Tropic Cyclone

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Tropical cyclone formation and motion in the Mozambique Channel

Corene J. Matyas

Department of Geography, University of Florida

3141 Turlington Hall, Gainesville, FL 32611

1-352-294-7508 (phone)

1-352-392-8855 (fax)

[email protected]

National Science Foundation BCS: 1053864

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Abstract Although tropical cyclones (TCs) forming in the Mozambique Channel are relatively

close to land and have affected vulnerable populations, few studies specifically examine these

storms. This study analyzed formation frequency and location and storm motion during 1948-

2010. A Geographic Information System (GIS) was employed to calculate storm trajectory and

determine whether or not landfall occurred. Reanalysis data from NCEP-NCAR were examined

to identify environmental conditions such as 500 hPa geopotential heights and precipitable water.

Nonparametric statistical tests explored relationships between these conditions, TC attributes,

and four teleconnections known to influence circulation patterns in the greater Southwest Indian

Ocean: the El Niño Southern Oscillation (ENSO), Indian Ocean Subtropical Dipole (IOSD),

Madden-Julian Oscillation (MJO), and Southern Annular Mode (SAM). Results show that 94

TCs formed in the channel, with approximately 50% making landfall. Formation frequency

varied under different phases of the SAM, IOSD, and MJO. Findings differed when the study

period was divided in half, suggesting that inclusion of data prior to 1979 be interpreted

cautiously. During the second period, formation tended to occur in the northern (southern)

portion of the channel when the IOSD and SAM were negative (positive). The MJO and SAM

were associated with differences in precipitable water values, while the MJO and IOSD were

associated with track curvature. Geopotential height anomalies at 500 hPa varied under the three

phases of ENSO.

Key words: tropical cyclone, Mozambique Channel, El Niño Southern Oscillation, Southern

Annular Mode, Madden-Julian Oscillation, Indian Ocean Subtropical Dipole

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1. Introduction

Tropical cyclones (TCs) forming in the Southwest Indian Ocean (SWIO) repeatedly

affect island nations and countries on the mainland of Africa (e.g., Vitart et al., 2003; Malherbe

et al., 2012). On average, 12-13 TCs form in the SWIO basin each year, accounting for about

14% of the global total (Jury, 1993; Ho et al., 2006; Mavume et al., 2010). The Mozambique

Channel (MC) is located on the western edge of the SWIO (Figure 1) and is bordered on either

side by two economically disadvantaged countries. Socio-economic inequality is high in

Mozambique (Silva, 2008) and it ranks 185th on the Human Growth and Development Index of

187 countries and UN-recognized territories (UNDP, 2011). Several TCs such as Eline (2000),

Dera (2001), and Favio (2007) have devastated the country in recent years (du Plessis, 2002;

Reason and Keibel, 2004; Reason, 2007; Klinman and Reason, 2008; Malherbe et al., 2012).

Madagascar experiences landfall on both the western and eastern sides of the island. Multiple

landfalls occurring in a single month have caused mudslides and crop failure (Naeraa and Jury,

1998; Brown, 2009). Due to the high vulnerability of populations in this region, it is important to

understand the conditions under which TCs form in the MC and the trajectories they take,

especially the conditions associated with landfall.

Although TCs forming in the MC are in close proximity to land, few studies have

specifically examined this subset of SWIO storms. Many TC climatology analyses for the greater

SWIO basin have only considered storms forming east of Madagascar (Jury, 1993; Jury et al.,

1999; Chang-Seng and Jury, 2010; Ash and Matyas, 2012). These studies omitted “Channel

TCs” as they comprise 10% or less of basin-wide activity. Mavume et al. (2010) and Ho et al.

(2006) did include the MC in their study area but did not report separate results for TCs forming

in the channel as opposed to those passing through it. Klinman and Reason (2008) and Reason

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(2007) stated that the small number of TCs generated in the MC normally track southwards

without making landfall, which could be another reason that they are under-studied.

Yet Channel TCs have caused deaths, injuries, and economic losses in the region. Reason

(2007) describes the environmental conditions present when Cyclone Dera (2001) formed in the

MC and made landfall over Mozambique where it added to the flooding rainfall already received

in the region. During the 2003 season, two Channel TCs made landfall in Mozambique and

caused wide-spread damage. Rainfall from Cyclone Delfina triggered flooding in the north-

central part of Mozambique, and the 43 m s-1 winds associated with Cyclone Japhet caused

structural damage farther south along the coastline (FAO, 2003; JTWC, 2003; Kadomura, 2005).

Thirty people perished during these two TCs and more than 400,000 people were displaced.

Matyas and Silva (2013) found that the eight-day rainfall event associated with Delfina likely

contributed to the economic decline of subsistence farmers measured two years later. The losses

caused by Dera, Delfina, and Japhet provide justification for research that focuses only on TCs

that form within the MC

The current study conducted an exploratory analysis of TCs that formed in the MC to a)

assess the typical conditions under which they form, b) characterize their movement, and c)

determine if atmospheric teleconnections known to influence TCs within the larger SWIO have

similar associations with TCs in the MC. The next section summarizes the results of previous

research to present an overview of the environmental conditions within the MC and to establish

how the teleconnections should influence conditions within the MC by discussing their influence

on TCs in the greater SWIO. Section three details the use of a Geographic Information System

(GIS) to construct the datasets, and describes the statistical tests performed to explore the

strength and direction of relationships between TC attributes, environmental conditions, and

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teleconnection indices. The results begin with a general description of the average conditions

under which TCs form and move in the MC. Associations between environmental conditions and

TC formation latitude and month, trajectory, and landfall location are presented next. Then,

relationships between formation frequency, location, and storm track are related to the

teleconnections. After discussion of the results, a concluding summary and suggestions for future

research are presented.

2. Environmental conditions in the Mozambique Channel

The MC has relatively weak easterly vertical wind shear and high sea surface

temperatures (SSTs) averaging 28° C during the austral summer, which are conditions conducive

to TC formation (Jury and Pathack, 1991; Suzuki et al., 2004; Mavume et al., 2010). Cross-

equatorial trade-wind flow is a key component for moisture advection into the MC (Jury and

Pathack, 1991) and the Intertropical Convergence Zone (ITCZ) is an important mechanism for

TC genesis. During the TC season, the ITCZ stretches across the channel between 15 – 20° S

(Jury and Pathack, 1991; Jury, 1993). Winds are easterly (westerly) in the upper levels and

westerly (easterly) in the lower levels for locations north (south) of the ITCZ. This area of wind

shear along the ITCZ provides cyclonic vorticity at low levels and divergent anticyclonic

outflow aloft to aid tropical cyclogenesis (Gray, 1968). TC genesis can also occur from transient

convective waves that slow when reaching the MC (Jury et al., 1991). The current study will

analyze SSTs, precipitable water, and vertical wind shear to explore the range of conditions

under which TCs form in the channel.

