Multi-year prediction skill of Atlantic hurricane activity in CMIP5 decadal hindcasts

Using a statistical relationship between simulated sea surface temperature and Atlantic hurricane activity, we estimate the skill of a CMIP5 multi-model ensemble at predicting multi-annual level of Atlantic hurricane activity. The series of yearly-initialized hindcasts show positive skill compared to simpler forecasts such as persistence and climatology as well as non-initialized forecasts and return anomaly correlation coefficients of ～0.6 and ～0.8 for five and nine year forecasts, respectively. Some skill is shown to remain in the later years and making use of those later years to create a lagged-ensemble yields, for individual models, results that approach that obtained by the multi-model ensemble. Some of the skill is shown to come from persisting rather than predicting the climate shift that occur in 1994–1995. After accounting for that shift, the anomaly correlation coefficient for five-year forecasts is estimated to drop to 0.4, but remains statistically significant up to lead years 3–7. Most of the skill is shown to come from the ability of the forecast systems at capturing change in Atlantic sea surface temperature, although the failure of most systems at reproducing the observed slow down in warming over the tropics in recent years leads to an underestimation of hurricane activity in the later period.     

Adaptive observations for hurricane prediction

Summary This study proposes a method that can be used to provide guidelines to aircraft reconnaissance for hurricane observations. The method combines numerical weather prediction (NWP) model with a statistical approach to target adaptive observations over areas where the hurricane predictions are very sensitive to the initial analysis for the NWP-model. A single model experiment is performed using regular initial analysis, while 50 other ensemble runs are performed from randomly perturbed initial states. Under the perfect model assumption, the single model experiment serves as a true state. The method first computes the forecast error variances at a certain verification time, e.g. hour 48, and then locates the maximum centers of variances. After the locations of the maximum forecast error variances are known, various correlations of different variables between these maximum variance points and the perturbation fields at the target time, e.g. hour 12, are calculated to identify those locations at the target time, over where the observational errors might be responsible for the growth of forecast error variances at the verification time. Statistically, these correlation fields indicate where the most sensitive areas are at the target time, i.e. where the need for additional observations is suggested. Hurricane Fran of 1996 is used to test the proposed method. The reason for choosing this case is that, during the first 48 hour forecast, the track forecast from NWP-model was very close to the best track. Two additional experiments were designed to examine the method. One experiment updates predicted variables at the target time (12 h) over the areas, to where the proposed method indicates the forecast would be sensitive. The updating combines observations (or truth) with the first guess (predicted) fields. Another experiment also modifies predicted variables at the target time (12 h), but over the areas where the method indicates the forecast errors are less correlated to. The results show that the modification has greatly reduced the forecast error variances at the verification time (48 h) in the first experiment, however it has a very little impact on the variance fields at the forecast hour (48 h) in the second experiment. It is very clear from our experiments, that the proposed method is able to identify sensitive areas, where additional observations can help to reduce hurricane forecast errors from an NWP-model. Received July 19, 1999 Revised November 28, 1999     

On the North Atlantic extreme cyclone activity

Compared are the parameters of the cyclone activity in some areas of the North Atlantic in the winter (from October to March) and summer (from April to September) seasons for the period from January 1, 1948 to March 31, 2010, as well as the activity for the cyclones with the moderate intensity with the pressure in the center from 1000 to 970 hPa and for extremely intense cyclones (970 hPa and lower). The characteristics of cyclone activity, the density and intensity of cyclones, are determined using a method of the automatic identification of cyclone centers from the data on the sea level pressure.     

超强台风\

利用欧洲中心ERA-Interim逐6 h再分析资料（水平分辨率0.125°×0.125°）、NOAA逐日海表温度资料（水平分辨率0.25°×0.25°）、日本HMW8卫星逐时黑体亮温TBB（水平分辨率0.05°×0.05°）资料对对流非对称台风\     

Cyclone activity and circulation oscillations in the North Atlantic

Carried out is the comparative analysis of the cyclone activity for different combinations of positive and negative values of the North Atlantic Oscillation (NAO) and East Atlantic Oscillation (EA) indices. The integral characteristics of the cyclone activity (density and intensity of cyclones) are computed on the basis of the method of automatic indication of cyclone centers from the sea-level pressure data. It is demonstrated that the NAO index is really the major indicator of cyclone activity anomaly formation in the North Atlantic, however, the variations of cyclone activity in the European region, of the number of cyclones and their integral intensity are better characterized by the EA index.     

