The atmospheric hydrological cycle and climate feedbacks: recent advances Richard P. Allan Department of Meteorology, University of Reading Thanks to Brian Soden and Viju John http://www.met.reading.ac.uk/~sgs02rpa [email protected]
Mar 28, 2015
The atmospheric hydrological cycle and climate feedbacks: recent advances
Richard P. AllanDepartment of Meteorology, University of Reading
Thanks to Brian Soden and Viju John
http://www.met.reading.ac.uk/~sgs02rpa [email protected]
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
• Increased Precipitation• More Intense Rainfall• More droughts• Wet regions get wetter, dry
regions get drier?• Regional projections??
Precipitation Change (%)
Climate model projections (IPCC 2007)
Precipitation Intensity
Dry Days
Range of cloud feedback
Uncertainty in strength of cloud feedback
Water vapour and T-lapse rate
ALLCloud Surface reflection
Total range
Str
engt
h of
Fee
dbac
k (W
m-2/o C
)
Hawkins and Sutton (2010) Clim. Dyn.See IPCC (2007)
How should the water cycle respond to climate change?
See discussion in: Allen & Ingram (2002) Nature; Trenberth et al. (2003) BAMS
Hawkins and Sutton (2010) Clim. Dyn.
Allen and Ingram (2002) Nature
How should the water cycle respond to climate change?
7%/K 3%/K
NCAS-Climate Talk 15th January 2010 Trenberth et al. (2009) BAMS
Physical basis: energy balance
NCAS-Climate Talk 15th January 2010
Rad
iativ
e co
olin
g, c
lear
(W
m-2K
-1)
Models simulate robust response of clear-sky radiation to warming (~2 Wm-2K-1) and a resulting increase in precipitation to balance (~2 %K-1)
e.g. Allen and Ingram (2002) Nature, Stephens & Ellis (2008) J. Clim
Allan (2009) J. Clim
NCAS-Climate Talk 15th January 2010
CC Wind Ts-To RHo
Muted Evaporation changes in models are explained by small changes in Boundary Layer:1) declining wind stress2) reduced surface temperature lapse rate (Ts-To)3) increased surface relative humidity (RHo)
Richter and Xie (2008) JGR
Evaporation
Current changes in tropical ocean column water vapour
Low level water vapour strongly constrained by Clausius Clapeyron relationship (~7%/K)
Changing observing systems applied to reanalyses cause spurious variability (e.g. ERA Interim)
John et al. (2009)
models
Wat
er V
apou
r (m
m)
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
Extreme PrecipitationPhysical basis: water vapour
1979-2002
• Low-level moisture rises with warming at ~7%/K due to Clausius Clapeyron
• Large-scale rainfall fuelled by moisture convergence– e.g. Trenberth et al. (2003) BAMS
Intensification of rainfall
• Extra latent heating:– Offsets some of extra condensation
/stabilises atmosphere? (O’Gorman and Schneider, 2009 PNAS)
– Invigorates storms? (Lenderink and van Meijgaard (2010) Environ. Res. Lett)
Contrasting precipitation response expected
Pre
cipi
tatio
n Heavy rain follows moisture (~7%/K)
Mean Precipitation linked to
radiation balance (~3%/K)
Light Precipitation (-?%/K)
Temperature For discussion: Trenberth et al. (2003) Bull. Americ. Meteorol. Soc; Allen & Ingram (2002) Nature
Models ΔP [IPCC 2007 WGI]
Is there a contrasting precipitation response in wet and dry regions?
Rainy season: wetter
Dry season: drier Chou et al. (2007) GRL
Precip trends, 0-30oN
The Rich Get Richer?
First argument:P ~ Mq.
So if P constrained to rise more slowly than q, this implies reduced M
P~Mq
Consequences: Circulation response
First argument:P ~ Mq.
So if P constrained to rise more slowly than q, this implies reduced M
Second argument:ω=Q/σ.
Subsidence (ω) induced by radiative cooling (Q) but the magnitude of ω depends on (Гd-Г) or static stability (σ).
If Г follows MALR increased σ. This offsets Q effect on ω.See Held & Soden (2006) and Zelinka & Hartmann (2010) JGR
P~Mq
Consequences: Circulation response
Models/observations achieve muted precipitation response by reducing strength of Walker circulation. Vecchi et al. (2006) Nature
P~Mq
Consequences: Circulation response
Pre
cip.
(%
)
Allan and Soden (2008) Science
Can we use observations to seek/confirm robust responses?
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)
(land+ocean)
SSM/I GPCP
Allan et al. (2010) Environ. Res. Lett.
Zhang et al. 2007 Nature
Detection of zonal trends over land
Contrasting precipitation response in wet and dry regions of the tropical circulation
Allan and Soden (2007); Allan et al. (2010) Environ. Res. Lett.
descent
ascentModelsObservations
Pre
cipi
tatio
n ch
ange
(%
)
Sensitivity to reanalysis dataset used to define wet/dry regions
Contrasting wet/dry precipitation responses
• Large uncertainty in magnitude of change: satellite datasets and models & time period
TRMM
GPCP Ascent Region Precipitation (mm/day)
John et al. (2009) GRL
• Robust response: wet regions become wetter at the expense of dry regions. Is this an artefact of the reanalyses?
Current trends in 30% wettest, 70% driest 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
Models
DR
Y
WE
T
Allan et al. (2010) Environ. Res. Lett.
