Integration the Meteorological Data for Monitoring the Troposphere Condition Over the Military Aerodrome in Dęblin

Abstract The integration of meteorological and tropospheric data is extremely important in precise monitoring of the atmosphere condition over a selected aerodrome. The paper presents the results of troposphere monitoring over the military aerodrome EPDE in Dęblin in Lubelskie Voivodeship in Poland. The three sources of meteorological data were applied for troposphere monitoring, namely: GNSS satellite technique, SYNOP data, TAF data. The troposphere empirical models within the GNSS satellite technique were utilized in the designation of the meteorological parameters, e. g. temperature, pressure and relative humidity. In paper, the meteorological parameters were estimated using three deterministic model, e.g.: SA model, RTCA-MOPS model and also GPT model.

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Is hand, foot and mouth disease associated with meteorological parameters?

Epidemiology and Infection ◽

10.1017/s0950268810002256 ◽

2010 ◽

Vol 138 (12) ◽

pp. 1779-1788 ◽

Cited By ~ 83

Author(s):

E. MA ◽

T. LAM ◽

C. WONG ◽

S. K. CHUANG

Keyword(s):

Wind Speed ◽

Relative Humidity ◽

Meteorological Parameters ◽

Meteorological Data ◽

Foot And Mouth Disease ◽

Mouth Disease ◽

Diurnal Difference ◽

Foot And Mouth ◽

Winter Peak ◽

The Relationship

SUMMARYWe examined the relationship between meteorological parameters and hand, foot and mouth disease (HFMD) activity. Meteorological data collected from 2000 to 2004 were tested for correlation with HFMD consultation rates calculated through the sentinel surveillance system in Hong Kong. The regression model constructed was used to predict HFMD consultation rates for 2005–2009. After adjusting for the effect of collinearity, mean temperature, diurnal difference in temperature, relative humidity, and wind speed were positively associated with HFMD consultation rates, and explained HFMD consultation rates well with 2 weeks' lag time (R2=0·119,P=0·010). The predicted HFMD consultation rates were also also well matched with the observed rates (Spearman's correlation coefficient=0·276,P=0·000) in 2005–2009. Sensitivity analysis showed that HFMD consultation rates were mostly affected by relative humidity and least affected by wind speed. Our model demonstrated that climate parameters help in predicting HFMD activity, which could assist in explaining the winter peak detected in recent years and in issuing early warning.

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Influence of Sunshine Hour and Relative Humidity on Total Solar Radiation at Nepalganj, Nepal

Patan Pragya ◽

10.3126/pragya.v6i1.34404 ◽

2020 ◽

Vol 6 (1) ◽

pp. 97-104

Author(s):

Usha Joshi ◽

P. M. Shrestha ◽

I. B. Karki ◽

N. P. Chapagain ◽

K. N. Poudyal

Keyword(s):

Relative Humidity ◽

Solar Radiation ◽

Meteorological Parameters ◽

Clean Energy ◽

Empirical Models ◽

Energy Resources ◽

Total Solar Radiation ◽

Sunshine Hour ◽

Empirical Constants ◽

Better Than

The solar energy is the abundantly available free and clean energy resources in Nepal. There are more than 300 sunny days because of Nepal lies in solar zone in a global map. The total solar radiation was measured by using CMP6 pyranometer at Nepalgunj (lat.:28.10oN, long.: 81.67oEand Alt. 165.0masl). The main objective of this study is to select the better empirical model and its empirical constants for the prediction of TSR for the year come. In this research, six different empirical models and meteorological parameters are utilized in the presence of regression technique for the years 2011 and 2012. Finally the different empirical constants are found. After the error analysis, the Swarthman-Oguniade model is found to perform better than others models. So the empirical constants of this model is utilized to predict the TSR of similar geographical sites of Nepal.

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The Study of Terrestrial Solar Radiation in Awka Using Measured Meteorological Data

Journal of Energy Research and Reviews ◽

10.9734/jenrr/2019/v2i430081 ◽

2019 ◽

pp. 1-6

Author(s):

Chinelo U. Ikeh ◽

Chukwunwike C. Okeke

Keyword(s):

