gerfs1 top-down approach to estimation of the regional carbon budget in west siberia s. maksyutov...
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GERFGERFS1S1
Top-down approach to estimation of the regional carbon budget in West Siberia
S. Maksyutov (1)
T. Machida, K. Shimoyama, N.Kadygrov, A. Itoh (1) P. Patra (2) M. Arshinov, O. Krasnov, B. Belan (3), N. Fedoseev (4)
(1) CGER/NIES, Tsukuba, Japan(2) FRCGC/JAMSTEC, Yokohama, Japan(3) IAO, Tomsk, Russia(4) Permafrost Research Institute, Yakutsk, Russia
Inverse modeling of regional CO2 fluxes using tower network in West Siberia
Transcom workshop, Purdue Univ., Apr 23-27, 2007
GERFGERFS1S1
Method: Inverse model of the atmospheric CO2 transport is applied to constrain surface CO2 fluxes by the observed patterns of the atmospheric CO2 (with seasonal cycles)
Components:
- Bottom-up estimate of C fluxes (long term), based on the terrestrial ecosystem NPP, respiration, biomass, biomass change.
1. Forward models: terrestrial ecosystem flux model (hourly to seasonal
scale): coupled to atmospheric transport model.
2. Inverse model of atmospheric transport, finding optimal corrections to the surface fluxes
Top-down approach to estimation of the regional carbon budget in West Siberia
GERFGERFS1S1
Q. (Back in 2002) Why do inverse modeling of carbon fluxes in West Siberia?
- Established collaboration programs on atmospheric and ground based observations
- Advantage for atmospheric transport modeling: simplified meteorology, flat terrain.
- Scientifically interesting region: strong impact by climate change.
Top-down approach to estimation of the regional carbon budget in West Siberia
GERFGERFS1S1
Top-down approach to estimation of the regional carbon budget in West Siberia
Integrated vegetation map (1x1 km)based on
GLC2000,forest inventory MODIS VCF vegetation continuous fields (500m)wetland typology map
GERFGERFS1S1
Bottom-up estimate of C fluxes (long term), based on the terrestrial ecosystem NPP, respiration, biomass, biomass change.
Inventory of the carbon content and its long-term changes using field observations and forest survey data.
- Forest inventory: provides observations of the wood stock (carbon stock) and annual change in forest area by category (felling, fire, etc)
- Soil carbon stock inventory (by agricultural soil profile observations)
- Wetlands (25% of the area, accumulators of peat deposits: need to know the area, and area fraction by landscape elements
Top-down approach to estimation of the regional carbon budget in West Siberia
GERFGERFS1S1
Empirical modeling of the forest carbon stock inventory and dynamicsForest state account (FSA): provides observations of the wood stock and annual
change in forest area by category (felling, fire, etc), Frequency: reporting 1 year, full reporting 5 years, unit survey about 15 years
Top-down approach to estimation of the regional carbon budget in West Siberia
FSA: regions and enterprises
FSA data for each unit: wood stock, area - by species, age class
Net Primary Production
0
100
200
300
400
500
600
700
800
0 100 200 300
Age, Year
I
II
III
IV
V
Va
Carbon, g/m2/yr
Input to empirical dynamic model
Cedar (pinus sibirica)
NPP by age and productivity class.
Based on yield tables.
