ArticlePDF Available

Abstract and Figures

It is well known that the frequency of cyclones is about four times higher over the Bay of Bengal when compared with the Arabian Sea. Most of the severe cyclones during pre-monsoon (April and May) and post-monsoon (October and November) seasons hit the east coast of India, causing colossal loss of life and damage to property. In this study an attempt has been made to show the importance of the upper ocean parameters known as the upper ocean heat content (UOHC) and the UOHC with stratification (UOHCS). The UOHC has been computed considering the stratification parameter (S) for the first time. Most of the severe cyclones are forming over the UOHC range between 40–80 kj/cm2 in the Bay of Bengal. The UOHCS was high ranging from 50–400 kj/cm2 compared to the Pacific Ocean, which is due to high stratification (S ∼2–4). Climatology of cyclone tracks and the UOHCS and in situ observation from Argo suggest that most of the tracks in the pre- and post-monsoon seasons are influenced by the high UOHCS (>120 kj/cm2). UOHC and S are the dominant factors during the pre- and post-monsoon seasons, respectively. In addition to the atmospheric parameters from ocean-side, UOHC and stratification appear to be the best parameters to examine the intensification and movement of the cyclones during the pre- and post-monsoon seasons over the Bay of Bengal.
Content may be subject to copyright.
Role of upper ocean parameters in the genesis, intensication and tracks of cyclones over the Bay
of Bengal
K. Maneesha
a
*, Y. Sadhuram
a
and K.V.S.R. Prasad
b
a
CSIR National Institute of Oceanography, Regional Centre Physical Oceanography Division, 176, Lawsons Bay Colony,
Visakhapatnam, India;
b
Department of Meteorology & Oceanography, Andhra University, Visakhapatnam, India
It is well known that the frequency of cyclones is about four times higher over the Bay of Bengal when compared with the
Arabian Sea. Most of the severe cyclones during pre-monsoon (April and May) and post-monsoon (October and November)
seasons hit the east coast of India, causing colossal loss of life and damage to property. In this study an attempt has been made
to show the importance of the upper ocean parameters known as the upper ocean heat content (UOHC) and the UOHC with
stratication (UOHC
S
). The UOHC has been computed considering the stratication parameter (S) for the rst time. Most of
the severe cyclones are forming over the UOHC range between 4080 kj/cm
2
in the Bay of Bengal. The UOHC
S
was high
ranging from 50400 kj/cm
2
compared to the Pacic Ocean, which is due to high stratication (S 24). Climatology of
cyclone tracks and the UOHC
S
and in situ observation from Argo suggest that most of the tracks in the pre- and post-
monsoon seasons are inuenced by the high UOHC
S
(>120 kj/cm
2
). UOHC and S are the dominant factors during the
pre- and post-monsoon seasons, respectively. In addition to the atmospheric parameters from ocean-side, UOHC and
stratication appear to be the best parameters to examine the intensication and movement of the cyclones during the pre-
and post-monsoon seasons over the Bay of Bengal.
1. Introduction
It is a well-known fact that the frequency of cyclones is
about four times higher over the Bay of Bengal when com-
pared with the Arabian Sea. Most of the severe cyclones
during pre-monsoon (April and May) and post-monsoon
(October and November) seasons generally move towards
the east coast of India, causing colossal loss of life and
damage to property. A few cyclones move either north-
wards or northeast and hit the Bangladesh or Myanmar
coasts (Sadhuram et al. 2004). The essential conditions
for the formation of cyclones are: (1) Sufcient ocean
thermal energy, (2) enhanced mid-troposphere relative
humidity, (3) conditional instability, (4) enhanced lower
troposphere relative vorticity, (5) minimum weak vertical
shear and (6) displacement at least 5 deg away from the
Equator (Gray 1968). Some recent studies on cyclones indi-
cate that the shear should be less during the formation
stage, while shear greater than 20 m/sec helps in the inten-
sication provided that all the other conditions are favour-
able (Zeng et al. 2008). In addition to the favourable
atmospheric conditions, without a sufcient ux supply
from the ocean it is not possible for intensication to take
place (Byers 1944; Emanuel 1986; Lin et al. 2009).
It is now known that the vertical thermal structure and
the upper ocean heat content (UOHC, referred to as tropical
cyclone heat potential or cyclone heat potential in some
earlier studies, with an integrated vertical temperature
from surface to depth of 26°C isotherm) play a vital role
in the intensication of storms rather than Sea Surface
Temperature (SST) (Shay et al. 2000; Goni & Trinanes
2003; Lin, Liu, Wu, Chiang & Sui 2003; Lin, Liu, Wu,
Wong et al. 2003b; Lin et al. 2005; Scharroo et al. 2005;
Pun et al. 2007). Hurricane Bret intensied when it
moved over the region of high heat potential (>90 kj/cm
2
)
in the western Gulf of Mexico (Goni et al. 2003,2009;
Shay et al. 2000). Further, Hurricanes Igor (tropical
Atlantic) and Celia (Eastern North Pacic), Typhoon
Megi (Western North Pacic) and Cyclone Phet
(Arabian Sea) intensied during 2010 over areas of
high UOHC. Lin et al. (2008) showed that Hurricanes
Katrina (2005), Rita (2005) and Mitch (1998) and
Super Typhoon Maemi (2003) also intensied over
regions of high UOHC. Lin et al. (2009) also observed
that Cyclone Nargis suddenly intensied when it
entered into a region of high UOHC (77105 kj/cm
2
).
Though UOHC variations in the Atlantic are small, the
inclusion of UOHC in the Statistical Hurricane Intensity
Prediction Scheme (SHIPS) forecast model reduced the
forecast errors up to 5% for all cases of category 5
cyclones and up to 20% for other cyclones (Mainelli
et al. 2008).
In the Bay of Bengal, seasonal variability of UOHC
was reported by Sarma et al. (1990). The UOHC was
© 2015 Institute of Marine Engineering, Science & Technology
*Corresponding author. Email: kkpalli_manisha@yahoo.com
Journal of Operational Oceanography, 2015
Vol. 8, No. 2, 133146, http://dx.doi.org/10.1080/1755876X.2015.1087185
found to be > 60 kj/cm
2
in the Andaman Sea, southern and
central Bay of Bengal, where generally the cyclones gen-
erate and move during the post-monsoon (October and
November) season (Sadhuram et al. 2004). The relation-
ship between the UOHC and the efciency of intensica-
tion (EI, ratio between the severe storms and the total
number of storms in a grid) under different seasons was
examined by Sadhuram et al. (2006). The UOHC was
found to be above 70 kj/cm
2
in the potential zones (5
deg N to 12 deg N post-monsoon; north of 15 deg N
summer monsoon) of cyclogenesis in the Bay of Bengal
(Kumar & Chakraborthy 2011). The importance of the
UOHC in the translation speed of the storms in the Bay
of Bengal was studied by Sadhuram et al. (2010). Goni
et al. (2010) reported that there was a decrease in
UOHC during 2009/10 in the Gulf of Mexico and the
southwestern Pacic Ocean, while there was an increase
in the western Pacic Ocean, Arabian Sea and Bay of
Bengal.
All the above studies emphasize the importance of the
UOHC in the genesis and intensication of storms.
Though the Bay of Bengal is a highly stratied ocean,
the importance of stratication while estimating the
UOHC has not been considered so far.
1.1. Importance of stratication in the Bay of Bengal
A recent study (Shay & Brewster 2010) highlighted the
importance of the stratication parameter (S) in addition
to the UOHC in the East Pacic Ocean. The authors
observed that UOHC with stratication (UOHC
S
) was
high along the hurricane passage areas in the East Pacic.
