precipitation variations over the iberian peninsula under climate change conditions c. rodríguez...

Precipitation variations over the Iberian peninsula under climate change conditions

C. Rodríguez Puebla y S. NietoDept. de Física General y de la Atmósfera

Universidad de Salamanca

28/10/2008 Seminario CLIVAR_Es , Madrid 11-13 Febrero 2009

Motivation

Why precipitation shows a trend to decrease over the Iberian peninsula?

Trenberth, et al. 2007: Observations: Surface and Atmospheric Climate Change. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change Cambridge University Press, Cambridge

2

IPCC report 2007

28/10/20083

Observed precipitation time series (DJFM)

Datos de la AEMet

Kendall’Z = -2.2

Datos grid (CRU-Ensembles)

Kendall’Z = -1.2

Precipitation trend AEMet Precipitation trend Cru_Ensemble)

4

Links between precipitation (DJFM) and the NAO for observations

Prec

ipi (

mm

/mes

)

NAO pattern for DJFM (shaded)Correlation pattern between mean precipitation over the IP and sea level pressure (SLP)

R= -0.67 ± 0.06

Lamb & Peppler 1987, BAMSHurrel et al. 2003, Geophysical Monograph vol. 134

Precip. NAO

Mean 68 mm 0

std 23.4 1

Kurtosis -0.2 -0.4

Skewness 0.5 -0.1

Kendall’Z -2.15 3.6

Sens’s -0.43 mm/mes

0.02

5

R= -0.95 ± 0.002

NAO effects on precipitation (DJFM)

EOF1 of precipitation_OBS (shaded) and correlation between NAO and precipitation(contour lines)

Var=74%

R= -0.67 ±0.06

6

R= -0.92 ± 0.03

28/10/20087

What models tell us about the trend of precipitation ?

7

Data: WCRP CMIP3, PCMDIhttp://www-pcmdi.llnl.gov/

Model names Center, Country Resolution and References

BCCR-BCM2.0 Bjerknes Centre for Climate Research, NorwayT63 L31(Deque et al., 1994)

CGCM3.1 (T63) Canadian Centre for Climate Modelling and Analysis, Canada T63 L31(Flato et al., 2000)

CSIRO-Mk3.5 Commonwealth Scientific and Industrial Research Organisation, Australia T63 L18(Gordon and Coauthors, 2002)

ECHAM5/MPI-OM Max Planck Institute for Meteorology, Germany T63 L31(Roeckner and Coauthors, 2003)

ECHO-G Meteorological Institute of the University of Bonn, Meteorological Research Institute of the Korea, Germany, Korea

T30 L19

FGOALS-g1.0 National Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, China

T42 L26

GFDL-CM2.1 NOAA/Geophysical Fluid Dynamics Laboratory, USA 2.0 o X 2.5 o L24(Delworth et al., 2006)

INGV-SXG Instituto Nazionale di Geofisica e Vulcanologia, Italy T106 L19INM-CM3.0 Institute for Numerical Mathematics, Russia 4 o X 5 o L21IPSL-CM4 Institut Pierre Simon Laplace, France 2.5 o x 3.75 o L19MIROC3.2(medres) Center for Climate System Research (University of Tokyo, Japan T42 L20

MRI-CGCM2.3.2 Meteorological Research Institute, Japan T42 L30

PCM National Center for Atmospheric Research, USA T42 L26(Kiehl et al., 2004)

UKMO-HadCM3 Hadley Centre for Climate Prediction and Research/Met. Office, UK 2.5 o X 3.75 o L19(Pope et al., 2007)

UKMO_HadGEM1 Hadley Centre for Climate Prediction and Research/Met. Office, UK 1.3o X 1.9 o

(Martin et al., 2006)

8

Experiments

Experiments Forcing

20C3M Simulations to the year 2000, starting end 1800 with pre-industrial conditions, with natural and anthropogenic forcing.

SRES A2 21 st simulations with strong CO2 forcing, approximately 820 ppm to the year 2100.

SRES A1B 21 st simulations with medium CO2 forcing approximately 700 ppm to the year 2100.

SRES B1 21 st simulations with low CO2 forcing approximately 550 ppm to the year 2100.

