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1] The year 2005 experienced several strong hurricanes intensifying in the Gulf of Mexico before making landfall that severely damaged the Gulf States, especially Hurricane Katrina. Remarkable similarities between sea surface temperature anomaly (SSTA) and major hurricane (categories 3 and higher) activity over the Gulf are identified. However, the intensification of individual hurricanes may not necessarily be temporally and spatially coincident with the distribution of warm waters or high sea surface temperature (SST). High SST values are found in advance of significant intensification of Hurricane Katrina. We emphasize that high SSTA which occurred at the right time and right place was conducive to the hurricane intensification. In particular, high SSTA in the northeastern quadrant of the storm track induced significant increases in surface latent heat fluxes (LHF) contributing to the rapid intensification of Katrina. We also compared and verified model simulations with buoy observations.
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Role of anomalous warm gulf waters in the intensification of Hurricane
Katrina
Menas Kafatos,
1
Donglian Sun,
1
Ritesh Gautam,
1
Zafer Boybeyi,
1
Ruixin Yang,
1
and Guido Cervone
1
Received 18 April 2006; revised 7 June 2006; accepted 17 July 2006; published 1 September 2006.
[1] The year 2005 experienced several strong hurricanes
intensifying in the Gulf of Mexico before making landfall
that severely damaged the Gulf States, especially Hurricane
Katrina. Remarkable similarities between sea surface
temperature anomaly ( SSTA) and major hurricane
(categories 3 and higher) activity over the Gulf are
identified. However, the intensification of individual
hurricanes may not necessarily be temporally and spatially
coincident with the distribution of warm waters or high sea
surface temperature (SST). High SST values are found in
advance of significant intensification of Hurricane Katrina.
We emphasize that high SSTA which occurred at the right
time and right place was conducive to the hurricane
intensification. In particular, high SSTA in the
northeastern quadrant of the storm track induced
significant increases in surface latent heat fluxes (LHF)
contributing to the rapid intensification of Katrina. We also
compared and verified model simulations with buoy
observations.
Citation: Kafatos, M., D. Sun, R. Gautam, Z.
Boybeyi, R. Yang, and G. Cervone (2006), Role of anomalous
warm gulf waters in the intensification of Hurricane Katrina,
Geophys. Res. Lett., 33, L17802, doi:10.1029/2006GL026623.
1. Introduction
[2] Despite large reductions in track forecast errors over
the past three decades [McAdie and Lawrence, 2000], there
has been little improvement in forecasts of storm intensity.
Observational and modeling studies have shown the signif-
icant influence of vertical wind shear on hurricane inte nsity
changes. Stron g vertical wind shear (jV
z
j) between t he
upper and lower troposphere prevents the intensification
of tropical cyclones due to the so-called ‘ventilation’ effect
of the hurricane warm core [Gray, 1968; Goldenberg and
Shapiro, 1996; Bracken and Bosart, 2000; Wong and Chan,
2004]. However, Zhu et al. [2004] found that Hurricane
Bonnie intensified simultaneously with the increase s of
vertical shear; suggesting that in addition to the magnitude
of wind shear, the direction of wind shear may as well be
significant for the intensification of hurricanes. The overall
dependence of tropical cyclone intensity on SST is well
documented [Fisher, 1958; Leipper, 1967; Emanuel, 1986,
1988; Holland, 1997], with an increase of 1K of SST
leading to a 1214 mb deepening in hurricane minimum
central pressure [Hong et al., 1995; Zhu et al., 2004]. SST
plays a fundamental role in the inter-annual variability of
tropical storm frequency and intensity [Vitart et al., 1999],
and a direct role in providing moist enthalpy (i.e., latent and
sensible heat flux) to intensify tropical cyclones [Goldenberg
et al., 2001].
[
3] The recent active period of intense hurricanes has
triggered a hot debate in the scientific community whether
the increase in the frequency and intensity of hurricanes is
due to either the natural climate variability such as the El
Nin˜o/Southern Oscillation (ENSO), quasi-biennial oscilla-
tion (QBO), and Atlantic Multidecadal Oscillation (AMO)
[Bove et al., 1998; Elsner et al., 1998; Gray, 1984; Shapiro
and Goldenberg, 1998; Goldenberg et al., 2001; Virmani and
Weisberg, 2006], or the human-induced global warming
[Knutson and Tuleya, 2004; Emanuel, 2005; Webster et al.,
2005]. Several studies suggest that global warming would
likely result in SST increase, which may result in an increase
in the inte nsity of tropical cyclones [Tsutsui, 2002; Webster et
al., 2005]. Other studies indicate the effect of warm core ring
associated with the loop current in the intensification of
hurricanes is important [Hong et al., 2000; Scharroo et al. ,
2005]. Nevertheless, they are all associated with the effects of
warm SST. At the same time, we note that not all tropical
cyclones associated with warm waters attain peak intensity
(categories 4 and 5) during their life cycle.
[
4] Specifically, the current period after 1995 has sig-
naled an active period, especially for major hurricanes
(categories 3, 4, and 5) [ Goldenberg et al., 2001]. The last
several years set records for the most intense hurricanes ever in
any given year, except for the El Nin˜o year 1997 when
hurricane occurrences wer e low. The SSTA trends over the
North Atlantic coincide well with the Atlantic Multidecadal
(50 years) Oscillation (AMO) [cf. Virmani and Weisberg,
2006]. However, as we will report later, there is evidence of
increasing trends that may be associated with global warming.
