Modélisation couplée (océan-atmosphère- biogéochimie) …...4ièmes Journées Scientifiques...
Transcript of Modélisation couplée (océan-atmosphère- biogéochimie) …...4ièmes Journées Scientifiques...
4ièmes Journées Scientifiques Equip@Meso : Sciences de l’Univers, Toulouse, CALMIP 26&27 Novembre 2015
Modélisation couplée (océan-atmosphère-biogéochimie) haute-résolution du système de
courant de Humboldt (Pérou/Chili)
Boris Dewitte (LEGOS) Séréna Illig, Véronique Garçon, Joel Sudre, Aurélien Paulmier, Oscar Vergara Katerina Goubanova (CERFACS) Ivonne Montes, Ken Takahashi (IGP, Pérou)
• General scientific motivations • Extreme El Niño dynamics • Regional air-sea interactions in the Peru upwelling system • Oxygen Minimum zone dynamics off Peru • Conclusions/Perspectives
Outline
Problématiques
Winds
Zone de Minimum d’Oxygène dans le Pacifique Sud-Est
Chlorophyl-a (Satellite)
Concentration en Oxygène (in situ) à 400m Rouge= concentration < à 0.5 ml/L)
Data= CARS Data =SeaWIFS
P=1020 HPa
Strato-Cumulus Cloud Deck
Problématiques
Evénements Extrême
Bilan radiatif
Pêches
Société
Climat
Biais en température de surface dans les modèles CMIP5
K. Goubanova
Besoin de recourir à la modélisation régionale haute résolution
Dynamique des événements Extrême El Niño (Modélisation océanique)
Halloween, 2015, Lima
1997
2009
2015
Eastern Pacific El Niño versus Modoki El Niño (or Central Pacific El Niño)
ENSO diversity (Obs.)
Observations are indicative of two regimes of variability (Takahashi and Dewitte, 2015)
Warmer in the far eastern Pac.
War
mer
in th
e ce
ntra
l Pac
ific
Data: SST (HadISST) (1950-2014)
Observed* nonlinear Bjerknes
feedback (SST/rain/wind)
The response in convection and wind stress to SST is more than 3 times for E > 1.5, i.e. strong eastern
Pacific warming -> stronger Bjerknes feedback
Piecewise linear fit: Multivariate adaptive regression splines
Takahashi and Dewitte, 2015
Linear regression of SST (colors), OLR (contours) and wind stress on the E index in observations
* Similar in CM2.1 but shifted westwards
Data: OLR (1974-2013), WAS-Wind (1950-2010)
(Dewitte et al., 2003, JGR)
Evolution of the 1997/98 El Niño
OGCM experiments
• TROP-LR (1/4°): Forced by Mercator as OBCs (S,T,U, SSH); ECMWF 6h forcing • TROPEAST-HR (1/12°) : Forced by TROP-LR (1/4°) as OBCs; ECMWF 6h forcings - 2 experiments: with and without non-linear advection included in the momentum equations (filter out TIWs activity)
Tropical Instability wave activity
Model validation Sea Level (JASON)
Mean thermocline (TAO)
Westerly Wind Burst during early 1997 and 2014
(Menkes et al., 2014, GRL)
CR CR - LIN
Evolution of SST and SL anomalies (model)
CR: Control Run simulation LIN: without non-linear advection included in the momentum equation from December 2013 -> Equatorial waves dissipate less
Regional air-sea interaction in the eastern Pacific (modélisation couplée océan-atmosphère)
The Humboldt region: a complex ocean-atmosphere coupled system
Schematic of the Hadley-Walker Cell in the Pacific
Atmospheric boundary
Layer ~ 1km
Surface winds
Stratocumulus
~ 10 km
12°S 14°S 18°S 22°S 26°S 30°S 34°S
95°W 90°W 85°W 80°W 75°W 70°W
~10 km
Wind profile
(Illig et al., 2015) Surface Ekman layer
SST gradient OMZ
upwelling
Merged Satellite Product (1km resolution) (Vasquez,
Dewitte et al., 2013)
Spatial scales to be resolved for coupled studies..
