Thermal Characteristics and Dynamics of Tropical Cyclone over Western North Pacific Ocean: A Case Study of Typhoon Songda (Chedeng) 2011
THERMAL CHARACTERISTICS AND DYNAMICS OF TROPICAL
CYCLONE OVER WESTERN NORTH PACIFIC OCEAN:
A CASE STUDY OF TYPHOON SONGDA (CHEDENG) 2011
YOPI ILHAMSYAH
GRADUATE SCHOOL
BOGOR AGRICULTURAL UNIVERSITY
BOGOR
2013
PERNYATAAN MENGENAI THESIS DAN
SUMBER INFORMASI SERTA PELIMPAHAN HAK CIPTA*
Dengan ini saya menyatakan bahwa Thesis berjudul Thermal
Characteristics and Dynamics of Tropical Cyclone over Western North Pacific
Ocean: A Case Study of Typhoon Songda (Chedeng) 2011 adalah benar karya
saya dengan arahan dari komisi pembimbing dan belum diajukan dalam bentuk
apa pun kepada perguruan tinggi mana pun. Sumber informasi yang berasal atau
dikutip dari karya yang diterbitkan maupun tidak diterbitkan dari penulis lain telah
disebutkan dalam teks dan dicantumkan dalam Daftar Pustaka di bagian akhir
Thesis ini.
Dengan ini saya melimpahkan hak cipta dari karya tulis saya kepada Institut
Pertanian Bogor.
Bogor, Juli 2013
Yopi Ilhamsyah
NRP G251110021
RINGKASAN
YOPI ILHAMSYAH. Karakteristik Termal dan Dinamika Siklon Tropis di
Samudera Pasifik Utara bagian Barat: Studi Kasus untuk Topan Songda
(Chedeng) 2011. Dibimbing oleh AHMAD BEY dan EDVIN ALDRIAN.
Siklon Tropis (ST) di Samudera Pasifik Utara bagian Barat sering terjadi
pada 10˚LU hingga 26˚LU dan 121˚BT hingga 170˚BT. Kelembaban nisbi pada
ketinggian 850-700 hPa berpengaruh untuk menghasilkan badai yang sangat
intens. Sementara itu, geser angin lemah antara ketinggian 850-200 hPa
merupakan salah satu faktor dinamika yang berpengaruh terhadap pembentukan
ST. Ketinggian 850-200 dipilih untuk meminimalisir pengaruh termodinamika
pada lapisan troposfer rendah. Topan Songda (Chedeng di Filipina) atau TSC
berlangsung dari tanggal 18 hingga 30 Mei 2011 dan menguat menjadi Super
Topan antara tanggal 24 - 27 Mei 2011. Lintasan melengkung yang panjang dan
pembentukan seluruh tahap dari waktu hidup ST, TSC menjadi kasus ideal untuk
ST. Tujuan penelitian ini adalah untuk menyelidiki pengaruh karakteristik termal
dan dinamika serta perubahannya terhadap intensitas ST.
Penelitian ini dilakukan dengan menggunakan model numerik Advanced
Research of Weather Research and Forecasting model (WRF ARW) versi 3.3.
Dua domain digunakan pada model. Domain pertama berada pada 02˚LU hingga
40˚LU dan 118˚BT hingga 149˚BT dengan resolusi spasial
) 33.1 km.
Domain kedua berada pada 09˚LU hingga 27˚LU and 119˚BT hingga 132˚BT
11 km. Langkah waktu ( ) dari model ini adalah 120 detik.
dengan
Model ini didukung oleh parameterisasi fisika yaitu: skema Yonsei University
(YSU) pada lapisan perbatas, skema Kain-Fritsch (KF) pada kumulus, dan skema
WRF Single-Moment 3-class pada mikrofisika. WRF ARW dengan tujuh skenario
berbeda dilakukan dalam penelitian, yaitu dengan menjalankan model WRF
keluaran standar beserta dengan data inisialnya, dengan mengatur penurunan dan
peningkatan 10 % hingga 20 % dari data inisial geser angin pada ketinggian 850200 hPa dan dengan mengatur penurunan 10 % hingga 20 % dari data inisial
kelembaban nisbi pada ketinggian 850-700 hPa.
Hasil penelitian menunjukkan bahwa korelasi negatif antara geser angin dan
intensitas ditemukan pada skenario geser angin. Geser angin sebesar 10 ms-1 yang
berdampak terhadap penguatan intensitas angin di awal periode pembentukan
Topan ditemukan pada skenario geser angin. Pengaruh perubahan geser angin
terhadap intensitas angin secara statistik berbeda nyata pada skenario geser angin
20 %. Selama tahap matang, intensitas angin lemah terjadi ketika geser angin
meningkat sebagaimana ditemukan pada WRF keluaran standar dan skenario
penurunan geser angin 20 %. Kondisi berbeda ditemukan pada skenario
peningkatan geser angin 20 % di mana geser angin cenderung lemah dan
berdampak terhadap peningkatan intensitas angin pada tahap ini. Sementara itu,
pengurangan suplai kelembaban pada ketinggian 850-700 hPa yang dihasilkan
dari skenario penurunan kelembaban nisbi sebesar 20 % berperan penting dalam
melemahkan intensitas angin sehingga berpengaruh terhadap penurunan energi
mekanik dari proses siklus sebesar 300 J kg-1.
Kata kunci: geser angin, intensitas angin, kelembaban nisbi, WRF ARW
SUMMARY
YOPI ILHAMSYAH. Thermal Characteristics and Dynamics of Tropical Cyclone
over Western North Pacific Ocean: A Case Study of Typhoon Songda (Chedeng)
2011. Under supervision of AHMAD BEY and EDVIN ALDRIAN.
The frequent occasion of Tropical Cyclone (TC) over Western North Pacific
(WNP) Ocean lies from 10˚N to 26˚N and 121˚E to 170˚E. Sources of TC
development come from warm ocean temperature where latent heat is released
during condensation processes and subsequently concentrated in the boundary
layer. Relative humidity at 850-700 hPa is responsible to produce the most intense
storm. Meanwhile, weak vertical wind shear between 850-200 hPa is one of the
dynamical factors that lead to the development of TC. Pressure level of 850-200
hPa is chosen to minimize the thermodynamic effect in the lower troposphere.
Typhoon Songda (Chedeng in the Philippines) or TSC lasted from May 18th to
30th, 2011 and strengthened into powerful Super Typhoon stage between May 24th
and 27th. Long curving track and the exhibition of all sequences of TC life cycle,
TSC is then considered as an ideal case of TC. The objective of the study with
case of TSC is to investigate the role of thermal characteristics and dynamics on
TC intensity.
The research is carried out by using Advanced Research of Weather
Research and Forecasting model (WRF ARW model) version 3.3. Two domains
are employed in the model. The first domain situate from 02˚N to 40˚N and 118˚E
to 149˚E and cover spatial resolution (
) of 33.1 km. The second domain
of 11 km. Timestep
situate from 09˚N to 27˚N and 119˚E to 132˚E with
of the model ( ) is 120 seconds. The model is supported by the following
physical parameterization, i.e., Yonsei University Scheme (YSU) in the boundary
layer, Kain-Fritsch scheme (KF) in the cumulus, and WRF Single-Moment 3-class
scheme in the microphysics. Initial meteorological condition prior to the
formation of the cyclone is generated using WRF ARW standard-release model.
Sensitivity of the model output is obtained from a selected single-parameter
change scenarios, namely, 10 % to 20 % decrease and increase of wind shear
initial data at 850-200 hPa, and by 10 % to 20 % decrease of relative humidity
initial data at 850-700 hPa.
The result showed that the negative correlations between wind shear and
intensity are found in wind shear scenarios. Wind shears of 10 ms-1 which lead to
strengthening of the wind intensity in the early period of Typhoon development
are found in wind shear scenarios. The effect of wind shear changes on wind
intensity is statistically significant in the 20 % wind shear scenarios. During
mature stage, weak wind intensity occurred when wind shear increase as given in
the WRF standard-release and the 20 % decreasing scenario. Different situation is
found in the 20 % increasing scenario where wind shear tend to weak and lead to
strong wind intensity at this stage. Meanwhile, the reduction of moisture supply at
850-700 hPa resulting from 20 % decreasing relative humidity play a major role in
the weakening of wind intensity and reduces mechanical energy of the cycle
process as much as 300 J kg-1.
Keywords: relative humidity, wind intensity, wind shear, WRF ARW
© Hak Cipta Milik IPB, Tahun 2013
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dalam bentuk apa pun tanpa izin IPB
THERMAL CHARACTERISTICS AND DYNAMICS OF TROPICAL
CYCLONE OVER WESTERN NORTH PACIFIC OCEAN:
A CASE STUDY OF TYPHOON SONGDA (CHEDENG) 2011
YOPI ILHAMSYAH
Thesis
as the requirements for the degree of
Magister Sains
in
Applied Climatology Study Program
GRADUATE SCHOOL
BOGOR AGRICULTURAL UNIVERSITY
BOGOR
2013
Penguji pada Ujian Thesis: Dr. Rahmat Hidayat, S.Si, M.Si
Thesis title : Thermal Characteristics and Dynamics of Tropical Cyclone over
Western North Pacific Ocean: A Case Study of Typhoon Songda
(Chedeng) 2011
Name
: Yopi Ilhamsyah
Reg.number : G251110021
Supervisor Committee
Prof. Dr. Ir. Ahmad Bey
Supervisor
Dr. Edvin Aldrian, M.Sc, APU
Co. Supervisor
Head of Study Program
Applied Climatology
Dean of Graduate School
Dr. Ir. Tania June, M.Sc
Dr. Ir. Dahrul Syah, MSc.Agr
Date of Examination: 07 June 2013
Date of Passed:
PREFACE
The author say “Alhamdulillah” gratitude to Allah for making the Thesis
entitled "Thermal Characteristics and Dynamics of Tropical Cyclone over
Western North Pacific Ccean: A Case Study of Typhoon Songda (Chedeng) 2011"
can be possibly presented. Tropical Cyclone is one of the deadliest natural
disasters. Even though various studies have been done to investigate Tropical
Cyclone, it, however, still remains a mystery. Tropical Cyclone (or Typhoon in
the Pacific) is most common over Western North Pacific Ocean. Every year,
during Summer-Autumn, typhoon frequencies increase in number and their
movement lie over vast tropical ocean, from low to middle even high latitude
ocean basin in the Northern Hemisphere. Typhoon Songda (Chedeng), formed in
the early period of intensification, was a massive Super Typhoon. Long curving
track and apparent storm transformation from early growth until reaching mature
and decaying stage initiate the present research. Therefore, the understanding of
thermal characteristics and dynamics of a Typhoon are essential to study tropical
disturbances over Western North Pacific Ocean.
The thesis is divided into five chapters. Chapter one presents basic ideas
behind the research containing background, statement of the problem, and
objective of the research. Chapter two provides review quotations from various
literatures to support the research. Chapter three deals with methodology divided
into subchapters, including location of the research, model performance, initial
condition, and experimental design of the research. Chapter four focusses on
results and discussion and last chapter presents the conclusion of the research and
suggestion for future research.
The author expresses gratitude to supervisors Prof. Dr. Ahmad Bey and Dr.
Edvin Aldrian, M.Sc for providing books, journals, constructive comments, and
suggestions to improve the thesis. Appreciation is given to the head of
Department of Geophysics and Meteorology IPB, Applied Climatology study
program IPB, teaching and administrative staffs. Special gratitude is given to my
father, my (late) mother, my wife and the Ilhamsyah family for moral support.
Thankful is also addressed to Mr. A. Fachri Radjab for giving an opportunity to
carry out the internship at TCWC BMKG and Mr. Zainal Abidin for kind
assistance during the internship. Another grateful is given to friends of KLI 48
and DIKTI under BPPS scholarship for providing financial assistance during my
master program. The author realizes the thesis is still far from perfect. Therefore,
useful comments and notes are greatly appreciated, and hopefully, the thesis can
benefit the readers.
