scholarly journals Impact of meteorological conditions on the incidence of acute aortic dissection

2018 ◽  
Vol 12 (12) ◽  
pp. 321-326 ◽  
Author(s):  
Payman Majd ◽  
Navid Madershahian ◽  
Anton Sabashnikov ◽  
Carolyn Weber ◽  
Wael Ahmad ◽  
...  
Keyword(s):  
Aortic Dissection ◽  
Air Temperature ◽  
Atmospheric Pressure ◽  
Predictive Power ◽  
Acute Aortic Dissection ◽  
Full Moon ◽  
Meteorological Data ◽  
Lunar Cycle ◽  
Meteorological Conditions ◽  
Different Types

Background: There is still much controversy about whether meteorological conditions influence the occurrence of acute aortic dissection (AAD). The aim of the present study was to investigate the possible correlation between atmospheric pressure, temperature, lunar cycle and the event of aortic dissection in our patient population. Methods: The clinical data for 348 patients with AAD (73% type Stanford A) were confronted with the meteorological data provided by the Cologne weather station over the same period. Results: There were no statistically significant differences between meteorological parameters on days of AAD events compared with control days. A logistic regression model showed that air pressure (odds ratio [OR] 1.004, 95% confidence interval [CI] 0.991–1.017, p = 0.542), air temperature (OR 0.978, 95% CI 0.949–1.008, p = 0.145), season ( p = 0.918) and month of the event ( p = 0.175) as well as presence of full moon (OR 1.579, 95% CI 0.763–3.270, p = 0.219) were not able to predict AAD events. Also, no predictive power of meteorological data and season was found on analysing their impact on different types of AAD events. Conclusions: Our study did not reveal any dependence of atmospheric pressure, air temperature or the presence of full moon on the incidence of different types of AAD.

scholarly journals Influence of meteorological conditions on noise dispersion in the Port of Thessaloniki

Noise Mapping ◽  
2020 ◽  
Vol 7 (1) ◽  
pp. 135-145 ◽  
Author(s):  
Stjepan Piličić ◽  
Igor Kegalj ◽  
Eirini Tserga ◽  
Teodora Milošević ◽  
Roberto Žigulić ◽  
...  
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Atmospheric Pressure ◽  
Meteorological Parameters ◽  
Meteorological Data ◽  
Environmental Noise ◽  
Meteorological Conditions ◽  
Major Influence ◽  
Noise Power ◽  
Noise Levels

AbstractAlthough noise dispersion models are widely used for the assessment of noise levels across different domains, the influence of meteorological conditions on environmental noise is usually neglected even though modelling requirements often list meteorological data as a key part for conducting successful modelling exercises. In order to evaluate the magnitude of influence of meteorological conditions on noise dispersion, different meteorological scenarios have been tested. The meteorological parameters that have been addressed include wind speed and direction, air temperature and atmospheric pressure. The simulations have been performed using data obtained from the Port of Thessaloniki, which include standard noise data (locations of noise sources and barriers, noise power levels of individual sources), as well as yearly averages and extremes for the meteorological parameters. Wind speed and direction have been shown to have a major influence on environmental noise levels. The modelled difference in levels due to changes in wind speed and direction reached 7 dB in several receivers indicating an effect that should not be neglected. Air temperature and atmospheric pressure had very little influence on noise levels. In conclusion, when addressing and modelling environmental noise levels, wind speed and direction must be properly accounted for and should not be neglected.

scholarly journals Modern meteorological observations for aviation purposes

2018 ◽  
Keyword(s):  
Air Temperature ◽  
Wind Direction ◽  
Atmospheric Pressure ◽  
Atmospheric Precipitation ◽  
Weather Conditions ◽  
Temporal Analysis ◽  
Aerodynamic Characteristics ◽  
Meteorological Conditions ◽  
International Standards ◽  
Favorable Weather

