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.

Modeling and Forecasting Systems for Fusarium Head Blight and Deoxynivalenol Content in Wheat in Argentina

Abstract: In Argentina, wheat Fusarium Head Blight (FHB) is predominantly caused by Fusarium graminearum, being deoxynivalenol (DON) the main associated mycotoxin. The sporadic weather-induced nature of FHB in the Pampas region led to the development of weather-based disease and DON forecasting systems. Infective events were identified by head wetting resulting from syncronic occurrence of precipitation and high relative humidity, around wheat anthesis. Retrospective model predictions were able to identify synoptic situations and meteorological predictors of increasing space-temporal scale (for developing specific short-range and seasonal weather forecasts), regarding the disease. In the north-eastern quadrant of the Pampas region, greater disease levels were expected with greater August Southern Annular Mode values and dominance of meridional north-northeastern atmospheric circulation in September. In the southern, the Southern Oscillation index and variables associated to blocking action situations in the south (October), strongly helped to explain disease variability. Climate change impact was assessed retrospectively analyzing the trend lines of FHB incidence predictions (1931–2010), which showed light positive slopes, larger towards southern Pampas region. Prospectively, the anomaly map resulting from the difference between disease incidence estimated by future meteorological data (2071–2100, A2 scenario) and baseline climate (1961–1990), presented positive deviations in the southern Pampas region. The spatial distribution of model-based FHB incidence values using only land weather station network data was compared satisfactorily with those using both land and satellite data. Conclusions derived from FHB forecasting systems and specific weather forecasts are being used to assist producers in disease control measures to be employed.

Longitudinal associations between weather, season, and mode of commuting to school among Spanish youths.

Abstract: Aim: To study the associations of weather conditions with the travel mode choice for commuting to and from school. Methods: A total of 6,979 Spanish youths aged 7 to 18 years old (80% adolescents aged 12‐18 years old, 51% male) completed a 5‐day survey of mode of commuting to school in autumn, winter, and spring. Weather data from the nearest weather station to each school was registered. We used Google Maps™ to calculate the distance from home to school. Multilevel logistic regression models were used to estimate odds of active travel based on weather and season. Results: We analysed a total of 163,846 discrete journeys. In winter, children (aged 7 to 11 years old) were less likely to choose an active mode of commuting to school (OR: 0.72, 95% CI: 0.59‐0.89, p=0.003). In spring, adolescents were more likely to choose an active mode of commuting to school (OR: 1.43, 95% CI: 1.19‐1.73, p<0.001). With higher mean temperatures, adolescents were more likely to choose an active mode of commuting from school (OR: 1.02, 95% CI: 1.00‐1.04, p=0.029). Conclusion: Certain weather conditions seem to influence the travel mode choice for commuting to and from school in youth, including season and temperature.

NASA Prediction of Worldwide Energy Resource High Resolution Meteorology Data For Sustainable Building Design

Abstract: A primary objective of NASA's Prediction of Worldwide Energy Resource (POWER) project is to adapt and infuse NASA's solar and meteorological data into the energy, agricultural, and architectural industries. Improvements are continuously incorporated when higher resolution and longer-term data inputs become available. Climatological data previously provided via POWER web applications were three-hourly and 1x1 degree latitude/longitude. The NASA Modern Era Retrospective-analysis for Research and Applications (MERRA) data set provides higher resolution data products (hourly and 1/2x1/2 degree) covering the entire globe. Currently POWER solar and meteorological data are available for more than 30 years on hourly (meteorological only), daily, monthly and annual time scales. These data may be useful to several renewable energy sectors: solar and wind power generation, agricultural crop modeling, and sustainable buildings. A recent focus has been working with ASHRAE to assess complementing weather station data with MERRA data. ASHRAE building design parameters being investigated include heating/cooling degree days and climate zones.