The zonal component of steering flow in the SWIO varies on an interannual scale (Vitart

et al., 2003). The Mascarene high is a key component of TC steering currents and is normally

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centered near 30° S and 75° E (Bessafi and Wheeler, 2006). Midlevel winds tend to be weak

(strong) and from the east (west) over the northern (southern) MC. Neumann and Randrianarison

(1976) and Jury and Pathack (1991) found that TCs in the MC moved towards the southwest or

south save for those tracking near the southwestern coast of Madagascar, which moved towards

the southeast. Chang-Seng and Jury (2010) explained that during favorable TC seasons in the

SWIO, a wave train in the jet stream occurs over the MC with a trough axis anchored over

Mozambique and ridge southeast of Madagascar. This leads to enhanced westerlies from the

subtropical jet and strong steering currents that can guide TCs southeast and out of the channel.

On the other hand, weak steering currents can lead to meandering trajectories and prevail when

geopotential heights are relatively high (Williams et al. 1984). The frequency with which TCs

take more straight trajectories towards the southeast as opposed to looping trajectories and

motion towards the south and southwest will be explored in this study.

In the SWIO, TC formation location and motion varies on interannual (Chang-Seng and

Jury, 2010) as well as intra-seasonal (Leroy and Wheeler, 2008) time scales. Researchers agree

that several atmospheric teleconnections influence TCs in the greater SWIO. Conditions

associated with the El Niño Southern Oscillation (ENSO) are a major contributor to the steering

flow in the region. Above normal SSTs occur throughout the tropical South Indian Ocean during

El Niño events due to a weakened Mascarene high that results in weak easterly winds and less

evaporative cooling (Manhique et al., 2011). Yet, TC genesis is reduced due to the high shear

created by enhanced westerly winds in the subtropics (Jury, 1993; Kuleshov et al., 2008;

Mavume et al., 2010). These strong westerlies cause TCs forming east of the MC to recurve

before reaching Madagascar, resulting in fewer landfalls (Ho et al., 2006; Kuleshov et al., 2008;

Ash and Matyas, 2012). When La Niña conditions are present, TCs may form far to the eastern

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boundary of the SWIO and take a long zonal track with landfall over the African countries due to

steering from a strong Mascarene high (Jury, 1993; Vitart et al., 2003; Mavume et al., 2010; Ash

and Matyas, 2012). The current study will determine whether TC attributes, SSTs, and steering

currents differ according to the phase of ENSO when TCs form in the MC.

Interannual variations in the Mascarene high also play an important role in the

development of the Indian Ocean Subtropical Dipole (IOSD) (Behera and Yamagata, 2001). The

IOSD is an oscillation of SSTs between the southwestern and southeastern Indian Ocean. During

a positive IOSD event, a strong Mascarene high creates weaker surface winds towards the west

that allow anomalously high SSTs to develop, while in the east, stronger winds enhance

evaporative cooling to produce anomalously low SSTs (Suzuki et al., 2004). In response, a

surface low pressure anomaly develops over the warm waters southeast of Madagascar. The

cyclonic circulation enhances moisture advection into southeast Africa (Washington and Preston,

2006) and convergence is enhanced over the southern portion of the MC (Reason, 2002). Thus

TC formation may be more frequent in the southern MC under positive IOSD conditions.

Experiments conducted by Reason (2002) show that during negative IOSD events, anomalous

high pressure develops over the anomalously cool waters southeast of Madagascar. The

resulting anticyclonic circulation creates strong divergent flow from the east at 850 hPa in the

southern portion of the MC and enhanced vertical wind shear due to strong northwesterly flow at

200 hPa. Winds over the northern MC are weaker in contrast. Suzuki et al. (2004) found below

normal SSTs in the southern channel during negative IOSD events. This suggests that formation

may occur more frequently in the northern rather than southern portion of the MC when the

IOSD is in a negative phase as SSTs are warmer there and vertical wind shear is reduced.

Hermes and Reason (2005) found that SSTs in both the South Atlantic and South Indian Oceans

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are modulated by wave number 3 or 4 patterns during positive dipole events and the Antarctic

Oscillation (AAO, described below) during negative dipole events. This suggests that

hemispheric-scale forcing influences the position and strength of the subtropical highs which

then influences the trade winds and westerlies, finally impacting SSTs on which the dipole

indices are based. The current study will investigate whether formation in the southern (northern)

portion of the channel may be enhanced under positive (negative) IOSD conditions and will also

look for linkages between the IOSD and AAO when TCs form in the channel.

Middle latitude wind circulations are an important influence on the recurvature of TCs

(Hodanish and Gray, 1993). Although previous research has linked the Arctic Oscillation with

TC formation and tracks in the northern hemisphere (Larson et al., 2005; Choi and Byun, 2010),

little can be found in the literature on the association of the Southern Annular Mode (SAM) and

SWIO TC tracks. The SAM, or Antarctic Oscillation, is a dipole of atmospheric pressure

between Antarctica and middle latitudes of the southern hemisphere that tends to be strongest

during December (Gong and Wang, 1999; Pohl et al., 2010). When the SAM is positive,

anomalous low (high) pressure occurs over Antarctica (the Southern Ocean), and the subtropical

jet and middle latitude westerly winds shift poleward in response. Stronger zonal winds located

15° – 30° S are associated with positive phases of the SAM (Meneghini et al., 2007), and this

latitude range coincides with TCs moving over the MC. During negative SAM periods,

anomalously high pressure over Antarctica forces westerly wind belts toward the equator.

Carvalho et al. (2005) also suggest that enhanced convection associated with the MJO located

over the Indian Ocean tends to associate with positive SAM. The current study will explore these

associations in conjunction with TC formation and motion within the MC.

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The Madden-Julian Oscillation (MJO) (Madden and Julian, 1994) exhibits a relationship

with TC formation globally (e.g., Bessafi and Wheeler, 2006; Ho et al., 2006; Camargo et al.,

2008; Barrett and Leslie, 2009), and Camargo et al. (2009) find that its strongest influence is in

the southern hemisphere. Low-level westerly wind anomalies coupled with upper-level easterlies

in the equatorial region lead to enhanced convergence and low-level cyclonic vorticity that

promotes convective cloud development. This area of enhanced convection begins in the Indian

Ocean and propagates eastward, becoming less pronounced as it traverses the Atlantic Ocean. In

the southern hemisphere, TC genesis is favored poleward and westward of the enhanced

convection (Ho et al., 2006; Leroy and Wheeler, 2008). Thus, for TCs owing their genesis to the

MJO, upper-tropospheric velocity potential values and anomalies should be negative indicating

easterly flow. Previous research also suggests that precipitable water is enhanced during the

convectively-active phase of the MJO (Khalsa and Steiner, 1988; Camargo et al., 2009).

