Features of the Spatiotemporal Variability of the Advective Heat Transfer in the Troposphere over the Pacific and Atlantic Oceans in the Northern Hemisphere for 1979–2018

Moraru, E. I.; Логинов, С. В.; Kharyutkina, E. V.

doi:10.1134/s000143382105011x

Cited by 2 publications

(5 citation statements)

References 9 publications

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“…Statistically significant fluctuations are mainly distinguished in the warm season at periods of 7 to 8 years, while shorter-period fluctuations also appear in the extreme values series. It should be noted that revealed periodicities can be caused by dynamic processes in the atmosphere described by global atmospheric mechanisms, such as North Atlantic Oscillation (NAO), Atlantic Multidecadal Oscillation (AMO), and South Oscillation (El Niño), where this periodicity (7-9 years) is also observed in their time series [33]. We suppose that this fact will be useful for the construction of climatic projections.…”

Section: Discussionmentioning

confidence: 83%

Time Series Analysis of Atmospheric Precipitation Characteristics in Western Siberia for 1979–2018 across Different Datasets

et al. 2022

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A comparative statistical analysis of the spatiotemporal variability of atmospheric precipitation characteristics (mean and extreme values) in Western Siberia was performed based on data acquired from meteorological stations, global precipitation datasets such as the project of Asian Precipitation—Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE) and from Global Precipitation Climatology Centre (GPCC), and reanalysis archives, including from National Centers of Environmental Prediction (NCEP-DOE) and the European Center for Medium Range Weather Forecasts (ERA5) for the period 1979–2018. The best agreement of the values from the observational data was observed with the values from GPCC. This archive also represented the periodicities in the time series of observational data from meteorological stations, especially in the short-period part of the spectrum. Underestimated values were revealed for the APHRODITE archive, while overestimated ones were found for the NCEP reanalysis data. In comparison with GPCC, the ERA5 dataset reproduced the general variability but with a smaller amplitude (the correlation coefficient was up to 0.9). In general, the median estimates of the precipitation amount derived from the meteorological stations’ data, as well from the reanalysis data, were in better agreement with each other rather than their extreme values. However, their temporal variability can be effectively described by other datasets.

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Section: Discussionmentioning

confidence: 83%

Time Series Analysis of Atmospheric Precipitation Characteristics in Western Siberia for 1979–2018 across Different Datasets

et al. 2022

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“…According to our study's results, these regions are characterized by the maximum number of specific humidity anomalies and the horizontal and vertical components of wind speed (as shown in Figures 4 and 5). This suggests that the changes in anomalies, as well as their PDFs, may be associated with advective and convective transfer of heat and moisture [9,31].…”

Section: Discussionmentioning

confidence: 99%

“…In this context, atmospheric circulation becomes a significant climate-forming factor. This is because air masses, while passing over areas of intense heat and moisture exchange, undergo transformation and transport heat and moisture to the continents, thus affecting climate variability [31].…”

Section: Discussionmentioning

confidence: 99%

“…The type of PDF anomalies for each parameter depends on various factors such as atmospheric processes, season, and region [9,31]. To identify the distribution types, the PDFs were calculated for each reanalysis node within the following latitudinal zones: low-0-30 • N, medium-31-60 • N and high-61-90 • N. Three PDF types were distinguished for all the considered parameters and their anomalies.…”

Section: Types Of Probability Distribution Densitiesmentioning

confidence: 99%

“…However, significant deviations from the normal distribution were revealed in the regions of baroclinic disturbances generation over the western parts of ocean in the mid-latitudes [27,28] and the maximal deviations were marked when the anomalies exceeded 3σ [22]. A leading role in the formation of areas with extreme "warm" temperatures around the globe belongs to advection, storm tracks, jet streams, centers of atmospheric action and atmospheric blockings [12,15,[30][31][32].…”

Section: Introductionmentioning

confidence: 99%

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Climatology of Synoptic Non-Gaussian Meteorological Anomalies in the Northern Hemisphere during 1979–2018

Loginov,

Moraru,

Kharyutkina

et al. 2024

Climate

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The analysis of spatial and temporal variability in the number of non-Gaussian extreme anomalies of climatic parameters was carried out for both the initial time series and synoptic variability in the troposphere of the Northern Hemisphere over the period 1979–2018, based on ERA-Interim reanalysis data. There are predominantly three types of empirical distribution densities at 850 hPa, each characterizing the processes of advective and convective heat transfer. At the beginning of the 21st century, compared to the end of the 20th century, there was an increase in the number of anomalies in vertical wind speed and specific humidity for the Northern Hemisphere. Additionally, there is an increase in the number of zonal wind speed anomalies in the low and middle latitudes. Regions with the maximum number of anomalies are primarily located over the continents, while for vertical wind speed anomalies, they are predominantly over the oceans. The application of R/S analysis and multifractal analysis has established that the identified tendencies (which are persistent processes) will continue in the identified regions. The time series of non-Gaussian anomalies (both initial and synoptic scales) exhibit a long-term memory of approximately four years, and synoptic extreme anomalies were found to be more predictable.

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Features of the Spatiotemporal Variability of the Advective Heat Transfer in the Troposphere over the Pacific and Atlantic Oceans in the Northern Hemisphere for 1979–2018

Cited by 2 publications

References 9 publications

Time Series Analysis of Atmospheric Precipitation Characteristics in Western Siberia for 1979–2018 across Different Datasets

Time Series Analysis of Atmospheric Precipitation Characteristics in Western Siberia for 1979–2018 across Different Datasets

Climatology of Synoptic Non-Gaussian Meteorological Anomalies in the Northern Hemisphere during 1979–2018

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