The upper ocean response of the MBRS to Hurricane Mitch: Integrating remote
sensing data with a triply nested-grid modeling system
Jinyu Sheng, Department of Oceanography, Dalhousie University,
Halifax, Nova Scotia, Canada B3H 4J1
1.IMARS, College of Marine Science, University of South Florida, St. Petersburg, FL
33701 USA 2.Department of Oceanography, Dalhousie University, Halifax, NS B3H
4J1, Canada 3.Institude de Researche pour le Developpement, BP A5-98848 Noumea
cedex, Nouvelle Caledonie 4.Marine Ecosystem Research, Cape Breton University,
Sydney, NS B1P 6L2, Canada
Abstract
The impact of the category 5 Hurricane Mitch (1998) on the upper ocean of the
Meso-American Barrier Reef System (MBRS) is investigated using a triply
nested-grid modeling system and remote sensing data. The nested system is forced by
6-hourly NCEP wind stresses for the first 294 days, and then by an idealized storm
wind forcing associated with Hurricane Mitch in the following 20 days. The nested
system is also forced by the monthly mean surface heat, and by fresh water fluxes.
The low salinity and extent of estuarine waters along the northern coast of Honduras
and the Belize shelf are specified based on SeaWiFS ocean color data. [Liang: I am
not clear on this. I thought you said SeaWiFS-derived salinity was used ONLY to
validate the model, and NOT used to specify the input of the model?] The nested
system generates strong divergent surface currents, intense near-inertial currents in
the wake of the storm, and sea surface temperature cooling biased to the right of the
storm track. [so what? Are these real? Or can we at least say: These results are
consistent (or agree) with something…] The modeling system also produces a strong
estuarine jet (low-salinity plume) extending from the coast to the deep ocean off
Honduras, which is consistent with SeaWiFS-derived salinity observations shortly
after the passage of Hurricane Mitch.
1. 1. Introduction
[Need to include a figure – perhaps a zoom-in image of Fig. 1 – to show these
locations; also useful for later references – the results section has many location
names that a reader may have no clue] The Meso-American Barrier Reef System
(MBRS), situated in the Mexico-Belize- Guatemala-Honduras coastal and shelf
regions, is one of the large-scale coral ecosystems in the Atlantic Ocean. Its immense
contributions to the stabilization and protection of coastal landscapes, maintenance of
coastal water quality and commercial value greatly benefit several million people
living in the adjacent coastal areas. However, coral reefs in the MBRS have been
affected by various natural and human disturbances and stresses in the region over the
last 30 years, including hurricanes, disease outbreaks, over exploration of coral reefs
sources by human beings, ecosystem contamination through land-based sources of
pollution and natural calamity from global warming. The impacts includes epidemics
of coral disease, coral bleaching, overgrowth of macro-algae, decimation of fish
populations and intense as well as widespread physical destruction.
The MBRS is significantly influenced by the subtropical gyre circulation in the west
Caribbean Sea. However, in-situ current measurements were rarely conducted on the
MBRS [Ezer et al., 2005]. The historical observations compiled by Craig [1966]
demonstrate that there are two offshore flows on the MBRS. One is northwestward
offshore flow as part of the Caribbean Currents (also called the Yucatan Current in the
north portion). Another is a southward flow along the Belize shelf and a cyclonic
circulation in the Gulf of Honduras (GOH). Fratantoni [2001] also analyzed the tracks
of two drifters deployed at 15 m depth of the west Glover’s Reef and east of Sapodilla
Cays on the MBRS. The drifter experiment data show a south moving, then eastward
trajectory for the first drifter following a cyclonic Gyre in the GOH. By contrast, the
second one moved northward about 200 km in 20 days. Ezer et al. explained that the
above two field observations show a contradiction of flow direction from Glover’s
Reef (south side) through the passage between Turneffe Islands Atoll and Lighthouse
Reef, which may indicate a change in the flow patterns due to seasonal changes, wind
or mesoscale variability, and a numerical study is needed. Despite that a lot of
numerical modeling work has been implemented to study circulation changes and
flow variability for the Caribbean Sea and the adjacent areas, there is less modeling
work for detailed circulations on the MBRS. Sou et al. [1996], Sheng and Tang [2003,
2004], Tang et al. [2006], Oey et al. [2005], Romanou et al. [2004] and Ezar et al.
