Super Tropical Cyclone Amphan in Bay of Bengal

Monitoring tropical cyclones in the Indian Ocean - 2012-2019

2012-2019

Super Tropical Cyclone Amphan in Bay of Bengal
Super Tropical Cyclone Amphan in Bay of Bengal

This case study combines a number of examples of tropical cyclones that formed and travelled over the Indian Ocean in the 2010s. We have tracked them using various satellite data and recorded some of the impacts they made in countries such as Myanmar, Madagascar and Mauritius.

Last Updated

17 March 2023

Published on

07 March 2023


Table of contents

Fani Luban Mekunu Vardah Fantala
Chapala Ashobaa Bansi Eunice and Diamondra Adjali
Hudhud Phailin Giovanna    

2019

Fani

28 Apr-2 May, India
By Sancha Lancaster, Vesa Nietosvaara, and HansPeter Roesli

Tropical Cyclone Fani made landfall in Odisha, northeastern India on 3 May 2019.

Cyclone Fani was classed as an 'extremely severe' storm when it made landfall in Odisha, with wind speeds up to 185 km/h. This made it the strongest storm to hit India in two decades. At least three people were reported to have died.

The Meteosat-8 enhanced infrared image (Figure 1) shows Fani as it started to make landfall on 3 May at 00:00 UTC

 Meteosat-8 enhanced infrared, 3 May 00:00 UTC
Figure 1: Meteosat-8 enhanced infrared, 3 May 2019 00:00 UTC

Fani formed from a depression located west of Sumatra on 26 April and it had intensified into a cyclonic storm within 24 hours. The Joint Typhoon Warning Center classed Fani as an equivalent to a Category 1 tropical cyclone (on the Saffir-Simpson scale) on 29 April and within hours it was upgraded to a Category 3-equivalent cyclone.

Figure 2 shows Fani on 28 April, in a rare sighting on satellite imagery of two tropical cyclones aligned along the same longitude, Fani (north) and Lorna (south). For in-depth case see Rare sighting of two tropical cyclones on same longitude.

Figure 2: Meteosat-8 Tropical Airmass RGB, 28 April 2019 02:00–08:00 UTC

Development proceeded more slowly over the following days but on 2 May the eye became more distinct, and Fani was upgraded to a Category 4 equivalent cyclone by the JTWC Shortly after, Fani started another period of rapid intensification, attaining 1-minute sustained winds of 250 km/h (155 mph) just below JTWC's Category 5-equivalent tropical cyclone intensity.

Figure 3 shows Meteosat-8's view of Fani's intensification to the time it made landfall in May

Figure 3: Meteosat-8 infrared, 2 May 18:00 2019 UTC–3 May 06:00 UTC

Warnings

Joint Typhoon Warning Center

Other image sources

Tropical Cyclone Fani (NASA Earth Observatory)

Media reports

Cyclone Fani Live Updates: Cyclone Fani Kills 3, Submerges Villages In Puri; Kolkata Airport To Be Shut) (NDTV)
Tropical cyclone Fani: India's biggest storm in decades makes landfall (The Guardian)


2018

Luban

6–14 Oct, Indian, Yemen
By HansPeter Roesli, and Shima al Yazidi (DGMET)

Luban went through the life cycle of a tropical storm over the Arabian Sea between 6 October and 14 October 2018.

The Regional Specialised Meteorological Centre (RSMC) in New Delhi upgraded Luban to a category-1 tropical cyclone on 10 October. The sequence of false-colour images of channel IR10.8 from Meteosat-8 (Figure 3) illustrates the evolution of Luban from her birth off the Indian coast to the landfall over eastern Yemen.

Figure 1: Meteosat-8 IR10.8, 6 October 2018 03:00 UTC-14 October 16:30 UTC

For cargo vessels and fishing boats in these parts of the Indian Ocean indications about the sea state were of paramount importance, in particular during the most intense period of Luban. In-situ measurements in the area are sparse and limited to few locations, so altimetry measurements from satellites can fill the gaps and provide more spatial coverage.

The Significant Wave Height (SWH) product from the SRAL altimeter on Sentinel-3 is a great aid. SWH is a parameter that is widely used to describe the ocean sea state. It is defined as four times the square root of the integral of the wave spectrum, and closely corresponds to the average height of the highest one third of waves.

Figures 5 and 6 are SWH samples over the Luban track. On 9 October, ahead of being categorised as a Category 1 storm, Luban had estimated wind speeds of 148km/h to 16km/h (80kt to 90kt). The SWH swath passed over her eastern side, as shown in Figure 5. The SWH product estimated a SWH maximum of 5.9m.

 Meteosat-10 High Resolution Visible with Sentinel-3 SRAL SWH overlaid, 9 Oct, 05:00 UTC
Figure 5: Meteosat-10 High Resolution Visible with Sentinel-3 SRAL SWH overlaid, 9 October 2018 05:00 UTC

During the tropical cyclone phase on 12 October an SWH swath was obtained with wind speeds of 185km/h to 204km/h (100kt to 110kt). The swath crossed the northern eye wall (Figure 3). There the maximum SWH reached 4.7m.

On 9 October the highest measured SWH was 6.6m at lat 14.1, long 62.7. On 12 October the highest was 6.4m at lat 11.9, long 56.6. Note: These high values do not show in the image due to smoothing of the colour scale along the track.

 Meteosat-10 High Resolution Visible with Sentinel-3 SRAL SWH overlaid, 12 October, 06:00 UTC
Figure 6: Meteosat-10 HRV with Sentinel-3 SRAL SWH overlaid, 12 October 2018 06:00 UTC
 Scatterplot of Forecast WAM SWH versus altimetry SWH
Figure 7: Scatterplot of Forecast WAM SWH v altimetry SWH

Altimetry may be employed to evaluate the performance of wave models. Figure 7 shows a comparison of altimetry SWH measurements on 9 October (Figure 4) and SWH estimates from the wave model (WAM). Except for a couple of outliers, the scatter plot shows a close resemblance between the model data and the altimetric measurements.