Therefore, current study will relate TC formation to the position of the convectively-active phase

of the MJO as well as the amount of precipitable water.

3. Data and methods

Six-hourly locations for TCs during 1948-2010 were obtained from version v03r04 of the

International Best Track Archive for Climate Stewardship (IBTrACS) dataset (Knapp et al.,

2010; Kruk et al., 2010). After importation into a Geographic Information System (GIS), careful

quality-control measures were employed to remove entries for the same TC reported by different

observing agencies. As the Regional Specialized Meteorological Center (RSMC) at La Reunion

is responsible for issuing advisories for the study region, observations from their database were

utilized to establish the track of each TC. Bessafi and Wheeler (2006) also utilized data from

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RSMC La Reunion in their study of SWIO TC relationships with ENSO and the MJO. Six

additional TCs were added from the Joint Typhoon Warning Center’s database. TCs forming in

the MC had a starting latitude 10-26° S and longitude 30-50° E. TCs forming over Madagascar

that did not enter the MC were excluded. Six-hourly intensity data were not considered as they

are known to be erroneous due to poor geostationary satellite coverage over the region prior to

1998 (Chang-Seng and Jury, 2010; Ramsay et al., 2012). However, the maximum intensity

obtained by each TC, (< 17.5 m s-1, 17-33 m s-1, or > 33 m s-1) was examined to determine if

counts were equal across time.

Several processing steps were performed to derive variables characterizing the TCs. First,

the dates of formation and dissipation, and the start and end coordinates were recorded. Storm

duration and average speed were calculated from these data. In the GIS, the six-hourly

coordinates for each TC were converted into an equidistant projection and transformed into a

single line feature. The midpoint of this line was calculated and its coordinates were recorded.

The GIS calculated the straight line distances and headings, or directions of motion, between the

start and midpoint, midpoint and end, and start and end. The variable storm heading refers to the

direction of motion of the TC from start to end. To distinguish among TCs that turned towards

the left rather than right, a turn ratio was calculated by dividing the direction of motion from start

to midpoint by that from midpoint to end. Values greater than one indicate a left-hand turn. A

measure of track sinuousity was constructed by dividing the overall track length by the straight

line distance from track start to end so that values larger than one indicate a more curved or

looped trajectory. Terry et al. (2013) utilized a similar method. Each track was also categorized

according to whether it intersected the coastlines of Mozambique or Madagascar, or did not

make landfall.

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Daily data from the NCEP-NCAR reanalysis project are available at a 2.5° latitude

longitude resolution (Kalnay et al., 1996) and were utilized to assess the environmental

conditions at the time and location of TC formation. Variables examined in this exploratory

analysis are precipitable water, deep-layer vertical wind shear (200 – 850 hPa), geopotential

heights and anomalies at 500 hPa, SSTs and anomalies, and velocity potential and anomalies at

200 hPa. As data begin in 1948, this year marks the start of the study period. The data

ascertained for each day when a TC formed within the MC were imported into a GIS and

overlain with the point of TC formation. The value present in a grid cell nearest to the location of

the TC center was utilized to determine the environmental conditions for the storm.

Index values obtained for ENSO, IOSD, SAM, and MJO (Table 1) were assigned to a TC

based on the day of formation. The phase of ENSO was represented by the Oceanic Nino Index

(ONI), which is a 3-month running mean of ERSST.v3b SST anomalies (1981-2010) in the

region 5oN-5oS, 120o-170oW. Positive (negative) values above (below) 0.5 (-0.5) are associated

with El Niño (La Niña) events. The IOSD index utilized is as defined by Behera and Yamagata

(2001) through an analysis of SST anomalies in the regions 29°–10°S, 85°–105°E and 42°–

30°S, 50°–80°E. Positive (negative) values of the monthly are associated with warm (cool) SSTs

and cyclonic (anticyclonic) flow southeast of Madagascar in the box centered near 36° S and 65°

E. The index developed by Nan and Li (2003) was utilized to represent the SAM as it was

available during the entire study period. This index was developed with data from the

NCEP/NCAR reanalysis and represents the difference in the normalized monthly zonal-mean sea

level pressure 40 - 70° S, where positive values indicate a poleward contraction of westerly

winds due to a weakened polar high. To characterize the MJO, Wheeler and Hendon (2004)

(WH04) developed daily indices for the leading two principal components derived from

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anomalies of outgoing longwave radiation and winds in the upper and lower troposphere.

Negative RMM2 values occur during phases 2 and 3, which correspond to days when the

convectively active phase of the MJO is located over the Indian Ocean (Ho et al., 2006). Values

from RMM1 are not utilized as both positive and negative values correspond with phases 2 and 3

and also 6 and 7 when the MJO is not positioned to aid convective cloud development over the

SWIO. As negative velocity potential values at 200 hPa indicate easterly flow that occurs when

the convectively active phase of the MJO is in a position to enhance cyclogenesis over the MC,

velocity potential and anomalies at 200 hPa were correlated with RMM2 to determine whether

velocity potential could be utilized to explore associations between the MJO and TC

characteristics prior to the availability of the WH04 index. Although Jury (1993) found that the

Quasi Biennial Oscillation (QBO) influences TCs in the greater SWIO, the current study did not

find any statistically significant relationships between the QBO and TCs in the MC, hence it not

discussed further. Similarly, Camargo and Sobel (2010) did not find a relationship between TC

activity and the QBO in the greater Southern Indian Ocean during 1953-2008.

