Operational atmospheric trace gas products from AIRS, IASI, CrIS

Operational atmospheric trace gas products from AIRS, IASI, CrIS
Chris Barnet NOAA/NESDIS/STAR (the office formally known as ORA) University of Maryland, Baltimore County (Adjunct Professor) AIRS Science Team Member NPOESS Sounder Operational Algorithm Team Member GOES-R Algorithm Working Group – Chair of Sounder Team NOAA/NESDIS representative to IGCO July 26, 2006 MSRI-NCAR Summer Workshop on Data Assimilation for the Carbon Cycle

Member’s of our Sounding Team who have contributed to the trace gas work.
Mitch Goldberg: AIRS & IASI Science Team, Climate Products Walter Wolf: Near Real Time Processing & Distribution to Users Lihang Zhou: Regression Retrieval & Near Real Time Web Page Eric Maddy: CO2 retrieval, “tuning”, vertical averaging functions. Xiaozhen Xiong: CH4 retrieval & analysis. Jennifer Wei: Ozone retrieval & trace gas correlations. Nick Nalli: In-Situ validation & aerosol corrections. Murty Divakarla: In-Situ Validation of core products. Fengying Sun: Convective, N2O, HNO3 products Xingpin Liu: Re-processing, Statistics, Product web-page Antonia Gambacorta (UMBC): UTH, OLR and climate indices. NOTE: Only a small fraction of our funding goes to support trace gas work. The majority supports the core products (temperature, moisture, and ozone).

Sounding Theory Notes for the discussion today is on-line
voice: (301) ftp site: ftp://ftp.orbit.nesdis.noaa.gov/pub/smcd/spb/cbarnet/ ..or.. ftp ftp.orbit.nesdis.noaa.gov, cd pub/smcd/spb/cbarnet Sounding NOTES, used in teaching UMBC PHYS-741: Remote Sounding ~/reference/rs_notes.pdf These are living notes, or maybe a scrapbook – it is not a textbook.

Topics for Today’s Lecture
Fossil Fuel Emissions – A personal way to look at it. Introduction to AIRS & IASI and our plans to use operational sounders to retrieve carbon products. Introduction to Sounding Methodology The forward model: Converting state vector to radiances. The inverse problem: Converting radiances to a state vector. Another application of variational analysis. Example of the AIRS CO Product. Example of the AIRS CH4 Product Example of the AIRS CO2 Product Inter-comparison of AIRS trace gas time series.

Topics for Tomorrow’s Lecture
Retrieval Vertical Weighting Functions. What are they. How are they used. Validation Techniques. Examples with T,q,O3. Comparisons of CO2 product with in-situ. Summary of some papers on using AIRS CO2 products in carbon assimilation systems. Trace gas product correlations – A better way to use AIRS data?

Why is increasing CO2 a concern?
1896 Svante Arrhenius computed a doubling of CO2 would make temperature rise 5-6 C – and it would take 3000 years Lifetime of CO2 in atmosphere is 100 years IPCC – doubling will likely occur by 2075 1957 Roger Revelle & Hans Suess wrote “Humans beings are now carrying out a large scale geophysical experiment of a kind that could not have happened in the past nor be reproduced in the future. Within a few centuries we are returning to the atmosphere and oceans the concentrated organic carbon stored in sedimentary rocks over hundreds of millions of years.” 2000 IPCC “that there has been a discernible human influence on global climate.” In 21st century predictions are: Temperature Rise: +2.5 to 10.4 F (+1.4 to 5.8 C) CO2 concentration: 540 to 970 ppm See Level Rise: (9-88 cm) sea level loss of 1000 miles of coastline in 21st century Polar ice cap will melt by (more recent estimate is 2050) US and Canada are in dispute as to whether future open waters in Arctic are owned by Canada or are international waters

Comparison with 1000 year ice core record of CO2 from Law Dome Antarctica
8/28/1859 Edwin Drake’s 1st oil well

How long will fossil fuels last?
“We produce people faster than oil” Kenneth S. Deffeyes in Beyond Oil: The view from Hubbert's Peak, 2005 But there is plenty of coal, tar sands, and shale ….

