Correlations and Hierarchical Clustering investigation between weather and SARS-CoV-2.

2020 ◽  
Vol 13 ◽  
Author(s):  
Kaoutar El handri ◽  
Abdellah Idrissi
Keyword(s):  
Meteorological Data ◽  
Rank Correlation ◽  
Economic Capital ◽  
Weather Data ◽  
Maximum Temperature ◽  
Weather Factors ◽  
Primary Analysis ◽  
Mean Temperature ◽  
Kendall Rank Correlation ◽  
And Control

Background:: Humanity today faces a global emergency. It is conceivably the greatest crisis of our generation. The coronavirus pandemic, which has many global implications, has led researchers worldwide to seek solutions to this crisis, including the search for effective treatment in the first place. Objective:: This study aims to identify the factors that can have an essential effect on COVID-19 comportment. Having proper management and control of imports of COVID-19 depends on many factors that are highly dependent on a country's sanitary capacity and infrastructure technology. Nevertheless, meteorological parameters can also be a connecting factor to this disease; seines temperature and humidity are compatible with the behavior of a seasonal respiratory virus. Methods:: In this work, we analyze the correlation between weather and the COVID-19 epidemic in Casablanca, the economic capital of Morocco. It is based on the primary analysis of COVID-19 surveillance data from the Ministry of Health of the Kingdom of Morocco and weather data from the meteorological data. Weather factors include minimum temperature (°C), maximum temperature (°C), mean temperature (°C), maximum wind speed (Km/h), humidity (%), and rainfall (mm). The Spearman and Kendall rank correlation test is used for data analysis. Between the weather components. Results:: The mean temperature, maximum temperature (°C) and Humidity were significantly correlated with the COVID-19 pandemic with respectively (r= -0.432, r = -0.480; r=0.402, and p=- 0.212, p= -0.160, and p= &-0.240). Conclusion:: This discovery helps reduce the incidence rate of COVID-19 in Morocco, considering the significant correlation between weather and COVID-19, of about more than 40%.

scholarly journals VULNERABILITY OF WEATHER ON COVID-19 PANDEMIC IN WEST JAVA, INDONESIA

2020 ◽  
Vol 6 (4) ◽  
pp. 123-128
Author(s):  
Ramadhan Tosepu ◽  
Devi Savitri Effendy ◽  
La Ode Ali Imran Ahmad ◽  
Hariati Lestari ◽  
Hartati Bahar ◽  
...  
Keyword(s):  
Data Analysis ◽  
Wind Speed ◽  
Rank Correlation ◽  
Secondary Data ◽  
Weather Data ◽  
Maximum Temperature ◽  
Weather Factors ◽  
West Java ◽  
Spearman’S Rank Correlation ◽  
The Republic

Background: COVID-19 is a pandemic that spreads very fast. Until now, COVID-19 has spread in 207 countries.Objective: This study aimed to analyze the correlation between weather factors and COVID-19 in West Java, Indonesia. This study used a secondary data analysis of weather data from the Meteorological Department of the Republic of Indonesia and surveillance of COVID-19 from the Ministry of Health of the Republic of Indonesia. The weather has five components, including minimum temperature (0C), maximum temperature (0C), temperature average (0C), humidity (%), amount of rainfall (mm), and wind speed (m/s). Data were analyzed using Spearman’s rank correlation test.Result: Of the weather components, only temperature average (r = 0.545; p 0.001) and humidity (r = -0.500; p 0.001) significantly correlated with COVID-19.Conclusion: The results can be used to decrease the pandemic of COVID-19 in Indonesia.

scholarly journals INFLUENCE OF THE METEOROLOGICAL CONDITIONS ON FOREST FIRES OCCURRENCES IN LICHINGA DISTRICT, NORTHERN MOZAMBIQUE

FLORESTA ◽  
2015 ◽  
Vol 45 (3) ◽  
pp. 577 ◽  
Author(s):  
Aires Afonso Mbanze ◽  
Antonio Carlos Batista ◽  
Alexandre França Tetto ◽  
Henrique Soares Koehler ◽  
Jose Bernardo Manteiga
Keyword(s):  
Forest Fires ◽  
Meteorological Data ◽  
Great Influence ◽  
Meteorological Conditions ◽  
Meteorological Station ◽  
Weather Data ◽  
Monitoring And Control ◽  
Tukey Test ◽  
Daily Weather Data ◽  
And Control

