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CO 2 Diurnal Profiling Using Simulated Multispectral Geostationary Measurements

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

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CO 2 Diurnal Profiling Using Simulated Multispectral Geostationary Measurements

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  1. CO2 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 • CO2 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 CO2 Profile Retrievals Introduction • CO2 diurnal cycle depends on surface sources, biospheric uptake and vertical mixing • In the daytime, photosynthesis removes CO2 and planetary boundary layer is efficiently mixed => low CO2 concentration near surface • At night, respiration produces CO2 and mixing is negligible => high CO2 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 CO2 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 CO2 concentration during an entire day (from Pino et al., 2010) Figure 3: Simulated summertime profiles for CO2 (Courtesy: R. Kawa) Figure 5: Comparison of CO2 profile retrievals using near IR only and using both near IR and thermal IR • Conclusions • There are large errors in CO2 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) Detection of PBL Variability References [1] D. Pino, et al., 19th 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. Figure 2: Sources and Sinks of CO2 (from Stephens et al., 2007) Related Presentation Sander et al., Improving Carbon Flux Estimates with Diurnal Profiling of Greenhouse Gases from Geostationary Orbit Figure 4: Comparison of boundary layer CO2 retrievals using near IR only and using both near IR and thermal IR

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