Dramaga, June 2013
Yopi Ilhamsyah
TABLE OF CONTENTS
LIST OF TABLES
i
LIST OF FIGURES
i
LIST OF APPENDIXES
ii
1 BACKGROUND
Background
Statement of the problem
Extent of the problem
Objective
1
1
2
2
3
2 LITERATURE REVIEW
3
3 METHODOLOGY
Location of the research
Tool and Material
Model performance
Physical parameterization
The initial condition
The experimental design
Typhoon wind intensity and stages
Radial and azimuthal velocity
Entropy and mechanical energy
5
5
6
6
7
8
8
9
10
10
4 RESULTS AND DISCUSSION
10
The evaluation of WRFSRL
11
The track and stages
11
TSC intensity
13
The cloud shape and wind structures
15
The Carnot cycle
18
The influences of thermal characteristics and dynamics on TSC intensity 20
The influences of thermal characteristics and dynamics changes on TSC
intensity
23
Wind shear scenarios in TSC life cycle
23
Relative humidity Scenarios in TSC life cycle
27
The impacts of intensity on status and tracks of TSC
28
The correlation of wind shear on TSC intensity and the influences of
scenarios on TSC intensity
30
Wind shear scenarios in the surface and vertical level
31
Relative humidity scenarios in the surface and vertical level
32
Entropy and mechanical energy
33
5 CONCLUSION AND SUGGESTION
Conclusion
34
34
Suggestion
34
REFERENCES
35
APPENDIX
39
BIOGRAPHY
60
LIST OF TABLES
1 Physical parameterization of WRFSRL
2 The adjustment scenarios of the research
3 Classification of Typhoon intensity, stages, and processes
8
9
10
LIST OF FIGURES
1 The occurrences of worldwide TC for period 1998–2007. Colors with
different symbols as shown in the legend inform TC stages on the
Saffir–Simpson scale for each individual pathway
2 NH monthly diagnostics of 850-200 hPa vertical wind shear (19582002) in ms-1 and SST (1977-2006) in ˚C. The locations of TC genesis
are indicated by oval marks
3 Geographical location and domains of WRFSRL over WNP Ocean.
D01 and D02 are the first and second domain, respectively
4 Tracks of TSC life cycle from May 20th to 30th, (a) WRFSRL (blue
line) and its comparison to JTWC (red line), and JMA (green line) and
(b) stages of WRFSRL track
5 Comparison of time-series of maximum wind speeds (ms-1) of TSC
from May 20th to 30th for WRFSRL (blue line), JTWC (red line), and
JMA (green line)
6 Comparison of time-series of SLP (hPa) of TSC from May 20th to 30th
for WRFSRL (blue line), JTWC (red line), and JMA (green line)
7 Swirling shape of TSC clouds at Super Typhoon stage on May 27th at
0000 UTC, (a) WRFSRL and (b) satellite imagery taken from MTSAT2 IR1 JMA (source: EEI-Lab. Kochi University)
8 Three-dimensional wind flow of TSC at Super Typhoon stage on May
27th at 0000 UTC. Bar chart in the left indicates the magnitudes of wind
speeds in ms-1 (not the terrain profile in the lowest background)
9 West-East vertical structures of TSC at Super Typhoon stage on May
27th at 0000 UTC, (a) azimuthal velocity (ms-1) and (b) radial velocity
(ms-1)
10 West-East vertical structures of TSC at Super Typhoon stage at 0000
UTC on May 27th, (a) maximum wind speeds (shaded and barb) in ms-1
and (b) vertical velocity in Pa s-1
11 West-East vertical structures of (a) (K) and (b) entropy (J kg-1K-1)
and description of Carnot cycle of TSC at on May 27th at 0000 UTC
12 Wind Shear at 850 – 200 hPa in ms-1 (focus area is given on the black
box) during (a) Tropical Depression on May 19th, (b) Super Typhoon
on May 27th, and (c) Extratropical Storm on May 30th at 0000 UTC
13 Time-series of (a) maximum wind speed (ms-1) of WRFSRL and (b)
scenario deviation from WRFSRL (ms-1) for WSHP10 (red line) and
WSHM10 (green line) from May 20th to 30th
14 Time-series of (a) SLP (hPa) of WRFSRL and (b) scenario deviation
from WRFSRL (hPa) for WSHP10 (red line) and WSHM10 (green
line) from May 20th to 30th
4
5
6
12
13
14
15
16
17
18
19
22
24
25
15 Time-series of (a) wind shear at 850-200 hPa (ms-1) of WRFSRL and
(b) scenario deviation from WRFSRL (ms-1) for WSHP10 (red line) and
WSHM10 (green line) from May 20th to 30th
16 Time-series of (a) maximum wind speed (ms-1) of WRFSRL and (b)
scenario deviation from WRFSRL (ms-1) for WSHP20 (red line) and
WSHM20 (green line) from May 20th to 30th
17 Time-series of (a) SLP (hPa) of WRFSRL and (b) scenario deviation
from WRFSRL (hPa) for WSHP20 (red line) and WSHM20 (green
line) from May 20th to 30th
18 Time-series of (a) wind shear at 850-200 hPa (ms-1) of WRFSRL and
(b) scenario deviation from WRFSRL (ms-1) for WSHP20 (red line)
and WSHM20 (green line) from May 20th to 30th
19 Time-series of (a) maximum wind speed (ms-1) of WRFSRL and (b)
scenario deviation from WRFSRL (ms-1) for RHM10 (red line) and
RHM20 (green line) from May 20th to 30th
20 Time-series of (a) SLP (hPa) of WRFSRL and (b) scenario deviation
from WRFSRL (hPa) for RHM10 (red line) and RHM20 (green line)
from May 20th to 30th
26
27
28
29
30
31
LIST OF APPENDIXES
1 Tracks of TSC lifecycle from May 20th to 30th, (a) WRFSRL, (b)
WSHM10, and (c) WSHP10
2 Tracks of TSC lifecycle from May 20th to 30th, (a) WRFSRL, (b)
WSHM20, and (c) WSHP20
3 Tracks of TSC lifecycle from May 20th to 30th, (a) WRFSRL, (b)
RHM10, and (c) RHM20
4 West-East vertical structures of TSC for temperature (˚C) in shaded and
relative humidity (%) in contour line (figures in the left side) and
temperature anomaly (˚C) in shaded (figures in the right side), (a and b)
at Tropical Storm on May 22nd (c and d) at Super Typhoon on May 27th,
(e and f) at Extratropical Storm on May 30th at 0000 UTC
5 Wind shear (ms-1) and maximum wind speeds (ms-1) on averages at all
stages of TSC life cycle resulting from different wind shear scenarios
WSH = wind shear and MWS = maximum wind speeds
6 Maximum wind speeds (ms-1) on averages at all stages of TSC life
cycle resulting from different relative humidity scenarios
7 Surface wind speeds at 10 m (shaded and vector) in ms-1 of TSC and
scenario deviation at Super Typhoon stage on May 27th at 0000 UTC,
(a) WRFSRL,(b) WSHM10, (c) WSHM20, (d) WSHP10, and (e)
WSHP20
8 West-East vertical structures of maximum wind speeds (shaded and
barb) in ms-1 of TSC and scenario deviation at Super Typhoon stage on
May 27th at 0000 UTC, (a) WRFSRL, (b) WSHM10, (c) WSHM20, (d)
WSHP10, and (e) WSHP20
39
40
41
42
44
45
46
47
9 Surface wind speeds at 10 m (shaded and vector) in ms-1 of TSC at
Super Typhoon stage on May 27th at 0000 UTC and scenario deviation
(a) WRFSRL, (b) RHM10, and (c) RHM20
10 West-East vertical structures of maximum wind speeds (shaded and
barb) in ms-1 of TSC and scenario deviation at Super Typhoon stage on
May 27th at 0000 UTC, (a) WRFSRL, (b) RHM10, and (c) RHM20
11 West-East vertical structures of entropy (J kg-1 K-1) as well as the
description of Carnot cycle of TSC and scenario deviation at Super
Typhoon stage on May 27th at 0000 UTC, (a) WRFSRL, (b) WSHM10,
(c) WSHM20, (d) WSHP10, and (e) WSHP20
12 West-East vertical structures of entropy (J kg-1 K-1) as well as the
description of Carnot cycle of TSC and scenario deviation at Super
Typhoon stage on May 27th at 0000 UTC, (a) WRFSRL, (b) RHM10,
and (c) RHM20
13 Sample script to adjust 10 % increasing scenario of NCEP FNL in the
initial condition in terms of zonal velocity at 850-200 hPa on May 27th
at 0000 UTC by using GRIB API
14 Sample script to calculate maximum wind speeds at Super Typhoon
stage
15 Sample script to calculate wind shear and west-east vertical section of
equivalent potential temperature for WRFSRL
16 Sample script to calculate west-east vertical section of maximum wind
speeds deviation from WRFSRL at Super Typhoon stage for RHM20
scenario
17 Script to calculate west-east vertical section of Entropy at Super
Typhoon stage for WRFSRL
18 Script to calculate mechanical energy of TSC at Super Typhoon stage
for WRFSRL
48
49
50
51
52
55
56
57
58
59
1
1 INTRODUCTION
Background
Western North Pacific (WNP) Ocean is one of the ocean basins that drive
the early genesis, the development until the dissipation of Tropical Cyclone (TC).
WNP is geographically situated in the Northern Hemisphere (NH) between 100˚180˚E and 0˚-60˚N and covers the region from the entire northern Equator of the
basin, including South China Sea to the west of International Date Line (IDL) in
the Central Pacific. WNP is well-known for the most dynamical basin to TC
occurrences (Neumann 1993; Lin et al. 2005, 2008). The frequent occasion of TC
lies from 10˚N to 26˚N and 121˚E to 170˚E (Holliday and Thompson 1979). TC
over this maritime region is likely to intensify during June-November with peak
activity occurred in the late NH summer on August (Emanuel 2003) and decline in
the late period of December. TC over WNP is locally called as Typhoon.
Principally, extensive periods of warm Sea Surface Temperature (SST) over
WNP play a major role in driving the frequencies of Typhoon events throughout
the year. Warm SST leads to higher rates of energy transfer from the ocean and
therefore increases Typhoon formation. Early study conducted by Gray (1968,
1975) showed SST exceeding 26.5°C was favorable environment for the genesis
of TC. Advanced studies by DeMaria et al. (2001), and Nolan et al. (2007a)
confirmed the previous results. The understanding of air-sea interaction is,
however, a principal explanation to describe the development of TC and its life
cycle. As a result of warm SST, the water vapor is released to the the air. The
rising air becomes saturate and condenses to form cloud where in this process;
large amounts of latent heat are released. The upward moist air are then
concentrated in the boundary layer which in turn drive to preserve the
intensification of TC over the ocean. Sufficient moisture in the middle
troposphere layer (850-700 hPa) is considered to have a major influence in
supplying heat to drive TC intensity. Schade and Emanuel (1999) found that
relative humidity at 850-700 hPa layer is responsible to produce the most intense
storm. Thus, the increase of humidity in the middle troposphere is one of thermal
characteristics that can be taken into account (Emanuel et al. 2004; Hill and
Lackmann 2009). The humid environment leads the themal energy to increase and
start circulating from warm to cold environment in a closed process, known as
Carnot cycle. Emanuel (1986) constructed a simple energy balance model to
explain the corresponding role of TC heat engine as a Carnot cycle. Moist entropy
from the lower level is the primary energy in the cycle. It allows air to flow
inward the boundary layer. At that moment, the air rises and releases heat at lower
temperature in the upper troposphere which further converts it from thermal to
mechanical energy.
On the other hand, weak vertical wind shear is one of the dynamical factors
that lead to the development of TC (Molinari et al. 2004; Latif et al. 2007). The
influence of vertical wind shear particularly between 850-200 hPa in controlling
TC intensity is based on climatological study by Gray (1968). Although he
considered 950 hPa as the lower limit of condensation level in the tropics, but,
pressure levels at 850-200 hPa was chosen to minimize thermodynamic effect in
2
the lower troposphere. It is then considered that changes of thermal characteristics
and dynamics of TC also influence the changes of TC intensity and mechanical
energy of the Carnot cycle.
The uses of simulation model had been conducted to investigate shear and
moisture changes and their implications on TC intensity, e.g., Wang and Holland
(1996), Frank and Ritchie (1999), and Wong and Chan (2004). However, their
study was based on full idealized physics simulation. In the present study, the
influences of shear and moisture changes on TC intensity was examined by using
three-dimensional numerical model by varying its initial condition.
