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High-resolution sea surface observations by spaceborne synthetic aperture radar (SAR) instruments are sorely neglected resources for meteorological applications in polar regions. Such radar observations provide information about wind speed and direction based on wind-induced roughness of the sea surface. The increasing coverage of SAR observations in polar regions calls for the development of SAR-specific applications that make use of the full information content of this valuable resource. Here we provide examples of the potential of SAR observations to provide details of the complex, mesoscale wind structure during polar low events, and examine the performance of two current wind retrieval methods. Furthermore, we suggest a new approach towards accurate wind vector retrieval of complex wind fields from SAR observations that does not require a priori wind direction input that the most common retrieval methods are dependent on. This approach has the potential to be particularly beneficial for numerical forecasting of weather systems with strong wind gradients, such as polar lows.

The Arctic sea-ice extent has strongly declined over recent decades. A large inter-annual variability is superimposed on this negative trend. Previous studies have emphasised a significant warming effect associated with latent energy transport into the Arctic region, in particular due to an enhanced greenhouse effect associated with the convergence of the humidity transport over the Arctic. The atmospheric energy transport into the Arctic is mostly accomplished by waves such as Rossby waves and cyclones. Here we present a systematic study of the effect on Arctic sea ice of these atmospheric wave types. Through a regression analysis we investigate the coupling between transport anomalies of both latent and dry-static energy and sea-ice anomalies. From the state-of-the-art ERA5 reanalysis product the latent and dry-static transport over the Arctic boundary (70$$^{\circ }$$ ∘ N) is calculated. The transport is then split into transport by planetary and synoptic-scale waves using a Fourier decomposition. The results show that latent energy transport as compared to that of dry-static shows a much stronger potential to decrease sea ice concentration. However, taking into account that the variability of dry-static transport is of an order of magnitude larger than latent, the actual impact on the sea ice appears similar for the two components. In addition, the energy transport by planetary waves causes a strong decline of the sea ice concentration whereas the transport by synoptic-scale waves shows only little effect on the sea ice. The study emphasises the importance of the large-scale waves on the sea ice variability.

This study gives a comprehensive picture of how atmospheric large-scale circulation is related to moisture transport and to distributions of moisture, clouds, and surface downward longwave radiation in the Arctic in winter. Anomaly distributions of the abovementioned variables are compared in 30 characteristic wintertime atmospheric circulation regimes, which are allocated from 15 years (2003–17) of mean sea level pressure data of ERA-Interim reanalysis applying the self-organizing map method. The characteristic circulation regimes are further related to known climate indices—the North Atlantic Oscillation (NAO), the Arctic Oscillation (AO), and Greenland blocking index—as well as to a frequent high pressure pattern across the Arctic Ocean from Siberia to North America, herein called the Arctic bridge. Effects of large-scale circulation on moisture, cloud, and longwave radiation are to a large extent occurring through the impact of horizontal moisture transport. Evaporation is typically not efficient enough to shape those distributions, and much of the moisture evaporated in the Arctic is transported southward. The positive phase of the NAO and AO increases moisture and clouds in northern Europe and the eastern North Atlantic Ocean, and a strong Greenland blocking typically increases those in the southwest of Greenland. When the Arctic bridge is lacking, the amount of moisture, clouds, and downward longwave radiation is anomalously high near the North Pole. Our results reveal a strong dependence of moisture, clouds, and longwave radiation on atmospheric pressure fields, which also appears to be important from a climate change perspective.

© Copyright 19 June 2019 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC §108) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form, such as on a website or in a searchable database, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. All AMS journals and monograph publications are registered with the Copyright Clearance Center (http://www.copyright.com). Questions about permission to use materials for which AMS holds the copyright can also be directed to permissions@ametsoc.org. Additional details are provided in the AMS Copyright Policy statement, available on the AMS website (http://www.ametsoc.org/CopyrightInformation). This study evaluates the performance of six atmospheric reanalyses (ERA-Interim, ERA5, JRA-55, CFSv2, MERRA-2, and ASRv2) over Arctic sea ice from winter to early summer. The reanalyses are evaluated using observations from the Norwegian Young Sea Ice campaign (N-ICE2015), a 5-month ice drift in pack ice north of Svalbard. N-ICE2015 observations include surface meteorology, vertical profiles from radiosondes, as well as radiative and turbulent heat fluxes. The reanalyses simulate surface analysis variables well throughout the campaign, but have difficulties with most forecast variables. Wintertime (January–March) correlation coefficients between the reanalyses and observations are above 0.90 for the surface pressure, 2-m temperature, total column water vapor, and downward longwave flux. However, all reanalyses have a positive wintertime 2-m temperature bias, ranging from 1° to 4°C, and negative (i.e., upward) net longwave bias of 3–19 W m−2. These biases are associated with poorly represented surface inversions and are largest during cold-stable periods. Notably, the recent ERA5 and ASRv2 datasets have some of the largest temperature and net longwave biases, respectively. During spring (April–May), reanalyses fail to simulate observed persistent cloud layers. Therefore they overestimate the net shortwave flux (5–79 W m−2) and underestimate the net longwave flux (8–38 W m−2). Promisingly, ERA5 provides the best estimates of downward radiative fluxes in spring and summer, suggesting improved forecasting of Arctic cloud cover. All reanalyses exhibit large negative (upward) residual heat flux biases during winter, and positive (downward) biases during summer. Turbulent heat fluxes over sea ice are simulated poorly in all seasons.

A doubling of the atmospheric CO2 content leads to global warming that is amplified in the polar regions. The CO2 forcing also leads to a change of the atmospheric energy transport. This transport change affects the local warming induced by the CO2 forcing. Using the Community Earth System Model (CESM), the direct response to the transport change is investigated. Divergences of the transport change associated with a CO2 doubling are implemented as a forcing in the 1 × CO2 preindustrial control climate. This forcing is zero in the global mean. In response to a CO2 increase in CESM, the northward atmospheric energy transport decreases at the Arctic boundary. However, the transport change still leads to a warming of the Arctic. This is due to a shift between dry static and latent transport components, so that although the dry static transport decreases, the latent transport increases at the Arctic boundary, which is consistent with other model studies. Because of a greenhouse effect associated with the latent transport, the cooling caused by a change of the dry static component is more than compensated for by the warming induced by the change of the latent transport. Similar results are found for the Antarctic region, but the transport change is larger in the Southern Hemisphere than in its northern counterpart. As a consequence, the Antarctic region warms to the extent that this warming leads to global warming that is likely enhanced by the surface albedo feedback associated with considerable ice retreat in the Southern Hemisphere.

