The influence of weather on fatal accidents in Austrian mountains

Abstract Projections of warmer global temperatures in fast approaching time horizons warrant planning strategies for reducing impacts on human morbidity and mortality. This study sought to determine whether increases in temperature and other changes in weather indices impacted rates of fatal accidents occurring in the popular mountainous regions of Austria with the purpose of improving mountain prevention and accident mitigation strategies. The study was based on the merging of 3285 fatal outdoor accidents reported by the Austrian Alpine Safety Board for the period 2006 to 2018 with daily meteorological data from 43 nearby climate stations during the same period. Multivariable logistic regression was used to model the odds of one or more fatal accidents per station and day with weather indices as predictors, controlling for weekend effects bringing more visitors to the mountains. Separate prediction models were performed for summer and winter activities, as well as for specific disciplines. Even after adjustment for concomitant effects impacting mountain fatal accidents, the daily weather indices of temperature, relative humidity, global radiation, cloudiness, snow cover and precipitation were statistically significantly associated with fatal accident risk. In particular, a one-degree Celsius increase in temperature was associated with a 13% increase in odds of a mountain biking accident in the summer and a 8% increase in odds of a mountain suicide in the winter. An increase in global radiation by 1 kWh/m2 was associated with a 11% and 28% increase in fatal accident odds for mountaineering in the summer and touring in the winter, respectively.

Author(s):  
Cristina Maria Pacurar ◽  
Victor Dan Păcurar ◽  
Marius Paun

The present paper proposes a fractal analysis of the Covid-19 dynamics in 45 European countries. We introduce a new idea of using the box-counting dimension of the epidemiologic curves as a means of classifying the Covid-19 pandemic in the countries taken into consideration. The classification can be a useful tool in deciding upon the quality and accuracy of the data available. We also investigated the reproduction rate, which proves to have significant fractal features, thus enabling another perspective on this epidemic characteristic. Moreover, we studied the correlation between two meteorological parameters: global radiation and daily mean temperature and two Covid-19 indicators: daily new cases and reproduction rate. The fractal dimension differences between the analysed time series graphs could represent a preliminary analysis criterion, increasing research efficiency. Daily global radiation was found to be stronger linked with Covid-19 new cases than air temperature (with a greater correlation coefficient -0.386, as compared with -0.318), and consequently it is recommended as the first-choice meteorological variable for prediction models.


2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Changhyun Choi ◽  
Jeonghwan Kim ◽  
Jongsung Kim ◽  
Donghyun Kim ◽  
Younghye Bae ◽  
...  

Prediction models of heavy rain damage using machine learning based on big data were developed for the Seoul Capital Area in the Republic of Korea. We used data on the occurrence of heavy rain damage from 1994 to 2015 as dependent variables and weather big data as explanatory variables. The model was developed by applying machine learning techniques such as decision trees, bagging, random forests, and boosting. As a result of evaluating the prediction performance of each model, the AUC value of the boosting model using meteorological data from the past 1 to 4 days was the highest at 95.87% and was selected as the final model. By using the prediction model developed in this study to predict the occurrence of heavy rain damage for each administrative region, we can greatly reduce the damage through proactive disaster management.


2017 ◽  
Vol 38 (4Supl1) ◽  
pp. 2363
Author(s):  
Rodrigo Dlugosz da Silva ◽  
Marcelo Augusto de Aguiar e Silva ◽  
Marcelo Giovanetti Canteri ◽  
Juliandra Rodrigues Rosisca ◽  
Nilson Aparecido Vieira Junior

