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Validation of TES Methane with HIPPO Observations

Validation of TES Methane with HIPPO Observations. For Use in Adjoint Inverse Modeling. Kevin J. Wecht. TES Science Team Meeting. 17 June 2010. Special thanks to: Annmarie Eldering Daniel Jacob Steve Wofsy Susan Kulawik Lin Zhang Eric Kort

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Validation of TES Methane with HIPPO Observations

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  1. Validation of TES Methane with HIPPO Observations For Use in Adjoint Inverse Modeling Kevin J. Wecht TES Science Team Meeting 17 June 2010 Special thanks to: AnnmarieEldering Daniel Jacob Steve Wofsy Susan Kulawik Lin Zhang Eric Kort Greg Osterman Christopher Pickett-Heaps Vivienne Payne

  2. TES Methane (Worden, Kulawik) HIPPO Methane (Wofsy, Kort) Validation Adjoint Inverse Modeling of Methane Sources GEOS-Chem CTM Apriori Sources • HIPPO Methane provides: • Large number of profiles • Wide latitudinal coverage • Remote from sources • (reduces collocation error) GEOS-ChemAdjoint Adjoint inverse analysis EDGAR v4, Kaplan, GFED 2, Yevich and Logan [2003] OPTIMIZATION OF SOURCES

  3. HIPPO HIAPER Pole-to-Pole Observation Program HIPPO II HIPPO I October 22 - November 20, 2009 January 9-30, 2009 147 vertical profiles 138 vertical profiles • Five missions: • Jan, Nov 2009 • April 2010, June & Aug 2011 • > 700 vertical profiles by finish • 80% surface – 330 hPa • 20% surface – < 200 hPa • Methane Instrument Properties • Frequency: 1 Hz • Accuracy/Precision: 1.0/0.6 ppb Photos courtesy: S. Wofsy Flight path Flight path Vertical Profile Vertical Profile

  4. HIPPO w/ TES op. HIPPO 250-450 hPa HIPPO I Jan 9-30, 2009 TES HIPPO vs. TES by Latitude RTVMR [ppb] HIPPO II Oct 22 – Nov 20, 2009 RTVMR [ppb] TES observation operator is applied to all profiles unless explicitly stated. Positive bias and significant noise, but latitudinal gradient is captured.

  5. TES over ocean TES over land HIPPO I Jan 9-30, 2009 Mean Bias HIPPO vs. TES by Latitude RTVMR [ppb] HIPPO II Oct 22 – Nov 20, 2009 RTVMR [ppb] HIPPO I: bias = 73.6 ppb, residual error = 41.1 ppb n = 129 HIPPO II: bias = 61.0 ppb, residual error = 44.8 ppb n = 147

  6. Distribution of Residual Error • HIPPO I All Observations Histograms of HIPPO – TES difference mean = 73.6 σ = 41.1 n = 129 Mean and standard deviation in units [ppb] HIPPO II also shows Gaussian residual error. Ocean Observations Land Observations mean = 78.0 σ = 37.3 n = 90 mean = 63.7 σ = 47.8 n = 39 Errors are normally distributed, important for derivation of inversion cost function.

  7. TES self-reported instrument error is ???-??? % ≈ ???-??? ppb TES bias and residual error vs. size of coincidence window Mean Bias Residual Error # Observations 24 hour Collocation Error 120 12 hour HIPPO I 80 [ppb] 40 Observation error 0 120 80 HIPPO II [ppb] 40 0 125 250 375 500 Distance [km] Distance [km] Distance [km] Quantify observation, representation error. Error and bias differ for HIPPO I and II.

  8. TES and GEOS-Chem along HIPPO I flight track HIPPO w/ TES op. GEOS-Chemw/ TES op. HIPPO I Jan 9-30, 2009 Model Comparison TES RTVMR [ppb] TES and GEOS-Chem averaged over the Pacific during the HIPPO I period RTVMR [ppb] Consistency with HIPPO

  9. TES and GEOS-Chem along HIPPO II flight track HIPPO w/ TES op. GEOS-Chemw/ TES op. HIPPO II Oct 22 – Nov 20, 2009 Model Comparison TES RTVMR [ppb] TES and GEOS-Chem averaged over the Pacific during the HIPPO II period RTVMR [ppb] Consistency with HIPPO

  10. GEOS-Chem NOAA GMD [ppb] GEOS-Chem [ppb] Model Comparison – NOAA GMD2008 Annual Average NOAA GMD [ppb] [ppb] GEOS-Chem and GMD surface methane Latitude • GEOS-Chem provides good simulation in the annual average • Seasonality to inter-hem. gradient • Missing northern hemisphere sources? Natural gas production? [ppb] GEOS-Chem is a good platform inter-comparison of data sets such as TES methane.

  11. GEOS-Chem GEOS-Chemw/ TES op. TES RTVMR [ppb] Model Comparison – TES2009 Annual Average GEOS-Chemw/ TES operator RTVMR Difference [ppb] • TES captures variability in GEOS-Chem, with large residual error. • Interpretation of latitudinal profile complicated by latitudinal structure of DOFS • Model overestimate around equator.

  12. TES RTVMR w/ mean TES – GEOS-Chem difference subtracted GEOS-Chem GEOS-Chem RTVMR GEOS-Chemw/ TES op. TES Model Comparison TES a priori RTVMR Difference: GEOS-Chem – TES [ppb] Quantitative source attribution of differences requires inverse modeling. [ppb]

  13. TES Methane (Kulawik, Osterman) HIPPO Methane (Wofsy, Kort) Validation Adjoint Inverse Modeling of Methane Sources GEOS-Chem CTM Apriori Sources • 4D-Var assimilation of TES data: • Optimize emissions on • 2x2.5 horizontal grid • monthly temporal res. • Evaluate results with HIPPO, NOAA GMD • Incorporation of additional satellite products GEOS-ChemAdjoint Adjoint inverse analysis EDGAR v4, Kaplan, GFED 2, Yevich and Logan [2003] OPTIMIZATION OF SOURCES

  14. Thank You! • TES captures latitudinal gradient in HIPPO data • TES is biased high but residual instrument error is within self-reported range • 73.6 ± 41.1 ppb during HIPPO I • 61.0 ± 44.8 ppb during HIPPO II • Pending prognosis of TES instrument, will validate again with HIPPO IV & V • Enabling Inverse Modeling: • Time period: TES provides useful information through the end of HIPPO II. • Quantification of bias, observation error, and representation error. • Error normally distributed. • Robust latitudinal gradient with greater coverage than surface stations • HIPPO and NOAA GMD will be used to evaluate inversion results. • Future incorporation of additional satellite products.

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