Multi-year predictability in a coupled general circulation model

Multi-year to decadal variability in a 100-year integration of a BMRC coupled atmosphere-ocean general circulation model (CGCM) is examined. The fractional contribution made by the decadal component generally increases with depth and latitude away from surface waters in the equatorial Indo-Pacific Ocean. The relative importance of decadal variability is enhanced in off-equatorial “wings” in the subtropical eastern Pacific. The model and observations exhibit “ENSO-like” decadal patterns. Analytic results are derived, which show that the patterns can, in theory, occur in the absence of any predictability beyond ENSO time-scales. In practice, however, modification to this stochastic view is needed to account for robust differences between ENSO-like decadal patterns and their interannual counterparts. An analysis of variability in the CGCM, a wind-forced shallow water model, and a simple mixed layer model together with existing and new theoretical results are used to improve upon this stochastic paradigm and to provide a new theory for the origin of decadal ENSO-like patterns like the Interdecadal Pacific Oscillation and Pacific Decadal Oscillation. In this theory, ENSO-driven wind-stress variability forces internal equatorially-trapped Kelvin waves that propagate towards the eastern boundary. Kelvin waves can excite reflected internal westward propagating equatorially-trapped Rossby waves (RWs) and coastally-trapped waves (CTWs). CTWs have no impact on the off-equatorial sub-surface ocean outside the coastal wave guide, whereas the RWs do. If the frequency of the incident wave is too high, then only CTWs are excited. At lower frequencies, both CTWs and RWs can be excited. The lower the frequency, the greater the fraction of energy transmitted to RWs. This lowers the characteristic frequency (reddens the spectrum) of variability off the equator relative to its equatorial counterpart. At low frequencies, dissipation acts as an additional low pass filter that becomes more effective, as latitude increases. At the same time, ENSO-driven off-equatorial surface heating anomalies drive mixed layer temperature responses in both hemispheres. Both the eastern boundary interactions and the accumulation of surface heat fluxes by the surface mixed layer act to low pass filter the ENSO-forcing. The resulting off-equatorial variability is therefore more coherent with low pass filtered (decadal) ENSO indices [e.g. NINO3 sea-surface temperature (SST)] than with unfiltered ENSO indices. Consequently large correlations between variability and NINO3 extend further poleward on decadal time-scales than they do on interannual time-scales. This explains why decadal ENSO-like patterns have a broader meridional structure than their interannual counterparts. This difference in appearance can occur even if ENSO indices do not have any predictability beyond interannual time-scales. The wings around 15–20°S, and sub-surface variability at many other locations are predictable on interannual and multi-year time-scales. This includes westward propagating internal RWs within about 25° of the equator. The slowest of these take up to 4 years to reach the western boundary. This sub-surface predictability has significant oceanographic interest. However, it is linked to only low levels of SST variability. Consequently, extrapolation of delayed action oscillator theory to decadal time-scales might not be justified.     

Interdecadal changes in the storm track activity over the North Pacific and North Atlantic

Analysis of NCEP-NCAR I reanalysis data of 1948–2009 and ECMWF ERA-40 reanalysis data of 1958–2001 reveals several significant interdecadal changes in the storm track activity and mean flow-transient eddy interaction in the extratropics of Northern Hemisphere. First, the most remarkable transition in the North Pacific storm track (PST) and the North Atlantic storm track (AST) activities during the boreal cold season (from November to March) occurred around early-to-mid 1970s with the characteristics of global intensification that has been noticed in previous studies. Second, the PST activity in midwinter underwent decadal change from a weak regime in the early 1980s to a strong regime in the late 1980s. Third, during recent decade, the PST intensity has been enhanced in early spring whereas the AST intensity has been weakened in midwinter. Finally, interdecadal change has been also noted in the relationship between the PST and AST activities and between the storm track activity and climate indices. The variability of storm track activity is well correlated with the Pacific Decadal Oscillation and North Atlantic Oscillation prior to the early 1980s, but this relationship has disappeared afterward and a significant linkage between the PST and AST activity has also been decoupled. For a better understanding of the mid-1970s’ shift in storm track activity and mean flow-transient eddy interaction, further investigation is made by analyzing local barotropic and baroclinic energetics. The intensification of global storm track activity after the mid-1970s is mainly associated with the enhancement of mean meridional temperature gradient resulting in favorable condition for baroclinic eddy growth. Consistent with the change in storm track activity, the baroclinic energy conversion is significantly increased in the North Pacific and North Atlantic. The intensification of the PST and AST activity, in turn, helps to reinforce the changes in the middle-to-upper tropospheric circulation but acts to interfere with the changes in the low-tropospheric temperature field.     

