estimation of regional co2 fluxes using concentration measurements from a ring of towers
DESCRIPTION
ChEAS 2005. Estimation of regional CO2 fluxes using concentration measurements from a ring of towers. Marek Uliasz, Andrew Schuh & Scott Denning Department of Atmospheric Science Colorado State University. Inversion experiments using CO 2 pseudo-data. RAMS. meteorological fields. LPDM. - PowerPoint PPT PresentationTRANSCRIPT
Estimation of regional CO2 fluxes usingconcentration measurements from
a ring of towers
Estimation of regional CO2 fluxes usingconcentration measurements from
a ring of towersMarek Uliasz, Andrew Schuh & Scott Denning
Department of Atmospheric ScienceColorado State University
Marek Uliasz, Andrew Schuh & Scott DenningDepartment of Atmospheric Science
Colorado State University
ChEAS 2005
Inversion experimentsusing CO2 pseudo-dataInversion experimentsusing CO2 pseudo-data
meteorological fields
RAMS
LPDM
meteorological fields
RAMS
influence functions
CO2 observations
LPDM
meteorological fields
RAMS
influence functionsinversions
CO2 observations
LPDM
CO2 flux estimate
a-priori estimates of CO2
surface & inflow fluxes
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Configuration of source areaswith WLEF tower in the centerof polar coordinates
Example of estimation of NEE averaged for August 2000 Bayesian inversion technique using influence function derived from CSU RAMS and Lagrangian particle model flux estimation for source areas in polar coordinates within 400 km from WLEF tower (better coverage by atmospheric transport) NEE decomposed into respiration and assimilation fluxes: R=R0, A=A0 f(short wave radiation, vegetation class) inversion calculations for increasing number of concentration data (time series from towers) NEE uncertainty presented in terms of standard deviation derived from posteriori covariance matrix inflow CO2 flux is assumed to be known from a large scale transport model in further work, concentration data from additional tower will be used to improve the inflow flux given by a large scale model
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a-priori NEE uncertainty
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2] distance [km]
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WLEF 76m(single level) WLEF all levels WLEF all levels
+ 6 additional towers
N N NE S W E S W E S W
DIRECTIONAL SECTOR
Conclusions from pseudo-data inversion:Conclusions from pseudo-data inversion:
Successful inversions for surface fluxes
as long as inflow flux is known Successful inversions for surface fluxes
as long as inflow flux is known
Difficulty to handle inflow flux(es) as
unknown parameter in inversions Difficulty to handle inflow flux(es) as
unknown parameter in inversions
meteorological fields
RAMS
influence functionsinversions
CO2 observations
LPDM
CO2 flux estimate
a-priori estimates of CO2
surface & inflow fluxes
meteorological fields
CO2 fields
CO2 fluxes
SiB-RAMS
influence functionsinversions
CO2 observations
LPDM
CO2 flux estimate
a-priori estimates of CO2
surface & inflow fluxes
SiB-RAMS >>> LPDMSiB-RAMS >>> LPDM
SiB-RAMSSiB-RAMS
LPDMLPDM
PCTMPCTM
SiB-RAMSSiB-RAMS
LPDMLPDM off-line transport model
forward/backward model
Lagrangian particle model
PCTMPCTM
SiB-RAMSSiB-RAMS
LPDMLPDM
PCTMPCTM
?
SiB-RAMSSiB-RAMS
LPDMLPDM
PCTMPCTM
meteorological fields
CO2 fields and fluxes
other fields
subdomain extraction for LPDMsubdomain extraction for LPDM
subdomain extraction for LPDMsubdomain extraction for LPDM
subdomain extraction for LPDMsubdomain extraction for LPDM
subdomain extraction for LPDMsubdomain extraction for LPDM
subdomain extraction for LPDMsubdomain extraction for LPDM
subdomain extraction for LPDMsubdomain extraction for LPDM
subdomain extraction for LPDMsubdomain extraction for LPDM
SiB-RAMS simulationsummer 20042 nested grids2001 NDVIby Andrew Schuh
*
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* * * *
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( )
ˆ ˆ( ) ( )
yx
yx
y x
x y
LLT
z
LL H
t
L LT H T H
W E S Nx x L y y L
C
C qdxdydt
C C dxdydz
uC C u C C dydzdt vC C vC C dxdzdt
=
=
= = = =
Φ =
+
+
+ + +
∫∫∫
∫∫∫
∫∫∫ ∫∫∫% %
surface fluxes
initial concentration
inflow fluxes
influence function for concentration measurements C*influence function for concentration measurements C*
concentration sample
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time [hours]
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z=396minflow fluxinitial field
contribution of initial field and inflow flux
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z=396minflow fluxinitial field
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contribution of initial field and inflow flux
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contribution of initial field and inflow flux
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z=396mrespirationassimilation
contribution of respiration and assimilation fluxes
contribution of respiration and assimilation fluxes
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z=30mrespirationassimilation
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time [hours]
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z=30mSiB-RAMSSiB-RAMS>>LPDM
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time [hours]
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z=76mSiB-RAMSSiB-RAMS>>LPDM
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time [hours]
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CO2 [ppm]
z=122mSiB-RAMSSiB-RAMS>>LPDM
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time [hours]
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CO2 [ppm]
z=244mSiB-RAMSSiB-RAMS>>LPDM
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time [hours]
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z=396mSiB-RAMSSiB-RAMS>>LPDM
Cold front passage across the ringCold front passage across the ring
modeling approach to CO2 data analysismodeling approach to CO2 data analysis
Application of influence functions to analyze CO2 episodes
Application of influence functions to analyze CO2 episodes
= LI-820 sampling from 75m above ground oncommunication towers.
= 40m Sylvania flux towerwith high-quality standardgases.
= 447m WLEF tower. LI-820, CMDLin situ and flaskmeasurements.
The Ring of Towers
The Ring of Towers
data provided by
Ken Davis, Scott J. Richardson and Natasha Miles, The Pennsylvania State University
data provided by
Ken Davis, Scott J. Richardson and Natasha Miles, The Pennsylvania State University
1200 UTC
CO2 from 5 sites, April 29, 2004CO2 from 5 sites, April 29, 2004
Ken Davis, Scott J. Richardson and Natasha Miles The Pennsylvania State
University
Ken Davis, Scott J. Richardson and Natasha Miles The Pennsylvania State
University
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W LEF
B rule
Bayfie ld
F en ce
W ittenberg
Further workFurther work
SiB-RAMS simulations for 2004 SiB-RAMS simulations for 2004
model evaluation against data (meteorology, CO2) model evaluation against data (meteorology, CO2) inversions for regional CO2 fluxes inversions for regional CO2 fluxes Interpretation of CO2 observations in selected episodesInterpretation of CO2 observations in selected episodes