Temperature forecasting and rain forecasting in today's environment is playing a major role in many fields like transportation, tour planning and agriculture. The purpose of this paper is to provide a real time forecasting to the user according to their current position and requirement. The simplest method of forecasting the weather, persistence, relies upon today's conditions to forecast the c...

Stochastic daily weather time-series models ("weather generators") are parameterized consistent with both local climate and probabilistic seasonal forecasts. Both single-station weather generators, and spatial networks of coherently operating weather generators are considered. Only a subset of parameters for individual station models (proportion of wet days, precipitation mean parameters on wet...

Despite the existence of several weather studies in the tourism literature, there remain some gaps in knowledge. Uncertainty about weather conditions persists despite the impressive improvements in modern forecasting techniques. This study is a first attempt to investigate how weather uncertainty affects tourism demand. The findings indicate that the impact of weather on tourism demand is likel...

Pfender, W. F., Gent, D. H., and Mahaffee, W. F. 2012. Sensitivity of disease management decision aids to temperature input errors associated with sampling interval and out-of-canopy sensor placement. Plant Dis. 96:726-736. Many plant disease epidemic models, and the disease management decision aids developed from them, are created based on temperature or other weather conditions measured in or...

the hargreaves-samani (hs) equation, which estimates reference evapotranspiration (et0) using only temperature as input, should be most suitable for et0 prediction based on weather forecasting data. in the current study, the hs equation is calibrated with daily et0 by the penman-monteith equation, and is evaluated to check the possibility of predicting daily et0 based on weather forecast data. ...

We propose a continuous-time autoregressive model for the temperature dynamics with volatility being the product of a seasonal function and a stochastic process. We use the Barndorff-Nielsen and Shephard model for the stochastic volatility. The proposed temperature dynamics is flexible enough to model temperature data accurately, and at the same time being analytically tractable. Futures prices...

Outbreaks of dengue occur in Queensland, Australia nearly every summer. In 2008-2009, there was an unusually large, protracted outbreak of dengue, comprised of 1,200 cases. We investigated the weather variables and their contribution to the 2008-2009 dengue outbreak in Queensland. Case data were obtained from the Communicable Disease Branch of Queensland Health for 2000-2010 for the towns of Ca...

BACKGROUND Patients frequently report that weather changes trigger headache or worsen existing headache symptoms. Recently, the method of empirical mode decomposition (EMD) has been used to delineate temporal relationships in certain diseases, and we applied this technique to identify intrinsic weather components associated with headache incidence data derived from a large-scale epidemiological...

a r t i c l e i n f o JEL classification: C18 C51 Keywords: Temperature Time series model Weather derivatives Seasonality GARCH In this paper we present a stochastic model for daily average temperature. The model contains seasonality, a low-order autoregressive component and a variance describing the heteroskedastic residuals. The model is estimated on daily average temperature records from Sto...