CO 2 Diurnal Profiling Using Simulated Multispectral Geostationary Measurements

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