1. Use of Biome-BGC with the ChEAS flux tower network to address scaling issues
Faith Ann Heinsch
NTSG, School of Forestry
The University of Montana
ChEAS Meeting
July 1, 2003

2. The BIOME-BGC Terrestrial Ecosystem Process Model
BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for vegetation and soil on a daily basis.
Model algorithms represent physical and biological processes that control fluxes of energy and mass:
New leaf growth and old leaf litterfall
Sunlight interception by leaves, and penetration to the ground
Precipitation routing to leaves and soil
Snow (SWE) accumulation and melting
Drainage and runoff of soil water
Evaporation of water from soil and wet leaves
Transpiration of soil water through leaf stomata
Photosynthetic fixation of carbon from CO2 in the air
N uptake from the soil
Distribution of C and N to growing plant parts
Decomposition of fresh plant litter and old soil organic matter
Plant mortality
Plant phenology
Fire/disturbance

3. BIOME-BGC Major Features:
Daily time step (day/night partitioning based on daily information)
Single, uniform soil layer hydrology (bucket model)
1 uniform snow layer of SWE (no canopy snow interception/losses)
1 canopy layer (sunlit/shaded leaf partitioning)
Dynamic phenology and C/N allocation (e.g. LAI, biomass, soil and litter)
Disturbance (fire) and mortality functions
Variable litter and soil C decomposition rates (3 litter and 4 soil C pools)
Major Features:

4. Meteorological Parameters Required by Biome-BGC
Daily maximum temperature (°C)
Daily minimum temperature (°C)
Daylight average temperature (°C)
Daily total precipitation (cm)
Daylight average partial pressure of water vapor (Pa)
Daylight average shortwave radiant flux density (W/m2)
Daylength (s)

5. LAI Site Data Latitude Elevation Slope/Aspect Soil Depth Soil Texture
Site Data
Latitude
Elevation
Slope/Aspect
Soil Depth
Soil Texture
Atmospheric CO2
Plant
Soil Organic Matter
Atmospheric N
Soil Mineral N
Allocation to New growth
N Uptake MR
Litter
PSN GR HR
Meteorological Data
Air Temperature
Radiation
Precipitation
Humidity
Evaporation/ Transpiration
Photosynthesis
Total Respiration
Soil and Litter Respiration
LAI
Snow
Soil
Outflow
Temperature C
Annual Input
N Deposition
N Fixation
Daily - Annual
Evapotranspiration
Respiration
Absorbed PAR
Daily - Annual Allocation
 Carbon, Nitrogen
-leaf (LAI)
-stem
-coarse root
-fine root
N Flux
C Flux
H2O
Periodic Input
 Disturbance
-fire
-harvest
-grazing
-agriculture

6. BIOME-BGC Eco-physiological Parameters
Biome-BGC uses a list of 43 parameters to differentiate biomes.
general eco-physiological characteristics
must be specified prior to each model
simulation
can be measured in the field, obtained from the
literature or derived from other measurements.
Default Biome types with defined parameters
Deciduous Broadleaf Forest (temperate)
Deciduous Needleleaf forest (larch)
Evergreen Broadleaf Forest (subtropical/tropical)
Evergreen Needleleaf Forest
Evergreen Shrubland
C3 Grassland
C4 Grassland

7. Integration Simulation Validation Model Estimates of: Hydrograph data
Biome
BGC
Landcover
database
Other inputs:
soils, elevation,
N-deposition
Surface
weather
Disturbance
history
Vegetation
parameter
Simulation
Model Estimates of:
Outflow
Snow ET Rh
NEE
NPP
Soil C
fPAR
Biomass
LAI
Hydrograph
data
SNOTEL
Flux tower
Ancillary
measurements
at flux sites
Satellite data
(MODIS,
AVHRR)
FIA, FHM,
Ecodata
(Inventory)
FIA = Forest Inventory and Analysis Program (USDA FS)
FHM = Forest Health Monitoring (EPA)
Ecodata = European – forest industry products, energy, and transportation data
Validation

8. BIOME-BGC Simulated Daily Carbon and Water Exchange
(1Barrow Tussock / Wet Sedge Tundra Site, 2000)
Daily 1Meteorology
Daily C Budget
good job of biomass, but showing much less C uptake than tower data – must all be going underground (can’t msr well)
doubled precip to prevent dryout.
1 Daily meteorological data obtained from Barrow W Post Station, 71.28N W

