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

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.

Noise Mapping ◽  
2020 ◽  
Vol 7 (1) ◽  
pp. 135-145 ◽  
Author(s):  
Stjepan Piličić ◽  
Igor Kegalj ◽  
Eirini Tserga ◽  
Teodora Milošević ◽  
Roberto Žigulić ◽  
...  

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.


2012 ◽  
Vol 610-613 ◽  
pp. 1033-1040
Author(s):  
Wei Dai ◽  
Jia Qi Gao ◽  
Bo Wang ◽  
Feng Ouyang

Effects of weather conditions including temperature, relative humidity, wind speed, wind and direction on PM2.5 were studied using statistical methods. PM2.5 samples were collected during the summer and the winter in a suburb of Shenzhen. Then, correlations, hypothesis test and statistical distribution of PM2.5 and meteorological data were analyzed with IBM SPSS predictive analytics software. Seasonal and daily variations of PM2.5 have been found and these mainly resulted from the weather effects.


2020 ◽  
Author(s):  
Hemant Kulkarni ◽  
Harshwardhan Vinod Khandait ◽  
Uday Wasudeorao Narlawar ◽  
Pragati G Rathod ◽  
Manju Mamtani

Whether weather plays a part in the transmissibility of the novel COronaVIrus Disease-19 (COVID-19) is still not established. We tested the hypothesis that meteorological factors (air temperature, relative humidity, air pressure, wind speed and rainfall) are independently associated with transmissibility of COVID-19 quantified using the basic reproduction rate (R0). We used publicly available datasets on daily COVID-19 case counts (total n = 108,308), three-hourly meteorological data and community mobility data over a three-month period. Estimated R0 varied between 1.15-1.28. Mean daily air temperature (inversely) and wind speed (positively) were significantly associated with time dependent R0, but the contribution of countrywide lockdown to variability in R0 was over three times stronger as compared to that of temperature and wind speed combined. Thus, abating temperatures and easing lockdown may concur with increased transmissibility of COVID-19.


2018 ◽  
Vol 64 (243) ◽  
pp. 89-99 ◽  
Author(s):  
JIZU CHEN ◽  
XIANG QIN ◽  
SHICHANG KANG ◽  
WENTAO DU ◽  
WEIJUN SUN ◽  
...  

ABSTRACTWe analyzed a 2-year time series of meteorological data (January 2011–December 2012) from three automatic weather stations on Laohugou glacier No. 12, western Qilian Mountains, China. Air temperature, humidity and incoming radiation were significantly correlated between the three sites, while wind speed and direction were not. In this work, we focus on the effects of clouds on other meteorological parameters and on glacier melt. On an average, ~18% of top-of-atmosphere shortwave radiation was attenuated by the clear-sky atmosphere, and clouds attenuated a further 12%. Most of the time the monthly average increases in net longwave radiation caused by clouds were larger than decreases in net shortwave radiation but there was a tendency to lose energy during the daytime when melting was most intense. Air temperature and wind speed related to turbulent heat flux were found to suppress glacier melt during cloudy periods, while increased water vapor pressure during cloudy days could enhance glacier melt by reducing energy loss by latent heat. From these results, we have increased the physical understanding of the significance of cloud effects on continental glaciers.


2019 ◽  
Vol 84 ◽  
pp. 01001
Author(s):  
Paweł Piotrowski ◽  
Dariusz Baczyński ◽  
Marcin Kopyt ◽  
Karolina Szafranek

The most important factor responsible for the quality of energy production forecasts in wind farms is the accurate wind speed forecast. An extensive statistical analysis of meteorological data (NWP) from 16 base nodes of the "300" grid in the "Łódź" area was made. The intention of the statistical analysis was to select potential explanatory variables for models predicting wind speed in the remaining 206 nodes of the grid’s mesh. Next, tests of selected prognostic methods were performed in order to compare their effectiveness with bilinear method which is not computationally complex. It should be emphasized that the main problem in spatial wind speed forecasting is the very large number of nodes for which the forecasts are calculated. As a consequence, more advanced and computationally complex forecasting methods cannot be applied in practice due to too long calculations time and difficulties in huge amounts of data processing. Conclusions with proposals of preferred forecasting methods that could be used in practice were developed.


2018 ◽  
Vol 40 ◽  
pp. 20
Author(s):  
Mauren Lucila Marques de Morais Micalichen ◽  
Nelson Luís da Costa Dias

The use of alternative sources of meteorological data has become increasingly common, making it possible to evaluate areas with no long or continuous series of meteorological data. In this context, the main objective of this study is to evaluate the performance of data series from the National Centers for Environmental Prediction / National Center for Atmospheric Research (NCEP/NCAR) for the state of Minas Gerais and verify the possible use of them in the absence of data observations of air temperature and wind speed. The analyzes were performed by comparing observation data from 17 meteorological stations and reanalysis data of the CFSR and CFSV2 models. From the results of the statistical analysis, it is observed that the air temperature reanalysis data presented a good performance in the region of study. However, wind speed data show a weak correlation. These results show that the air temperature data from these reanalyses have the potential to be used as an alternative source of data. Further studies are suggested regarding the use of wind speed data from these reanalyses.


