Modeling of air temperatures using a combination of TBATS and SVM models for various climatic locations in Europe

2020 ◽  
Author(s):  
Magdalena Gos ◽  
Piotr Baranowski ◽  
Jaromir Krzyszczak ◽  
Małgorzata Murat ◽  
Iwona Malinowska
Keyword(s):  
Time Series ◽  
State Space ◽  
Air Temperature ◽  
Weather Conditions ◽  
Exponential Smoothing ◽  
Climatic Conditions ◽  
State Space Models ◽  
Temperate Climate ◽  
Support Vector ◽  
Air Temperatures

<p>By modelling and forecasting  of meteorological  time  series it is possible to  improve   understanding  of  the  weather dynamics and fluctuations as a result of climate change . The most frequently used forecasting models are exponential smoothing, ARIMA models (Box and Jenkins, 1970), state-space models (Harvey, 1989) and innovations State Space Models (Hyndman et al., 2008).</p><p>The aim of this study was to check the effectiveness of the coupled TBATS and Support Vector Machines (SVM) model, supplied with some measured meteorological quantities to forecast air temperature for six years for four climatic localizations in Europe. The study was calculated from northern (Jokioinen in Finland), central (Dikopshof located in the west part of Germany and Nossen in the south part of Germany) and southern (Lleida in Spain) Europe to present different climatic conditions. Jokioinen city has a subarctic climate that has severe winters, with cool and short summers and strong seasonality. Lleida has a semi-arid climate with Mediterranean. Dikopshof represents maritime temperate climate. There are significant precipitation throughout the year in Dikopshof and Nossen. In the study we study on air temperature dataset collected on a daily basis from January 1st 1980 to December 31st 2010 (11322 days).</p><p>For all the studied sites coupled TBATS/SVM models occurred to be effective in predicting air temperature courses, giving an improved precision (up to 25%) in forecasting of the seasonality and local temperature variations, compared to pure SVM or TBATS modelling. The precision of prediction of the maximum and minimum air temperatures strongly depended on the dynamics of the weather conditions, and varied for different climatic zones.</p><p>This study has been partly financed from the funds of the Polish National Centre for Research and Development in frame of the project: MSINiN, contract number: BIOSTRATEG3/343547/8/NCBR/2017.</p><p> </p><p>Reference to a journal publication:</p><p>BOX, G.E.P. – Jenkins, G. 1970. Time Series Analysis: forecasting and control. Holden-Day, p. 20-31.</p><p>HARVEY A. 1989. Forecasting Structural Time Series Model and the Kalman Filter. New York, Cambridge University press., p. 32-41.</p><p>HYNDMAN, R.J. – KOEHLER, A.B. – ORD, J.K. – SNYDER, R.D. 2008. Forecasting with Exponential Smoothing: The State Space Approach. Springer-Verlag, p. 50-62.</p>

scholarly journals Quantifying the Independent Influences of Land Cover and Humidity on Microscale Urban Air Temperature Variation in Hot Summer: Methods of Path Analysis and Genetic SVR

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1377
Author(s):  
Weifang Shi ◽  
Nan Wang ◽  
Aixuan Xin ◽  
Linglan Liu ◽  
Jiaqi Hou ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Land Cover ◽  
Path Analysis ◽  
Temperature Variation ◽  
Direct Effect ◽  
Air Temperature ◽  
Urban Areas ◽  
Support Vector ◽  
Urban Air ◽  
Air Temperatures

Mitigating high air temperatures and heat waves is vital for decreasing air pollution and protecting public health. To improve understanding of microscale urban air temperature variation, this paper performed measurements of air temperature and relative humidity in a field of Wuhan City in the afternoon of hot summer days, and used path analysis and genetic support vector regression (SVR) to quantify the independent influences of land cover and humidity on air temperature variation. The path analysis shows that most effect of the land cover is mediated through relative humidity difference, more than four times as much as the direct effect, and that the direct effect of relative humidity difference is nearly six times that of land cover, even larger than the total effect of the land cover. The SVR simulation illustrates that land cover and relative humidity independently contribute 16.3% and 83.7%, on average, to the rise of the air temperature over the land without vegetation in the study site. An alternative strategy of increasing the humidity artificially is proposed to reduce high air temperatures in urban areas. The study would provide scientific support for the regulation of the microclimate and the mitigation of the high air temperature in urban areas.

scholarly journals Identification of solar radiation effect on climatic indicators of the territory of Ukraine