Note: The SWH measurements from Sentinel-3 SRAL (Ku-band) have an accuracy of around 5% of SWH, globally. Under heavy precipitation the accuracy may be slightly degraded, but there is no significant validation data to assess the quality in these extreme conditions. Such overlays have been published in the past for Hurricane Katrina. There too, satellite altimeters (ERS-2, Envisat, GFO, TOPEX, and Jason-1 at the time) showed consistent results for SWH throughout their tracks across the hurricane up to at least 10m wave height. See: Scharroo, R., W. H. F. Smith, and J. L. Lillibridge, Satellite altimetry and the intensification of Hurricane Katrina and Reply to Comment on "Satellite altimetry and the intensification of Hurricane Katrina" , Eos Trans. AGU.


Mekunu

22-26 May, Oman, Yemen
By Sreerekha Thonipparambil

Tropical Cyclone Mekunu was a Category 3 tropical cyclone that made landfall near Salalah, Oman on 26 May 2018.

Tropical cyclone Mekunu developed as a low pressure over North Indian Ocean on 21 May 2018, reached its peak intensity on 25 May, before making a landfall near Salalah, Oman on the 26 May.

 Meteoat-11 Airmass RGB, 23 May 17:15 UTC
Figure 8: Meteoat-11 Airmass RGB, 23 May 17:15 UTC

Mekunu had one-minute sustained winds estimated at 115mph and produced about 280mm rainfall in 24 hours — more than three times the annual rainfall average in the region. The storm and the resulting flooding caused destruction including casualties in Oman and Yemen.

The capability of satellite microwave observations to measure the warm core of tropical cyclones is presented in this case study. Unlike visible and infrared channels, channels of microwave sounding instruments like AMSU, onboard Metop and NOAA satellites, can be used to analyse the vertical structure of warm core.

For Mekunu, this is demonstrated in the warm brightness temperature anomalies in Channels 7 (54.94GHz) and 8 (55.54GHz) of AMSU. These channels peak at altitudes which are not affected by clouds, around 200hPa and 100hPa respectively. The warm brightness temperature anomalies increase as the cyclone intensifies. The series of images below depicts this behaviour as the storm develops, intensifies and dissipates. Images courtesy of the CIMSS Tropical Cyclones website .

For very strong storms the warm anomalies can be seen in channels 6 (54.4GHz) and 5 (53.596GHz) too (peaking at around 350hPa and 550hPa, respectively). The direct correlation of AMSU brightness temperature anomalies with both wind speed and minimum sea level pressure can be used to estimate the intensity of the tropical cyclone.

Channel 8

Metop-B AMSU-A Channel 8 Brightness Temperature, 22 May 17:33 UTC. Credit: CIMSS
Figure 9: Metop-B AMSU-A Channel 8 Brightness Temperature, 22 May 17:33 UTC. Credit: CIMSS
NOAA-18 AMSU-A Channel 8 Brightness Temperature, 23 May 16:00 UTC. Credit: CIMSS
Figure 10: NOAA-18 AMSU-A Channel 8 Brightness Temperature, 23 May 16:00 UTC. Credit: CIMSS
NOAA-18 AMSU-A Channel 8 Brightness Temperature, 24 May 15:49 UTC. Credit: CIMSS
Figure 11: NOAA-18 AMSU-A Channel 8 Brightness Temperature, 24 May 15:49 UTC. Credit: CIMSS
NOAA-18 AMSU-A Channel 8 Brightness Temperature, 25 May 15:39 UTC. Credit: CIMSS
Figure 12: NOAA-18 AMSU-A Channel 8 Brightness Temperature, 25 May 15:39 UTC. Credit: CIMSS
Metop-B AMSU-A Channel 8 Brightness Temperature, 24 May 17:52 UTC. Credit: CIMSS
Figure 13: Metop-B AMSU-A Channel 8 Brightness Temperature, 24 May 17:52 UTC. Credit: CIMSS

Channel 7

Metop-B AMSU-A Channel 7 Brightness Temperature, 22 May 17:33 UTC. Credit: CIMSS
Figure 14: Metop-B AMSU-A Channel 7 Brightness Temperature, 22 May 17:33 UTC. Credit: CIMSS
NOAA-18 AMSU-A Channel 7 Brightness Temperature, 23 May 16:00 UTC. Credit: CIMSS
Figure 15: NOAA-18 AMSU-A Channel 7 Brightness Temperature, 23 May 16:00 UTC. Credit: CIMSS
NOAA-18 AMSU-A Channel 7 Brightness Temperature, 24 May 15:49 UTC. Credit: CIMSS
Figure 16: NOAA-18 AMSU-A Channel 7 Brightness Temperature, 24 May 15:49 UTC. Credit: CIMSS
NOAA-18 AMSU-A Channel 7 Brightness Temperature, 25 May 15:39 UTC. Credit: CIMSS
Figure 17: NOAA-18 AMSU-A Channel 7 Brightness Temperature, 25 May 15:39 UTC. Credit: CIMSS
Metop-B AMSU-A Channel 7 Brightness Temperature, 24 May 17:52 UTC. Credit: CIMSS
Figure 18: Metop-B AMSU-A Channel 7 Brightness Temperature, 24 May 17:52 UTC. Credit: CIMSS

Channel 6

Metop-B AMSU-A Channel 6 Brightness Temperature, 22 May 17:33 UTC. Credit: CIMSS
Figure 19: Metop-B AMSU-A Channel 6 Brightness Temperature, 22 May 17:33 UTC. Credit: CIMSS
NOAA-18 AMSU-A Channel 6 Brightness Temperature, 23 May 16:00 UTC. Credit: CIMSS
Figure 20: NOAA-18 AMSU-A Channel 6 Brightness Temperature, 23 May 16:00 UTC. Credit: CIMSS
NOAA-18 AMSU-A Channel 6 Brightness Temperature, 24 May 15:49 UTC. Credit: CIMSS
Figure 21: NOAA-18 AMSU-A Channel 6 Brightness Temperature, 24 May 15:49 UTC. Credit: CIMSS
NOAA-18 AMSU-A Channel 6 Brightness Temperature, 25 May 15:39 UTC. Credit: CIMSS
Figure 22: NOAA-18 AMSU-A Channel 6 Brightness Temperature, 25 May 15:39 UTC. Credit: CIMSS
Metop-B AMSU-A Channel 6 Brightness Temperature, 24 May 17:52 UTC. Credit: CIMSS
Figure 23: Metop-B AMSU-A Channel 6 Brightness Temperature, 24 May 17:52 UTC. Credit: CIMSS

