A Probabilistic Approach to the Prediction of Snow Loads

1974 ◽  
Vol 1 (1) ◽  
pp. 28-49 ◽  
Author(s):  
N. Isyumov ◽  
A. G. Davenport
Keyword(s):  
Formation Process ◽  
Extreme Values ◽  
Meteorological Data ◽  
Digital Simulation ◽  
Probabilistic Approach ◽  
Snow Accumulation ◽  
Meteorological Variables ◽  
Snow Load ◽  
Design Values ◽  
Snow Loads

The magnitudes of loads imposed by snow depend upon a number of climatological and meteorological variables and as a result exhibit marked variations geographically, due to local effects within a particular region, and with time. The snowload formation process, which depends both on the macro- and microclimates of such meteorological variables as the depth of the snowfall, the snowfall density, wind speed, air temperature etc., as well as, the size and geometry of particular roofs and the influence of their immediate environment, is discussed.A model of the snow load formation process based on a mass balance approach, which takes into account the deposition of snow by individual snowfalls and the depletion of the snow load by wind action and thermal effects, is introduced. The use of this approach requires the establishment of statistical descriptions of the various meteorological variables, as well as a knowledge of the physical process of snow accumulation and depletion for a particular roof. The statistical properties of some of the more important meteorological variables are discussed. Also presented are some model derived data of snow accumulation and depletion for particular roofs located in different terrain.It is shown that even relatively simple statistical descriptions of the relevant meteorological data and snow accumulation and depletion mechanisms can lead to realistic predictions of roof snow loads. Snow loads on a flat roof are generated by a digital simulation technique and compared with full scale observations. Annual extreme values of the simulated snow load process are presented and compared with currently specified design values. Comments are made regarding the practicability of this approach.

scholarly journals Remote monitoring of the snow loads on a roof of buildings

2016 ◽  
Vol 56 (2) ◽  
pp. 246-252
Author(s):  
V. A. Lobkina ◽  
I. A. Kononov ◽  
A. A. Potapov
Keyword(s):  
Remote Monitoring ◽  
Winter Season ◽  
Snow Accumulation ◽  
Snow Melting ◽  
Snow Load ◽  
Load Change ◽  
Load Cells ◽  
Snow Loads ◽  
Flat Roof ◽  
Snow Loading

Obtaining actual data on a change in the value of snow load for a snowfall is an important task the solution of which is usually neglected. The purpose of the work was to obtain a data on dynamics of the snow load change on a roof for a snowfall. A system for remote monitoring of the snow load was developed for this purpose. This system allows continuous gathering and transmission of the data on the snow load change from a unit of area. Obtaining this information gives an indication of the size of snow loading and dynamics of the snow accumulation during snowfall. The developed system provides continuous collection and transmission of data about the changing snow load per unit area. This information makes possible judging values of the snow load and its dynamics during a snowfall. Using of this system allows monitoring of snow accumulation during a snowfall. Discreteness of the system is 1 minute, and the sensitivity to the load change is 50 g. The platform is designed for a load less than 100 kg. When a snowfall ends the platform should be cleaned. In 2015, the system has been just tested, but in future we plan to use the system without cleaning for the whole snow season. In this connection, the more powerful sensors will be used. The system consists of a rectangular platform with an area of 1 m2, and it is equipped with four load cells «TOQUES» BBA at the corners. It was used for two months from late January to mid-March. In total, nine snowfalls were observed. In the winter season of 2014/15, increases of snow loads changed within the range of 10–100 kg/m2. Analysis of the data shows that the maximum snow load exerted on the roof takes place at a snowfall peak, after that it decreases under the influence of external factors. Three main factors influencing formation of the snow loads on a flat roof are as follows: the quantity of solid precipitation, the snow melting, and redistribution of snow by wind. Using of the system allows obtaining actual values of snow load on roofs of buildings instead of data calculated from the snow weight on the ground. These values can be then used to correct standards for the snow loads.

