Typically 20-40 extreme cyclone events (sometimes called 'weather bombs') occur in the Arctic North Atlantic per winter season, with an increasing trend of 6 events/decade over 1979-2015, according ...to 6 hourly station data from Ny-Ålesund. This increased frequency of extreme cyclones is consistent with observed significant winter warming, indicating that the meridional heat and moisture transport they bring is a factor in rising temperatures in the region. The winter trend in extreme cyclones is dominated by a positive monthly trend of about 3-4 events/decade in November-December, due mainly to an increasing persistence of extreme cyclone events. A negative trend in January opposes this, while there is no significant trend in February. We relate the regional patterns of the trend in extreme cyclones to anomalously low sea-ice conditions in recent years, together with associated large-scale atmospheric circulation changes such as 'blockinglike' circulation patterns (e.g. Scandinavian blocking in December and Ural blocking during January-February).
The response of the Arctic atmosphere to low and high sea ice concentration phases based on European Center for Medium-Range Weather Forecast (ECMWF) Re-Analysis Interim (ERA-Interim) atmospheric ...data and Hadley Centre's sea ice dataset (HadISST1) from 1989 until 2010 has been studied. Time slices of winter atmospheric circulation with high (1990-2000) and low (2001-2010) sea ice concentration in the preceding August/September have been analysed with respect to tropospheric interactions between planetary and baroclinic waves. It is shown that a changed sea ice concentration over the Arctic Ocean impacts differently the development of synoptic and planetary atmospheric circulation systems. During the low ice phase, stronger heat release to the atmosphere over the Arctic Ocean reduces the atmospheric vertical static stability. This leads to an earlier onset of baroclinic instability that further modulates the non-linear interactions between baroclinic wave energy fluxes on time scales of 2.5-6 d and planetary scales of 10-90 d. Our analysis suggests that Arctic sea ice concentration changes exert a remote impact on the large-scale atmospheric circulation during winter, exhibiting a barotropic structure with similar patterns of pressure anomalies at the surface and in the mid-troposphere. These are connected to pronounced planetary wave train changes notably over the North Pacific.
This study forms part II of two papers describing ECHAM6-FESOM, a newly established global climate model with a unique multi-resolution sea ice-ocean component. While part I deals with the model ...description and the mean climate state, here we examine the internal climate variability of the model under constant present-day (1990) conditions. We (1) assess the internal variations in the model in terms of objective variability performance indices, (2) analyze variations in global mean surface temperature and put them in context to variations in the observed record, with particular emphasis on the recent warming slowdown, (3) analyze and validate the most common atmospheric and oceanic variability patterns, (4) diagnose the potential predictability of various climate indices, and (5) put the multi-resolution approach to the test by comparing two setups that differ only in oceanic resolution in the equatorial belt, where one ocean mesh keeps the coarse ~1° resolution applied in the adjacent open-ocean regions and the other mesh is gradually refined to ~0.25°. Objective variability performance indices show that, in the considered setups, ECHAM6-FESOM performs overall favourably compared to five well-established climate models. Internal variations of the global mean surface temperature in the model are consistent with observed fluctuations and suggest that the recent warming slowdown can be explained as a once-in-one-hundred-years event caused by internal climate variability; periods of strong cooling in the model (‘hiatus’ analogs) are mainly associated with ENSO-related variability and to a lesser degree also to PDO shifts, with the AMO playing a minor role. Common atmospheric and oceanic variability patterns are simulated largely consistent with their real counterparts. Typical deficits also found in other models at similar resolutions remain, in particular too weak non-seasonal variability of SSTs over large parts of the ocean and episodic periods of almost absent deep-water formation in the Labrador Sea, resulting in overestimated North Atlantic SST variability. Concerning the influence of locally (isotropically) increased resolution, the ENSO pattern and index statistics improve significantly with higher resolution around the equator, illustrating the potential of the novel unstructured-mesh method for global climate modeling.
A new climate model has been developed that employs a multi-resolution dynamical core for the sea ice-ocean component. In principle, the multi-resolution approach allows one to use enhanced ...horizontal resolution in dynamically active regions while keeping a coarse-resolution setup otherwise. The coupled model consists of the atmospheric model ECHAM6 and the finite element sea ice-ocean model (FESOM). In this study only moderate refinement of the unstructured ocean grid is applied and the resolution varies from about 25 km in the northern North Atlantic and in the tropics to about 150 km in parts of the open ocean; the results serve as a benchmark upon which future versions that exploit the potential of variable resolution can be built. Details of the formulation of the model are given and its performance in simulating observed aspects of the mean climate is described. Overall, it is found that ECHAM6–FESOM realistically simulates many aspects of the observed climate. More specifically it is found that ECHAM6–FESOM performs at least as well as some of the most sophisticated climate models participating in the fifth phase of the Coupled Model Intercomparison Project. ECHAM6–FESOM shares substantial shortcomings with other climate models when it comes to simulating the North Atlantic circulation.
