Initialization of the Noah Land Surface Model and its Coupling to CFS

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Initialization of the Noah Land Surface Model and
its Coupling to CFS

• Ken Mitchell, Rongqian Yang, Jesse Meng
• and EMC Land Team
• Environmental Modeling Center (EMC)
• National Centers for Environmental Prediction
• NOAA Annual Climate Diagnostics and Prediction
  Workshop
• Boulder, CO
• 23-27 October 2006

Much of this work sponsored by the CPPA program
of the NOAA Climate Program Office
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Outline of Presentation

• The Noah Land Surface Model (Noah LSM)
• The Global Land Data Assimilation System with
  Noah LSM (GLDAS/Noah)
• CFS summer forecasts (N.H. summer)
• Impact of Noah LSM without GLDAS/Noah I.C.s
• Impact of Noah LSM with GLDAS/Noah I.C.s
• CFS winter forecasts (N.H. winter)
• CONUS focus

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Dynamical Ensemble Hydrological PredictionThe
Coupled and Uncoupled Approaches A) Coupled
B) Uncoupled
precipitation
Atmospheric Model (GFS)
Bias-corrected Precipitation Forecasts (ensemble)
Post Processor (Bias Correction)
Precipitation
Fluxes

Land Surface Model (Noah)
Land Surface Model (Noah)
Runoff (ensemble)
Runoff (ensemble)
River Routing Model
River Routing Model
Stream Flow (ensemble)
Stream Flow (ensemble)
Post Processor
Post processor
Final Product
Final Product
This presentation is about improving the coupled
land/atmosphere approach via the CFS
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CFS Improvement Thrusts(See also earlier
presentation by Suru Saha this session)

• Higher resolution
• T126 vs T62 (about 1-deg vs. 2-deg)
• Improved physics
• Atmosphere
• Ocean
• Sea ice
• Land
• Improved initial analysis / data assimilation
• Atmosphere
• Ocean
• Land
• Stochastic forcing

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Improving CFS Land Physics

• Current Ops CFS applies OSU LSM
• OSU LSM Oregon State University (late 1980s)
• H. Pan, L. Mahrt, M. Ek, J. Kim, P. Rusher,
  others
• Next-Gen CFS in CTB applies Noah LSM
• History of Noah LSM
• Development led by EMC (1990s, 2000s)
• Descendant of OSU LSM (but with many extensions)
• Available as a community LSM from NCEP public
  server (1-d column model)
• Key partners
• Federal NWS/OHD, Air Force, NESDIS/ORA,
  NASA/HSB, NCAR/RAP, CPC
• Universities OSU, Princeton, Rutgers, U.
  Oklahoma, U. Arizona
• Implementation History at NCEP
• Eta mesoscale model (Jan 1996)
• Regional Reanalysis and R-CDAS (2004)
• GFS global model (May 2005)
• Also implemented in
• EMC N. American Land Data Assimilation System
  (NLDAS)
• EMC and NASA/HSB Global Land Data Assimilation
  System (GLDAS)
• NASA/HSB Land Information System(LIS)

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• Noah LSM versus OSU LSM in NCEP Global Model
• 4 soil layers (10,30,60,100 cm) vs. 2 soil
  layers (10, 190 cm)
• land surface evaporation reduced high bias in
  warm-season
• vegetation cover improved properties and
  seasonality
• improved seasonal cycle of green vegetation
  fraction
• spatially varying root depth (1-2 m) vs.
  constant 2 m
• add frozen soil physics (freeze/thaw latent
  heat, limit infiltration)
• snowpack physics improvements greatly reduced
  early melt bias
• add snow density state variable (retain SWE)
• retain some snowmelt in snowpack and allow
  refreezing
• refine functions for snow cover fraction and
  snow albedo
• add patchy snow cover treatments to
• snow sublimation, sensible ground heat flux,
  skin temp
• improved numerics/robustness for very shallow
  snow
• transpiration refine soil moisture threshold for
  stress onset
• direct soil evaporation revise dependence on
  soil moisture
• smaller ground heat flux bias
• especially wet soil, under snowpack, under
  dense vegetation
• new functions for soil thermal diffusivity and
  soil heat capacity

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LAND DATA ASSIMILATION SYSTEMS

• Three Broad Approaches
• 1) Coupled Land/Atmosphere 4DDA
• precipitation forcing at land surface is from
  parent atmospheric model
• Precipitation may have large bias gtlarge soil
  moisture bias
• Soil moisture may be nudged to reduce impact of
  precipitation bias
• Exp. 1 based on external soil moisture
  climatology
• NCEP/NCAR Global Reanalysis 1
• Exp. 2 based on model-minus-observed precip
  differences
• NCEP/DOE Global Reanalysis 2 (GR2)
• GR2 provides initial land states for ops CFS/OSU
• 2) Uncoupled Land 4DDA (land model only)
• observed precipitation used directly in land
  surface forcing
• should execute same LSM on same grid terrain as
  coupled model
• Exp EMC uncoupled GLDAS
• GLDAS provides initial land states for CTB tests
  of CFS/Noah
• 3) Hybrid Land 4DDA e.g.Regional Reanalysis

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CFS Land Experiments (8) Land Experiments of CFS
T126 with CFS/Noah and CFS/OSU
Choice of Land Model
Intended Ops
?
Current Ops
GR2 denotes NCEP/DOE Global Reanalysis 2
Experiment Goal 10 years x 2 seasons
(winter/summer) x 10 members x 8
Experiments Experiments Completed to date 2
years X 8-10 members x the 3 experiments denoted
above by ? -- Summer 1999 (wet U.S. monsoon),
2000 (dry U.S. monsoon) -- Winter 1983
(strong ElNino), 1989 (significant LaNina)
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How do GLDAS/Noah and GR2/OSU land states compare?

