Chris BarnetNOAA/NESDIS/STAR

(the office formally known as ORA)

University of Maryland, Baltimore County (Adjunct Professor)AIRS Science Team Member

NPOESS Sounder Operational Algorithm Team MemberGOES-R Algorithm Working Group – Chair of Sounder Team

NOAA/NESDIS representative to IGCO

July 26, 2006MSRI-NCAR Summer Workshop on

Data Assimilation for the Carbon Cycle

Operational atmospheric trace gas products from AIRS, IASI, CrIS

Mitch Goldberg: AIRS & IASI Science Team, Climate ProductsWalter Wolf: Near Real Time Processing & Distribution to UsersLihang Zhou: Regression Retrieval & Near Real Time Web PageEric 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 productsXingpin Liu: Re-processing, Statistics, Product web-pageAntonia Gambacorta (UMBC): UTH, OLR and climate indices.

Member’s of our Sounding Team who have contributed to the trace gas work.

NOTE: Only a small fraction of our funding goes to support tracegas work. The majority supports the core products (temperature, moisture, and ozone).

3

Sounding Theory Notes for the discussion today is on-line

voice: (301)-316-5011email: chris.barnet@noaa.govftp 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.pdfThese are living notes, or maybe a scrapbook – it is not a textbook.

4

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.

5

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?

6

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 2100 (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

7

Comparison with 1000 year ice core record of CO2 from Law Dome Antarctica

8/28/1859 Edwin Drake’s 1st oil well

8

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 ….

9

Average of 1 tonne of C emitted to the atmosphere per person per year

Andres & Marland, Fung, Matthews, 1999, GBC, v.10

10

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

11

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

12

84% of modern energy comes from fossil fuels (oil, coal, gas)

20.95 briq/pound, new paper7.5 briq/pound, recycled

3.2 kWh/pound, new1.2 kWh/pound, recycled

Paper

0.32 lbs-C/kWh6.54 briq/kWh

1200 lbs of CO2/MWh3.67 CO2/C

Electricity(PEPCO statement)

4 briq/mile, 220 briq/hour/car58,000 briq/year/driver11 trillion briq/year in US

5 lbs-C/gal (C8H18)0.2 lbs-C/mile

Driving a 25 m/g Car191.276 million US drivers

<14,500 m/driver>

1.5 briq/can75 billion briq/yr in US(150 w/o recycling)

7.5 kWh/pound, 100 billion Al-cans/yr used in US,34 Al-cans/pound

Aluminum Electroyte Process 1998: 38 billion pounds produced worldwide

325,000 briq/hour or1225 briq/person/hour (full)

30 lbs-C/mile2.25 briq/mile

DC-10267 seats

133,852 briq/hour or847 briq/person/hour (full)

12 lbs-C/mile1.55 briq/mile

Boeing 757-200158 seats

Per-unit amount of C release to atmosphereBasic Conversion FactsEnergy Source

13

As you use Energy, think Briquets(that last in atmosphere for 100 years)

65 briq/dayWater Heater(w/o washer)

10 briq/loadClothes Dryer

33 briq/day17 cu ft Refrigerator

20 briq/loadClothes Washer (water+washer)

1 briq/dayCeiling Fan190 briq/day24,000 BTUcentral AC

1.5 briq/hrTV or Computer70 briq/day9000 BTUWindow AC

1 briq/hr60 W light400 briq/dayWinter Heating(1200 cu ft home)

14

Even dietary choices make a difference

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

• In 2002 food production accounted for 17% of all fossil fuel use.

• Farm Equipment

• Ships & Trucking

15

And the demand continues to rise ….

Residential use of air conditioners in the USA has almost doubled in last 20 years

16

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

17

Acronyms• Infrared 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

18

NOAA/NESDIS 20 year StrategyUsing 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

19

AIRS Was Launched on the EOS Aqua Platform May 4, 2002

AIRS

HSB

AMSU-A1(3-15)

AMSU-A2(1-2)

Delta II 7920

MODIS

Aqua Acquires 325 Gb of data per day

20

AIRS has a Unique Opportunity to Explore & Test New Algorithms for Future Operational Sounder Missions.

5/4/2002

≥ 9/2008

12/18/2004

7/15/2004

Apr. 28, 2006

21

IASI Launch Was Supposed to Be Launched Last Week – Delayed Until Sep.

July 5, 2006 July 14, 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

• Baikonurunavailable until Sep.

22

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?)

23

Instruments measure radiance (energy/time/area/steradian/frequency-interval)

Convert to Brightness Temperature = Temperature that the Planck Function is equal to measured radiance at a given frequency.

This is what we measure

This is how I will show it.