• Analyse daily rainfall over tropical oceans– SSM/I v6 satellite data, 1988-2008 (F08/11/13)– Climate model data (AMIP experiments)
• Create rainfall frequency distributions
• Calculate changes in the frequency of events in each intensity bin
• Does frequency of most intense rainfall rise with atmospheric warming?
Precipitation Extremes
Can we seek robust responses in precipitation extremes using satellite observations?
METHOD
Increases in the frequency of the heaviest rainfall with warming: daily data from models and microwave satellite data (SSM/I)
Reduced frequency Increased frequencyAllan and Soden (2008) Science; Allan et al. (2010) Environ. Res. Lett.
• Increase in intense rainfall with tropical ocean warming (close to Clausius Clapeyron)
• SSM/I satellite observations at upper range of model range
Turner and Slingo (2009) ASL: dependence on convection scheme?
Observational evidence of changes in intensity/duration (Zolina et al. 2010 GRL)
Links to physical mechanisms/relationships required (Haerter et al. 2010 GRL)
Yu and Weller (2007) BAMS
(Wentz et al. 2007, Science)
Are models underestimating current precipitation/evaporation responses?
• Could decadal fluctuations in atmospheric circulation be influencing current water cycle response?– Sohn and Park (2010) JGR
Walker circulation index (top) and sea level pressure anomalies (bottom) over equatorial Pacific (1948-2007)
Hadley circulation index over 15oS-30oN band
Could changes in aerosol influence decadal changes in the hydrological cycle? e.g. Wild et al. (2008) GRL
Wielicki et al. (2002) Science; Wong et al. (2006) J. Clim; Loeb et al. (2007) J. Clim
Mishchenko et al. (2007) Science
Andrews et al. (2009) J Climate
Is water cycle response sensitive to nature of radiative forcing?
How does the water cycle respond to ramp-down in CO2?
• CO2 forcing experiments
• Initial precip response supressed by CO2 forcing
• Stronger response after CO2 rampdown
HadCM3: Wu et al. (2010) GRL
CMIP3 coupled model ensemble mean: Andrews et al. (2010) Environ. Res. Lett.
Degree of hysteresis determined by forcing related fast responses and linked to ocean heat uptake
Forcing related fast responses
Andrews et al. (2010) GRL
Total Slow
• Surface/Atmospheric forcing determines “fast” adjustment of precipitation
• Robust slow response to T• Mechanisms described in Dong
et al. (2009) J. Clim
• CO2 physiological effect potentially substantial (Andrews et al. 2010 Clim. Dyn.; Dong et al. 2009 J. Clim)
• Hydrological Forcing:
HF=kdT-dAA-dSH
(Ming et al. 2010 GRL; also Andrews et al. 2010 GRL)
Pre
cip
itatio
n re
spo
nse
(%
/K)
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?
What are the important land-surface and ocean-atmosphere feedbacks which determine the response?
Future work: Binning precipitation by regime
Vert
ical m
oti
on
(ω
) %
iles
ascen
t d
escen
t
Coldest Warmest
Precipitation (mm/day)
Warm convective
Sub tropics
*
* - mid-latitudes
Regime-dependent responses(a) P (mm/day); % area (b) Model–GPCP P (%) (c) 2080-99 – 1980-99 P (%/K); (d) ω
Vert
ical m
oti
on
(ω
)
perc
en
tile
s
ascen
t
descen
t
Models overestimate drizzle in tropics
Robust increases in precipitation for mid/high latitudes & convective tropics
Less rainfall in dry tropics. Reduced circulation.
• Global mean precipitation– Controlled by energy balance (~2-3%/K)– Water vapour and clear-sky radiative cooling
• Intense rainfall– Low-level moisture rises fuel intensification of rainfall (~7%/K)
• Wet/dry region responses– Contrasting wet/dry region responses (wet get wetter)– Moisture transport & water vapour/energy balance constraints
• Outstanding Issues– Regional responses – Aerosol and decadal variability– Links to Cloud Feedback– Observing System– Transient responses: fast adjustment to forcing
Conclusions
Extra Slides
A=0.4 (1-A)=0.6
dPw/dT=7%/K dPd/dT
dP/dT=3%/K
Assume wet region follows Clausius Clapeyron (7%/K) and mean precip follows radiation constraint (~3%/K)
Pw=6 mm/day Pd=1 mm/day
P=3 mm/day
Wet Dry
A is the wet region fractional area
P is precipitation
T is temperature
A=0.4 (1-A)=0.6
dPw/dT=7%/K dPd/dT
dP/dT=3%/K
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)
Pw=6 mm/day Pd=1 mm/day
P=3 mm/day
Wet Dry
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
Trends in clear-sky radiation in coupled models
Clear-sky shortwave absorptionSurface net clear-sky longwave
Allan (2009) J. Clim
Precipitation in the Europe-Atlantic region (summer)
Dependence on NAO
Physical Basis: Moisture Transport
Cha
nge
in M
oist
ure
Tra
nspo
rt,
dF (
pg/d
ay)
If the flow field remains relatively constant, the moisture transport scales with low-level moisture.Model simulation
scaling
Held and Soden (2006) J Climate
Projected (top) and estimated (bottom)
changes in Precipitation minus Evaporation Δ(P-E)
Held and Soden (2006) J Climate
~
• Sample grid boxes:– 30% wettest– 70% driest
• Do wet/dry trends remain?
Avoid reanalyses in defining wet/dry regions
Allan et al. (2010) Environ. Res. Lett.