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A Climatology of Arabian Sea Cyclonic Storms
AMATO T. EVAN
Department of Environmental Sciences, University of Virginia, Charlottesville, Virginia
SUZANA J. CAMARGO
Lamont-Doherty Earth Observatory, The Earth Institute at Columbia University, Palisades, New York
(Manuscript received 8 January 2010, in final form 25 August 2010)
ABSTRACT
On average 1–2 tropical cyclones form over the Arabian Sea each year, and few of these storms are intense
enough to be classified as very severe or super cyclonic storms. As such, few studies have explicitly identified
the seasonal to interannual changes in environmental conditions that are associated with Arabian Sea tropical
cyclogenesis. However, over the last 30 yr several intense Arabian storms did form and make landfall, with
large impacts, which motivates this new study of the basin. The conclusions of earlier studies are visited by
utilizing modern observational and reanalysis data to identify the large-scale features associated with Arabian
tropical cyclone variability on seasonal time scales. Then year-to-year changes in environmental conditions
that are related to interannual variability in Arabian storms during the pre- and postmonsoon periods are
elucidated. The analysis of the relationship between large-scale environmental variables and seasonal storm
frequency supports conclusions from work completed more than 40 yr prior. Investigation of the year-to-year
changes in premonsoon storm frequency suggests that May (June) storms are associated with an early (late)
onset of the southwest monsoon. The findings also demonstrate that November cyclones (the month when the
majority of postmonsoon cyclogenesis occurs) primarily form during periods when the Bay of Bengal ex-
periences a broad region of high sea level pressure, implying that November storms form in either the Arabian
Sea or the Bay of Bengal but not in both during the same year. Finally, the analysis of changes in a genesis
potential index suggests that long-term variability in the potential for a storm to form is dictated by changes in
midlevel moisture.
1. Introduction
Although only a couple Arabian Sea cyclonic storms
form each year, occasionally a very powerful storm will
make landfall. The strongest storm in the recent record
was super cyclonic storm Gonu, which formed in early
June 2007 and made landfall in both Oman and Iran.
Gonu caused an estimated $4 billion (U.S. dollars) in
damages and collectively 100 deaths in Oman, United
Arab Emirates, and Iran (JTWC 2007). To date, Gonu is
the closest any cyclone on record had come to actually
entering the Persian Gulf. One of the most destructive
Arabian Sea storms, in terms of loss of human life, was
very severe cyclonic storm 03A, which made landfall
in the western Indian state of Gujarat in 1998 with a
maximum sustained wind speed of 105 kt (54 m s
21
).
More than 1100 deaths were attributed to this storm,
many of which were reported to be workers in salt mines
that were not evacuated prior to landfall (JTWC 1998).
Although the damage from Gonu and very severe cy-
clonic storm 03A was intense, landfall of seemingly in-
nocuous storms can present opportunity for devastating
losses. For example, in October 2008 deep depression
02A made landfall in Yemen with a sustained wind speed
of only 25 kt (13 m s
21
). Despite the weak nature of the
storm, there was report of widespread flooding, 22 000
displaced people, 180 deaths, and $1 billion in damages
(WHO 2009).
Because the northern Indian Ocean as a whole has
relatively few cyclonic storms in a given year (Lander
and Guard 1998), there are few publications related to
climate and tropical cyclones (TCs) here and even fewer
that explicitly consider storms that form over the Arabian
Sea. Gray (1968) performed a comprehensive summary
of global tropical cyclone activity and the conditions that
Corresponding author address: Amato T. Evan, Department of
Environmental Sciences, University of Virginia, 291 McCormick
Road, Charlottesville, VA 22904.
E-mail: ate9c@virginia.edu
140 JOURNAL OF CLIMATE VOLUME 24
DOI: 10.1175/2010JCLI3611.1
Ó2011 American Meteorological Society
forced observed seasonality of cyclogenesis in every
basin. With regard to storms forming over the Arabian,
Gray (1968) identified the bimodal seasonal cycle of
Arabian storm frequency and attributed the depression
of July and August cyclogenesis to strong vertical shear
in the presence of intense upper-level easterlies and the
seasonal displacement of the monsoon trough over the
Indian subcontinent. Gray otherwise noted that Arabian
storms tended to form during the spring northward ad-
vancement or fall southward withdraw of the monsoon
trough, and that vertical shear values were favorable
poleward of the trough when the trough’s meridional
position was between 58and 108N.
Recently Camargo et al. (2010) summarized more re-
cent findings on tropical cyclones and climate globally,
and here we discuss the subset of Arabian Sea tropical
cyclones in slightly more detail. Lee et al. (1989) exam-
ined environmental characteristics surrounding severe
cyclonic storm 02A, which formed over the Arabian Sea
in June 1979. Lee et al. (1989) identified a series of east-
ward frontal systems that appear to strengthen the Somali
jet and extend its low-level flow eastward across the
Arabian. This intensification of low-level westerlies en-
hanced the cyclonic circulation of a preexisting distur-
bance that was just poleward of the jet axis, which, when
combined with the development of sufficient upper-level
outflow channels, provided the needed conditions for
storm organization and genesis. Camargo et al. (2009)
used fields ofthe so-called genesis potential (GP) index in
conjunction with the Wheeler and Hendon (2004) Madden–
Julian oscillation (MJO) index to determine the role of
the MJO in global cyclogenesis. Camargo et al. (2009)
demonstrated that enhanced values of the GP index
over the northern Indian Ocean during August–October
(ASO) for the active phases of the MJO over the Indian
Ocean were associated with increases in midlevel mois-
ture and low-level vorticity. However, given the bimodal
distribution of Arabian Sea storms, diagnosis of the re-
lationship between Arabian storms and the MJO would
be made more relevant by instead considering the periods
of May–June and October–November. Using cyclone
data from a storm atlas published by the India Meteo-
rological Department (IMD) for the period 1877–1989,
Singh et al. (2000) found neither long-term linear trends
in seasonal Arabian Sea cyclonic storm frequency nor
a statistically significant correlation with the Southern
Oscillation index. However, the quality of this historical
data is not discussed, and therefore it is impossible to
evaluate the robustness of the Singh et al. (2000) results
without further details on the data sources and short-
comings.