[2003, 2005] used different ocean models to study the large-scale circulation in the
Caribbean Sea and the Gulf of Mexico, including the effects of tides and hurricane
storms. Among them, Sheng et al., Ezer et al. and Tang et al. focus on the western
Caribbean Sea and the MBRS. Sheng and Tang (2004) studied the circulation over the
MBRS using a two-level nested-grid model with a fine-resolution (about 6 km) inner
model imbedded inside the coarse-resolution (20 km? Note: in the conclusion you
said it is 19 km!) model for the western Caribbean Sea [Sheng and Tang, 2003]. Tang
et al. used a triply nested-grid z-level modeling system with different horizontal
resolutions of 20 km, 6 km and 2 km to study circulation and hydrodynamic
connectivity associated with the reef atolls on the Belize shelf. The nested system
reproduced reasonably well the mean circulation (including the cyclonic circulation in
the GOH) and the seasonal variations. By using a three-dimensional model (based on
POM [spell out]) with a variable horizontal resolution ranging from 3 km along the
MBRS to 8 km on the open boundary, Ezar [Ezer?] et al. examined the influence of
topography, circulation, wind, density and eddies on the flow along the MBRS and
explain the physical processes associated with the observed reversal flows among
Turneffe and Lighthouse Reefs and Gloves Reefs described by Craig and Fratantoni
respectively.
Despite the pioneering model simulations, responses of the upper ocean of the MBRS
to major storms or hurricanes have not been studied. Here we examine
storm-induced circulations as well as temperature and salinity variations in the upper
ocean of the MBRS using Hurricane Mitch as an example.
Hurricane Mitch is one of the most disastrous storms in history in the north Atlantic
Ocean. It swept through the southern MBRS from late October to early November in
1998 and resulted in the regionwide death toll more than 9000. Hurricane Mitch also
caused the massive rainfall, land sliding and coastal flooding along the
Belize-Guatemala-Honduras-Nicaragua coast. Mitch was upgraded from a tropic
depression into a hurricane storm in the southern Caribbean Sea (76.1W, 11.6N) on
22 October with the minimum surface pressure of 1002 mb and the maximum wind
speeds of 30 knots. Thereafter, the storm was strengthened to a Saffir-Simpson
category-5 hurricane storm by October 26 with the maximum sustained wind speeds
of 155 knots and the minimum surface pressure of 905 mb over the southwest
Nicaragua Rise (83.1W, 16.9N). From October 27, the storm started to skirt the
northern coast of Honduras and generated the anomalous precipitation, significant
coastal flooding and landsliding. Hurricane Mitch made landfall over Honduras
during the morning of the 29th October with the maximum wind speeds of 85 knots
and a minimum central pressure of 970 mb. After landing Mitch was downgraded to a
tropical depression and moved slowly from southward to westward and entered the
Gulf of Mexico on November 2, 1998 (Figure 1)..
It should be noted that various numerical studies have been conducted in the past to
examine storm-induced circulations in other coastal and open oceans. Leipper [1967],
Geisler [1970], Chang and Anthes [1978], Csanady [1982] Greatbatch [1983], Brink
[1989] and Dickey [1998] etc. used various models to simulate the upper ocean
response to extreme storm events. The model parameterizations associated with wind
stress and vertical mixing are also discussed in these studies. Geisler [1970]
investigated the linear dynamics of the ocean response to a moving storm without
considering mixed layer effects. Price [1981] suggested to parameterize the vertical
eddy viscosity and diffusivity coefficients in the upper ocean in terms of the mean
velocity difference across the base of the mixed layer. With such assumption, these
numerical models reasonably produce the rightward bias of the upper ocean response
to a moving storm. Following Price’s method, Zhai et al. [2004] studied
storm-induced inertial oscillations associated with a moving storm on a step-shelf in
the northwest Atlantic Ocean. Sheng et al. [2006] studied storm-induced circulations
on the Scotian Shelf during Hurricane Juan using a nested-grid ocean model. All of
these studies demonstrate that the upper ocean response to a moving storm can be
characterized as the intense inertial oscillations and sea surface temperature cooling in
the wake of storm biased to the right of the storm track, strongly depending on the
hurricane translation [transition?] speed.
