Using MM5 to Hindcast the Ocean Surface Forcing Fields over the Gulf of Maine and Georges Bank Region*

Chen, Changsheng; Beardsley, Robert C.; Hu, Song; Xu, Qinghai; Lin, Huichan

doi:10.1175/jtech-1682.1

Cited by 39 publications

(35 citation statements)

References 28 publications

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“…The wind forcing was the bi-monthly averaged wind stress over GB, which was estimated from a 27-year meteorological model hindcast (Table 1). That hindcast was conducted using the GoM meso-scale meteorological model (MM5) (Chen et al, 2005(Chen et al, ) for 1978(Chen et al, -2004, with assimilation of all available buoy measurements. To estimate variations in the nutrient flux due to the temporal fluctuations of wind stress, we also drove the model with inclusion of the wind stress variation determined by the standard deviation calculating from hourly wind stress during each bi-monthly period (Table 2).…”

Section: Experiments #4mentioning

confidence: 99%

Tidal pumping and nutrient fluxes on Georges Bank: A process-oriented modeling study

Townsend

Chen

et al. 2008

Journal of Marine Systems

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Process-oriented studies with the unstructured-grid, three-dimensional Finite-Volume Coastal Ocean Model (FVCOM) of Georges Bank were used to examine the importance of physical processes on the cross-isobath transport of nutrients onto the Bank. Starting from idealized vertical profiles of NO 3 constructed from summertime climatologic fields, the nutrient field was integrated in time using a conservative tracer equation with both homogenous and stratified initial hydrography and both tide and wind forcing. The model results reveal that: a) nutrient fluxes are spatially inhomogeneous, with the greatest nutrient flux generated by tidal pumping into surface waters along the edge of the Bank's northern flank; b) a surface nutrient maximum occurs on the northeast flank as a result of advection along the northern edge and bifurcation of the flow as waters circulate clockwise and spread laterally around the eastern portion of the Bank; c) advection enriches nutrient concentrations downstream and around the Bank, generating a donut-shaped pattern of elevated nutrients; and d) waters on the top of the Bank, especially in the southwest portions, experience the lowest nutrient flux rates. The length of time required to reach a quasi-equilibrium state of nutrient distribution over the Bank is controlled primarily by tidal advection, with cross-frontal fluxes modulated by stratification, surface wind stress, and the initial nutrient concentration in the Gulf of Maine source waters.Published by Elsevier B.V.

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Section: Experiments #4mentioning

confidence: 99%

Tidal pumping and nutrient fluxes on Georges Bank: A process-oriented modeling study

Townsend

Chen

et al. 2008

Journal of Marine Systems

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“…NECOFS is a coupled atmospheric-ocean model system, with a mesoscale meteorological model (MM5 or WRF) [Chen et al, 2005] for surface forcing, the Gulf of Maine FVCOM (GoM-FVCOM) [Chen et al, 2011] for oceanic currents, temperature and salinity; and SWAVE [Qi et al, 2009] for surface waves. MM5 is the fifth-generation NCAR/Penn State non-hydrostatic mesoscale model [Dudhia et al, 2002] and WRF is the Weather Research and Forecast model [Skamarock et al, 2008].…”

Section: Necofsmentioning

confidence: 99%

Surface circulation in Block Island Sound and adjacent coastal and shelf regions: A FVCOM-CODAR comparison

Sun

Chen

Beardsley

et al. 2016

Progress in Oceanography

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CODAR-derived surface currents in Block Island Sound over the period of June 2000 throughSeptember 2008 were compared to currents computed using the Northeast Coastal Ocean Forecast System (NECOFS). The measurement uncertainty of CODAR-derived currents, estimated using statistics of a screened nine-year time series of hourly-averaged flow field, ranged from 3-7 cm/s in speed and 4°-14° in direction. The CODAR-derived and model-computed kinetic energy spectrum densities were in good agreement at subtidal frequencies, but the NECOFS-derived currents were larger by about 28% at semi-diurnal and diurnal tidal frequencies. The short-term (hourly to daily) current variability was dominated by the semidiurnal tides (predominantly the M 2 tide), which on average accounted for ~87% of the total kinetic energy. The diurnal tidal and subtidal variability accounted for ~4% and ~9% of the total kinetic energy, respectively. The monthly-averaged difference between the CODAR-derived and model-computed velocities over the study area was 6 cm/s or less in speed and 28° or less in direction over the study period. An EOF analysis for the low-frequency vertically-averaged model current field showed that the water transport in the Block Island Sound region was dominated by modes 1 and 2, which accounted for 89% and 7% of the total variance, respectively. Mode 1 represented a relatively stationary spatial and temporal flow pattern with a magnitude that varied with season. Mode 2 was characterized mainly by a secondary cross-shelf flow and a relatively strong along-shelf flow. Process-oriented model experiments indicated that the relatively stationary flow pattern found in mode 1 was a result of tidal rectification and its magnitude changed with seasonal stratification. Correlation analysis between the flow and wind stress suggested that the cross-shelf water transport and its 3 temporal variability in mode 2 were highly correlated to the surface wind forcing. The mode 2 derived onshore and offshore water transport, and was consistent with wind-driven Ekman theory.The along-shelf water transport over the outer shelf, where a large portion of the water flowed from upstream Nantucket Shoals, was not highly correlated to the surface wind stress.

