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Jennifer Wei1,2, Antonia Gambacorta1,2,
Eric Maddy1,2, Xiaozhen Xiong1,2, Fengyin Sun1,2,
Xingpin Liu1,2, Murty Divakarla2,3…..
Chris Barnet2, Mitch Goldberg2
START08/pre-HIPPO Workshop
Jan. 09, 2008
AIRS/IASI Trace Gas Products (Level 2)
1Perot Systems Government Services2NOAA/NESDIS/STAR 3IMSG
Trace Gas Product Potential from Operational Thermal Sounders
Haskins, R.D. and L.D. Kaplan 1993
Gas Range (cm-1) Precision d.o.f. Interfering Gases AIRS IASI
H2O 1200-1600 15% 4-6 CH4, HNO3 NASA DAAC Apr 2008
O3 1025-1050 10% 1.25 H2O,emissivity NASA DAAC Apr 2008
CO 2080-2200 15% 1 H2O,N2O NASA DAAC Apr 2008
CH4 1250-1370 1.5% 1 H2O,HNO3,N2O NASA DAAC Apr 2008
CO2680-795
2375-23950.5% 1 H2O,O3
T(p)NOAA NESDIS Apr 2008
Volcanic SO2 1340-1380 50% ?? < 1 H2O,HNO3 TBD TBD
HNO3860-920
1320-133050% ?? < 1 emissivity
H2O,CH4,N2ONOAA NESDIS Apr 2008
N2O 1250-13152180-22502520-2600
5% ?? < 1 H2OH2O,CO
NOAA NESDIS Apr 2008
CFCl3 (F11) 830-860 20% - emissivity No plans No plans
CF2Cl (F12) 900-940 20% - emissivity No plans No plans
CCl4 790-805 50% - emissivity No plans No plans
Example of Ozone from AIRS
What has been learned so far…..•High degree of consistency with dynamical
variability of UTLS•Realistically map chemical transitions between
stratosphere and troposphere•Show reasonable agreement with aircraft data over a
large dynamical range of ozone•Comparisons with ozonesonde show good
agreement between 400-50 mb rangeBian J., A. Gettelman, H. Chen, L. L. Pan (2007), Validation of satellite ozone profile retrievals using Beijing ozonesonde data, J. Geophys. Res., 112, D06305, doi:10.1029/2006JD007502.
Monahan K. P., L. L. Pan, A. J. McDonald, G. E. Bodeker, J. Wei, S. E. George, C. D. Barnet, E. Maddy (2007), Validation of AIRS v4 ozone profiles in the UTLS using ozonesondes from Lauder, NZ and Boulder, USA, J. Geophys. Res., 112, D17304, doi:10.1029/2006JD008181.
Divakarla et al. (2008), JGR-A, submitted.
X
Ozone A priori for Version 6 retrieval
Consideration of a tropopause referenced climatology
Altitude
Tropopause referencedRelative Alt.
Pan et al, 2004
Example of Carbon Monoxide from AIRS
What has been learned so far….•CO can be used to estimate horizontal and vertical transport during combustion events.
•CO can be used to help us distinguish combustion sources (fossil or biomass) from other sources/sinks in our methane and carbon dioxide products.
•CO and Ozone may help us improve atmospheric vertical transport models in the mid-troposphere.
Warner, J., M. M. Comer, C. D. Barnet, W. W. McMillan, W. Wolf, E. Maddy, and G. Sachse (2007), A comparison of satellite tropospheric carbon monoxide measurements from AIRS and MOPITT during INTEX-A, J. Geophys. Res., 112, D12S17, doi:10.1029/2006JD007925.
500 mb700 mb850 mb
UMBC Courtesy of W. McMillan ([email protected])
AIRS CO and Trajectories
CO from northern Alaskan fires was transported to the lower atmosphere in SE of US
CO from southern Alaska Fires was transported to Europe at high altitudes (5 km)
Example of Methane from AIRS([email protected])
What has been learned so far…•The accuracy is about 0.5-1.5% depending on different altitudes, and sensitive region is at 200-300mb in the tropics and 300-500 mb in the high northern hemisphere (HNH).
•Observed significant summer enhancement of CH4 in HNH (possibly due to wetland emissions/thawing permafrost, paper submitted to GRL by Xiong et al.)
•Observed significant plume of CH4 over the Tibetan Plateau (collaborate with S. Houweling, paper in preparation)
•Use AIRS CH4 in conjunction with model simulations to better quantify the source region
Comparison of CH4 product &
ESRL/GMD Continuous Ground Site
Barrow Alaska
3deg. x 3deg. gridded retrieval averaged over 60-70 lat, & -165 to -90 long.
AIRS CH4 comparison to ESRL Aircraft
Xiong, X., C. Barnet, C. Sweeney, E. S. Maddy, X. Liu, L. Zhou, and M. D. Goldberg (2008), Characterization and Validation of Methane Products from the Atmospheric Infrared Sounder (AIRS), J. Geophys. Res., doi:10.1029/2007JG000500, in press.
CH4 plume over Tibetan Plateau
Paper is in preparation
AIRS CH4 at 300 mb
Courtesy of L. Pan
Xiong et al., Satellite Observed Increase of Tropospheric Summer Methane Concentration: Is it due to Wetland Emission over the High Northern Hemisphere?, GRL, 2008 (submitted)
Example of Carbon Dioxide from AIRS([email protected])
What has been learned so far….•Maximum measurement sensitivity from AIRS in the middle to upper troposphere – broadly weighted column measurement. • Retrievals require significant spatial and temporal averaging (~5 day / 400 km) to improve S/N. •Total uncertainty in middle-to-upper troposphere:
• 1 ppmv in tropics vs. high altitude aircraft (JAL Matsueda) • 2 ppmv in middle/high latitudes vs. ESRL/GMD aircraft.