AbstractThe aim of this study was to assess the influence of meteorological conditions on the fire occurrences in forest stands of Lichinga district, in the period from 2010 to 2012. Data about fire occurrences records of the district of Lichinga and two others close districts (Lago and Sanga) were provided by the Center for Monitoring and Control of Forest Fires (CCMIF) of the company Chikweti. Daily weather data: temperature, rainfall and relative humidity of the same period, recorded at 13:00 PM, by the meteorological station of the Institute of Agronomic Research of Mozambique (IIAM) in Lichinga district were also provided to this work. Meteorological data were submitted to regression analysis and Tukey test. The results showed a significant variation in temperature and humidity on both tests. The overlapping of fire occurrences and meteorological variables, suggested a great influence of the meteorological conditions in the occurrence of fires, mainly due to the very long dry periods. In 2010 there was a delay in the occurrence of fires; this was related to the rainy season which was slightly longer. September and October was the months that recorded the highest number of fire occurrences throughout the studied period.ResumoInfluência das condições meteorológicas na ocorrência dos incêndios florestais no distrito de Lichinga, norte de Moçambique. O objetivo deste estudo foi avaliar a influência das variáveis meteorológicas na ocorrência de incêndios em povoamentos florestais no distrito de Lichinga, no período de 2010 a 2012. Para tal, foram analisados os registros de ocorrências de incêndios do distrito de Lichinga e de outros dois distritos vizinhos (Lago e Sanga), disponibilizados pelo Centro de Controle e Monitoramento de Incêndios Florestais (CCMIF) da empresa Chikweti Forest of Niassa, e dados meteorológicos diários de temperatura (máxima e mínima), precipitação e umidade relativa, do mesmo período, registrados às 13 horas, pela estação meteorológica do Instituto de Investigação Agronômica de Moçambique em Lichinga (IIAM-Lichinga). Os dados meteorológicos foram submetidos ao teste de análise de regressão e ao teste de Tukey, tendo sido observado uma variação significativa da temperatura e umidade em ambos os testes. A sobreposição das ocorrências dos incêndios com as variáveis meteorológicas demostrou uma grande influênca dessas variáveis na ocorrência dos incêndios, principalmente devido aos períodos secos prolongados. No ano 2010 observou-se um atraso na ocorrência dos incêndios, devido ao período chuvoso que foi ligeiramente mais longo. Os meses que registraram maior número de ocorrências em todo o período foram setembro e outubro.Palavras-chave: Povoamentos florestais; variáveis meteorológicas; prevenção de incêndios florestais.

scholarly journals Ekonometryczny model krótkoterminowego prognozowania zużycia gazu

Nafta-Gaz ◽  
2021 ◽  
Vol 77 (7) ◽  
pp. 454-462
Author(s):  
Tadeusz Kwilosz ◽  
◽  
Bogdan Filar ◽  
Keyword(s):  
Information Exchange ◽  
Weather Data ◽  
Maximum Temperature ◽  
Short Term ◽  
Weather Factors ◽  
Explanatory Variables ◽  
Transmission Pipeline ◽  
Gas Consumption ◽  
Gas Market ◽  
The Right

In order to develop a mathematical model of short-term gas demand, it is necessary to analyze the latest mathematical forecasting methods in order to select and adapt the right one (meeting the condition of efficiency and effectiveness). It is necessary to recognize and analyze factors (mainly environmental) affecting the result of short-term forecasts and sources of data that can be used. The result of the work is a numerical model of short-term gas demand for a selected territorial unit of the country. The developed model was calibrated and tested on historical data describing environmental conditions and real gas consumption. A heterogeneous linear econometric model was designed and calibrated on the basis of a selected set of attributes (explanatory variables). The estimated parameters of the model were statistically verified. It is worth noting that in the short term of the forecast (7 days) there are no significant changes in the gas market environment (launching new investments, connecting new users to the system, or changes in demand resulting from changing macroeconomic conditions). Other technical factors, such as production line failures at customers or industrial downtime, are difficult to predict, or knowledge about their occurrence is rarely available. For this reason, the only factors that may have an impact on changes in gas demand in the short term are weather factors, which were selected as explanatory variables for the developed model. Historical weather data was retrieved from the OpenWeatherMapHistoryBulk web service. Daily values of gas consumption for one of the voivodships of southern Poland were used as the response variable. The data was downloaded from the information exchange system of the transmission pipeline operator. The data covers a three-year period, as only such data has been made public. The explanatory variables include the daily values of weather data such as: average temperature, chilled temperature, minimum temperature, maximum temperature, atmospheric pressure, relative humidity, wind speed and wind direction.