However, the Bay of Bengal is highly stratied due to a
high inux of fresh water, and thus study of UOHCs is
very important but such studies are not done so far over
this region.
The Bay of Bengal (north-eastern Indian Ocean) is
bounded by land mass except in the south and covers an
area of 2.2 × 10
6
km
2
(Lafond 1966). The winds blow
from the northeast from November to February, southerly
from March to May, and southwest from June to October
(Varkey et al. 1996). Several major river systems the
Ganges-Brahmaputra, the Irrawadi-Salwan and the
Krishna-Godavari drain into the Bay of Bengal. The
total run-off from the peninsular rivers, which peaks
during the summer monsoon (June to September)
amounts to 2.95 × 10
12
m
3
/yr (Sengupta et al. 2006). This
huge river run-off and excess precipitation (Prasad 1997)
results in low-salinity surface waters. The weak winds
coupled with the low salinity makes the Bay of Bengal a
Figure 1. Monthly distribution of climatological wind shear (m/s, 200850 mb) and the genesis locations of cyclones in the Bay of Bengal
from 1981 to 2008.
134 K. Maneesha et al.
highly-stratied basin. The static stability of the water
column is three to four times higher than the Arabian Sea
(Prasannakumar et al. 2002). The near-surface stratied
layer plays a major role in the genesis of cyclones in the
Bay of Bengal (Murty et al. 2000). Hence, in this present
study, the UOHC is computed including the stratication
parameter (S; Shay & Brewster 2010) which has not been
reported on before for the Bay of Bengal. The role of
UOHC and UOHC
S
in the genesis and intensication of
storms in the Bay of Bengal is thus addressed in this study.
2. Data and methods
UOHC and UOHC
S
and the stratication parameter (S) in
the Bay of Bengal are computed from the following
equations.
UOHC =
r
CPD26
0
(T26)dZ (1)
where ρis the density of water column above 26°C iso-
therm, C
P
is the specic heat of seawater at constant
pressure, Tis the average temperature of two consecutive
layers of a depth increment dZ and D26 is the depth of
the 26°C isotherm (Sarma et al. 1990; Sadhuram et al.
2004).
UOHC
S
is computed following the method of Shay and
Brewster (2010):
UOHCS=UOHCS(2)
S is calculated from the equation
S=
Nmax
N0
,(3)
where N
0
is the reference buoyancy frequency and N
max
is the maximum value of the Brunt Vaisala frequency,
Where N=
g
r
d
r
dZ
(4)
World Ocean Atlas-2009 (WOA09) Data (Antonov et al.
2010; Locarnini et al. 2010) is available from the National
Oceanic and Atmospheric Administration (NOAA)
website. A 1 × 1 grid was used in the computations. The
data on cyclone tracks were taken from the Cyclone Atlas
2007 of the Indian Meteorological Department.
Figure 2. Monthly distribution of climatological absolute vorticity (s
1
, 850 mb) and the genesis locations of cyclones in the Bay of
Bengal from 1981 to 2008.
Journal of Operational Oceanography 135
Daily Argo data was taken from the Coriolis Global
Data Center. Daily atmospheric data was taken from
National Centers for Environmental Prediction/National
Center for Atmospheric Research (NCEP-NCOAR) reana-
lysis data.
3. Results and discussion
3.1. Atmospheric parameters
In the present study three parameters namely, wind shear,
vorticity and relative humidity are studied with respect to
their role in the genesis of cyclones. Figure 1 shows that
most of the genesis locations occurred over the regions
where the wind shear is less than 10 m/sec. Wind shear is
found to be greater than 23 m/sec in the month of Decem-
ber over the northern part of Bay of Bengal. Figure 2 shows
that most of the genesis locations occurred in the regions
where the relative vorticity is above 2 × 10
05
S
1
.Figure
3shows that the relative humidity varies from 20 to 70%
over the Bay of Bengal, and most of the cyclones form
under conditions where the relative humidity is greater
than 40%. After the genesis, studies on the intensication
and movement of cyclones are essential for the proper fore-
cast mechanism. Hence there is a need to study the ocean
parameters which play a major role in the intensication
of cyclones.
3.2. Daily atmospheric data during different
cyclones (case studies)
Daily atmospheric data (Figures 46) during different
cyclones shows that near the formation locations there is
a low shear, high humidity and sufcient relative vorticity.
Wind shear was almost less than 10 m/s along the track in
all the cases (Figure 4). Minimum relative vorticity was
also maintained along the track (Figure 5). After formation,
in some cases cyclones are sustained even under conditions
of low humidity (Figure 6). So, these atmospheric par-
ameters are necessary for the formation and sustainability
of the cyclones, but they are not the sole causal factors.
The other major factors that affect the cyclones originate
in the ocean itself; thus, we need to study the ocean par-
ameters that inuence cyclones.
3.3. Upper ocean heat content (UOHC)
In general, the UOHC in the Bay of Bengal is found to vary
from 20130 kj/cm
2
and most of the cyclones have their
genesis where the UOHC is greater than 40 kj/cm
2
. From
Figure 3. Monthly distribution of climatological relative humidity (%, 600 mb) and the genesis locations of cyclones in the Bay of Bengal
from 1981 to 2008.
136 K. Maneesha et al.
January to March, the north and western Bay of Bengal has low
(<30 kj/cm
2
) UOHC, while in May high (>90 kj/cm
2
)values
are observed in the western and central bay, with a peak
(>110 kj/m
2
). In the post-monsoon season (October and
November), UOHC greater than 70 kj/cm
2
is observed in the
north-eastern area of the bay. Most of the genesis locations
are found to coincide with high UOHC values (Figure 7)and
similar observations have been reported by Sadhuram et al.
(2004), who found that the UOHC was greater than 60 kj/
cm
2
in the eastern part of the bay during post-monsoon
season, which is close to the present results. It is observed
that in the month of May cyclones intensify in the western
bay, where the UOHC is >110 kj/cm
2
, whereas in the post-
monsoon season most of the cyclones intensify near the
coast. From these results it is inferred that a threshold value
of about 40 kj/cm
2
is necessary for the genesis and intensica-
tion of storms in the Bay of Bengal.
The intensication and dissipation of the cyclones
mostly takes place in the north and west of the Bay of
Bengal, where high UOHC values persist in the months
of April and October, then low valuese of UOHC during
November and December (Figure 8).
3.4. Stratication parameter (S)
In the present study, the stratication parameter (S) is
calculated from Equation (3) using the maximum Brunt
Vaisala frequency (N
max
) and the reference frequency
(N
o
; Shay & Brewster 2010). Typical vertical structures
of the Brunt Vaisala frequency at four different locations
in the Bay of Bengal are shown in Figure 9.N
max
is high
(29 cph) at a depth of 25 m in the eastern area of the bay,
and low (20 cph) in the western area. It is above 22 cph
in the northern and southern areas. Stratication (S)
values in the Bay of Bengal are found to vary between
2 and 5; they are high in the northern area (S>4),
which extends to the south along the coast in the
eastern area. From June to December there is high
stratication (S>3) in the northern and central areas of
the Bay of Bengal. High stratication (S>3) is also
observed in the eastern and western areas during the
post-monsoon months due to high river discharge
during the summer monsoon season. It was found that
most of the cyclones are generating where S is greater
than 2.8, except during December. The maximum
number of cyclones form during October, when high S
Figure 4. Distribution of climatological wind shear (m/s, 200850 mb) and the tracks of cyclones in the Bay of Bengal from 2007
to 2013.
Journal of Operational Oceanography 137
Figure 5. Distribution of climatological absolute vorticity (s
1
, 850 mb) and the tracks of cyclones in the Bay of Bengal from 2007 to 2013.
