scholarly journals Sediment production in flysch badlands: A case study from Slovenian Istria

2020 ◽  
Vol 60 (1) ◽  
Author(s):  
Gregor Kovačič
Keyword(s):  
Air Temperature ◽  
Precipitation Amount ◽  
Meteorological Station ◽  
The Other ◽  
Average Wind Speed ◽  
Sediment Production ◽  
Average Wind ◽  
Erosion Pins ◽  
Minimum Air Temperature

This article deals with the results of seven years of measurements of sediment release from the flysch badlands in the Rokava River headwaters. Measurements of sediment production were carried out in erosion plots, and measurements of cliff (or rockwall) retreat using erosion pins. Selected meteorological time series from the Portorož Airport meteorological station were included in the analysis. The calculation showed that from 2008 to 2015 (149 measurements) sediment production was 36 kg/m² per year and the flysch cliff retreated by 146 mm or 21 mm per year. The amount of sediment produced is moderately positively correlated with the number of days between successive measurements (r = 0.51), with a recorded daily transition of air temperature over/below 0 °C (r = 0.56) and slightly more weakly correlated with the precipitation amount (r = 0.45). On the other hand, the amount of sediment produced has a low negative correlation with average air temperature (r = −0.29) and average minimum air temperature (r = −0.30). However, no statistically significant correlation was calculated between the amount of sediment produced and average wind speed.

scholarly journals Klimatska obilježja otoka Palagruže, Hrvatska

Geoadria ◽  
2017 ◽  
Vol 8 (1) ◽  
pp. 39
Author(s):  
Živko Trošić ◽  
Dražen Jašić ◽  
Vinko Marinković
Keyword(s):  
Air Temperature ◽  
Precipitation Amount ◽  
Meteorological Station ◽  
Rank Statistic ◽  
Climatic Data ◽  
Air Temperatures ◽  
The Mean ◽  
Instrumental Period ◽  
C 30 ◽  
Minimum Air Temperature

The paper presents a brief review of contemporary research on climatic features of Palagruža Island, both in the pre-instrumental and instrumental period. The analysis was made upon climatic data provided by the meteorological station of Palagruža. For comparison purposes, data from the station in Split-Marjan was used, covering the standard climate period 1961-1990. The results show, among other things, that there is a decreasing trend of annual mean maximum air temperatures for 0.37 °C/30 years, average air temperature for 0.05 °C/30 years, and the mean minimum air temperature for 0.04 °C/30 years. There is a decreasing trend of annual mean of precipitation amount for 62 mm/30 years. Spearman rank statistic shows that neither of the trends noted above is statistically significant at 0.05 level (two-tailed t-test) 

scholarly journals Adapting River Bridge Infrastructures To Climate Change

2021 ◽  
Author(s):  
Akinola Ifelola
Keyword(s):  
Climate Change ◽  
Stream Velocity ◽  
Climate Change Scenarios ◽  
Average Wind Speed ◽  
Southern Ontario ◽  
Ottawa River ◽  
Air Temperatures ◽  
Average Wind ◽  
The Impact

Climate change forecasts project up to 20% increase in precipitation for southern Ontario based on several climate change scenarios and models and an unpredictable change an average wind speed that may range from 5% reduction to 15% increase by the year 2100 compared to 1971 to 2000 reference period. Average annual air temperatures are predicted to increase between 2.5 and 3.7°C by 2050 from baseline average between 1961 and 1990. This research studied the impact of climate change on bridge infrastructure using the Portage bridge on the Ottawa river in southern Ontario as a case study. Result shows that increase in precipitation due to climate change will cause 0.3m/s increase in stream velocity and about 0.85m increase in water level for a 100-year storm. This increase will result in scour depths at bridge piers to increase by 0.86 m while bending moments on piers increased by 21 kNm. Shear forces also increased by 43 kN.

scholarly journals Climate of submontane location Stará Lesná (1988–2013)

