scholarly journals Quality Control of Agro-meteorological Data Measured at Suwon Weather Station of Korea Meteorological Administration

2015 ◽  
Vol 17 (1) ◽  
pp. 25-34 ◽  
Author(s):  
Gyu-Lim Oh ◽  
Seung-Jae Lee ◽  
Byoung-Choel Choi ◽  
Joon Kim ◽  
Kyu-Rang Kim ◽  
...  
Keyword(s):  
Quality Control ◽  
Meteorological Data ◽  
Weather Station ◽  
Korea Meteorological Administration

scholarly journals Modelling the mass balance of northwest Spitsbergen glaciers and responses to climate change

1997 ◽  
Vol 24 ◽  
pp. 203-210 ◽  
Author(s):  
Kevin M. Fleming ◽  
Julian A. Dowdeswell ◽  
Johannes Oerlemans
Keyword(s):  
Climate Change ◽  
Mass Balance ◽  
Meteorological Data ◽  
Balance Model ◽  
Greenhouse Warming ◽  
Weather Station ◽  
Mass Balances ◽  
Area Distribution ◽  
Sensitivity Tests ◽  
Precipitation Increase

An energy-balance model is used to calculate mass balance and equilibrium-line altitudes (ELAs) on two northwest Spitsbergen glaciers, Austre Brøggerbreen and Midre Lovénbreen, whose mass balances are at present negative, and for which greater than 20 year records of mass-balance data are available. The model takes meteorological data, ice-mass area distribution with altitude, and solar radiation as inputs. Modelling uses mean daily meteorological data from a nearby weather station, adjusted for altitude. Average net balances modelled for 1980–89 using models tuned to the decade’s average were –0.44 and –0.47 m w.e. for Lovénbreen and Brøggerbreen, respectively, compared with the measured averages of –0.27 and –0.36 m. Sensitivity tests on glacier response to greenhouse warming predict a net balance change of –0.61 m year–1 per °C temperature rise relative to today, and a rise in ELA of 90 m °C–1. Modelling of Little lee Age conditions in Spitsbergen suggests that a 0.6°C cooling or a precipitation increase of 23% would yield zero net mass balance for Lovénbreen and that further cooling would increase net balance by 0.30 m year–1 °C–1. Set in the context of similar modelling of southern Norwegian, Alpine and Greenland ice masses, these results support the suggestion that glaciers with a maritime influence (i.e. higher accumulation) are most sensitive to climate change, implying a gradient towards decreasing sensitivity as accumulation decreases eastward and with altitude in Svalbard.

scholarly journals Impact Assessment for Building Energy Models Using Observed vs. Third-Party Weather Data Sets

2020 ◽  
Vol 12 (17) ◽  
pp. 6788 ◽  
Author(s):  
Eva Lucas Segarra ◽  
Germán Ramos Ruiz ◽  
Vicente Gutiérrez González ◽  
Antonis Peppas ◽  
Carlos Fernández Bandera
Keyword(s):  
Energy Demand ◽  
Meteorological Data ◽  
Building Energy ◽  
Third Party ◽  
Weather Data ◽  
Data Sets ◽  
Weather Station ◽  
Energy Models ◽  
The Impact ◽  
Energy Strategies

The use of building energy models (BEMs) is becoming increasingly widespread for assessing the suitability of energy strategies in building environments. The accuracy of the results depends not only on the fit of the energy model used, but also on the required external files, and the weather file is one of the most important. One of the sources for obtaining meteorological data for a certain period of time is through an on-site weather station; however, this is not always available due to the high costs and maintenance. This paper shows a methodology to analyze the impact on the simulation results when using an on-site weather station and the weather data calculated by a third-party provider with the purpose of studying if the data provided by the third-party can be used instead of the measured weather data. The methodology consists of three comparison analyses: weather data, energy demand, and indoor temperature. It is applied to four actual test sites located in three different locations. The energy study is analyzed at six different temporal resolutions in order to quantify how the variation in the energy demand increases as the time resolution decreases. The results showed differences up to 38% between annual and hourly time resolutions. Thanks to a sensitivity analysis, the influence of each weather parameter on the energy demand is studied, and which sensors are worth installing in an on-site weather station are determined. In these test sites, the wind speed and outdoor temperature were the most influential weather parameters.

