Dai Yongjiu1, Bi Xunqiang2, Filippo Goirgi2

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Preliminary results of the coupling of CLM with
ICTP RegCM3

• Dai Yongjiu1, Bi Xunqiang2, Filippo Goirgi2

1, Beijing Normal University, China 2, Abdus
Salam ICTP, Italy
2
Outline

1. Motivation
2. Common Land Model
3. Coupling CLM with RegCM3
4. Preliminary results

3
Outline

1. Motivation
2. Common Land Model
3. Coupling CLM with RegCM3
4. Preliminary results

4
ICTP RegCM3

• Dynamics
• MM5 Hydrostatic (Grell et al 1994)
• Non-hydrostatic (MM5 or WRF, in progress)
• Radiation
• CCM3.6.6 (Kiehl 1996)
• Large-Scale Clouds Precipitation
• SUBEX (Pal et al 2000)
• Cumulus convection
• Grell (1993) FC80 Closure
• Anthes-Kuo (1977)
• MIT/Emanuel (1991)
• Betts-Miller (1993)
• Boundary Layer
• Holtslag (1990)
• Tracers/Aerosols
• Qian et al (2001) Solmon et al (2005)
• includes dusts (Zakey, in progress)

• Land Surface
• BATS1e (Dickinson et al 1993)
• SUB-BATS (Giorgi et al 2003)
• CLM (Dai et al 2003, Dai Bi, in progress)
• IBIS (Foley Winter in progress)
• Ocean Fluxes
• BATS1e (Dickinson et al 1993)
• Zeng et al (1998)
• Air-Sea Coupling (MITogcm, OASIS coupler, in
  progress)
• Nesting
• Numerous GCM/Reanalysis Interfaces
• Double nesting (one-way)
• Computations
• User-Friendly
• Multiple Platforms
• Parallel Code (Pu Bi, Gao)

http//www.ictp.trieste.it/pubregcm/RegCM3
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Motivation for coupling CLM with RegCM3

• BATS1e, behaves well, but
• There are some problems for several vegetations
• For irrigated crop, eccentric behavior !!!
• Over ocean, in both weak and strong wind
  conditions, tends to over-estimate LH flux.
• Not enough vertical resolution (one vegetation
  layer, one snow layer, 3 soil layers)
• Lack the code maintenance (frozen code, no funds
  to update it since 1993)

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Ocean Flux SchemeBATS vs. Zeng

• The BATS1e bulk aerodynamic algorithm uses the
  Monin-Obukhov similarity relations without
  special treatments of convective or very stable
  conditions.
• Overestimate latent heat in both weak and strong
  wind conditions
• The Zeng algorithm describes all stability
  conditions and includes a gustiness velocity to
  account for the additional flux induced by
  boundary layer scale variability

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Biosphere-Atmosphere Transfer Scheme BATS1E
(Dickinson et al 1993)

• One canopy layer
• Stomatal conductance (Jarvis-type) model
• 20 vegetation types
• One snow layer
• 3 soil layers(10cm, 12m, 3m)
• Soil T Force-restore
• Soil moisture Diffusive/gravitational

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Motivation for coupling CLM with RegCM3

• Common Land Model, state of the art !
• In PILPS and extensive off-line tests, CLM can
  get better results than BATS1e and other LSMs
  (Dai, 2003)
• The coupling of CLM with CCM3, CLM behaves better
  than LSM (Zeng, 2002)
• CLM has been coupled with CCSM3(CAM3), WRF, IAP
  AGCM, RSM, LDAS, RegCM,
• High vertical resolution (one vegetation layer,
  up to 5 snow layers, 10 soil layers)
• Better maintenance, Free updated CLM code and doc
  are at http//climate.eas.gatech.edu/dickinsono
  r http//www.cgd.ucar.edu/tss/clm

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Outline

1. Motivation
2. Common Land Model
3. Coupling CLM with RegCM3
4. Preliminary results

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Whats the Common Land Model ?

• Motivation
• A general land processes model is used as a
  common tools in climate and weather forecasting
  models.
• History
• 1996, Concept of CLM, by R. E. Dickinson
• 1999, Initial CLM code released by Y. Daibased
  on LSM, BATS1e, IAP94
• 3 year model validation (off-line and coupling)
• 2002, 2 branch CLM versions are officially
  released.Community Land Model 3.0, Maintained
  by NCAR
• Common Land Model 3.0, Maintained by
  Georgia Tech

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CLM (1999 version) major characteristics ?

1. Enough unevenly spaced layers to adequately
   represent soil temperature and soil moisture, and
   a multi-layer parameterization of snow processes
   
2. An explicit treatment of the mass of liquid water
   and ice water and their phase change within the
   snow and soil system
3. A runoff parameterization following the TOPMODEL
   concept
4. A canopy photosynthesis-conductance model that
   describes the simultaneous transfer of CO2 and
   water vapor into and out of vegetation
5. A tiled treatment of subgrid fraction of energy
   and water balance.

