Scenari di cambiamento climatico in Italia e nel Mediterraneo SCENARI DI CAMBIAMENTO CLIMATICO IN...

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  • SCENARI DI CAMBIAMENTO CLIMATICO

    IN ITALIA E NEL MEDITERRANEO

    "Stato delle conoscenze riguardo ai cambiamenti climatici in Italia” Ministero dell'ambiente sala Europa, 27 Febbraio 2012, Roma

    Silvio Gualdi, CMCC

  • 2

    Who we are

    • An Italian research center on climate science and policy

    • A network of Italian public and private research institutions

    • Funded by the Italian Ministries MIUR, MATTM and MEF

    • Within the framework of the National Research Plan

    Partners:

    • INGV - National Institute on Geophisics and Vulcanology

    • UNISA - University of Salento

    • UNISANNIO - University of Sannio

    • CIRA - Italian Center for Spatial Research

    • FEEM - Enrico Mattei ENI Foundation

    • UV - University “Ca Foscari” of Venice

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    Associated Centers:

    • CNR - Consiglio Nazionale delle Ricerche - Dipartimento Terra Ambiente

    • University of Tuscia

    • IAMB - Istituto Agronomico Mediterraneo di Bari

    • CRMPA - Centro di Ricerca in Matematica Pura e Applicata

    • University of Sassari

    • Consorzio SPACI

    • OGS - Istituto Nazionale di Oceanografia e di Geofisica Sperimentale18

    Who we are

  • 4

    Network

  • 5

    Activities

    Numerical Numerical SimulationsSimulations

    Agricultural Agricultural Impacts:Impacts: ForestsForests

    Agricultural Agricultural Impacts:Impacts:

    CropsCrops

    Impacts:Impacts: Energy and Energy and

    EconomyEconomy

    Impacts:Impacts: HealthHealth

    Impacts:Impacts: Mediterranean Mediterranean

    SeaSea

    Numerical

    Methods Software

    Development

    Impacts:Impacts: The Coastal ZoneThe Coastal Zone

    Climate Research

  • 1. Previsioni Climatiche: scale (intra-)stagionali - multiannuali

    2. Proiezioni di Cambiamento Climatico: breve (decennali) e lungo (centennali) termine

    3. Info-Clima: interazione con gli stakeholders e utilizzatori

    4. Relazioni Istituzionali & Politiche di adattamento

    � Produzione di previsioni climatiche e proiezioni di cambiamento climatico e della comunicazione dei risultati e delle informazioni ottenute a diverse tipologie di utilizzatori (decisori e portatori d’interesse dall’industria, organismi politici pubblici e di pianificazione e infine scienziati e ricercatori di altre discipline)

    Divisione di Servizi Climatici (SERC)

    � Le previsioni climatiche e le proiezioni di cambiamento climatico sono basate sui modelli del CMCC, globali e regionali ad alta risoluzione.

    � Ricerca nell’ambito delle politiche di adattamento ai cambiamenti climatici e attività di supporto tecnico-scientifico alle istituzioni nei processi di negoziazioni multilaterali nel campo dei cambiamenti climatici (EU, IPCC, UNFCCC).

    4 Gruppi:

  • SERC Director S. Gualdi

    Climate Change Projections

    S. Gualdi

    Division Manager L. Amato

    Assistant I. Mazzocco M. Galisi

    Climate Predictions A. Bellucci

    Info-Climate A. Lanza

    P. Athanasiadis

    A. Borrelli

    S. Materia

    E. Banos A. Sanna S. Medri

    S. Venturini

    L. Reda

    E. Scoccimarro

    M. Zampieri

    F. Massari

    System and Numerical Support

    Institutional Relations & Adaptation Policies

    S. Castellari

    SERC Organization Chart

  • The CMCC Climate Model (CMIP5 configuration)

    Land Surface

    SILVA (Alessandri 2006)

    Atmosphere ECHAM5

    (from 200-to-80 km) (Roeckner et al 1996, 2003)

    Global Ocean

    OPA 8.2 (ORCA2) (Madec et al, 1998)

    Sea Ice LIM (ORCA2) (Timmerman et al, 2005)

    Coupler OASIS3

    (Valcke et al, 2000)

    Coupling Daily (or higher frequency) & no flux adjustment

    Marine Bio- Geochemistry

    PELAGOS Vichi et al. 2007

    Med Sea NEMO-MFS

    (~6.7 km) Oddo et al. (2009)

  • The CMCC Climate Model (CMIP5 configuration)

    Atmosphere ECHAM5

    (from 200-to-80 km) (Roeckner et al 1996, 2003)

    Global Ocean

    OPA 8.2 (ORCA2) (Madec et al, 1998)

    Coupler OASIS3

    (Valcke et al, 2000)

    Coupling Daily (or higher frequency) & no flux adjustment

    PHYSICAL CORE

    CMCC-CM

    Fogli et al. (2010) Scoccimarro et al. (2011)

  • The CMCC Climate Model (CMIP5 configuration)

    Land Surface

    SILVA (Alessandri 2006)

