Angie Pendergrass NCAR CGD / CCR · 1990 1995 2000 2005 2010 2015 ... Time series of climatic...
Transcript of Angie Pendergrass NCAR CGD / CCR · 1990 1995 2000 2005 2010 2015 ... Time series of climatic...
Precipitation variabilityincreases in a warming climate
Angie Pendergrass NCAR CGD / CCR
with input (recently) from Reto Knutti,(intermittently) Ben Sanderson,
(less recently) Flavio Lehner and Clara Deser
Regional and Global Climate Modeling Program Cooperative Agreement DE-FC02-97ER62402
mean extremesvariability
1-3
[%K-
1 ]
>=7
???
Held and Soden 2006many others before and after
Trenberth 1999Allen and Ingram 2002many others before and after
ImpactsSociety: Growth of children under 5 (Shively 2017)Science: Some studies assume no change in variability (Thompson et al 2015) or a change following mean (Delta-change method, widely used in hydrology)
Rind et al 1989
Precip variance increases with mean
1990 1995 2000 2005 2010 2015
Time
Precip
0
Time
Precip
0
Time
Precip
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Mean
Standard deviation
Time
Precip
0
Mean
Standard deviation
~ 2 %/K
Rind et al 1989
Precip variance increases with mean
Mearns…. Shields 1995Variability of daily precip increases in regional simulations
Voss 2002
Groisman et al 1999
Raisanen 2002
CMIP2 variability increases with moistureor mean precip
Zwiers and Kharin 1998Precip standard deviation increases 7% in 2xCO2
Tsonis 1996
Karl et al 1994
1990 1995 2000 2005 2010 2015
Vertical velocity
Specific humidity
Rain rate
Moistening increases precipitation variability
MoistenedInitial
Rind et al 1989
Precip variance increases with mean
Mearns…. Shields 1995Variability of daily precip increases in regional simulations
Raisanen 2002
CMIP2 variability increases with moisture or mean precip
Hunt and Elliott 2004Changes in precip variability not important at the grid point lev
Zwiers and Kharin 1998Precip standard deviation increases 7% in 2xCO2
Tsonis 1996
Karl et al 1994
1990 1995 2000 2005 2010 2015
“…at the grid box level it is also difficult to differentiate between PDFsfor control and green-house conditions for surface temperature andrainfall. Time series of climatic variables for selected geographical pointsor regions highlight the continuing influence of interannual climaticvariability throughout the greenhouse simulations.”
Hunt and Elliott 2004
Wetherald 2009, 2010
Rind et al 1989
Precip variance increases with mean
Mearns…. Shields 1995Variability of daily precip increases in regional simulations
Raisanen 2002
CMIP2 variability increases with moisture or mean precip
Giorgi and Bi 2005
Raisanen 2005
Hunt and Elliott 2004Changes in precip variability not important at the grid point lev
Zwiers and Kharin 1998Precip standard deviation increases 7% in 2xCO2
Tsonis 1996
Karl et al 1994
1990 1995 2000 2005 2010 2015
Bonfils et al 2015ENSO precip change
Chung et al 2014ENSO precip change
Huang and Xie 2015ENSO precip change
Huang 2016ENSO precip change
Power et al 2013ENSO precip change
Seager et al 2012Hydroclimate variability and warming: ENSO
1990 1995 2000 2005 2010 2015
Boer 2009Decadal potential predictability
Key questions• Are there important changes in precipitation
variability with warming? • At what rate does precipitation variability
change? What drives its changes?– Mean precipitation? – Moisture?
• How does changing precipitation variability depend on timescale? – Is ENSO special?
Model simulations
• Historical+RCP8.5 scenarios, 1950-2100– CESM1 Large Ensemble: 40 members– GFDL-ESM2M Large Ensemble: 30
members– CMIP5 ensemble: 36 models
• Metric: Standard deviation
CMIP5 multi-model mean (2071-2100)-(1976-2005)
Change in standard deviation of seasonal-mean precipitation
[% K-1]
Spatially aggregated precipitation variability change
SummerExtratropics
Spatial aggregation: Fischer et al
Spatially aggregated precipitation variability changeSummerExtratropics
Spatially aggregated precipitation variability changeSummerExtratropics
Spatially aggregated precipitation variability changeSummerExtratropics
Null hypothesis: Ensemble members randomly drawn from the base period compared to each other
Spatially aggregated precipitation variability change
Extratropical land
Spatially aggregated precipitation variability change
Spatially aggregated precipitation variability change
Are there important changes in precipitation variability with warming?
• Yes; precipitation variability increases over a larger fraction of land area than it decreases
At what rate does precipitation variability change? What drives it?
1. Increasing mean precipitation?
Precipitation standard deviation change
Tropical land
Multi-model, seasonal mean.30-year periods centered on
progressive decades, compared to 1976-2005
TTropical land
Precipitation standard deviation change
Standard deviation change
TTropical land
Precipitation standard deviation change
Standard deviation change
Mean change
T
T
(%/K)
Mean change
Standard deviationchange
TJJA DJF
T
CMIP5 multi-model mean, (2071-2100) – (1976-2005)
At what rate does precipitation variability change? What drives it?
1. Increasing mean precipitation?
1. Increasing moisture?
Moisture
At what rate does precipitation variability change? What drives it?
• The standard deviation increases at least as much as mean precipitation, but less than moisture
• Explanation: Increasing moisture along with weakening circulation (Vecchi and Soden 2007)
Precip variance response differs between CESM1 and GFDL large ensembles
Tropical land
Isolate neutral ENSO years
1950-2000, 2050-2100 (following Power et al 2013)Neutral ENSO defined as PC1 of tropical surface temperature <0.5std
Tropical land
ENSO’s role: spatially limited
[%]
Fraction of variance (which is additive): Take the square
Standard deviation by timescale: A continuum
Standard deviation by timescale: A continuum
CMIP5multi-model, annual mean(2071-2100) - (1976-2005)
T
T
T
T
Mean, Variability,Extremes
Change in mean precipitation
Change in standard deviation of seasonal
mean precipitation
Change in standard deviation of daily
precipitation
Change in annual maximum daily
precipitation (rx1day)
(%/K)
T
T
GHCN-Daily GSN network station observations
(%/K)
Observed changes
Key points- Precipitation variability increases over most land
areas, consistent with the expectation from increases in mean and extreme precipitation.
- The rate that precipitation variability increases is at least as high as mean precipitation and no higher than the rate of moistening.
- The rate of increase of variability is similar across timescales from daily to decadal.
- Observed variability of daily precipitation increased at most stations than in the last half of the 20th century.