WES User Manual

3D/2D modelling suite for integral water solutions

Delft3D

WES

User Manual

WES

Wind Enhance Scheme for cyclone modelling

User Manual

Version: 3.01 SVN Revision: 68491

27 September 2021 WES, User Manual

Published and printed by: Deltares telephone: +31 88 335 82 73 Boussinesqweg 1 fax: +31 88 335 85 82 2629 HV Delft e-mail: [email protected] P.O. 177 www: https://www.deltares.nl 2600 MH Delft The Netherlands

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Copyright © 2021 Deltares All rights reserved. No part of this document may be reproduced in any form by print, photo print, photo copy, microfilm or any other means, without written permission from the publisher: Deltares. Contents

Contents

List of Figures v

List of Tables vii

1 A Guide to the manual1 1.1 Changes with respect to previous versions...... 1

2 Introduction 3 2.1 Functions and data flow of WES...... 3 2.2 Definition of the circular or the ‘spiderweb’ grid...... 4 2.3 Overview of the in- and output files...... 5

3 Getting Started7 3.1 How to run WES...... 7

4 Files description9 4.1 The main Input file <∗.inp> file...... 9 4.2 History points, <∗.xyn> file...... 9 4.3 Creating a track file <∗.trk> ...... 9 4.4 Possible input parameters with respect to the tropical cyclone intensity....9 4.5 The diagnostic file...... 10

5 Conceptual description 11 5.1 Brief description of Holland’s model...... 11 5.2 Further improvements to the original model...... 12 5.3 Conversion factors...... 13

6 The approach in WES 15 6.1 Method 1: computing wind and pressure fields from Vmax, A and B ..... 15 6.2 Method 2: computing wind and pressure fields from Vmax, R35, R50 and R100 15 6.3 Method 3: computing wind and pressure fields from Vmax, pdrop and Rw ... 16 6.4 Method 4: computing wind and pressure fields from Vmax, pdrop (Rw is not known)...... 16 6.5 Methods 5 and 6: Computing wind and pressure fields from Vmax and Rw (pdrop is not known)...... 16 6.5.1 Method 5: Computing wind and pressure fields from Vmax and Rw (pdrop is not known), pdrop based on empirical model based on US hurricane statistics...... 16 6.5.2 Method 6: Computing wind and pressure fields from Vmax and Rw (pdrop is not known), pdrop based on empirical model for Indian tropical cyclones...... 18 6.6 Method 7: computing wind and pressure fields from Vmax ...... 19

7 The approach in WES 21 7.1 Method 1: computing wind and pressure fields from Vmax, A and B ..... 21 7.2 Method 2: computing wind and pressure fields from Vmax, R35, R50 and R100 21 7.3 Method 3: computing wind and pressure fields from Vmax, Pdrop and Rw ... 22 7.4 Method 4: computing wind and pressure fields from Vmax, Pdrop (Rw is not known)...... 22 7.5 Methods 5 and 6: Computing wind and pressure fields from Vmax and Rw (Pdrop is not known)...... 22 7.5.1 Method 5: Pdrop based on empirical model based on US hurricane statistics...... 22 7.5.2 Method 6: Pdrop based on empirical model for Indian tropical cyclones 23

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7.6 Method 7: computing wind and pressure fields from Vmax ...... 24

8 Comparisons with observations 25 8.1 Comparison of Radius of Maximum Wind (Rw) and maximum wind speed.. 25 8.2 Comparison of Wind speed and direction with satellite data...... 27 8.2.1 QuickSCAT winds...... 27 8.2.2 ERS winds...... 30 8.2.3 Comparison of WES Winds with measured ground data...... 35

9 Comparison of different methods 37

10 Glossary of terms 39

References 41

A Description of used files 43 A.1 Description of the main input file for WES <∗.inp> ...... 43 A.2 History points, <∗.xyn> ...... 44 A.3 Description of the cyclone parameters in the track file, <∗.trk> ...... 45 A.4 Spiderweb file...... 46 A.5 Conversion Factors for wind speed...... 46 A.6 Common Errors and Suggested Solutions in WES...... 48

iv Deltares List of Figures

List of Figures

2.1 Tropical cyclone winds on a circular grid...... 4 2.2 Definition of the spiderweb grid...... 4

3.1 Screen shot from WES requesting the name of the main input file...... 7 3.2 Specifying the name of the main input file...... 7 3.3 Screen shot from WES while processing...... 8 3.4 Screen shot from WES showing error in running WES...... 8

5.1 Example of calculated wind speed for given A and B values...... 11 5.2 Asymmetric wind due to translation of the cyclone. Wind vectors ||⃗a|| > ||⃗b|| . 13

6.1 A and B value computed using two different methods...... 16 6.2 Left: Central pressure drop depicted agains maximum wind for 13 hurricanes in USA between 2000 – and 2005 data; Right: Comparison between the empirical relation to hurricane Ike data (data source: http://weather.unisys.com/hurricane)...... 17 6.3 Central pressure vs maximum wind for WES, HURDAT observations and Hol- lands’ P–W model and Dvorak for the dependent dataset (source: Holland (2008))...... 18 6.4 B as a function of Maximum wind speed (Vmax) for Indian tropical cyclones. 18

7.1 A and B value computed using two different methods...... 22 7.2 Left: Central pressure drop depicted agains maximum wind for 13 hurricanes in USA between 2000 – and 2005 data; Right: Comparison between the empirical relation to hurricane Ike data (data source: http://weather.unisys.com/hurricane)...... 23 7.3 Central pressure vs maximum wind for WES, HURDAT observations and Hol- lands’ P–W model and Dvorak for the dependent dataset (source: Holland (2008))...... 24 7.4 B as a function of Maximum wind speed (Vmax) for Indian tropical cyclones. 24

8.1 (from top to bottom) Comparison between the observed and computed Radius of Maximum Wind and maximum wind speed for Vizag, Kakinada, and Orissa Cyclones...... 26 8.2 QuickSCAT wind measured at 28/10/1999 (Orissa Cyclone - 05B). Black coloured wind barbs indicates rain contaminated data...... 27 8.3 Comparison of WES winds and direction with derived winds from QuickSCAT satellite for 4 different sectors (Orissa Cyclone)...... 28 8.4 Comparison of WES winds and direction with derived winds from QuickSCAT satellite for 4 different sectors (Cuddalore Cyclone)...... 29 8.5 Comparison of ERS and parametric wind speeds and directions (Method A) on three radial cross sections on 28/10/1999 at 0400 Z. Triangles represent ERS data, crosses model data...... 31 8.6 Comparison of ERS and parametric wind speeds and directions (Method B) on four radial cross sections on 28/10/1999 at 0400 Z. Triangles represent ERS data, crosses model data...... 32 8.7 Comparison of ERS and parametric wind speeds and directions (Method A) on four radial cross sections on 28/11/2000 at 0400 Z. Triangles represent ERS data, crosses model data...... 34 8.8 Comparison of ERS and parametric wind speeds and directions (Method B) on four radial cross sections on 28/11/2000 at 0400 Z. Triangles represent ERS data, crosses model data...... 35

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8.9 Comparison of WES generated wind speed and direction with ground observation...... 36

9.1 Computed Katrina wind speed on the 25th of August 2005 for 6 different methods in WES...... 38

A.1 Gust factors for cyclone wind speed (Curve C) as a function of time (Krayer and Marshall, 1992)...... 47

vi Deltares List of Tables

List of Tables

5.1 Wind conversion factor from 1 minute (60 sec) average to 10 minutes (600 sec) average from Harper et al. (2010)...... 13

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viii Deltares 1 A Guide to the manual

This user manual provides detailed information on running of WES program, version 3.3. To make this manual more accessible we will briefly describe the contents of each chapter and appendices.

