Réf. Ulbrich & al. 2008 - A

Référence bibliographique complète

ULBRICH, U., PINTO, J.G., KUPFER, H., LECKEBUSCH, G.C., SPANGEHL, T., REYERS, M. 2008. Changing Northern Hemisphere Storm Tracks in an Ensemble of IPCC Climate Change Simulations. Journal of Climate, 21, 1669-1679. DOI: 10.1175/2007JCLI1992.1

Abstract: Winter storm-track activity over the Northern Hemisphere and its changes in a greenhouse gas scenario (the Special Report on Emission Scenarios A1B forcing) are computed from an ensemble of 23 single runs from 16 coupled global climate models (CGCMs). All models reproduce the general structures of the observed climatological storm-track pattern under present-day forcing conditions. Ensemble mean changes resulting from anthropogenic forcing include an increase of baroclinic wave activity over the eastern North Atlantic, amounting to 5%–8% by the end of the twenty-first century. Enhanced activity is also found over the Asian continent and over the North Pacific near the Aleutian Islands. At high latitudes and over parts of the subtropics, activity is reduced. Variations of the individual models around the ensemble average signal are not small, with a median of the pattern correlation near r = 0.5. There is, however, no evidence for a link between deviations in present-day climatology and deviations with respect to climate change.

Mots-clés
 

Organismes / Contact

• Institute for Meteorology, Freie Universität Berlin, Berlin, Germany - ulbrich@met.fu-berlin.de
• Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany
• Institute for Meteorology, Freie Universität Berlin, Berlin, Germany
• Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany

The work was partly supported by the European Union in the ENSEMBLES project (Contract GOCE-CT-2003-505593-ENSEMBLES) and by the German research ministry Grant “Collaborative Climate Computing Grid (C3-Grid)” under Grant 01AK801E.


(1) - Paramètre(s) atmosphérique(s) modifié(s)
(2) - Elément(s) du milieu impacté(s)
(3) - Type(s) d'aléa impacté(s)
(3) - Sous-type(s) d'aléa
Storm Tracks   Storms  

Pays / Zone
Massif / Secteur
Site(s) d'étude
Exposition
Altitude
Période(s) d'observation
Northern Hemisphere        

1961–2000
2081–2100


(1) - Modifications des paramètres atmosphériques
Reconstitutions
 
Observations
 
Modélisations
 
Hypothèses
 

Informations complémentaires (données utilisées, méthode, scénarios, etc.)
 

(2) - Effets du changement climatique sur le milieu naturel
Reconstitutions
 
Observations
 
Modélisations
 
Hypothèses
 

Sensibilité du milieu à des paramètres climatiques
Informations complémentaires (données utilisées, méthode, scénarios, etc.)
 

 


(3) - Effets du changement climatique sur l'aléa
Reconstitutions
 
Observations
 
Modélisations

While the former Intergovernmental Panel on Climate Change (IPCC) report (Houghton et al. 2001, p. 73) stated that there was little agreement among models concerning future changes in storm intensity, frequency, and variability, the IPCC AR4 (Solomon et al. 2007) mentions that “extra-tropical storm tracks are projected to move poleward, with consequent changes in wind, precipitation, and temperature patterns, continuing the broad pattern of observed trends over the last half-century.” This summarizes a number of recent scientific results cited in the report. In the present paper, the authors highlight some of the recent publications on this issue, including both studies for present-day and future climate, which are based on single model runs, on ensembles of runs with the same GCM, and on multimodel ensembles [see review in the study].

In summary, the papers considering the effect of the anthropogenic climate change on midlatitude synoptic activity produce an emerging picture of corroborating results, in spite of the remaining variety in detail arising from the following:
- different individual signals resulting from the different model(s) and model run(s) considered, which depend on the specific model considered and on the decadal variability superimposed on the anthropogenic signals;
- specific characteristics of different cyclone identification and tracking schemes;
- different measures quantifying the strength of midlatitude baroclinic wave activity; and
- opposing signal effects for intense and weaker cyclones, which lead to a dependence of results on the chosen thresholds.

In the present study, the authors use a multimodel ensemble of coupled global circulation model (CGCM) simulations collected for the so-called IPCC diagnostic exercise, exploring the model ensemble’s representation of the observational horizontal storm-track pattern, the ensemble mean climate signal, and the individual models’ deviations. This work is related to the recent studies of Yin (2005) and Lambert and Fyfe (2006) who had focused on the zonal and hemispheric mean signals in synoptic activity.

The authors have investigated a 23-member ensemble of simulations performed with 16 different GCMs for the present day and for future (scenario A1b) climate forcing in terms of storm-track activity, computed from daily mean MSLP data. With respect to present-day climate, the models perform well in reproducing the observed climatological pattern. The ensemble mean performs as good as the single individual model closest to the NCEP–NCAR climatology. The climate change signal for the model ensemble provides evidence for increasing storm-track activity in the eastern North Atlantic/western Europe, the North Pacific, and parts of the Asian continent. Many individual model signals are only in modest agreement with the common signal, but only one of the models has a negative correlation with the ensemble mean signal pattern. This is the same model, which is worst in representing the observed storm-track pattern, but the authors also found other models with rather low agreement, and so there was no obvious justification to treat it as an outlier. They have also compared signal patterns from pairs of individual models, finding that negative pattern correlations occur for several such pairs. It is also noted that the individual models’ deviations from the ensemble mean signal do not apparently reflect deviations in present-day climatology.

