Spatio-temporal variability of atmospheric rivers and associated atmospheric parameters in the Euro-Atlantic region

We study the spatio-temporal variability of Atmospheric Rivers (ARs) and associated integrated water vapor and atmospheric parameters over the Euro-Atlantic region using long-term reanalysis datasets. Winds, temperature, and specific humidity at different pressure levels during 1979–2018 are used to study the water vapor transport integrated between 1000 and 300 hPa (IVT300) in mapping ARs. The intensity of ARs in the North Atlantic has been increasing in recent times (2009–2018) with large decadal variability and poleward shift (~ 5° towards the North) in landfall during 1999–2018. Though different reanalysis datasets show similar spatial patterns of IVT300 in mapping ARs, bias in specific humidity and wind components led to IVT300 mean bias of 50 kg m⁻¹ s⁻¹ in different reanalysis products compared to ERA5. The magnitude of winds and specific humidity in the lower atmosphere (below 750 hPa) dominates the total column water vapor and intensity of ARs in the North Atlantic. Reanalysis datasets in the central North Atlantic show an IVT300 standard deviation of 200 kg m⁻¹ s⁻¹ which is around 33% of the ARs climatology (~ 600 kg m⁻¹ s⁻¹). Though ARs have a higher frequency of landfalling over Western Europe in winter half-year, the intensity of IVT300 in winter ARs is 3% lower than the annual mean. The lower frequency of ARs in the summer half-year shows 3% higher IVT300 than the annual mean. While ARs in the North Atlantic show a strong decadal change in frequency and path, the impact of the North Atlantic Oscillation (NAO) and Scandinavian blocking on the location of landfall of ARs are significant. Furthermore, there is a strong latitudinal dependence of the source of moisture flux in the open ocean, contributing to the formation and strengthening ARs.

     

Use of variability modes to evaluate AR4 climate models over the Euro-Atlantic region

This paper analyzes the ability of the multi-model simulations from the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) to simulate the main leading modes of variability over the Euro-Atlantic region in winter: the North-Atlantic Oscillation (NAO), the Scandinavian mode (SCAND), the East/Atlantic Oscillation (EA) and the East Atlantic/Western Russia mode (EA/WR). These modes of variability have been evaluated both spatially, by analyzing the intensity and location of their anomaly centres, as well as temporally, by focusing on the probability density functions and e-folding time scales. The choice of variability modes as a tool for climate model assessment can be justified by the fact that modes of variability determine local climatic conditions and their likely change may have important implications for future climate changes. It is found that all the models considered are able to simulate reasonably well these four variability modes, the SCAND being the mode which is best spatially simulated. From a temporal point of view the NAO and SCAND modes are the best simulated. UKMO-HadGEM1 and CGCM3.1(T63) are the models best at reproducing spatial characteristics, whereas CCSM3 and CGCM3.1(T63) are the best ones with regard to the temporal features. GISS-AOM is the model showing the worst performance, in terms of both spatial and temporal features. These results may bring new insight into the selection and use of specific models to simulate Euro-Atlantic climate, with some models being clearly more successful in simulating patterns of temporal and spatial variability than others.     

Euro-Atlantic circulation types and modes of variability in winter

Extra-tropical atmospheric circulation variability is addressed in this study using two complementary approaches: circulation types and modes of variability. Principal component analysis (PCA) in T- and S-modes has been used to estimate the features. An objective synoptic classification of Euro-Atlantic atmospheric circulation is described. Eight circulation types have been identified and described in terms of their spatial features, mean frequency and lifetime, transitions and trends. The most persistent type is connected with the presence of a ridge over the British Isles and Iceland, while the less persistent type is related to a tilted ridge west of the continent. Increases in the persistence of some circulation types such as the Scandinavian and the Euro-Atlantic blockings and a ridge with axis over Western Europe have been found in the 1990s. Data from two independent re-analyses are used to test the robustness of the results. The main differences between the two datasets have been found in the distribution of events as a function of their duration. In a second step, the main modes of variability over the Euro-Atlantic area have been identified using daily data. An analysis of the relationship between these modes and the circulation types suggests that specific circulation types shift the phases of certain modes of variability.     