Aiming at assessing the performance of alternative methods to Penman-Monteith FAO56 for estimating the reference evapotranspiration (ETo) for Londrina, Paraná, Brazil, the methods temperature radiation, Hicks-Hess, Hargreaves-Samani (1982), Turc, Priestley-Taylor, Tanner-Pelton, Jensen-Haise, Makkink, modified Hargreaves, Stephens-Stewart, Abtew, global radiation, Ivanov, Lungeon, Hargreaves-Samani (1985), Benavides-Lopez, original Penman, Linacre, Blaney-Morin, Romanenko, Hargreaves (1974), McCloud, Camargo, Hamon, Kharrufa, McGuiness-Bordne, and Blaney-Criddle were compared to that standard method recommended by FAO. The estimations were correlated by linear regression and assessed by using the Person’s correlation coefficient (r), concordance index (d), and performance index (c) using a set of meteorological data of approximately 40 years. The methods modified Hargreaves, Stephens-Stewart, Abtew, global radiation, Ivanov, Lungeon, Hargreaves-Samani (1985), Benavides-Lopez, original Penman, and Linacre should be avoided, as they did not present excellent results. The methods McCloud, Camargo, Hamon, Kharrufa, McGuinness-Bordne, Blaney-Criddle, Hargreaves (1974), Romanenko, and Blaney-Morin were classified as very bad, not being recommended. In contrast, the methods temperature radiation, Hicks-Hess, Hargreaves-Samani (1982), Turc, Priestley-Taylor, Tenner-Pelton, Jensen-Haise, and Makkink presented excellent performance indices and can be applied in the study region.


Fire ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 55
Author(s):  
Gary L. Achtemeier ◽  
Scott L. Goodrick

Abrupt changes in wind direction and speed caused by thunderstorm-generated gust fronts can, within a few seconds, transform slow-spreading low-intensity flanking fires into high-intensity head fires. Flame heights and spread rates can more than double. Fire mitigation strategies are challenged and the safety of fire crews is put at risk. We propose a class of numerical weather prediction models that incorporate real-time radar data and which can provide fire response units with images of accurate very short-range forecasts of gust front locations and intensities. Real-time weather radar data are coupled with a wind model that simulates density currents over complex terrain. Then two convective systems from formation and merger to gust front arrival at the location of a wildfire at Yarnell, Arizona, in 2013 are simulated. We present images of maps showing the progress of the gust fronts toward the fire. Such images can be transmitted to fire crews to assist decision-making. We conclude, therefore, that very short-range gust front prediction models that incorporate real-time radar data show promise as a means of predicting the critical weather information on gust front propagation for fire operations, and that such tools warrant further study.


2017 ◽  
Vol 38 (4Supl1) ◽  
pp. 2363
Author(s):  
Rodrigo Dlugosz da Silva ◽  
Marcelo Augusto de Aguiar e Silva ◽  
Marcelo Giovanetti Canteri ◽  
Juliandra Rodrigues Rosisca ◽  
Nilson Aparecido Vieira Junior

Aiming at assessing the performance of alternative methods to Penman-Monteith FAO56 for estimating the reference evapotranspiration (ETo) for Londrina, Paraná, Brazil, the methods temperature radiation, Hicks-Hess, Hargreaves-Samani (1982), Turc, Priestley-Taylor, Tanner-Pelton, Jensen-Haise, Makkink, modified Hargreaves, Stephens-Stewart, Abtew, global radiation, Ivanov, Lungeon, Hargreaves-Samani (1985), Benavides-Lopez, original Penman, Linacre, Blaney-Morin, Romanenko, Hargreaves (1974), McCloud, Camargo, Hamon, Kharrufa, McGuiness-Bordne, and Blaney-Criddle were compared to that standard method recommended by FAO. The estimations were correlated by linear regression and assessed by using the Person’s correlation coefficient (r), concordance index (d), and performance index (c) using a set of meteorological data of approximately 40 years. The methods modified Hargreaves, Stephens-Stewart, Abtew, global radiation, Ivanov, Lungeon, Hargreaves-Samani (1985), Benavides-Lopez, original Penman, and Linacre should be avoided, as they did not present excellent results. The methods McCloud, Camargo, Hamon, Kharrufa, McGuinness-Bordne, Blaney-Criddle, Hargreaves (1974), Romanenko, and Blaney-Morin were classified as very bad, not being recommended. In contrast, the methods temperature radiation, Hicks-Hess, Hargreaves-Samani (1982), Turc, Priestley-Taylor, Tenner-Pelton, Jensen-Haise, and Makkink presented excellent performance indices and can be applied in the study region.