Relative Humidity ◽

Solar Radiation ◽

Meteorological Parameters ◽

Meteorological Data ◽

Ground Surface ◽

Weather Station ◽

Wet Season ◽

Integrated Sensor ◽

Useful Knowledge ◽

Energy Conversion Systems

This work investigated the terrestrial solar radiation over Awka, South Eastern Nigeria using meteorological parameters of terrestrial temperature and relative humidity collected during 2013- 2014 respectively, using Davis weather station vantage pros2 (with Integrated Sensor Suite, ISS) positioned close to the ground surface. The data were logged at 30 minutes interval continuously for each day during the period. Hourly, daily and monthly averages of terrestrial radiation during dry and wet seasons were calculated from the data obtained. The result indicated that the terrestrial radiation during dry season is generally higher than during the wet season. The month of March has the highest value of terrestrial solar radiation of 410 Wm-2 , while the least terrestrial radiation of about 381 Wm-2 occurred in August. The result also showed that terrestrial solar radiation correlates positively with water vapour and more positively with temperature at 0.57 and 0.81 coefficients respectively. The results obtained from this work provide useful knowledge that is necessary to enhance the deployment of solar energy conversion systems.

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Prediction of daily global solar radiation using different empirical models on the basis of meteorological parameters at Trans Himalaya Region, Nepal

BIBECHANA ◽

10.3126/bibechana.v18i1.29203 ◽

2021 ◽

Vol 18 (1) ◽

pp. 159-169

Author(s):

Usha Joshi ◽

I B Karki ◽

N P Chapagain ◽

K N Poudyal

Keyword(s):

Relative Humidity ◽

Solar Radiation ◽

Meteorological Parameters ◽

Energy Resource ◽

Global Solar Radiation ◽

Empirical Models ◽

Mean Bias Error ◽

Percentage Error ◽

Sunshine Hour ◽

Empirical Constants

Global Solar Radiation (GSR) is the cleanest and freely available energy resource on the earth. GSR was measured for six years (2010 -2015) at the horizontal surface using calibrated first-class CMP6 pyranometer at Kathmandu (Lat. 27.70o N, Long. 85.5oE and Alt. 1350m). This paper explains the daily, monthly, and seasonal variations of GSR and also compares with sunshine hour, ambient temperature, relative humidity, and precipitation to GSR. The annual average global solar radiation is about 4.16 kWh/m2/day which is a significant amount to promote solar active and passive energy technologies at the Trans-Himalaya region. In this study, the meteorological parameters are utilized in the regression technique for four different empirical models and finally, the empirical constants are found. Thus obtained coefficients are utilized to predict the GSR using meteorological parameters for the years to come. In addition, the predicted GSR is found to be closer to the measured value of GSR. The values are justified by using statistical tools such as coefficient of determination (R2), root mean square error (RMSE), mean percentage error (MPE), and mean bias error (MBE). Finally, the values of R2, RMSE, MPE, and MBE are found to be 0.792, 1.405, -1.014, and 0.011, respectively for the model (D), which are based on sunshine hour, temperature and relative humidity. In this model, the empirical constants, a = 0.155, b = 0.134, c = 0.014 and d = 0.0007 are determined which can be utilized at the similar geographical locations of Nepal. BIBECHANA 18 (2021) 159-169

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Effects of Some Meteorological Parameters on Visibility in the Niger Delta Region of Nigeria

Physical Science International Journal ◽

10.9734/psij/2019/v21i130092 ◽

2019 ◽

pp. 1-11

Author(s):

C. O. Nwokocha ◽

C. U. Okujagu ◽

P. I. Enyinna

Keyword(s):

Relative Humidity ◽

Wind Direction ◽

Niger Delta ◽

Meteorological Parameters ◽

Meteorological Data ◽

Inverse Correlation ◽

High Hydrocarbon ◽

Niger Delta Region ◽

Port Harcourt ◽

Environmental Prediction

Effects of meteorological parameters of relative humidity and wind direction on visibility in the Niger Delta, Nigeria (4.15°N-7.17°N, 5.05°E-8.68°E) for a period of 31 years (1981-2012) have been investigated. The data on visibility, relative humidity and wind direction were obtained from Nigerian Meteorological Agency (NIMET) and National Center for Environmental Prediction (NCEP) respectively. The visibility and meteorological data were analyzed to study the temporal variation of atmospheric visibility and its relationship with meteorological parameters in the region. The analysis was done using statistical techniques and the results show that cities in the Eastward (Calaber, Uyo and Port Harcourt) have more inverse correlation between Relative humidity and visibility while Westward cities (Owerri, Warri and Akure) are more directly correlated to visibility. Again it shows that visibility is more correlated with relative humidity in places of high hydrocarbon activities like Port Harcourt while it is better correlated with wind direction in places with less hydrocarbon activities like Akure.