Transient wave activity and its fluxes in the North Atlantic Ocean simulated by a global eddy-resolving model

Eight-year daily mean output of a quasi-global eddy-resolving model is examined with a focus on the large-scale dynamical characteristics of the North Atlantic Ocean in a framework of potential vorticity (PV) and its derivatives. The model has reproduced some of the observed features of the mean potential vorticity field well. The three-dimensional structure of the mean potential vorticity supports baroclinic instability in most of the basin. Eddies are found to play important roles in the formation and maintenance of the mean potential vorticity fields. The contribution of relative vorticity to the mean potential vorticity field is found to be negligible for the most part. However, relative vorticity contribution to the source/sink of potential vorticity and eddy potential enstrophy is not negligible. We also find that eddies are not necessarily diffusive even on a basin-scale.     

Development of a hurricane boundary-layer wind model

Summary Hurricanes cause a variety of damage due to high winds, heavy rains, and storm surges. This study focuses on hurricanes’ high winds. The most devastating effects of sustained high winds occur in the first few hours of landfall. During the short period, hurricanes’ rainfall often increases, while the low-level pressure gradients continue to weaken. Latent heating does not appear to strengthen the surface winds. The indicator is that dry mechanisms such as the boundary layer processes and terrain are responsible for the damaging winds in the coastal areas. In this study, the design of a dry hurricane boundary layer wind model is described. The goal is to develop a forecast tool with near-real time applications in expeditious wind damage assessment and disaster mitigation during a hurricane landfall event. Different surface roughness lengths and topographic features ranging from flat land to the mountainous terrain of Taiwan were used in the model simulation experiments to reveal how the coastal environment affected the hurricane surface winds. The model performed quite well in all cases. The experiments suggested that the downward transfer of high momentum aloft played a significant role in the maintenance of high wind speeds at the surface. The surface wind maximums were observed on the lee sides of high terrain. The surface streamline analyses showed that the high mountains tended to block the relatively weak flow and caused small eddies, while they forced the stronger flow to turn around the mountains. Due to great difficulty in data collection, the hurricane boundary layer over land remains one of the least understood parts of the system. The dry model proves to be an effective way to study many aspects of hurricane boundary layer winds over a wide range of terrain features and landfall sites. The model runs efficiently and can be run on a medium-size personal computer. Received March 16, 2001 Revised September 10, 2001     

Formation and pathways of North Atlantic Deep Water in a coupled ice–ocean model of the Arctic–North Atlantic Oceans

We investigate the formation process and pathways of deep water masses in a coupled ice–ocean model of the Arctic and North Atlantic Oceans. The intent is to determine the relative roles of these water masses from the different source regions (Arctic Ocean, Nordic Seas, and Subpolar Atlantic) in the meridional overturning circulation. The model exhibits significant decadal variability in the deep western boundary current and the overturning circulation. We use detailed diagnostics to understand the process of water mass formation in the model and the resulting effects on the North Atlantic overturning circulation. Particular emphasis is given to the multiple sources of North Atlantic Deep Water, the dominant deep water masses of the world ocean. The correct balance of Labrador Sea, Greenland Sea and Norwegian Sea sources is difficult to achieve in climate models, owing to small-scale sinking and convection processes. The global overturning circulation is described as a function of potential temperature and salinity, which more clearly signifies dynamical processes and clarifies resolution problems inherent to the high latitude oceans. We find that fluxes of deep water masses through various passages in the model are higher than observed estimates. Despite the excessive volume flux, the Nordic Seas overflow waters are diluted by strong mixing and enter the Labrador Sea at a lighter density. Through strong subpolar convection, these waters along with other North Atlantic water masses are converted into the densest waters [similar density to Antarctic Bottom Water (AABW)] in the North Atlantic. We describe the diminished role of salinity in the Labrador Sea, where a shortage of buoyant surface water (or excess of high salinity water) leads to overly strong convection. The result is that the Atlantic overturning circulation in the model is very sensitive to the surface heat flux in the Labrador Sea and hence is correlated with the North Atlantic Oscillation. As strong subpolar convection is found in other models, we discuss broader implications.     

