INCORPORATING CLIMATE CHANGE INTO ENGINEERING DESIGN ALONG THE - - PowerPoint PPT Presentation

INCORPORATING CLIMATE CHANGE INTO ENGINEERING DESIGN ALONG THE EASTERN AUSTRALIA COAST

William Peirson, Thomas Shand, Nathan Guerry, Mahmudul Hassan, James Ruprecht, Jason Evans, Ron Cox

Funding from: US Army Engineer Research and Development Centre International Research Office (1413-EN-01) Australian Climate Change Adaptation Research Network for Settlements and Infrastructure (ACCARNSI) NSW Government Office of Environment and Heritage under its Adaptation Hub, Coastal Adaptation Node

FLOODS → ←STORMS

PROBLEM

PRESENT MEAN SEA LEVEL WHERE PEOPLE LIVE AND SERVICES ARE NOW NSW PRESENT COASTAL PLANNING PROCESS 100 YEAR ARI STORM 100 YEAR ARI FLOOD + REALITY FUTURE PLANNING?

10s TO 100s OF $ BILLIONS IN ADAPTATION

SEA LEVEL RISE

Opportunity

• Big storms of concern in more temperate zones can be identified in

climate models

• Temperate coastal zones are big population centres in USA and

Australia

• Big storms are a major contributor to large scale flooding and storm

surge

• This information is not being used in any practical sense to assess

adaptive capacity

• Cost of overadaptation is potentially crippling

STORM DESIGN CONTRIBUTIONS

Water levels

• Mean sea level – approximately static for the last 4000 years
• Atmospheric tide – analysis of historical data yields reliable
• predictions. Numerical models???
• Barometric set up – driven by atmospheric pressure – negligible lag

in most Australian coastal waters

• Wind set up – wind-induced – greatest in shallow waters
• Wave set up (down) – due to breaking of storm waves are generated

by wind

• Backwater – due to rain-induced runoff
• (Runup – vertical extent of wave movement at shoreline)

GLOBAL CIRCULATION MODELS

GCMs and IPCC

• Complex numerical models (tools )
• Three dimensional grid over the globe (typical horizontal resolution of

400 km, 15 layers in the atmosphere and 20 layers in the oceans).

• Small scale processes (e.g. clouds, boundary layers) cannot be

properly modelled, therefore averaged

• Include feedback mechanisms for water vapour and warming, clouds

and radiation, ocean circulation and ice and snow albedo.

• Different parametric approaches yield different results.

http://www.ipcc-data.org/ddc_gcm_guide.html

www.sas.usace.army.mil/.../images/drought.jpg

GCMs and IPCC

GCM types

• Reanalysis models

–

• bserved data are assimilated into the models

– hindcast of observed climate history – no forecast capability – NCEP-NCAR 20th Century Reanalysis V2 – ECMWF Reanalysis 40 – (NOT THE SUBJECT OF THIS PRESENT PRESENTATION)

• Predictive-type models

– initiated with ‘spin-up’ conditions – propagate according to their internal physics – should yield statistical distributions of atmospheric behaviour that are consistent with measured data. – predictive capability for future climates when configured with a corresponding emission scenario.

Predictive GCM objectives

1. Consistency with global projections (1.4°C to 5.8°C by 2100) 2. Physical plausible. 3. Applicable to impact assessments. 4. Representative of the potential range of future regional climate change. 5. Accessible for impact assessment.

Present Project

• A first pass assessment of the ability of GCM performance in

temperate zones: surface pressures, winds, rain

• Suite of reanalysis and predictive GCMs
• A collaborative study of WRL, USACE and UNSWCCRC

www.sas.usace.army.mil/.../images/drought.jpg

Model ID Sponsor, Country CSIRO-Mk3.0 Commonwealth Scientific Industrial and Research Organisation, Australia CSIRO-Mk3.5 Commonwealth Scientific Industrial and Research Organisation, Australia GFDL-CM2.0 Geophysical Fluid Dynamics Laboratory, United States of America GFDL-CM2.1 Geophysical Fluid Dynamics Laboratory, United States of America GISS-ER NASA/ Goddard Institute for Space Studies, United States of America NCAR-CCSM3 National Centre for Atmospheric Research, United States of America MIUBEG ECHO-G Meteorological Institute of the University of Bonn, Meteorological Research Institute of KMA, and Model & Data Group, Germany/ Korea