The coupled regional climate model HIRHAM‐NAOSIM is used to investigate feedbacks between September sea ice anomalies in the Arctic and atmospheric conditions in autumn and the subsequent winter. A ...six‐member ensemble of simulations spanning the period 1949–2008 is analyzed. The results show that negative Arctic sea ice anomalies are associated with increased heat and moisture fluxes, decreased static stability, increased lower tropospheric moisture, and modified baroclinicity, synoptic activity, and atmospheric large‐scale circulation. The circulation changes in the following winter display meridionalized flow but are not fully characteristic of a negative Arctic Oscillation pattern, though they do support cold winter temperatures in northern Eurasia. Internally generated climate variability causes significant uncertainty in the simulated circulation changes due to sea ice‐atmosphere interactions. The simulated atmospheric feedback patterns depend strongly on the position and strength of the regional sea ice anomalies and on the analyzed time period. The strongest atmospheric feedbacks are related to sea ice anomalies in the Beaufort Sea. This work suggests that there are complex feedback mechanisms that support a statistical link between reduced September sea ice and Arctic winter circulation. However, the feedbacks depend on regional and decadal variations in the coupled atmosphere‐ocean‐sea ice system.
Key Points
Coupled regional model simulates Arctic feedbacks
Summer sea ice anomalies affect atmospheric winter circulation
Atmospheric feedback patterns depend on the regional sea ice anomaly
Observations from 1979 to 2014 show a positive trend in the summer sea ice melt rate with an acceleration particularly in June and August. This is associated with atmospheric circulation changes such ...as a tendency toward a dipole pattern in the mean sea level pressure (SLP) trend with an increase over the Arctic Ocean and a decrease over Siberia. Consistent with previous studies, we here show the statistical relationship between the summer sea ice melt rate and SLP and that more than one SLP pattern is associated with anomalously high melt rates. Most high melt rates occur during high pressure over the Arctic Ocean accompanied by low pressure over Siberia, but a strong Beaufort High and advection of warm air associated with a cyclone located over the Taymyr Peninsula can also trigger anomalous high ice melt. We evaluate 10‐member ensemble simulations with the coupled atmosphere‐ice‐ocean Arctic regional climate model HIRHAM‐NAOSIM. The simulations have systematically low acceleration of sea ice melt rate in August, related to shortcomings in representing the strengthening pressure gradient from the Barents/Kara Sea toward Northern Greenland in recent decades. In general, the model shows the same classification of SLP patterns related to anomalous melt rates as the observations. However, the evolution of sea ice melt‐related cloud‐radiation feedback over the summer reveals contrary effects from low‐level clouds in the reanalysis and in the simulations.
Key Points
Trends in Arctic sea ice melt rate and mean sea level pressure in summer months May–August 1979–2014 are quantified
Coupled regional climate simulations reproduce observed statistical relation between melt rate and atmospheric circulation, but show deficits in August
Contrary sea ice melt‐related cloud‐radiation feedback evolving over the summer are found
This paper presents an analysis of the low-frequency variability of the midtropospheric atmospheric flow of the Northern Hemisphere during winter in terms of teleconnection patterns and atmospheric ...flow regimes. Teleconnection patterns have been determined by two different methods, correlation analysis and empirical orthogonal function analysis. Flow regimes have been determined by analysing the structure of a spherical probability density function in a low-dimensional state space spanned by the three leading empirical orthogonal functions. To assess the ability of state-of-the-art coupled atmosphere-ocean general circulation models (AOGCMs), multi-model simulations for present day conditions, performed for the 4th assessment report of the Intergovernmental Panel on Climate Change have been analysed. The comparison with observations reveals, that state-of-the-art AOGCMs are able to describe the low-frequency variability in terms of teleconnections and flow regimes realistically. The analyses of simulations for future climate scenarios reveal changes in the strengths of the centers of action. Concerning climate regimes, two new regimes appear and additionally, slight changes were found in the structure of some regimes.
This paper presents combined winter climate regimes for the 1766–2000 period over the North Atlantic/European sector. We expand previous studies on recurrent regimes by combining spatially ...high‐resolved independent reconstructions of the 500 hPa geopotential height, land surface air temperature, and precipitation fields. Nonlinear Principal Component Analysis is applied to the data in order to account for the underlying nonlinear dynamics of climate regimes. Three recurrent winter climate regimes are detected. One regime resembles in its pressure, temperature, and precipitation pattern the positive phase of the North Atlantic Oscillation, whereas the other two regimes are European blocking situations.
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