Here we follow Tang et al. and use a triply nested-grid modeling system to study
circulations during Hurricane Mitch in 1998. Following this introduction, next section
discusses the remote sensing data used in this study. Section 3 describes the triply
nested-grid modeling system for the MBRS based on the smoothed semi-prognostic
mothod [Greatbatch et al., 2004; Sheng et al., 2005]. Section 4 presents the model
results, including near-surface and sub-surface currents and SST cooling over the
MBRS during Hurricane Mitch. Section 5 compares the model-simulated river plumes
with the remote senseing data on the MBRS after the passage of Hurricane Mitch, and
assesses the model skills in reproducing the strom-induced circulation. Finally, a brief
summary and discussion is presented in Section 6.
2. 2. Remote Sensing Data during Hurricane Mitch
[moved to introduction]
Large-scale ocean observations by means of remote sensing provide critical
information for the initialization and verification of atmosphere and ocean numerical
models [Ishizaka, 1990]. In this study, we will use remote sensing data to
parameterize the low salinity water to provide boundary condition and validation of
the nested circulation model.
Because of the cooling effect, significant drops in sea surface temperature (SST),
typically from 1 to 6oC, have been reported (Jordan, 1964; Wright, 1969; Fedorov et
al., 1979; Pudov et al., 1979; Smith, 1982; Cornillon et al., 1987; Nelson, 1996). We
examined SST imagery from the Advanced Very High Resolution Radiometer
(AVHRR) and TRMM Microwave Imager (TMI) during Hurricane Mitch for the
study region. Unfortunately, due to the significant cloud cover and precipitation, there
is no valid data for the study region. We therefore used ocean color data from the
Sea-viewing Wide Field-of-view Sensor (SeaWiFS) in this study.
SeaWiFS high-resolution (1.1 km/pixel at nadir) data were captured and processed
using the software package SeaDAS4.4 at the University of South Florida. After
several rounds of reprocessing to incorporate calibration and algorithm updates, the
data products are considered of science quality (McClain et al., 2004). Images from an
earlier processing were used to demonstrate the water circulation patterns around
MBRS (Andrefouet et al., 2002). [actually Figure 2 doesn’t appear necessary] As an
example, Figure 2 shows the contrast between chlorophyll-a concentration images
before (Fig. 2a) and after (Figs. 2b-2d) Hurricane Mitch. On 24 October when Mitch
was still far away the turbid water was restricted to the Honduras coast and Belize
shelf. After Mitch, the turbid plume extended from the northeast coast of Honduras to
the deep ocean, the Bay Islands (150 km, eastward, Figure 2b), and further north to
the Belize shelf on 3 November (Figure 2c). .
The nested model cannot model chlorophyll. However, it is able to model salinity.
Therefore, it is desirable to use surface salinity distribution maps derived remote
sensing data to tune and validate the model performance. Numerous studies have
documented the inverse relationship between surface salinity and absorption
coefficient of colored dissolved organic matter (aCDOM, m-1), and the latter can often
be derived from satellite ocean color data (e.g., Ferrari and Dowell, 1998; D’Sa et al.,
2002; Hu et al., 2003; Hu et al., 2004). Although this technique is not mature, and in
particular there is no in situ data around MBRS to tune the relationship between
salinity and aCDOM, as a first attempt we derived salinity from SeaWiFS data in the
following way.
SeaWiFS spectral remote sensing reflectance data in the visible bands (412, 443, 490,
510, 555, and 670 nm, respectively) were used to derive the backscattering coefficient
(bbp) of detritus (a sum of all non-living particles) and the total absorption coefficient
of CDOM+detritus (i.e., aCDM = aCDOM + aD) using a quasi-analytical algorithm (Lee
et al., 2002). Then, to derive aCDOM from aCDM, an empirical equation was used to
estimate aD as: aD(440) = 2.075x(bbp(555))1.02 (n=110, r=0.89, 0.001 < aD(440) <
0.12). The empirical relationship was derived from field data collected from 8
oceanographic cruises on the west Florida shelf in 2000 and 2001 (Jennifer
Cannizzaro, University of South Florida, unpublished data). After the removal of
aD(440) from aCDM(440), aCDOM(440) was converted to salinity as: salinity = 36.1 10xaCDOM(440) (0 < aCDOM(440) < 3.61 m-1). The conversion was based on limited
field data collected in SW Florida coastal waters and is subject to uncertainties off the
Honduras coast and Belize shelf because there is no in situ data to tune the empirical
relationship between salinity and aCDOM(440). However, we emphasize that our focus
is to see if the model can reproduce the general salinity patterns rather than the
absolute salinity values derived from SeaWiFS.