2014 ◽  
Vol 44 (2) ◽  
pp. 95-113
Author(s):  
Svetlana Bíčárová ◽  
Jozef Mačutek ◽  
Dušan Bilčík
Keyword(s):  
Air Temperature ◽  
Sunshine Duration ◽  
Precipitation Amount ◽  
Mixed Forest ◽  
Climatic Data ◽  
Strong Wind ◽  
Average Wind Speed ◽  
Growing Season Length ◽  
Meteorological Observatory ◽  
Tatra Mts

Abstract This paper focuses on evaluation of climatic data obtained at Meteorological Observatory GPI SAS Stará Lesná according to the classical daily observations carried out for period 1988-2013. Location is situated at the foothills of the High Tatra Mts. and represents submontane climate zone favourable for temperate coniferous and mixed forest vegetation. According to observations climate of Star´a Lesná is characterized by average annual air temperature 5.9 °C that seasonally varies from -3.5 °C (DJF) to 15.2 °C (JJA). Air-temperature extremes range between -26.5 and 34.2 °C. Daily air temperature maxima and derived indices such as the number of summer days indicate moderate warming during last decade. Growing season length is about 195 days. Average annual precipitation is 744 mm, seasonal comparison shows nearly twice more precipitation amount in summer than winter half year. Snow depth is 35 cm on average, extraordinary over 50 cm. Relative air humidity is about 78%. Wet periods lasted from 5 to 13 consecutive wet days; substantially longer are dry periods from 14 to 39 days. Average sunshine duration is 1806 hours per year. The number of sunny days is clearly lower than the number of cloudy days. Surface air pressure 920.4 hPa relates to altitudinal position of site. Wind blows mostly from the more open southern side. Although average wind speed is rather low (2.1 m/s), occurrence of strong wind gusts above 40 m/s can cause such a spatial destruction of natural environment as in November 2004

scholarly journals Sensitivity Analysis of Quality Assurance Using the Spatial Regression Approach—A Case Study of the Maximum/Minimum Air Temperature

2005 ◽  
Vol 22 (10) ◽  
pp. 1520-1530 ◽  
Author(s):  
Kenneth G. Hubbard ◽  
Jinsheng You
Keyword(s):  
Air Temperature ◽  
Time Window ◽  
Spatial Regression ◽  
Optimal Number ◽  
Quality Data ◽  
Distance Weighting ◽  
Time Offset ◽  
Inverse Distance ◽  
Minimum Air Temperature

Abstract Both the spatial regression test (SRT) and inverse distance weighting (IDW) methods have been applied to provide estimates for the maximum air temperature (Tmax) and the minimum air temperature (Tmin) in the Applied Climate Information System (ACIS). This is critical to the processes of estimating missing data and identifying suspect data and is undertaken here to ensure quality data in ACIS. The SRT method was previously found to be superior to the IDW method; however, the sensitivity of the performance of both methods to input parameters has not been evaluated. A set of analyses is presented for both methods whereby the sensitivity to the radius of inclusion, the regression time window, the regression time offset, and the number of stations used to make the estimates are examined. Comparisons were also conducted between the SRT and the IDW methods. The performance of the SRT method stabilized when 10 or more stations were applied in the estimates. The optimal number of stations for the IDW method varies from only a few to 30. The results indicate that the best estimates obtained using the IDW method are still inferior to the worst estimates obtained using the SRT method.

Research on the Ultra-Short-Term Bus Load Forecasting Method Considering Meteorological Mutation

2015 ◽  
Vol 713-715 ◽  
pp. 1431-1435
Author(s):  
Dong Xiao Niu ◽  
Bing Jie Li ◽  
Yan Lu ◽  
Zhe Chen ◽  
Jian Kun Liu
Keyword(s):  
Weather Conditions ◽  
Good Prediction ◽  
Average Wind Speed ◽  
Average Temperature ◽  
Average Wind ◽  
Forecasting Method ◽  
Svm Model ◽  
Average Relative Humidity ◽  
Exponential Smoothing Method

Because small value and rapid changes, bus load is severely affected by meteorological factors. The article focuses on the precipitation, the average pressure, the average wind speed, the average temperature and the average relative humidity, and identifies the meteorological mutations. In the case when there is no mutation, predict the load trends based on the Single Exponential Smoothing method, otherwise, if there exists meteorological mutation, use SVM model to predict the load, as well as in the event of extreme weather conditions, start the emergency warning plan. By the case study of the No.1 main transformer of certain area in Jiangsu Province, the result shows that this method has good prediction results.

