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Prediction of Track and Intensity of the Tropical Cyclonic using High
Resolution WRF-ARW Model
Md. A. E. Akhter*1,2
and M. M. Alam1
1Department of Physics, Khulna University of Engineering & Technology, Bangladesh
2SAARC Meteorological Research Centre, Bangladesh
*Corresponding author : [email protected]
Abstract:
High resolution Advanced Research WRF (ARW) meso-scale model version 3.5.1 adopted from
National Center for Atmospheric Research (NCAR) is used to simulate the track and intensity of the
tropical cyclonic of the Bay of Bengal. WSM3 microphysics and Kain Fritisch’s cumulus
parameterization scheme has been used with Yonsei University planetary boundary layer. Horizontal
resolution of 9 km is used. The objective of this study is to simulate the track, and intensity of the
tropical cyclone Nargis, Thane and Mahasen to observe the performance of WRF (ARW) model. The
model simulated track, sea level pressure and wind are compared with those taken from Indian
Meteorological Department (IMD). Model simulates landfall position and time with fair accuracy.
Keyword: WRF Model, Tropical Cyclone, Intensity, Track, Landfall Position.
1. INTRODUCTION
Tropical cyclones (TCs) are one of the most dangerous natural calamities throughout the globe. Every year, they
cause considerable loss of life and do immense damage to property due to strong MSWs, torrential rainfall and
storm surges. These occur during the pre-monsoon (April–May), early monsoon (June), late and post-monsoon
(September– November) periods. Originating in both the Bay of Bengal and Arabian Sea, tropical cyclones
often attain velocities of more than 160 km/h and are notorious for causing intense rain and storm tides (surges)
as they cross the coast of India, Bangladesh and other coasts. Strong MSWs, heavy and torrential rains and the
cumulative effect of storm surges and astronomical tides are the three major elements of tropical cyclone
disaster. This is also the basin where TCs do the most damage due to the combined effects of terrain, geography,
and lack of communications. The need for sea surface temperature (SST) greater than 26.5◦C and a deep lower
level moist layer and absence of strong vertical shear for development from a tropical low to a cyclonic storm
and further intensification has been referred to in many studies [1]. More than 200,000 people perished in the
Bhola cyclone of 1970 in Bangladesh.
Predictions of tropical cyclones have improved steadily over the last three decades, mostly due to a
combination of better observations, especially the satellite and radar, improvement in dynamical models and
improved understanding of physical processes and mechanisms that govern the motion of tropical cyclones. The
current emphasis of international tropical cyclone research is to achieve greater accuracy of tropical cyclone
track and intensity prediction, especially in the short range (48–72 h in advance), by maximizing the use of non-
conventional data, meso-scale analysis, and the physical parameterization in nonhydrostatic environment at
higher model resolution. In India, development of objective techniques for forecasting track of TCs began in
1972 [3] by using a computer oriented half persistence and half climatology technique. There is a study [3]
related to forecasting movement of TCs by adopting a primitive equation barotropic model. Some authors have
used multi-level primitive equation models with parameterization of physical processes [4, 5]. Quasi-Lagrangian
Model (QLM) has also been implemented in IMD for operational track forecast up to 72 h in the year 2000.
QLM [6] have been evaluated in 2003 and its performance is found to be even better. The effect of different
initial condition on the track and intensity of tropical cyclone are done using MM5 and WRF models [7]. The
simulation of track and landfall of tropical cyclones over the Bay of Bengal is done [8,9], Prediction of severe
tropical cyclones over the Bay of Bengal during 2007–2010 using high-resolution mesoscale model is also done
[10].
In this study, the high resolution Advanced Research WRF (ARW) meso-scale model adopted from NCAR
is used to simulate the track and intensity of the tropical cyclone Nargis, Thane and Mahasen. The objective of
the present study is to evaluate the performance of the model towards simulation of track and intensity of
tropical cyclone.
