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Evaluation of severe wind hazard from tropical cyclones - current and future climate simulations

Pacific-Australia Climate Change Science and Adaptation Planning Program

Geoscience Australia
Record 2014/47

A.A. Siqueira, C. Arthur, M. Woolf



australian government: geoscience australia logo.

Department of Industry

Minister for Industry: The Hon Ian Macfarlane MP


Parliamentary Secretary: The Hon Bob Baldwin MP
Secretary: Ms Glenys Beauchamp PSM

Geoscience Australia

Chief Executive Officer: Dr Chris Pigram
This paper is published with the permission of the CEO, Geoscience Australia

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© Commonwealth of Australia (Geoscience Australia) 2014

With the exception of the Commonwealth Coat of Arms and where otherwise noted, all material in this publication is provided under a Creative Commons Attribution 3.0 Australia Licence. (http://www.creativecommons.org/licenses/by/3.0/au/deed.en)

Geoscience Australia has tried to make the information in this product as accurate as possible. However, it does not guarantee that the information is totally accurate or complete. Therefore, you should not solely rely on this information when making a commercial decision.

Geoscience Australia is committed to providing web accessible content wherever possible. If you are having difficulties with accessing this document please email clientservices@ga.gov.au.

ISSN 2201-702X (PDF)

ISBN 978-1-925124-41-5 (PDF)

GeoCat 79681



Bibliographic reference: Siqueira, A.A., Arthur, C., & Woolf, M. 2014. Evaluation of severe wind hazard from tropical cyclones - current and future climate simulations. Pacific-Australia Climate Change Science and Adaptation Planning Program. Record 2014/47. Geoscience Australia, Canberra. http://dx.doi.org/10.11636/Record.2014.047

Contents

Evaluation of severe wind hazard from tropical cyclones - current and future climate simulations 1

Pacific-Australia Climate Change Science and Adaptation Planning Program 1

Executive Summary 5

Executive Summary 5

1.Introduction 7

1.Introduction 7

2.PACCSAP study area 8

2.PACCSAP study area 8

3.Data 9

3.Data 9


a.Historical best-track record 10

a.Historical best-track record 10

b.Tropical Cyclone-Like Vortices (TCLVs) 11

b.Tropical Cyclone-Like Vortices (TCLVs) 11

4.Methods 12

4.Methods 12

a.Tropical Cyclone Risk Model - TCRM 13

a.Tropical Cyclone Risk Model - TCRM 13

b.TCLV direct-detection 16

b.TCLV direct-detection 16

5.Results and discussion 17

5.Results and discussion 17

a.Historical climate cyclonic wind hazard (1981-2011) 18

a.Historical climate cyclonic wind hazard (1981-2011) 18

b.TCLV-derived cyclonic wind hazard 23

b.TCLV-derived cyclonic wind hazard 23

5.b.1Current climate simulations (1981-2000) 24

5.b.1Current climate simulations (1981-2000) 24

5.b.2Future climate simulations (2081-2100) 26

5.b.2Future climate simulations (2081-2100) 26

c.Comparison between current and future climate simulations 27

c.Comparison between current and future climate simulations 27

5.c.1Individual models comparison 28

5.c.1Individual models comparison 28

5.c.2Model ensemble 33

5.c.2Model ensemble 33

6.Conclusions 38

6.Conclusions 38

Glossary 39

Glossary 39

Acknowledgements 40

Acknowledgements 40

References 41

References 41

7.PACCSAP country capitals location 42

7.PACCSAP country capitals location 42

8.25, 50 and 100 return period cyclonic wind speed for current and future climate simulations 42

8.25, 50 and 100 return period cyclonic wind speed for current and future climate simulations 42

a.Current climate simulations (1981-2000) 43

a.Current climate simulations (1981-2000) 43

b.Future climate simulations (2081-2100) 46

b.Future climate simulations (2081-2100) 46

9.Historical best-track record (1981-2011) and current climate simulations (1981-2000) 48

9.Historical best-track record (1981-2011) and current climate simulations (1981-2000) 48

10.Future climate simulations (2081-2100) for each capital 62

10.Future climate simulations (2081-2100) for each capital 62

11.Spatial distribution of the relative change in the 500-year return period cyclonic wind speed 77

