The nature of Arctic polar vortices in chemistry-climate models

The structure of the Arctic stratospheric polar vortex in three chemistry–climate models (CCMs) taken from the CCMVal-2 intercomparison is examined using zonal mean and geometric-based methods. The geometric methods are employed by taking 2D moments of potential vorticity fields that are representative of the polar vortices in each of the models. This allows the vortex area, centroid location and ellipticity to be determined, as well as a measure of vortex filamentation. The first part of the study uses these diagnostics to examine how well the mean state, variability and extreme variability of the polar vortices are represented in CCMs compared to ERA-40 reanalysis data, and in particular for the UMUKCA-METO, NIWA-SOCOL and CCSR/NIES models. The second part of the study assesses how the vortices are predicted to change in terms of the frequency of sudden stratospheric warmings and their general structure over the period 1960–2100. In general, it is found that the vortices are climatologically too far poleward in the CCMs and produce too few large-scale filamentation events. Only a small increase is observed in the frequency of sudden stratospheric warming events from the mean of the CCMVal-2 models, but the distribution of extreme variability throughout the winter period is shown to change towards the end of the twentyfirst century.

The impact of 21st century Arctic sea ice decline on the climate and mass balance of the Greenland ice sheet and Svalbard’s glaciers and ice caps

The Arctic is a region particularly susceptible to rapid climate change. General circulation models (GCMs) suggest a polar amplification of any global warming signal by a factor of about 1.5 due, in part, to sea ice feedbacks. The dramatic recent decline in multi-year sea ice cover lies outside the standard deviation of the CMIP3 ensemble GCM predictions. Sea ice acts as a barrier between cold air and warmer oceans during winter, as well as inhibiting evaporation from the ocean surface water during the summer. An ice free Arctic would likely have an altered hydrological cycle with more evaporation from the ocean surface leading to changes in precipitation distribution and amount. Using the U.K. Met Office Regional Climate Model (RCM), HadRM3, the atmospheric effects of the observed and projected reduction in Arctic sea ice are investigated. The RCM is driven by the atmospheric GCM HadAM3. Both models are forced with sea surface temperature and sea ice for the period 2061-2090 from the CMIP3 HadGEM1 experiments. Here we use an RCM at 50km resolution over the Arctic and 25km over Svalbard, which captures well the present-day pattern of precipitation and provides a detailed picture of the projected changes in the behaviour of the oceanic-atmosphere moisture fluxes and how they affect precipitation. These experiments show that the projected 21stCentury sea ice decline alone causes large impacts to the surface mass balance (SMB) on Svalbard. However Greenland’s SMB is not significantly affected by sea ice decline alone, but responds with a strongly negative shift in SMB when changes to SST are incorporated into the experiments. This is the first study to characterise the impact of changes in future sea ice to Arctic terrestrial cryosphere mass balance.

Sources of multi-decadal variability in Arctic sea ice extent

The observed dramatic decrease in September sea ice extent (SIE) has been widely discussed in the scientific literature. Though there is qualitative agreement between observations and ensemble members of the Third Coupled Model Intercomparison Project (CMIP3), it is concerning that the observed trend (1979–2010) is not captured by any ensemble member. The potential sources of this discrepancy include: observational uncertainty, physical model limitations and vigorous natural climate variability. The latter has received less attention and is difficult to assess using the relatively short observational sea ice records. In this study multi-centennial pre-industrial control simulations with five CMIP3 climate models are used to investigate the role that the Arctic oscillation (AO), the Atlantic multi-decadal oscillation (AMO) and the Atlantic meridional overturning circulation (AMOC) play in decadal sea ice variability. Further, we use the models to determine the impact that these sources of variability have had on SIE over both the era of satellite observation (1979–2010) and an extended observational record (1953–2010). There is little evidence of a relationship between the AO and SIE in the models. However, we find that both the AMO and AMOC indices are significantly correlated with SIE in all the models considered. Using sensitivity statistics derived from the models, assuming a linear relationship, we attribute 0.5–3.1%/decade of the 10.1%/decade decline in September SIE (1979–2010) to AMO driven variability.

