CMEMS regional reanalyses - Copernicus Climate … · Copernicus Marine Environnement Monitoring Service (CMEMS) regional reanalyses 19/05/2016 C3S Regional Reanalysis Workshop, Reading

Copernicus Marine Environnement

Monitoring Service (CMEMS)

regional reanalyses

19/05/2016 C3S Regional Reanalysis Workshop, Reading 1

Jonathan Beuvier, Marie Drévillon, Karina von Schuckmann,

Gilles Garric, Yann Drillet, Pierre-Yves Le Traon

Mercator Océan, Ramonville Saint-Agne, France

OUTLINE

2

• CMEMS organisation

• CMEMS Multi-Year Products (MYP)

• Ocean State Report (OSR), Ocean Monitoring Indices (OMI)

• Data reprocessing, a pre-requisite input for reanalyses

• Status of regional reanalyses in CMEMS

• Requirements for regional reanalyses forcings

• Mercator Océan reanalyses

• Atmospheric forcings correction method for global reanalyses

• MEDRYS, a Mediterranean Sea regional reanalysis

19/05/2016 2C3S Regional Reanalysis Workshop

Cliquez et modifiez le titre

CMEMS technical « internal » Framework:

building blocks

Figure 1: System overview of Copernicus Marine Environment monitoring service chain as presented by the

European Commission to the GMES/Copernicus User Forum.

From the Technical Annex of the Delegation Agreement between the EU and Mercator Ocean

319/05/2016 C3S Regional Reanalysis Workshop

CMEMS Multi-Year Products (MYP):

CONTINUITY

AIM:

• Maintain MYP time series close to real time 1 year before RT

(long term goal: few month before RT)

MOTIVATION:

• Guarantee for user delivery state-of-the-art operational MYP

products and services

• Develop a robust basis for annual ocean state reporting

CHALLENGE:

• Operational production of MYP close to RT


CMEMS MYP: Ocean monitoring

and reporting: 2 fundamental toolsCMEMS Ocean State Report (OSR)

CMEMS Ocean Monitoring Indicators (OMIs)

Operational time series which allow a regular

monitoring of the ocean state, variability and change at

global and European scale from 1992 up to RT,

together with a quality description and scientific context


CMEMS MYPConsistency DM/NRT, but not a

priori optimized for climate

applications

Climate MYPClimate quality (consistency and

homogeneity), but cannot answer

operational MYP requirements

1 2

PRIORITIES for OCEAN MONITORING INDICATORS

CMEMS OMI* from MYP

Climate quality & state-of-the-art

merge these two

philosophies on the long-term

*OMI: Ocean Monitoring Indicator

&1 2

CMEMS MYP: Ocean monitoring

and reporting



• In situ T(z), S(z) mainly for data assimilation (but also velocity

from drifters, elevations from tide gauges etc…)

• Sea level anomalies from satellite altimetry

• SST

• Sea ice concentration, drift, thickness

• Winds

Reprocessing of observations done by CMEMS TACs:

a pre-requisite


IN SITU reprocessing : main input for

3D ocean data assimilation

1950 1970 1990 2010

___ XBT V1 V2___ MBT___ CTD___ Profilers___ ondulating CTD and Sea Mammals___ others

including EN4 and NATO declassified observations


Ocean basins in situ sampling

rates

Ocean reanalysis in the Southern oceans is still a challenge



Altimetry: important input for ocean RANUse of all the altimeter missions available from end 1992, up to now: 10 altimeter missions (+2 futures) ~75

cumulative years of altimeter measurements to process



CMEMS regional ocean RANs statusMFC (productioncenter)

Model (horresolution)

Data assimilation

Period currentlycovered

Surface forcing (horresolution)

Rivers IC/BC

ARC (NERSC) HYCOM V2.2.12 DeterministicEnKFSST, T(z), S(z), Atlimetry, Iceconcentration

1991-2014 ERA interim (~80km, 6h / 3h for SW)

Monthlyclim

clim

BAL (SMHI)(2017)

NEMO V3.6 (~3.7 km)

3DEnVARSST, T(z), S(z), icecharts

1992-2014 EURO4M (~22km, 6h) EHYPE GLO RAN/clim

IBI (MO/PdE)

NEMO V2.3 (~9km) SEEK SAM2V2 + 3DVAR biascorrectionSST, T(z), S(z), Atlimetry

2002-2014 ERA interim (~80km, 3h) Ifremer + EHYPE

GLO RAN

MED (INGV) NEMO V3.4 OceanVAR3DVARSST, T(z), S(z), Atlimetry

1987-20141955-2014

ERA interim (~80km, 6h)AMIP (~130km, 12h)