AMSU-A Brightness Temperature Anomaly

Metop-B AMSU-A Brightness Temperature Anomaly, 22 May 17:33 UTC. Credit: CIMSS
Figure 24: Metop-B AMSU-A Brightness Temperature Anomaly, 22 May 17:33 UTC. Credit: CIMSS
NOAA-18 AMSU-A Brightness Temperature Anomaly, 23 May 16:00 UTC. Credit: CIMSS
Figure 25: NOAA-18 AMSU-A Brightness Temperature Anomaly, 23 May 16:00 UTC. Credit: CIMSS
NOAA-18 AMSU-A Brightness Temperature Anomaly, 24 May 15:49 UTC. Credit: CIMSS
Figure 26: NOAA-18 AMSU-A Brightness Temperature Anomaly, 24 May 15:49 UTC. Credit: CIMSS
NOAA-18 AMSU-A Brightness Temperature Anomaly, 25 May 15:39 UTC. Credit: CIMSS
Figure 27: NOAA-18 AMSU-A Brightness Temperature Anomaly, 25 May 15:39 UTC. Credit: CIMSS
Metop-B AMSU-A Brightness Temperature Anomaly, 24 May 17:52 UTC. Credit: CIMSS
Figure 28: Metop-B AMSU-A Brightness Temperature Anomaly, 24 May 17:52 UTC. Credit: CIMSS

Other image sources

Cyclone Mekunu in the northwest Indian Ocean (CIMSS Blog)

Media reports

Cyclone Mekunu kills eleven and leaves dozens missing (The National)


2016

Vardah

8-19 Dec, Indian, Somalia
By Jochen Kerkmann and HansPeter Roesli

Using Meteosat-8 imagery it was possible to track the full lifetime of Tropical Cyclone Vardah.

Vardah was born from convective clusters west of the Little Andaman island. From 8 to 12 December it crossed the Gulf of Bengal on a straight track at the latitude of Chennai, India, where it made landfall on 12 December. At least seven people were reported to have died and thousands were displaced as a result of the storm.

The sequence of IR10.8 images shows the cyclic outbreak of severe convection (cloud tops as cold as 180 K), with a longer hiatus early on 10 December.

Figure 29: Meteosat-8 infrared animation, 8 December 2016 00:00 UTC–19 December 06:00 UTC
 Met-8 HRV, 15 Dec 05:00–10:00 UTC (animated gif)
Figure 30: Meteosat-8 HRV, 15 December 2016 05:00–10:00 UTC

Interestingly, after making landfall in eastern India, Vardah crossed the Indian Subcontinent from east to west, surviving the land impact, and re-emerged on the other side of India.

On 15 December, the low-level circulation centre (LLCC) of Vardah is well seen on the animated gif of Meteosat-8 High Resolution Visible (HRV) images (Figure 30).

In the following days, Vardah moved westwards at constant speed, as can be seen from the the track (Figure 31), not gaining any strength (it did not reach hurricane force), but with a persisting LLCC.

Finally, on 18/19 December, it reached the east coast of Africa making its second landfall, this time in Somalia, see the Meteosat-8 Natural Colour RGB (Figure 32), where it probably caused widespread rainfalls (assumed due to lack of available rainfall data).

 Met-8 VIS0.8, 19 Dec 06:00 UTC
Figure 31: Meteosat-8 VIS0.8, 19 December 2016 06:00 UTC. Track of Vardah, 8–19 December overlaid (Credit: ePort).
 Met-8 Natural Colour RGB, 19 Dec, 06:00 UTC
Figure 32: Meteosat-8 Natural Colour RGB, 19 December 2016 06:00 UTC. Credit: ePort.

Himawari-8 image of Vardah

Himawari-8 animation of the cyclone making landfall (Credit: CIRA Loop of the Day )

Media reports

Cyclone Vardah: Several dead as storm lashes Indian coast (BBC News)


Fantala

12-18 Apr, Madagascar, Seychelles, Mauritius
By Jochen Kerkmann

Fantala became a named Tropical Cyclone on 11 April with maximum winds of around 63km/h (40mph). By 18 April the cyclone had intensified into a powerful Category 5 storm with maximum sustained winds of more than 280km/h (175mph).

On the Meteosat-10 images from 18 April at 04:00 UTC (Figure 33) a very well-developed eye of about 44km diameter could be clearly seen.

HRV image comparison

High Resolution Visible image blended with IR10.8 compare1
compare2
 

Figure 33: Meteosat-10 HRV image, 18 April 2016 04:00 UTC. For comparison, the Sandwich product is also shown to highlight the coldest parts of the system (dark red corresponds to 185K).
Full resolution IR10.8 image with a larger area around Fantala.

 Meteosat-10 HRV image, 18 April 13:30 UTC
Figure 34: Meteosat-10 HRV image, 18 April 13:30 UTC

On Figure 34, the HRV image from 18 April, 13:30 UTC, the overshooting tops can be clearly seen illuminated by the evening Sun.

An overshooting convective cloud top (OT) is a dome-like protrusion above a cumulonimbus anvil, often penetrating into the lower stratosphere. It is a manifestation of a very strong updraft in the convective cloud.

OTs can be most easily identified in the high resolution visible channel imagery as the lumpy textured appearance, although only during daytime.

The VIIRS instrument on Suomi-NPP also captured imagery of the eye of Tropical Cyclone Fantala when it was a Category 5 storm.

It was reported that the Seychelles island of Farquhar suffered significant damage overnight 17 April into 18 April, after Fantala passed over the archipelago's outer island.

No injuries were reported despite the fact the cyclone brought winds of up to 345km/h (214mph).

The Meteosat-10 IR animation (Figure 35) over the area around the Farquhar islands shows the moment when Fantala crosses the southern Farquhar island.

At around 15.15 to 15.30 UTC, the island is in the eye of the tropical cyclone.

 Met-10, 17 April 2015, 13:30–18:00 UTC
Figure 35: Meteosat-10 infrared, 17 April 2016 13:30–18:00 UTC
 Met-10, 17 April 2015, 13:30 UTC
Figure 36: Meteosat-10 High Resolution Visible, 17 April 2016 13:30 UTC

About two hours before the eye crossed Farquhar, the High Resolution Visible image (Figure 36) was captured. Again the eye of Fantala can be clearly seen, as can the overshooting tops, illuminated by the morning/evening Sun.

Subsequently, Madagascar did not get much rain, there were some large swells and storm surges.

