Investigating mechanisms of future
changes in precipitation extremes
simulated in GCMs
Seita Emori
National Institute for Environmental Studies
I’d like to thank Dr. M. Sugiyama (CRIEPI), Dr. H. Shiogama
(NIES), and Dr. S. Brown (UKMO).
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Research on physical basis of
precipitation extreme changes
Precipitable water
(Clausius-Clapeyron)
Trenberth (1999)
Allen and Ingram (2002)
Precipitable water + vertical motion
Emori and Brown (2005)
Pall et al. (2007)
Lenderink & van Meijgaard (2008)
Precipitable water + vertical motion
+ vertical profile
+ temperature when precipitating
O’Gorman and Schneider
(2009a, 2009b)
Sugiyama et al. (2009)
• Research on mostly statistical analyses are excluded
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Precipitable water + vertical motion
(Emori and Brown, 2005)
• Use daily mean 500hPa vertical velocity (w ) as a proxy of
‘dynamic disturbance’ at each grid/day
• Composite daily precipitation for each w-class to give
‘expected’ precipitation for given w at each grid
• Is the change in precipitation due to:
– Change in w? (dynamic change)
– Change in expected precipitation for given w?
(non-dynamic or ‘thermodynamic’ change)
Cf. Bony et al. (2004) for cloud-radiation analysis
expected precipitation
Extreme Precipitation Change
(99th percentile)
P99+P99
P99
w*99
w*99+w*99
0
500hPa vertical velocity (upward)
P99  Pw (w )
Pw
Pw
*
*
*
 P99 
w99   Pw (w99 )  
w99
w
w
*
99
Dynamic
Thermodynamic
Covariation
Results
ensemble mean of 4 CMIP3 CGCMs and 2 AGCMs
Annual Mean Precipitation Change
Total
Dynamic
Thermodynamic
99th percentile Precipitation Change
Total
Dynamic
-50
0
Thermodynamic
+50 [%] (relative to control)
Precipitable water + vertical motion
+ vertical profile
(Sugiyama et al., 2009)
• Space-time CDF of daily precipitation
(Allen and Ingram 2002, Pall et al. 2007)
– Create CDF by combining space and time for very rare events
Sample size (30S-30N, MIROC medres，ocean + land):
128 (long.) X 32 (lat.) X 365 days X 20 years＝29,900,800
This enables calculation of very rare events (eg. 99.999%-itle)
– Focus on ocean grid points (avoid mountain effects)
– Composite various variables with respect to daily precipitation
extremes
6
MIROC-hires Tropics (30S-30N)
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MIROC-hires Tropics (30S-30N)
Precipitable water
+ 500hPa omega
Precipitation
Precipitable water
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Approx.
humidity
budget

 q
 dp
 P  E
    (uq) 
 t
 g
 dq  dp
   w 
P
 dp  g

q dp 
 W  w500
a     w
p g 

W w500 a P



W
w500
a
P
a: gross moisture stratificaiton
(e.g., Chou et al. 2009)
Parameter that characterizes vertical
profiles of humidity and vertical motion
 q *  dp

b    w 
 p  e* g
b P

b
P
b: O’Gorman and Schneider (2009)
Condensation, assuming vertical
motion follows a pseudoadiabatic
lapse rate
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MIROC-hires Tropics (30S-30N)
dT in denominator
omitted
• Change in ‘a’ is negative and suppressing the
overestimation of the scaling by precipitable water + vertical
motion, especially for higher percentiles.
• Negative change in ‘a’ is due to changes in vertical profiles
of humidity (moist adiabat) and vertical motion.
10
MIROC-hires Tropics (30S-30N)
• The profile of vertical motion shifts upward under global
warming.
• Change in omega is smaller in lower layers than at 500hPa.
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MIROC-hires Mid-latitudes (30N-60N, DJF)
dT in denominator
omitted
• Change in vertical motion is small.
• Precipitation change is mostly constrained by
thermodynamics.
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CMIP3 models Tropics
• Models disagree a lot.
• 6 models: ΔP > Δ(precipitable water)
( ) in legend: Δ(precipitable water)
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CMIP3 models Mid-latitudes
• Models agree better.
• Mostly constrained by
precipitable water.
( ) in legend: Δ(precipitable water)
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Conclusions
• Mid-latitude precipitation extremes: mostly
thermodynamic
– With correction on vertical profiles (moist adiabat)
• Tropical precipitation extremes: require full knowledge of
vertical motion (strength and vertical profile)
• Precipitation extremes exceeding the ClausiusClapeyron prediction might occur, as shown in MIROC
and some CMIP3 models.
– Reproducing them in GCM is challenging because of
significance of disturbances like tropical cyclones.
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