Arctic Oscillation and Antarctic Oscillation in internal atmospheric variability

n this study, we investigated the features of Arctic Oscillation (AO) and Antarctic Oscillation (AAO), that is, the annular modes in the extratropics, in the internal atmospheric variability attained through an ensemble of integrations by an atmospheric general circulation model (AGCM) forced with the global observed SSTs. We focused on the interannual variability of AO/AAO, which is dominated by internal atmospheric variability. In comparison with previous observed results, the AO/AAO in internal atmospheric variability bear some similar characteristics, but exhibit a much clearer spatial structure: significant correlation between the North Pacific and North Atlantic centers of action, much stronger and more significant associated precipitation anomalies, and the meridional displacement of upper-tropospheric westerly jet streams in the Northern/Southern Hemisphere. In addition, we examined the relationship between the North Atlantic Oscillation (NAO)/AO and East Asian winter monsoon (EAWM). It has been shown that in the internal atmospheric variability, the EAWM variation is significantly related to the NAO through upper-tropospheric atmospheric teleconnection patterns.

A model of the three-dimensional evolution of Arctic melt ponds on first-year and multiyear sea ice

During winter the ocean surface in polar regions freezes over to form sea ice. In the summer the upper layers of sea ice and snow melts producing meltwater that accumulates in Arctic melt ponds on the surface of sea ice. An accurate estimate of the fraction of the sea ice surface covered in melt ponds is essential for a realistic estimate of the albedo for global climate models. We present a melt-pond–sea-ice model that simulates the three-dimensional evolution of melt ponds on an Arctic sea ice surface. The advancements of this model compared to previous models are the inclusion of snow topography; meltwater transport rates are calculated from hydraulic gradients and ice permeability; and the incorporation of a detailed one-dimensional, thermodynamic radiative balance. Results of model runs simulating first-year and multiyear sea ice are presented. Model results show good agreement with observations, with duration of pond coverage, pond area, and ice ablation comparing well for both the first-year ice and multiyear ice cases. We investigate the sensitivity of the melt pond cover to changes in ice topography, snow topography, and vertical ice permeability. Snow was found to have an important impact mainly at the start of the melt season, whereas initial ice topography strongly controlled pond size and pond fraction throughout the melt season. A reduction in ice permeability allowed surface flooding of relatively flat, first-year ice but had little impact on the pond coverage of rougher, multiyear ice. We discuss our results, including model shortcomings and areas of experimental uncertainty.

Impact of melt ponds on Arctic sea ice simulations from 1990 to 2007

The extent and thickness of the Arctic sea ice cover has decreased dramatically in the past few decades with minima in sea ice extent in September 2007 and 2011 and climate models did not predict this decline. One of the processes poorly represented in sea ice models is the formation and evolution of melt ponds. Melt ponds form on Arctic sea ice during the melting season and their presence affects the heat and mass balances of the ice cover, mainly by decreasing the value of the surface albedo by up to 20%. We have developed a melt pond model suitable for forecasting the presence of melt ponds based on sea ice conditions. This model has been incorporated into the Los Alamos CICE sea ice model, the sea ice component of several IPCC climate models. Simulations for the period 1990 to 2007 are in good agreement with observed ice concentration. In comparison to simulations without ponds, the September ice volume is nearly 40% lower. Sensitivity studies within the range of uncertainty reveal that, of the parameters pertinent to the present melt pond parameterization and for our prescribed atmospheric and oceanic forcing, variations of optical properties and the amount of snowfall have the strongest impact on sea ice extent and volume. We conclude that melt ponds will play an increasingly important role in the melting of the Arctic ice cover and their incorporation in the sea ice component of Global Circulation Models is essential for accurate future sea ice forecasts.

Impact of a new anisotropic rheology on simulations of Arctic sea ice

new rheology that explicitly accounts for the subcontinuum anisotropy of the sea ice cover is implemented into the Los Alamos sea ice model. This is in contrast to all models of sea ice included in global circulation models that use an isotropic rheology. The model contains one new prognostic variable, the local structure tensor, which quantifies the degree of anisotropy of the sea ice, and two parameters that set the time scale of the evolution of this tensor. The anisotropic rheology provides a subcontinuum description of the mechanical behavior of sea ice and accounts for a continuum scale stress with large shear to compression ratio and tensile stress component. Results over the Arctic of a stand-alone version of the model are presented and anisotropic model sensitivity runs are compared with a reference elasto-visco-plastic simulation. Under realistic forcing sea ice quickly becomes highly anisotropic over large length scales, as is observed from satellite imagery. The influence of the new rheology on the state and dynamics of the sea ice cover is discussed. Our reference anisotropic run reveals that the new rheology leads to a substantial change of the spatial distribution of ice thickness and ice drift relative to the reference standard visco-plastic isotropic run, with ice thickness regionally increased by more than 1 m, and ice speed reduced by up to 50%.

