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Kevin W. Bowman 1,2 ,

Observing System Simulation Experiments (OSSE) in support of GEO-CAPE science and measurement requirements definition . Kevin W. Bowman 1,2 , Paul Hamer 1 , Stanley Sander 1,2 , Annmarie Eldering 1,2 , Reinhard Beer 1 1 Jet Propulsion Laboratory California Institute of Technology

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Kevin W. Bowman 1,2 ,

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  1. Observing System Simulation Experiments (OSSE) in support of GEO-CAPE science and measurement requirements definition Kevin W. Bowman1,2, Paul Hamer1, Stanley Sander1,2, Annmarie Eldering1,2, Reinhard Beer1 1Jet Propulsion Laboratory California Institute of Technology 2Joint Institute for Regional Earth System Science and Engineering University of California, Los Angeles

  2. The EOS era • The Earth Observing System (EOS) for which the A-train is the flagship constellation, has provided unprecedented knowledge of atmospheric composition • The A-train will no longer exist in its present form within 5-10 years. What’s next?

  3. NRC Decadal Survey National Research Council (NRC) has presented a road map for the next generation of Earth remote sensing instruments for NASA

  4. GEO-CAPE GEO-CAPE is a geostationary sounder over North America. It’s scientific objectives are: improving air quality forecasts through chemical data assimilation; monitoring pollutant emissions and accidental releases, and understanding pollution transport on regional to intercontinental scales. What kind of instrumentation can build on the A-train experience and satisfy these science requirements?

  5. Panspectral Fourier Transform Spectrometer (PanFTS) PanFTS will combine the Functionality of several Instruments e.g. TES, GOSAT, Sciamachy Wide spectral coverage (0.27 – 15 mm) permits simultaneous observations By reflected sunlight and Thermal emission (day/night) Pollutants O3, CO, NO2, HCHO, NH3 Greenhouse Gases CO2, CH4, N2O, O3, H2O Tracers HDO, N2O, O2, O4 Ocean Color 250 m pixel size: visible channel From NASA IIP Panspectral FTS, Stanley Sander, PI

  6. PanFTS Observing Scenario 900 km x 900 km ground swath patch 128x128 FPA Spectra in pixel • Geostationary orbit near 80 W longitude • Sequential imaging of 49 patches • 900 km x 900 km IFOV using 128x128 pixel array (7 km resolution)

  7. Impact of UV-Vis-IR on assimilated ozone Does combining UV-Vis-IR radiance measurements improve air quality predictions over IR-only? Ozone pseudo-observations of a virtual GEO-CAPE instrument are assimilated into a model. The top panel panel uses a virtual instrument that measures infrared (IR) radiances to infer ozone concentrations. The bottom panel uses a virtual instrument that measures both infrared along with ultraviolet and visible radiation (UV-Vis-IR). The UV-Vis-IR changes the ozone prediction by up to a factor of 2 compared to the IR-only case. A pan-spectral UV-Vis-IR Fourier Transform Spectrometer is currently support for GEO-CAPE by a NASA IIP- Stan Sander PI

  8. Sensitivity Analysis: August 1st, 2006, sensitivity of NY ozone at 2:30 pm to its precursors region of maximum sensitivity of boundary layer ozone in New York to free tropospheric NOx target region The sensitivity of ozone in NY to free troposphericNOx on 7/29/06 over Nebraska roughly half of the sensitivity to local NOx on 08/01/06

  9. How sensitive is ozone to local NOx? Strong diurnal variation Boundary layer ozone is sensitive to local NOx up to 3 days before Highest sensitivity to morning NOx

  10. Does knowing free tropospheric ozone improve boundary layer ozone prediction? The maximum sensitivity of ozone in NY to free tropospheric ozone is roughly .2 two days before.

  11. Does knowing ozone today improveozone predictability for the following day? The sensitivity of ozone to ozone on 07/31/08 is about half of ozone on 08/01/08

  12. BACKUP

  13. Air quality predictions with satellites in GEO vs LEO OSSE configuration: A “nature” model ozone fields are sampled with both a low-orbit and geo-stationary orbit virtual platforms to create pseudo- observations. These pseudo-observations are assimilated into a “standard” model to pull its ozone fields to the nature model. Surface ozone from assimilation of IR satellite in LEO is shown in top panel Surface ozone from assimilation of IR satellite in GEO is shown in bottom panel Air quality predictions with satellites in GEO have clear advantages over satellites in LEO

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