CO2 Retrievals from the Atmospheric Infrared Sounder: Methodology and Validation, Maddy, E. S. and Barnet, C. D. and Goldberg, M. D. and Sweeney, C. and Liu, X., Accepted to JGR-A
Validation: AIRS CO2 (6km – 8km) vs ESRL/GMD Aircraft (2.5km – 8km)
• Right: Taylor diagram [Taylor, JGR, 2001] for 2005 aircraft matchups illustrates retrieval skill (end of arrow) relative to a priori (beginning of arrow).
• Left: AIRS retrieval and ESRL aircraft timeseries at Poker Flat, Alaska shows good agreement in placement of seasonal cycle and year-to-year variability.
ESRL/GMD Aircraft vs. AIRS Retrieval CO2
NOAA AIRS CO2 Product is Still in Development
• Product is CO2(p) profile with associated averaging kernels.• Measuring a product to 0.5% is inherently difficult
– Cloud clearing error (also error estimates) strongly impacts the CO2 product.– Errors in moisture of ±10% is equivalent to ±0.7 ppmv errors in CO2.– Errors in surface pressure of ±5 mb induce ±1.8 ppmv errors in CO2.– AMSU side-lobe errors corrupt the ability to use the 57 GHZ O2 band as a
T(p) reference point.
Reduction of Core product retrieval errors is critical for CO2.• Currently, we can characterize seasonal and latitudinal mid-
tropospheric variability to test product reasonableness.• The real questions is whether thermal sounders can contribute to the
source/sink questions.– Requires accurate vertical & horizontal transport models – Having simultaneous O3, CO, CH4, and CO2 products is a unique contribution
that thermal sounders can make to improve the understanding of transport.
IASI & AIRS Global Measurements 4 Times/Day
AQUAMETOP
• Initial Joint Polar System: an agreement between NOAA & EUMETSAT to exchange data and products.– NASA/Aqua in 1:30 pm orbit (May 2002)– EUMETSAT/IASI in 9:30 am orbit (October 2006)
The NOAA Unique Level 2 Processing System
• The NOAA level 2 processing is a unique system to compute atmospheric core and trace gas products.
• The whole architecture is a file-driven system compatible with multiple instruments.
• This system has been developed during the Aqua mission, using AIRS/AMSU/MODIS Instruments.
• Although the system was built for AIRS, it was designed to be expandable for both IASI and CrIS.
• This system has been thoroughly validated using several in-situ measurement campaigns (e.g., ESRL/GMD Aircraft, JAL, INTEX, etc.)
• This system is a reliable, well tested and fast package that we are migrating into operations for IASI.
IASI & AIRS Carbon Monoxide ( October 22nd 2007)
1 2
3 4
Spectral Coverage Comparison: AIRS, IASI, & CrIS
CO2 CO2O3 COCH4
AIRS, 2378 chs
CrIS, 1305 chs
IASI, 8461 chs
2400/
Preliminary selection of IASI channels for physical retrieval.
(NOTE: All channels except non-LTE are used in regression)
Ignored – non- LTE
CC 69
T 152
Q 87
O3 53
CO 33
CH4 59
CO2 79
HNO314
N2O 58
Instrument Noise, NEΔT at 250 K
CO2CO2CH4 CO
RMS Simulation Inter-Comparison
Preliminary validation results:Temperature, water vapor, ozone
(focus day October 19th, 2007)
Selected IASI Nighttime Ascending Granules
Near AIRS Nighttime Descending Granules (~4 hour difference)
Standard deviation of retrievals-ECMWF
IASI (blue), IASI CLEAR (red) AIRS (cyan), AIRS CLEAR (green)
Standard Deviation
w.r.t. ECMWF
Dashed lines are NOAA
Cloudy Regression and Solid lines are Physical Retrieval
Using Physical QA
Temperature, T(p) Water, q(p) Ozone, O3(p)
Bias of retrievals – ECMWFIASI (blue), IASI CLEAR (red) AIRS (cyan), AIRS CLEAR
(green)
BIAS w.r.t.
ECMWF
Dashed lines are NOAA Cloudy Regression and Solid lines are Physical Retrieval
Using Physical QA
Towards Operational Status (April 08)
• Have not installed the regression derived from cloud cleared radiances. Will be installed in Jan. 2008.
• Have not computed tuning for AMSU & MHS (used Aqua AMSU tuning). Will be installed in Jan. 2008.
• Have not installed the local angle correction (needed for cloud clearing). Will be installed Jan. 2008.
• No attempt has been made to perform sub-pixel ILS correction.– There is an advantage to cloud clearing in that FOV’s are averaged with
clearest having highest weight.– This will be studied and installed in version 2.
• Only quick optimization has been done.– Need to derive optimal functions & regularization parameters, Jan/Feb. 2008.– Preliminary list of channels looks good, minor changes to channel list.
• Pre-launch Radiative Transfer Algorithm (RTA). Post-launch RTA from UMBC, expected any time soon
• Empirical bias corrections, empirical noise term (to compensate for sub-pixel ILS), etc. are still very crude.
Our interest in participating to the START 08/pre-HIPPO
campaign:
• Compare with in situ co-located trace gas measurements to validate and assess the performance of IASI L2 products
• Exchange data and products