Typhoon Songda (called Chedeng in the Philippines) (hereafter refer to
TSC) was the fourth named TC of the 2011 NH tropical season. TSC was the
most devastating storm that striked WNP Ocean for the period of 2011. It lasted
from May 18th to 30th, 2011 for two continuous weeks and strengthened to boost
peak activity of powerful Super Typhoon stages between May 24th and 27th. Long
curving track and the exhibition of all sequences of TC life cycle, TSC was then
considered as an ideal case of TC. Its development and intensification, however,
still remained questions. The fact that TSC is not a subject of exploration yet soon
motivates the present research. The purposes of the research with a case of TSC
presented herein will investigate the influences of thermal characteristics and
dynamics on TSC intensity and their changes effect on TSC intensity as well as
mechanical energy of the Carnot cycle. The primary points of emphasis are
relative humidity and vertical wind shear as mentioned earlier.
Statement of the problem
TC is powerful synoptic-scale systems that is formed over warm tropical
ocean. The development of TC is driven by some thermodynamics and dynamics
prerequisites, some of them are: vertical wind shear and middle troposphere
moisture. The development of TC that last for many days over the ocean can be
recognized by its intensity in terms of maximum wind speeds and sea-level
pressure (SLP). It is then considered that the changes on TC intensity are caused
by the changes of thermal characteristics and dynamics of TC. Thus, by choosing
a definite case of a strong development of TC, in this case TSC, the present study
will focus on research questions about how thermal characteristics and dynamics
and their changes play a major role on TSC intensity.
Extent of the problem
The extents of the problem of the present research are as follows:
TC discussed in this study refers to a case for TSC 2011.
Changes of thermal characteristics focus on middle troposphere layer of
relative humidity at 850-700 hPa while dynamic factor is the vertical wind
shear at 850 – 200 hPa.
Emphasis is on 6-hourly changes of TSC intensity from early genesis to
decaying stage.
The intensity is based on maximum wind speeds in Typhoon scale issued by
JTWC.
3
Objective
The purpose of the research is to investigate the influence of thermal
characteristics and dynamics, and their changes on TC intensity.
The research is expected to provide a better understanding on roles of
thermal characteristics and dynamics, and their changes effect on TC intensity
which is useful to assist operational weather forecaster to produce good shortrange forecasts of TC intensities.
2 LITERATURE REVIEW
The sequence of TC processes are often revealed by the following terms,
i.e., genesis, formation, development, and intensification. Genesis is defined as
transition phase from Tropical Disturbance to Tropical Depression (the formation
of a rotational motion with a few hundred km in scale), however, the term
development is often used instead of formation to describe the transition from
Tropical Depression to Tropical Storm with a maximum wind speeds of 17 ms-1.
Meanwhile, the term intensification is used to identify mature stage of a storm
from Tropical Storm to severe TC (also locally known as Typhoon in the Pacific
or Hurricane in the Atlantic) with a maximum wind speeds of 33 ms-1 (Frank
1987). Meanwhile, terms such as: large scale formation and core formation are
commonly used to distinguish the sequence processes of TC development
(McBride 1995).
Annually, there are about 80 to 90 TC occurrence over tropical oceans.
Based on climatological conditions associated with tropical cyclogenesis, most
common TC occasion form over tropical ocean under five following
characteristics (Gray 1968, 1975):
SST above 26.5˚C to 50 m depth of ocean mixed layer;
a deep layer of conditional instability;
increased values of cyclonic low level absolute vorticity;
organized deep convection in an area with large-scale ascent and high middle
level humidity, and
weak to moderate vertical wind shear.
Most TC are formed between 10˚ and 30˚ latitude in both hemispheres.
Large Coriolis force effect in the middle latitude initiates and keeps maintaining
TC rotation away from the Equator. In rare occasions, TC is found close to the
Equator, e.g., Tropical Storm Vamei in 2001 and Cyclone Agni in 2004, and of
particular interest among researchers (e.g., Chang et al. 2003). Figure 1 shows
worldwide distributions of TC. It is shown that the frequencies and the intensities
of TC over WNP ocean is highest since Intertropical Convergence Zone (ITCZ)
during high-sun season of NH (spring-summer) drives intensive solar heating and
makes TC over WNP become more frequent to occur (Zehnder et al. 1999).
TC frequently emerges over tropical oceans where warm water exist to at least 50
m depth. Dare and McBride (2011) analyzed SST data over period 1981-2008
extending from the Equator to 35˚N and 35˚S and concluded that more than 93 %
of TC development occurred at SST exceeding 26.5˚C and 98 % above 25.5˚C.
4
Therefore, SST value between 25.5˚C and 26.5˚C turned into preferences on TC
genesis. Sufficient warm is needed to maintain the energy supply of the storms.
Warm SST is conducive to strengthen TC. The energy is derived from substantial
amounts of water vapor due to evaporation. The water vapor then condenses and
releases latent heat in the atmospheric boundary layer. The heat latter fuel the
intensity of TC.
The relation between moist environment in the middle troposphere and TC
genesis had been the subjects of discussions among researchers. Sippel and Zhang
(2008) found that deep moisture is one of the initial characteristics for TC
formation. Bister and Emanuel (1997) carried out field experiment and found that
the increase of equivalent potential temperature in the middle troposphere
indicated the sufficient thermal characteristics on TC genesis. Raymond et al.
(1998) also found a correlation between relative humidity and the reduction of
downdraft. Later Raymond and Sessions (2007) gave an opinion that in fact their
field experiment showed that equivalent potential temperature had increased in the
middle level, the essential TC genesis was due to the stabilization in the low level.
However, it still needs to be further investigated whether relative humidy is useful
to diagnose the development of TC.
Weak vertical wind shear of less than 10-15 ms-1 over a deep layer 850-200
hPa, is another precondition factor on TC genesis. Climatologically, wind shear is
weaker in early NH summer. As tropical and subtropical ocean enter a warm
season, wind shear become stronger and winter Hadley cell strengthens through
local summer and into autumn as shown in figure 2. Oval marks in figure 2
indentify the locations of vertical wind shear and SST that conducive for TC
genesis as proved by Chan and Liu (2004). Vertical wind shear can have an effect
on the distribution and convection in TC. It can favorable in increasing the
convection and strengthening the upper-level outflow of the storm as well as the
structure and storm motion (Reasor et al. 2004).
Figure 1 The geographical distribution of TC worldwide TC over the period of
1998–2007. Colors with different symbols are stages of the Saffir–
Simpson scale for each individual pathway (Llyod and Vecchi 2011)
5
Figure 2 NH monthly diagnostics of (a) 850-200 hPa vertical wind shear (19582002) in ms-1 and (b) SST (1977-2006) in ˚C. The locations of TC
genesis are indicated by oval marks (Laing and Evans 2011)
On the other hand, environmental wind shear will cause the storm to
reorganize through induced convection on the downshear side of the storm that
will initially generate an axisymmetry. Finally the storm will either (i) reintensify
as a tropical system, having generated enough convection to retain its tropical
structure in the sheared environment; or (ii) become extratropical and reintensify
because of the wind shear; or (iii) decay (Laing and Evans, 2011). Vertical wind
shear has been shown to have an impact on different TC intensity (e.g.,
Corbosiero and Molinari 2002).
3 METHODOLOGY
Location of the research
The research was carried out in the laboratory of Meteorology and
Atmospheric Pollution, Department of Geophysics and Meteorology, Bogor
Agricultural University from September 2012 to April 2013. The domain of study
areas was between 03˚N - 43˚N and 117˚E - 150˚E for period of TSC life cycle
from May 18th to 30th, 2011 (see Fig. 3).
6
Figure 3 Geographical location and domains of WRFSRL over WNP Ocean. D01
and D02 are the first and second domain, respectively
Tool and Material
Model Performance
The research was carried out by performing Advanced Research of Weather
Research and Forecasting model (WRF ARW model) version 3.3. WRF ARW is a
non-hydrostatic three-dimensional numerical model with terrain-following in the
vertical-sigma coordinate. Basically, WRF ARW is governed by the following
fundamental equations of mass, heat, momentum, water, and gaseous and aerosol
conservation. In tensor notation, the equations are expressed as (Pielke 2002):
Where
is potential temperature, described by
7
and
is virtual temperature. Meanwhile, the ideal gas law takes form
The set of equations above are then solved numerically by means of finitedifference method. More complete explanation about dynamics and
thermodynamics as well as numerical solutions of the model is given in
Skamarock et al. (2008). Two domains were employed in the model (Fig. 3). The
first domain consisted of 103 x 138 horizontal grids and covered spatial
) of 33.1 km. The second domain consisted of 133 x 190
resolutions (
horizontal grids at 11 km in spatial resolution. The two domains were utilized to
analyze the result. Timestep of the model ( ) was 120 seconds. In addition, 28
pressure levels ranging from 1000 to 10 hPa were employed in the model. The
model was also supported by the following physical parameterization:
Surface and Planetary Boundary Layer (PBL) scheme,
cumulus scheme, and
microphysics scheme.
List of physical parameterization used in the model was given in table 1.
Similar parameterization was also adopted by Osuri et al. (2012) to simulate
different TC over north Indian Ocean.
Physical parameterization
YSU PBL is derived from Hong et al. (2006). YSU PBL offers a revised
version of a vertical diffusion algorithm which can produce a better prediction in
weather and climate forecasting research. In this scheme, the fluxes are
represented bycounter-gradient terms. To obtain a better buoyancy profile, a bulk
Richardson number of zero is used at the top of PBL. A smaller magnitude of the
counter-gradient mixing is also used in the scheme to define a well-mixed
boundary layer profile. A revised vertical diffusion equation for prognostic
variables is written as
where Kc is eddy diffusivity coefficient and
is a correction to the local gradient.
Term of
represent the flux at inversion layer. Meanwhile, term of
is a
revised proposed in the YSU PBL scheme. A comprehensive explanation about
YSU PBL scheme, including a revised prognostic equations and numerical
method solution can be found in Hong et al. (2006).
KF cumulus scheme is based on Kain (2004). This scheme is an update of
older version which also use simple cloud model with moist updraft and
8
downdraft and simple calculation of microphysics. KF scheme is implemented to
estimate rate of environmental inflow which can be expressed by
where Muo is radius and mass flux of the cloud at cloud base and dz is a unit
height interval. More explanation can refer to Kain (2004).
The initial condition
The data applied in the initial boundary conditions of the model were:
2-minutes resolutions of USGS terrain height data,
2-minutes resolutions of global 24-category USGS land use/cover data, and
1.0˚ latitude x 1.0˚ longitude grids NCEP Final Analysis (NCEP FNL) data
with grib2 format.
The description of the NCEP FNL dataset are as follows: (a) 6-hourly in
temporal resolution, i.e., 0000, 0600, 1200, and 1800 UTC, (b) pressure levels are
available from 1000 to 10 hPa, and (c) consist of meteorological variables such as:
surface pressure, SLP, geopotential height, temperature, evaporation, relative and
specific humidity, zonal and meridional velocity, vertical velocity, etc. The
information as well as the data is available online through
http://rda.ucar.edu/datasets/ds083.2/#description. The initial data applied in the
initial condition of WRF ARW model hereafter refer to WRF standard-release
model initial data (or WRFSRL).