The purpose of this article. Meteorological support for aviation is a component of the safety systems. With the development of aviation technology, the requirements for it are growing. Today, aviation remains the most demanding user of meteorological information. The main parameters that affect the aircraft’s aerodynamic characteristics include air temperature, wind direction, atmospheric pressure, the height of the lower cloud boundary, the amount of precipitation and the frequency of dangerous meteorological phenomena. The aim of the study is a spatio-temporal analysis of meteorological parameters at the air base Chuguiv, Kharkiv region. Main material. Time series of daily average, average monthly air temperature, relative humidity, cloudiness, atmospheric pressure, atmospheric precipitation, wind direction and frequency of dangerous meteorological phenomena for the period 2008-2017 were processed as initial data. Changes in meteorological values during the year, season and month were studied. Favorable weather conditions for flights have been determined. Recommendations are developed regarding the performance of flights under various weather conditions. To date, many different aircraft flight models have been developed in non-standard weather situations. In T.V.Safonova’s work the forecast of the indicators of airports functioning and flights on routes in difficult meteorological conditions is considered. Consequently, aviation must have timely meteorological information increasing the safety, regularity and economy of flights for effective implementation of practical tasks. Conclusions. Analysis of the literature has showed that complex meteorological conditions create critical situations on routes and require further detailed study. To maintain a high level of meteorological service for aviation that meets international standards, it is necessary to conduct scientific and applied research in the field of aviation climatology and improve existing methods of aviation forecasting.

scholarly journals The Effects of Changing Meteorological Parameters on Fatal Aortic Catastrophes

2019 ◽  
Author(s):  
Brigitta Szilágyi ◽  
Márton Berczeli ◽  
Attila Lovas ◽  
Zoltán Oláh ◽  
Klára Törő ◽  
...  
Keyword(s):  
Aortic Aneurysm ◽  
Aortic Dissection ◽  
Atmospheric Pressure ◽  
Process Model ◽  
Meteorological Parameters ◽  
Acute Aortic Dissection ◽  
Occurrence Rate ◽  
Cox Process ◽  
The Relationship ◽  
Non Parametric

Abstract Introduction: Over the spam of the last decade, medical research has been increasingly putting greater emphasis on the study of meteorological parameters due to their connection to cardiovascular diseases. The main goal of this study was to explore the relationship between fatal aortic catastrophes and changes in atmospheric pressure and temperature. Methods: We used a Cox process model to quantify the effects of environmental factors on sudden deaths resulting from aortic catastrophes. We used transfer entropy to draw conclusion about the causal connection between mortality and meteorological parameters. Our main tool is a computer program which we developed earlier in order to evaluate the relationship between pulmonary embolism mortality and the weather on data sets comprised of aortic aneurysm (AA) and acute aortic dissection (AAD) cases, where one of these two medical conditions had led to the fatal rupture of the aorta. Our source for these cases were the autopsy databases of Semmelweis University, from the time period of 1994 to 2014. We have examined 160 aneurysm and 130 dissection cases in relation to changes in meteorological parameters. The algorithm implemented in our program is based on a non-parametric a Cox process model. It is capable to split slowly varying unknown global trends from fluctuations potentially caused by weather. Furthermore, it allows us to explore complex non-linear interactions between meteorological parameters and mortality. Results: The model measures the relative growth of the expected number of events on the nth day caused by the deviation of environmental parameters from its mean value. The connection between ruptured aortic aneurysms (rAA) and changes in atmospheric pressure is more significant than their connection with mean daily temperatures. With the increase in atmospheric pressure, the rate of rAA mortality also increased. The effects of meteorological parameters were weaker for deaths resulting from acute aortic dissections (AAD), although low mean daily temperatures increased the intensity of occurrence for AAD-related deaths. Conclusion: The occurrence rate of fatal aortic catastrophes showed a slight dependence on the two examined parameters within our groups. Keywords: acute aortic dissection; ruptured aortic aneurysm; Cox process model; non-parametric approach; statistical learning

scholarly journals COMPARAÇÃO ENTRE DADOS METEOROLÓGICOS OBTIDOS POR ESTAÇÕES CONVENCIONAIS E AUTOMÁTICAS NO ESTADO DO PIAUÍ, BRASIL*

Irriga ◽  
2017 ◽  
Vol 22 (2) ◽  
pp. 220-235
Author(s):  
Aureliano De Albuquerque Ribeiro ◽  
Aderson Soares De Andrade Júnior ◽  
Everaldo Moreira Da Silva ◽  
Marcelo Simeão ◽  
Edson Alves Bastos
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Air Temperature ◽  
Atmospheric Pressure ◽  
Meteorological Data ◽  
Pearson Correlation ◽  
Absolute Error ◽  
Average Relative Humidity ◽  
Operational Issues ◽  
Meteorological Elements