• See Session 1 Poster
• by Jesse Meng et al.
• Some examples shown next
• in which GLDAS is designated as LIS
• LIS denotes the Land Information System
  infrastructure for land data assimilation that
  EMC has transitioned to NCEP test beds via
  partnership with the LIS development group in the
  NASA/GSFC Hydrological Sciences Branch.

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2-m total soil moisture 01 May Climatology
LIS/Noah
GR2/OSU
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Soil Moisture and Precip AnomaliesMay 1999
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Illinois 2-meter Soil Moisture mm 1985-2004
Total
Vtype 12
Climatology
Anomaly
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2-m total soil moisture 01 May Climatology
LIS/Noah
GR2/OSU
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2-m total soil moisture 01 May 1999 Anomaly
LIS/Noah
GR2/OSU
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2-m total soil moisture 30 Dec Climatology
LIS/Noah
GR2/OSU
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2-m total soil moisture 30 Dec 1982 Anomaly
LIS/Noah
GR2/OSU
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Summer1999 (wet U.S. monsoon) vs. 2000 (dry
U.S. monsoon)

• CFS/Noah/GLDAS
• vs.
• CFS/OSU/GR2 and CFS/Noah/GR2
• 10-members each
• (initialized from late April and early May)

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Observed Monthly Precipitation Anomaly
Right Column 2000
Left Column 1999
Top Row July
1999 Wetter Monsoon
Bottom Row August
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Interannual Difference 1999-minus-2000July
Total Precipitation Anomalies (mm)10-member
Ensemble Mean
T126 CFS / Noah / GLDAS
T126 CFS / OSU / GR2
T126 CFS / Noah / GR2
CFS with Noah is superior Provided
Noah-consistent initial land states provided!!
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Interannual Difference 1999-minus-2000JULY mean
2m Temperature Anomalies (K)10-member Ensemble
Mean
T126 CFS / Noah / GLDAS
T126 CFS / OSU / GR2
Both CFS/Noah and CFS/OSU have wrong sign in
southwest and midwest, but amplitde of CFS/Noah
error is substantially less than CFS/OSU.
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Interannual Difference 1999-minus-2000July mean
500 mb Height Anomalies (m)10-member Ensemble
Mean
T126 CFS / Noah / GLDAS
T126 CFS / OSU / GR2
Verifying NARR Analysis
No clear advantage for either CFS/Noah/GLDAS or
CFS/OSU/GR2
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Winter1983 (ElNino) vs. 1989 (LaNina)

• CFS/Noah/GLDAS
• vs.
• CFS/OSU/GR2
• 8-members each
• (initialized from late November and early
  December)

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Interannual Difference 1983-minus-1989Jan-Feb-Ma
r mean SST Anomalies (K)
T126 CFS / OSU / GR2
OBSERVED
Interannual difference in CFS predicted winter
mean SST agreed well with observed.
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Interannual Difference 1983-minus-1989Jan-Feb
(JF) Precipitation Anomalies (mm)8-member
Ensemble Mean
T126 CFS / Noah / GLDAS
T126 CFS / OSU / GR2
Verifying NARR Analysis
CFS/Noah/GLDAS not much different from
CFS/OSU/GR2. CFS/Noah/GLDAS does show
some indication of some improvement around
southern west coast.
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Interannual Difference 1983-minus-1989Jan-Feb
(JF) 2m Temperature Anomalies (K)8-member
Ensemble Mean
T126 CFS / Noah / GLDAS
T126 CFS / OSU / GR2
Verifying NARR Analysis
Neither CFS/Noah/GLDAS or CFS/OSU/GR2 shows any
particular advantage over the other. CFS/OSU
better in some regions, CFS/Noah better in other
regions.
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Interannual Difference 1983-minus-1989Jan-Feb
(JF) 500 Mb Height Anomalies (m)8-member
Ensemble Mean
T126 CFS / Noah / GLDAS
T126 CFS / OSU / GR2
Verifying NARR Analysis
Both CFS/Noah and CFS/OSU have rather poor
(albeit different) height anomaly pattern
compared to observed. CFS/Noah shows some slight
advantage along west coast and Southeast coast
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Conclusions

• The Noah LSM exhibits a promising preliminary
  indication of improving CFS summer season
  forecasts of precipitation and 2m air temperature
  over CONUS
• Provided Noah LSM compatible initial land states
  are provided by GLDAS/Noah
• The Noah LSM does not appear to improve CFS
  winter season forecasts of precipitation and
  height fields
• Much more follow-on work is needed
• Finish 10-year CFS/Noah and CFS/OSU climatology
• Assess other years and other regions besides
  CONUS
• Examine entire Jun-Jul-Aug period, not just July
• Investigate entire atmospheric and land water
  budget
• atmospheric moisture convergence versus surface
  evaporation