In this manuscript we use Joint Typhoon Warning
Center (JTWC) best-track data in conjunction with
observational records and reanalysis data to identify
coherent large-scale conditions associated with Arabian
Sea tropical cyclone frequency on seasonal to inter-
annual time scales. Our goal is to revisit earlier findings
regarding the seasonality of Arabian storms (i.e., Gray
1968) and to identify environmental conditions associ-
ated with observed year-to-year changes in Arabian
cyclogenesis. The remainder of this article is organized
as follows: Section 2 describes data used in this study;
section 3 presents a recent climatology of Arabian storm
frequency and intensity; section 4 discusses intraseasonal
cyclonic storm variability in terms of large-scale envi-
ronmental features; section 5 examines the environmen-
tal conditions associated with year-to-year changes in
Arabian cyclones; and section6 uses the genesis potential
index as another method to understand intra- and in-
terannual Arabian cyclonic storm variability. Section 7
concludesthepaperwithasummaryofthefindingsand
a discussion of other factors not considered here that
may be important to understanding Arabian Sea cyclonic
storm frequency and intensity.
2. Data
Here we consider Arabian Sea tropical cyclones over
the period of 1979–2008 using position and intensity
estimates reported in the JTWC best-track dataset (Chu
et al. 2002). Although JTWC annual tropical cyclone
reports (ATCRs) began to include storm summaries for
the Arabian Sea in 1972, JTWC best-track data for the
Arabian are likely to be of good quality post-1978, since
it is after this date that the ATCRs and best-track re-
cords consistently agree on the number of tropical cy-
clones that formed in thebasin (Chu et al. 2002). Intensity
estimates are reported as the maximum 1-min sustained
wind speed at 10-m height in knots and are made using
the Dvorak model (Dvorak 1975, 1982, 1984, 1995). As
such the quality of these intensity estimates may be low
(Chu et al. 2002).
At the time of writing the International Best Track
Archive for Climate Stewardship (IBTrACS) (Knapp
et al. 2010) included best-track data from the IMD for
the Arabian over the period of 1991–2008. Agreement
in identification of a tropical cyclone for the IMD and
JTWC data (both from the IBTrACS) was high. In
general, disagreement only occurred for cases when the
JTWC identified very weak and short-lived storms whose
maximum wind speeds peaked just above 34 kt for one
or two 6-hourly periods, which were not identified in
the IMD analysis. Intensity estimates from the JTWC and
IMD did differ (both are also from IBTrACS), with the
IMD estimates being consistently 5–10 kt lower than
those from JTWC. However, this may be the result of
1JANUARY 2011 E V A N A N D C A M A R G O 141
comparing 1-min JTWC and 3-min IMD wind speeds
(Knapp et al. 2010). Because we are interested in long-
term changes in Arabian cyclone activity, here we only
use position and intensity data from the JTWC archive.
For our analysis of large-scale conditions associated
with Arabian cyclogenesis, we employ reanalysis fields
from the National Centers for Environmental Prediction–
National Center for Atmospheric Research (NCEP–
NCAR) Global Reanalysis 1 (Kalnay et al. 1996) and sea
surface temperature (SST) data from both the Met Office
Hadley Centre Sea Ice and Sea Surface Temperature
dataset (HadISST) (Rayner et al. 2003) and the Na-
tional Oceanic and Atmospheric Administration Opti-
mum Interpolation Sea Surface Temperature (NOAA
OISST) dataset for the genesis potential index calcula-
tions (Reynolds et al. 2002). Details of how the genesis
potential index was derived and can be calculated are
given in Camargo et al. (2007).
3. Recent cyclonic storm activity
We define an Arabian Sea cyclone as a storm whose
best-track genesis occurs in the northern Indian Ocean
and west of 778E. Most Arabian Sea cyclones form close
to the western coast of the Indian subcontinent and
follow a northerly or northeasterly track. Several storms
have formed more toward the center of the basin or
closer to the equator and have taken a more easterly
path (Fig. 1). Since the vast majority of recent publica-
tions on tropical cyclones and climate have focused on
understanding activity in the Atlantic basin, it is useful
to define the nomenclature used for Arabian Sea storms
in terms of the Atlantic storm intensity classification
system (Table 1).
Based on the JTWC best-track data for the period
1979–2008, 41 cyclonic storms formed in the Arabian
Sea, of which 23 made landfall with tropical depression
or stronger intensities. The average lifetime of these
storms was 3.4 days, and the range of lifetimes is 1–9 days.
In this record 8 storms were classified as severe cyclonic
storms, 7 were classified as very severe cyclonic storms,
and 1 super cyclonic storm was recorded.
One metric of gauging storm frequency and duration
is cyclonic storm days: the number of days that a tropical
cyclone, whose lifetime maximum best-track wind speed
is at least 35 kt (17 m s
21
), is present in the basin. The
annual distribution of monthly total cyclonic storm days
over the Arabian Sea is bimodal, with peaks in activ-
ity occurring May–June and then October–December
(MJOND), with decreased tropical cyclone activity
during the peak of the Indian monsoon (Fig. 2; Gray
1968). Over the period of 1979–2008, there has been an
average of 4.7 cyclonic storm days per year over the
Arabian Sea, with 1981, 1990, 1991, 2000, 2005, 2008
having 0 storms; and 1998 and 2004 having more than
15 cyclonic storm days (Fig. 3). There is an apparent
increase in cyclonic storm days over the period of 1992–
2008 when compared to 1979–91. The mean annual cy-
clonic storm days for the earlier period is 2.3, while the
mean for the latter is 6.4. The difference of 4.1 cyclonic
storm days between the two time spans is statistically
significant at the 97% level based on the tscore of a two-
tailed Student’s tstatistic on the two populations (as well
as when using the Tukey Honestly Significant Differ-
ence Test based on our post hoc determination of the
1991 separation between the two periods). There were
FIG. 1. Map of the Arabian Sea cyclonic storm tracks for the
period 1979–2008. Filled circles represent the genesis points for
each storm. Only storms with genesis in the Arabian Sea are
included here.
TABLE 1. Classification convention for TCs over the Arabian Sea
and the North Atlantic (and eastern Pacific). Winds for Arabian
and Atlantic storms are reported as 1-min averages. Note that the
Atlantic equivalent category for an Arabian storm is an approxi-
mation.