Monthlyclim

Clim/GLO RT

NWS (UKMO)

NEMO FOAM AMM7 V1 (~7 km)

NEMOVAR 3DVARSST

1985-2014 ERA interim (~80km, 3h) EHYPE Clim/GLO RAN (UKMO) and BAL IOW GETM

GLO (MO) NEMO V3.1 (~25 km) SEEK + 3DVAR bias correctionSST, T(z), S(z), Atlimetry, Iceconcentration

1992-2014 ERA interim (~80km, 3h) Monthlyclim

Clim


• All have biogeochemistry component, MED MFC is the most

advanced in BGC data assimilative RAN

• Ensembles of RAN -> NWS MFC, GLO MFC

Good to know


Status of multi year products MED

NEMO3.4

Data assimilationOCEANVAR

OGSTM-BFM4.0

Data assimilation3DVAR

Assimilated variable: chlaOC_L3_REP_OBS_009_073

Forcing and boundaries:- ECMWF ERAinterim/AMIP- Climatological river runoff- ERAInterim

precipitation/CMAP precipitation

- Atlantic BCs from PSY3 global model

Assimilated variables: T, S, SLASLA_L3_REP_OBS_008_020 [008_19], MEDATLAS, SEADATANET, INSITU_OBS_013_035 (Argo-XBT-CTD)

Forcing and boundaries- Climatological river discharges- Atlantic BCs from MEDATLAS- Atm forcing from literature

CMEMS products

CMEMS-MED-MFC V2 reanalysis: model setup and products

PHYS BIO

1955

1960

1970

1980

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

REAN-PHYS-006-004

REAN-PHYS-006-009

REAN-BIO-006-008

Satellite SST (surface flux nudging):GOS-CNR-SST-HR-RAN/DT-MEDITERRANEAN –SST_MED_SST_L4_NRT_OBSERVATIONS_010_004_a/HadSST1

Multi Model Ensemble –Multi Year ProductCourtesy of I. Golbeck BSH

MME MYP – single MYPsspatial coverage

IBIRYSV1: will provide a larger domain

We need at least 3 MYP in the same area.

MME - MYP

• SST mean standarddeviation for 2011


Spatial resolution

~20 km

Time resolution

hourly if possible

Parameter list:

most make use of CORE BULK: if flux formulation used:

2-m air temp total, solar and non-solar heat flux (accumulated)

2-m specific humidity SST used to compute the heat fluxes

10-m wind components (u and V) wind stress components (tauU and tauV)

air pressure at sea level air pressure at sea level

total cloudiness water flux components (evaporation, precipitation, snow)

downward shortwave radiation (accumulated)

downward longwave radiation (accumulated) need of fluxes as balanced as possible (especially for semi-

total precipitation (accumulated) enclosed basins)

snow precipitation (accumulated)

Provide uncertainty estimates -> sensitivity studies, ensembles

For winds: can be estimated with CMEMS OSI TAC

Double penalty effects with high resolution?

Ensemble atsmopheric reanalyses to build ensemble oceanic reanalyses and multi-model ensembles

River runoff data:

need of long-term datasets to be used instead of climatologies

General requirements for atmospheric forcing

for regional oceanic RAN

Also true for future GLO 1/12° RAN!


SSS

model – Levitus98 climatologyRainfalls ERAInterim – PMWC

(2002-2006)

SST spatial errors structures

SST (2002)model – RTG

Downward SW Flux 2002 ERAinterim - GEWEX

SSS spatial errors structures

Devpt method to correct SW, LW & Precipitations Large Scale ERA-Interim Fluxes with GEWEX SRB and PMWC

Forcings corrections: background


ERAI : monthly mean

Climatology

Satellite: monthly

mean Climatology

Climatology of

corrective factor

Daily ERAI field:

large scalex

Daily ERAI: small

scale

Daily Corrected ERAI

large scale+

Daily Corrected ERAI field

The correction is local (i,j).

Large scales correction only.

Gewex SRB climatology (1999-2007) for SW & LW

fluxes.

PMWC Climatology (1992-2006) for rainfalls fluxes.

No correction at high latitudes (> 65N and < 60S)

No correction for climatology < 1W.m-2

or <50mm/yr (hyper arid climate).

• No change of interannual signal.

• No change of synoptic patterns

(cyclones).

• The method can be applied outside

the satellite period.

