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UNIVERSITY of ROME “TOR VERGATA” XXV Doctoral Program A study of the Tiber R iver dynamics and coastal primary production with satellite data, circulation and primary production models Institute of Atmospheric Sciences and Climate

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slide1

UNIVERSITY of ROME “TOR VERGATA”

XXV Doctoral Program

A study of the Tiber River dynamics and coastalprimary production with satellite data, circulation and primary production models

Instituteof AtmosphericSciences and Climate

of the Italian National ResearchCouncil (ISAC-CNR).

Cinzia Pizzi

slide2

Motivation

The algalbiomassactivityismodified from rivers’ load:

NEGATIVE EFFECT

POSITIVE EFFECT

ROME

Rome

TYRRHENIAN SEA

TIBER PLUME

NASA MODIS - Sediment plume from the Tiber River, Italy (http://modis.gsfc.nasa.gov/)

slide3

Motivation

POSITIVE EFFECT

NUTRIENTS INCREASE

ALGAL PRODUCTIVITY

SUPPORTS

MARINE FOOD WEB

slide4

Motivation

NEGATIVE EFFECT

  • POLLUTANTS
  • (heavy metal, hydrocarb., etc.)
  • NUTRIENTS SURPLUS
  • HARMFUL ALGAL BLOOMS

RED TIDE BLOOM

  • DANGEROUS
  • MARINE ECOSYSTEM
  • TOURISM
  • FISHING

(www.centroricerchemarine.it)

slide5

OBJECTIVES

Development of a

COASTAL MONITORING TOOL

for the Tyrrhenian Sea (Tiber river)

Rome

COASTAL & OFFSHORE AREAS MORE EXPOSED TO THE TIBER LOAD

  • TIBER PLUME DYNAMICS

MODULATION ON PRIMARY

PRODUCTION

  • TIBER PLUME EFFECT
slide6

Analyzed periods

WINTER CASE STUDY

Exceptional

Tiber River discharge

(1660 m3/s) since 1965

DECEMBER 2008

Typical

Tiber River discharge

(860 m3/s)

NOVEMBER 2010

SUMMER CASE STUDY

Typical

Tiber River discharge

(210 m3/s)

JULY 2010

slide7

Dataset1) SATELLITE DATASET (MODIS/AQUA)

  • (December 2008, July and November 2010)
  • 1. SurfaceChlorophyll-a (chl- mg m-3)

2. Diffuse light attenuationcoefficientat 490 nm (K490; m-1)

  • 3. Turbid water flag (L2flag – CASE 1 or open seawater & CASE 2 or coastal water)
slide8

output

output

Dataset2) MODEL DATASET (Dr. Inghilesi, ISPRA runs)

  • (December 2008, July and November 2010)
  • current, temperature, salinityfields
  • POM (Princeton Ocean Model)
  • LAM (Limited Area Model) wind to force POM circulation
  • Trajectory/distribution of syntheticparticlesreleasedat Tiber estuary
  • 2) Lagrangian model (nested in POM)

POM salinity/current fields

Lagrangian diffusion particles

slide9

Dataset 3) Wind data

LAM WIND MODEL DATA

(POM FORCING)

  • ASCAT WIND SATELLITE DATA
  • (LAM WIND VALIDATION)
slide10

Results 1) LAM WIND VALIDATION WITH ASCAT

  • (December 2008, July and November 2010)
slide11

Dataset4) Primary Production (PP) from VGPNN model

(Vertically Generalized Production Neural Network; Scardi, 2001)

  • (December 2008, July and November 2010)
  • Data input:
  • SATELLITE DATA (MYOCEAN products):
  • Surfacechlorophyll(chl- mg m-3)
  • Sea Surface Temperature (SST – C°)
  • Photosynthetically AvailableRadiation(PAR-E m-2 day-1)
  • MODEL DATA (Circulation POM)
  • Mixed Layer Depth (MLD)

Data output:

Primary Production (PP - g C m2day-1) for the Tyrrhenian Sea

slide12

Results 2) River plume dynamics

Current & particledistribution (DECEMBER 2008)

30 Dec.

5 Dec.

  • DECEMBER 2008
  • Coastal - offshore interaction dynamics IMPORTANT
  • Coastal circulation driven by offshore oceanographic features, NOT by wind
  • Tiber plume moves northwestwards

Sea Surface Temperature (DECEMBER 2008)

Wind & particleconcentration (DECEMBER 2008)

5 Dec.

30 Dec.

19 Dec.

wind

45°

Ekman

Ekman

90°

slide13

Results 2) River plume dynamics

Current & Particledistribution (NOVEMBER 2010)

25 Nov.

5 Nov.

  • NOVEMBER 2010
  • Coastal - offshore dynamics is
    • partlycoupled to Tyrrhenian Sea cycloniceddy (e.g. Nov 25)
    • partlywinddriven(e.g. Nov5)
  • THEREFORE: Tiber plume moves both northwestwards & southeastwards

Sea Surface Temperature (NOVEMBER 2010)

25 Nov.

5 Nov.

12 Nov.

wind

45°

Ekman

Ekman

90°

Wind & particleconcentration (NOVEMBER 2010)

slide14

Results 2) River plume dynamics

Current & particledistribution (JULY 2010)

14 Jul.

30 Jul.

  • JULY 2010
  • The cold cyclonic gyre is absent
  • Wind driven circulation
  • Tiber plume moves northwestwards,
  • southeastwards & offshore
  • Plume is more mobile because the summer MLD is shallower i.e. plume is thinner.