Increased hurricane intensities with CO2-induced warming as simulated using the GFDL hurricane prediction system

 The impact of CO₂-induced global warming on the intensities of strong hurricanes is investigated using the GFDL regional high-resolution hurricane prediction system. The large-scale initial conditions and boundary conditions for the regional model experiments, including SSTs, are derived from control and transient CO₂ increase experiments with the GFDL R30-resolution global coupled climate model. In a case study approach, 51 northwest Pacific storm cases derived from the global model under present-day climate conditions are simulated with the regional model, along with 51 storm cases for high CO₂ conditions. For each case, the regional model is integrated forward for five days without ocean coupling. The high CO₂ storms, with SSTs warmer by about 2.2 °C on average and higher environmental convective available potential energy (CAPE), are more intense than the control storms by about 3–7 m/s (5%–11%) for surface wind speed and 7 to 24 hPa for central surface pressure. The simulated intensity increases are statistically significant according to most of the statistical tests conducted and are robust to changes in storm initialization methods. Near-storm precipitation is 28% greater in the high CO₂ sample. In terms of storm tracks, the high CO₂ sample is quite similar to the control. The mean radius of hurricane force winds is 2 to 3% greater for the composite high CO₂ storm than for the control, and the high CO₂ storms penetrate slightly higher into the upper troposphere. More idealized experiments were also performed in which an initial storm disturbance was embedded in highly simplified flow fields using time mean temperature and moisture conditions from the global climate model. These idealized experiments support the case study results and suggest that, in terms of thermodynamic influences, the results for the NW Pacific basin are qualitatively applicable to other tropical storm basins. Received: 20 July 1998/Accepted: 24 December 1998     

Stochastically-forced multidecadal variability in the North Atlantic: a model study

Observations show a multidecadal signal in the North Atlantic ocean, but the underlying mechanism and cause of its timescale remain unknown. Previous studies have suggested that it may be driven by the North Atlantic Oscillation (NAO), which is the dominant pattern of winter atmospheric variability. To further address this issue, the global ocean general circulation model, Nucleus for European Modelling of the Ocean (NEMO), is driven using a 2,000 years long white noise forcing associated with the NAO. Focusing on key ocean circulation patterns, we show that the Atlantic Meridional Overturning Circulation (AMOC) and Sub-polar gyre (SPG) strength both have enhanced power at low frequencies but no dominant timescale, and thus provide no evidence for a oscillatory ocean-only mode of variability. Instead, both indices respond linearly to the NAO forcing, but with different response times. The variability of the AMOC at 30°N is strongly enhanced on timescales longer than 90 years, while that of the SPG strength starts increasing at 15 years. The different response characteristics are confirmed by constructing simple statistical models that show AMOC and SPG variability can be related to the NAO variability of the previous 53 and 10 winters, respectively. Alternatively, the AMOC and the SPG strength can be reconstructed with Auto-regressive (AR) models of order seven and five, respectively. Both statistical models reconstruct interannual and multidecadal AMOC variability well, while on the other hand, the AR(5) reconstruction of the SPG strength only captures multidecadal variability. Using these methods to reconstruct ocean variables can be useful for prediction and model intercomparision.     

Response of the North Atlantic subpolar gyre to persistent North Atlantic oscillation like forcing

The response of the North Atlantic subpolar gyre (SPG) to a persistent positive (or negative) phase of the North Atlantic oscillation (NAO) is investigated using an ocean general circulation model forced with idealized atmospheric reanalysis fields. The integrations are analyzed with reference to a base-line integration for which the model is forced with idealized fields representing a neutral state of the NAO. In the positive NAO case, the results suggest that the well-known cooling and strengthening of the SPG are, after about 10 years, replaced by a warming and subsequent weakening of the SPG. The latter changes are caused by the advection of warm water from the subtropical gyre (STG) region, driven by a spin-up of the Atlantic meridional overturning circulation (AMOC) and the effect of an anomalous wind stress curl in the northeastern North Atlantic, which counteracts the local buoyancy forcing of the SPG. In the negative NAO case, however, the SPG response does not involve a sign reversal, but rather shows a gradual weakening throughout the integration. The asymmetric SPG-response to the sign of persistent NAO-like forcing and the different time scales involved demonstrate strong non-linearity in the North Atlantic Ocean circulation response to atmospheric forcing. The latter finding indicates that analysis based on the arithmetic difference between the two NAO-states, e.g. NAO+ minus NAO?, may hide important aspects of the ocean response to atmospheric forcing.     

A new prediction model for grain yield in Northeast China based on spring North Atlantic Oscillation and late-winter Bering Sea ice cover

Accurate estimations of grain output in the agriculturally important region of Northeast China are of great strategic significance for guaranteeing food security. New prediction models for maize and rice yields are built in this paper based on the spring North Atlantic Oscillation index and the Bering Sea ice cover index. The year-to-year increment is first forecasted and then the original yield value is obtained by adding the historical yield of the previous year. The multivariate linear prediction model of maize shows good predictive ability, with a low normalized root-mean-square error (NRMSE) of 13.9%, and the simulated yield accounts for 81% of the total variance of the observation. To improve the performance of the multivariate linear model, a combined forecasting model of rice is built by considering the weight of the predictors. The NRMSE of the model is 12.9% and the predicted rice yield explains 71% of the total variance. The corresponding cross-validation test and independent samples test further demonstrate the efficiency of the models. It is inferred that the statistical models established here by applying year-to-year increment approach could make rational prediction for the maize and rice yield in Northeast China before harvest. The present study may shed new light on yield prediction in advance by use of antecedent large-scale climate signals adequately.     