There is a growing demand for the estimation of solar energy potential at high latitude locations. This study compares four datasets; Cloud, Albedo, Radiation dataset Edition 2 (CLARA), Surface Solar Radiation dataset – Heliosat Edition 2 (SARAH), ECMWF Reanalysis 5 (ERA5) and Arctic System Reanalysis v2 (ASR) on high latitude locations. Global horizontal irradiance (GHI) from these datasets is compared with in-situ ground-measurements over multiple locations in Norway. The first two datasets are mainly based on satellite estimation of solar radiation, while the latter two are based on a combination of a weather-prediction model, satellite data, and other observations. The datasets are evaluated against quality-controlled in-situ measurements of solar radiation from pyranometers. Overall, CLARA, SARAH, and ERA5 show moderate errors, while those of ASR are considerably larger. Monthly averages of global horizontal irradiance have mean absolute deviation (MAD) of 5.6 Wm−2, 5.0 Wm−2, 6.8 Wm−2, and 16.1 Wm−2 for CLARA, SARAH, ERA5, and ASR, respectively. Seasonal error analysis of these datasets reveals that CLARA and SARAH have low errors in all seasons. The datasets are classified into clear-sky, intermediate-cloudiness, and overcast categories, by using two thresholds of cloudiness based on the ratio of radiation at ground to its corresponding clear-sky value (clear-sky index). The categories obtained from satellite and reanalysis data are then compared against estimates based on corresponding in-situ observations; this analysis shows that both CLARA and SARAH perform better than ERA5 and ASR for these categories. SARAH and CLARA perform similarly in all types of conditions, but a gradual increase in errors for an increase of cloudiness is observed for ERA5 and ASR. Yearly energy analysis shows that CLARA performs better than other datasets for locations above latitude 65°N, and SARAH performs better in locations below 65°N. A further analysis is performed to assess the cloud sensing abilities of ERA5. On a shorter time scale, there are errors due to inaccurate representation of clouds, however on longer time scales i.e. months and years, these errors are considerably reduced. ERA5 is observed to overestimate TCWC (the total cloud water content defined as the mass of water and ice in a cloud) in clear-sky and intermediate-cloudy categories, while in overcast category it is underestimated. Generally, an overestimation of solar radiation is observed in reanalysis and an underestimation is observed in satellite methods.

Source at https://doi.org/10.5194/tc-13-491-2019. The accuracy of the initial state is very important for the quality of a forecast, and data assimilation is crucial for obtaining the best-possible initial state. For many years, sea-ice concentration was the only parameter used for assimilation into numerical sea-ice models. Sea-ice concentration can easily be observed by satellites, and satellite observations provide a full Arctic coverage. During the last decade, an increasing number of sea-ice related variables have become available, which include sea-ice thickness and snow depth, which are both important parameters in the numerical sea-ice models. In the present study, a coupled ocean–sea-ice model is used to assess the assimilation impact of sea-ice thickness and snow depth on the model. The model system with the assimilation of these parameters is verified by comparison with a system assimilating only ice concentration and a system having no assimilation. The observations assimilated are sea ice concentration from the Ocean and Sea Ice Satellite Application Facility, thin sea ice from the European Space Agency's (ESA) Soil Moisture and Ocean Salinity mission, thick sea ice from ESA's CryoSat-2 satellite, and a new snow-depth product derived from the National Space Agency's Advanced Microwave Scanning Radiometer (AMSR-E/AMSR-2) satellites. The model results are verified by comparing assimilated observations and independent observations of ice concentration from AMSR-E/AMSR-2, and ice thickness and snow depth from the IceBridge campaign. It is found that the assimilation of ice thickness strongly improves ice concentration, ice thickness and snow depth, while the snow observations have a smaller but still positive short-term effect on snow depth and sea-ice concentration. In our study, the seasonal forecast showed that assimilating snow depth led to a less accurate long-term estimation of sea-ice extent compared to the other assimilation systems. The other three gave similar results. The improvements due to assimilation were found to last for at least 3–4 months, but possibly even longer.

Horizontal moisture transport has a manifold role in the Arctic climate system as it distributes atmospheric water vapour and thereby shapes the radiative and hydrological conditions. Moisture tran ...

Atmospheric meridional energy transport into the Arctic plays an important role in Arctic weather and climate. The transport of latent energy in the form of water vapour strongly influences the Arctic atmosphere. The transport is achieved by circulation mechanisms on various scales and is largely comprised of extreme transport events. Here, we use a Fourier-based method of dividing the latent energy transport into spatial scales and investigate the extent to which extreme events in latent energy transport on planetary and synoptic scales have changed over the past four decades, and how they influence the Arctic winter temperatures. We find that wintertime extreme transport events on planetary scales are associated with warm temperature anomalies across the entire Arctic, while the extreme events on synoptic scales have less impact on the Arctic temperatures. We show that over the past four decades, there has been a significant increase in the wintertime latent energy transport by planetary-scale systems, and a decrease in synoptic-scale transport. This shift may have contributed to the amplified warming observed in the Arctic winter over the past decades.

Svalbard is a near pristine Arctic environment, where long-range transport from mid-latitudes is an important air pollution source. Thus, several previous studies investigated the background nitrogen oxides (NOx) and tropospheric ozone (O3) springtime chemistry in the region. However, there are also local anthropogenic emission sources on the archipelago such as coal power plants, ships and snowmobiles, which may significantly alter in situ atmospheric composition. Measurement results from three independent research projects were combined to identify the effect of emissions from various local sources on the background concentration of NOx and O3 in Svalbard. The hourly meteorological and chemical data from the ground-based stations in Adventdalen, Ny-Ålesund and Barentsburg were analysed along with daily radiosonde soundings and weekly data from O3 sondes. The data from the ERA5 reanalysis were used to evaluate the prevailing synoptic conditions during the fieldwork. Although the correlation between the NOx concentrations in the three settlements was low due to dominant influence of the local atmospheric circulation, cases with common large-scale meteorological conditions increasing the local pollutant concentration at all sites were identified. In colder and calmer days and days with temperature inversions, the concentrations of NOx were higher. In contrast to NOx values, O3 concentrations in Barentsburg and at the Zeppelin station in Ny-Ålesund correlated strongly, and hence the prevailing synoptic situation and long-range transport of air masses were controlling factors for them. The Lagrangian models HYSPLIT and FLEXPART have been used to investigate air mass transport and transformations during the large scale O3 depletion and enrichment events. The factors affecting Arctic springtime photochemistry of O3 have been investigated thoroughly using Lagrangian and Eulerian numerical weather prediction model data and Metop GOME-2 satellite observations.

Superimposed on a strong observed decline in Arctic sea ice extent there is large inter-annual variability. Recent research indicates that atmospheric temperature fluctuations are the main drivers for this variability. They can result both from local ocean heat release and from poleward atmospheric energy transport. Previous studies have emphasised a significant warming effect associated with latent energy transport into the Arctic region. In particular this is due to enhanced greenhouse effect associated with the convergence of the humidity transport over the Arctic. While previously some sea ice minima events have been linked to anomalous moist air convergence, a systematic study of this linkage between energy transport and sea ice variability was missing. Through a regression analysis we here investigate the coupling between transport anomalies of both latent and dry-static energy and sea ice anomalies. From the state-of-the-art ERA5 reanalysis product the latent and dry-static transport over the Arctic boundary (70°N) is calculated. The transport is then split into transport by planetary and synoptic-scale waves using a Fourier decomposition. Lagged regression analysis of sea ice concentration anomalies on the transport anomalies reveal the statistical linkage between the occurrence of sea ice anomalies after transport events. The results show that latent energy transport as compared to that of dry-static energy induces a much stronger decrease in sea ice concentration. One day after maximum of the latent transport event by planetary waves, sea-ice concentration shows a significant decrease lasting up to at least 45 days. In addition, the energy transport by planetary waves shows a greater effect on the sea ice concentration than transport by synoptic-scale waves. Hence, this study emphasizes the important impact of latent energy transport by planetary waves on the sea ice variability.