Figure 6. Distribution of climatological relative humidity (%, 600 mb) and the tracks of cyclones in the Bay of Bengal from 2007 to 2013.
138 K. Maneesha et al.
values (S>3) prevail over the bay (Figure 10). Most of
the intensication locations in the pre-monsoon (April
and May) and post-monsoon (October and November)
months correspond with locations of high (S>3) strati-
cation (Figure 11).
3.5. Upper ocean heat content with stratication
(UOHC
S
)
UOHC
S
is found to vary from 50400 kj/cm
2
, with
maximum values occurring in the central and northern
areas of the Bay of Bengal during the pre-monsoon
months, as well as in June. From July to November,
UOHC
S
is high in the eastern and western areas. Most of
the cyclones form over regions where UOHC
S
>120 kj/
cm
2
, which is almost double the value of 60 kj/cm
2
without stratication (Figure 12).
Shay and Brewster (2011) reported UOHC
S
values of
114129 kj/cm
2
in the east and west Pacic and 120150
kj/cm
2
in the North West Caribbean Sea. It is interesting
to note that UOHC
S
values are almost double in the Bay
of Bengal compared to those of the Pacic, which is
Figure 7. Monthly distribution of climatological UOHC and the genesis locations of cyclones from 1981 to 2008.
Figure 8. Climatology of the intensication (red dots) and dissipation (blue dots) locations of cyclones overlaid on UOHC.
Journal of Operational Oceanography 139
mainly due to the high stratication in the bay. In general
cyclones are found to intensify over regions where
UOHC >120 kj/cm
2
; most of the cyclones in the pre-
monsoon (April and May) season intensify over regions
where UOHC
S
>224 kj/cm
2
in the northern area of the
bay. But in the post-monsoon season, most of the intensi-
cation is takes place in the eastern area of the bay, where
UOHC
S
>150 kj/cm
2
(Figure 13).
Figure 9. Typical vertical proles of Brunt Vaisala frequencies at four different locations in the Bay of Bengal.
Figure 10. Distribution of stratication (S) and the genesis locations of the cyclones.
140 K. Maneesha et al.
This study, comprising of various upper ocean par-
ameters during the intensication of the cyclones,
showed that some minimum threshold values are required
in all parameters such as D26, UOHC, S and UOHC
S
for
the intensication of cyclones over the Bay of Bengal. In
the southern part of the bay (5 to 15 deg N), the cyclones
are likely to intensify where UOHC >90 kj/cm
2
in the pre-
monsoon season and >30 kj/cm
2
in the post-monsoon
season. The stratication parameter (S) is generally >2.4
in the pre-monsoon season and >2.8 in the post-
monsoon season, whereas in the northern area (>15 deg
N), most of the cyclones intensify where UOHC >60 kj/
cm
2
in the pre-monsoon season and >40 kj/cm
2
in the
post-monsoon season. Also, S is generally >2.6 in the
pre-monsoon season and >2.8 in the post-monsoon
season. The threshold values in the parameter UOHC
S
,
which is the combined effect of both UOHC and S were
also observed.
Figure 11. Climatology of the intensication (red dots) and dissipation (blue dots) locations of cyclones overlaid on stratication (S).
Figure 12. Distribution of UOHC
S
(kj/cm
2
) and the genesis locations of the cyclones.
Journal of Operational Oceanography 141
3.6. Cyclone tracks in relation to UOHC, S and
UOHC
S
during the pre- and post-monsoon seasons
Climatology of the monthly frequencies of cyclones from
1891 to 2008 shows that most of the severe cyclones
occurred in the pre- and post-monsoon seasons. From the
climatology of the cyclone tracks from 1891 to 2008, it
can be seen that cyclones in the pre-monsoon season gen-
erally travel north and northeast, while in the post-
monsoon season they tend to move in the north and
northwest directions (Figure 14). The spatial distributions
of UOHC, S and UOHC
S
in the pre- and post-monsoon
months are plotted along with cyclone tracks, and it was
found that the tracks generally follow the high UOHC
S
regions. But UOHC
S
is a combination of both UOHC
and S. In the pre-monsoon season (April and May), S is
comparatively less (<3) than in the post-monsoon season
but the increase in UOHC during the same period is
caused by the high insolation. So, in the pre-monsoon
Figure 13. Climatology of the intensication (red dots) and dissipation (blue dots) locations of cyclones overlaid on UOHC
S
(kj/cm
2
).
Figure 14. Distribution of stratication (S) and the climatology of cyclone tracks.
142 K. Maneesha et al.
Figure 15. Distribution of UOHC
S
(kj/cm
2
) and the climatology of cyclone tracks.
Figure 16. Distribution of stratication (S), UOHC (kj/cm
2
) and UOHC
S
(kj/cm
2
) a few days before the occurrence of Cyclones Sidr,
Nargis and Aila.
Journal of Operational Oceanography 143
season, the increase in UOHC
S
is mainly due to high
UOHC (Figure 15). In the post-monsoon season, S is on
the higher side (>3) in the central, eastern and western
areas of the Bay of Bengal due to the freshwater discharge
during the monsoon season. The UOHC in the post-monsoon
season is comparatively less (<85 kj/cm
2
) than in the pre-
monsoon season. Here the high UOHC
S
is mainly due to strati-
cation. So, UOHC appears to be the dominant factor in the pre-
monsoon season, while stratication is the dominant factor in the
post-monsoon season. The combined effect can be seen in
UOHC
S
, which in turn inuences the genesis, intensication
and tracks of the cyclones.
Figure 17. Distribution of stratication (S), UOHC (kj/cm
2
) and UOHC
S
(kj/cm
2
) a few days before the occurrence of Cyclones Laila,
Thane, Neelam and Mahasen.
144 K. Maneesha et al.
3.7. A few case studies using Argo daily data
The upper ocean parameters, comprising stratication,
UOHC and UOHC
S
, prior to the genesis of the cyclones
have been examined for a few case studies during the
period from 2007 to 2013 (Cyclones Sidr to Mahasen)
using daily ARGO data.
Cyclone Sidr formed in the southern area of the Bay of
Bengal and was sustained during 916 November 2007,
during which time it moved north and started intensifying
(based on IMD cyclone track data) in the central Bay of
Bengal, where UOHC
S
>250 kj/cm
2
persists (Figure 16).
UOHC and S varied from 6075 kj/cm
2
and 33.5
respectively.
Cyclone Nargis also formed in the southern area of the
Bay of Bengal and was sustained during 27 April3May
2008, during which time it moved northwest but was
then diverted to the northeast. As shown in Figure 16,
Cyclone Nargis intensied twice during the course of its
existence. It was found that rst intensication at 85 deg
E, 14 deg N occurred under conditions of high UOHC
S
(>350 kj/cm
2
), while the second intensication occurred
under conditions of high stratication (S3).
Cyclone Aila formed in the northern area of the Bay of
Bengal and was sustained during 2327 May 2009. It
formed under conditions of high UOHC
S
(Figure 16). In
this case, the intensication cannot be explained based on
our argument due to the unavailability of Argo data near
to coast.
Cyclone Laila formed in the southern area of the Bay of
Bengal and was sustained during 1722 May 2010, during
which time it moved in northwest. It formed and intensied
as a category-1 cyclone under conditions of high UOHC
S
(>400 kj/cm
2
). Due to its high energy input, it was sustained
for two days over land after hitting the coast, causing a lot of
damage along the east coast of India (Figure 17).
Cyclone Thane formed in the southern area of the Bay
of Bengal and was sustained during 2530 December 2011,
during which time it moved west and intensied as cat-
egory-1 cyclone under conditions of high stratication
near to the coast. It crossed the coast in the north of Sri
Lanka (Figure 17).