Land-atmosphere energy exchange in Arctic tundra and boreal forest: available data and feedbacks to climate

This paper summarizes and analyses available data on the surface energy balance of Arctic tundra and boreal forest. The complex interactions between ecosystems and their surface energy balance are also examined, including climatically induced shifts in ecosystem type that might amplify or reduce the effects of potential climatic change. High latitudes are characterized by large annual changes in solar input. Albedo decreases strongly from winter, when the surface is snow-covered, to summer, especially in nonforested regions such as Arctic tundra and boreal wetlands. Evapotranspiration (QE) of high-latitude ecosystems is less than from a freely evaporating surface and decreases late in the season, when soil moisture declines, indicating stomatal control over QE, particularly in evergreen forests. Evergreen conifer forests have a canopy conductance half that of deciduous forests and consequently lower QE and higher sensible heat flux (QH). There is a broad overlap in energy partitioning between Arctic and boreal ecosystems, although Arctic ecosystems and light taiga generally have higher ground heat flux because there is less leaf and stem area to shade the ground surface, and the thermal gradient from the surface to permafrost is steeper. Permafrost creates a strong heat sink in summer that reduces surface temperature and therefore heat flux to the atmosphere. Loss of permafrost would therefore amplify climatic warming. If warming caused an increase in productivity and leaf area, or fire caused a shift from evergreen to deciduous forest, this would increase QE and reduce QH. Potential future shifts in vegetation would have varying climate feedbacks, with largest effects caused by shifts from boreal conifer to shrubland or deciduous forest (or vice versa) and from Arctic coastal to wet tundra. An increase of logging activity in the boreal forests appears to reduce QE by roughly 50% with little change in QH, while the ground heat flux is strongly enhanced.

Impact of sudden Arctic sea-ice loss on stratospheric polar ozone recovery

We investigate the sensitivity of Northern Hemisphere polar ozone recovery to a scenario in which there is rapid loss of Arctic summer sea ice in the first half of the 21st century. The issue is addressed by coupling a chemistry climate model to an ocean general circulation model and performing simulations of ozone recovery with, and without, an external perturbation designed to cause a rapid and complete loss of summertime Arctic sea ice. Under this extreme perturbation, the stratospheric response takes the form of a springtime polar cooling which is dynamical rather than radiative in origin, and is caused by reduced wave forcing from the troposphere. The response lags the onset of the sea-ice perturbation by about one decade and lasts for more than two decades, and is associated with an enhanced weakening of the North Atlantic meridional overturning circulation. The stratospheric dynamical response leads to a 10 DU reduction in polar column ozone, which is statistically robust. While this represents a modest loss, it has the potential to induce a delay of roughly one decade in Arctic ozone recovery estimates made in the 2006 Scientific Assessment of Ozone Depletion.

Statistical characterization of arctic polar-night jet oscillation events

A novel diagnostic tool is presented, based on polar-cap temperature anomalies, for visualizing daily variability of the Arctic stratospheric polar vortex over multiple decades. This visualization illustrates the ubiquity of extended-time-scale recoveries from stratospheric sudden warmings, termed here polar-night jet oscillation (PJO) events. These are characterized by an anomalously warm polar lower stratosphere that persists for several months. Following the initial warming, a cold anomaly forms in the middle stratosphere, as does an anomalously high stratopause, both of which descend while the lower-stratospheric anomaly persists. These events are characterized in four datasets: Microwave Limb Sounder (MLS) temperature observations; the 40-yr ECMWF Re-Analysis (ERA-40) and Modern Era Retrospective Analysis for Research and Applications (MERRA) reanalyses; and an ensemble of three 150-yr simulations from the Canadian Middle Atmosphere Model. The statistics of PJO events in the model are found to agree very closely with those of the observations and reanalyses. The time scale for the recovery of the polar vortex following sudden warmings correlates strongly with the depth to which the warming initially descends. PJO events occur following roughly half of all major sudden warmings and are associated with an extended period of suppressed wave-activity fluxes entering the polar vortex. They follow vortex splits more frequently than they do vortex displacements. They are also related to weak vortex events as identified by the northern annular mode; in particular, those weak vortex events followed by a PJO event show a stronger tropospheric response. The long time scales, predominantly radiative dynamics, and tropospheric influence of PJO events suggest that they represent an important source of conditional skill in seasonal forecasting.

