Interdecadal changes in the storm track activity over the North Pacific and North Atlantic

Abstract

Analysis of NCEP-NCAR I reanalysis data of 1948–2009 and ECMWF ERA-40 reanalysis data of 1958–2001 reveals several significant interdecadal changes in the storm track activity and mean flow-transient eddy interaction in the extratropics of Northern Hemisphere. First, the most remarkable transition in the North Pacific storm track (PST) and the North Atlantic storm track (AST) activities during the boreal cold season (from November to March) occurred around early-to-mid 1970s with the characteristics of global intensification that has been noticed in previous studies. Second, the PST activity in midwinter underwent decadal change from a weak regime in the early 1980s to a strong regime in the late 1980s. Third, during recent decade, the PST intensity has been enhanced in early spring whereas the AST intensity has been weakened in midwinter. Finally, interdecadal change has been also noted in the relationship between the PST and AST activities and between the storm track activity and climate indices. The variability of storm track activity is well correlated with the Pacific Decadal Oscillation and North Atlantic Oscillation prior to the early 1980s, but this relationship has disappeared afterward and a significant linkage between the PST and AST activity has also been decoupled. For a better understanding of the mid-1970s’ shift in storm track activity and mean flow-transient eddy interaction, further investigation is made by analyzing local barotropic and baroclinic energetics. The intensification of global storm track activity after the mid-1970s is mainly associated with the enhancement of mean meridional temperature gradient resulting in favorable condition for baroclinic eddy growth. Consistent with the change in storm track activity, the baroclinic energy conversion is significantly increased in the North Pacific and North Atlantic. The intensification of the PST and AST activity, in turn, helps to reinforce the changes in the middle-to-upper tropospheric circulation but acts to interfere with the changes in the low-tropospheric temperature field.

Appendix

1.1 Barotropic and baroclinic energy conversion

The barotropic energy conversion (BTEC) can be expressed by the inner product of the D-vector of the basic flow and the E-vector of the transient parts (Cai et al. 2007). The D-vector defined as ${\vec{\text{D}}} = \left( {\frac{{\partial {\bar{\text{u}}}}}{{\partial {\text{x}}}} - \frac{{\partial {\bar{\text{v}}}}}{{\partial {\text{y}}}},\frac{{\partial {\bar{\text{v}}}}}{{\partial {\text{x}}}} + \frac{{\partial {\bar{\text{u}}}}}{{\partial {\text{y}}}}} \right)$ consists of the stretching and shearing deformations. The E-vector defined as ${\vec{\text{E}}} = \left( {\frac{1}{2}\left( {\overline{{{\text{v}}^{\prime 2} }} - \overline{{{\text{u}}^{\prime 2} }} } \right), - \overline{{{\text{u}}^{\prime } {\text{v}}^{\prime } }} } \right)$ is a measure of the local shape and horizontal orientation of eddies (Cai and Mak 1990).

$$ {\text{BTEC}} = \frac{{{\text{p}}_{0} }}{\text{g}}\left\{ {\frac{1}{2}\left( {\overline{{{\text{v}}^{\prime 2} }} - \overline{{{\text{u}}^{\prime 2} }} } \right)\left( {\frac{{\partial {\bar{\text{u}}}}}{{\partial {\text{x}}}} - \frac{{\partial {\bar{\text{v}}}}}{{\partial {\text{y}}}}} \right) + \left( { - \overline{{{\text{u}}^{\prime } {\text{v}}^{\prime } }} } \right)\left( {\frac{{\partial {\bar{\text{v}}}}}{{\partial {\text{x}}}} + \frac{{\partial {\bar{\text{u}}}}}{{\partial {\text{y}}}}} \right)} \right\} $$

where, g is the acceleration of gravity and p₀ is 1,000 hPa. The overbar and prime represent the climatological mean and transient parts, respectively.