Climatology of snowfall and related meteorological variables with application to roof snow load specifications

1977 ◽  
Vol 4 (2) ◽  
pp. 240-256 ◽  
Author(s):  
N. Isyumov ◽  
M. Mikitiuk
Keyword(s):  
Statistical Models ◽  
Meteorological Data ◽  
Aerodynamic Characteristics ◽  
Extreme Value Statistics ◽  
Meteorological Variables ◽  
Snow Hydrology ◽  
Design Problems ◽  
Snow Load ◽  
Roof Shape ◽  
Engineering Design Problems

Representative statistical models of snowfall and related meteorological variables, important in snow hydrology research, are also required for many engineering design problems. Design roof snow loads, if based on the balance between deposition of snow by individual snowfalls and subsequent depletion by wind action and various thermodynamic mechanisms, in addition to aerodynamic characteristics of particular roof shapes, require the development of statistical models of various meteorological variables which influence the process.Mathematical models suitably describing the statistics of individual snowfall amounts, wind speed and directions, and air temperature are presented in this paper. These results are based on the analysis of daily meteorological data obtained at some 28 Canadian stations with typical record lengths of about 30 years. The suitability of the developed probability distribution of daily snowfall magnitudes is examined through comparisons of both derived parent and extreme value statistics with available full scale observations. The joint statistics of these meteorological variables are also examined and a methodology for approximately accounting for their interdependence is presented.The relevance of the overall winter climatology of an area to roof snow load formation is discussed. Results of a Monte Carlo simulation, which show the dependence of the snow load for a particular roof shape on the climatology of snowfall and related meteorological variables, are presented.

scholarly journals Probabilistic Assessment of Roof Snow Load and the Calibration of Shape Coefficients in the Eurocodes

2021 ◽  
Vol 11 (7) ◽  
pp. 2984
Author(s):  
Pietro Croce ◽  
Paolo Formichi ◽  
Filippo Landi
Keyword(s):  
Conversion Factor ◽  
Reference Value ◽  
Construction Site ◽  
Probability Of Exceedance ◽  
Snow Load ◽  
Shape Coefficient ◽  
Annual Probability ◽  
Wind Exposure ◽  
Design Values ◽  
One Year

In modern structural codes, the reference value of the snow load on roofs is commonly given as the product of the characteristic value of the ground snow load at the construction site multiplied by the shape coefficient. The shape coefficient is a conversion factor which depends on the roof geometry, its wind exposure, and its thermal properties. In the Eurocodes, the characteristic roof snow load is either defined as the value corresponding to an annual probability of exceedance of 0.02 or as a nominal value. In this paper, an improved methodology to evaluate the roof snow load characterized by a given probability of exceedance (e.g., p=0.02 in one year) is presented based on appropriate probability density functions for ground snow loads and shape coefficients, duly taking into account the influence of the roof’s geometry and its exposure to wind. In that context, the curves for the design values of the shape coefficients are provided as a function of the coefficient of variation (COVg) of the yearly maxima of the snow load on the ground expected at a given site, considering three relevant wind exposure conditions: sheltered or non-exposed, semi-sheltered or normal, and windswept or exposed. The design shape coefficients for flat and pitched roofs, obtained considering roof snow load measurements collected in Europe during the European Snow Load Research Project (ESLRP) and in Norway, are finally compared with the roof snow load provisions given in the relevant existing Eurocode EN1991-1-3:2003 and in the new version being developed (prEN1991-1-3:2020) for the “second generation” of the Eurocodes.

scholarly journals Seasonal influence of snow conditions on Dall’s sheep productivity in Wrangell-St Elias National Park and Preserve

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0244787
Author(s):  
Christopher L. Cosgrove ◽  
Jeff Wells ◽  
Anne W. Nolin ◽  
Judy Putera ◽  
Laura R. Prugh
Keyword(s):  
Snow Depth ◽  
National Park ◽  
Meteorological Data ◽  
Multiple Regression Model ◽  
Snow Accumulation ◽  
Population Declines ◽  
Climate Conditions ◽  
Remote Cameras ◽  
Snow Conditions ◽  
Dall’S Sheep