2021 ◽  
Author(s):  
AHMET IRVEM ◽  
Mustafa OZBULDU

Abstract Evapotranspiration is an important parameter for hydrological, meteorological and agricultural studies. However, the calculation of actual evapotranspiration is very challenging and costly. Therefore, Potential Evapotranspiration (PET) is typically calculated using meteorological data to calculate actual evapotranspiration. However, it is very difficult to get complete and accurate data from meteorology stations in, rural and mountainous regions. This study examined the availability of the Climate Forecast System Reanalysis (CFSR) reanalysis data set as an alternative to meteorological observation stations in the computation of potential annual and seasonal evapotranspiration. The PET calculations using the CFSR reanalysis dataset for the period 1987-2017 were compared to data observed at 259 weather stations observed in Turkey. As a result of the assessments, it was determined that the seasons in which the CFSR reanalysis data set had the best prediction performance were the winter (C'= 0.76 and PBias = -3.77) and the autumn (C' = 0.75 and PBias = -12.10). The worst performance was observed for the summer season. The performance of the annual prediction was determined as C'= 0.60 and PBias = -15.27. These findings indicate that the results of the PET calculation using the CFSR reanalysis data set are relatively successful for the study area. However, the data should be evaluated with observation data before being used especially in the summer models.


2015 ◽  
Vol 33 (3) ◽  
pp. 477 ◽  
Author(s):  
Nadja Gomes Machado ◽  
Marcelo Sacardi Biudes ◽  
Carlos Alexandre Santos Querino ◽  
Victor Hugo De Morais Danelichen ◽  
Maísa Caldas Souza Velasque

ABSTRACT. Cuiab´a is located on the border of the Pantanal and Cerrado, in Mato Grosso State, which is recognized as one of the biggest agricultural producers of Brazil. The use of natural resources in a sustainable manner requires knowledge of the regional meteorological variables. Thus, the objective of this study was to characterize the seasonal and interannual pattern of meteorological variables in Cuiab´a. The meteorological data from 1961 to 2011 were provided by the Instituto Nacional de Meteorologia (INMET – National Institute of Meteorology). The results have shown interannual and seasonal variations of precipitation, solar radiation, air temperature and relative humidity, and wind speed and direction, establishing two main distinct seasons (rainy and dry). On average, 89% of the rainfall occurred in the wet season. The annual average values of daily global radiation, mean, minimum and maximum temperature and relative humidity were 15.6 MJ m–2 y–1, 27.9◦C, 23.0◦C, 30.0◦C and 71.6%, respectively. Themaximum temperature and the wind speed had no seasonal pattern. The wind speed average decreased in the NWdirectionand increased in the S direction.Keywords: meteorological variables, climatology, ENSO. RESUMO. Cuiabá está localizado na fronteira do Pantanal com o Cerrado, no Mato Grosso, que é reconhecido como um dos maiores produtores agrícolas do Brasil. A utilização dos recursos naturais de forma sustentável requer o conhecimento das variáveis meteorológicas em escala regional. Assim, o objetivo deste estudo foi caracterizar o padrão sazonal e interanual das variáveis meteorológicas em Cuiabá. Os dados meteorológicos de 1961 a 2011 foram fornecidos pelo Instituto Nacional de Meteorologia (INMET). Os resultados mostraram variações interanuais e sazonais de precipitação, radiação solar, temperatura e umidade relativa do ar e velocidade e direção do vento, estabelecendo duas principais estações distintas (chuvosa e seca). Em média, 89% da precipitação ocorreu na estação chuvosa. Os valores médios anuais de radiação diária global, temperatura do ar média, mínima e máxima e umidade relativa do ar foram 15,6 MJ m–2 y–1, 27,9◦C, 23,0◦C, 30,0◦C e 71,6%, respectivamente. A temperatura máxima e a velocidade do vento não tiveram padrão sazonal. A velocidade média do vento diminuiu na direção NW e aumentou na direção S.Palavras-chave: variáveis meteorológicas, climatologia, ENOS.