Wind
speed (kt)
Arabian Sea
classification
Approx Atlantic
equivalent
17–33 Tropical depression Tropical depression
34–47 Cyclonic storm Named tropical storm
48–63 Severe cyclonic storm Named tropical storm
64–119 Very severe
cyclonic storm
Hurricane categories 1–3
$120 Super cyclonic storm Hurricane categories 4 and 5
142 JOURNAL OF CLIMATE VOLUME 24
an average of 0.8 storms per year pre-1992 and 1.8 storms
per year post-1992; however, the average storm lifetime
remained more or less constant (3.0 and 3.7 days for the
pre- and post-1992 dates, respectively). Therefore, the
increase in cyclonic storm days is more reflective of an
increase in storm frequency than duration. It is possible
that this increase in cyclonic storm days is related to im-
provements in observational platforms or changes in op-
erational guidelines (e.g., Landsea et al. 2006), and it is
not possible to demonstrate that the increase in storm-
days is physical without further analysis of the best-track
data and its origin.
During the presouthwest monsoon period (May–June;
Fig. 2), from one year to the next, storms generally occur
either during May or June; however, they seldom occur
consecutively in both (Fig. 3). We hypothesize this pref-
erence for one month over the other is a function of the
southwest monsoon onset date, with an early onset fa-
voring May storms and a late onset favoring June storms,
a theory we develop further in section 3 that is consistent
with Gray (1968). During the active months following the
southwest monsoon withdrawal (September–December;
Fig. 2), the division in activity between the pre- and post-
1991 periods is clear, with only 5 months registering some
storm activity in the earlier epoch and 17 active months
in the later epoch (Fig. 3).
Another useful metric for quantifying tropical cyclone
activity is accumulated cyclone energy (ACE; Bell 2003),
which is the sum of the square of a storm’s maximum
sustained 1-min wind speed. Since ACE is a summation
over the lifetime over the storm, seasonal ACE values
are a function of storm frequency, duration, and intensity.
A monthly histogram of ACE for the period 1979–2008
shows that ACE for the premonsoon period is more than
double that of the postmonsoon period (Fig. 4). Clima-
tological total ACE for May and June is 40 and 47 kt
2
,
respectively, while the total ACE for November, the
busiest month in the postmonsoon period, is 25 kt
2
.
Similar to the time series of TC days, there are clearly
two periods of storm activity in the annual ACE time
series, although the division in the ACE series occurs
6 yr after the TC days separation: 1979–97 and 1998–
2008 (Fig. 5). Annual average ACE of the earlier period
(2.2 kt
2
) is roughly one-fourth the average annual ACE
value of the later period (8.2 kt
2
). While increases in
cyclonic storm days over the last 30 yr appear to be re-
lated to increases in storm-days during both the pre- and
postsouthwest monsoon period (Fig. 3), the dramatic
increase in annually averaged ACE is seemingly domi-
nated by four premonsoon cyclonic storms (Fig. 5): very
severe cyclonic storm TC 03A (June 1998), very severe
cyclonic storm TC 02A (May 1999), very severe cyclonic
storm TC 01A (May 2001), and super cyclonic storm
Gonu (June 2007). However, the fact that ACE appears
to dramatically increase at 1998 is suspect, since this is
also the period in time when a Meteosat geostationary
satellite that was positioned at 08E longitude was re-
positioned to 638E, establishing 3-hourly IR and visible
satellite observations directly over the Arabian Sea (e.g.,
Knapp and Kossin 2007). It is probable that an increase
in satellite observations would lead to increased and
earlier detection of weak storms, or it allow for changes
in the JTWC 6-hourly intensity estimates (Landsea et al.
2006). Independent satellite intensity analysis suggests
FIG. 2. Histogram of the number of cyclonic storm days, by
month, for the period 1979–2008. See text for the definition of
a cyclonic storm day. Only storms with genesis over the Arabian
Sea are considered.
FIG. 3. (top) Annual time series and (bottom) monthly scatter-
plot of cyclonic storm days (CS-days) over the Arabian Sea for the
period 1979–2008. In the (bottom) the number of days is indicated
by the fill color of each circle.
1J
ANUARY 2011 E V A N A N D C A M A R G O 143
that seasonal intensity over the northern Indian Ocean is
decreasing over time (Kossin et al. 2007); however, up-
dates to the intensity estimate methodology that account
for dramatic temporal changes in regional satellite cov-
erage show an increase in the intensity of the strongest
storms over the last quarter century (Elsner et al. 2008).
Given the low confidence in the Arabian intensity esti-
mates (Chu et al. 2002) without further data analysis, it is
not yet possible to determine if any portionof the upward
trend in Arabian Sea cyclones, as seen in the JTWC best
track, are physical.
4. Seasonal variability
It is well known that the southwest monsoon circula-
tion dominates the large-scale features of the Arabian
Sea, and that no cyclonic storms develop over the Ara-
bian while the monsoon trough is at its most northerly
position and located over the Indian subcontinent (Fig. 2).
Gray (1968) explored the environmental controls es-
tablishing the bimodal seasonal cycle of Arabian cyclo-
genesis. As mentioned earlier Gray (1968) found that
pre- and postmonsoon storms occurred when the mon-
soon trough was located at 58–108N latitude; however, he
found that during the monsoon onset (July–August),
copious vertical shear and displacement of the trough
over the Indian subcontinent precluded intensification
of any convective system. Gray (1968) also speculated
that cool Arabian Sea surface temperatures associated
with the monsoon onset would not have an important
effect on storm genesis.
Here we revisit these 4-decade-old findings in more
detail by analyzing the seasonal evolution of large-scale
features relevant to cyclone genesis and intensification,
namely sea surface temperature, upper- and lower-level
convergence, wind speed and direction, vertical wind
shear, low-level vorticity, and sea level pressure (SLP).
While this is not an exhaustive list of environmental
conditions that are important to understanding cyclone
activity, at least for the Arabian Sea, these features do
seem to well describe large-scale conditions as they re-
late to cyclone activity in this basin.