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2. MODEL DESCRIPTION AND INITIAL CONDITIONS
The cumulus convection used in this case is modified Kain-Fritisch scheme [912]. The cloud microphysics
scheme is WRF Single-Moment (WSM) 3-class simple ice scheme, which is a simple efficient scheme with ice
and snow processes suitable for mesoscale grid sizes [10, 11 13,14]. It replaces NCEP 3 scheme. The long-wave
radiation parameterization is the Rapid Radiative Transfer Model (RRTM) scheme, which is an accurate scheme
using look-up tables for efficiency accounts for multiple bands, trace gases, and microphysics species [12,15].
The short-wave radiation scheme is as per the Dudhia scheme, which allows simple downward integration for
efficient cloud and clear-sky absorption and scattering [13,16]. The Planetary Boundary Layer (PBL)
parameterization is the Yonsei University Scheme (YSU) [14,17], which is the next generation MRF–PBL. An
overview of the model used in this study is provided in Table 1.
3. DESCRIPTION OF THE SYSTEM
Very Severe Cyclonic Strom Nargis
The system ‘Nargis’ initially appeared as a low pressure area over southeast Bay of Bengal on 26 April and
concentrated into a depression at 0300UTC of 27 April. The system slightly moved northwestwards and
intensified into a depression and then into a cyclone at 00UTC of 28 April over southwest and adjoining
southeast and west central Bay of Bengal about 550 km east of Chennai. The system remained practically
stationary for some time and further intensified into an SCS at 09UTC of 28 April and into a VSCS at 0300UTC
of 29 April over west central and adjoining southwest and southeast Bay of Bengal. The system moved slightly
to the north and then eastwards for a period of about 30 h from 0600UTC of 1 May till 1500UTC of May
towards the Myanmar coast and crossed the coast of Myanmar between 1730 and 1930 h IST on 2 May 2008 as
a ‘VSCS’ (figure 1). Even after the landfall the system was maintaining its intensity as a VSCS for a period of
about 12 h. The VSCS ‘Nargis’ devastated large parts of the low-lying delta region of the Irrawaddy River.
MSWs exceeded 190 kmph as the storm ripped through the Myanmar’s biggest city Yangon (estimated
population 6 million) for over more than ten hours. Homes were flattened, more sturdy structures damaged, trees
uprooted and power lines downed. In rural parts of the country up to 95% of all homes were destroyed. In the
history of Myanmar it had never faced such a disastrous weather system in past 40 years.
Cyclone Thane
and into a depression in the same evening over the north Interior Tamil Nadu. It weakened further and lay as a
A depression formed over southeast Bay of Bengal at 0900 UTC of 10th
May 2013 near latitude 5.0°N and
longitude 92.0°E. It moved northwestwards and intensified into a deep depression in the evening of the same
day. Continuing its northwestward movement, it further intensified into a cyclonic storm, Mahasen in the
morning of 11th
May 2013. Under the influence of the anticyclonic circulation lying to the east, the cyclonic
storm changed its direction of movement initially from northwesterly to northerly and then to north-
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First the NCAR version 3.1 of Advanced Research WRF (ARW) model has been used. Detail description of the
model is documented in [11]. For the diagnostic study the GFS data at 1◦×1◦ grid is used from 00 UTC of
December 26 to 00 UTC of December 31, 2011.
in the early morning of 26th
December, 2011 and into a cyclonic storm ‘THANE’ in the same midnight. It then
moved west-northwestwards and intensified into a severe cyclonic storm in the afternoon and into a very severe
A depression formed over southeast Bay of Bengal in the evening of 25th
December, 2011 and lay centred about
1000 km southeast of Chennai. It gradually moved north-northwestwards and intensified into a deep depression
December, 2011 with a MSW speed of 120-140 kmph. After landfall, the system rapidly weakened into a severe
cyclonic storm over north coastal Tamil Nadu at 0830 hrs IST of 30th
and into a deep depression around noon
cyclonic storm in the evening of 28th
December, 2011. It then moved west-southwestwards and crossed north
Tamil Nadu & Puducherry coast between Cuddalore and Puducherry within 0630 and 0730 hrs IST of 30th
well marked low pressure area over north Kerala and neighbourhood in early morning of 31st December, 2011.
