1. The Impact of SST and Vegetation Changes on Long-Term Drought
Fourth International CLIVAR
Climate of the 20th Century Workshop
Hadley Centre for Climate Prediction and Research
13-15 March 2007
Siegfried Schubert, Max Suarez, Philip Pegion,
Randal Koster and Julio Bacmeister
Global Modeling and Assimilation Office
Goddard Space Flight Center

2. Questions Addressed Approach
What are the relative roles of the Pacific and Atlantic in forcing long term drought over the United States?
What is the impact of “Global Warming”?
What is the impact of vegetation changes?
Approach
Assess impact in AGCM simulations forced with idealized SST patterns of variability, and with historical changes in vegetation

3. AGCM: NSIPP-1 (NASA S-I Prediction Project)
Climatology and Skill (Bacmeister et al. 2000, Pegion et al. 2000, Schubert et al. 2002)
Great Plains drought (Schubert et al. 2003; 2004)
Global grid point dynamical core, 4rth Order (Suarez and Takacs 1995)
Relaxed Arakawa-Schubert Convection (Moorthi and Suarez 1992)
Shortwave/Longwave Radiation (Chou et al. 1994, 1999)
Mosaic interactive land model (Koster and Suarez 1992, 1996)
1st Order PBL Turbulence Closure (Louis et al. 1982)
Model resolution: 3 degree latitude by 3.75 degree longitude (34 levels)
C20C AGCM runs with Specified SST
HadISST and sea ice dataset ( )
22 ensemble members - same SST, different ICs
AGCM runs forced with leading SST EOFs
AGCM runs forced with historical changes in vegetation type (cropland and pasture)

4. Annual Mean Great Plains Precipitation Correlated with SST (1901-2004)
Observations
Model - individual ens. members
Model - correlation with ensemble Mean

5. Leading EOFs and Time series (annual mean SST - 1901-2004)
Global Warming Pattern
Pacific Pattern
Siegfried,
Trend positive ( )
Trend negative ( )
Phil
Atlantic Pattern

6. Begin by looking at Impacts of Pacific and Atlantic Patterns

7. SST EOFs and Correlations with Precipitation (Ensemble mean 1901-2004)

8. Idealized Experiments
NATL
warm
neutral
cold ww wn cw nw nc wc cn cc
PacInd
SST Forcing patterns (warm phase)

9. Annual Mean Precipitation Responses
Major drought conditions WN
-CN WW CW WC CC NW
-NC
Responses to individual EOFs
Responses to combined EOFs
Pluvial conditions

10. Annual cycle of Response to Pacific and Atlantic Patterns

23. Seasonality in the Response to Pacific SST
v’2 850 and Z200
V 850 and Precip
DJF
Shift in storm tracks
MAM
JJA
SST forcing
Changein LLJ
Runs carried out with the NSIPP 1 AGCM - response to Pacific SST forcing (2 stds of second EOF of annual mean SSTs)
SON

24. Seasonality in the Response to Atlantic SST
slp and Z200
V 850 and Precip
Seasonality in the Response to Atlantic SST
SST forcing

25. Impact of Soil Moisture Feedbacks on JJA PrecipitationCW CW
Interactive soil moisture
No soil moisture feedbacks WC WC

26. Response to Global Warming Pattern

27. Impact of Global Warming/Cooling Pattern
Positive Phase
Annual Mean Surface Temperature
Negative Phase
Hi Siegfried and Randy,
The trend runs are in /atmos/pegion/mpp/cli_20/eof_forced_runs/
there are several directories there, trend/pos and trend/neg are the runs you want to look at. There are grads control files in the top level directory.
The *clim* files in each directory are the 50-year average for each run. The control for these runs are in
/atmos/pegion/c20c/exp003/monthlies/
On my webpages, trend positive 1 (TP1) is ( enso_pos_natl_neg_trend_pos + enso_neg_natl_pos_trend_pos)/2.0-clim
trend positive 2 (TP2) is trend_pos - clim
trend negative 1 (TN1) is ( enso_pos_natl_neg_trend_neg + enso_neg_natl_pos_trend_neg)/2.0-clim
trend negative 2 (TN2) is trend_neg - clim
The cleanest comparison is TP2 and TN2 °C