The experimental design
The research was implemented by performing WRFSRL and by adjusting
thermal characteristics and dynamics of TSC in terms of relative humidity and
zonal and meridional velocity, respectively. The adjustment of the thermal
characteristics of TSC was carried out by decreasing 10 % to 20 % of WRFSRL
NCEP FNL relative humidity initial data at 850-700 hPa. Meanwhile, the
adjustment of the dynamics was carried out by increasing 10 % to 20 % scenarios
and decreasing 10 % to 20 % scenarios of WRFSRL NCEP FNL zonal and
meridional velocity initial data at 850-200 hPa. List of the adjustment scenarios
Table 1 Physical parameterization of WRFSRL
Parameterization
Surface layer
Land surface
PBL
Cumulus
Longwave radiation
Shortwave radiation
Microphysics
Scheme
Monin-Obukhov with Carlson-Boland viscous sublayer
Noah land surface model
Yonsei university PBL (YSU)
Kain-Fritsch scheme (KF)
Rapid Radiative Transfer Model (RRTM) scheme
Dudhia scheme
WRF Single-Moment 3-class scheme
9
Table 2 The adjustment scenarios of the research
Thermal characteristics
and dynamics
Experimental design
Adjustment
Names
Abbreviation
scenarios
10 % decrease
Wind Shear Minus 10
WSHM10
Wind shear (zonal and
20 % decrease
Wind Shear Minus 20
WSHM20
meridional velocity) at
10 % increase
Wind Shear Plus 10
WSHP10
850-200 hPa
20 % increase
Wind Shear Plus 20
WSHP20
Relative humidity at
10 % decrease
RH Minus 10
RHM10
850-700 hPa
20 % decrease
RH Minus 20
RHM20
are given in table 2. Once the initial data had been adjusted, the model was ready
to be tested, the steps were as follows:
Running WRFSRL along with its initial data. The wind intensity and track of
TSC resulting from WRFSRL was then evaluated by comparing them with
those of Joint Typhoon Warning Center (JTWC), Japan Meteorological
Agency (JMA), and Reanalysis data and also by checking the Root Mean
Square Error (RMSE) and Coefficient of Determination (R2) between the
intensity of WRFSRL and JTWC. WRFSRL was then used to analyze the
influence of thermal characteristics and dynamics on TSC intensity prior to
implementing the adjustment scenario. The result was also compared with
satellite images. JTWC and JMA best track and intensity data can be found in
http://weather.unisys.com/hurricane/w_pacific/2011H/index.php
and
http://www.jma.go.jp/jma/jma-eng/jma-center/rsmc-hp-pub-eg/besttrack.html
while Reanalysis data was taken from NCEP/NCAR NOAA through
http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.html
with
spatial coverages of 2.5° latitude x 2.5° longitude which is further interpolated
into 33 km in accordance with the first domain of the model.
Implementing RHM10 and RHM20, re-running the model, and discussed the
intensity changes and changes of mechanical energy of Carnot cycle at mature
stage.
Implementing WSHM10, WSHM20, WSHP10, and WSHP20, re-running the
model, and discussed the intensity changes and changes of mechanical energy
of Carnot cycle at mature stage.
Paired T-test was used to determine significant intensity differences of
maximum wind speeds and SLP for each stages. The selected simulation days
were from May 18th to 30th, 2011 during TSC lifetime. Hence, the entire life
cycles of TSC from early disturbance until reaching the mature, and decaying
stage could be well-observed. In addition, model needed to perform a warm-start
simulation in the first day of simulation in order to adjust the initial boundary
condition as well as physical parameters in the model. Thus, analysis focussed on
the second day on May 19th, 2011.
Typhoon wind intensity and stages
The intensity based on maximum sustained winds in Typhoon classification
issued by JTWC and sequences of TC processes defined by Frank (1987) are
given in table 3.
10
Table 3 Classification of Typhoon intensity, stages, and processes
Maximum wind speeds (ms-1)
Stages
Processes
14-15
Tropical Depression
Genesis
16-28
Tropical Storm
Development
29-37
Typhoon 1
38-46
Typhoon 2
47-59
Typhoon 3
Intensification
60-69
Typhoon 4
> 70
Super Typhoon
Radial and azimuthal velocity
By deriving eq. 3, wind components of radial and azimuthal velocity can be
written as follows
Entropy and Mechanical Energy
Entropy was calculated by using the following expression (Emanuel 1986,
1988):
and mechanical energy of Carnot heat engine of TSC was written as
where
is thermodynamic efficiency (or Carnot cycle effieciency), given by
Where is specific heat of air at constant pressure (1,004 J kg-1 K-1), r is
mixing ratio, T is absolute temperature, Lv is latent heat of vaporization (2,500
), R is specific gas constant for dry air (287 J kg-1 K-1), P is
J/
pressure, To, and Po are reference values of 287 K and 1000 hPa. Subscripts c and
a are storm center and ambient environment, respectively. Meanwhile, Ts and TT
are surface temperature and entropy-weighted mean temperature of the storm‟s
outflow, respectively.
4 RESULTS AND DISCUSSION
The results and discussion of the present study were divided by three
sections. The first section discussed the evaluation of WRFSRL. The evaluation
11
was carried out by comparing TSC track, stages and maximum wind speeds
resulting from WRFSRL with JTWC and JMA as well as by checking the RMSE
and R2 between maximum wind speeds of WRFSRL and JTWC. The abilities of
WRFSRL to mimic the actual situation of TSC with regard to the whirling clouds
shape and wind structure were also discussed in the section. The second section
discussed the influences of thermal characteristics and dynamics on TSC intensity
by performing WRFSRL while the third section discussed intensity changes of
TSC resulting from the adjustment scenarios.
The evaluation of WRFSRL
The track and stages
Figure 4 showed the comparison of the tracks of TSC over WNP Ocean
among WRFSRL, JTWC, and JMA. It was shown that JTWC and JMA showed
nearly identical. The slight difference of about 63 km on average was found upon
reaching Tropical Depression and Tropical Storm stages in the early development
of TSC from May 20th to 22nd. Meanwhile, the track of WRFSRL compared to
JTWC and JMA showed differences. The differences in the path were obviously
found when TSC gradually transformed into Typhoon 1 to Typhoon 4 from May
22th to 26th. It was shown that from May 22th to 25th, it moved about 142 km on
average westward of JTWC and JMA tracks while on May 25th, it intercepted
JTWC and JMA tracks at 129 ˚E and 12 ˚N and turned eastward more or less 135
km from JTWC and JMA tracks later on the day. However, the three tracks were
almost alike upon reaching Super Typhoon from May 26th to 27th. The similarities
continued until TSC weaken from Typhoon 4 to Typhoon 3 on May 28th. Yet, the
distinction was again found when TSC had undergone into Extratropical Storm
from May 29th to May 30th. On May 29th, WRFSRL track shifted about 145 km
north of JTWC and JMA whereas on May 30th, it turned south of JTWC and JMA
tracks. The fair deviations arise in the opening and closing simulation upon
reaching Tropical and Extratropical Storm where less maximum wind speeds
occurred. Consequently, it might not have significant impact to the worst
devastation. The chosen of YSU and KF in the physical parameterization scheme
played an important role in obtaining well-simulated track as well as the intensity
in terms of maximum wind speeds as discussed in the next subchapter. Osuri et al.
(2012) in their state-of-the-art WRF experiments reported that YSU and KF
achieved better track and intensity than some other combinations of physical
parameterization.
Based on WRFSRL, it was shown that the early genesis and development of
TSC started on May 20th until 22nd at 1200 UTC which was initiated by SLP drop
from 1007 to 1001 hPa in the western Pacific Ocean. The disturbance moved
northwest and developed into Tropical Depression on May 20th at 0600 UTC (see
Fig. 4b). Furthermore, 30 hours later in the late afternoon of May 21th, it grew to
be Tropical Storm with wind speeds of 15 ms-1 (see Fig. 5). The status kept lasting
for 18 hours as well as wind speeds gradually rise up to 22 ms-1 and in opposition
SLP fall into 1001 hPa in the middle hours of May 22nd. As reaching Typhoon 1
on May 23rd at 0000 UTC and moving toward the Philippines, JMA issued the
13
TSC intensity
Max.Wind Speeds (ms-1)
Figure 5 showed time-series of TSC maximum wind speeds of WRFSRL
and its comparison to maximum wind speeds originated from JTWC, JMA, and
Reanalysis data. It was shown that WRFSRL was not well-coincided with those of
JTWC, JMA and even Reanalysis data. Reanalysis data showed much lower
intensity compared to JTWC, JMA, and WRFSRL which presented poorindication of the Typhoon event. The maximum wind speeds of Reanalysis data of
about 30 ms-1 occurred on May 29th which indicated a time-lag in reaching peak
intensity of Typhoon. Much lower intensity from Reanalysis data might be due
large spatial coverage of the data which was 2.5°. Even though, it has been
interpolated into 30 km which was similar to spatial resolution given in the first
domain, however, it did not give significant increase of wind speeds which
resulted in a poor-description to the Typhoon development and intensification.
The WRFSRL showed that stronger maximum wind speeds was found as soon as
TSC reached Typhoon 1 on May 23rd at 0000 UTC. The stronger maximum wind
speeds was still observed until TSC had changed into the decaying stage in the
final simulation. It was also shown that the strongest wind speeds occurred on
May 27th at 0000 UTC rather than on May 26th at 1800 UTC as given by JTWC.
Thus, WRFSRL had 6-hour time-lag in simulating the peak intensity of TSC. The
maximum wind speeds between WRFSRL and JTWC during mature stage were
74 ms-1 and 72 ms-1, respectively. In addition, the lower maximum wind speeds
was found at some points during Tropical Depression and Tropical Storm from
May 20th at 0000 UTC to May 22nd at 1200 UTC. At this stage, the wind only
reached 22 ms-1 in speeds compared to 28 ms-1 on magnitude of JTWC. In the
development stages from May 23rd to 25th, wind speed of WRFSRL showed a
rapid increase compared to JTWC and JMA. The reason behind this still remains
question. As discussed before that YSU and KF scheme was essential in obtaining
better intensity. However, in this research, the selections of appropriate PBL and
Cumulus scheme to obtain better TC intensity still need to be further investigated.
80
WRFSRL
JTWC
JMA
Reanalysis Data
60
40
20
0
Date and Time (UTC)
Figure 5 Comparison of time-series of maximum wind speeds (ms-1) of TSC from
May 20th to 30th for WRFSRL (blue line), JTWC (red line), JMA (green
line), and Reanalysis data (violet line)
14
1020
WRFSRL
JTWC
JMA
Reanalysis Data
SLP (hPa)
1000
980
960
940
920
900
Date and Time (UTC)
Figure 6 Comparison of time-series of SLP (hPa) of TSC from May 20th to 30th
for WRFSRL (blue line), JTWC (red line), JMA (green line), and
Reanalysis Data (violet line)
On the contrary, JMA showed much lower maximum wind speeds than
JTWC mostly during the mature stage on May 26th. The reasonable explanation
might be due to the model resolution used by JMA. Based on Angove and Falvey
(2011), JTWC applied many leading operational models with highest resolution to
forecast short-term (72-hour) ongoing events of TC intensity and track. Numerous
model outputs that had been evaluated and compared with satellite images and
radar were then fitted by means of a certain statistical technique developed by
JTWC to improve and to achieve best track and intensity. Davis et al. (2008)
found that different resolution used by the models could influence the position and
intensity of TC. Thus, the model resolution was behind the reason for the
emergence of intensity differences in terms of maximum wind speeds among
WRFSRL, JTWC, and JMA. Tory and Frank (2010) reported that the chosen of
physical parameterization in the model configuration could also influence
differences on intensity simulation. On the other hand, based on the calculation of
RMSE and R2 between WRFSRL and JTWC, it was found that RMSE and R2
values were 12.45 ms-1 and 0.53, respectively. It further implied that the model
was moderate-performed since small deviation found in the model. Besides, the
model was able to capture the maximum wind speeds during mature stage. For
that reason, WRFSRL was then utilized to explain the influences of thermal
characteristics and dynamics on TSC intensity.
Figure 6 gave time-series of TSC SLP of WRFSRL and its comparison to
SLP derived from JTWC and JMA. It was shown that JTWC and JMA intensity in
terms of SLP coincided each other, but not in terms of maximum wind speeds as
discussed above. Meanwhile, WRFSRL did not show any significant decreases of
SLP. The lowest SLP during peak intensity of TSC on May 27 at 0000 UTC was
940 hPa which was 20 hPa higher than JTWC and JMA. The calculated RMSE
and R2 between WRFSRL and JTWC/JMA were 12.83 and 0.8, respectively.
Pressure and maximum wind speeds in TC intensity was known to have an
inverse relationship which was often indicated by negative correlation coefficient.
If pressure is low, maximum wind speeds is high since the air flow from high to
20
in the eye wall at longitude 124.25˚E and in the outer core at longitude 126 ˚E and
another two points were set in the upper level (200 hPa), which were exactly at
the same longitude as the bottom.