scholarly journals CFSR- NCEP Performance for weather data forecasting in the Pernambuco Semiarid, Brazil

DYNA ◽  
2020 ◽  
Vol 87 (215) ◽  
pp. 204-213
Author(s):  
Marcela Daniela Mollericona Alfaro ◽  
Iug Lopes ◽  
Abelardo Antônio Assunção Montenegro ◽  
Brauliro Gonçalves Leal
Keyword(s):  
Potential Evapotranspiration ◽  
Meteorological Data ◽  
Efficiency Index ◽  
Weather Data ◽  
Maximum Temperature ◽  
Climate Forecast System ◽  
Climate Forecast System Reanalysis ◽  
Semi Arid Region ◽  
D Values ◽  
Environmental Prediction

The present study aims to evaluate meteorological data -with real time actualization- from the Climate Forecast System Reanalysis (CFRS) of the National Centers for Environmental Prediction (NCEP), comparing them with data from local stations in two mesoregions: Sertão de Pernambuco (SP) and Sertão do São Francisco (SFF), semi-arid region of Pernambuco, Brazil. Statistical performance indicators were used for the period since 1979 to 2014 and the variables: precipitation (P), average, minimum and maximum temperature (Tm, Tn, Tx respectively), relative humidity (HR), wind speed (Vv), solar radiation (RS) and potential evapotranspiration (ETo). Tn, Tm and Tx showed the best results for the determination coefficient (R2), Willmott concordance index (d), Nash-Sutcliffe efficiency index (NSE) and percentage bias (PBIAS). ETo, P and HR obtained acceptable values for R2, d and NSE. CFSR data shows good performance with d values between 0.63 and 0.94.

scholarly journals Current and Future Distribution of Ricania shantungensis (Hemiptera: Ricaniidae) in Korea: Application of Spatial Analysis to Select Relevant Environmental Variables for MaxEnt and CLIMEX Modeling

Forests ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 490 ◽  
Author(s):  
Sunghoon Baek ◽  
Min-Jung Kim ◽  
Joon-Ho Lee
Keyword(s):  
Spatial Analysis ◽  
Environmental Variables ◽  
Spatial Association ◽  
Weather Data ◽  
Maximum Temperature ◽  
Economic Damage ◽  
Entropy Model ◽  
Potential Habitat ◽  
Mean Temperature ◽  
Agricultural Areas

Since the first report on its occurrence in 2010, Ricania shantungensis Chou & Lu in Korea has quickly spread. This pest population in agricultural areas has increased by over 100% each year and has caused serious economic damage in the last few years. This study was conducted to predict the potential habitat and the current and future distribution of R. shantungensis in Korea using CLIMEX and the Maximum Entropy Model (MaxEnt), and to suggest a new parameter selection method for both modeling programs. Weights of variables used in CLIMEX and those used in MaxEnt were determined using spatial association indices of spatial analysis by distance indices (SADIE). Weather data of Zhejiang province in China and those of all Korean territories were compared with Climate Matching in CLIMEX. MaxEnt was applied and evaluated with 295 data points on the presence and absence of R. shantungensis and eight environmental variables that were preselected by spatial and correlation tests. In MaxEnt, maximum temperature of the warmest month, annual mean temperature, mean temperature of the coldest month, and precipitation of the driest month were determined to be the most important variables affecting the distribution of R. shantungensis in Korea. The results of this study indicated that R. shantungensis had a higher probability of occurrence in western areas than in eastern areas of Korea, and showed great potential to spread eastward. These results are expected to be helpful for managing R. shantungensis in Korea and selecting relevant environmental variables for species distribution modeling.

