North Atlantic Oscillation Events Research Articles

On the Formation and Maintenance of the Interannual Variability of the North Atlantic Oscillation

Abstract Motivated by the observation that the interannual variability of the North Atlantic Oscillation (NAO) is associated with the ensemble emergence of individual NAO events occurring on the intraseasonal time scale, one naturally wonders how the intraseasonal processes cause the interannual variability and what the dynamics are underlying the multiscale interaction. Using a novel time-dependent and spatially localized multiscale energetics formalism, this study investigates the dynamical sources for the NAO events with different phases and interannual regimes. For the positive-phase events (NAO+), the intraseasonal-scale kinetic energy (K1) over the North Atlantic sector is significantly enhanced for NAO+ occurring in the negative NAO winter regime (NW), compared to those in the positive winter regime (PW). It is caused by the enhanced inverse cascading from synoptic transients and reduced energy dispersion during the life cycle of NAO+ in NW. For the negative-phase events (NAO−), K1 is significantly larger during the early and decay stages of NAO− in NW than that in PW, whereas the reverse occurs in the peak stage. Inverse cascading and baroclinic energy conversion are primary drivers in the formation of the excessive K1 during the early stage of NAO− in NW, whereas only the latter contributes to the larger K1 during the decay stage of NAO− in NW compared to that in PW. The barotropic transfer from the mean flow, inverse cascading, and baroclinic energy conversion are all responsible for the strengthened K1 in the peak stage of NAO− in PW.

The Influence of Arctic Sea Ice Concentration Perturbations on Subseasonal Predictions of North Atlantic Oscillation Events

The Influence of Arctic Sea Ice Concentration Perturbations on Subseasonal Predictions of North Atlantic Oscillation Events

Combined influence of ENSO and North Atlantic Oscillation (NAO) on Eurasian Steppe during 1982–2018

As the most influential atmospheric oscillation on Earth, the El Niño/Southern Oscillation (ENSO) can significantly change the surface climate of the tropics and subtropics and affect the high latitudes of northern hemisphere areas through atmospheric teleconnection. The North Atlantic Oscillation (NAO) is the dominant pattern of low-frequency variability in the Northern Hemisphere. As the dominant oscillations in the Northern Hemisphere, the ENSO and NAO have been affecting the giant grassland belt in the world, the Eurasian Steppe (EAS), in recent decades. In this study, the spatio-temporal anomaly patterns of grassland growth in the EAS and their correlations with the ENSO and NAO were investigated using four long-term leaf area index (LAI) and one normalized difference vegetation index (NDVI) remote sensing products from 1982 to 2018. The driving forces of meteorological factors under the ENSO and NAO were analyzed. The results showed that grassland in the EAS has been turning green over the past 36 years. Warm ENSO events or positive NAO events accompanied by increased temperature and slightly more precipitation promoted grassland growth, and cold ENSO events or negative NAO events with cooling effects over the whole EAS and uneven precipitation decreased deteriorated the EAS grassland. During the combination of warm ENSO and positive NAO events, a more severe warming effect caused more significant grassland greening. Moreover, the co-occurrence of positive NAO with cold ENSO or warm ENSO with negative NAO kept the characteristic of the decreased temperature and rainfall in cold ENSO or negative NAO events, and deteriorate the grassland more severely.

Fast and Slow Subpolar Ocean Responses to the North Atlantic Oscillation: Thermal and Dynamical Changes

AbstractClimate model hindcasts are analyzed to reveal the impacts of the North Atlantic Oscillation (NAO) on the North Atlantic subpolar ocean, which exhibits variability on seasonal to decadal timescales. The ocean response to a single winter NAO event is separated into fast and slow responses. The fast response persists over winter–spring seasons, during which wind stress and heat flux anomalies associated with the NAO rapidly modify ocean temperatures via changes in Ekman transport and ocean‐atmosphere heat exchanges. The slow response persists for 3–4 years, during which overturning and gyre circulations redistribute opposing‐signed surface temperature anomalies created by the NAO. This redistribution modifies east‐west temperature contrasts altering the meridional heat transport associated with gyres and changing the strength of the overturning circulation. Hence, the fast and slow responses lead to opposing‐signed subpolar temperature anomalies in time from the competing effects of local forcing and horizontal heat convergence.