Dan Lindsey, an atmospheric scientist with NOAA/NESDIS, tweeted an infrared image from 17 April at 22:45 UTC (Figure 35).

The MODIS instrument on the NASA-owned Terra satellite also captured the clear eye of the cyclone, as shown on the MODIS Band 1 (VIS0.6) image at 500m resolution, 17 April at 6:45 UTC.

 Suomi-NPP VIIRS infrared image, 17 April 22:45 UTC (Source: NOAA/NASA RAM/CIRA)
Figure 37: Suomi-NPP VIIRS infrared image, 17 April 2016 22:45 UTC (Source: NOAA/NASA RAM/CIRA)

The Joint Typhoon Warning Center forecast from 17 April suggested that Fantala would turn round and move back towards the east later in April.

The tropical cyclone began to weaken late on 18 April, with maximum sustained winds of 193km/h (120mph) being recorded at 06:00 UTC on 19 April.

This is partly due to its unusual track, moving back the same way it approached Madagascar, over waters that it already mixed up previously, thus weakening the intensity.

The progress of Tropical Cyclone Fantala, as it passed over the Indian Ocean towards Madagascar, intensifying as it went, can be seen on the Meteosat-10 Airmass RGB, imagery (Figure 38).

 Animated gif of Met-10 Airmass RGB, 12 April 00:00 UTC–18 April 07:00 UTC
Figure 38: Meteosat-10 Airmass RGB, 12 April 2016 00:00 UTC–18 April 07:00 UTC

CIMSS blog coverage

Cyclone Fantala in the Indian Ocean (CIMSS Blog)

Media reports

Satellite Images Illustrate the Power of Category 5 Tropical Cyclone Fantala Near Madagascar (The Weather Channel)
Tropical cyclone ‘Fantala’ hits Seychelles island of Farquhar; infrastructure damaged (Seychelles News Agency)


2015

Chapala

28 Oct-3 Nov, Yemen, Arabian Sea
By Gabriele Formentini, Mark Higgins, Ian Mills, HansPeter Roesli

Tropical Cyclone Chapala was one of the strongest cyclones to ever hit Yemen. It was formed from a depression in the Eastern Arabian Sea on 28 October. The formation and progression of the storm can be seen in the Meteosat-7 infrared loop, 27 October 07:00 UTC– 1 November 07:00 UTC.

It is unusual for cyclones in this basin to pass along the Gulf of Eden and make landfall in Yemen, which this cyclone did.

The visible image from Meteosat-7 (Figure 1) shows the storm as it began to weaken. The winds are from the ASCAT instrument on Metop-B.

 Meteosat-7 Visible image with ASCAT winds overlaid, 1 November 05:30 UTC.
Figure 39: Meteosat-7 Visible image with ASCAT winds overlaid, 1 November 2015 05:30 UTC.
 Track of Tropical Cyclone Chapala
Figure 40: Track of Tropical Cyclone Chapala

From 29 October onward Tropical Cyclone Chapala moved westward (Figure 40), in some contrast to the track forecasts that had it moving north-westward toward the coast where Yemen and Oman meet. At the same time, it evolved into a Category 3 storm and accelerated its forward speed.

Following their experience from the Tropical Cyclone Ashobaa in the summer and due to the incorrect track forecasts, Oman braced for an emergency situation along its southern coastline. Fortunately, the stormy weather only grazed the area with short downpours and high wind at places.

During the Category 3 stage the cyclone underwent some wall replacement cycles, as can be seen on the Meteosat-10 Enhanced Tropical Airmass animation, 29 October 00:00 UTC–3 November 12:00 UTC and showed a big eye (Figure 41).

 Metosat-10 Tropical Airmass, 2 Nov 07:00 UTC
Figure 41: Metosat-10 Tropical Airmass, 2 November 2015 07:00 UTC

On 3 November, hurtling passed Socotra, it made landfall on the Yemeni coast well inside the Gulf of Aden.

The powerful storm dumped huge amounts of rain on an arid region. At least 228mm of rain was originally estimated to have fallen, in areas which usually get an average of 101mm of rain per year.

Later NASA's Global Precipitation Measurement mission showed rainfall amounts up to 380mm over south central Yemen and along the coast, with the highest total over Yemen being 398mm (~16in). Gusts of 167km/h (103mph) were reported in Yemen.

Shortly after crossing the coast, when the source of moisture was removed, the typhoon quickly decayed.

On the Meteosat-10 Airmass RGB imagery tuning is used which takes into account the colder cloud tops with respect to mid-latitude.

Addendum

In his comprehensive scientific report on Tropical Cyclone Chapala, Gabriele Formentini, from SMHI, took a closer look at the wind and wave data from the time period.

Overview of the report

The overall forecast reliability for the tropical cyclone Chapala was good from the beginning, however, the rapid intensification process the storm went through between 29–30 October was not well forecast, either by the global models or the official weather forecast.

The use of the satellite imagery and data is of inestimable value in the understanding of the processes involved in the evolution of such systems and could help explain what happened during those 12–24 hours that Chapala went from a strong tropical cyclone to a Category 4 hurricane.

The unusual track of the storm had a significant impact in our daily Weather Routing job at SMHI. The western Arabian Sea and Gulf of Aden is well known as one of the most dangerous stretches of water for shipping, due to the Somalian piracy activity. All the merchant vessels have to sail through the Gulf of Aden Internationally Recommended Transit Corridor (IRTC) in groups in order to exploit the additional protection and assurance of being in a group. Chapala had a track that crossed the IRTC and the impact on the vessels route was important.

Tropical Cyclone Chapala was formed from a depression in the Eastern Arabian Sea on 28 October. The ASCAT wind product from 28 October, 17:24 UTC (Figure 42), revealed winds speeds of up to 50kts (about 90km/h) and also allowed a clear view of the detailed surface circulation (note also the wind vector wind ambiguity of 180° in the black box).

 Metop-B, 28 October 2016, 17:24 UTC
Figure 42: Metop-B ASCAT 2 km winds, 28 October 2015 17:24 UTC. Credit: NOAA/NESDIS.
 Metop-B, 31 October 2016, 05:59 UTC
Figure 43: Metop-B ASCAT 25km winds, 31 October 2015 05:59 UTC. Credit: NOAA/NESDIS.

From 29 October the tropical cyclone started its movement west, with an average speed of 7–8kts (13–15km/h). On 30 October when it reached Category 4 status a very clear eye could be seen on MODIS imagery, 30 October 09:10 UTC.