What this study did not do

1. Downscale – Statistical – Numerical 2. Resolve short duration events – GCMs use 24 hour time step

Statistical comparison between model surface predictions and high quality coastal observations

earthobservatory.nasa.gov

3 key questions

earthobservatory.nasa.gov

• 1. Do GCMs show signs of numerical saturation – that is, do extreme

pressures, winds, precipitation reach ceiling levels that are not exceeded due to resolution or physics?

• 2. To what degree do GCMs replicate observed latitudinal variation in

extreme values?

• 3. What changes in extreme values can be observed between climate of

the 20th century (c30m) and plausible future climates (SRES A2)?

Q1: Do GCMs show signs of numerical saturation?

earthobservatory.nasa.gov

Q2: Do GCMs replicate observed latitudinal variation in extremes?

• Extreme mean sea level pressures are well predicted. (solid line

shows measured data, other line styles are models)

Q2: Do GCMs replicate observed latitudinal variation in extremes?

• Extreme winds are remarkable. (Dashed line shows 24 hour 20year ARI design

from AS1170 + CEM EM 1110-2-1100 (Part 2) Figure II-2-1, symbols are models)

2 4 6 8 10 12 14 16 18 20 ONSHORE WIND VELOCITY (m/s)

• 44
• 42
• 40
• 38
• 36
• 34
• 32
• 30
• 28
• 26
• 24

LATITUDE

NOTE: winds over

• cean are ~ 5 to 8m/s

higher than over land. Figure shows ocean values.

Q2: Do GCMs replicate observed latitudinal variation in extremes?

• Significant latitudinal gradient in 20 year ARI precipitations.(solid line

shows measured data, other line styles are models)

How well can downscaling improve these estimates?

Q3: What changes in extremes are predicted 20thC to future?

• No statistically significant change in 20 year ARI mean sea level

pressure from 20th century climate up to 2100 A2 emission scenario can be discerned.

• No statistically significant variation in 20 year ARI precipitation

can be discerned up to 2100 horizon under an A2 emission scenario.

• No statistically significant change in 20 year ARI mean winds

under A2 emission scenario can be discerned to 2050.

Q3: What changes in extremes are predicted 20thC to future?

• Over a 100 year time horizon, a decrease in the onshore component
• f wind velocity between 0 and 4ms-1 is predicted at the 20 year ARI.
• 5
• 4
• 3
• 2
• 1

1 2 3 4 5 CHANGE IN WIND VELOCITY (m/s)

• 44
• 42
• 40
• 38
• 36
• 34
• 32
• 30
• 28
• 26
• 24

LATITUDE

Corresponding reductions in set up and coastal breaking wave heights are anticipated.

Conclusions and Recommendations

• Coastal storm attack has both marine and inland contributions.
• GCM skill in representing 20 year ARI mean sea level pressure, wind and precipitation

has been quantified.

• Clear extreme distributions of the state variable relevant to larger-scale coastal storm

attack are available.

• Changes for the A2 scenario are predicted to be negligible except a slight decrease in

wind is predicted.

• More intense storms less frequently means little change at a given design ARI.
• This study has not investigated changes in wind direction but robust determinations are

likely to be elusive.

• Defining the joint probabilities of the individual contributions and adaptive capacity are

now being assessed.

PROBLEM

PRESENT MEAN SEA LEVEL WHERE PEOPLE LIVE AND SERVICES ARE NOW NSW PRESENT COASTAL PLANNING PROCESS 100 YEAR ARI STORM 100 YEAR ARI FLOOD + REALITY FUTURE PLANNING?

10s TO 100s OF $ BILLIONS IN ADAPTATION

SEA LEVEL RISE