Dall’s sheep (Ovis dalli dalli) are endemic to alpine areas of sub-Arctic and Arctic northwest America and are an ungulate species of high economic and cultural importance. Populations have historically experienced large fluctuations in size, and studies have linked population declines to decreased productivity as a consequence of late-spring snow cover. However, it is not known how the seasonality of snow accumulation and characteristics such as depth and density may affect Dall’s sheep productivity. We examined relationships between snow and climate conditions and summer lamb production in Wrangell-St Elias National Park and Preserve, Alaska over a 37-year study period. To produce covariates pertaining to the quality of the snowpack, a spatially-explicit snow evolution model was forced with meteorological data from a gridded climate re-analysis from 1980 to 2017 and calibrated with ground-based snow surveys and validated by snow depth data from remote cameras. The best calibrated model produced an RMSE of 0.08 m (bias 0.06 m) for snow depth compared to the remote camera data. Observed lamb-to-ewe ratios from 19 summers of survey data were regressed against seasonally aggregated modelled snow and climate properties from the preceding snow season. We found that a multiple regression model of fall snow depth and fall air temperature explained 41% of the variance in lamb-to-ewe ratios (R2 = .41, F(2,38) = 14.89, p<0.001), with decreased lamb production following deep snow conditions and colder fall temperatures. Our results suggest the early establishment and persistence of challenging snow conditions is more important than snow conditions immediately prior to and during lambing. These findings may help wildlife managers to better anticipate Dall’s sheep recruitment dynamics.

scholarly journals Impact of meteorological factors on number of new COVID-19 cases in Pune

2021 ◽  
Vol 8 (9) ◽  
pp. 4307
Author(s):  
Saurabh Mahajan ◽  
Ravi Devarakonda ◽  
Gautam Mukherjee ◽  
Nisha Verma ◽  
Kumar Pushkar
Keyword(s):  
Meteorological Data ◽  
Secondary Data ◽  
Significant Negative Correlation ◽  
Meteorological Variables ◽  
Strong Positive Correlation ◽  
Daily Number ◽  
Average Temperature ◽  
Time Period ◽  
Indian Meteorological Department ◽  
The Impact

Background: Coronaviruses are a family of viruses that can result in different types of illnesses, most commonly, as Severe acute respiratory syndrome (SARS). Researches have shown that the atmospheric variables and the density of population have affected the transmission of the disease. Meteorological variables like temperature, humidity among others have found to affect the rise of pandemic in positive or negative ways.  Respiratory virus illnesses have shown seasonal variability since the time they have been discovered and managed. This study investigated the relationship between the meteorological variables of temperature, humidity and precipitation in the spread of COVID-19 disease in the city of Pune.Methods: This record based descriptive study is conducted after secondary data analysis of number of new cases of COVID-19 per day from the period 01 May to 24 December 2020 in Pune. Meteorological data of maximum (Tmax), minimum (Tmin) and daily average temperature (Tavg), humidity and precipitation were daily noted from Indian meteorological department website. Trend was identified plotting the daily number of clinically diagnosed cases over time period. Pearson’s correlation was used to estimate association between meteorological variables and daily detected fresh cases of COVID-19 disease.  Results: Analysis revealed significant negative correlation (r=-0.3563, p<0.005) between daily detected number of cases and maximum daily temperature. A strong positive correlation was seen between humidity and daily number of cases (r=0.5541, p<0.005).Conclusions: The findings of this study will aid in forecasting epidemics and in preparing for the impact of climate change on the COVID epidemiology through the implementation of public health preventive measures.

scholarly journals Concentração de Material Particulado (PM10) na Região de Tangará da Serra-MT, Sul da Amazônia Legal (Particulate Matter Concentration in Tangará da Serra Region, Southern Legal...)