Asymmetries in Circulation Anomalies Related to the Phases of the North Atlantic Oscillation on Synoptic Time Scales

AbstractThe North Atlantic Oscillation (NAO) index is often characterized by independent positive and negative NAO events with a characteristic spatial pattern and a typical lifetime of around 1 week. These events are separated by periods of near‐neutral NAO conditions. Here, we challenge this view by showing in reanalysis and observed data that the strength and spatial shape of NAO events depends on the NAO index prior to the window of 1 week and this dependency is most pronounced for negative NAO events. The influence is seen in the mean sea level pressure, and in other important features, including blocking frequency and jet stream characteristics, and also in air surface temperature and precipitation in parts of Europe. This new appreciation is important for efforts to improve methods for subseasonal‐to‐seasonal predictions of NAO.

Optimal Precursors Identification for North Atlantic Oscillation Using the Parallel Intelligence Algorithm

The North Atlantic Oscillation (NAO) with abnormal sea level pressure (SLP) differences influence the westerly wind strength and storm tracks in the North Atlantic, which further affects the winter climate in the northern hemisphere. The predictability of NAO has become an important area of climate research in recent years. The identification of optimal precursors (OPRs) would help to investigate the dynamics of atmospheric and oceanic motions, as well as the nonlinear characteristic. The conditional nonlinear optimal perturbation (CNOP) method has been widely used in research on the OPR of the climatic event to explore which kind of initial perturbation is most likely to trigger climate events. However, the previous works on NAO’s OPR are based on a simple ideal model, which cannot describe the evolution process of NAO. Moreover, the commonly used algorithms that rely on the adjoint model are not suitable for the large complicated numerical models that do not have corresponding adjoint models, like Community Earth System Model (CESM). To break through the limitation, this paper proposes the parallel principal component analysis (PCA)-based particle swarm optimization (PSO) and genetic algorithm (GA) hybrid algorithm (PGAPSO) algorithm to identify the OPR of NAO using CESM. For different initial conditions, OPRs identified by the proposed method can always make the basic state develop into NAO events with corresponding phases. Compared with other adjoint-free approaches, the proposed method has relatively better fitness values and more mature patterns. The results also reveal that the proposed method can avoid falling into a local optimum and has strong robustness. In terms of performance, the proposed method searches in feature space with a much lower number of dimensions, thus improving efficiency. In addition, the proposed method is accelerated with multiple parallel frameworks to enhance performance, and it achieves the speedup ratio of 40.2.

NAO Influence on the MJO and its Prediction Skill in the Subseasonal-to-Seasonal Prediction Models

AbstractBased on the database of the Subseasonal to Seasonal (S2S) Prediction project of the World Weather Research Programme (WWRP) / World Climate Research Programme (WCRP), the influence of the North Atlantic Oscillation (NAO) on the Madden- Julian Oscillation (MJO) and its forecast skill is investigated. It is found that most models can capture the MJO phase changes following positive and negative NAO events. About 20 days after initialized with a positive (negative) NAO, the forecast MJO appears more frequently in phase 7 (3), which corresponds to reduced (enhanced) convection in the tropical Indian Ocean and enhanced (suppressed) convection in the western Pacific. In most S2S models the MJO prediction skill is dependent on the NAO amplitude and phase in the initial condition. A strong NAO leads to a better MJO forecast skill than a weak NAO. The MJO skill tends to be higher when the forecast starts from a negative NAO than a positive NAO. These results indicates that there is a strong Northern extratropical influence on the MJO and its forecast skill. It is important for numerical models to better represent the NAO influence to improve the simulation and prediction of the MJO.