GERFGERFS1S1
Top-down approach to estimation of the regional carbon budget in West Siberia
soil profiles1 -Soil carbon database
2- IIASA Russia CD
45
50
55
60
65
70
60 65 70 75 80 85 90
lon
lat lat
lat
1. Comparison of the soil carbon surveys in recent 30 years indicates soil carbon loss to erosion. (Titlyanova et al)
Problem: While forests and wetlands provide carbon sink, the agricultural lands show some loss of carbon
2. Long term observations of the soil carbon after conversion to arable lands
show stabilization of carbon content after ~50years. (Barsukov et al)
Siberian soil carbon profile database (Titlyanova et al)
soil map
Surgut1993 -
NovosibirskYakutsk
GERFGERFS1S1
Top-down approach to estimation of the regional carbon budget in West Siberia
Airborne observations: air sampling and analysis
GERFGERFS1S1
Top-down approach to estimation of the regional carbon budget in West SiberiaOBSERVATIONS
Igrim(IGR)(63o12’N, 64o24’E)47m, 24m
Demyanskoe(DEM)(59o47’N, 70o52’E)
63m, 45m
Parabel(PRB)(58o15’N, 82o24’E)67m, 35m
Berezorechka (BRZ)(56o09’N, 84o20’E)
80m, 40m, 20m, 5m
Yakutsk(YAK)(62o50’N, 129o21’E)70m, 11m
Noyabrsk(NOY)(63o26’N, 76o46’E)
43m, 21m
planned
NoyabrskIgrim
Beloretsk
Demyanskoe
Azovo
Parabel
Berezorechka
Savuushka
ZotinoYakutsk
Igrim(IGR)(63o12’N, 64o24’E)47m, 24m
Demyanskoe(DEM)(59o47’N, 70o52’E)
63m, 45m
Parabel(PRB)(58o15’N, 82o24’E)67m, 35m
Berezorechka (BRZ)(56o09’N, 84o20’E)
80m, 40m, 20m, 5m
Yakutsk(YAK)(62o50’N, 129o21’E)70m, 11m
Noyabrsk(NOY)(63o26’N, 76o46’E)
43m, 21m
Working
NoyabrskIgrim
Vaganovo
Demyanskoe
Azovo
Parabel
Berezorechka
Savuushka
ZotinoYakutsk
Observations: hourly data, -> selected afternoon data and fitted with Globalview type fits
350375400425
350375400425
CO
2 [
ppm
]
63m 45m
350375400425
350375400425
43m 21m
350375400425
350375400425
47m 24m
350375400425
350375400425
67m 35m
2002 2003 2004 2005 2006 2007350375400425
350375400425
BRZ
DEM
NOY
IGR
PRB
YEAR
70m 11m
YAK
350375400425
350375400425
80m 40m
GERFGERFS1S1
Top-down approach to estimation of the regional carbon budget in West Siberia
Inverse modeling: monthly fluxes from 66 regions
64 region map 66 region map (color map – by region number)
Inverse model used in this study is documented in: Patra, P.K., M. Ishizawa, S. Maksyutov, T. Nakazawa, and G. Inoue, (2005)
Global Biogeochem. Cycles, 19, GB3005, doi:10.1029/2004GB002258.
Seasonal variation of CO2 Flux with 66 region inversion and 1 year (2005) of tower data
-4
-3
-2
-1
0
1
2
3
4
2004.9 2005 2005.1 2005.2 2005.3 2005.4 2005.5 2005.6 2005.7 2005.8 2005.9 2006g/d
ay
/m2
CASA land44 CASA + TDI, land44
-4
-3
-2
-1
0
1
2
3
4
2004.9 2005 2005.1 2005.2 2005.3 2005.4 2005.5 2005.6 2005.7 2005.8 2005.9 2006g/d
ay
/m2
CASA land43 CASA + TDI, land43
-4
-3
-2
-1
0
1
2
3
4
2004.9 2005 2005.1 2005.2 2005.3 2005.4 2005.5 2005.6 2005.7 2005.8 2005.9 2006g/d
ay
/m2
CASA land27 CASA + TDI, land27
-4
-3
-2
-1
0
1
2
3
4
2004.9 2005 2005.1 2005.2 2005.3 2005.4 2005.5 2005.6 2005.7 2005.8 2005.9 2006g/d
ay
/m2
CASA land25 CASA + TDI, land25
W.Siberia South (top), North (bottom)
Central.Siberia South (bottom), North (top)