Multiple nonparametric statistical tests were conducted to evaluate the relationships

between the variables described above. As TC observations in the SWIO are known to be more

accurate after 1979 due to the availability of infrared satellite imagery (Chang-Seng and Jury,

2010), the study period was divided into Period 1 (1948-1979) and Period 2 (1980-2010) in

addition to examining data across the entire study period. This division also roughly corresponds

to the Indo-Pacific region climate shift in 1976 (e.g., Giese et al., 2002; Terray and Dominiak,

2005). Mann-Whitney U tests (Mann and Whitney, 1947) are performed on all variables to

assess whether 1979/80 was the appropriate breakpoint for the two periods. Categorical chi-

square tests (Wilks, 1995) determined whether statistically significant differences in formation

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frequency occurred a) under each teleconnection phase, and c) among the three most active

months of December, January, and February. Kruskal-Wallis tests (Kruskal and Wallis, 1952)

compared median values for variables when formation occurred in December, January, or

February as well as when landfall occurred in Mozambique or Madagascar, or when no landfall

occurred. Spearman’s rank correlation coefficients (Zar, 1972) were calculated between track

attributes of formation latitude, sinuousity, length, and turn ratio and all continuous variables to

evaluate the strength and direction of these relationships. Finally, Mann-Whitney U and Kruskal-

Wallis tests are performed with TCs grouped according to teleconnection value for all

continuous variables to explore relationships between teleconnections and environmental

conditions.

4. Results

During 1948-2010, 94 TCs formed in the MC. Although there were eleven years in which

no TCs formed, eleven years also experienced three or more formations and an average of 1.5

TCs occurred each year overall. While 54 TCs formed during Period 1, 40 formed during Period

2 (Figure 2a). TCs attained higher intensities during Period 2, Χ2 (2, N = 94) = 21.140, p = 0.000.

Mann-Whitney U tests comparing the ranks of variables between Period 1 and 2 confirm the

decision to examine separately 1948-1979 and 1980-2010 (Table 2). During Period 2, TCs

moved with higher forward speeds and had more curved trajectories while velocity potential and

anomaly values were lower. Precipitable water, SSTs, and 500 hPa geopotential height and

anomaly values increased as did the SAM and IOSD indices. Thus, results will be presented for

each period separately as well as for all years combined.

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4.1 General conditions on the day of formation

Two key thermodynamic components of TC formation are warm ocean waters from

which latent and sensible heat fluxes help to intensify the storm, and high amounts of

environmental moisture, which is the key component of the storm’s water budget (Malkus and

Rhiel, 1960; Emanuel, 1986; Rodgers et al., 1994). Climatologically, SSTs average 28° C

during the peak months of TC activity in the MC (Jury and Pathack, 1991; Suzuki et al., 2004).

The average SST in the vicinity of formation was 29.5° C, with only 3 TCs forming over SSTs

less than 28° C (Figure 3a). Globally, precipitable water values average 40-50 mm over regions

where TCs form (Chu, 2002; Inoue et al., 2002). While average values over the central Indian

Ocean can reach 50 mm, Ferraro et al. (1996) determined that for December-February, values

were somewhat lower over the MC at 40 mm. Most TCs were located within regions above 40

mm, with an average of nearly 50 mm (Figure 3b). Actual values may be higher as Trenberth and

Guillermot (1998) discovered a low bias over tropical latitudes for the reanalysis-derived

precipitable water fields. As previously stated, both SST and precipitable water values had

statistically significant increases from Period 1 to 2 (Table 2) as other studies have found (e.g.,

Chu, 2002). The increasing SSTs promote higher evaporation rates, which contribute to

increased precipitable water values in general (Stephens, 1990; Chu, 2002).

Strong vertical wind shear typically inhibits TC development (Gray, 1968), while

somewhat weaker shear near the ITCZ can enhance the positive vorticity needed for tropical

cyclogenesis (Jury and Pathack, 1991; Jury, 1993). The current study finds that the meridional

component of the 200-850 hPa wind shear was typically from the south (Figure 3c). However,

the zonal component ranged from a strong westerly to easterly (Figure 3d). Stronger westerlies

as well as anomalously low geopotential height anomalies at 500 hPa (Figure 3e) accompany

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troughs in the subtropical jet stream that anchor over Mozambique as discussed by Chang-Seng

and Jury (2010). TCs forming south of the ITCZ may have their development enhanced by a

stronger poleward outflow jet (Sinclair, 2002) when this trough is present. On the other hand,

faster winds aloft from the east may at times be due to the influence of the convectively active

phase of the MJO. These easterly wind anomalies at 200 hPa are associated with anticyclonic

flow aloft and are coupled with convergent flow near the surface that aids cyclogenesis over the

MC as shown in Figure 8a of Rui and Wang (1990). Negative velocity potential values at 200

hPa can be associated with the convectively active phase of the MJO or strong flow associated

with the tropical easterly jet (Figure 3f).

4.2 Relationships between environmental conditions and TC attributes

The latitude that divides the study region (10 – 26° S) into half is 18° S. The average

latitude of formation was 18.4° S, indicating that more TCs formed in the southern half than

northern half of the channel (Figure 4a). The environmental conditions and attributes of storm

motion related to the location of storm formation were examined through the calculations of

Spearman’s rank correlation coefficients between all variables and the latitude of formation.

Overall, TCs forming in the north experienced higher SSTs and easterly deep-layer wind shear

(Table 3). In Period 1, formation in the north corresponded to a left turn and southeastward

motion. For TCs forming farther north during Period 2, the lack of strong westerly winds

produced a slower and more curved or looping trajectory. Likely due to enhanced westerly flow

aloft, TCs forming in the south had faster speeds of motion with straighter trajectories. Also in

Period 2, TCs formed farther south when the IOSD and SAM indices were positive.

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Given that the position of the ITCZ shifts through 15-20° S during the TC season, TC

formation frequency, location, tracks, and environmental conditions should vary by month. In

the MC, 86% of formation occurred during December, January, and February (Figure 2b).

Although Mavume et al. (2010) reported that formation in the MC was rare in December, 18% of

activity in the current study occurred during this month. Although formation peaks in January

(February) during Period 1 (2), differences in formation frequency within each period and across

the two periods were not statistically significant at the 0.05 level when December, January, and

February formation counts were subjected to chi-square tests (not shown). When analyzing data

across the entire study period, formation occurred farther south during December (Table 4).

None of the variables associated with TC location or track were significantly different during

Period 1. For Period 2, February TCs dissipated at more equatorward latitudes and westward

longitudes, were of shorter length, and tended to turn right (Table 4). During both periods and for

all years combined, 200-850 hPa vertical wind shear was westerly, weak, and easterly for TCs

forming in December, January, and February, respectively, as would be expected given the

climatological position of the ITCZ each month (Table 4).

The sinuousity, storm heading, and turn ratio values quantify storm motion and strong

associations of these variables with environmental conditions could aid track prediction. A TC

with a very straight track has a sinuousity value between 1.0-1.1 while Delfina’s track that made

a large loop over Mozambique is associated with a value of 2.4. The majority of tracks were

minimally curved (Figure 4b), with 52% (29%) having a value less than the median of 1.25 (1.1).

