Robin Hogan

1
Clouds and climate

• Robin Hogan
• (with input from Anthony Illingworth, Keith
  Shine, Tony Slingo and Richard Allan)

2
Overview

• The importance of clouds feedbacks
• Feedbacks associated with specific cloud types
• Getting clouds right in current climate models
• Evaluation of simulated clouds (e.g. using
  A-train data)
• Accurate radiation schemes (e.g. cloud
  inhomogeneity)
• Tackling feedbacks and model cloud schemes
• Analogues for global warming
• Using new observations as a tight constraint on
  model development
• Convection and high-resolution modelling

3
Cloud feedbacks
IPCC (2007)

• Main uncertainty in climate prediction arises due
  to the different cloud feedbacks in models that
  are not associated with aerosols!

4
Key cloud feedbacks

• Boundary-layer clouds
• Many studies show these to be most sensitive for
  climate
• Not just stratocumulus cumulus actually cover
  larger area
• Properties annoyingly dependent on both
  large-scale divergence and small-scale details
  (entrainment, drizzle etc)
• Mid-level and supercooled clouds
• Potentially important negative feedback (Mitchell
  et al. 1989) but their occurrence is
  underestimated in nearly all models
• Mid-latitude cyclones
• Expect pole-ward movement of storm-track but even
  the sign of the associated radiative effect is
  uncertain (IPCC 2007)
• Deep convection and cirrus
• climateprediction.net showed that convective
  detrainment is a key uncertainty lower values
  lead to more moisture transport and a greater
  water vapour feedback (Sanderson et al. 2007)
• But some ensemble members unphysical (Rodwell
  Palmer 07)

5
Evaluating models
AMIP massive spread in model water content -
need some observations!

• A-Train can now provide this via new techniques
  combining the radar and lidar

6
July 2006 global IWC comparison
A-Train Model

• Too little spread in model
• Better than AMIP comparison implied!

Temperature (C)

• Much more detailed evaluation of models
  (including high resolution ones) will proceed
  within NCEO and CASCADE
• NCAS should be involved in using these
  comparisons to improve the model

7
Cloud structure in radiation schemes
Fix only inhomogeneity Tripleclouds (fix
both) Plane-parallel Fix only overlap
TOA Shortwave CRF
TOA Longwave CRF
Current models Plane-parallel
Fix only overlap
Fix only inhomogeneity
Tripleclouds minus plane-parallel (W m-2)
New Tripleclouds scheme fix both!
With help from NCAS CMS, Jon Shonk shortly to
implement interactively in Met Office climate
model
next step apply Tripleclouds in Met Office
climate model
8
Analogues for global warming
Models with most positive cloud feedback under
climate change

• A model that predicts cloud feedbacks should also
  predict their dependence with other cycles, e.g.
  tropical regimes
• Tropical boundary-layer clouds in suppressed
  conditions cause greatest difference in cloud
  feedback
• IPCC models with a positive cloud feedback best
  match observed change to BL clouds with increased
  T (Bony Dufresne 2005)
• Apply to other cycles (seasonal, diurnal, ENSO
  phase)
• Can we use such analysis to find out why BL
  clouds better represented?
• Novel compositing methods?
• Can we throw out bad models?

Observations
Other models
Convective
Suppressed
Bony and Dufresne (2005)
9
Mixed-phase clouds

• Potentially strong negative feedback
• Warmer climate ? more clouds in liquid phase ?
  more reflective? longer lifetime (Mitchell et
  al. 1989)
• But mid-level clouds underestimated in nearly all
  models

10
Further activities required

• Using observations in model development
• Climate models in NWP mode (or single column
  version forced by large-scale tendencies
  preferred by Pier Siebesma)
• Re-run many times with different physics and
  compare to single radar/lidar sites (or A-train
  observations for global runs)
• Remove unjustified complexity (e.g. double-moment
  ice?)
• Deep convection
• Need to bite the bullet and modify the convection
  scheme in the light of cloud-resolving runs (e.g.
  CASCADE)?
• Observational constraint on water vapour
  detrained from convection, e.g. combination of
  AIRS and CloudSat?
• Even more tricky areas
• Is there any hope of getting a reliable long-term
  cloud signal from historic datasets (e.g.
  satellites)?
• How do we get cloud feedback due to storm-track
  movement?
• Coupling of clouds to surface changes, e.g. in
  the Arctic?