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EGU: 25Apr2012, Wed. Structural Interrelationships of the Evaporation-Precipitation Satellite-based Fields: Application of the Complex Networks By Irina Petrova 1,2* Alexander Löw 1 , Christian Klepp 1,2. 1 Max-Planck Institute for Meteorology, MPI, www.mpimet.mpg.de

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1 max planck institute for meteorology mpi mpimet mpg de

EGU: 25Apr2012, Wed

Structural Interrelationships of the Evaporation-Precipitation Satellite-based Fields: Application of the Complex NetworksBy Irina Petrova 1,2*Alexander Löw 1, Christian Klepp 1,2

1 Max-Planck Institute for Meteorology, MPI, www.mpimet.mpg.de

2 Meteorological Institute, KlimaCampus, University of Hamburg,

Hamburg, Germany

* [email protected]


1 max planck institute for meteorology mpi mpimet mpg de

Goals and Objectives:

  • Analyze topology of the single/ coupled precipitation

  • and evaporation networks

  • 2.Investigate the prominent global teleconnection patterns

    in the constructed networks

  • 3. Identify physical properties within the Climate Networks fields

2

d(2,3)

3

1

d(1,3)


1 max planck institute for meteorology mpi mpimet mpg de

Datasets and Experimental Setup:

Datasets used::

HOAPS: Hamburg Ocean Atmosphere Parameters and fluxes from Satellite data [http//:www.hoaps.org]

GPCC: The Global Precipitation Climatology Center [http//:www.gpcc.dwd.de]

HOAPS

(satellite, ocean)

1987-2005

HOAPS-3

(ocean)

GPCC

(gauge, land)

Evaporation

  • T63 (1.8)

  • Monthly

  • 1992-2005

  • 7968 vertices

Precipitation

  • T63 (1.8)

  • Monthly

  • 1992-2005

  • 13834 vertices

1


1 max planck institute for meteorology mpi mpimet mpg de

Datasets and Experimental Setup:

Datasets used::

HOAPS: Hamburg Ocean Atmosphere Parameters and fluxes from Satellite data [http//:www.hoaps.org]

GPCC: The Global Precipitation Climatology Center [http//:www.gpcc.dwd.de]

HOAPS

(satellite, ocean)

1987-2005

HOAPS-3

(ocean)

GPCC

(gauge, land)

Evaporation

  • T63 (1.8)

  • Monthly

  • 1992-2005

  • 7968 vertices

Precipitation

  • T63 (1.8)

  • Monthly

  • 1992-2005

  • 13834 vertices

1


1 max planck institute for meteorology mpi mpimet mpg de

CCN Construction:

Model used::

PYCLIMATENETWORK:[J.F Donges et al. 2009]

Single/ Coupled Evap-Precip Networks:

  • Similarity Criteria:

  • - Pearson correlation (zero lag)

  • - Spearman rank (zero lag)

  • Threshold: 99,9% significance level (t-test)


1 max planck institute for meteorology mpi mpimet mpg de

Teleconnection Patterns: ENSO

Degree Centrality field of the Precipitation Network

Source - point

Correlation values of the ICTZ location neighbours

within the Precipitation Network


1 max planck institute for meteorology mpi mpimet mpg de

Teleconnection Patterns: NAO+ and NAO-

Degree centrality of the precipitation network [Dec-Mar]Thrsh=0.43

Correlation of monthly mean Dec-Mar precipitation with the station-based NAO index [Andersson et al. 2010]


1 max planck institute for meteorology mpi mpimet mpg de

Teleconnection Patterns: NAO+ and NAO-

Positive Correlations within the precipitation network [Dec-Mar]

of the neighbours at two locations: Bergen (Norway) and Gibraltar

Correlation of monthly mean Dec-Mar precipitation with the station-based NAO index [Andersson et al. 2010]


1 max planck institute for meteorology mpi mpimet mpg de

Coupled EVAP-PRECIP Fields:

Evaporation

Precipitation

1

Cross Degree Centralities of coupled

Precipitation-Evaporation Networks (thresh. = 0,25)


1 max planck institute for meteorology mpi mpimet mpg de

Downstream Source Feature:

Precipitation field: Receiver - point

1

Correlation Values of the Precipitation Neighbours Within the Evaporation Field

and Cross-Degree Centrality (background filed) (Thrsh=0,25)


1 max planck institute for meteorology mpi mpimet mpg de

Outlook: Conclusions and Expectations

  • 1. Evap-Precip Network structure resembles major teleconnection patterns

  • 2. High DC coupled evap-precip fields reveal spatial source-receptor feature

  • 3. Statistical analysis operation V.S. CCN physical features

  • (Surrogate data, Transfer Entropy)

  • 4. Comparison/ validation of the CMIP5 ESM-MPI using HOAPS dataset

2

d(2,3)

3

1

d(1,3)


1 max planck institute for meteorology mpi mpimet mpg de

Acknowledgements:

The author is grateful for the fruitful collaboration, information and PYCLIMATENETWORK software support to the Potsdam Institute for Climate Research(PIK), and especially to Jonathan Donges and Norbert Marwan

The author is also thankful to the HOAPS group at MPI-M, UniHH and DWD for the provided HOAPS - GPCC datasets.


1 max planck institute for meteorology mpi mpimet mpg de

THANK YOU

[email protected]


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