Winter cloudiness variability in the Mediterranean region and its connection to atmospheric circulation features

The temporal and spatial variability of winter total cloud cover in southern Europe and the Mediterranean region and its connection to the synoptic-scale features of the general atmospheric circulation are examined for the period 1950–2005, by using the diagnostic and intrinsic NCEP/NCAR Reanalysis data sets. At first, S-mode factor analysis is applied to the time series of winter cloud cover, revealing five factors that correspond to the main modes of inter-annual variability of cloudiness. The linkage between each of the five factors and the atmospheric circulation is examined by constructing the 500 hPa and 1,000 hPa geopotential height anomaly patterns that correspond to the highest/lowest factor scores. Then, k-means cluster analysis is applied to the factor scores time series, classifying the 56 years into six distinct clusters that describe the main modes of spatial distribution of cloudiness. Eventually, canonical correlation analysis is applied to the factor scores time series of: (1) 500 and 1,000 hPa geopotential heights over Europe and the North Atlantic Ocean and (2) total cloud cover over southern Europe and the Mediterranean, in order to define the main centers of action in the middle and the lower troposphere that control winter cloudiness variability in the various sub-regions of the area under study. Three statistically significant canonical pairs are revealed, defining the main modes of atmospheric circulation forcing on cloudiness variability. North Atlantic oscillation and European blocking activity modulate the highest percentage of cloudiness variability. A statistically significant negative trend of winter cloudiness is found for central and southern Europe and the Mediterranean region. This negative trend is associated with the corresponding positive trends in NAO and European blocking activity.     

Long term changes in ice and discharge regime of rivers in the Baltic region in relation to climatic variability

The river ice regime is considered a sensitive indicator of climate change and within this study long term changes (in case of River Daugava starting from 1530, but for other studied rivers starting from first half of twentieth century) river ice regimes in the Baltic region have been studied. The ice cover duration on the rivers (17 rivers) in the Baltic countries and Belarus has decreased during the recent decades. In addition to this, long term observational records of ice break on the rivers of the studied region exhibit a pattern of periodic changes in the intensity of ice regime. Both the ice regime and the seasonal river discharge are shown to be strongly influenced by large-scale atmospheric circulation processes over North Atlantic that manifests through close correlation with North Atlantic Oscillation index.     

Simulation of state-dependent high-frequency atmospheric variability associated with ENSO

High-frequency atmospheric variability depends on the phase of El Nino/Southern Oscillation (ENSO). Recently, there is increasing evidence that state-dependent high-frequency atmospheric variability significantly modulates ENSO characteristics. Hence, in this study, we examine the model simulations of high-frequency atmospheric variability and, further, its dependency on the El Nino phase, using atmospheric and coupled GCMs (AGCM and CGCM). We use two versions of physical packages here—with and without convective momentum transport (CMT)—in both models. We found that the CMT simulation gives rise to a large climatological zonal wind difference over the Pacific. Also, both the climate models show a significantly improved performance in simulating the state-dependent noise when the CMT parameterization is implemented. We demonstrate that the better simulation of the state-dependent noise results from a better representation of anomalous, as well as climatological, zonal wind. Our further comparisons between the simulations, demonstrates that low-frequency wind is a crucial factor in determining the state-dependency of high-frequency wind variability. Therefore, it is suggested that the so-called state-dependent noise is directly induced by the low-frequency wind anomaly, which is caused by SST associated with ENSO.     

On atmospheric radiative feedbacks associated with climate variability and change

Using the method of radiative ‘kernels’ an analysis is made of water vapour, lapse rate and ‘Planck’ (uniform vertical temperature) long wave feedbacks in models participating in the World Climate Research Program (WCRP) Coupled Model Intercomparison Project phase 3 (CMIP3). Feedbacks are calculated at climate change timescales from the A1B scenario, and at three ‘variability’ timescales from the corresponding preindustrial experiments: seasonal, interannual and decadal. Surface temperature responses show different meridional patterns for the different timescales, which are then manifest in the structures of the individual feedbacks. Despite these differences, mean water vapour feedback strength in models is positive for all models and timescales, and of comparable global magnitude across all timescales except for seasonal, where it is much weaker. Taking into consideration the strong positive lapse rate feedback at seasonal timescales, combined water vapour/lapse rate feedback is indeed similar across all timescales. To a good approximation, global water vapour feedback is found to be well represented by the temperature response along with an assumption of unchanged relative humidity under both variability and climate change. A comparison is also made of model feedbacks with reanalysis derived feedbacks for seasonal and interannual timescales. No strong relationships between individual modelled feedbacks at different timescales are evident: i.e., strong feedbacks in models at variability timescales do not in general predict strong climate change feedback, with the possible exception of seasonal timescales. There are caveats on this (and other) findings however, from uncertainties associated with the kernel technique and from, at times, very large uncertainties in estimating variability related feedbacks from temperature regressions.     

