In order to review the present status of bioclimate research and weather-health forecasting in Japan, development is first described briefly for the periods of the first and second halves of the 20th Century. Important topics for further development are demonstrated to be: temperature change; lifestyle changes; historical approaches used such as weather-related proverbs, old documents, etc.; an...

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WRF-Chem simulations of aerosol seasonal variability in the San Joaquin Valley (SJV), California, are evaluated by satellite and in situ observations. Results show that the WRF-Chem model successfully captures the distribution and magnitude of and variation in SJV aerosols during the cold season. However, aerosols are not well represented in the warm season. Aerosol simulations in urban areas d...

ecological changes resulting from climate conditions can severely affect human societies especially in the area of economy and safety. climate catastrophes may cause social and economic tension. forecasting such changes accurately can help the government to control the disasters and to achieve possible benefits (such as water supply in flood). weather forecasting is the application of science a...

Evolutionary training methods for Artificial Neural Networks can escape local minima. Thus, they are useful to train recurrent neural networks for short-term weather forecasting. However, these algorithms are not guaranteed to converge fast or even converge at all due to their stochastic nature. In this paper, we present an algorithm that uses implicit gradient information and is able to train ...

Wetzel and Martin present an ingredients-based methodology for forecasting winter season precipitation. Although they are to be commended for offering a framework for winter-weather forecasting, disagreements arise with some of their specific recommendations. In particular, this paper clarifies the general philosophy of ingredients-based methodologies and shows how the methodology presented by ...

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This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV). The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and ...

The multi-point values of an appropriate smoothing parameter of HP-filter algorithm for midterm electricity load demand (MELD) forecasting are proposed. The case study employs the data based on the organization of the Electricity Generating Authority of Thailand (EGAT). The research shows the growth at rate of weather and economic factors influencing to the electricity demand. The main focus of...