1 / 26

Gridded Biome-BGC Simulation with Explicit Fire-disturbance

Gridded Biome-BGC Simulation with Explicit Fire-disturbance. Sinkyu Kang, John Kimball, Steve W. Running Numerical Terradynamic Simulation Group, School of Forestry, Univeristy of Montan. Purpose. Demonstrate Gridded Biome-BGC run in BOREAS.

nairi
Télécharger la présentation

Gridded Biome-BGC Simulation with Explicit Fire-disturbance

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Gridded Biome-BGC Simulation with Explicit Fire-disturbance Sinkyu Kang, John Kimball, Steve W. Running Numerical Terradynamic Simulation Group, School of Forestry, Univeristy of Montan

  2. Purpose Demonstrate Gridded Biome-BGC run in BOREAS. Illustrate Biome-BGC modification for explicit fire-disturbance simulation

  3. Process of Gridded BGC • Batch run of Biome-BGC combined with input and output modules • Using IDL platform Spatial & temporal data INI, EPC, MET file for point Biome BGC run Batch run of point Biome BGC Generate gridded outputs

  4. Considering Explicit Fire-Disturbance Raw Data Size and location Before 1959: constant fire mortality After 1959: external fire mortality from the raw data

  5. Considering Explicit Fire-Disturbance Generate fire grid Year cell[i,j] annual fire file 83 84 85 86 87

  6. Considering Explicit Fire-Disturbance Modifed INI & EPC files 1.0 (DIM) multiplier for shortwave radiation CO2_CONTROL (keyword - do not remove) 1 (flag) 0=constant 1=vary with file 2=constant, file for Ndep 286.923 (ppm) constant atmospheric CO2 concentration kco21862.txt (file) annual variable CO2 filename FIRE_CONTROL (keyword - do not remove) 1 (flag) 0=constant fire mortality 1=vary with file fire-5-14.txt (file) annual variable fire mortality (year fire_mortality) SITE (keyword) start of site physical constants block Run Modified Biome-BGC ECOPHYS ENF-cool (wet conifer) 1 (flag) 1 = WOODY 0 = NON-WOODY ……………………………………………………. 0.005 (1/yr) annual whole-plant mortality fraction 0.005 (1/yr) mean annual fire mortality fraction 0.26 (1/yr) annual carbon fraction consumed by fire 1.5 (ratio) (ALLOCATION) new fine root C : new leaf C 1.1 (ratio) (ALLOCATION) new stem C : new leaf C

  7. ET (mm/y) & NPP (gC/m2/y) LAI (m2/m2) Daily fire mortality Constant fire mortality > 1959 < Explicit fire occurrence Internal fire-disturbance External fire-disturbance

  8. Modification of Biome-BGC • Biome-BGC v.411 • 47 source files • 8 header files • 2 library files • In this study, even this small change demanded • modification of 7 source files • modification of 4 header files • addition of a new subroutine source file

  9. Application to the Boreal Forest Biome Experimental Design Grid size (simulation unit): 66 columns and 60 rows (ca. 660300km2) Each simulation uses • identical land cover and soil property over the entire grid • identical spatial meteorological variable (1994~1996) Every simulation differs in • land cover types (DBF, Grass, DC, WC) • constant or varying ambient CO2 and internal or external fire-disturbance • Nine climate change scenario (control, 2oC, 20% precipitation) Total 108 cases of gridded Biome-BGC runs

  10. Land Cover 300km 660km

  11. Topography N N

  12. Climate (3-yr mean) Tmax Tmin Precipitation Radiation

  13. Sample Result 1 – Land cover DBF (412, 87.5 g/m2) Grass (347, 48.6 g/m2) DC (279, 26.2 g/m2) WC (140, 8.7 g/m2)

  14. Sample Result 2 – CO2 WC, Const. CO2 (140, 8.7 g/m2) Difference (23, 2.8 g/m2) Const. CO2 – Increasing CO2 WC, Increasing CO2 (163, 11.1 g/m2)

  15. Sample Result 3 - Fire Difference (-1.4, 3.7 g/m2) External fire – Increasing CO2 WC, Increasing CO2 (163, 11.1 g/m2) WC, External fire (161, 11.8 g/m2)

  16. Sample Result 4 – Climate Change PRCP*TEMP: PRCP(-1,0,+1), TEMP(-1,0,+1), EX: +1-1 (1.2*prcp & -2 of Temp.) 00 +10 -10 +1+1 +1-1 -1+1 -1-1 DBF, Const. CO2

  17. Climate Scenario 1.2P 0.8P 1.2P(+2T) 1.2P(-2T) 0.8P(+2T) 0.8P(-2T)

  18. Future consideration • Model Initialization Spin-up run: • initialize soil and vegetation variable at balanced equilibrium condition • time consuming process as number of gridcells increase Extrapolation from satellite measurement: • satellite-driven LAI  initialize vegetation carbon variables using allometry rules (Landsat & MODIS in watershed and regional scale) • Replace model phenology with RS phenology (ex. MODIS)

  19. Grass PSN (gC m-2 d-1) yearday Reinitialize using satellite-driven LAI + allometry from spin-up simulation MOD17: daily PSN (MOD17A2) BGC: daily PSN with spin-up simulation MOD15-BGC: daily PSN using input LAI from MOD15

  20. COOP. Weather Station, Alabama

  21. Warm (13.3 oC) Cool (6.2 oC)

  22. Model Overview Soil temperature model Spatially-explicit estimations Field sampling & measurement RS DEM Meteorological Data Soil Data 1.Respiration 2.Temperature 3.Water content 4.SOM Field LAI NDVI Meteorological Models 1.Air temperature 2.Precipitation 3.Solar radiation 4.Vapor pressure deficit LAI-NDVI model Soil moisture model Soil respiration model

  23. LAI model LAI model LAI-NDVI model Leaf emergency (Je)  (Ta-5oC) > 88oC Maximum LAI (Jm) (Aug. 15 in this study) End of litterfall (Jb)  (Ta-10oC) < -150oC

  24. NDVI (Landsat TM, August, 1991) Mean 0.55 STDEV 0.13 (solid dots are locations where LAI was measured.)

  25. LAI-NDVI model Landsat TM image in Aug. 1991 LAI measured in Aug. 1998 and 1999 using LI-COR 2000

  26. LAI-NDVI Model : Leaf Emergence and Expand 120 (0~3.8 m2 m-2) 125 130 135 140 145

More Related