Effets de la scarification du site sur le micro-environnement

1980 ◽  
Vol 10 (4) ◽  
pp. 476-482 ◽  
Author(s):  
André P. Plamondon ◽  
Denis C. Ouellet ◽  
Gaston Déry
Keyword(s):  
Soil Water ◽  
Air Temperature ◽  
Soil Surface ◽  
The Other ◽  
Maximum Temperature ◽  
Soil Water Tension ◽  
Air Temperatures ◽  
Soil Temperatures ◽  
Water Tension ◽  
Minimum Air Temperature

Soil and air temperatures, and soil water tension were measured at two sites from June 1972 to August 1973 in order to determine the effect of scarification. This study is part of a project concerning yellow birch regeneration. The minimum air temperature at 30 cm height and at the soil surface were, respectively, 0.5 and 1.0 °C higher at the scarified site; on the other hand, the maximum temperature at 30 cm was lower. The soil temperatures during the summer were 2 to 4 °C higher at the scarified site according to the level considered. Soil water tension was much lower in the scarified station between 0 and 15 cm depth, but the effect decreased during the second summer of the study.

scholarly journals Spatial Accuracy of Climate Networks: A Case Study in Nebraska

2014 ◽  
Vol 53 (8) ◽  
pp. 1932-1942 ◽  
Author(s):  
Andrea J. Coop ◽  
Kenneth G. Hubbard ◽  
Martha D. Shulski ◽  
Jinsheng You ◽  
David B. Marx
Keyword(s):  
Air Temperature ◽  
Weather Data ◽  
Reference Network ◽  
Daily Maximum ◽  
Spatial Accuracy ◽  
Climate Data ◽  
Historical Climatology ◽  
Mean Square Errors ◽  
Minimum Air Temperature

AbstractClimate data are increasingly scrutinized for accuracy because of the need for reliable input for climate-related decision making and assessments of climate change. Over the last 30 years, vast improvements to U.S. instrumentation, data collection, and station siting have created more accurate data. This study explores the spatial accuracy of daily maximum and minimum air temperature data in Nebraska networks, including the U.S. Historical Climatology Network (HCN), the Automated Weather Data Network (AWDN), and the more recent U.S. Climate Reference Network (CRN). The spatial structure of temperature variations at the earth’s surface is compared for timeframes 2005–09 for CRN and AWDN and 1985–2005 for AWDN and HCN. Individual root-mean-square errors between candidate station and surrounding stations were calculated and used to determine the spatial accuracy of the networks. This study demonstrated that in the 5-yr analysis CRN and AWDN were of high spatial accuracy. For the 21-yr analysis the AWDN proved to have higher spatial accuracy (smaller errors) than the HCN for both maximum and minimum air temperature and for all months. In addition, accuracy was generally higher in summer months and the subhumid area had higher accuracy than did the semiarid area. The findings of this study can be used for Nebraska as an estimate of the uncertainty associated with using a weather station’s data at a decision point some distance from the station.

scholarly journals Comparison of Three Methods for Wind Turbine Capacity Factor Estimation

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Y. Ditkovich ◽  
A. Kuperman
Keyword(s):  
Wind Turbine ◽  
Nonlinear Approximation ◽  
Capacity Factor ◽  
Valuable Insight ◽  
Power Curve ◽  
Average Wind Speed ◽  
Turbine Performance ◽  
Average Wind ◽  
Turbine Capacity