~30 km
Regional coupled model
S. Illig
Oceanic model configuration (ROMS) : South East Pacific Parent domain (ℙ): [22°S-12°N ; 88°W-70°W] at 1/12° Embedded Coastal Peru Zoom domain (ℤ) with AGRIF: [17°S-4.5°S ; 85°W-70°W] at 1/36° 37 (sigma) vertical levels Bathy GEBCO_08
Atmospheric model configuration (WRF) : South East Pacific Parent domain (ℙ): [22°S-12°N ; 88°W-62°W] at 1/6° Embedded Coastal Peru Zoom domain (ℤ) with AGRIF: [17°S-4.5°S ; 85°W-70°W] at 1/18° 40 vertical levels
Simulating the Peruvian Upwelling System -Atmosphere
Differences between WRF Parent and Zoom
dist in km (km)
10-2
N/m
2
Simulating the Peruvian Upwelling System - PCE
Increasing ROMS & WRF resolution More realistic bottom topo Upwelling trapped at topo SST at the coast Marked drop-off PCC and PCUC off shore SST SST cross-shore gradient
Zoom
dist in km dist in km dist in km
Dynamique de la zone du Minimum d’Oxyègne dans le Pacifique Sud-Est
(modélisation couplée océan-biogéochimie)
OMZ are expanding over the last 5 decades
Stramma et al. (2008), Science Years
Evolution of the OMZ in Eq. Pacific
Mean Oxygen concentration at 400m depth
This “expansion” of the OMZs is quantified as a negative trend in
oxygen concentrations.
∂O2/∂t < 0
Deficiency of the OGCM in simulating the OMZs
Global medium resolution coupled model have severe biases in simulating the OMZs. This is due to:
Biases in the equatorial circulation (in
particular the EUC extension) The too low resolution that leads to an
unrealistic amplitude of EKE Biases in remineralization due to
inappropriate parametrization
Obs.
Oxygen Trend (global zonal average at 300db)
Forced Global Simulations Stramma et al. (2012)
Tropical Oceans
Typical pathways of the feeding sources of the Peru Undercurrent in high-resolution oceanic model
Montes et al. 2010 (1/9°)
Dewitte et al. 2012 (1/12°)
Along-shore currents at 12°S
Regional modeling allows overcoming some of the global model biases. (Indian: Resplandy et al. (2012); Benguela: Gutknecht et al. (2013); Peru: Montes et al. (2014)).
Montes et al. (2014)
Regional modeling of the OMZs: State of the Art
Simulations Observations
OMZ thickness (in meters)
Bettencourt et al., (2015), Nature Geoscience
Map of backward FSLE Frontal position
45µM
Mean [O2] at 60 and 200m, inside 45µM and mean frontal position at 410m
The OMZ boundaries are maintained by mesoscale activity (i.e. mean O2 transport is much weaker than eddy-induced transport) Can the changes in eddy flux explain the variability of the OMZ?
Regional modeling of the OMZ: Role of mesoscale dynamics
Biogeochemical coupled model Ocean model: ROMS_AGRIF. Biogeochemical module: BioEBUS
(N2P2Z2D2, Koné et al, 2005; Gutknecht et al., 2013a).
Resolution: 1/12°. Period: 1958-2008 (15 years of spin-up). Atmospheric forcing: statistically
downscaled NCEP winds (Goubanova et al., 2011). Climatological bulk formula derived heat fluxes.
Oceanic forcing: 3-day SODA (0.25°x0.25°). Bathymetry: GEBCO 30 arc-second grid. (Dewitte et al., 2015)
(Gutierrez et al., 2008)
Dissolved Oxygen off Callao (12°S)
22 µM
Dissolved Oxygen off Callao (12°S) (1958-2008)
2000-2008 mean 1958-2008 mean
Evolution of composite anomalies of dissolved oxygen at 200m (anomalies are normalized by their variance)
DJF MAM JJA
EP El Niño
CP El Niño
Significance at the 95% level
Time
Conclusions • L’étude des bords Est des océans (en particulier système du Pérou/Chili) requiert une modélisation haute-résolution pour:
• Résoudre les échelles typiques de l’upwelling et de la circulation atmosphérique côtière (e.g. wind drop-off) • Mieux prendre en compte les mécanismes d’intéraction air-mer à fine échelle • Comprendre la dynamique non-linéaire des événements El Niño extrêmes (connexion entre la dynamique équatoriale et côtière) • Mieux comprendre la dynamique des zones de minimum d’Oxygène (effet d’upscalling sur le climat) • Pour comprendre et interpréter les biais dans les modèles globaux à « basse résolution » (modèles du GIEC)
Modélisation régionale intégrée (e.g. regional Earth Modeling system) – océan-atmosphère-biogéochimie-chimie atmosphérique-dynamique de population