Seasonal variation of CO2 Flux with 66 region inversion and 1 year (2005) of tower data
W.Siberia South (top), North (bottom)
Central.Siberia South (bottom), North (top)
-4
-3
-2
-1
0
1
2
3
4
2004.9 2005 2005.1 2005.2 2005.3 2005.4 2005.5 2005.6 2005.7 2005.8 2005.9 2006g/d
ay
/m2
CASA land44 CASA + TDI, land44
-4
-3
-2
-1
0
1
2
3
4
2004.9 2005 2005.1 2005.2 2005.3 2005.4 2005.5 2005.6 2005.7 2005.8 2005.9 2006g/d
ay
/m2
CASA land43 CASA + TDI, land43
-4
-3
-2
-1
0
1
2
3
4
2004.9 2005 2005.1 2005.2 2005.3 2005.4 2005.5 2005.6 2005.7 2005.8 2005.9 2006g/d
ay
/m2
CASA land27 CASA + TDI, land27
-4
-3
-2
-1
0
1
2
3
4
2004.9 2005 2005.1 2005.2 2005.3 2005.4 2005.5 2005.6 2005.7 2005.8 2005.9 2006g/d
ay
/m2
CASA land25 CASA + TDI, land25
Seasonal variation of CO2 Flux with 66 region inversion and WITHOUT 1 year (2005) of tower data
W.Siberia South (top), North (bottom)
Central.Siberia South (bottom), North (top)
-4
-3
-2
-1
0
1
2
3
4
2004.9 2005 2005.1 2005.2 2005.3 2005.4 2005.5 2005.6 2005.7 2005.8 2005.9 2006g/d
ay
/m2
CASA CASA + TDI, land25
-4
-3
-2
-1
0
1
2
3
4
2004.9 2005 2005.1 2005.2 2005.3 2005.4 2005.5 2005.6 2005.7 2005.8 2005.9 2006g/d
ay/m
2
CASA CASA + TDI, land27
-4
-3
-2
-1
0
1
2
3
4
2004.9 2005 2005.1 2005.2 2005.3 2005.4 2005.5 2005.6 2005.7 2005.8 2005.9 2006g/d
ay/m
2
CASA CASA + TDI, land43
-4
-3
-2
-1
0
1
2
3
4
2004.9 2005 2005.1 2005.2 2005.3 2005.4 2005.5 2005.6 2005.7 2005.8 2005.9 2006g/d
ay/m
2
CASA CASA + TDI, land44
land44
-1.3
-0.8
-0.3
0.3
0.8
2004.9 2005 2005.1 2005.2 2005.3 2005.4 2005.5 2005.6 2005.7 2005.8 2005.9 2006
CO
2 F
lux
[tC
/ha/
Mo
nth
]
CASA TDI Sim-CYCLE
land43
-1.3
-0.8
-0.3
0.3
0.8
2004.9 2005 2005.1 2005.2 2005.3 2005.4 2005.5 2005.6 2005.7 2005.8 2005.9 2006C
O2
Flu
x [
tC/h
a/M
on
th]
CASA TDI Sim-CYCLE
land27
-1.3
-0.8
-0.3
0.3
0.8
2004.9 2005 2005.1 2005.2 2005.3 2005.4 2005.5 2005.6 2005.7 2005.8 2005.9 2006
CO
2 F
lux
[tC
/ha/
Mo
nth
]
CASA TDI Sim-CYCLE
land25
-1.3
-0.8
-0.3
0.3
0.8
2004.9 2005 2005.1 2005.2 2005.3 2005.4 2005.5 2005.6 2005.7 2005.8 2005.9 2006
CO
2 F
lux
[tC
/ha
/Mo
nth
]
CASA TDI Sim-CYCLE
Seasonal variation of CO2 Flux, Comparison with another biospheric model (Simcycle)
W.Siberia South (bottom), North (top)
Central.Siberia South (bottom), North (top)
GERFGERFS1S1
Top-down approach to estimation of the regional carbon budget in West Siberia
Summary and conclusions:
Tower observations in 2002-2006 were fitted using data filtering procedure (Nakazawa et al) at 5 W.S. sites to produce Globalview type fits.
Only daytime observations were used
Seasonal flux variability in well constrained regions shows same amplitude as CASA (prior) but earlier summer drawdown.
Seasonal variability in under-constrained ones is not that reasonable.
The inverted fluxes amplitude and seasonality look similar to those simulated by Simcycle – prognostic model, which may suggest that:
1) the inverse model fluxes are reasonable (biologically)2) regional scale inverse model might be used as a tool to observe(!) regional
scale seasonality of natural terrestrial carbon cycle