Average of 1 tonne of C emitted to the atmosphere per person per year
Andres & Marland, Fung, Matthews, 1999, GBC, v.10

Maybe it’s easier to think in terms of Jeeps of Carbon put into atmosphere

Or we can Convert Carbon Emission into Charcoal Briquets
Idea by Gerry Stokes (UMCP) 5-lb bag has ≈ 100 briquets Each briquet is ≈ 0.05 lb of carbon

84% of modern energy comes from fossil fuels (oil, coal, gas)
Energy Source Basic Conversion Facts Per-unit amount of C release to atmosphere Driving a 25 m/g Car million US drivers <14,500 m/driver> 5 lbs-C/gal (C8H18) 0.2 lbs-C/mile 4 briq/mile, 220 briq/hour/car 58,000 briq/year/driver 11 trillion briq/year in US Boeing 158 seats 12 lbs-C/mile 1.55 briq/mile 133,852 briq/hour or 847 briq/person/hour (full) DC-10 267 seats 30 lbs-C/mile 2.25 briq/mile 325,000 briq/hour or 1225 briq/person/hour (full) Electricity (PEPCO statement) 1200 lbs of CO2/MWh 3.67 CO2/C 0.32 lbs-C/kWh 6.54 briq/kWh Paper 3.2 kWh/pound, new 1.2 kWh/pound, recycled 20.95 briq/pound, new paper 7.5 briq/pound, recycled Aluminum Electroyte Process 1998: 38 billion pounds produced worldwide 7.5 kWh/pound, 100 billion Al-cans/yr used in US, 34 Al-cans/pound 1.5 briq/can 75 billion briq/yr in US (150 w/o recycling) Kerosene use in 1908 was for lamps

Clothes Washer (water+washer)
As you use Energy, think Briquets (that last in atmosphere for 100 years) Winter Heating (1200 cu ft home) 400 briq/day 60 W light 1 briq/hr 9000 BTU Window AC 70 briq/day TV or Computer 1.5 briq/hr 24,000 BTU central AC 190 briq/day Ceiling Fan 1 briq/day Clothes Washer (water+washer) 20 briq/load 17 cu ft Refrigerator 33 briq/day Clothes Dryer 10 briq/load Water Heater (w/o washer) 65 briq/day

Even dietary choices make a difference
In 2002 food production accounted for 17% of all fossil fuel use. Farm Equipment Ships & Trucking Eating a diet with 49% red meat adds 3.57 ton of CO2 into the atmosphere (versus a vegetarian diet) – equivalent to driving a SUV. From Eshel & Martin, BAMS May, 2006

And the demand continues to rise ….
Residential use of air conditioners in the USA has almost doubled in last 20 years

And with 6 billion people, and counting, it adds up …
80 million barrels of oil consumed per day, worldwide 47% gasoline 28% diesel fuel 10% jet fuel 12% asphalt, plastics DVD’s,CD’s) 3% petrochemical feedstocks  200 lbs-C per barrel of oil 16 billion lbs-C/day 5.8 trillion lbs-C/year 2.65 billion tonnes-C/year from oil Total Fossil Fuel Consumption is 5.75 billion tonnes-C per year 46% f/ oil 27% f/ coal 27% f/ Natural Gas

Acronyms Infrared Instruments Microwave Instruments
AIRS = Atmospheric Infrared Sounder IASI = Infrared Atmospheric Sounding Interferometer CrIS = Cross-track Infrared Sounder HES = Hyperspectral Environmental Suite Microwave Instruments AMSU = Advanced Microwave Sounding Unit HSB = Humidity Sounder Brazil MHS = Microwave Humidity Sensor ATMS = Advanced Technology Microwave Sounder AMSR = Advanced Microwave Scanning Radiometer Imaging Instruments MODIS = MODerate resolution Imaging Spectroradiometer AVHRR = Advanced Very High Resolution Radiometer VIIRS = Visible/IR Imaging Radiometer Suite ABI = Advanced Baseline Imager Other CALIPSO = Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations EUMETSAT = EUropean organization for exploitation of METeorological SATellites GOES = Geostationary Environmental Operational Satellite IGCO = International Global Carbon Observation (theme within IGOS) IGOS = Integrated Global Observing System METOP = METeorological Observing Platform NESDIS = National Environmental Satellite, Data, and Information Service NPOESS = National Polar-orbiting Operational Environmental Satellite System NDE = NPOESS Data Exploitation NPP = NPOESS Preparatory Project OCO = Orbiting Carbon Observatory STAR = office of SaTellite Applications and Research