The large-scale dynamics of the southwest monsoon
are described in numerous publications, and here we
refer the reader to Hastenrath (1991, chapter 6) for a
more detailed explanation of the circulation patterns
described here. The southwest summer monsoon is as-
sociated with a low level southwesterly jet off the east-
ern coast of northern equatorial Africa (the Somali or
East African jet), and a southerly cross-equatorial flow
along the western Indian Ocean (Fig. 6). Surface wind
stress associated with the jet forces an offshore Ekman
flow, upwelling along the coast of East Africa and the
Arabian Peninsula, and cooling of the Arabian Sea dur-
ing the height of the monsoon period (Fig. 6).
Based on Hadley SST data spanning the period of
1979–2008, the forcing of Arabian sea surface temper-
atures by low-level winds is strongest during July and
August and results in a bimodal annual distribution of
regional SST, with maximums in May (absolute) and
October (relative), and nearly equivalent minimums in
January and July (Fig. 7). Climatologically, the jet and
the southerly cross-equatorial flow begin to develop in
May–June; the maximum in the lower-jet-level wind
speeds and surface ocean cooling is during July–August;
FIG. 4. Monthly histogram of ACE for the period 1979–2008.
ACE is only calculated for storms having genesis points over
the Arabian Sea and a maximum sustained wind speeds .34 kt
(17 m s
21
).
FIG. 5. As in Fig. 3, but for ACE.
144 JOURNAL OF CLIMATE VOLUME 24
and by October, the low-level circulation over much of
the Arabian is northerly and the monsoon trough is
displaced to near the equator (Fig. 6). Despite the strong
wind-driven cooling along the western boundary of the
Arabian Sea, ocean surface temperatures over many
parts of the basin remain above 26.58C, an empirical
threshold for cyclogenesis (Gray 1968), throughout the
entire year (Fig. 6), and most storms form along the
eastern boundary of the Arabian (Fig. 1), where surface
temperatures are 18–48C warmer than those of the ba-
sin’s western sector (Fig. 6).
The Somali jet breaks eastward once it leaves the
coast of eastern Africa, and this westerly branch of the
jet has a latitudinal shift according to the season, with
the jet position slightly north of the equator during the
boreal spring, at a northerly maximum during July–
August, and then taking up a position near or south of
the equator during the fall (Fig. 8). Large-scale low-level
relative vorticity (here calculated as the 925–700-mb
layer-mean vorticity) is stratified about the westerly
branch of the Somali jet, with negative vorticity equa-
torward and positive vorticity poleward of the jet’s axis.
Cyclongenesis consistently occurs poleward of the jet’s
monthly climatological axis (Fig. 8) (Gray 1968). To
some degree the annual cycle of the position and in-
tensity of the jet, coupled with the cool ocean surface
temperatures that result from wind-driven upwelling
along the eastern coast of Africa, explain the pattern
of cyclogenesis from one month to the next over the
Arabian. For example, during the months of July and
August, the jet is at its most poleward position and the
only regions where climatological low-level vorticity
values are favorable for cyclogenesis (Fig. 8) are also
those areas where ocean temperatures are cool because
of wind-driven upwelling and temperature advection
(Fig. 6). During the pre- and postmonsoon periods of
May–June and October–November, respectively, the
FIG. 6. Maps of monthly-mean SST (shaded) and 10-m winds (arrows) for the months of (left) May, (middle) August, and (left) October.
The climatology period is 1979–2008.
FIG. 7. Annual cycle of monthly-mean Arabian Sea SST (8C;
7.58–208N, 508–808E) for the period 1979–2008.
1J
ANUARY 2011 E V A N A N D C A M A R G O 145
equatorialposition of the jet and broad region of positive
vorticity values (Fig. 8) that are coupled with warmer
regional ocean temperatures (Fig. 6) provide a larger
favorable region for storm development.
The genesis points of Arabian Sea cyclones, position
of the Somali jet, and pattern of Arabian Sea SST are
clearly related (Fig. 8). However, the Arabian Sea also
exhibits an annual cycle of vertical wind shear that is
very relevant to understanding the seasonal pattern of
cyclone development (layer vertical shear is defined as
the difference between the 200–150- and 925–700-hPa
layers, calculated using 6-hourly reanalysis data over the
period of 1979–2008; Gray 1968). Over the Arabian Sea,
vertical shear largely follows the magnitude and di-
rection of the 200-hPa wind: during the late fall, winter
(not shown), and early spring months, the upper tropo-
spheric flow poleward of 108N is dominated by the
subtropical westerly jet; and upper-level flow during the
summer months is similarly controlled by the tropical
easterly jet, which develops in late spring and has a
maximum in magnitude during July–August (Fig. 9).
Climatological vertical shear values are between 5 and
10 m s
21
in the regions where cyclone genesis events have
been recorded for the months of May, October, and
November (Fig. 9), suggesting that during these months,
cyclone formations are not necessarily shear limited. As
FIG. 8. Maps of monthly-mean low-level relative vorticity (shaded) and 850-hPa vector winds (arrows). TC genesis locations for each
month are denoted by a cross, and storms that reached a maximum 1-min sustained wind speed of 64 kt (33 m s
21
) are indicated by a circle
at the genesis location. Climatology period for vorticity, winds, and cyclogenesis is 1979–2008.
146 JOURNAL OF CLIMATE VOLUME 24
discussed earlier, during these months the relatively low
shear values are also accompanied by positive low-level
vorticity (Fig. 8) and warm SST (Fig. 6). Cyclogenesis
during the months of June and September occurred in
regions where long-term mean shear values were 10–
25 m s
21
(Fig. 9), implying that storms forming during
the summer months, when the tropical easterly jet is
a maximum in magnitude, are likely to be shear limited.
5. Interannual variability
Although Arabian Sea cyclogenesis has been noted in
May–June and August–December, most storms (70%),
and nearly all (90%) of the very severe and super cy-
clonic storms, form during the months of May, June, and
November. Therefore, it is instructive to examine how
conditions during these months differed when cyclo-
genesis is active (with TCs) and inactive (without TCs)
seasons. To do this we analyze the reanalysis fields com-
posited on storm counts. We define anomalous conditions
associated with storm genesis to be the difference be-
tween the mean fields for months when tropical cyclo-
genesis did occur and the mean fields for months when no
storm genesis took place. Statistical significance is at-
tributed to the composite differences using a two-tailed
Student’s ttest and a 90% significance of difference
threshold.
