WP6 :  Coupled basin-wide processes determining the 

climatology

Duration : 48 months          Start date: 1/11/2013                                                     End date : 30/10/2017

Leader

WP6 : Coupled basin-wide processes determining the climatology

Main Objective: Reducing systematic errors in the simulation of Tropical Atlantic

Climate in atmosphere-ocean models.

Sub-objectives:1. Evaluate the systematic biases in existing models/simulations and formulate

hypothesis regarding the likely mechanisms responsible for such biases.2. Perform and analyse coordinated sensitivity experiments with

partial/regional flux corrections.3. Targeted model-specific sensitivity experiments to discriminate causes of

biases development4. Design model modifications and assess their impact on mean biases

WP6 : Coupled basin-wide processes determining the climatology

To achieve these objectives the work is split in 4 tasks:

Task 6.1: Analysis of forecast to investigate the causes of systematic model error[CERFACS, IC3, MF-CNRM, UiB, UniRes]

Task 6.2:  Coordinated sensitivity studies to identify possible causes of model systemantic error and their robustness across models[CERFACS, MF-CNRM, UiB, UniRes, UPMC, UREAD, WU]

Task 6.3:  Further diagnostic sensitivity studies to pinpoint model deficiencies leading to systematic biases[CERFACS, GEOMAR, MF-CNRM, UCAD, UiB, UniRes, UPMC, UREAD, WU]

Task 6.4:  Towards improved models: sensitivity studies involving specific model formulation, configurations and parameterisations[MF-CNRM, UiB, UniRes, UCAD, UPMC, UCPH, UREAD, WU]

M20

WP6:  Coupled basin-wide processes determining the climatologyTasks                                                                                                   Deliverables and Milestones  

M20: workshop on diagnostics and analysis strategies for bias development (m1, report) [CERFACS]

Task 6.1: Analysis of forecast to investigate the causes of systematic model error[CERFACS, IC3, MF-CNRM, UiB, UniRes]

D6.1

M21

M22

M21: Workshop on results of bias analysis and on design of coordinated experiments (m12, common with WP7)[UniRes]

D6.1: Common bias development phenomenology (m24, Report) [MF-CNRM]

M22: Common experiments performed (task 6.2) and made available to CT3 and WP11 (m30, data)[GEOMAR]

Task 6.2:  Coordinated sensitivity studies to identify robustness of various causes of model systemantic error[CERFACS, MF-CNRM, UiB, UniRes, UPMC, UREAD, WU]

M20

WP6:  Coupled basin-wide processes determining the climatologyTasks                                                                                                   Deliverables and Milestones  

D6.2: Common diagnostic experiments and proposed model development sensitivity studies (m36, Report) [UniRes]

Task 6.3: Further diagnostic sensitivity studies to understand causes of model systematic error[CERFACS, GEOMAR, MF-CNRM, UCAD, UiB, UniRes, UPMC, UREAD, WU]

D6.1

M21

M22

M23

Y1

Y2

Y3

Y4 D6.3

D6.2

Task 6.4:  Towards improved models: sensitivity studies involving specific model formulation, configurations and parameterisations[MF-CNRM, UiB, UniRes, UCAD, UPMC, UCPH, UREAD, WU]

M23: Short description of experiments under task 6.3 and first results (m42, report) [UCPH]

D6.3: Report on best practices for the simulation TA climate, including improved understanding of key processes (m48, Report, common with WP7-WP8-WP9)[WU]

Upcoming M&Ds for the first two years:M20 (30/11/2013)  Meeting to discuss diagnostics and analysis strategies (next Wednesday)M21 (30/10/2014)  Workshop to decide the design of common experiments for WP6D6.1 (30/10/2015)  Common bias development phenomenologyM24 (30/10/2015)  Meeting to discuss on experiments for tasks 7.2

WORK for the first two years:

1st year : Analysis of existing s2d experiments for bias development 2nd year : Coordinated sensitivity experiments and model specific sensitivity studies  

Partners objectives for the next 2 years

UiB + UniResN. Keenlyside, T. Toniazzo, +2PDRAs +1PhD

Task 6.1 (6PM in 2014): Analysis of bias development within the tropical Atlantic as function of season and lead time in existing s2d integrations (Sys-4, GloSea5, EC-Earth) & comparison with previous results from some CMIP5 integrations. Regression analysis to estimate feedbacks between SSTs and winds, surface fluxes and precipitation (including land).