COMPARAÇÃO ENTRE DADOS METEOROLÓGICOS OBTIDOS POR ESTAÇÕES CONVENCIONAIS E AUTOMÁTICAS NO ESTADO DO PIAUÍ, BRASIL*  AURELIANO DE ALBUQUERQUE RIBEIRO1; ADERSON SOARES DE ANDRADE JÚNIOR2; EVERALDO MOREIRA DA SILVA3; MARCELO SIMEÃO4 E EDSON ALVES BASTOS2 1Doutorando em Engenharia Agrícola, Universidade Federal do Ceará, Av. Mister Hull, s/n - Pici, bloco 804, 60455-760, Fortaleza - CE, [email protected] Embrapa Meio-Norte, Teresina, PI, [email protected], [email protected] Professor Adjunto II da Universidade Federal do Piauí, Campus Professora Cinobelina Elvas, Bom Jesus, PI, [email protected] Mestre em Agronomia: Solos e Nutrição de Plantas, Universidade Federal do Piauí, Campus Professora Cinobelina Elvas, Bom Jesus, PI, [email protected]*Extraído da dissertação de mestrado do primeiro autor  1 RESUMOO registro de elementos climáticos é efetuado por estações meteorológicas convencionais e automáticas. Porém, por questões operacionais e de custo, as estações automáticas estão substituindo as convencionais. Contudo, para que as séries de dados dessas estações sejam únicas, há a necessidade de estudos comparativos entre as duas estações. O estudo teve como objetivo comparar dados meteorológicos obtidos por estações convencionais (EMC) e automáticas (EMA) em municípios do Estado do Piauí (Paulistana, Picos, São João do Piauí, Floriano, Parnaíba e Piripiri). Os elementos meteorológicos avaliados foram: temperaturas do ar máxima (°C) mínima (ºC) e média (ºC), umidade relativa média do ar (%), velocidade do vento a 10 m (m s-1), precipitação pluviométrica (mm) e pressão atmosférica média (hPa). As comparações dos dados foram feitas por meio dos seguintes indicadores estatísticos: precisão (R2), erro absoluto médio (EAM), coeficiente de correlação (r), índice de concordância de Willmott (d) e índice de confiança (c). Os melhores ajustes dos dados foram constatados para a precipitação e pressão atmosférica; intermediários, para a temperatura do ar, umidade relativa do ar média e os piores, para a velocidade do vento. A umidade relativa média do ar foi o elemento analisado que mostrou as maiores diferenças entre a EMC e a EMA. Palavras-chave: Agrometeorologia, elementos climáticos, sensores. RIBEIRO, A. A.; ANDRADE JÚNIOR, A. S.; SILVA, E.M.; SIMEÃO, M.; BASTOS, E.A.COMPARISON OF METEOROLOGICAL DATA RECORDED BY CONVENTIONAL AND AUTOMATIC STATIONS IN PIAUÍ STATE, BRAZIL   2 ABSTRACTClimatic elements are recorded by both conventional and automatic weather stations. However, due to cost and operational issues, automatic stations are replacing the conventional. So that  data sets from these stations are unique, there is a need for comparative studies between the two types of stations. The aim of this study was to compare meteorological data obtained by conventional and automatic stations in towns of the State of Piauí, Brazil (Paulistana, Picos, São João do Piauí, Floriano and Piripiri).The meteorological elements evaluated were: maximum (°C) minimum (°C) and average (°C) air temperature, average relative humidity (%), wind speed at 10 m (m s-1), rainfall (mm) and average atmospheric pressure (hPa). Data comparison was by the following statistical indicators: precision (R2), mean absolute error (EAM), Pearson correlation coefficient (r), Willmott’s index of agreement (d) and confidence index (c).  The best data adjustments were observed for rainfall and atmospheric pressure; intermediates for the air temperature, average relative humidity and worst for the wind speed.  The air average relative humidity was the analyzed element that showed the greatest differences between EMC and EMA. Keywords: Agrometeorology, meteorological elements, sensors 

scholarly journals INFLUENCE OF METEOROLOGICAL CONDITIONS ON VOLATILE ORGANIC COMPOUND SPREAD IN THE ATMOSPHERIC BOUNDARY LAYER

