scholarly journals Updated Moving Forecasting Model of Air Maximum Temperature

2021 ◽  
Vol 877 (1) ◽  
pp. 012032
Author(s):  
Khalid Hashim ◽  
Hussein Al-Bugharbee ◽  
Salah L. Zubaidi ◽  
Nabeel Saleem Saad Al-Bdairi ◽  
Sabeeh L. Farhan ◽  
...  
Keyword(s):  
Time Series ◽  
Air Temperature ◽  
High Performance ◽  
Training Sample ◽  
Temperature Time Series ◽  
Ar Model ◽  
Maximum Temperature ◽  
Forecasting Model ◽  
Temperature Time ◽  
Maximum Air Temperature

Abstract In the current study, a moving forecasting model is used for the purpose of forecasting maximum air temperature. A number of recordings are used for building the AR model and next, to forecasting some temperature values ahead. Then the AR model coefficients are updating due to shifting the training sample by adding new temperature values in order to involve the change in temperature time series behaviour. The current work shows a high performance all over the temperature time series, which considered in the analysis.

scholarly journals Non-stationary temporal characterization of the temperature profile of a soil exposed to frost in south-eastern Canada

2008 ◽  
Vol 15 (3) ◽  
pp. 409-416 ◽  
Author(s):  
F. Anctil ◽  
A. Pratte ◽  
L. E. Parent ◽  
M. A. Bolinder
Keyword(s):  
Time Series ◽  
Soil Temperature ◽  
Temperature Profile ◽  
Air Temperature ◽  
Soil Depth ◽  
Time Lag ◽  
Power Spectra ◽  
Temperature Time Series ◽  
Soil Temperatures ◽  
Temperature Time

Abstract. The objective of this work was to compare time and frequency fluctuations of air and soil temperatures (2-, 5-, 10-, 20- and 50-cm below the soil surface) using the continuous wavelet transform, with a particular emphasis on the daily cycle. The analysis of wavelet power spectra and cross power spectra provided detailed non-stationary accounts with respect to frequencies (or periods) and to time of the structure of the data and also of the relationships that exist between time series. For this particular application to the temperature profile of a soil exposed to frost, both the air temperature and the 2-cm depth soil temperature time series exhibited a dominant power peak at 1-d periodicity, prominent from spring to autumn. This feature was gradually damped as it propagated deeper into the soil and was weak for the 20-cm depth. Influence of the incoming solar radiation was also revealed in the wavelet power spectra analysis by a weaker intensity of the 1-d peak. The principal divergence between air and soil temperatures, besides damping, occurred in winter from the latent heat release associated to the freezing of the soil water and the insulation effect of snowpack that cease the dependence of the soil temperature to the air temperature. Attenuation and phase-shifting of the 1-d periodicity could be quantified through scale-averaged power spectra and time-lag estimations. Air temperature variance was only partly transferred to the 2-cm soil temperature time series and much less so to the 20-cm soil depth.

scholarly journals Uncertainty evaluation of Climatol ' s adjustment algorithm applied to daily air temperature time series

2020 ◽  
Author(s):  
Oleg Skrynyk ◽  
Enric Aguilar ◽  
Jose Guijarro ◽  
Luc Yannick Andreas Randriamarolaza ◽  
Sergiy Bubin
Keyword(s):  
Time Series ◽  
Air Temperature ◽  
Temperature Time Series ◽  
Uncertainty Evaluation ◽  
Temperature Time

scholarly journals Modeling ambient air temperature time series using neural networks

1998 ◽  
Vol 103 (D16) ◽  
pp. 19509-19517 ◽  
Author(s):  
G. Mihalakakou ◽  
M. Santamouris ◽  
D. Asimakopoulos
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Air Temperature ◽  
Ambient Air ◽  
Temperature Time Series ◽  
Ambient Air Temperature ◽  
Temperature Time

Relationship between heating/cooling period and changing temperature conditions in the urban areas of Hungary

2020 ◽  
Author(s):  
Csenge Dian ◽  
Attila Talamon ◽  
Rita Pongrácz ◽  
Judit Bartholy
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Energy Consumption ◽  
Extreme Values ◽  
Building Design ◽  
Temperature Time Series ◽  
Maximum Temperature ◽  
Design Parameters ◽  
Daily Average ◽  
Temperature Time

<p>Climate change, extreme weather conditions, and local scale urban heat island (UHI) effect altogether have substantial impacts on people’s health and comfort. The urban population spends most of its time in buildings, therefore, it is important to examine the relationship between weather/climate conditions and indoor environment. The role of buildings is complex in this context. On the one hand UHI effect is mostly created by buildings and artificial surfaces. On the other hand they account for about 40% of energy consumption on European average. Since environmental protection requires increased energy efficiency, the ultimate goal from this perspective is to achieve nearly zero-energy buildings. When estimating energy consumption, daily average temperatures are taken into account. The design parameters (e.g. for heating systems) are determined using temperature-based criteria. However, due to climate change, these critical values are likely to change as well. Therefore, it is important to examine the temperature time series affecting the energy consumption of buildings. For the analysis focusing on the Carpathian region within central/eastern Europe, we used the daily average, minimum and maximum temperature time series of five Hungarian cities (i.e. Budapest, Debrecen, Szeged, Pécs and Szombathely). The main aim of this study is to investigate the effect of changing daily average temperatures and the rising extreme values on building design parameters, especially heating and cooling periods (including the length and average temperatures of such periods).</p>

scholarly journals Spatial and Temporal Distribution of Air Temperature in the Northern Hemisphere

2013 ◽  
Vol 6 (3) ◽  
pp. 177-182
Keyword(s):  
Time Series ◽  
20Th Century ◽  
Northern Hemisphere ◽  
Air Temperature ◽  
Temporal Distribution ◽  
Surface Air Temperature ◽  
Temperature Time Series ◽  
Mean Values ◽  
The Mean ◽  
Temperature Time

In the present study, the spatial and temporal surface air temperature variability for the Northern Hemisphere has been examined, for the period 1900-1996. Factor Analysis has been applied to 5o Latitude x 10o Longitude grid box data covering the area from almost the equator to 70o N. These data are anomalies of the mean annual air temperature from the respective mean values of the period 1961- 1990. The analysis showed that, mainly 20 regions were determined in the Northern Hemisphere with significantly covariant air temperature time series. The comparison of the trends of the mean annual surface air temperature time series of these regions, revealed such common characteristics as the minimum of the first decade of the 20th century and the recent years warming. The results of this study are also compared to the respective results of a former study in which data for the last half of the century (1948-1996) have been analyzed. The findings extracted indicate the stability of climate distribution in Northern Hemisphere during the 20th century.

Multi-Fractal Analy is of Daily Air Temperature Time Series in Coastal Areas of China

2020 ◽  
Vol 26 (3) ◽  
pp. 348-362
Author(s):  
LI Zhong-liang ◽  
HE Guang-xin ◽  
SHEN Wei-shou ◽  
ZHEN Xiao-ju ◽  
HAN Jing
Keyword(s):  
Time Series ◽  
Air Temperature ◽  
Coastal Areas ◽  
Temperature Time Series ◽  
Temperature Time
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