1. Modeling framework for estimation of regional CO2 fluxes using concentration measurements from a ring of towers Modeling framework for estimation of regional CO2 fluxes using concentration measurements from a ring of towers Marek Uliasz and Scott Denning Department of Atmospheric Science Colorado State University Marek Uliasz and Scott Denning Department of Atmospheric Science Colorado State University Ninth Symposium on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface - 2005 AMS Annual Meeting 9-13 January, 2005, San Diego, California

2. Over the past 420,000 years atmospheric CO 2 has varied between 180 and 280 parts per million, with concomitant swings of 10° C in the Earth’s climate. Since the Industrial Revolution, CO 2 has risen dramatically, with an observed warming of 0.5° C in the past 100 years. 370 ppm Vostok (400k yr) Ice Core data (Petit et al, 1999) Law Dome ice core Etheridge et al (1999) South Pole Flask Data NOAA/CMDL (2001) Atmospheric CO 2

3.  Atmospheric CO 2 data  Modeling framework for regional inversions  The ring of towers campaign  Example of CO 2 flux estimation using pseudo-data  Modeling approach to CO 2 analysis Cold front passage Lake signature  Atmospheric CO 2 data  Modeling framework for regional inversions  The ring of towers campaign  Example of CO 2 flux estimation using pseudo-data  Modeling approach to CO 2 analysis Cold front passage Lake signature OUTLINE

4. Atmospheric CO 2 Observations ~2000

5. Atmospheric CO 2 Observations ~2007

6. Orbiting Carbon Observatory (Planned August 2007 launch) Estimated accuracy for single column ~1.6 ppmv 1 x 1.5 km IFOV 10 pixel wide swath 105 minute polar orbit 26º spacing in longitude between swaths 16-day return time

7. Atmospheric CO 2 Observations ~2000

8. = LI-820 sampling from 75m above ground on communication towers. = 40m Sylvania flux tower with high-quality standard gases. = 447m WLEF tower. LI-820, CMDL in situ and flask measurements. 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

9. CSU RAMS LPD model influence functions Bayesian inversion modeling framework regional meteorology atmospheric transport source-receptor matrix data analysis estimation of regional CO 2 fluxes global transport inflow fluxes SiB

10. CSU RAMS LPD model influence functions Bayesian inversion modeling framework regional meteorology atmospheric transport source-receptor matrix data analysis estimation of regional CO 2 fluxes SiB Ensemble Data Assimilation Maximum Likelihood Ensemble Filter

11. CSU RAMS LPD model influence functions Bayesian inversion modeling framework regional meteorology atmospheric transport source-receptor matrix data analysis estimation of regional CO 2 fluxes Parameterized Chemical Transport Model (PCTM) Parameterized Chemical Transport Model (PCTM) global transport inflow fluxes SiB Ensemble Data Assimilation Maximum Likelihood Ensemble Filter

12. Climatology of influence functions for August 2000 influence functions derived from RAMS/LPD model simulations passive tracer different configurations of concentration samples - time series from - a single level of WLEF tower - all levels of WLEF tower - WLEF tower + six 76m towers

13. Configuration of source areas with WLEF tower in the center of 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=R 0, A=A 0 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 CO 2 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

14. Cold front passage across the ring modeling approach to CO 2 data analysis

15. 1200 UTC CO 2 from 5 sites, April 29, 2004 Ken Davis, Scott J. Richardson and Natasha Miles The Pennsylvania State University

16. [10 -10 x sm -3 ]

17. sunset

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28. sunrise

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40. seasonal cycle of CO 2 flux at WLEF tower

41. seasonal cycle diurnal cycle of CO 2 flux at WLEF tower

42. Lake signature in CO 2 data modeling approach to CO 2 data analysis

43. influence function: August 2003 influence function: August 2003 entire domain

44. influence function: August 2003 influence function: August 2003 land entire domain

45. influence function: August 2003 influence function: August 2003 land water entire domain

46. Relative contribution of different source areas to tracer concentrations at 400m WLEF tower May-November 2003 land 85.4% Lake Superior 9.5% Lake Michigan 1.8% other waters 3.1%

47. Relative contribution of different source areas to tracer concentrations at 400m WLEF tower May-November 2003 land 85.4% Lake Superior 9.5% Lake Michigan 1.8% other waters 3.1%

48. Relative contribution of different source areas to tracer concentrations at 400m WLEF tower May-November 2003 land 85.4% Lake Superior 9.5% Lake Michigan 1.8% other waters 3.1%

49. Relative contribution of different source areas to tracer concentrations at 400m WLEF tower May-November 2003 land 85.4% Lake Superior 9.5% Lake Michigan 1.8% other waters 3.1%

50. Relative contribution of different source areas to tracer concentrations at 400m WLEF tower May-November 2003 land 85.4% Lake Superior 9.5% Lake Michigan 1.8% other waters 3.1%

51. Difference in observed CO 2 at 400m WLEF tower between transport from Lake Superior and transport from land with 95% confidence intervals Difference in observed CO 2 at 400m WLEF tower between transport from Lake Superior and transport from land with 95% confidence intervals 1996 2003

52. Difference in observed CO 2 at 400m WLEF tower between transport from Lake Superior and transport from land with 95% confidence intervals Difference in observed CO 2 at 400m WLEF tower between transport from Lake Superior and transport from land with 95% confidence intervals 1996 2003 data analysis in wind sectors without modeling

53. Travel time between Lake Superior and WLEF tower two transport patterns in September

54. Further work Data analysis using influence functions: Exploring vertical transport Influence functions integrated with CO 2 fluxes SiB-RAMS simulation Data analysis using influence functions: Exploring vertical transport Influence functions integrated with CO 2 fluxes SiB-RAMS simulation Estimations of Regional CO 2 Fluxes PCTM >> RAMS >> LPDM pseudo-data inversions inversions using the data from the ring of towers Estimations of Regional CO 2 Fluxes PCTM >> RAMS >> LPDM pseudo-data inversions inversions using the data from the ring of towers