The comparison of CO 2 from TCCON profile retrievals and aircraft overpass data

1. Inter-comparison of retrieved CO2 from TCCON, combining TCCON and TES to the overpass flight data Le Kuai1, John Worden1, Susan Kulawik1, Edward Olsen1, Debra Wunch3, Run-Lie Shia3, Brian Connor2, Charles Miller1, and Yuk Yung3 Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Mail stop: 233-200, Pasadena, CA 91109 BC Consulting Ltd., 6 Fairway Dr, Alexandra 9320, New Zealand California Institute of Technology, 1200 E. California Blvd., Pasadena, CA, 91125 CALIFORNIA INSTITUTE OF TECHNOLOGY Abstract: The Total Carbon Column Observing Network (TCCON) provides measurements of column abundances of CO2, CO, CH4 and other molecules that absorb in the near infrared with high accuracy and high precision (e.g.< 0.25% for CO2). Therefore, this dataset serves as a link between satellite measurements and ground-based in situ network. In this study, a retrieval algorithm is developed to retrieve the CO2 profiles in addition to the column-averaged dry-air mole fractions (DMF) (XCO2). The inter-comparison between the TCCON retrieved CO2 products and flight measurements are focus at Lamont as well as Parkfallsin this work. The retrieved profiles capture the first order vertical variability in the overpass aircraft measured profile at both sites. TCCON XCO2 have about 1% negative bias to the integrated aircraft data with TCCON averaging kernel applied. The root-mean-square (RMS) of the current retrieved XCO2is about 0.12%. The boundary layer partial column-averaged CO2can be determined by subtract the column amount within and above free troposphere (e.g. above 600 hPa) by TES Geos-chem assimilated data from the total column amount by TCCON profile retrievals. These boundary layer CO2 estimation also shows a good agreement with the integration of flight profile within the boundary layer (e.g. below 600 hPa). This method to disentangle the boundary layer CO2can be applied to combine any total column measurement (e.g. TCCON or GOSAT) with any free tropospheric CO2 data (e.g. TES or AIRS). With a long term boundary layer CO2, the CO2 surface flux can be better estimated. 2. Total column-averaged DMF comparison To determine dry XCO2, the normal way is to remove amount of water from the total amount of air. Our retrieval simultaneously retrieves H2O by shift its a priori profile. The derived dry XCO2 using retrieved H2O profile has small bias but low precision. Since O2 can also be retrieved, the method by normalizing the retrieved O2 not only provides dry XCO2 but also improves the precision. It is noticed that about 1% negative bias is induced because the limited knowledge of the spectroscopy in O2 band. Figure 3. With O2 Correction Without O2 Correction: The comparison of CO2 from TCCON profile retrievals and aircraft overpass data Profile retrieval set up The CO2 profile is retrieved at 10 levels. Other interference gas, such as H2O, HDO and CH4 are simultaneously retrieved by shift their a priori profiles to minimize the residual of the observed and model calculated spectra. The signal to noise ratio used in retrieval is 200 for the covariance for measurement random noise. 3. Determine boundary layer partial column by combining TCCON and TES data Comparison of dry mole fraction (DMF) profile: fCO2(z) Comparison of total column-averaged DMF: XCO2 Comparison of partial column-averaged DMF in boundary layer: pXCO2BDL(combining TCCON and TES) Figure 5. Time window selection : Short enough to measure a same air parcel by flight and TCCON. Long enough for sufficient number of profiles from TCCON for a good statistical treatment. Figure 1. Figure 4. Covariance for CO2 Covariance for temperature Aircraft measured dry profile TCCON retrieved wet profile Overpass time windows: 800 hPa 600 hPa Lamont: Lat=36°, Lon=-97° Parkfalls: Lat=46°, Lon=-90° Table 1. Pcuf-off Combining TCCON and TES assimilated data, the boundary layer partial column CO2 is determined by subtract the partial column amount within and above free troposphere from the total column amount by TCCON. The remained partial column amount in boundary layer is weighted by the partial column amount of dry air in the boundary layer for . The comparison of to those by integral the flight profile within boundary layer shows small bias and high precision. The knowledge of boundary layer CO2 was greatly improved by combining TCCON and TES assimilated CO2 data compared to the climatology a priori. Table 2. • 1. Profile comparison: Applying the averaging kernel and a priori constraint vector to the aircraft data (Flt) ( which is on TCCON grid) yields Flt_AK, a profile which accounts for the TCCON sensitivity and vertical resolution. Flt_AKalso represents the profile that would be retrieved from TCCON measurements in the absence of other errors. The comparison should performed between the TCCON profile (Ret) and aircraft data have had the TCCON operator applied (Flt_AK). These profile comparisons give a good overview of the variability and bias in TCCON profile. This table lists the bias of the mean retrieved XCO2 in each of sixteen time windows relative to the flight data. The true variability of the retrievals during most time window is consist with the expected measurement error. It suggests that the instrument random noise account for the variability of retrievals within the time window scale. Some of days have unusual large variability because of the cloud coverage (e.g. 2009/03/04, 2009/08/22, etc.). The standard deviation of these bias is 0.46 ppm. The expected systematic error due to the temperature covariance matrix show in fig 1 is about 0.6 ppm. It suggests that the variability of the bias is mostly due to the systematic error such as temperature uncertainties. Inter-comparison of TCCON combining TES to SGP flight measurements Error analysis Table 4. TES SGP FLT • Apply averaging kernel • FLT_AK: Figure 6. Parkfalls: Figure 2. There are more flight measurements at Lamont in 2009 but these CO2 profiles only go up to 5 to 6 Km. However, it still allow us to compare the boundary layer CO2 from combining TCCON and TES to the flight data. For the comparison of total column, a priori CO2 is replace above the ceiling of the flight measurements. Here are sixteen days’ comparison in 2009 from January to December when flight measurements are available. The bias and precision of XCO2 are both consist with previous results. The bias in boundary layer CO2 stay small but root mean square (RMS) is increased due to two outliers. These two outliers are because flight boundary layer CO2 are outside the a priori constrain region. • Convert to dry profile • A priori: • Retrieved: 2004/07/12 2004/07/15 2004/08/02 2008/05/12 Table 3. Lamont: Conclusions: The profile retrieval of TCCON measurement can capital most of the CO2 vertical variability in the atmosphere. It integrated column-averaged CO2 abundance has 1.24% negative bias to flight integrated column-averaged abundance. The precision is 0.12%. By subtract free tropospheric partial column amount from TES-GEOS assimilated data from the total column amount from TCCON data, the partial column-averaged abundance in boundary layer can be estimated. The comparison to the integral of flight measurements at SGP in the boundary layer has small bias and 1.46 ppm for RMS. It improves the RMS for the XCO2 of the a priori to the flight column CO2. There are about 50 similar SGP flight CO2 profile near Lamont in 2009 in total. More points will be added to the future similar analysis to provide more robust conclusion. More total column and partial column in boundary layer data will be provided at other TCCON sites with different latitudinal and longer temporal coverage. They will allow us to study the spatial and temporal variability of both column and boundary layer CO2. Furthermore, the boundary layer CO2 could help constrain and improve the estimation of the surface flux. 2009/01/30 2009/07/31 2009/08/02 2009/08/03 2010/07/18