A First Generation Dynamical Tropical Cyclone Storm Surge ... · A FIRST GENERATION DYNAMICAL...

Bureau Research Report - 031

A First Generation Dynamical Tropical Cyclone Storm Surge Forecast System Part 1: Hydrodynamic model

Diana Greenslade, Andy Taylor, Justin Freeman, Holly Sims, Eric Schulz, Frank Colberg, Prasanth

Divakaran, Mirko Velic and Jeff Kepert

October 2018

A FIRST GENERATION DYNAMICAL TROPICAL CYCLONE STORM SURGE FORECAST SYSTEM PART 1: HYDRODYNAMIC MODEL


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A First Generation Dynamical Tropical Cyclone

Storm Surge Forecast System

Part 1: Hydrodynamic model

Diana Greenslade, Andy Taylor, Justin Freeman, Holly Sims, Eric Schulz,

Frank Colberg, Prasanth Divakaran, Mirko Velic and Jeff Kepert

Bureau Research Report No. 031

October 2018

National Library of Australia Cataloguing-in-Publication entry

Author: Diana Greenslade, Andy Taylor, Justin Freeman, Holly Sims, Eric Schulz, Frank Colberg, Prasanth

Divakaran, Mirko Velic and Jeff Kepert

Title: A First Generation Dynamical Tropical Cyclone Storm Surge Forecast System Part 1:

Hydrodynamic model ISBN: 978-1-925738-08-7

Series: Bureau Research Report – BRR031


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Enquiries should be addressed to:

Diana Greenslade:

Bureau of Meteorology

GPO Box 1289, Melbourne

Victoria 3001, Australia

[email protected]:

Copyright and Disclaimer

© 2016 Bureau of Meteorology. To the extent permitted by law, all rights are reserved and no part of

this publication covered by copyright may be reproduced or copied in any form or by any means except

with the written permission of the Bureau of Meteorology.

The Bureau of Meteorology advise that the information contained in this publication comprises general

statements based on scientific research. The reader is advised and needs to be aware that such

information may be incomplete or unable to be used in any specific situation. No reliance or actions

must therefore be made on that information without seeking prior expert professional, scientific and

technical advice. To the extent permitted by law and the Bureau of Meteorology (including each of its

employees and consultants) excludes all liability to any person for any consequences, including but not

limited to all losses, damages, costs, expenses and any other compensation, arising directly or indirectly

from using this publication (in part or in whole) and any information or material contained in it.


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Contents

ABSTRACT ................................................................................................................. 1

1. Introduction ....................................................................................................... 2

2. Other operational storm surge forecast systems ........................................... 4

3. Surface forcing .................................................................................................. 6

4. Hydrodynamic modelling.................................................................................. 9

4.1 Model configuration ................................................................................................ 10

4.2 Offshore territories .................................................................................................. 11

4.3 Subsetted domain ................................................................................................... 13

4.4 Wave set-up ............................................................................................................ 14

5. Verification ...................................................................................................... 15

5.1 Observations ........................................................................................................... 16

5.2 Summary of Performance ....................................................................................... 17

5.3 Case Study results .................................................................................................. 20 5.3.1 TC Anthony ......................................................................................................... 20 5.3.2 TC Yasi ............................................................................................................... 22 5.3.3 TC Ita .................................................................................................................. 25 5.3.4 TC Lam ............................................................................................................... 28 5.3.5 TC Marcia ........................................................................................................... 29 5.3.6 TC Olwyn ............................................................................................................ 31 5.3.7 TC Nathan .......................................................................................................... 33

5.4 Comparison with existing systems ......................................................................... 34

6. Further Work ................................................................................................... 38

7. Acknowledgements......................................................................................... 40

8. References ....................................................................................................... 41


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List of Figures

Fig. 1 Velocity magnitude and velocity vectors from Best Track data for TC Yasi on 2 February 2011 at 0400 UTC. The calculated velocity field includes storm forward motion, friction and inflow angle correction. .............................................................................................. 8

Fig. 2 Domain of the full tropical grid. This is subsetted for each run. ..................................... 10

Fig. 3 Spatial extents of all grids tested for Christmas Island, with a snapshot of storm surge height at 3:00 UTC on 22nd March 2014 from TC Gillian overlaid. ............................... 12

Fig. 4 Time series of maximum value of sea level in each grid. ............................................... 13

Fig. 5 Best Tracks for the seven events examined................................................................... 16

Fig. 6 Hourly fixes of the Best Track for TC Anthony (light blue crosses) and location of 3 tide gauges (red diamonds) used for verification .................................................................. 20

Fig. 7 Left hand panel shows the location of the Bowen tide gauge (green pin) in relation to the local coastline and the model's coastal grid points (white circles). The closest grid point is indicated by the red circle. Right hand panel shows de-tided Bowen station data (black diamonds) during TC Anthony compared with the model hindcast at the closest grid point. Blue line is surge only, green line is wave set-up and red line is surge + wave set-up. 21

Fig. 8 Same as Fig. 7 but for Shute Harbour ............................................................................ 21

Fig. 9 Same as Fig. 7 but for Laguna Quays ............................................................................ 21

Fig. 10 Hourly fixes of the Best Track for TC Yasi (blue crosses) and location of the 6 tide gauges (red diamonds) used for verification ............................................................................... 22

Fig. 11 Left hand panel shows the location of the Cairns tide gauge (green pin) in relation to the local coastline and the model's coastal grid points (white circles). The closest grid point is indicated by the red circle. Right hand panel shows de-tided Cairns station data (black diamonds) during TC Yasi compared with the model hindcast at the closest grid point. Blue line is surge only, green line is wave set-up and red line is surge + wave set-up. 23

Fig. 12 Same as Fig. 11 but for Mourilyan .................................................................................. 23

Fig. 13 Same as Fig. 11 but for Clump Point .............................................................................. 23

Fig. 14 Same as Fig. 11 but for Cardwell ................................................................................... 24

Fig. 15 Same as Fig. 11 but for Townsville ................................................................................ 24

Fig. 16 Same as Fig. 11 but for Cape Ferguson ........................................................................ 24

Fig. 17 Hourly fixes of the Best Track for TC Ita (green crosses) and location of the 6 tide gauges (red diamonds) used for verification. .............................................................................. 25

Fig. 18 Left hand panel shows the location of the Cooktown tide gauge (green pin) in relation to the local coastline and the model's coastal grid points (white circles). The closest grid point is indicated by the red circle. Right hand panel shows de-tided Cooktown station data (black diamonds) during TC Ita compared with the model hindcast at the closest grid point. Blue line is surge only, green line is wave set-up and red line is surge + wave set-up. 26

Fig. 19 Same as Fig. 18 but for Cairns ....................................................................................... 26

Fig. 20 Same as Fig. 18 but for Cardwell ................................................................................... 26

Fig. 21 Same as Fig. 18 but for Townsville ................................................................................ 27

Fig. 22 Same as Fig. 18 but for Cape Ferguson ........................................................................ 27


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Fig. 23 Same as Fig. 18 but for Bowen ...................................................................................... 27

Fig. 24 Hourly fixes of the Best Track for TC Lam (pink crosses) and location of the 2 tide gauges (red diamonds) used for verification. .............................................................................. 28

Fig. 25 Left hand panel shows the location of the Weipa tide gauge (green pin) in relation to the local coastline and the model's coastal grid points (white circles). The closest grid point is indicated by the red circle. Right hand panel shows de-tided Weipa station data (black diamonds) during TC Lam compared with the model hindcast at the closest grid point. Blue line is surge only, green line is wave set-up and red line is surge + wave set-up. 29

Fig. 26 Same as Fig. 25 but for Groote Eylandt ......................................................................... 29

Fig. 27 Hourly fixes of the Best Track for TC Marcia (orange crosses) and location of the 2 tide gauges (red diamonds) used for verification. ................................................................. 30

Fig. 28 Left hand panel shows the location of the Rosslyn Bay tide gauge (green pin) in relation to the local coastline and the model's coastal grid points (white circles). The closest grid point is indicated by the red circle. Right hand panel shows de-tided Rosslyn Bay station data (black diamonds) during TC Marcia compared with the model hindcast at the closest grid point. Blue line is surge only, green line is wave set-up and red line is surge + wave set-up. ............................................................................................................................. 31

Fig. 29 Same as Fig. 28 but for Port Alma ................................................................................. 31

Fig. 30 Hourly fixes of the Best Track for TC Olwyn (purple crosses) and location of the tide gauge (red diamond) used for verification. ..................................................................... 32

Fig. 31 Left hand panel shows the location of the Point Murat tide gauge (green pin) in relation to the local coastline and the model's coastal grid points (white circles). The closest grid point is indicated by the red circle. Right hand panel shows de-tided Point Murat station data (black diamonds) during TC Olwyn compared with the model hindcast at the closest grid point. Blue line is surge only, green line is wave set-up and red line is surge + wave set-up. ............................................................................................................................. 32

Fig. 32 Hourly fixes of the Best Track for TC Nathan (red crosses) and location of the tide gauge used for verification (red diamond). ................................................................................ 33

Fig. 33 Left hand panel shows the location of the Cooktown tide gauge (green pin) in relation to the local coastline and the model's coastal grid points (white circles). The closest grid point is indicated by the red circle. Right hand panel shows de-tided Cooktown station data (black diamonds) during TC Nathan compared with the model hindcast at the closest grid point. Blue line is surge only, green line is wave set-up and red line is surge + wave set-up. ............................................................................................................................. 34


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List of Tables

Table 1 Peak values for each grid............................................................................................. 13

Table 2 Details of the Tropical Cyclones used for verification. Maximum observed surge refers to sea level after removal of astronomical tides and centering of the residuals (see Section 5.1). ................................................................................................................. 15