[
5] On August 23, 2005, Katrina formed into a tropical
depression (TD) from a broad area of low pressure in the
central Bahamas. Over the next few days, Katrina rapidly
intensified into a category 5 after it crossed south Florida on
August 26, 2005 and entered the warm Gulf of Mexico with
SST values over 30C. Katrina made second landfall as a
powerful category 4 storm over the southeastern Louisiana
and southern Mississippi on August 29, 2005, causing
catastrophic flooding to the city of New Orleans and the
surrounding areas, resulting in thousands of deaths.
[
6] In this study, we focus our analysis on the variations
of SST for the Hurricane Katrina case. We note the recent
increase in Gulf hurricane activity, especially for intense
hurricanes (categories 3, 4, and 5), while studies in the past
predicted only minor differences in intense hurricane activ-
ity in the Gulf [Goldenberg et al., 2001]. Furthermore, the
significant role of SST and the resulting air-sea interactions
GEOPHYSICAL RESEARCH LETTERS, VOL. 33, L17802, doi:10.1029/2006GL026623, 2006
1
Center for Earth Observing and Space Research, School of Computa-
tional Sciences, George Mason University, Fairfax, Virginia, USA.
Copyright 2006 by the American Geophysical Union.
0094-8276/06/2006GL026623
L17802 1of5
associated with the intensification of Katrina are inves-
tigated, t hrough the combination of satellite and buoy
observations along with numerical model simulations.
2. Data and Methodology
[7] The following data and methodology apply in our
study:
2.1. Data
[
8] a. SST from the tropical rainfall measuring mission
(TRMM) microwave imager (TMI) at 25 km resolution
from the Remote Sensing Systems (http://www.ssmi.com).
The advantage of using SST from microwave observations,
like the TMI, is that it provides retrievals even under intense
cloudy conditions associated with hurricanes.
[
9] b. Buoy observations of winds, SST, surface air
temperature, and dew point from the National Data Buoy
Center (NDBC) (http://www.ndbc.noaa.gov/).
2.2. Methodology
[
10] In order to investigate the impact of warm SSTA on
Katrina’s intensity variations, using the latest PSU/UCAR
mesoscale model MM5 (version 3.7), two control experi-
ments were designed. In the first experiment, SST data from
the TMI observations on August 26, 2005 were used as the
model’s initial conditions (hereafter referred to as fixed SST
or FSST). In the second experiment, a uniform 1.5C
anomaly was added to FSST in order to capture the impact
of high SST anomaly on the hurricane’s characteristics
(referred to hereafter as FSST + 1.5). We performed a
96-h simulation initialized at 00Z August 26, 2005 using
a triply nested grid configuration with grid resolutions of
54, 18 and 6 km, covering the stages of Katrina’s rapid
intensification across the Gulf and the subsequent landfall in
the northern Gulf coast. The other model’s initial and lateral
boundary conditions were obtained from the NOAA NCEP
GFS (Global Forecasting System) 1 1 global analysis.
A bogus vortex representing the inner circulation of Katrina
was used in the model initial conditions [Goerss and
Jefferies, 1994; Zhu et al., 2004]. In order to test the effect
of pre-existing warm SST, SST was held unchanged during
the simulations.
3. Warm Gulf Waters and Hurricane Katrina
[11] As shown in Figure 1, the NDBC buo y 42040
observations at South of Dauphin Island, AL (29.18N,
88.21W), located northeast of Katrina’s track (Figure 2a
shows the location of the buoy with a red star), indicated
SST over 30C in advance of about two days before Katrina
reached its strongest intensity or the maximum wind speed
(gust). However, the increase of wind speed associated with
Katrina’s intensification resulted in the decrease of SST. As
a result of evaporative cooling in the near-surface environ-
ment under warm SST (at least 27C) conditions, the surface
air temperature (Ta) decreased significantly (Figure 1a)
[Cione et al., 1999] and the sea-air temperature difference
(SST-Ta) reached its largest value at the time of the peak
hurricane intensity (Figure 1b) [Shay et al., 2000]. The
increase in air-sea temperature contrast induced the strength-
ening of atmosphere-ocean heat flux exchange. We have
computed the surface heat fluxes from the buoy observations,
including sensible heat flux (SHF) and latent heat flux (LHF)
as follows:
SHF ¼ r
a
C
p
C
s
U
10
SST T
a
ðÞ
LHF ¼ r
a
LC
E
U
10
q
s
q
a
ðÞ
ð1Þ
where q
s
is the specific humidity (gkg
1
) of the water
surface, q
a
is the specific humidity of the air near the
surface, U
10
is the surface wind speed (m/s) at 10m height,
L is the latent heat of vaporization (M Jkg
1
), and r
a
is the
surface air density (kgm
3
), Cp is the specific heat of air,
Cs and C
E
are the exchange coefficients. The calculated
SHF and LHF, with the use of constant exchange
coefficients (Cs = 0.9e 3 and C
E
= 1.35e 3), are the
strongest at the time of maximum hurricane intensity
(Figure 1c) due to the atmosphere-ocean energy exchange,
which causes storms to receive energy from warm oceans
for further intensification.
[
12] From the buoy observations, it is found that the
storm intensity changes are well correlated with the sea-air
temperature contrast (SST-Ta) and surface heat fluxes over
the time. However, buoy stations are sparse and unevenly
distributed. From the numerical model (MM5) simulations,
the spatial distribution of the maximum LHF values at the
intense stages (category 3 and up) was found to be located
at the right side of the storm track (Figure 2a), where winds
were also usually stronger (Figure 2a) and most clouds and
precipitation develop [ Zhu et al., 2004]. LHF is believed to
Figure 1. Time series of (a) wind speed, SST, and Ta,
(b) sea level pressure (SLP) and sea-air temperature contrast
(SST-Ta), and (c) surface sensible heat flux (SHF) and latent
heat flux (LHF) from buoy 42040 observations.