While it is unlikely that monthly-mean reanalysis fields
are influenced sufficiently by the short-lived Arabian
storms to bias our composites, as this possibility was
FIG. 9. As in Fig. 8, but for monthly-mean vertical wind shear (shaded) and 200-hPa vector winds (arrows).
1J
ANUARY 2011 E V A N A N D C A M A R G O 147
148 JOURNAL OF CLIMATE VOLUME 24
discussed in Swanson (2008), we briefly examined this is-
sue. We considered the differences of June 2007 monthly-
mean fields of the reanalysis variables with another June
2007 mean constructed without including data from those
days when super cyclonic storm Gonu was present in the
basin. Not surprisingly, there was no noticeable change in
the monthly-mean fields that can be attributed to the
passage of this storm (not shown).
For the case of cyclonic storms in May, statistically
significant anomalous conditions include cooler ocean
surface temperatures off the Somali coast that extend
eastward at 108N, low SLP, an enhanced Somali jet and
positive vorticity north of the jet axis, a developing
tropical easterly jet with an upper-level anticyclone cen-
tered over northwestern India, increased vertical wind
shear south of 158N, increased midlevel moisture, and
broad upper-level divergence (Fig. 10). These anomalous
conditions are similar to those present during the south-
west summer monsoon; anomalous onshore low-level
flow along the western coast of the Indian subcontinent,
which forces cooler ocean surface temperatures, is co-
incident with a tropical easterly jet work together to in-
crease the local vertical shear (Figs. 6, 8, and 9). Thusly,
conditions are favorable for May storms to form when
there is an early monsoon onset. Interestingly, May cy-
clogenesis is more favorable when ocean temperatures
are anomalously cool and the magnitude of vertical shear
is anomalously large (Fig. 10).
In many ways anomalous conditions for June storm
genesis are opposite of those for May cyclogenesis. June
storms are associated with an enhanced Somali jet with
a more equatorial position and offshore low-level flow
along the Indian subcontinent, anomalous upper-level
westerlies, low SLP across much of the basin, and an
increase in vorticity in the region of genesis (Fig. 11).
These conditions are consistent with the patterns of
upper- and lower-level winds before the monsoon onset
(Figs. 8 and 9), thus implying that June genesis is asso-
ciated with a late onset of the southwest monsoon. Al-
though weaker vertical shear and increased midlevel
moisture are also present when June storms form, the
differences are not statistically significant, and lower and
upper-level convergence fields are not organized well
enough as to suggest important differences in large-scale
vertical motion.
During the month of November, enhanced cyclonic
storm activity is not as clearly associated with a typical
monsoon circulation. Low-level equatorial easterlies,
an upper-level ridge over the northern Indian subcon-
tinent, and high SLP over the Bay of Bengal conspire to
force regional low-level convergence and upper-level
divergence in the November genesis region (Fig. 12). In
addition, midlevel relative humidity is anomalously high
across much of the Arabian (Fig. 12), which is coincident
with negative anomalies of outgoing longwave radiation
(not shown). There is nearly no anomalous change in
vertical shear or surface temperature in the genesis re-
gion, and no statistically significant anomalies of low-
level vorticity and SLP are associated with November
cyclogenesis (Fig. 12).
As high SLP over the Bay of Bengal is coincident with
Arabian Sea cyclogenesis for the month of November
(Fig. 12), there is the interesting possibility that when
conditions are favorable over the Arabian Sea for
storms to form, they are not over the Bay of Bengal. This
is born out in composites of outgoing longwave radia-
tion, which show positive anomalies over the Bay of
Bengal when composited on Arabian Sea storms. From
1979 to 2008, 9 Arabian Sea and 14 Bay of Bengal
tropical cyclones formed. During 21 years of the 1979–
2008 period, 1 storm formed in either the Arabian Sea
or the Bay of Bengal, no storms formed at all during
8 of these years, and during only 1 yr (1986) did a storm
form in both basins (Table 2). This 1986 Bay of Bengal
storm formed far to the north and had a lifetime of
only 18 h.
To test if this shift of November cyclogenesis to either
the Arabian Sea or the Bay of Bengal observed in the
best-track data is statistically significant, we randomly
reassigned the years during which genesis occurred for
the 14 Bay of Bengal storms and the 9 Arabian Sea
storms and then counted the number of years an overlap
of storms (1 Arabian and 1 Bay of Bengal during the
same November) would occur over the 30-yr span. This
was repeated 10 000 times, and a distribution of the
number of years a storm formed in both basins was
FIG. 10. Anomalous large-scale features associated with May Arabian cyclonic storm genesis. Maps represent the differences between
means of months that did and did not contain a cyclonic storm. Statistical significance at the 90% level is based on a tscore from a two-
tailed ttest of the separation of the means from the two distributions at each grid cell and is indicated by a solid black contour. Features
considered here are (a) SST, (b) 850- and (c) 200-hPa winds, (d) SLP, (e) low-level layer-mean vorticity, (f) layer-mean vertical shear,
(g) 600-hPa relative humidity, and (h) 850- and (i) 200-hPa convergence. Cyclone genesis points are indicated by a cross, and storms that
reached a wind speed of 64 kt or greater during their lifetime are indicated by a circle. Period for the composites is 1979–2008.
1J
ANUARY 2011 E V A N A N D C A M A R G O 149
constructed from the results. From the cumulative dis-
tribution function of this distribution, less than 0.4% of
the simulations resulted in a distribution analogous to
that in the observations, where a storm formed in both
basins during only one year (the average was 4.5 years
that had November storms occur in both basins). There-
fore, we suggest that the lack of overlap between No-
vember storms seen in the best-track data is statistically
significant at the 99% level and is consistent with our
composite analysis. Future work will be aimed at identi-
fying the physical mechanisms that force this preference
for November genesis in one basin or another.
Thus far our analysis has focused on various climato-
logical conditions as they relate to monthly storm ac-
tivity, and it has neglected explicit considerations of
stability. The following section addresses the role of
atmospheric stability in conjunction with vertical shear,
low-level vorticity, midlevel humidity, and ocean surface
temperatures by analysis of the so-called genesis poten-
tial index.