The ASCAT wind product from 31 October at 05:59 UTC (Figure 43) shows that the tropical cyclone continued to move towards the west with wind speeds above 50 knots (93 km/h).

The VIIRS image from 1 November 21:46 UTC (Figure 44) shows Chapala between Socotra Island, the south of Yemen and the northern region of Somalia. The satellite image, together with the near-simultaneous ECMWF wave model analysis of 2 November at 00:00 UTC (Figure 45), revealed significant wave height values of up to 12m, which were confirmed by Jason-2 altimeter measurements (overpass between 21:00 and 00:00 UTC).

 Suomi-NPP, 01 November 2016, 21:46 UTC
Figure 44: Suomi-NPP VIIRS Visible, 1 November 2015 21:46 UTC
 Jason-2, 02 November 2016, 00:00 UTC
Figure 45: Jason-2 Sign Wave Height and altimeter corrected wave height (analysis), 2 November 2015 00:00 UTC. Credit: ECMWF/Jean Bidlot

On 3 November Chapala went over land causing severe damage in Yemen, Socotra and in northern parts of Somalia. In the worst affected areas, such as the southern region of Yemen, rainfall records were broken.

 Before (19 Oct, 2015) and after (4 Nov, 2015) Landsat-8 satellite images of a flooded wadi and coastal area of Yemen resulting from Cyclone Chapala. (Credit: NASA Earth Observatory)
Figure 46: Before (19 October, 2015) and after (4 November, 2015) Landsat-8 satellite images of a flooded wadi and coastal area of Yemen resulting from Cyclone Chapala. Credit: NASA Earth Observatory.

Landsat-8 satellite images (Figure 46) enable us to evaluate the effects of the Tropical Cyclone Chapala inland, where a large flooded area is clearly seen. Due to the flooding, thousands were evacuated from the most vulnerable parts of coastal regions. At Al Mukalla (Yemen), the sea level rose up to 9m and rainfall records were broken causing eight deaths.

Download Gabriele's full report

Other image source

Tropical Cyclone Chapala seen from the International Space Station (Twitter/Capt Scott Kelly)

Media reports

Cyclone Chapala Makes Landfall in Yemen (PHOTOS) (The Weather Channel)
Cyclone Chapala dumps years' worth of rain in Yemen, causing extensive damage (Mashable)


Ashobaa

6-11 June, Arabian Sea, Oman
By Hilal Al-Hajri and Shima Al-Yazidi (PACA), Jochen Kerkmann, HansPeter Roesli

In early June 2015 Tropical Cyclone Ashobaa formed over the Indian Ocean, then headed towards Oman.

After forming as tropical storm off the Indian subcontinent, Ashobaa moved over the Arabian Sea, becoming a Category 1 cyclone. According to the Oman Department of Meteorology, the island of Masirah (off the east coast of Oman) received 239.4mm of rain during the three days that Ashobaa affected the country.

The progress of the tropical cyclone can be seen in the Meteosat-7 infrared animation, 5 June 12:00 UTC–15 June 06:00 UTC, from sudden birth on 5 June, explosive on 7 June, to slow dissipation from 10 to 15 June, after landfall there was recurrent severe convection near Masirah Island.

 Meteosat-7 sandwich product, 8 June 12:00 UTC (IR blended with VIS background image)
Figure 47: Meteosat-7 sandwich product, 8 June 2015 12:00 UTC (IR blended with VIS background image)
 Meteosat-7 Visible, 6 June 06:30 UTC–10 June 13:00 UTC (animated gif)
Figure 48: Meteosat-7 Visible, 6 June 06:30 UTC–10 June 2015 13:00 UTC (animated gif)

Ashobaa started to develop in the Indian Ocean, near Indian subcontinent, and was classified as a low pressure on 5 June. It was 1400km away from the Oman coast.

The low pressure started to intensify and move north to north west. On 7 June the surface wind around the centre reached between 46–56km/h ( 25–30kts) and the system was classified as a deep depression.

At that time the system was still travelling north to north west and was located 1200km away from the Oman coast.

On 8 June the system started to intensify very quickly (Figure 48) and became a named tropical storm (Ashobaa), see Met-10 Dust RGB image with ECMWF 10m model winds overlaid (Credit: EUMeTrain). The wind speed around the centre was between 64–74km/h (35–40kts) and the movement became more west to north west, see also Day Microphysics RGB (8 June 11:00 UTC) from the Indian Meteorological Agency's Insat 3D satellite.

The Metop AVHRR image (Figure 49) shows the extensive, high-level cirrus outflow from the relatively small tropical storm.

 Metop-A AVHRR IR10.8 image blended on the Night Microphysics background image, 8 June 17:05 UTC
Figure 49: Metop-A AVHRR IR10.8 image blended on the Night Microphysics background image, 8 June 2015 17:05 UTC

On day-night band imagery from NOAA's Suomi-NPP satellite, from 8 June at 20:45 UTC the cyclone's structure could be clearly seen.

On 9 June the tropical storm moved closer to Oman — approximately 500km off the coast. At that time the advocated high and medium cloud touched the Oman coast and sea condition were rough, with waves reaching 3.5m.

For tropical storms like Ashobaa it is often difficult to locate the centre (defined as low level circulation centre) of the system in simple VIS or IR images. In these cases, it is recommendable to use microwave imagery like the 89 GHz Channel from MHS on Metop, or comparable channels on other satellites like the 37 or 85 GHz channels on TMI, or the 85 GHz channel on SSMI, or, even better, to use the wind vectors from scatterometer instruments like ASCAT to locate the centre of the cyclone. For more info, have a look at the lecture from Sheldon Kusselson (NOAA) , presented in 2012 during a satellite training workshop in Pretoria, South Africa

Figure 50 shows the AVHRR IR image from 9 June 05:29 UTC and compares it to the 89 GHz image from MHS. The centre of the cyclone is not visible on the IR image but clearly appears on the MHS image.

Metop image comparison

Metop-A MHS Channel 01 compare1
compare2
 

Figure 50: Comparison of Metop-A infrared and microwave images, 9 June 2015 05:29 UTC

Likewise, the scatterometer winds shown in Figure 5 help to locate the centre of Ashobaa that is not visible in the AVHRR VIS/IR images.

