A pitchfork-like relationship between reduced Barents-Kara sea ice and Ural atmospheric circulation

Abstract

Atmospheric circulation monthly anomalies over the Ural region are key indicators of Eurasian climate anomalies. Here, whether there exists a one-to-two correspondence relationship that generally agrees with the supercritical pitchfork bifurcation model, referred to as a pitchfork-like relationship, between reduced sea ice concentration (SIC) in the Barents-Kara Seas in specific months and the lagging Ural circulation anomalies is explored. Based on the monthly observational SIC data and two reanalyses during 1979/1980 − 2020/2021, two typical examples are found by estimating the joint probability density function. Results show that when the gradually reduced SIC in September (January) passes a critical threshold, the preferred Ural circulation patterns in October (February) exhibit a regime transition from the flat zonal westerlies to wavy westerlies with a Ural trough and wavy westerlies with a Ural ridge. Because both the barotropic and baroclinic conversion of energy from the climatological-mean flow to Ural circulation anomalies exhibit a regime transition from one regime to two regimes. It might be associated with the increased both positive and negative shear vorticity of background westerly wind over the Ural region before the regime transition, contributed by the thermodynamic effect of the SIC reduction. After the regime transition, positive and negative anomaly events of Ural atmospheric circulation occur with equal probability under the same SIC. Our results suggest an increased incidence of both positive and negative anomalies of Ural atmospheric circulation and also the Siberian High, under the recent SIC reduction, which implies a low predictability of Eurasian climate anomalies in October and February.

Solar Influences on Winter Atmospheric Circulation Over the Ural, North Atlantic and North Pacific Regions: Pitchfork‐Like Relationships

“…What's more, states of the monthly mean atmosphere indicated by the Z925/Z850 indices are typically time‐varying and not the “equilibrium state.” Therefore, following the wording of D. D. Li et al. (2023), we refer to the relationships between the TSI and the Z925/Z850 indices observed in data as “pitchfork‐like (PL) relationships” rather than the term “supercritical pitchfork bifurcation.”…”

“…D. D. Li et al. (2023) found a PL relationship between the sea ice concentration in the Barents‐Kara Seas in September (January) and the 850 hPa relative vorticity anomalies over the Ural region in October (February). Hence, we conjecture that the PL relationship between a slow‐varying external forcing factor (e.g., TSI) and an atmospheric variable (e.g., geopotential height) is widespread in the three regions.…”

“…An empirical formula to estimate the lower bound of bandwidth ( W ) is given by Emerson and Hoaglin (1983) and D. D. Li et al. (2020, 2023): $$$W=D/\left(10\,{\log }_{10}\,N\right),$$$ where D is the range of the sample data, and N is the sample size. In general, to get a smooth PDF curve, it's best to choose a slightly larger bandwidth than the W calculated.…”

“…Following previous studies (D. D. Li et al, 2020Li et al, , 2023, we use the MATLAB function "ksdensity" to estimate the joint PDF of bivariate data. This function uses a normal kernel function with a bandwidth of a smoothing window to obtain a smoothed density curve over bins (refer to https://www.mathworks.com/help/stats/ksdensity.…”

“…html). An empirical formula to estimate the lower bound of bandwidth (W) is given by Emerson and Hoaglin (1983) and D. D. Li et al (2020Li et al ( , 2023:…”