Climatology and interannual variability of storm-tracks in the Euro-Atlantic sector: a comparison between ERA-40 and NCEP/NCAR reanalyses

An objective methodology is applied to ERA-40 (European Centre for Medium-Range Weather Forecasts 40-year Reanalysis) and NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalyses, to build two storm-track databases for the Euro-Atlantic sector (85°W–70°E; 20°N–75°N), spanning the period December 1958–March 2000. The technique uses the full temporal (6-hourly) and spatial resolutions (1.125° and 2.5° regular grids, for ERA-40 and NCEP/NCAR, respectively) available. It is shown that the strong discrepancies in the number of storms in each dataset (higher for ERA-40) result from differences in the resolution of the fields subject to the storm detecting/tracking algorithm, and also from the characteristics of the integration models and assimilation schemes used for each reanalysis. An intercomparison of ERA-40 and NCEP/NCAR storm-tracks is performed for spatial distribution, and main characteristics, of the overall cyclone population and of a class of severe storms—explosive cyclones. Despite the discrepancies in storm numbers, both reanalyses agree on the main cyclone activity areas (formation, minimum central pressure, and lysis). The most pronounced differences occur where subsynoptic systems are frequent, as these are better resolved by ERA-40 data. The interannual variability of cyclone counts, analysed per intensity classes and for different regions of the domain, reveals reasonable agreement between the two datasets on the sign of trends (generally positive in northern latitudes, and negative in the Azores-Mediterranean band), but discrepancies regarding their strength in the most southern areas, where the mismatches between ERA-40 and NCEP/NCAR detected lows are greatest. Submitted to Climate Dynamics in December 2004     

春季中国南方雨带年际变动与大气环流异常

利用1960—2008年中国693个站逐日降水资料和NCEP/NCAR日平均再分析资料,采用统计分析方法,分析了中国南方春季降水强度和位置的年际变率及其与大气环流的关系。结果表明:在年代际尺度上,江南春季降水在20世纪60年代中、后期偏少,70年代中期到80年代初偏多,90年代初开始减少;在年际尺度上,当春季西太平洋副热带高压和青藏高原东侧的低层低压系统加强,并且异常中心分别位于20°N以南和30°N以南时,异常西南风主要位于长江以南地区,在异常西南风逐渐减弱区出现明显的辐合,伴随着该地区低层空气质量辐合、对流层上升运动和水汽辐合加强,造成江南地区降水偏多,此时来自西太平洋的异常水汽到达南海后,没有在南海聚集,而是转向北输送到江南;当春季西太平洋副热带高压以及青藏高原东侧低压系统加强且异常中心位于30°N以北时,异常西南风盛行在中国东部大部分地区,此时低层异常空气质量辐合、对流层异常上升运动以及异常水汽通量辐合区都向北移到江淮地区,使江淮地区降水增加,而华南地区为异常空气质量辐散、异常下沉运动以及异常水汽通量辐散,伴随着降水减少,这时异常水汽主要来自西太平洋副热带地区。由于上述观测结果与通过改变东亚和周边海域海-陆热力差异的数值试验结果有很好的一致性,因此,这里观测到的降水和大气环流异常可以被东亚区域热力差异异常激发出来。     

Spatio-temporal variability of dry and wet periods in eastern China

Summary An analysis, based on rain gauge observations, of the time-space variability of dry and wet periods during the last fifty years in eastern China is presented. The Standardized Precipitation Index (SPI) is used to assess the climatic conditions of the area, and principal component analysis (PCA) is applied to capture the pattern of co-variability of the index at different stations. Results suggest that the northern part of eastern China is experiencing dry conditions more frequently from the 1970s onwards indicated by a negative trend in the SPI time series. Long-term fluctuations characterize the SPI signal and contribute to the power spectrum variance at periods ranging from interdecadal to interannual time scales, that is respectively, 24 years and from 16 to 4–3.7 years. These periodic components provide a useful resource for long-term predictability of dry and wet periods in eastern China.     