11.Spatial distribution of the relative change in the 500-year return period cyclonic wind speed 77

a.NorESM1-M 78

a.NorESM1-M 78

b.CSIRO-Mk3.6 81

b.CSIRO-Mk3.6 81

c.IPSL-CM5A 84

c.IPSL-CM5A 84

d.MRI-CGM3 87

d.MRI-CGM3 87

e.GFDL-ESM2M 90

e.GFDL-ESM2M 90



Executive Summary

In June 2012 Geoscience Australia was commissioned by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) to undertake detailed wind hazard assessments for 14 Pacific Island countries and East Timor as part of the Pacific-Australia Climate Change Science and Adaptation Planning (PACCSAP) program. The PACCSAP program follows on from work Geoscience Australia did for the Pacific Climate Change Science Program (PCCSP) looking at the Coupled Model Intercomparison Project phase 3 (CMIP3) generations of climate models. The objective of this study was to improve scientific knowledge by examining past climate trends and variability to provide regional and national climate projections. This document presents results from current and future climate simulations of severe wind hazard from tropical cyclones for the 15 PACCSAP partner countries and describes the data and methods used for the analysis.

The cyclonic wind hazard was estimated for current (1981 to 2000) and future (2081 to 2100) climate scenarios. Tropical cyclone-like vortices from climate simulations conducted by CSIRO using six Coupled Model Intercomparison Project phase 5 (CMIP5) models (BCC-CSM1.1, NorESM1-M, CSIRO-Mk3.6, IPSL-CM5A, MRI-CGM3 and GFDL-ESM2M), as well as the International Best Track Archive for Climate Stewardship, were used as input to the Geoscience Australia’s Tropical Cyclone Risk Model to generate return period wind speed for the 15 PACCSAP partner countries. The Tropical Cyclone Risk Model is a statistical-parametric model of tropical cyclone behaviour, enabling users to generate synthetic records of tropical cyclones representing many thousands of years of activity.

The CMIP5 models tended to disagree when considering the relative change in the annual TC frequency. According to Taylor, et.al (2012), disagreement between CMIP5 models may be due to the variety of model formulations and model resolutions as well as the climate “noise”. BCC-CSM1M and IPSL-CM5A models presented an increase in the annual TC frequency for East Timor, northern hemisphere and southern hemisphere. On the other hand, NorESM1M showed a decrease in the annual TC frequency for the same areas. The other three models showed a mix of increase and decrease in their annual TC frequency.

The tropical cyclone annual frequency derived from the CMIP5 models ensemble mean indicated a slight increase in the tropical cyclone frequency within all three regions considered in this study; however a t-Test (Two-Sample Assuming Unequal Variances) showed that this increase was not statistically significant at the 5% confidence level.

The 500-year return period cyclonic wind speed was analysed and discussed in more detail in this report, since it is used as a benchmark for the design loads on residential buildings. Results indicated that there was not a consistent spatial trend for the relative change in the 500-year return period cyclonic wind speed when outputs of the TCRM using the CMIP5 models were compared individually.

When looking at individual capital cities, there was a slight increase in the 500-year return period cyclonic wind speed ensemble mean varying between 0.8% (Port Vila) to 9.1% (Majuro). A decline of around 2.4% on average in the 500-year return period cyclonic wind speed ensemble mean was observed in Dili, Suva, Nukualofa and Ngerulmud. However, the relative change in the 500-year return period cyclonic wind speed ensemble mean was not considered significant when compared to the ensemble mean standard deviation.

Based on the CMIP5 models ensemble mean, the TCRM spatial relative change outputs did not show any particular consistency for the 500-year cyclonic wind speed amongst the three study regions (East Timor, northern hemisphere and southern hemisphere). Areas where the Marshall Islands and Niue are located presented an increase in the 500-year cyclonic wind speed, while a decrease was observed in areas south of Vanuatu, east of Solomon Islands, south of Fiji and some areas in Tonga.

The range of projected changes in tropical cyclone frequency and intensity derived from CMIP5 models generally provided non statistically significant results. However, this information combined with other PACCSAP program outputs has the potential to be used to build partner country capacity to effectively adapt and plan for potential increases in the impact or risk posed by tropical cyclones under future climate.


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