This value is higher than the 1.17 found by Terry et al. (2013) when considering TCs throughout

the SWIO. The straightest trajectories were associated with a storm heading towards the east,

starting longitude in the west but ending in the east, poleward midpoint and ending latitudes,

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shorter duration, lower precipitable water and SST values, and a faster storm speed (Table 5).

These are all characteristics associated with strong westerly steering currents. Tracks were also

relatively straight when the TC formed during a positive IOSD month and when velocity

potential values were positive. The absence of significant correlations during Period 1 may be

due to the lack of infrared satellite data prior to 1980 to accurately determine storm positions

every six hours. Table 2 also supports this finding as trajectories tend to be less curved during

Period 1. The relative start and end locations appear to be more reliable given that correlations

with storm heading do not differ as much between the two periods. The majority of TCs move

southeastward when their overall trajectory is calculated (Figure 4c). TCs tend to move south or

southwest rather than southeast or east when they form in the eastern portion of the channel over

higher SSTs and experience easterly vertical wind shear (Table 5). These findings differ from

those of Neumann and Randrianarison (1976) and Jury and Pathack (1991) who observed that

TCs moving through the MC track mainly to the south or southwest. The average turn ratio value

suggests that a slight tendency existed for a turn towards the left rather than right (Figure 4d). A

left turn, which is associated with a value greater than one, tends to occur when starting and

ending longitudes are towards the east (Table 5). The lack of a significant correlation between

heading and turn ratio demonstrates that the direction of turn is not related to the overall

direction of storm motion from start to end.

More than 50% of Channel TCs made landfall. As expected, median values of storm heading

and the longitudes of the track midpoints were more westward for Mozambique landfalls and

eastward for landfalls over Madagascar (Table 6). Storms tended to pass out of the channel

without making landfall when velocity potential anomalies were higher, suggesting that the MJO

did not influence cyclogenesis for these TCs and/or the tropical easterly jet was weak or absent

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(Figure 5a), whereas highly negative velocity potential values occurred when TCs made landfall

over Madagascar (Figure 5b). Due to the relatively small number of landfalls over Mozambique,

a new result emerged when all years were considered. Landfalls occurred over Mozambique

when geopotential heights were higher on the day of formation, suggesting that the trough

discussed by Chang-Seng and Jury (2010) with its strong winds that would normally steer TCs

southeastward was likely absent. When the subtropical ridge is fairly strong in the region (Figure

6a), weak steering currents permit TCs to drift westward to landfall over Mozambique (Reason,

2007). Geopotential heights were lower overall in the region when TCs did not make landfall

over Mozambique (Figure 6b). The current study’s results also comport with those of Vitart et al.

(2003) who analyzed TCs forming throughout the SWIO and found that landfall over

Mozambique was more frequent when zonal flow was weak.

4.3 Associations between teleconnections and TC attributes

Three of the four teleconnections exhibited strong associations with TC formation

frequency in the MC (Table 7). During Period 1, 79% (72%) TCs formed when the IOSD (SAM)

was in its negative phase. In nearly 45% of cases, both the IOSD and SAM were negative on the

day of TC formation. An examination of the monthly index values for all December, January,

February, and March months regardless of TC formation across 1948-1979 indicates that the

majority of months experienced negative IOSD and SAM index values. Thus, it should be

expected that more TCs would also form during these months. Given that previous research has

documented a positive trend in SAM over time, it is not surprising that more months exhibited

positive rather than negative SAM values in Period 2. TC formation frequency was also higher in

positive SAM months during this period (Table 3) while there was no significant difference in

19

formation frequency when the phase of IOSD was considered. Monthly values of the SAM and

IOSD were not correlated in either period or over the entire study period. The MJO may have

exhibited an association with formation frequency in Period 2. Velocity potential and anomalies

were negative on days when 72% and 80% of formations occurred respectively, suggesting that

the MJO may have had a stronger influence on cyclogenesis than in Period 1. That median

values of velocity potential anomalies for each month were lower in Period 2 than in Period 1

also supports this finding (Table 2). ENSO did not have a significant association with formation

frequency. This result agrees with that of Ramsay et al. (2012) when they considered 237 TCs

forming west of approximately 75° E (their Figure 1 and Table 3).

The primary association between ENSO and TCs in the MC is through steering currents

at 500 hPa (Table 8). The geopotential height anomalies were highest over the MC when TC

formation occurred during El Niño events (Figure 7a). When formation occurred during ENSO-

neutral and La Niña months, the spatial pattern of the lower height values from northwest to

southeast (Figure 7 b, c) may coincide with the occurrence of tropical temperature troughs

(TTTs). These cloud bands connect the tropics to the extratropics as they stretch northwest to

southeast and trigger multi-day rainfall events over southern Africa (Todd and Washington,

1999). During La Niña events, TTTs tend to occur over Mozambique, but shift east of

Madagascar when El Niño prevails, contributing to widespread drought in southeastern Africa

(Usman and Reason, 2004; Manhique et al., 2011). The below normal SSTs associated with La

Niña events (Table 8) coincides with the findings of a statistically significant negative

correlation between SSTs and the ONI over a 40-year period by Washington and Preston (2006).

A strong Mascarene high is key in the development of a positive IOSD (Behera and

Yamagata, 2001; Suzuki et al., 2004). The strengthening of the Mascarene high in Period 2 may

20

explain why the IOSD exhibited significant associations with TC locations and track shape

during this period (Table 9) but not in Period 1 when the IOSD index was mostly negative (Table

7). When the index was positive, TCs formed farther west and moved with relatively straight

trajectories as compared to when the index was negative (Table 9). Latitude of formation also

had a negative correlation with the IOSD meaning the formation occurred in the southern portion

of the MC when the IOSD was positive (Table 3). These findings are in agreement with previous

research describing atmospheric conditions during strong positive IOSD events. Reason (2002)

showed that convergence was enhanced at 850 hPa south of 18° S, which would aid

cyclogenesis, and northwesterly winds aloft could help to steer TCs southeastward. The spatial

pattern of geopotential height anomalies (Figure 8a) supports this explanation. Behera and

Yamagata (2001) found significant positive correlations between the IOSD and rainfall

anomalies in the MC south of 15° S with negative correlations north of 12° S. They also

discussed how anomalously cool waters suppress atmospheric convergence in the ITCZ as far

west as the coast of Somalia, which could limit tropical cyclogenesis within the northern/eastern

portion of the MC. When the IOSD index is negative, strongly divergent flow at 850 hPa south

of 18° S (Reason 2002) would limit TC formation in this region, while weaker winds towards the

north may allow for formation given a source of convergence such as the ITCZ or the MJO.

