Surface air temperature in the Canadian Arctic: scaling and pattern change

Suteanu, Cristian; Mandea, Mioara

doi:10.1007/s00703-012-0206-8

Cited by 7 publications

(12 citation statements)

References 46 publications

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“…Differences in exponent values compared to SUTEANU and MANDEA (2012), however, seem to be mainly explained by the selection of the scaling interval for the determination of the exponent. In most cases, minimum temperature time series have higher persistence than maximum temperature, in agreement with other studies (KIRALY et al 2006;SUTEANU 2011;SUTEANU and MANDEA 2012).…”

Section: Results Concerning Scaling Aspectssupporting

confidence: 80%

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Statistical Variability and Persistence Change in Daily Air Temperature Time Series from High Latitude Arctic Stations

Suteanu

2014

Pure Appl. Geophys.

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In the last decades, Arctic communities have been reporting that weather conditions are becoming less predictable. Most scientific studies have not been able to consistently confirm such a trend. The question regarding the possible increase in weather variability was addressed here based on daily minimum and maximum surface air temperature time series from 15 high latitude Arctic stations from Canada, Norway, and the Russian Federation. A range of analysis methods were applied, distinguished mainly by the way in which they treat time scale. Statistical L-moments were determined for temporal windows of different lengths. While the picture provided by L-scale and L-kurtosis is not consistent with an increasing variability, L-skewness was found to change towards more positive values, reflecting an enhancement of warm spells. Haar wavelet analysis was applied both to the entire time series and to running windows. Persistence diagrams were generated based on running windows advancing through time and on local slopes of Haar analysis graphs; they offer a more nuanced view on variability by reflecting its change over time on a range of temporal scales. Local increases in variability could be identified in some cases, but no consistent change was detected in any of the stations over the studied temporal scales. The possibility for other intervals of temporal scale (e.g., days, hours, minutes) to potentially reveal a different situation cannot be ruled out. However, in the light of the results presented here, explanations for the discrepancy between variability perception and results of pattern analysis might have to be explored using an integrative approach to weather variables such as air temperature, cloud cover, precipitation, wind, etc.

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Section: Results Concerning Scaling Aspectssupporting

confidence: 80%

“…To this end we applied the same methodology to running windows. The window length proved not to have a substantial impact on the outcome of this analysis, as was also the case in WALSH et al (2005) andMANDEA (2012). Results for 7-year long windows shifted by one year are presented here.…”

Section: Results Concerning Scaling Aspectsmentioning

confidence: 77%

Statistical Variability and Persistence Change in Daily Air Temperature Time Series from High Latitude Arctic Stations

Suteanu

2014

Pure Appl. Geophys.

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“…On the other hand, all other analyses, irrespective of scale, indicate fBm, with the exception of the intraday scales portion of the DFA, which indicates persistent fBm.with α > 1.5 (the value for Brownian motion) The SA yields α ≈ 1.4 for all scales; DFA for day-month scales yields α = 1.38 but for intraday scales α = 1.63. The overall result is not surprising, however, because although a number of similar analyses hitherto have found persistent fGn with H between~0.6 and~0.8 [Bunde and Havlin, 2002;Királi and Jánosi, 2005;Suteanu and Mandea, 2012;Varotsos et al, 2013], these analyses used long time series at coarser temporal resolution to investigate, e.g., the presence of long-term memory. Strangely, classification as fGn or fBm, persistent or antipersistent does not seem to be the norm, so the figures in the aforementioned references must be examined individually, this being the basis for positioning of the annotation in Figure 7.…”

Section: Discussionmentioning

confidence: 71%

Complexity signatures for short time scales in the atmosphere above Adventdalen, Svalbard

Hall

2014

JGR Atmospheres

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Atmospheric parameters from the troposphere above Adventdalen, Svalbard, 78°N, 16°E, are examined for signatures of complexity in their respective stochastic components over time scales from~1 h to 1 year. Several approaches are used, all of which can estimate values of the generalized Hurst exponent, α, which can in turn be compared with each other and with similar independent characterizations, usually via the classic Hurst exponent, H, obtained from location-specific and globally averaged time series. For tropopause altitude, the stochastic component exhibits the signature of a persistent fractional Gaussian noise (fGn) with α ≈ 0.75. For surface air temperature, the indications are for fractional Brownian motion (fBm) with α ≈ 1.4. Using recent high time-resolution data from a single high-latitude location, this identification of fBm is relevant for short-term memory as opposed to findings from many other studies addressing possible long-term memory, which demonstrate fGn with α = H ≈ 0.7. Furthermore, the lack of similarity between the results for surface air temperature and tropopause altitude suggests that different underlying processes are responsible for stochastic variability.

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“…When sunlight is present, the maximum temperature occurs around ~12 to ~15 UT (i.e., approximately 14 local time). It is not, however, a goal here to study surface air temperature variation per se (e.g., see the modern approach of Suteanu and Mandea [] and references therein), but rather to compare these local intraday values to the corresponding tropopause response as was done for intra‐annual timescales by Hall et al . [] previously.…”

Section: Results: Surface Air Temperaturesmentioning

confidence: 99%

The radar tropopause at 78°N, 16°E: Characteristics of diurnal variation

Hall

2013

JGR Atmospheres

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[1] A continuous 5 year time series of tropopause altitude made by the SOUSY VHF radar on Svalbard (78°N, 16°E) is examined for diurnal variation. The data have a nominal time resolution of 1 h, allowing for investigation of intraday timescales not normally possible using radiosonde observations. Periodicities identified in tropopause altitude are found to vary with season. Surface air temperature measurements naturally exhibit diurnal variations which depend on season: however, it is demonstrated that, using a simple scenario of constant adiabatic lapse rate in the troposphere, the tropopause altitude variation that might be anticipated from that of the surface air temperature is not in agreement with the radar observation. Of several mechanisms that could be postulated for this discrepancy, it is demonstrated that a likely candidate is intraday top-down forcing from the stratosphere.

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Surface air temperature in the Canadian Arctic: scaling and pattern change

Cited by 7 publications

References 46 publications

Statistical Variability and Persistence Change in Daily Air Temperature Time Series from High Latitude Arctic Stations

Statistical Variability and Persistence Change in Daily Air Temperature Time Series from High Latitude Arctic Stations

Complexity signatures for short time scales in the atmosphere above Adventdalen, Svalbard

The radar tropopause at 78°N, 16°E: Characteristics of diurnal variation

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