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Xiuhua Zhu, John Bye, Klaus Fraedrich, and Isabella Bordi

Abstract

Climate variability is often studied in terms of fluctuations with respect to the mean state, whereas the dependence between the mean and variability is rarely discussed. Here, a new climate metric is proposed to measure the relationship between means and standard deviations of annual surface temperature computed over nonoverlapping 100-yr segments. This metric is analyzed based on equilibrium simulations of the Max Planck Institute Earth System Model (MPI-ESM): the last-millennium climate (800–1799), the future climate projection following the A1B scenario (2100–99), and the 3100-yr unforced control simulation. A linear relationship is globally observed in the control simulation and is thus termed intrinsic climate variability, which is most pronounced in the tropical region with negative regression slopes over the Pacific warm pool and positive slopes in the eastern tropical Pacific. It relates to asymmetric changes in temperature extremes and associates fluctuating climate means with increase or decrease in intensity and occurrence of both El Niño and La Niña events. In the future scenario period, the linear regression slopes largely retain their spatial structure with appreciable changes in intensity and geographical locations. Since intrinsic climate variability describes the internal rhythm of the climate system, it may serve as guidance for interpreting climate variability and climate change signals in the past and the future.

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Ian Simmonds, Kevin Keay, and John Arthur Tristram Bye

Abstract

Presented here is an objective approach to identify, characterize, and track Southern Hemisphere mobile fronts in hemispheric analyses of relatively modest resolution, such as reanalyses. Among the principles in its design were that it should be based on broadscale synoptic considerations and be as simple and easily understood as possible. The resulting Eulerian scheme has been applied to the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA)–Interim and a climatology of frontal characteristics, at both the 10-m and 850-hPa levels, derived for the period 1 January 1989–28 February 2009. The knowledge of the character of these features is central to understanding weather and climate over the hemisphere.

In both summer and winter the latitude belt 40°–60°S hosts the highest frequency of frontal points, but there are significant zonal asymmetries within this band. The climatology reveals that the longest fronts are in the Indian Ocean where mean lengths exceed 2000 km. The mean frontal intensity over the hemisphere tends to be greater at 850 hPa than at 10 m, and greater in winter than in summer. The frontal intensity also shows its maximum in the Indian Ocean. In the mean, the meridional tilt of these fronts is northwest–southeast over much of the midlatitudes and subtropics, and increases with latitude toward the equator. The tilts are of overwhelmingly opposite sign in the coastal Antarctic and subantarctic regions.

Broadly speaking, the number of fronts and their mean length and mean intensity exhibit maxima in winter in the midlatitudes (30°–50°S), but show a sizeable semiannual variation (maxima in fall and spring) during the year at higher latitudes.

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John A. T. Bye, Roland A. D. Byron-Scott, and Adrian H. Gordon

Abstract

The authors present an analytical climate model, which has the features that (i) the atmosphere is a simple oscillator for all periods ≤1 year, (ii) the ocean stores heat, (iii) the ocean exchanges momentum with the atmosphere, and (iv) random forcing exists due to atmospheric thermodynamics and oceanic dynamics. The piecewise analytical integration of coupled linear equations for sea temperature, air-sea temperature difference, and air-sea velocity difference generates experimental climates. The exchange parameters of the algorithm, except for the exchange coefficient for heat with the deep ocean, am calibrated to the observed climate using the annual cycle, and random forcing is applied over intervals of one year. The atmospheric random forcing leads to bounded random walks, the extent of which increases as the exchange coefficient with the deep ocean decreases, and the oceanic random forcing generates a stationary response. It is found that the observed statistics of the global temperature series can be reproduced by either a relatively large heat exchange coefficient with the deep ocean and little oceanic variability or a smaller exchange coefficient with a larger oceanic variability. Plausible exchange coefficient values imply random walk lengths of at least a century-long timescale.

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