Topic
Weather station
About: Weather station is a research topic. Over the lifetime, 1789 publications have been published within this topic receiving 42864 citations. The topic is also known as: meteorological station & meteorological observation post.
Papers published on a yearly basis
Papers
More filters
TL;DR: The authors observed the visible butterfly migration at Falsterbo peninsula, the southwesternmost point in Sweden, where red admirals are seen most autumns flying towards the Danish coast on their way to more southern parts of Europe.
35 citations
TL;DR: In this article, the authors examined additional factors affecting ambient temperature correction of weather station data in forensic entomology, including length of correlation period, distance between BDS and weather station, and periodicity of ambient temperature measurements.
Abstract: This paper expands on Archer (J Forensic Sci 49, 2004, 553), examining additional factors affecting ambient temperature correction of weather station data in forensic entomology. Sixteen hypothetical body discovery sites (BDSs) in Victoria and New South Wales (Australia), both in autumn and in summer, were compared to test whether the accuracy of correlation was affected by (i) length of correlation period; (ii) distance between BDS and weather station; and (iii) periodicity of ambient temperature measurements. The accuracy of correlations in data sets from real Victorian and NSW forensic entomology cases was also examined. Correlations increased weather data accuracy in all experiments, but significant differences in accuracy were found only between periodicity treatments. We found that a >5°C difference between average values of body in situ and correlation period weather station data was predictive of correlations that decreased the accuracy of ambient temperatures estimated using correlation. Practitioners should inspect their weather data sets for such differences.
35 citations
TL;DR: In this article, daily shortwave solar radiation accumulations were estimated using three existing models over the period 1990 through 2000 for 10 locations across the North Central Region of the USA where hourly automated weather stations provided observations of solar radiation.
34 citations
TL;DR: In this article, a new statistical downscaling framework is proposed to evaluate the climate change impact on wind resources in Taiwan Strait, where a two-parameter Weibull distribution function is used to estimate the wind energy density distribution in the strait.
34 citations
TL;DR: In this article, the authors quantify the effects of three unrelated but complementary aspects of uncertainty in weather station interpolations on SDM performance using MaxEnt, including topographic heterogeneity, interannual variability, and distance to station on the over- and under-prediction of modeled North American bird distributions.
Abstract: Species distribution models (SDMs) are used to generate hypotheses regarding the potential distributions of species under different environmental conditions, such as forecasts of species range shifts in response to climate change and predictions of invasive species range expansions. However, an accurate description of species' geographic ranges as a function of the environment requires that species observations and climatic variables are measured at the same spatial and temporal resolution, which is usually not the case. Weather station data are interpolated and these resulting continuous data layers are incorporated into SDMs, often without any uncertainty assessment. Here we quantify the effects of three unrelated but complementary aspects of uncertainty in weather station interpolations on SDM performance using MaxEnt. We examine the influence of topographic heterogeneity, interannual variability, and distance to station on the over- and under-prediction of modeled North American bird distributions. Our species observations are derived from presence-absence information for 20 bird species with well-known distributions. These three metrics of uncertainty in interpolated weather station data have varying contributions to over- and under-prediction errors in SDMs. Topographic heterogeneity had the highest contribution to omission errors; the lowest contribution to commission errors was from Euclidean distance to station. The results confirm the importance of establishing an appropriate relational basis in time and space between species and climatic layers, providing key operational criteria for selection of species observations fed into SDMs. Our findings highlight the importance of identifying weather stations locations used in interpolated products, which will allow a characterization of some aspects of uncertainty and identification of regions where users need to be particularly careful when making a decision based on a SDM.
34 citations