6. Analysis of the GP index
The GP index is an empirically derived index used to
characterize the suitability of local environmental con-
ditions for cyclone genesis (Emanuel and Nolan 2004),
and an in-depth description of the GP index and its
constituents can be found in Camargo et al. (2007).
Briefly, the GP index as used here is defined as
GP 5105h
3/2f
50
3Vpot
70
3
(1 10.1Vshear)2, (1)
where his the absolute vorticity at 850 hPa (s
21
), fis
the relative humidity at 600 hPa (%), V
pot
is the po-
tential intensity (PI, m s
21
) (Emanuel 1988; Bister and
Emanuel 2002a,b), and V
shear
is the magnitude of the ver-
tical wind shear between 850 and 200 hPa (m s
21
). Daily
global GP fields are from the NCEP–NCAR Global
Reanalysis 1 (Kalnay et al. 1996) and the NOAA OISST
(Reynolds et al. 2002) dataset. The GP data have a
horizontal resolution of 2.58. We note that the absolute
magnitude of any GP value is arbitrary and has no direct
physical significance.
Regionally averaged monthly-mean GP index data
can reproduce the annual cycle of cyclonic storms over
the northern Indian Ocean (Camargo et al. 2007). In
addition,the spatial pattern of climatological monthly GP
index reflects the position of historical cyclone genesis
points during each month of the tropical cyclone season
(Fig. 13). Genesis generally occurs in regions where the
climatological-mean GP index has high values, and GP is
mostly low in those areas where no cyclone genesis has
been observed (Fig. 13). In contrast, we also find two May
and one October genesis points west of about 658Ein
regions of climatologically low GP (Fig. 13).
Monthly GP index data also reflect the year-to-year
changes in storm frequency. Differences in monthly GP
index fields composited around storm genesis (similar
to that described in more detail in section 4) all show
positive GP anomalies for years during which a storm
formed, and the spatial patterns of those anomalies well
describe the best-track genesis positions (Fig. 14). In
general genesis coincides with regions of positive GP
anomalies, except for one May storm and one October
storm that formed over the western sector of the Ara-
bian Sea, and for one November storm and one De-
cember storm that formed very close to the equator. It is
also interesting to note that November GP anomalies
are less than zero over the Bay of Bengal when com-
posited on Arabian Sea genesis (only the western part of
the Bay of Bengal is shown, Fig. 14), further supporting
the theory of an ‘‘either/or’’ basin preference for No-
vember storm formation.
We note that a similar composite analysis using PI
instead did not show broad regions of positive potential
intensity anomalies that were clearly associated with
genesis locations. Hart et al. (2007) found a memory of
40–60 days in PI fields after the passage of a storm in the
Atlantic and Pacific basins, and so we also examined the
effect of TCs on local PI to determine if the storms
themselves may be affecting our GP composite analysis.
We repeated the methods of Hart et al. (2007) for all
Arabian Sea storms during 1979–2008, but we instead
found that on average the PI anomalies decay on an
e-folding time scale of 5–7 days (not shown). Therefore,
the possibility of the storms strongly affecting the GP
composite analysis is very low.
One benefit of utilizing GP data is the ability to evaluate
the temporal and spatial characteristics of basinwide storm
activity independent of best-track data. We create a sea-
sonal time series of Arabian GP that is an average of
monthly GP values in the locations where historical cy-
clogenesis has occurred. This is in effect drawing a box
around the locations where storms have formed in the past
(this ‘‘box’’ changes from one month to the next) and then
averaging the GP values in this area to calculate seasonal
means. The time series of Arabian seasonal GP has a min-
imum in 1984 and a maximum in 1993 and exhibits a sta-
tistically significant upward trend (Fig. 15). From 1986 to
2003 seasonal GP varies with a very regular pattern of local
minima (1986, 1991, 1997) that are immediately followed
by local maxima (1987, 1993, 1999), then again minima
(with values larger than the previous minima: 1989, 1995,
2001), and lastly another maxima (with values that are
smaller than the previous maxima: 1990, 1996, 2002). This
150 JOURNAL OF CLIMATE VOLUME 24
FIG. 11. As in Fig. 10, but for anomalous large-scale features associated with June Arabian cyclonic storm genesis.
1J
ANUARY 2011 E V A N A N D C A M A R G O 151
FIG. 12. As in Fig. 10, but for anomalous large-scale features associated with June Arabian cyclonic storm genesis.
152 JOURNAL OF CLIMATE VOLUME 24
3- and 6-yr periodicity is odd, but we have not yet identi-
fied an artificial source of the repetition and for now
should assume it is physical. A 1-4-6-4-1 low-pass filter of
the seasonal GP time series shows the low frequency
decrease in GP values from 1979 until 1985 and the
subsequent increase in GP through 2008, as well as the
5–6-yr periodicity in the time series that persists from at
least 1985 to 2008 (Fig. 15). The difference between
mean GP values pre- and post-1992 (1.0 and 1.4,
respectively) is statistically significant at the 99% level.
Therefore, also considering the statistically significant
upward trend, to some extent the GP data does support
a physical interpretation of the increase in cyclonic
storms days (Fig. 3), which we determined was largely
due to increases in storm frequency rather than duration.
It is well known that Indian monsoon dynamics can be
externally forced by ENSO (e.g., Shukla and Paolino
1983; Kumar et al. 2006), and it is possible that tropical
FIG. 13. Monthly-mean GP over the Arabian. GP climatology period is 1979–2008, and data are from daily reanalysis atmospheric and
weekly SST fields. Note that genesis points are only plotted for storms that formed over the Arabian Sea.
TABLE 2. Years during which November TCs formed over the Arabian Sea or the Bay of Bengal. The only year when a storm formed in
both basins was 1986.