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“…1) from September 1 to December 10 for each year. MM5 is a meso-scale meteorological model developed by Dudhia et al (2003) and configured to the GoM by Chen et al (2005).…”

Section: Box Model Setup Mixed Layer Box Biological Modelsmentioning

confidence: 99%

“…Biological parameters used in NP, NPZ, and NPZD baseline models. N: nitrate, P: phytoplankton, Z: zooplankton, D: detritus in the box model, the surface light intensity used in the 1D models varies with time using the shortwave radiation time series at Stn A from the MM5 model (Chen et al 2005). For the FVCOM-NPZD ex periments, the initial condition for the nitrate concentration was specified as Type-2, and the initial conditions for phytoplankton, zooplankton, and detritus were specified as the small amount of 0.01 μM N (phytoplankton, zooplankton and detritus are measured in terms of nitrogen).…”

Section: Seawifs Chlorophyll Datamentioning

confidence: 99%

“…1) from September 1 to December 10 for each year. MM5 is a meso-scale meteorological model developed by Dudhia et al (2003) and configured to the GoM by Chen et al (2005).Nitrogen is assumed to be the limiting nutrient for the fall bloom, which is usually dominated by smaller, non-diatom species (O'Reilly & Busch 1984). We integrated the models starting from August 31 in each instance.…”

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Effects of surface forcing on interannual variability of the fall phytoplankton bloom in the Gulf of Maine revealed using a process-oriented model

Hu¹,

Chen²,

Ji³

et al. 2011

Mar. Ecol. Prog. Ser.

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SeaWiFS (Sea-viewing Wide Field-of-view Sensor) chlorophyll data revealed strong interannual variability in fall phytoplankton dynamics in the Gulf of Maine, with 3 general features in any one year: (1) rapid chlorophyll increases in response to storm events in fall; (2) gradual chlorophyll increases in response to seasonal wind-and cooling-induced mixing that gradually deepens the mixed layer; and (3) the absence of any observable fall bloom. We applied a mixed-layer box model and a 1-dimensional physical-biological numerical model to examine the influence of physical forcing (surface wind, heat flux, and freshening) on the mixed-layer dynamics and its impact on the entrainment of deep-water nutrients and thus on the appearance of fall bloom. The model results suggest that during early fall, the surface mixed-layer depth is controlled by both wind-and coolinginduced mixing. Strong interannual variability in mixed-layer depth has a direct impact on short-and long-term vertical nutrient fluxes and thus the fall bloom. Phytoplankton concentrations over time are sensitive to initial pre-bloom profiles of nutrients. The strength of the initial stratification can affect the modeled phytoplankton concentration, while the timing of intermittent freshening events is related to the significant interannual variability of fall blooms. KEY WORDS: Fall phytoplankton bloom · Surface forcing · Freshening · Interannual variability · Gulf of Maine · Modeling Resale or republication not permitted without written consent of the publisherMar Ecol Prog Ser 427: 2011 deep nutrients into the upper water column, where light is not limiting. While the fall bloom is mainly composed of the smaller-sized phytoplankton groups (dino flagellates) (O'Reilly & Busch 1984) rather than larger diatoms that are common in the spring bloom, the importance of the fall bloom to overall ecosystem structure and function can be significant. Greene & Pershing (2007) have speculated that climate changeinduced freshening at higher latitudes could enhance downstream phytoplankton blooms in the fall, which, in turn, could affect zooplankton dynamics in the region. The interannual variability of the fall bloom might also have important implications for populations at higher trophic level. For instance, Friedland et al. (2008) linked the fall bloom to haddock recruitment on Georges Bank, arguing that the intensity of the fall bloom influences maternal well-being and egg viability the following spring, although the detailed mechanisms remain to be further examined.Our key question here is: What are the mechanisms and physical-biological dynamics controlling the interannual variability of fall phytoplankton blooms? If, for example, the erosion of stratification and the concomitant nutrient flux are the triggers of the bloom, one would expect that both local forcing (such as wind and cooling) and remotely controlled surface freshening can result in interannual variations in phytoplankton development. This can be modified further by storm events that c...

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Using MM5 to Hindcast the Ocean Surface Forcing Fields over the Gulf of Maine and Georges Bank Region*

Cited by 39 publications

References 28 publications

Tidal pumping and nutrient fluxes on Georges Bank: A process-oriented modeling study

Tidal pumping and nutrient fluxes on Georges Bank: A process-oriented modeling study

Surface circulation in Block Island Sound and adjacent coastal and shelf regions: A FVCOM-CODAR comparison

Effects of surface forcing on interannual variability of the fall phytoplankton bloom in the Gulf of Maine revealed using a process-oriented model

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