Cyclone Neelam was sustained during 2931 October
2012 near to Sri Lanka, during which time it moved north-
west and crossed the coast as a tropical storm within a short
period. It was formed and sustained under conditions of
high stratication (3.54; Figure 17).
Cyclone Mahasen formed in the southern area of the
Bay of Bengal and was sustained during 1016 May
2013, during which time it primarily moved northwest,
later changing course and moving northeast. Landfall
occurred over the northern part. It was formed under con-
ditions of high UOHC
S
(>400 kj/cm
2
) and was sustained
for ve days under the conditions of UOHC
S
of 300
400 kj/cm
2
(Figure 17).
The results of the above case studies align well with the
conclusions drawn from the climatological studies. Most of
the case studies suggest that pre-monsoon cyclones occur
and are sustained in regions of high UOHC
S
, whereas
post-monsoon cyclones occur and are sustained in
regions of high stratication. Hence, in addition to the
atmospheric parameters, oceanic parameters like stratica-
tion and UOHC
S
are also important in the intensication of
cyclones.
4. Conclusions
In this study, an attempt has been made to identify the role
of the upper ocean parameters (UOHC and UOHC
S
) in the
intensication and movement of tropical cyclones. Case
studies using Argo data were also performed in support
of the results drawn from the climatology. Freshwater dis-
charge plays a vital role in the stratication of the upper
layer, which was not considered in the previous studies
while estimating the UOHC. Here, the stratication par-
ameter (S) is used to estimate UOHC
S
following Shay
and Brewster (2010).
(1) It was found that a UOHC of >40 kj/cm
2
is usual
during the genesis and intensication of cyclones
in the Bay of Bengal. Stratication (S) varies
from 25 and most of the cyclones in October
form in the region where S>3. UOHC
S
varies
from 50400 kj/cm
2
, which is higher than in the
east and west Pacic and also the Caribbean
(Shay & Brewster 2011). Most of the cyclones
form, intensify and moving over regions of high
UOHC
S
(>120 kj/cm
2
). The minimum threshold
UOHC and UOHC
S
required for the intensication
of cyclones are 30 and 120 kj/cm
2
, respectively.
(2) Severe pre- and post-monsoon cyclones over the
Bay of Bengal are mainly inuenced by the
UOHC
S
and stratication.
Acknowledgements
The authors are thankful to Dr. SWA Naqvi, Director, National
Institute of Oceanography, and Dr. V.S.N. Murty, Scientist-in-
charge, NIO Regional centre, Visakhapatnam for their support
and encouragement. Thanks is offered to the NOAA for pro-
viding the climatology data sets (WOA-09) and the IMD,
New Delhi for the data on cyclone tracks. IRI/LDEO Climate
Data Library for the NCEP-NCAR reanalysis data. Dr. Mrs.
Maneesha is thankful to SERB-Department of Science and
Technology for funding. This is NIO contribution number
5782.
Disclosure statement
No potential conict of interest was reported by the authors.
Journal of Operational Oceanography 145
References
Antonov JI, Seidov D, Boyer TP, Locarnini RA, Mishonov AV,
Garcia HE, Baranova OK, Zweng MM, Johnson DR. 2010.
World Ocean Atlas 2009, Volume 2: Salinity. S. Levitus,
Ed. NOAA Atlas NESDIS 69, Washington, D.C.: U.S.
Government Printing Ofce, 184pp.
Byers HR. 1944. General meteorology. New York: McGraw-Hill,
645 pp.
Emanuel KA. 1986. An airsea interaction theory for tropical
cyclones. Part 1: Steady-state maintenance. J Atmos Sci.
43:585605.
Goni GJ, DeMaria M, Knaff J, Sampson C, Ginis I, Bringas F,
Mavume A, Lauer C, Lin I-I, Ali MM, et al. 2009.
Applications of satellite-derived ocean measurementsto tropical
cyclone intensity forecasting. Oceanography. 22(3):176183.
Goni GJ, Knaff JA and Lin I-I 2010. TC heat potential. In Arndt
DS, Baringer MO and Johnson MR, Eds. State of the Climate
in 2009. Bull Am Met Soc. 91(6):99100.
Goni GJ, Trinanes JA. 2003. Ocean thermal structure monitoring
could aid in the intensity forecast of tropical cyclones. Eos,
Trans Amer Geophys Union. 84:573580.
Gray WM. 1968. A global view of the origin of tropical disturb-
ances and storms. Mon Wea Rev. 96:669700.
Kumar B, Chakraborthy A. 2011. Movement of seasonal eddies
and its relation with seasonal eddies and cyclone heat poten-
tial and cyclogenesis points in the Bay of Bengal. Nat
Hazards. 59(3):16711689.
Lafond EC. 1966. Bay of Bengal. In: Fairbridge RW, editor. The
encyclopedia of oceanography. New York: Van Nostrand
Reinhold Co; p. 110118.
Lin I-I, Liu WT, Wu CC, Chiang JCH, Sui CH. 2003. Satellite
observations of modulation of surface winds by typhoon-
induced upper ocean cooling. Geophys Res Lett. 30:1131.
doi:10.1029/2002GL015674
Lin I-I, Liu WT, Wu CC, Wong GTF, Chen Chu Z, Liang WD,
Yang Y, Liu KK. 2003. New evidence for enhanced ocean
primary production triggered by tropical cyclone. Geophys
Res Lett. 30(13):1718. doi:10.1029/2003GL017141
Lin I-I, Wu C-C, Emanuel KA, Lee I-H, Wu C-R, Pun I-F. 2005.
The interaction of supertyphoon maemi (2003) with a warm
ocean eddy. Mon Wea Rev. 133:26352649.
Lin I-I, Wu C-C, Pun I-F. 2008. Upper ocean thermal structure and
the western North Pacic category 5 typhoons, Part I: Ocean
features and category 5 Typhoons intensication. MonWea
Rev. 136:32883306.
Lin I-I, Chen CH, Pun IF, Liu WT, Wu CC. 2009. Warm ocean
anomaly, air-sea uxes and the rapid intensication of tropical
cyclone Nargis, 2008. Geophys Res Letts, 36:LO3817.
doi:10.1029/2008GL035815.
Locarnini RA, Mishonov AV, Antonov JI, Boyer TP, Garcia HE,
Baranova OK, Zweng MM, Johnson DR. 2010. World Ocean
Atlas 2009, Volume 1: Temperature. S. Levitus, Ed. NOAA
Atlas NESDIS 68, Washington, D.C.: U.S. Government
Printing Ofce, 184pp.
Mainelli MM, DeMaria M, Shay LK, Goni G. 2008.
Application of oceanic heat content estimation to operational
forecasting of recent category 5 hurricanes. Wea Forecasting.
23:316.
Murty VSN, Sarma MSS, Tilvi V. 2000. Seasonal cyclogenesis
and the role of nearsurface stratied layer in the Bay of
Bengal. PORSEC Proceedings. 1:453457.
Prasad TG. 1997. Annual and seasonal mean buoyancy uxes for
the tropical Indian Ocean. Current Sci. 73:667674.
Prasanna kumar S, Muralidharan PM, Prasad TG, Gauns M,
Ramaiah N, de Souza SN, Sardesai S, Madhupratap M.
2002. Why Bay of Bengal less productive during summer
monsoon compared to Arabian sea? Geophys Res Letts. 29
(24):2235. doi:10.1029/2002GL016013
Pun IF, Lin II, Wu CR, Ko DS, Liu WT. 2007. Validation and
application of altimetry-derived upper ocean thermal
structure in the Western North Pacic Ocean for typhoon
intensity forecast. IEEE Trans Geosci Remote Sens. 45(6):
16161630.
