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Chlorophyll bloom in the western equatorial Pacific during the 1998 El Niño / La Niña transition: the role of Kiribati Islands as seen from satellite, in-situ data, and a high-resolution simulation. Monique Messié , Marie-Hélène Radenac and Jérôme Lefèvre LEGOS, Toulouse and Nouméa.

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seawifs chlorophyll concentration may 25th to june 1st 1998

Chlorophyll bloom in the western equatorial Pacific during the 1998 El Niño / La Niña transition: the role of Kiribati Islands as seen from satellite, in-situ data, and a high-resolution simulation

Monique Messié, Marie-Hélène Radenac and Jérôme LefèvreLEGOS, Toulouse and Nouméa

SeaWiFS chlorophyll concentration: May 25th to June 1st, 1998

hypothesis from previous studies
Hypothesis from previous studies
  • Context at the beginning of 1998:

- nitrate-limited ecosystem (Chavez et al., 1999), shallow nutricline

- reappearance of the EUC (source of iron, Gordon et al., 1997 )

  • Mechanisms: wind-driven upwelling and vertical mixing(Murtugudde et al., 1999; Wilson and Adamec, 2001; Ryan et al., 2002)
  • the bloom mechanisms appear to be quite well understood

BUT

  • nutricline and EUC shoaling occurred in the whole equatorial Pacific
  • strongest easterlies near the dateline
  • why did the bloom occur in this particular region?
what we observe
What we observe…

SeaWiFS chlorophyll concentration (left), Topex-ERS SLA (top right), TMI SST (down rigth) : March 22th to 28th, 1998. White stars: TAO buoys.

kiribati islands

Tarawa/Abaiang

AbaiangTarawa

Kiribati Islands as seen by MODIS(http://visibleearth.nasa.gov)

Kiribati Islands

SeaWiFS chlorophyll concentration: March 22th to 28th, 1998. White stars: TAO buoys.

aim of the study
Aim of the study

 to assess whether the islands played any role in the bloom generation and development

Outline

- Data and model presentation

- Bloom chronology

 bloom generation

 bloom peak

 bloom demise

- Conclusions

  • impact on the dynamics of the region
  • perturbations induced on nutrient fields and chlorophyll concentrations
slide6
Data
  • Satellite data:
  • surface chlorophyll concentration (SeaWiFS, 1/10°, 8-day)
  • SLA (Topex/Poseidon-ERS, 1/3°, weekly)
  • SST (TMI, 1/4°, weekly)

SeaWiFS chlorophyll concentration: March 22th to 28th, 1998. White stars: TAO buoys.

  • In-situ data: TAO moorings at 165°E and 180°
  • temperature profiles
  • current profiles at 165°E, 0°
model

Run K: bathymetry

Model
  • Regional Ocean Modeling System (ROMS): split-explicit, free-surface, σ-coordinate (Shchepetkin and McWilliams, 2005)
  • grid: 160°E-178°W, 6°S-11°N, 1/6°, 30 vertical levels2 grids (smoothed ETOPO2 bathymetry): - with islands: run Kiribati (K), land masking

- with no islands: run No Kiribati (NK)

  • period:1996-1998
  • boundary forcing: ORCA2 configuration of the OPA model
  • surface forcing: daily wind stress (TAO-ERS), 6-hour NCEP reanalysis
  • Regional Ocean Modeling System (ROMS): split-explicit, free-surface, σ-coordinate (Shchepetkin and McWilliams, 2005)
  • grid: 160°E-178°W, 6°S-11°N, 1/6°, 30 vertical levels2 grids (smoothed ETOPO2 bathymetry): - with islands: run Kiribati (K), land masking

- with no islands: run No Kiribati (NK)

  • period:1996-1998
  • boundary forcing: ORCA2 configuration of the OPA model
  • surface forcing: daily wind stress (TAO-ERS), 6-hour NCEP reanalysis
model validation

165°E-0°N: Uzonal (m s-1, color) and temperature (°C, black contours)

Model validation

Surface data: SST (TMI), SLA (Topex/Poseidon-ERS)

TAO data: temperature and Uzonal profiles

  • Globally good agreement for surface and TAO data BUT:
  • EUC too weak, shoaling too late
  • cold bias in the bloom region
bloom evolution

(data results)

1. Bloom generation:an island mass effect?

  • data results: island mass effect, impact on SLA
  • model results: islands impact on dynamics and nitrate-rich water masses

islands position

Bloom evolution

0°N-2°N averaged (December 1997 – September 1998)

bloom demise

bloom peak: a sudden input of iron?

bloom generation:an island mass effect?

island mass effect

1. bloom generation

 400

U incident current speed  0.5 m.s-1L dimension of the island  80 kmν horizontal eddy viscosity  100 m²s-1

Island mass effect

(data results)

