Natasha Miles, Scott Richardson, Arlyn Andrews, Kathy Corbin, Kenneth Davis, Liza Diaz, Scott Denning, Erandi Lokupitiya, Douglas Martins, Paul Shepson,

Colm Sweeney, and Tris WestICDC8: September 2009

Atmospheric Results from the NACP’s Mid Continent Intensive Field Campaign

• Overall goal of Mid-Continental Intensive: Seek convergence between top-down and bottom-up estimates of the regional flux

• “Oversample” the atmosphere in the study region

• Atmospheric results– Purdue Univ / NOAA ALAR

(aircraft) Campaign– NOAA aircraft program– 9 tower sites (NOAA, PSU, U of

Minn)– NOAA Carbon Tracker– CSU SiBcrop-RAMS model– Comparisons to agricultural and

satellite data

LEFRosemount

~ 500 km

Atmospheric results from the NACP’sMid Continental Intensive

NOAA / Purdue University ALAR

Regional Survey15 – 25 June 2007

Colm Sweeney (NOAA/ESRL)Paul Shepson (Purdue University)Doug Martins (Purdue University)

Front

15 June 2007 17 June 2007

385 ppm

365 ppm

NOAA / Purdue University ALAR

Lagrangian Flux Estimates: 19 June 2007

In-situ Profiles

Flight Path

Flux = -10.3±2.4 μmol/m2/s

Martins et al., 2009

Regionally-averaged aircraft CO2 flux

Flux tower: soybeans

Flux tower: corn

Tower-based eddy covariance fluxes from the Brooks Field Site near Ames, IA

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Deviation from global mean [CO2]

Climatology of 12 of 16 currently running NOAA aircraft project sites• 2 – 3 profiles / month at each site• Increase in amplitude of the seasonal cycle from west to east

NOAA Aircraft Program CO2 Measurements

C. Sweeney (NOAA)

PSU Ring 2 towers• Network of 5 cavity ring-down spectroscopy

(Picarro, Inc.) instruments surrounding Iowa (April 2007 – October 2009)– Centerville, IA– Galesville, WI– Kewanee, IL– Mead, NE– Round Lake, MN

• Additional well-calibrated site on Ameriflux tower at Missouri Ozarks, MO

NOAA tall towers in MCI region

• Non-dispersive infrared spectroscopy (LiCor, Inc.) instruments

• LEF (1994 – current) • WBI (July 2007 – current)

U. Of Minn Rosemount* tower• Tunable diode laser instrument• May 2007 – current

* data courtesy of T. Griffis

Rosemount

LEF

Spatial differences / gradients during 2007 growing season on a daily time scale

• Large differences / gradients for some site pairs

• West Branch - Centerville

Difference Gradient

Spatial differences / gradients during growing season on a daily time scale

• Large differences /

gradients for some site pairs

• West Branch - Centerville (160 km)

• Other site pairs: lower differences / gradients

• Mead – Centerville (300 km)

• Median differences: 6.0 and 1.7 ppm

• Median gradients: 0.04 and 0.006 ppm/km

Difference Gradient

Seasonal cycle

• Large variance in seasonal drawdown, despite being separated by ~ 500 km

• 2 groups: 33 – 39 ppm drawdown and 24 – 29 ppm drawdown (difference of about 10 ppm)

Mauna Loawbi aircraft

* NOAA (Andrews/Sweeney) ** U of Minn (Griffis)

Seasonal cycle

• Large variance in seasonal drawdown, despite being separated by ~ 500 km

• 2 groups: 33 – 39 ppm drawdown and 24 – 29 ppm drawdown (difference of about 10 ppm)

Mauna Loawbi aircraft

* NOAA (Andrews/Sweeney) ** U of Minn (Griffis)

Seasonal cycle

• Large variance in seasonal drawdown, despite being separated by ~ 500 km

• 2 groups: 33 – 39 ppm drawdown and 24 – 29 ppm drawdown (difference of about 10 ppm)

Mauna Loawbi aircraft

* NOAA (Andrews/Sweeney) ** U of Minn (Griffis)

Corn NPP in the Mid Continental Intensive region: 2007

T. West

Corn NPP in the Mid Continental Intensive region: 2007

Sites with larger seasonal [CO2] drawdown- Consistent with “Corn belt” according to NPP

T. West

Model-data comparisons (forwards results)

SiBcrop-RAMS (K. Corbin; A. Schuh; E. Lokupitiya; A.S. Denning)

• June-August 2007• Regional • Coupled with crop phenology

model for corn and soybean developed by Lokupitiya et al. (2009); *wheat to be added

NOAA-ESRL Carbon Tracker (A. Andrews; A. Jacobson)

• 2007• Global• Optimized to best fit data on

global obs network (not including Ring 2)

http://carbontracker.noaa.govcorn

wheat*

soy

Observations vs Carbon Tracker: 2007

• Overall drawdown in CT 2008 is too weak• But some features of modeled variability are consistent with obs

- large variability- mm has less drawdown than wbi, rl, and kw in both model and obs

Obs - model (ppm)

2007

Observations vs Carbon Tracker: 2007

• Suggestive that CT model could be improved by adding crop details• Trajectory analysis: LEF residuals large for southerly trajectories, small for

northerly trajectories

Corn belt sites

Liza Diaz (PSU)

Observations vs SiBcrop-RAMS: 2007 growing season

• Overall drawdown compares well• Problems with spatial distribution

growing season

Observations vs SiBcrop-RAMS: 2007 growing season

Corn belt sites

Obs – model (ppm)

Problems with spatial distribution• Corn belt sites: not enough drawdown• Centerville, LEF: too much drawdown• Using more realistic percentages for land cover, especially for

corn, may improve results

Seasonal cycle: interannual variability

• West Branch (wbi) and Centerville (ce) differ significantly from 2007 to 2008

• From agricultural statistics (NASS), total estimated NPP of corn (T. West) 222 PgC for 2007 207 PgC for 2008

Mauna Loawbi aircraft

* NOAA (Andrews/Sweeney) ** U of Minn (Griffis)

Flooding in the Midwestern U.S.: June 2008

Dell Creek breach of Lake Delton, WI U.S. Air Force

Cedar Rapids, IA Don Becker (USGS)

Delay in seasonal drawdown

• 2008 [CO2] minima is delayed by 2 – 4 weeks, compared to 2007

• Effect of flood?

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Normalized Difference Vegetation Index (NDVI) for Iowa crops

• Satellite-based: 2-week delay of phenological curve for 2008 compared to 2007, for both corn and soy

T. West

Summary

• Aircraft and tower results both indicate large spatial gradients between sites despite relatively small site separations

• Seasonal cycle: – Difference amongst sites, some with very large seasonal drawdown

• Comparisons of tower obs to CarbonTracker and SiBcrop-RAMS– Important to model agriculture correctly– Transport important also

• Interannual variability: flooding in June 2008, atmospheric data corroborated by satellite and agricultural statistics data

• What spatial density of tower measurements is necessary? To be answered by including subsets of the Ring 2 data in the inversions

Natasha MilesPenn State Universitynmiles@met.psu.edu