Table 3 Comparison between observed and modelled peak surge amplitude for the 7 TC events studied here. MAEs less than 0.5m are highlighted in green. ..................................... 18

Table 4 Comparison between observed and modelled peak surge timing for the seven TC events studied here. ..................................................................................................... 19

Table 5 Comparison between ROMS and SEAtide errors in peak surge amplitude. All values except percentages in (m). Green shading indicates the lowest absolute error for each site. ............................................................................................................................... 36

Table 6 Comparison between ROMS and SEAtide errors in peak surge timing. ..................... 37

ABSTRACT

A new Tropical Cyclone (TC) storm surge forecast system has been developed. This Tropical Storm

Surge system is a step-change from previous parametric storm surge systems used operationally at the

Bureau of Meteorology. Parametric TC vortices are derived from the Bureau of Meteorology’s Official

Forecast Track and its associated ensemble tracks. These are gridded and used to force the

hydrodynamic model, ROMS (Regional Ocean Modelling System). Wave set-up (derived from

AUSWAVE-R) and astronomical tides are linearly combined with the ROMS storm surge to provide

forecasts of coastal sea level at a spatial resolution of approximately 2.5 km around the tropical

Australian coastline. Storm surge hindcasts have been evaluated for seven recent TC events using post-

analysed ‘Best Track’ TC parameters through comparison with tide gauge observations of coastal sea

level. The mean bias in the maximum surge for the seven test cases is -1 cm, suggesting that there is

negligible systematic over- or under-prediction in the system. The mean absolute error of peak surge

amplitude is 26 cm. This demonstrates a substantial improvement over existing operational systems.

1. INTRODUCTION

Storm surge can be defined as an elevation of water level at the coast resulting from strong winds and

reduced atmospheric pressure. Storm surges are very often associated with Tropical Cyclones (TCs) as

they come onshore and may also be generated by intense low-pressure systems in non-tropical areas.

Storm surge typically includes wave setup – an additional elevation of the water level due to wave-

breaking. Storm tide is the combination of storm surge and astronomical tide – if a storm surge arrives

at high tide, the impacts can be considerably more damaging than if it arrives at low tide.

The Bureau of Meteorology has recently undertaken a project to enhance its operational storm surge

forecasting system. The project consists of three key components: 1) an event-based TC ensemble

storm surge system implemented for Queensland, the Northern Territory and Western Australia, 2) a

national storm surge system for forecasting anomalous sea levels due to mid-latitude storms and tropical

lows (Allen et al., 2018), and 3) operationalisation of an existing aggregate sea level monitoring and

alert system at tide gauge locations (Taylor and Brassington, 2017). There are many scientific and

technical commonalities to each of the three components of the project.

This report describes only the first component, the event-based TC system. Furthermore, it focusses on

the hydrodynamic model aspect of this process with an evaluation of the ensemble forecasts to come in

a later report. It should also be noted that the first two of the systems listed above are traditionally

referred to as ‘storm surge’ systems despite the fact that they ultimately both include the effects of

astronomical tides.

Historically, the three relevant Bureau Regional Offices have had their own, different systems for

forecasting storm surges due to TCs. Establishing a common, nationally consistent workflow for storm

surge forecasts that integrates seamlessly with other systems and procedures is of significant value from

an operational perspective. A further rationale for the present development is that the existing systems

are all based on parametric and/or scenario-based techniques (e.g. SEAtide, see section 2) which, while

fast to run, have some limitations. For example, the parametric technique assumes equilibrium

conditions, i.e. that a TC is propagating in a straight line with constant intensity parameters which is

not typically the case in reality.

The capability to run a dynamical storm surge model exists, however this has not previously been done

on an operational basis for a number of reasons. Firstly, within a TC forecasting environment, the storm

surge forecast needs to be produced very rapidly. This was not possible at the time the existing storm

surge forecast systems were implemented, but current computational capacity means that this is now

possible within operational constraints. Secondly, the Bureau’s Official Forecast Track (OFT) for any

individual TC is not directly connected to any one particular NWP model, but is produced from a

consensus of a number of different models by forecasters using the TC-Module system (Donaldson and

Taylor, 2018). Thus if a storm surge forecast were to be produced using forcing from an individual

model such as ACCESS-TC (Davidson et al., 2014; Puri et al., 2013), there would likely be

inconsistencies between the storm surge forecast and the OFT. This is highly undesirable when

emergency management issues are considered.

A further factor that has previously limited dynamical deterministic storm surge forecasts is that the

surge forecast is very sensitive to errors in the TC location, velocity, intensity, size etc. Mean TC track

errors for Bureau OFTs during the time period 2010 to 2015 were 97 km for 24 hour forecasts and 156

km for 48 hour forecasts (Australian Bureau of Meteorology, 2016). This suggests that ensemble storm

surge forecasting is required in order to take account of the forecast uncertainty. Within TC-Module,

there is an application that produces a forecast of wind speed exceedance probabilities from the OFT.

The technique is based on the development of an ensemble of TC tracks using the ‘DeMaria’ method

(DeMaria et al., 2009) which takes into account historical TC track and intensity errors. This produces

an ensemble of TC tracks based on the OFT.

In this project, this TC track ensemble, in addition to the OFT, is used as the basis for forcing an

ensemble of storm surge models in order to provide probabilistic storm surge forecasts. There are a

number of steps involved in this process. Firstly, it should be noted that the ensemble tracks have been

developed to provide wind speed exceedance probabilities, and they are not always physically realistic.

Thus, they must be modified to ensure that they are dynamically consistent for forcing a storm surge

model. This is documented in Kepert (2014) and is not addressed in this report. For each ensemble

member, a series of gridded forcing fields are produced from the TC track. Once the forcing fields have

been developed, these are used to force a hydrodynamic model to produce an ensemble of storm surge

forecasts, and finally, the resulting surge forecasts are combined with wave set-up and astronomical

tides to produce forecasts of storm tide at the coast.

This report focusses on describing the configuration and verification of the hydrodynamic/storm surge

model aspect of this process. The forecasts, including ensembles, are not addressed here but will be

described and evaluated in a separate document. The report is structured as follows: Section 2 places

this work in context by describing some other relevant operational storm surge forecast systems;

Section 3 describes the technique of converting the TC vortex to a gridded forcing field; Section 4

describes the model setup and some experiments undertaken with the hydrodynamic model to provide

guidance on aspects of model configuration such as spatial resolution and domain; Section 5 presents

an evaluation of the system for a number of recent TCs, including a comparison with existing

operational systems; and Section 6 presents some indications of further work that could be undertaken

to improve the system.

2. OTHER OPERATIONAL STORM SURGE FORECAST SYSTEMS

There are many other countries around the world that are vulnerable to the impacts of TCs and storm

surges. Two examples of existing operational systems used to forecast the impacts of storm surge due

to TCs are those based at the Japan Meteorological Agency (JMA) and the United States National

Weather Service (NWS). These are both based on dynamical storm surge models, and are described

below, along with some other relevant developments within Australia.

JMA currently operates an Asian-area storm surge model to provide predictions of surge within the

Tokyo Regional Specialised Meteorological Centre (RMSC) area of responsibility (Hasegawa et al.,

2017). The hydrodynamic model is based on the vertically integrated shallow water equations and has

a spatial resolution of approximately 3.7 km. The domain covers 0°N to 42°N and 95° E to 160°E. The

model is forced by surface winds and pressure from the JMA mesoscale atmospheric model (spatial

resolution of 0.25° by 0.2°) on an ongoing basis providing 72-hour forecasts every 6 hours. When there

is a TC in the region, an additional 5 model runs are undertaken, forced with a simple parametric TC

model ‘bogussed’ into the atmospheric forcing. These 5 extra forecasts are selected using cluster

analysis on 27 ensemble members of the JMA Typhoon Ensemble Prediction System (Kyouda and

Higaki, 2015). Gridded astronomical tides are added to the predicted storm surge to provide forecasts

of total sea level. Wave set-up is not currently included.

The U.S. NWS uses the Sea, Lake and Overland Surges from Hurricanes (SLOSH) model (Jelesnianski

et al., 1992) for a range of storm surge predictions and hazard assessments (Glahn et al., 2009). For

real-time TC storm surge forecasts, it is applied in deterministic mode over 32 domains, or ‘basins’

covering the U.S. East coast and offshore regions. The position of the forecast track determines which

basins will be run. SLOSH forcing is provided by parametric TC information from the official forecast

(location, radius-to-maximum-winds, pressure gradient). Using ‘best track’ (see section 5) parametric

TC information for a set of 13 storms, SLOSH was found to be accurate to within 20% of the peak surge

value most of the time, although the errors could be significantly larger (Glahn et al., 2009).

In addition to the deterministic forecast, probabilistic forecasts are derived from the Probabilistic Storm

Surge model (P-surge), which is comprised of an ensemble of SLOSH forecasts. The forcing for each

ensemble member is created by modifying the official forecast TC position, size and intensity based on

past errors, specifically errors in the along-track distance, cross-track distance and intensity (Taylor and

Glahn, 2008). Verification of P-surge was undertaken using SLOSH hindcasts, rather than directly using

observations, because of the low number of good quality storm surge observations available. There are

two main products created from P-surge, both generated on a grid covering the area of interest. The first

of these is the probability of storm surge greater than a particular pre-determined value, and the second

is the storm surge value that is exceeded by a particular percentage (typically 10%) of the ensemble

members.

Within the Bureau of Meteorology’s Tropical Cyclone Warning Centres in Queensland and the

Northern Territory, the existing system used to provide operational forecasts of storm surge is the

SEAtide system (SEA, 2005, 2016). SEAtide is a parametric modelling system, developed following

the approach described in Harper (2001). A number of geographical regions covering the coastline of

interest are established and many thousands of potential tropical cyclone scenarios are constructed in

order to determine the storm tide response in each region as a function of the incident storm parameters.

