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.

Estimation of Soil Moisture and Irrigation Requirement of Upland using Soil Moisture Model applied WRF Meteorological Data

Abstract: The aim of this study was to develop a soil moisture simulation model equipped with meteorological data enhanced by WRF (Weather Research and Forecast) model, and this soil moisture model was applied for quantifying soil moisture content and irrigation requirement. The WRF model can provide grid based meteorological data at various resolutions. For applicability assessment, comparative analyses were conducted using WRF data and weather data obtained from weather station located close to test bed. Water balance of each upland grid was assessed for soils represented with four layers. The soil moisture contents simulated using the soil moisture model were compared with observed data to evaluate the capacity of the model qualitatively and quantitatively with performance statistics such as correlation coefficient (R), coefficient of determination (R2) and root mean squared error (RMSE). As a result, R is 0.76, is 0.58 and RMSE 5.45 mm in soil layer 1 and R 0.61, 0.37 and RMSE 6.73 mm in soil layer 2 and R 0.52, 0.27 and RMSE 8.64 mm in soil layer 3 and R 0.68, 0.45 and RMSE 5.29 mm in soil layer 4. The estimated soil moisture contents and irrigation requirements of each soil layer showed spatiotemporally varied distributions depending on weather and soil texture data incorporated. The estimated soil moisture contents using weather station data showed uniform distribution about all grids. However the estimated soil moisture contents from WRF data showed spatially varied distribution. Also, the estimated irrigation requirements applied WRF data showed spatial variabilities reflecting regional differences of weather conditions.

Winter Offshore/Onshore Wind Differences in Southeastern Hudson Bay, Canada

Abstract: Acquisition of two 38-day wind data sets collected over a fast-ice shelf and at a nearby coastal weather station (Kuujjuarapik) in Hudson Bay allowed the calculation for the first time of an offshore/onshore wind speed ratio for an ice-covered environment. Mean wind over the ice was 29% higher than at the coast, compared to values of 65% for open ocean locations. This reflects the effect of the higher drag coefficient of the sea ice that more strongly attenuates the wind than does the sea surface. The data set also allowed the evaluation of the change in the wind field by local topography. Thus, a strong orographic effect was found in the SW quadrant, as winds of less than 5 m/s were deflected toward the SE and NW.

The answer is blowing in the wind: Weather effects on personality ratings.

Abstract: . This study examined the effects of weather on personality self-ratings. Single-assessment data were derived from the German General Social Survey conducted in 2008. For a subset of the participants (N = 478), official weather station data for the day a personality inventory was completed could be determined. Among these respondents, 140 (29%) completed the personality inventory on an unambiguously sunny day, 59 (12%) completed the measure on an unambiguously rainy day, and 279 (59%) completed the questionnaire on a day characterized by mixed weather conditions. Results revealed that self-ratings for some personality domains differed depending on the weather conditions on the day the inventory was completed. When compared with corresponding self-ratings collected under mixed weather conditions, ratings for the Big Five dimension of Openness to Experience were significantly lower on rainy days and ratings for Conscientiousness were significantly lower on sunny days. These results are suggestive of...

Comprehensive investigations on Life Cycle Climate Performance of unitary air-conditioners.

Abstract: Life Cycle Climate Performance (LCCP) evaluation of air conditioning systems helps to mitigate the carbon emissions from the rapidly expanding air conditioning systems. Nevertheless, different counties have different system evaluation standards, weather conditions, grid emission factors, and material carbon emission coefficients. Furthermore, new R-410A alternatives like R-466A were rarely discussed. Besides, some researchers used the weather station data instead of onsite weather data. However, the weather data collected from the UMDCP campus and the College Park airport in the USA were different up to 5 °C due to the heat island effect. This paper used a unitary air conditioner as a case study and compared the LCCP calculation results for 11 cities worldwide for five different refrigerants. As excellent candidates for replacing R-410A from the LCCP perspective, R-32, R-290, R-452B, and R-466A are considered in this study. Then, the results using field test data and weather station data were compared. In conclusion, annual energy consumption is a significant factor in high-emission-factor countries. In some low-emission-factor countries, the LCCP can be decreased by up to 60% by using R-290. The differences between the actual inlet air temperature to the outdoor unit and local weather station measured temperature can result in up to an 8% difference in LCCP. For future work, more works on futuristic assumptions for grid emission factors and variable speed systems are needed while considering the expansion of renewable energies and energy efficient variable speed systems.