Abstract. Polar amplification – the phenomenon where external radiative forcing produces a larger change in surface temperature at high latitudes than the global average – is a key aspect of anthropogenic climate change, but its causes and consequences are not fully understood. The Polar Amplification Model Intercomparison Project (PAMIP) contribution to the sixth Coupled Model Intercomparison Project (CMIP6; Eyring et al., 2016) seeks to improve our understanding of this phenomenon through a coordinated set of numerical model experiments documented here. In particular, PAMIP will address the following primary questions: (1) what are the relative roles of local sea ice and remote sea surface temperature changes in driving polar amplification? (2) How does the global climate system respond to changes in Arctic and Antarctic sea ice? These issues will be addressed with multi-model simulations that are forced with different combinations of sea ice and/or sea surface temperatures representing present-day, pre-industrial and future conditions. The use of three time periods allows the signals of interest to be diagnosed in multiple ways. Lower-priority tier experiments are proposed to investigate additional aspects and provide further understanding of the physical processes. These experiments will address the following specific questions: what role does ocean–atmosphere coupling play in the response to sea ice? How and why does the atmospheric response to Arctic sea ice depend on the pattern of sea ice forcing? How and why does the atmospheric response to Arctic sea ice depend on the model background state? What have been the roles of local sea ice and remote sea surface temperature in polar amplification, and the response to sea ice, over the recent period since 1979? How does the response to sea ice evolve on decadal and longer timescales? A key goal of PAMIP is to determine the real-world situation using imperfect climate models. Although the experiments proposed here form a coordinated set, we anticipate a large spread across models. However, this spread will be exploited by seeking “emergent constraints” in which model uncertainty may be reduced by using an observable quantity that physically explains the intermodel spread. In summary, PAMIP will improve our understanding of the physical processes that drive polar amplification and its global climate impacts, thereby reducing the uncertainties in future projections and predictions of climate change and variability.

This paper examines the possible linkage between the recent reduction in Arctic sea-ice extent and the wintertime Arctic Oscillation (AO)/North Atlantic Oscillation (NAO). Observational analyses using the ERA interim reanalysis and merged Hadley/Optimum Interpolation Sea Surface Temperature data reveal that a reduced (increased) sea-ice area in November leads to more negative (positive) phases of the AO and NAO in early and late winter, respectively. We simulate the atmospheric response to observed sea-ice anomalies using a high-top atmospheric general circulation model (AGCM for Earth Simulator, AFES version 4.1). The results from the simulation reveal that the recent Arctic sea-ice reduction results in cold winters in mid-latitude continental regions, which are linked to an anomalous circulation pattern similar to the negative phase of AO/NAO with an increased frequency of large negative AO events by a factor of over two. Associated with this negative AO/NAO phase, cold air advection from the Arctic to the mid-latitudes increases. We found that the stationary Rossby wave response to the sea-ice reduction in the Barents Sea region induces this anomalous circulation. We also found a positive feedback mechanism resulting from the anomalous meridional circulation that cools the mid-latitudes and warms the Arctic, which adds an extra heating to the Arctic air column equivalent to about 60% of the direct surface heat release from the sea-ice reduction. The results from this high-top model experiment also suggested a critical role of the stratosphere in deepening the tropospheric annular mode and modulation of the NAO in mid to late winter through stratosphere-troposphere coupling.

[1] The atmosphere-land-ocean fluxes of CO 2 were derived for 64 partitioned areas of the globe (22 over the ocean and 42 over the land) using a time-dependent inverse (TDI) model for the period of January 1988 to December 2001. The model calculation partially follow the TransCom-3 protocol, and is constrained by atmospheric CO 2 concentration data from 87 stations and fully time-dependent atmospheric transport model simulations. The air-to-land and air-to-sea fluxes averaged over the 1990s are estimated at 1.15 ± 0.74 and 1.88 ± 0.53 Pg-C yr À1 , respectively. These estimates, however, remain uncertain owing to sampling biases arising from the sparse distribution of atmospheric CO 2 data, are compared with other estimates by various methods. The sensitivity analysis indicates that the differences in fluxes and flux variability caused by the choices of initial conditions for the TDI model are smaller compared to those due to the selection of measurement networks. Our model results capture interannual variations in global and regional CO 2 fluxes realistically. The estimated oceanic CO 2 flux anomalies appear to be closely related to prominent climate modes such as El Niño-Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and the Pacific Decadal Oscillation (PDO). The results from the correlation analyses show that the oceanic CO 2 flux in the tropics is strongly influenced by the ENSO dynamical cycle, and that in the sub-polar regions by upwelling of sub-surface waters in the winter and plankton blooms in the spring.