L17802 KAFATOS ET AL.: WARM GULF WATERS AND HURRICANE KATRINA L17802
2of5
be one of the major drivers in the hurricane energy systems
and plays a vital role in development and intensification of
tropical cyclones (TC) [Guinn and Schubert, 1993; Bender
and Ginis, 2000; Hong et al., 2000; Shay et al., 2000;
Gautam et al., 2005].
[
13] Satellite observations show the SST was unusually
warm and around 30C over the entire Gulf before Katrina’s
perturbation [Scharroo et al., 2005]. At the same time, the
SSTA from the TMI observations was more than 1C along
the hurricane track and its right side (Figure 2b). Consid-
ering the large heat capacity of the ocean, this anomaly is
very significant. It has been shown that relatively modest
changes i n SST of order 1C can effectively alter the
maximum total enthalpy (latent plus sensible heat flux) by
40% or more [Cione and Uhlhorn, 2003]. Katrina under-
went rapid intensification into category 5 when it moved
across the Gulf with high SSTA to the right side of its track
(also at the location of the maximum LHF). This may imply
high SSTA at the right side of the storm track may be a very
important factor for hurricane intensification.
[
14] The model simulations indicated that the maximum
LHF was always located at the northeastern quadrant of the
storm track, at least during the intense stages (category 3
and up), primarily due to the ambient flow relative to the
storm motion and diabetic heating resulted from the spatial
distribution of SSTA. Also, time series of LHF always
shows the largest value at the time of the hurricane’s
maximum intensity.
[
15] From equation (1), we can see that LHF depends on
both wind speed and SST, as q
s
is calculated from SST.
Increase in wind speed also enhances the LHF. In order to
distinguish the effect of SST on the LHF from wind speed,
we performed two numerical experiments in which all other
conditions, including winds, were identical, but only the
SSTs were different. As consistent with the buoy observa-
tions (Figure 1c), numerical model simulations show that
when the LHF increased and peaked during August 28 and
29, 2005, Katrina received and accumulated energy through
the ocean-atmosphere energy exchange and the central sea
level pressure (SLP) reached its lowest value and Katrina
attained its strongest intensity (Figure 3). From these two
experiments with the same wind speed but different SSTs,
we can clearly identify the effects of warm SST inducing
significant increases in LHF, especially at the stages when
Katrina underwent rapid intensification (Figure 3). While
the difference in the minimum SLP between the two experi-
ments is not evident until the 48-h simulation, when the
storm began to receive more energy supply through the air-
sea interaction processes (Figure 3), this is consistent with
the buoy observations (Figure 1).
[
16] In order to validate the model simulations, we have
also calculated surface LHF from buoy 42001 observations
according to equation (1). The exchange coefficient C
E
in
equation (1) reflects the efficiency of the vertical exchange
Figure 2. (a) MM5 simulated track, surface winds
(vectors) and LHF (W/m
2
) at 72 h simulation valid at 00Z
29, August 2005. The locations of buoys 42040 and 42001
are indicated with red stars. (b) Weekly mean (ending on
August 27, 2005) SST anomaly in relative to 8-year (1998
2005) average and the circles of different colors indicate the
observed track and intensity of Hurricane Katrina.
Figure 3. (a) Time series of MM5 simulated area-averaged
(400 km 400 km over the inner region centered on the
eye) LHF with the MRF PBL scheme and minimum SLP
from the two numerical experiments, and the observed
minimum SLP. (b) Comparison of LHF values from buoy
42001 observations using exchange coefficients from Cione
et al. [1999] and Bentamy et al. [2003] methods and MM5
simulations with Blackadar and MRF PBL schemes.
L17802 KAFATOS ET AL.: WARM GULF WATERS AND HURRICANE KATRINA L17802
3of5
of water vapor and energy flux and is affected by the
stability of the surface air. Several studies show that C
E
depends on wind speed and different empirical relationships
[Liu et al., 1979; Large and Pond, 1982; Cione et al., 1999;
Bentamy et al., 2003], while Emanuel [2005] suggests the
dependence of C
E
on temperature. Here, we performed two
experiments: In one experiment, C
E
was determined under
relatively high wind c onditions >20 m/s and increase
linearly with wind speed [Cione et al., 1999], referred as
the Cione method here:
C
E
¼ 0:75 þ 0:067U
10
ðÞ*10
3
ð2Þ
[17] While in another method, C
E
decreases with wind
speed [Bentamy et al., 2003], referred as the Bentamy
method here.
C
E
¼ a exp bU
10
þ cðÞ½þ
d
U
10
þ 1

*10
3
ð2
0
Þ
Where a = 0.146, b = 0.292, c = 2.206648, and
d = 1.6112292.
[
18] The LHF values from the Bentamy method, during
the maximum hurricane intensity (category 5), are almost
half compared to that from the Cione method, while the
differences during other times are small. The LHF values
from numerical model MM5 simulations depend on the
PBL schemes used. The Blackadar an d Medium-Range
Forecast (MRF) schemes are selected for tests here; since
they have nearly identical representations of surface fluxes
except for the exchange coefficients or the definition of the
non-dimensional stability functions are different. The LHF
values produced by the Blackadar PBL scheme [Zhang and
Anthes, 1982] are almost twice as low as those from the
MRF PBL scheme at the time of the maximum intensity,
while the differences during other stages are not evident. As
a result, the simulated intensity from the Blackadar PBL
scheme is weaker than that from the MRF scheme (not
shown). It is found that MM5 simulated LHF from the
Blackadar PBL scheme is close to that calculated from the
buoy observations using the C
E
decreasing with the wind
speed (the Bentamy method), while the MRF PBL scheme
is close to the Cione method with the C
E
increasing with the
winds (Figure 3b). Previous study by Braun and Tao [2000]
also showed the remarkable sensitivity of Hurricane Bob
(1991) to several PBL schemes in the MM5 and suggested
the dependenc e of simulated intensity on surface exchange
coefficients for heat and momentum or the parameterization
of surface fluxes. A special PBL model may be needed
especially for hurricane case.