scholarly journals Weather and Aggressive Behavior among Patients in Psychiatric Hospitals—An Exploratory Study

2020 ◽  
Vol 17 (23) ◽  
pp. 9121
Author(s):  
Jakub Lickiewicz ◽  
Katarzyna Piotrowicz ◽  
Patricia Paulsen Hughes ◽  
Marta Makara-Studzińska
Keyword(s):  
Aggressive Behavior ◽  
Meteorological Data ◽  
Rank Correlation ◽  
Psychiatric Hospitals ◽  
Weather Conditions ◽  
Mental Illnesses ◽  
Weather Factors ◽  
Coercive Measures ◽  
The Impact ◽  
The Relationship

Background: The number of meteoropaths, or people negatively affected by weather conditions, is rising dramatically. Meteoropathy is developing rapidly due to ever poorer adaptations of people to changes in weather conditions. Strong weather stimuli may not only exacerbate symptoms in people with diseases of the cardiovascular and respiratory systems but may also induce aggressive behavior. Researchers have shown that patients suffering from mental illnesses are most vulnerable to changes in the weather and postulate a connection between the seasons and aggressive behavior. Methods: The goal of the study was to analyze the relationship between coercive measures and weather factors. The researchers identified what meteorological conditions prevailed on days with an increased number of incidents of aggressive behavior leading to the use of physical coercion towards patients in a psychiatric hospital in Poland. In order to determine the impact of weather conditions on the frequency at which physical coercion measures were used, the hospital’s “coercion sheets” from 1 January 2015 to 31 March 2017 were analyzed. The data were correlated with meteorological data. In order to determine the relationship between the occurrence of specific weather conditions and the number of coercive interventions (N), researchers utilized Spearman’s rank correlation analysis together with two-dimensional scatter diagrams (dependency models), multiple regression, stepwise regression, frequencies, and conditional probability (%). Results: Lower barometric pressure and foehn wind increased aggressive behavior in patients that led to coercive measures. For temperature (positive correlation) and humidity (negative correlation), there was a poor but statistically significant correlation. Conclusions: Monitoring weather conditions might be useful in predicting and preventing aggression by patients who are susceptible to weather changes

Exploring Weather Data to Predict Activity Attendance in Event-based Social Network

2021 ◽  
Vol 15 (2) ◽  
pp. 1-25
Author(s):  
Jifeng Zhang ◽  
Wenjun Jiang ◽  
Jinrui Zhang ◽  
Jie Wu ◽  
Guojun Wang
Keyword(s):  
Real Life ◽  
Prediction Performance ◽  
Weather Data ◽  
Gradient Boosting ◽  
User Interest ◽  
Weather Factors ◽  
Event Duration ◽  
Outdoor Activities ◽  
Weather Factor ◽  
Event Based

Event-based social networks (EBSNs) connect online and offline lives. They allow online users with similar interests to get together in real life. Attendance prediction for activities in EBSNs has attracted a lot of attention and several factors have been studied. However, the prediction accuracy is not very good for some special activities, such as outdoor activities. Moreover, a very important factor, the weather, has not been well exploited. In this work, we strive to understand how the weather factor impacts activity attendance, and we explore it to improve attendance prediction from the organizer’s view. First, we classify activities into two categories: the outdoor and the indoor activities. We study the different ways that weather factors may impact these two kinds of activities. We also introduce a new factor of event duration. By integrating the above factors with user interest and user-event distance, we build a model of attendance prediction with the weather named GBT-W , based on the Gradient Boosting Tree. Furthermore, we develop a platform to help event organizers estimate the possible number of activity attendance with different settings (e.g., different weather, location) to effectively plan their events. We conduct extensive experiments, and the results show that our method has a better prediction performance on both the outdoor and the indoor activities, which validates the reasonability of considering weather and duration.

scholarly journals Utilising Open Geospatial Data to Refine Weather Variables for Building Energy Performance Evaluation—Incident Solar Radiation and Wind-Driven Infiltration Modelling