Task 6.2 (3PM in 2014): s2d integrations with NorESM-LTask 6.2 (3PM in 2014): coordinated sensitivity experiments with NorESM-L

Task 6.3 (4PM in 2015): hypothesis-driven sensitivity studies on systematic model drift at short (~12-18 month) lead-time with NorESM-L Task 6.4 (2PM in 2015): modified parametrisation, resolution and configuration tests with NorESM-L (← EPOCASA); parameter estimation using EnKF. Comparison with SUper MOdelling results.

2013: M20: workshop on Wednesday!!2014: M30: contributing to shared data-base diagnostics from existing s2d experiments2014: M21: joint WP6-7 workshop on bias-development mechanisms (coordinator)2015: M24: contributing to joint WP6-7 workshop on bias-correction experiments2016: M22: contributing to data-base of new experiments2016: M23: contributing to description of sensitivity experiments2016: M28: participating in TAV meeting

D6.1 (month 24, MF-CNRM): assessment on bias development in s2d integrations

Near Inertial Waves (Task 6.4)

NIWs are poorly reproduced by GCMs & poorly observed, but they affect the position of the ITCZ (next slide). We will do the following:

- assess their strength and their dependency on wind in the Atlantic Mooring array and in NorESM (WP3,5; D3.3; MS17-19)- with Mats Bentsen we will parameterize NIWs in NorESM (slide 3) and assess their impact on climate (WP6; D6.1-3, M21 ???)- with Thomas Toniazzo we will then use NorESM to quantify the impact on predictability (WP11; D11.1-2, MS35,36)

UCPHM. Jochum & PhD student

Task 6.1 Analysis of bias development on existing simulations

a) Seasonal forecasts performed with the CERFACS-HR model (existing)(comparison to the low resolution version of the model together with MF-CNRM)

- Model: ARPEGE v5.3(T359 ~50km) + NEMO 3.4 (ORCA025) + climatological sea ice- Initial conditions: GLORYS ocean reanalysis (Ferry et al. 2010)- Start dates: 1st May and 1st November every year within 1993-2009 period- 3 members for 7 months, daily-frequency diagnostic

- Decadal forecasts performed with the CERFACS-HR model (existing at the end of 2014)- Model and i.c.: same as above, except for LIM2 sea ice- 1st November only (1993-2009), 3 members, daily diagnostics

Task 6.2 Coordinated sensitivity studies

- Development on the technical framework for PREFACE: Implementation of flux correction and nudging techniques (tests) on CERFACS-HR model.

- Participation to the coordinated experiments proposed in task 6.2

CerfacsE. Sanchez-Gomez

Task 6.1 Analysis of bias development on existing simulationsa) Seasonal forecasts performed with the CERFACS-HR model

Start on 1st May Start on 1st November

Monthly SST differences from GLORYS climatology drift as a function of the forecast range. Grey hatching indicates where the value of the anomaly is above the inter-members standard deviation (3 members).

MF-CNRMA. Voldoire, R. Roehrig, Post-Doc

Home model : CNRM-CM LR = atm 1.5° / ocean 1°

Characterize the drift of CNRM-CM on existing seasonal forecast experiments (done for SPECS)

Dependency of the drift according to the start date (season)

Comparison with results obtained on decadal experiments (Voldoire et al.)

Comparison of the systematic biases in the LR/HR versions of the model (in collab with Cerfacs)

Sensitivity to model components

ocean vertical resolution

new atmospheric physics

Sensitivity tests

To convective heating on continents

Coordinated sensitivity tests

Post-Doc position opened on this WP

UPMC - OCATA : regional coupled platform

- NEMO ATLTROP : 0.25°, L75, with 2-way nesting AGRIF zoom.

- WRF : ~0.22°

(Both models ready to run ; coupling to be developed.)

Task 6.4 : ~5 months experiments (MAMJJ) for :- testing the impact of PBL and surface layer parameterisations on the atmospheric response to SST and SST gradients (WRF-forced mode),- testing the impact of surface wind drift on the different terms of ocean surface heat budget (NEMO-forced and coupled mode).

