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This study seeks to derive the sea surface temperature (SST) response to anthropogenic forcing from observations over the last century, using simple methods inspired from pattern scaling. As in pattern scaling, the spatial response is assumed to scale with global-mean and annual-mean surface temperature. The long-term aim of this work is to generate anthropogenically forced SST and sea ice patterns for the recent past and near-term future, and use them to force atmosphere-land climate models for attribution and prediction purposes. The present work compares estimation methodologies and, within a Monte Carlo framework based on large initial condition ensembles of climate model simulations, examines the robustness of the patterns obtained. The different methods explored here yield a similar SST spatial response, mostly reflecting the observed SST linear trend map. The different methods nevertheless provide distinctive temporal evolution of the global-mean and annual-mean SST response, which in turn affects the temporal evolution of the global-mean and annual-mean air surface temperature simulated in corresponding prescribed SST simulations. The estimated SST spatial response consists mostly of a warming of the midlatitude coasts near the western boundary currents, the tropical Indian Ocean, and the Arctic Ocean. This pattern generally agrees with previously published observational and modeling studies. Based on Monte Carlo analysis of the large ensembles, it is found that between 36% and 56% of its spatial variance results from anthropogenic forcing. Overall, the work herein provides constraints on the uncertainty associated with the spatial variability of an anthropogenically forced component of climate change derived from observations, which can potentially be used for climate attribution and prediction. [ABSTRACT FROM AUTHOR]

Recent observational and modeling studies have demonstrated a link between eastern tropical Pacific Ocean (TPO) warming associated with the El Niño--Southern Oscillation (ENSO) and the negative phase of the wintertime northern annular mode (NAM). The TPO--NAM link involves a Rossby wave teleconnection from the tropics to the extratropics, and an increase in polar stratospheric wave driving that in turn induces a negative NAM anomaly in the stratosphere and troposphere. Previous work further suggests that tropical Indian Ocean (TIO) warming is associated with a positive NAM anomaly, which is of opposite sign to the TPO case. The TIO case is, however, difficult to interpret because the TPO and TIO warmings are not independent. To better understand the dynamics of tropical influences on the NAM, the current study investigates the NAM response to imposed TPO and TIO warmings in a general circulation model. The NAM responses to the two warmings have opposite sign and can be of surprisingly similar amplitude even though the TIO forcing is relatively weak. It is shown that the sign and strength of the NAM response is often simply related to the phasing, and hence the linear interference, between the Rossby wave response and the climatological stationary wave. The TPO (TIO) wave response reinforces (attenuates) the climatological wave and therefore weakens (strengthens) the stratospheric jet and leads to a negative (positive) NAM response. In additional simulations, it is shown that decreasing the strength of the climatological stationary wave reduces the importance of linear interference and increases the importance of nonlinearity. This work demonstrates that the simulated extratropical annular mode response to climate forcings can depend sensitively on the amplitude and phase of the climatological stationary wave and the wave response. [ABSTRACT FROM AUTHOR]