Cyclone Mahasen
northeasterly on 13th
and 14th May respectively. On 15
th May, it further came under the influence of the mid-
latitude westerly trough running roughly along 77°E, which further helped in enhancing the north-northeastward
speed of the cyclonic storm. The cyclonic storm crossed Bangladesh coast near lat.22.8°N and long. 91.4°E,
about 30 km south of Feni around 0800 UTC of 16th
May 2013 with a sustained maximum surface wind speed
of about 85-95 kmph. After the landfall, it continued to move north-northeastwards and weakened gradually due
to interaction with land surface. It weakened into a deep depression over Mizoram in the evening and into a
depression over Manipur around mid-night of 16th
. It further weakened into a well marked low pressure area
over Nagaland in the early morning and moved away towards Myanmar as a low pressure area in the morning of
17th
May.
Table 1: Domain design of the model
Horizontal grid distance 9 km
Integration time step 30 s
Map projection Mercator
Horizontal grid system Arakawa-C grid
Vertical co-ordinate Sigma co-ordinates 28 σ levels
Time integration scheme Third-order Runge–Kutta scheme
Spatial Differencing scheme Second to Sixth order schemes
Radiation parameterizations RRTM, Dudhia scheme
Surface layer parameterizations Monin–Obukhov scheme, thermal diffusion scheme
Cumulus parameterization Kain- Fritisch schemes
PBL parameterization YSU scheme
Microphysics WSM 3 simple ice scheme
Land surface Unified Noah Land surface Model
4. RESULTS AND DISCUSSION
The results obtained from several numerical experiments using WRF model are used to predict the intensity and
track of the tropical cyclones Nargis, Thane and Mahasen those form in the Bay of Bengal. The model was run
for 96 hours for intensity prediction and 96 and 72 hours for track prediction. Model output of each cyclone has
been produced at three hours interval and processed using Grid Analysis and Display System (GrADS). Model
simulated Minimum Sea Level Pressure (MSLP), Maximum Sustained Wind (MSW) and tracks are compared
with those reported by India Meteorological Department (IMD) and discussed in the following sections.
4.1. MSLP and MSW of the Tropical Cyclone Events
MSLP and MSW of a TC are of great importance as they help to measure the intensity of a TC. Since TCs
develop over vast oceanic areas, where observations are sparse or not available, it is of great difficulty to make
any validation of model simulated MSLP and MSW with real observable data from sea before the landfall. But
now meteorologists are able to estimate MSLP and MSW using interpretations of satellite products. To obtain
model simulated intensity (MSLP and MSW); model is run for 96 hours for the cyclone Nargis, Thane and
Mahasen. These run are based on the initial fields of 00 UTC on 29 April 2008, 00 UTC of 27 December 2011,
00 UTC of 13 May 2013 for the Cyclone Nargis, Thane and Mahasen respectively. Time variation of model
simulated and observed MSLP and MSW of TC Nargis, Thane and Mahasen are presented as in Figure 1. The
lowest MSLP and highest MSW with their obtaining time are tabulated in the Table 2.