[
19] Nevertheless, what we want to emphasize here is that
no matter what method or PBL scheme is used, the spatial
and temporal distributions of LHF are found to be similar.
The maximum LHF is always located to the right side of the
storm track at its intense stages, coincident with the location
of high warm SSTA. Time series of LHF always shows the
largest value at the time of hurricane’s maximum intensity.
4. Summary and Discussions
[20] Remarkable resemblance is found between SSTA
and the major hurricane acti vities over the Gulf. High SSTA
played an important role in the recent increase of intense
hurricane activity over the Gulf, especially after 1995.
However, the intensification of individual hurricanes may
not be spatially and temporally coincident with the distri-
bution of warm waters or high SST. This may be due to the
fact that in addition to warm SST, the spatial location of
high SST anomaly over the open ocean with respect to the
storm track is another significant factor.
[
21] Observations show Katrina intensified when it
entered the warm Gulf with SST over 30C. SST is
found to increase in advance of the intensification of
Hurricane Katrina, also confirmed by numerical simula-
tions. This is because it may need some time for a
tropical cyclone to accumulate energy for further intensi-
fication. High SSTA at the northeastern quadrant of the
storm track over the Gulf induced significant increases in
surface heat fluxes and appears to have played a vital role
in Katrina’s intensificatio n. Our present analysis combin-
ing numerical model simulations together with satellite
and buoy observations shows the significant impact of
anomalous warm Gulf waters on the rapid intensification
of Hurricane Katrina and th e r ole of high SSTA in
governing the air-sea interactions associated with the
intensification of Katrina into a category-5 hurricane.
[
22] Acknowledgments. This work was supported by the VAccess/
MAGIC project funded by the NASAs Science Applications Program, and
the NSF from grant NSF0543330. We are grateful to the reviewers for their
thorough review and helpful comments.
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... However, throughout the post-monsoon season , the accumulated cyclone energy (ACE) diminished with shifting weather conditions over India (Mohapatra and Kumar 2017). Cyclones are known to influence atmospheric, meteorological, ocean parameters, and ocean productivity (Shay et al. 2000;Kundu et al. 2001;Gautam et al. 2005;Kafatos et al. 2006;Sarkar 2017;Chauhan et al. 2021;Tang et al. 2023). The stratospheric and tropospheric exchanges are influenced by tropical cyclones, leading to ozone concentration changes (Pathakoti et al. 2016;Chauhan et al. 2018). ...
... This increase in temperature during cyclonic periods, particularly in sea surface temperature, provides the necessary energy and moisture for cyclone formation and intensification. The warm ocean water and atmospheric conditions are fundamental to the development and strengthening of cyclones (Cowell et al. 2006;Kafatos et al. 2006;Deo and Ganer 2015;Balaguru et al. 2016;Mishra and Ojha 2020). ...
... However, throughout the post-monsoon season , the accumulated cyclone energy (ACE) diminished with shifting weather conditions over India (Mohapatra and Kumar 2017). Cyclones are known to influence atmospheric, meteorological, ocean parameters, and ocean productivity (Shay et al. 2000;Kundu et al. 2001;Gautam et al. 2005;Kafatos et al. 2006;Sarkar 2017;Chauhan et al. 2021;Tang et al. 2023). The stratospheric and tropospheric exchanges are influenced by tropical cyclones, leading to ozone concentration changes (Pathakoti et al. 2016;Chauhan et al. 2018). ...
... This increase in temperature during cyclonic periods, particularly in sea surface temperature, provides the necessary energy and moisture for cyclone formation and intensification. The warm ocean water and atmospheric conditions are fundamental to the development and strengthening of cyclones (Cowell et al. 2006;Kafatos et al. 2006;Deo and Ganer 2015;Balaguru et al. 2016;Mishra and Ojha 2020). ...
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During the pre- and post-monsoon season, the eastern and western coasts are highly vulnerable to cyclones. The tropical cyclone “Tauktae” formed in the Arabian Sea on 14 May 2021 and moved along the west coast of India, and landfall occurred on 17 May 2021. During the cyclone, the maximum wind speed was 220 km/h with a pressure of 935 mb afecting meteoro- logical, atmospheric parameters, and weather conditions of the northern and central parts of India causing devastating dam- age. Analysis of satellite, Argo, and ground data show pronounced changes in the oceanic, atmospheric, and meteorological parameters associated during the formation and landfall of the cyclone. During cyclone generation (before landfall), the air temperature (AT) was maximum (30.51 °C), and winds (220 km/h) were strong with negative omega values (0.3). The relative humidity (RH) and rainfall (RF) were observed to be higher at the location of the cyclone formation in the ocean and over the landfall location, with an average value of 81.28% and 21.45 mm/day, respectively. The concentration of total column ozone (TCO), CO volume mixing ratio (COVMR), H2 O mass mixing ratio (H2 O MMR), aerosol parameters (AOD, AE) and air quality parameter (PM) was increased over land and along the cyclone track, leading to a deterioration in the air quality. The strong wind mixes the air mass from the surroundings to the local anthropogenic emissions, and causing strong mixing of the aerosols. The detailed results show a pronounced change in the ocean, land, meteorological, and atmospheric parameters showing a strong land–ocean-atmosphere coupling associated with the cyclone.