Again, the spatial pattern of geopotential height anomalies (Figure 8b) supports this finding. The

weaker steering currents correspond to more curved trajectories during negative IOSD months.

As previously stated, few studies have related TC attributes to the SAM in the SWIO.

When TCs formed under positive SAM conditions, precipitable water values tended to be higher,

zonal shear was more strongly from the west (Table 9), and formation occurred farther south

(Table 3). A component of TC steering is provided by anticyclones traveling eastward (Williams

21

et al., 1984). These anticyclones tend to be stronger under positive SAM conditions (Figure 9a),

which likely facilitates a faster motion towards the east as indicated by the negative correlation

between the zonal component of vertical wind shear and positive storm heading (Table 5).

Weaker steering currents exist when the subtropical ridge expands equatorward (Figure 9b) as

might occur under negative SAM conditions (Carvalho et al., 2005). Depending upon the

location of the axis of the ridge, the weak steering currents could then cause Channel TCs to

move slowly southwestward at first rather than quickly southeastward (Williams et al., 1984).

In the southern hemisphere, tropical cyclogenesis is favored poleward and westward of

the most active convection associated with the MJO, which corresponds to phases 2 and 3 for

formation in the MC (Ho et al., 2006). Ten of 40 TCs formed during phases 2 or 3 during Period

2. Mann-Whitney U tests were performed after combining observations occurring in phases 2 or

3 into one group and all other phases in the second group. Results showed ranks for velocity

potential and anomaly values were significantly lower for the phase 2/3 group (U = 83.0, p =

0.047; U = 68.5, p = 0.009). The Spearmann’s rank correlation coefficient between RMM2 and

velocity potential (velocity potential anomalies) is 0.668 (0.710). These results suggest that

although not always associated with the MJO, negative velocity potential values may often be

related to enhanced convection during phases 2 and 3 given the strong association between

RMM2 and velocity potential (Table 9). Lower velocity potential values were associated with

TC tracks of longer duration and length that travelled farther south. Also, when velocity potential

values were lower, precipitable water values were higher. As the MJO is associated with positive

total precipitable water anomalies (Kikuchi and Takayabu, 2003), this finding suggests that TC

formation is aided when the MJO advects moisture into the region. When RMM2 is negative,

tracks tend to be more curved and the IOSD is more negative than positive (Table 9). A chi-

22

square test examining formation frequency under all eight of the WH04 phases was insignificant

(χ2=3.60; p=0.825), suggesting that other mechanisms for tropical cyclogenesis are also

important over the MC along with the MJO.

5. Discussion

Taken collectively, the results of this study suggest that a difference exists between the

northern and southern portions of the channel in regards to environmental conditions, TC

formation and trajectories, and associations with atmospheric teleconnections. Formation north

of 18°S where SSTs were higher and easterly vertical wind shear prevailed was associated with

curved trajectories and an initial motion south or southwestward. Negative IOSD and SAM

indices were also associated with TC formation in the northern portion of the channel.

Trajectories that were straight occurred under positive IOSD conditions when formation

occurred in the poleward half of the channel. These relationships make physical sense when

placed in the context of observational and modeling work performed by previous researchers.

Future research on TCs in the MC should utilize multivariate regression analysis to determine the

relative contributions by the existing conditions in explaining the variance in TC activity. This

technique was employed in the greater SWIO by Jury et al. (1999) to predict the number of TC

days using environmental conditions over the SWIO east of Madagascar.

This study found numerous differences when comparing Period 1 and 2, confirming the

need to examine these periods separately. This is an important consideration when interpreting

the results of previous research. Many previous studies utilized data that spanned the 1960s

through the 1990s or early 2000s (Jury and Pathack, 1991; Jury, 1993; Jury et al., 1999; Chang-

Seng and Jury, 2010). Improved accuracy in the positions of TCs every six hours due to the

23

availability of infrared satellite data likely explains the emergence of numerous statistically

significant relationships among track shape and environmental conditions during Period 2. It also

suggests that the Period 1 findings should be interpreted with caution. Changes in the

atmospheric circulation over the SWIO after the Indo-Pacific climatic shift of 1976-77 may also

account for differences in the strengths of the associations of teleconnections with TC attributes.

As high-quality data continue to become available, these relationships should be tested further.

Given the strong association between the Mascarene high, 500 hPa geopotential height

patterns, and the SAM, IOSD, and ENSO, analysis of lag times between changes in the strength

of the Mascarene high and TC formation and motion should be explored in future research. The

SAM is the leading mode of climate variability for the extratropical Southern Hemisphere as it

characterizes exchanges in atmospheric mass between the middle and high latitudes (Pohl et al.,

2010). The SAM is becoming increasingly positive through time due to stratospheric warming

caused by ozone depletion and increasing greenhouse gases (Jones and Widmann, 2004; Shindell

and Schmidt, 2004). When the SAM index is positive, the Mascarene high is stronger (Xue et al.,

2004), and this high is a critical component in the circulation patterns that develop in the

subtropics during the different phases of the IOSD and ENSO (Fauchereau et al., 2003; Hermes

and Reason, 2009; Manhique et al., 2011). A stronger Mascarene high can lead to more IOSD

positive events that enhance TC formation with straighter trajectories in the southern MC.

This study has identified a key difference for TCs in the MC as compared to the greater

SWIO in regards to ENSO. TC formation in the greater SWIO is most prevalent over enhanced

SSTs just east of Madagascar during El Niño events, and are located farther east during La Niña

events (Ho et al,. 2006; Kuleshov et al., 2008; Ash and Matyas, 2012). The current study did not

find a link between ENSO and TC formation location or frequency. This could be due to the fact

24

that SSTs are typically warmer in the MC than in the SWIO at the same latitude (Jury and

Pathack, 1991) so that above normal SSTs are not needed before cyclogenesis can occur. The

geometry of the MC could also play a role as the differences in SST patterns and formation

locations in the greater SWIO span a longitude range of 20°+ while the MC is approximately 8°

wide at some locations narrowing to 4.5° wide near 15.5° S. Ho et al. (2006) performed Mann-

Whitney U tests on data spanning 1979-2004 and unlike in the greater SWIO, they did not find a

significant difference in TC formation within the MC according to the phase of ENSO that was

significant at the 95% confidence level. Thus, the current study supports their findings.

An explanation for the difference in results between the two periods as well as to other

studies could be inclusion of all TCs regardless of intensity. Studies such as those by Ho et al.

(2006) and Mavume et al. (2010) only utilized TCs that attained tropical storm intensity. The

Period 2 analysis approaches this delimitation as it only contains two tropical depressions.