Mechanisms of the atmospheric response to North Atlantic multidecadal variability: a model study

The atmospheric circulation response to decadal fluctuations of the Atlantic meridional overturning circulation (MOC) in the IPSL climate model is investigated using the associated sea surface temperature signature. A SST anomaly is prescribed in sensitivity experiments with the atmospheric component of the IPSL model coupled to a slab ocean. The prescribed SST anomaly in the North Atlantic is the surface signature of the MOC influence on the atmosphere detected in the coupled simulation. It follows a maximum of the MOC by a few years and resembles the model Atlantic multidecadal oscillation. It is mainly characterized by a warming of the North Atlantic south of Iceland, and a cooling of the Nordic Seas. There are substantial seasonal variations in the geopotential height response to the prescribed SST anomaly, with an East Atlantic Pattern-like response in summer and a North Atlantic oscillation-like signal in winter. In summer, the response of the atmosphere is global in scale, resembling the climatic impact detected in the coupled simulation, albeit with a weaker amplitude. The zonally asymmetric or eddy part of the response is characterized by a trough over warm SST associated with changes in the stationary waves. A diagnostic analysis with daily data emphasizes the role of transient-eddy forcing in shaping and maintaining the equilibrium response. We show that in response to an intensified MOC, the North Atlantic storm tracks are enhanced and shifted northward during summer, consistent with a strengthening of the westerlies. However the anomalous response is weak, which suggests a statistically significant but rather modest influence of the extratropical SST on the atmosphere. The winter response to the MOC-induced North Atlantic warming is an intensification of the subtropical jet and a southward shift of the Atlantic storm track activity, resulting in an equatorward shift of the polar jet. Although the SST anomaly is only prescribed in the Atlantic ocean, significant impacts are found globally, indicating that the Atlantic ocean can drive a large scale atmospheric variability at decadal timescales. The atmospheric response is highly non-linear in both seasons and is consistent with the strong interaction between transient eddies and the mean flow. This study emphasizes that decadal fluctuations of the MOC can affect the storm tracks in both seasons and lead to weak but significant dynamical changes in the atmosphere.     

Spatio-temporal variability of seasonal rainfall in western equatorial Africa

This study reveals homogeneous sub-regions over the poorly studied area of western equatorial Africa (10S?C7N and 7E?C30E). Monthly totals of 141 stations covering the period 1955?C1984 are used. The stations are grouped based on the similarity of their interannual rainfall variability. In addition to annual totals, four different seasons are examined separately for regionalization, an approach that has lacked in previous studies. The four 3-month seasons are defined as follows: January?CFebruary?CMarch (JFM), April?CMay?CJune (AMJ), July?CAugust?CSeptember (JAS), and October?CNovember?CDecember (OND). Two different algorithms are applied and compared: the rotated principal component analysis (RPCA) in conjunction with Ward's method, and the RPCA in conjunction with k-means method. The principal components that explain about 65% of total variance are retained and then varimax rotated. The corresponding scores are utilized as input for cluster analysis. Using Ward's method, five sub-regions are recognized for AMJ, JAS and OND and 4 sub-regions for JFM and annual data. The regions are geographically well distributed over the area and consist of roughly the same number of stations. The F-test is used to evaluate the homogeneity of each sub-region. The results show that all sub-regions are strongly homogeneous. Assuming the same number of clusters, the k-means method provides comparable spatial patterns with those of Ward's method. However, there are some differences, which are more evident in JAS and OND. Like Ward's method, the values of F-ratio for the k-means algorithm also confirm the homogeneity of all seasons/sub-regions. The interannual variability of rainfall for each season/sub-region is also provided and compared.     

Spatio-temporal variability and predictability of summer monsoon onset over the Philippines

The spatio-temporal variability of boreal summer monsoon onset over the Philippines is studied through the analysis of daily rainfall data across a network of 76 gauges for the period 1977 to 2004 and the pentad Merged Analysis of Precipitation from the US Climate Prediction Center from 1979 to 2006. The onset date is defined using a local agronomic definition, namely the first wet day of a 5-day period receiving at least 40 mm without any 15-day dry spell receiving <5 mm in the 30 days following the start of that period. The onset is found to occur rather abruptly across the western Philippines around mid-May on average and is associated with the set-up of a “classical” monsoonal circulation with low-level easterlies subsequently veering to southerly, and then southwesterly. The onset manifests itself merely as a seasonal increase of rainfall over the eastern Philippines, where rainfall occurs throughout most of the year. Interannual variability of the onset date is shown to consist of a spatially coherent large-scale component, rather similar over the western and eastern Philippines, with a moderate to high amount of local-scale (i.e. station scale) noise. In consequence, the large-scale signal can be easily retrieved from any sample of at least 5–6 stations across the network although the local-scale coherence and fingerprint of the large-scale signal of the onset date are found to be stronger over the central Philippines, roughly from Southern Luzon to Northern Mindanao. The seasonal predictability of local onset is analyzed through a cross-validated canonical correlation analysis using tropical Pacific and Indian Ocean sea surface temperature in March and the 850 hPa May wind field from dynamical forecast models as predictors. The regional-scale onset, defined as the average of standardized local-scale anomalies in onset date, shows good predictive skill (r ≈ 0.8). Moreover, most of the stations show weak to moderate skill (median skill = 0.28–0.43 depending on the scheme) with spatial averaging across stations typically increasing skill to >0.6.     