Realization and use of a digital portable Weather Station - An integrated example of technological applications of low cost and high quality professional hardware platforms for innovative laboratory teaching in the classroom

2020 ◽  
Author(s):  
Pietro Crimi
Keyword(s):  
Communication Networks ◽  
Meteorological Data ◽  
Low Cost ◽  
Online Communication ◽  
Lower Troposphere ◽  
Mobile Systems ◽  
Advanced Technology ◽  
Weather Data ◽  
Weather Station ◽  
Laboratory Teaching

<p>As part of the innovation in the laboratory teaching of Natural Sciences, an experimental path of learning of Atmospheric Sciences and Microclimates is proposed in continuation and evolution, which was presented with a poster at the GIFT workshop 2017, an experience of project, construction and use of a mobile and portable Weather Station with digital features.By identifying the main parameters that measure the physical characteristics of the lower troposphere and the corresponding sensors responsible for detecting instantaneous weather data, a project was developed for the construction of a mini weather station with an assembly system of modular electronic components in "open source" , such as those of the "Arduino" platform (series of electronic boards equipped with a microcontroller). In this way, a device for controlling the main weather parameters (temperature, atmospheric pressure, relative humidity, ...) in real time in any part of the territory was achieved relatively quickly and easily. The hardware platform in pre-assembled version, with specific microcontrollers and USB interface for connections to the most advanced computer devices, together with the sensors, which can be acquired through the online network, allow you to create a completely inexpensive but absolutely professional, effective and efficient weather mobile system as well as easily transportable in various external and internal environments. The subsequent data collection, through visualization with advanced technology display and fast and online communication networks, by means of applications for mobile systems (tablets and smartphones), integrated by field observations, define the instantaneous weather and to process meteorological data in statistical terms with simple operations and graphs.</p>

scholarly journals Determining the Optimal Spatial Distribution of Weather Station Networks for Hydrological Modeling Purposes Using RCM Datasets: An Experimental Approach

2014 ◽  
Vol 15 (1) ◽  
pp. 517-526 ◽  
Author(s):  
Richard Arsenault ◽  
François Brissette
Keyword(s):  
River Basin ◽  
Optimization Algorithm ◽  
Water Resource Management ◽  
Hydrological Modeling ◽  
Climate Model ◽  
Meteorological Data ◽  
High Density ◽  
Limiting Factor ◽  
Weather Station ◽  
Weather Stations

Abstract In many hydrological studies, the main limiting factor in model performance is the low meteorological data quality. In some cases, no meteorological records even exist. Installing weather stations becomes a necessity in these areas when water resource management becomes an issue. The objective of this study is to propose a new experimental and exploratory method for determining the optimal density of a weather station network when being used for long-term hydrological modeling. Data from the Canadian Regional Climate Model at 15-km resolution (CRCM15) were used to create a virtual network of stations with long and complete series of meteorological data over the Toulnustouc River basin in central Québec, Canada. The weather stations to be fed to HSAMI, Hydro-Québec's lumped rainfall–runoff hydrological model, were selected in order to minimize the number of stations while maintaining the best hydrological performance possible using a multi-objective optimization algorithm. It was shown that the number of stations making up the network on the Toulnustouc River basin should be at least two but not higher than four. If the stations are positioned optimally, there is little to no gain to be made with a denser network. The optimization algorithm clearly identified that combinations of two or three stations can result in better hydrological performance than if a high-density network was fed to the model. Thus, the major conclusion of this study is that if weather stations are positioned at optimal locations, a very few number of them are required to model runoff with as good as or better performance than when a high-density network is used.

Estimating wetness duration on maize ears from meteorological observations

1998 ◽  
Vol 78 (1) ◽  
pp. 149-154 ◽  
Author(s):  
P. S. Rao ◽  
T. J. Gillespie ◽  
A. W. Schaafsma
Keyword(s):  
Fungal Infections ◽  
Meteorological Data ◽  
Physical Models ◽  
Dew Point ◽  
Spatial And Temporal Variability ◽  
Threshold Models ◽  
Moderate Degree ◽  
Weather Station ◽  
Surface Wetness ◽  
Energy Balance Approach

The onset and cessation of surface wetness on maize ears were simulated with six models, using hourly meteorological data, to examine the linkage between wetness duration and possible forecasting of fungal infections that produce mycotoxins. Two threshold models (using relative humidity and dew point temperature), one regression model (using humidity and wind speed), and three physical models based on the energy balance approach, were compared. Also, spatial and temporal variability in wetness duration was measured and simulated at three sites located at distances up to 29 km from a central weather station. The estimated wetness values were compared with observations from cylindrical wetness sensors placed near ear level in maize canopies. The results relate to potential mycotoxin warning systems and indicate that threshold models can provide reasonable estimates of ear wetness duration in this region, that a comprehensive physical model can give superior estimates, and that wetness estimates made from a central weather station data can be extended to nearby crop fields with a moderate degree of confidence. Key words: epidemiology, mycotoxins, surface wetness models

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