2021 ◽  
Vol 25 (2) ◽  
pp. 60-65
Author(s):  
S.A. Kurolap ◽  
V.S. Petrosyan ◽  
O.V. Klepikov ◽  
V.V. Kulnev ◽  
D.Yu. Martynov

Based on the analysis of official statistics from the Voronezh Hydrometeorological Service, the patterns of the dynamics of pollutants (formaldehyde and soot) are investigated depending on the combination of various meteorological parameters — air temperature, wind speed, relative air humidity. A positive relationship has been established between the increase in atmospheric pollution with formaldehyde and air temperature. With increasing wind speed and relative humidity, the concentration of formaldehyde and soot in the atmosphere of the city, as a rule, decrease. The maximum permissible level of carcinogenic risk to public health has been established, causing concern. The obtained patterns can be used to predict the level of technogenic pollution of the city’s atmosphere, depending on meteorological conditions.


2020 ◽  
Author(s):  
Philippe Gatien

<p>Water temperature modelling has become an essential tool in the management of ectotherm species downstream of dams in North American rivers. The main objective of this project is to compare different datasets and their ability to adequately simulate water temperatures in the Nechako River, (B.C., Canada) downstream of a major dam where the flow is not managed for hydroelectric production, but spills are programmed to cool the downstream reaches. This will ultimately lead to a reassessment of water management in the context of climate change to ensure the survival of fish migrating or living in the reaches located downstream of the dam during warm periods.</p><p>Water in the Nechako River stems from the Nechako reservoir at the Skins lake spillway and flows into river through a series of lakes prior to reaching Finmoore, where federal regulations stipulate that water temperatures must be maintained below 20 °C. The river has multiple tributaries on it’s 250 km journey including the Nautley river. The river flow is simulated using a 1D unsteady flow simulation and lateral inflows using HEC-RAS.</p><p>Water temperature simulations are then conducted using different datasets. The first is a series of observed meteorological data spanning from 2017 to present day from two different weather stations near the river. The second dataset is ERA5, a reanalysis product that’s gridded every 0.25°. Eleven stations nearest to the river were extracted over the same period as the observations. Both datasets were used to calibrate five parameters (dust coefficient, three wind function parameters and the Richardson number) three times using the mean absolute error (MAE), Nash-Sutcliffe coefficient (NS) and root mean squared error (RMSE) by comparing the observed and simulated temperatures near Finmoore.</p><p>Individual calibrations were performed over each available summer from early June to late August and then validated over the rest of the data to ensure the robustness of the results.</p><p>Overall, the reanalysis dataset outperformed the available observations for thermal representation of the river.</p><p>To further understand the thermal model, a sensitivity analysis was performed on the different inputs (inflow water temperature, air temperature, wind speed, etc.). The model showed very little sensitivity to the characteristics of the inflow (temperature, volume) as the point of interest was so far downstream. In fact, environmental factors such as air temperature had a greater impact on water temperature than upstream conditions at the reservoir spillway. This effect seems to be mostly attributable to Cheslatta Lake with its long water residence time that can reach upwards of three days.</p><p>The potential effects of climate change on water temperature were then investigated by modifying existing weather data like air temperature with the delta method on a monthly basis using the RCP8.5 emission scenario. Water temperatures increased throughout by roughly 2.5°C downstream, near Finmoore.</p><p> </p>


2017 ◽  
Vol 56 (4) ◽  
pp. 937-952 ◽  
Author(s):  
XiaoJuan Yang ◽  
Yuan Liu ◽  
Wei Bai ◽  
BuChun Liu

AbstractDrought is a typical disaster in the main soybean production area of northeast China. The spatiotemporal variations of drought related to soybean production based on a crop water deficit index (CWDI) and sensitivity to meteorological variables were investigated in northeast China using daily meteorological data from 87 weather stations from 1981 to 2010. Statistical analysis revealed that precipitation could not meet the water demands of soybeans during the seedling–branching, filling, and maturing stages, and excessive drought occurred more often in northeast China. The Mann–Kendall test indicated that the soybean CWDI significantly increased during the filling stage. Kriging spatial analysis showed that the most drought-prone area was located in the west of northeast China. Explanations for the spatiotemporal variations of the drought for soybean production were explored in terms of meteorological variables. Statistical analysis showed that the crop evapotranspiration, air temperature, wind speed, and number of sunshine hours were significantly higher and the precipitation and relative humidity were significantly lower in the drought-prone area than in the dry area less prone to droughts. An explored method of sensitive analysis quantitatively revealed that precipitation and humidity negatively affected the CWDI, whereas temperature, wind speed, and number of sunshine hours positively affected the CWDI. The CWDI was most sensitive to precipitation. These results not only provide valuable information for soybean planning and management but also produce important background and physical evidence for the influence of climate on the drought related to soybean production in northeast China.


2012 ◽  
Vol 512-515 ◽  
pp. 2543-2548
Author(s):  
Li Chun Zhang ◽  
Kuan Jun Zhu

Galloping is one of the gravely natural disasters witch put a significant threat to Grid security and stability. In this paper, a comprehensive, systematic research and analysis about transmission line galloping in China in recent years was done. Laws and characteristics of galloping disaster was analyzed in many aspects, including time and place that the galloping occurred, name of transmission line, voltage and structural parameters of line, meteorological data (air temperature, wind speed, ice, etc. ),the topography information where the transmission line located , the duration of galloping, and the destruction forms coursed by galloping. This work provides an important research reference not only for anti-galloping methods but enhancing the ability of withstanding natural disasters in Grid.


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