Transcript Slide 1

AIRS/IASI Trace Gas Products
(Level 2)
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
1Perot
Systems Government Services
2NOAA/NESDIS/STAR
3IMSG
Trace Gas Product Potential from
Operational Thermal Sounders
Gas
Range (cm-1)
Precision
d.o.f.
Interfering Gases
AIRS
IASI
H2 O
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
CO2
680-795
2375-2395
0.5%
1
H2O,O3
T(p)
NOAA NESDIS
Apr 2008
Volcanic SO2
1340-1380
50% ??
<1
H2O,HNO3
TBD
TBD
HNO3
860-920
1320-1330
50% ??
<1
emissivity
H2O,CH4,N2O
NOAA NESDIS
Apr 2008
N2O
1250-1315
2180-2250
2520-2600
5% ??
<1
H2O
H2O,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
Haskins, R.D. and L.D. Kaplan 1993
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 range
Bian 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
referenced
Relative 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.
AIRS CO and Trajectories
500 mb
700 mb
850 mb
CO from northern Alaskan fires
was transported to the lower
atmosphere in SE of US
UMBC
CO from southern Alaska
Fires was transported to
Europe at high altitudes (5
km)
Courtesy of W. McMillan ([email protected])
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
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)
AIRS CH4 at 300 mb
Courtesy of L. Pan
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 midtropospheric 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
AQUA
•
METOP
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
   / 2400
AIRS, 2378 chs
IASI, 8461 chs
CrIS, 1305 chs
CO2
O3
CH4
CO CO2
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
HNO3
14
N2O
58
Instrument Noise, NEΔT at 250 K
CO2
CH4
CO2
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)
Temperature, T(p)
Water, q(p)
Ozone, O3(p)
Standard
Deviation
w.r.t.
ECMWF
Dashed lines
are NOAA
Cloudy
Regression
and Solid
lines are
Physical
Retrieval
Using
Physical QA
Bias of retrievals – ECMWF
IASI (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
[email protected]
[email protected]