Method of forcings correction


The example of the MEDRYS reanalysis

More « climate-oriented » regional reanalysis :

• use of dedicated tools (numerical model, forcings, data assimilation

system settings) for the Mediterranean Sea

• to have the more consistent and the more interannual as possible

lateral forcings (Atlantic boundary conditions, atmospheric forcings,

river runoffs) with the same characteristics all along the simulated

period

• configurations closed to Regional Climate System Models (RCSM)

• Work done in the frame of the MISTRALS (Mediterranean

Integrated STudies at Regional And Local Scales) and Med-

CORDEX (Mediterranean contribution to the Coordinated

Regional Climate Downscaling Experiment) international

programs.


Regional oceanic configuration:

NEMO-MED12 model

20

• NEMO v3.1 code (Mercator oper

version at Météo-France HPC)

• Horizontal grid from ORCA12 at

6-8 km < Rossby deformation

radius ~10-15 km

(eq. to a 1/14°-1/18° regular grid)

• Z vertical grid with 75 levels (1m

to 135m thickness)

• New high resolution bathymetry

(MERCATOR-LEGOS v10

product at 1/120° resolution)

• Closed boundary at 11°W

-11 -7.5

-6

Atlantic buffer zone :

Newtonian dampings to ORAS4 monthly anomalies

with following time scales τ :

and S (3D) : τ between 2 days -> 90 days

SSH : τ between 1.7 second -> 90 days

Bathymetry (m)


Atmospheric forcings, initial and

boundary conditions

21

• Free simulation starting in October 1979 from Medatlas-1979 (Rixen et al., 2005) in

the Mediterranean side and from WOA05 (Levitus et al., 2005) in the Atlantic side.

The reanalysis starts from the state of the free run on the 30th September 1992

(beginning of the altimetry era).

33 main rivers + Black Sea (interannual datasets from Ludwig et al., 2009 and Stanev &

Peneva, 2002): freshwater added as precipitation at mouth points + coastal runoff

(residual land-surface freshwater budget).

• 12-km and 3h-atmospheric fluxes from ALDERA

(CNRM), dynamical downscaling of the ERA-Interim

reanalysis with ALADIN-Climate (Herrmann et al. 2011).

SST retroaction for the free run (Barnier et al. 1995),

coefficient of -40 W/m²/K (CLIPPER Project 1999).

The total heat flux of the free run is used for the

reanalysis (including the retroaction term).

No SSS damping, 2D water flux correction in the water flux.

Topography of ALADIN-Climate


Regional oceanic reanalyses MEDRYS1

22

Ocean model:

NEMOMED12v75 model, ALDERA forcing

Observations:

In-situ (Coriolis CORA4.0/CORA4.1 database) and satellite

data (SST AVHRR-AMSR and SLA from SALTO/DUACS)

Data assimilation scheme(Lellouche et al., 2013)

3DVAR correction

at large space- and time-scale

multivariate multidata

SEEK filter algorithm

+ Tbias(k)

Control Space

SSH

T(k)

S(k)

Modal Space(Reduced Space)

3D modesacting on 3D space

SEEKAnalysis

U(k)

V(k)

+ SSHbias

+ Sbias(k)

One analysis per several days

(7-day/5day cycle)

+ no shock thanks to

repartition of the anaylsis

correction over the week

MEDRYS1V1 MEDRYS1V2


Experimental design for MEDRYS1 reanalyses

23

MEDRYS1V2


24

Added value of the high-resolution in ALDERA

ALADIN-150km

ALADIN-50km

ALADIN-12km

(ALDERA)

Wind and heat flux on the 14th March 2013 Wind direction and speed on the 16th September 2012

25

Need of fluxes giving balanced budgets(from Hamon et al. 2016)

Heat flux components

Water flux components

Any questions?

26

Thank you for your attention!

19/05/2016 C3S Regional Reanalysis Workshop, Reading

Statistics on assimilated data: SLA

27

MEDRYS1V1 MEDRYS1V2

6.5cm

5.0cm

-0.8cm -0.7cm

Statistics on assimilated data: SST

28

MEDRYS1V1 MEDRYS1V2

0.74°C0.57°C

-0.060°C -0.026°C

Statistics on assimilated data: in-situ

29

MEDRYS1V1 MEDRYS1V21993

-1000

-500

-200

-2000

2013

0

-1000

-500

-200

0

1993 2013

-2000

1993 2013

1993 2013

Temperature

Salinity

Monthly heat and salt contents

3010/02/2016

(courtesy G. Jorda for the IMEDEA construction)

S3D[600m-bottom]

T3D[0-150m] S3D[0-150m]

T3D[600m-bottom]

T3D[150-600m] S3D[150-600m]

Documents

CMEMS regional reanalyses - Copernicus Climate … · Copernicus Marine Environnement Monitoring Service (CMEMS) regional reanalyses 19/05/2016 C3S Regional Reanalysis Workshop, Reading