In this study, the potential for sea ice concentration prediction using machine‐learning methods is investigated. Three different sea ice prediction models are compared: one high‐resolution dynamical assimilative model and two statistical machine‐learning models. The properties of all three models are explored, and the quality of their forecasts is compared. The dynamical model is a state‐of‐the‐art coupled ocean and sea ice ensemble‐prediction system with assimilation. The observations assimilated are high‐resolution sea ice concentration from synthetic aperture radar (SAR) and sea surface temperature from infrared instruments. The machine‐learning prediction models are a fully convolutional network and a k‐nearest neighbors method. These methods use several variables as input for the prediction: sea ice concentration, sea surface temperature, and 2‐m air temperature. Earlier studies have applied machine‐learning approaches primarily for seasonal ice forecast. Here we focus on short‐term predictions with a length of 1–4 weeks, which are of high interest for marine operations. The goal is to predict the future state of the sea ice using the same categories as traditional ice charts. The machine‐learning forecasts were compared to persistence, which is the assumption that the sea ice does not change over the forecasting period. The machine‐learning forecasts were found to improve upon persistence in periods of substantial change. In addition, compared to the dynamical model, the k‐nearest neighbor algorithm was found to improve upon the 7‐day forecast during a period of small sea ice variations. The fully convolutional network provided similar quality as the dynamical forecast. The study shows that there is a potential for sea ice predictions using machine‐learning methods.

Atmospheric energy transport into the Arctic (>70° N) has been shown to greatly alter the Arctic temperatures and the development of the Arctic weather and climate. Recent research suggests that latent energy transport into the Arctic by large, planetary-scale atmospheric systems cause a stronger and more long-lasting impact on near surface temperatures, than energy transported by smaller, synoptic scale systems. This implies that Rossby waves impact Arctic climate more than synoptic cyclones. Therefore, shifts in circulation patterns driving atmospheric energy transport into the Arctic on different scales have a potential to change Arctic climate.Here, we show that the annual mean impact of latent energy transport on Arctic temperatures is dominated by the winter season transport. Furthermore, by examining the ERA5 dataset for the years 1979-2018, we find that over the past four decades, there has been a shift in the mean winter season latent energy transport, from smaller, synoptic scale systems (-0.03 PW/decade), towards larger, planetary scale systems (+0.05 PW/decade) which as mentioned, have a larger climatic impact. As a consequence, this shift is estimated to have increased the Arctic temperatures. We find that the trends are driven by an increase in the extreme transport events (here we examine the upper 97.5th percentile). The upper extremes have increased more than the average on the planetary scale, and decreased more on the synoptic scale. The decrease in extreme synoptic scale transport at 70° N has been confirmed in other analyses of high vorticity weather systems. By examining the extreme transport events on seasonal scales, we reveal differences in the temporal distribution of planetary vs. synoptic scale extreme events, and identify areas of the Arctic that receive the strongest impact with respect to increases in near-surface temperatures.

The Arctic region shows some of the world's most significant signs of climate change. The atmospheric energy transport plays an important role for the Arctic climate; the atmospheric transport contributes an amount of energy into the Arctic that is comparable to that provided directly by the sun. From recently developed Fourier and wavelet based methods it has been found that the planetary component of the latent heat transport affects that Arctic surface temperatures stronger than the decomposed dry-static energy transport and the synoptic scale component of the latent heat transport. A large concern for humanity is that the climate change in polar regions will lead to significant melting of the ice sheets and glaciers. In fact the discharge water from the Greenland ice sheet has recently increased to the extent that this ice sheet is one of the major contributorsto sea-level rise. Here we test the hypothesis that the recent rapid increase in melt of the Greenland ice sheet is linked to a shift of planetary-scale waves transporting warm and humid air over the ice sheet.The effect of the atmospheric energy transport is investigated by correlating the divergence of energy over the Greenland ice sheet with the surface mass balance of this ice sheet. The divergence of latent heat transport is found to correlate positively with the surface mass balance along the edges of the ice sheet, and negatively in the interior. This indicates that a convergence of latent at the edges of the ice sheet lead to a increased mass discharge from the ice sheet, whilst in the interior converging latent heat indicates an accumulation of mass to the ice sheet. To investigate the effect of transport by planetary and synoptic scale waves on the Greenland ice sheet surface mass balance the mass flux component of the transport divergence is decomposed into wavenumbers through the application of a Fourier series. The divergences of transport contributions of each wavenumber are then correlated with the surface mass balance of the Greenland ice sheet. The correlations between the surface-mass balance and divergence of transport contributions by different wavenumbers reveals the relative impact of atmospheric circulation systems, such as Rossby waves and cyclones, on the Greenland ice sheet mass balance. Further, identifying shifts in the circulation patterns over Greenland by applying self organizing maps, or similar methods, and investigations of how these circulation patterns affect the energy transport over Greenland by atmospheric waves of different scales are also pursued.

The atmospheric meridional energy transport in the Northern Hemisphere midlatitudes is mainly accomplished by planetary and synoptic waves. A decomposition into wave components highlights the strong seasonal dependence of the transport, with both the total transport and the contributions from planetary and synoptic waves peaking in winter. In both winter and summer months, poleward transport extremes primarily result from a constructive interference between planetary and synoptic motions. The contribution of the mean meridional circulation is close to climatology. Equatorward transport extremes feature a mean meridional equatorward transport in winter, while the planetary and synoptic modes mostly transport energy poleward. In summer, a systematic destructive interference occurs, with planetary modes mostly transporting energy equatorward and synoptic modes again poleward. This underscores that baroclinic conversion dominates regardless of season in the synoptic wave modes, whereas the planetary waves can be either free or forced, depending on the season.

The capability of a regional (AROME‐Arctic) and a global (ECMWF HRES) weather‐prediction model are compared for simulating a well‐observed polar low (PL). This PL developed on 3–4 March 2008 and was measured by dropsondes released from three flights during the IPY‐THORPEX campaign. Validation against these measurements reveals that both models simulate the PL reasonably well. AROME‐Arctic appears to represent the cloud structures and the high local variability more realistically. The high local variability causes standard error statistics to be similar for AROME‐Arctic and ECMWF HRES. A spatial verification technique reveals that AROME‐Arctic has improved skills at small scales for extreme values. However, the error growth of the forecast, especially in the location of the PL, is faster in AROME‐Arctic than in ECMWF HRES. This is likely associated with larger convection‐induced perturbations in the former than the latter model. Additionally, the PL development is analysed. This PL has two stages, an initial baroclinic and a convective mature stage. Sensible heat flux and condensational heat release both contribute to strengthen the initial baroclinic environment. In the mature stage, latent heat release appears to maintain the system. At least two conditions must be met for this stage to develop: (a) the sensible heat flux sufficiently destabilises the local environment around the PL, and (b) sufficient moisture is available for condensational heat release. More than half of the condensed moisture within the system originates from the surroundings. The propagation of the PL is “pulled” towards the area of strongest condensational heating. Finally, the sensitivity of the PL to the sea‐surface temperature is analysed. The maximum near‐surface wind speed connected to the system increases by 1–2 m·s−1 per K of surface warming and a second centre develops in cases of highly increased temperature.