Chapter 2: Introduction, provides an overview of the WES functions, area of applications and the software and hardware configurations of WES.

Chapter 3: Getting Started, gives a brief overview of the input files required, data flow within the program, the output files of the program and finally, the steps executed byWES.

Chapter 4: Files description, provides practical information of the model input files

Chapter 5: Conceptual description, describes the equations in WES.

Chapter 7: The approach in WES, describes a number of methods available in WES to generate the the wind and pressure fields.

Chapter 8: Comparisons with observations, comparison of numerical results and observations of 4 different tropical cyclones.

Chapter 9: Comparison of different methods, comparison of wind and pressure fields generated with different methods in WES.

Chapter 10: Glossary of terms, contains a list of terms and abbreviations used in this manual and their explanations.

References, provides a list of publications referenced by this manual.

Appendix A: Description of used files, gives a description of all the files that can be used in WES. This information is required for generating some files manually or by other means of other utility programs.

1.1 Changes with respect to previous versions

Version Description

3.32.01 Output on history points can now be generated.

3.32.00 Default of radius of maximum wind Rmax is changed from 13.5 [nmi] to 25[nmi]. Input file format of the -file is changed.

3.31.00 In 2014, the method of computation has been changed. In previous versions (3.30.01 and earlier), the translation speed is added to the computed winds which produced maximum wind speed that is higher than the maximum mean speed specified. In the latest version this translation speed is taken intoac- count prior to the computation. Therefore, when repeating the test cases described the resulting wind speed will be slightly lower than mentioned in this report.

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2 of 50 Deltares 2 Introduction

Accurate depiction of the inundation requires the accurate computation of the Storm Surge that again depends on the accuracy of the wind forcing it receives.

Tropical cyclone winds usually are accounted for in the Numerical Weather Prediction (NWP) data. However, the grid resolution used in these models is usually not sufficient to accurately represent the strong variations on the wind gradients near its centre due to low grid resolution. Furthermore, the deficiencies in the parameterisation of Cumulus Convection in NWP models do not bring out the tropical cyclone features in their true intensity and size. Hence, the wind and pressure in the tropical cyclone that are predicted by these models are generally underestimated. To overcome this difficulty, all meteorological agencies resort to supply some bogus data to bring out the tropical cyclone in the analysis. The methods used to generate winds are by Rankine Vortex or by generating some synthetic vortex or by the technique suggested by Holland(1980). The winds generated with this approach are geostrophic in nature. Asymmetry, which is usually encountered in the observed wind field, is brought out by vectorial addition of the translatory movement of the tropical cyclone. For the detailed description of this scheme we refer to chapter 8 of this document.

For storm surge simulations with Delft3D-FLOW, a Wind Enhance Scheme (WES) following Holland(1980) has been devised to generate tropical cyclone wind field. The program com- putes surface winds and pressure around the specified location of a tropical cyclone centre and given a number of tropical cyclone parameters (track data: i.e. maximum wind speed, pressure drop, radius of maximum wind and positions of the tropical cyclone). The tropical cyclone track data given by any Meteorological Agency can be taken by WES. However, JTWC, is the only agency that predicts sustained maximum winds at regular intervals.

The scheme was initially developed by the UK Met Office. Further improvements to the method have been applied to make the program more robust and yield more reliable and consistent results. The program also calculates the radius of the maximum winds offering a possibility to compare the output with Radius of Maximum Winds (Rmw) derived from radar and satellite observations.

The output of WES is suitable as input for Delft3D-FLOW and D-Flow FM, to simulate a storm surge.

2.1 Functions and data flow of WES The main functions and data flow of WES is to synthesize the tropical cyclone windand pressure drop on a circular or ‘spiderweb’ type grid (see Figure 2.1).

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Figure 2.1: Tropical cyclone winds on a circular grid

2.2 Definition of the circular or the ‘spiderweb’ grid For the synthesising of the tropical cyclone wind, an elegant technique has been adopted requiring data on a polar co-ordinate grid centred on the centre of the tropical cyclone (Stelling, 1999). On this, so-called ’spiderweb’ grid, the tropical cyclone wind and pressure fields are generated. The number of grid points in the spiderweb both in the radial and in the tangential direction is user specifiable. The radius of the tropical cyclone must be specified bytheuser. If the radius is changed, the grid cell size will vary according to number of grid cells specified.

Figure 2.2: Definition of the spiderweb grid

4 of 50 Deltares Introduction

2.3 Overview of the in- and output files Input files The following input files are needed to run WES: <∗.inp> file: This is the main input file for WES. The files contain information regarding input and output files and WES run options. <∗.trk> file: This file contains the tropical cyclone track information that is either created manually (by editing it) or by another separate program.

The ‘∗’ sign above represents arbitrary filename. It is advisable however to use a filename containing date and time stamp for all the files.

Output files WES produces the following output files: file: A file containing the synthesised tropical cyclone wind speed and pressure (drop) on a polar co-ordinate grid or the spiderweb grid (see detailed description in section A.6). file: A diagnostic or the log file containing the steps carried out by WES+ some intermediary results. It may also contain ERROR and WARN- ING messages from the program in case they occurred, so appropriate actions may be taken to correct them.

The name above represents the basename that is identical to the input filename contained in the <∗.inp> file.

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6 of 50 Deltares 3 Getting Started

3.1 How to run WES When invoking wes on the commandline, one may specify the input file <∗.inp> manually as the program argument. If not specified, it will ask you to specify this file name,see Figure 3.1.

Figure 3.1: Screen shot from WES requesting the name of the main input file

Type the file name as indicated in Figure 3.2.

Figure 3.2: Specifying the name of the main input file

Once the input file is given, the details of the input files are read and processed.

The screen shots of WES when running is given, Figure 3.3.

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Figure 3.3: Screen shot from WES while processing

The detailed information regarding the processed input can also be seen in one of the output files of WES <∗.dia>.

If there are any errors in the input file WES will stop and it will generate the message “Abnor- mal end of the program” (see Figure 3.4).

Figure 3.4: Screen shot from WES showing error in running WES

If no error is encountered, WES will produce the output files: file and .

8 of 50 Deltares 4 Files description

4.1 The main Input file <∗.inp> file The main input file must be available describing the options for running WES (e.g. the details about the spiderweb grid size, the required extent of the diagnostic file - brief or detailed, etc.). For a detailed description of all the parameters in the <∗.inp> file, see section A.1.

4.2 History points, <∗.xyn> file History points are defined by their location. The locations need to be specified bytheir spherical coordinates (longitude, latidude: λ, ϕ) and their name in a file, preferred extension <*.xyn>. For these points time series are written to the diagonostic file for windspeed [knots] and nautical direction [degrees].

Example:

269.632 30.050 'EastBank1' 270.043 29.263 'GrandIsle' 270.593 28.932 'PilotsStEast' 270.56 30.282 'Waveland' 269.582 29.777 'WestBank1'

For a detailed description of file <∗.xyn> file, see section A.2.

4.3 Creating a track file <∗.trk> This file may be edited manually. This file contains the main information on the tropical cyclone parameters: ⋄ the initial and predicted positions of the storm centre (in geographical co-ordinates), ⋄ the direction and speed of movement of the storm centre during the previous 6 hours, ⋄ the intensity of the storm in terms of associated maximum winds and the corresponding pressure drop in Pascal.

For a detailed description of all the parameters in the <∗.trk> file, see section A.3

4.4 Possible input parameters with respect to the tropical cyclone intensity The important input parameters for WES that determines the tropical cyclone wind intensity are: A This parameter along with the parameter B below, determines the radius at which maximum wind speeds occur. It is very unlikely that the value of this parameter is known. B This parameter determines the shape of the wind and pressure profile as a function of distance from the storm centre. In some regions B has been determined from climatological data and you may wish to use this value. In the modified form, the B is calculated from Vmax, which can vary from day to day in a given tropical cyclone. Hence B value not kept constant between the initial and predicted intensities of tropical cyclone. Vmax The maximum sustained wind in the tropical cyclone [knots]. This parameter is compulsory. It is estimated from satellite data and other observed data.

