A1258609321ZloDR - PowerPoint PPT Presentation

Title: A1258609321ZloDR


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Summer Season Predictions with the Next NCEP CFS
Using Different Land Models and Different
Initial Land States
Assistance from other EMC members Suru Saha,
Cathy Thiaw, Shrinivas Moorthi
NOAA 32nd Climate Diagnostics and Prediction
Workshop (CDPW) 22-26 October 2007
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Outline

• Operational CFS
• CONUS summer season forecast skill precip, 2m-T,
  Pacific SST
• Next-generation CFS
• Analysis physics upgrades Atmos, Ocean, Land,
  Sea-Ice
• Double horizontal resolution
• CO2 trend
• CFS Experiment Design Land Summer Emphasis
• Land Models Two models (Noah LSM, OSU LSM)
• Land initial states Two sources (Global Reanal
  2, GLDAS)
• CFS Experiment Results
• CONUS precipitation 2-m air temperature
• Pacific SST
• Conclusions Future Work
• Future Work winter runs

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Performance of Currently Operational CFS(shown
in next four frames)

• -- SST (high correlation skill in tropical
  Pacific),
• -- CONUS precipitation (low correlation skill in
  summer)
• -- CONUS 2-m air temperature (low correlation
  skill in summer)

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CFS Tropical Pacific SST skill is very
competitive with empirical methods their
composite
15-member CFS reforecasts
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Ops CFS Seasonal SST Forecast SkillCorrelation
of CFS SST forecast with observed SST over
1982-2003For April initial conditions 15-member
ensemble mean
Correlation skill of SST prediction for central
and eastern tropical Pacific is rather high
1-Month Lead
6-Month Lead
More examples at http//www.cpc.ncep.noaa.gov/pro
ducts/people/wwang/cfs_skills/
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Ops CFS Seasonal Precipitation Forecast
SkillCorrelation of CFS precip forecast with
observed precip 1982-2003For April initial
conditions 15-member ensemble mean
Short-lead summer forecast correlation skill is
low across bulk of CONUS (lower than longer-lead
winter forecast)
1-Month Lead (valid summer)
6-Month Lead (valid winter)
More examples at http//www.cpc.ncep.noaa.gov/pro
ducts/people/wwang/cfs_skills/
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Ops CFS Seasonal Temperature Fcst Skill over
CONUSCorrelation of forecast with observed 2mT
over 22-year hindcastFor April initial
conditions 15-member ensemble mean
Short-lead summer forecast correlation skill is
low across majority of CONUS
More examples at http//www.cpc.ncep.noaa.gov/pro
ducts/people/wwang/cfs_skills/
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Experimental CFS versus Ops CFSSee workshop
Monday presentation by Hua-Lu Pan et al.

• Upgrades to CFS physics
• Atmosphere, ocean, land, sea-ice
• Double the CFS resolution
• T126 / L64 versus T62 / L28
• New CFS vertical coordinate
• Hybrid sigma-pressure versus sigma
• New analysis systems
• Atmosphere, ocean, land

The CFS experiments presented below incorporate
the upgrades highlighted above in red, with a
focus on the land upgrades.
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Experimental CFS Land Model UpgradeNoah LSM
(new) versus OSU LSM (old)

• Noah LSM
• 4 soil layers (10, 30, 60, 100 cm)
• Frozen soil physics included
• Surface fluxes weighted by snow cover fraction
• Improved seasonal cycle of vegetation cover
• Spatially varying root depth
• Runoff and infiltration account for sub-grid
  variability in precipitation soil moisture
• Improved soil snow thermal conductivity
• Higher canopy resistance
• Other

• OSU LSM
• 2 soil layers (10, 190 cm)
• No frozen soil physics
• Surface fluxes not weighted by snow fraction
• Vegetation fraction never less than 50 percent
• Spatially constant root depth
• Runoff infiltration do not account for subgrid
  variability of precipitation soil moisture
• Poor soil and snow thermal conductivity,
  especially for thin snowpack

Noah LSM replaced OSU LSM in operational NCEP
medium-range Global Forecast System (GFS) in late
May 2005
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Annual mean biases in surface energy fluxes In
five operational GCMs during 2003-2004 w.r.t.
nine flux-station sites distributed
world-wide from K. Yang et al. (2007, J. Meteor.
Soc. Japan)
Mean Bias Error (MBE)
lE Latent Heat Flux H Sensible Heat Flux Rn
Net Radiation µ Global mean
Pre-May 2005 NCEP GFS had large positive bias in
surface latent heat flux and corresponding large
negative bias in surface sensible heat flux.
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Mean GFS surface latent heat flux 09-25 May
2005 Upgrade to Noah LSM significantly reduced
the GFS surface latent heat flux (especially in
non-arid regions)
Pre-May 05 GFS with OSU LSM
Post-May 05 GFS with new Noah LSM
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CFS Land Experiments 4 configurations
Experiments of T126 CFS with CFS/Noah and
CFS/OSU25-year summer reforecasts (10 member
ensembles) from April initial conditions of
1980-2004
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(No Transcript)
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GLDAS versus Global Reanalysis 2 (GR2)Land
Treatment