24

Spectral Coverage of Thermal Sounders (Example BT’s for AIRS, IASI, & CrIS)

AIRS, 2378Channels

CrIS1305

IASI, 8401Channels

CO2 CO2O3 COCH4

25

Thermal Sounder “Core” Products(on 45 km footprint, unless indicated)

TBD1.0 KCloud Top TemperaturesTBD0.5 kmCloud Top PressuresTBD5%Fractional Cloud Cover (13.5 km)5%5%Total Precipitable Water

15%/2-km15%/2-km layerMoisture Profile1K/1-km1K/1-km layerTemperature Profile

TBD1.0KLand Surface Temperature0.8 K0.5 KSea Surface Temperature< 1 K1.0KCloud Cleared IR Radiances

Current EstimateRMS RequirementGeophysical Products(failed 2/2003)1.0-1.2 KHSB Radiance (13.5 km)

1-2 K0.25-1.2 KAMSU Radiance10-15%20%AIRS VIS/NIR Radiance< 0.2 %3%AIRS IR Radiance (13.5 km)

Current EstimateRMS RequirementRadiance Products

26

Trace Gas Product Potential from Operational Thermal Sounders

T(p)15%1400-1500UTH

emissivity50%790-805CCl4

emissivity20%900-940CF2Cl (F12)emissivity20%830-860CFCl3 (F11)

H2OH2O,CO

10%10%

1250-13152180-2250

N2O

emissivityH2O,CH4

40%25%

860-9201320-1330

HNO3

H2O,HNO31000%1340-1380SO2

H2O,O32 ppm2 ppm

680-7952375-2395

CO2

H2O,HNO320 ppb1250-1370CH4

H2O,N2O15%2080-2200CO

H2O,emissivity10%1025-1050O3

InterferencePrecisionRange (cm-1)gas

Haskins, R.D. and L.D. Kaplan 1993

ProductAvailable

Now

In Work

Held Fixed

27

Radiance at the Satellite isComposed 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.

28

Thermal sounder forward modelExample: upwelling radiance term

Each channel samples a finite spectral region

Vertical temperature gradient is critical for thermal sounding.

Absorption coefficients, κ, for a any spectrally active molecular species, i, (e.g., water, ozone, CO2, etc.) must be computed.

κ is a strong function of pressure, temperature, and interaction with other species.

Inversion of this equation is highly non-linear and under-determined.

Full radiative transfer equation includes surface, down-welling, and solar reflection terms.

29

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.

30

The Solar (or Direct) term, without scattering, is given by

• Source Function, H, is the Sun for AIRS & OCO

• Ω(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.

31

Comparison of Satellite Methods

Measure independently.

Solve for aerosol microphysics

Minimal impact to mid-trop.

Aerosols

Main utility

Data availability

Interference

Surface Issues

Clouds

Measures

Source Function

Carbon budgetReduce uncertainty of the carbon budget

Improve transportUpper boundary for OCO.

Future missionsResearch grade, 2-3 mission, no follow-on

20+ years, launch almost guaranteed

Very weak interference

Weak interaction with T(p), q(p)

Strong interaction with T(p), q(p)

Need reflectivity, ρNeed reflectivity, ρVery little sensitivity

Clear or Solve for Microphysics

Clear or Solve for Microphysics

Correction via cloud clearing

Total Column/ProfileTotal ColumnMid-trop column

LASERSunPlanck Function

ActivePassive-SolarPassive-Thermal

32

AIRS Spectra from around the Globe20-July-2002 Ascending LW_Window

33

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).

Derivative of the forward model is required to minimize J.

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 = λI) due to lack of knowledge of correlations. In the future we will replace this with a measured covariance.

34

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:

35

This cost function minimizes observations minus computed radiances

• Linear minimization of cost function is equivalent to expanding Obs-calc’sinto a Taylor expansion

• In a linear operator, the different components of geophysical space can be separated.

36

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.

37

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

38

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.

39

Retrieval of Atmospheric Trace GasesRequires 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 NE∆T is required.– Minimal systematic effects (scan angle polarization, day/night

orbital effects, etc.)

40

Assimilation of Radiances versus Products: Pro’s and Con’s

Retrieval weights the radiances as high as possible, since determined state is on instrument sampling “grid.”

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.

A-priori used in retrieval may be different than assimilation model. We used very simple a-priori to assess ret. skill.

Small biases in T(p), q(p), O3(p),due to representation error, have large impact on derived CO2.

Most accurate forward model is used with a model of detailed instrument characteristics.

Require fast forward model, and derivative of forward model.

CO2 product error covariance has vertical, spatial, and temporal off-diagonal terms.

Instrument error covariance is usually assumed to be diagonal, for apodizedinterferometers (e.g. IASI) this is not accurate.

Product volume is small: all instrument channels can be used to minimize all parameters (T,q,O3,CO,CH4,CO2,clouds,etc.)

Product volume is large:In practice, a spectral subset (10%) and spatial subset (5%) of the observations is made

Assimilate CO2 ProductAssimilate Radiance

41

Example of Carbon Monoxide Products from AIRS

in collaboration with

W. Wallace McMillin, Juying Warner & Michele McCourt

University of Maryland, Baltimore County

UMBC

W. McMillan (mcmillan@umbc.edu) AIRS Science Team Meeting, Cal Tech, 3/8/06

42

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. 2005. GRL v.32 doi:10.1029/2004GL0218– McCourt, PhD dissertation, UMBC, 2006

43

AIRS CO Kernel Functions areSensitive to H2O(p), T(p) & CO(p).