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Rmax The radius of maximum sustained wind in the tropical cyclone ([nmi]) associated with the parameter Vmax mentioned earlier. When not specified then a default value of 25 [nmi] will be assumed. pdrop Represents the difference between the ambient and central pressures [hPa]. This parameter is estimated from√ satellite images, or may be computed using the following relation Vmax = C pdrop (see chapter 8). In some cases pdrop and Vmax will be the only pieces of data available. Radius of 35, 50 & 100 knots wind These parameters are estimated from observations and are reported in JTWC bulletins.

These parameters are to be specified in a certain combination in order to allow WES topro- duce the desired output (see chapter 7).

The values for the parameters described above may be obtained from tropical cyclone advisories produced by JTWC, UKMO, IMD, JMA or any other Meteorological institutes in the world. In all advisories, the present and forecast positions of the tropical cyclones are given. The tropical cyclone intensity parameter however is only specified in the JTWC (Hawaii) advisory in the form of prevailing and forecast maximum winds or in the IMD tropical cyclone bulletins as prevailing tropical cyclone intensity (specified in categories). Specifying the positions, the prevailing and the expected wind speeds and pressure drops information are sufficient to synthesise the tropical cyclone winds. In this case certain assumptions havetobe made about the model parameters (see chapter 8).

JTWC advisory also contains information on the present and expected radius of 100 knots wind (R100), 50 knots wind (R50), and 35 knots wind (R35) as a function of position (c.q. time). In this case the assumptions mentioned earlier are not required and WES can use the above radii in order to find an optimal fitting of the synthesised winds to the observed values. When not available or not used the related columns for these parameters in the -file must be filled with the “Missing Index” value= ( 1.0 × 1030).

A detailed description of the <∗.trk> file is given in Appendix A.3. Also of importance is the explanation on how WES will treat the different options and when redundant information is specified in this file.

4.5 The diagnostic file The diagnostic file (<∗.dia>): In the <∗.inp> file, the option EXTENDED_REPORT enables the user to specify whether an extended diagnostics are to be produced or not. Extended diagnostics include process-logging, extensive error and warning messages, etc. Compact diagnostic will only contain process-logging and main error messages. If the user mentions “YES” for EXTENDED_REPORT, extended diagnostics will be produced else compact diagnostics will be produced.

In the extended mode the following information are dumped to the diagnostic file. 1 The contents of the input file, <∗.inp>-file. 2 The contents of tropical cyclone track file, <∗.trk>, read including the computed constants and parameters such as A, B and pdrop, the pressure drop for different time step. 3 Summary of data in the spiderweb file for Delft3D, which consists of date and time ofthe tropical cyclone position, maximum wind speed in [knots], its direction and radius of the maximum winds and direction in which it occurs.

10 of 50 Deltares 5 Conceptual description

Cyclone wind fields are generated around the given centre positions of the storm, following Holland’s method in order to obtain the wind and pressure fields (above sea surface) ona high-resolution grid. The parametric model that has been adopted in WES is based upon Holland(1980). And it has been improved slightly by introducing asymmetry. This asymmetry is brought about by applying the translation speed of the cyclone centre displacement as steering current and by introducing rotation of wind speed due to friction.

This model has basically five parameters: 1 the location of the cyclone centre, 2 the radius of maximum wind, 3 the maximum wind speed, 4 the central pressure and 5 the current motion vector of the vortex.

5.1 Brief description of Holland’s model

Following Holland, the geostrophic wind speed Vg of a cyclone is expressed as: q rf V (r) = ABp exp(−A/rB)/ρrB + r2f 2/4 − (5.1) g drop 2 where r distance from the centre of the cyclone, f Coriolis parameter, ρ density of air (assumed to be constant equal to 1.10 kg m−3), pdrop = pn − pc

pn ambient pressure (theoretically at infinite radius, however in this model the average pressure over the model domain is used) pc central pressure, A, B parameters.

Wind speed as functions of A & B

100.00 B= 1.75 A= 5.00E+06 B= 1.5 A= 5.00E+06 B= 1.25 A= 5.00E+06 B= 1.25 A= 1.00E+06 75.00 B= 1.25 A= 5.00E+05

50.00 W speed ind (m /s) 25.00

0.00 0 50000 100000 150000 200000 250000 300000 Distance (m)

Figure 5.1: Example of calculated wind speed for given A and B values

Parameters A and B are determined empirically. Physically parameter A determines the relation of the pressure or wind profile relative to the origin, and parameter B defines the shape of the profile, see Figure 5.1. Holland states that for plausible ranges of central and

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ambient pressures and radii of maximum wind speeds B is constrained to be between 1 and 2.5.

In the region of maximum winds the Coriolis force is small in comparison to the pressure gradi- ent and centrifugal forces, and therefore the air is in cyclostrophic balance. The cyclostrophic wind Vc at a distance r in this region is given by: q B B Vc(r) = AB(pdrop) exp(−A/r )/ρr (5.2)

By setting d Vc/dr = 0, the radius of maximum winds (Rw) can be obtained and is given as follows:

1/B Rw = A (5.3)

The Rw is independent of the relative values of ambient and central pressure and it is defined entirely by the scaling parameters A and B. Substituting Equation (5.3) back into Equa- tion (5.2) yields an expression for the maximum wind speed as follows: q Vmax = Bpdrop/ρ e (5.4)

where e is the base of the natural logarithm (=2.71828. . . ).

Parameters A and B can now be expressed as functions of measurable quantities as follows:

B A = Rw (5.5) ρ e V 2 B = max (5.6) pdrop

and the central pressure drop is given by ρ e V 2 p = max (5.7) drop B

By substituting equations 5.5 and 5.6 into equation 5.1 we can also express the geostrophic wind Vg as function of Rw:

p rf V (r) = (R /r)BV 2 exp(1 − (R /r)B) + r2f 2/4 − (5.8) g w max w 2 The equations above are valid for geostrophic winds. Before deriving A and B the wind speed and pressure values are now scaled to their geostrophic values.

5.2 Further improvements to the original model After determining the values of parameter A and B, the cyclone winds as a function of distance r and direction θ on a spiderweb like grid can be computed. The computed winds are then adjusted to account for the asymmetry introduced by the interaction of the cyclone with the steering flow (Chan and Gray, 1982) by adding the translatory movement of the cyclone to the existing wind field. On the northern hemisphere this vectorial addition increases the winds on the right hand side of the direction of the cyclone movement and reduces the winds on the left hand side and the other way around on the southern hemisphere, see Figure 5.2, so bringing out an asymmetry in the wind field.

12 of 50 Deltares Conceptual description

Cyclone track Cyclone track

b Northern hemisphere Southern hemisphere

Figure 5.2: Asymmetric wind due to translation of the cyclone. Wind vectors ||⃗a|| > ||⃗b||

The wind direction (northern hemisphere) is rotated 20◦ in the anti clock-wise (cyclonic) direction so that the wind spirals in towards the centre (Shea and Gray, 1973) to account for the frictional effects. Also for the same reason a reduction factor of 0.7 is applied for the geostrophic wind to generate winds at 10 meters above mean sea level. For wind speed this involves a multiplication by a factor represented by Preduce, and for pressure drop divided by 2 1 Preduce. Preduce is currently set to 0.7, the appropriate value over water .

