Search Results
Abstract
This article investigates the prominent features of the Southern Hemisphere (south of 20°S) atmospheric circulation when extracted using EOF analysis and a k-means clustering algorithm. The focus is on the southern annular mode (SAM), the nature of its recent trend, and the zonal symmetry of associated spatial patterns. The study uses the NCEP–Department of Energy Atmospheric Model Intercomparison Project II Reanalysis (NCEP-2) (period 1979–2009) to obtain robust patterns over the recent years and the Twentieth Century Reanalysis Project (period 1871–2008) to document decadal changes. Also presented is a comparison of these signals against a station-based reconstruction of the SAM index and a gridded interpolated dataset [Hadley Centre Sea Level Pressure dataset version 2 (HadSLP2)].
Over their common period, both reanalyses are in fair agreement, both in terms of spatial patterns and temporal variability. In particular, both datasets show weather regimes that can be interpreted as the opposite phases of the SAM. At the decadal time scale, the study shows that the trend toward the positive SAM phase (as inferred from the usual EOF-based index) is related more to an increase in the frequency of clusters corresponding to the positive phase, with little changes in the frequency of the negative SAM events. Similarly, the long-term tropospheric warming trend already discussed in the literature is shown to be related more to a decrease in the number of abnormally cold days, with little changes in the number of abnormally warm days. The cluster analysis therefore allows for complement descriptions based on simple indexes or EOF decompositions, highlighting the nonlinear nature of the decadal changes in the Southern Hemisphere atmospheric circulation and temperature.
Abstract
This article investigates the prominent features of the Southern Hemisphere (south of 20°S) atmospheric circulation when extracted using EOF analysis and a k-means clustering algorithm. The focus is on the southern annular mode (SAM), the nature of its recent trend, and the zonal symmetry of associated spatial patterns. The study uses the NCEP–Department of Energy Atmospheric Model Intercomparison Project II Reanalysis (NCEP-2) (period 1979–2009) to obtain robust patterns over the recent years and the Twentieth Century Reanalysis Project (period 1871–2008) to document decadal changes. Also presented is a comparison of these signals against a station-based reconstruction of the SAM index and a gridded interpolated dataset [Hadley Centre Sea Level Pressure dataset version 2 (HadSLP2)].
Over their common period, both reanalyses are in fair agreement, both in terms of spatial patterns and temporal variability. In particular, both datasets show weather regimes that can be interpreted as the opposite phases of the SAM. At the decadal time scale, the study shows that the trend toward the positive SAM phase (as inferred from the usual EOF-based index) is related more to an increase in the frequency of clusters corresponding to the positive phase, with little changes in the frequency of the negative SAM events. Similarly, the long-term tropospheric warming trend already discussed in the literature is shown to be related more to a decrease in the number of abnormally cold days, with little changes in the number of abnormally warm days. The cluster analysis therefore allows for complement descriptions based on simple indexes or EOF decompositions, highlighting the nonlinear nature of the decadal changes in the Southern Hemisphere atmospheric circulation and temperature.
Abstract
This paper introduces a set of descriptors applied to weather regimes that allow for a detailed monitoring of the location and intensity of their atmospheric centers of action (e.g., troughs and ridges) and the gradients between them, when applicable. Descriptors are designed to document the effect of climate variability and change in modulating the character of daily weather regimes, rather than merely their occurrence statistics. As a case study, the methodology is applied to Aotearoa New Zealand (ANZ), using ERA5 ensemble reanalysis data for the period 1979–2019. Here, we analyze teleconnections between the regimes and their descriptors and large-scale climate variability. Results show a significant modulation of centers of action by the phase of the southern annular mode, with a strong relationship identified with the latitude of atmospheric ridges. Significant associations with El Niño–Southern Oscillation are also identified. Modes of large-scale variability have a stronger influence on the regimes’ intrinsic features than their occurrence. This demonstrates the usefulness of such descriptors, which help explain the relationship between midlatitude transient perturbations and large-scale modes of climate variability. In future research, this methodological framework will be applied to analyze (i) low-frequency changes in weather regimes under climate change, in line with the southward shift of storm tracks, and (ii) regional-scale effects on the climate of ANZ, resulting from interaction with its topography.
Abstract
This paper introduces a set of descriptors applied to weather regimes that allow for a detailed monitoring of the location and intensity of their atmospheric centers of action (e.g., troughs and ridges) and the gradients between them, when applicable. Descriptors are designed to document the effect of climate variability and change in modulating the character of daily weather regimes, rather than merely their occurrence statistics. As a case study, the methodology is applied to Aotearoa New Zealand (ANZ), using ERA5 ensemble reanalysis data for the period 1979–2019. Here, we analyze teleconnections between the regimes and their descriptors and large-scale climate variability. Results show a significant modulation of centers of action by the phase of the southern annular mode, with a strong relationship identified with the latitude of atmospheric ridges. Significant associations with El Niño–Southern Oscillation are also identified. Modes of large-scale variability have a stronger influence on the regimes’ intrinsic features than their occurrence. This demonstrates the usefulness of such descriptors, which help explain the relationship between midlatitude transient perturbations and large-scale modes of climate variability. In future research, this methodological framework will be applied to analyze (i) low-frequency changes in weather regimes under climate change, in line with the southward shift of storm tracks, and (ii) regional-scale effects on the climate of ANZ, resulting from interaction with its topography.
