SPECSSeasonal-to-decadal climate

Prediction for the improvement of European Climate Services

F.J. Doblas-ReyesICREA and IC3, Barcelona,

Spain

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Progression from initial-value problems with weather forecasting at one end and multi-decadal to century projections as a forced boundary condition problem at the other, with climate prediction (sub-seasonal, seasonal and decadal) in the middle. Prediction involves initialization and systematic comparison with a simultaneous reference.

Meehl et al. (2009)

Climate time scales

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Seasonal predictions

DJF

T2m

JJA

T2m

JJA

Prec

DJF

Prec

Correlation of System 3 seasonal forecasts of temperature (top) and precipitation (bottom) wrt GHCN and GPCC over 1981-2005.

Only values significant with 80% conf. plotted.

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(Top) Near-surface temperature multi-model ensemble-mean correlation from CMIP5 decadal initialised predictions (1960-2005), five-year start date frequency; (bottom) correlation difference with

the uninitialised predictions of 2-5 year (left) and 6-9 year (right) wrt ERSST and GHCN.

Init ensemble-

mean correlationInit minus

NoInit ensemble-

mean correlation difference

Doblas-Reyes et al. (2013)

Decadal predictions

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Averaged precipitation over 10ºW-10ºE for 1982-2008 for GPCP (climatology) and ECMWF System 4 (systematic error) with start dates November (6-month lead time), February (3) and May (0).

GPCP climatology

ECMWF S4 - GPCP (MAY)ECMWF S4 - GPCP (FEB)ECMWF S4 - GPCP (NOV)

Systematic error: WAM

(NOV)

(FEB)(MAY

)

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Seasonal forecasts of November Niño3.4 ERSST (four-month lead) with a persistence-based statistical model, the ECMWF System 3 and CFSV2 forecast systems and the combination of the two.

Calibration/combination

Rodrigues et al. (2013)

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SPECS motivationWhat: to produce quasi-operational and actionable local climate information

Why: need information with improved forecast quality, a focus on extreme climate events and enhanced communication and services for RCOFs, NHMSs and a wide range of public and private stakeholders

How: with a new generation of reliable European climate forecast systems, including initialised ESMs, efficient regionalisation tools and combination methods, and an enhanced dissemination and communication protocol

Where: over land, focus on Europe, Africa, South America

When: seasonal-to-decadal time scales over the longest possible observational period

http://www.specs-fp7.eu

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SPECS objective

SPECS will deliver a new generation of European climate forecast systems, including initialised Earth System Models (ESMs) and efficient regionalisation tools to produce quasi-operational and actionable local climate information over land at seasonal-to-decadal time scales with improved forecast quality and a focus on extreme climate events, and provide an enhanced communication protocol and services to satisfy the climate information needs of a wide range of public and private stakeholders.

Substantial links to GEOSS for Climate

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Consortium

+ Brazil

20 partners, coordination IC3No. Participant organisation name Participant legal name Country

1 Institut Català de Ciències del Clima IC3 ES

2 Instituto Nacional de Pesquisas Espaciais INPE BR

3Max-Planck-Gesellschaft zur Förderung der Wissenschaften e.V. represented by Max-Planck-Institut für Meteorologie

MPG DE

4 Het Koninklijk Nederlands Meteorologisch Instituut KNMI NL

5 Atmospheric, Oceanic and Planetary Physics, University of Oxford UOXF UK

6 Météo-France MeteoF FR

7Centre Européen de Recherche et Formation Avancée en Calcul Scientifique

CERFACS FR

8 Norsk Institutt for Luftforskning NILU NO

9Agenzia Nazionale per le Nuove Tecnologie, l'Energia e lo Sviluppo Economico Sostenibile

ENEA IT

10 University of Leeds UNIVLeeds UK

11 University of Exeter UNEXE UK

12 Meteorologisk Institutt Met.no NO

13 Vortex VORTEX ES

14 Met Office METOFFICE UK

15 Sveriges Meteorologiska Och Hydrologiska Institut SMHI SE

16Institut Pierre et Simon Laplace, Centre National de la Recherche Scientifique

CNRS FR

17 University of Reading UREAD UK

18 Agencia Estatal Consejo Superior de Investigaciones Científicas CSIC ES

19 European Centre for Medium-Range Weather Forecasts ECMWF UK

20 Universität Hamburg UniHH DE

Long list of affiliated partners and stakeholders, among which GEO

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SPECS is part of ECOMS

European Climate Observations, Modelling and Services (ECOMS) initiative with these objectives:

ensure close coordination between projects and activities in Europe in the area of seasonal to decadal climate predictions towards climate services

provide thought leadership to the European Commission on future priorities in the area of seasonal to decadal climate predictions towards climate services.

