Chris Barnet NOAA/NESDIS/STAR (the office formally known as ORA) AIRS Science Team Member NPOESS Sounder Operational Algorithm Team Member GOES-R Algorithm Working Group – Chair of Sounder Team May 11, 2006 Carbon Fusion, Edinburgh The Challenges in using Atmospheric Trace Gas Products from Thermal Sounders 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: CO 2 retrieval, “tuning”, vertical averaging functions. Xiaozhen Xiong: CH 4 retrieval Xingpin Liu: Re-processing, Statistics, Product web-page

2 Topics Introduction to our plans to use operational sounders to retrieve carbon products. Example of CO Product Example of CH4 Product & Validation Efforts Example of CO2 Product & Validation Efforts Inter-comparison of AIRS trace gas products.

3 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 –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

4 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. 201?: Migrate AIRS/IASI/CrIS algorithm into GOES-R HES/ABI

5 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

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

7 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?)

8 Spectral Coverage of Thermal Sounders (Example Radiances: AIRS, IASI, & CrIS) AIRS, 2378 Channels CrIS 1305 IASI, 8401 Channels CO 2 O3O3 CO CH 4

9 Thermal sounder forward model Example: upwelling radiance term Each channel samples a finite spectral region Vertical temperature gradient is critical for thermal sounding. Absorption coefficients, , for a any spectrally active molecular species, i, (e.g., water, ozone, CO2, etc.) must be computed.  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.

10 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 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. Currently we are using minimum variance approach (C = I) due to lack of knowledge of correlations.

11 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.

12 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

13 Thermal Sounder “Core” Products (on 45 km footprint, unless indicated) Radiance ProductsRMS RequirementCurrent Estimate AIRS IR Radiance (13.5 km)3%< 0.2 % AIRS VIS/NIR Radiance20%10-15% AMSU Radiance K1-2 K HSB Radiance (13.5 km) K(failed 2/2003) Geophysical ProductsRMS RequirementCurrent Estimate Cloud Cleared IR Radiances1.0K< 1 K Sea Surface Temperature0.5 K0.8 K Land Surface Temperature1.0KTBD Temperature Profile1K/1-km layer1K/1-km Moisture Profile15%/2-km layer15%/2-km Total Precipitable Water5% Fractional Cloud Cover (13.5 km)5%TBD Cloud Top Pressures0.5 kmTBD Cloud Top Temperatures1.0 KTBD

14 Trace Gas Product Potential from Operational Thermal Sounders gasRange (cm -1 )PrecisionInterference UTH %T(p) O3O %H2O,emissivity CO %H2O,N2O CH ppbH2O,HNO3 CO ppm H2O,O3 SO %H2O,HNO3 HNO % 25% emissivity H2O,CH4 N2ON2O % H2O H2O,CO CFCl 3 (F11) %emissivity CF 2 Cl (F12) %emissivity CCl %emissivity Haskins, R.D. and L.D. Kaplan 1993 Product Available Now In Work Held Fixed

15 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), O 3 (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.)

16 Radiances versus Products Assimilate RadianceAssimilate 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.”

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

18 The CO (& O 3 ) Product Improves Utility of the CH 4 and CO 2 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

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

mb 700 mb 850 mb UMBC W. McMillan AIRS Science Team Meeting, Cal Tech, AIRS CO and Trajectories

mb 700 mb 850 mb UMBC W. McMillan AIRS Science Team Meeting, Cal Tech, AIRS CO and Trajectories

mb 700 mb 850 mb UMBC W. McMillan AIRS Science Team Meeting, Cal Tech, AIRS CO and Trajectories

mb 700 mb 850 mb UMBC W. McMillan AIRS Science Team Meeting, Cal Tech, AIRS CO and Trajectories

mb 700 mb 850 mb UMBC W. McMillan AIRS Science Team Meeting, Cal Tech, AIRS CO and Trajectories

mb 700 mb 850 mb UMBC W. McMillan AIRS Science Team Meeting, Cal Tech, AIRS CO and Trajectories

mb 700 mb 850 mb UMBC W. McMillan AIRS Science Team Meeting, Cal Tech, 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)

27 Example of Methane Products from AIRS

28 AIRS CH 4 Kernel Functions are Sensitive to H 2 O(p) & T(p) PolarMid-LatitudeTropical Isothermal vertical structure weakens sensitivity. moisture optical depth pushes peak sensitivity upwards.

