Simulated versus observed patterns of warming over the extratropical Northern Hemisphere continents during the cold season

Abstract

A suite of the historical simulations run with the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) models forced by greenhouse gases, aerosols, stratospheric ozone depletion, and volcanic eruptions and a second suite of simulations forced by increasing CO 2 concentrations alone are compared with observations for the reference interval 1965-2000. Surface air temperature trends are disaggregated by boreal cold (November-April) versus warm (May-October) seasons and by high latitude northern (N: 40°-90°N) versus southern (S: 60°S-40°N) domains. A dynamical adjustment is applied to remove the component of the coldseason surface air temperature trends (over land areas poleward of 40°N) that are attributable to changing atmospheric circulation patterns. The model simulations do not simulate the full extent of the wintertime warming over the high-latitude Northern Hemisphere continents during the later 20th century, much of which was dynamically induced. Expressed as fractions of the concurrent trend in global-mean sea surface temperature, the relative magnitude of the dynamically induced wintertime warming over domain N in the observations, the simulations with multiple forcings, and the runs forced by the buildup of greenhouse gases only is 7∶2∶1, and roughly comparable to the relative magnitude of the concurrent sea-level pressure trends. These results support the notion that the enhanced wintertime warming over high northern latitudes from 1965 to 2000 was mainly a reflection of unforced variability of the coupled climate system. Some of the simulations exhibit an enhancement of the warming along the Arctic coast, suggestive of exaggerated feedbacks.spatial patterns of warming | climate model diagnostics | dynamically-induced warming | polar amplification

Different roles of dynamic and thermodynamic effects in enhanced semi‐arid warming

“…The PLS regression predicts a dependent variable (predictand) based on a set of independent variables (predictors) and has been applied in various types of climate research, including paleoclimate reconstruction (Kalela-Brundin, 1999), diagnosing year-to-year variations in snowpack and hurricanes (Smoliak et al, 2010), examining the accelerated warming over the mid-to-high latitudes of the NH (Wallace et al, 2012), and investigating the recent warming hiatus which is effective in revealing the key role played by the dynamic cooling effect in this hiatus (Guan et al, 2015). In this study, the PLS regression is applied in a pointwise manner, i.e.…”

“…The dynamical adjustment methodology used in this study was explicitly introduced by Wallace et al (2012) and Smoliak et al (2015) and is based on the partial least squares (PLS) regression of the surface air temperature against the SLP. The PLS regression predicts a dependent variable (predictand) based on a set of independent variables (predictors) and has been applied in various types of climate research, including paleoclimate reconstruction (Kalela-Brundin, 1999), diagnosing year-to-year variations in snowpack and hurricanes (Smoliak et al, 2010), examining the accelerated warming over the mid-to-high latitudes of the NH (Wallace et al, 2012), and investigating the recent warming hiatus which is effective in revealing the key role played by the dynamic cooling effect in this hiatus (Guan et al, 2015).…”

“…The dynamically induced component of this warming is thought to be dominated by internal variability in the climate system represented by the Atlantic multi-decadal oscillation (AMO) (Chylek et al, 2014;Mann et al, 2014), the north Atlantic oscillation (NAO) (Huang et al, 1998;Li et al, 2013) and the Pacific decadal oscillation (PDO) (Trenberth and Hurrell, 1994). The effects of these phenomena on rainfall (Neupane and Cook, 2013;Zhang and Cook, 2014) and continental temperatures (Wallace et al, 2012;Smoliak et al, 2015) have been thoroughly investigated in recent decades. In particular, a dynamical adjustment method was proposed by Wallace et al (2012), and their results showed that the changes in atmospheric circulation explained approximately 41% of the warming that occurred over land areas poleward of 40 ∘ N in the boreal cold season during the significant warming period of .…”

“…The effects of these phenomena on rainfall (Neupane and Cook, 2013;Zhang and Cook, 2014) and continental temperatures (Wallace et al, 2012;Smoliak et al, 2015) have been thoroughly investigated in recent decades. In particular, a dynamical adjustment method was proposed by Wallace et al (2012), and their results showed that the changes in atmospheric circulation explained approximately 41% of the warming that occurred over land areas poleward of 40 ∘ N in the boreal cold season during the significant warming period of .…”

“…In this study, we applied a dynamical adjustment method (Wallace et al, 2012;Smoliak et al, 2015) to the temperature to divide it into dynamic and thermodynamic components. The different behaviours of the dynamic and thermodynamic temperatures may reveal the underlying ESAW mechanism, especially in the three typical semi-arid regions of the mid-to-high latitudes in Asia, Europe, and North America.…”