Sadhuram Y, Maneesha K, Ramana Murty TV. 2010. Importance
of upper ocean heat content in the intensication and trans-
lation speed of cyclones over the Bay of Bengal. Current
Sci. 99(9):11911193.
Sadhuram Y, Ramana Murty TV, Somayajulu YK. 2006.
Estimation of cyclone heat potential in the Bay of Bengal
and its role in the genesis and intensication of the storms
in Bay of Bengal. Ind J Mar Sci. 35(2):132138.
Sadhuram Y, Rao BP, Shastri PNM and Subrahmanyam MV.
2004. Seasonal variability of cyclone heat potential in the
Bay of Bengal. Nat Hazards. 32:191209.
Sarma YVB, Murty VSN, Rao DP. 1990. Distribution of cyclone
heat potential in the Bay of Bengal. Indian J Mar Sci. 19:102
106.
Scharroo R, Smith WHF, Lillibridge JL. 2005. Satellite altimetry
and the intensication of Hurricane Katrina. Eos,Trans Amer
Geophys Union. 86:366367.
Sengupta D, Raj BGN, Shenoi SSC. 2006. Surface fresh water
from Bay of Bengal run off and Indonesian through ow in
the tropical Indian Ocean. Geophys Res Letts. 33(15):
L22609. doi:10.1029/2006GL027573
Shay LK, Brewster JK. 2011. Eastern Pacic oceanic heat content
estimation for hurricane intensity forecasting. Mon Wea Rev.
138:21102131.
Shay LK, Goni GJ, Black PG. 2000. Effects of a warm
oceanic feature on Hurricane Opal. Mon Wea Rev.
128:13661383.
Varkey MJ, Murty VSN, Suryanarayana A. 1996. Physical
Oceanography of the Bay of Bengal and Andaman sea. In
Ansel AD, Gibson RD, Barnes N, editors. Oceanography
and marine biology. An annual review, 34. London: UCL
Press; p. 170.
Zeng Z, Chen L, Wang Y. 2008. An observational study of
environmental dynamical control of tropical cyclone intensity
in the Atlantic. Mon Wea Rev. 136:33073322.
146 K. Maneesha et al.
... Many previous studies (Shay et al. 2000;Wu et al. 2007;Lin et al. 2009a, b;Goni et al. 2009;Vissa et al. 2013a, b) also emphasized the importance of upper ocean heat content (UOHC), eddies, and other ocean features in the intensification and genesis of TCs. Several studies (Sadhuram et al. 2004(Sadhuram et al. , 2006(Sadhuram et al. , 2012Maneesha et al. 2015;Patnaik et al. 2014) investigated the importance of various ocean features in the intensification and genesis of TCs over the Bay of Bengal (BOB) during both the pre-monsoon (April-May) and post-monsoon (October-November) seasons. These studies inferred that for the genesis of TCs over BOB, a minimum tropical cyclone heat potential (TCHP) threshold of 40 kJ cm −2 is required. ...
... The atmospheric variables like tropospheric RH at 500 hPa, total precipitable water, relative vorticity at 850 hPa, divergence at 200 hPa, and vertical wind shear (VWS) as well as the oceanic parameters, viz. SST, ocean heat content, and warm ocean subsurface are the essential components for cyclogenesis, intensity and governs the life cycle of TCs over the NIO basin (Girishkumar and Ravichandran 2012;Patnaik et al. 2014;Maneesha et al. 2015;Sun et al. 2015;Roy Chowdhury et al. 2020b). Therefore, this study is made to examine how these parameters are responsible for genesis, rapid intensification, and evolution of the considered NIO SUCS cases (Table 1) and discussed in this section. ...
... The weak VWS scenario generally favors TC genesis and intensification, the moderate condition creates an unfavorable (neutral) environment for weak (mature) systems, and the strong scenario favors rapid weakening. According to the studies of Maneesha et al. (2015), most of the BOB TCs originate in the areas where VWS values are < 10m/s. Over AS, the genesis of TCs mostly occurs in the regions where the VWS values range within 5-10 m/s (Evan and Camarago 2011). ...
Article
Full-text available
An attempt is made to investigate the various atmospheric and oceanic conditions that contributed to the genesis and rapid intensification (RI) of the super cyclonic storms (SUCS) formed over the north indian ocean (NIO) basin during 1982–2020. The vertical wind shear supported genesis, with values being weak to moderate in all cases. The Genesis potential parameter was> 30 in four out of six cases, whereas Gonu and Odisha SUCS had values ≤ 30. Equatorial Rossby (ER) wave was the dominant of all the convectively coupled equatorial waves (CCEWs), followed by Madden Julian Oscillation (MJO) before their genesis. In the case of Amphan, all the three CCEWs (i.e., MJO, ER, and Kelvin wave) were present. The ocean conditions were more conducive for tropical cyclone (TC) genesis than the atmospheric conditions. Both sea surface temperature and tropical cyclone heat potential (TCHP) supported the cyclogenesis. In most cases, the setting up of the pre-genesis scenario was heavily influenced by the ocean characteristics, whereas the atmospheric conditions were not that supportive. The environmental conditions that prevailed before RI showed the presence of thick warm waters, a sufficient supply of moisture at the middle of the troposphere, and moderate wind shear in all cases. Sea surface temperature, mid-tropospheric relative humidity, and low-level relative vorticity all had a substantial role in the RI process of all SUCS storms across the NIO basin. During the RI days, TCHP ≥ 60 kJ cm⁻² was observed for Amphan and Gonu, with thick barrier layers for all cases. Gonu encountered a warm core eddy along its track, which provided extra fuel for the RI process. All six TCs are slow to moderate moving ones, which facilitated them to spend sufficient time over the ocean surface and interact with the warm waters to get positive feedback for the RI process.
... The remarkable upper-layer warming trend in the Indian Ocean played a role in the slowdown of global-mean surface warming during the 2000s (e.g., Lee et al. 2015;Nieves et al. 2015;Liu et al. 2016;Cheng et al. 2017;Gao et al. 2018;Li et al. 2018;Rathore et al. 2020). The increase of the Indian OHC (IOHC) also has notable regional impacts, including the rapid sea level rise in low-lying coastal areas (e.g., Han et al. 2010;Nicholls and Cazenave 2010;Jyoti et al. 2019), increased occurrence and severity of marine heatwaves and coral bleaching events (e.g., Wernberg et al. 2013;Feng et al. 2015;Maneesha et al. 2015;Zinke et al. 2015;Oliver et al. 2018), and modulated behaviors of tropical cyclones (e.g., Lin et al. 2013;Maneesha et al. 2015;Albert and Bhaskaran 2020;Vidya et al. 2020;Rathore et al. 2022). In this regard, investigating the IOHC trend is helpful for understanding and predicting climate change at both regional and global levels. ...
... The remarkable upper-layer warming trend in the Indian Ocean played a role in the slowdown of global-mean surface warming during the 2000s (e.g., Lee et al. 2015;Nieves et al. 2015;Liu et al. 2016;Cheng et al. 2017;Gao et al. 2018;Li et al. 2018;Rathore et al. 2020). The increase of the Indian OHC (IOHC) also has notable regional impacts, including the rapid sea level rise in low-lying coastal areas (e.g., Han et al. 2010;Nicholls and Cazenave 2010;Jyoti et al. 2019), increased occurrence and severity of marine heatwaves and coral bleaching events (e.g., Wernberg et al. 2013;Feng et al. 2015;Maneesha et al. 2015;Zinke et al. 2015;Oliver et al. 2018), and modulated behaviors of tropical cyclones (e.g., Lin et al. 2013;Maneesha et al. 2015;Albert and Bhaskaran 2020;Vidya et al. 2020;Rathore et al. 2022). In this regard, investigating the IOHC trend is helpful for understanding and predicting climate change at both regional and global levels. ...