9

Mean precipitation patterns over the Iberian peninsula

10

CRU-ENSEMBLES

20C3M

SRES A2 SRES A1B

Precipitation simulations averaged over the Iberian peninsula: 20C3M and SRES A2

Multi-model precipitation averaged over the IP

11

Precipitation trend

Precipitation simulations averaged over the Iberian peninsula: 20C3M and SRES A1B


12

Precipitation trend

Precipitation simulations averaged over the Iberian peninsula: 20C3M and SRES B1


20C3M A2 A1B B1

Kendall’Z -0.4 -4.8 -4.7 -1.2

Sen’s (mm/mes)

-0.012 -0.09 -0.08 -0.02

13

Relative precipitation changes: (SRES– 20C3M)*100/20C3M

14

SRES A2 SRES A1B

SRES B1

Mehods to obtain the NAO

1. EOF (Bretherton, 1992, Wallace 1981)

2. Selection of stations (Jones, 1997)

3. SLP averaged over areas (Stephenson 2006, Kuzmina 2005)

4. Project the SLP of model data onto the NAO pattern from reanalysis data.

1528/10/2008

Multi-model

20C3M SRESA2 SRESA1B SRESB1

R (1 and 4) 0.99 0.99 0.99 0.99

Precipitation response to NAO

28/10/200816

Model names 20C3M Correlation NAO/precipitation(IP)

SRES A2 Correlation NAO/precipitation(IP)

SRES A1B Correlation NAO/precipitation(IP)

SRES B1 Correlation NAO/precipitation(IP)

BCCR-BCM2.0 -0.67 ± 0.05 -0.68± 0.04 -0.60 ± 0.04 -0.74 ± 0.03CGCM3.1 (T63) -0.62 ± 0.04 -0.59 ± 0.04 -0.66 ± 0.03 -0.55 ± 0.04

CSIRO-Mk3.5 -0.52 ± 0.06 -0.68 ± 0.04 -0.60 ± 0.03 -0.58 ± 0.04

ECHAM5/MPI -0.62 ± 0.07 -0.78 ± 0.04 -0.70 ± 0.04 -0.77 ± 0.04

ECHO-G -0.64 ± 0.05 -0.69 ± 0.03 -0.70 ± 0.04 -0.78 ± 0.03

FGOALS-g1.0 -0.73 ± 0.03 -0.60 ± 0.02 -0.53 ± 0.03

GFDL-CM2.1 -0.80 ± 0.04 -0.77 ± 0.03 -0.76 ± 0.03 -0.69 ± 0.04

INGV-SXG -0.72 ± 0.04 -0.74 ± 0.03 -0.70 ± 0.03INM-CM3.0 -0.68 ± 0.06 -0.57 ± 0.04 -0.58 ± 0.04 -0.60 ± 0.04IPSL-CM4 -0.76 ± 0.04 -0.69 ± 0.04 -0.78 ± 0.04MIROC3.2(medres) -0.57 ± 0.05 -0.71 ± 0.03 -0.74 ± 0.03 -0.69 ± 0.03MRI-CGCM2.3.2 -0.79 ± 0.05 -0.90 ± 0.03 -0.85 ± 0.03 -0.83 ± 0.04PCM -0.65 ± 0.05 -0.71 ± 0.04 -0.75 ± 0.04

UKMO-HadCM3 -0.68 ± 0.06 -0.74 ± 0.03 -0.67 ± 0.04 -0.79 ± 0.04

UKMO_HadGEM1 -0.57 ± 0.06 -0.61 ± 0.04 -0.62 ± 0.05

Precipitation response to NAO for multi-models

28/10/200817

20C3M A2 A1B B1

R -0.64 -0.76 -0.77 -0.71

b (slope) -0.07 -0.12 -0.12 -0.11

a (cte) 2.13 2.02 1.99 2.07

28/10/200818


EOF1 of precipitation_model (shaded) and Correlation between NAO and precipitation(contour lines)

Links between precipitation and NAO 20C3M

R= -0.907 ± 0.004 R= -0.89 ± 0.03

28/10/200819



Links between precipitation and NAO SRES A2

R= -0.979 ± 0.001 R= -0.84 ± 0.04

28/10/200820



Links between precipitation and NAO SRES A1B

R= -0.979 ± 0.001 R= -0.92 ± 0.02

Links between precipitation and NAO SRES B1

28/10/200821



R= -0.978 ± 0.001 R= -0.91 ± 0.02

Summary and Conclusions

Observed precipitation over the Iberian peninsula shows: a trend to decrease in DJFM opposite correlation with NAO

21 st century simulations indicate a decrease in precipitation with greater significance for strong CO2 forcing.

The links between precipitation and NAO will become more significant for 21 st century simulations with strong forcing of CO2.

Therefore, the rate to decrease of Iberian precipitation will accelerate under climate change conditions.

22

Acknowledments

To the AEMet and Institute of Meteorology and Geophysics of Portugal for precipitation data.

EU-FP6 project ENSEMBLES (http://www.ensembles-eu.org) and ECA&D (http://eac.knmi.nl .) for precipitation data.

To the modelling groups for the model data CMIP3 and PCMDI that archives and distributes the data.

To the NCEP/NCAR for the reanalysis data and the CPC for SLP and teleconnection indices.

This research is supported with National and Regional projects CGL2005-06600-CO3- 01/CLI, CGL2008-04619/CLI and CyL SA123A08.

To the software developers GrADS and CDAT

Thank you very much for your attention

precipitation variations over the iberian peninsula under climate change conditions c. rodríguez...

Documents