Intercomparison of Surface Heat Transfer Near the Arctic Marginal Ice Zone for Multiple Reanalyses: A Case Study of September 2009

Inoue, Jun; Hori, Masataka; Enomoto, Takeshi; Kikuchi, Takashi

doi:10.2151/sola.2011-015

Cited by 31 publications

(31 citation statements)

References 14 publications

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“…For example, the atmospheric fluxes of sensible and latent heat into the Arctic basin that are required to offset the radiative imbalance are mostly associated with cyclones (Jakobson and Vihma, 2010;Skific and Francis, 2013;Woods et al, 2013). The present analysis is also very timely in that we are now in a period of rapid change in the Arctic sea ice and many other parameters (Screen and Simmonds, 2010;Inoue et al, 2011;Jackson et al, 2011;Cavalieri and Parkinson, 2012;Comiso, 2012;Duarte et al, 2012;Livina and Lenton, 2013;Simmonds, 2015). Cyclones appear to be tied up with those changes in complex ways (Simmonds et al, 2008;Simmonds and Keay, 2009;Screen et al, 2011;Simmonds and Rudeva, 2012;Parkinson and Comiso, 2013), and there is increasing attention being devoted to extreme weather and destructive Arctic cyclones (e.g.…”

Section: Introductionmentioning

confidence: 86%

A comparison of tracking methods for extreme cyclones in the Arctic basin

Simmonds

Rudeva

2014

Tellus A: Dynamic Meteorology and Oceanography

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A B S T R A C T Dramatic climate changes have occurred in recent decades over the Arctic region, and very noticeably in nearsurface warming and reductions in sea ice extent. In a climatological sense, Arctic cyclone behaviour is linked to the distributions of lower troposphere temperature and sea ice, and hence the monitoring of storms can be seen as an important component of the analysis of Arctic climate. The analysis of cyclone behaviour, however, is not without ambiguity, and different cyclone identification algorithms can lead to divergent conclusions. Here we analyse a subset of Arctic cyclones with 10 state-of-the-art cyclone identification schemes applied to the ERA-Interim reanalysis. The subset is comprised of the five most intense (defined in terms of central pressure) Arctic cyclones for each of the 12 calendar months over the 30-yr period from 1 January 1979 to 31 March 2009. There is a considerable difference between the central pressures diagnosed by the algorithms of typically 5Á10 hPa. By contrast, there is substantial agreement as to the location of the centre of these extreme storms. The cyclone tracking algorithms also display some differences in the evolution and life cycle of these storms, while overall finding them to be quite long-lived. For all but six of the 60 storms an intense tropopause polar vortex is identified within 555 km of the surface system. The results presented here highlight some significant differences between the outputs of the algorithms, and hence point to the value using multiple identification schemes in the study of cyclone behaviour. Overall, however, the algorithms reached a very robust consensus on most aspects of the behaviour of these very extreme cyclones in the Arctic basin.

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Section: Introductionmentioning

confidence: 86%

A comparison of tracking methods for extreme cyclones in the Arctic basin

Simmonds

Rudeva

2014

Tellus A: Dynamic Meteorology and Oceanography

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“…This effect is most significant in the marginal ice zone-sea ice concentrations between 15-85%-due to the proximity of open water to sea ice, allowing for cold air advection over open water [62,150].…”

Section: Sea Icementioning

confidence: 99%

“…In this situation, strong turbulent fluxes are enhanced by BL convection from the juxtaposition of cold air over a warm surface [194]. Through these effects, the movement of warm and cold air masses have significant local effects on ocean heat storage, surface temperatures, and sea ice [150,190,195]. Changes in Arctic surface turbulent fluxes influence atmospheric circulation patterns ( Figure 5).…”