2007 ◽  
Vol 15 (3) ◽  
pp. 135-143 ◽  
Author(s):  
Tatjana Laškova ◽  
Vytenis Zabukas ◽  
Petras Vaitiekūnas
Keyword(s):  
Wind Speed ◽  
Organic Compound ◽  
Air Temperature ◽  
Volatile Organic Compound ◽  
Atmospheric Pressure ◽  
Complex Analysis ◽  
Ambient Air ◽  
Meteorological Conditions ◽  
Environmental Humidity ◽  
Volatile Organic

The problem of volatile organic compound (VOC) emission from oil terminals is discussed in the paper. Short‐term analyses were performed to determine dependence of VOC on wind speed, environmental humidity and atmospheric pressure at minimal ambient air temperature variations (1–3 °C). 10‐day VOC concentration analyses were performed using gas chro‐matography. Complex analysis of experimental investigation and meteorological conditions (air temperature, environmental humidity, atmospheric pressure, wind speed and direction) was carried out considering the types of loading operations and oil products at the oil terminal. Dependencies between VOC concentration and separate meteorological parameters were determined.

Searching for weather in varves: use of ultra-high-resolution scanning techniques to reconstruct seasonal meteorological conditions

2021 ◽  
Author(s):  
Paul Zander ◽  
Maurycy Żarczyński ◽  
Wojciech Tylmann ◽  
Shauna-kay Rainford ◽  
Martin Grosjean
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Lake Sediments ◽  
Predictive Power ◽  
Accumulation Rate ◽  
Meteorological Data ◽  
Meteorological Conditions ◽  
Additive Models ◽  
Geochemical Data ◽  
Formation Processes

<p>Varved lake sediments are recognized as valuable archives of paleoclimatic information due to their precise chronological control. However, paleoclimate reconstructions based on the composition of biochemical varves are relatively rare (Zolitschka et al., 2015). We applied novel high-resolution scanning techniques to the varved sediments of Lake Żabińskie, Poland to obtain spatially resolved geochemical data at a resolution of 60 μm covering the period 1966-2019. Relative abundances of elements were measured in resin-embedded sediment slabs using a Bruker M4 Tornado micro-XRF scanner. Chloropigments-<em>a</em> and bacteriopheopigments-<em>a</em> were measured on a wet sediment core using a Specim Hyperspectral core scanner (Butz et al., 2015). The high resolution of the scanning data, and the relatively thick well-preserved varves (average thickness = 6.4 mm), enables a close examination of seasonal scale sediment composition and varve formation processes. Time series of geochemical variables within each varve year were classified into 4 varve type groups based on the dissimilarity measure ψ for multivariate time series (Benito and Birks, 2020; Gordon and Birks, 1974). Based on a Multivariate Analysis Of Variance test, these groups of years experienced significant (p<0.05) differences in seasonal meteorological conditions, particularly wind speed and temperature.  Additionally, a correlation analysis on mean annual geochemical values from the aforementioned scanning techniques and conventional CNS analysis, and seasonal meteorological data revealed significant (p<0.05) correlations with windiness and temperature. Based on these relationships, we applied generalized additive models to predict spring and summer (MAMJJA) temperature and number of windy days (spring through fall), yielding models with significant predictive power. Based on model selection, the variables with the most predictive power for spring and summer temperature were Ti (negative correlation) and total C. The variables with the most predictive power for windiness were Si, sediment accumulation rate, and varve type. This study highlights the usefulness of high-resolution scanning techniques to improve our understanding of varve formation processes and relationships between varve composition and climate variables in biochemical varves.</p><p> </p><p><strong>References</strong></p><p>Benito, B. M. and Birks, H. J. B.: distantia: an open‐source toolset to quantify dissimilarity between multivariate ecological time‐series, Ecography (Cop.)., 43(5), 660–667, doi:10.1111/ecog.04895, 2020.</p><p>Butz, C., Grosjean, M., Fischer, D., Wunderle, S., Tylmann, W. and Rein, B.: Hyperspectral imaging spectroscopy: a promising method for the biogeochemical analysis of lake sediments, J. Appl. Remote Sens., 9(1), 096031, doi:10.1117/1.jrs.9.096031, 2015.</p><p>Gordon, A. D. and Birks, H. J. B.: Numerical methods in Quaternary palaeoecology: II. Comparison of pollen diagrams, New Phytol., 73(1), 221–249, doi:10.1111/j.1469-8137.1974.tb04621.x, 1974.</p><p>Zolitschka, B., Francus, P., Ojala, A. E. K. and Schimmelmann, A.: Varves in lake sediments - a review, Quat. Sci. Rev., 117, 1–41, doi:10.1016/j.quascirev.2015.03.019, 2015.</p>

