Impacts of Climate and basin-scale variability on the seeding and production of Calanus finmarchicus in the Gulf of Maine and Georges Bank

	Avijit Gangopadhyay
	With Bisagni, Gifford and Batcheldar
	GLOBEC meeting, WHOI
	2nd October, 2006

List of Investigators

	Avijit Gangopadhyay (PI – Basin-scale physical modeling)
	Jim Bisagni (UMass Dartmouth) – Satellite SST field, Hydrographic analysis
	Dian Gifford (URI) – Zooplankton data analysis
	Hal Batchelder (OSU) – IBM modeling

Goals and Objectives

	to probe the connections between Calanus finmarchicus distributions and the physical oceanographic properties, climate variability, and basin-scale circulation changes that are likely to affect the copepodŐs transport onto Georges Bank.
	We will do this using a combination of numerical model simulations and observational data.

Ongoing NASA project

	Basin scale modeling for North Atlantic
	High and Low NAO simulations
	Focus on Gulf Stream and Labrador Sea
	Nutrient Dynamics – Depletion vs. Dilution
	Physics and nutrient flux experiments
	(with Ayan Chaudhuri)

NA Basin-scale Simulations

NCEP vs SOC -- January

NCEP vs. SOC -- Annual

Net Heat Flux Components

	Net Heat Flux is given as
	Qnet = QH+QE+QLW+QSW
	where,
	QH =  Sensible Heat Loss
	QE =  Latent Heat Loss
	QLW =  Longwave Loss
	QSW =  Shortwave Heat Gain
	Is the NCEP climatology underestimating/overestimating any of these components?

Latent Heat Loss

Sensible Heat Loss

Shortwave Heat Gain

Longwave Heat Flux

Calibrating NCEP against SOC

	The NCEP Climatology thus overestimates the Net Heat Loss for the North Atlantic Region due to overestimation of Latent and Sensible Heat Loss terms and underestimation of Shortwave Gain term.
	This overestimation is leading to spurious results in the Low NAO Model simulation.
	Functional regression is used resolve the overestimation in NCEP Climatology as follows:
	Slope (m) and Intercept (y) are determined for each month using the SOC and NCEP climatologies for 1980-1993 (High NAO)
			SOC(high NAO) = m*NCEP(high NAO) + y
			m and y are used to adjust the NCEP Climatology for 1958-1971 (Low NAO)
			Predicted NCEP (low NAO) = m*NCEP(low NAO) y, also
			Predicted NCEP (high NAO) = [SOC(high NAO)-y] / m

Calibrating NCEP with SOC

Readjusting NCEP

Improved Results

Improved Results

Present and Future

	1/6 degree simulations will be completed by December 2006
	High-resolution field generation (ROMS + FORMS)
	Biological model simulations
	Computational platforms – SGI Altix 350 (8p) at SMAST; NOAA (FSL) at Colorado (64p); NASA Columbia and Palm Clusters

Possible high resolution fields

	Use Feature oriented regional modeling system (FORMS) for GOMGB (Gangopadhyay et al., 2003)
	270 non-dimensional structure functions for temperature and salinity along and across seven features in the Gulf/Bank
	Calibrate with SST 5-day composite (BisagniŐs lab)
	Use basin-scale simulations as background
	Multiscale Objective analysis will meld basin-to-regional scale fields
	Use these high-resolution fields for biological simulations

ROMS & FORMS – A Synthesis

ROMS + FORMS Basin-Scale + Regional Synoptic fields

Proposed Biological simulations

	Individual-based models (HPB)
	Lagrangian pathways
	Zooplankton data as initial and validation fields (DG)
	Seeding vs. production hypothesis testing
	Impact of Labrador water inflow on Slope sea and GOMGB regions

Summary

	NASA-funded Basin-scale simulation is in progress
	Wind forcing fields during 1988-1999 are ready
	Will use this set-up to start GLOBEC period simulations
	Biological IBM towards understanding impact of climate and BSV on calfin seeding and production

Bio-physical Hypotheses

	Hypothesis: The occurrence of large populations of Calanus finmarchicus in the coupled GB/GoM system REQUIRES (1) high seed stocks (supply) of diapausing C.finmarchicus in the deeper ocean regions nearby (GOM basins and the Slope Sea), (2) that the deep C. finmarchicus stocks terminate diapause at the appropriate time to be synchronous with continental shelf spring blooms, and (3) a nutrient enriched, highly productive ecosystem in the GB/GoM to sustain high growth and survival rates of Calanus that will provide seed for the subsequent year.
	Prediction A: Overwintering Calanus finmarchicus seed stocks are LOW and GB/GoM productivity is HIGH when the water masses of the Slope Sea have little influence (input) from Labrador-Irminger Gyre (Labrador Slope Water) water masses (due to the relatively nutrient replete bottom waters and low Calanus supply in Warm Slope Waters), but C. finmarchicus recruitment is good because of a near-perfect match between the time of diapause awakening and the time of the spring bloom, the latter of which is large because of the higher concentration of nutrients in deep warm slope waters.
	Prediction B: Overwintering C.  finmarchicus seed stocks are HIGH and GB/GoM productivity is LOW when the water masses of the Slope Sea have a large proportion of Labrador Sea water (due to the relatively nutrient-depleted bottom waters and high C. finmarchicus supply in cold Labrador Slope Water), but  recruitment and productivity are poor because of the generally low springtime productivity (low nutrients) and a timing mismatch between diapause awakening, ascent and reproduction and the NW Atlantic spring bloom.

Methodology

	Set up and run an individual based model (IBM) for the Northwest Atlantic, using the high-NAO (1980-1993) and low-NAO (1962-1971) forced physical fields from an ongoing eddy-resolving North Atlantic simulation.
	Perform a set of eddy-resolving basin-scale model simulations during 1988-1999 starting from already existing high-NAO simulations (from the ongoing NASA project) and run the IBM to study the interannual variability of C. finmarchicus seeding and production in this region.
	Analyze long-term in-situ physical and biological datasets and satellite-derived sea surface temperature (SST) along with in-situ physical, biological, and chemical data collected during the GLOBEC core-measurement period (1995-1999), and validate the basin-scale physical and biological fields to develop a broader understanding of C. finmarchicus seeding and production.
	Generate four-dimensional high-resolution (5-km) physical fields using basin-scale fields and available data during 1993-1999, and run a series of IBM simulations at higher resolution  in order to address questions relating ecosystem variability on the Scotian Shelf, on Slope Sea and within the Gulf of Maine and on Georges Bank to the large-scale fluctuations of the NAO.