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.

scholarly journals <i>Brief communication</i> "A statistical validation for the cycles found in air temperature data using a Morlet wavelet-based method"

2010 ◽  
Vol 17 (3) ◽  
pp. 269-272 ◽  
Author(s):  
S. Nicolay ◽  
G. Mabille ◽  
X. Fettweis ◽  
M. Erpicum
Keyword(s):  
Air Temperature ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Weather Forecast ◽  
Temperature Data ◽  
Temperature Time Series ◽  
Climatic Data ◽  
Statistical Validation ◽  
Confidence Levels ◽  
Temperature Time

Abstract. Recently, new cycles, associated with periods of 30 and 43 months, respectively, have been observed by the authors in surface air temperature time series, using a wavelet-based methodology. Although many evidences attest the validity of this method applied to climatic data, no systematic study of its efficiency has been carried out. Here, we estimate confidence levels for this approach and show that the observed cycles are significant. Taking these cycles into consideration should prove helpful in increasing the accuracy of the climate model projections of climate change and weather forecast.

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
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