29 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

30 Comparison of CH 4 product & ESRL/GMD Continuous Ground Site Barrow Alaska 3deg. x 3deg. gridded retrieval averaged over lat, & -165 to -90 lng

31 Comparisons of AIRS product to ESRL/GMD Aircraft Observations ESRL/GMD aircraft profiles are the best validation for thermal sounders since they measure a thick atmospheric layer.

32 ESRL/GMD Flask Data from Poker Flats, Alaska: Seasonal cycle is a function of altitude Surface Flasks (Barrow) 1.5 km 850 mb 5.5 km 500 mb 7.5 km 385 mb

33 We need to determine how much of our CH 4 signal is from stratospheric air Dobson-Brewer circulation Can depress high latitude, high altitude methane signals in winter/spring time-frame. UT/LS region in high latitudes has “older” air. We will explore tracer correlations to unravel surface vs stratospheric sources. (working w/ L. Pan, NCAR)

34 Example of Carbon Dioxide Products from AIRS

35 LW Thermal CO 2 Kernel Functions are also Sensitive to H 2 O, T(p), & O 3 (p). Mid-Latitude TPW = 1.4 cm Polar TPW = 0.5 cm Tropical TPW = 2.5 cm Isothermal vertical structure weakens sensitivity moisture optical depth pushes peak sensitivity upwards

36 Also providing the vertical information content & comparing CO 2 product with models AIRS mid-trop measurement column CO 2 Transport Model Randy Kawa (GSFC) Fraction Determined from AIRS Radiances Averaging Function Peak Pressure

37 Preliminary Comparisons to ESRL/GMD aircraft Comparison of AIRS & ESRL/GMD observations.. Usually  5 hour time difference Limit retrievals within 200 km of aircraft. Spot vs. regional sampling Retrieval is average of “good” retrievals 3 – 50 ret’s are used in each dot.  = ± 3.1 ppmv, correlation = 0.83 Investigation of outliers is in-work.

38 Comparisons to JAL aircraft observations & ESRL/GMD MBL model Matsueda et al aircraft – single level measurement ESRL/GMD Marine Boundary Layer Model (surface measurement) AIRS CO2 retrieval from GRIDDED dataset – mid-trop thick layer measurement JAL Aircraft data provided by H. Matsueda

39 Same as before, but in-situ CO2 adjusted by a-priori in retrieval JAL Aircraft data provided by H. Matsueda In-situ data is adjusted by the % of a-priori in our regularized retrieval. This depresses the seasonal amplitude of the in-situ data and is a gauge of our retrieval performance. Differences should exist between single level (surface or altitude) observations and AIRS thick layer observations.

40 Again, to what extent does stratospheric age of air play a role? Model runs of Brewer-Dobson circulation effect are courtesy of Run-Lie Shia, Mao-Chang Liang, Charles E. Miller, and Yuk L. Yung, California Inst. Of Technology & NASA Jet Propulsion Lab. Surface measurements (dashed line) and model of 500 mb concentration (solid line) can differ by 5 ppm (NOTE: Vert. Scale is ppm) Brewer-Dobson effect has altitude, latitude, and seasonal variation with a maximum in northern winter/spring

41 NOAA AIRS CO 2 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 O 3, CO, CH 4, and CO 2 products is a unique contribution that thermal sounders can make to improve the understanding of transport.

42 … And many groups are working on AIRS CO2 algorithms P.I.MethodologyType of Scenes Temperature/CO2 Separation Alain Chédin & Cyril Crevoisier Neural NetworkClear57 GHz O2 (Aqua/AMSU) Richard Engelen4DVARClear57 GHz O2 (all AMSU’s) & radiosonde Moustafa ChahinePartial Vanishing Derivatives (unconstrained LSQ) Clear & Cloudy Multi-spectral (15 vs 4 µm) and 57 GHz (Aqua/AMSU) Larrabee StrowUnconstrained LSQClearT(p) = ECMWF Chris BarnetRegularized LSQ (optimal estimation) Clear & Cloudy Multi-spectral (15 vs 4 µm) and 57 GHz (Aqua/AMSU)

43 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., O 3, CO, CH 4 interaction) Aug.2003Mar.2006

44 29 month time-series of AIRS products Eastern China Zone (20  lat  45, 110  lon  130) Correlation of CH 4 with skin temperature is significantly smaller

45 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

46 For more information : 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