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

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Presentation on theme: "Gridded Biome-BGC Simulation with Explicit Fire-disturbance Sinkyu Kang, John Kimball, Steve W. Running Numerical Terradynamic Simulation Group, School."— 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 DataSize and location Before 1959: constant fire mortality After 1959: external fire mortality from the raw data

5 Generate fire grid Year cell[i,j] annual fire file Considering Explicit Fire-Disturbance

6 Considering Explicit Fire-Disturbance 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 (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 Modifed INI & EPC files Run Modified Biome-BGC ECOPHYS ENF-cool (wet conifer) 1 (flag) 1 = WOODY 0 = NON-WOODY …………………………………………………… (1/yr) annual whole-plant mortality fraction (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 Grid size (simulation unit): 66 columns and 60 rows (ca. 660  300km 2 ) Each simulation uses  i dentical 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 CO 2 and internal or external fire- disturbance  Nine climate change scenario (control,  2 o C,  20% precipitation) Total 108 cases of gridded Biome-BGC runs Experimental Design

10 660km 300km Land Cover

11 Topography N N

12 Climate (3-yr mean) TmaxTmin PrecipitationRadiation

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

14 Sample Result 2 – CO2 Difference (23, 2.8 g/m2) Const. CO2 – Increasing CO2 WC, Const. CO2 (140, 8.7 g/m2) 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, External fire (161, 11.8 g/m2) WC, Increasing CO2 (163, 11.1 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.) DBF, Const. CO2

17 Climate Scenario 0.8P 1.2P(+2T) 1.2P 0.8P(-2T)0.8P(+2T) 1.2P(-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 MOD17: daily PSN (MOD17A2) BGC: daily PSN with spin-up simulation MOD15-BGC: daily PSN using input LAI from MOD15 PSN (gC m -2 d -1 ) yearday Grass Reinitialize using satellite-driven LAI + allometry from spin-up simulation

20 COOP. Weather Station, Alabama

21 Warm (13.3 o C) Cool (6.2 o C)

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

23 Leaf emergency (J e )  (T a -5 o C) > 88 o C End of litterfall (J b )  (T a -10 o C) < -150 o C Maximum LAI (J m ) (Aug. 15 in this study) LAI model LAI-NDVI model LAI model

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 LAI measured in Aug and 1999 using LI-COR 2000

26 120 (0~3.8 m 2 m -2 ) LAI-NDVI Model : Leaf Emergence and Expand


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