NCAS-Climate Talk

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Current Changes in the Global Water Cycle

• Richard P. Allan
• Diffusing slowly to Met Department/NCAS-Climate
  from ESSC
• Thanks to Brian Soden, Viju John, William Ingram,
  Peter Good, Igor Zveryaev, Mark Ringer and Tony
  Slingo

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Introduction
Observational records and climate projections
provide abundant evidence that freshwater
resources are vulnerable and have the potential
to be strongly impacted by climate change, with
wide-ranging consequences for human societies and
ecosystems. IPCC (2008) Climate Change and Water
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How should the water cycle respond to climate
change?
Precipitation Change () relative to 1961-1990 2
scenarios, multi model (IPCC, 2001)
See discussion in Allen Ingram (2002) Nature
Trenberth et al. (2003) BAMS
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Climate model projections (IPCC 2007)

• Increased Precipitation
• More Intense Rainfall
• More droughts
• Wet regions get wetter, dry regions get drier?
• Regional projections??

Precipitation Intensity
Dry Days
Precipitation Change ()
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Physical basis energy balance
Trenberth et al. (2009) BAMS
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Models simulate robust response of clear-sky
radiation to warming (2-3 Wm-2K-1) and a
resulting increase in precipitation to balance
(3 K-1) e.g. Allen and Ingram (2002)
Nature, Stephens Ellis (2008) J. Clim, Lambert
and Webb (2008) GRL
Allan (2009) J Clim
Radiative cooling, clear (Wm-2K-1)
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Physical basis water vapour

• Clausius-Clapeyron
• Low-level water vapour (7/K)
• Intensification of rainfall
• Moisture transport
• Enhanced P-E patterns
• See Held and Soden (2006) J Clim

1979-2002
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Evaporation
Richter and Xie (2008) JGR
CC Wind Ts-To RHo
Muted Evaporation changes in models are explained
by small changes in Boundary Layer1) declining
wind stress2) reduced surface temperature lapse
rate (Ts-To)3) increased surface relative
humidity (RHo)
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Current changes in the water cycle As observed
by satellite datasets and simulated by models
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Current changes in tropical ocean column water
vapour
John et al. (2009)
Water Vapour (mm)
models
AMIP3 CMIP3 CMIP3 volc
Allan (2009)
despite inaccurate mean state, Pierce et al.
John and Soden (both GRL, 2006) - see also
Trenberth et al. (2005) Clim. Dyn., Soden et al.
(2005) Science
ERA40 NCEP ERAINT SSM/I
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Tropical ocean precipitation

• dP/dSST
• GPCP 10/K (1988-2008)
• AMIP 3-11 /K (1979-2001)
• dP/dt trend
• GPCP 1/dec
• (1988-2008)
• AMIP 0.4-0.7/dec
• (1979-2001)
• (landocean)

SSM/I GPCP
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Wet (ascent) and Dry (descent) regimes
GPCP Ascent Region Precipitation (mm/day)

• Robust response wet regions become wetter at
  the expense of dry regions
• Large uncertainty in magnitude of change
  satellite datasets and models time period

TRMM
John et al. (2009) GRL
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Contrasting precipitation response in wet and dry
regions of the tropical circulation
ascent
Models
Observations
Precipitation change ()
descent
Sensitivity to reanalysis dataset used to define
wet/dry regions
Updated from Allan and Soden (2007) GRL
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Avoid reanalyses in defining wet/dry regions

• Sample grid boxes
• 30 wettest
• 70 driest
• Do wet/dry trends remain?

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Current trends in wet/dry regions of tropical
oceans

• Wet/dry trends remain
• 1979-1987 GPCP record may be suspect for dry
  region
• SSM/I dry region record inhomogeneity 2000/01?
• GPCP trends 1988-2008
• Wet 1.8/decade
• Dry -2.6/decade
• Upper range of model trend magnitudes

DRY WET
Models
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Precipitation Extremes

• Trends in tropical wet region precipitation
  appear robust.
• What about extreme precipitation events?

• Analyse daily rainfall over tropical oceans
• SSM/I satellite data, 1988-2008
• Climate model data (AMIP experiments)
• Create monthly PDFs of rainfall intensity
• Calculate changes in the frequency of events in
  each intensity bin
• Does frequency of most intense rainfall rise with
  atmospheric warming?