Arctic ozone depletion in 2002–2003 measured by ASUR and comparison with POAM observations

We present ozone loss estimated from airborne measurements taken during January–February and March in the Arctic winter 2002/2003. The first half of the winter was characterized by unusually cold temperatures and the second half by a major stratospheric sudden warming around 15–18 January 2003. The potential vorticity maps show a vortex split in the lower stratosphere during the major warming (MW) in late January and during the minor warming in mid-February due to wave 1 amplification. However, the warming can be termed as a vortex displacement event as there was no vortex split during the MW period at 10 hPa. Very low temperatures, large areas of polar stratospheric clouds (PSCs), and high chlorine activation triggered significant ozone loss in the early winter, as the vortex moved to the midlatitude regions. The ozone depletion derived from the ASUR measurements sampled inside the vortex, in conjunction with the Mimosa-Chim model tracer, shows a maximum of 1.3 ± 0.2 ppmv at 450–500 K by late March. The partial column loss derived from the ASUR ozone profiles reaches up to 61 ± 4 DU in 400–550 K in the same period. The evolution of ozone and ozone loss assessed from the ASUR measurements is in very good agreement with POAM observations. The reduction in ozone estimated from the POAM measurements shows a similar maximum of 1.3 ± 0.2 ppmv at 400–500 K or 63 ± 4 DU in 400–550 K in late March. Our study reveals that the Arctic winter 2002/2003 was unique as it had three minor warmings and a MW, yet showed large loss in ozone. No such feature was observed in any other Arctic winter in the 1989–2010 period. In addition, an unusually large ozone loss in December, around 0.5 ± 0.2 ppmv at 450–500 K or 12 ± 1 DU in 400–550 K, was estimated for the first time in the Arctic. A careful and detailed diagnosis with all available published results for this winter exhibits an average ozone loss of 1.5 ± 0.3 ppmv at 450–500 K or 65 ± 5 DU in 400–550 K by the end of March, which exactly matches the ozone depletion derived from the ASUR, POAM and model data. The early ozone loss together with considerable loss afterwards put the warm Arctic winter 2002/2003 amongst the moderately cold winters in terms of the significance of the ozone loss.

Comparison of polar ozone loss rates simulated by one-dimensional and three-dimensional models with Match observations in recent Antarctic and Arctic winters

Simulations of ozone loss rates using a three-dimensional chemical transport model and a box model during recent Antarctic and Arctic winters are compared with experimental loss rates. The study focused on the Antarctic winter 2003, during which the first Antarctic Match campaign was organized, and on Arctic winters 1999/2000, 2002/2003. The maximum ozone loss rates retrieved by the Match technique for the winters and levels studied reached 6 ppbv/sunlit hour and both types of simulations could generally reproduce the observations at 2-sigma error bar level. In some cases, for example, for the Arctic winter 2002/2003 at 475 K level, an excellent agreement within 1-sigma standard deviation level was obtained. An overestimation was also found with the box model simulation at some isentropic levels for the Antarctic winter and the Arctic winter 1999/2000, indicating an overestimation of chlorine activation in the model. Loss rates in the Antarctic show signs of saturation in September, which have to be considered in the comparison. Sensitivity tests were performed with the box model in order to assess the impact of kinetic parameters of the ClO-Cl2O2 catalytic cycle and total bromine content on the ozone loss rate. These tests resulted in a maximum change in ozone loss rates of 1.2 ppbv/sunlit hour, generally in high solar zenith angle conditions. In some cases, a better agreement was achieved with fastest photolysis of Cl2O2 and additional source of total inorganic bromine but at the expense of overestimation of smaller ozone loss rates derived later in the winter.