However, almost half of the TCs in Period 1 did not reach tropical storm status. Interestingly, a

shift occurs in Period 1 from mostly tropical depressions to mostly tropical storms around 1961

(Figure 2a), coincident with the time that TCs first received names. One explanation for the

relative increase in intensity could be the improvements in satellite-based observations since

1979 that allow for more accurate observation of the circulation center.

6. Conclusions

This study examined 94 TCs that formed within the Mozambique Channel during 1948-2010.

Nonparametric statistical tests explored the strength and direction of relationships between TC

formation and motion attributes, environmental conditions, and teleconnections known to

influence TCs in the greater SWIO. Precipitable water values, SSTs, and geopotential heights

25

and anomalies all exhibited significant increases over time while velocity potential declined.

Findings differed when the study period was divided in half, suggesting that inclusion of data

prior to 1979 be interpreted cautiously. The SAM, IOSD and the MJO exhibited associations

with TC formation frequency, location, and track, while ENSO only exhibited associations with

geopotential height anomalies at 500 hPa. TC motion attributes were characteristic of the

circulation patterns and influences on TC trajectories described by previous researchers for the

greater SWIO. Over half of the TCs made landfall, and although landfall over Mozambique was

infrequent, it tended to occur when geopotential heights were relatively high on the day of

formation, while differences in velocity potential values were apparent when comparing TCs that

did vs. did not make landfall.

Given that this study is one of few that has specifically focused on TC formation within the

MC, the analysis only considered conditions on the day of TC formation. Even with this

limitation, significant results were discovered that both support those of previous research in the

greater SWIO and demonstrate how TC activity in the MC differs from that the SWIO. These

findings suggest that TCs over the MC merit further study. Environmental conditions should be

examined on days leading up to formation and while the TC is tracking over the channel. Given

the strong link between the Mascarene high and the teleconnections explored in this study, lag

times between changes in the Mascarene high could be utilized to predict TC attributes.

Additional variables such as outgoing longwave radiation, wind vectors, and vorticity at 850 hPa

should be examined to more precisely identify cloud systems that are the precursors to TC

formation in the MC. A multivariate regression analysis could also be employed to more closely

ascertain the relative contribution of each variable when predicting TC activity in the MC.

26

Acknowledgements This research was supported by the National Science Foundation BCS-1053864. Undergraduate

student Christian Kamrath assisted in formatting the NCEP-NCAR Reanalysis data for

importation into the GIS. Two anonymous reviewers helped to improve the manuscript.

27

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35

Tables Table 1. Teleconnections examined in the study with abbreviations, period when data were

available, and source of data.

Teleconnection Period Source

El Niño Southern

Oscillation

Monthly

1950 - present

http://www.cpc.ncep.noaa.gov/products/analysis_monito

ring/ensostuff/ensoyears.shtml

Indian Ocean

Subtropical Dipole

Monthly

1958 - 2007

http://www.jamstec.go.jp/res/ress/behera/iosdindex.html

Southern Annular

Mode

Monthly

1948 - present

http://www.lasg.ac.cn/staff/ljp/data-NAM-SAM-

NAO/SAM(AAO).htm

Madden-Julian

Oscillation

Daily

1974 - present

http://cawcr.gov.au/staff/mwheeler/maproom/RMM/RM

M1RMM2.74toRealtime.txt

36

Table 2. Results of Mann-Whitney U tests comparing median group values from Periods 1 and 2.

Variable Units Period 1

median

Period 2

median

U p-value

SAM - -0.89 0.74 1569.5 0.000

Velocity potential 200 hPa m2 s-1 569,000 -2,262,000 580 0.000

Vel. pot. anomaly 200 hPa m2 s-1 10,500 -2,422,000 591 0.000

SST °C 28.45 28.85 1582 0.000

Geopotential ht. 500 hPa m 5834 5845 1481.5 0.002

IOSD - -0.56 0.18 955.5 0.003

Avg. forward speed m s-1 3.3 4.4 1423 0.009

Height anomaly 500 hPa m -28.6 -16.9 1417.5 0.010

Precipitable water mm 49.0 50.6 1356.5 0.034

Sinuousity - 1.18 1.28 1310.0 0.052

37

Table 3. Significant coefficients of Spearman’s rank correlation tests between latitude and all

other variables. All values are significant at alpha = 0.1, italic values 0.05, and bold 0.01.

Variables Period 1 Period 2 All Years

SST 0.505 0.435 0.435

Zonal Shear -0.596 -0.340 -0.507

Turn Ratio 0.324 0.294

Storm Heading 0.288 0.223

Midpoint Latitude 0.632 0.405

Speed -0.427

SAM -0.326 -0.229

Sinuousity 0.316

IOSD -0.295

38

Table 4. Statistically significant results of Kruskal Wallis tests for TC attributes, environmental

conditions, and teleconnection indices in three primary TC months.

Variable Units December

median

January

median

February

median

H p-

value

Period 1

Zonal Shear m s-1 8.78 0.15 -6.48 10.663 0.005

Vel. Pot. Anom. 200 hPa m2 s-1 -296,600 1,771,000 -1,457,500 9.180 0.010

SST °C 27.95 28.25 28.55 6.428 0.040

Period 2

Turn Ratio - 1.03 0.98 0.78 9.302 0.010

Zonal S m s-1 8.75 3.2 -6.3 8.511 0.014

Length km 2069 2662 1465 8.150 0.017

Ending Longitude degrees 50.2 51.7 44.7 7.275 0.026

Ending Latitude degrees -31.4 -32.0 -22.1 6.955 0.031

Velocity Pot. 200 hPa m2 s-1 -956,600 -6,202,500 -1,782,500 6.468 0.039

Vel. Pot. Anom. 200 hPa m2 s-1 -1,041,000 -5,270,500 -1,677,000 6.229 0.044

All Years

Starting Latitude degrees -20.3 -18.1 -18.4 5.952 0.051

Velocity Pot. 200 hPa m2 s-1 857,000 -385,500 -1,781,000 6.419 0.040

SST °C 28.9 29.5 29.8 6.673 0.036

Zonal Shear m s-1 8.75 0.80 -6.3 19.345 0.000

39

Table 5. Spearman rank correlation coefficients for all continuous variables and sinuousity,

storm heading, and turn ratio. All values are statistically significant at alpha = 0.1, italic values

0.05 and bold 0.01.

Variable

Per.1

Sinuousity

Per. 2

All

Per 1.

Heading

Per 2.