Three EU projects are the core of ECOMS: EUPORIAS, NACLIM and SPECS, with a total funding of 26 Meuros.

All EU projects related to climate research and climate services are part of ECOMS.

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Overall strategy

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SPECS impact

SPECS and ECOMS bring together several communities: climate modelling, weather and climate forecasting, impact modelling, downscaling.

The main project deliverables are a set of public tools and data from the most ambitious coordinate seasonal-to-decadal global prediction experiments to this date.

Coordinated experimentsCore: impact of soil moisture and sea-ice initialization, increased resolution,

improved stratosphere and enhanced sample sizeTier 1: impact of snow initialization, interactive vegetation/phenology, sensitivity

to aerosol and solar irradiance.Central repository using revised CMIP5/CORDEX standards.

Large number of affiliated partners and stakeholders, including major international programmes.

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Future GLACE-3 SPECS could be the European contribution to the future GLACE-

3.

GLACE-3 will aim at assessing the impact of initializing soil moisture and snow.

Four-month long forecasts, 10-member ensembles, 1986-2012, start in November, February, May, June, July, August, ERA-Interim based forcings (WFDEI, WATCH), prescribed and fixed vegetation maps and biophysical properties.

Four experiments: CLIM: initialize with soil moisture and snow climatology. INI1: initialize with reanalysis of soil moisture and snow. PERFECTBOUNDARY: prescribe daily soil moisture and snow reanalysis. INI2: initialize with multi-model reanalysis of soil moisture and snow.

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CMIP5 decadal predictions

Decadal predictions (2-5 forecast years) from the CMIP5 multi-model (6 systems,

initialized solid, historical and RCP4.5 dashed) over 1960-2005 for global-

mean temperature, the Atlantic multi-decadal variability and the interdecadal Pacific oscillation. GISS and ERSST data

used as reference.

Doblas-Reyes et al. (2013) Forecast time (4-year averages)

Correlation of the ensemble-mean prediction as function of forecast time. Grey area for the 95% confidence level.

Root mean square error, where dots represent the forecast times for which

Init and NoInit are significantly different at 95% confidence level.

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Predictions of the recent hiatus

Guemas et al. (2013)

(Top) First three forecast years of the decadal predictions (five-member ensembles performed with the EC-Earth2.3 forecast system over 1960-2005 for global-mean sea surface temperature. The ensemble mean is plotted with a thicker dot.

(Bottom) Three historical simulations (extended with the RCP4.5 scenario) performed with EC-Earth2.3. The ensemble mean is plotted with a thicker line.

ERSST data used as reference in black.

Positive impact of the initialization.

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Seasonal predictions of 10-metre wind speed from ECMWF System 4 from the November 2010 start date, with the climatology computed from 1981-2010. Reference from ERA Interim.

Probability most likely tercile (%) DJF 2010

Very likely (>90%) Likely (>66%) About as likely as not (33-66%) Likely Very likely

Below Normal Normal Above Normal

Observed 10m wind speed (m/s) DJF 2010 Forecast 10m wind speed (m/s) DJF 2010

1.4

1.2

1.0

0.8

0.6

0.4

0.2

-0.2

-0.4

-0.6

-0.8

-1.0

-1.2

-1.4

2.0 1.8 1.6 1.4 1.2 1.00.8 0.6 0.4 0.2

-0.2 -0.4 -0.6 -0.8 -1.0 -1.2 -1.4 -1.6 -1.8-2.0

Climate information

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SPECS and GFCS

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SPECS links to GEO Direct link to task “CL-01 Climate Information for Adaptation”

through the use of the climate-observing component of GEOSS and the acceleration of the integration of climate products and services into adaptation processes.

“C3 Weather, Climate and Earth-System Prediction Systems” through the SPECS contributions to WWRP’s Subseasonal-to-Seasonal (S2S) and Polar Prediction Project (PPP), and in particular via the Year of Polar Prediction (YOPP), and the strong role played in the WCRP Working Group of Seasonal-to-Interannual Prediction (WGSIP) and the Polar Climate Predictability Initiative (PCPI). SPECS will play a central role in the design of CMIP6.

“C4 Easy Access to, and Use of, Climate Information” through the contribution to the Global Framework for Climate Services (GFCS) and the public dissemination of the SPECS products.