Article
The heat content in the Indian Ocean has been increasing owing to anthropogenic greenhouse warming. Yet, where and how the anthropogenic heat is stored in the Indian Ocean have not been comprehended. Analysis of various observational and model-based datasets since the 1950s reveals a robust spatial pattern of the 0-700 m ocean heat content trend (ΔOHC), with enhanced warming in the subtropical southern Indian Ocean (SIO) but weak to minimal warming in the tropical Indian Ocean (TIO). The meridional temperature gradient between the TIO and SIO declined by 16.4%±7.5% during 1958-2014. The heat redistribution driven by time-varying surface winds plays a crucial role in shaping this ΔOHC pattern. Sensitivity experiments using a simplified ocean dynamical model suggest that changes in surface winds over the Indian Ocean, particularly those of the SIO, caused a convergence trend in the upper SIO and a divergence trend in the upper TIO. These wind changes primarily include the enhancements of westerlies in the Southern Ocean and the subtropical anticyclone in the SIO. Albeit with systematic biases, the ΔOHC pattern and surface wind changes simulated by Coupled Model Intercomparison Project Phase-6 (CMIP6) models broadly resemble the observation and highlight the essence of external forcing in causing these changes. This heat storage pattern is projected to persist in the model-projected future, potentially impacting future climate.
... The location and intensity of high TCHP, that is, west off the Kerala coast with a high value up to 80 kJ⋅cm −2 , compares very well with the observed TCHP (∼80 kJ⋅cm −2 ). The role of ocean heat content is not only limited to the genesis, but also to intensity changes of TCs (Lin et al., 2005;Maneesha et al., 2015). Singh and Koll Roxy (2020) showed that the combination of high upper-ocean heat content with persisting large positive SST anomalies favoured the cyclogenesis of Ockhi in the presence of Madden-Julian Oscillation (MJO) phase 4. The mixed-layer depth near the track is as high as 80 m as shown in Figure 4a. ...
Article
Full-text available
A very severe cyclonic storm (VSCS), Ockhi was conceived in the Bay of Bengal and moved over the Arabian Sea undergoing rapid intensification (RI) in the early stages of its life cycle. Ockhi is simulated using the high‐resolution coupled Hybrid Coordinate Ocean Model and the Hurricane Weather Research Forecast model. The study suggests that sea surface temperature warmer than the seasonal climatological mean with the availability of a large tropical cyclone heat potential (TCHP) has acted as a potential cause for RI when the TC moved over that region. We have conducted experiments with (CP) and without (UCP) ocean coupling. The predicted tracks of UCP and CP experiments agree well with the India Meteorological Department's best track data. However, CP showed a significant improvement in intensity prediction with 61 and 19% for mean sea level pressure and maximum sustained surface wind at 10 m respectively in comparison to UCP. The presence of thermal and haline stratification in the subsurface affects surface cooling. The subsurface turbulent heat flux calculated for the high‐TCHP region under the TC suggests that the upward transport of heat, which increases the enthalpy flux, becomes necessary to bring about RI. The primary circulation, secondary circulation, inflow, thermal structure, moisture distribution and mass flux within the TC environment during the 24‐hr RI period are analyzed to investigate the evolution of TC characteristics for both UCP and CP experiments. The analyses suggest that the UCP experiments show higher values of intensity as compared to CP experiments. Further, a more organized evolution of updrafts is present in the CP simulation, maybe due to the formation of a stable boundary layer. The study shows the significant influence of coupling on surface enthalpy controlling boundary layer characteristics and thus ultimately producing a more organized TC.
Chapter
The severe storms are the disturbed state of the atmosphere and could come in the forms of thunderstorms, squall lines, cloudbursts, tornadoes, hail, tropical cyclones, typhoons, hurricanes, windstorms, dust and sand storms, winter storms, blizzards, etc. They can be understood and analyzed through meteorological observations and derived information. Besides, they could be represented through a numerical weather model to study the associated physical processes, meteorological characteristics and dynamics. However, the advancement in understanding indicates a role of large scale synoptic conditions and ocean and land feedback in governing these regional and local storms. Also, they show climatological variability and a connection to the changing climate. While the whole globe experiences such storms depending upon their geographical relevance, severity depends upon the prevailing meteorological conditions, and strength of the land and ocean feedbacks. South Asia and India experiences most of these storms and the associated characteristics are found to be altering with a changing climate in this region. Based on the geographical relevance, some of these storms exhibited primarily in South Asia and India are described and discussed in this chapter.
Article
Full-text available
This study examines the formation and intensification of tropical cyclones in the Bay of Bengal, focusing on the Upper Ocean Heat Content (UOHC) and other atmospheric and oceanic factors. By analyzing data from 1980 to 2014, we developed a modified Genesis Potential Index (GPI) that incorporates parameters like UOHC, vertical wind shear, relative humidity, and sea surface temperatures. Our findings indicate significant seasonal variations influenced by monsoons, with distinct Cyclogenesis patterns during the pre-monsoon and post-monsoon periods. Additionally, there is an increasing trend in the frequency and intensity of cyclones in recent decades, likely linked to global warming and changing climate patterns, such as the El Niño-Southern Oscillation (ENSO). The refined GPI model shows improved predictive capability for Cyclogenesis in the Bay of Bengal, enhancing early warning systems and disaster preparedness. This research underscores the critical need to integrate atmospheric and oceanic parameters in cyclone model to better understand and predict these severe weather events, ultimately aiding in the mitigation of their impact on vulnerable coastal regions. Continued research and advancements in model techniques are essential to address the challenges posed by a changing climate.
Article
Full-text available
The primary goal of the present paper is to examine variations in frequency and intensity of cyclonic storms over Arabian Sea using Accumulated cyclone energy (ACE) and Genesis Potential Index (GPI) from 1991–2020.For this purpose wavelet analysis is applied to surface and sub-surface ocean parameters viz Sea surface temperature (SST), Latent heat flux (LHF), Mixed layer depth (MLD), Depth of D26 Isotherm and Tropical cyclone heat potential (TCHP) to delve the probable changes. It is observed that the ACE signifies the intensity of tropical storms, has risen by 17.6% during the recent decade (2011–2020). LHF and SST are in phase with the intensification of cyclonic storms from Continuous wavelet transform (CWT) power spectrum analysis. Both SST and GPI were strongly correlated(0.8, 95% significant level) during pre-monsoon season.Siginifcant coherence was observed between frequency of cyclonic storms and TCHP in the recent decades through wavelet coherence transform technique. The cross wavelet transform (XWT) shows the frequency of cyclonic storms and SSTs are in phase during Indian Ocean dipole events. By these observations,this study helps in advance forecasting about formation and intensification of cyclonic storms over Arabian Sea.
Article
Cyclone Amphan is one of the severe cyclones that occurred over the Bay of Bengal region. It has undergone rapid intensification over the northern part, i.e., north of 14° N after its formation. This can be attributed to the intrusion of warm saline waters with temperatures around 31 °C, salinity greater than 33 psu from the coast, and the presence of anticyclonic eddy that moved across the track. Within an anticyclonic eddy sinking, warm, high saline waters are promoted further sinking through diffusive convective mixing processes. Analysis of in situ and model data showed that these waters formed as a thick water column with high heat content in the northern part of the track, which in turn helped the rapid intensification of cyclone Amphan. This thick water column was also clearly evident in tropical cyclone heat potential. A high chlorophyll concentration of 4.5 – 5.3 mg/m3 was observed before the saline water intrusion across the cyclone path. North of 15oN, a sudden drop in the surface chlorophyll concentration of 0.2–1 mg/m3was observed, which can be attributed to further sinking of saltwater due to vertical convective mixing, which suppressed the cyclone-induced upwelling over this region.