2015 ◽  
Vol 7 (6) ◽  
pp. 1145
Author(s):  
Patricia Simone Palhana Moreira ◽  
Rivanildo Dallacort ◽  
Idilaine De Fatima Lima ◽  
Rafael Cesar Tieppo ◽  
Cristiano Santos
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Meteorological Data ◽  
Average Concentration ◽  
Atmospheric Particulate Matter ◽  
Meteorological Variables ◽  
State University ◽  
Mato Grosso ◽  
Short Period ◽  
Matter Concentration

O objetivo do presente trabalho foi analisar as concentrações de material particulado presente na atmosfera de Tangará da Serra-MT, e correlacioná-los com as variáveis meteorológicas, informações de saúde e com o número de focos de queimada no Estado de Mato Grosso. Os dados de material particulado foram amostrados diariamente a cada 5 minutos, com auxilio do coletor DataRam4, no período de agosto de 2008 a julho de 2009. Os dados meteorológicos foram disponibilizados pelo Instituto Nacional de Meteorologia - INMET, o qual possui uma estação meteorológica instalada na Universidade do Estado de Mato Grosso – UNEMAT. A média de concentração do período foi de 30,1 ug.m-3. Os meses de agosto, setembro e outubro apresentaram concentrações mais altas de material particulado, nestes meses também ocorreram os maiores números de queimadas no Estado. Nos meses em que foram registrados os picos de concentração, houve dias em que os padrões de qualidade do ar foram ultrapassados. No mês de outubro, que foi o de maior concentração, as médias diárias ultrapassaram 150 ug.m-3 em três dias. As concentrações de material particulado (PM10) foram altas apenas em um período relativamente curto, de apenas três meses, nos demais meses as concentrações foram baixas, não ultrapassando os limites de qualidade do ar.  A B S T R A C T The aim of this work was to analyze the atmospheric particulate matter concentrations in Tangara da Serra MT, and correlate them with meteorological variables, health information and the number of fire spots in Mato Grosso State. The particulate matter data were sampled every five minutes daily with a DataRam4 collector, from August 2008 to July 2009. Meteorological data were acquired from the National Institute of Meteorology - INMET, which has a weather station at the Mato Grosso State University - UNEMAT. The average concentration for the period was 30.1 ug.m-3. The months of August, September and October showed higher concentrations of particulate matter, in these months also occurred the highest number of fire spots in the State. In the months that had the concentrations peak, there were days when the air quality standards were exceeded. In October, which had the highest concentration, the daily average exceeded 150 ug.m-3 in three days. The concentrations of particulate matter (PM10) were high, but only in a relatively short period of three months, in the remaining months the concentrations were low, not exceeding the limits of air quality. Keywords: Meteorological Variables, Fire Spots, Meteorology.  

scholarly journals SEASONAL AND INTERANNUAL PATTERN OF METEOROLOGICAL VARIABLES IN CUIABÁ, MATO GROSSO STATE, BRAZIL

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
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Meteorological Data ◽  
Seasonal Pattern ◽  
Global Radiation ◽  
Meteorological Variables ◽  
Maximum Temperature ◽  
Wet Season ◽  
Agricultural Producers ◽  
Mato Grosso

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.

scholarly journals Development of a meteorological forecast for snow accumulation on transmission lines

1993 ◽  
Vol 18 ◽  
pp. 107-112
Author(s):  
Tatsuhito Ito ◽  
Masaru Yamaoka ◽  
Hisayuki Ohura ◽  
Takashi Taniguchi ◽  
Gorow Wakahama
Keyword(s):  
Air Temperature ◽  
Transmission Lines ◽  
Wind Direction ◽  
Mesoscale Model ◽  
Meteorological Data ◽  
Snow Accumulation ◽  
Surface Winds ◽  
Temperature And Precipitation ◽  
Wet Snow

In Hokkaido we have often experienced hazardous accidents, such as tower collapses and conductor breakage, caused by wet-snow accretion on transmission lines, and over many years have developed countermeasures for wet-snow accretion. Recently we have been developing a system to forecast areas where snow accretion may occur. We used the southern part of Hokkaido, divided into 5 km × 5 km meshes, as a forecast area; our predictions were hourly, 3–24 hours in advance. A method of predicting meteorological data which forms an important part of the system predicts three elements which influence wet-snow accretion: air temperature, precipitation, and wind direction and speed. We used an interpolation for predicting temperature and precipitation and a one-level, mesoscale model for diagnosing surface winds for wind direction and speed. By applying the method to many examples of wet-snow accretion, we checked the prediction of weather elements.

