Cloud Service for Analysis and Interactive Visualization of Weather Data in Armenia

The Lesser Caucasus Mountains are crossing through the territory of Armenia, creating vast differences in altitude, terrain, temperature and precipitation in provinces and towns. Even Armenia’s lowlands are 500 to 1500m above sea level. Armenias highlands extend up to Aragats mountain at 4090m where, 75% of the territory is above 1000m, 50% is above 2000m, and 3.4% is above 3000m. This paper presents a cloud service with interactive visualization and analytical capabilities for weather data in Armenia by integrating the two existing infrastructures for observational data and numerical weather prediction. The weather data used in the platform consist of near-surface atmospheric elements including air temperature, relative humidity, pressure, wind and precipitation. The visualization and analitycs have been implemented for 2m air temperature. Cloud service provides the Armenian State Hydrometeorological and Monitoring Service with analytical capabilities to make a comparative analysis between the observation data and the results of a numerical weather prediction model for per station and region for a given period.

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Characterization of downwelling radiance measured from a ground-based microwave radiometer using numerical weather prediction model data

Atmospheric Measurement Techniques ◽

10.5194/amt-9-281-2016 ◽

2016 ◽

Vol 9 (1) ◽

pp. 281-293 ◽

Cited By ~ 3

Author(s):

M.-H. Ahn ◽

H. Y. Won ◽

D. Han ◽

Y.-H. Kim ◽

J.-C. Ha

Keyword(s):

Prediction Model ◽

Numerical Weather Prediction ◽

Reference Data ◽

Weather Prediction ◽

Numerical Weather Prediction Model ◽

Radiosonde Data ◽

Absolute Calibration ◽

Observation Data ◽

Numerical Weather ◽

Better Than

Abstract. The ground-based microwave sounding radiometers installed at nine weather stations of Korea Meteorological Administration alongside with the wind profilers have been operating for more than 4 years. Here we apply a process to assess the characteristics of the observation data by comparing the measured brightness temperature (Tb) with reference data. For the current study, the reference data are prepared by the radiative transfer simulation with the temperature and humidity profiles from the numerical weather prediction model instead of the conventional radiosonde data. Based on the 3 years of data, from 2010 to 2012, we were able to characterize the effects of the absolute calibration on the quality of the measured Tb. We also showed that when clouds are present the comparison with the model has a high variability due to presence of cloud liquid water therefore making cloudy data not suitable for assessment of the radiometer's performance. Finally we showed that differences between modeled and measured brightness temperatures are unlikely due to a shift in the selection of the center frequency but more likely due to spectroscopy issues in the wings of the 60 GHz absorption band. With a proper consideration of data affected by these two effects, it is shown that there is an excellent agreement between the measured and simulated Tb. The regression coefficients are better than 0.97 along with the bias value of better than 1.0 K except for the 52.28 GHz channel which shows a rather large bias and variability of −2.6 and 1.8 K, respectively.

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Application of Statistical Weather Data From the Numerical Weather Prediction Model COSMO-2 for Noise Mapping Purposes

Acta Acustica united with Acustica ◽

10.3813/aaa.918421 ◽

2011 ◽

Vol 97 (3) ◽

pp. 403-415 ◽

Cited By ~ 3

Author(s):

J.M. Wunderli ◽

M.W. Rotach

Keyword(s):

Prediction Model ◽

Numerical Weather Prediction ◽

Weather Prediction ◽

Numerical Weather Prediction Model ◽

Weather Data ◽

Noise Mapping ◽

Numerical Weather

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The Drying Out of Soil Moisture following Rainfall in a Numerical Weather Prediction Model and Implications for Malaria Prediction in West Africa

Weather and Forecasting ◽

10.1175/2009waf2222240.1 ◽

2009 ◽

Vol 24 (6) ◽

pp. 1549-1557 ◽

Cited By ~ 3

Author(s):

Xuefeng Cui ◽

Douglas J. Parker ◽

Andrew P. Morse

Keyword(s):

Soil Moisture ◽

Prediction Model ◽

Malaria Transmission ◽

Numerical Weather Prediction ◽

Weather Prediction ◽

Numerical Weather Prediction Model ◽

Scale Model ◽

Near Surface ◽

Rainfall Events ◽

Numerical Weather

Abstract This paper investigates the response of the land surface and the lowest section of the atmospheric surface layer to rainfall events and through the subsequent drying out period. The impacts of these sequences of rainfall and drying events in controlling near-surface temperatures are put into the context of malaria transmission modeling using temperature controls on the survivability of mosquitoes that are developing the malaria parasite. Observations using measurements from a dwelling hut, constructed to a local design at Wankama near Niamey, Niger, show that as the atmosphere gets moister and colder following rainfall, there is a potentially higher risk of malaria transmission during the rainy days. As the atmosphere gets warmer and drier during the drying period, there is a potentially decreasing rate of malaria transmission as the increasing temperature reduces the survivability of the mosquitoes. A numerical weather prediction model comparison shows that the high-resolution limited-area model outperforms the global-scale model and shows good agreement with the observations. Statistical analysis from the model results confirms that the findings are not restricted to a single location or single time of the day. It was also found that air temperatures over forest areas do not change as much during the study period, since the longer memory of the soil moisture means there is relatively little influence from single rainfall events.

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