Accepted manuscript version. Published version available at https://doi.org/10.1016/j.solener.2018.05.009. Licensed CC BY-NC-ND 4.0. Estimating/retrieving solar radiation through satellite-based remote sensing provides larger spatial coverage compared to other methods. Accurate estimates of incoming solar radiation is important when planning new solar energy installations. In addition, these estimates are also used in climate studies. Geostationary satellites are ideal for estimating solar radiation but cannot be used for high latitudes because of an unfavourable viewing angle; however, polar-orbiting satellites provide an alternative. CLoud, Albedo RAdiation edition 2 (CLARA-A2) is the latest retrieval product of cloud properties, surface albedo and surface solar radiation by Satellite Application Facility on Climate Monitoring (CM-SAF) based on Advance Very High Resolution Radiometer (AVHRR) observations from polar orbiting satellites. This data set covers the whole earth and provides daily and monthly averages. In this study, we have evaluated the CLARA-A2 data set and the previous version CLARA-A1 to in-situ high-quality observations from specific locations in Scandinavia, with a focus on solar radiation at high latitudes. The results show that both datasets perform within the target accuracies of CM-SAF, although the new data points, which were previously not available in CLARA-A1 due to snow-cover and cloud differentiation, have high deviations. Nevertheless, yearly average energy estimates are more accurate in CLARA-A2 because of these new points. For Swedish locations, mean absolute deviation (MAD) of 8.1 W m−2 and 8.7 W m−2 for CLARA-A1 and A2 respectively were calculated for updated values. Similarly, for Norwegian locations MAD of 8 W m−2 and 8.9 W m−2 were calculated for CLARA-A1 and A2. Overall, for all locations MAD lies at 8.1 W m−2 and 8.8 W m−2 for CLARA-A1 and A2, respectively. CLARA A2 has more temporal data points than CLARA A1, however, the MAD of the new data points that were not available in CLARA-A1 are 15.2 W m−2 and 17.7 W m−2 for Swedish and Norwegian sites, respectively.

Link to publishers version: http://dx.doi.org/10.1016/j.coldregions.2016.11.002 Hazardous marine icing is a major concern for ships operating in Arctic waters during freezing conditions. Sea spray generated by the interaction between a ship and ocean waves is the most important water source in these dangerous icing events. Although there exist several data sets with observations of ice accretion in conjunction with meteorological and oceanographic parameters, these data sets often have shortcomings and only a few are obtained in Arctic-Norwegian waters. In this study, icing rates from a large coast-guard vessel type, the KV Nordkapp class, are used for verification of a newly proposed Marine-Icing Model for the Norwegian COast Guard (MINCOG). Ship observations, NOrwegian ReAnalysis 10km data (NORA10), and wave data based on empirical statistical relationships between wind and waves are all applied in MINCOG and the results are compared. The model includes two different empirically-derived formulations of spray flux. It is found that in general the best results for different verification scores are obtained by using a combination of observed atmosphere and ocean-wave parameters from the ships, and wave period and direction from NORA10, regardless of the spray-flux formulation applied. Furthermore, the results illuminate that wave parameters derived from formulas based on empirical relationships between the local wind speed and significant wave height and wave period, compared to those obtained from observations or NORA10, considerably worsen icing-rate predictions in Arctic-Norwegian waters when applied in MINCOG.

In this study, we show assimilation results from a coupled ocean sea-ice model. The model has a horizontal resolution of 2.5 km. In the assimilation system, we assimilate high-resolution ice charts, structured on a 1 km grid. We compare the assimilation of passive microwave observations with the assimilation of ice charts. It is shown that the ice charts have a larger impact on the assimilation system than the passive microwave observations. In addition, a few results from the assimilation system with ice charts are shown. These indicate improvements for the assimilation system assimilating ice charts compared to a free-run without assimilation and an assimilation system assimilating passive microwave observations.

We investigate factors influencing European winter (DJFM) air temperatures for the period 1979–2015 with the focus on changes during the recent period of rapid Arctic warming (1998–2015). We employ meteorological reanalyses analysed with a combination of correlation analysis, two pattern clustering techniques, and back‐trajectory airmass identification. In all five selected European regions, severe cold winter events lasting at least 4 days are significantly correlated with warm Arctic episodes. Relationships during opposite conditions of warm Europe/cold Arctic are also significant. Correlations have become consistently stronger since 1998. Large‐scale pattern analysis reveals that cold spells are associated with the negative phase of the North Atlantic Oscillation (NAO‐) and the positive phase of the Scandinavian (SCA+) pattern, which in turn are correlated with the divergence of dry‐static energy transport. Warm European extremes are associated with opposite phases of these patterns and the convergence of latent heat transport. Airmass trajectory analysis is consistent with these findings, as airmasses associated with extreme cold events typically originate over continents, while warm events tend to occur with prevailing maritime airmasses. Despite Arctic‐wide warming, significant cooling has occurred in northeastern Europe owing to a decrease in adiabatic subsidence heating in airmasses arriving from the southeast, along with increased occurrence of circulation patterns favouring low temperature advection. These dynamic effects dominated over the increased mean temperature of most circulation patterns. Lagged correlation analysis reveals that SCA‐ and NAO+ are typically preceded by cold Arctic anomalies during the previous 2–3 months, which may aid seasonal forecasting., Wintertime associations of warm weather in the Arctic and cold events in Europe have become stronger during the Arctic amplification of climate warming. Although winters have warmed in Europe, significant winter cooling has occurred in northeastern Europe in cases of airmasses originating from southeast. The positive phase of the North Atlantic Oscillation is typically preceded by cold Arctic anomalies during the previous 2–3 months, which may aid seasonal forecasting.

The timing of melt onset affects the surface energy uptake throughout the melt season. Yet the processes triggering melt and causing its large interannual variability are not well understood. Here we show that melt onset over Arctic sea ice is initiated by positive anomalies of water vapor, clouds, and air temperatures that increase the downwelling longwave radiation (LWD) to the surface. The earlier melt onset occurs; the stronger are these anomalies. Downwelling shortwave radiation (SWD) is smaller than usual at melt onset, indicating that melt is not triggered by SWD. When melt occurs early, an anomalously opaque atmosphere with positive LWD anomalies preconditions the surface for weeks preceding melt. In contrast, when melt begins late, clearer than usual conditions are evident prior to melt. Hence, atmospheric processes are imperative for melt onset. It is also found that spring LWD increased during recent decades, consistent with trends toward an earlier melt onset.

