Towards determining ‘reliable’ 21st century precipitation and temperature change signal from IPCC CMIP3 climate simulations

Abha Sood

Brett Mullan, Stephen Stuart & Sam DeanClimate Variability Group, NIWA, Wellington

Task:To quantify 21st century regional Precipitation and Temperature climate change signal for end users in agriculture, industry, government, …

Consistency and predictability &

Accuracy and Reliability

Can this be achieved?

Model Credibility

Some problems!!

Start from the beginning!

Change in December-February precipitation (in %), between 1971-2000 and 2071-2099, under an A2 emission scenario

The Experiment

Control ‘Warm’SST forcing, DJF, 1971-2000 (20cL)

‘Warm’ - Control-1.8°C cutoff in SST

-1.7°C cutoff in SST

Results: MSLP

Control ‘Warm’

MSLP Changes , DJF, 21cL-20cL

‘Warm’ - ControlMore blocking More blocking - but not as much as Ctl

Consistency and predictability

. . .

is realized in models based on physical principlesall components of climate system are represented tuning models is restrictedmore advanced model include crucial chemical and biological

processes

Advances are achieved byiteratively improving representation of climate relevant processes in all components of climate models guided by advances in understanding of- climate dynamics, - feedback mechanisms, - representation of climate states for initialization,- drivers of climate change

Accuracy and reliability

. . .

is realized in models byevaluating the ability of reconstructing pertinent features of recent

climate and wide range of past climatesmore information allow probabilistic approach which leads to

decrease in uncertainty and ultimately to ‘narrowing’ of the confidence levels

- advances achieved bysample CMIP3/5 model subset based on model

performance over the region of interest removing known biases in forcing fields (eg SST,SIC) and

in projected climate data

Caution: Future climate may still stray beyond IPCC projection some estimates may be too conservative

Approach:

Multi-Model Ensemble (MME): - more information reduces uncertainties - identification and quantification of modes of internal variability - determine extremes

Model Evaluation and Bias Correction (BC): - ‘realistic’ input for climate impact studies and risk evaluation - helps reveal key model errors

Model Improvement: - remove obvious forcing errors (SST, Sea Ice) - atmosphere ocean coupling at the marginal sea ice zone, - marine boundary layer clouds, - atmospheric chemistry, ♦ ♦ ♦

based onprior

knowledge ofthe system

alsoValidation

and Verification

incomplete informationbased on

limited ensemble

Mullan, Dean (2008)

CMIP3 - IPCC20cL: 1971-200021cN: 2011-204021cM: 2041-207021cL: 2071-2099

•upper and lower bounds, ‘middle of road’ of SRES emission scenarios• multidecadal ocean variability and initial ocean/climate state•perturbations of SST forcing•Selection of CMIP3 models•bias correction of SST forcing

SRES A2 A1B B1

UKMO-HadCM3 x x x

MPI-ECHAM5 x x o

GFDL-CM2.1 x o o

CSIRO-MK3.5 x o o

Regional Climate Model

StatisticalDownscaling

GCM 1

GCM 2

GCM 3

GCM x

Bias-Correction&

Downscaling

Downstream Models:

RiverSnow

Glacier

Climate Change Studies

Climate Change Studies

Climate Change Studies

Regional Modelling & Physical Impacts

Emission Scenarios

Present, Future, Paleo

A2 SST-BC forcing: revised, 20cL DJF

20cL: 1971-200021cL: 2071-2099

Bias correction increases variability and corrects mean

Validation:1972-2000 (VCSN)

DJF JJA

reanalysis driven

A2 SST-BC forcing: revised, 21cL - 20cL DJF

20cL: 1971-200021cL: 2071-2099

BC HadCM3 SST forcing (A2) : rev, DJF

20cL: 1971-200021cN: 2011-204021cM: 2041-207021cL: 2071-2099

21cN - 20cL 21cL - 20cL

21cM - 20cL

Summer Precipitation Change (in %)

BC HadCM3 SST forcing (A2) : rev, DJF

20cL: 1971-200021cN: 2011-204021cM: 2041-207021cL: 2071-2099

21cN - 20cL 21cL - 20cL

21cM - 20cL

Bias corrected Summer Precipitation Change (in %)

A2 SST-BC forcing: rev – ctl, 21cL- 20cL DJF

20cL: 1971-200021cL: 2071-2099

Transient climate change signal: DJF Precipitation

20cL: 1971-2000 21cN: 2011-2040 21cM: 2041-2070 21cL: 2071-2099

revised - control

Transient climate change signal: JJA Precipitation

20cL: 1971-2000 21cN: 2011-2040 21cM: 2041-2070 21cL: 2071-2099

revised - control

Transient climate change signal: JJA Precipitation

20cL: 1971-2000 21cN: 2011-2040 21cM: 2041-2070 21cL: 2071-2099

revised - control

DJF MSLP & Precipitation – 20cL (Observed SST)

Con

trol

obs

erve

d S

ST

Rev

ise

d o

bser

ved

SS

T

DJF MSLP & Precipitation – 20cL (HadCM3 SST)

Had

CM

3 S

ST

Bia

s C

orre

cted

Had

CM

3 S

ST

DJF Southern Annular Mode Index

HadISST + HadCM3 bias corrected HadCM3

MSLP and Precipitation Changes, DJF, 21cL-20cL (MPI)

MSLP and Precipitation Changes, DJF, 21cL-20cL (MIROCM)

ConclusionsRegional climate change over NZ domain is dominated by changes in large scale circulation pattern

Large climate change signal 21st century trend may be nonlinear bias correction reduces signal Trends in temperature increase over time whereas

precipitation may fluctuate

Climate change involves not only changes in mean but also in variability

Reasonably ‘reliable’ climate change signal by bias correcting but is superimposed by large internal variability – low precision

Are there preferred climate states, climate attractors … associated with climate change?

Future Work

Climate model development and improvements

Run more ensemble members; physical and initial state

Projection of the behaviour of climate modes into future considering multi-decadal variability

Improvements in bias correction methodology and initialization concerns

Are there preferred climate states, climate attractors … associated with climate change?

&

Questions?

Summary• Sensitivity in projections of rainfall change - caused by ‘trivially small’ differences in prescribed SSTs

- result in changes in stationary wave patterns & rainfall

- now have a number of GCM/RCM runs that reproduce this instability

• Similar sensitivity present for initial condition ensembles as for parameter/physics ensembles

• Challenges for interpretation of NZ climate changes - a problem with ‘climate scenario paradigm’ - ICs don’t matter!?

- alternatively, maybe 30-year future climatology is too short a period

- nevertheless, there is a climate change ‘signal’

• What now? - explore with further ensemble runs & further analysis

- use a different atmosphere GCM

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