Probabilistic seasonal prediction of the winter North Atlantic Oscillation and its impact on near surface temperature

The North Atlantic Oscillation (NAO) is a major winter climate mode, describing one-third of the inter-annual variability of the upper-level flow in the Atlantic European mid-latitudes. It provides a statistically well-defined pattern to study the predictability of the European winter climate. In this paper, the predictability of the NAO and the associated surface temperature variations are considered using a dynamical prediction approach. Two state-of-the-art coupled atmosphere–ocean ensemble forecast systems are used, namely the seasonal forecast system 2 from the European Centre for Medium Range Weather Forecast (ECMWF) and the multi-model system developed within the joint European project DEMETER (Development of a European Multi-Model Ensemble Prediction System for Seasonal to Inter-annual Prediction). The predictability is defined in probabilistic space using the debiased ranked probability skill score with adapted discretization (RPSS_D). The potential predictability of the NAO and its impact are also investigated in a perfect model approach, where each ensemble member is used once as observation. This approach assumes that the climate system is fully represented by the model physics. Using the perfect model approach for the period 1959–2001, it is shown that the mean winter NAO index is potentially predictable with a lead time of 1 month (i.e. from 1st of November). The prediction benefit is rather small (6% skill relative to a reference climatology) but statistically significant. A similar conclusion holds for the near surface temperature variability related to the NAO. Again, the potential benefit is small (5%) but statistically significant. Using the forecast approach, the NAO skill is not statistically significant for the period 1959–2001, while for the period 1987–2001 the skill is surprisingly large (15% relative to a climate prediction). Furthermore, a weak relation is found between the strength of the NAO amplitude and the skill of the NAO. This contrasts with El Niño/Southern Oscillation (ENSO) variability, where the forecast skill is strongly amplitude dependent. In general, robust results are only achieved if the sensitivity with respect to the sample size (both the ensemble size and length of the period) is correctly taken into account.

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This revised version was published online in May 2005. Some black and white figures were replaced by coloured figures.     

Evaluation of the North Atlantic Oscillation as simulated by a coupled climate model

 The realism of the Hadley Centre’s coupled climate model (HadCM2) is evaluated in terms of its simulation of the winter North Atlantic Oscillation (NAO), a major natural mode of the Northern Hemisphere atmosphere that is currently the subject of considerable scientific interest. During 1400 y of a control integration with present-day radiative forcing levels, HadCM2 exhibits a realistic NAO associated with spatial patterns of sea level pressure, synoptic activity, temperature and precipitation anomalies that are very similar to those observed. Spatially, the main model deficiency is that the simulated NAO has a teleconnection with the North Pacific that is stronger than observed. In a temporal sense the simulation is compatible with the observations if the recent observed trend (from low values in the 1960s to high values in the early 1990s) in the winter NAO index (the pressure difference between Gibraltar and Iceland) is ignored. This recent trend is, however, outside the range of variability simulated by the control integration of HadCM2, implying that either the model is deficient or that external forcing is responsible for the variation. It is shown, by analysing two ensembles, each of four HadCM2 integrations that were forced with historic and possible future changes in greenhouse gas and sulphate aerosol concentrations, that a small part of the recent observed variation may be a result of anthropogenic forcing. If so, then the HadCM2 experiments indicate that the anthropogenic effect should reverse early next century, weakening the winter pressure gradient between Gibraltar and Iceland. Even combining this anthropogenic forcing and internal variability cannot explain all of the recent observed variations, indicating either some model deficiency or that some other external forcing is partly responsible. Received: 20 August 1998 / Accepted: 12 May 1999     

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.     

Storm cyclones in the North Atlantic

Considered are long-term features and characteristics of storm activity variability in the North Atlantic based on the method of automatic identification of cyclone centers using the data on sea level pressure as well as the estimates of the maximum speed of the surface wind in the area of cyclones. Integral regional parameters of the variability of storm cyclone frequency for the gradations of the surface wind speed are presented for some areas of the North Atlantic. Investigated is the interrelation between extremely deep and storm cyclones.