28. Histograms of Daily Surface Temperature
Southern Great Plains
Northern Great Plains
Negatively skewed
Negatively skewed
extremes
extremes
Define sgp and ngp, runs are for how many years? Which months?
If in dry regime: Soil moisture positive skew (because close to lower limit)->, evap - positive skewed - > neg skewed Tsfc (because of neg relationship between T and evap)
Not true if in wet regime (say further east) - then neg evap skewed
Need to look at what regime we are in - supposedly we are in the dry soil moisture regime
Red: +GW SST, Blue: -GW SST, Black: climatological SST

29. Composite Fields for Extreme Warm Days
Southern Great Plains
Northern Great Plains
I have made composite for both the Northern and Southern Great plains. The northern composite is for temperatures > 305K, and the southern temperature cutoff is 309.
Phil
Evap drives Temp (neg relationship) - consistency in the plots
If temp drives evap - reverse relationship

30. From Hailan Wang Response to Globally Uniform SST Anomaly: 0.32K
Response to Global Warming Anomaly Pattern
From Hailan Wang

31. Response to Vegetation Changes

32. C20C Project - Dataset Basic data set: Modified vegetation types:
•annual crop and pasture fraction on a 0.5 degree global grid for 1700 to 1992
(Nathalie de-Noblet) •
Modified vegetation types:
•cropland and pasture for the 'observed data sets' replace the agriculture vegetation type from the Sib dataset, other vegetation types are adjusted accordingly
•the 'observed' data were re-scaled to have the same mean as the Sib data
Also, I will have some plots for the Vegetation runs shortly.
The varying vegetation fraction was computed as follows:
Fraction of Cropland and Pasture for the 'observed data sets' replace the agriculture vegetation type from the Sib dataset.
I wasn't able to create any new vegetation tiles, so if the Sib data has no agriculture in a grid cell, then the new tile file won't have any farmland either. Also, I re-scaled the 'observed' data to have the same mean as the Sib data for 1990.
There are data sets available at:
which include annual crop and pasture fraction on a 0.5 degree global grid for 1700 to 1992 (Nathalie de-Noblet has indicated that this file may be extended to 2002 to coincide with the HadISST sea surface temperature and sea ice data sets. If any C20C group needs other parameter data sets for running their land surface model, please let us know, and Maggie will try to help generate them, in consultation with Nathalie.
Both Richard Betts and Nathalie de Noblet have agreed to provide global geographies of crops and
pasturelands for each timeslice. It would also be wise to agree on the natural vegetation pattern so
we impose a common perturbation on to a common land cover field. Richard has volonteered to
provide natural vegetation from the IGBP-DIS classes that we can then map onto the PFTs used in
individual models. Nathalie has natural vegetation divided into 11 natural PFTs. Either of these
would be suitable and perhaps the 11-PFT classification aids simplicity but we would welcome
advice from GLASS

35. 100 year control with modern veg and climatological SST minus 200 year run with fixed 1902 vegetation (not opposite sign form previous plot) and climatological SST

38. Summary and Conclusions
Both the Pacific and Atlantic Patterns impact precip in the Great Plains
Cold (warm) Pacific leads to drought (pluvial conditions)
Warm (cold ) Atlantic leads to drought (pluvial conditions)
Largest impacts occur when Pacific and Atlantic have opposite signed SST anomalies
The influence of the Atlantic pattern is largest during the summer and fall
impact is on the flow of moisture entering from the Gulf of Mexico
The Pacific pattern impacts Great Plains precipitation during all seasons
during winter and spring the influence appears to be primarily through changes in the planetary waves and associated changes in storm tracks
during summer and fall the impact appears to be also through an impact on the low level moisture entering the US from the Gulf
The Global Warming pattern shows some regional impact over land
E.g. substantial warming over North America
Similar warming impacts are found with uniform SST warming
Little impact on precipitation
Just beginning to look at vegetation impacts (cropland and pasture)
Appear to be some intriguing regional temperature impacts (e.g. North America)