5.3 Conversion factors Any wind speed that is mentioned in the advisories and or computed by the NWP models is defined as wind speed that has been averaged over a certain period of time. Forexample, JTWC advisory mentions wind speeds that are based on 1-minute average while the IMD uses the wind speed based on 3-minutes average. For storm surge simulations, at least 10 minute average winds should be applied.

To allow a specification of maximum wind speed, Vmax, originating from any sources and in order to enable WES to compute wind speed in consistent manner for your use, a conversion factor is introduced. It is used to convert maximum wind speed specifiedy ( -minute averaged, input) in the (input) track file to the required, x-minute, averaged (output) wind data required by the user.

Conversion factor from 1 minute average to 10 minutes average for different areas can be obtained by Harper et al. (2010) which for convenience has been copied below:

Table 5.1: Wind conversion factor from 1 minute (60 sec) average to 10 minutes (600 sec) average from Harper et al. (2010).

Vmax600 = KVmax60 At-Sea Off-Sea Off-land In-land K 0.93 0.90 0.87 0.84

As in Delft3D no distinction is made between land and sea, a value between 0.9 and 0.93 is recommended.

Another way to determine the conversion value is by determining the inverse ratio of the Gust factor for those averaging periods respectively. For a detailed overview and treatment of the Gust factor and the conversion factor we refer to section A.4.

1WES does not account for frictional effects of land

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14 of 50 Deltares 6 The approach in WES

Equation (5.8) synthesises cyclonic winds assuming that the values of parameters A and B are known. However, in practical situation these parameters are usually not directly available. Consequently, in operational / forecast mode the tropical cyclone winds and pressure field is computed based on (measured/observed/forecast) physical quantities that are reported in the tropical cyclone advisories: Vmax, Rw, Pressure drop and or Radius of 100, 65, 50 and 35 knots wind (if and when the wind exceeds the associated speed).

Unfortunately cyclone advisories originating from different meteorological agencies do not contain identical information for which a standard procedure can be developed. Below we summarise the contents of some of the advisories: ⋄ Cyclone advisories from UK Met Office contain the present and 72 hours forecast ofthe cyclone positions accompanied by a qualitative description of the changes in the cyclone strength (intensifying, weakening etc.). ⋄ JTWC advisories contains the present and 48 hours forecast of the cyclone positions accompanied by a quantitative description of the cyclone strength with the help of four parameters:

1 Maximum sustainable winds (Vmax) at present positions, 2 Radius of 35 knots wind (R35) at present and future positions, 3 Radius of 50 knots wind (R50) at present and future positions and 4 Radius of 100 knots wind (R100) at present and future positions. ⋄ IMD advisories contain the present and 36 hours forecast positions of the tropical cyclone and a qualitative description of the changes in its strength (intensifying, weakening etc.) ⋄ In all advisories the present tropical cyclone translation speed and its direction are mentioned.

The method to compute the wind and pressure fields in WES depends on the tropical cyclone parameters specified and is described below.

6.1 Method 1: computing wind and pressure fields from Vmax, A and B

In case the parameters A, B and Vmax are specified, then the wind and pressure fields can directly be computed using equations Equation (5.7) and Equation (5.8).

6.2 Method 2: computing wind and pressure fields from Vmax, R35, R50 and R100

The available data (wind speed associated with R35, R50 and R100), together with Vmax, can been used to fit Equation (5.1) with these parameters and obtain the appropriate values of A and B. The value of Rw is then determined from Equation (5.3).

The method described here has been tested on a number of tropical cyclones in India and Vietnam. As an example Figure 7.1 shows the results in one of the case tested namely the Orissa Cyclone (05B) – 1999. The method is found to produce consistent result when at least 3 out of 4 values of R35, R50 and R100 are available (i.e. in case of a strong tropical cyclone). Otherwise the method is less dependable.

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Figure 6.1: A and B value computed using two different methods

6.3 Method 3: computing wind and pressure fields from Vmax, pdrop and Rw

If all the three parameters Vmax, pdrop and Rw are known then the tropical cyclone wind field can be easily computed using Equations 5.5, 5.6 and 5.8.

However, usually these parameters are not available all at the same time. So the following solutions are available in WES (see next sections).

6.4 Method 4: computing wind and pressure fields from Vmax, pdrop (Rw is not known)

If the value of Rw is not known or specified then a default value of 25 km for Rw will be assumed.

6.5 Methods 5 and 6: Computing wind and pressure fields from Vmax and Rw (pdrop is not known) When the pressure drop is not specified two methods can be applied:

1 pdrop based on empirical model based on US hurricane statistics. 2 pdrop based on empirical model for Indian tropical cyclones.

6.5.1 Method 5: Computing wind and pressure fields from Vmax and Rw (pdrop is not known), pdrop based on empirical model based on US hurricane statistics Based on data of 13 hurricanes (Ida, Bill, Hannah, Gustav, Dolly, Dean, Dennis, Emily, Katrina, Rita, Wilma, Charley and Ivan1); that occurred in USA between the year 2000 and 2005, we have derived an empirical relation between the pressure drop and quadrate of maximum wind speed (as suggested by Equation (5.7)). This empirical relation reads (See Figure 7.2 left):

2 pdrop = 2Vmax (6.1)

Substituting this to Equation (5.7) yields a B value equal to: 1 B = ρ e = 1.563. (6.2) 2

1source: http://weather.unisys.com/hurricane

16 of 50 Deltares The approach in WES

Wind speed and Pdrop relation y = 2x2 20000 Wind speed and Pdrop relation EMPIRICAL RELATION 10000 WES derived relation ALL (excl. IKE) IKE Power (EMPIRICAL RELATION) 2 15000 y = 2x Power (WES derived relation)

10000 6000 P drop (Pa) ressure Pressure drop (Pa) drop Pressure

5000

2000 0 30 50 70 0 20 40 60 80 100 Wind Speed (m/s) Wind speed (m/s)

Figure 6.2: Left: Central pressure drop depicted agains maximum wind for 13 hurricanes in USA between 2000 – and 2005 data; Right: Comparison between the empirical relation to hurricane Ike data (data source: http://weather.unisys.com/hurricane).

This relation is applied to data from Hurricane Ike (see Figure 7.2 right) seems to system- atically underestimate the pressure drop for winds < 50 m/s and slightly overestimate the pressure (drop) for wind speed > 50 m/s. Lower wind speed in this graph depicts the winds after the 8th of September. The systematic bias during this period may be caused by the fact that the ambient pressure during the last stages of Ike is slightly lower than 1010 mbar.

Once the value of B is determined, subsequently, the value of pdrop can be determined.

Holland(2008) devised a new empirical relation for relating maximum winds to central pressure in tropical cyclones. He determined a derivative of the Holland B parameter, Bs, which relates the pressure drop directly to surface winds. This parameter Bs is a function of pressure drop at the centre of the tropical cyclone, intensification rate, latitude, and translation speed.

To compare the empirical relation given by Equation (7.1) to the recent Hollands findings, Figure 7.3 is presented.

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Figure 6.3: Central pressure vs maximum wind for WES, HURDAT observations and Hol- lands’ P–W model and Dvorak for the dependent dataset (source: Holland (2008))

6.5.2 Method 6: Computing wind and pressure fields from Vmax and Rw (pdrop is not known), pdrop based on empirical model for Indian tropical cyclones The following empirical method has been devised after investigating a number of tropical cyclones in the Bay of Bengal as an option after the observation that method 2 often fails to produce a reliable result, due to limited number of parameters.

The method is based on practice applied by IMD that uses a constant value to relate the maximum sustained wind speed with the pressure drop. The value of B is subsequently determined by fitting the data from a number of tropical cyclone occurring in India. This relation is described by a linear function where B is set equal to 1.18 for 20 knot winds (approximately 10 m/s). It linearly increases towards a value of 1.55 for wind speed equals 150 knots (approximately 77 m/s; see Figure 7.4). Once the value of B is determined, subsequently, the value of pdrop can be determined.

