Réf. Brunetti & al. 2009 - A

Référence bibliographique complète

BRUNETTI, M., LENTINI, G., MAUGERI, M., NANNI, T., AUER, I., BÖHM, R., SCHÖNER, W. 2009. Climate variability and change in the Greater Alpine Region over the last two centuries based on multi-variable analysis. International Journal of Climatology, 29, 2197-2225.

Abstract: An extensive analysis of the HISTALP database is presented with the aim of giving a comprehensive picture of secular climate variability and change in the Greater Alpine Region (GAR, 4–19 E, 43–49 N). The HISTALP database encompasses 242 sites and concerns temperature, pressure, precipitation, cloudiness, sunshine duration, vapour pressure and relative humidity. The analyses are based on four regional mean records representing different GAR low-level areas and on an additional mean record representing high-level locations.

The first goal of the paper is to give an overview of the seasonal and annual records for the different variables, aiming to highlight both variability on decadal time scale and long-term evolution. Then it focuses on trend and correlation analysis. Trends are presented both for the period of common data availability for all regional average series and for moving windows that permit studying the trends over a wide range of timescales. Correlations among the different variables are presented both for the regional average series and for their high-pass-filtered versions.

The analyses, beside highlighting a warming that is about twice as large as the global trend, also show that the different variables have responded in different ways to this warming and that the mutual interactions linking the different variables are often present only at specific temporal scales and only in parts of the GAR and in defined seasons. In spite of this complex behaviour, which may also be due to some residual inhomogeneities still affecting the data, the analyses give evidence that the HISTALP database has an excellent internal consistency and show that the availability of a multi-variable database turns out to be very useful in order to evaluate the reliability of the reconstruction of each variable and to better understand the behaviour and the mutual interactions of the different variables.

Mots-clés

Homogenised series - Alpine region - Temperature - Pressure - Precipitation - Cloudiness - Sunshine duration - Vapour pressure - Relative humidity

 

Organismes / Contact

• Institute of Atmospheric Sciences and Climate, via Gobetti, 101—I-40129 Bologna, Italy (m.brunetti@isac.cnr.it)
Department of Physics—via Celoria, 16—I-20133 Milan, Italy
• Central Institute for Meteorology and Geodynamics, Hohe Warte 38, A-1190 Vienna, Austria

 

(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

 Temperature - Pressure - Precipitation - Cloudiness - Sunshine duration - Vapour pressure - Relative humidity

 

 

 

 

Pays / Zone

Massif / Secteur

Site(s) d'étude

Exposition

Altitude

Période(s) d'observation

Greater Alpine Region (GAR, 4–19 E, 43–49 N)

 

 

 

 

 ~1800-2005

 

(1) - Modifications des paramètres atmosphériques

Reconstitutions

 

Observations

The analyses highlighted an average GAR warming of about 1.3 K per century over the common period covered by all the variables (1886–2005). Such a warming turns out to be slightly stronger (1.4 K per century) over the 1906–2005 period (reference period of the IPCC AR4) and it results in about twice as large as the global trend referred to by IPCC (2007). The different variables responded in different ways to this warming. In particular, vapour pressure is the variable showing the most evident link to the temperature increase, with a positive trend of about 0.5 hPa per century. Beside vapour pressure, only pressure shows a clear signal in response to the warming, with an increase of about 1 hPa per century. In this case, however, the seasonal trends are very different, with most part of the increase being concentrated in spring (2 hPa per century). If only the low-level areas are considered, relative humidity also has a clear long-term trend, with a decrease of about 5% per century. Such a decrease is, however, not shown by the record representing the high-level locations.

The other meteorological variables show lower spatial and seasonal coherence of long-term tendencies. In particular, precipitation has an interesting North–South dipole, with positive trend in the Northern side of the Alps and a decrease in the Southern side of the Alps. A dipolar structure is also shown by the cloudiness and sunshine duration trends, even though in this case the most remarkable difference concerns the Eastern and the Western parts of the GAR.