Figure 11b showed that the low pressure at point 2 led the air to flow from
point 1 to point 2. The entropy in point 2 was slightly higher than in point 1 which
was due to the increase of mixing ratio from evaporation. It was noted that the
increase of mixing ratio had an effect to the increase of TC intensity. Due to the
pressure gradient, moist air in point 2 rose adiabatically to point 3 in the upper
level of the eye wall. At this point, entropy was higher than point 2. The
divergence of air in point 3 was driven by pressure differences between point 3
and 4. Heat lost during upper level outflow from point 3 to point 4 was due to
cooling radiation, thus, entropy in point 4 was smaller than in point 3. At the end
of the Carnot cycle, the ai
CYCLONE OVER WESTERN NORTH PACIFIC OCEAN:
A CASE STUDY OF TYPHOON SONGDA (CHEDENG) 2011
YOPI ILHAMSYAH
GRADUATE SCHOOL
BOGOR AGRICULTURAL UNIVERSITY
BOGOR
2013
PERNYATAAN MENGENAI THESIS DAN
SUMBER INFORMASI SERTA PELIMPAHAN HAK CIPTA*
Dengan ini saya menyatakan bahwa Thesis berjudul Thermal
Characteristics and Dynamics of Tropical Cyclone over Western North Pacific
Ocean: A Case Study of Typhoon Songda (Chedeng) 2011 adalah benar karya
saya dengan arahan dari komisi pembimbing dan belum diajukan dalam bentuk
apa pun kepada perguruan tinggi mana pun. Sumber informasi yang berasal atau
dikutip dari karya yang diterbitkan maupun tidak diterbitkan dari penulis lain telah
disebutkan dalam teks dan dicantumkan dalam Daftar Pustaka di bagian akhir
Thesis ini.
Dengan ini saya melimpahkan hak cipta dari karya tulis saya kepada Institut
Pertanian Bogor.
Bogor, Juli 2013
Yopi Ilhamsyah
NRP G251110021
RINGKASAN
YOPI ILHAMSYAH. Karakteristik Termal dan Dinamika Siklon Tropis di
Samudera Pasifik Utara bagian Barat: Studi Kasus untuk Topan Songda
(Chedeng) 2011. Dibimbing oleh AHMAD BEY dan EDVIN ALDRIAN.
Siklon Tropis (ST) di Samudera Pasifik Utara bagian Barat sering terjadi
pada 10˚LU hingga 26˚LU dan 121˚BT hingga 170˚BT. Kelembaban nisbi pada
ketinggian 850-700 hPa berpengaruh untuk menghasilkan badai yang sangat
intens. Sementara itu, geser angin lemah antara ketinggian 850-200 hPa
merupakan salah satu faktor dinamika yang berpengaruh terhadap pembentukan
ST. Ketinggian 850-200 dipilih untuk meminimalisir pengaruh termodinamika
pada lapisan troposfer rendah. Topan Songda (Chedeng di Filipina) atau TSC
berlangsung dari tanggal 18 hingga 30 Mei 2011 dan menguat menjadi Super
Topan antara tanggal 24 - 27 Mei 2011. Lintasan melengkung yang panjang dan
pembentukan seluruh tahap dari waktu hidup ST, TSC menjadi kasus ideal untuk
ST. Tujuan penelitian ini adalah untuk menyelidiki pengaruh karakteristik termal
dan dinamika serta perubahannya terhadap intensitas ST.
Penelitian ini dilakukan dengan menggunakan model numerik Advanced
Research of Weather Research and Forecasting model (WRF ARW) versi 3.3.
Dua domain digunakan pada model. Domain pertama berada pada 02˚LU hingga
40˚LU dan 118˚BT hingga 149˚BT dengan resolusi spasial
) 33.1 km.
Domain kedua berada pada 09˚LU hingga 27˚LU and 119˚BT hingga 132˚BT
11 km. Langkah waktu ( ) dari model ini adalah 120 detik.
dengan
Model ini didukung oleh parameterisasi fisika yaitu: skema Yonsei University
(YSU) pada lapisan perbatas, skema Kain-Fritsch (KF) pada kumulus, dan skema
WRF Single-Moment 3-class pada mikrofisika. WRF ARW dengan tujuh skenario
berbeda dilakukan dalam penelitian, yaitu dengan menjalankan model WRF
keluaran standar beserta dengan data inisialnya, dengan mengatur penurunan dan
peningkatan 10 % hingga 20 % dari data inisial geser angin pada ketinggian 850200 hPa dan dengan mengatur penurunan 10 % hingga 20 % dari data inisial
kelembaban nisbi pada ketinggian 850-700 hPa.
Hasil penelitian menunjukkan bahwa korelasi negatif antara geser angin dan
intensitas ditemukan pada skenario geser angin. Geser angin sebesar 10 ms-1 yang
berdampak terhadap penguatan intensitas angin di awal periode pembentukan
Topan ditemukan pada skenario geser angin. Pengaruh perubahan geser angin
terhadap intensitas angin secara statistik berbeda nyata pada skenario geser angin
20 %. Selama tahap matang, intensitas angin lemah terjadi ketika geser angin
meningkat sebagaimana ditemukan pada WRF keluaran standar dan skenario
penurunan geser angin 20 %. Kondisi berbeda ditemukan pada skenario
peningkatan geser angin 20 % di mana geser angin cenderung lemah dan
berdampak terhadap peningkatan intensitas angin pada tahap ini. Sementara itu,
pengurangan suplai kelembaban pada ketinggian 850-700 hPa yang dihasilkan
dari skenario penurunan kelembaban nisbi sebesar 20 % berperan penting dalam
melemahkan intensitas angin sehingga berpengaruh terhadap penurunan energi
mekanik dari proses siklus sebesar 300 J kg-1.
Kata kunci: geser angin, intensitas angin, kelembaban nisbi, WRF ARW
SUMMARY
YOPI ILHAMSYAH. Thermal Characteristics and Dynamics of Tropical Cyclone
over Western North Pacific Ocean: A Case Study of Typhoon Songda (Chedeng)
2011. Under supervision of AHMAD BEY and EDVIN ALDRIAN.
The frequent occasion of Tropical Cyclone (TC) over Western North Pacific
(WNP) Ocean lies from 10˚N to 26˚N and 121˚E to 170˚E. Sources of TC
development come from warm ocean temperature where latent heat is released
during condensation processes and subsequently concentrated in the boundary
layer. Relative humidity at 850-700 hPa is responsible to produce the most intense
storm. Meanwhile, weak vertical wind shear between 850-200 hPa is one of the
dynamical factors that lead to the development of TC. Pressure level of 850-200
hPa is chosen to minimize the thermodynamic effect in the lower troposphere.
Typhoon Songda (Chedeng in the Philippines) or TSC lasted from May 18th to
30th, 2011 and strengthened into powerful Super Typhoon stage between May 24th
and 27th. Long curving track and the exhibition of all sequences of TC life cycle,
TSC is then considered as an ideal case of TC. The objective of the study with
case of TSC is to investigate the role of thermal characteristics and dynamics on
TC intensity.
The research is carried out by using Advanced Research of Weather
Research and Forecasting model (WRF ARW model) version 3.3. Two domains
are employed in the model. The first domain situate from 02˚N to 40˚N and 118˚E
to 149˚E and cover spatial resolution (
) of 33.1 km. The second domain
of 11 km. Timestep
situate from 09˚N to 27˚N and 119˚E to 132˚E with
of the model ( ) is 120 seconds. The model is supported by the following
physical parameterization, i.e., Yonsei University Scheme (YSU) in the boundary
layer, Kain-Fritsch scheme (KF) in the cumulus, and WRF Single-Moment 3-class
scheme in the microphysics. Initial meteorological condition prior to the
formation of the cyclone is generated using WRF ARW standard-release model.
Sensitivity of the model output is obtained from a selected single-parameter
change scenarios, namely, 10 % to 20 % decrease and increase of wind shear
initial data at 850-200 hPa, and by 10 % to 20 % decrease of relative humidity
initial data at 850-700 hPa.
The result showed that the negative correlations between wind shear and
intensity are found in wind shear scenarios. Wind shears of 10 ms-1 which lead to
strengthening of the wind intensity in the early period of Typhoon development
are found in wind shear scenarios. The effect of wind shear changes on wind
intensity is statistically significant in the 20 % wind shear scenarios. During
mature stage, weak wind intensity occurred when wind shear increase as given in
the WRF standard-release and the 20 % decreasing scenario. Different situation is
found in the 20 % increasing scenario where wind shear tend to weak and lead to
strong wind intensity at this stage. Meanwhile, the reduction of moisture supply at
850-700 hPa resulting from 20 % decreasing relative humidity play a major role in
the weakening of wind intensity and reduces mechanical energy of the cycle
process as much as 300 J kg-1.
Keywords: relative humidity, wind intensity, wind shear, WRF ARW
© Hak Cipta Milik IPB, Tahun 2013
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dalam bentuk apa pun tanpa izin IPB
THERMAL CHARACTERISTICS AND DYNAMICS OF TROPICAL
CYCLONE OVER WESTERN NORTH PACIFIC OCEAN:
A CASE STUDY OF TYPHOON SONGDA (CHEDENG) 2011
YOPI ILHAMSYAH
Thesis
as the requirements for the degree of
Magister Sains
in
Applied Climatology Study Program
GRADUATE SCHOOL
BOGOR AGRICULTURAL UNIVERSITY
BOGOR
2013
Penguji pada Ujian Thesis: Dr. Rahmat Hidayat, S.Si, M.Si
Thesis title : Thermal Characteristics and Dynamics of Tropical Cyclone over
Western North Pacific Ocean: A Case Study of Typhoon Songda
(Chedeng) 2011
Name
: Yopi Ilhamsyah
Reg.number : G251110021
Supervisor Committee
Prof. Dr. Ir. Ahmad Bey
Supervisor
Dr. Edvin Aldrian, M.Sc, APU
Co. Supervisor
Head of Study Program
Applied Climatology
Dean of Graduate School
Dr. Ir. Tania June, M.Sc
Dr. Ir. Dahrul Syah, MSc.Agr
Date of Examination: 07 June 2013
Date of Passed:
PREFACE
The author say “Alhamdulillah” gratitude to Allah for making the Thesis
entitled "Thermal Characteristics and Dynamics of Tropical Cyclone over
Western North Pacific Ccean: A Case Study of Typhoon Songda (Chedeng) 2011"
can be possibly presented. Tropical Cyclone is one of the deadliest natural
disasters. Even though various studies have been done to investigate Tropical
Cyclone, it, however, still remains a mystery. Tropical Cyclone (or Typhoon in
the Pacific) is most common over Western North Pacific Ocean. Every year,
during Summer-Autumn, typhoon frequencies increase in number and their
movement lie over vast tropical ocean, from low to middle even high latitude
ocean basin in the Northern Hemisphere. Typhoon Songda (Chedeng), formed in
the early period of intensification, was a massive Super Typhoon. Long curving
track and apparent storm transformation from early growth until reaching mature
and decaying stage initiate the present research. Therefore, the understanding of
thermal characteristics and dynamics of a Typhoon are essential to study tropical
disturbances over Western North Pacific Ocean.
The thesis is divided into five chapters. Chapter one presents basic ideas
behind the research containing background, statement of the problem, and
objective of the research. Chapter two provides review quotations from various
literatures to support the research. Chapter three deals with methodology divided
into subchapters, including location of the research, model performance, initial
condition, and experimental design of the research. Chapter four focusses on
results and discussion and last chapter presents the conclusion of the research and
suggestion for future research.
The author expresses gratitude to supervisors Prof. Dr. Ahmad Bey and Dr.
Edvin Aldrian, M.Sc for providing books, journals, constructive comments, and
suggestions to improve the thesis. Appreciation is given to the head of
Department of Geophysics and Meteorology IPB, Applied Climatology study
program IPB, teaching and administrative staffs. Special gratitude is given to my
father, my (late) mother, my wife and the Ilhamsyah family for moral support.
Thankful is also addressed to Mr. A. Fachri Radjab for giving an opportunity to
carry out the internship at TCWC BMKG and Mr. Zainal Abidin for kind
assistance during the internship. Another grateful is given to friends of KLI 48
and DIKTI under BPPS scholarship for providing financial assistance during my
master program. The author realizes the thesis is still far from perfect. Therefore,
useful comments and notes are greatly appreciated, and hopefully, the thesis can
benefit the readers.