Analysis of the Influencing Factors of Drought Events Based on GRACE Data under Different Climatic Conditions: A Case Study in Mainland China

The occurrence of droughts has become more frequent, and their intensity has increased in mainland China. With the aim of better understanding the influence of climate background on drought events in this region, we analyzed the role of the drought-related factors and extreme climate in the formation of droughts by investigating the relationship between the drought severity index (denoted as GRACE-DSI) based on the terrestrial water storage changes (TWSCs) derived from Gravity Recovery and Climate Experiment (GRACE) time-variable gravity fields and drought-related factors/extreme climate. The results show that GRACE-DSI was consistent with the self-calibrating Palmer Drought Severity Index in mainland China, especially for the subtropical monsoon climate, with a correlation of 0.72. Precipitation (PPT) and evapotranspiration (ET) are the main factors causing drought events. However, they play different roles under different climate settings. The regions under temperate monsoon climate and subtropical monsoon climate were more impacted by PPT, while ET played a leading role in the regions under temperate continental climate and plateau mountain climate. Moreover, El Niño–Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO) events mainly caused abnormalities in PPT and ET by affecting the strength of monsoons (East Asian and Indian monsoon) and regional highs (Subtropical High, Siberian High, Central Asian High, etc.). As a result, the various affected regions were prone to droughts during ENSO or NAO events, which disturbed the normal operation of atmospheric circulation in different ways. The results of this study are valuable in the efforts to understand the formation mechanism of drought events in mainland China.

NAO predictability from external forcing in the late 20th century

The North Atlantic Oscillation (NAO) is predictable in climate models at near-decadal timescales. Predictive skill derives from ocean initialization, which can capture variability internal to the climate system, and from external radiative forcing. Herein, we show that predictive skill for the NAO in a very large uninitialized multi-model ensemble is commensurate with previously reported skill from a state-of-the-art initialized prediction system. The uninitialized ensemble and initialized prediction system produce similar levels of skill for northern European precipitation and North Atlantic SSTs. Identifying these predictable components becomes possible in a very large ensemble, confirming the erroneously low signal-to-noise ratio previously identified in both initialized and uninitialized climate models. Though the results here imply that external radiative forcing is a major source of predictive skill for the NAO, they also indicate that ocean initialization may be important for particular NAO events (the mid-1990s strong positive NAO), and, as previously suggested, in certain ocean regions such as the subpolar North Atlantic ocean. Overall, we suggest that improving climate models’ response to external radiative forcing may help resolve the known signal-to-noise error in climate models.

Subseasonal predictability of the North Atlantic Oscillation

Skillfully predicting the North Atlantic Oscillation (NAO), and the closely related northern annular mode (NAM), on ‘subseasonal’ (weeks to less than a season) timescales is a high priority for operational forecasting centers, because of the NAO’s association with high-impact weather events, particularly during winter. Unfortunately, the relatively fast, weather-related processes dominating total NAO variability are unpredictable beyond about two weeks. On longer timescales, the tropical troposphere and the stratosphere provide some predictability, but they contribute relatively little to total NAO variance. Moreover, subseasonal forecasts are only sporadically skillful, suggesting the practical need to identify the fewer potentially predictable events at the time of forecast. Here we construct an observationally based linear inverse model (LIM) that predicts when, and diagnoses why, subseasonal NAO forecasts will be most skillful. We use the LIM to identify those dynamical modes that, despite capturing only a fraction of overall NAO variability, are largely responsible for extended-range NAO skill. Predictable NAO events stem from the linear superposition of these modes, which represent joint tropical sea-surface temperature-lower stratosphere variability plus a single mode capturing downward propagation from the upper stratosphere. Our method has broad applicability because both the LIM and the state-of-the-art European Centre for Medium-Range Weather Forecasts Integrated Forecast System (IFS) have higher (and comparable) skill for the same set of predicted high skill forecast events, suggesting that the low-dimensional predictable subspace identified by the LIM is relevant to real-world subseasonal NAO predictions.

The Influence of Sudden Arctic Sea-Ice Thinning on North Atlantic Oscillation Events

ABSTRACT Utilizing the Community Atmosphere Model, version 4 (CAM4), the influence of sudden Arctic sea-ice thinning on North Atlantic Oscillation (NAO) events is investigated on a sub-seasonal time scale. First, the control simulation with CAM4 using prescribed daily boundary conditions produces realistic descriptions for the frequency and evolution of NAO events. Second, sensitivity experiments are then conducted to investigate the impact of sudden Arctic sea-ice thinning on NAO events. Numerical results show that the NAO has obvious responses to sudden sea-ice thinning over 10 days. Finally, the NAO responses to sudden sea-ice thinning are related to the positions of the NAO event. Further diagnostic analysis reveals that when the poleward centre of a positive NAO event is located west (east) of Greenland, cold (warm) advection would be induced because of the sudden sea-ice thinning along with the northward (southward) wind. This cooling (warming) causes the air to contract (expand) and further results in a decrease (increase) in the geopotential height and sea level pressure fields, which corresponds to a positive NAO (negative NAO) response. The results of this investigation show that the response of atmospheric circulation to boundary conditions is determined by both boundary condition changes and the atmospheric circulation regime, which provides an understanding of the effect on an NAO event of sudden sea-ice thinning on a sub-seasonal time scale.