2020 ◽  
Author(s):  
Jaeyoung Song ◽  
Gretchen R. Miller ◽  
Anthony T. Cahill ◽  
Luiza Aparecido ◽  
Georgianne W. Moore

Abstract. This study compares the performance of the Community Land Models (CLM4.5 and CLM5) against tower and ground measurements from a tropical montane rainforest in Costa Rica. The study site receives over 4,000 mm of mean annual precipitation and has high daily levels of relative humidity. The measurement tower is equipped with eddy-covariance and vertical profile systems able to measure various micrometeorological variables, particularly in wet and complex terrain. In this work, results from point-scale simulation for both CLM4.5 and its updated version (CLM5) are compared to observed canopy flux and micro-meteorological data. Both models failed to capture the effects of frequent rainfall events and mountainous topography on the variables of interest (temperatures, leaf wetness, and fluxes). Overall, CLM5 alleviates some errors in CLM4.5 but CLM5 still cannot precisely simulate a number of canopy processes for this forest. Soil, air, and canopy temperatures, as well as leaf wetness, remain too sensitive to incoming solar radiation rates despite updates to the model. As a result, daytime vapor flux and carbon flux are overestimated, and modeled temperature differences between day and night are higher than those observed. Slope effects appear in the measured average diurnal variations of surface albedo and carbon flux, but CLM5 cannot simulate these features. This study suggests that both CLM models still require further improvements concerning energy partitioning processes, such as leaf wetness process, photosynthesis model, and aerodynamic resistance model for wet and mountainous regions.


2002 ◽  
Vol 6 (1) ◽  
pp. 39-48 ◽  
Author(s):  
E. Blyth

Abstract. This paper describes a comparison between two soil moisture prediction models. One is MORECS (Met Office Rainfall and Evaporation Calculation Scheme), the Met Office soil moisture model that is used by agriculture, flood modellers and weather forecasters to initialise their models. The other is MOSES (Met Office Surface Exchange Scheme), modified with a runoff generation module. The models are made compatible by increasing the vegetation information available to MOSES. Both models were run with standard parameters and were driven using meteorological observations at Wallingford (1995-1997). Detailed soil moisture measurements were available at a grassland site and a woodland site in this area. The comparison between the models and the observed soil moisture indicated that, for the grassland site, MORECS dried out too quickly in the spring and, for the woodland site, was too wet. Overall, the performance of MOSES was superior. The soil moisture predicted by the new, modified MOSES will be included as a product of Nimrod - the 5 km x 5km gridded network of observed meteorological data across the UK. Keywords: Soil moisture, model, observation, field capacity


2010 ◽  
Vol 51 (55) ◽  
pp. 49-55 ◽  
Author(s):  
A. Humbert ◽  
D. Gross ◽  
R. Müller ◽  
M. Braun ◽  
R.S.W. van de Wal ◽  
...  

AbstractA narrow bridge of floating ice that connected the Wilkins Ice Shelf, Antarctica, to two confining islands eventually collapsed in early April 2009. In the month preceding the collapse, we observed deformation of the ice bridge by means of satellite imagery and from an in situ GPS station. TerraSAR-X images (acquired in stripmap mode) were used to compile a time series. The ice bridge bent most strongly in its narrowest part (westerly), while the northern end (near Charcot Island) shifted in a northeasterly direction. In the south, the ice bridge experienced compressive strain parallel to its long axis. GPS position data were acquired a little south of the narrowest part of the ice bridge from 19 January 2009. Analysis of these data showed both cyclic and monotonic components of motion. Meteorological data and re-analysis of the output of weather-prediction models indicated that easterly winds were responsible for the cyclic motion component. In particular, wind stress on the rough ice melange that occupied the area to the east exerted significant pressure on the ice bridge. The collapse of the ice bridge began with crack formation in the southern section parallel to the long axis of the ice bridge and led to shattering of the southern part. Ultimately, the narrowest part, only 900 m wide, ruptured. The formation of many small icebergs released energy of >125 ×106 J.


Sign in / Sign up

Export Citation Format

Share Document