4.1.1. MSLP and MSW of the Tropical Cyclone Nargis
It appears from the Figure1 that model simulated MSLP gradually drops (having little bit oscillation) with time
and attains peak intensity with minimum pressure 956 hPa at 00 UTC on 02 May 2008 and thereafter MSLP
increases gradually. Finally just before the landfall the MSLP is 960 hPa at 03 UTC of 02 May 2008. On the
other hand, the observed MSLP 962 hPa is obtained at 06 UTC of 02 May and remain same up to 12 UTC of 02
May 2008 and thereafter MSLP increases gradually. Landfall of the system occurs at 12 UTC of 02 May with
observed value of MSLP 962 hPa. The variation of model simulated MSLP compare to that of observed with
time shows that the model simulates realistic temporal variation of MSLP but simulated value is higher than
observed values up to 18 UTC of 30 April and then becomes lower up to 03 UTC of May 02 and then becomes
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Dynamics Nonhydrostatic
Model domain 4.590–26.56
0N, 76.35
0–97.64
0E
higher up to 00 UTC of May 03. Again, the simulated highest MSW is 44 m/s and obtained at 00 UTC of 02
May 2008 where as that for observed is 46 m/s and obtained at 06 UTC of 02 May 2008 and retains this value
up to 15 UTC on 02 May 2008. These lowest values MSLP and highest MSW with their obtaining time are
tabulated in Table 2. From the Figure 1 and Table 2, it is clear that the simulated intensity of cyclone Nargis
intensify earlier than the observation.
4.1.2. MSLP and MSW of the Tropical Cyclone Thane
Figure 1 shows the comparative evolution of observed MSLP and simulated MSLP of TC Thane. It appears
from the Figures 1 that model simulated and observed MSLP gradually drops with time and attains peak
intensity just before the landfall and thereafter MSLP increases. The Model simulated MSLP of 973 hPa is
obtained at 12 UTC of 29 December whereas the observed MSLP 969 hPa is obtained at 21 UTC of 29
December 2011. The model simulated MSLP at the centre of the cyclone is obtained before 09 hours from the
observed MSLP. The variation of model simulated MSLP compared to that of observed with time shows that
both the models simulated realistic temporal variation of MSLP. The simulated highest MSW is 36 m/s and
obtained at 15 UTC of 29 December 2011 where as that for observed is 40 m/s and obtained at 03 UTC of 29
December 2011 retains this value up to 00 UTC on 30 December 2011. These lowest values MSLP and highest
MSW with their obtaining time are tabulated in Table 2. The simulated MSLP of cyclone Thane intensifies
earlier than the observation but the simulated MSW of cyclone Thane intensifies later than the observation.
4.1.3. MSLP and MSW of the Tropical Cyclone Mahasen
Figure 1 shows the comparative evolution of observed MSLP and simulated MSLP of TC Mahasen. It appears
from the Figures 1 that model simulated and observed MSLP gradually drops with time and attains peak
intensity just before the landfall and thereafter MSLP increases. The Model simulated MSLP of 952 hPa is
obtained at 15 UTC of 14 May 2013 and attain this value up to 21 UTC of 14 May 2013 whereas the observed
MSLP 990 hPa is obtained at 06 UTC of 15 May 2013 and attain this value up to 06 UTC of 16 May 2013. The
model simulated MSLP at the centre of the cyclone is obtained before 15 hours from the observed MSLP. The
variation of model simulated MSLP compared to that of observed with time shows a realistic temporal variation
of MSLP. Simulated MSLP are lower than those of observed. The simulated highest MSW is 49 m/s and
obtained at 15 UTC of 14 May 2013 where as that for observed is 23 m/s and obtained at 06 UTC of 15 May
2013 and retains this value up to 06 UTC on 16 May 2013. These lowest values MSLP and highest MSW with
their obtaining time are tabulated in Table 2. The simulated intensity of cyclone Mahasen intensifies earlier than
the observation.
The Absolute Error (AE) and Root Mean Square Error (RMSE) for the MSLP and MSW are tabulated in Table
3. Minimum errors are found for cyclone Thane.
4.2. Track Pattern of Tropical cyclones
Model simulated track of TC Nargis, Thane and Mahasen along with observed track are plotted in the Figures 2.