The atmospheric northward energy transport plays a crucial role for the Arctic climate; this transport brings to the Arctic an amount of energy comparable to that provided directly by the sun. The transport is accomplished by atmospheric waves–for instance large-scale planetary waves and meso-scale cyclones–and the zonal-mean circulation. These different components of the energy transport impact the Arctic climate differently. A split of the transport into stationary and transient waves constitutes a traditional way of decomposing the transport. However this procedure does not take into account the transport accomplished separately by the planetary and synoptic-scale waves. Here a Fourier decomposition is applied, which decomposes the transport with respect to zonal wave numbers. Reanalysis and model data reveal that the planetary waves impact Arctic temperatures much more than do synoptic-scale waves. In addition the latent transport by these waves affects the Arctic climate more than does the dry-static part. Finally, the EC-Earth model suggests that changes of the energy transport over the twentyfirst century will contribute to Arctic warming, despite the fact that in this model the total energy transport to the Arctic will decrease. This apparent contradictory result is due to the cooling induced by a decrease of the dry-static transport by planetary waves being more than compensated for by a warming caused by the latent counterpart.

The Arctic summer sea ice has diminished fast in recent decades. A strong year-to-year variability on top of this trend indicates that sea ice is sensitive to short-term climate fluctuations. Previous studies show that anomalous atmospheric conditions over the Arctic during spring and summer affect ice melt and the September sea ice extent (SIE). These conditions are characterized by clouds, humidity, and heat anomalies that all affect downwelling shortwave (SWD) and longwave (LWD) radiation to the surface. In general, positive LWD anomalies are associated with cloudy and humid conditions, whereas positive anomalies of SWD appear under clear-sky conditions. Here the effect of realistic anomalies of LWD and SWD on summer sea ice is investigated by performing experiments with the Community Earth System Model. The SWD and LWD anomalies are studied separately and in combination for different seasons. It is found that positive LWD anomalies in spring and early summer have significant impact on the September SIE, whereas winter anomalies show only little effect. Positive anomalies in spring and early summer initiate an earlier melt onset, hereby triggering several feedback mechanisms that amplify melt during the succeeding months. Realistic positive SWD anomalies appear only important if they occur after the melt has started and the albedo is significantly reduced relative to winter conditions. Simulations where both positive LWD and negative SWD anomalies are implemented simultaneously, mimicking cloudy conditions, reveal that clouds during spring have a significant impact on summer sea ice while summer clouds have almost no effect.

Source at https://doi.org/10.1017/jog.2018.33. Increasing ship traffic and human activity in the Arctic has led to a growing demand for accurate Arctic weather forecast. High-quality forecasts obtained by models are dependent on accurate initial states achieved by assimilation of observations. In this study, a multi-variate nudging (MVN) method for assimilation of sea-ice variables is introduced. The MVN assimilation method includes procedures for multivariate update of sea-ice volume and concentration, and for extrapolation of observational information spatially. The MVN assimilation scheme is compared with the Ensemble Kalman Filter (EnKF) using the Los Alamos Sea Ice Model. Two multi-variate experiments are conducted: in the first experiment, sea-ice thickness from the European Space Agency’s Soil Moisture and Ocean Salinity mission is assimilated, and in the second experiment, sea-ice concentration from the ocean and Sea Ice Satellite Application Facility is assimilated. The multivariate effects are cross-validated by comparing the model with non-assimilated observations. It is found that the simple and computationally cheap MVN method shows comparable skills to the more complicated and expensive EnKF method for multivariate update. In addition, we show that when few observations are available, the MVN method is a significant model improvement compared to the version based on one-dimensional sea-ice concentration assimilation.

This is the pre-peer reviewed version of the following article: Stoll, P., Graversen, R., Noer, G. & Hodges, K. (2018). An objective global climatology of polar lows based on reanalysis data. Quarterly Journal of the Royal Meteorological Society. https://doi.org/10.1002/qj.3309, which has been published in final form at https://doi.org/10.1002/qj.3309. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. Here we present an objective global climatology of polar lows. In order to obtain objective detection criteria, the efficacy of several parameters for separating polar lows from other cyclones has been compared. The comparison and the climatology are based on the ERA‐Interim reanalysis from 1979 ‐ 2016 and the high‐resolution Arctic System Reanalysis from 2000 ‐ 2012. The most effective parameters in separating polar lows from other extra‐tropical cyclones were found to be the difference between the sea‐level pressure at the centre of the low and its surroundings, the difference in the potential temperature between the sea surface and the 500 hPa level, and the tropopause wind speed poleward of the system. Other parameters often used to identify polar lows, such as the 10 m wind speed and the temperature difference between the sea surface and the 700 hPa level, were found to be less effective. The climatologies reveal that polar lows occur in all marine basins at high latitudes, but with high occurrence density in the vicinity of the sea‐ice edge and coastal zones. The regions showing the highest degree of polar‐low activity are the Denmark Strait and the Nordic Seas, especially for the most intense polar lows. In the North Atlantic and Pacific, the main polar‐low season ranges from November to March. In the Southern Hemisphere, polar lows are mainly detected between 50 ‐ 65 S from April to October, indicating that this hemisphere compared to its northern counterpart has a two months longer, but less intense, polar‐low season. No significant hemispheric long‐term trends are observed, although some regions, such as the Denmark Strait and the Nordic Seas, experience significant downward and upward trends in polar lows, respectively, over the last decades. For intense polar lows, a significant decaying trend has been observed for the Northern Hemisphere.

The predominant decadal to multidecadal variability in the Arctic region is a feature that is not yet well-understood. It is shown that the Barents Sea is a key region for Arctic-wide variability. This is an important topic because low-frequency changes in the ocean might lead to large variations in the sea-ice cover, which then cause massive changes in the ocean-atmosphere heat exchanges. Here we describe the mechanism driving surface temperatures and heat fluxes in the Barents Sea based primarily on analyzes of one global coupled climate model. It is found that the ocean drives the low-frequency changes in surface temperature, whereas the atmosphere compensates the oceanic transport anomalies. The seasonal dependence and the role of individual components of the ocean-atmosphere energy budget are analyzed in detail, showing that seasonally-varying climate mechanisms play an important role. Herein, sea ice is governing the seasonal response, by acting as a lid that opens and closes during warm and cold periods, respectively, thereby modulating the surface heat fluxes.

This is a post-peer-review, pre-copyedit version of an article published in Climate Dynamics. The final authenticated version is available online at: http://dx.doi.org/10.1007/s00382-017-3722-x. Poleward energy transport in the atmosphere and oceans constitutes an important branch of the global energy budget, and its role in the climate system has been the subject of many studies. In the atmosphere, the transport is affected by “eddies” and large scale meridional cells, both with zero net mass transport across latitude circles, but also partly by processes associated with a net transport of mass across latitude circles. The latter must cease to operate in steady state, but they may be significant when time variability of the heat budget is considered. Indeed, examination of reanalysis data on short (daily to monthly) timescales shows that mass variations on these timescales result in surprisingly large fluctuations (in excess of 1015 W = 1 PW) in the poleward heat transport. These fluctuations are referred to as “extensive”, for they primarily alter the mass integrated energy of the region considered, but not its averaged value. It is suggested that extensive fluctuations mask more meaningful climate signals present in the heat transport variability ​on monthly and interannual timescales, and a new formulation is proposed to isolate the latter. This new formulation is applied successfully to reanalysis data and climate model simulations.