... Estas TSMs calientes fueron un factor importante para que Otis alcanzara la categoría 5 en la escala Saffir-Simpson. Este tipo de rápidas intensificaciones debido a TS-Ms mayores a 30°C han ocurrido previamente en casos como los del huracán Katrina de 2005, que interactuó con un anillo caliente del océano y por ello, desarrolló una rápida intensificación(Kafatos et al., 2006). Estas TSMs calientes responden a la presencia de El Niño. ...
Chapter
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El huracán Otis se formó el 22 de octubre de 2023 sobre aguas más cálidas a lo normal, asociadas a la presencia de la oscilación climática El Niño-Oscilación del Sur (ENOS). Otis se intensificó rápidamente en un periodo menor a 6 horas, pasando de tormenta tropical a huracán categoría 5 en la escala Saffir-Simpson. Otis ha tenido una de las intensificaciones más rápidas en el Océano Pacífico oriental, sólo por detrás de Patricia de 2015. El tamaño de Otis estuvo dentro del rango promedio, así como su velocidad de traslación. Sin embargo, sus vientos alcanzaron 268 km/h, rompiendo así récords en la intensidad del viento con que un ciclón tropical ha tocado tierra en las costas del Océano Pacífico oriental desde 1949. En este capítulo, se utilizaron datos de reanálisis de quinta generación del Centro Europeo para el Pronóstico a Mediano Plazo (ECMWF, por sus siglas en inglés) a una resolución espacial de 0.25°, datos diarios de satelitales del Proyecto de Medición Global de la Precipitación (GPM, por sus siglas en inglés) y del Proyecto del Ensamble Pesado de Precipitación proveniente de Varias Fuentes (MSWEP, por sus siglas en inglés), ambos productos tienen una resolución espacial de 0.1°, así como datos de la Capa de mezcla del Reanálisis Global de la Física Oceánica (GLORYS, por sus siglas en inglés), que tienen una resolución espacial de 0.08°, para analizar las condiciones atmosféricas y oceánicas durante los días en los que se formó Otis e ingresó a Acapulco, Guerrero. Los resultados indican que las condiciones atmosféricas y oceánicas convergieron para hacer que Otis se intensificara rápidamente, ocasionando que la principal amenaza fuera la intensidad de viento aunado con el tiempo corto de preparación para enfrentar este hidrometeoro.
... The precise time window during which a hurricane can be affected by an ocean warming event is still an area of active research and may vary depending on the circumstances. Some studies 14,82 focused on the first few days after the MHW event ends to address the strongest impact of an ocean warming event on RI event, while others 2,11 suggest that the impact may continue for several weeks or more and a sequence of vertical mixing, horizontal advection, upwelling and surface heat flux can contribute to favorable shelf conditions for RIs. In the present study, the temporal threshold is defined such that the time span of a MHW event must fall within 10 days of the beginning date of RI. ...
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Tropical cyclones can rapidly intensify under favorable oceanic and atmospheric conditions. This phenomenon is complex and difficult to predict, making it a serious challenge for coastal communities. A key contributing factor to the intensification process is the presence of prolonged high sea surface temperatures, also known as marine heatwaves. However, the extent to which marine heatwaves contribute to the potential of rapid intensification events is not yet fully explored. Here, we conduct a probabilistic analysis to assess how the likelihood of rapid intensification changes during marine heatwaves in the Gulf of Mexico and northwestern Caribbean Sea. Approximately 70% of hurricanes that formed between 1950 and 2022 were influenced by marine heatwaves. Notably, rapid intensification is, on average, 50% more likely during marine heatwaves. As marine heatwaves are on the increase due to climate change, our findings indicate that more frequent rapid intensification events can be expected in the warming climate.
... The black, blue and red box indicate the PD, 2 × CO 2 , and 4 × CO 2 scenarios. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.) in LHFLX ocn sends a lot of energy from the ocean to the atmosphere and can contribute to TC intensification (Green and Zhang, 2013;Kafatos et al., 2006;Lin et al., 2009). With the CO 2 increase, the change in LHFLX ocn is larger in the NIO than in the WNP, which can be inferred to enhance TC in the NIO and contribute to a strong RS (Fig. 4c, h). ...
... a major control over the strength of hurricanes (Kafatos et al. 2006), dispersion of pollutants ), offshore energy operations (Koch et al. 1991), and even coastal ecosystem health (Hetland et al. 1999;Weisberg et al. 2014). Despite decades of scientific inquiry and major field program initiatives, the fundamental problem of LC predictability remains (Committee on Advancing Understanding of Gulf of Mexico Loop Current Dynamics 2018). ...
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It has been established that idealized western boundary currents, which encounter a gap in their supporting boundary, will assume one of two dominant steady states: a loop current state and a gap leaping state, and that transitions between these states display hysteresis. However, a question of whether the idealized geometries considered to date apply to the Gulf of Mexico Loop Current (LC) remained. Here, the nonlinear potential vorticity advection-diffusions equations are solved, for Gulf of Mexico topography, using Newton’s method. We demonstrate that, in application to the LC in the Gulf of Mexico, the original conclusions do hold and additionally describe peculiarities of the more realistic steady states. The existence of our numerically calculated steady LC states in the actual Gulf of Mexico are supported through analysis of historical sea surface height data, and implications of our results for LC modeling and forecasting are discussed.
... A reasonable prediction of the inner-core structural change and storm radius may improve the forecast of TC intensity, intensity change and RI (Rappaport et al. 2009;Chen 2011). It is a well-established fact that a pre-existing high-SST anomaly at the right side of the TC track contributes to RI by inducing latent heat Cux (LHF) (Kafatos et al. 2006). Using satellite microwave measurements and buoy observations, similar results are also shown by Sun et al. (2007). ...