Metop image comparison

Metop-A Visible with ASCAT winds overlaid compare1
compare2
 

Figure 51: Comparison of Metop-A visible images, on which the second image has ASCAT winds overlaid, 10 June 2015 05:18 UTC

Ashobaa's closer proximity to the Oman coast could be seen in both Meteosat-10 and Metop-B imagery. This Meteosat-10 HRV loop from 02:00–09:30 UTC shows the cyclone approaching the coast.

 Metop-B, 09 June 2015, 04:49 UTC
Figure 52: Metop-B IR10.8, 9 June 2015 04:49 UTC
 Metop-B, 09 June 2015, 04:49 UTC
Figure 53: Metop-B Natural Colour RGB, 9 June 2015 04:49 UTC

As the cyclone moved closer to Oman, the need to make a rainfall estimation forecast became more important, as it was likely that the country could receive substantial amounts of rain.

For countries which don't have a rainfall radar network, NOAA has developed a method called eTrap (ensemble Tropical.Rainfal Potential). This method allows for the generation of probabilistic forecasts of rainfall in addition to deterministic rainfall totals.

Each eTRaP is made up of forecasts using LEO satellite observations from NOAA/Metop (MHS), NASA (TRMM) and DMSP (SSMIS).

The three basic assumptions for eTrap are:

  1. satellite rain rate estimates are accurate;
  2. forecast tracks are accurate, and
  3. rain rates over 24 h period are in steady state.

The resulting 24-hour forecasts (issued on 10 June and 11 June at 00:00 UTC) for Ashobaa showed rainfall amounts between 25 and 100mm for the coastal region of Oman.

By 10 June, as the cyclone started to move over the Omani coast, it started to weaken slightly. Looking at satellite imagery it appeared that this was due, in part, to dry-dusty air being ingested into the system. An area of low-level dust north-east of the system can be clearly seen on the Meteosat-10 Dust and Natural Colour RGB images (Figure 54). The dust, which originated over Iran and Afghanistan, is visible over Pakistan, the Sea of Oman and northern Oman. There are also large areas of sunglint (over the sea and some low-level clouds, see Natural Colour RGB), which should not be confused with dust.

Meteosat image comparison

Meteosat-10 Dust RGB compare1
compare2
 

Figure 54: Comparison of Meteosat-10 images showing the dust, 10 June 2015 02:00 UTC

On 11 and 12 June, Ashobaa very slowly moved westward approaching Masirah Island on the south coast of Oman, but not making landfall. As can be seen in Figures 55 and 56, the structure of Ashobaa is better seen in Meteosat-7 visible imagery than in Meteosat-10 HRV images. Both have comparable horizontal resolution for this area, but Meteosat-7 visible images have a higher contrast for thin and thick clouds due to the position of Meteosat-7 over the Indian Ocean (57 deg E, nearly NADIR viewing for Oman area).

 Meteosat-7 , 11 June 06:00 UTC
Figure 55: Meteosat-7 Visible , 11 June 2015 06:00 UTC
 Meteosat-10, 11 June 06:00 UTC
Figure 56: Meteosat-10 HRV, 11 June 2016 06:00 UTC

Other image source

Cyclone Ashobaa over the Arabian Sea (NASA Earth Observatory)

Media reports

Ashobaa effect in Oman: Heavy rain floods Sur, Masirah areas; rescue work on (Oman Times)
No Ashobaa casualties (Oman Observer)


Bansi

10-18 Jan, Madagascar, Mauritius, Réunion
By Jochen Kerkmann and HansPeter Roesli

On 11 January Tropical Cyclone Bansi formed north of Réunion Island in the Southern Indian Ocean and in less than 24 hours had intensified into a category 3 storm.

By January 12 the storm had rapidly consolidated and the bands of thunderstorms circling the centre had expanded. Bands of thunderstorms which were spiralling around the storm, wrapped around it from the northwest to the southeast and finally wrapped into the centre from the west.

According to the Joint Typhoon Warning Center (JTWC) as of 06:00 UTC on 12 January, the centre of Bansi was located close to 17.25°S 55.9°E, approximately 350km northwest of Mauritius, with maximum sustained winds of 185km/h, equivalent to a Category 3 storm on the Saffir-Simpson Hurricane Winds scale (SSHWS), and was tracking east at 13km/h towards the island archipelago of Saint Brandon. Hurricane force winds were extending 56 km from the centre of the storm, while tropical storm force winds were extending outwards up to 195km.

Metop-B, 12 January 2015, 05:13 UTC
Figure 57: Metop-B AVHRR RGB, 12 January 2015 05:13 UTC
Met-7, 12 January 2015, 09:00 UTC
Figure 58: Meteosat-7 IODC Visible (0.7), 12 January 2015 09:00 UTC.
Download VIS animation 11 January 02:30 UTC–15 January 10:30 UTC
Met-10, 12 January 2015, 11:00 UTC
Figure 59: Meteosat-10 HRV, 12 January 2015 11:00 UTC
Met-10, 12 January 2015, 18:00 UTC
Figure 60: Meteosat-10 IR10.8, 12 January 2015 18:00 UTC
Download animation , 10 January 12:00 UTC–15 January 12:00 UTC.

13 January activity

By the morning of 13 January Bansi's maximum sustained winds had reached 260km/h, equivalent to a Category 4 storm, with gusts of more than 300km/h.

Metop-B Natural Colour RGB with ASCAT winds overlay, 13 January 05:45 UTC
Figure 61: Metop-B Natural Colour RGB with ASCAT winds overlay, 13 January 2015 05:45 UTC. Download zoomed-in version

The high winds speeds can be seen on the Metop-B image with ASCAT winds overlaid from 13 January, 05:45 UTC.

Met-7 infrared, 15 January 02:00, showing the width of the eye
Figure 62: Meteosat-7 infrared, 15 January 2015 02:00 UTC, showing the width of the eye

15 January activity

Later on 13 January the storm started to weaken slightly, but on 15 January started to re-intensified into a Category 4 storm, bringing high winds and heavy rainfall to Mauritius. As it intensified again the eye of the storm quadrupled in size, as can be seen in the zoomed-in infrared image right.

16 and 17 January activity

Met-7 infrared, 15 January 02:00, showing the width of the eye
Figure 63: Meteosat-7 infrared, 15 January 2015 02:00 UTC, showing the width of the eye

The visible imagery from Meteosat-7, 16 January 07:30 UTC, shows another tropical system, Tropical Cyclone Chedza, over the Mozambique Channel. The distinct eyes of both storms can be clearly seen in the image. The infrared animation, Meteoesat-7, 10 January 00:00 UTC–18 January 06:00 UTC shows the progress of both cyclones.