scholarly journals Association of Daily Mean Temperature and Temperature Variability With Onset Risks of Acute Aortic Dissection

2021 ◽  
Author(s):  
Xinyu Yu ◽  
Liangtao Xia ◽  
Jiewen Xiao ◽  
Jin Zheng ◽  
Nina Xu ◽  
...  
Keyword(s):  
Relative Risk ◽  
Aortic Dissection ◽  
Acute Aortic Dissection ◽  
Meteorological Data ◽  
Temperature Variability ◽  
Cold Temperatures ◽  
Exposure Response ◽  
Mean Temperature ◽  
Lag Effect ◽  
The Impact

Background The association between ambient temperature and cardiovascular diseases has been well established, but evidence of temporal changes in the risk of acute aortic dissection (AAD) onset is lacking. Methods and Results We conducted an 8‐year time‐series study based on data from 2120 patients diagnosed with AAD at Tongji Hospital (Wuhan, China). Daily meteorological parameters were measured in the study area. Spearman's rank correlation analysis was applied to measure the associations between daily meteorological data and air pollution indicators. A distributed lag nonlinear model following quasi‐Poisson regression was used to express the nonlinear exposure‐response relationships and lag effects of daily mean temperature and temperature variability on the occurrence of AAD. Considering a 25‐day lag effect, lower or higher temperatures with reference to 25°C did not alter the onset risk of AAD. The lag effect of daily mean temperature on the incidence of AAD is statistically significant within 2 days, and the impact of daily mean temperature on the risk is most influential on the day. The exposure‐response curve between daily mean temperature and onset risks of AAD at lag 0 showed that the extremely cold temperature (2.5th percentile, 0.5°C) significantly increased the AAD risk for the total (relative risk, 1.733; 95% CI, 1.130–2.658) and type A dissection (relative risk, 3.951; 95% CI, 1.657–9.418). Temperature variability within 1 week did not affect the onset risks of AAD for the total. Conclusions We confirmed that extremely cold temperatures significantly increased the AAD risk, which could contribute to early prevention and timely diagnosis of the disease.

scholarly journals The seasonal nature of tourist flows in relation to meteorological conditions as illustrated by the case of Zachodniopomorskie Voivodeship

2016 ◽  
Vol 34 (34) ◽  
pp. 33-45
Author(s):  
Czesław Koźmiński ◽  
Bożena Michalska
Keyword(s):  
Statistical Analysis ◽  
Wind Speed ◽  
Air Temperature ◽  
Time Trends ◽  
Polynomial Regression ◽  
Meteorological Data ◽  
Meteorological Conditions ◽  
Monthly Basis ◽  
Tourist Flows ◽  
Overnight Stays

Abstract The analysis is based on the materials published by the Statistical Office in Szczecin for 2000-14, presented on a monthly basis, concerning the total number of tourists (including foreign tourists) and the overnight stays. The distribution of the number of tourists and their accommodation per month and season was correlated with mean monthly values for air temperature, cloudiness and wind speed. Meteorological data for the period 2000-14, as averaged for the whole voivodeship, was obtained from four IMGW stations (Świnoujście, Koszalin, Szczecin and Szczecinek). Statistical analysis was conducted and time trends of the number of tourists and overnight stays were identified for individual months with the use of linear and polynomial regression. The seasonal nature of tourist flows was assessed by the number of tourists and accommodation provided for tourists in summer compared to winter, and spring to autumn. Air temperature and cloudiness were found to have the greatest effect on the uneven distribution of tourist numbers across a year. Each year, approximately 1.7 million tourists visit Zachodniopomorskie Voivodeship, 1.1 million of which (i.e. 66%) stay on the coast.