B = Vm2 ?e / pd 1.352308 2.50 B derived directly form hindcast data B as a function of wind speed used in WES 2.25

2.00

1.75B

1.50

1.25

1.00 0 10 20 30 40 50 60 70 80 Wind speed (m/s)

Figure 6.4: B as a function of Maximum wind speed (Vmax) for Indian tropical cyclones

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For A, a value between 4.1 · 106 and 4.2 · 106 has been applied. An example of the result is shown in Figure 7.1 for the Orissa Cyclone (05B) – 1999 test case.

6.6 Method 7: computing wind and pressure fields from Vmax

The only data used in this method is the maximum wind speed Vmax. Through some error minimisation procedure the value of A and Rw is determined. However this method is proven not to be robust and is only maintained in WES for backward compatibility reason. The use of this method is no longer recommended.

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20 of 50 Deltares 7 The approach in WES

Equation (5.8) synthesises cyclonic winds assuming that the values of parameters A and B are known. However, in practical situation these parameters are usually not directly available. Consequently, in operational/forecast mode the tropical cyclone winds and pressure field is computed based on (measured/observed/forecast) physical quantities that are reported in the tropical cyclone advisories: Vmax, RW , Pressure drop and or Radius of 100, 65, 50 and 35 knots wind (if and when the wind exceeds the associated speed).

The method to compute the wind and pressure fields in WES depends on the tropical cyclone parameters specified and is described below.

7.1 Method 1: computing wind and pressure fields from Vmax, A and B

In case the parameters A, B and Vmax are specified, then the wind and pressure fields can directly be computed using equations Equation (5.7) and Equation (5.8).

7.2 Method 2: computing wind and pressure fields from Vmax, R35, R50 and R100

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Figure 7.1: A and B value computed using two different methods

7.3 Method 3: computing wind and pressure fields from Vmax, Pdrop and Rw

If all the three parameters Vmax, Pdrop and Rw are known then the tropical cyclone wind field can be easily computed using Equations 5.5, 5.6 and 5.8.

However, usually these parameters are not available all at the same time. So the following solutions are available in WES (see next sections).

7.4 Method 4: computing wind and pressure fields from Vmax, Pdrop (Rw is not known)

If the value of Rw is not known or specified then a default value of 25 km for Rw will be assumed.

7.5 Methods 5 and 6: Computing wind and pressure fields from Vmax and Rw (Pdrop is not known) When pressure drop is not specified two methods can be applied:

7.5.1 Method 5: Pdrop based on empirical model based on US hurricane statistics Based on data of 13 hurricanes (Ida, Bill, Hannah, Gustav, Dolly, Dean, Dennis, Emily, Katrina, Rita, Wilma, Charley and Ivan1); that occurred in USA between the year 2000 and 2005, we have derived an empirical relation between the pressure drop and quadrate of maximum wind speed (as suggested by Equation (5.7)). This empirical relation reads (See Figure 7.2 left):

2 Pdrop = 2Vmax (7.1)

1source: http://weather.unisys.com/hurricane

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Substituting this to Equation (5.7) yields a B value equal to: 1 B = ρ e = 1.563. (7.2) 2

10000 6000 P drop (Pa) ressure Pressure drop (Pa) drop Pressure

5000

2000 0 30 50 70 0 20 40 60 80 100 Wind Speed (m/s) Wind speed (m/s)

Figure 7.2: Left: Central pressure drop depicted agains maximum wind for 13 hurricanes in USA between 2000 – and 2005 data; Right: Compari- son between the empirical relation to hurricane Ike data (data source: http://weather.unisys.com/hurricane).

Once the value of B is determined, subsequently, the value of Pdrop can be determined.

To compare the empirical relation given by Equation (7.1) to the recent Hollands findings, Figure 7.3 is presented.

7.5.2 Method 6: Pdrop based on empirical model for Indian tropical cyclones The following empirical method has been devised after investigating a number of tropical cyclones in the Bay of Bengal as an option after the observation that method 2 often fails to produce a reliable result, due to limited number of parameters.

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Figure 7.3: Central pressure vs maximum wind for WES, HURDAT observations and Hol- lands’ P–W model and Dvorak for the dependent dataset (source: Holland (2008))

B = Vm2 ?e / pd 1.352308 2.50 B derived directly form hindcast data B as a function of wind speed used in WES 2.25

2.00

1.75B

1.50

1.25

1.00 0 10 20 30 40 50 60 70 80 Wind speed (m/s)

Figure 7.4: B as a function of Maximum wind speed (Vmax) for Indian tropical cyclones

proximately 77 m/s; see Figure 7.4). Once the value of B is determined, subsequently, the value of Pdrop can be determined.

For A, a value between 4.1E+06 and 4.2E+06 has been applied. An example of the result is shown in Figure 7.1 for the Orissa Cyclone (05B) – 1999 test case.

7.6 Method 7: computing wind and pressure fields from Vmax

24 of 50 Deltares 8 Comparisons with observations

For comparison with observations (or derived parameters from observations) the following tropical cyclones and parameters have been selected.

Tropical cyclone Parameter(s) compared

Name Id Year Month Radius of Wind speed Ground ob- Wind speed Max. wind & direc- servation & direction and Max. tion profile (wind speed (statistic – Wind speed (QuickSCAT & direction) ERS data) data)

Visakhapatnam (Vizag) 05B 1994 Nov ✓ - - - Kakinada 05B 1996 Nov ✓ - - - Orissa 05B 1999 Oct ✓ ✓ ✓ ✓ Cuddalore 03B 2000 Nov - ✓ - ✓

When comparing the computed wind with observation data, it is important to bear in mind that the tropical cyclone centre is usually given in latitude and longitude up to a tenth of a degree. So due to round off error the actual positions may actually differ up to ± 5 km from the specified point. This might introduce discrepancies in the results when compared tothe observed values, especially in the region where wind gradients are high.

8.1 Comparison of Radius of Maximum Wind (Rw) and maximum wind speed

The radius of maximum wind (Rw) and the maximum wind speed data originates from JTWC tropical cyclone bulletins and IMD RSMC report. Methods 2 and 6 (see chapter 7) was subsequently adopted to synthesise the tropical cyclone winds. The resulting wind speed was then compared with the data.

Rw can also be compared against the radius of maximum reflectivity (Rmr) which can be measured by radar (Rmr is a measure of Rw).

The JTWC provides two values for radii for 35, 50 and 100 knots winds in their bulletin. One number represents the value for the north-eastern semicircle and the other one for remaining areas. In the computation of the wind an average of these two values has been used. Fur- thermore the bulletins are issued every 12 hours. To compute the wind field for every 6 hours interpolation of these values have been applied.

Figures 8.1a to 8.1c depict the plots of radius of maximum wind and the maximum wind speed during the life cycle of the tropical cyclone from the Vizag-1998, Kakinada-1996 and Orissa- 1999 cyclones.

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(a) Cyclone Vizag (1998)

(b) Cyclone Kakinada (1996)

Figure 8.1: (from top to bottom) Comparison between the observed and computed Ra- dius of Maximum Wind and maximum wind speed for Vizag, Kakinada, and Orissa Cyclones

In Figure 8.1c, the Orissa Cyclone case, the radius of maximum wind (Rw) gradually de- creased from a value of 42 km on the 26th October to a value of 7.5 km on the 29th October when the tropical cyclone reached its peak intensity. The radius of maximum wind increases after the tropical cyclone made landfall and became weaker. The triangles shown in the diagram represents the Rmr values measured by the radar at Paradip and the squares in the diagram represents 0.5 times of the eye diameter (= radius of the eye). The reported accuracy of the observed data is represented in the figures by an error bar. The agreement with Rmr and Rw in this case is remarkably good. Similar holds for the computed maximum wind speed, especially for the winds computed using method A. Figures 8.1a and 8.1b represent

26 of 50 Deltares Comparisons with observations

the diagrams for Vizag and Kakinada cyclones. Similar conclusion can be drawn for the Vizag cyclone case. The Rw values in the Kakinada cyclone case however, are slightly larger than the reported Rmr value.