Dramaga, June 2013
Yopi Ilhamsyah
TABLE OF CONTENTS
LIST OF TABLES
i
LIST OF FIGURES
i
LIST OF APPENDIXES
ii
1 BACKGROUND
Background
Statement of the problem
Extent of the problem
Objective
1
1
2
2
3
2 LITERATURE REVIEW
3
3 METHODOLOGY
Location of the research
Tool and Material
Model performance
Physical parameterization
The initial condition
The experimental design
Typhoon wind intensity and stages
Radial and azimuthal velocity
Entropy and mechanical energy
5
5
6
6
7
8
8
9
10
10
4 RESULTS AND DISCUSSION
10
The evaluation of WRFSRL
11
The track and stages
11
TSC intensity
13
The cloud shape and wind structures
15
The Carnot cycle
18
The influences of thermal characteristics and dynamics on TSC intensity 20
The influences of thermal characteristics and dynamics changes on TSC
intensity
23
Wind shear scenarios in TSC life cycle
23
Relative humidity Scenarios in TSC life cycle
27
The impacts of intensity on status and tracks of TSC
28
The correlation of wind shear on TSC intensity and the influences of
scenarios on TSC intensity
30
Wind shear scenarios in the surface and vertical level
31
Relative humidity scenarios in the surface and vertical level
32
Entropy and mechanical energy
33
5 CONCLUSION AND SUGGESTION
Conclusion
34
34
Suggestion
34
REFERENCES
35
APPENDIX
39
BIOGRAPHY
60
LIST OF TABLES
1 Physical parameterization of WRFSRL
2 The adjustment scenarios of the research
3 Classification of Typhoon intensity, stages, and processes
8
9
10
LIST OF FIGURES
1 The occurrences of worldwide TC for period 1998–2007. Colors with
different symbols as shown in the legend inform TC stages on the
Saffir–Simpson scale for each individual pathway
2 NH monthly diagnostics of 850-200 hPa vertical wind shear (19582002) in ms-1 and SST (1977-2006) in ˚C. The locations of TC genesis
are indicated by oval marks
3 Geographical location and domains of WRFSRL over WNP Ocean.
D01 and D02 are the first and second domain, respectively
4 Tracks of TSC life cycle from May 20th to 30th, (a) WRFSRL (blue
line) and its comparison to JTWC (red line), and JMA (green line) and
(b) stages of WRFSRL track
5 Comparison of time-series of maximum wind speeds (ms-1) of TSC
from May 20th to 30th for WRFSRL (blue line), JTWC (red line), and
JMA (green line)
6 Comparison of time-series of SLP (hPa) of TSC from May 20th to 30th
for WRFSRL (blue line), JTWC (red line), and JMA (green line)
7 Swirling shape of TSC clouds at Super Typhoon stage on May 27th at
0000 UTC, (a) WRFSRL and (b) satellite imagery taken from MTSAT2 IR1 JMA (source: EEI-Lab. Kochi University)
8 Three-dimensional wind flow of TSC at Super Typhoon stage on May
27th at 0000 UTC. Bar chart in the left indicates the magnitudes of wind
speeds in ms-1 (not the terrain profile in the lowest background)
9 West-East vertical structures of TSC at Super Typhoon stage on May
27th at 0000 UTC, (a) azimuthal velocity (ms-1) and (b) radial velocity
(ms-1)
10 West-East vertical structures of TSC at Super Typhoon stage at 0000
UTC on May 27th, (a) maximum wind speeds (shaded and barb) in ms-1
and (b) vertical velocity in Pa s-1
11 West-East vertical structures of (a) (K) and (b) entropy (J kg-1K-1)
and description of Carnot cycle of TSC at on May 27th at 0000 UTC
12 Wind Shear at 850 – 200 hPa in ms-1 (focus area is given on the black
box) during (a) Tropical Depression on May 19th, (b) Super Typhoon
on May 27th, and (c) Extratropical Storm on May 30th at 0000 UTC
13 Time-series of (a) maximum wind speed (ms-1) of WRFSRL and (b)
scenario deviation from WRFSRL (ms-1) for WSHP10 (red line) and
WSHM10 (green line) from May 20th to 30th
14 Time-series of (a) SLP (hPa) of WRFSRL and (b) scenario deviation
from WRFSRL (hPa) for WSHP10 (red line) and WSHM10 (green
line) from May 20th to 30th
4
5
6
12
13
14
15
16
17
18
19
22
24
25
15 Time-series of (a) wind shear at 850-200 hPa (ms-1) of WRFSRL and
(b) scenario deviation from WRFSRL (ms-1) for WSHP10 (red line) and
WSHM10 (green line) from May 20th to 30th
16 Time-series of (a) maximum wind speed (ms-1) of WRFSRL and (b)
scenario deviation from WRFSRL (ms-1) for WSHP20 (red line) and
WSHM20 (green line) from May 20th to 30th
17 Time-series of (a) SLP (hPa) of WRFSRL and (b) scenario deviation
from WRFSRL (hPa) for WSHP20 (red line) and WSHM20 (green
line) from May 20th to 30th
18 Time-series of (a) wind shear at 850-200 hPa (ms-1) of WRFSRL and
(b) scenario deviation from WRFSRL (ms-1) for WSHP20 (red line)
and WSHM20 (green line) from May 20th to 30th
19 Time-series of (a) maximum wind speed (ms-1) of WRFSRL and (b)
scenario deviation from WRFSRL (ms-1) for RHM10 (red line) and
RHM20 (green line) from May 20th to 30th
20 Time-series of (a) SLP (hPa) of WRFSRL and (b) scenario deviation
from WRFSRL (hPa) for RHM10 (red line) and RHM20 (green line)
from May 20th to 30th
26
27
28
29
30
31
LIST OF APPENDIXES
1 Tracks of TSC lifecycle from May 20th to 30th, (a) WRFSRL, (b)
WSHM10, and (c) WSHP10
2 Tracks of TSC lifecycle from May 20th to 30th, (a) WRFSRL, (b)
WSHM20, and (c) WSHP20
3 Tracks of TSC lifecycle from May 20th to 30th, (a) WRFSRL, (b)
RHM10, and (c) RHM20
4 West-East vertical structures of TSC for temperature (˚C) in shaded and
relative humidity (%) in contour line (figures in the left side) and
temperature anomaly (˚C) in shaded (figures in the right side), (a and b)
at Tropical Storm on May 22nd (c and d) at Super Typhoon on May 27th,
(e and f) at Extratropical Storm on May 30th at 0000 UTC
5 Wind shear (ms-1) and maximum wind speeds (ms-1) on averages at all
stages of TSC life cycle resulting from different wind shear scenarios
WSH = wind shear and MWS = maximum wind speeds
6 Maximum wind speeds (ms-1) on averages at all stages of TSC life
cycle resulting from different relative humidity scenarios
7 Surface wind speeds at 10 m (shaded and vector) in ms-1 of TSC and
scenario deviation at Super Typhoon stage on May 27th at 0000 UTC,
(a) WRFSRL,(b) WSHM10, (c) WSHM20, (d) WSHP10, and (e)
WSHP20
8 West-East vertical structures of maximum wind speeds (shaded and
barb) in ms-1 of TSC and scenario deviation at Super Typhoon stage on
May 27th at 0000 UTC, (a) WRFSRL, (b) WSHM10, (c) WSHM20, (d)
WSHP10, and (e) WSHP20
39
40
41
42
44
45
46
47
9 Surface wind speeds at 10 m (shaded and vector) in ms-1 of TSC at
Super Typhoon stage on May 27th at 0000 UTC and scenario deviation
(a) WRFSRL, (b) RHM10, and (c) RHM20
10 West-East vertical structures of maximum wind speeds (shaded and
barb) in ms-1 of TSC and scenario deviation at Super Typhoon stage on
May 27th at 0000 UTC, (a) WRFSRL, (b) RHM10, and (c) RHM20
11 West-East vertical structures of entropy (J kg-1 K-1) as well as the
description of Carnot cycle of TSC and scenario deviation at Super
Typhoon stage on May 27th at 0000 UTC, (a) WRFSRL, (b) WSHM10,
(c) WSHM20, (d) WSHP10, and (e) WSHP20
12 West-East vertical structures of entropy (J kg-1 K-1) as well as the
description of Carnot cycle of TSC and scenario deviation at Super
Typhoon stage on May 27th at 0000 UTC, (a) WRFSRL, (b) RHM10,
and (c) RHM20
13 Sample script to adjust 10 % increasing scenario of NCEP FNL in the
initial condition in terms of zonal velocity at 850-200 hPa on May 27th
at 0000 UTC by using GRIB API
14 Sample script to calculate maximum wind speeds at Super Typhoon
stage
15 Sample script to calculate wind shear and west-east vertical section of
equivalent potential temperature for WRFSRL
16 Sample script to calculate west-east vertical section of maximum wind
speeds deviation from WRFSRL at Super Typhoon stage for RHM20
scenario
17 Script to calculate west-east vertical section of Entropy at Super
Typhoon stage for WRFSRL
18 Script to calculate mechanical energy of TSC at Super Typhoon stage
for WRFSRL
48
49
50
51
52
55
56
57
58
59
1
1 INTRODUCTION
Background
Western North Pacific (WNP) Ocean is one of the ocean basins that drive
the early genesis, the development until the dissipation of Tropical Cyclone (TC).
WNP is geographically situated in the Northern Hemisphere (NH) between 100˚180˚E and 0˚-60˚N and covers the region from the entire northern Equator of the
basin, including South China Sea to the west of International Date Line (IDL) in
the Central Pacific. WNP is well-known for the most dynamical basin to TC
occurrences (Neumann 1993; Lin et al. 2005, 2008). The frequent occasion of TC
lies from 10˚N to 26˚N and 121˚E to 170˚E (Holliday and Thompson 1979). TC
over this maritime region is likely to intensify during June-November with peak
activity occurred in the late NH summer on August (Emanuel 2003) and decline in
the late period of December. TC over WNP is locally called as Typhoon.
Principally, extensive periods of warm Sea Surface Temperature (SST) over
WNP play a major role in driving the frequencies of Typhoon events throughout
the year. Warm SST leads to higher rates of energy transfer from the ocean and
therefore increases Typhoon formation. Early study conducted by Gray (1968,
1975) showed SST exceeding 26.5°C was favorable environment for the genesis
of TC. Advanced studies by DeMaria et al. (2001), and Nolan et al. (2007a)
confirmed the previous results. The understanding of air-sea interaction is,
however, a principal explanation to describe the development of TC and its life
cycle. As a result of warm SST, the water vapor is released to the the air. The
rising air becomes saturate and condenses to form cloud where in this process;
large amounts of latent heat are released. The upward moist air are then
concentrated in the boundary layer which in turn drive to preserve the
intensification of TC over the ocean. Sufficient moisture in the middle
troposphere layer (850-700 hPa) is considered to have a major influence in
supplying heat to drive TC intensity. Schade and Emanuel (1999) found that
relative humidity at 850-700 hPa layer is responsible to produce the most intense
storm. Thus, the increase of humidity in the middle troposphere is one of thermal
characteristics that can be taken into account (Emanuel et al. 2004; Hill and
Lackmann 2009). The humid environment leads the themal energy to increase and
start circulating from warm to cold environment in a closed process, known as
Carnot cycle. Emanuel (1986) constructed a simple energy balance model to
explain the corresponding role of TC heat engine as a Carnot cycle. Moist entropy
from the lower level is the primary energy in the cycle. It allows air to flow
inward the boundary layer. At that moment, the air rises and releases heat at lower
temperature in the upper troposphere which further converts it from thermal to
mechanical energy.
On the other hand, weak vertical wind shear is one of the dynamical factors
that lead to the development of TC (Molinari et al. 2004; Latif et al. 2007). The
influence of vertical wind shear particularly between 850-200 hPa in controlling
TC intensity is based on climatological study by Gray (1968). Although he
considered 950 hPa as the lower limit of condensation level in the tropics, but,
pressure levels at 850-200 hPa was chosen to minimize thermodynamic effect in
2
the lower troposphere. It is then considered that changes of thermal characteristics
and dynamics of TC also influence the changes of TC intensity and mechanical
energy of the Carnot cycle.
The uses of simulation model had been conducted to investigate shear and
moisture changes and their implications on TC intensity, e.g., Wang and Holland
(1996), Frank and Ritchie (1999), and Wong and Chan (2004). However, their
study was based on full idealized physics simulation. In the present study, the
influences of shear and moisture changes on TC intensity was examined by using
three-dimensional numerical model by varying its initial condition.