4.2.1. Track Pattern of Tropical cyclone Nargis
The track forecasts of TC Nargis for 96 and 72 hrs are based on the initial fields of 00 UTC on 29 April and 00
UTC on 30 April 2008 respectively. It is seen from Figure 2 that the model simulated track for 96 and 72 hours
are parallel to observed track but it is deviated south and north side of the observed track. Figure shows that
model is able to generate northwest, north and northeast movement of the system very well. It reveals that track
obtained from 72 hrs simulation are more close to the India Meteorological Department (IMD) best track
compared to the track obtained from 96 hrs simulation. However, there are some errors in the landfall with
respect to position and time landfall tabulated in Table 4. Simulated landfall time are 0450 UTC of 02 May and
0750 UTC of 02 May 2008 using 96 and 72 hrs forecast where as observed landfall time is 1200 UTC of 02
May 2008. So, 96 and 72 hours forecast shows landfall time 7 and 2 hours earlier than the observed landfall
time. Again, Simulated landfall positions are (18.450 N, 94.30
0 E) and (16.35
0 N, 94.31
0 E) using 96 and 72 hrs
forecast where as observed landfall position is (16.000 N, 94.30
0 E). So, 96 and 72 hours forecast shows landfall
position 274 and 43 km north of the observed landfall position. Again, RMSE and AE for 96 and 72 hours
forecast are 278 and 133 km respectively (Table 5).
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4.2.2. Track Pattern of Tropical cyclone Thane
Model simulated track of TC Thane along with observed track are plotted in the Figures 2. The track forecasts
of TC Thane for 96 and 72 hrs are based on the initial fields of 00 UTC of 27 December and 00 UTC of 28
December 2011 respectively. It is seen from Figure 2 that the simulated track obtained by running the model for
96 and 72 hours is parallel to observed track. 96 hours simulated track is mainly north side of observed track but
72 hours forecast track is overlapping north and south side of observed track. Finally 72 hours forecast run is
parallel and close to observed one.
However, there are some errors in the landfall with respect to position and time landfall tabulated in Table 4.
Simulated landfall time are 0915 UTC of 30 December and 2300 UTC of 29 December 2011 using 96 and 72
hrs forecast where as observed landfall time is 0100 UTC of 30 December 2011. So, 96 and 72 hours forecast
shows landfall time 8.75 and 2 hours earlier than the observed landfall time. Again, Simulated landfall positions
are (14.400 N, 80.20
0 E) and (11.89
0 N, 79.99
0 E) using 96 and 72 hrs forecast where as observed landfall
position is (11.600 N, 79.77
0 E). So, 96 and 72 hours forecast shows landfall position 314 and 41 km north of
the observed landfall position. Again, RMSE and AE for 96 and 72 hours forecast are 241 and 47 km
respectively (Table 5).
4.2.3. Track Pattern of Tropical cyclone Mahasen
Models simulated track of TC Mahasen along with observed track are plotted in the Figures 2. The track
forecasts of TC Mahasen for 96 and 72 hrs are based on the initial fields of 00 UTC of 13 May and 14 May
2013 respectively. Both of tracks are parallel to observed one and deviated east side of the observed track.
However, there are some errors in the landfall with respect to position and time landfall tabulated in Table 4.
Simulated landfall time are 1900 UTC of 16 May and 1930 UTC of 16 May 2013 using 96 and 72 hrs forecast
where as observed landfall time is 0715 UTC of 16 May 2013. So, 96 and 72 hours forecast shows landfall time
11.75 and 12.25 hours later than the observed landfall time. Again, Simulated landfall positions are (22.520 N,
91.680 E) and (22.40
0 N, 91.78
0 E) using 96 and 72 hrs forecast where as observed landfall position is (22.80
0 N,
91.350 E). So, 96 and 72 hours forecast shows landfall position 48 and 64 km east of the observed landfall
position. Again, RMSE and AE for 96 and 72 hours forecast are 168 and 229 km respectively (Table 5).
Again average landfall position are 212 and 49 km for 96 and 72 hours forecast respectively and average
landfall time are 8.83 and 6.08 hours for 96 and 72 hours forecast respectively (Table 4). Again, mean RMSE
and AE for 96 and 72 hours forecast are 229 and 136 km respectively (Table 5). Track obtained from 72 hours
forecast shows better performance Thane 96 hours forecast track.