Tropical cyclone Chedza passed over Madagascar on 16/17 January, leaving at least 14 dead and causing severe floods and landslides.

Other image sources

Tropical Cyclone Bansi in the Indian Ocean (CIMSS Blog)
NASA-NOAA's Suomi NPP Satellite Sees Tropical Cyclone Bansi's Eye Almost Quadruple in Area (NASA)
Real-time storm coverage (SSEC, University of Wisconsin-Madison)

Media report

Mauritius braces for tropical storm (Global Times)


Eunice and Diamondra

26 Jan-1 Feb, Mascarene Islands
By HansPeter Roesli

At the end of January, a few days after the tropical cyclone twins Bansi and Chedza, another pair of tropical depressions developed in the Southern Indian Ocean.

Diamondra started on 26 January, but never reached tropical cyclone status and dissolved during 28 February.

One day after Diamondra formed, tropical depression Eunice developed in the west, north of Rodrigues island, part of the Mascarene Islands.

Meteosat-7 infrared image of the twin tropical storms, 28 January 15:00 UTC
Figure 64: Meteosat-7 infrared image of the twin tropical storms, 28 January 2015 15:00 UTC

The Meteosat-7 infrared animation, 28 January 00:00 UTC–1 February 18:00 UTC, follows Eunice and Diamondra during the seven days where they stayed very close together. Eunice's well-structured eye can be clearly seen.

The outflow from the storm tops was also spectacular, marked by spiralling cirrus bands.

Download animation, 28 January 00:00 UTC–1 February 18:00 UTC

Metop-B IR10.8 with ASCAT winds overlaid, 30 January 17:21 UTC
Figure 65: Metop-B IR10.8 with ASCAT winds overlaid, 30 January 2015 17:21 UTC

Eunice rapidly evolved into a tropical cyclone and intensified further into a category-5 storm on 30 January. Eunice became the fourth tropical cyclone of the 2015 Southern Indian Ocean season.

The combination of AVHRR channel IR10.8 and the wind field from ASCAT on Metop-B shows the cloud and wind patterns, as well as her spatial extension close to the time of her maximum intensity.

After reaching maximum sustained wind speeds of around 260km/h, Eunice started to weaken on 1 February.

Other image sources

Composite image from EUMETSAT and JMA satellites (Flickr)
Eunice (Southern Indian Ocean) (NASA)
Real-time storm coverage (SSEC, University of Wisconsin-Madison)

Media reports

Tropical Cyclone Eunice Reaches Category 5 Status (The Weather Channel)


2014

Adjali

14-17 Nov, Southern Indian Ocean
By Ivan Smiljanic

The start of the cyclone season for South-West Indian Ocean began in 2014 with the severe tropical storm named Adjali.

The system developed on 14 November and moved in a south-easterly direction over the next few days.

On 19 November the deep convection collapsed and the weakened system started to change its direction to the south west.

There was no impact on land because the trajectory of the cyclone covered only areas of open sea.

 Met-7, 17 November 2014 03:30 UTC
Figure 66: Meteosat-7 Visible 0.75µm band, 17 November 2014 03:30 UTC
 Met-7, 16 November 2014 11:30 UTC
Figure 67: Meteosat-7 Visible 0.75µm band, 16 November 2014 11:30 UTC

Due to a strong convective forcing an area of low pressure developed in the south west Indian Ocean on 15 November.

One of the triggers for such intense convective development could be the propagation of gravity waves from the convective system that rapidly developed some hours before, approximately 1000km southwest from it.

This was the first tropical cyclone that formed during the South Indian Ocean cyclone season that normally starts in late November/early December and lasts until May. It was considered to be a relatively early development of a cyclone.

The system had a northwest-south-southeast loop at the beginning of formation and later continued its trajectory towards the south east for a few days.

The wide bands of thunderstorms developed around the centre of circulation (Figure 66) with many overshooting tops detected on the Meteosat-7 visible image with 2.5km per pixel resolution of the MVIRI instrument (Figure 67). The prominent eye of the system can also be seen at a few stages, looking at the half hourly infrared animation 13 November, 09:00 UTC–19 November, 17:00 UTC.

Maximum sustained winds exceeded 110km/h and the system, as a whole, was moving with the average speed of around 10–15km/h.

 Met-7, 17 November 2014 06:00-07:00 UTC
Figure 68: Meteosat-7 WV 6.9µm band overlaid with the U component of the high level wind isotachs at 300hPa, indicating the jet streak south/southeast to the tropical cyclone, 17 November 2014 06:00-07:00 UTC
 Trajectory of the tropical cyclone Adjali.
Figure 69: Trajectory of the tropical cyclone Adjali. Indication of the stages and the forecast trajectories on 19 November 2014 (Credit: Météo-France)

South of the system an area of high pressure was present. Moving to the edge of this high pressure system the tropical cyclone was strongly influenced by the upper north-westerly winds which had a negative influence on development of convection (Figure 68).

This vertical shear strongly downgraded the intensity of the cyclone and the residual low level cyclonic system changed its path to a westerly direction (Figure 69).

No damage nor human casualties were reported since the trajectory of the system covered only areas of opened ocean.

Other image source

GPM Measured Tropical Storm Adjali's Rainfall Before Dissipation (NASA)

Media report

Tropical Storm Adjali Making The Curve In The Southern Indian Ocean (Science 20)


Hudhud

6-15 Oct, India, Nepal, Tibet
By Mark Higgins, Jochen Kerkmann, Sancha Lancaster, HansPeter Roesli

Tropical Cyclone Hudhud was the strongest tropical cyclone of 2014 within the North Indian Ocean, with 1-minute sustained winds of 215km/h (130mph).

On 11 October Hudhud intensified in a very severe cyclone, with a visible eye. It made landfall in Visakhapatnam on 12 October with winds speeds of 180km/h, gusting to 200km/h. The cyclone left a trail of destruction across the region and five dead, despite a massive evacuation effort.

Two days later the tail-end of the cyclone triggered blizzards and avalanches on the Annapurna circuit, a popular hiking route in Nepal. At least 39 people died and dozens more were reported missing.