Sea Surface Temperature (JULY 2010)

Wind & particleconcentration(JULY 2010)

30 Jul.

14 Jul.

wind

45°

Ekman

Ekman

90°

24 Jul.

slide15

Results 2) River plume dynamics

ModelTiberplume

20 Dec.

SatelliteTiberplume

  • Model/plumecirculationwellreproducesreality asseen from satellite data

CHL K490 (water transparency) Tw(coastal and offshore water)

20 Dec.

20 Dec.

20 Dec.

slide16

Results 3) Plumeeffects on primary production

Comparisonbetween Primary production and dailyTiber discharge

S. Marinella – Anzio

slide17

Results 3) Plumeeffects on primary production

time lag=8 days

Algal biomass seems

to be favoured by

Tiber river discharge

slide18

Results2) Plumeeffects on primary production

Particle concentration (Cp) model output

December 2008

satellite chl (mg m-3)

P. Production PP (g C m-2 day-1)

High PP atgyre edge:

favored by submesoscale dynamics

(Lévy et al., 2001)

slide20

Hypotheses on observed summer PP variability

1) Nutrients are not limiting in the control box

ZOOPLANKTON GRAZING

(TOP - DOWN CONTROL)

2) Nutrients are limiting in the control box:

NUTRIENTS SUPPLY FROM:

  • SUMMER AGRICULTURAL
  • FERTILIZING

COASTAL UPWELLING

slide21

Conclusions

  • Model/plumecirculationreasonablywellreproduces reality asseenfrom satellite validation
  • THIS WORK: PROTOTYPE TOOL FOR COASTAL MONITORING
  • APPLICATIONS: WFD (Water Framework Directive)
  • MFSD (Marine Framework Strategy Directive)

WINTER: plume is heavily influenced by offshore structures (Tyrrhenian eddy)

basin - wide dynamics important for coastal monitoring

SUMMER: plume is wind mesoscale driven (absence of organized offshore dynamic structures impact in the coast)

PRIMARY PRODUCTION: seems more directly connected to winter peak Tiber discharge; summer correlation not likely (to be verified)

  • FUTURE WORK
  • Extension to multi-year satellite/model datasets
  • Integration with in situ data (ISAC-CNR Tyrrhenian sea 2010- 2013 cruises)
slide22

REFERENCES

Barale V. and D. Larkin (1998). “Optical remote sensing of coastalplumes an run-off in the mediterranean

region”. Journal of CoastalConservation, 4: 51-68

Bignami, F., Sciarra, R., Carniel, S., and R. Santoleri (2007). “Variabilityof Adriatic Sea coastalturbid

watersfrom SeaWiFS Imagery”. Journal of GeophysicalResearch, vol. 112, C03S10,

doi:10.1029/2006JC003518

Fong, D. A. and W. R. Geyer(2002). “The AlongshoreTransport of Freshwater in a Surface-Trapped

River Plume”. Journal of PhysicalOceanography, 32: 957-972

Lévy, M., Klein, P. and A. M. Treguier (2001). "Impacts of sub-mesoscale physics on phytoplankton

production and subduction“. Journal Marine Research, 59: 535-565

Pinardi, N., Allen, I., Demirov, E., De Mey, P., Korres, G., Lascaratos, A., Traon, P. Y., Maillard, C., Manzella,

G. and C. Tziavos (2003). “The Mediterranean oceanforecastingsystem: first phase of

implementation(1998-2001)”.Annals of Geophysics, 21: 3-20

Ruti, P. M., Marullo, S., D'Ortenzi, F. and M. Tremant(2008) “ Comparisonof analyzed and measured

windspeedsin the perspective of oceanicsimulations over the Mediterranean basin:

Analyses, QuikSCATand buoydata”. Journal of Marine Systems 70: 33–48

Santoleri, R., Banzon, V., Marullo, S., Napolitano, E., D’Ortenzio, F. and R. Evans (2003). “Year-to-year

variabilityof the phytoplanktonbloom in the southernAdriatic Sea (1998–2000): Sea-viewing

Wide Field-of-viewSensor observations and modelingstudy”. Journal of GeophysicalResearch, 108,

(c9), 8122, doi:10.1029/2002jc001636

Sorgente, R., Drago, A. F. and A. Ribotti (2003). “Seasonalvariability in the Central Mediterranean Sea

circulation”. Annales Geophysicae 21: 299–322

Scardi, M., (2001). “Advancesin neural network modeling of phytoplanktonprimaryproduction ”.

EcologicalModelling 146: 33-45