• GLDAS an uncoupled land simulation system
  driven by observed precipitation analyses (CPC
  CMAP analyses)
• Executed using same grid, land mask, terrain
  field and Noah LSM as GFS in experimental CFS
• Non-precipitation land forcing is from GR2
• Executed retrospectively from 1979-2006 (after
  spin-up)
• GR2 a coupled atmosphere/land assimilation
  system wherein land component is driven by model
  predicted precipitation
• applies the OSU LSM
• nudges soil moisture based on differences between
  model and CPC CMAP precipitation

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GLDAS/Noah (top ) versus GR2/OSU (bottom)
2-meter soil moisture ( volume) May 1st
Climatology 01 May 1999 Anomaly
Observed 90-day Precipitation Anomaly (mm) valid
30 April 99
GLDAS/Noah
GLDAS/Noah
GR2/OSU
GR2/OSU
Left column GLDAS/Noah soil moisture climo is
generally higher then GR2/OSU Middle column
GLDAS/Noah soil moisture anomaly pattern agrees
better than that of GR2/OSU with observed
precipitation anomaly (right column top)
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Monthly Time Series (1985-2004) of Area-mean
Illinois 2-meter Soil Moisture
mmObservations (black), GLDAS/Noah (purple),
GR2/OSU (green)
The climatology of GLDAS/Noah soil moisture is
higher and closer to the observed climatology
than that of GR2/OSU, while the anomlies of all
three show generally better agreement with each
other (though some exceptions)
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Results of CFS Experiments

• All remaining frames

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JJA Precipitation Correlation Skill
CFS/Noah/GR2 case is clearly worst case (least
spatial extent of positive correlation). Remaining
three cases appear to have similar spatial
extent of positive correlation, but distributed
differently among sub-regions. Still
disappointingly small spatial extent
of correlations above 0.5 in all four
configurations.
From hindcasts for years 1981-2004. Ten-member
ensemble mean shown for each panel.
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JJA Precipitation Correlation Skill
As in previous frame, except Ops CFS result now
shown in upper right panel. Compared to Ops CFS,
the three viable experimental CFS configurations
do not show notably higher spatial extent of
positive correlation nor notably higher values of
positive correlation. Still disappointingly
small spatial extent of correlations above 0.5 in
all four configurations.
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OSU/GR2 somewhat better over CONUS Noah/GLDAS
worst over Canada
Noah/ GLDAS
Noah/ GR2
Noah/ GLDAS Climo
OSU/ GR2
10 Members each case (same initial dates)
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All experimental configurations better than Ops
CFS, mostly likely due to CO2 trend included in
experimental CFS but absent in ops CFS
Noah/ GLDAS
Noah/ GR2
Noah/ GLDAS Climo
This Frame same as previous, except Ops CFS (from
15 members) shown in lower right.
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JJA SST Correlation Skill
All four configurations yield similar SST
correlation patterns
CFS Noah/GR2
CFS Noah/GLDAS
CFS Noah/GLDAS Climo
CFS OSU/GR2
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JJA SST Correlation Skill
Ops CFS (lower right) better in Nino 3.4 but
worse over western warm pool
CFS Noah/GLDAS
CFS Noah/GR2
Ops CFS
CFS Noah/GLDAS Climo
This Frame same as previous, except Ops CFS (from
15 members) shown in lower right.
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Conclusions Future Work

• The relatively low CFS seasonal prediction skill
  for summer precipitation over CONUS is not
  materially improved by the tested upgrade in land
  surface physics and land data assimilation
• An upgrade to the land surface model of a GCM can
  possibly degrade GCM performance if the upgraded
  land model is not also incorporated into the data
  assimilation suite that supplies the initial land
  states
• The addition of a CO2 trend to the experimental
  CFS is likely the major source of the improvement
  in experimental CFS summer season surface
  temperature forecasts relative to the currently
  operational CFS
• The land model and land assimilation upgrades did
  not appear to materially increase the summer
  season surface temperature prediction skill of
  the CFS
• The use of initial soil moisture states with
  instantaneous soil moisture anomalies did not
  appear to provide an advantage over
  climatological soil moisture states, provided the
  soil moisture climatology was produced by the
  same land model being tested in the GCM
• The Tuesday workshop poster by Soo-Hyun Yoo et
  al. evaluated these same CFS experiments over the
  Asian-Australian Monsoon, showing modestly
  positive impact over that region from the land
  model upgrades presented here
• Future work will carry out this same suite of
  experiments for winter season hindcasts.