Assessment of global hindcast and real-time biogeochemical ...godae-data/OceanView/Events/... · Discussion on the impact of physical data assimilation Assessment of global hindcast

Discussion on the impact of physical data

assimilation

Assessment of global hindcast and real-time

biogeochemical systems designed at

Mercator Ocean:

PERRUCHE1 C., Y. DRILLET1, E. GUTKNECHT1, C., J. PAUL1,

E. GREINER2, M. GEHLEN3

1 Mercator Océan, France 2 CLS, France 3 LSCE, France

12/07/2016 GODAE Joint MEAP-DA-TT, Santa Cruz

Introduction

Copernicus Marine Service

Copernicus: EU program dedicated to Earth Observation and Monitoring

- Collect satellite and in situ Data

- Turn these data into information through services divided in 6 thematic

streams: atmosphere, land, marine and climate monitoring, emergency

management, security

Marine service coordinated by

Mercator Ocean

Mercator Ocean in charge of the

Global Analysis and Forecast

product in the catalogue

physical state

biogeochemical state


Cliquez et modifiez le titre

Introduction

The PISCES model

Aumont et al. (2015)

- 24 prognostic variables, 5 limiting nutrients, 2

phytoplankton and zooplankton species, 3 detritus

compartments

- Redfieldian model (constant C/N/P ratio)

- variable C / Chl, C/Fe, C/Si ratios

- Carbon and oxygen cycles

- No feedback of chlorophyll concentration on

temperature profile

- Monod model (Monod, 1942): no diurnal cycle

- Balance between external inputs and losts in the

sediments after particule sinking

- External inputs: rivers (Fe, Si, and P), dust (Fe, Si

and P) and sedimentary iron (friction)


Introduction

GLOBAL ¼°

REAL TIME

- NEMO3.2

- Spatial resolution: ¼°

- 50 vertical levels

- Initial conditions: WOA et GLODAP

- 2007 – real time

- Offline coupling

- Ocean forcing: operational analyses ¼°

daily (with physical data assimilation of

SST, SLA data and in situ T et S)

- Atmospheric forcing: operational analyses

ECMWF bulk CORE

- Anthropogenic Carbon (Masarie and Tans,

1995)

HINDCAST (1998 – 2014)

- NEMO3.5

- Spatial resolution: ¼°

- 75 vertical levels

- Initial conditions: WOA et GLODAP

- 1992 – 2014 (disseminated from 1998 on)

- Offline coupling

- Ocean forcing: free hindcast (1/4°) daily (no

assimilation)

- Atmospheric forcing: ERA-INTERIM bulk

CORE

- Anthropogenic Carbon (Masarie and Tans,

1995)


Outputs:

Weekly means

each week: hindcast,

nowcast, forecast

Outputs:

Daily and monthly

means

Assessment HINDCAST

GLOBAL ¼°: Interannual simulation

Good accordance in large scale structures

CHL

Air-Sea CO2

flux

(gC/m2/yr)

Globcolour DATA 2014

Takahashi clim

MODEL 2014

MODEL clim 1998 - 2014


Seasonal cycle in North Atlantic

CHL

Globcolour

Daily

CHL Model

Daily

MLD Model

Daily

2002 2010 - Seasonal cycle correctly reproduced

- Secondary bloom in autumn during

the mixed layer deepening

(nutrient limitation)

- Main bloom in spring during the

mixed layer shallowing (light

limitation)

- In summer, the mixed layer is very

shallow, and there is low primary

production


Assessment HINDCAST



CHL

Globcolour

Daily

CHL Model

Daily

MLD Model

Daily

2002 2010 - Almost no chlorophyll in modelled

oligotrophic gyre (in data ~0.05 mg/m3)

- Beginning of the bloom too early (lag of

one month)

Mean chl

Median chl

Percentile

80 chl


2002

- The bloom is propagating too fast northward

- The bloom is not lasting enough in summer

Assessment HINDCAST


Data

Model


CHL

Globcolour

Daily

CHL Model

Daily

MLD Model

Daily

2002 2010


- Almost no chlorophyll in modelled

oligotroph gyres (in data ~0.05 mg/m3)

- Beginning of the bloom too early (lag of

one month)

- The bloom is propagating too fast northward

- The bloom is not lasting enough in summer

- Restratification: not a continuous process, successive

shallowing periods interrupted by periods of deepening:

phytoplankton react instantaneously

Assessment HINDCAST



CHL

Globcolour

Daily

CHL Model

Daily

MLD Model

Daily

2002 2010

- Strong interannual

variability of the

bloom timing

- Earlier bloom in

2010

- Stronger bloom in

2002

- Well reproduced by

the model


Assessment HINDCAST


Interannual variability of the bloom in North Atl.