Arabian Sea Bay of Bengal
Storm years 1979, 1980, 1982, 1986, 1993, 1994, 1997, 2003, 2004 1981, 1983–88, 1992, 1995, 1998, 2002, 2005, 2007, 2008
1J
ANUARY 2011 E V A N A N D C A M A R G O 153
cyclone activity in the Arabian Sea is related to ENSO in
the same way that monsoon rainfall is coupled to ENSO
variability in the 2–7-yr time scales (Torrence and
Webster 1999). Perhaps more relevant is that strong
Nin
˜o events are often accompanied by a delayed mon-
soon onset (Joseph et al. 1994). However, we have not
found a robust connection between metrics for storm
activity and ENSO. For example, using a definition for
an ENSO event similar to that of Trenberth (1997),
mean seasonal (MJOND) cyclonic storm days and ACE
values are not statistically different when separated by
seasonal positive and negative ENSO events (95% sig-
nificance level). In addition, difference maps of mean
monthly GP for different ENSO phases, created in a
manner similar to that done in Fig. 14 and for the same
months, do not show large and coherent regions of posi-
tive or negative GP anomalies over the Arabian (not
shown). It is likely that the periodicity in the smoothed
GP time series (Fig. 15) is at some level forced by ENSO.
However, without a clear physical mechanism for de-
termining how this relationship evolves over time, it is
difficult to ascertain the relevance of ENSO to Arabian
tropical cyclone activity without a more in-depth in-
vestigation, which is beyond the scope of this work.
In theory, reanalysis data are consistent over time, and
therefore we are able to extend the Arabian Sea GP
time series in Fig. 15 back to 1950 (Fig. 16). Over the last
60 yr, seasonal Arabian GP has exhibited large decadal-
scale swings; GP is above the long-term mean for much
of the first half of the time series and below that mean
during the second half of the record. The maximum in
GP occurs in 1960 and the minimum in 1984, with near-
mean values at the beginning and end of the record.
Interestingly, the 30-yr period we consider here is the
minimum in GP, and therefore storm formation, over
the last 60 yr (Fig. 16). Spectral analysis on the 59-yr GP
time series (not shown) suggests that a 3–6-yr periodicity
in GP that exists from the mid-1980s through 2000 (Fig.
15) is local to that period only and not a regular feature
of the entire dataset.
It is possible that the GP time series suffers from some
nonphysical artifact in the reanalysis data. One way to
estimate, to first order, the validity of the GP data over
these long time scales is to plot Arabian Sea storm
counts from the JTWC best track over this same period.
Keeping in mind that there is little confidence in the
best-track storm counts pre-1978, the level of agreement
between these two totally independent estimates of
FIG. 14. Anomalous monthly-mean GP composites. Difference maps created by subtracting monthly-mean GP for months without storm
activity from the mean for months that did contain at least one storm (1979–2008).
154 JOURNAL OF CLIMATE VOLUME 24
storm formation is surprising (Fig. 16). Besides the up-
swing in storm counts from 1970 to 1978, the two lines
follow the same decadal patterns, and the correlation
coefficient between the two is 0.78 (60% of the variance
in one time series can be explained by the other). In ad-
dition, the nonfiltered annual time series of Arabian GP
and JTWC storm counts is well correlated with an Rvalue
of 0.62 (39% of variance explained, not shown). Differ-
ences between the JTWC data and the GP for the 1970–
78 could be due to error in the storm counts, a breakdown
in the robustness of the GP formulation over this period,
biases in the NCEP data, or a mix of all three.
To identify the factors that are forcing observed var-
iability in the seasonal Arabian Sea GP time series (Fig.
16), and by association storm formation, we plot simi-
larly constructed time series of SST, low-level vorticity,
layer-mean vertical wind shear, and 600-hPa relative
humidity, as these are all input to the GP calculations
(Fig. 17). The time series of SST is increasing over this
period at a rate of 0.018Cyr
21
, similar to that reported
by Clark et al. (2000), and the time series of relative
humidity is decreasing at a rate of 0.13% yr
21
, while
relative vorticity and vertical shear remain generally flat
(Fig. 17). It is obvious that the smoothed relative hu-
midity time series (Fig. 17) is most similar to the GP
series (Fig. 16), and the two are correlated with an Rvalue
of 0.90 (81% variance explained). The smoothed pattern
of relative vorticity (Fig. 17) is also similar to that of GP
(Fig. 16), with a correlation Rvalue of 0.71 (51% var-
iance explained) for the smoothed series. The time se-
ries of vertical shear is not well correlated with GP, and
the SST time series is negatively correlated with the GP
data (Rvalue of 20.52). Thusly, changes in relative vor-
ticity and midlevel moisture seem to dominate the long-
term variability of Arabian GP.
A time series of 600-hPa relative humidity (Fig.17) and
specific humidity (notshown) are nearly indistinguishable
(Rvalue of 0.98 for the unsmoothed annual time series of
each), while 600-hPa temperature is not well correlated
with relative humidity. It is plausible that dynamically
forced reductions in midlevel moisture are driving the
decline in relative humidity and therefore GP over the
last 60 yr.
7. Discussion and concluding remarks
In this study we have attempted to understand the
relationship between Arabian Sea cyclonic storms and
their large-scale environment by analyzing observational
and reanalysis data. Analysis of monthly cyclonic storm
days and ACE indicate that starting in the early 1990s,
there has been an increase in the numbers, duration, and
intensity of Arabian Sea cyclones (Figs. 3 and5), although
data quality issues suggests these increases in storm
metrics are likely nonphysical. There is a well-known,
bimodal distribution to seasonal Arabian cyclonic storm
activity (Figs. 2 and 4). We demonstrated how the sea-
sonal cycle in activity is a function of the state of the
coupled low-level winds and surface ocean temperature
(Fig. 6) by presenting long-term monthly-mean maps of
low-level winds and relative vorticity, vertical wind shear,
and 200-hPa winds, showing how these environmental
features change together over the course of the cyclone
FIG. 15. Time series of seasonal Arabian Sea GP. The seasonal
time series (thin line) is an average of GP data for the months of the
Arabian cyclone season (May, June, and September–December)
in the regions where historical cyclogenesis has occurred. The
smoothed series (thick black line) is created by applying a 5-yr low-
pass filter (1-4-6-4-1) to the seasonal series.
FIG. 16. Time series of seasonal Arabian Sea GP (black line) and
storm counts (gray line) for the period 1950–2008. These smoothed
time series are created by filtering the annual time series of each
variable with a 5-yr low-pass filter. Annual time series is defined as
in Fig. 15.