3. 3. The Ocean Circulation Model Setup and External
Forcing
1. 3.1 The Triply Nested-Grid Modeling System
[I leave this section to Jinyu]
The triply nested-grid circulation modeling system used in this study was constructed
from a primitive-equation z-level model known as CANDIE [spell out] [Sheng et al.,
1998]. CANDIE has been successfully applied to address various problems on
continental shelf seas, including wind-driven circulations over an idealized coastal
canyon [Sheng et al., 1998], a density-driven coastal current [Sheng,2001], tidal
circulation in the Gulf of St. Lawrence [Lu et al., 2001], and seasonal circulation in
the northwestern Atlantic Ocean [Sheng et al., 2001]. Most recently, CANDIE has
been applied to the west Caribbean Sea by Sheng and Tang [2003,2004] and Tang et
al. [2006], Lunenburg Bay of Nova Scotia by Sheng and Wang [2004] and Wang et al.
[2006] , and Lake Huron and Georgian Bay by Sheng and Rao [2006].
The nested system in this study includes three major components: the
coarse-resolution outer model (about 19 km) covering the west Caribbean Sea (WCS)
(72[EQUATION]W-90[EQUATION]W, 8[EQUATION]N-24[EQUATION]N), the
intermediate-resolution middle model (about 6 km) covering the MBRS and Yucatan
Strait
(84[EQUATION]W-89[EQUATION],
15.5[EQUATION]N-20[EQUATION]N), and the fine-resoluition inner model (about
2
km)
covering
the
north
coast
(85[EQUATION]W-88[EQUATION]W,
of
Honduras
and
Bay
Islands
15.6[EQUATION]N-17[EQUATION]N).
(Figure 3) The time steps are set to about 14.4 minutes in the outer model, 5.5 minutes
in the middle model and about 2.2 minutes in the inner model, respectively. The
nested system uses the digital bathymetry database of 2-minute resolution (DBDB2)
developed by the Ocean Dynamics and Prediction Branch, the Naval Research
Laboratory of the United States [Dong-Shan Ko, personal communication, 2003;
[EQUATION]]. Three subcomponents of the nested system have the same 28
unevenly spaced zlevels with the fine-resolution zlevel of 2 m for top ten sea levels
and relatively coarse-resolution zlevels of about 500 m near the bottom. The centers
of zlevels are located respectively at 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 25, 40, 75, 140,
230, 340, 450, 575, 725, 900, 1250, 1750, 2250, 2750, 3250, 3750, 4250, and 4750 m.
Choosing such domains of middle and inner models is due mainly to the geographic
location of the MBRS in the Mexico-Belize-Honduras coast of the west Caribbean
Sea and the significant impact of Hurricane Mitch (1998) on the Honduras coast and
the Belize shelf.
The nested system uses the vertical mixing scheme suggested by Price et al. [1981]
for vertical eddy viscosity and diffusivity coefficients [EQUATION] and
[EQUATION]. In this scheme a scale velocity ([EQUATION]) defined as the
magnitude of the mean velocity difference across the base of the ocean mixing layer is
used to parameterize vertical mixing. The readers are referred to Sheng et al. [2005]
for detailed discussion about advantage of this scheme applied to simulation of upper
ocean response to a moving hurricane storm. The horizontal mixing scheme of
Smagorinsky [1963] is used to parameterize the horizontal eddy viscosity coefficient
[EQUATION] and diffusivity coefficient [EQUATION] which are related to model
grid spacing ([EQUATION], [EQUATION]), and velocity shear and strain in the
eastward and northward directions. Since the Smagorinsky scheme is resolution
dependent, the parameterization of horizontal mixing in three subcomponents of the
nested system is different. The nested system also uses the fourth-order numerical
[Dietrich, 1997] and Thuburn’s flux limiter to discretize the nonlinear advection terms
[Thuburn, 1996].
To exchange information between the inner and outer models and reduce the model
drift we follow Sheng et al. [2001, 2005] and Greatbatch et al. [2004] and use the
two-way nesting technique based on the smoothed semi-prognostic method developed
by Sheng et al. A free-slip boundary condition is used at lateral solid (or closed)
boundaries in the three subcomponents of the nested system. Along the open
boundaries of each subcomponent, the normal flow, temperature and salinity fields
are calculated using adaptive open boundary conditions [Marchesiello et al., 2001].
The depth-mean normal flows across the outer model open boundaries are set to be
the monthly mean results produced by a (1/3)[EQUATION] Atlantic model based on
FLAME. [Carsten Eden, personal communication, 2003]. The outer(middle) model
results are used to specify the boundary conditions along the open boundaries of the
middle(inner) models.