The storm tide predictions are based on previously developed numerical models of storm tide for

specific coastal regions (e.g. SEA, 2002). This information is then summarised into a further numerical

parametric model for each region that enables rapid retrieval of response information. For Western

Australia (WA), a similar parametric system has been developed based on the GEMS surge model

(Hubbert and McInnes, 1999). In order to provide a storm surge forecast, key features of the TC (e.g.

location, maximum wind speed, speed of forward movement) 12 hours prior to landfall are used to

provide maximum surge values at a specified number of locations along the WA coast. A standard 0.5m

is added for wave setup.

There have been a number of research projects within Australia to develop real-time storm surge

forecast systems. Under a Queensland state government project, Burston et al. (2013a) proposed a real-

time storm surge system for the Queensland coast based on the Bureau of Meteorology ensemble TC

tracks. They acknowledged that the raw tracks were not suitable for storm surge forecasting and so a

method was developed to reconstitute a set of tracks from the ensemble. Forcing fields were generated

using a Holland et al. (2010) parametric TC profile. Hydrodynamic modelling was undertaken using

the MIKE21 Flexible Mesh model (Warren and Bach, 1992). Tides were linearly added to storm surge

forecasts but wave set-up was not incorporated. An inundation modelling approach was also developed

at higher spatial resolution (80-100m) but found to be too computationally expensive to run in real-time

(Burston et al., 2013b).

A previous research and development activity at the Bureau of Meteorology (Davidson et al., 2005)

involved the development of a storm surge forecast system that was forced by TC-LAPS, the previous

operational TC NWP system (Davidson and Weber, 2000). This system used a 2D shallow water model

developed by Sanderson (1997) and incorporated a technique to account for possible errors in the TC-

LAPS forecast through manual adjustment of the TC parameters.

3. SURFACE FORCING

The accuracy of a storm surge model forecast is heavily reliant on the quality of the atmospheric forcing

used. It is well known that standard NWP models are not typically able to capture the intensity of a

Tropical Cyclone, so often, specialised TC models are used (e.g. ACCESS-TC). However, as noted in

the Introduction, for an operational forecast system, it is not ideal to run a storm surge model under a

specific NWP model, so for this project an ensemble of gridded surface wind and pressure fields is

derived from a series of synthetic vortex parameters obtained from TC Module. A further step could

be to blend the gridded surface fields with a background NWP field to provide a more physically

realistic forcing field. This is not done for the present system, but is discussed in Section 6 as a possible

future development.

A wide variety of TC vortex profile functions are available. For this project, the modified Rankine

vortex (Hughes, 1952) is used, mainly because it is also used in the wind radius prediction component

of the De Maria ensemble generation scheme. This choice thus has the virtue of being consistent with

the wind radius generation method. In addition, recent work has demonstrated that the modified Rankine

vortex is more accurate than alternative profiles such as the Holland vortex for storm surge and wave

modelling (e.g. Bastidas et al., 2016). The formulation of the vortex described here incorporates

asymmetry in the wind fields induced by the storm forward motion and an inflow angle correction to

the gradient wind field.

In the present report, we focus on storm surge hindcasts using 'Best Track' forcing. The 'Best Track' for

any TC is a time series of TC parameters, produced by forecasters, or other analysts, after the end of

the TC season, and taking into account all available observations. The specific parameters required from

the Best Track data to describe the TC at any time are:

1. Longitude of the storm centre,

2. Latitude of the storm centre,

3. Maximum wind speed, Vm

4. Radius of maximum wind, rm

5. A cyclone size parameter, α (0 < α < 1)

The velocity profile of the modified Rankine vortex is calculated through the radial integration of the

axisymmetric vorticity following Kepert (2013). Storm asymmetry is introduced by radially modifying

the velocity distribution to include the storm forward motion velocity:

𝑉(𝑟, 𝜃) = 𝑉(𝑟) + 𝛿𝑓𝑚𝑉𝑓𝑚 sin 𝜃 (3.1)

where θ is the angle relative to the storm direction, δfm is the fraction of forward motion and is in the

range 0.5 to 1 and Vfm is the storm forward motion velocity. Under this formulation, for southern

hemisphere storms, Vm is located 90 anticlockwise to the storm direction vector. The location of Vm

can be anywhere from 65 to 114 (Harper, 2001). In the subsequent model we locate the storm

maximum velocity at 65 anticlockwise from the storm direction and use δfm = 0.5. The storm velocity

is calculated using a forward difference of best track data where the distance covered by the storm over

the time period between consecutive fixes is determined by the haversine formula. Setting Vfm = 0, the

vortex reduces to the axisymmetric structure.

The best track velocity data is modified according to equation (3.1) and we use the median velocity of

the best track sector data to determine the wind speed at 64 nm, 48 nm and 34 nm radii. A lower bound

of 0.1 ms−1 for Vm is imposed.

The application of equation (3.1) to the symmetric formulation given by Kepert (2013) results in the

the radial velocity no longer flowing inward along isobars. The inflow angle is (Phadke et al., 2003)

𝛽 =

{

10 (1 +

𝑟

𝑟𝑚) 𝑟 ≤ 𝑟𝑚

20 + 25 (𝑟

𝑟𝑚− 1) 𝑟𝑚 ≤ 𝑟 < 1.2𝑟𝑚

25 𝑟 ≥ 1.2𝑟𝑚

(3.2)

and the angle correction is applied by rotating the gradient wind vectors inward by β,

𝑢𝑟 = 𝑢 cos(−𝛽) − 𝑣 sin(−𝛽) (3.3)

𝑣𝑟 = 𝑢 sin(−𝛽) + 𝑣 cos(−𝛽) (3.4)

The conversion of 10 m winds, u10, to surface stress follows Large and Pond (1981) with the drag

coefficient capped in accordance with Powell et al (2003),

𝐶𝑑103 = {

1.2 𝑢10 < 10.92 𝑚𝑠−1

0.49 + 0.065𝑢10 10.92 𝑚𝑠−1 ≤ 𝑢10

2.635 𝑢10 ≥ 23.23 𝑚𝑠−1

< 23.23 𝑚𝑠−1 (3.5)

Fig. 1 Velocity magnitude and velocity vectors from Best Track data for TC Yasi on 2 February 2011 at 0400

UTC. The calculated velocity field includes storm forward motion, friction and inflow angle correction.

An example velocity field for TC Yasi using the best track data at 0400 UTC on 2 February 2011 is

given in Fig. 1.

Atmospheric pressure is given by

𝑃(𝑟) = 𝑃𝑐 + ∫ 𝜌 (𝑉2(𝑠)

𝑠+ 𝑓𝑉(𝑠))

𝑟

0𝑑𝑠 (3.6)

where 𝑃𝑐 is the minimum central pressure in hPa, and ρ = 1.15 kg m3 is density. The central pressure of

the storm is calculated using the wind-pressure relationship of Knaff and Zehr (2007) with the latitudinal

corrections suggested by Courtney and Knaff (2009).

In its operational configuration, the stress and pressure forcing fields are generated on a 0.5° resolution

grid and then interpolated onto the hydrodynamic model grid using a cubic interpolation method.

4. HYDRODYNAMIC MODELLING

The Regional Ocean Modelling System (ROMS; Shchepetkin and McWilliams, 2005) was selected as

the hydrodynamic modelling component for both the TC event-based storm surge system and the

national system. This was based on a comprehensive review of a large number of possible numerical

models (Colberg et al., 2013) and a strategy to limit the number of different modelling systems used

within the Bureau of Meteorology for coastal ocean modelling applications. ROMS is a hydrostatic,

primitive equation model, featuring a nonlinear free-surface.

For the present storm surge implementation, ROMS solves the depth-averaged momentum and

continuity equations:

𝜕𝑼

𝜕𝑡+𝑼. ∇𝑼 + 𝒇 × 𝑼 = −𝑔∇η +

𝝉𝑠−𝝉𝑏

𝜌𝐻+ 𝒗 (4.1)

𝜕𝜂

𝜕𝑡+𝐻∇.𝐔 =

1

𝑔𝜌

∂𝑃

∂𝑡 (4.2)

where 𝑼 = (�̅�, �̅�) is the depth averaged velocity, t is time, 𝒇 is the Coriolis term, 𝑔 is the gravitational

constant, is the free surface height, 𝜌 is density, H is the total depth, 𝝉𝑠 and 𝝉𝑏 are the surface and

bottom stress respectively, 𝒗 is the viscosity and P is atmospheric pressure. By not including any

vertical structure in the model, some modes of variability may not be included or well simulated.

However, it is likely that the baroclinic component is very weak (Peng and Li, 2015) and it is reasonable

to ignore it, particularly for TC surge. This approach is consistent with the National storm surge system

(Allen et al., 2018) and also current international practice, as discussed in Section 2.

At the domain boundaries the normal component of the depth-average velocity is subject to the Flather

boundary condition (Flather, 1976) while the sea level is subject to a Chapman boundary condition

with zero external forcing (Chapman, 1985). Other details of the model configuration are as follows.

Spatially uniform quadratic bottom drag is used, with a drag coefficient of 1 x 10-3. The bathymetry

data used is the Geoscience Australia 9-arc second bathymetry (Whiteway, 2009) merged with the 30-

arc second GEBCO_2014 Grid, (version 20150318, http://www.gebco.net) for the area north of 8oS

(where the Geoscience Australia data does not exist). The time step is 6 seconds. Wetting/drying is

turned on with a critical depth of 0.1m. During a computational step, if the total water depth is less than

the critical depth then no flux is allowed out of that cell, however, water can flow into the cell. The

land-sea mask was generated using the zero contour level of the interpolated bathymetry and manually

post-processed to remove single cell land points, isolated wet cells and single cell channels and bays.