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Investigation of Relationship between Particulate Matter (PM2.5 and PM10) and Meteorological Parameters at Roadside Area of First Penang Bridge

Journal of Tropical Resources and Sustainable Science (JTRSS) ◽

10.47253/jtrss.v5i1.652 ◽

2017 ◽

Vol 5 (1) ◽

pp. 33-39

Author(s):

Mahani Yusoff ◽

Muhammad Arieff Mat Shukri ◽

Norrimi Rosaida Awang ◽

Musfiroh Jani ◽

Zairah Ab Kadir ◽

...

Keyword(s):

Particulate Matter ◽

Relative Humidity ◽

Negative Correlation ◽

Meteorological Parameters ◽

Meteorological Data ◽

Strong Positive Correlation ◽

Positive Correlation ◽

Weak Negative Correlation ◽

Pm2.5 And Pm10 ◽

Roadside Area

The present study was focusing to characterize the particulate matter (PM2.5 and PM10) at the roadside of First Penang Bridge and the associated meteorological parameters influence such as precipitation, temperature, and relative humidity. The study was conducted by focusing on the roadside area of First Penang Bridge (N05°21.375’; E100°23.584’). A total of 12 samples thrice per month for each particulate matter size were collected starting from June 2015 to September 2015. Meteorological data were obtained from the Meteorological Department of Penang on a daily basis and 24-hours averages. Descriptive statistical analysis was conducted in characterizing the relationship between particulate matter concentrations and the target meteorological parameters. Results showed that PM2.5 and PM10 concentrations ranged between 18.06 – 79.51 ?g/m3 and 22.38 – 130.90 ?g/m3 with the overall mean concentration of 39.35 ?g/m3 for PM2.5 and 45.24 ?g/m3 for PM10. For the PM2.5, weak negative correlation was obtained between PM and precipitation (r = -0.462), strong negative correlation with relative humidity (r = -0.799) and weak positive correlation between temperature (r = 0.456). PM10 showed weak negative correlation between PM with temperature (r = -0.061) and precipitation (r = -0.022), and strong positive correlation between PM and relative humidity (r = 0.130).

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Effects of atmospheric dynamics and aerosols on the fraction of supercooled water clouds

Atmospheric Chemistry and Physics ◽

10.5194/acp-17-1847-2017 ◽

2017 ◽

Vol 17 (3) ◽

pp. 1847-1863 ◽

Cited By ~ 30

Author(s):

Jiming Li ◽

Qiaoyi Lv ◽

Min Zhang ◽

Tianhe Wang ◽

Kazuaki Kawamoto ◽

...

Keyword(s):

Relative Humidity ◽

Vertical Velocity ◽

Meteorological Parameters ◽

Temporal Correlation ◽

Supercooled Liquid ◽

Satellite Observation ◽

Static Stability ◽

Global Scale ◽

Atmospheric Dynamics ◽

Horizontal Wind

Abstract. Based on 8 years of (January 2008–December 2015) cloud phase information from the GCM-Oriented Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Cloud Product (GOCCP), aerosol products from CALIPSO and meteorological parameters from the ERA-Interim products, the present study investigates the effects of atmospheric dynamics on the supercooled liquid cloud fraction (SCF) during nighttime under different aerosol loadings at global scale to better understand the conditions of supercooled liquid water gradually transforming to ice phase. Statistical results indicate that aerosols' effect on nucleation cannot fully explain all SCF changes, especially in those regions where aerosols' effect on nucleation is not a first-order influence (e.g., due to low ice nuclei aerosol frequency). By performing the temporal and spatial correlations between SCFs and different meteorological factors, this study presents specifically the relationship between SCF and different meteorological parameters under different aerosol loadings on a global scale. We find that the SCFs almost decrease with increasing of aerosol loading, and the SCF variation is closely related to the meteorological parameters but their temporal relationship is not stable and varies with the different regions, seasons and isotherm levels. Obviously negative temporal correlations between SCFs versus vertical velocity and relative humidity indicate that the higher vertical velocity and relative humidity the smaller SCFs. However, the patterns of temporal correlation for lower-tropospheric static stability, skin temperature and horizontal wind are relatively more complex than those of vertical velocity and humidity. For example, their close correlations are predominantly located in middle and high latitudes and vary with latitude or surface type. Although these statistical correlations have not been used to establish a certain causal relationship, our results may provide a unique point of view on the phase change of mixed-phase cloud and have potential implications for further improving the parameterization of the cloud phase and determining the climate feedbacks.