The baroclinic generation from mean available potential energy to eddy available potential energy (BCEC I) is roughly proportional to the poleward eddy heat flux multiplied by the meridional temperature gradient (Dole and Black 1990; Cai et al. 2007).

$$ \begin{aligned} {\text{C}}_{1} & = \left( {\frac{{{\text{p}}_{0} }}{\text{p}}} \right)^{{{\text{C}}_{\text{V}} /{\text{C}}_{\text{P}} }} \frac{\text{R}}{\text{g}} \\ {\text{C}}_{2} & = {{{\text{C}}_{1} \left( {\frac{{{\text{p}}_{0} }}{\text{p}}} \right)^{{{\text{R/C}}_{\text{P}} }} } \mathord{\left/ {\vphantom {{{\text{C}}_{1} \left( {\frac{{{\text{p}}_{0} }}{\text{p}}} \right)^{{{\text{R/C}}_{\text{P}} }} } {\left( { - \frac{{{\text{d}}\Uptheta }}{\text{dp}}} \right)}}} \right. \kern-\nulldelimiterspace} {\left( { - \frac{{{\text{d}}\Uptheta }}{\text{dp}}} \right)}} \\ {\text{BCEC I}} & = - {\text{C}}_{2} \left( {\overline{{{\text{u}}^{\prime } {\text{T}}^{\prime } }} \frac{{\partial {\bar{\text{T}}}}}{{\partial {\text{x}}}} + \overline{{{\text{v}}^{\prime } {\text{T}}^{\prime } }} \frac{{\partial {\bar{\text{T}}}}}{{\partial {\text{y}}}}} \right) \\ \end{aligned} $$

where, R is the gas constant for dry air and C_P (C_V) is the specific heat of dry air at the constant pressure (volume). Θ indicates potential temperature.

The energy conversion between eddy available potential energy and eddy kinetic energy (BCEC II) can be expressed by upward heat flux (Dole and Black 1990; Cai et al. 2007)

$$ {\text{BCEC II}} = - {\text{C}}_{1} \left( {\overline{{\omega^{\prime } {\text{T}}^{\prime } }} } \right). $$

1.2 Eddy feedback

The geopotential height and temperature tendency from eddy feedback are calculated by vorticity and heat flux convergences of the transient eddies according to Cai et al. (2007)

$$ \begin{aligned} \frac{{\partial {\text{h}}}}{{\partial {\text{t}}}} & = \nabla^{ - 2} \left[ { - \frac{{{\text{f}}_{0} }}{\text{g}}\overline{{\nabla \cdot ({\vec{\text{V}}}^{\prime } \zeta^{\prime } )}} } \right] \\ \frac{{\partial {\text{T}}}}{{\partial {\text{t}}}} & = - \overline{{\nabla \cdot ({\vec{\text{V}}}^{\prime } {\text{T}}^{\prime } )}} . \\ \end{aligned} $$

1.3 Lepage test statistic

The Lepage test statistic is a useful tool for detecting significant changes between two samples (Yonetani and McCabe 1994). Using the Lepage test, we can detect changes in the mean and in the variance of variable through time. The Lepage test statistic is calculated as follow.

$$ {\text{Lepage}}\,{\text{test}}\,{\text{statistic}} = \frac{{\left[ {\sum\nolimits_{{{\text{i}} = 1}}^{\text{N}} {{\text{i}} \cdot {\text{u}}_{\text{i}} - \frac{1}{2}{\text{n}}_{1} ({\text{N}} + 1)} } \right]^{2} }}{{\frac{1}{12}{\text{n}}_{1} {\text{n}}_{2} ({\text{N}} + 1)}} + \frac{{\left[ {\sum\nolimits_{{{\text{i}} = 1}}^{{{\text{n}}_{1} }} {{\text{i}} \cdot {\text{u}}_{\text{i}} + \sum\nolimits_{{{\text{i}} = {\text{n}} + 1}}^{\text{N}} {({\text{N}} - {\text{i}} + 1){\text{u}}_{\text{i}} } - \frac{1}{4}{\text{n}}_{1} ({\text{N}} + 2)} } \right]^{2} }}{{\frac{{{\text{n}}_{1} {\text{n}}_{2} ({\text{N}} - 2)({\text{N}} + 2)}}{{48({\text{N}} - 1)}}}} $$

where, n₁ and n₂ are sample sizes of samples a and b respectively. The N is sum of n₁ and n₂. The u_i = 1 when the ith record in a combined sample of ranked values of samples a and b belongs to the sample a, and u_i = 0 when it belongs to the sample b. If the Lepage test statistic is greater than 5.99 (9.21), the change between two samples is significant at a 95% (99%) confidence level. Details of Lepage test are described in Yonetani and McCabe (1994).