Trends and variability in column-integrated atmospheric water vapor

An analysis and evaluation has been performed of global datasets on column-integrated water vapor (precipitable water). For years before 1996, the Ross and Elliott radiosonde dataset is used for validation of European Centre for Medium-range Weather Forecasts (ECMWF) reanalyses ERA-40. Only the special sensor microwave imager (SSM/I) dataset from remote sensing systems (RSS) has credible means, variability and trends for the oceans, but it is available only for the post-1988 period. Major problems are found in the means, variability and trends from 1988 to 2001 for both reanalyses from National Centers for Environmental Prediction (NCEP) and the ERA-40 reanalysis over the oceans, and for the NASA water vapor project (NVAP) dataset more generally. NCEP and ERA-40 values are reasonable over land where constrained by radiosondes. Accordingly, users of these data should take great care in accepting results as real. The problems highlight the need for reprocessing of data, as has been done by RSS, and reanalyses that adequately take account of the changing observing system. Precipitable water variability for 1988–2001 is dominated by the evolution of ENSO and especially the structures that occurred during and following the 1997–98 El Niño event. The evidence from SSM/I for the global ocean suggests that recent trends in precipitable water are generally positive and, for 1988 through 2003, average 0.40±0.09 mm per decade or 1.3±0.3% per decade for the ocean as a whole, where the error bars are 95% confidence intervals. Over the oceans, the precipitable water variability relates very strongly to changes in SSTs, both in terms of spatial structure of trends and temporal variability (with a regression coefficient for 30°N–30°S of 7.8% K^?1) and is consistent with the assumption of fairly constant relative humidity. In the tropics, the trends are also influenced by changes in rainfall which, in turn, are closely associated with the mean flow and convergence of moisture by the trade winds. The main region where positive trends are not very evident is over Europe, in spite of large and positive trends over the North Atlantic since 1988. A much longer time series is probably required to obtain stable patterns of trends over the oceans, although the main variability could probably be deduced from past SST and associated precipitation variations.     

Heatwaves in Europe: areas of homogeneous variability and links with the regional to large-scale atmospheric and SSTs anomalies

This work presents a methodology to study the interannual variability associated with summertime months in which extremely hot temperatures are frequent. Daily time series of maximum and minimum temperature fields (T _max and T _min, respectively) are used to define indexes of extreme months based on the number of days crossing thresholds. An empirical orthogonal function (EOF) analysis is applied to the monthly indexes. EOF loadings give information about the geographical areas where the number of days per month with extreme temperatures has the largest variability. Correlations between the EOF principal components and the time series of other fields allow plotting maps highlighting the anomalies in the large scale circulation and in the SSTs that are associated with the occurrence of extreme events. The methodology is used to construct the “climatology” of the extremely hot summertime months over Europe. In terms of both interannual and intraseasonal variability, there are three regions in which the frequency of the extremely hot days per month homogeneously varies: north-west Europe, Euro-Mediterranean and Eurasia region. Although extremes over those regions occur during the whole summer (June to August), the anomalous climatic conditions associated with frequent heatwaves present some intraseasonal variability. Extreme climate events over the north-west Europe and Eurasia are typically related to the occurrence of blocking situations. The intraseasonal variability of those patterns is related to the amplitude of the blocking, the relative location of the action centre and the wavetrain of anomalies downstream or upstream of the blocking. During June and July, blocking situations which give extremely hot climate conditions over north-west Europe are also associated with cold conditions over the eastern Mediterranean sector. The Euro-Mediterranean region is a transition area in which extratropical and tropical systems compete, influencing the occurrence of climate events: blockings tend to be related to extremely hot months during June while baroclinic anomalies dominate the variability of the climate events in July and August. We highlight that our method could be easily applied to other regions of the world, to other fields as well as to model outputs to assess, e.g. the potential change of extreme climate events in a warmer climate.     