Three approaches to calculating capacity factor of fixed speed wind turbines are reviewed and compared using a case study. The first “quasiexact” approach utilizes discrete wind raw data (in the histogram form) and manufacturer-provided turbine power curve (also in discrete form) to numerically calculate the capacity factor. On the other hand, the second “analytic” approach employs a continuous probability distribution function, fitted to the wind data as well as continuous turbine power curve, resulting from double polynomial fitting of manufacturer-provided power curve data. The latter approach, while being an approximation, can be solved analytically thus providing a valuable insight into aspects, affecting the capacity factor. Moreover, several other merits of wind turbine performance may be derived based on the analytical approach. The third “approximate” approach, valid in case of Rayleigh winds only, employs a nonlinear approximation of the capacity factor versus average wind speed curve, only requiring rated power and rotor diameter of the turbine. It is shown that the results obtained by employing the three approaches are very close, enforcing the validity of the analytically derived approximations, which may be used for wind turbine performance evaluation.

scholarly journals Mangrove Microclimate: A Case Study from Southeastern Brazil

2013 ◽  
Vol 17 (2) ◽  
pp. 1-16 ◽  
Author(s):  
Nádia Gilma Beserra de Lima ◽  
Emerson Galvani
Keyword(s):  
Solar Radiation ◽  
Air Temperature ◽  
Global Solar Radiation ◽  
Southeastern Brazil ◽  
Average Wind Speed ◽  
Physical Constraints ◽  
Average Wind ◽  
Relative Air Humidity ◽  
Mangrove Environment ◽  
Terrestrial Environments

Abstract A mangrove is a transitional coastal ecosystem between marine and terrestrial environments that is characterized by salinity and constant tidal flooding. Mangroves contain plant communities that are adapted to several physical constraints, including the climate. The purpose of this study was to analyze the variations in climatic attributes (air temperature, relative air humidity, global solar radiation, wind, and rainfall) in the mangroves located in the municipality of Iguape, on the southern coast of the state of São Paulo, Brazil. In addition, it was determined whether the existing variation is related to the presence of the canopy environment. A microclimate tower was installed with two weather stations to obtain an analysis of the variation of the climatic attributes above and below the canopy. The results indicate that global solar radiation had an average transmissivity of 26.8%. The air temperature at 10 m was higher than that at the sensor at 2 m. The average rainfall interception for the mangrove environment was 19.6%. Both the maximum gust and average wind speed decreased by approximately 63.7% at 2 m. The mangrove canopy was found to be an important control on the variation of climatic attributes. On a microclimatic scale, the climate attributes had a direct influence on the spatial distribution of vegetation. Additionally, characteristics of the canopy are the main control for this variation, especially for the distribution of rainfall and the amount of solar radiation below the canopy, which influence the distribution of plant species in the environment.

scholarly journals Adapting River Bridge Infrastructures To Climate Change

2021 ◽  
Author(s):  
Akinola Ifelola
Keyword(s):  
Climate Change ◽  
Stream Velocity ◽  
Climate Change Scenarios ◽  
Average Wind Speed ◽  
Southern Ontario ◽  
Ottawa River ◽  
Air Temperatures ◽  
Average Wind ◽  
The Impact

Climate change forecasts project up to 20% increase in precipitation for southern Ontario based on several climate change scenarios and models and an unpredictable change an average wind speed that may range from 5% reduction to 15% increase by the year 2100 compared to 1971 to 2000 reference period. Average annual air temperatures are predicted to increase between 2.5 and 3.7°C by 2050 from baseline average between 1961 and 1990. This research studied the impact of climate change on bridge infrastructure using the Portage bridge on the Ottawa river in southern Ontario as a case study. Result shows that increase in precipitation due to climate change will cause 0.3m/s increase in stream velocity and about 0.85m increase in water level for a 100-year storm. This increase will result in scour depths at bridge piers to increase by 0.86 m while bending moments on piers increased by 21 kNm. Shear forces also increased by 43 kN.

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