Temporal scales of coastal variability and land-ocean processes J. Salisbury, J. Campbell, D. Vandemark, A. Mahadevan, B. Jonsson, H. Xue, C. Hunt.

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Presentation transcript:

Temporal scales of coastal variability and land-ocean processes J. Salisbury, J. Campbell, D. Vandemark, A. Mahadevan, B. Jonsson, H. Xue, C. Hunt

miss2 Slides for discussion: Temporal scales of coastal variability and land-ocean processes

Issues –Land fluxes daily variability –Phytoplankton - respiration –Production/sinking dynamics –Tides –Storms –Fronts –Probability of MODIS imagery in GOM?

Wayne Esaias Oceanus, 1981

U.S. Geological Survey Marine and Coastal Geology Program

% Coverage per image MODIS coverage in the Gulf of Maine All data Jonsson, Salisbury Mahadevan, 2007

% Coverage per image MODIS coverage in the Gulf of Maine > 30% Jonsson, Salisbury Mahadevan, 2007

% Coverage MODIS coverage in the Gulf of Maine > 60% Jonsson, Salisbury Mahadevan, 2007

Cruise days (in red) where we had >25% satellite coverage

miss2

Process studies: the case for staring

Relationship Between River Inputs and Coastal Ecosystem Properties Satellite evidence points towards linkages between high chlorophyll and river outflow 3 May 2004

Relationship Between River Inputs and Coastal Ecosystem Properties Relationship between river DIN flux and satellite-derived chlorophyll Eastern Box Western Box Source: Lohrenz et al. (2008)

Mao et al., 2005 (JGR)

DOC concentrations vs. EVI Ipswich MA

Station Data

Short-term changes of bio-optical properties

Backscattering and Chl-a December 2004January 2005

Backscattering and Chl-a Power spectra

Short-term changes in cyanobacteria bloom size

Addressing horizontal motion in remotely sensed data: Lagrangian tracking of satellite products with a numerical model: NASA-NNH07ZDA001N-Carbon J.Salisbury (PI), A. Mahadevan, B. Jonsson, J.Tweddle and D. Vandemark.

Jonsson, Salisbury, Mahadevan, Campbell, (2008a, 2008b) POC t1 POC t2 (POC t2 - POC t1 ) (t2 - t1)  DIC uptake Ocean color (MODIS) derived POC tracked over “Lagrangian” space-time Same premise: to the first order:  POC PHYTO ≈  DIC uptake ≈ NCP

More assumptions: 1. For this exercise, phytoplankton POC PHYTO : Chl was constant (~60:1)* 3. Sinking, vertical mixing and phyto DOC are minimal, over short (2-7 day) time scales 2. Depth of integration was Kd 490nm -1

Methods: 1. Characterize advection in 2 dimensions using a circulation model

Methods: Seed the model with satellite-derived POC (POC based on chlorophyll shown)

POC at t 2 (+ 5 days) POC at t 1 Estimate the difference in a Lagrangian frame of reference

Jonnson et al., numbers are reasonable (relative to Salisbury et al, 2009) - seasonal variability is correct - slightly above zero (inferred heterotrophic) over 3 years Median NCP - we need to try this in an area with less clouds The results provide estimates of Gulf of Maine NCP over 3 years

Results are promising but we need to address: - We need phytoplankton carbon from space! - Mixing, advection (vertical and horizontal) - Air-sea exchange of CO 2 - Disparate ocean color and SST data sets One broad conclusion for both topics: Satellite color data contain valuable information about the temporal and spatial dynamics of DIC uptake in the surface ocean.

This research is supported by: NASA NASA-NNH07ZDA001N-Carbon NASA - NNX06AE29G -NIP - and NOAA NOAA NA05NOS Thanks!

Our Lagrangian analysis methods also provide a realistic time- space interpolation.

Interpolation of a MODIS chl row over 5 days Linear Time (5days) Longitude Lagrangian

Results from Chalk-ex related to GEOCAPE: highlighting rapid rates of dispersion of inanimate chalk particles in a Slope environment William M. Balch, Bigelow Laboratory for Ocean Sciences, POB475, McKown Point Rd, W. Boothbay Harbor, ME 04575

Chalk particles have slow sinking rates are optically active…

Mass of chalk

Area of chalk patch