NOAA/NESDIS 20 year Strategy Using Existing Operational Sounders.
Now: Develop and core & test trace gas algorithms using the Aqua (May 4, 2002) AIRS/AMSU/MODIS Instruments Compare products to in-situ (e.g., ESRL/GMD Aircraft, JAL, INTEX, etc.) to characterize error characteristics. The A-train complement of instruments (e.g., MODIS, AMSR, CALIPSO) can be used to study effects of clouds, surface emissivity, etc. 2006: Migrate the AIRS/AMSU/MODIS algorithm into operations with METOP (2006,2011,2016) IASI/AVHRR. Study the differences between instruments, e.g., effects of scene and clouds on IASI’s instrument line-shape. 2009: Migrate the AIRS/IASI algorithm into operations for NPP (2009?) & NPOESS (2012?,2015?) CrIS/ATMS/VIIRS. These are NOAA Unique Products within the NOAA NDE program. 2013: Migrate AIRS/IASI/CrIS algorithm into GOES-R HES/ABI

AIRS Was Launched on the EOS Aqua Platform May 4, 2002
MODIS AMSU-A1(3-15) AMSU-A2(1-2) AIRS HSB Delta II 7920 Aqua Acquires 325 Gb of data per day

AIRS has a Unique Opportunity to Explore & Test New Algorithms for Future Operational Sounder Missions. Apr. 28, 2006 12/18/2004 5/4/2002 7/15/2004 ≥ 9/2008

IASI Launch Was Supposed to Be Launched Last Week – Delayed Until Sep.
July 5, 2006 July 14, 2006 METOP Satellite is 4085 kg, 6.3 x 2.5 x 2.5 meters. Onboard SOYUZ-ST at the Baikonur Space Centre in Kazakhstan Baikonur unavailable until Sep. July 14, 2006

In 2007 we will have IASI & AIRS making global measurements, 4/day
Initial Joint Polar System: An agreement between NOAA & EUMETSAT to exchange data and products. NASA/Aqua in 1:30 pm orbit EUMETSAT/IASI in 9:30 am orbit (July 2006) NPOESS/CrIS in 1:30 pm orbit (2009?)

Instruments measure radiance (energy/time/area/steradian/frequency-interval)
This is what we measure This is how I will show it. Convert to Brightness Temperature = Temperature that the Planck Function is equal to measured radiance at a given frequency.

Spectral Coverage of Thermal Sounders (Example BT’s for AIRS, IASI, & CrIS)
Channels IASI, 8401 Channels CrIS 1305 CO2 O3 CH4 CO CO2

Thermal Sounder “Core” Products (on 45 km footprint, unless indicated)
Radiance Products RMS Requirement Current Estimate AIRS IR Radiance (13.5 km) 3% < 0.2 % AIRS VIS/NIR Radiance 20% 10-15% AMSU Radiance K 1-2 K HSB Radiance (13.5 km) K (failed 2/2003) Geophysical Products Cloud Cleared IR Radiances 1.0K < 1 K Sea Surface Temperature 0.5 K 0.8 K Land Surface Temperature TBD Temperature Profile 1K/1-km layer 1K/1-km Moisture Profile 15%/2-km layer 15%/2-km Total Precipitable Water 5% Fractional Cloud Cover (13.5 km) Cloud Top Pressures 0.5 km Cloud Top Temperatures 1.0 K

Trace Gas Product Potential from Operational Thermal Sounders
Range (cm-1) Precision Interference UTH 15% T(p) O3 10% H2O,emissivity CO H2O,N2O CH4 20 ppb H2O,HNO3 CO2 2 ppm H2O,O3 SO2 1000% HNO3 40% 25% emissivity H2O,CH4 N2O H2O H2O,CO CFCl3 (F11) 20% CF2Cl (F12) CCl4 50% Product Available Now In Work CO resonance at 0.25 cm, needs FWHM<2.25 cm-1 to capture HNO3: -1.4 K/100% at 879, -1.17K/100% at N2O: -0.44H/5% at 1300, K/5% at CFCl3(F11): 0.08/10% at 847 CF2Cl(F12): 0.124/10% at 922 SO2: -0.2K/1000% at 1345,1371 cm-1 CCl4: K/10% at 795 Held Fixed Haskins, R.D. and L.D. Kaplan 1993

Radiance at the Satellite is Composed of Many Terms
Surface Radiance Up-welling Radiance Direct Solar radiance Down-welling Reflected Radiance Scattering (not shown) is composed of reflections of the Sun from particles within the atmosphere. Multiple scattering (not shown) is reflections between particles.