North-South spatial variability of the seasonal

bloom triggering : well reproduced by the model

local process: due to the variability of the ML

deepening in winter

CHL

Globcolour

Monthly

CHL

Model

Monthly


Assessment HINDCAST


GlobColour Model

Good representation of the two 1st modes of variability (spatial signature and time series)

Clear correlation with ENSO index (Thomas et al., 2012)

Mo

de

#1

Mo

de

#2

Interannual variability in the Pacific Ocean

EOF decomposition of chlorophyll (1998 – 2014)


Assessment HINDCAST


Anomaly Chl 40S-40N (detrended and deseasonalized)

ENSO index (MEI) x(-1)

Distribution of OMZs (Oxygen Minimum Zone)

MODEL clim 1998 - 2014 CLIM WOA 2013

O2 min

Thickness of

the hypoxic

layer


Assessment HINDCAST


Coherency between model and climatology

Year 1995: Annual mean at the equator

ASSIM

WITH ASSIM

Stronger equatorial

upwelling in average

Subsurface upwelling

between 200 and 1000 m

depth

More variability in

equatorial vertical velocities

The assimilation system:

• Kalman filter with SEEK formulation

• 3D-Var bias correction in temperature and salinity for the slowly evolving large scales

Data assimilated: SST, SLA, In situ temperature and salinity

Both

with IAU


Mean W

(m/day)

Impact of assimilation

Equatorial Upwelling

NO ASSIM

Std W

(m/day)

NO ASSIM ASSIM

DATA

Year 1995: Annual mean of chlorophyll concentration

Tropical band much larger with ASSIM

No warmpool anymore

Still a work in progress

Next system with a corrected MSSH



Equatorial Upwelling

Chl Globcolour 8days OSS2015 product (L4), superimposed modelled SSH with assimilation

Gulf Stream

Mid-august

2000

Agulhas current

Mid-september

2000

Good accordance

between the

modelled front of

SSH and the

chlorophyll

distribution: the front

acts as a natural

boundary from

which eddies are

detaching



Positioning of fine-scale structures

Modelled Chl (daily), superimposed modelled SSH with assimilation

NO ASSIM

January, 15th

ASSIM

January, 15th

Better positioning of

the front with

assimilation of

physical data

Boundary between

oligotrophic gyre and

subpolar gyre more

zonal



Positioning of fine-scale structures

Conclusion & Perspectives


• Adjustement of the equatorial upwelling to physical data assimilation: Still work-in-progress, need to disentangle the effect of each parameter assimilation (T, S, SSH)

• The assimilation clearly allows a better positioning of frontal and mesoscale structures

• September 2016: In Copernicus, new operational system forced by the GLOBAL 1/12° operational analysis (coarsening offline towards ¼°)

• Next simulation NEMO3.6: Start from the 20th century simulation realized in the ERACLIM2 project (cf talk of P. Laloyaux)

• Assimilation of ocean color data for 2017 (see poster J. Lamouroux)

22/07/2016 Name of the event, Place

The end !

GLOBAL ¼°: Next systems

• September 2016: In Copernicus, new operational system

forced by the GLOBAL 1/12° operational analysis

(coarsening offline towards ¼°)

• Next simulation NEMO3.6: Start from the 20th century

simulation realized in the ERACLIM2 project: see talk of

P. Laloyaux (NEMO3.6, 1°, 130 years of spin-up)

• Assimilation of ocean color data for 2017 (see poster J.

Lamouroux)


ANIMATION


ANIMATION



Impact of assimilation: better positionning of

fronts and mesoscale structures

Mo

de

#1

Mo

de

#2

Modèle GlobColour

Anomaly Chl 40S-40N x (-1)

SST anomaly

Good representation of the two 1st modes of variability (spatial signature and time series)

Good correlation with ENSO index (Thomas et al., 2012)


Interannual variability

EOF decomposition of chlorophyll

Assessment HINDCAST


NO ASSIM

April, 15th

ASSIM

April, 15th

Modeled Chl (daily), superimposed modeled SSH with assimilation

Better positionning

of the front with

assimilation of

physical data



Positionning of fine-scale structures

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Assessment of global hindcast and real-time biogeochemical ...godae-data/OceanView/Events/... · Discussion on the impact of physical data assimilation Assessment of global hindcast