2. 3.2 Model Forcing and Parameterization of Moving Storm
[this section needs to be clarified to a lay person]
We initize the nested system with January mean climatology of temperature and
salinity (TS), derived by da Silva et al. (1994) [is this correct?]. These data are based
on … [describe briefly how they are derived – from satellites? Buoys? Cruise surveys?
Or merged data?] The nested system is forced by the 6-hourly NCEP wind stresses
[describe NCEP winds – what are they? How are they derived?] and heat flux
constructed by da Silva et al. [1994] in the first 294 days. The net heat flux through
the sea surface [EQUATION] is expressed as [[EQUATION] et al., 1995]:
[EQUATION]
[what is SSTmodel? It is used as an input to calculate heat flux, but how is it derived?]
where [EQUATION] is the monthly mean net heat flux taken from da Silva et al.
[1994], SST[EQUATION] is the monthly mean sea surface temperature, and
[EQUATION] is the coupling coefficient defined as [EQUATION], where
[EQUATION] is the thickness of the top z-level, [EQUATION] is the specific head,
and [EQUATION] is the restoring time scale which is set to 10 days except for a
special area in Campeche near the Yucatan Strait where the restoring time scale is set
(1)
to 5 days. The implied value of [EQUATION] is about 35 W [EQUATION], which is
comparable to values calculated from observations [e.g. Haney, 1971]. We also
restore the model sea surface salinity to the monthly mean climatology at a time scale
of 10 days
A simple vortex is used to represent the wind stresses associated with a moving storm
during Hurricane Mitch in 1998 [Fogarty, personal communication, 2006].
[EQUATION]
where [EQUATION] is the radial ([EQUATION]) or tangential ([EQUATION]) wind
stress (positive for [EQUATION] and negative for [EQUATION] as a function of
radius and azimuth ([EQUATION]) measured counterclockwise from the right hand
side of a perpendicular line through the storm motion vector, [EQUATION] is the
maximum wind stress which is located at [EQUATION] (the term is negative for
[EQUATION]), [EQUATION] is the outer radius where [EQUATION] vanishes,
[EQUATION] is the asymmetry factor set to unit in this study. We set [EQUATION]
to 20 km and [EQUATION] to 300 km based on the satellite images for Hurricane
Mitch. [EQUATION] is determined in terms of the observed maximum sustained
wind speeds provided by the Southeast Regional Climate Center (SERCC) in the
United States. The conventional bulk formula of Large and Pond [1981] is used to
convert wind speeds to wind stresses. The drag coefficient is set to a constant value of
2.2[EQUATION]10[EQUATION] if the maximum sustained wind speeds are larger
than 33 m s[EQUATION] [Powell et al., 2003]. These parameters are used to
represent approximately the structure and intensity of Hurricane Mitch. The realistic
storm track provided by SERCC is also used to simulate the moving storm. The
instantaneous translational speeds of Hurricane Mitch are calculated based on the
6-hourly storm track data in the nested system.
4. 4. The Simulated Upper Ocean Response to Hurricane
Mitch
1. 4.1 Simulated Ocean Ccurrents
[I leave most of this section to Jinyu – to me it is too long. Being too long means no
focus]
[this first paragraph should belong to the Method section]
(2)
To simulate the Mitch-induced circulation in the west Caribbean Sea we first integrate
the nested system for 294 days with the conventional monthly-mean climatology,
surface heat flux and 6-hourly NCEP wind stresses. We then add a parameterized
vortex (described in Section 3.2) associated with a moving storm for next 20 days
(from October 22 to November 10, 1998). Low salinity waters (salinity ~ 25) of 2 m
deep are also specified at twelve river mouths along the Honduras coast and Belize
Shelf from October 22 (day 294). The thickness of the low salinity water deepens to 5
m (on day 301) with an "e-folding" temporal scale [what does this mean?] of 12 days
as Hurricane Mitch brought massive rainfall [I can’t have a clear picture on how
salinity values and depths change with time – this needs to be clarified]. The model
simulation with such parameterizations is taken as a control run [what does “control”
mean? Do you have another run WITHOUT such parameterization?].