4.1 Model configuration

There is a balance to be found between specifying a large domain in order to fully capture the relevant

atmospheric forcing, and a small domain in order to run the model as quickly as possible. In addition,

there is a balance to be found between specifying fine resolution in order to better resolve the variability

of the sea level and describe the coastline more realistically, and low resolution in order to reduce

computational cost.

For the full tropical domain, a ‘ribbon’ grid was selected in preference to a rectangular grid because: a)

for the domain of interest, i.e. the tropical coastline of Australia, it will have inherently higher resolution

near the coast compared to offshore, and b) a ribbon grid is more computationally efficient for ROMS

as it minimises the number of land points used over the continent. A domain was established, covering

all anticipated latitudes within which a Tropical Cyclone might make landfall (see Fig. 2). Eight grids

of different spatial resolutions covering this domain were tested. Note that the characteristics of the

ribbon grid means that the spatial resolution across the grid is not uniform. The mean resolutions of the

grids tested ranged from 1.26 km (929 x 6273 grid points) to 10 km (117 x 785 grid points).

Fig. 2 Domain of the full tropical grid. This is subsetted for each run.

A number of synthetic storms were modelled for each of the eight grid configurations, and the results

were assessed on the basis of: 1) location of maximum sea-level anomaly, 2) root-mean-square (rms)

variability of sea-level anomaly in a small region (approximately 50 km by 50 km) surrounding the

location of the maximum, and 3) computational time.

The impact of spatial resolution on sea-level variability was found to be relatively small. The approach

used was as follows. The average rms value (part (2) above) for each storm was plotted as a function of

the inverse of the total grid size. A line of best fit extrapolated to the origin therefore

provides an approximate value of the rms for a hypothetical ‘infinite’ resolution grid. With this

approach, the coarsest grid examined showed a difference of 5% in rms sea-level variability compared

to the hypothetical ‘infinite’ resolution grid, and the finest resolution grid examined showed a difference

of 1%. Based on this analysis and requirements from users, the configuration selected was a grid with

a mean resolution of 2.5 km. Spatial resolutions of the coastal cells within this grid range from 1.9 km

to 4 km. This grid showed a difference in rms sea-level variability of approximately 2% compared to

an ‘infinite’ grid.

4.2 Offshore territories

In addition to mainland Australia, there is a requirement to produce storm surge forecasts for a number

of offshore territories, namely Cocos Island, Christmas Island, Norfolk Island and Lord Howe Island.

Macquarie Island is not included for the tropical system because it is highly unlikely that a TC would

impact there.

Lord Howe Island is located within the tropical grid shown in Fig. 2, but Cocos, Christmas, and Norfolk

Islands are not, so they require separate grids to be developed. Some previous studies undertaking

storm surge modelling for small islands with steep continental slopes have used relatively small grids

surrounding the area of interest. For example, McInnes et al. (2014) used a domain size of

approximately 500 km x 500 km surrounding the Fiji archipelago to model storm surge impacts there.

Conversely, Kennedy et al. (2012) used a domain size approximately 3,000km by 3,000 km surrounding

the Hawaiian Islands in their study of storm surge inundation. A relevant point is that the former study

did not include wind-wave processes and the latter did. This may explain the difference in domain size,

because a larger domain is desirable for modelling wind-wave processes in order to ensure that the fetch

is included. For the present study, the wave estimates are obtained from an alternate source (see Section

4.4), so we do not need to ensure that the full wave fetch is covered.

In order to establish the optimal domain size for the Australian offshore territories, a series of 9 grids

of different spatial extents (‘Grid 0’ being the smallest grid, and ‘Grid 8’ the largest grid) was developed

encompassing Christmas Island. These are shown in Fig. 3. All grids were rectangular, with the same

spatial resolution of 2 km. In this experiment, we consider the largest grid (Grid 8) to be the ‘truth’ and

assess how the results degrade as the domain is reduced. Sea-level observations are not used here as the

intent is to assess the relative difference in sea level.

Fig. 3 Spatial extents of all grids tested for Christmas Island, with a snapshot of storm surge height at 3:00

UTC on 22nd March 2014 from TC Gillian overlaid.

The forcing used for this series of experiments was an eight-day time series of hourly surface stress and

pressure during TC Gillian, which passed very close to Christmas Island in March 2014 (Bureau of

Meteorology, 2014a). Surface forcing fields were derived from the Best Track vortex details for TC

Gillian1 merged into ACCESS-R. For each grid, the maximum sea level was found within the region of

the smallest grid (i.e. grid 0) and is listed in Table 1. The maximum values for grids 0 to 6 are also

plotted as a function of time in Fig. 4. (Grids 7 and 8 are not shown here as they are very similar to grid

6). It can be seen that as the grids become larger, the maximum values converge. Little change can be

seen once the grid becomes larger than grid 6, and so grid 6 is used here, which has a spatial extent of

approximately 1,000 km by 1,000 km. The domains for Norfolk Island and Cocos Island are also set to

this size.

1 The pressure and wind stress fields used in this section were obtained using an early version of the

forcing field derivation technique, which was later abandoned. However, since the same forcing was

used for all experiments, and the intent is to assess the relative difference in sea levels, it was not

necessary to re-compute the forcing fields.

Grid Nx by Ny Peak Value (m)

% difference from

previous peak

value

Grid 0 201 x 251 0.3022 -

Grid 1 255 x 306 0.3189 5.5%

Grid 2 309 x 361 0.3310 3.8%

Grid 3 364 x 416 0.3419 3.3%

Grid 4 418 x 472 0.3539 3.5%

Grid 5 473 x 527 0.3627 2.5%

Grid 6 527 x 582 0.3700 2.0%

Grid 7 582 x 638 0.3765 1.8%

Grid 8 693 x 636 0.3778 0.35%

Table 1 Peak values for each grid

Fig. 4 Time series of maximum value of sea level in each grid.

4.3 Subsetted domain

In order to reduce computational resources in its operational configuration, the full domain shown in

Fig. 2 is not used for an individual TC. Instead, a subset of the full grid is defined as a function of the

forecast track (or tracks, in the case of an ensemble.) The geospatial extent of the subsetted grid is

determined from the minimum and maximum longitude values of all ensemble tracks. An additional

padding (currently set at 1,000 km) is applied to the spatial extent of the grid to ensure that the model

domain extent is sufficient to resolve the oceanic dynamics. This means that as the OFT and ensemble

tracks change for different base-times, i.e. between forecasts, the subsetted domain may be different.

4.4 Wave set-up

Wave setup is an additional elevation of water level at the coast due to wave breaking. This process

transfers momentum from the wave field to the depth integrated water column in the surf zone. This is

distinct from wave overtopping, or wave run-up, which relate to the impact of individual waves on

shoreline structures or beaches. Wave setup can be a significant contribution to the total coastal sea

level during Tropical Cyclones, particularly in regions with steep continental slopes (e.g. Kennedy et

al., 2012), such as much of the east coast of Australia.

It is possible to directly calculate the wave set-up from a spectral wave model such as SWAN or

potentially WAVEWATCH3 (it is not currently incorporated in WW3 so would require additional

effort) using radiation stress theory. This is not possible at present due to the computational cost. In

addition, the spatial resolution of national or regional scale wave models does not typically allow

estimates of wave spectra close enough to the coastline. Therefore, wave set-up is typically parametrised

based on estimates of the wave field some distance offshore.

For the initial implementation of the Tropical Storm Surge System the wave setup is calculated from

deterministic AUSWAVE-R operational forecasts (Durrant and Greenslade, 2011; BNOC, 2016). This

is the approach developed by CSIRO for their contribution to the storm surge project (O’Grady et al.

2015). The advantage of this approach is that it is based on an existing Bureau operational system and

the computational cost is minimal. However there are some disadvantages to this approach. These are

identified and briefly discussed in Section 6 and further details may be found in Greenslade (2016).

The parametrisation of wave set-up o( ) was derived from multiple simulations around the Australian

coast made with the SWAN nearshore wave model and is calculated as follows:

( )4

1

7

1

32.08.031.0

−

=

o

s

soL

HSH (4.3)

where Hs is Significant Wave Height (from AUSWAVE-R), Lo is peak wavelength (from AUSWAVE-

R) and S is the bathymetric slope. Bathymetric slopes were determined around the Australian coastline

from the ROMS grid interpolated bathymetry dataset. Operationally, a coastal grid points file is created,

which consists of all the valid model grid points closest to the coast, with single grid point islands

removed where necessary. Total sea level is provided at these coastal points, consisting of the ROMS

surge, wave setup as described above, and tidal predictions interpolated from a pre-computed gridded

tidal prediction file.

5. VERIFICATION

Seven recent TCs are used as test cases for evaluating the system. These are listed in Table 2. These

particular TCs were chosen predominantly due to the availability of a set of sea-level observations from

tide gauges. Five of the TCs made landfall in the Queensland region, one in the Northern Territory and

one in Western Australia.

Tropical

Cyclone Dates

Maximum

Category

Location of maximum

observed surge

Amplitude of maximum

observed surge (m)

QLD TC

Anthony Jan 2011 2 Bowen 0.95

QLD TC Yasi

Jan/Feb

2011 5 Cardwell 5.14

QLD TC Ita Apr 2014 5 Cooktown 1.09

NT TC Lam Feb 2015 4 Groote-Eylandt 0.99

QLD TC

Marcia Feb 2015 5 Port Alma 1.86

WA TC

Olwyn Mar 2015 3 Point Murat 1.07

QLD TC

Nathan Mar 2015 2 Cooktown 0.75

Table 2 Details of the Tropical Cyclones used for verification. Maximum observed surge refers to sea level after

removal of astronomical tides and centering of the residuals (see Section 5.1).