Spatio-temporal variability of moisture conditions within the Urban Canopy Layer

Summary ¶Re-analysed data from an urban climate research project in Munich, Germany, were used to investigate the spatio-temporal variability of moisture conditions (expressed here in vapour pressure VP) within the Urban Canopy Layer UCL. The results, which apply to three main sites and additional subsidiary ones, cover both summer and winter months. The summer month variation of VP is characterised by higher monthly mean values of VP for all three sites, howbeit with considerable inter-site differences. The temporal variability of mean VP values at diurnal time scales is also examined. With respect to the UCL, they reveal different amplitudes and times of occurrence of their extreme values. In addition, results of car traverses performed during clear sky conditions in downtown Munich show a remarkable small-scale spatio-temporal variability of VP.In relation to a sealed downtown site within a courtyard in Munich, a time-dependent urban moisture excess (UME) was formed. A positive correlation between UME and the urban heat island (UHI) could be verified in general. However, it was slightly negative with a very low coefficient of determination in the summer month when the maximum UME preceded the maximum UHI up to 5hrs. As example for the effects of air moisture on the urban climate within the UCL, the role of VP on a thermal index (physiologically equivalent temperature PET) was investigated. Based on one-year data from another urban climate project in Munich, a positive correlation between PET and VP was found, although the coefficient of determination was somewhat low. However, during a human-biometeorological case study on a typical summer day in the northern downtown of Freiburg, a medium-sized city in southwest Germany, PET and VP showed a negative correlation (possibly because the specific temporal course of VP at the measuring points was mainly influenced by thermally induced turbulence).     

The impact of internal atmospheric variability on the North Pacific SST variability

The impact of internal atmospheric variability on North Pacific sea surface temperature (SST) variability is examined based on three coupled general circulation model simulations. The three simulations differ only in the level of atmospheric noise occuring over the ocean at the air-sea interface. The amplitude of atmospheric noise is controlled by use of the interactive ensemble technique. This technique simultaneously couples multiple realizations of a single atmospheric model to a single realization of an ocean model. The atmospheric component models all experience the same SST, but the ocean component is forced by the ensemble averaged fluxes thereby reducing the impact of internal atmospheric dynamics at the air-sea interface. The ensemble averaging is only applied at the air-sea interface so that the internal atmospheric dynamics (i.e., transients) of each atmospheric ensemble member is unaffected. This interactive ensemble technique significantly reduces the SST variance throughout the North Pacific. The reduction in SST variance is proportional to the number of ensemble members indicating that most of the variability can simply be explained as the response to atmospheric stochastic forcing. In addition, the impact of the internal atmospheric dynamics at the air-sea interface masks out much of the tropical-midlatitude SST teleconnections on interannual time scales. Once this interference is reduced (i.e., applying the interactive ensemble technique), tropical-midlatitude SST teleconnections are easily detected.     

Cold-season atmospheric response to the natural variability of the Atlantic meridional overturning circulation

The influence of the natural variability of the Atlantic meridional overturning circulation (AMOC) on the atmosphere is studied in multi-centennial simulations of six global climate models, using Maximum Covariance Analysis (MCA). In all models, a significant but weak influence of the AMOC changes is found during the Northern Hemisphere cold-season, when the ocean leads the atmosphere by a few years. Although the oceanic pattern slightly varies, an intensification of the AMOC is followed in all models by a weak sea level pressure response that resembles a negative phase of the North Atlantic Oscillation (NAO). The signal amplitude is typically 0.5?hPa and explains about 10% of the yearly variability of the NAO in all models. The atmospheric response seems to be due primarily due to an increase of the heat loss along the North Atlantic Current and the subpolar gyre, associated with an AMOC-driven warming. Sea-ice changes appear to be less important. The stronger heating is associated to a southward shift of the lower-tropospheric baroclinicity and a decrease of the eddy activity in the North Atlantic storm track, which is consistent with the equivalent barotropic perturbation resembling the negative phase of the NAO. This study thus provides some evidence of an atmospheric signature of the AMOC in the cold-season, which may have some implications for the decadal predictability of climate in the North Atlantic region.