9. BIOME-BGC Simulated Cumulative Net Carbon Exchange
(1Barrow Tussock / Wet Sedge Tundra Site)
C sink (+)
run for a couple of years with re-init every yr
resp dominate – source for much of yr
may not be true if sat during winter
really more like what Atqasuk where it is drier (BGC does not do Barrow well).
C source (-)
1 Daily meteorological data obtained from Barrow W Post Station, 71.28N W

10. Biome-BGC runs for 4 areas in Alaska Site Name Latitude
C source (+)
C sink (+)
Biome-BGC runs
for 4 areas in Alaska
Alaska Study Region
C source (+)
C sink (+)
electra sites
sap flow, etc.
grew forest, compared with Seawinds data and now MODIS
latit variation between sites for C02 exchange -> freeze-thaw variation
Site Name Latitude
Kenai AK N
Bonanza Creek AK N
Coldfoot AK N
Atigun AK N

11. Biome-BGC Estimates of LAI Park Falls, WI

12. Biome-BGC Estimates of NEE and GPP

13. Suggested Improvements to Biome-BGC Simulations at ChEAS Flux Tower Sites

14. Wetland-BGC
Presently being tested in Barrow, AK and the Niyak floodplain near Glacier Park, MT
Dynamic groundwater component
Previously 1 soil layer, now 2 (saturated/unsaturated)
Designed to be require minimal additional data
Methane??

15. Unique Site Disturbance History
Natural Disturbances
Timing
Intensity
Examples
Fire
Blowdown
Managed Disturbances
Timing
Intensity
Examples
Fertilization
Harvest
Slash burn
Plant

16. Ensembling of Simulations
Temporal
Necessary for historic disturbances
1 simulation for each year of the meteorological record
Obscures effects of meteorology to allow recovery to be seen
Spatial
Non-interactive
Age class
Old growth forests
Selective harvest and replant
Vegetation Type
ENF vs. DBF
Hydrology
Upland vs. wetland

17. Disturbance History
Credit: P. Thornton, NCAR

18. Seasonal Cycle of GEP
Credit: P. Thornton, NCAR

19. Annual LAI in Final Simulation Year
Credit:
P. Thornton,
NCAR

20. Annual NEE in Final Simulation Year
Credit:
P. Thornton,
NCAR

21. Annual ET in Final Simulation Year
Credit:
P. Thornton,
NCAR

22. Suggested Improvements
Difficult to attribute discrepancies to either the model or measurements
Probably a combination of:
Site-specific parameterization
Low maximum stomatal conductance
Incorrect treatment of respiration at low Tair
Site-specific measurement biases
Undermeasurement of warm season respiration
Need to find a way to decompose NEE

24. Biome-BGC Default Eco-physiological Parameters: Evergreen Needleleaf Forest

25. Example Initialization File
MET_INPUT (keyword) start of meteorology file control block
BIOME-BGC
Example Initialization
File
metdata/TDE.mtc41 meteorology input filename
(int) header lines in met file
RESTART (keyword) start of restart control block
(flag) 1 = read r
estart file = don't read
restart file
(flag) 1 = write restart file 0 = don't write
restart file
(flag) 1 = use restart metyear 0 = reset metyear
restart/TDE_n.endpoint input restart filename
restart/TDE.
endpoint output restart filename
TIME_DEFINE (keyword -
do not remove)
(int) number of meteorological data years
(int) number of simulation years
(int) first simulation year
(flag) = spinup simulation 0 = normal
simulation
(int) maximum number of spinup years (if spinup
simulation)
CLIM_CHANGE (keyword -
do not remove)
(deg C) offset for Tmax
(deg C) off
set for Tmin
(DIM) multiplier for Prcp
(DIM) multiplier for VPD
(DIM) multiplier for shortwave radiation
CO2_CONTROL (keyword -
do not remove)
(flag) 0=constant 1=vary with fil
e 2=constant, file
for Ndep
(ppm) constant atmospheric CO2 concentration
TDE_co2.txt (file) annual variable CO2 filename
SITE (keyword) start of site physical constants block
(m) effective soil dept
h (corrected for rock
fraction)
(%) sand percentage by volume in rock -
free soil
(%) silt percentage by volume in rock -
free soil
(%) clay percentage by volume in rock -
free soil
(m)
site elevation
(degrees) site latitude ( -
for S.Hem.)
(DIM) site shortwave albedo
(kgN/m2/yr) wet+dry atmospheric deposition of N
(kgN/m2/yr) symbiotic+asymbiotic fixation of N