Typhoon Songda (called Chedeng in the Philippines) (hereafter refer to
TSC) was the fourth named TC of the 2011 NH tropical season. TSC was the
most devastating storm that striked WNP Ocean for the period of 2011. It lasted
from May 18th to 30th, 2011 for two continuous weeks and strengthened to boost
peak activity of powerful Super Typhoon stages between May 24th and 27th. Long
curving track and the exhibition of all sequences of TC life cycle, TSC was then
considered as an ideal case of TC. Its development and intensification, however,
still remained questions. The fact that TSC is not a subject of exploration yet soon
motivates the present research. The purposes of the research with a case of TSC
presented herein will investigate the influences of thermal characteristics and
dynamics on TSC intensity and their changes effect on TSC intensity as well as
mechanical energy of the Carnot cycle. The primary points of emphasis are
relative humidity and vertical wind shear as mentioned earlier.
Statement of the problem
TC is powerful synoptic-scale systems that is formed over warm tropical
ocean. The development of TC is driven by some thermodynamics and dynamics
prerequisites, some of them are: vertical wind shear and middle troposphere
moisture. The development of TC that last for many days over the ocean can be
recognized by its intensity in terms of maximum wind speeds and sea-level
pressure (SLP). It is then considered that the changes on TC intensity are caused
by the changes of thermal characteristics and dynamics of TC. Thus, by choosing
a definite case of a strong development of TC, in this case TSC, the present study
will focus on research questions about how thermal characteristics and dynamics
and their changes play a major role on TSC intensity.
Extent of the problem
The extents of the problem of the present research are as follows:
TC discussed in this study refers to a case for TSC 2011.
Changes of thermal characteristics focus on middle troposphere layer of
relative humidity at 850-700 hPa while dynamic factor is the vertical wind
shear at 850 – 200 hPa.
Emphasis is on 6-hourly changes of TSC intensity from early genesis to
decaying stage.
The intensity is based on maximum wind speeds in Typhoon scale issued by
JTWC.
3
Objective
The purpose of the research is to investigate the influence of thermal
characteristics and dynamics, and their changes on TC intensity.
The research is expected to provide a better understanding on roles of
thermal characteristics and dynamics, and their changes effect on TC intensity
which is useful to assist operational weather forecaster to produce good shortrange forecasts of TC intensities.
2 LITERATURE REVIEW
The sequence of TC processes are often revealed by the following terms,
i.e., genesis, formation, development, and intensification. Genesis is defined as
transition phase from Tropical Disturbance to Tropical Depression (the formation
of a rotational motion with a few hundred km in scale), however, the term
development is often used instead of formation to describe the transition from
Tropical Depression to Tropical Storm with a maximum wind speeds of 17 ms-1.
Meanwhile, the term intensification is used to identify mature stage of a storm
from Tropical Storm to severe TC (also locally known as Typhoon in the Pacific
or Hurricane in the Atlantic) with a maximum wind speeds of 33 ms-1 (Frank
1987). Meanwhile, terms such as: large scale formation and core formation are
commonly used to distinguish the sequence processes of TC development
(McBride 1995).
Annually, there are about 80 to 90 TC occurrence over tropical oceans.
Based on climatological conditions associated with tropical cyclogenesis, most
common TC occasion form over tropical ocean under five following
characteristics (Gray 1968, 1975):
SST above 26.5˚C to 50 m depth of ocean mixed layer;
a deep layer of conditional instability;
increased values of cyclonic low level absolute vorticity;
organized deep convection in an area with large-scale ascent and high middle
level humidity, and
weak to moderate vertical wind shear.
Most TC are formed between 10˚ and 30˚ latitude in both hemispheres.
Large Coriolis force effect in the middle latitude initiates and keeps maintaining
TC rotation away from the Equator. In rare occasions, TC is found close to the
Equator, e.g., Tropical Storm Vamei in 2001 and Cyclone Agni in 2004, and of
particular interest among researchers (e.g., Chang et al. 2003). Figure 1 shows
worldwide distributions of TC. It is shown that the frequencies and the intensities
of TC over WNP ocean is highest since Intertropical Convergence Zone (ITCZ)
during high-sun season of NH (spring-summer) drives intensive solar heating and
makes TC over WNP become more frequent to occur (Zehnder et al. 1999).
TC frequently emerges over tropical oceans where warm water exist to at least 50
m depth. Dare and McBride (2011) analyzed SST data over period 1981-2008
extending from the Equator to 35˚N and 35˚S and concluded that more than 93 %
of TC development occurred at SST exceeding 26.5˚C and 98 % above 25.5˚C.
4
Therefore, SST value between 25.5˚C and 26.5˚C turned into preferences on TC
genesis. Sufficient warm is needed to maintain the energy supply of the storms.
Warm SST is conducive to strengthen TC. The energy is derived from substantial
amounts of water vapor due to evaporation. The water vapor then condenses and
releases latent heat in the atmospheric boundary layer. The heat latter fuel the
intensity of TC.
The relation between moist environment in the middle troposphere and TC
genesis had been the subjects of discussions among researchers. Sippel and Zhang
(2008) found that deep moisture is one of the initial characteristics for TC
formation. Bister and Emanuel (1997) carried out field experiment and found that
the increase of equivalent potential temperature in the middle troposphere
indicated the sufficient thermal characteristics on TC genesis. Raymond et al.
(1998) also found a correlation between relative humidity and the reduction of
downdraft. Later Raymond and Sessions (2007) gave an opinion that in fact their
field experiment showed that equivalent potential temperature had increased in the
middle level, the essential TC genesis was due to the stabilization in the low level.
However, it still needs to be further investigated whether relative humidy is useful
to diagnose the development of TC.
Weak vertical wind shear of less than 10-15 ms-1 over a deep layer 850-200
hPa, is another precondition factor on TC genesis. Climatologically, wind shear is
weaker in early NH summer. As tropical and subtropical ocean enter a warm
season, wind shear become stronger and winter Hadley cell strengthens through
local summer and into autumn as shown in figure 2. Oval marks in figure 2
indentify the locations of vertical wind shear and SST that conducive for TC
genesis as proved by Chan and Liu (2004). Vertical wind shear can have an effect
on the distribution and convection in TC. It can favorable in increasing the
convection and strengthening the upper-level outflow of the storm as well as the
structure and storm motion (Reasor et al. 2004).
Figure 1 The geographical distribution of TC worldwide TC over the period of
1998–2007. Colors with different symbols are stages of the Saffir–
Simpson scale for each individual pathway (Llyod and Vecchi 2011)
5
Figure 2 NH monthly diagnostics of (a) 850-200 hPa vertical wind shear (19582002) in ms-1 and (b) SST (1977-2006) in ˚C. The locations of TC
genesis are indicated by oval marks (Laing and Evans 2011)
On the other hand, environmental wind shear will cause the storm to
reorganize through induced convection on the downshear side of the storm that
will initially generate an axisymmetry. Finally the storm will either (i) reintensify
as a tropical system, having generated enough convection to retain its tropical
structure in the sheared environment; or (ii) become extratropical and reintensify
because of the wind shear; or (iii) decay (Laing and Evans, 2011). Vertical wind
shear has been shown to have an impact on different TC intensity (e.g.,
Corbosiero and Molinari 2002).
3 METHODOLOGY
Location of the research
The research was carried out in the laboratory of Meteorology and
Atmospheric Pollution, Department of Geophysics and Meteorology, Bogor
Agricultural University from September 2012 to April 2013. The domain of study
areas was between 03˚N - 43˚N and 117˚E - 150˚E for period of TSC life cycle
from May 18th to 30th, 2011 (see Fig. 3).
6
Figure 3 Geographical location and domains of WRFSRL over WNP Ocean. D01
and D02 are the first and second domain, respectively
Tool and Material
Model Performance
The research was carried out by performing Advanced Research of Weather
Research and Forecasting model (WRF ARW model) version 3.3. WRF ARW is a
non-hydrostatic three-dimensional numerical model with terrain-following in the
vertical-sigma coordinate. Basically, WRF ARW is governed by the following
fundamental equations of mass, heat, momentum, water, and gaseous and aerosol
conservation. In tensor notation, the equations are expressed as (Pielke 2002):
Where
is potential temperature, described by
7
and
is virtual temperature. Meanwhile, the ideal gas law takes form
The set of equations above are then solved numerically by means of finitedifference method. More complete explanation about dynamics and
thermodynamics as well as numerical solutions of the model is given in
Skamarock et al. (2008). Two domains were employed in the model (Fig. 3). The
first domain consisted of 103 x 138 horizontal grids and covered spatial
) of 33.1 km. The second domain consisted of 133 x 190
resolutions (
horizontal grids at 11 km in spatial resolution. The two domains were utilized to
analyze the result. Timestep of the model ( ) was 120 seconds. In addition, 28
pressure levels ranging from 1000 to 10 hPa were employed in the model. The
model was also supported by the following physical parameterization:
Surface and Planetary Boundary Layer (PBL) scheme,
cumulus scheme, and
microphysics scheme.
List of physical parameterization used in the model was given in table 1.
Similar parameterization was also adopted by Osuri et al. (2012) to simulate
different TC over north Indian Ocean.
Physical parameterization
YSU PBL is derived from Hong et al. (2006). YSU PBL offers a revised
version of a vertical diffusion algorithm which can produce a better prediction in
weather and climate forecasting research. In this scheme, the fluxes are
represented bycounter-gradient terms. To obtain a better buoyancy profile, a bulk
Richardson number of zero is used at the top of PBL. A smaller magnitude of the
counter-gradient mixing is also used in the scheme to define a well-mixed
boundary layer profile. A revised vertical diffusion equation for prognostic
variables is written as
where Kc is eddy diffusivity coefficient and
is a correction to the local gradient.
Term of
represent the flux at inversion layer. Meanwhile, term of
is a
revised proposed in the YSU PBL scheme. A comprehensive explanation about
YSU PBL scheme, including a revised prognostic equations and numerical
method solution can be found in Hong et al. (2006).
KF cumulus scheme is based on Kain (2004). This scheme is an update of
older version which also use simple cloud model with moist updraft and
8
downdraft and simple calculation of microphysics. KF scheme is implemented to
estimate rate of environmental inflow which can be expressed by
where Muo is radius and mass flux of the cloud at cloud base and dz is a unit
height interval. More explanation can refer to Kain (2004).
The initial condition
The data applied in the initial boundary conditions of the model were:
2-minutes resolutions of USGS terrain height data,
2-minutes resolutions of global 24-category USGS land use/cover data, and
1.0˚ latitude x 1.0˚ longitude grids NCEP Final Analysis (NCEP FNL) data
with grib2 format.
The description of the NCEP FNL dataset are as follows: (a) 6-hourly in
temporal resolution, i.e., 0000, 0600, 1200, and 1800 UTC, (b) pressure levels are
available from 1000 to 10 hPa, and (c) consist of meteorological variables such as:
surface pressure, SLP, geopotential height, temperature, evaporation, relative and
specific humidity, zonal and meridional velocity, vertical velocity, etc. The
information as well as the data is available online through
http://rda.ucar.edu/datasets/ds083.2/#description. The initial data applied in the
initial condition of WRF ARW model hereafter refer to WRF standard-release
model initial data (or WRFSRL).