Recent studies have shown that atmospheric processes in spring play an important role for the initiation of the summer ice melt and therefore may strongly influence the September sea ice concentration (SSIC). Here a simple statistical regression model based on only atmospheric spring parameters is applied in order to predict the SSIC over the major part of the Arctic Ocean. By using spring anomalies of downwelling longwave radiation or atmospheric water vapor as predictor variables, correlation coefficients between observed and predicted SSIC of up to 0.5 are found. These skills of seasonal SSIC predictions are similar to those obtained using more complex dynamical forecast systems, despite the fact that the simple model applied here takes neither information of the sea ice state, oceanic conditions nor feedback mechanisms during summer into account. The results indicate that a realistic representation of spring atmospheric conditions in the prediction system plays an important role for the predictive skills of a model system.

A vertically nonuniform warming of the troposphere yields a lapse rate feedback by altering the infrared irradiance to space relative to that of a vertically uniform tropospheric warming. The lapse rate feedback is negative at low latitudes, as a result of moist convective processes, and positive at high latitudes, due to stable stratification conditions that effectively trap warming near the surface. It is shown that this feedback pattern leads to polar amplification of the temperature response induced by a radiative forcing. The results are obtained by suppressing the lapse rate feedback in the Community Climate System Model, version 4 (CCSM4). The lapse rate feedback accounts for 15% of the Arctic amplification and 20% of the amplification in the Antarctic region. The fraction of the amplification that can be attributed to the surface albedo feedback, associated with melting of snow and ice, is 40% in the Arctic and 65% in Antarctica. It is further found that the surface albedo and lapse rate feedbacks interact considerably at high latitudes to the extent that they cannot be considered independent feedback mechanisms at the global scale.

The seasonal melt–freeze transitions are important to continuously monitor over Arctic sea ice in order to better understand Arctic climate variability. The Ku-band scatterometer QuikSCAT (13.4 GHz ...

Source at https://doi.org/10.1016/j.wace.2019.100200. Ship icing may lead the ship and crew in great jeopardy. Usually, predictions of such ice build-up are based on the modelling of the heat fluxes capable of freezing sea water originated from wave-ship interactions. This study, on the other hand, follows a different and more general approach by investigating the relationship between the weather situation and icing both using observed parameters from 17 ships operating in Arctic-Norwegian waters from 1980 to 2006, and by applying upper-air parameters derived from NOrwegian ReAnalysis 10 km data (NORA10). In the atmosphere, the memory aloft is larger than that near the surface providing capability of medium-range icing predictions based on such upper-air parameters. It is demonstrated that cold-air outbreak from the ice-covered ocean areas is the dominant weather situation during icing. However, around 10% of the icing events arise in cold-air outbreak mountain-wave situations with downslope windstorms near the coastlines of Northern Norway and Svalbard. It is shown that snow showers and frontal snow, mostly in combination with sea spray, increase the risk of icing. Finally, a simple model applying the temperature and temperature anomaly at 850 hPa is found to be more accurate than methods based on temperature and wind close to the surface. The model is further improved by including wind at 850 hPa.

The seasonal melt-freeze transitions are fun- damental features of the Arctic climate system. The representation of the pan-Arctic melt and freeze onset (north of 60°N) is assessed in two reanalyse ...

Earth’s climate sensitivity to radiative forcing induced by a doubling of the atmospheric CO2 is determined by feedback mechanisms, including changes in atmospheric water vapor, clouds and surface albedo, that act to either amplify or dampen the response. The climate system is frequently interpreted in terms of a simple energy balance model, in which it is assumed that individual feedback mechanisms are additive and act independently. Here we test these assumptions by systematically controlling, or locking, the radiative feedbacks in a state-of-the-art climate model. The method is shown to yield a near-perfect decomposition of change into partial temperature contributions pertaining to forcing and each of the feedbacks. In the studied model water vapor feedback stands for about half the temperature change, CO2-forcing about one third, while cloud and surface albedo feedback contributions are relatively small. We find a close correspondence between forcing, feedback and partial surface temperature response for the water vapor and surface albedo feedbacks, while the cloud feedback is inefficient in inducing surface temperature change. Analysis suggests that cloud-induced warming in the upper tropical troposphere, consistent with rising convective cloud anvils in a warming climate enhances the negative lapse-rate feedback, thereby offsetting some of the warming that would otherwise be attributable to this positive cloud feedback. By subsequently combining feedback mechanisms we find a positive synergy acting between the water vapor feedback and the cloud feedback; that is, the combined cloud and water vapor feedback is greater than the sum of its parts. Negative synergies surround the surface albedo feedback, as associated cloud and water vapor changes dampen the anticipated climate change induced by retreating snow and ice. Our results highlight the importance of treating the coupling between clouds, water vapor and temperature in a deepening troposphere.

The summer sea-ice extent in the Arctic has decreased in recent decades, a feature that has become one of the most distinct signals of the continuing climate change. However, the interannual variab ...

Pronounced warming in the Arctic region, coined Arctic amplification, is an important feature of observed and modelled climate change1, 2. Arctic amplification is generally attributed to the retreat of sea-ice3 and snow, and the associated surface-albedo feedback4, in conjunction with other processes5, 6, 7, 8. In addition, the predominant thermal surface inversion in winter has been suggested to pose a negative feedback to Arctic warming by enhancing infrared radiative cooling9. Here we use the coupled climate model EC-Earth10 in idealized climate change experiments to quantify the individual contributions of the surface and the atmosphere to infrared radiative cooling. We find that the surface inversion in fact intensifies Arctic amplification, because the ability of the Arctic wintertime clear-sky atmosphere to cool to space decreases with inversion strength. Specifically, we find that the cold layers close to the surface in Arctic winter, where most of the warming takes place, hardly contribute to the infrared radiation that goes out to space. Instead, the additional radiation that is generated by the warming of these layers is directed downwards, and thus amplifies the warming. We conclude that the predominant Arctic wintertime temperature inversion damps infrared cooling of the system, and thus constitutes a positive warming feedback.

During summer 2007 the Arctic sea-ice shrank to the lowest extent ever observed. The role of the atmospheric energy transport in this extreme melt event is explored using the state-of-the-art ERA-Interim reanalysis data. We find that in summer 2007 there was an anomalous atmospheric flow of warm and humid air into the region that suffered severe melt. This anomaly was larger than during any other year in the data (1989–2008). Convergence of the atmospheric energy transport over this area led to positive anomalies of the downward longwave radiation and turbulent fluxes. In the region that experienced unusual ice melt, the net anomaly of the surface fluxes provided enough extra energy to melt roughly one meter of ice during the melting season. When the ocean successively became ice-free, the surface-albedo decreased causing additional absorption of shortwave radiation, despite the fact that the downwelling solar radiation was smaller than average. We argue that the positive anomalies of net downward longwave radiation and turbulent fluxes played a key role in initiating the 2007 extreme ice melt, whereas the shortwave-radiation changes acted as an amplifying feedback mechanism in response to the melt.