26. Example Initialization File (cont.)
RAMP
_NDEP (keyword -
do not remove)
BIOME-BGC
Example Initialization File (cont.)
(flag) do a ramped N -
deposition run? 0=no, 1=yes
(int) reference year for industrial N deposition
(kgN/m2/yr) industrial N deposition value
EPC_FILE (keyword -
do no
t remove)
dbf.epc (file) TDE DBF ecophysiological constants
W_STATE (keyword) start of water state variable initialization block
(kg/m2) water stored in snowpack
(DIM) initial soil water as a proportion of sa
turation
C_STATE (keyword) start of carbon state variable initialization block
(kgC/m2) first -
year maximum leaf carbon
(kgC/m2) first -
year maximum stem carbon
(kgC/m2) coarse woody debris carbon 0.
(kgC/m2) litter carbon, labile pool
(kgC/m2) litter carbon, unshielded cellulose pool
(kgC/m2) litter carbon, shielded cellulose pool
(kgC/m2) litter carbon, lignin pool
(kgC/m2)
soil carbon, fast microbial recycling pool
(kgC/m2) soil carbon, medium microbial recycling pool
(kgC/m2) soil carbon, slow microbial recycling pool
(kgC/m2) soil carbon, recalcitrant SOM (slowest)
N_STA
TE (keyword) start of nitrogen state variable initialization block
(kgN/m2) litter nitrogen, labile pool
(kgN/m2) soil nitrogen, mineral pool
OUTPUT_CONTROL (keyword -
do not remove)
outputs/TDE_out (text) pr
efix for output files
1 (flag) 1 = write daily output 0 = no daily output
0 (flag) 1 = monthly avg of daily variables 0 = no monthly avg
0 (flag) 1 = annual avg of daily variables 0 = no annual avg
1 (flag) 1 = write annual output 0 =
no annual output
1 (flag) for on -
screen progress indicator
DAILY_OUTPUT (keyword)
3 (int) number of daily variables to output
epv.vwc (%)
wf.soilw_trans (kg m^ - 2)
wf.canopyw_evap (kg m^ - 2)
ANNUAL_OUTPUT
(keyword)
(int) number of annual output variables
annual maximum projected LAI
vegetation C
END_INIT (keyword) indicates the end of the initialization file

27. What if Some Met Data is Missing?
Use a nearby weather station
Use MT-CLIM to estimate radiation and humidity measurements from Tmax, Tmin
designed to handle complex terrain
uses a base station to calculate “site” data
Use DAYMET (conterminous U.S. only)
uses several met stations surrounding site
data available from
takes into account complex terrain

28. Soil Water Potential Curves
BIOME-BGC 1Soil Water –
Soil Water Potential Curves
(%)
(MPa)
Soil Class Silt loam Silt Loam
β-value
VWC_sat
PSI_sat
1after Cosby et al., 1984

29. BIOME-BGC Environmental Controls on Canopy Conductance (Walker Branch Site)
M_total,sun,shade = (MPPFD,sun,shade * MTmin * MVPD * MPSI)
where multipliers range from 0 (full Gs reduction) to 1 (no effect)
Gs, sun,shade = Gs,max * M_total, sun,shade

30. MODIS vs. Biome-BGC LAI
MODIS sees higher lai – modeling for deciduous stand, but pixel sees mixed forest

36. GPP Estimates of 5X5 km Grid
This is the GPP of the 5X5 km grid surrounding each tower site.

37. Park Falls/WLEF, WI

38. Park Falls/WLEF, WI: Tower vs. DAO

39. GPP from MOD17A2 Algorithm Default (DAO) Data As Input Meteorology

40. GPP from MOD17A2 Algorithm Tower Data As Input Meteorology