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Tropical cyclone rapid intensification (RI) is a major challenge to operational forecasters. Amphan was the most deadly cyclone over the north Indian Ocean basin as it caused 128 deaths in the region. This study aimed to understand the impacts of sea-surface temperatures (SSTs) generated from two leading operational agencies (i.e., Indian National Centre for Ocean Information Services (INCOIS) and National Centre for Medium-Range Weather Forecasting (NCMRWF)) in India on the RI and mature super cyclonic (SuCS) phases of the Amphan (2020) using the weather research and forecasting (WRF4.0) model. Three experiments were carried out using SSTs from INCOIS (INC), NCMRWF (NCM) and control (CNT) with an identical configuration at 3 km resolution with a lead time of up to 96 h. The results suggest that INC offered the best forecast in terms of track, intensity, RI and structure during the three different phases of the SuCS, i.e., RI, mature and weakening stages. The CNT yielded forecasts with the highest errors. The results of the model are validated with in-situ buoy and radar observations establishing that INC robustly captured the intensification rate and the structure compared to NCM and CNT. It is also revealed that 30–120 km radii are the key eyewall region contributing to the RI and mature phase of the SuCS Amphan through diabatic heating and convective bursts. The diabatic heating has been placed between 600 and 400 hPa near the eyewall region, and it is well supported by the formation of frozen hydrometeors in the SuCS. INC simulation is able to bring out those features accurately, leading to better intensity prediction, whereas NCM and CNT overestimated those features resulting in unrealistic intensification in the simulations. This study has a direct consequence to the operational forecasting agencies and disaster managers for policy and preparedness.
... The altering climatic conditions brought various extreme events and natural hazards across the globe, such as floods, typhoons/cyclones/ hurricanes (Balaguru et al., 2016;Mei and Xie, 2016), forest fire, volcanic explosions (Jing et al., 2020), extreme rainfall, landslide, dust storm (Harrison et al., 2001), drought (Bhuiyan et al., 2006;Dorjsuren et al., 2016), salinity intrusion (Nguyen et al., 2020), etc. Most of these natural hazards are directly related to the change in earth energy evolution due to various human disturbances and natural processes (Kafatos et al., 2006;Chauhan et al., 2018;Nguyen and Liou, 2019a). Recently, the frequency of various natural calamities and their intensities are rising at a rapid pace (Van Aalst, 2006;Wu et al., 2021). ...
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Tropical storms (TSs)/Typhoons (TYs) in the Northwest Pacific (NWP) region are one of the most devastating natural hazards, which cause large-scale impacts on human life and infrastructure. In August 2020, a total of 9 tropical storms were identified by International Best Track Archive for Climate Stewardship (IBTrACS) in the NWP region. These TSs/TYs made their landfall over the coastal parts of China, North Korea, and South Korea, while none of them made their landfall over Taiwan. These conditions were unique in recent years and induced drought conditions in Taiwan during 2020. We have carried out a three-dimensional analysis of oceanic, atmospheric, and meteorological parameters for the evaluation of changes associated with typhoons during August 2020. The model, satellite, and ground observations data have been used for the assessment of the impact of these TS/TYs on the ocean, atmosphere, and air quality. The rise in ocean temperature (1 °C–2 °C) was observed even at the depth of 100 m. Strong upwelling of the ocean water in the NWP originated a change in the mixed layer depth and also has affected the salinity in South China, East China, and the Philippines Sea. The strong convective forces during the storm conditions produced a prominent rise in CO and Ozone concentration. These typhoons also affected the air quality of Taiwan during August 2020. The transboundary air pollutants triggered the enhancement in particulate matter (PM1.0 and PM2.5) and surface ozone over Taiwan, which resulted in major health hazards to a large population.
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During the pre- and post-monsoon season, the eastern and western coasts are highly vulnerable to cyclones. The tropical cyclone "Tauktae" formed in the Arabian Sea on 14 May 2021 and moved along the western coast of India, and landfall occurred on 17 May 2021. During the cyclone, the maximum wind speed was 220 km/hr with a pressure of 935 millibars. This cyclone influenced the meteorological and atmospheric parameters and weather conditions of western, northern, and central India and caused devastating damage. A detailed satellite, Argo, and ground data analysis have been carried out to study the changes in the ocean, atmospheric and meteorological parameters during the cyclone formation until the landfall and beyond. During cyclone generation, the air temperature (AT) was maximum (30.51 o C), and winds (220 km/h) was strong with negative omega values (0.3). RH and RF were higher near the origin and landfall location of the cyclone, with an average of 81.28% and 21.45 mm/day, respectively. The concentration of traces gases (NO 2 , SO 2 , CH 4 , TCO, COVMR, and H 2 OMMR) and aerosols (AOD, AE and PMs) loading were increased over land along the cyclone track that degraded the quality of air. The detailed analysis shows pronounced changes in the land, ocean, meteorological and atmospheric parameters. The strong wind associated with the cyclone amalgamated the surrounding airmass degraded the air quality, and severely threatened the people living in the landfall areas. The results discussed in the present study show a pronounced change in the ocean, land, meteorological and atmospheric parameters and a strong coupling between the land-ocean-atmosphere associated with the cyclone.