Polar Mid-Latitude Tropical

44

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.

45

Sensitivity Analysis for CO retrieval

Knj

en

46

500 mb700 mb850 mb

UMBC W. McMillan (mcmillan@umbc.edu) AIRS Science Team Meeting, Cal Tech, 3/8/06

AIRS CO and TrajectoriesJuly 2004 Fires in Alaska

47

500 mb700 mb850 mb

UMBC W. McMillan (mcmillan@umbc.edu) AIRS Science Team Meeting, Cal Tech, 3/8/06

AIRS CO and Trajectories

48

500 mb700 mb850 mb

UMBC W. McMillan (mcmillan@umbc.edu) AIRS Science Team Meeting, Cal Tech, 3/8/06

AIRS CO and Trajectories

49

500 mb700 mb850 mb

UMBC W. McMillan (mcmillan@umbc.edu) AIRS Science Team Meeting, Cal Tech, 3/8/06

AIRS CO and Trajectories

50

500 mb700 mb850 mb

UMBC W. McMillan (mcmillan@umbc.edu) AIRS Science Team Meeting, Cal Tech, 3/8/06

AIRS CO and Trajectories

51

500 mb700 mb850 mb

UMBC W. McMillan (mcmillan@umbc.edu) AIRS Science Team Meeting, Cal Tech, 3/8/06

AIRS CO and Trajectories

52

500 mb700 mb850 mb

UMBC W. McMillan (mcmillan@umbc.edu) AIRS Science Team Meeting, Cal Tech, 3/8/06

AIRS CO and Trajectories

53

500 mb700 mb850 mb

UMBC W. McMillan (mcmillan@umbc.edu) AIRS Science Team Meeting, Cal Tech, 3/8/06

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)

54

Example of Methane Products from AIRS

55

Methane Sources

energy (pipes,wells,coa

l mines)18%

landfills7%

wastewater4%

domestic ruminants

13%

biomass burning

7%

rice paddies13%

animal wastes5%

tropical wetlands

16%

boreal/arctic wetlands

8%termites

2%other7%

en

Ref.: Lelieveld, 1998 & Houwelling 2002 (600 Tg total) Note: Approximately 50% of sources are anthropogenic

Trees (Keppler et al. 2005) may contribute 62-235 Tg (10-35%), mostly in tropics

56

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.

57

Sensitivity Analysis for CH4retrieval

Knj

en

58

Also providing the vertical information content to understand CH4 product

AIRS mid-trop measurement column

CH4 total column f/ transport model (Sander Houweling, SRON)

Fraction Determined from AIRS Radiances

Peak Pressure of AIRS Sensitivity

59

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)

60

Example of Carbon Dioxide Products from AIRS

61

LW Thermal CO2 Kernel Functions are also Sensitive to H2O, T(p), & O3(p).

Mid-LatitudeTPW = 1.4 cm

PolarTPW = 0.5 cm

TropicalTPW = 2.5 cm

Isothermal vertical structure weakens

sensitivity

moisture optical depth pushes peak sensitivity upwards

62

Sensitivity Analysis for CO2 retrieval in 15 µm band

Knjen

63

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

64

Sensitivity Analysis for CO2 retrieval in 10 µm band

65

Sensitivity Analysis for CO2 retrieval in 4 µm band

66

Also providing the vertical information content & comparing CO2 product with models

AIRS mid-trop measurement column

CO2 Transport ModelRandy Kawa (GSFC)

Fraction Determined from AIRS Radiances

Averaging Function Peak Pressure

67

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.

68

CH4

CO

CO2

O3

CH4 & Tsurf

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)

Aug.2003 Mar.2006

69

29 month time-series of AIRS productsEastern China Zone (20 ≤ lat ≤ 45, 110 ≤ lon ≤ 130)

Correlation of CH4 with skin temperature is significantly smaller

70

29 month time-series of AIRS productsSouth America Zone (-25 ≤ lat ≤ EQ , -70 ≤ lon ≤ -40)

Biomass burning

Correlation of CH4 with skin temperature is non-existent

71

For more information:http://www.orbit.nesdis.noaa.gov/smcd/spb/airs/index.html

• 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 e-mail:

chris.barnet@noaa.gov

72

… And many groups are working on AIRS CO2 algorithms

T(p) = ECMWFClearUnconstrained LSQLarrabee Strow

Temperature/CO2Separation

Type of Scenes

MethodologyP.I.

Clear & Cloudy

Clear

Clear & Cloudy

Clear

Clear

Multi-spectral (15 vs 4 µm) and 57 GHz (Aqua/AMSU)

Regularized LSQ(optimal estimation)

Chris Barnet

T(p) = ECMWFNeural NetworkWilliam Blackwell

Multi-spectral (15 vs 4 µm) and 57 GHz (Aqua/AMSU)

Partial Vanishing Derivatives(unconstrained LSQ)

Moustafa Chahine

57 GHz O2 (all AMSU’s)& radiosonde

4DVARRichard Engelen

57 GHz O2 (Aqua/AMSU)Neural NetworkAlain Chédin & Cyril Crevoisier

73

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

74

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?