1J
ANUARY 2011 E V A N A N D C A M A R G O 155
season to establish regions over the Arabian Sea that are
favorable for storm development (Figs. 8 and 9), consis-
tent with earlier findings (Gray 1968).
We hypothesized that in addition to shaping the
pattern of seasonal variability, year-to-year changes in
large-scale features over the Arabian Sea also forced
interannual variability in storm frequency. To test this
we analyzed difference maps of SST, SLP, relative vor-
ticity, vertical wind shear, 850- and 200-hPa vector winds,
600-hPa relative humidity, and upper- and lower-level
convergence, composited around storm counts for the
three most active months (May, June, and November).
These composite maps all suggest that large-scale fea-
tures coherently organize themselves in such a way as
to create an anomalous environment that is conducive
to cyclonic storm activity. We found that May cyclo-
genesis events were associated with large-scale condi-
tions, consistent with an early southwest monsoon onset
(Fig. 10), while June storms were associated with condi-
tions consistent with a delayed monsoon onset (Fig. 11).
November storms were most clearly associated with sea
level pressure anomalies over the Bay of Bengal, implying
a preference for November storm formation in either the
ArabianortheBayofBengalbutnotinbothatthesame
time (Fig. 12; Table 2).
We used the genesis potential index as another way of
understanding the relationship between Arabian tropi-
cal cyclones and the large-scale environment. Long-term-
mean GP fields all show positive GP anomalies in the areas
of historical cyclogenesis (Fig. 13), supporting the hypoth-
esis that over the course of the season, environmental
features coherently organize themselves in such a way
as to create regions suitable for cyclogenesis. Monthly
GP difference maps, composited around cyclonic storm
frequency generally show positive GP anomalies in the
regions where storm genesis has taken place, supporting
our hypothesis that year-to-year changes in large-scale
environmental conditions force interannual variability
Arabian storms (Fig. 14).
Since monthly GP fields reproduce the seasonal pat-
terns of cyclogenesis, we analyzed a regional Arabian
GP time series to determine if the time evolution of the
GP is useful in understanding the time series of seasonal
Arabian cyclonic storm days and ACE. Over the last
30 yr, seasonal Arabian GP has increased (Fig. 15), sup-
porting a physical interpretation of the upward trends
in storm metrics from the best track. However, when
looking over the last 60 yr, seasonal Arabian GP was
much higher during the late 1950s through the early
1960s, and that recent values were below the mean. Sur-
prisingly, seasonalmean GPwas very well correlated with
annual Arabian Sea storm counts from the historical re-
cord (Fig. 16). We lookedat time series of GP constituent
variables and found that most of the variance in the GP
data (Fig. 15) can be explained by changes in relative
humidity, and to a lesser degree changes in relative vor-
ticity (Fig. 17).
GP values are large over the Persian Gulf from July
through September (Fig. 13). Clearly no storm genesis
could be expected over this relatively small body of water,
and entrainment of dry desert air from the surrounding
environment into any storm that may enter the gulf would
overwhelm the effect of very warm water temperatures
and climatologically low vertical shear (Fig. 9). However,
it is interesting to speculate on the fate of a storm that
would track into the Persian Gulf, especially since this
nearly occurred in 2007 with super cyclonic storm Gonu.
The large-scale dynamics of the Indian Ocean and the
southwest monsoon are complicated, owing to the cou-
pled response to external forcing, such as the Southern
Oscillation (e.g., Shukla and Paolino 1983), and the re-
gion’s internal dynamics (Saji et al. 1999; Webster et al.
1999). We have attempted to compartmentalize the dy-
namics of the Arabian to simplify the analysis of factors
FIG. 17. Seasonal Arabian time series of (from top to bottom)
SST, low-level vorticity, layer-mean vertical wind shear (note the
inverse yscale for vertical shear), and 600-hPa relative humidity.
Description for individual time series plots as in Fig. 15.
156 JOURNAL OF CLIMATE VOLUME 24
influencing cyclonic storm development here. However,
because of this simplification, we are neglecting the role
of coupled equatorial processes, such as the equatorial
Indian dipole (Saji et al. 1999; Webster et al. 1999),
variability of the Seychelles–Chagos thermocline ridge
(Vialard et al. 2009), and the influences of these pro-
cesses on the strength and timing of Arabian low-level
winds and coastal upwelling (Izumo et al. 2008). Here
we also do not account for the effect of the MJO on the
year-to-year variability of seasonal Arabian Sea tropical
cyclone activity (Camargo et al. 2009). It is possible that
considering the enhanced convective activity associated
with one or more phases of the MJO, in conjunction with
the large-scale ocean–atmosphere patterns associated
with cyclogenesis we describe here, will help to paint
a more complete picture of the environmental condi-
tions associated with Arabian Sea storm activity.
The Arabian Sea is also a region with intense dust
outbreaks that originate over either the Arabian Pen-
insula or the Pakistan–Afghanistan region (e.g., Evan
et al. 2006). It is interesting to speculate on the possi-
bility that dust outbreaks here may indirectly influence
tropical cyclone activity in a manner similar to what has
been proposed for African dust outbreaks and Atlantic
hurricanes (Evan et al. 2008). Initial efforts to determine
the importance of mineral aerosols on Arabian Sea SST,
performed in a manner similar to those in Evan et al.
(2009) for the Atlantic, imply that Arabian Sea SST is
not sensitive to mineral aerosols via the aerosol direct
effect (not shown). However, other work has suggested
the dust outbreaks may alter the state of the southwest
monsoon via the so-called elevated heat pump (Lau
et al. 2009). If springtime dust outbreaks deposit mineral
aerosols over snow- and ice-covered surfaces of the
Himalayan foothills, the resulting reduction in albedo
would provide an elevated heat source via the absorp-
tion of solar radiation by the aerosols, resulting in an
upper-level warm-core anticyclone over northern In-
dian and enhanced monsoon flow (Lau et al. 2009).
However, whether this proposed causal chain is robust is
debatable, and any consequences on seasonal Arabian
Sea tropical cyclone activity are not yet clear.
Acknowledgments. Partial support for this work was
provided by a grant from Risk Prediction Initiative. We
are grateful for correspondence with R. Murnane and
R. Pappert. We thank Christopher Landsea and two
anonymous reviewers for their comments on an ear-
lier version of this paper.
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