01-12-2000 1

Towards predicting climate Towards predicting climate system changes and diagnosing system changes and diagnosing

feedbacks from observationsfeedbacks from observations

Gabi Hegerl, GeoSciences, U EdinburghGabi Hegerl, GeoSciences, U Edinburgh

Thanks to: Reto Knutti, Thanks to: Reto Knutti, Simone Morak, Susan Simone Morak, Susan

Solomon, Xuebin Solomon, Xuebin Zhang, Francis Zwiers Zhang, Francis Zwiers

Photo credits: Tagesschau/NCDC

01-12-2000 2

Estimating climate feedbacks and predicting future changes

Modelling approach: Model as well as possible based on mechanisms

Inverse / top-down approach: Diagnosing responses and with it feedbacks from observed changes– How to do it– Findings– Interpretation

01-12-2000 3

Needed1. Observations y with well-estimated

uncertainties

2. Estimate of climate variability (to assess which observed changes can be explained without forcing); (observations; or climate models checked against observed / palaeo reconstructed long-term variability).

3. Fingerprints for external forcing X=(xi),i=1..n ; models of any complexity that is appropriate for problem

01-12-2000 4

Transient climate response relates directly to observed attributable warming

• Estimated warming at the time of CO2 doubling in response to a 1% per year increase in CO2

Separate the greenhouse gas fingerprint from

response to natural forcings and response to other anthropogenic forcing (aerosol direct and indirect, ozone trop. And strat.)

Estimate scaling factors ai

u,v: noise residualvuxay ii )(

01-12-2000 5

Attributable warming….

Scaling factors for greenhouse gas, other anthropogenic and natural fingerprints

Translated into estimate of attributable warming

01-12-2000 6

Fig 9.21

=> overall estimate based on rescaling diverse individual model-based estimates

Figure: from Hegerl et al., 2007 after Stott et al. 2006

Yields an estimate of transient climate response

01-12-2000 7

Equilibrium climate sensitivity

Does not relate in a simple way to observed warming rate, but needs estimate of ocean heat uptake with uncertainty;

Example: last millennium

Comparison of several reconstructions with amplitude uncertainties (dotted) with energy balance model simulation

Hegerl et al., 2006

01-12-2000 8

Estimating ECS

Run EBM with > 1000 model simulations, varying equilibrium climate sensitivity, effective ocean diffusivity, and aerosol forcing

Estimate likelyhood that residual between reconstruction and range of EBM simulations is indistinguishable from best fit residual

Var(Res-resmin ) ~ F(k,l) ( ., 2001)after Forest et al

Account for uncertainties:

•Calibration uncertainty of reconstruction•Data noise and internal variability•Uncertainty in magnitude of past solar and volcanic forcing

01-12-2000 9

Result:20th century forward modeling most other results are top-down (asking what model parameters yield simulations consistent with data)

Knutti and Hegerl, 2008

remaining uncertainties ranging from large to small`

01-12-2000 10

Conclusions for large scales

Top down/inverse approaches indicate consistent estimates as forward modelling, but larger uncertainties

Similar approaches can be applied to constrain carbon cycle sensitivity (Frank et al., 2010)

And have been applied to estimate aerosol effects on temperature yielding recently ~ consistent estimates

Regional changes and their effect on feedbacks, for example, through vegetation, are another matter…

Depend on seasonal changes in temperature distribution, and precipitation

01-12-2000 11

Change in temperature distribution Eastern North

America 1950-2006: change in vegetation?

(Portmann et al., PNAS 2009)

similarly: Eastern Asia – aerosols? (from Morak)

TN90Expected from Tmin Expected from Tmax

01-12-2000 12

Regional: circulation

can be important

Gillett et al., NGEO, 2008 => attributable human influence

SAM congruent

residual

modelobservation

01-12-2000 13

Fig. SPM-6

IPCC SPM

Feedbacks will depend on precipitation change

Mechanism: Clausius Clapeyron => wetter when warmer

Longwave forcing suppresses some of the response

Dynamics and circulation have major influence Allen and Ingram, 2002

Equ. 2xCO2 models

Transient change

01-12-2000 14

Estimate from observations

Santer et al., 2010: detectable changes in water vapour

Zhang et al., 2007: detectable changes in land precipitation

01-12-2000 15

Fingerprint detection and

attribution study

Detectable signal, but larger than simulated!

(scaling > 0 but also >1!)

01-12-2000 16

Similar problems may occur in response to shortwave forcing

Photo: NASA after Trenberth et al., GRL, 2007

Similarly, attributable change in Arctic precipitation (Min et al., 2009) is significantly larger than simulated

01-12-2000 17

Shortwave Geoengineering: We should be very worried, and not trust model simulated impacts!

(Hegerl and Solomon, 2009)

Global land precipitation: Observed vs models

(5-yr smoothed)

(from Hegerl et al., 2007; adapted from Lambert et al., 2005)

01-12-2000 18

Conclusions

Changes in temperature distribution may point at missing processes on regional scale

Precipitation shows a detectable human influence, but the observed changes are larger than simulated!

Errors in models (missing / erroneous feedbacks), forcings, observations or all of this?

Missing local processes and feedbacks as well as problems in precipitation changes will affect simulations of earth system feedbacks

Top down estimates provide important evaluation of modelled feedbacks, and point at problems for regional changes and precipitation