Article
In this study, the behaviour of cyclones in the Bay of Bengal in future climatic conditions is analysed with the help of an ocean-atmosphere coupled model. The weather research and forecasting (WRF) model is coupled with the regional ocean modelling system (ROMS) using a model coupling toolkit in the framework of coupled ocean atmosphere wave sediment transport (COAWST) modelling system. The pseudo global warming (PGW) methodology is used to project the cyclones to future climatic (2075) conditions for Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios. The present study considered two cyclones, namely extremely severe cyclonic storm Phailin (2013) and very severe cyclonic storm Titli (2018). The results show that the coupled model well captured the behaviour of cyclones in the atmosphere and the ocean. Compared to the current conditions, the maximum sustainable wind speed increases by 7.2 km/h for both cyclones for the RCP 8.5 scenario in far future (2075). The accumulated cyclone energy (ACE), power dissipation index (PDI) and precipitation increase in future climatic condition. The increase is more significant for RCP 8.5 compared to RCP 4.5 scenario. The cyclone damage potential (CDP) too increases in future climates, the increase is 25% and 113% for RCP 8.5 scenario for cyclone Phailin and Titli respectively. The cyclones intensify more in the future than current conditions due to the combined effect of increased upper ocean heat content (UOHC) and reduced translation speed. In future, during the passage of cyclones, the UOHC is seen to reduce more, which indicates that more energy is transferred from the ocean to the atmosphere. The analysis of the UOHC, the moisture content in the atmosphere, and the atmospheric instability in future conditions show that the atmospheric and ocean conditions are more favourable for the formation of intense cyclones in the future.
Article
Full-text available
This atlas consists of a description of data analysis procedures and horizontal maps of annual, seasonal, and monthly climatological distribution fields of salinity at selected standard depth levels of the world ocean on a one-degree latitude-longitude grid. The aim of the maps is to illustrate large-scale characteristics of the distribution of ocean salinity. The fields used to generate these climatological maps were computed by objective analysis of all scientifically quality-controlled historical salinity data in the World Ocean Database 2009. Maps are presented for climatological composite periods (annual, seasonal, monthly, seasonal and monthly difference fields from the annual mean field, and the number of observations) at selected standard depths.
Article
Full-text available
Remotely sensed infrared images of Hurricane Katrina taken on 26, 27, and 28 August 2005 (Figure 1, left panels) show the aerial extent of the cloud cover and the central “eye” increasing as the storm that swamped areas of the U.S. Gulf Coast intensified. Computer animations of such image sequences show forecasters the tracks of storms and are a familiar staple of weather news. Less well known is the role that satellite altimetry plays both in forecasting conditions that can intensify a tropical storm and in observing the storm conditions at the sea surface. Satellite altimeter data indicate that Katrina intensified over areas of anomalously high dynamic topography rather than areas of unusually warm surface waters. Altimeter data from Katrina also for the first time observed the building of a storm surge.
Article
Full-text available
Several large-scale climate patterns influenced climate conditions and weather patterns across the globe during 2010. The transition from a warm El Nino phase at the beginning of the year to a cool La Nina phase by July contributed to many notable events, ranging from record wetness across much of Australia to historically low Eastern Pacific basin and near-record high North Atlantic basin hurricane activity. The remaining five main hurricane basins experienced below-to well-below-normal tropical cyclone activity. The negative phase of the Arctic Oscillation was a major driver of Northern Hemisphere temperature patterns during 2009/10 winter and again in late 2010. It contributed to record snowfall and unusually low temperatures over much of northern Eurasia and parts of the United States, while bringing above-normal temperatures to the high northern latitudes. The February Arctic Oscillation Index value was the most negative since records began in 1950. The 2010 average global land and ocean surface temperature was among the two warmest years on record. The Arctic continued to warm at about twice the rate of lower latitudes. The eastern and tropical Pacific Ocean cooled about 1 C from 2009 to 2010, reflecting the transition from the 2009/10 El Nino to the 2010/11 La Nina. Ocean heat fluxes contributed to warm sea surface temperature anomalies in the North Atlantic and the tropical Indian and western Pacific Oceans. Global integrals of upper ocean heat content for the past several years have reached values consistently higher than for all prior times in the record, demonstrating the dominant role of the ocean in the Earth's energy budget. Deep and abyssal waters of Antarctic origin have also trended warmer on average since the early 1990s. Lower tropospheric temperatures typically lag ENSO surface fluctuations by two to four months, thus the 2010 temperature was dominated by the warm phase El Nino conditions that occurred during the latter half of 2009 and early 2010 and was second warmest on record. The stratosphere continued to be anomalously cool. Annual global precipitation over land areas was about five percent above normal. Precipitation over the ocean was drier than normal after a wet year in 2009. Overall, saltier (higher evaporation) regions of the ocean surface continue to be anomalously salty, and fresher (higher precipitation) regions continue to be anomalously fresh. This salinity pattern, which has held since at least 2004, suggests an increase in the hydrological cycle. Sea ice conditions in the Arctic were significantly different than those in the Antarctic during the year. The annual minimum ice extent in the Arctic-reached in September-was the third lowest on record since 1979. In the Antarctic, zonally averaged sea ice extent reached an all-time record maximum from mid-June through late August and again from mid-November through early December. Corresponding record positive Southern Hemisphere Annular Mode Indices influenced the Antarctic sea ice extents. Greenland glaciers lost more mass than any other year in the decade-long record. The Greenland Ice Sheet lost a record amount of mass, as the melt rate was the highest since at least 1958, and the area and duration of the melting was greater than any year since at least 1978. High summer air temperatures and a longer melt season also caused a continued increase in the rate of ice mass loss from small glaciers and ice caps in the Canadian Arctic. Coastal sites in Alaska show continuous permafrost warming and sites in Alaska, Canada, and Russia indicate more significant warming in relatively cold permafrost than in warm permafrost in the same geographical area. With regional differences, permafrost temperatures are now up to 2 C warmer than they were 20 to 30 years ago. Preliminary data indicate there is a high probability that 2010 will be the 20th consecutive year that alpine glaciers have lost mass. Atmospheric greenhouse gas concentrations continued to rise and ozone depleting substances continued to decrease. Carbon dioxide increased by 2.60 ppm in 2010, a rate above both the 2009 and the 1980-2010 average rates. The global ocean carbon dioxide uptake for the 2009 transition period from La Nina to El Nino conditions, the most recent period for which analyzed data are available, is estimated to be similar to the long-term average. The 2010 Antarctic ozone hole was among the lowest 20% compared with other years since 1990, a result of warmer-than-average temperatures in the Antarctic stratosphere during austral winter between mid-July and early September.
Article
Full-text available
An attempt has been made to extend the analysis of environmental dynamical control of tropical cyclone (TC) intensity recently performed for the western North Pacific to the North Atlantic. The results show that both the vertical shear and translational speed have negative effects on TC intensity, which is consistent with previous findings for other basins. It shows that few TCs intensified when they moved faster than 15 m s−1. The threshold vertical shear of 20 m s−1—defined as the difference of total winds between 200 and 850 hPa averaged within 5° latitude around the TC center—is found above which few TCs intensified and below which most TCs could reach their lifetime peak intensity. The average intensity of total TCs in the Atlantic is a bit smaller than that in the western North Pacific. The SST-determined empirical maximum potential intensity (EMPI) for a TC for 1981–2003 in this study is slightly higher than that found for 1962–92 by DeMaria and Kaplan in the Atlantic, however. To be consistent with the theoretical TC MPI, a new EMPI has been constructed, which includes the effect of thermodynamic efficiency. This new EMPI marginally improves the estimation of real TC maximum intensity because the thermodynamic efficiency is largely determined by SST. To include the environmental dynamical control of TC intensity, a dynamical efficiency has been introduced, which is inversely proportional to the combined amplitude of the vertical shear and translational speed. With this dynamical efficiency, an empirical maximum intensity (EMI) for Atlantic TCs has been constructed. This EMI includes not only the positive contribution by SST but also the effects of both thermodynamic and dynamical efficiencies, and it provides more accurate estimations of TC maximum intensity. Furthermore, the formulation of the new EMI explains the observed behavior of TC maximum intensity by thermodynamic and dynamical controls in a transparent and easy-to-interpret manner.
