Carbon dioxide from TES

Susan KulawikF. W. IrionDylan JonesRay NassarKevin BowmanThanks to Chip Miller, Mark Shephard, Vivienne Payne

S. Kulawik – February, 2009

S. Kulawik – February, 2009

Challenges• More accuracy is required than for any other TES species

– Year over year increase in CO2 ~2 ppm (0.5%) – Seasonal variability ~5-15 ppm in the Northern Hemisphere (1-3%)– Plumes at ground stations are ~20 ppm (4%)

• TATM and CO2 information is entangled– A +1K temperature error propagates into about +25 ppm CO2 error – CO2 retrieved by itself in the TES 2B1 filter has 2 DOF. When co-

retrieved with TATM, the CO2 DOF drops to 0.6.

• GMAO TATM is not adequate for TES CO2 retrievals– TATM errors propagate into CO2 unless TATM is retrieved

Strategy

• Retrieve using 670-725, 970-990, 1070-1120 cm-1 spectral regions

• Remove spectral areas showing poor fit, spikes, or spectroscopic issues

• Co-retrieve TATM, H2O, CO2, cloud parameters, and surface temperature

• Use a loose CO2 constraint, expecting averaging data

AIRS selected windows

S. Kulawik – February, 2009

Measurements

American Samoa

Macquarie Island

CONTRAILCONTRAIL

TES Mauna Loa

TES

• TES measurement box– 13-35N x 128-158E– 2006 - 2008– Peak information at 511 hPa– Ocean, low cloud OD

• CONTRAIL aircraft – 9-11 km, Northern & Southern

hemisphere. – Through 2006

• Mauna Loa – 19.5N, 155.6E, 3.4km– Through 2009

• American Samoa– 54.5S, 159E, surface site– Through 2008

S. Kulawik – February, 2009

TES Northern Hemisphere results

Individual targetsPredicted error 7.9 ppmStandard deviation 8.1 ppm

Monthly averages of ~200 targetsApprox 1 ppm errors compared to validation data5.6 ppm low bias, constant valueHighly correlated with Mauna Loa observatory 1.5 +- 0.5 ppm yearly increase – Mauna Loa 1.8 +- 0.2

ppm

Uniform CO2 prior

TES monthly aveTES monthly ave

CONTRAIL aircraft dataCONTRAIL aircraft data Mauna LoaMauna Loa

S. Kulawik – February, 2009

Southern hemisphere results

• Monthly averages of ~130 targets– Approx 2 ppm errors compared to validation data– 5 ppm low bias compared to American Samoa ground station– 1.7 +- 0.3 ppm yearly increase -- Samoa 1.9 +- 0.1 ppm

Uniform CO2 prior

CONTRAIL aircraft dataCONTRAIL aircraft dataSamoa ground stationSamoa ground station

S. Kulawik – February, 2009

TES monthly aveTES monthly ave

Observing System Simulation Experiment (OSSE) - Ray Nassar

TES• 20 x 30 degree x 1 month averages

– 0.3 – 1.1 DO0.5 – 2.0 ppm errors

GLOBALVIEW• 76 surface stations

MODEL• GEOS-Chem with NASA GMAO met . fields,

specialized CO2 source/sink inputs

FLUXES• 14 regions of combustion and terrestrial

exchange + “rest of world” (29 elements)• A priori flux uncertainty:

– 100% for terrestrial biosphere– 30% for combustion

S. Kulawik – February, 2009

OSSE - Ray Nassar -cont

A posteriori flux uncertainties:• TES: improves flux uncertainty from 100% to 15-

28% for biosphere fluxes• 76 surface stations: comparable to TES if 0.1

ppm errors assumed; worse performance if 1 ppm errors assumed

TES and surface station sensitivities are complementary and future work will explore combinations of TES, surface stations, OCO, and GOSAT

S. Kulawik – February, 2009

S. Kulawik – January, 2009

Spectral view

• Signal apparent in residual– Working with AER (Vivienne

Payne, Mark Shephard) to resolve and test spectroscopy improvements

– Also Javier Martin-Torres is going to compare radiances with FUTBOLIN forward model

Conclusions

• TES observes CO2

– Correct seasonal cycles and patterns for NH and SH ocean– Yearly increase seen– OSSE shows TES data will improve flux estimates

• Future plans– Validation– land, bias characterization, global comparisons

to AIRS, Carbontracker, spectroscopy updates

– Generate 3 months of TES CO2 for assimilation and flux estimates

S. Kulawik – February, 2009

Work at JPL was carried out under contract to NASA with funds from ROSES 2007. Work by Nassar et al. funded by Natural Sciences and Engineering Research Council (NSERC) of Canada. We acknowledge use of GLOBALVIEW-CO 2, Mauna Loa, and Samoa data from NOAA-ESRL and CONTRAIL data from World Data Centre for Greenhouse Gases (WDCGG).

References• Matsueda, H., H. Y. Inoue, and M. Ishii (2002), Aircraft observation of carbon dioxide at 8‑13 km altitude

over the western Pacific from 1993 to 1999. Tellus, 54B(1), 1‑ 21, doi: 10.1034/j. 1600‑0889.2002.00304.x

• U.S. Department of Commerce | National Oceanic and Atmospheric Administration Earth System Research Laboratory | Global Monitoring Division http://www.esrl.noaa.gov/gmd/dv/site/SMO.html

S. Kulawik – February, 2009

Future plans• Validation

– Global characterization of bias – Land targets (comparing to airplane flights, e.g. SGP)– Effects of strategy on TATM, other species– Comparisons to AIRS and CarbonTracker

• Science– 3 months of TES CO2 output for assimilation and inversion by Dylan

Jones’ group to estimate fluxes– CO2 data in Atlantic/Pacific near US for REAM model comparisons

(Y.Choi)– CO2/CO ratios for elevated CO regions

Work at JPL was carried out under contract to NASA with funds from ROSES 2007. Work by Nassar et al. funded by Natural Sciences and Engineering Research Council (NSERC) of Canada. We acknowledge use of GLOBALVIEW-CO2, Mauna Loa, and Samoa data from NOAA-ESRL and CONTRAIL data from World Data Centre for Greenhouse Gases (WDCGG).

S. Kulawik – February, 2009

S. Kulawik – January, 2009

TATM Effects

• Retrieve CO2 with TATM fixed at GMAO and selected windows– Signal too large– Peak too late

• Co-retrieved TES TATM vs GMAO shows seasonal fluctuations

S. Kulawik – January, 2009

Spectral view (cont)

• Idea from Mark Shephard– Compare radiance

change from dCO2 and dTATM

– Select radiances most influenced by dCO2 (red)

– Would mean a sequential retrieval