Table 2: Lowest MSLP and highest MSW
Cyclone Lowest MSLP Highest MSW
Simulated observed simulated observed
Value
(hPa)
Date/time
(DD/UTC)
Value
(hPa)
Date/time
(DD/UTC)
Value
(m/s)
Date/time
(DD/UTC)
Value
(m/s)
Date/time
(DD/UTC)
Nargis 956 02/00 962 02/06 44 02/00 46 02/06
Thane 973 29/12 969 29/21 36 29/15 40 29/03
Mahasen 952 14/15 990 15/06 49 14/15 23 15/06
Table 3: RMSE and AE of intensity of selected TCs
Cyclone Error for MSLP Error for MSW
Absolute Error
(hPa)
RMSE
(hPa)
Absolute Error
(m/s)
RMSE
m/s)
Nargis 13.58 15.13 10.30 12.67
Thane 4.17 5.39 5.43 6.79
Mahasen 30.19 32.12 17.53 18.29
Average 15.98 17.55 11.09 12.58
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Table 4: Landfall point and time error of TCs
Cyclone obs/
models
Forecast
Hours
Initial
condition
Date/Tim
e (UTC)
Landfall
time
Date/Time
(UTC)
Landfall position Error
Lat)N LonE Distance
(km)
Time
(hours)
Nargis Obs 02/1200 16.00 94.30
Model 96 29/0000 02/0450 18.45 94.30 274 n 7E
72 30/0000 02/0750 16.35 94.31 43 n 4E
Thane Obs 30/0100 11.60 79.77
Model 96 27/0000 30/0915 14.40 80.20 314 n 8.75 D
72 28/0000 29/2300 11.89 79.99 41 n 2 E
Mahasen Obs 16/0715 22.80 91.35
Model 96 05/1300 16/1900 22.52 91,68 48 e 11.75D
72 05/1400 16/1930 22.40 91.76 64 e 12.25D
Mean 96 212 8.83
72 49 6.08
e indicates deviation toward eastern direction, w indicates deviation west of the actual landfall
position, n indicates deviation toward northern direction, D indicates forecast landfall time is
delayed compared to actual time, and E indicates forecast landfall time is earlier to actual
landfall time.
Table 5: RMSE and AE of track of TC
Cyclone Forecast Hours RMSE of track
(km)
Average Error of
track (km)
Nargis 96 278 257
72 133 127
Thane 96 241 202
72 47 42
Mahasen 96 168 132
72 229 171
Mean 96 229 197
72 136 113
5. CONCLUSION
In this study, WRF ARW model was used to predict the intensity and track of the tropical cyclones. From the
simulations the following results come forward:
1. Simulated SLPs of TC are comparable with those obtained from IMD except for cyclone Mahasen but
time variation patterns are similar in all cases.
2. Simulated 10 m MSWs of TC are comparable with those obtained from IMD except for cyclone
Mahasen but time variation patterns are similar in all cases.
3. The track from 72 hours simulation track is better than that of 96 hours simulation except for cyclone
Mahasen.
4. The landfall position error and time error for 72 hours simulation is very little than that of 96 hours
simulation except for cyclone Mahasen.
Hence it may be concluded that the WRF model can be used to forecast the tropical cyclone of the Bay of
Bengal.
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Acknowledgements: The authors gratefully acknowledge the NCEP/NCAR for their reanalysis data sets used
for the present study. One of the authors Md. Abdullah Elias Akhter is thankful to the Ministry of Science and
Information & Communication Technology, Bangladesh for the sanction of fellowship.
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Figure 1: Model simulated and observed MSLP and MSW of TC Nargis, Thane and Mahasen
TC Nargis TC Thane TC Mahasen
Figure 2: Model simulated and observed tracks of TC Nargis, Thane and Mahasen
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