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Basic Diagnosis and Prediction of Persistent Contrail Occurrence Using High-Resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part II: Evaluation of Sample Models

Journal of Applied Meteorology and Climatology ◽

10.1175/2009jamc2057.1 ◽

2009 ◽

Vol 48 (9) ◽

pp. 1790-1802 ◽

Cited By ~ 5

Author(s):

David P. Duda ◽

Patrick Minnis

Keyword(s):

Relative Humidity ◽

Wind Direction ◽

Meteorological Data ◽

Logistic Models ◽

Satellite Observations ◽

Lapse Rate ◽

Prediction System ◽

Advanced Regional Prediction System ◽

Regional Prediction ◽

Surface Models

Abstract A probabilistic forecast to accurately predict contrail formation over the conterminous United States (CONUS) is created by using meteorological data based on hourly meteorological analyses from the Advanced Regional Prediction System (ARPS) and the Rapid Update Cycle (RUC) combined with surface and satellite observations of contrails. Two groups of logistic models were created. The first group of models (SURFACE models) is based on surface-based contrail observations supplemented with satellite observations of contrail occurrence. The most common predictors selected for the SURFACE models tend to be related to temperature, relative humidity, and wind direction when the models are generated using RUC or ARPS analyses. The second group of models (OUTBREAK models) is derived from a selected subgroup of satellite-based observations of widespread persistent contrails. The most common predictors for the OUTBREAK models tend to be wind direction, atmospheric lapse rate, temperature, relative humidity, and the product of temperature and humidity.

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Statistical Analysis of Weather Effects on PM2.5

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.610-613.1033 ◽

2012 ◽

Vol 610-613 ◽

pp. 1033-1040

Author(s):

Wei Dai ◽

Jia Qi Gao ◽

Bo Wang ◽

Feng Ouyang

Keyword(s):

Statistical Analysis ◽

Wind Speed ◽

Relative Humidity ◽

Statistical Methods ◽

Predictive Analytics ◽

Hypothesis Test ◽

Meteorological Data ◽

Weather Conditions ◽

Statistical Distribution ◽

Weather Effects

Effects of weather conditions including temperature, relative humidity, wind speed, wind and direction on PM2.5 were studied using statistical methods. PM2.5 samples were collected during the summer and the winter in a suburb of Shenzhen. Then, correlations, hypothesis test and statistical distribution of PM2.5 and meteorological data were analyzed with IBM SPSS predictive analytics software. Seasonal and daily variations of PM2.5 have been found and these mainly resulted from the weather effects.

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Hydro-meteorological data preparation for ecosystem hydrological modelling in the riparian forest of Hidegvíz Valley experimental catchment

10.5194/egusphere-egu21-12285 ◽

2021 ◽

Author(s):

Csenge Nevezi ◽

Tamás Bazsó ◽

Zoltán Gribovszki ◽

Előd Szőke ◽

Péter Kalicz

Keyword(s):

Air Temperature ◽

Meteorological Parameters ◽

Extreme Event ◽

Riparian Forest ◽

Meteorological Data ◽

Rain Gauge ◽

Hydrological Modelling ◽

Data Preparation ◽

Air Humidity ◽

Groundwater Levels

In the Hidegv&#237;z Valley experimental catchment in Hungary the meteorological data have been collected since the 1990s and used for various purposes including hydrological studies. Current research began in 2018&#8211;19, that aimed to reveal the connections between the hydrological and botanical characteristics in riparian forests and a wet meadow. Changes that occurred in both ecosystems in the groundwater levels, soil moisture and vegetation, showed that the local meteorological events influence these factors. Therefore we decided to analyse longer periods in which meteorological extremes strongly influenced hydrological conditions and so status of ecosystems. Further measurements and their analysis were also required because more accuracy and detail were needed for future water balance modelling.The measured data between 2017&#8211;2020 were chosen as a starting database. For the first analysis we selected three meteorological parameters, i. e. the precipitation, the air temperature, and the air humidity. These parameters were measured by automated instruments, except for the precipitation. We found that the automated tipping-bucket rain gauge needs validation by a manual measurement (Hellmann-type rain gauge), because the data that collected by the automated device will be invalid if the rain intensity is too high.In 2017 and 2018, the annual precipitation was distributed evenly, but in the following two years we observed some extremes. In 2019 and 2020, the spring was especially dry, the lowest monthly sum was 1.2 mm in 2020 April. 2019 April was similar (19.5 mm), but after the drought period intense rainfall events arrived in May, resulted a monthly total of 214.1 mm. Air temperature and air humidity has not been showed such extremes as the precipitation.This study showed that detailed analysis of meteorological parameters is crucial for hydrological modelling data preparation because errors and extreme event can cause serious problems during modelling process and, also in case of evaluation of model results.The research has been supported by the Ministry of Agriculture in Hungary.

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