Observed Long- and Short-lived North Atlantic Oscillation Events: Role of the Stratosphere

Utilizing three different sets of reanalysis data, this study examines the long- and short-lived observed positive North Atlantic Oscillation (NAO) events (referred to as NAO+_LE and NAO+_SE) and long- and short-lived observed negative NAO events (referred to as NAO−_LE and NAO−_SE). Composite results indicate that the NAO-like circulation anomalies associated with the long-lived NAO events can reach the stratosphere, while they are primarily confined to the troposphere in the short-lived NAO events. Thus, the coupling/connection of stratospheric and tropospheric circulation anomalies is much better (worse) in the long-lived (short-lived) NAO events. A series of modified stratospheric initial-value experiments conducted with a simplified model indicate that a better (worse) connection between stratospheric and tropospheric circulation anomalies in the initial-value fields tend to gradually induce the NAO-like tropospheric circulation anomalies in the troposphere on the subsequent days, and thus naturally elongate (reduce) the lifetimes of the original NAO events by altering the tropospheric synoptic eddy vorticity flux over the North Atlantic region.

CNOP-P-Based Parameter Sensitivity Analysis for North Atlantic Oscillation in Community Earth System Model Using Intelligence Algorithms

Model error, which results from model parameters, can cause the nonnegligible uncertainty in the North Atlantic Oscillation (NAO) simulation. Conditional nonlinear optimal perturbation related to parameter (CNOP-P) is a powerful approach to investigate the range of uncertainty caused by model parameters under a specific constraint. In this paper, we adopt intelligence algorithms to implement the CNOP-P method and conduct the sensitivity analysis of parameter combinations for NAO events in the Community Earth System Model (CESM). Among 28 model parameters of the atmospheric component, the most sensitive parameter combination for the NAO + consists of parameter for deep convection (cldfrc_dp1), minimum relative humidity for low stable clouds (cldfrc_rhminl), and the total solar irradiance (solar_const). As for the NAO − , the parameter set that can trigger the largest variation of the NAO index (NAOI) is comprised of the constant for evaporation of precip (cldwat_conke), characteristic adjustment time scale (hkconv_cmftau), and the total solar irradiance (solar_const). The most prominent uncertainties of the NAOI ( Δ NAOI ) caused by these two combinations achieve 2.12 for NAO + and −2.72 for NAO − , respectively. In comparison, the maximum level of the NAOI variation resulting from single parameters reaches 1.45 for NAO + and −1.70 for NAO − . It is indicated that the nonlinear impact of multiple parameters would be more intense than the single parameter. These results present factors that are closely related to NAO events and also provide the direction of optimizing model parameters. Moreover, the intelligence algorithms adopted in this work are proved to be adequate to explore the nonlinear interaction of parameters on the model simulation.

Prediction of North Atlantic Oscillation Index Associated with the Sea Level Pressure Using DWT-LSTM and DWT-ConvLSTM Networks

The North Atlantic Oscillation (NAO), which manifests as an irregular atmospheric fluctuation, has a profound effect on the global climate change. The NAO index (NAOI) is the quantitative indicator that can reflect the intensity of the NAO events, and its traditional definition is the normalized sea level pressure (SLP) difference between Azores and Iceland. From the variation tendency of the NAOI, we found that it is difficult to predict the NAO with the characteristics of variability and complexity. As a data-driven approach, the deep neural network presents great potential in learning the mechanisms of climate forecasting. In this paper, we adopt long short-term memory (LSTM) and ConvLSTM to predict the NAO from two aspects, NAOI and SLP, respectively. In previous studies, LSTM has been regarded as a resultful method for time series prediction. ConvLSTM can capture both the temporal and spatial interdependencies of the SLP field; then, the NAOI can be calculated from the SLP output. In order to improve the prediction reliability, we utilize the discrete wavelet transform (DWT) as a preprocessing technique to decompose original data into different frequencies, considering the local time dependency. It can effectively preserve the features of high-frequency data and forecast extreme events more accurately. The proposed DWT-LSTM and DWT-ConvLSTM models are compared against multiple advanced models, such as LSTM, Holt-Winters, support vector regression (SVR), and gated recurrent unit (GRU). The results indicate that both DWT-LSTM and DWT-ConvLSTM perform better, particularly at peak values. As for the 31 NAO events from 2006 to 2015, our models achieve the lowest prediction error and the best stability. Compared with the forecast products of CPC named Global Forecast System (GFS) and the ensemble forecasts (ENSM), our models are much closer to observation in multistep forecasting.