scholarly journals Avalanches Forecasting Using Machine Learning Methods

2021 ◽  
Vol 19 (2) ◽  
pp. 92-101
Author(s):  
N. A. Radeev
Keyword(s):  
Machine Learning ◽  
Snow Cover ◽  
Predictive Power ◽  
Meteorological Data ◽  
Meteorological Conditions ◽  
Snow Avalanches ◽  
Mountainous Areas ◽  
Learning Methods ◽  
Machine Learning Methods ◽  
Machine Learning Models

The occurrence of snow avalanches is mainly influenced by meteorological conditions and the configuration of snow cover layers. Machine learning methods have predictive power and are capable of predicting new events. From the trained machine learning models, an ensemble is obtained that predicts the possibility of avalanches. The model obtained in the article uses avalanche data, meteorological data and generated data on the state of snow cover for training. This allows the resulting solution to be used in more mountainous areas than solutions using a wider range of less available data.Snow data is generated by the SNOWPACK software package.

P32 Do meteorological factors influence the occurrence of acute aortic dissection?A ten-year retrospective institutional review

2020 ◽  
Vol 41 (Supplement_1) ◽  
Author(s):  
R Usui ◽  
T Yoshizumi ◽  
H Oshima ◽  
A Usui
Keyword(s):  
Logistic Regression ◽  
Aortic Dissection ◽  
Temperature Difference ◽  
Atmospheric Pressure ◽  
Minimum Temperature ◽  
Acute Aortic Dissection ◽  
Meteorological Factors ◽  
Maximum Temperature ◽  
Maximum Temperature Difference ◽  
Cutoff Values

Abstract Purpose Some studies have reported a relationship between meteorological factors and the occurrence of acute aortic dissection (AAD). Nevertheless, the results of the studies are heterogeneous. Furthermore, whether the absolute values or fluctuation of meteorological factors influence the occurrence of AAD remains controversial. The aim of this study was to determine the meteorological factors associated with the occurrence of AAD. Methods Two hundred eighty-two consecutive patients (male, n = 178; female, n = 104; average age, 68 years) admitted to our hospital for AAD in the 10 years from September 1st 2008 were included in this study. One hundred fifty-seven patients had type A dissection. The correlation between the clinical data and the local meteorological data over the same period (provided by the National Meteorological Agency) was analyzed. We compared the following factors on days of AAD occurrence and non-occurrence: minimum and maximum temperature, minimum and maximum temperature difference between day of occurrence and previous day, difference between maximum and minimum temperature, atmospheric pressure and atmospheric pressure difference between day of occurrence and previous day (Δatmospheric pressure), and minimum and maximum temperature difference from climatological standard normal (CSN). Cutoff values were determined by ROC curve analyses and odds ratios (ORs) were calculated by a logistic regression analysis of meteorological factors with statistically significant differences. Results ignificant differences between the days of AAD occurrence and non-occurrence were observed for minimum and maximum temperature (p < 0.0001), atmospheric pressure (p < 0.0001) and Δatmospheric pressure (p = 0.0286), minimum temperature difference from CSN (p < 0.0001), and maximum temperature difference from CSN (p = 0.0010). The cutoff values were as follows: minimum temperature, 4°C; maximum temperature, 15.1°C; atmospheric pressure, 1008.9hPa; Δatmospheric pressure, 0.4hPa; minimum temperature difference from CSN, 1°C; and maximum temperature difference from CSN, -0.2°C. The univariate logistic regression model showed revealed the following significant predictors of the occurrence of AAD; minimum temperature (OR2.42, p < 0.0001), maximum temperature (OR2.23, p < 0.0001), air pressure (OR1.75, p < 0.0001), Δatmospheric pressure (OR 1.44, p = 0.0030), minimum temperature difference from CSN (OR1.80, p < 0.0001) and maximum temperature difference from CSN (OR1.58, p = 0.0003). However, only minimum temperature (OR1.60, 95% CI 1.00-2.53, p = 0.0478) and maximum temperature difference from CSN (OR1.45, 95% CI 1.11-1.89, p = 0.0062) remained significant in the multivariate analysis. Conclusion Meteorological factors, especially a minimum temperature under 4°C strongly influenced the occurrence of AAD. A maximum temperature difference from CSN of over -0.2°C was also a significant predictor of AAD.

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