    Atmosphere ECHAM5

    (from 200-to-80 km) (Roeckner et al 1996, 2003)

    Global Ocean

    OPA 8.2 (ORCA2) (Madec et al, 1998)

    Sea Ice LIM (ORCA2) (Timmerman et al, 2005)

    Coupler OASIS3

    (Valcke et al, 2000)

    Coupling Daily (or higher frequency) & no flux adjustment

    Marine Bio- Geochemistry

    PELAGOS Vichi et al. 2007

    CARBON CYCLE

    CMCC-CESM

    Vichi et al. (2011)

  • The CMCC Climate Model (CMIP5 configuration)

    Atmosphere ECHAM5

    (from 200-to-80 km) (Roeckner et al 1996, 2003)

    Global Ocean

    OPA 8.2 (ORCA2) (Madec et al, 1998)

    Coupler OASIS3

    (Valcke et al, 2000)

    Coupling Daily (or higher frequency) & no flux adjustment

    Med Sea NEMO-MFS

    (~6.7 km) Oddo et al. (2009)

    FOCUS ON THE MEDITERRANE

    AN REGION

    CMCC-CMED

    Gualdi et al. (2011)

  • The CMCC Climate Model

    Land Surface

    SILVA (Alessandri 2006)

    Atmosphere ECHAM5

    (from 200-to-80 km) (Roeckner et al 1996, 2003)

    Global Ocean

    OPA 8.2 (ORCA2) (Madec et al, 1998)

    Sea Ice LIM (ORCA2) (Timmerman et al, 2005)

    Coupler OASIS3

    (Valcke et al, 2000)

    Coupling Daily (or higher frequency) & no flux adjustment

    Ocean initial conditions from spin-up or from CMCC analyses

    Atmospheric I.C. from AMIP-type

    runs or from Re- analyses (ERA)

    Initialization (off-line)

    Marine Bio- Geochemistry

    PELAGOS Vichi et al. 2007

    Med Sea NEMO-MFS

    (~6.7 km) Oddo et al. (2009)

  • Climate simulations: explore the mechanisms that drive the climate variability and climate change. Process oriented investigations on a wide range of spatial and temporal scales.

    Climate projections: assess the climate change signal according to prescribed scenarios of radiative forcing. Generally long simulations starting from spin-up initial conditions. Identification of long-term trends and of changes in the statistics of parameters of interest.

    Short-term projections: assess the climate variations due to both the internal variability and changes in the external forcings. Ensembles of short- term (~10-to-30 years) projections, but initialized with observed conditions (specific start date). Change in the statistics of parameters of interest.

    How do we use our climate model?

    Seasonal predictions: assess the climate variations mostly due to the internal variability of the climate system. 6-to-12 month simulations initialized with observed conditions (specific start date). Prediction of possible anomalous conditions in the “current statistics” (current climate).

  • 10 *(

    °C /d

    ec ad

    e) T2m trend 2001-2050 DJF

    T2m trend 2001-2050 JJA

    (m m

    /d ay

    )/ de

    ca de

    Prec trend 2001-2050 DJF

    Prec trend 2001-2050 JJA

    Deviation of the global mean surface temperature (wrt 1840-70 mean)

    T2m and Precipitation

    projected trends

    Future Climate Change Projections

  • 2000 20351960 1965 1970 1990 2005 …1985 203020101975 1980 1995 2015 2020

    30-year hindcast/forecast simulations grouped into 3-members ensembles, for different start dates

    • CMCC CGCM (ECHAM5+OPA/LIM) • CMIP5 GHG & aerosol RF • RCP4.5 scenario (2005 onward) • solar variability • ocean init.: from ODA products

    RCP4.5

    Short Term Projections (Decadal Predictions)

  • Short-term fluctuations due to both natural variability and anthropogenic radiative forcing

    Observ

    North Atlantic annual-mean SST

    Time series of SSTA in the North Atlantic [0-60N;50W-10W] Hindcast for 5-prediction years and Observations (5-year running mean)

    Some predictive skill is evident when 5-yrs slices out of each hindcast simulation are retained

    Short Term Projections (Decadal Predictions)

  • Downscaling

    LIMITED AREA MODEL: COSMO-CLM

    From Global

    To Local

    • Horizontal resolution: 14 km • Vertical resolution: 40 levels • Non-hydorstatic

  • Orography From Global

    To Local

    • Horizontal resolution: 8 km • Vertical resolution: 40 levels • Non-hydorstatic

    LIMITED AREA MODEL: COSMO-CLM

    Downscaling

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    From Global

    To Local

    • Horizontal resolution: 2.7 km • Vertical resolution: 40 levels • Non-hydorstatic

    LIMITED AREA MODEL: COSMO-CLM

    Downscaling

  • # Simulation CMCC-CESM Earth sys-model

    CMCC-CMS stratosphere

    CMCC-CM

    3.1 Pre-industrial control X X X 3.2 Historical (1850-2005) X X X 3.3 AMIP (1978-2008) X X 4.1 RCP4.5 (2006-2100) X 4.2 RCP8.5 (2