The Meteosat-7 imagery (Figures 70 and 71) below shows Tropical Cyclone Hudhud over the Bay of Bengal, heading towards India. On the infrared imagery, 10 October 03:00 UTC, the large scale of the cyclone can be seen, with the most intense areas shown in dark red (coldest cloud tops).

 Met-7, 10 October 2014, 03:00 UTC
Figure 70: Meteosat-7 IR11µm, 10 October 2014 03:00 UTC
 Met-7, 10 October 2014, 03:00 UTC
Figure 71: Meteosat-7 IR image with 12.5 km ASCAT winds, 10 October 2014 03:00 UTC

The Meteosat-7 IR image with 12.5km ASCAT winds overlay, 10 October 03:00 UTC (Figure 71), shows the area with hurricane force winds in the centre. On both images a well-defined eye is not visible, however, the ASCAT data shows the tight circulation centre.

The animation of the Meteosat-7 visible imagery (Figure 72), shows Hudhud's progression from tropical storm to cyclone as it crossed the Bay of Bengal.

Figure 72: Meteosat-7 visible, 6 October 2014 00:00 UTC–10 October 08:30 UTC

Around the time of the imagery the Joint Typhoon Warning Center reported that the cyclone was "tracking along the southern periphery of the subtropical ridge (STR) to the north (Figure 73): "The cyclone is expected to remain on a generally west-northwestward trajectory under the steering influence of the STR throughout the forecast period. Favorable upper-level conditions are expected to improve, allowing tc 03b [the cyclone] to steadily intensify peaking at 105 knots prior to landfall near Visakhapatnam by tau 48 [in the following 48 hours]."

 Joint Typhoon Warning Center forecast track for TC Hudhud, 10 October.
Figure 73: Joint Typhoon Warning Center forecast track for TC Hudhud, 10 October 2014

In Figure 74 both Tropical Cyclone Hudhud and Super Typhoon VongFong can be seen. Both were forecast to make landfall (in India and Japan respectively), over the weekend of 11/12 October.

 Metop-A/B with ASCAT passes composite image of two tropical cyclones
Figure 74: Metop-A/B with ASCAT passes composite image of two tropical cyclones

The Korean Meteorological Administration's COMS-1 satellite also saw the two cyclones on 11 October (Figure 75).

Tropical Cyclone Hudhud over Bay of Bengal
Figure 75: COMS-1 Visible, 11 October 2014 05:15 UTC

11/12 October

 Met-7 enhanced IR, 12 October 2014, 06:00 UTC
Figure 76: Meteosat-7 enhanced IR, 12 October 2014 06:00 UTC
View the KMZ file on Google Earth
Download 24-hour animation , Meteosat-7, 12 October 00:00 UTC–13 October 00:00 UTC.
 Metop-A, Natural Colour RGB, 12 October 2014, 04:14 UTC
Figure 77: Metop-A, Natural Colour RGB, 12 October 2014 04:14 UTC

13–15 October

 Metop AVHRR image from 14 October 04:17 UTC
Figure 78: Metop AVHRR, 14 October 2014 04:17 UTC

The Meteosat-7 visible imagery animation (Figure 79) shows Hudhud as it crossed Nepal. Towards the end of the animation the heavy snowfall over Nepal and Tibet is visible.

Figure 79: Meteosat-7 Visible, 13 October 01:30 UTC–15 October 2014 10:30 UTC.

On Figure 78, the Metop AVHRR image from 14 October 04:17 UTC, thick ice clouds can be seen over Nepal (cyan colour).

The cyclone season in the North Indian Ocean is unusual, compared to the cyclone seasons in the Pacific and the Atlantic, with the peak activity occurring in May–June and October/November and almost no tropical cyclones forming in July to September.

Warning

Tropical Cyclone warnings (JTWC)

Other image source

Real time storm coverage (NOAA/CIMSS)

Media reports

Cyclone Hudhud hits Andhra Pradesh, leaves a trail of destruction (Indian Express)
India Cyclone Leads to Blizzard in Nepal That Leaves at Least 27 Dead (Mashable)


2013

Phailin

9-12 Oct, Andaman Islands, India
By HansPeter Roesli

Tropical Cyclone Phailin (Sapphire in Thai) was born over the Andaman Islands in the Bay of Bengal.

It caused major damage and deaths when it made landfall in India. The animation (Figure 80) shows Phailin on its way towards India, when it reached category-5 strength, before weakening a little bit. It made landfall shortly after the last image was taken.

It has been reported that at least 23 people were killed by the cyclone which hit the states of Andhra Pradesh and Odisha, with winds of around 200km/h (125mph). It was estimated to have caused damage of more than £220m.

A mass evacuation took place as the cyclone headed towards India on 11 October. It had been predicted to reach Super Cyclone strength but weakened slightly before landfall.

Figure 80: Meteosat-7 Visible, 12 October 2013 00:00–18:00 UTC

The infrared animation in Figure 81 shows lifecyle of the cyclone, from 9-12 October.

Figure 81: Meteosat-7 infrared, 9 October 2013 09:00 to 12 October 23:00

Media reports

India's Cyclone Phailin leaves trail of destruction (BBC News)
Cyclone Phailin hits 90 lakh people; 23 dead, lakhs of homes damaged (Times of India)


2012

Giovanna

11-13 Feb, Madagascar, Réunion, Mauritius
By Jochen Kerkmann

Giovanna reached 10-minute sustained winds of 195 km/h (120 mph) and 1-minute sustained winds 230 km/h (145 mph). As a result of the cyclone, there were 35 deaths along the Madagascar coast, Réunion, and Mauritius, and it was the first intense tropical cyclone to impact Madagascar since Cyclone Bingiza in February 2011.

Cyclones of this intensity (Category 3 to 4) often cause severe damage and large waves estimated up to 8 m (26 ft) high affected the coast of Réunion.

In this Meteosat-9 infrared imagery (Figure 82) the coloured areas represent higher, colder clouds, with the strongest winds in the pink/lilac areas.

Figure 82: Meteosat-9 IR, 11 February 2012 11:15 UTC- 13 February 08:15 UTC

The Meteosat-9 HRV loop (Figure 83) shows two eyewall replacement cycles in Tropical Cyclone Giovanna on 13 February. These may occur in intense tropical cyclones with winds greater than 185 km/h.

Figure 83: Meteosat-9 HRV, 13 February 2012 03:00-13:45 UTC