This is the peer reviewed version of the following article: Dekhtyareva, A., Holmén, K., Maturilli, M., Hermansen, O. & Graversen, R. (2018). Effect of seasonal mesoscale and microscale meteorological conditions in Ny-Ålesund on results of monitoring of long-range transported pollution. Polar Research, 37(1). https://doi.org/10.1080/17518369.2018.1508196. Source at https://doi.org/10.1080/17518369.2018.1508196. Ny-Ålesund is an international research settlement where the thermodynamics and chemical composition of the air are monitored. The present work investigates the effects of micrometeorological conditions, mesoscale dynamics and local air pollution on the data collected at two different locations around the village. Daily filter measurements of sulphur dioxide and non-sea salt sulphate from the temporary Ny-Ålesund station and permanent Zeppelin mountain station have been analysed along with meteorological data. The influence of different factors representing micrometeorological phenomena and local pollution from ships has been statistically investigated. Seasonal variation of the correlation between the data from Ny-Ålesund and Zeppelin stations is revealed, and the seasonal dependence of the relative contribution of different factors has been analysed. The median concentrations of SO42- measured in Ny-Ålesund increased significantly on days with temperature inversions in winter. In spring, concentrations of SO2 and SO42- were higher than normal at both stations on days with temperature inversions, but lower on days with strong humidity inversions. In summer, local ship traffic affects the SO2 data set from Ny-Ålesund, while no statistically significant influence on the Zeppelin data set has been observed. The pollution from ships has an effect on SO42- values at both stations; however, the concentrations in Ny-Ålesund were higher when local pollution accumulated close to the ground in days with strong humidity inversions.

Autumn 2006 was extraordinarily mild in many parts of Europe. Near-surface temperatures were more than three standard deviations above the 1961–1990 climatology. Even accounting for global warming, this event was far outside the probability density function of previous observations or climate model simulations. To investigate the mechanisms behind this event, the energy-budget for Autumn 2006 in Europe is estimated. Atmospheric energy-transport convergence over Europe is calculated and compared with the net energy flux at the top of the atmosphere as well as at the earth’s surface. The central North-Atlantic Ocean constituted the major source of energy. Here, the release of both sensible and latent heat was anomalously high. Atmospheric circulation played a crucial role by transporting the excess energy into Europe. Of this energy excess, dry-static energy was larger than the latent part, partly due to an additional contribution derived from a conversion of latent energy to sensible heat, which occurred upstream of the study area in the eastern Atlantic. In Europe, surface turbulent-energy fluxes into the atmosphere respond to atmospheric energy-transport convergence and are accordingly suppressed due to the anomalously high temperature and humidity content of the overlying air. The net outflow of radiational energy to space is anomalously high but not sufficient to offset the large positive anomaly of energy found over Europe. Even though the relative humidity was near its normal values in Europe, the specific humidity was considerably higher than usual. The high water-vapour content induced a local radiative positive feedback, increasing the opacity of the atmosphere to long-wave radiation. This appears to have significantly contributed to the extreme event. Atmospheric circulation played a crucial role in sustaining this feedback loop.

In situ atmospheric observations in the central Arctic are few and mostly from near the surface. A majorityare from coastal regions whereas soundings over the Arctic Ocean are rare. This limits our ...

Near-surface warming in the Arctic has been almost twice as large as the global average over recent decades-a phenomenon that is known as the 'Arctic amplification'. The underlying causes of this temperature amplification remain uncertain. The reduction in snow and ice cover that has occurred over recent decades may have played a role. Climate model experiments indicate that when global temperature rises, Arctic snow and ice cover retreats, causing excessive polar warming. Reduction of the snow and ice cover causes albedo changes, and increased refreezing of sea ice during the cold season and decreases in sea-ice thickness both increase heat flux from the ocean to the atmosphere. Changes in oceanic and atmospheric circulation, as well as cloud cover, have also been proposed to cause Arctic temperature amplification. Here we examine the vertical structure of temperature change in the Arctic during the late twentieth century using reanalysis data. We find evidence for temperature amplification well above the surface. Snow and ice feedbacks cannot be the main cause of the warming aloft during the greater part of the year, because these feedbacks are expected to primarily affect temperatures in the lowermost part of the atmosphere, resulting in a pattern of warming that we only observe in spring. A significant proportion of the observed temperature amplification must therefore be explained by mechanisms that induce warming above the lowermost part of the atmosphere. We regress the Arctic temperature field on the atmospheric energy transport into the Arctic and find that, in the summer half-year, a significant proportion of the vertical structure of warming can be explained by changes in this variable. We conclude that changes in atmospheric heat transport may be an important cause of the recent Arctic temperature amplification.

The ERA-40 reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) is an atmospheric data-set based on a comprehensive collection of observations and a state-of-the-art system for assimilating data. High-quality data, encompassing more than four decades, have successfully been used in a wide range of applications, including climate change studies. However, even though the ERA-40 data-set benefits from improvements in the assimilation procedures since the release of earlier reanalyses, ERA-40 exhibits unrealistic behaviour as regards some atmospheric quantities, including the water budget and the Brewer–Dobson Circulation. In addition, the results presented here show significant mass-budget inconsistencies. Over inter-annual timescales (greater than one year), the vertically-averaged meridional mass transport is unrealistic and cannot be explained on the basis of naturally occurring physical processes. This mass inconsistency also yields spurious signals in meridional fluxes of other atmospheric quantities, such as energy. The total atmospheric mass content, on the other hand, shows a realistic evolution on daily timescales during the satellite era, from about 1979 onwards. Through this period, the variability of the total mass on intra-annual timescales (less than one year) and annual timescales is consistent with differences between evaporation and precipitation. Here it is demonstrated that unrealistic mass fluxes are present in ERA-40 because of inherent properties of the data assimilation process. In assimilating model forecasts, between analysis time-steps, systematic and unrealistic changes of the local surface-pressure field in the assimilating model are encountered. These local mass changes are associated with mass fluxes. During the assimilation procedure, observations reset the surface-pressure field, whereas the mass fluxes are not adjusted properly. This is because surface-pressure observations are plentiful and accurate, in contrast to wind observations. Consequently, the analysed mass fluxes show a spurious development, even though the mass field itself is well captured. A correction method can be applied in order to eliminate the spurious fluxes. For trend calculations it is demonstrated that this method yields more realistic results than those obtained from the original ERA-40 data. Copyright © 2007 Royal Meteorological Society

The warming of the near-surface air in the Arctic region has been larger than the global mean surface warming. There is general agreement that the Arctic amplification of the surface air temperature (SAT) trend to a considerable extent is due to local effects such as the retreat of sea ice, especially during the summer months, and earlier melting of snow in the spring season. There is no doubt that these processes are important causes of the Arctic SAT trend. It is less clear, however, whether the trend may also be related to recent changes in the atmospheric midlatitude circulation. This question is the focus of the present paper. Model experiments have shown that in a warmer climate responding to, for example, a doubling of CO2, the atmospheric northward energy transport (ANET) will increase and cause polar SAT amplification. In the present study, the development of the ANET across 60°N and its linkage to the Arctic SAT have been explored using the ERA-40 reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). It is found that during 1979–2001, the ANET has experienced an overall positive but weak trend, which was largest during the period from the mid-1980s to the mid-1990s. In addition, it is found that the Arctic SAT is sensitive to variability of the ANET across 60°N and hence to variability of the midlatitude circulation: A large ANET is followed by warming of the Arctic where ANET leads by about 5 days. The warming is located primarily north of the Atlantic and Pacific sectors, indicating that baroclinic weather systems developing around the Icelandic and Aleutian lows are important for the energy transport. Furthermore, it is suggested here that a small, but statistically significant, part of the mean Arctic SAT trend is linked to the trend in the ANET. Another important indicator of the midlatitude circulation is the Arctic Oscillation (AO). Through the 1980s and early 1990s the AO index has shown a positive trend. However, even though a part of the SAT trend can be related to the AO in localized parts of the Arctic area, the mean Arctic SAT trend shows no significant linkage to the AO.