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 802
Author(s):  
Kristian Skeie ◽  
Arild Gustavsen
Keyword(s):  
Solar Radiation ◽  
Web Service ◽  
Meteorological Data ◽  
Surface Wind ◽  
Building Energy ◽  
Energy Performance ◽  
Geospatial Data ◽  
Weather Data ◽  
Building Site ◽  
Incident Solar Radiation

In building thermal energy characterisation, the relevance of proper modelling of the effects caused by solar radiation, temperature and wind is seen as a critical factor. Open geospatial datasets are growing in diversity, easing access to meteorological data and other relevant information that can be used for building energy modelling. However, the application of geospatial techniques combining multiple open datasets is not yet common in the often scripted workflows of data-driven building thermal performance characterisation. We present a method for processing time-series from climate reanalysis and satellite-derived solar irradiance services, by implementing land-use, and elevation raster maps served in an elevation profile web-service. The article describes a methodology to: (1) adapt gridded weather data to four case-building sites in Europe; (2) calculate the incident solar radiation on the building facades; (3) estimate wind and temperature-dependent infiltration using a single-zone infiltration model and (4) including separating and evaluating the sheltering effect of buildings and trees in the vicinity, based on building footprints. Calculations of solar radiation, surface wind and air infiltration potential are done using validated models published in the scientific literature. We found that using scripting tools to automate geoprocessing tasks is widespread, and implementing such techniques in conjunction with an elevation profile web service made it possible to utilise information from open geospatial data surrounding a building site effectively. We expect that the modelling approach could be further improved, including diffuse-shading methods and evaluating other wind shelter methods for urban settings.

scholarly journals Leadership and Motivation as Important Aspects of the International Company’s Corporate Culture

2021 ◽  
Vol 13 (7) ◽  
pp. 3916
Author(s):  
Ingrida Košičiarová ◽  
Zdenka Kádeková ◽  
Peter Štarchoň
Keyword(s):  
Corporate Culture ◽  
Rank Correlation ◽  
Chi Square ◽  
Exact Test ◽  
Main Research ◽  
Leadership Motivation ◽  
Kendall Rank Correlation ◽  
Friedman's Test ◽  
Chi Square Test

Although the issue of corporate culture has been taken over and addressed in the literature from various perspectives, there are very few researchers about the role of leadership and motivation in it, respectively very few researchers have addressed them as important components of the international company’s corporate culture. The present paper aims to point out that leadership and motivation can be perceived as important aspects of the international company’s corporate culture. The object of the investigation was an international company (situated in Italy) and its five subsidiaries (situated in Italy, Czech Republic, Germany, and Turkey). As the main research method, there was chosen the method of the questionnaire survey, which was attempted by all the company’s employees (totally 270 respondents). The questionnaire was divided into three separate, but logically related parts—leadership, motivation, and corporate culture, and submitted to two groups of respondents—the company’s management and its employees. In total 11 hypotheses were formulated and further evaluated by the methods of Pearson Chi-square Test, Fisher’s Exact Test, Cramer’s V coefficient, Kendall rank correlation coefficient, Eta coefficient, Spearman coefficient, Mann–Whitney U test and Wilcoxon W statistics, Kruskal–Wallis test, and Friedman’s test. The results of the research have proven that leadership and motivation are important parts of the corporate culture.

THE TEMPERATURES OF SURFACE FIRES IN JACK PINE BARREN: I. THE VARIATION IN TEMPERATURE WITH TIME

1966 ◽  
Vol 44 (10) ◽  
pp. 1285-1292 ◽  
Author(s):  
David W. Smith ◽  
John H. Sparling
Keyword(s):  
Jack Pine ◽  
Maximum Temperature ◽  
Surface Fires ◽  
Mean Temperature ◽  
The Mean ◽  
Maximum Temperatures

The temperatures of 18 fires in an open jack pine barren near Timmins, Ontario, have been recorded. The maximum temperature recorded was 545 °C, although in other determinations fire temperatures in excess of 1000 °C were reached. The mean temperature of all fires was 340.6 ± 133.2 °C. Three fires at 230, 345, and 545 °C were considered in detail.The maximum temperature of a fire was normally recorded at heights of 5 cm or 10 cm above the surface. Maximum temperatures of hotter fires usually occurred at greater heights than cooler ones. Duration and the temperature ("intensity") of the fire are important aspects of fire studies.

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