As Mitch upgraded from a tropical depression to a hurricane storm in the Colombian
[again, annotate all names locations on fig. 1] Basin of the southern Caribbean Sea on
October 22 the maximum sustained wind speeds were about 45 knots. Figures 4a,b
show the model-simulated currents at depths of 1 m and 75 m on October 23 (day 295)
in the three sub-domains of nested system, respectively. The model results
demonstrate a near-surface divergent circulation due to the storm in the southern
Caribbean Sea with a horizontal extension of about 200 km radially in the outer model.
The calculated maximum near-surface currents are more than 1 m s[EQUATION]
around the storm center. Because the hurricane storm is still at an initial stage with
less energy penetrated into deep ocean, the sub-surface circulation at depth of 75 m is
still dominated by the monthly-mean climatology and characterized by the
conventional through-flows known as the Caribbean Current in the western Caribbean
Sea (outer model in Figure 4b). Mitch is far from the MBRS at this time and the ocean
circulation on the MBRS produced in the middle and inner models is also controlled
by the monthly-mean climatology at depth and characterized by the Caribbean
through flows and other small-scale circulations generated in the GOH near the
Honduras coast.
On October 26 (day 298), Mitch moved to the southwest Nicaragua Rise adjacent to
the MBRS and fully developed into a Categore-5 storm with the maximum sustained
wind speeds of 155 knots. The model-calculated maximum near-surface currents are
larger than 3 m s[EQUATION] near the storm center and the storm-influenced area
extends to 300 km radially in the outer model. In the meantime, the intense inertia
currents are generated in the wake of the storm with a bias to the right side of the
storm track (Figure 5a), which is consistent with the previous studies by Chang and
Anthes [1978], Price [1981] and Greatbatch [1983]. The model results also
demonstrate the storm-induced sub-surface circulation at depth of 75 m in the outer
model (Figure 5b). The calculated maximum currents at this depth are about 2 m
s[EQUATION] and southwestward on the Nicaragua Rise. In comparison with the
near-surface circulation generated by the storm the sub-surface circulation is less
influenced by Hurricane Mitch since the conventional Caribbean through-flows are
dominant in the western Caribbean Sea at this time, which indicates the significant
decay of storm-generated turbulent energy with depth. Hurricane Mitch starts to
influence the MBRS through the east and north open boundary in the middle and
inner models respectively. The near-surface currents produced in the middle and inner
models demonstrate the significant effects of the hurricane storm on the Caribbean
through-flows from 17[EQUATION]N to 20[EQUATION]N and circulation in the
GOH and the Honduras coast. The enhanced velocity of the through-flows is more
than 50 cm s[EQUATION] on average in the middle model and the near-surface
circulation patterns are adjusted by the storm in the inner model. By contrast, the
sub-surface circulation at 75 m on the MBRS has slightly been impacted by Hurricane
Mitch at this time. The model-calculated currents are very comparable to those on day
295 (three days ago) in the middle and inner models.
Hurricane Mitch approached to the Honduras coast and made landfall on October 29
(day 301) with the maximum sustained wind speeds of 85 knots. The model results
show that the near-surface divergent circulation is strongly intensified by the storm
right before landfall of Hurricane Mitch on the Honduras coast (Figure 6a). The
maximum near-surface currents calculated in the inner model are about 5 m
s[EQUATION] on the north coast of Honduras. In the middle model the
storm-induced near-surface circulation spreads northwestward and southwestward
from 18[EQUATION]N respectively. The Caribbean through-flows are significantly
strengthened by the divergent circulation on the southern MBRS and the maximum
near-surface currents produced in the outer model are more than 2 m s[EQUATION]
on the northwest MBRS and the Yucatan Strait. The model results also demonstrate
the significant influence of Mitch on sub-surface circulation at depth of 75 m at this
time (Figure 6b). The storm-generated turbulence penetrates to the deep ocean and
disturbs the local circulation generated by the monthly-mean climatology and
produces a divergent recirculation on the north coast of Honduras. The calculated
maximum currents are more than 2 m s[EQUATION] in the inner model. The
sub-surface circulations produced in the middle and outer models also demonstrate
the significant influence of the storm turbulence on the Caribbean through-flows and
longshore current on the Honduras coast (Figure 6b).
After landfall Mitch went through the inland of Honduras and Guademala and
degraded to a tropical depression on November 1 (day 304) with the maximum
sustained wind speeds of 25 knots. The intense near-surface inertial currents produced
in three sub-models strengthen the Caribbean through flows on the MBRS and the
longshore currents along the Honduras coast on day 304 (Figure 7a). The velocity of
through-flows is more than 1 m s[EQUATION] on the Belize Shelf and 1.5 m
s[EQUATION] through the Yucatan Strait. The near-surface longshore currents show
velocity larger than 30 cm s[EQUATION] on average in the inner model. The
sub-surface circulation at depth of 75 m produced in three sub-models is significantly
reduced to the previous states as the monthly-mean climatology is the dominant
forcing before Hurricane Mitch in the western Caribbean Sea and the MBRS.