The experimental design
The research was implemented by performing WRFSRL and by adjusting
thermal characteristics and dynamics of TSC in terms of relative humidity and
zonal and meridional velocity, respectively. The adjustment of the thermal
characteristics of TSC was carried out by decreasing 10 % to 20 % of WRFSRL
NCEP FNL relative humidity initial data at 850-700 hPa. Meanwhile, the
adjustment of the dynamics was carried out by increasing 10 % to 20 % scenarios
and decreasing 10 % to 20 % scenarios of WRFSRL NCEP FNL zonal and
meridional velocity initial data at 850-200 hPa. List of the adjustment scenarios
Table 1 Physical parameterization of WRFSRL
Parameterization
Surface layer
Land surface
PBL
Cumulus
Longwave radiation
Shortwave radiation
Microphysics
Scheme
Monin-Obukhov with Carlson-Boland viscous sublayer
Noah land surface model
Yonsei university PBL (YSU)
Kain-Fritsch scheme (KF)
Rapid Radiative Transfer Model (RRTM) scheme
Dudhia scheme
WRF Single-Moment 3-class scheme
9
Table 2 The adjustment scenarios of the research
Thermal characteristics
and dynamics
Experimental design
Adjustment
Names
Abbreviation
scenarios
10 % decrease
Wind Shear Minus 10
WSHM10
Wind shear (zonal and
20 % decrease
Wind Shear Minus 20
WSHM20
meridional velocity) at
10 % increase
Wind Shear Plus 10
WSHP10
850-200 hPa
20 % increase
Wind Shear Plus 20
WSHP20
Relative humidity at
10 % decrease
RH Minus 10
RHM10
850-700 hPa
20 % decrease
RH Minus 20
RHM20
are given in table 2. Once the initial data had been adjusted, the model was ready
to be tested, the steps were as follows:
Running WRFSRL along with its initial data. The wind intensity and track of
TSC resulting from WRFSRL was then evaluated by comparing them with
those of Joint Typhoon Warning Center (JTWC), Japan Meteorological
Agency (JMA), and Reanalysis data and also by checking the Root Mean
Square Error (RMSE) and Coefficient of Determination (R2) between the
intensity of WRFSRL and JTWC. WRFSRL was then used to analyze the
influence of thermal characteristics and dynamics on TSC intensity prior to
implementing the adjustment scenario. The result was also compared with
satellite images. JTWC and JMA best track and intensity data can be found in
http://weather.unisys.com/hurricane/w_pacific/2011H/index.php
and
http://www.jma.go.jp/jma/jma-eng/jma-center/rsmc-hp-pub-eg/besttrack.html
while Reanalysis data was taken from NCEP/NCAR NOAA through
http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.html
with
spatial coverages of 2.5° latitude x 2.5° longitude which is further interpolated
into 33 km in accordance with the first domain of the model.
Implementing RHM10 and RHM20, re-running the model, and discussed the
intensity changes and changes of mechanical energy of Carnot cycle at mature
stage.
Implementing WSHM10, WSHM20, WSHP10, and WSHP20, re-running the
model, and discussed the intensity changes and changes of mechanical energy
of Carnot cycle at mature stage.
Paired T-test was used to determine significant intensity differences of
maximum wind speeds and SLP for each stages. The selected simulation days
were from May 18th to 30th, 2011 during TSC lifetime. Hence, the entire life
cycles of TSC from early disturbance until reaching the mature, and decaying
stage could be well-observed. In addition, model needed to perform a warm-start
simulation in the first day of simulation in order to adjust the initial boundary
condition as well as physical parameters in the model. Thus, analysis focussed on
the second day on May 19th, 2011.
Typhoon wind intensity and stages
The intensity based on maximum sustained winds in Typhoon classification
issued by JTWC and sequences of TC processes defined by Frank (1987) are
given in table 3.
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Table 3 Classification of Typhoon intensity, stages, and processes
Maximum wind speeds (ms-1)
Stages
Processes
14-15
Tropical Depression
Genesis
16-28
Tropical Storm
Development
29-37
Typhoon 1
38-46
Typhoon 2
47-59
Typhoon 3
Intensification
60-69
Typhoon 4
> 70
Super Typhoon
Radial and azimuthal velocity
By deriving eq. 3, wind components of radial and azimuthal velocity can be
written as follows
Entropy and Mechanical Energy
Entropy was calculated by using the following expression (Emanuel 1986,
1988):
and mechanical energy of Carnot heat engine of TSC was written as
where
is thermodynamic efficiency (or Carnot cycle effieciency), given by
Where is specific heat of air at constant pressure (1,004 J kg-1 K-1), r is
mixing ratio, T is absolute temperature, Lv is latent heat of vaporization (2,500
), R is specific gas constant for dry air (287 J kg-1 K-1), P is
J/
pressure, To, and Po are reference values of 287 K and 1000 hPa. Subscripts c and
a are storm center and ambient environment, respectively. Meanwhile, Ts and TT
are surface temperature and entropy-weighted mean temperature of the storm‟s
outflow, respectively.
4 RESULTS AND DISCUSSION
The results and discussion of the present study were divided by three
sections. The first section discussed the evaluation of WRFSRL. The evaluation
11
was carried out by comparing TSC track, stages and maximum wind speeds
resulting from WRFSRL with JTWC and JMA as well as by checking the RMSE
and R2 between maximum wind speeds of WRFSRL and JTWC. The abilities of
WRFSRL to mimic the actual situation of TSC with regard to the whirling clouds
shape and wind structure were also discussed in the section. The second section
discussed the influences of thermal characteristics and dynamics on TSC intensity
by performing WRFSRL while the third section discussed intensity changes of
TSC resulting from the adjustment scenarios.
The evaluation of WRFSRL
The track and stages
Figure 4 showed the comparison of the tracks of TSC over WNP Ocean
among WRFSRL, JTWC, and JMA. It was shown that JTWC and JMA showed
nearly identical. The slight difference of about 63 km on average was found upon
reaching Tropical Depression and Tropical Storm stages in the early development
of TSC from May 20th to 22nd. Meanwhile, the track of WRFSRL compared to
JTWC and JMA showed differences. The differences in the path were obviously
found when TSC gradually transformed into Typhoon 1 to Typhoon 4 from May
22th to 26th. It was shown that from May 22th to 25th, it moved about 142 km on
average westward of JTWC and JMA tracks while on May 25th, it intercepted
JTWC and JMA tracks at 129 ˚E and 12 ˚N and turned eastward more or less 135
km from JTWC and JMA tracks later on the day. However, the three tracks were
almost alike upon reaching Super Typhoon from May 26th to 27th. The similarities
continued until TSC weaken from Typhoon 4 to Typhoon 3 on May 28th. Yet, the
distinction was again found when TSC had undergone into Extratropical Storm
from May 29th to May 30th. On May 29th, WRFSRL track shifted about 145 km
north of JTWC and JMA whereas on May 30th, it turned south of JTWC and JMA
tracks. The fair deviations arise in the opening and closing simulation upon
reaching Tropical and Extratropical Storm where less maximum wind speeds
occurred. Consequently, it might not have significant impact to the worst
devastation. The chosen of YSU and KF in the physical parameterization scheme
played an important role in obtaining well-simulated track as well as the intensity
in terms of maximum wind speeds as discussed in the next subchapter. Osuri et al.
(2012) in their state-of-the-art WRF experiments reported that YSU and KF
achieved better track and intensity than some other combinations of physical
parameterization.
Based on WRFSRL, it was shown that the early genesis and development of
TSC started on May 20th until 22nd at 1200 UTC which was initiated by SLP drop
from 1007 to 1001 hPa in the western Pacific Ocean. The disturbance moved
northwest and developed into Tropical Depression on May 20th at 0600 UTC (see
Fig. 4b). Furthermore, 30 hours later in the late afternoon of May 21th, it grew to
be Tropical Storm with wind speeds of 15 ms-1 (see Fig. 5). The status kept lasting
for 18 hours as well as wind speeds gradually rise up to 22 ms-1 and in opposition
SLP fall into 1001 hPa in the middle hours of May 22nd. As reaching Typhoon 1
on May 23rd at 0000 UTC and moving toward the Philippines, JMA issued the
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TSC intensity
Max.Wind Speeds (ms-1)
Figure 5 showed time-series of TSC maximum wind speeds of WRFSRL
and its comparison to maximum wind speeds originated from JTWC, JMA, and
Reanalysis data. It was shown that WRFSRL was not well-coincided with those of
JTWC, JMA and even Reanalysis data. Reanalysis data showed much lower
intensity compared to JTWC, JMA, and WRFSRL which presented poorindication of the Typhoon event. The maximum wind speeds of Reanalysis data of
about 30 ms-1 occurred on May 29th which indicated a time-lag in reaching peak
intensity of Typhoon. Much lower intensity from Reanalysis data might be due
large spatial coverage of the data which was 2.5°. Even though, it has been
interpolated into 30 km which was similar to spatial resolution given in the first
domain, however, it did not give significant increase of wind speeds which
resulted in a poor-description to the Typhoon development and intensification.
The WRFSRL showed that stronger maximum wind speeds was found as soon as
TSC reached Typhoon 1 on May 23rd at 0000 UTC. The stronger maximum wind
speeds was still observed until TSC had changed into the decaying stage in the
final simulation. It was also shown that the strongest wind speeds occurred on
May 27th at 0000 UTC rather than on May 26th at 1800 UTC as given by JTWC.
Thus, WRFSRL had 6-hour time-lag in simulating the peak intensity of TSC. The
maximum wind speeds between WRFSRL and JTWC during mature stage were
74 ms-1 and 72 ms-1, respectively. In addition, the lower maximum wind speeds
was found at some points during Tropical Depression and Tropical Storm from
May 20th at 0000 UTC to May 22nd at 1200 UTC. At this stage, the wind only
reached 22 ms-1 in speeds compared to 28 ms-1 on magnitude of JTWC. In the
development stages from May 23rd to 25th, wind speed of WRFSRL showed a
rapid increase compared to JTWC and JMA. The reason behind this still remains
question. As discussed before that YSU and KF scheme was essential in obtaining
better intensity. However, in this research, the selections of appropriate PBL and
Cumulus scheme to obtain better TC intensity still need to be further investigated.
80
WRFSRL
JTWC
JMA
Reanalysis Data
60
40
20
0
Date and Time (UTC)
Figure 5 Comparison of time-series of maximum wind speeds (ms-1) of TSC from
May 20th to 30th for WRFSRL (blue line), JTWC (red line), JMA (green
line), and Reanalysis data (violet line)
14
1020
WRFSRL
JTWC
JMA
Reanalysis Data
SLP (hPa)
1000
980
960
940
920
900
Date and Time (UTC)
Figure 6 Comparison of time-series of SLP (hPa) of TSC from May 20th to 30th
for WRFSRL (blue line), JTWC (red line), JMA (green line), and
Reanalysis Data (violet line)
On the contrary, JMA showed much lower maximum wind speeds than
JTWC mostly during the mature stage on May 26th. The reasonable explanation
might be due to the model resolution used by JMA. Based on Angove and Falvey
(2011), JTWC applied many leading operational models with highest resolution to
forecast short-term (72-hour) ongoing events of TC intensity and track. Numerous
model outputs that had been evaluated and compared with satellite images and
radar were then fitted by means of a certain statistical technique developed by
JTWC to improve and to achieve best track and intensity. Davis et al. (2008)
found that different resolution used by the models could influence the position and
intensity of TC. Thus, the model resolution was behind the reason for the
emergence of intensity differences in terms of maximum wind speeds among
WRFSRL, JTWC, and JMA. Tory and Frank (2010) reported that the chosen of
physical parameterization in the model configuration could also influence
differences on intensity simulation. On the other hand, based on the calculation of
RMSE and R2 between WRFSRL and JTWC, it was found that RMSE and R2
values were 12.45 ms-1 and 0.53, respectively. It further implied that the model
was moderate-performed since small deviation found in the model. Besides, the
model was able to capture the maximum wind speeds during mature stage. For
that reason, WRFSRL was then utilized to explain the influences of thermal
characteristics and dynamics on TSC intensity.
Figure 6 gave time-series of TSC SLP of WRFSRL and its comparison to
SLP derived from JTWC and JMA. It was shown that JTWC and JMA intensity in
terms of SLP coincided each other, but not in terms of maximum wind speeds as
discussed above. Meanwhile, WRFSRL did not show any significant decreases of
SLP. The lowest SLP during peak intensity of TSC on May 27 at 0000 UTC was
940 hPa which was 20 hPa higher than JTWC and JMA. The calculated RMSE
and R2 between WRFSRL and JTWC/JMA were 12.83 and 0.8, respectively.
Pressure and maximum wind speeds in TC intensity was known to have an
inverse relationship which was often indicated by negative correlation coefficient.
If pressure is low, maximum wind speeds is high since the air flow from high to
20
in the eye wall at longitude 124.25˚E and in the outer core at longitude 126 ˚E and
another two points were set in the upper level (200 hPa), which were exactly at
the same longitude as the bottom.
Figure 11b showed that the low pressure at point 2 led the air to flow from
point 1 to point 2. The entropy in point 2 was slightly higher than in point 1 which
was due to the increase of mixing ratio from evaporation. It was noted that the
increase of mixing ratio had an effect to the increase of TC intensity. Due to the
pressure gradient, moist air in point 2 rose adiabatically to point 3 in the upper
level of the eye wall. At this point, entropy was higher than point 2. The
divergence of air in point 3 was driven by pressure differences between point 3
and 4. Heat lost during upper level outflow from point 3 to point 4 was due to
cooling radiation, thus, entropy in point 4 was smaller than in point 3. At the end
of the Carnot cycle, the ai