2018 ◽  
Keyword(s):  
Solar Radiation ◽  
Solar Energy ◽  
Air Temperature ◽  
Temperature Regime ◽  
Atmospheric Pressure ◽  
Weather Conditions ◽  
Climatic Conditions ◽  
Practical Significance ◽  
Statistical Dependence ◽  
Physical Processes

Formulation of the problem. Understanding that solar energy is the main source of the majority of biological, chemical and physical processes on Earth, investigation of its influence on different climatic fields allows us to define the features of its space and hour fluctuations. To define radiation and temperature regime of the territory it is necessary to determine climatic features of the spreading surface, which absorbs and will transform solar energy. Considering the fact that modern climatic changes and their consequences cover all components of the system, today there is a problem of their further study for comprehension of atmospheric processes, modeling weather conditions on different territories depending on the properties. The purpose of the article is to determine interrelations between indexes of solar radiation (the Wolf's number) and air temperature, atmospheric pressure on the territory of Ukraine during 1965-2015, their change in space and time. Methods. Correlative method is one of the main methods of a statistical analysis which allows us to receive correlation coefficients of solar radiation variability indexes, air temperature, atmospheric pressure on the territory of the research. This technique estimates the extent of solar radiation influence on temperature regime of the territory and distribution of atmospheric pressure. Results. Coefficients of correlation, which characterize variability of solar radiation indexes, air temperature and atmospheric pressure on the explored territory have been received by means of statistical correlation analysis method. This technique allows us to estimate the degree and nature of solar radiation influence on a temperature regime of the territory and distribution of atmospheric pressure. It has been defined that direct correlative connection between indexes of solar radiation is characteristic of air temperature and atmospheric pressure fields. Significant statistical dependence between incoming solar radiation on the territory of Ukraine and atmospheric pressure has been noted during the spring and autumn periods mainly at the majority of stations. Between indexes of solar radiation and air temperature the inverse correlative connection in winter will be transformed to a direct connection during the spring and summer periods. Scientific novelty and practical significance. Physical processes, which happen in the atmosphere, are characterized by complex interrelations. For further research it is important to define solar radiation value and the extent of influence on climatic conditions.

scholarly journals Sea surface temperature variations in the south-eastern BalticSea in 1960–2015

Baltica ◽  
2018 ◽  
Vol 30 (2) ◽  
pp. 75-85 ◽  
Author(s):  
Viktorija Rukšėnienė ◽  
Inga Dailidienė ◽  
Loreta Kelpšaitė-Rimkienė ◽  
Tarmo Soomere
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Air Temperature ◽  
Weather Conditions ◽  
Sea Surface ◽  
South Eastern ◽  
Air Temperatures ◽  
Joint Application ◽  
Open Sea ◽  
And Cluster Analysis

This study focuses on time scales and spatial variations of interrelations between average weather conditions and sea surface temperature (SST), and long-term changes in the SST in south-eastern Baltic Sea. The analysis relies on SST samples measured in situ four times a year in up to 17 open sea monitoring stations in Lithuanian waters in 1960–2015. A joint application of non-metric multi-dimensional scaling and cluster analysis reveals four distinct SST regimes and associated sub-regions in the study area. The increase in SST has occurred during both winter and summer seasons in 1960–2015 whereas the switch from relatively warm summer to colder autumn temperatures has been shifted by 4–6 weeks over this time in all sub-regions. The annual average air temperature and SST have increased by 0.03°C yr–1 and 0.02°C yr–1, respectively, from 1960 till 2015. These data are compared with air temperatures measured in coastal meteorological stations and averaged over time intervals from 1 to 9 weeks. Statistically significant positive correlation exists between the SST and the average air temperature. This correlation is strongest for the averaging interval of 35 days.

The Incidence of Climatic Conditions Favourable to Coffee Berry Disease in Kenya

1971 ◽  
Vol 7 (4) ◽  
pp. 303-314 ◽  
Author(s):  
J. M. Waller
Keyword(s):  
Air Temperature ◽  
Spore Germination ◽  
Growing Season ◽  
Climatic Conditions ◽  
Tree Canopy ◽  
Disease Development ◽  
Spore Dispersal ◽  
Coffee Berry ◽  
Coffee Berry Disease ◽  
Air Temperatures

SUMMARYClimatic conditions affecting the development of CBD are assessed by measuring wetness within the tree canopy and air temperature. Saturation of the tree canopy, necessary for spore dispersal, occurs most frequently at the tops of trees and the duration of wetness permitting spore germination is most prolonged at night. Night air temperatures are closest to berry temperatures and are important in assessing infection periods. Disease development in 1968 and 1969 was related to the number of infection periods during the growing season. Polythene tree covers which kept trees sufficiently dry to stop disease development were used in determining infection at different times of the year.

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