2. 4.2 Simulated Sea Surface Temperature
Previous studies show that without large disturbance due to the extreme storm events
SST ranges between 25[EQUATION] - 28[EQUATION] over most western
Caribbean Sea in October and November. The Campeach Bank is cooler due to the
intense coastal upwelling, with SST around 24[EQUATION]C (Sheng et al. 2003).
Using this climatology as baseline boundary condition,
we simulated SST in this
region with and without Hurricane Mitch, and evaluated the cooling effect by
examining the difference.
Figure 8 shows the SST evolution from day 299 (27 October) to 301 (29 October)
during which Mitch upgraded to its maximum strength. Along the storm track are two
low SST pools in the western and southern Caribbean Sea on day 299 (Figure 8a).
The latter results from the long wandering of Mitch right after upgrading from a
tropical depression to a hurricane with slow transition speed for about three days
(October 22-24). The cool pool is biased to the right side of the storm track with the
minimum SST of 24[EQUATION]C. In the next three days (October 25-27) the storm
moved rapidly to the southern MBRS in the western Caribbean Sea and slowed down
again from day 299 (October 27), when a new pool of low SST occured with a right
bias to the storm track. The sea surface temperature cooling is due mainly to the
storm-generated turbulence penetrating to the deep ocean and fully mixing the upper
warm water with the deep cold water. The SST drops significantly and the lowest SST
is about 22[EQUATION]C in the pool center on the MBRS (Figure 8b). As Mitch
approached to the north coast of Honduras with the decreased translational speeds of
the storm the low SST pool further extends horizontally through day 300 and is more
biased to the right side of storm track with the lowest SST less than
22[EQUATION]C (Figures 8c,d). On day 301 (October 29), the storm was about to
make landfall and the cool pool is still in development. The model-calculated lowest
SST drops below 20[EQUATION]C near the storm center (Figure 8e,f). In the
meantime, the previous low SST pool still exists in the southern Caribbean Sea with a
gradual rise of SST. The above model results are consistent well with many previous
studies on storm-induce sea surface cooling in the ocean and shelf region. The readers
are referred to Chang and Anthes [1978] for more discussions on the rightward bias of
SST cooling associated with the rightward bias of the inertial currents behind the
storm. [Perhaps we don’t need this much detail in this paragraph]
The cooling effect is manifest in the difference (i.e., anomaly) between the above
results and those from the model simulations under “normal” conditions (i.e., without
the idealized vortex associated with Mitch) Figure 9 shows the SST difference
(anomaly) due to Mitch from day 299 to 301. The two SST cooling pools are found to
have SST anomalies of –2oC and –6 to –8oC, respectively. These results agree well
with hurricane-induced cooling values reported earlier in other regions.
5. 5. Simulated River Plume [to be consistent with
previous subtitles, just use “simulated river plume]
[this was already described in the Method section]
Figure 10 shows the simulated river plume, as compared with those from the
SeaWiFS estimates. Low salinity waters (<35.5) along the coast were well captured
by the model. Indeed, salinity measured by an oceanographic buoy in one of the atolls
dropped to 25 after Mitch (Bjorn Kjerfve, Texas A&M U, personal comm.). On 1
November (day 304) the model showed the low-salinity water on the southern MBRS,
from the Honduras coast of 85[EQUATION]W to about 18.5[EQUATION]N. The
model also showed the spreading of low salinity water eastward along the Honduras
coast from the Gulf of Honduras [annotate the image], consistent with concurrent
remote sensing data (Figure 10a). On 3 November (day 306) the modeled plume
expands further to 19[EQUATION]N and turns westward with the Caribbean
through-flows (Figure 10d). After Mitch and on 14 November (day 317, Fig. 10f), the
model showed another plume due to rainfall along the Honduras coast. This new
plume, characterized by
<35.5 salinity, extends over 17[EQUATION]N on the
southern MBRS, and then moves northwestward with the Caribbean through-flows to
the Belize Shelf. The model results also show an eastward spreading of low salinity
waters along the Honduras coast [where? I can’t see it. Perhaps you want to annotate
the flow patterns with numbers, and then you can discuss them more easily in the
text].