The locations of the Best Tracks for each of these TCs are shown in Fig. 5. These post-analysed Best

Tracks provide a basis for the best possible forcing that can be produced using the method described in

Section 3, and in principle, should provide the best possible characterisation of the resulting storm surge.

For these hindcast case studies, the parameters for determining the wave set-up (see Equation 4.3) are

extracted from AUSWAVE-R historical forecasts taking an analysis field and the subsequent hourly

forecasts until the next analysis is available. This results in an hourly sequence of wave fields consisting

of analyses at 6-hourly intervals (or 12 hours depending on the date), with 5 hours (or 11 hours) of

short-range forecasts between each analysis.

Fig. 5 Best Tracks for the seven events examined.

5.1 Observations

The storm surge hindcasts are evaluated against tide gauge observations. Tide gauges report relative

sea level at a sparse set of point locations; typically in sheltered harbours on structures such as jetties.

These locations are not ideal for sampling the extremes of storm surges, but currently provide the most

fit-for-purpose objective data set available. The measured coastal sea-level signal contains variability

attributable to phenomena across a very wide range of time and space scales, including astronomical

tides, storm surges, tsunamis, infra-gravity waves, seiching and seasonal variability.

All available tide gauge observations were obtained during each event and a series of pre-processing

steps was applied to each sea-level time series to facilitate direct comparison to the model. Temporal

samples were homogenised to regular 10-minute intervals and predicted harmonic tides were

subtracted. The resulting residuals were centred around zero, i.e. the bias (calculated over a time period

of approximately 20 days surrounding the peak surge) was removed from the observations. These pre-

processing steps focus attention on the dynamics of the storm surge and intentionally disregard the other

aspects of what will ultimately constitute a skilful forecast guidance. For this study, the resulting tide

gauge time series were inspected to select those that were near the TC landfall location and showed a

discernible surge (a residual of 0.5m or greater). This provided a total of 21 time series of observed

storm surge over the seven TCs examined.

5.2 Summary of Performance

A summary of the storm surge verification results for all of the case studies is shown in Table 3 and

Table 4. These present the amplitude and timing of the peak observed surge at each tide gauge, along

with the results from the Best Track simulations. Mean values (of maximum sea level) shown in the

tables are calculated as an average over all tide gauges. The components of the sea level (surge and

wave setup) are also provided separately. The question of whether tide gauges observe wave set-up is

debatable. In general, wave set-up is a phenomenon occurring on beaches or exposed coastlines where

waves are breaking, whereas tide gauges are typically located within sheltered harbours. However, the

tide gauges used for this study are mostly quite exposed to the open ocean. Consequently, the tide gauge

observations used here are treated as representative of total surge, i.e. including a wave set-up

component.

Overall, the mean bias in the maximum surge amplitude is -1 cm. This is negligible and suggests that

there is no systematic over- or under-prediction in the system. The mean absolute error of peak surge

is 26 cm. This is a moderate error (approximately 30%) when compared with the mean observed surge

of 1.25 m. However, it is a significant improvement over existing systems (see section 5.4). For 18 of

the 21 sites (86%), the error is less than 0.5m, or 10% of the observed peak (whichever is larger). This

is well within the Bureau of Meteorology's target for operational acceptance (at least 80% of sites with

errors less than 0.5m or 10%).

Peak timings are presented in Table 4. These need to be interpreted with caution as there is one event

(TC Lam) which occurred on a relatively long time scale. In addition, some of the sites had multiple

peaks of similar amplitude which can result in large errors in timing even if the amplitude errors are

very small. This is discussed in the next section. The mean bias in the timing is -30 minutes (negative

means that model is early) and the average absolute value of the error in the timing of the peak is 90

minutes. However, when TC Lam is removed from the average, the absolute difference reduces to 64

minutes, with the mean bias remaining approximately the same (-29 minutes). This early bias may be

partially explained by the fact that the model grid points are always slightly offshore compared to the

tide gauge locations, so the storm surge will arrive at the location of the model grid point before arriving

at the tide gauge.

Note that the observed times were interpolated to 10-minute intervals at 5, 15, 25… minutes past the

hour, while the modelled times are output at 10-minute intervals at 0, 10, 20… minutes past the hour,

so the modelled and observed times are not exactly coincident. This 5-minute offset is not considered a

major issue here, but it should be borne in mind that the minimum achievable difference is 5 minutes.

TC Tide gauge location

Observed

maximum

(m)

Modelled

maximum

(m)

Surge

(m)

Setup

(m)

Diff

(m)

|Diff|

(m)

Diff

(%)

Anthony

Shute Harbour 0.50 0.84 0.76 0.09 0.34 0.34 67.2

Bowen 0.95 0.77 0.68 0.09 -0.18 0.18 18.9

Laguna Quays 0.87 1.61 1.53 0.08 0.74 0.74 85.4

Yasi

Cape Ferguson 1.87 2.00 1.48 0.52 0.13 0.13 7.2

Townsville 2.25 2.04 1.86 0.18 -0.21 0.21 9.2

Cairns 0.96 0.81 0.57 0.24 -0.15 0.15 15.7

Clump Point 2.74 2.55 2.05 0.49 -0.19 0.19 6.8

Cardwell 5.14 4.60 4.36 0.24 -0.54 0.54 10.4

Mourilyan 1.10 1.29 0.52 0.77 0.19 0.19 17.2

Ita

Cape Ferguson 0.62 0.57 0.34 0.23 -0.05 0.05 8.6

Cairns 0.57 0.50 0.36 0.14 -0.07 0.07 11.9

Townsville 0.51 0.42 0.33 0.09 -0.09 0.09 18.0

Cooktown 1.09 1.56 1.30 0.27 0.47 0.47 42.7

Cardwell 0.52 0.61 0.52 0.09 0.09 0.09 17.8

Bowen 0.56 0.34 0.23 0.10 -0.22 0.22 39.6

Lam Groote Eylandt 0.99 0.48 0.46 0.02 -0.51 0.51 51.3

Weipa 0.76 0.30 0.27 0.02 -0.46 0.46 60.5

Marcia Rosslyn Bay 0.52 0.98 0.93 0.05 0.46 0.46 89.4

Port Alma 1.86 1.69 1.66 0.03 -0.17 0.17 9.1

Olwyn Point Murat 1.07 0.98 0.66 0.32 -0.09 0.09 8.1

Nathan Cooktown 0.75 0.95 0.71 0.24 0.20 0.20 26.1

Mean

1.25 1.23 1.03 0.20 -0.01 0.26 29.6

Table 3 Comparison between observed and modelled peak surge amplitude for the 7 TC events studied here.

MAEs less than 0.5m are highlighted in green.

TC Tide gauge location Observed peak

time

Modelled peak

time

Difference

(minutes)

|Difference|

(minutes)

Anthony

Shute Harbour Jan 30 9:55 Jan 30 11:10 75 75

Bowen Jan 30 11:45 Jan30 12:10 25 25

Laguna Quays Jan 30 9:55 Jan 30 10:40 45 45

Yasi

Cape Ferguson Feb 2 15:05 Feb 2 15:50 45 45

Townsville Feb 2 16:45 Feb 2 16:20 -25 25

Cairns Feb 2 17:15 Feb 2 17:00 -15 15

Clump Point Feb 2 14:45 Feb 2 14:10 -35 35

Cardwell Feb 2 15:15 Feb 2 15:10 -5 5

Mourilyan Feb 2 16:45 Feb 2 13:40 -185 185

Ita

Cape Ferguson April 12 22:55 April 12 23:20 25 25

Cairns April 12 5:15 April 12 6:00 45 45

Townsville April 12 21:25 April 12 22:20 55 55

Cooktown April 11 15:25 April 12 13:00 -145 145

Cardwell April 12 14:05 April 12 9:50 -255 255

Bowen April 13 4:15 April 13 4:10 -5 5

Lam Groote Eylandt Feb 19 1:35 Feb 18 19:20 -375 375

Weipa Feb 18 23:15 Feb 19 4:20 305 305

Marcia Rosslyn Bay Feb 20 1:45 Feb 19 23:50 -115 115

Port Alma Feb 20 5:25 Feb 20 4:30 -55 55

Olwyn Point Murat March 12 17:15 March 12 17:30 15 15

Nathan Cooktown March 19 17:25 March 19 16:40 -45 45

Mean -30 90

Table 4 Comparison between observed and modelled peak surge timing for the seven TC events studied here.

5.3 Case Study results

In this section, the comparisons between modelled and observed surge for each TC event are presented

and examined in detail. In the time series plots, the vertical axes are kept constant for all locations for

each TC (but vary from TC to TC), in order to be able to compare the relative signal between locations.

Furthermore, the temporal range of the figures (the horizontal axis) is kept at 2.5 days for all TCs (except

TC Ita and TC Lam which were long-lived events) for consistency.

5.3.1 TC Anthony

Tropical Cyclone Anthony (Auden, 2011) was initially identified as a tropical low in the northwest

Coral Sea on the 22nd January 2011 (see Fig. 5). The low moved away from the Queensland coast and

formed into a TC on the 23rd of January. This system oscillated between a low intensity TC and a

tropical low over the next few days as it circulated in the Coral Sea. As a tropical low, it began to

propagate towards the central Queensland coast on January 29th. It re-intensified into a marginal

Category 2 system before making landfall near Bowen just before 10pm on January 30th.

Fig. 6 Hourly fixes of the Best Track for TC Anthony (light blue crosses) and location of 3 tide gauges (red

diamonds) used for verification

Observations of the storm surge from TC Anthony were available from 3 tide gauges. The locations of

these gauges are shown are in Fig. 6. Figure 7 to Figure 9 show comparisons of the observed and

modelled sea level. In each figure, the left hand panel shows the location of the tide gauge in relation

to the output coastal grid points, and the right hand panel shows the time series of modelled versus

observed surge.