Thermal sounder forward model Example: upwelling radiance term
Absorption coefficients, , for a any spectrally active molecular species, i, (e.g., water, ozone, CO2, etc.) must be computed. Each channel samples a finite spectral region  is a strong function of pressure, temperature, and interaction with other species. Full radiative transfer equation includes surface, down-welling, and solar reflection terms. Inversion of this equation is highly non-linear and under-determined. Vertical temperature gradient is critical for thermal sounding.

All the physics is in the absorption coefficient
The absorption coefficient is a complicated and highly non-linear function Line Strengths, Sij, result from many molecular vibrational-rotational transitions.

The Solar (or Direct) term, without scattering, is given by
Source Function, H, is the Sun for AIRS & OCO (t) is the Earth’s orbital distance. Bi-directional transmittance contains all the atmospheric physics Surface reflectivity is a strong function of geometry and surface type.

Comparison of Satellite Methods
Passive-Thermal Passive-Solar Active Source Function Planck Function Sun LASER Measures Mid-trop column Total Column Total Column/Profile Clouds Correction via cloud clearing Clear or Solve for Microphysics Aerosols Minimal impact to mid-trop. Solve for aerosol microphysics Measure independently. Surface Issues Very little sensitivity Need reflectivity,  Interference Strong interaction with T(p), q(p) Weak interaction with T(p), q(p) Very weak interference Data availability 20+ years, launch almost guaranteed Research grade, 2-3 mission, no follow-on Future missions Main utility Improve transport Upper boundary for OCO. Reduce uncertainty of the carbon budget Carbon budget

AIRS Spectra from around the Globe
20-July-2002 Ascending LW_Window This shows the ascending data (day-time) for the current AIRS “focus day” of 20 July The image is of a longwave window channel brightness temperature (using a GOES colormap), along with various sample spectra. We’ve had global observations of high spectral resolution before (IRIS and IMG), but they were not really atmospheric profile sounders. The AIRS data is very clean, and the applications are numerous. This is what many of us have been waiting for, and working towards for many years. There are many un-tapped opportunities: SO2 detection from volcanoes, the blue-spike fire detection, new cloud detection techniques, low level inversion detection for severe weather, new spectroscopy investigations, climate change signatures, …

Retrieval is a minimization of cost function, optimized for the instrument
Covariance of observed minus computed radiances: includes instrument noise model and spectral spectroscopic sensitivity to components of X that are held constant (Physics a-priori spectral information). Covariance of product (e.g., CO, CH4, CO2) can be used to optimize minimization of this underdetermined problem. For trace gas retrievals we are using minimum variance approach (C = I) due to lack of knowledge of correlations. In the future we will replace this with a measured covariance. Derivative of the forward model is required to minimize J.

Iterative Solution to the Cost Function has many forms
Optimal estimation can “pivot” off of the a-priori state. Equivalent to “pivoting” from the previous iteration: The background term, modifies obs-calc’s to converge to a regularized solution. Form used in our algorithm:

This cost function minimizes observations minus computed radiances
Linear minimization of cost function is equivalent to expanding Obs-calc’s into a Taylor expansion In a linear operator, the different components of geophysical space can be separated.

The Problem is Physical and can be solved by Parts
Careful analysis of the physical spectrum will show that many components are physically separable (spectral derivatives are unique) Select channels within each step with large K and small en This makes solution more stable. And has significant implications for operational execution time.

Sounding Strategy in Cloudy Scenes: Co-located Thermal & Microwave (& Imager)
Sounding is performed on 50 km a field of regard (FOR). FOR is currently defined by the size of the microwave sounder footprint. IASI/AMSU has 4 IR FOV’s per FOR AIRS/AMSU & CrIS/ATMS have 9 IR FOV’s per FOR. ATMS is spatially over-sampled can emulate an AMSU FOV. AIRS, IASI, and CrIS all acquire 324,000 FOR’s per day

Spatial variability in scenes is used to correct radiance for clouds.
Assumptions Only variability in AIRS pixels is cloud amount Reject scenes with surface & moisture variability Within FOR (9 AIRS scenes) there is variability of cloud amount Reject scenes with uniform cloud amount Less than four cloud types per FOR We use the microwave radiances and 9 sets of cloudy infrared radiances to determine a set of 4 parameters to derive 1 set of cloud cleared infrared radiances. Roughly 70% of any given day satisfies these assumptions.