An extreme heat wave occurred in Russia in the summer of 2010. It had serious impacts on humans and natural ecosystems, it was the strongest recorded globally in recent decades and exceeded in amplitude and spatial extent the previous hottest European summer in 2003. Earlier studies have not succeeded in comparing the magnitude of heat waves across continents and in time. This study introduces a new Heat Wave Magnitude Index that can be compared over space and time. The index is based on the analysis of daily maximum temperature in order to classify the strongest heat waves that occurred worldwide during the three study periods 1980–1990, 1991–2001, and 2002–2012. In addition, multimodel ensemble outputs from the Coupled Model Intercomparison Project Phase 5 are used to project future occurrence and severity of heat waves, under different Representative Concentration Pathways, adopted by the Intergovernmental Panel on Climate Change for its Fifth Assessment Report (AR5). Results show that the percentage of global area affected by heat waves has increased in recent decades. Moreover, model predictions reveal an increase in the probability of occurrence of extreme and very extreme heat waves in the coming years, in particular, by the end of this century, under the most severe IPCC AR5 scenario, events of the same severity as that in Russia in the summer of 2010 will become the norm and are projected to occur as often as every 2 years for regions such as southern Europe, North America, South America, Africa, and Indonesia.

When climate is forced by a doubling of CO2, a number of feedback processes are induced, such as changes of water vapor, clouds, and surface albedo. Here the CO2 forcing and concomitant feedbacks are studied individually using a general circulation model coupled to an aquaplanet mixed layer ocean. A technique for fixing the radiative effects of moisture and clouds by reusing these variables from 1 × CO2 and 2 × CO2 equilibrium climates in the model’s radiation code allows for a detailed decomposition of forcings, feedbacks, and responses. The cloud feedback in this model is found to have a weak global average effect and surface albedo feedbacks have been eliminated. As in previous studies, the water vapor feedback is found to approximately double climate sensitivity, but while its radiative effect is strongly amplified at low latitudes, the resulting response displays about the same degree of polar amplification as the full all-feedbacks experiment. In fact, atmospheric energy transports are found to change in a way that yields the same meridional pattern of response as when the water vapor feedback is turned off. The authors conclude that while the water vapor feedback does not in itself lead to polar amplification by increasing the ratio of high- to low-latitude warming, it does double climate sensitivity both at low and high latitudes. A polar amplification induced by other feedbacks in the system, such as the Planck and lapse rate feedbacks here, is thus strengthened in the sense of increasing the difference in high- and low-latitude warming.

The Arctic climate change is analyzed in an ensemble of future projection simulations performed with the global coupled climate model EC-Earth2.3. EC-Earth simulates the twentieth century Arctic climate relatively well but the Arctic is about 2 K too cold and the sea ice thickness and extent are overestimated. In the twenty-first century, the results show a continuation and strengthening of the Arctic trends observed over the recent decades, which leads to a dramatically changed Arctic climate, especially in the high emission scenario RCP8.5. The annually averaged Arctic mean near-surface temperature increases by 12 K in RCP8.5, with largest warming in the Barents Sea region. The warming is most pronounced in winter and autumn and in the lower atmosphere. The Arctic winter temperature inversion is reduced in all scenarios and disappears in RCP8.5. The Arctic becomes ice free in September in all RCP8.5 simulations after a rapid reduction event without recovery around year 2060. Taking into account the overestimation of ice in the twentieth century, our model results indicate a likely ice-free Arctic in September around 2040. Sea ice reductions are most pronounced in the Barents Sea in all RCPs, which lead to the most dramatic changes in this region. Here, surface heat fluxes are strongly enhanced and the cloudiness is substantially decreased. The meridional heat flux into the Arctic is reduced in the atmosphere but increases in the ocean. This oceanic increase is dominated by an enhanced heat flux into the Barents Sea, which strongly contributes to the large sea ice reduction and surface-air warming in this region. Increased precipitation and river runoff lead to more freshwater input into the Arctic Ocean. However, most of the additional freshwater is stored in the Arctic Ocean while the total Arctic freshwater export only slightly increases.

[1] The variability in the middle- and high-latitude stratosphere and troposphere on annual and intraannual timescales is investigated with focus on the differences between the two hemispheres. Results obtained with the National Centers for Environmental Prediction reanalysis data are compared to a general circulation model simulation. Although downward propagation of zonal mean zonal wind anomalies from the stratosphere to the troposphere are found on intraannual timescales in both hemispheres the two hemispheres show several differences. First, the intraannual variability is around 30% weaker in the southern hemisphere (SH) than in the northern hemisphere (NH). Second, in the SH the downward propagation is concentrated to the spring season while it is found during the whole winter half-year in the NH. Third, the coupling between the stratosphere and the troposphere is weaker and faster in the SH compared to the NH. Also, the annual cycle of the zonal mean zonal wind is quite different in the two hemispheres. In the SH the annual cycle is strong, shows a downward propagation with a timescale of two months, and includes higher annual harmonics of considerable strength. In the NH the annual cycle is weaker, shows no downward propagation, and is more sinusoidal. In both hemispheres the annual cycle and the intraannual variability are weaker in the model than in the reanalysis. The downward propagation in the model closely resembles that of the reanalysis both on intraannual timescales and in the annual cycle. In the SH the model underestimates the importance of the higher annual harmonics.

Replying to: P. W. Thorne , 10.1038/nature07256 ; A. N. Grant, S. Bronnimann & L. Haimberger , 10.1038/nature07257 ; C. M. Bitz & Q. Fu , 10.1038/nature07258 (2008) These three communications https://www.nature.com/articles/nature07256 https://www.nature.com/articles/nature07257 https://www.nature.com/articles/nature07258 1,2,3 question the validity of some of our conclusions4. We found Arctic temperature trend amplification well above the boundary layer. In summer, the maximum amplification is found at a height of around 2 km, and no amplification is encountered near the surface. These findings appear in two state-of-the-art reanalyses, ERA-40 (ref. 5) and JRA-25 (ref. 6). Both these data sets show roughly the same overall vertical structure, and we believe our conclusions can be based on either of them. However, they show considerable differences regarding the magnitudes of the Arctic trends (see our Supplementary Information4), but our conclusions are not based on the absolute magnitudes.