All

Per. 1

Turn

Per. 2

All

Heading 0.447 0.239

Start Lat. 0.316 0.220 0.288 0.223 0.324 0.294

Start Long. 0.396 0.304 0.287 0.298 0.264 0.205

Midpt. Long. -0.526 -0.565 -0.539

Midpt. Lat. 0.319 -0.351

End Long. -0.391 -0.224 -0.741 -0.638 -0.697 0.268 0.283 0.277

End Lat. 0.264 0.369 0.295 -0.288 -0.248

Length -0.343 0.252 0.209

Duration 0.256 0.459 0.321

Precip. Water 0.350 0.235

SST 0.296 0.208 0.266 0.204

Speed -0.352 -0.191 -0.244

Zonal Shear -0.272 -0.416 -0.317 0.287

IOSD -0.419

Vel. Pot. -0.302 -0.231

40

Table 6. Statistically significant results of Kruskal Wallis tests for landfall over Mozambique or

Madagascar, or no landfall.

Variable Units Mozambique

median

No landfall

median

Madagascar

median

Test

statistic

p-value

Period 1 n=5 n=26 n=23

Storm Heading degrees 187.9 162.3 127.8 14.109 0.001

Midpt. Longitude degrees 41.4 41.2 43.4 10.455 0.005


Vel. Pot. Anom. m2 s-1 -2,574,000 1,494,000 -1,046,500 6.501 0.039

Period 2 n=7 n=19 n=14


RMM2 - 0.524 0.537 -0.456 7.793 0.020


Starting Latitude degrees -16.4 -20.2 -16.0 7.207 0.027

Ending Latitude degrees -22.7 -25.8 -21.8 6.712 0.035

Year - 2001 1999 1992 6.489 0.039

Vel. Pot. Anom. m2 s-1 -5,134,000 -664,000 -6,388,500 6.348 0.042

All Years n=12 n=45 n=37



Vel. Pot. Anom. m2 s-1 -3,271,500 85,000 -1,926,000 11.020 0.004


Duration days 7.4 4.8 5.8 7.210 0.027

Geopot. ht. 500 m 5856 5838 5839 6.760 0.034

41

Table 7. Counts of TC formation for each teleconnection during Period 1, Period 2, and all years

with associated chi-square statistics and p-values.

Telecon. P1 X2

p-

value P2 X2

p-

value Total X2

p-

value

El Niño 21 1.885 0.390 10 1.850 0.397 31 1.326 0.515

Neutral 18 17 35

La Niña 13 13 26

Vel. Pot. - 27 0.000 1.000 32 14.400 0.000 59 6.128 0.013

Vel. Pot + 27 8 35

IOSD + 8 12.737 0.000 20 0.444 0.505 28 4.378 0.036

IOSD - 30 16 46

SAM+ 19 4.741 0.029 26 3.600 0.058 45 0.170 0.680

SAM- 35 14 49

42

Table 8. Statistically significant results of Kruskal Wallis tests for phase of ENSO during Periods

1 and 2 with group median values.

Variable

El Niño

Median

Neutral

Median

La Niña

Median H p-value

Period 1

SST (°C) 29.55 29.30 28.85 10.069 0.007

Height Anom. 500 hPa (m) -18.4 -37.1 -40.5 6.181 0.045

Geopot. Height 500 hPa (m) 5840 5826 5822 5.663 0.059

Period 2

Height Anom. 500 hPa (m) -.015 -15.6 -20.5 6.235 0.044


All Years

Height Anom. 500 hPa (m) -14.9 -22.4 -26.9 6.855 0.032


SST (°C) 29.7 29.6 29.5 5.381 0.068

43

Table 9. Statistically significant results of Mann-Whitney U tests for teleconnection groups

during Periods 1 and 2 with group median values.

Teleconnection Variable

Negative

Median

Positive

Median U p-value

Period 1

Velocity Potential Duration (days) 7.5 4.5 213.0 0.010

Velocity Potential Length (km) 1837 1326 224.0 0.043

SAM Precip. Water (mm) 47.9 50.9 437.5 0.057

Velocity Potential Precip. Water (mm) 50.1 48.1 252.5 0.061

Period 2

Velocity Potential RMM2 -0.27 1.14 245.0 0.004

SAM U Shear (m s-1) -8.5 3.2 134.0 0.005


IOSD Sinuousity 1.47 1.22 94.0 0.056

SAM Start Latitude -16.0 -19.7 58.5 0.058

RMM2 IOSD -0.34 0.86 219.5 0.058

RMM2 Sinuousity 1.44 1.24 124.0 0.064

IOSD Start Longitude (°) 42.2 40.6 89.0 0.066

All Years

Velocity Potential RMM2 -0.42 0.91 965.0 0.001


Velocity Potential Length (km) 1996 1424 703.0 0.005

Velocity Potential Duration (Days) 6.5 4.0 763.5 0.019

Velocity Potential End Longitude (°) -28.9 -23.4 1363.5 0.021

SAM Precip. Water (mm) 49.2 50.6 1368.5 0.044

RMM2 Sinuousity 1.47 1.24 173.0 0.069

44

Figure Captions

Figure 1. Map depicting Mozambique Channel and surrounding countries.

Figure 2. Histograms depicting a) the number of tropical cyclones forming each 3-year period

grouped by maximum intensity, and b) number forming each month during Period 1 and Period

2.

Figure 3. Histograms depicting conditions on the day of formation for 94 tropical cyclones a) sea

surface temperature, b) precipitable water, c) meridional component of 200-850 hPa vertical

wind shear , d) zonal component of 200-850 hPa vertical wind shear, e) geopotential height

anomaly at 500 hPa, and f) velocity potential at 200 hPa.

Figure 4. Histograms depicting a) latitude of formation, b) track curvature, c) storm heading

from start to end point, and d) turn ratio for all 94 tropical cyclones.

Figure 5. Average velocity potential anomalies at 200 hPa for tropical cyclones that a) did not

make landfall, and b) made landfall over Madgascar.

Figure 6. Average geopotential heights at 500 hPa on the day of formation for tropical cyclones

that (a) made landfall over Mozambique, and (b) did not make landfall over Mozambique.

Figure 7. Average geopotential height anomalies at 500 hPa on the day of formation for tropical

cyclones forming during months classified as a) El Niño, b) ENSO-neutral, and c) La Niña.

Figure 8. Average geopotential height anomalies at 500 hPa on the day of formation during

Period 2 for a) positive IOSD with relatively straight tracks, and b) negative IOSD with more

curved tracks.

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Figure 9. Average geopotential height anomalies at 500 hPa on the day of formation during

Period 2 for a) positive SAM, and b) negative SAM.

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