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CO 2 Diurnal Profiling Using Simulated Multispectral Geostationary Measurements Vijay Natraj, Damien Lafont, John Worden, Annmarie Eldering Jet Propulsion.

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Presentation on theme: "CO 2 Diurnal Profiling Using Simulated Multispectral Geostationary Measurements Vijay Natraj, Damien Lafont, John Worden, Annmarie Eldering Jet Propulsion."— Presentation transcript:

1 CO 2 Diurnal Profiling Using Simulated Multispectral Geostationary Measurements Vijay Natraj, Damien Lafont, John Worden, Annmarie Eldering Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA Contact: Vijay Natraj, Phone: +1-818-354-9229, Email: Vijay.Natraj@jpl.nasa.gov References [1] D. Pino, et al., 19 th Symposium on Boundary Layers and Turbulence, P1.1, 2010 [2] B. Stephens, et al., Science, 316, 1732-1735, 2007. [3] R.J.D. Spurr, J. Quant. Spectrosc. Radiat. Transfer, 102(2), 316-342, 2006. Introduction CO 2 diurnal cycle depends on surface sources, biospheric uptake and vertical mixing In the daytime, photosynthesis removes CO 2 and planetary boundary layer is efficiently mixed => low CO 2 concentration near surface At night, respiration produces CO2 and mixing is negligible => high CO 2 concentration near surface Surface measurements cannot distinguish between biospheric uptake and surface flux One-time profile measurement cannot distinguish between vertical mixing and surface flux Flux Estimates Previous estimates indicate that northern lands are strong sinks and tropical lands are strong sources Direct estimates from soils and plants disagree with these estimates Models with wrong vertical gradient of CO 2 estimate more NH land uptake and larger tropical land source to balance budget Continuous high spatial and temporal resolution measurements necessary to distinguish between free troposphere and lower troposphere concentrations Figure 1: Evolution of CO 2 concentration during an entire day (from Pino et al., 2010) Conclusions There are large errors in CO 2 flux estimates Multispectral geostationary measurements with high temporal resolution could be very beneficial Combined near IR and thermal IR retrieval is able to correctly characterize PBL variability for a sample summertime midwest scenario Combined retrieval is also able to capture more features of the vertical profile More simulations being run to test multispectral retrieval tool on a variety of scenarios (wintertime midlatitude, tropical, southern hemisphere) CO 2 Diurnal Profiles and RT Methodology Solar, viewing and azimuth angles calculated for a geostationary satellite viewing (40 N, 95 W) Spectral regions: 1.6 μm, 2 μm, 15 μm Near IR: multiple scattering and thermal emission accounted for; VLIDORT used Thermal IR: scattering neglected; IDL-ELANOR used Aerosols and clouds not considered Surface albedo of 0.2 used in the near IR; thermal IR emissivities taken from ASTER spectral library Detection of PBL Variability Figure 4: Comparison of boundary layer CO 2 retrievals using near IR only and using both near IR and thermal IR CO 2 Profile Retrievals Figure 5: Comparison of CO 2 profile retrievals using near IR only and using both near IR and thermal IR Figure 2: Sources and Sinks of CO 2 (from Stephens et al., 2007) Figure 3: Simulated summertime profiles for CO 2 (Courtesy: R. Kawa) Related Presentation Sander et al., Improving Carbon Flux Estimates with Diurnal Profiling of Greenhouse Gases from Geostationary Orbit


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