Trend analyses have also shown that the mutual interactions linking the different variables have to be investigated considering a wide range of temporal scales. In fact, in several cases, it can be observed that two variables showing a certain link in their year-to-year and decadal variability, tend not to show the same behaviour in their long-term evolution. On the other hand, there are cases in which there is a consistency in long-term trends that has no counterpart in the variability at shorter timescales.

In some cases, these differences are easily explained. An example concerns sunshine duration and relative humidity in the NE area: in spite of high significant negative correlation, in the last decades both records exhibit a clear long-term decrease. The decrease of relative humidity is probably due to the fact that, as a consequence of soil water limitation, evapotranspiration does not increase so much to balance the higher capacity of the atmosphere in storing water vapour, whereas the decrease of sunshine duration is probably due to an increase of atmospheric aerosol. In other cases it is difficult to find a physical explanation to the phenomenon, in particular, for some of the cloudiness–sunshine duration pairs that exhibit an unexpected agreement in their long-term trends. The most evident case concerns the summer high-level records.

The presence of some physically inexplicable divergences in the agreement at different timescales might indicate that some residual inhomogeneities still affect the HISTALP database, in spite of the remarkable homogenisation effort. Notwithstanding some minor problems, which will probably be addressed in the future by means of the availability of new data and metadata, it is worth highlighting that the HISTALP database shows an excellent internal consistency and that such a high-quality multi-variable database turns out to be a very useful tool both to evaluate the reliability of the reconstruction of each variable and to better understand the behaviour and the mutual interactions of the different variables.

An interesting example concerns the coherent relative humidity pattern, as compared to vapour pressure at low-level and their different behavior at high-level in the last decades. In this period, in the L region, the vapour pressure increase (of approximately 0.8 hPa) was not enough to balance the temperature increase of more than 1 K. Therefore relative humidity decreased considerably. On the contrary, the smaller increase of about 0.4 hPa at high elevation was sufficient to keep relative humidity rather stable (or only slightly decreasing) in the mountains, because of the lower saturation vapour pressure in the colder air at high elevations.

Naturally the task of understanding the mutual interactions linking the different variables was not completely successful in all cases. An important link that has to be studied more in detail concerns temperature and pressure. In fact, even though the comparison between such variables displays interesting similarities on a wide range of timescales (from the long-term evolution to the year-to-year variability) and even though such similarities may suggest that the GAR long-term temperature evolution may have been influenced, at least partially, by variations in atmospheric circulation, the conclusion that the stronger warming of the GAR as compared to the global warming might be explained by a long-term evolution of the atmospheric circulation has to be considered with great caution, because (1) temperature and pressure are not completely independent of one another, especially if station level data are considered, (2) the long-term evolution of pressure is not mirrored by the long-term evolutions of precipitation, cloudiness and sunshine duration expected on the basis of their relations with pressure at shorter timescales.

So, the results of the analysis of the HISTALP multivariable database seem to be not conclusive as far as the influence of long-term changes in atmospheric circulation on the warming in the GAR is considered. The data, beside suggesting a possible influence of long-term changes in atmospheric circulation on the warming in the GAR, may also indicate either that the long-term evolution of pressure does not display a simple link with changes in the atmospheric circulation or that the long-term evolutions of precipitation, cloudiness and sunshine duration are also linked to processes that do not depend on atmospheric circulation (e.g. atmospheric aerosols).

Modélisations

 

Hypothèses

 

 

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

The HISTALP multi-variable database was analysed with the aim of giving a comprehensive picture of secular climate variability and change in the Greater Alpine Region (GAR). The analyses were performed on four regional mean records representing the different GAR low-level areas and on one additional mean record representing all-GAR high-level locations.

 

(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

 

Hypothèses

 

 

Paramètre de l'aléa

Sensibilité des paramètres de l'aléa à des paramètres climatiques

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

 

 

 

 

(4) - Remarques générales

 

 

(5) - Syntèses et préconisations

 

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