Section: Atmospheric Circulationmentioning

confidence: 99%

On the Increasing Importance of Air-Sea Exchanges in a Thawing Arctic: A Review

et al. 2018

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Forty years ago, climate scientists predicted the Arctic to be one of Earth's most sensitive climate regions and thus extremely vulnerable to increased CO 2 . The rapid and unprecedented changes observed in the Arctic confirm this prediction. Especially significant, observed sea ice loss is altering the exchange of mass, energy, and momentum between the Arctic Ocean and atmosphere.As an important component of air-sea exchange, surface turbulent fluxes are controlled by vertical gradients of temperature and humidity between the surface and atmosphere, wind speed, and surface roughness, indicating that they respond to other forcing mechanisms such as atmospheric advection, ocean mixing, and radiative flux changes. The exchange of energy between the atmosphere and surface via surface turbulent fluxes in turn feeds back on the Arctic surface energy budget, sea ice, clouds, boundary layer temperature and humidity, and atmospheric and oceanic circulations. Understanding and attributing variability and trends in surface turbulent fluxes is important because they influence the magnitude of Arctic climate change, sea ice cover variability, and the atmospheric circulation response to increased CO 2 . This paper reviews current knowledge of Arctic Ocean surface turbulent fluxes and their effects on climate. We conclude that Arctic Ocean surface turbulent fluxes are having an increasingly consequential influence on Arctic climate variability in response to strong regional trends in the air-surface temperature contrast related to the changing character of the Arctic sea ice cover. Arctic Ocean surface turbulent energy exchanges are not smooth and steady but rather irregular and episodic, and consideration of the episodic nature of surface turbulent fluxes is essential for improving Arctic climate projections.

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“…While the box model, which uses ice concentrations and ice surface temperatures derived from remote sensing data, reproduces the measured 2-m air temperature quite well, the temperature of the reanalysis is about 4 • C too high. This is probably due to the sea ice boundary conditions in ERA-Interim with fixed values for the ice thickness of 1.5 m (White, 2006) and for the ice concentration of 100 % north of 82.5 • N (Inoue et al, 2011), which reduce the surface temperature variability.…”

Section: An Example Of Evolution Along a Single Trajectorymentioning

confidence: 99%

“…In order to obtain accurate fluxes, which determine the energy budgets, the sea ice concentration should be well represented in climate and weather prediction models. Also for reanalyses, a correct representation of ice concentrations is crucial for heat flux calculations (Inoue et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

The impact of heterogeneous surface temperatures on the 2-m air temperature over the Arctic Ocean under clear skies in spring

et al. 2013

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Abstract. The influence of spatial surface temperature changes over the Arctic Ocean on the 2-m air temperature variability is estimated using backward trajectories based on ERA-Interim and JRA25 wind fields. They are initiated at Alert, Barrow and at the Tara drifting station. Three different methods are used. The first one compares mean ice surface temperatures along the trajectories to the observed 2-m air temperatures at the stations. The second one correlates the observed temperatures to air temperatures obtained using a simple Lagrangian box model that only includes the effect of sensible heat fluxes. For the third method, mean sensible heat fluxes from the model are correlated with the difference of the air temperatures at the model starting point and the observed temperatures at the stations. The calculations are based on MODIS ice surface temperatures and four different sets of ice concentration derived from SSM/I (Special Sensor Microwave Imager) and AMSR-E (Advanced Microwave Scanning Radiometer for EOS) data. Under nearly cloud-free conditions, up to 90 % of the 2-m air temperature variance can be explained for Alert, and 70 % for Barrow, using these methods. The differences are attributed to the different ice conditions, which are characterized by high ice concentration around Alert and lower ice concentration near Barrow. These results are robust for the different sets of reanalyses and ice concentration data. Trajectories based on 10-m wind fields from both reanalyses show large spatial differences in the Central Arctic, leading to differences in the correlations between modeled and observed 2-m air temperatures. They are most pronounced at Tara, where explained variances amount to 70 % using JRA and 80 % using ERA. The results also suggest that near-surface temperatures at a given site are influenced by the variability of surface temperatures in a domain of about 200 km radius around the site.

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Intercomparison of Surface Heat Transfer Near the Arctic Marginal Ice Zone for Multiple Reanalyses: A Case Study of September 2009

Cited by 31 publications

References 14 publications

A comparison of tracking methods for extreme cyclones in the Arctic basin

A comparison of tracking methods for extreme cyclones in the Arctic basin

On the Increasing Importance of Air-Sea Exchanges in a Thawing Arctic: A Review

The impact of heterogeneous surface temperatures on the 2-m air temperature over the Arctic Ocean under clear skies in spring

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