Retrieval of Atmospheric Trace Gases Requires Unprecedented Instrument Specifications
Need Large Spectral Coverage (multiple bands) & High Sampling (currently, we use 1680 AIRS and 14 AMSU channels in our algorithm) Increases the number of unique pieces of information Ability to remove cloud and aerosol effects. Allow simultaneous retrievals of T(p), q(p), O3(p). Need High Spectral Resolution & Spectral Purity Ability to isolate spectral features → vertical resolution Ability to minimize sensitivity to interference signals.. Need Excellent Instrument Noise & Instrument Stability Low NEΔT is required. Minimal systematic effects (scan angle polarization, day/night orbital effects, etc.)

Assimilation of Radiances versus Products: Pro’s and Con’s
Assimilate Radiance Assimilate CO2 Product Product volume is large: In practice, a spectral subset (10%) and spatial subset (5%) of the observations is made Product volume is small: all instrument channels can be used to minimize all parameters (T,q,O3,CO,CH4,CO2,clouds,etc.) Instrument error covariance is usually assumed to be diagonal, for apodized interferometers (e.g. IASI) this is not accurate. CO2 product error covariance has vertical, spatial, and temporal off-diagonal terms. Require fast forward model, and derivative of forward model. Most accurate forward model is used with a model of detailed instrument characteristics. Small biases in T(p), q(p), O3(p),due to representation error, have large impact on derived CO2. A-priori used in retrieval may be different than assimilation model. We used very simple a-priori to assess ret. skill. Tendency to weight the instrument radiances lower (due to representation error) to stabilize the model. Need correlation lengths to stabilize model horizontally, vertically, and temporally. Retrieval weights the radiances as high as possible, since determined state is on instrument sampling “grid.”

Example of Carbon Monoxide Products from AIRS in collaboration with
W. Wallace McMillin, Juying Warner & Michele McCourt University of Maryland, Baltimore County W. McMillan AIRS Science Team Meeting, Cal Tech, 3/8/06 UMBC

The CO (& O3) Product Improves Utility of the CH4 and CO2 Products
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 can be used to estimate horizontal and vertical transport during combustion events. CO (and Ozone) may help us improve atmospheric vertical transport models in the mid-troposphere. Inter-comparison w/ aircraft (e.g., ESRL/GMD, INTEX-A, INTEX-B), and MOPITT products is in-work. McMillan et al GRL v.32 doi: /2004GL0218 McCourt, PhD dissertation, UMBC, 2006

AIRS CO Kernel Functions are Sensitive to H2O(p), T(p) & CO(p).
Polar Mid-Latitude Tropical

Utilization of thermal product requires knowledge of vertical averaging
Thermal instruments measure mid-tropospheric column Peak of vertical weighting is a function of T profile and water profile and ozone profile. Age of air is on the order of weeks or months. Significant horizontal and vertical displacements of the trace gases from the sources and sinks. Solar/Passive instruments (e.g., SCIA, OCO) & laser approaches measure a total column average. Mixture of surface and near-surface atmospheric contribution Age of air varies vertically.

Sensitivity Analysis for CO retrieval
Knj

AIRS CO and Trajectories
July 2004 Fires in Alaska 500 mb 700 mb 850 mb UMBC W. McMillan AIRS Science Team Meeting, Cal Tech, 3/8/06

500 mb 700 mb 850 mb UMBC W. McMillan AIRS Science Team Meeting, Cal Tech, 3/8/06

500 mb 700 mb 850 mb CO from southern Alaska Fires was transported to Europe at high altitudes (5 km) CO from northern Alaskan fires was transported to the lower atmosphere in SE of US UMBC W. McMillan AIRS Science Team Meeting, Cal Tech, 3/8/06

Example of Methane Products from AIRS

Methane Sources Ref.: Lelieveld, 1998 & Houwelling 2002 (600 Tg total)
Note: Approximately 50% of sources are anthropogenic Trees (Keppler et al. 2005) may contribute Tg (10-35%), mostly in tropics

AIRS CH4 Channel Kernel Functions are Sensitive to H2O(p) & T(p)
Polar Mid-Latitude Tropical Isothermal vertical structure weakens sensitivity. moisture optical depth pushes peak sensitivity upwards.

