Neonatal survival was positively affected by spring precipitation independently of population density. The effect of weather on lamb winter survival did not vary with density. This also involved fitting quadratic effects in weather variables, testing the full‐time series excluding weather and the final models for lag 2 delayed density dependence and graphical examination of any apparent trends. Then the monthly load, the radiation, collector parameters, and system size numbers are combined to produce the final result. The number of variables for inclusion then varied between two and 10, depending on the species. Analyses were restricted to 31 species that are recorded from a sufficient number of sites and years to produce an all‐sites collated index. Correlation and regression analyses were used to assess the impact of weather on bicycle use. In closing, we reiterate that our primary aim in this study was to introduce a technique for estimating the probability of occurrence of extreme space weather events. Our results allowed us to answer a basic question, at least in an approximate way: How likely are such events? The answer is actually pretty simple; It is off season!

The answer of course depends on what you mean by “event” and how severe you define “extreme” to be. Thin plate smoothing splines with elevation as an independent variable were used for the global interpolation of mean monthly rainfall and temperature. Winter survival was positively correlated with temperature and precipitation during the previous spring, negatively correlated with density, and independent of winter temperature or snowfall. Our study clearly demonstrates density-dependence in lamb survival. Some of the effects of weather on lamb survival are density-independent, others are mediated by an interaction with population density. ABSTRACT: The paper describes a method for the spatial interpolation of the site-specific LARS-WG stochastic weather generator to produce ‘realistic’ daily weather data for the gaps between observed sites. The interpolation method showed a good performance at the 3 sites when compared to the observed data, the main differences occurring when the spline method was unable to reproduce closely the observed mean values. A thorough evaluation showed that the method is both accurate (95 to 99% correct) and has good coverage (between 60 and 78% of known factors were identified). However, such assessments are often applied across regions and so there is a need for an interpolation method to provide input daily weather at many sites or grid-boxes where observed weather data is not available.

Weather is one factor that is believed to have a significant impact on bicycle use as a transportation mode. The results of studies such as this one can be used in conjunction with previous findings to estimate the proportion of present-day automobile travel that could be transferred to bicycle travel, if appropriate bicycle facilities are provided. The study reveals that a larger proportion of travel to work is done by bicycle than of travel for discretionary purposes regardless of weather conditions. I argue that weather enters visual awareness not as a scenic panorama but as an experience of light. Some people like to visit the country during the pleasant summer months while others go to experience the most picture-perfect time during Christmas. January to March being the wettest months. Everything seems slowly but surely returning to being conservative. Understanding demographic processes will be essential to construct robust models of population responses to climate change. Weather radars with conventional antenna cannot provide desired volume scan updates at intervals of one minute or less, which is essential for significant improvement in warning lead time of impending storm hazards.

This property has fundamental implications for weather and climate prediction as it allows an assessment of the reliability and hence confidence in the probability distribution of the forecasts. This finding has some important implications for efforts to develop a new incident detection agorithm for freeways, based on the nature of the flow-occupancy relationship. End of the world is not merely a saying; its implications would vary from place to place and country to country. The effects of density‐dependent processes operating on a local scale are included implicitly in the model through their indirect effects on population change at the regional scale. A justification for analysing overall change is the observed widespread synchrony in butterfly population fluctuations on a large spatial scale, which is ascribed partly to weather‐related regional stochasticity (Pollard et al. 1986; Pollard Sutcliffe et al. Andrew Orrison of the National Oceanic and Atmospheric Administration’s (NOAA) Weather Prediction Center advises that people should keep track of flight schedules and weather reports.