Mechanisms of midlatitude cross-tropopause transport using a potential vorticity budget approach

[ 1] A potential vorticity (PV) budget method has been used to attribute vertical transport across the near-tropopause ( 1 PVU surface) in extratropical weather systems to radiative, latent heating and cooling, and mixing processes. Sources and sinks of PV due to nonconservative processes are calculated online and advected as passive tracers. There is reasonable agreement between the spatial distribution of transport determined from the PV budget method and the transport across the 1 - 2 PVU zone from a passive tracer and trajectories, but different aspects of exchange can be diagnosed with each method. Stratosphere-to-troposphere transport occurred in the broad upper level PV anomalies and was attributed mainly to latent heating and cooling processes; troposphere-to-stratosphere transport occurred toward the tail of a PV filament and in a ridge region and was attributed mainly to radiative processes. The contribution of mixing processes to transport was comparatively small. Using the PV budget method, the domain integrated exchange across the 1 PVU surface was from stratosphere to troposphere, and the magnitude of 1 x 10(15) kg over a 2 day winter integration in a large North Atlantic domain is consistent with stratosphere-troposphere exchange calculations from other studies. This exchange arises from an approximate balance between the dominant stratosphere-to-troposphere transport due to latent heating and cooling processes and troposphere-to-stratosphere transport due to radiative processes. The direction of transport across the tropopause in a fold was found to be critically dependent on the PV surface considered to represent the tropopause.

Sensitivity of simulated regional Arctic climate to the choice of coupled model domain

The climate over the Arctic has undergone changes in recent decades. In order to evaluate the coupled response of the Arctic system to external and internal forcing, our study focuses on the estimation of regional climate variability and its dependence on large-scale atmospheric and regional ocean circulations. A global ocean–sea ice model with regionally high horizontal resolution is coupled to an atmospheric regional model and global terrestrial hydrology model. This way of coupling divides the global ocean model setup into two different domains: one coupled, where the ocean and the atmosphere are interacting, and one uncoupled, where the ocean model is driven by prescribed atmospheric forcing and runs in a so-called stand-alone mode. Therefore, selecting a specific area for the regional atmosphere implies that the ocean–atmosphere system can develop ‘freely’ in that area, whereas for the rest of the global ocean, the circulation is driven by prescribed atmospheric forcing without any feedbacks. Five different coupled setups are chosen for ensemble simulations. The choice of the coupled domains was done to estimate the influences of the Subtropical Atlantic, Eurasian and North Pacific regions on northern North Atlantic and Arctic climate. Our simulations show that the regional coupled ocean–atmosphere model is sensitive to the choice of the modelled area. The different model configurations reproduce differently both the mean climate and its variability. Only two out of five model setups were able to reproduce the Arctic climate as observed under recent climate conditions (ERA-40 Reanalysis). Evidence is found that the main source of uncertainty for Arctic climate variability and its predictability is the North Pacific. The prescription of North Pacific conditions in the regional model leads to significant correlation with observations, even if the whole North Atlantic is within the coupled model domain. However, the inclusion of the North Pacific area into the coupled system drastically changes the Arctic climate variability to a point where the Arctic Oscillation becomes an ‘internal mode’ of variability and correlations of year-to-year variability with observational data vanish. In line with previous studies, our simulations provide evidence that Arctic sea ice export is mainly due to ‘internal variability’ within the Arctic region. We conclude that the choice of model domains should be based on physical knowledge of the atmospheric and oceanic processes and not on ‘geographic’ reasons. This is particularly the case for areas like the Arctic, which has very complex feedbacks between components of the regional climate system.