Chapter
Tropical cyclones (TCs) are devastating natural hazards that originate in the Bay of Bengal and the Indian Ocean from April to November each year. They make landfall at the southwestern coasts of India and Bangladesh. In the last decade, four major TCs hit the southwestern coast of India. Two cyclones Hudhud and Titli developed in October and Fani and Amphan in May. We have carried out the analysis of sea surface temperature (SST), relative humidity (RH), carbon monoxide volume mixing ration (CO VMR), aerosols optical depth (AOD), angstrom exponent (AE), and volume size distribution of (Vol) of aerosols to find the changes in an atmospheric and meteorological parameter associated with these cyclones. The rise of SST is the prime cause of cyclone development. During May 2020, we found relatively high SST compared to other years. Relative humidity plays a vital role in the middle and lower troposphere. Changes are also seen in CO concentration before and after the cyclone's landfall even at far distant places. Changes in AOD and AE indicate aerosols’ vigorous mixing associated with the cyclonic conditions. These cyclones also impacted the air quality of the coastal cities of India and caused the enhancement in the concentration of finer particles.
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It has long been accepted that interannual fluctuations in sea surface temperature (SST) in the Atlantic are associated with fluctuations in seasonal Atlantic basin tropical cyclone frequency. To isolate the physical mech- anism responsible for this relationship, a singular value decomposition (SVD) is used to establish the dominant covarying modes of tropospheric wind shear and SST as well as horizontal SST gradients. The dominant SVD mode of covarying vertical shear and SST gradients, which comprises equatorially confined near-zonal vertical wind shear fluctuations across the Atlantic basin, is highly correlated with both equatorial eastern Pacific SST anomalies (associated with El Nino) and West African Sahel rainfall. While this mode is strongly related to tropical storm, hurricanes, and major hurricane frequency in the Atlantic, it is not associated with any appreciable Atlantic SST signal. By contrast, the second SVD mode of covarying vertical shear and horizontal SST gradient variability, which is effectively uncorrelated with the dominant mode, is associated with SST fluctuations concentrated in the main tropical cyclone development region between 108 and 208N. This mode is significantly correlated with tropical storm and hurricane frequency but not with major hurricane frequency. Statistical tests confirm the robustness of the mode, and lag correlations and physical reasoning demonstrate that the SST anomalies are not due to the developing tropical cyclones themselves. Anomalies of SST and vertical shear during years where the mode has substantial amplitude confirm the resemblance of the individual fields to the modal structure, as well as the association of hurricane development with the warmer SSTs. Although SSTs are of secondary importance to vertical shear in modulating hurricane formation, explaining only ;10% of the interannual variability in hurricane frequency over the ;50% explained by vertical shear, the results support the conclusion that warmer SSTs directly enhance development. The lack of correlation with major hurricanes implies that the underlying SSTs are not a significant factor in the development of these stronger systems.
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Hurricane Opal (1995) experienced a rapid, unexpected intensification in the Gulf of Mexico that coincided with its encounter with a warm core ring (WCR). The relative positions of Opal and the WCR and the timing of the intensification indicate strong air-sea interactions between the tropical cyclone and the ocean. To study the mutual response of Opal and the Gulf of Mexico, a coupled model is used consisting of a nonhydrostatic atmospheric component of the Naval Research Laboratory's Coupled Ocean-Atmosphere Mesoscale Prediction System (COAMPS), and the hydrostatic Geophysical Fluid Dynamics Laboratory's Modular Ocean Model version 2 (MOM 2). The coupling between the ocean and the atmosphere components of the model are accomplished by conservation of heat, salt, momentum, as well as the sensible and latent heat fluxes at the air-sea interface. The atmospheric model has two nests with spatial resolutions of 0.6° and 0.2°. The ocean model has a uniform resolution of 0.2°. The oceanic model domain covers the Gulf of Mexico basin and coincides with a fine-mesh atmospheric domain of the COAMPS. The initial condition for the atmospheric component of COAMPS is the archived Navy Operational Global Atmospheric Prediction System operational global analysis, enhanced with observations. The initial ocean condition for the oceanic component is obtained from a 2-yr MOM 2 simulation with climatological forcing and fixed mass inflow into the Gulf. The initial state in the Gulf of Mexico consists of a realistic Loop Current and a shed WCR. The 72-h simulation of the coupled system starting from 1200 UTC 2 October 1995 reproduces the observed storm intensity with a minimum sea level pressure (MSLP) of 918 hPa, occurring at 1800 UTC 4 October, a 6-h delay compared to the observation. The rapid intensification to the maximum intensity and the subsequent weakening are not as dramatic as the observed. The simulated track is located slightly to the east of the observed track, placing it directly over the simulated WCR, where the sea surface temperature (SST) cooling is approximately 0.5°C, consistent with buoy measurements acquired within the WCR. This cooling is significantly less over the WCR than over the common Gulf water due to the deeper and warmer layers in the WCR. Windinduced currents of 150 cm s-1 are similar to those in earlier idealized simulations, and the forced current field in Opal's wake is characterized by near-inertial oscillations superimposed on the anticyclonic circulation around the WCR. Several numerical experiments are conducted to isolate the effects of the WCR and the ocean-atmosphere coupling. The major findings of these numerical experiments are summarized as follows. 1) Opal intensifies an additional 17 hPa between the times when Opal's center enters and exits the outer edge of the WCR. Without the WCR, Opal only intensifies another 7 hPa in the same period. 2) The maximum surface sensible and latent heat flux amounts to 2842 W m-2. This occurs when Opal's surface circulation brings northwesterly flow over the SST gradient in the northwestern quadrant of the WCR. 3) Opal extracts 40% of the available heat capacity (temperature greater than 26°C) from the WCR. 4) While the WCR enhances the tropical cyclone and ocean coupling as indicated by strong interfacial fluxes, it reduces the negative feedback. The negative feedback of the induced SST cooling to Hurricane Opal is 5 hPa. This small feedback is due to the relatively large heat content of the WCR, and the negative feedback is stronger in the absence of the WCR, producing a difference of 8 hPa in the MSLP of Opal.