8.2 Comparison of Wind speed and direction with satellite data As long as the tropical cyclone is at the ocean comparison of model result with observations has to rely on winds derived from the satellite data, as conventional observations are hardly available over the oceans. Fortunately, ERS satellite and more recently QuickSCAT derives wind data from scatterometer data, despite some limitations. The accuracy of the winds is claimed to be 1.4 m/s up to the speeds of 20 m/s and an accuracy of 10 % beyond that. The maximum measurable speeds with the scatterometer are 50 knots (≈ 25 m/s). Hence, at higher wind speeds comparison cannot be made. This QuickSCAT data from the year 1999 onwards is available at the site1.

8.2.1 QuickSCAT winds WES computed winds has been compared with QuickSCAT data for the Orissa cyclone (26-30 Oct, 1999) and Cuddalore Cyclone (27–29 Nov, 2000). The comparison is made by printing out the graphs that have been downloaded from the above referred internet site and reading the wind speed and direction visually.

Figure 8.2: QuickSCAT wind measured at 28/10/1999 (Orissa Cyclone - 05B). Black coloured wind barbs indicates rain contaminated data.

Despite the fact that this method of comparison is imperfect and very error prone, it is never- theless useful to check the main characteristics of the wind fields produced. An example plot of QuickSCAT observed data is depicted in Figure 8.2c for the Orissa Cyclone case.

1http://manati.wwb.noaa.gov/cgi-bin/qscat_day-1.pl

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Figure 8.3: Comparison of WES winds and direction with derived winds from QuickSCAT satellite for 4 different sectors (Orissa Cyclone)

The following figures depicts 4 cross-sections of the wind derived with WES. The wind speeds and direction of the winds from QuickSCAT data are shown in each diagram at the appropriate points. Figures 8.3 and 8.4 shows the wind speed and direction at 28th October, 1999-12UTC (Orissa Cyclone) and 28th November, 2000-12UTC (Cuddalore Cyclone). There is a very good agreement for wind speeds and wind directions in most of the cross-sections.

The results of WES, especially the wind speed in the Orissa case and the wind direction in the Cuddalore case show good agreements with the satellite observations. Especially when we bear in mind that the comparison has been done by estimating the wind speed and direction visually from a printed graph and the fact in some occasion the wind measured was contaminated due to rainfall.

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Figure 8.4: Comparison of WES winds and direction with derived winds from QuickSCAT satellite for 4 different sectors (Cuddalore Cyclone)

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8.2.2 ERS winds Comparison with ERS winds are carried out in a different manner as we had direct access to the measured data (provided by the UK Met. Office). Therefore we could compare the computed results with observation points at the exact locations. Furthermore, statistical com- putations were possible. In the following figures and tables the comparison of the WES results, both using method A and B, with the observed ERS derived winds are presented. When inter- preting the figures and tables below please note that the maximum measurable speedswith the ERS are 50 knots (≈ 25 m/s). Hence, winds at higher speeds were not included in the analysis.

Orissa case – Method 2 (using JTWC advisories containing R35, R50 and R100)

A = 6.5 × 106 B = 1.46 (8.1)

Vmax = 39 m/s pdrop = 31.2 hP a Rw = 46.5 km (8.2)

Number of Max distance Mean wind RMS wind Mean wind RMS wind observa- from tropical speed er- speed er- direction direction tion points cyclone cen- ror ror error error tre (km) (m/s) (m/s) (degrees) (degrees)

0 100 n.a n.a n.a n.a 26 200 -3.3032 3.4498 8.4202 10.8345 108 300 -0.945 2.1533 6.9905 9.8197 245 400 0.696 2.5343 4.5498 10.2488 389 500 1.2626 2.6822 2.005 13.1879

Orissa case – Method 6 (using IMD data; Vmax and pdrop)

A = 4.04 × 106 B = 1.33 (8.3)

Vmax = 41.5 m/s pdrop = 38.7 hP a Rw = 16.5 km (8.4)

0 100 n.a n.a n.a n.a 26 200 -5.93 6.06 7.95 11.14 107 300 -2.99 3.73 5.58 8.79 243 400 -1.00 2.92 3.75 9.97 381 500 -0.17 2.69 1.79 13.18

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Figure 8.5: Comparison of ERS and parametric wind speeds and directions (Method A) on three radial cross sections on 28/10/1999 at 0400 Z. Triangles represent ERS data, crosses model data

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Figure 8.6: Comparison of ERS and parametric wind speeds and directions (Method B) on four radial cross sections on 28/10/1999 at 0400 Z. Triangles represent ERS data, crosses model data

Cuddalore case – Method 2 (using JTWC advisories containing R35, R50 and R100)

A = 6.47 × 106 B = 1.44 (8.5)

Vmax = 26.0 m/s pdrop = 14.0 hP a Rw = 54.5 km (8.6)

28 100 -5.1043 7.7524 9.6597 34.9876 106 200 -1.6102 4.2264 11.7438 23.7 234 300 0.1976 3.2852 8.9879 18.092 409 400 1.2197 3.1091 6.2995 16.9551 627 500 1.8009 3.1167 4.9857 16.411

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Cuddalore case – Method 6 (using IMD data; Vmax and pdrop)

A = 4.23 × 106 B = 1.37 (8.7)

Vmax = 50.4 m/s pdrop = 55.4 hP a Rw = 12.5 km (8.8)

33 100 -7.60 9.08 -2.27 54.71 118 200 -2.83 4.96 5.33 34.14 253 300 -0.98 3.55 4.45 25.22 439 400 0.04 2.94 2.77 22.25 643 500 0.62 2.73 2.47 20.38

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Figure 8.7: Comparison of ERS and parametric wind speeds and directions (Method A) on four radial cross sections on 28/11/2000 at 0400 Z. Triangles represent ERS data, crosses model data

34 of 50 Deltares Comparisons with observations

Figure 8.8: Comparison of ERS and parametric wind speeds and directions (Method B) on four radial cross sections on 28/11/2000 at 0400 Z. Triangles represent ERS data, crosses model data

Based on the figures above one might conclude that both the methods used by WES toderive the tropical cyclone winds are comparable. However, when the maximum winds are compared than a slightly better result is obtained by applying Method 6. The agreement between the derived wind directions with the observed data is reasonably accurate.

The derived wind speed is quite accurate up to approximately 12 m/s. Deviations along some cross-sections then increase up to 7 m/s on average for the wind speed values between 12 and 25 m/s. Similar to the QuickSCAT case we were not able to determine the rain contami- nation in the measured data.

8.2.3 Comparison of WES Winds with measured ground data Some surface wind speeds during Orissa cyclone (05B) – 1999 originating from ground observations has been collected from IMD Hyderabad Met. Office for comparison purposes. The results are shown in Figure 8.9. From the figures it is clear that the WES winds are ableto

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reproduce the surface wind measurements with sufficient degree of accuracy. One exception forms the results at Puri. However when a location slightly North of Puri is selected then the results are again quite good.

Figure 8.9: Comparison of WES generated wind speed and direction with ground observation

36 of 50 Deltares 9 Comparison of different methods

The different methods to compute the wind and pressure fields in WES that is made available in WES will produce results that differs marginally from each other.

