Coupled Simulations of [CO2] Coupled Simulations of [CO2] with SiB-RAMSwith SiB-RAMS

Aaron Wang, Kathy Corbin,Scott Denning,

Lixin Lu, Ian Baker, John Kleist

““Average” Summer Cold Average” Summer Cold FrontFront

• Drops for a couple of days before the front

• Rises ~10 ppm just before

• Drops right afterward

Why does this happen?!

Composite of 17 summertime cold fronts over 5 years

Simple Biosphere Model: SiB2Simple Biosphere Model: SiB2

Sellers et al., 1996

Single Vegetation Canopy

Calculates transfer of energy, mass, and momentum between atmosphere and vegetation

13 Vegetation Types

3 Soil Layers

12 Soil Classes

Two-Stream Approximation

Model

Photosynthesis Model of

Farquhar et al. [1980]

Stomatal model of Ball [1988]

Water Vapor, Sensible Heat, and CO2 Fluxes

Expressed As Differences in

Potentials Divided by Resistances

SiB2-RAMS 10-Day Simulation • Centered on WLEF tall tower in Park Falls, WI• 4 nested grids - Grid 3 450 by 450 km 5 km grid increment - Grid 4 97 by 97 km 1 km grid increment• Explicitly represented cloud processes • 18 LST August 10, 2001 to 18 LST August 20, 2001 - Cold front Aug 12 ~ 2 LST - Cold front Aug 15 ~ 23 LST - Cold front Aug 17 ~ 18 LST

SiB-RAMS SimulationsSiB-RAMS Simulations

SiB2-RAMS vs. WLEFSiB2-RAMS vs. WLEF

SiB2-RAMS NEE vs. WLEFSiB2-RAMS NEE vs. WLEF

SiB2-RAMS 396 m [COSiB2-RAMS 396 m [CO22] vs. WLEF] vs. WLEF

Conclusions on FrontConclusions on Front

• Blobs!• NEE blobs formed by weather anomalies

acting on Re and GPP• NEE blobs make regional CO2 blobs• Weather acts on CO2 blobs, advecting

them around and causing big variations at WLEF

• Why do we usually see positive blobs with summer cold fronts?!

Orbiting Carbon Observatory (OCO)Orbiting Carbon Observatory (OCO)• Scheduled to launch in 2008• 3 high-resolution spectrometers measuring reflected sunlight

- 0.76 mm O2 A-band- 1.61 and 2.06 mm CO2 bands

• Column-average CO2 dry air mole fraction (XCO2)• Single shot precision of ~0.5% • 1:15 PM equator crossing time• 16-day repeat cycle•10 km-wide cross-track field of view (FOV) at nadir• FOV divided into eight 1.25-km wide samples• 2.25-km down-track resolution at nadir

Errors to Avoid Errors to Avoid

1)Spatial Representation Errors: To what degree can one satellite track from a heterogeneous domain accurately represent the average CO2 concentration at the inversion resolution?

2) Temporal Representation Errors: Will measurements at 1:15 PM accurately capture the CO2 diurnal average?

3) Clear-Sky Errors: What is the sign and magnitude of local clear-sky errors? Will the measurements have temporal sampling errors from under-sampling synoptic events?

Satellite COSatellite CO22 in Transport Inversions? in Transport Inversions?

Assessment of Clearsky Bias from ObsAssessment of Clearsky Bias from Obs

• Select daytime values:- 1 PM (like seeing “holes between clouds”)- 11 AM – 4 PM (like big clear areas)

• Sub-divide the data into clear subsets

• Fit two harmonics to both the complete daytime datasets and the clear subsets

• Calculate the error: clear fit – total fit

Observed Clearsky BiasObserved Clearsky Bias

CO2 NEE CO

• Negative errors year-round• WLEF errors smaller than HF• Mean 1 PM error at WLEF is –1.15 ppm• Mean 1 PM error at HF is –2.57 ppm

• Negative summer errors• No significant winter errors• WLEF errors smaller than HF

• Anthropogenic emissions• Negative errors year-round • Similar shape to CO2 errors• 20 ppb of CO ~ .5 ppm of CO2

Explanatory Hypothesis: Explanatory Hypothesis: What could be going on?What could be going on?

• Year-round negative errors in both [CO] and [CO2] has two possible implications:

1) Boundary layer is deeper on clear days diluting [CO2]2) Cloudy days have advection of high [CO2]

• Investigated boundary layer depths using ECMWF re-analysis

Clear-sky boundary layer depth errors

• In the summer, boundary layers are ~250 m deeper than on cloudy days• In the winter, boundary layers are nearly the same on clear and cloudy days

SiB-RAMS Error EvaluationSiB-RAMS Error Evaluation

OCO Track

“Transport Model” Grid Cell

~1-degree• Grid 3 x = 5 km• Grid 4 x = 1 km • Sample total column

[CO2] along 10-km wide N-S “OCO tracks”

• Compare to “true” variation in domain

Same case presented before (summer cold front, 2001)

Total Column [COTotal Column [CO22] & Cloud Cover] & Cloud Cover

• Cloudy days have higher CO2

Cloud cover and the total column modeled CO2 concentration over WLEF. Cloud cover of 0 is clear sky, 1 is cloudy.

Total Column COTotal Column CO2 2 Grid 4Grid 4

1 PM total column CO2 concentrations, in ppm.

97 km

97 km

Cloud Cover Grid 4Cloud Cover Grid 4

Daily cloud cover at 1 PM. ClearCloudy

97 km

97 km

Total Column COTotal Column CO2 2 Grid 3Grid 3

Daily 1 PM total column CO2 concentrations, in ppm.

450 km

450 km

Cloud Cover Grid 3Cloud Cover Grid 3

Daily cloud cover at 1 PM.

ClearCloudy

450 km

450 km

Spatial Representation ErrorsSpatial Representation Errors Grid 4 Grid 3

• Nearly symmetrical between under and overestimation• On grid 4, 95% of OCO tracks within 0.2 ppm of domain avg• On grid 3, 95% of OCO tracks within 0.8 ppm of domain avg

Simulated OCO at 1 PM – Corresponding 1 PM Domain Average

Lower Higher

Temporal Representation Temporal Representation ErrorsErrors

•Temporal variability not well sampled with a single measurement

• Using satellite [CO2] to optimize diurnally-averaged concentrations introduces large errors into the inversion

Grid 4 Grid 3

OCO track at 1 PM – Domain-Average Diurnal Mean

““Local” Clear-Sky ErrorsLocal” Clear-Sky ErrorsGrid 4 Grid 3

Clear Grid Cells – All Grid Cells for Each Track

• Error is symmetrical between under and overestimation• Main influence is advection, not biology• On grid 4, 95% of the tracks are within 0.1• On grid 3, 95% of the tracks are within 1.0

Temporal Sampling ErrorsTemporal Sampling ErrorsGrid 4 Grid 3

OCO clearsky mean – 10-Day Total Mean from Each Track

• All tracks have large bias of ~0.5 ppm• Contributing factors:

- Under-sampling of synoptic events- Local suppression of NEE: bias of ~0.5 mol/m2/s

Temporal Sampling ErrorsTemporal Sampling ErrorsGrid 4 Grid 3

OCO at 1 PM – 10-Day Domain Average• Error primarily negative due to lower CO2 on clear days• Each peak shows errors from a different day• Largest errors come from completely clear days

Satellite ConclusionsSatellite Conclusions

• Spatial representation error not bad relative to spectroscopy

• Ditto for diurnal cycle• “Local” clearsky error (due to

NEE) not bad• HUGE errors associated with

temporal undersampling of synoptic variability (because of frontal clouds!)