Relationship between Solar Wind—Magnetosphere Energy and Eurasian Winter Cold Events

The profound impact of solar irradiance variations on the decadal variability of Earth’s climate has been investigated by previous studies. However, it remains a challenge to quantify the energetic particle precipitation (EPP) influence on the surface climate, which is an emerging research topic. The solar wind is a source of magnetospheric EPP, and the total energy input from the solar wind into Earth’s magnetosphere (Ein) shows remarkable interdecadal and interannual variability. Based on the new Ein index, this study reveals a significant interannual relationship between the annual mean Ein and Eurasian cold extremes in the subsequent winter. Less frequent cold events are observed over Eurasia (primarily north of 50°N) following the higher-than-normal Ein activity in the previous year, accompanied by more frequent cold events over northern Africa, and vice versa. This response pattern shows great resemblance to the first empirical orthogonal function of the variability of cold extremes over Eurasia, with a spatial correlation coefficient of 0.79. The pronounced intensification of the positive North Atlantic Oscillation events and poleward shift of the North Atlantic storm track associated with the anomalously higher Ein favor the anomalous extreme atmospheric circulation events, and thus less frequent extreme cold temperatures over northern Eurasia on the interannual time scale. It is further hypothesized that the wave-mean flow interaction in the stratosphere and troposphere is favorable for the connection of Ein signals to tropospheric circulation and climate in the following winter.

The Effect of the Madden–Julian Oscillation on the North Atlantic Oscillation Using Idealized Numerical Experiments

AbstractThe aim of the paper is to investigate the influence of the Madden–Julian oscillation (MJO) on the North Atlantic Oscillation (NAO) using a quasigeostrophic model on the sphere. A simplified forcing based on potential vorticity anomalies in the tropics is used to mimic the MJO. The idealized nature of our setup allows us to determine the distinct roles played by stationary and synoptic waves. This is done by means of several series of almost 10 000 short runs of 30 days. Ensemble averages and a streamfunction budget analysis are used to study the modifications of the flow induced by the MJO. We find that a stationary Rossby wave is excited in the tropics during MJO phase 3. The western part of the Pacific jet is displaced poleward, which modifies the transient eddy activity in that basin. These changes create a ridge south of Alaska, which favors equatorward propagation of synoptic waves and larger poleward eddy momentum fluxes from the eastern Pacific toward the Atlantic, increasing the frequency of occurrence of the positive NAO events. The situation is essentially reversed following phase 6 of the MJO and conducive to the negative phase of the NAO. For a realistic MJO forcing amplitude, we find increases in both NAO phases to be around 30%, in reasonable agreement with the observations given the model simplicity. Finally, we present a series of experiments to assess the relative importance of linear versus nonlinear effects.

Spatial Asymmetric Tilt of the NAO Dipole Mode and Its Variability

The dipole structure of the North Atlantic Oscillation (NAO) is examined in this study by defining the tilt of the NAO dipole centers on synoptic time scales. All the positive NAO phase (NAO+) and negative NAO phase (NAO−) events are divided into three tilting types according to their definition; namely, northeast–southwest (NE–SW), north–south symmetric (N–S, not tilted), and northwest–southeast (NW–SE) tilting NAO events. Then, the associated surface air temperature (SAT), geopotential height, zonal wind, and SST (surface sea temperature) anomalies of each type are examined. It is found that, for different asymmetric NAO tilt types, the local SATs exhibit significantly different distributions. The zonal wind has a good match with the NAO dipole tilt, which also includes the positive feedback of the NAO circulation. The basic zonal flow that removes the NAO days also exhibits a clear tilt structure that favors the tilt of the NAO dipole. Moreover, it is found that the Atlantic Multidecadal Oscillation (AMO) may be an important factor affecting the tilt of the NAO dipole. The AMO index has a significant 15-year lead for the NAO index and basic zonal flow index, with a high correlation coefficient, which might be seen as a precondition that indicates the tilt of the NAO events, especially on decadal or multidecadal time scales. However, the physical mechanisms and processes are still not fully understood.