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A response is made to the comments of Michaels et al. concerning a recent study by the authors. Even after considering Michaels et al.'s comments, the authors stand behind the conclusions of the original study. In contrast to Michaels et al., who exclusively emphasize uncertainties that lead to smaller future changes, uncertainties are noted that could lead to either smaller or larger changes in future intensities of hurricanes than those summarized in the original study, with accompanying smaller or larger societal impacts.
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The synoptic-scale flow during tropical cyclogenesis and cyclolysis over the North Atlantic Ocean is investigated using compositing methods. Genesis and lysis are defined using the National Hurricane Center (NHC, now known as the Tropical Prediction Center) best-track data. Genesis (lysis) occurs when NHC first (last) identifies and tracks a tropical depression in the final best track dataset. Storm-centered composites are created with the Analysis of the Tropical Oceanic Lower Level (ATOLL; ∼900 hPa) and 200-hPa winds for June-November produced by NHC for the years 1975-93. Results show that significant regional differences exist in 200-hPa flow during genesis across the Atlantic basin. Composites of genesis in the western part of the basin show a 200-hPa trough (ridge) located to the west (east) of the ATOLL disturbance. In the eastern half of the basin composites of genesis show a sprawling 200-hPa ridge centered northeast of the ATOLL disturbance. The major axis of this elliptically shaped 200-hPa anticyclone extends zonally slightly poleward of the ATOLL level disturbance. Another composite of relatively rare genesis events that are associated with the equalorward end of frontal boundaries show that they generally occur in the equatorward entrance region of a jet streak in conjunction with an ATOLL cyclonic vorticity maximum in a region where vertical shear is minimized. An approximation of the Sutcliffe-Trenberth form of the quasigeostrophic omega equation is used to estimate the forcing for vertical motion in the vicinity of developing tropical cyclones. Forcing for ascent is found in all three genesis composites and is accompanied by a nonzero minimum in vertical shear directly above the ATOLL cyclonic vorticity maximum. Vertical shear over developing depressions is found to be near 10 m s -1, suggestive that weak shear is necessary during tropical cyclogenesis to help force synoptic-scale ascent. Composites of tropical cyclone lysis show much weaker ATOLL cyclonic vorticity when compared to the genesis composites. The magnitude of the vertical shear and the forcing for ascent above the lysis ATOLL disturbance are stronger and weaker, respectively, than in the genesis composites. These differences arise due to the presence of a jet-streak and a longer half-wavelength between the trough and ridge axes in the lysis 200-hPa flow composite. The genesis flow patterns are decomposed by crudely removing the signature of the developing cyclone and its associated convection. Two separate and very different flow patterns commonly observed during genesis over the eastern and western Atlantic Ocean are found to be very similar once the flows are decomposed. Both flows are characterized by strong deformation at low levels and at 200 hPa with an upper-level jet exit region near the developing depression.
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A thermodynamic approach to estimating maximum potential intensity (MPI) of tropical cyclones is described and compared with observations and previous studies. The approach requires an atmospheric temperature sounding, SST, and surface pressure; includes the oceanic feedback of increasing moist entropy associated with falling surface pressure over a steady SST; and explicitly incorporates a cloudy eyewall and a clear eye. Energetically consistent, analytic solutions exist for all known atmospheric conditions. The method is straightforward to apply and is applicable to operational analyses and numerical model forecasts, including climate model simulations.The derived MPI is highly sensitive to the surface relative humidity under the eyewall, to the height of the warm core, and to transient changes of ocean surface temperature. The role of the ocean is to initially contribute to the establishment of the ambient environment suitable for cyclone development, then to provide the additional energy required for development of an intense cyclone. The major limiting factor on cyclone intensity is the height and amplitude of the warm core that can develop; this is closely linked to the height to which eyewall clouds can reach, which is related to the level of moist entropy that can be achieved from ocean interactions under the eyewall. Moist ascent provides almost all the warming above 200 hPa throughout the cyclone core, including the eye, where warm temperatures are derived by inward advection and detrainment mixing from the eyewall. The clear eye contributes roughly half the total warming below 300 hPa and produces a less intense cyclone than could be achieved by purely saturated moist processes.There are necessarily several simplifications incorporated to arrive at a tractable solution, the consequences of which are discussed in detail. Nevertheless, application of the method indicates very close agreement with observations. For SST < 26°C there is generally insufficient energy for development. From 26° to 28°C SST the ambient atmosphere warms sharply in the lower troposphere and cools near the tropopause, but with little change in midlevels. The result is a rapid increase of MPI of about 30 hPa °C1. At higher SST, the atmospheric destabilization ceases and the rate of increase of MPI is reduced.
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To investigate the impacts of anthropogenic global warming on tropical cyclone (TC) activity, climate simulations were conducted under the present, and CO2-warmed conditions, using the National Center for Atmospheric Research Community Climate Model version 2. The CO2-warmed condition includes doubled atmospheric CO2 concentration, and about 1 degreesC of tropical sea surface temperature (SST) warming. Simulated TCs were objectively selected from twice daily instantaneous outputs during an eight-year time integration period of each simulation. The changes associated with global warming were examined in terms of the frequency of occurrence, and mean intensity of TCs. The frequency of global TC occurrence remains unchanged in response to the CO2-induced warming. Although the hydrologic cycle is generally enhanced in the warmed climate, increased precipitation does not necessarily make a great impact on TC activity. This unchanged global TC frequency seems to coincide with almost neutral variations in the zonally-averaged moist instability in the tropics. However, there is some uncertainty in the model regarding the treatment of physical processes that control moisture distributions in the middle to lower troposphere. On the regional scale, the CO2-induced changes in TC occurrence were generally not statistically significant. TC intensities were enhanced over warmed SST regions in the western Pacific, which contribute to the significantly increased mean intensity of global TCs.