High resolution simulation of recent Arctic and Antarctic stratospheric chemical ozone loss compared to observations

Simulations of polar ozone losses were performed using the three-dimensional high-resolution (1∘ × 1∘) chemical transport model MIMOSA-CHIM. Three Arctic winters 1999–2000, 2001–2002, 2002–2003 and three Antarctic winters 2001, 2002, and 2003 were considered for the study. The cumulative ozone loss in the Arctic winter 2002–2003 reached around 35% at 475 K inside the vortex, as compared to more than 60% in 1999–2000. During 1999–2000, denitrification induces a maximum of about 23% extra ozone loss at 475 K as compared to 17% in 2002–2003. Unlike these two colder Arctic winters, the 2001–2002 Arctic was warmer and did not experience much ozone loss. Sensitivity tests showed that the chosen resolution of 1∘ × 1∘ provides a better evaluation of ozone loss at the edge of the polar vortex in high solar zenith angle conditions. The simulation results for ozone, ClO, HNO3, N2O, and NO y for winters 1999–2000 and 2002–2003 were compared with measurements on board ER-2 and Geophysica aircraft respectively. Sensitivity tests showed that increasing heating rates calculated by the model by 50% and doubling the PSC (Polar Stratospheric Clouds) particle density (from 5 × 10−3 to 10−2 cm−3) refines the agreement with in situ ozone, N2O and NO y levels. In this configuration, simulated ClO levels are increased and are in better agreement with observations in January but are overestimated by about 20% in March. The use of the Burkholder et al. (1990) Cl2O2 absorption cross-sections slightly increases further ClO levels especially in high solar zenith angle conditions. Comparisons of the modelled ozone values with ozonesonde measurement in the Antarctic winter 2003 and with Polar Ozone and Aerosol Measurement III (POAM III) measurements in the Antarctic winters 2001 and 2002, shows that the simulations underestimate the ozone loss rate at the end of the ozone destruction period. A slightly better agreement is obtained with the use of Burkholder et al. (1990) Cl2O2 absorption cross-sections.

Identifying uncertainties in Arctic climate change projections

Wide ranging climate changes are expected in the Arctic by the end of the 21st century, but projections of the size of these changes vary widely across current global climate models. This variation represents a large source of uncertainty in our understanding of the evolution of Arctic climate. Here we systematically quantify and assess the model uncertainty in Arctic climate changes in two CO2 doubling experiments: a multimodel ensemble (CMIP3) and an ensemble constructed using a single model (HadCM3) with multiple parameter perturbations (THC-QUMP). These two ensembles allow us to assess the contribution that both structural and parameter variations across models make to the total uncertainty and to begin to attribute sources of uncertainty in projected changes. We find that parameter uncertainty is an major source of uncertainty in certain aspects of Arctic climate. But also that uncertainties in the mean climate state in the 20th century, most notably in the northward Atlantic ocean heat transport and Arctic sea ice volume, are a significant source of uncertainty for projections of future Arctic change. We suggest that better observational constraints on these quantities will lead to significant improvements in the precision of projections of future Arctic climate change.

The Greenland Ice Sheet's surface mass balance in a seasonally sea-ice free Arctic

General circulation models predict a rapid decrease in sea ice extent with concurrent increases in near surface air temperature and precipitation in the Arctic over the 21st century. This has led to suggestions that some Arctic land ice masses may experience an increase in accumulation due to enhanced evaporation from a seasonally sea ice free Arctic Ocean. To investigate the impact of this phenomenon on Greenland ice sheet climate and surface mass balance (SMB) a regional climate model, HadRM3, was used to force an insolation-temperature melt SMB model. A set of experiments designed to investigate the role of sea ice independently from sea surface temperature (SST) forcing are described. In the warmer and wetter SI + SST simulation Greenland experiences a 23% increase in winter SMB but 65% reduced summer SMB, resulting in a net decrease in the annual value. This study shows that sea ice decline contributes to the increased winter balance, causing 25% of the increase in winter accumulation; this is largest in eastern Greenland as the result of increased evaporation in the Greenland Sea. These results indicate that the seasonal cycle of Greenland's SMB will increase dramatically as global temperatures increase, with the largest changes in temperature and precipitation occurring in winter. This demonstrates that the accurate prediction of changes in sea ice cover is important for predicting Greenland SMB and ice sheet evolution.