The modeled plume patterns as well as the salinity values are visually comparable
with those obtained from SeaWiFS observations. However, the storm-induced ocean
circulation is sensitive to topograph and mixing. The COARSE-RESOLUTION
bathymetry [2-minute grid], the idealized parameterization of the sub-grid mixing,
and the input salinity values could all affect the model performance. Although our
primary purpose is to show the first attempt to couple remote sensing data with a
nested-modeling system to study the low-salinity plume, a sensitivity analysis study
will be presented in the Appendix to show the influence of the input salinity values on
the modeled plume.
6. 6. Summary and Discussion
A triply nested-grid ocean circulation modeling system is used to simulate the
storm-induced circulation and low-salinity plume around the MBRS during Hurricane
Mitch in late October 1998. The nested system includes three components:
fine-resolution inner model (2 km), intermediate-resolution middle model (6 km), and
coarse-resolution outer model (19 km) [earlier you said it’s 20 km]. Twenty-eight
uneven zlevels were specified in the nested system, with 2 m for the top ten zlevels
and 500 m near the bottom [depth = ?]. The nested system is forced by climatological
heat flux [is this correct?], by 6-hourly NCEP wind stress, and bywind forcing from
Hurricane Mitch. The model results suggest that the maximum near-surface currents
are about 5 m s[EQUATION] under Mitch, With the storm-induced turbulence
reaching 75 m in depth.. The storm-induced intense inertial currents in the wake of the
storm show the rightward bias, resulting in the rightward-biased SST cooling.
Compared with “normal” conditions (i.e., those without the Mitch) and depending on
the location, the cooling ranged between –02 to -8[EQUATION]C, consistent with
previous findings in other regions for hurricane-induced cooling.
A novel attempt was made to simulate the SeaWiFS-observed low-salinity plume
after Mitch. Based on SeaWiFS imagery where surface salinity was derived
empirically by assuming the inverse relationship between salinity and colored
dissolved organic matter, in the nested model low salinity was specified at twelve
river mouths along the Honduras coast and Belize Shelf and was allowed to vary with
time in its value and depth, corresponding to anomalous precipitation and flooding
due to Mitch. The model produced comparable plume patterns to SeaWiFS
observations in both space and time. However, the modeled magnitude of the low
salinity values is less satisfactory, possibly due to the coarse-resolution bathymetry
(2-minute resolution), idealized sub-grid scale mixing parameterization and relatively
arbitrary low-salinity input along the Honduras coast and Belize Shelf. For example,
the sensitivity study (Appendix, Figure 11) demonstrates different plume scales with
different model parameterizations (Appendix, Figure 11).
These preliminary results demonstrate the advantage of an integrated approach
(numerical modeling + remote sensing) to assess environmental changes of a delicate
marine ecosystem (MBRS) due to anomaly events (hurricanes). Future improvements
should include higher-resolution bathymetry (which can be potentially derived from
passive remote sensing sensors, such as Landsat, for shallow, clear waters) to account
for bottom friction and should include more realistic freshwater input.
Acknowledgments
We wish to thank Chris Fogarty, Doug Mercer, ... for their useful suggestions. We
also thank ... for providing . This project is financially supported by the National
Aeronautics and Space Administration (NASA).
Appendix: Sensitivity Studies on the Influence of Input
Salinity Values on Plume Patterns
In the results shown above we specified the minimum salinity of 25 at the 12 river
mouths during Mitch. To examine the sensitivity of the simulated plume patterns on
the input salinity values, two more experiments were conducted with the minumum
salinity set to 20 (EXP I) and 28 (EXP II), respectively. Other model
parameterizations remained unchanged. Figure 11 shows the difference between EXP
I and EXP II. Although the general patterns are similar, the plumes in EXP-I appear
larger and further north, with lower salinity near the coast. The results further
demonstrate that although the general plume patterns can be modeled reasonably well
under the current parameterization, the exact size of the plume as well as the absolute
salinity values within the plume strongly depend on the salinity input, whose accuracy
can only be assured through systematic measurements.
On the figures:
Fig. 1. Add a zoom-in figure to highlight the MBRS, with all names mentioned in the
text annotated on the image, otherwise a reader may have no clue on what/where you
talk about.
Fig. 2. This figure is not necessary, because Andrefouet et al. already showed better
images. The figure caption needs to be changed if the figure is finally included.
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