aww2013: climate modelling: a guide to investment decisions by vicky pope

7/29/2019 AWW2013: Climate modelling: A Guide to Investment Decisions by Vicky Pope

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C mate mo e ng: A gu e to investment decisions

Vicky Pope

Met Office Hadley Centre



The impact of a global temperature rise

of 4 ºC

Change in temperature from pre‐industrial climate

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Melting

ice

Methane

release

Ocean

Reduced

crops

Increased

drought

ore

heatwaves

Acidification

Rainforest

loss

fireStronger

tropical storms

Current City population • 3‐10 million • 10‐20 million© Crown copyright Met Office



The benefits of integrated services:for policy and long term planning



Bridging the Gaps and Bridging the Scales

Weather/Climate Model : 25 -100km

Regional

Weather/Climate Regional Impacts

Regional Impacts

Models : Hydrology,model : 25 - 12km Model:Vegetation,

Topography

Local Local Decision-

Making : Land

use Water use

downscaling model :

AdaptiveResponses

-

© Crown copyright Met Office



Future Nile flow:

A Climate

Chan e

Risk

Mana ement

Pro ramme

• Impact on

water

resources

by 2050s

• Possible adaptation

• Regional climate

models

an e orecas ng

system

•

• Rainfall and river runoff –wide range of possible

outcomes

Image NASA




Changes in rain and snowfall in the high W E

Summer precipitation (Indian monsoon)Winter precipitation (Western disturbances)

NW

J00020502100H1950200020502100-202461950200020502100-20246JK00020502100HP1950200020502100-10010203040NB1950200020502100-10010203040JK00020502100HP1950200020502100-0.50.00.51.01.5NB1950200020502100-0.50.00.51.01.5JK00020502100HP1950200020502100-1.5-1.0-0.50.00.51.0NB1950200020502100-1.5-1.0-0.50.00.51.0

Karakoram Hindu Kush Jammu‐Kashmir ,

Uttarakhand & West Nepal

Bhutan

i o n m m / d a y


g e i n

p r e c i p i t a t


C h a

d a y

Karakoram


n s n o w f a l l m m

/


C

h a n g e i

Time‐ Met Office model ‐ MPI model



Probability forecasts of coastal flood risk:

Balanced a roach

to

decision

makin

U er limit of from UKCP models

"high++“ model

Change in

extreme sea

level of 50 year

storm




Energy project

results

© Crown copyright Met Office© Crown copyright Met Office



The benefits of integrated services:

for planning and civil contingencies



Seamless predictionSupporting decision making

N o w

o u r s

a y s

e e k

n t h

o n a l

a d a l

a t e

a t e

c e r y

H 1

‐

1 ‐ m

S e a s

D

e C l i

P a s t c

l i

C o n f i d e

b

o u n d a

Analysis of

past

weather

climate risks

Eg. Agriculture: this informs

crop choice and planting date

Monthly to decadal

predictions informs

probability of drought, cold,

heat.

minimise crop

failure

risk. Pre icting

routine

an

hazardous weather conditions

and disseminating tailored

and timely warnings.

Contingency planners,

national and international

humanitarian response,

overnment and rivate

Global and regional climate

predictions.

Informs mitigation policy and


Forecast lead‐time

u c, emergency response,

international disaster risk

reduction

infrastructure investmenta a p a o n c o ces. mpac s

on water resurces, heat

stress,

crops,

infrastructure.



Example of seasonal prediction of

reservoir

management

Ghana , • 1000MWatt facility: provides ~50% of

Ghana’s electricity

Lake

Volta

• Rainfall has strong seasonal dependency:

peak

months

June‐

September

• Inflow prediction needed to assess likely

requirement for oil‐fired generation

• …thus lake‐level is monitored closel !




Summary

•

adaptation‐

e.g. River

Nile,

Hamalayas

• .

skilful in some regions and aggregated over

re ions such as lar e water catchments – Volta

• ‘Seamless prediction’ addresses climate

• Integrated approach provides environmental


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