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Spatial overlaping areas of several teleconection indices on Spain´s
Mediterranean façade according to spring rainfall.
J.C. González-Hidalgo (1), J.A. Lopez-Bustins (2),
J. Martin-Vide (2), M. Brunetti (3), T. Nanni (3),
P. Stepanek (4), M. de Luis (1)
(1) Department of Geography, Zaragoza University, Spain(2) Group of Climatology, University of Barcelona, Spain(3) ISAC-CNR, Bologna, Italy(4) Czech Hydrometeorological Institute, Brno, Czech Republic
INTRODUCTION
• Hydrological cycle modification by global warming might affect precipitation. This impact could be more important than the global warming itself.
• Rainfall variability analyses is one of the main objectives of the IPCC, particularly in those areas which are strongly dependent upon water resources (e.g. Mediterranean basin).
• Global projections are not useful at local scale. High spatial resolution analysis are absolutely required.
HYPOTHESIS
In the Mediterranean façade of Spain monthly precipitation is simultaneously affected by different atmospheric patterns.
These patterns can be dominant or not depending on the different regions and months.
There are overlapping areas.
The analysis of these patterns may help us to understand the Mediterranean rainfall variability.
STUDY AREA
Mediterranean façade of Iberian Peninsula (Spain),
1/3 of Iberian Peninsula, 37% of conterminous Spain, 182,000 km2
Precipitation is characterized by irregular, seasonal and torrential nature
Precipitation database consists of monthly, homogeneous and complete series over 1,100 meteorological stations (period 1951-2000),
Overall density 1 station / 150-200 km2.
Information is available to 1500 m o.s.l.
DATA BASE
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Altitude m Series
< 250 292
250-500 255
500-750 227
750-1000 189
1000-1500 137
1500-1750 9
>1750 4
Monthly Precipitation data, Mediterranean of Spain MOPREDAMES
and METHOD
• Pearson’s correlation coefficient between monthly precipitation dataset and teleconnection indices:
NAOI series from Jones et al. (1997, IJC 17, 1433-1450.)
MOI series from CRU web site
McI series from Brunetti et al. (2002, IJC 22, 1455-1471)
WeMOI series from Martin-Vide and Lopez-Bustins (2006, IJC 26, 1455-1475).
Dipoles of NAOI, MOI, McI and WeMOI teleconnection indices
Padua
Lod AirpIsrael
Marseille Padua
Lod AirpIsrael
Marseille
Gibraltar/San Fernando
Iceland
J F M Ap My Jn Jl Ag S O N DNAOI-MOI 0,88 0,81 0,73 0,57 0,40 0,37 ns 0,32 0,65 0,73 0,84 0,87NAOI-WeMOI 0,36 ns ns 0,35 ns ns ns ns ns ns ns 0,48NAOI-McI 0,44 0,44 0,35 ns 0,38 0,32 0,42 0,32 0,46 0,46 0,55 0,42MOI McI 0,65 0,71 0,52 ns 0,72 0,58 0,78 0,78 0,31 0,45 0,65 0,62MOI WeMOI 0,55 0,34 0,43 0,64 0,47 0,49 ns ns 0,32 0,48 0,53 0,64McI WeMOI ns -0,38 -0,33 -0,47 ns ns ns ns -0,33 -0,43 ns ns
Correlation between indices
• NAOI correlates with MOI and McI but not with WeMOI.
• MOI correlates with McI and WeMOI
• McI correlates poorly with WeMOI (and negatively)
WeMOI is independent of NAOI,
MOI is the mediterranean expresion of NAOI, and
McI is a subregional pattern linked to MOI-NAOI
RESULTS
In the study area February-May precipitation is under different teleconnection indices influence.
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Pearson > 0.50, <-0.50
FEBRUARY correlation between rainfall and teleconnection
Highest teleconnection index correlation (number of stations)
February March April May
NAOI 88
MOI 412
McI 48
WeMOI 546
FEBRUARY (not properly spring month)
MOI predominates (inland), and WeMOI (east coastland)
NAOI signal is weeker than MOI and it is only detected as predominant in a few meteorological station NW
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• Negative correlation
Pearson > 0.50, <-0.50
MAY correlation between rainfall and teleconnection
MOI
McI WeMOI
NAO
Highest teleconnection index correlation (number of stations)
February March April May
NAOI 366
MOI 107
McI 135
WeMOI 193
MAY The overall spatial distribution of the atmospheric The overall spatial distribution of the atmospheric
patterns influence is not homogeneous.patterns influence is not homogeneous. NAOI is still the most correlated index with NAOI is still the most correlated index with
precipitation on the Iberian Mediterranean façade.precipitation on the Iberian Mediterranean façade.
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+/- NAOI
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None
CONCLUSIONS• In the study area February-May precipitation is under
different teleconnection indices influence.
CONCLUSIONS
• Atlantic fluxes increase their influence on spring rainfall while Mediterranean ones decrease (opposed results for autumn and winter analyses).
Highest teleconnection index correlation (number of stations)
February March April May
NAOI 88 292 503 366
MOI 412 734 76 107
McI 48 42 73 135
WeMOI 546 30 201 193
CONCLUSIONS
• Monthly analysis let us to detect spatial and temporal shifts of the highest correlated areas between precipitation and the teleconection indices.
• The low correlation (although significant) between NAOI and precipitation suggests that MOI explains better than NAOI February-March precipitation over eastern Iberian Peninsula.
• This approach could help us to understand the nature of eastern Iberia rainfall variability.
And… overall ………….
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Thank you very much
Autumn and winter analysis can be found in
• Geophysical Research Abstracts, Vol. 9, 02219, 2007. SRef-ID: 1607-7962/gra/EGU2007-A-02219
• EMS7/ECAM8 Abstract, Vol 4, EMS2007-A-00190, 2007. 7th EMS Annual Meeting / 8th ECAM.
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