Fig. 7 Left hand panel shows the location of the Bowen tide gauge (green pin) in relation to the local coastline

and the model's coastal grid points (white circles). The closest grid point is indicated by the red circle. Right hand

panel shows de-tided Bowen station data (black diamonds) during TC Anthony compared with the model

hindcast at the closest grid point. Blue line is surge only, green line is wave set-up and red line is surge + wave

set-up.

Fig. 8 Same as Fig. 7 but for Shute Harbour

Fig. 9 Same as Fig 7 but for Laguna Quays

It can be seen that the ROMS simulation performs reasonably well at Bowen, with some slight

underestimation (18cm) of the peak, but overestimates the peak of the surge at Shute Harbour and

Laguna Quays.

5.3.2 TC Yasi

Severe TC Yasi developed as a tropical low northwest of Fiji on 29th January 2011 (Australian Bureau

of Meteorology, 2011) and started propagating towards the west (see Fig. 5). The system rapidly

intensified to a cyclone category and was named Yasi on the 30th January. Yasi maintained its westward

propagation and further intensified to a Category 3 in the afternoon of the 31st January and then

Category 4 in the evening of the 1st February. During this time, Yasi started to accelerate towards the

tropical Queensland coast. Yasi was upgraded to a marginal Category 5 system early on 2nd February

and maintained this intensity as it made landfall early on Thursday 3rd February. Yasi is one of the

most powerful cyclones to have affected Queensland on record. A disaster situation was declared on 2

February for a number of coastal areas from Cairns to Mackay along the coast, and to Mount Isa in the

west. High erosion damage to beaches was reported and there was also damage to local infrastructure

in the Mission Beach to Cardwell area (Queensland Department of Environmental and Resource

Management, 2011).

Fig. 10 Hourly fixes of the Best Track for TC Yasi (blue crosses) and location of the 6 tide gauges (red

diamonds) used for verification

Comparisons of the modelled surge and wave setup with tide gauge observations are shown in Fig. 11

to Fig. 16. It is worth noting that at Mourilyan the wave set-up reaches 0.77 m, which is the highest

wave set-up value seen for any of these case studies and somewhat of an outlier. This is likely due to

the value of the coastal slope at this location. It can be seen that the total surge (ROMS + wave setup)

matches the observed surge very well for this location, and indeed for most locations for this TC. The

total surge at Cardwell is of interest as it is the highest observed surge considered in these case studies.

The ROMS system underestimates this surge by approximately 10%. A large portion of this is likely to

be due to the wave setup – the value of wave setup seen at the peak here is 24cm, which is likely an

underestimate as other studies have estimated the wave setup to be closer to 40cm (e.g. Hetzel et al.,

submitted).

Fig. 11 Left hand panel shows the location of the Cairns tide gauge (green pin) in relation to the local coastline

and the model's coastal grid points (white circles). The closest grid point is indicated by the red circle.

Right hand panel shows de-tided Cairns station data (black diamonds) during TC Yasi compared with

the model hindcast at the closest grid point. Blue line is surge only, green line is wave set-up and red

line is surge + wave set-up.

Fig. 12 Same as Fig. 11 but for Mourilyan

Fig. 13 Same as Fig. 11 but for Clump Point

Fig. 14 Same as Fig. 11 but for Cardwell

Fig. 15 Same Fig. 11 but for Townsville

Fig. 16 Same as Fig. 11 but for Cape Ferguson

Close inspection of the observed time series at Mourilyan shows that the surge consists of two separate

peaks, which are very similar in amplitude but occur about 3 hours apart. The peak of the surge from

the ROMS system matches these peaks well in amplitude but occurs closest to the first peak, which is

marginally lower than the second observed peak, and which is where the timing of the peak is defined.

This is reflected in the verification statistics as noted in section 5.2. Similar features can be seen at

Townsville and Cape Ferguson.

5.3.3 TC Ita

TC Ita began life as a tropical low southwest of the Solomon Islands and was classified as a Category

1 cyclone on the afternoon of April 5th 2014 (Australian Bureau of Meteorology, 2014b). The cyclone

moved slowly westwards, and then remained stationary for two days while continuing to intensify,

reaching Category 3 on April 8th. It then recommenced its westward motion, until the afternoon of

April 10 when it intensified extremely rapidly, reaching Category 5 within 6 hours. At the same time it

turned southwest towards the Queensland coast. TC Ita weakened somewhat in the hours leading up to

landfall and was rated as a Category 4 at landfall on the evening of Friday the 11th.

Upon landfall, TC Ita continued to track southward. It weakened reasonably quickly and passed west

of Cooktown as a Category 2 cyclone. It spent two days propagating southwards over land, but near

the coast, weakening to Category 1. TC Ita eventually moved off the Queensland coast on the night of

April 13th, transitioning into an extra tropical low and accelerating away from the coast.

Fig. 17 Hourly fixes of the Best Track for TC Ita (green crosses) and location of the 6 tide gauges (red

diamonds) used for verification.

Observations of the storm surge from TC Ita were available from 6 tide gauges (see Fig. 17). The

following figures show the location of each tide gauge in relation to the model grid, and the time series

of modelled versus observed sea level at each gauge.

Fig. 18 Left hand panel shows the location of the Cooktown tide gauge (green pin) in relation to the local

coastline and the model's coastal grid points (white circles). The closest grid point is indicated by the red

circle. Right hand panel shows de-tided Cooktown station data (black diamonds) during TC Ita

compared with the model hindcast at the closest grid point. Blue line is surge only, green line is wave

set-up and red line is surge + wave set-up.

Fig. 19 Same as Fig. 18 but for Cairns

Fig. 20 Same Fig. 18 but for Cardwell

Fig. 21 Same as Fig. 18 but for Townsville

Fig. 22 Same as Fig. 18 but for Cape Ferguson

Fig. 23 Same as Fig. 18 but for Bowen

Maximum observed surge for this event was around 1 m at Cooktown. The ROMS model overestimated

the surge by over 40 cm there and was somewhat early, but performed better at the other locations. It

can be seen that the surge was relatively small elsewhere since the TC at that stage was propagating

southwards over land.

5.3.4 TC Lam

Severe TC Lam was the first severe cyclone to cross the Northern Territory coast for nearly a decade

(Australian Bureau of Meteorology, 2015a). On Sunday 15 February 2015, a tropical low over the

northwest Coral Sea crossed Cape York Peninsula and entered the Gulf of Carpentaria. It developed

quickly during the next two days as it moved slowly towards the west. The system was named TC Lam

early on Tuesday 17 February, whilst located over the northern Gulf of Carpentaria. Lam strengthened

into a Category 2 TC that same day and continued to intensify and move slowly westward. Lam was

upgraded to Category 3 on Wednesday 18 February, shortly before it passed directly over the Cape

Wessel Islands (between 136⁰E and 137⁰E longitude). Due to the slow movement of the cyclone, gale-

force winds were experienced at Cape Wessel for a period of approximately 30 hours. Severe TC Lam

took a turn towards the southwest at around midnight on Wednesday 18 February. It then tracked

parallel to the west coast of the Wessel Islands throughout Thursday 19 February, while intensifying

further. Severe TC Lam reached Category 4 intensity that evening and crossed the mainland coast early

on Friday 20 February.

Fig. 24 Hourly fixes of the Best Track for TC Lam (pink crosses) and location of the 2 tide gauges (red


Observations of the storm surge from TC Lam were available from 2 tide gauges. Figure 25 to Figure

26 show the location of each tide gauge in relation to the model grid, and the time series of modelled

versus observed sea level at each gauge. Modelled time series are limited in this case as the Best Track

vortices were not available beyond 0Z on February 20th, when TC Lam made landfall

Fig. 25 Left hand panel shows the location of the Weipa tide gauge (green pin) in relation to the local coastline

and the model's coastal grid points (white circles). The closest grid point is indicated by the red circle.

Right hand panel shows de-tided Weipa station data (black diamonds) during TC Lam compared with

the model hindcast at the closest grid point. Blue line is surge only, green line is wave set-up and red

line is surge + wave set-up.

Fig. 26 Same as Fig. 25 but for Groote Eylandt

As noted in the description of the event, TC Lam was a broad and slow moving event, and the surge

observations reflect this, with peak sea levels of up to 1 m occurring over a period of several days. Note

that these locations are quite distant from the TC track and the peak surges occur around 19th February,

which is when the TC was propagating parallel to the Wessel Islands. The variability in sea level seen

here is due to surge that has propagated away from the regions where it was generated. Despite that fact

that these time series do not represent storm surge at landfall, the model/obs comparisons are included

here, predominantly because there are so few observations available of surge greater than 0.5m, that

any observation at all can provide useful information.

5.3.5 TC Marcia

The tropical low that eventually became severe TC Marcia was first identified in the Coral Sea on

Sunday, February 15th 2015 (Australian Bureau of Meteorology, 2015b). Marcia was tracked over the

next few days as it drifted eastward with little change in intensity. During the afternoon of Wednesday

February 18th 2015, the low pressure system reached TC intensity and was named Marcia, before

beginning to move towards the southwest. Tropical cyclone Marcia continued to intensify during

February 18th and reached Category 2 intensity by that evening. It continued on a south-westerly track

on the 19th and rapidly intensified, increasing by two categories to a Category 4 severe TC in

approximately 12 hours. Late on February 19th, Marcia made a sharp turn towards the south and

intensified even further, and was estimated to have reached Category 5 intensity at 4am on Friday 20th

February.

Severe TC Marcia crossed the coast at Shoalwater Bay as a Category 5 system in the morning of

February 20th. It was a relatively compact system compared to other severe TCs such as severe TC

Yasi and weakened quickly as it moved over land during the day.