Targeted Observations for Improving Prediction of the NAO Onset

Based on the viewpoint that the North Atlantic Oscillation (NAO) has an intrinsic timescale of approximate two weeks and can be treated as an initial value problem, targeted observations for improving the prediction of the onset of NAO events are investigated by using the conditional nonlinear optimal perturbation (CNOP) method with a quasi-geostrophic model. The results show that flow-dependent sensitive areas for the prediction of NAO onset are mainly located over North Atlantic and its upstream regions. Targeted observations over the main sensitive areas could improve NAO onset prediction in most cases (approximately 75%) due to reduced errors in anomalous eddy vorticity forcing (EVF) projection in the typical NAO mode. Moreover, a flow-independent sensitive area is determined based on the winter climatological flow, which is located over North America and its adjacent ocean. The NAO onset prediction can also be improved by targeted observations over the flow-independent sensitive area, but the skill improvement is somewhat lower than that derived from observations over the flow-dependent sensitive area. The above results indicate that targeted observations over sensitive areas identified by the CNOP method can help to improve the onset prediction of NAO events.

The Long- and Short-Lived North Atlantic Oscillation Events in a Simplified Atmospheric Model

Abstract This study investigates the North Atlantic Oscillation (NAO) events with relatively long and short lifetimes based on an 8000-day perpetual-boreal-winter [December–February (DJF)] run result of the idealized Geophysical Fluid Dynamics Laboratory (GFDL) dynamical core atmospheric model. We identify the so-called long- and short-lived positive and negative NAO events from the 8000-day model output. The composite 300-hPa geopotential height anomalies show that the spatial patterns of the composite long-lived NAO events closely resemble the Northern Hemisphere annular mode (NAM) because the NAO dipole is accompanied with a statistically significant North Pacific meridional dipole (NPMD) at similar latitudes as that of the NAO dipole. The composite short-lived NAO events exhibit the locally confined canonical NAO. Twelve sets of modified initial-value experiments indicate that an absence (a presence) of the NPMD-type perturbations at the early stage of the long (short)-lived NAO events will decrease (increase) their intensities and naturally shorten (lengthen) their lifetimes. Thus, the preceding NPMD is an early factor that is conducive to the emergence of the long-lived NAO events in the model. We argue that through directly modulating the synoptic eddy forcing over the North Atlantic region, the preceding NPMD can gradually arouse the NAO-like circulation anomalies on the following days. That is the reason why the preceding NPMD can modulate the intensities and lifetimes of the NAO events.

Evaluation of the Forecast Performance for North Atlantic Oscillation Onset

By utilizing operational forecast products from TIGGE (The International Grand Global Ensemble) during 2006 to 2015, the forecasting performances of the European Centre for Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction (NCEP), Japan Meteorology Agency (JMA) and China Meteorological Administration (CMA) for the onset of North Atlantic Oscillation (NAO) events are assessed against daily NCEP–NCAR reanalysis data. Twenty-two positive NAO (NAO+) and nine negative NAO (NAO−) events are identified during this time period. For these NAO events, control forecasts, one member of the ensemble that utilizes the currently most proper estimate of the analysis field and the best description of the model physics, are able to predict their onsets three to five days in advance. Moreover, the failure proportion for the prediction of NAO− onset is higher than that for NAO+ onset, which indicates that NAO− onset is harder to forecast. Among these four operational centers, ECMWF has performs best in predicting NAO onset, followed by NCEP, JMA, and then CMA. p]The forecasting performance of the ensemble mean is also investigated. It is found that, compared with the control forecast, the ensemble mean does not improve the forecasting skill with respect to the onset time of NAO events. Therefore, a confident forecast of NAO onset can only be achieved three to five days in advance.