Article
Full-text available
Two remote sensing data sets, the Tropical Rainfall Measurement Mission Sea Surface Temperature (SST) and the NASA QuikSCAT ocean surface wind vectors, are analysed to study ocean-atmosphere interactions in cold SST regions formed in the trail of two typhoon events. Anomalously cold SST patches up to 6°C below the surrounding warm tropical ocean SST are found along the trail of typhoon tracks as cold, deep waters are entrained up to the mixed layer due to typhoon forcing. In both typhoon events, significant and systematic weakening of surface wind speed is found over cold SST patches relative to surface wind speed in surrounding regions. The wind speed anomalies disappear as the patches recover to the level of the surrounding SST. The results are consistent with the mechanism proposed by Wallace et al. that surface winds are modulated by SST via stability. As wind within the well-mixed boundary layer moves over the cold patch, boundary layer stability increases, vertical mixing is suppressed, and the vertical wind shear increases; reduction in surface wind speed is caused. In particular, our result shows that this mechanism can act on relatively small spatial (~100 km) and short (~1 day) time scales.
Article
Full-text available
Research investigating the importance of the subsurface ocean structure on tropical cyclone intensity change has been ongoing for several decades. While the emergence of altimetry-derived sea height obser- vations from satellites dates back to the 1980s, it was difficult and uncertain as to how to utilize these measurements in operations as a result of the limited coverage. As the in situ measurement coverage expanded, it became possible to estimate the upper oceanic heat content (OHC) over most ocean regions. Beginning in 2002, daily OHC analyses have been generated at the National Hurricane Center (NHC). These analyses are used qualitatively for the official NHC intensity forecast, and quantitatively to adjust the Statistical Hurricane Intensity Prediction Scheme (SHIPS) forecasts. The primary purpose of this paper is to describe how upper-ocean structure information was transitioned from research to operations, and how it is being used to generate NHC's hurricane intensity forecasts. Examples of the utility of this information for recent category 5 hurricanes (Isabel, Ivan, Emily, Katrina, Rita, and Wilma from the 2003-05 hurricane seasons) are also presented. Results show that for a large sample of Atlantic storms, the OHC variations have a small but positive impact on the intensity forecasts. However, for intense storms, the effect of the OHC is much more significant, suggestive of its importance on rapid intensification. The OHC input improved the average intensity errors of the SHIPS forecasts by up to 5% for all cases from the category 5 storms, and up to 20% for individual storms, with the maximum improvement for the 72-96-h forecasts. The qualitative use of the OHC information on the NHC intensity forecasts is also described. These results show that knowledge of the upper-ocean thermal structure is fundamental to accurately forecasting inten- sity changes of tropical cyclones, and that this knowledge is making its way into operations. The statistical results obtained here indicate that the OHC only becomes important when it has values much larger than that required to support a tropical cyclone. This result suggests that the OHC is providing a measure of the upper ocean's influence on the storm and improving the forecast.
Article
Recent evidence supports the premise that the subsurface ocean structure plays an important role in modulating air–sea fluxes during hurricane passage, which in turn, affects intensity change. Given the generally sparse in situ data, it has been difficult to provide region-to-basin-wide estimates of isotherm depths and upper-ocean heat content (OHC). In this broader context, satellite-derived sea surface height anomalies (SSHAs) from multiple platforms carrying radar altimeters are blended, objectively analyzed, and combined with a hurricane-season climatology to estimate isotherm depths and OHC within the context of a reduced gravity model at 0.25° spatial intervals in the eastern Pacific Ocean where tropical cyclone intensity change occurs. Measurements from the Eastern Pacific Investigation of Climate in 2001, long-term tropical ocean atmosphere mooring network, and volunteer observing ship deploying expendable bathythermograph (XBT) profilers are used to carefully evaluate satellite-based measurements of upper-ocean variability. Regression statistics reveal small biases with slopes of 0.8–0.9 between the subsurface measurements compared with isotherm depths (20° and 26°C), and OHC fields derived from objectively analyzed SSHA field. Root-mean-square differences in OHC range between 10 and 15 kJ cm−2 or roughly 10%–15% of the mean signals. Similar values are found for isotherm depth differences between in situ and inferred satellite-derived values. Blended daily values are used in the Statistical Hurricane Intensity Prediction Scheme (SHIPS) forecasts as are OHC estimates for the Atlantic Ocean basin. An equivalent OHC variable is introduced that incorporates the strength of the thermocline at the base of the oceanic mixed layer using a climatological stratification parameter /No, which seems better correlated to hurricane intensity change than just anomalies as observed in Hurricane Juliette in 2001.
Article
Accurate prediction of the track and intensity of tropical cyclones is highly important for planning the evacuation of densely populated coastal areas and for impact assessment. Though forecasts of Atlantic hurricane tracks have improved greatly during recent years, large errors in intensity forecasts still remain. Dynamical and statistical models are currently being used, with a different range of success, to predict the location of tropical cyclone intensity changes. Statistical prediction models attempt to quantify the relationship between tropical cyclone intensification and variables that can be estimated or observed in real time.
Article
On 4 October 1995, Hurricane Opal deepened from 965 to 916 hPa in the Gulf of Mexico over a 14-h period upon encountering a warm core ring (WCR) in the ocean shed by the Loop Current during an upper-level atmospheric trough interaction. Based on historical hydrographic measurements placed within the context of a two-layer model and surface height anomalies (SHA) from the radar altimeter on the TOPEX mission, upper- layer thickness fields indicated the presence of two warm core rings during September and October 1995. As Hurricane Opal passed directly over one of these WCRs, the 1-min surface winds increased from 35 to more than 60 m s21, and the radius of maximum wind decreased from 40 to 25 km. Pre-Opal SHAs in the WCR exceeded 30 cm where the estimated depth of the 208C isotherm was located between 175 and 200 m. Subsequent to Opal's passage, this depth decreased approximately 50 m, which suggests upwelling underneath the storm track due to Ekman divergence. The maximum heat loss of approximately 24 Kcal cm22 relative to depth of the 268C isotherm was a factor of 6 times the threshold value required to sustain a hurricane. Since most of this loss occurred over a period of 14 h, the heat content loss of 24 Kcal cm22 equates to approximately 20 kW m22. Previous observational findings suggest that about 10%-15% of upper-ocean cooling is due to surface heat fluxes. Estimated surface heat fluxes based upon heat content changes range from 2000 to 3000 W m 22 in accord with numerically simulated surface heat fluxes during Opal's encounter with the WCR. Composited AVHRR-derived SSTs indicated a2 8-38C cooling associated with vertical mixing in the along-track direction of Opal except over the WCR where AVHRR-derived and buoy-derived SSTs decreased only by about 0.58-18C. Thus, the WCR's effect was to provide a regime of positive feedback to the hurricane rather than negative feedback induced by cooler waters due to upwelling and vertical mixing as observed over the Bay of Campeche and north of the WCR.