Comparison with other studies suggests that the regional increase found for the storm track at sea level is exceeded in intensity and zonal extension by the signals at upper levels: Yin (2005) considered the zonal mean storm-track signal in a multimodel ensemble obtained from the same data source as used in the present study, and found evidence that the increase of the signal with height is caused by increasing baroclinicity. Note, however, that even though the present results show poleward shifts of storm-track activity in some areas (e.g., the North Pacific), they do not resemble the clear poleward shift of zonal mean eddy activity in the upper troposphere found by Yin (2005). Pinto et al. (2007b) considered the storm-track signal at 500 hPa in a small ensemble performed with the ECHAM5 model, that is, the model identified in the present study as the one with the best agreement of the climate change signal with the ensemble mean. They showed a 500-hPa storm-track signal that is extending downstream from the areas of maximum increase in the Atlantic into the Asian continent, thus linking the areas of increasing activity at the surface. Note that the ECHAM5 model also features a very good representation of the MSLP fields (Van Ulden and van Oldenborgh 2006).

The results seem to corroborate estimates based on climate projections, which indicate an increasing storm risk over western Europe under climate change (Pinto et al. 2006, 2007a,b; Leckebusch et al. 2006, 2007). The ECHAM5 model is one of the GCMs providing the basis for these suggestions. It appears that a physical interrelation between increasing storm-track activity, intensifying extreme cyclones, and windstorm events could be evident. One should bear in mind, however, that the area of intensifying storm-track activity (related to the sequence of local high and low pressures) cannot be interpreted as an area of increased windstorm risk. For the ECHAM5 A1B scenario, for example, the area with significantly increasing extreme wind storms (Pinto et al. 2007b) is largely located downstream of the area with increasing stormtrack activity in the eastern North Atlantic.

Using ensembles should minimize the insecurity arising from natural climate variability as it is produced by the models. This variability requires that either longer time series and/or larger ensembles of model runs are produced and evaluated. Finding similar correlations between the climate change patterns from runs produced with the same GCM on the one hand, and the respective intermodel correlations on the other hand, the authors suggest that the 20-yr scenario period that is used is still a bit short for adequately dealing with temporal variability. With respect to the present approach of including all available models with equal weight, one could argue that excluding outliers from the ensemble could produce more consistent results. Their identification (either from their representation of present-day climatology or from the agreement of climate signals with the ensemble mean, e.g.), however, is not unambiguous. A thorough investigation into the reasons for a model’s seemingly bad representation of present-day climate, or for a signal that contradicts many other models, is the more adequate way to deal with this part of insecurity about climate change [see, e.g., Greeves et al. (2007) for an assessment of storm-track sensitivities arising from the formulation of the Hadley Centre’s models dynamical cores and resolution].

The current paper demonstrated that a common greenhouse gas signal can be identified from an ensemble of model simulation, using a specific quantification measure for storm-track activity. After asking what causes the impression of diverging results in different studies on changing storm tracks, the authors think that the different approaches used for quantifying them are part of the story. In general, the existence of the different approaches to study storm tracks is well justified, because “mid-latitude storms are complicated features and as such require a variety of analytical methods to assess their representation in models” (Greeves et al. 2007). Because the different analytical methods highlight different aspects of the storm tracks, they do not necessarily have to produce identical climatological or climate change patterns [in spite of usage of the same data source; see, e.g, Hoskins and Hodges (2002)]. Further work is needed to understand these differences, because they can help to understand this part of the physical climate system and its sensitivity to rising greenhouse gas concentrations [see Jiang and Perrie (2007) for a recent example of such an investigation].

Hypothèses
 

Paramètre de l'aléa
Sensibilité des paramètres de l'aléa à des paramètres climatiques
Informations complémentaires (données utilisées, méthode, scénarios, etc.)
 

The authors have chosen to consider the period associated with present-day greenhouse gas forcing (1961–2000) and the period for the final two decades of the Special Report on Emission Scenarios (SRES) A1B scenario (2081–2100). Other scenarios are not considered in the present study, but according to results of Lambert and Fyfe (2006) and Pinto et al. (2007b) the signals typically increase with increasing forcing.

Because of the large amount of data featuring slightly different spatial resolutions and their availability only as daily averages, the authors refrained from a thorough identification of cyclones and their tracks. Instead, they use a simple approach for the quantification of synoptic wave activity (“storm track”) after Blackmon (1976) and Blackmon et al. (1977). It was originally defined as the standard deviation of the bandpass- (2–6 days) filtered variability of 500-hPa geopotential heights, thus representing the sequence of upper-air troughs and ridges as the tropospheric counterparts of the surface cyclones and high pressure systems (Wallace and Gutzler 1981; Blackmon et al. 1984a,b; Wallace et al. 1988). Because the IPCC data archive used does not contain daily height data for the 500-hPa level, the authors decided to perform the respective computations based on the available mean sea level pressure (MSLP) data. Note that the storm track is not affected by changes in the long-term mean MSLP (in contrast to cyclone core depth) so that changes can directly be assigned to the transient waves. Because it includes variability of both high and low surface pressure systems it should be distinguished from results of feature- (mostly cyclone) tracking schemes partly also operating with MSLP data. Grid points at high orography (>1000 m MSL) were excluded from all consideration to avoid a possible influence of extensive extrapolation below ground. The models’ representation of present-day climate was validated using the National Centers for Environmental Prediction (NCEP)–NCAR reanalysis (Kalnay et al. 1996) for the period of 1958/59– 1997/98.


(4) - Remarques générales

Cyclones and the associated baroclinic waves are key features of midlatitude weather and climate. Their occurrence, tracks, and intensities are most relevant for both climate means (e.g., Knappenberger and Michaels 1993; Hurrell 1995; Rogers 1997; Trigo et al. 2000), and for the generation of extreme events (e.g., Ulbrich et al. 2001, 2003a,b; Mudelsee et al. 2004). Their consideration in numerical models can provide insight into the mechanisms of simulated present-day variability and to anthropogenic climate change as simulated under the respective scenarios.


(5) - Syntèses et préconisations
 

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