For instance, when reproducing the Katrina hurricane winds on 28th of August 2005 1200 UTC we have applied the 7 different methods with the following parameter values:

Method Vmax Rmax R_100 R_65 R_50 R_35 B A Pd [nmi] [nmi] [nmi] [nmi] [nmi] [Pa]

1 145 - - - - - 1.20 2E+05 - 2 145 14 28 75 118 188 - - - 3 145 14 ------10600 4 145 ------10600 5 145 ------6 145 ------10600 7 145 ------

The results are depicted in Figure 9.1, along with H*winds model output1 and observed data2. Based on the results we can conclude that for this specific case, method 7 shouldn’t be used 3 at all . For this specific case, Method 3 (or 4 where Rmax is set to a default value of 12.5 nautical miles) performs the best.

Furthermore, as expected, the asymmetry feature in WES due to interaction with land mass is poorly represented. WES is, by design, (not yet) capable of including the effect of land mass.

1See http://www.aoml.noaa.gov/hrd/data_sub/wind.html 2See http://tidesandcurrents.noaa.gov/ 3As mentioned earlier only available in WES for backward compatibility reason

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Figure 9.1: Computed Katrina wind speed on the 25th of August 2005 for 6 different methods in WES

38 of 50 Deltares 10 Glossary of terms IMD India Meteorological Department JMA Japanese Meteorological Agency JTWC Joint Typhoon Warning Centre NWP Numerical Weather Prediction NOAA National Oceanic and Atmospheric Administration of teh United States AOML Atlantic Oceanographic and Meteorological Laboratory - on eof the facilities of NOAA PC Personal Computer QuickSCAT A polar orbiting satellite carrying a scaterometer; the data from this satellite can measured winds up to 40 knots. ERS European Remote Sensing satellite UKMO United Kingdom Meteorological Office WES Wind Enhance Scheme

dia Standard file name extension used for WES Diagnostic file hPa unit for pressure (hecto)Pascal inp Standard file name extension used for WES input file kts unit for wind magnitude in Knots spw Standard file name extension used for WES Spiderweb file trk Standard file name extension used for WES Track file H*wind Tropical cyclone wind and pressure data obtained from H*Wind Project (Hurricane Research Division of AOML/NOAA). The data is based on an integrated tropical cyclone observing system in which wind measurements from a variety of observation platforms are used to develop an objective analysis of the distribution of wind speeds in a hurricane.

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40 of 50 Deltares References

Chan, J. and W. Gray, 1982. “Tropical cyclone movement and surrounding flow relationships.” Monthly Weather Review 110: 1354–1374.

D-Flow FM UM, 2015. D-Flow FM Hydro- and Morphodynamics User Manual. Deltares, 1.1.124 ed.

Delft3D-FLOW UM, 2013. Delft3D-FLOW User Manual. Deltares, 3.14 ed.

Harper, B. A., J. D. Kepert and J. D. Ginger, 2010. “Guidelines for Converting between Various Wind Averaging Periods in Tropical Cyclone Conditions.” WMO WMO/TD-No. 1555.

Holland, G., 1980. “An Analytical Model of the Wind and Pressure Profiles in Hurricanes.” Monthly Weather Review 108: 1212–1218.

Holland, G., 2008. “A Revised Hurricane Pressure–Wind Model.” Monthly Weather Review 136: 3432–3445.

Krayer, W. and R. Marshall, 1992. “Gust Factors Applied to Hurricane Winds.” Bulletin Ameri- can Met. Society 73:5.

Shea, D. and W. Gray, 1973. “The Hurricane’s Inner Core Region I. Symmetric and Asymmet- ric Structure.” Journal of the Atmospheric Sciences 30: 1544–1564.

Stelling, G. S., 1999. Internal note on Cyclone modelling. Tech. rep., WL | Delft Hydraulics, Delft, The Netherlands.

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42 of 50 Deltares A Description of used files

A.1 Description of the main input file for WES <∗.inp> Sample Input file for WES< ( name.inp>).

comment = WES run comment = This file is created on 200009281600UTC comment = Grid Delft3D file 259 by 129 cyclone_par._file = d:\WES\Orissa_cyclone.trk spiders_web_dimens. = 400 16 radius_of_cyclone = 600000.000 wind conv. fac (trk)= 0.894 no._of_his._data = 0 his._data_file_name = obs._data_file_name = extended_report = YES wes_threshold_speed = 35 nodata_value = -999

Remark: ⋄ Keywords are case-insensitive comment All lines proceeded by the keyword comment will be treated as comments. There can be any number of comments. cyclone_par._file The name of the track parameter file (ASCII file containing positions and the cyclone parameters). Advised extension for the file name is: . The path of the existing file may be included otherwise the current working directory will be assumed. spiders_web_dimens. The dimension of the spider-web grid as well as the maximum radius of the cyclone. The grid resolution in the radial direction (i.e. ratio of cyclone radius/number of points) must be sufficient to resolve the expected wind gradients. From our experience, the following values may be prescribed for the dimensions and cyclone radius (Rcyc): 400 by 16 points and 600,000 meters respectively. The resolution in the radial direction is then equal to 1500 meters. A resolution between 1000 – 2000 meters is required especially when dealing with compact cyclones with high wind gradients. radius_of_cyclone Radius of the cyclone, see also description of keyword spiders_web_dimens.. wind conv. fac (trk) When measuring wind force, small (temporal) scale fluctua- tions are averaged during a certain period. Each country defines its own standard and defines a different averaging period. To produce a consistent output and to allow you to use input data from different sources, separate conversion factors for the cyclone wind magnitude has been defined, the wind conv. fac (trk). This factor will be applied to convert the values from the averaging period used in the cyclone advisories to the, required, x-minute average by the user, see also section A.5. For example, cyclone wind data from JTWC is usually based on 1 minute average. If the output is to be based on 3 minutes average as per IMD convection, then a multiplication factor equal to 0.894 to the cyclone parameters (wind conv. fac (trk)) should be specified. no._of_his._data Number of history data station (maximum 9). When specified, then at the end of the diagnostic file a time series of wind data (magnitude + direction) for these stations will be produced.

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his._data_file_name File name containing station locations. obs._data_file_name File name containing observation data (not yet active). extended_report This option enables you to specify whether extended diagnostics are to be produced or not. Extended diagnostics include e.g. process- logging, extensive error and warning messages, etc. Compact diagnostic will only contain process-logging and main error messages. wes_threshold_speed Wind speeds below this threshold wind speed will be ignored. To reproduce results from previous WES versions (version 3.31 and lower) a value “0” [knts] shopuld be specified. nodata_value To reproduce results from previous WES versions (version 3.31 and lower) a value “0” shopuld be specified.

A.2 History points, <∗.xyn> File contents Description of history points characterised by their spherical coordinates and name. Filetype ASCII File format Free formatted. Filename Generated Manually offline

Record description:

Record Record description

each record Location of the history point specified by spherical coordinates (2 reals; longitude, latitude: λ, ϕ) Name of observation point.

The file format is the same used for the observation points of D-Flow Flexible Mesh,see (D-Flow FM UM, 2015)

Restrictions: ⋄ One record per history point. ⋄ The name of the history point should be between single quotes. ⋄ The first 14 characters of the history point name will be printed in the diagonstic file.

Example: File containing 5 observation points:

269.632 30.050 'EastBank1' 270.043 29.263 'GrandIsle' 270.593 28.932 'PilotsStEast' 270.56 30.282 'Waveland' 269.582 29.777 'WestBank1'

44 of 50 Deltares Description of used files

A.3 Description of the cyclone parameters in the track file, <∗.trk> File description:

File contents: Description of observed features of the cyclone and predicted future positions and characteristics. File Format: ASCII free formatted data. Any record preceded by an asterisk (∗) prior to the cyclone track data is treated as a comment.