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Horizontal and vertical representation

• Horizontal
• Every surface grid cell can be subdivided into
  any number of tiles.
• Energy and water balance calculations are
  performed over each tile at every time step, and
  each tile maintains its own state variables.
• The tiles in a grid square respond to the mean
  conditions in the overlying atmospheric grid box,
  and this grid box, in turn, responds to the
  area-weighted fluxes of heat and moisture from
  the tiles.
• The tiles within a grid square do not interact
  with each other directly.
• Mosaic treatment

• Vertical
• one vegetation layer.
• 10 soil layers, and the thickness 17.5, 27.6,
  45.5, 75.0, 123.6, 203.8, 336.0, 553.9, 913.3,
  and 1137.0 mm with a total thickness of 3430 mm.
• up to 5 snow layers (depending on snow depth).
  Contrary to more usual practice, the snow layers
  from top to bottom are numbered as negative
  values.

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Model Reliability and Maintenance?

• The model has been extensively evaluated in
  off-line and coupling runs in different groups
  independently. Good performance in off-line and
  coupling validation.
• Maintenance and future development (physics
  parameterization and land data development) based
  on the major land model groups
• Dai at Beijing Normal University,
• Dickinson at Georgia Tech,
• Bonan at NCAR,
• Houser at GSFC/NASA,
• Zeng at U. Arizona,
• Yang at UT Austin,
• Denning at CSU

Common Land Model
Community Land Model
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New development in Common Land Model

1. Two big leaf model for leaf temperatures,
   photosynthesis-stomatal resistance
2. Two-stream approximation for canopy albedo
   calculation with the solution for singularity
   point, and the calculations for radiation for the
   separated canopy (sunlit and shaded)
3. New numerical scheme of iteration for leaf
   temperatures calculation
4. New treatment for canopy interception with the
   consideration of the fraction of convection and
   large-scale precipitation
5. Turbulent transfer under canopy

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• New development in Common Land Model
• Soil thermal and hydrological processes with
  theconsideration of the depth to bedrock
• Surface runoff and sub-surface runoff
• Rooting fraction and the water stress on
  transpiration
• Use a grass tile 2m height air temperature in
  place of an area average for matching the routine
  meteorological observation
• Perfect energy and water balance within every
  time-step
• A slab ocean-sea ice model
• Albedo Parameterization Based on MODIS and LDAS
  data.

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• New development in Community Land Model
• Replace biome-type land cover classification
  scheme with plant function type representation
  and its related
• New methods to enable simulation of the
  terrestrial carbon cycle
• New methods to enable simulation of dynamic
  vegetation
• Two-stream approximation for canopy radiation
  transfer
• River routing model.

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Outline

1. Motivation
2. Common Land Model
3. Coupling CLM with RegCM3
4. Preliminary results

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RegCM3 Modeling System Flow Chart
ECMWF ERA40 NNRP1NNRP2 EH5OM FVGCM HadAMH REGCM

PostProc
PreProc
Main
NetCDF output FERRET, NCL
Global Terrrestrial Data
Global 1x1 SST Data
GrADS output ATM.yyyymmddhh RAD.yyyymmddhh SRF.yyy
ymmddhh CHE.yyyymmddhh
POSTPROC
SST
Terrain
ICBC
POSTPROCv5d
ICBCyyyymmddhh
Vis5D
RegCM Main
SIGMAtoP
DOMAIN.INFO
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Land surface characteristic field
Terrain

• Raw Source data
• Global, Resolution 30sec.x 30sec.
• ( 0.925 km)
• - Elevation data
• USGS DEM
• - Vegetation/land-use data
• USGS (24 category 1)
• - Soil texture data global
• FAO global USGS US domain
• 2 vertical layers 0-30 cm 30-100cm.

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USGS Land Use/Land Cover Legend
0. Ocean 1. Urban and Built-Up Land 2. Dry-land
Cropland and Pasture 3. Irrigated Cropland and
Pasture 4. Mixed Dry-land / Irrigated Cropland
and Pasture 5. Cropland / Grassland Mosaic 6.
Cropland/Woodland Mosaic 7. Grassland 8.
Shrubland 9. Mixed Shrubland/Grassland 10.
Savanna
11. Deciduous Broadleaf Forest 12. Deciduous
Needleleaf Forest 13. Evergreen Broadleaf Forest
14. Evergreen Needleleaf Forest 15. Mixed
Forest 16. Inland Water Bodies 17. Herbaceous
Wetland 18. Wooded Wetland 19. Barren or
Sparsely Vegetated 20. Herbaceous Tundra 21.
Wooded Tundra 22. Mixed Tundra 23. Bare Ground
Tundra 24. Snow or Ice
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90 sec x 90 sec
1. Urban 1. Urban 7. Grassland
16. Lake 7. Grassland 7. Grassland
15. Mixed forest 19. Barren 16. Lake
5 patches 1. Urban 2/9 7. Grassland 3/9 15.
Mixed forest 1/9 16. Lake 2/9 19. Barren 1/9
regroup 30 sec. data to 60, 30, 10, 5, 3, 2 min.
data
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16-category Soil categories
1. Sand 2. Loamy Sand 3. Sandy Loam 4. Silt
Loam 5. Silt 6. Loam 7. Sandy Clay Loam 8. Silty
Clay Loam 9. Clay Loam 10. Sandy Clay 11. Silty
Clay 12. Clay 13. Organic Materials 14. Water 15.
Bedrock 16. Other
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90 sec x 90 sec
3. Sandy loam 4.Silt Loam 1. Sand
9.Clay Loam 1. Sand 12 Clay
5 Silt 6. Loam 12. Clay
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Soil temperature and Soil Moisture
ICBC