Task 6.2: participating to the common experiments of sensitivity studies + analysis =regionalised nudging / relaxation and decoupling to surface fields in short experiments, regional decoupling + restoring atmospheric winds, etc.

Task 6.3 (~9 months experiments) : studying the impact of NEMO 1° => NEMO 0.25° on the bias development

UPMCG. DeCoëtlogon, F. Hourdin, C. Rio

2014-2015

IPSL-CM5 : global coupled model with 4 different possible configurationsEach has the possibility to switch model physics : IPSL-CM5a (old) or IPSL-CM5b (new).

1° ocean (NEMO L30), 1° atmosphere (LMDZ)

0.25° ocean (NEMO L75), 1° atmosphere (LMDZ)

will be ready soon (Jan. 2014)

With no Zoom :

With a zoom in the atmosphere : (=> 0.3°)

(Similar to this one, but in the Trop. Atl. ! i.e. 60°W-40°E / 30°S-30°N)

To be developed.

To be developed.

To be developed.

UPMCG. DeCoëtlogon, F. Hourdin, C. Rio

GEOMARM. Latif, R. J. Greatbatch, and J. Harlass

22

Focus on mitigating the warm bias in coupled models in the southeastern Atlantic.

Problems in both the atmospheric and oceanic components.

Questions: (i) investigate the bias in an atmosphere model (ECHAM5) with specified (observed?) SST.

(ii) investigate the bias in

the KCM using correction

techniques, e.g. flux correction,

the semi-prognostic/pressure

correction method in the

ocean component.

CMIP5 multi-model mean SST bias

Task 6.2: Coordinated runs to identify robustness of causes for model biasTaking part in the common set of 4 experiments with EC-EARTH to investigate model bias. Short (<9 months) initialized ensemble runs in hindcast mode• Full coupling TA, SST forcing outside• Total flux correction TA• Momentum flux correction TA• solar heat flux correction TA

Task 6.3: Understanding causes of model biasesUsing flux correction simulations in climate mode to investigate the link between bias reduction and TA internal variability.

Task 6.4: Towards improved modelsImplementing and testing new parameterizations in EC-EARTH using seasonal hindcasts. • Marine atmospheric planetary boundary layer• Ocean mixed layer (TKE scheme) including surface-wave effects (Langmuir circulation).

WU In Collab.with KNMI, R. Haarsma

Model EC-EARTH V3 (atm. T255; ocean 1 degr.)

IC3I. Andreu-Burillo, F. Doblas-Reyes

IC3 contributes to

Task 6.1 Analysis of forecast to investigate the causes of systematic model error (UiB, UniRes, MF-CNRM, CERFACS, IC3), e.g. the impact of oceanic horizontal or vertical resolution on initial drift will be assessed from model integrations with varying configuration.

D6.1: Assessment of bias development in s2d integrations: Report on the results for the initial model drift in existing s2d experiments, in terms of seasonality, timing and pattern. This synthesis will also take into account results from SPECS on processes acting in the Pacific [month 24].

D6.3: Report on best practices for simulating TAV: This report will summarize key results obtained from WP5, WP6, WP7, WP8 and WP9 concerning modelling of tropical Atlantic variability (TAV) on s2d time-scales [month 48].

Milestones: MS20 (Agreement on common methodology for initial drift analysis, month 1) and MS24 (Model bias-correction methods, month 24).

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)

(NOV)

(FEB)(MAY

)

Doblas-Reyes et al. (2013)

WAM systematic error

Mean SST bias for JJA (May start date) over 1993-2009 with respect to ERA-Interim for System4, EC-Earth3 T255L91-ORCA1L46 and

T511L91-ORCA025L75.

Mean bias: seasonal forecasts

EC-Earth3 T255-ORCA1

EC-Earth3 T511-ORCA025

System4

UREADJ. Shonk, S. Woolnough (9PM)

(coordinated with similar activities in SPECS)

1) Analysis of evolution of systematic biases in UKMO and ECMWF seasonal forecasting systems (6.1) (2months over next year)

2) Contribute integrations with UKMO seasonal forecasting system to coordinated sensitivity studies (6.2) (3 months in Year 2)

3) Targeted sensitivity studies focused on UKMO system (6.3) (4 months in Year 3)

– perform experiments with regional de-coupling or fluxe/stress correction focused on possible sources of biases specific to UKMO system