Data-Driven Probabilistic Thermal Stress Analysis of a Gas Turbine Casing

2018 ◽  
Author(s):  
Zixi Han ◽  
Mian Li ◽  
Zixian Jiang ◽  
Zuoxing Min ◽  
Sophie Bourmich
Keyword(s):  
Monte Carlo ◽  
Thermal Stress ◽  
Boundary Conditions ◽  
Gas Turbine ◽  
Probabilistic Approach ◽  
Computational Time ◽  
Strength Assessment ◽  
Fixed Design ◽  
Design Values ◽  
Turbine Casing

Strength requirement is one of the most important criteria in the design of gas turbine casing. Traditionally, deterministic analyses are used in strength assessment, with boundary conditions and loads set as fixed design values. However, real boundary conditions and loads in the operation can often differ from the fixed design values, such that the mechanical integrity of the turbine casing can vary from the strength and fatigue calculations. In this work, the effect of the variability of the boundary conditions and loads is investigated on the static thermal stress problem of gas turbine casings using a probabilistic approach. The probability distribution is estimated using a Monte Carlo simulation based on the distribution of boundary conditions and loads obtained from field measurements. The finite element analysis is used to calculate the stress corresponding to different boundary conditions and a surrogate model is built to reduce the computational time of Monte Carlo simulations. This methodology is applied to a real engineering case which better quantifies the strength assessment result.

scholarly journals Climatic and atmospheric circulation pattern variability from ice-core isotope/geochemistry records (Altai, Tien Shan and Tibet)

2006 ◽  
Vol 43 ◽  
pp. 49-60 ◽  
Author(s):  
Vladimir B. Aizen ◽  
Elena M. Aizen ◽  
Daniel R. Joswiak ◽  
Koji Fujita ◽  
Nozomu Takeuchi ◽  
...  
Keyword(s):  
Air Temperature ◽  
Isotope Geochemistry ◽  
Eastern Mediterranean ◽  
Meteorological Data ◽  
Ice Core ◽  
Ice Cores ◽  
Snow Accumulation ◽  
Tien Shan ◽  
Synoptic Climatology ◽  
The Tibetan Plateau

AbstractSeveral firn/ice cores were recovered from the Siberian Altai (Belukha plateau), central Tien Shan (Inilchek glacier) and the Tibetan Plateau (Zuoqiupu glacier, Bomi) from 1998 to 2003. The comparison analyses of stable-isotope/geochemistry records obtained from these firn/ice cores identified the physical links controlling the climate-related signals at the seasonal-scale variability. The core data related to physical stratigraphy, meteorology and synoptic atmospheric dynamics were the basis for calibration, validation and clustering of the relationships between the firn-/ice-core isotope/ geochemistry and snow accumulation, air temperature and precipitation origin. The mean annual accumulation (in water equivalent) was 106 gcm−2 a−1 at Inilchek glacier, 69 gcm−2 a−1 at Belukha and 196 g cm−2 a−1 at Zuoqiupu. The slopes in regression lines between the δ18O ice-core records and air temperature were found to be positive for the Tien Shan and Altai glaciers and negative for southeastern Tibet, where heavy amounts of isotopically depleted precipitation occur during summer monsoons. The technique of coupling synoptic climatology and meteorological data with δ18O and d-excess in firn-core records was developed to determine climate-related signals and to identify the origin of moisture. In Altai, two-thirds of accumulation from 1984 to 2001 was formed from oceanic precipitation, and the rest of the precipitation was recycled over Aral–Caspian sources. In the Tien Shan, 87% of snow accumulation forms by precipitation originating from the Aral–Caspian closed basin, the eastern Mediterranean and Black Seas, and 13% from the North Atlantic.

Sign in / Sign up

Export Citation Format

Share Document