• ERA40
• Global, Resolution 2.5ox 2.5o, 4 layer
• NCEP/NCAR reanalysis type I
• Global, Resolution 2.5ox 2.5o

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Outline

1. Motivation
2. Common Land Model
3. Coupling CLM with RegCM3
4. Preliminary results

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ICTP RegCM3with new packages

• Land Surface
• BATS1e (Dickinson et al 1993)
• SUB-BATS (Giorgi et al 2003)
• CLM (Dai et al 2003, Dai Bi, in progress)
• IBIS (Foley Winter in progress)
• Ocean Fluxes
• BATS1e (Dickinson et al 1993)
• Zeng et al (1998)
• Air-Sea Coupling (MITogcm, OASIS coupler, in
  progress)
• Nesting
• Numerous GCM/Reanalysis Interfaces
• Double nesting (one-way)
• Computations
• User-Friendly
• Multiple Platforms
• Parallel Code (Pu Bi, Gao)

• Dynamics
• MM5 Hydrostatic (Grell et al 1994)
• Radiation
• CCM3.6.6 (Kiehl 1996)
• Large-Scale Clouds Precipitation
• SUBEX (Pal et al 2000)
• Cumulus convection
• Grell (1993) FC80 Closure
• Anthes-Kuo (1977)
• MIT/Emanuel (1991)
• Betts-Miller (1993)
• Zhang-McFarlane (new closure)
• Boundary Layer
• Holtslag (1990)
• Tracers/Aerosols
• Qian et al (2001) Solmon et al (2005)
• includes dusts (Zakey, in progress)

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The End
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A Two-big-Leaf Model for Canopy Temperature,
Photosynthesis and Stomatal Conductance (Journal
of Climate, June 2004)
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Two-stream Approximation for Canopy Albedoes
Calculation with the Solution for Singularity
Point (Journal of Climate, June 2004)
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Singular points at two-stream approximation
radiative transfer model of Sellers (1985)

• 1.

are the coefficients of the projected area in
solar incident direction
2.
are the the scattering coefficient of
phytoelements and upscatter parameters for
diffuse and direct beams
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New treatment for canopy interception with the
consideration of the fraction of convection and
large-scale precipitation
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Turbulent transfer under canopy(Treatment of
under-canopy turbulence in land models by Zeng et
al. 2004, Journal of Climate)
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Soil thermal and hydrological processes with the
consideration of the depth to bedrock
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Depth to bedrock
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Representation of the Land Surface and its
Overlying Near Surface Air Temperature in Climate
Models
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• All covers smaller than 1 are either discarded,
  and carried to the largest area tile in
  grid-squares, with the exception of grass that is
  assumed to always be at least 1.
• Use of a grass tile temperature in place of an
  area average or of an average of daily maximum
  and minimum values rather than a 24-hr average
  can change the estimates of daily temperatures
  over regions by up to half a degree as a result
  of the diurnal patterns of surface temperatures
  and their dependence on cover.

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Albedo Parameterization Based on MODIS and LDAS
data
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New Conceptual Model Bare Soil Albedo
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New Conceptual Model Vegetation Albedo
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New Conceptual Model Static Localization Factor
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New Conceptual Model Optimization Solution
Parameters
Optimization Solver
FSQP FORTRAN Feasible Sequential Quadratic
Programming http//www.aemdesign.com/downloadfsqp.
htm Designed to find the optimal solution for the
minimization of the maximum of a set of smooth
objective functions subject to equality and
inequality constraints, linear or nonlinear, and
simple bounds on the variables. It requires the
accurate definition of the objective functions
and constraint functions as well as the gradients
of these functions to achieve a robust solution.

Zhou, J. L., A. L. Tits, and C. T. Lawrence,
1997 Users Guide for FFSQP Version 3.7 A
FORTRAN Code for Solving Constrained Nonlinear
(Minimax) Optimization Problems, Generating
Iterates Satisfying All Inequality and Linear
Constraints. Institute for Systems Research,
University of Maryland, Technical Report
SRC-TR-92-107r5, College Park, MD 20742, 44 pp.
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Grassland
OLD
NEW
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NEW correlation
NEW relative bias
OLD correlation
OLD relative bias
Direct Visible
Direct Near Infrared
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NEW correlation
NEW relative bias
OLD correlation
OLD relative bias
Diffuse Visible
Diffuse Near Infrared