Evaluation and diagnosis of General Circulation Climate Models (GCMs)

Iñigo Errasti Arrieta inigo.errasti@ehu.es

EOLO Research Group

on Meteorology, Climate and Environment

www.ehu.es/eolo/index.html

Dept. Nuclear Engineering and Fluid Mechanics University College of Engineering, Gasteiz University of the Basque Country (EHU/UPV)

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OUTLINE

0. EOLO research group

1. General Circulation Models (GCMs)

2. IPCC Assessment Reports on climate change

3. AR4 model validation over the Iberian Peninsula

4. Other AR4 model validation studies

EOLO RESEARCH GROUP0

Included into the Department of Applied Physics II (Faculty of Science and Tecnology and Engineering Colleges, UPV/EHU).

Staff:

Areas of interest:

• Javier Díaz de Argandoña • Agustín Ezcurra • Gabriel Ibarra-Berastegi • Jon Sáenz • Juan A. Zubillaga • Isabel Herrero • Iñigo Errasti Arrieta

- Analysis of climate variability - Simulation of past and present regional climates - Operational numerical weather prediction - Future climate simulations - Validation of General Circulation Models (GCMs)

Website: www.ehu.es/eolo/index.html 3

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GENERAL CIRCULATION MODELS (GCMs) 1

MOST ADVANCED TOOLS available for simulating the response of the global climate system to increasing GHG concentrations

• Numerical 3D Models

• Global Climate Models

• Represent the physical processes in the atmosphere, ocean, cryosphere and land surface. They depict the main features of the atmospheric and oceanic circulation

• Simpler models have also been used to provide globally- or regionally-averaged estimates of the climate response, but …

• Only GCMs have the potential to provide geographically and physically consistent estimates of regional climate change

• GCMs depict the climate using a three dimensional grid with a horizontal resolution of between 100 and 200 km, 30 to 40 vertical layers in the atmosphere and up to 45 layers in the oceans

GENERAL CIRCULATION MODELS (GCMs) 1

CLIMATE SUBSYSTEMS / INTERACTIONS / PROCESSES IN GCMs

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• The complexity of GCMs has increased over the last few decades

• Additional physics incorporated in the models and increasing space resolution

- A fully GCM takes about 25-30 years to code !! - High performance computers (HPCs) - Processing in paralel (cluster of computers to

solve the equations at each grid point)

1990

1996

2001

2007

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GENERAL CIRCULATION MODELS (GCMs) 1

The behaviour of the atmosphere is governed by a set of physical laws

• Equations can’t be solved analytically => numerical methods • Knowledge of initial conditions of system necessary • Interactions between atmosphere and ocean important => COUPLING

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24 IPCC AR4 CGM MODELS (WCRP CMIP3) 1

IPCC ASSESSMENT REPORTS ON CLIMATE CHANGE 2

Shared Nobel peace award 2007

• Large number of scientists to assess the research on climate change performed throughout the world.

• Organized in three Working Groups (WGI, WGII, WGIII)

• So far, four reports:

TAR WGI:- FAR: First Assessment Report (1990) - SAR: Second Assessment Report (1996) - ~ 1000 Lead authors - TAR: Third Assessment Report (2001) - 515 contributing authors - AR4: Fourth Assessment Report (2007) - 420 reviewers

- 21 review editors

AR4 WGI: The Physical Science Basis of Climate Change: Chapter 8. Climate models and their evaluation

and to come…

- AR5: Fifth Assessment Report (2014)

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IPCC ASSESSMENT REPORT #4 ON CLIMATE CHANGE2

(*) Anomalies relative to the 1901-1950 averaged temperatures

AR4 20C3M SIMULATION: uses preindustrial initial conditions and is forced with historical GHGs from the 20th century. CO2 concentrations change from 286 to 367 ppm.