Fig. 27 Hourly fixes of the Best Track for TC Marcia (orange crosses) and location of the 2 tide gauges (red


Observations of the storm surge from TC Marcia were available from 2 tide gauges. Figure 28 to Figure

29 show the location of each tide gauge in relation to the model grid, and the time series of modelled

versus observed sea level at each gauge.

Fig. 28 Left hand panel shows the location of the Rosslyn Bay tide gauge (green pin) in relation to the local


circle. Right hand panel shows de-tided Rosslyn Bay station data (black diamonds) during TC Marcia



Fig. 29 Same as Fig. 28 but for Port Alma

The observed storm surge was relatively small at Rosslyn Bay in this case, reaching just over 0.5m and

barely discernible in the observations. At Port Alma, there a clear surge signal in the observations and

this is well captured by the model. However, it is worth noting that the tide gauge is located within the

estuary some distance away from the coastline – the closest model grid point in this case is just over 5

km away from the tide gauge. This may explain the fact that the modelled surge arrives almost an hour

earlier than in the observations.

5.3.6 TC Olwyn

TC Olwyn began as a tropical low in an active monsoon trough approximately 900 kilometres north of

Exmouth on 8 March, 2015. It initially moved slowly towards the east, then towards the south on 10

March. It maintained a southerly track while slowly strengthening and was named TC Olwyn on 11th

March, when it was 500 kilometres north of Karratha (Australian Bureau of Meteorology, 2015c).

Olwyn intensified while moving towards the south-southwest and reached Category 2 in the evening of

11 March. The system accelerated as it approached Exmouth and strengthened to Category 3 intensity

on 12th March when it was located about 155 kilometres north northeast of Exmouth. On 13th March,

Olwyn tracked in a southerly direction down the Gascoyne coast. Olwyn then weakened to Category 2

intensity during the evening of 13 March as it passed to the east of Denham, crossing the coast shortly

afterwards.

Fig. 30 Hourly fixes of the Best Track for TC Olwyn (purple crosses) and location of the tide gauge (red

diamond) used for verification.

Observations of the storm surge from TC Olwyn were available from only 1 tide gauge. Fig. 31 shows

the location of this tide gauge in relation to the model's coastal grid-points, and the time series of

modelled versus observed sea level.

Fig. 31 Left hand panel shows the location of the Point Murat tide gauge (green pin) in relation to the local


circle. Right hand panel shows de-tided Point Murat station data (black diamonds) during TC Olwyn



In this case, the modelled surge replicates the observed surge very well, for both the amplitude and the

timing.

5.3.7 TC Nathan

The final case study considered here is TC Nathan. The tropical low that would become TC Nathan was

first identified and tracked on the morning of Monday 9 March, 2015 in the northern Coral Sea

(Australian Bureau of Meteorology, 2015d). During the next 36 hours the low drifted towards the west-

southwest while slowly intensifying, and was named as Category 1 cyclone Nathan on the evening of

Tuesday 10 March. The cyclone continued to move west-southwest towards Cape York Peninsula while

developing further, reaching Category 2 after another 12 hours on the morning of Wednesday 11 March.

Following this, Nathan remained stationary off the Cape York Peninsula coast for roughly two days at

Category 2 strength.

Nathan was then steered to the east away from the coast for the next two days and became slow moving

then drifted very slowly south for two more days, all this time fluctuating between Category 1 and

Category 2 in intensity. Finally Nathan was again steered westwards towards the Cape York Peninsula

coast and intensified, reaching Category 4 strength in the last hours before it made landfall at about 4am

on Friday 20 March north of Cooktown.

Fig. 32 Hourly fixes of the Best Track for TC Nathan (red crosses) and location of the tide gauge used for

verification (red diamond).

Only one tide gauge (Cooktown) is considered here as the tide gauges within the Gulf of Carpentaria

did not show any discernible surge.

Fig. 33 Left hand panel shows the location of the Cooktown tide gauge (green pin) in relation to the local


circle. Right hand panel shows de-tided Cooktown station data (black diamonds) during TC Nathan



The total storm surge is somewhat overestimated here, with modelled surge of 95 cm compared to

observed surge of 75 cm. The actual ROMS surge component matches the observed surge very well –

it is the wave setup component that contributes to the overestimation. This is also the case for the

Cooktown during TC Ita – the surge matches much better if the wave setup component is not included.

This suggests that perhaps Cooktown is a tide gauge for which wave setup is not observed.

5.4 Comparison with existing systems

Within the Bureau of Meteorology’s Tropical Cyclone Warning Centres in Queensland, the Northern

Territory, and WA, parametric systems are used to provide operational forecasts of storm surge. These

have been briefly described in Section 2.In this section, the storm surge hindcasts at tide gauge locations

from these systems are compared, where possible, with those described in the previous section from the

ROMS system. The operational systems are provided with the same Best Track forcing information as

the ROMS system. Only the 5 QLD events using SEAtide are included here. SEAtide forecasts are not

currently available at tide gauge locations for TC Lam due to the configuration of SEAtide in the

Northern Territory, and the WA system provides a 'worst case' forecast, which is not comparable with

the deterministic forecasts assessed here. There are a total of 18 valid observations of surge for which

hindcasts are available from both the ROMS system and SEAtide.

A summary of the errors in peak surge amplitude for each system is presented in Table 5. For these 18

observed surges, the Mean Absolute Error (MAE) for ROMS (25 cm) is half that of SEAtide (51 cm).

The bias for ROMS (4 cm) is also significantly smaller than that of SEAtide (-41 cm). It should be noted

that SEAtide values refer to surge only as wave set-up is not provided at tide gauge locations. If it is

assumed that wave set-up is around 20 cm (see Table 3), and this is added to the SEAtide estimates,

this would result in a somewhat smaller negative bias (approximately -20 cm) for SEAtide and a smaller

MAE (39 cm). The lowest absolute error for each site is shaded in green and it can be seen that ROMS

has the lowest MAE for 13 out of 18 sites (72%).

It should also be noted that there are limitations to the underlying technique used for SEAtide which

means that it is not really able to provide a surge forecast for some locations when the TC track is

complex. This is a limitation of any parametric system. SEAtide assumes that once the TC has made

landfall, it continues its track without changing direction or intensity. This means that it is not able to

model a complex track such as that of TC Ita, which propagated southwards along the coast after making

landfall. This can be seen in the very low amplitudes of the SEAtide surge for TC Yasi at Cairns and

Cape Ferguson and most locations for TC Ita. If the cases for which the amplitude of the surge is 0.0

m or 0.1 m are removed, then the performance of SEAtide improves somewhat. The bias reduced to -

32cm (-12cm if wave setup is added) and the MAE reduces to 47 cm (39 cm if wave setup is added).

A summary of the errors in peak surge timing is shown in Table 6 for the 5 Queensland TCs. The

statistics here for ROMS (bias = -32 minutes and MAE = 67 minutes) are similar to those overall as

presented in section 5.2, except that the absolute value of the difference is considerably smaller, since

TC Lam is not included here. SEAtide can be seen to perform very poorly in terms of timing. This is

predominantly due to the inclusion of locations for which SEAtide is not designed to predict surge, as

discussed above. If the cases for which the amplitude of the surge is 0.0 m or 0.1 m are removed as

before, the performance of SEAtide is more comparable to ROMS (mean bias of 26 minutes and

absolute difference of 84 minutes).

In summary, these results demonstrate that not only is the dynamic ROMS system able to provide

forecasts of surge for a larger set of locations than existing systems, but in addition, the accuracy of the

ROMS system is a significant improvement over the existing parametric systems, given the same Best

Track forcing.

ROMS SEATIDE

Obs max

(centred)

Best track

max Difference

Abs

(Difference)

Percent

difference

Best

track

max

Difference Abs

(Difference)

Percent

difference

TC

Anthony

Shute Harbour 0.50 0.84 0.34 0.34 68 0.4 -0.10 0.10 20

Bowen 0.95 0.77 -0.18 0.18 19 0.7 -0.25 0.25 26

Laguna Quays 0.87 1.61 0.74 0.74 85 0.6 -0.27 0.27 31

TC Yasi

Cardwell 5.14 4.6 -0.54 0.54 11 5.3 0.16 0.16 3

Clump Point 2.74 2.55 -0.19 0.19 7 2.4 -0.34 0.34 12

Townsville 2.25 2.04 -0.21 0.21 9 1.0 -1.25 1.25 56

Cape Ferguson 1.87 2 0.13 0.13 7 0.5 -1.37 1.37 73

Mourilyan 1.10 1.29 0.19 0.19 17 0.4 -0.70 0.70 64

Cairns 0.96 0.81 -0.15 0.15 16 0.0 -0.96 0.96 100

TC Ita

Cape Ferguson 0.62 0.57 -0.05 0.05 9 0.0 -0.62 0.62 100

Cairns 0.57 0.5 -0.07 0.07 12 0.1 -0.47 0.47 82

Townsville 0.51 0.42 -0.09 0.09 18 0.0 -0.51 0.51 100

Cooktown 1.09 1.56 0.47 0.47 43 0.9 -0.19 0.19 18

Cardwell 0.52 0.61 0.09 0.09 18 0.1 -0.42 0.42 81

Bowen 0.56 0.34 -0.22 0.22 40 0.0 -0.56 0.56 100

TC

Marcia

Roslyn Bay 0.52 0.98 0.46 0.46 88 0.8 0.28 0.28 54

Port Alma 1.86 1.69 -0.17 0.17 9 1.6 -0.26 0.26 14

TC

Nathan

Cooktown 0.75 0.95 0.20 0.20 27 1.2 0.45 0.45 60

Average 1.30 1.34 0.04 0.25 27.86 0.89 -0.41 0.51 55.22

Table 5 Comparison between ROMS and SEAtide errors in peak surge amplitude. All values except percentages in (m). Green shading indicates the lowest absolute error for

each site.