  • increase of chlorophyll concentration and biological productivity downstream of an oceanic island

Study of the Tarawa/Abaiang island:low-latitude island  characteristics of the wake predictable from Reynolds number (Heywood et al., 1996)

  • possible mechanism: flow disturbance  eddies formation  increased vertical mixing

 threshold for eddy sheding 70 a vortex street of eddies is supposed to occur downstream of the Tarawa/Abaiang group of islands

effect on sla

1. bloom generation

Effect on SLA

(data results)

 signature of eddies?

vertical mixing and increased productivity

Topex/Poseidon - ERS Sea Level Anomalies: January 5th to June 14th, 1998.

islands impact on dynamics

1. bloom generation

°C

°C

Run K output: surface temperature (color) and currents (arrows), March 26th to 30th, 1998

Run K output: surface temperature (color) and currents (arrows), March 26th to 30th, 1998

24°C-isotherm depth averaged between 0°N and 2°N and EUC depth (March-April 1998)

Islands impact on dynamics

(model results)

In the wake of the islands:

  • cold SST, low SSH and high water density
  • meanders and eddies
  • shoaling of temperature isolines in the upper part of the thermocline; same for density isolines and EUC
nitrate type passive tracer

1. bloom generation

SeaWiFS data

Run K PasTr

0°N-2°N PasTr average (dimensionless).

White contour : bloom area (0.3 and 0.5 mg m-3 iso-[Chl])

SeaWiFS Chl concentration (mg m-3): March 22th to 28th, 1998. Run K, N-tracer: March 24th to 28th, 1998.

Nitrate-type passive tracer

(model results)

 Passive tracer: [PasTr] = 0 for T > 24°C[PasTr] = 27 – 1.1235 T for T  24°C

processes at work

1. bloom generation

local changesvertical advection horizontal advection vertical mixing

0°N-2°N passive tracer diagnostics(50 m upper layer): bloom generation (24/02-20/04)

longitude

Processes at work

(model results)

 near the islands position: vertical advection

 at the bloom location: vertical advection and vertical mixing

bloom evolution1

(data results)

2. Bloom peak:a sudden input of iron?

  • data results: TAO data at 165°E, 0°N
  • model results: islands impact on the EUC and iron-type lagrangian floats

islands position

Bloom evolution

0°N-2°N averaged (December 1997 – September 1998)

bloom demise

bloom peak: a sudden input of iron?

bloom generation:an island mass effect?

tao data

2. bloom peak

bloom peak

TAO data 165°E-0°N: Uzonal (m s-1, color) and temperature (°C, black contours)

TAO data

(data results)

  • end of April: current reversal at 40m depth  weakening of the island mass effect  cannot explain the highest Chl concentrations
  • current reversal: because of the potential iron-rich EUC shoaling  sudden input of iron?
iron type lagrangian floats

2. bloom peak

0

Run K

Run NK

temporal distribution

Example of Fe-floats initial position (March 28th, 160°E). Black lines: zonal current isolines.

depth (m)

Run K

Run NK

spatialdistribution

-500

-5

0

5

latitude

Iron-type lagrangian floats

(model results)

 injection in the EUC at the western boundary, for z < -80 m and u > 80% max(uEUC), every 10 days from January 27th to June 6th.

 results: study of the first appearance of Fe-floats in the 50 m upper layer

bloom evolution2

(data results)

3. Bloom demise:eastward advection of chlorophyll-poor waters?

  • data and model surface current
  • passive tracer diagnostics

islands position

Bloom evolution

0°N-2°N averaged (December 1997 – September 1998)

bloom demise

bloom peak: a sudden input of iron?

bloom generation:an island mass effect?

horizontal advection

3. bloom demise

(model results)

bloom demise

local changesvertical advection horizontal advection vertical mixing

0°N-2°N passive tracer diagnostics in June (50 m upper layer)

longitude

Horizontal advection

(data results)

TAO data 165°E-0°N: Uzonal (m s-1, color) and temperature (°C, black contours)

 probably surface current reversal in June

 eastward current during the bloom demise

 horizontal advection drives the bloom demise

conclusion bloom sequence
Conclusion:bloom sequence

mg m-3

demise

 bloom generation (Jan-Apr):island mass effect  eddies, vertical mixing + wind-driven upwelling  nitrate input

peak

generation

 bloom peak (Apr-May):EUC shoaling enhanced by the presence of the islands barrier  sudden input of iron  dramatic increase of chlorophyll concentration

 bloom demise (May-Jun):EUC surfacing  surface currents reversal  eastward advection of nutrient-poor waters

conclusion

Conclusion

  • Influence of Kiribati Islands on the bloom generation and development: - disruption of the dynamics and nutrient fields - responsible for the strength and location of nitrate and iron inputs
  • Need of a coupled physical/biological model