AR4 VALIDATION OVER THE IBERIAN PENINSULA3

Analysis of the ability of 24 AR4 GCMs to simulate the observed seasonal cycle of mean monthly sea level pressure (SLP), surface air temperature (TAS) and precipitation (PR) over the Iberian Peninsula in late XX

z Firstly, a comparison between observed and modelled SLP, SAT and PR data at each Iberian grid point is computed.

- Seasonal cycles

- Probability density functions (PDFs)

z Secondly, we proceed to establish a ranking of model performance.

DATASETS: ERA40 (observations) AR4 (simulations)

ASSUMPTION: A model that accurately describes the present climate is more likely to make a better projection of future climate than a model which

Iberia covered by 30 points (2.5º x 2.5º grid).

reproduces today’s climate over a particular region less accurately 10

AR4 VALIDATION OVER THE IBERIAN PENINSULA3

Example 1. a) Observed (ERA40) and simulated (MIROC3.2-HIRES) SLP seasonal cycles at one Iberian grid point. b) ERA40 and GISS-AOM SLP seasonal cycles at another Iberian grid point.

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AR4 VALIDATION OVER THE IBERIAN PENINSULA3

Example 2. a) IAP-FGOALS seasonal cycle is inadequate in comparison with observed ERA40 seasonal cycle. b) However, the modeled IAP-FGOALS PDF fits better the ERA40 PDF.

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AR4 VALIDATION OVER THE IBERIAN PENINSULA3

Roor mean square error (rms) on seasonal cycles

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AR4 VALIDATION OVER THE IBERIAN PENINSULA3

Skill score (s) on PDFs (Maxino et al, 2007)

AR4 VALIDATION OVER THE IBERIAN PENINSULA3

MODEL RANKING. Obtention of a global rank index

Data management and statistical tools based on OpenSource code running on LINUX platforms ( cdo, python, pyclimate, R, GRADS, gnuplot, GMT, … )

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Analysis of the ability of 22 AR4 GCMs to simulate the observed seasonal cycle and anomalies of mean monthly sea level pressure (SLP) over the Northern Atlantic in late XX

OTHER AR4 MODEL VALIDATION STUDIES 4.1

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OTHER AR4 MODEL VALIDATION STUDIES 4.2

Ability of 7 AR4 models to simulate current daily Zonally Averaged Surface Air Temperature (ZASAT) meridional profiles from 1961 to 1998

In EBMs, the mean surface temperature T can be derived from the energy balance:

x=1

Heating forcing

x=0

-1 < x < 1 x =sin ( )φ

Transport term parameterized

ZASAT expanded in Legendre series

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ZASAT(x)= c P ( )∑ n n x n=0

SOME PEER-REVIEWED PUBLICATIONS5

• Errasti I., Ezcurra A., Sáenz J., Ibarra-Berastegi G. and Zorita E. (2013). Comparison of the main characteristics of the daily zonally averaged surface air temperature as represented by reanalysis and seven CMIP3 models. Theoretical and Applied Climatology. DOI: 10.1007/s00704-013-0842-z.

• Errasti I., Ezcurra A., Sáenz J. and Ibarra-Berastegi G. (2011) Validation of IPCC AR4 models over the Iberian peninsula. Theoretical and Applied Climatology. 103, 1-2, 61-79.

• Ibarra-Berastegi G., Sáenz J., Ezcurra A., Elías A., Diaz Argandoña J., Errasti I. (2011). Downscaling of surface moisture flux and precipitation in the Ebro valley (Spain) using analogues followed by random forests and multiple linear regression. Hydrology and Earth System Science. 15, 1895-1907.

• Ibarra-Berastegi G., Sáenz J., Ezcurra A., Ganzedo U., Díaz de Argandoña J., Errasti I., Fernández-Ferrero A., Polanco-Martínez J. (2009). Assessing spatial variability of SO2 field as detected by an air quality network using self-organizing maps, cluster, and principal component analysis. Atmospheric Environment. 43, 3829-3836.

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THE END6

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