[1] We explore implications for modeling and noise analysis of stochastic seasonal processes of climatic origin in geodetic time series. Seasonal signals are generally modeled as sinusoids with annual periods (and harmonics thereof), each with constant amplitude and phase. However, environmental noise that underlies the seasonal signal in geodetic time series has a reddened power spectral densi...

INTRODUCTION The seasonal variability in hospitalization for tuberculosis may in part relate to super-imposed bacterial or predisposing respiratory viral infections. We aimed to study the temporal association between hospitalization for culture-confirmed pulmonary tuberculosis (PTB), invasive pneumococcal disease (IPD) and influenza virus epidemics in South African children. METHODS We undert...

4 The seasonal cycle of the heating of the atmosphere is divided into a component due to direct 5 solar absorption in the atmosphere, and a component due to the flux of energy from the 6 surface to the atmosphere via latent, sensible, and radiative heat fluxes. Both observations 7 and coupled climate models are analyzed. The vast majority of the seasonal heating of the 8 Northern extratropics (...

Animals cope with seasonal variation in environmental factors by adjustments of physiology and life history. When seasonal variation is partly predictable, such adjustments can be based on a genetic component or be phenotypically flexible. Animals have to allocate limited resources over different demands, including immune function. Accordingly, immune traits could change seasonally, and such ch...

The seasonal mean of a climate variable is affected by processes with timescales from less than seasonal to interannual or longer. In this paper, the seasonal mean is conceptualised as consisting of intraseasonal and slowly varying (longer than a season) components. The slow component of the seasonal mean is related to slowly varying internal and external processes which are potentially predict...

A meteor radar in the UK (near 52 N) has been used to measure the mean winds of the mesosphere/lowerthermosphere (MLT) region over the period 1988–2000. The seasonal course and interannual variability is characterised and comparisons are made with a number of models. Annual mean wind trends were found to be +0.37 ms−1 yr−1 for the zonal component and +0.157 ms−1 yr−1 for the meridional componen...

Wind and temperature observations in the mesosphere and lower thermosphere (MLT) from the Upper Atmosphere Research Satellite (UARS) reveal strong seasonal variations of tides, a dominant component of the MLT dynamics. Simulations with the Spectral mesosphere/lower thermosphere model (SMLTM) for equinox and solstice conditions are presented and compared with the observations. The diurnal tide i...

In this study, a hybrid approach based on seasonal decomposition (SD) and least squares support vector regression (LSSVR) model is proposed for air passenger forecasting. In the formulation of the proposed hybrid approach, the air passenger time series are first decomposed into three components: trend-cycle component, seasonal factor and irregular component. Then the LSSVR model is used to pred...

Present study is about using of nonparametric models for GDP (Gross Domestic Product) per capita prediction in Turkey. It has been considered two alternative situations due to seasonal effects. In the first case, it is discussed a semi-parametric model where parametric component is dummy variable for the seasonality. In the second case, it is considered the seasonal component to be a smooth fun...

This paper studies two types of seasonal time series models with periodic variances. Covariance structures of the noise component in the models are discussed. For parameters in the regression component, the performance of the least squares estimates relative to the best linear unbiased estimates is investigated, and some lower bounds for the eecient coeecient deened by the covariance matrices o...