldexplain 41% of variance to work efficiency; and 3) Two factors of work motivations affected work efficiency of employees at Rajamangala University of Technology Phra Nakhon. These two factors could predict 57% of variance to work efficiency. Keywords: Organizational Climate Work Motivation Work Efficiency

At present the climate is changing due to changing environment. Industrial pollution Smoke from the traffic of cars on the road. Dust from the burning of forests etc. This change makes the climate change rapidly. Affect the temperature rise. In addition the temperature changes also affect the air pressure is changing as well. By the temperature relationship Atmospheric pressure and wind direction change dramatically in the climate such as wind storm precipitation and wind direction. This research is a forecast of air pressure and wind. To analyze the precipitation Wind and storm in the future. This is a summary of wind rain and storm in Southeast Asia including Thailand. The mathematical model used for forecasting is the Global Climate Model which is a powerful model. The initial condition of the forecasts was from the Intergovernmental Panel on Climate Change (IPCC) and the European Center for Medium Range Weather Forecasts (ECMWF) and after forecasting examined or measured the accuracy of the forecasts by Lyapunov exponent (LE) is the most commonly used forecasting method and is the basis of other methods of forecasting accuracy. In addition it is also used to measure the accuracy of the forecast is Finite time Lyapunov exponent (FTLE). Forecasting results show that the initial conditions used in forecasting result in atmospheric pressure and wind direction varying according to different starting conditions. So the temperature the air pressure and the winds cause the rain and the climate change.

The objective of this research is to develop a small and low-cost weather station. The station will be wireless transmit and receive data via radio signals. The 45mW solar cell will be used as a solar irradiance sensor which is very expensive for the weather station and the PIC18F97J60 controller will control the transmitter and receiver system. Moreover the author has developed the weather monitoring software by using LabVIEW. After testing the measurement percentage errors with the reference weather station the results showed that the relative humidity measurement error is equal to 3.106% the temperature measurement error is equal to 0.685% the wind speed is about 4.527% the wind direction measurement error is equal to 5.236% and the solar irradiance measurement error is equal to 0.501%. The longest working distance between the weather sensor and receiver unit is equal to 145 meters.

Weather predictions by an atmospheric model are determined by the uncertainties in the initial condition and the imperfection of the model. It is difficult to provide accurate weather prediction. The efficiency of weather predictions model is obtained from the analyses of Lyapunov exponent. In addition the predictability measurements is applied from Lyapunov exponent are finite size Lyapunov exponent finite time Lyapunov exponent local Lyapunov exponent together with a new method called supremum Lyapunov exponent are used to measure predictability of the northeast monsoon (winter monsoon) by the Educational Global Climate Model (EdGCM) and to test sensitivity of the model to small initial perturbations. The EdGCM sensitive to initial perturbations it is suitable for predictability of the northeast monsoon. The EdGCM is run for 142-year predictions from the year 1958 to 2100. However only the outputs of geopotential height at 500hPa of December from 2012 to 2100 are used for predictability measurement. The results show that the EdGCM predictability for the northeast monsoon forecast is about 120 years. So the EdGCM can be predictability of the long range forecast. Supremum Lyapunov Exponent Click to buy NOW! PDF-XChange Viewer www.docu-track.com Click to buy NOW! PDF-XChange Viewer www.docu-track.com

The forecasting method is important because it can predict phenomena in the future. The accuracy of the forecast depends on the model and the initial conditions. In addition the predictability measurement method is important can be check the accurate of forecasts. In this research is winter monsoon forecasts in Thailand by the shallow water model. The data from The Bjerknes Centre for Climate Research (BCCR) University of Bergen Norway. The global climate model is Bergen Climate Model (BCM) Version 2.0 (BCCR-BCM2.0) of the Intergovernmental Panel on Climate Change (IPCC) is used. The Lyapunov exponent (LE) is the predictability measurement method for verify the efficiency of model and establish the new predictability measurement method by the time series analysis. The result to show that the new predictability measurement method by the time series analysis can be measure the efficiency of the winter monsoon forecasts in Thailand by the shallow water model for December 2015 to December 2056 are suitable.