Sensitivity Analysis for CH4 retrieval
Knj

Also providing the vertical information content to understand CH4 product
CH4 total column f/ transport model (Sander Houweling, SRON) AIRS mid-trop measurement column Peak Pressure of AIRS Sensitivity Fraction Determined from AIRS Radiances

Can we monitor Permafrost?
1 cubic meter of methane hydrate contains 164 cubic meters of CH4 more hydrate than all the world's oil, gas, and coal combined Methane presently contibutes .8 W/m2 to global warming – half of CO2, but 100 times more per molecule. global estimate ranges from 2.8 x 1015 to 8 x 1018 trillion cubic meters of CH4 25% of CH4 hydrates reside within USA borders (e.g., Alaska North Slope, Gulf of Mexico, Blake Ridge off coast of S.Carolina)

Example of Carbon Dioxide Products from AIRS

Isothermal vertical structure weakens sensitivity
LW Thermal CO2 Kernel Functions are also Sensitive to H2O, T(p), & O3(p). Polar TPW = 0.5 cm Mid-Latitude TPW = 1.4 cm Tropical TPW = 2.5 cm moisture optical depth pushes peak sensitivity upwards Isothermal vertical structure weakens sensitivity

Sensitivity Analysis for CO2 retrieval in 15 µm band
Knj

Same as before but at edge of scan (45 deg)

Also providing the vertical information content & comparing CO2 product with models
AIRS mid-trop measurement column CO2 Transport Model Randy Kawa (GSFC) Fraction Determined from AIRS Radiances Averaging Function Peak Pressure

NOAA AIRS CO2 Product is Still in Development
Measuring a product to 0.5% is inherently difficult Empirical bias correction (a.k.a. tuning) for AIRS is at the 1 K level and can affect 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 minimize the impact of the 57 GHZ O2 band as a T(p) reference point. Bottom Line: Core product retrieval problems must be solved first. 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.

AIRS measures multiple gases (and temperature, moisture and cloud products) simultaneously
29 month time-series of AIRS trace gas products: Alaska & Canada Zone (60  lat  70 & -165  lon  -90) July 2004 Alaskan fires are evident in CO signal (and CH4 ??) Seasonal methane is correlated to surface temperature (wetlands emission?) We have begun to investigate correlations that should exist between species (e.g., O3, CO, CH4 interaction) CH4 CO CO2 O3 CH4 & Tsurf Aug.2003 Mar.2006

29 month time-series of AIRS products Eastern China Zone (20  lat  45, 110  lon  130)
Correlation of CH4 with skin temperature is significantly smaller

29 month time-series of AIRS products South America Zone (-25  lat  EQ , -70  lon  -40)
Biomass burning Correlation of CH4 with skin temperature is non-existent

For more information: http://www. orbit. nesdis. noaa
Trace GAS web-pages allow a quick look at the trace gas products as a function of geography, time, and comparisons with in-situ datasets. USERID & PASSWORD Request via

… And many groups are working on AIRS CO2 algorithms
P.I. Methodology Type of Scenes Temperature/CO2 Separation Alain Chédin & Cyril Crevoisier Neural Network Clear 57 GHz O2 (Aqua/AMSU) Richard Engelen 4DVAR 57 GHz O2 (all AMSU’s) & radiosonde Moustafa Chahine Partial Vanishing Derivatives (unconstrained LSQ) Clear & Cloudy Multi-spectral (15 vs 4 µm) and 57 GHz (Aqua/AMSU) Larrabee Strow Unconstrained LSQ T(p) = ECMWF William Blackwell Chris Barnet Regularized LSQ (optimal estimation)

Comparison of Sciamachy CO2 with AIRS CO2 (R. Engelen, ECMWF)
Barkley, M.P., P.S. Monks, R.S. Engelen, GRL submitted 2006 SCIAMACY on left (total column measure. AIRS on right (mid-trop measure) Monthly mean is subtracted in each frame May (top), June, July & Sept 2003 (bottom) are shown

Outline for Tomorrow’s Lecture
Retrieval Vertical Weighting Functions. What are they. How are they used. Validation Techniques. Examples with T,q,O3. Comparisons of CO2 product with in-situ. Summary of some papers on using AIRS CO2 products in carbon assimilation systems. Trace gas product correlations – A better way to use AIRS data?

Operational atmospheric trace gas products from AIRS, IASI, CrIS

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