ROMS SEATIDE

TC Tide gauge

location

Observed

peak day

Observed

peak time

Modelled

peak day

Modelled

peak time

Difference

(minutes)

Difference

(minutes)

Modelled

peak day

Modelled

peak

time

Difference

(minutes)

|Difference|

(minutes)

Anthony

Shute

Harbour Jan-30 9:55 Jan-30 11:10 75 75

Jan-30 11:09 74 74

Bowen Jan-30 11:45 Jan-30 12:10 25 25 Jan-30 13:09 84 84

Laguna

Quays Jan-30 9:55 Jan-30 10:40 45 45

Jan-30 11:29 94 94

Yasi

Cape

Ferguson Feb-02 15:05 Feb-02 15:50 45 45

Feb-02 15:01 -4 4

Townsville Feb-02 16:45 Feb-02 16:20 -25 25 Feb-02 15:31 -74 74

Cairns Feb-02 17:15 Feb-02 17:00 -15 15 Feb-02 21:51 216 216

Clump

Point Feb-02 14:45 Feb-02 14:10 -35 35

Feb-02 13:01 -104 104

Cardwell Feb-02 15:15 Feb-02 15:10 -5 5 Feb-02 16:11 56 56

Mourilyan Feb-02 16:45 Feb-02 13:40 -185 185 Feb-02 21:01 256 256

Ita

Cape

Ferguson Apr-12 22:55 Apr-12 23:20 25 25

Apr-10 12:00 -3535 3535

Cairns Apr-12 5:15 Apr-12 6:00 45 45 Apr-11 23:59 316 316

Townsville Apr-12 21:25 Apr-12 22:20 55 55 Apr-10 12:00 -3445 3445

Cooktown Apr-11 15:25 Apr-12 13:00 -145 145 Apr-11 13:49 -96 96

Cardwell Apr-12 14:05 Apr-12 9:50 -255 255 Apr-11 23:59 -846 846

Bowen Apr-13 4:15 Apr-13 4:10 -5 5 Apr-10 12:00 -3855 3855

Marcia

Rosslyn

Bay Feb-20 1:45 Feb-19 23:50 -115 115

Feb-20 0:39 -66 66

Port Alma Feb-20 5:25 Feb-20 4:30 -55 55 Feb-20 5:19 -6 6

Nathan Cooktown Mar-19 17:25 Mar-19 16:40 -45 45 Mar-19 18:59 94 94

Mean -32 67 -602 735

Table 6 Comparison between ROMS and SEAtide errors in peak surge timing.

6. FURTHER WORK

This report has documented the initial setup and configuration of the Tropical Storm Surge system. Its

performance in terms of hindcast accuracy has been shown to be a significant improvement over the

SEAtide storm surge system. This report has focussed on verifying the hydrodynamic model (ROMS)

forced by parametrised TC vortices derived from Best Track information. The operational system

consists of a set of ensemble forecasts forced by a set of ensemble TC tracks derived using the

‘DeMaria’ method (DeMaria et al., 2009). In order to fully verify the forecast system, there is a need to

consider the probabilistic information obtained from the ensemble storm surge forecast system. This

will be the subject of a further report. Similarly, although significant for the full forecasting system, the

harmonic tidal component of sea level and spatial reference levels have not been addressed in this

document.

Verifications have been undertaken for seven TC test cases occurring in recent years, but this included

only one extreme event, where observed surge was greater than 2 m (TC Yasi). For this case the surge

was slightly underestimated (10%). This suggests that in order to provide confidence in forecasts of

storm surge using this system, further verifications for extreme events are needed.

Verification would be greatly facilitated through establishing an improved database of tide gauge

observations and metadata. The Bureau operates only a small subset of the existing tide gauges and

thus treatment of ‘3rd party’ instruments is important. Associating observed sea levels with official tide

predictions and site metadata is also required. Such homogenous data handling has been lacking to

date and continues to present challenges. Improving the Bureau's sea level verification data foundations

would offer immediate benefits not only to TC case studies, but to a range of coastal and ocean

forecasting systems.

Representation of the bottom momentum loss is a modelling detail worth further attention. Spatially

variable bottom friction parametrisation is likely to be more realistic in regions such as the Great Barrier

Reef, where individual reefs are not resolved by the grid. Some initial investigation into this aspect was

undertaken for the Queensland domain (see section 4.1) and could be leveraged for further work.

Alternative parametrisations of the wind stress could also be investigated. In this first implementation,

a capped version of the Large and Pond (1981) formula is used, as described in section 3. Air-sea

interaction and momentum fluxes within extreme environments such as TCs is an active area of research

and there are numerous alternative methods for deriving wind stress that could be evaluated.

Initially this project explored options to merge the TC vortex with a background NWP field (i.e.

ACCESS-R) to provide a more realistic of set of forcing fields for the ROMS model. This approach

was ultimately abandoned due to challenges in developing techniques to remove existing vortices for

the real-time application. However, the lack of a background NWP field may become an issue in an

ensemble system, particularly for cases where the tracks diverge substantially in space as the TC makes

landfall. The distribution of sea level at any particular forecast location is made up of sea level from

each of the ensemble tracks. For any tracks that are distant from the forecast location, the surface forcing

fields will be 'null' at that location, and the probability distribution of sea-levels there will not be an

accurate reflection of the true probability distribution. A further benefit of merging the vortex with a

background NWP field is that it will be more consistent with the National Storm Surge System and will

be a step towards an integrated coastal sea level forecast system.

A key limitation of the existing system is the way in which wave set-up is calculated. For the initial

operational implementation, wave setup is based on offshore estimates of Significant Wave Height and

Peak Period obtained from deterministic AUSWAVE-R forecasts and calculated using a

parameterisation developed by CSIRO (O’Grady et al., 2015), which also depends on bathymetric

slope. There are two aspects by which this could be improved. Firstly, and specifically related to the

ensemble system, by developing offshore wave fields that are related to each ensemble member, rather

than using the same wave field (i.e. AUSWAVE-R forced by ACCESS-R) for all ensemble members,

and secondly though improving the algorithm used for the calculation of wave setup from the offshore

wave information. See Greenslade (2016) for further discussion on these options.

Allen et al (2018), amongst other authors, have shown that non-linear interactions between tide and

surge can, on occasion, have a significant impact on coastal sea level. These interactions are neglected

in the present system, by linearly superimposing the astronomical tide and surge components. This issue

should be explored in future, although it is expected that there will be an increase in the computational

resources required, which will need to be balanced against any gain in skill.

The definition of the spatial grid has a significant impact on computational cost, which is a major

constraint for operational systems, particular those underpinning warning services. A more generalised

spatial solution (e.g. a relocatable domain, unstructured grid etc.) could reduce the computational cost,

and/or provide coverage of further locations and extension of verification opportunities.

There is considerable scope for improved systems integration. This report has not addressed issues

related to solutions-architecture, however, future development should be well informed of ongoing

changes in the operational environment, including developments in related hydrodynamic systems, such

as OceanMAPS, AUSWAVE or tropical NWP prediction systems.

In the longer term, inundation forecasts may be possible. The existing storm surge system produces

forecasts of coastal sea level, with the implicit assumption that a higher sea level means a more severe

impact. Emergency managers are familiar with these types of forecasts and have existing procedures to

include this information in their decision-making processes. However, a potential enhancement to the

forecast system could be through the development of inundation forecasts. This would provide much

more detailed information on the expected impacts for any particular TC event and could refine the

areas where evacuation is (or isn’t) required. Coastal inundation has already been addressed within the

Bureau of Meteorology to a limited extent for the Joint Australian Tsunami Warning Centre (Allen and

Greenslade, 2016). One issue to address is whether coastal inundation should be considered via an

holistic approach, encompassing inundation from all potential sources, or if each existing forecast

system should be further developed individually, using techniques that may be specific to that

application.

A related issue is the interaction with hydrological phenomena such as river flow. There are two-way

interactions that would need to be taken account of, with coastal sea level from the surge system

providing boundary conditions for river levels, and conversely, a variable river flow could potentially

have an impact on the coastal sea level, particularly in estuaries. A further related issue is the effect of

heavy rainfall, which has been shown to have an impact on coastal sea level in TC conditions (e.g.

Wong and Toumi, 2016). Initial efforts to explore these aspects have been undertaken by De

Kleermaeker et al (2018) along with an investigation into the possibility of impact forecasting.

The Bureau of Meteorology is currently putting a considerable amount of effort into the development

of coastal modelling. In addition to the Tropical Storm Surge system described in this report, the

National Storm Surge system has been implemented operationally (Allen et al., 2018) and a baroclinic

high resolution coastal modelling system, also based on ROMS, is being developed for the Great Barrier

Reef region under the eReefs project. The tsunami model that underpins warnings from the Joint

Australian Tsunami Warning Centre is another relevant modelling system. While most of these systems

are in their infancy, and each system is intended for a different purpose, there is potential in the longer

term to merge them into a single coastal dynamics forecast system which could service a number of

different purposes.

7. ACKNOWLEDGEMENTS

• Andrew Donaldson, Jason Brownlee and Stephen Taylor are thanked for their assistance with TC

Module and providing the Best Track data.

• Tony Wedd (QLDRO) is thanked for providing the comparison data from SEAtide used in Section

5.4. Brad Santos, Andrew Burton (WARO) and Ian Shepherd (NTRO) are also thanked for useful

discussions relating to existing forecast systems.

• Stewart Allen is acknowledged for creating the first version of the ribbon grid.

• Mikhail Entel, Stewart Allen and Tony Hirst are thanked for constructive reviews of early drafts of

the manuscript.

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