METHOD
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Increases in the frequency of the heaviest
rainfall with warming daily data from models and
microwave satellite data (SSM/I)
Reduced frequency Increased frequency
Updated from Allan and Soden (2008) Science
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• Increase in intense rainfall with tropical ocean
  warming (close to Clausius Clapeyron)
• SSM/I satellite observations at upper range of
  model range

No apparent link to convection scheme? What about
CMIP experiments? e.g. Turner and Slingo (2009)
ASL
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One of the largest challenges remains improving
predictability of regional changes in the water
cycle
Changes in circulation systems are crucial to
regional changes in water resources and risk yet
predictability is poor.
How will catchment-scale runoff and crucial local
impacts and risk respond to warming?
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Precipitation in the Europe-Atlantic region
(summer) Dependence on NAO
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Current changes in the water cycle over
Europe-Atlantic region
Water vapour Precipitation
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Outstanding issues

• Are satellite estimates of precipitation,
  evaporation and surface flux variation reliable?
• Are regional changes in the water cycle, down to
  catchment scale, predictable?
• How well do models represent land surface
  feedbacks. Can SMOS mission help?
• How is the water cycle responding to aerosols?
• Linking water cycle and cloud feedback issues

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Extra Slides
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Conclusions

• Robust Responses
• Low level moisture clear-sky radiation
• Mean and Intense rainfall Observed
• precipitation response at upper end of model
  range?
• Contrasting wet/dry region responses
• Less Robust/Discrepancies
• Moisture at upper levels/over land and mean state
• Inaccurate precipitation PDFs
• Magnitude of change in precipitation in satellite
  datasets/models
• Further work
• Decadal changes in global energy budget, aerosol
  forcing effects and cloud feedbacks links to
  water cycle
• Precipitation and radiation balance datasets
  forward modelling
• Surface feedbacks ocean salinity, soil moisture
  (SMOS?)
• Boundary layer changes and surface fluxes

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Wet
Dry
DISCUSSION
dPw/dT7/K
dPd/dT
Assume wet region follows Clausius Clapeyron
(7/K) and mean precip follows radiation
constraint (3/K)
Pw6 mm/day
Pd1 mm/day
A0.4
(1-A)0.7
P3 mm/day
dP/dT3/K
A is the wet region fractional area P is
precipitation T is temperature
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Wet
Dry
dPw/dT7/K
dPd/dT
Assume wet region follows Clausius Clapeyron
(7/K) and mean precip follows radiation
constraint (3/K) dP/dT A(dPw/dT)(1-A)(dPd/dT)
? dPd (dP-AdPw)/(1-A)
Pw6 mm/day
Pd1 mm/day
A0.4
(1-A)0.7
P3 mm/day
dP/dT3/K
A Pw Pd dPd/dTs (mm/day/K) (/K)
0.4 0.2 6 9 1 1.5 -0.1 -0.05 -10 -4.5
0.1 10.5 2.2 0.02 0.9
A is the wet region fractional area P is
precipitation T is temperature
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SMOS ESAs SMOS (Soil Moisture and Ocean
Salinity) launched November 2009
Evaporation changes over land are not globally
measured. New data on soil moisture could be
vital in understanding changes in evaporation and
regional water cycle feedbacks over land. The
addition of ocean salinity measurements are also
of potential value in understanding P-E changes
and ocean circulating response
Courtesy of Ian Davenport
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Cloud Feedback

• Can HadIR provide any information on cloud
  feedback
• For example, the FAT hypothesis (fixed anvil
  temperature)
• Anvil outflow determined by position of zero
  radiative cooling
• which is determined by the rapid decline in
  water vapour with altitude
• which is determined by Clausius Clapeyron
• Hypothesis As temperature rises, outflow rises
  in altitude but not temperature which remains
  fixed
• e.g. Hartmann and Larson (2003) Zelinka and
  Hartmann in press

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Are the issues of cloud feedback and the water
cycle linked?
2008
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Response of the hydrological cycle is sensitive
to the type of forcing
Andrews et al. (2009) J Climate
Partitioning of energy between atmosphere and
surface is crucial to the hydrological response
this is being assessed in the PREPARE project
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How does UTH respond to warming?
Minschwaner et al. (2006) J Clim
Lindzen (1990) BAMS
Mitchell et al. (1987) QJRMS
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Precipitation projections (IPCC)
Radiation budget, hydrological cycle and climate
feedbacks
Decadal changes in water vapour, precipitation
and its extremes are beginning to be detected
Precip. ()
Allan and Soden (2008) Science