Record description:

record 1–N Text header (comments) defining the file and the content of thefol- lowing records (to be superseded by an asterisk in the first column). record N+1 Direction of movement over past x hours in degrees (real), speed over past x hours in knots (real); x is an arbitrary time span. record N+2 Comment record N+3 Comment record N+4 The following enumeration corresponds with the column numbering the -file: 1 Year of prediction (integer), 2 Month of prediction (integer), 3 Day of prediction (integer), and 4 Hour of prediction (integer), 5 Latitude of centre in decimal degrees (real), 6 Longitude of centre in decimal degrees (real), 7 Method 8 Maximum sustained velocity in knots (real), 9 Radius of maximum wind in Nautical miles (real). 10 Radius of 100 knots winds in Nautical miles (real), 11 Radius of 65 knots winds in Nautical miles (real), 12 Radius of 50 knots winds in Nautical miles (real), 13 Radius of 35 knots winds in Nautical miles (real), 14 Constant B (real), as defined in Holland(1980) 15 Constant A (real), as defined in Holland(1980) 16 Central pressure drop (background pressure − central pressure) in Pa (real).

Record N+4 may be repeated as many times as required.

Restrictions: ⋄ Comment record N −1 should contain the cases sensitive letters Dm and Vm. The next line has two real numbers. Example: * Dm (Degrees) Vmove(knots) or * Dm Vm ⋄ Any undefined values (or values that are not used) should be indicated using themiss- ing data value PMDI (Parameter Missing Data Index = 1.e30).

Example: Cyclone track for 13 positions:

* File for tropical cyclone * File contains Cyclone information ; TIMES in UTC * File created by vatvani * UNIT = knots, Nautical miles, Pascal * METHOD= 1:A&B; * 2:R100 R65 etc;

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* 3:Vmax,Pdrop,Rmax * 4:Vmax,Pdrop; Rmax default * 5:Vmax & Rmax (Rmax may be default - US data; Pd = 2 Vm*Vm); * 6:Vmax (Indian data); * 7: OLD METHOD - Not advised * Dm (Degrees) Vmove(knots) 280.0 5.0 * Date and time lat lon Meth Vmax Rmax R100 R65 R50 R35 Par B Par A Pdrop *yyyy mm dd HH deg deg - knots [nmi] [nmi] [nmi] [nmi] [nmi] [-] [-] [Pa] 2000 11 26 06 9.8 90.5 4 25 1e30 1e30 1e30 1e30 1e30 1e30 1e30 275 2000 11 26 12 10.1 89 4 25 1e30 1e30 1e30 1e30 1e30 1e30 1e30 275 2000 11 26 18 10.4 89 4 25 1e30 1e30 1e30 1e30 1e30 1e30 1e30 275 2000 11 27 00 10.8 88 4 25 1e30 1e30 1e30 1e30 1e30 1e30 1e30 275 2000 11 27 06 11.1 86.8 4 30 1e30 1e30 1e30 1e30 1e30 1e30 1e30 450 2000 11 27 12 11.3 85.8 4 45 1e30 1e30 1e30 1e30 1e30 1e30 1e30 1000 2000 11 27 18 11.4 85.2 4 45 1e30 1e30 1e30 1e30 1e30 1e30 1e30 1000 2000 11 28 00 11.6 83.8 4 55 1e30 1e30 1e30 1e30 1e30 1e30 1e30 1500 2000 11 28 06 11.6 83 4 65 1e30 1e30 1e30 1e30 1e30 1e30 1e30 2090 2000 11 28 12 11.6 82.2 4 77 1e30 1e30 1e30 1e30 1e30 1e30 1e30 2940 2000 11 28 18 11.6 81.4 4 102 1e30 1e30 1e30 1e30 1e30 1e30 1e30 6560 2000 11 29 00 11.6 80.8 4 90 1e30 1e30 1e30 1e30 1e30 1e30 1e30 4020 2000 11 29 06 11.6 80.1 4 66 1e30 1e30 1e30 1e30 1e30 1e30 1e30 2090

Action taken by WES when input parameters are over specified When parameters that are not required by the specified method in the input file are assigned with values (other than the PMDI values, i.e. 1.e30) then they will be overwritten by the program.

Please note that Vmax is compulsory and must be assigned with a proper value.

A.4 Spiderweb file File type ASCII. File format Free formatted, keyword based. File name containing wind speed in [m/s], wind (from) direction in [degree] and atmospheric pressure in [Pa] or [millibar].

A detailed description of this file is given in the(Delft3D-FLOW UM, 2013).

A.5 Conversion Factors for wind speed Different Meteorological agencies use different averaging period to measure the surface wind. Subsequently, all the wind speed data they use are converted to these averaging period in order to allow them to compare their data with the observations. Some of the agencies may use one-minute average while others uses 3 min and 10 min averages. To compare the data from one agency to those from the other agency then corrections must be applied by multiplying one set of the wind speeds with an appropriate factor.

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Figure A.1: Gust factors for cyclone wind speed (Curve C) as a function of time (Krayer and Marshall, 1992).

Figure A.1 depicts the gust factors as a function of time. Gust factor is given along the y-axis and the time along the x-axis. A, B, C are the curves depicting various relations for the gust factors that has been reported by different scientist in the past. If we stick to Curve C for example and we want to find the conversion factor to convert one minute average wind speed to a three minute averaged wind speed then the factor can be determined as follows: f C1−3 Gust factor for 3 minutes average/gust factor for 1 minutes average, = 1.18/1.32 = 0.894

f In the Indian project we have applied a correction factor C1−3 = 0.88 that has been used by IMD. Because this value does not differ much from the value found above and to be consistent with IMD we have applied their factor in WES when the maximum wind speed reported by JTWC bulletin is used as input data.

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A.6 Common Errors and Suggested Solutions in WES 1 ERROR Cyclone/typhoon parameter file not found Reason: This error occurs if the path of the track file is not specified / incorrectly specified in <∗.inp> file. Action: The correct path should be given. 2 ERROR (3∗) MAX. radius value must be between 150 & 1500 KM Reason: Maximum value of the radius of the cyclone is incorrect in the <∗.inp> file Action: Check the value of the radius of the cyclone. This should be in meters. 3 ERROR Sp.web grid dimension must be >0 Reason: This error occurs if the values against the variable “SPIDERS_WEB_DIMENS” in the <∗.inp> file are less than zero. In that case replace the values with 16. Thenumber 16 refers to the 16 direction of compass in which the grid values are computed and the number 400 refers to the number of values on each radius. Action: Write appropriate dimensions for the spiderweb in the <∗.inp> file 4 ERROR Cyclone/typhoon parameter file not found Reason: This error occurs if the correct path for "CYCLONE_PAR._FILE" is not mentioned in the <∗.inp> file or when the parametric file is missing. Action: Give the correct path or enter the appropriate name of the parameter file 5 ERROR reading predicted track, itime=’,itime Reason: In <∗.trk> file, if there is a blank space between the entries in one line andthe subsequent line, this error occurs. Action: There should not be any empty lines at the end or in between the data. 6 ERROR - Max. WIND SPEED NOT SPECICIFIED Reason: The maximum wind speed should not be 1e30 or left blank. Action: number should be given in the <∗.trk> file under max. wind speed. 7 ERROR - INCOMPLETE DATA UNABLE TO CONTINUE Reason: This error occurs if the data is not complete Action: Check the availability of all appropriate input data parameters in .trk file and <∗.inp> file 8 ERROR specified input file not found Reason: If the correct path of the existing <∗.inp> file is not defined while invoking WES program or wrong <∗.inp> file name is given this error occurs. Action: Give the correct path and name of the <∗.inp> file while invoking WES. 9 ERROR Extended Report option must equal YES or NO Reason: In the <∗.inp> file Choose “YES” or “NO” depending on the requirement. It should not be left blank. Action: The Extended Report option should be specified “YES” or “NO”

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