A poster supporting the HIRDLS data held at the BADC (High Resolution Dynamics Limb Sounder (HIRDLS) instrument)

Craft, J

Craig, CA

Edwards, DP

Gille, JC

Halvorson, CM

Johnson, BR

Lambert, A

Massie, ST

McInerney, JM

Stone, KA

English

Centre for Environmental Data Analysis Digital Repository

• Inversion Scheme• Level 1 radiances --> Level 2 products.• Optimal estimation (Rodgers, 1976, 1990)• Requires a priori and measurement covariances• Prototype retrieval algorithm• Examine appropriate combinations of radiance channels to retrieve:• Temperature/pressure, aerosols, constituent gases• Examine multiplex retrievals using the HIRDLS viewing geometry:• Initially : profile-by-profile independent retrievals• More advanced : along track/across track/whole orbit batch retrievals• Operational retrieval algorithm• Computational considerations• 8000 profiles x 10 products per day• Approximations : trade-off accuracy vs speed• General Requirements• initial guess profile(s) for species being retrieved :• climatology (interpolated)• or “nearest” profile at previous retrieval stage• or co-located profile at previous retrieval stage• contaminant profiles for gases contributing to emission but notbeing retrieved at same retrieval step :• as listed for initial guess profile• or co-located data at current retrieval stage• retrieval order• retrieve those species which contaminate other channels first• retrieval grouping• joint retrievals for channels with cross-contaminationRetrievalTarget Contaminants Channels  1   T/p CO2 O3 N2O H2O Aerosol 2 3 4 52 Aerosol H2O N2O CO2 O3 HNO3 CH4 1 6 13 193 O3 CO2 H2O N2O CFC12 Aerosol 10 11 124 H2O CH4 O2 O3 CO2 Aerosol 18 205 NO2 H2O CH4 O2 Aerosol 21HNO3 8CFC11 76CFC12H2O CO2 O3 Aerosol9N2O5 14N2O 15ClONO2 167CH4H2O CO2 HNO3 CF4 Aerosol17Retrieval Sequence• Aerosol Channels• HIRDLS has 4 “designated” aerosol channels in which the contaminants are gasesretrieved in other channels.• Channel Wavelength Contaminants• 01 17.38 µm CO2, H2O, N2O• 06 12.07 µm CO2, O3, H2O• 13 8.26 µm CO2, O3, HNO3, N2O, CH4• 19 7.10 µm H2O• Sulfate Aerosols• spherical liquid drops, Mie theory appropriate• recent measurements of low temperature refractive indices• under background conditions we may assume that scattering is negligible• under severe volcanic conditions the single scatter albedo in the HIRDLS wavelengthrange may approach a few percent• Polar Stratospheric Clouds / Cirrus• Scattering becomes significant problem for large particles• Non-sphericity of particles• Include scattering in HIRDLS forward model (correlated-k?)• All channels will show large effects in presence of  PSC / cirrus• Spectral signatures of PSCs/cirrus/sulfate• Difficult to correct gas channels adequately(e.g. refractive indices for PSCs are not well known)• Cloud detection• each vertical column of detector focal plane array has an aerosol channelAerosolsSulfate NAT ICEError Characterization• Error analyses performed using the AFGL tropical atmospheric model• Temperature (4 channels, 02, 03, 04, 05)• Ozone (3 channels, 10 11,12)• Water vapor (2 channels, 18, 20)• Nitrogen dioxide (1 channel, 21)• CH4, N2O, ClONO2, N2O5 (4 channels, 14, 15, 16, 17)• Measurement error (channel noise only, pointing jitter not included).• A priori error (temperature 20K, constituents 75% VMR off diagonal elementscalculated using a correlation scale length of 10km)• Forward model error (0.3% rms of radiance)• Temperature error not included for constituent analysesTotal ErrorMeasurement NoiseForward Model ErrorA Priori ErrorLimb Radiance Spectra• Typical atmospheric limb-radiance spectra calculated for a tangent heightof 25 km at mid-latitude• HIRDLS Channel band pass filters are represented schematically806040200700650600550CO2403020100700650600550N2O403020100700650600550O3H2O0.80.40.0Response700650600550Wavenumber [cm-1]Ch.1 2 3 4 5Radiance (x10-3) [W/(m2 .sr.cm-1 )]1612840940920900880860840820CFC11HNO3CFC123.02.01.00.0940920900880860840820CO2 CO2Aerosol3.02.01.00.0940920900880860840820ClONO2O3H2O0.80.40.0Response940920900880860840820Wavenumber [cm-1]Ch.6 7 8 9Radiance (x10-3) [W/(m2 .sr.cm-1 )]30201001150110010501000950O31.00.80.60.40.20.01150110010501000950CO2H2O1.00.80.60.40.20.01150110010501000950N2OCFC12Aerosol0.80.40.0Response1150110010501000950Wavenumber [cm-1]Ch.10 11 12Radiance (x10-3) [W/(m2 .sr.cm-1 )]642014001350130012501200CH42.52.01.51.00.50.014001350130012501200N2OO3HNO32.52.01.51.00.50.014001350130012501200N2O5 ClONO2CO2C 22.52.01.51.00.50.014001350130012501200H2OAerosolCF40.80.40.0Response14001350130012501200Wavenumber [cm-1]Ch.13 14 15 16 17Radiance (x10-3) [W/(m2 .sr.cm-1 )]3.02.01.00.01650160015501500145014001350H2O0.60.50.40.30.20.10.01650160015501500145014001350O3HNO3NO23.02.01.00.01650160015501500145014001350CH40.60.50.40.30.20.10.01650160015501500145014001350CO2 O20.80.40.0Response1650160015501500145014001350Wavenumber [cm-1]Ch.18 19 20 21Radiance (x10-3) [W/(m2 .sr.cm-1 )]• Climatological data are required for each contaminant species in theHIRDLS channels• Gridded data on standard pressure surfaces• Temporal and spatial resolution depends on the species• Consider a priori constraints to be “virtual measurements”• represents priori knowledge of the atmospheric state and variability• combine with the direct measurements• Statistical constraint• regard the a priori profile and covariance (determined from climatology) as an additionalmeasurement and its uncertainty• retrieved state is a weighted mean of the true and a priori states plus a noise contribution• covariance is chosen to limit the bias introduced in the retrieved state• Matrix Inversion• ensures non-singular matrices• Diagnostics• retrieval formalism allows the influence of the a priori on the retrieved product to bequantifiedClimatology DataField Temporal SpatialCO2 Fixed 1-D ProfileO3 Monthly 2-D Zonal MeanH2O Monthly 2-D Zonal MeanNO2 Monthly, Diurnal 2-D Zonal MeanCFC11 Monthly 2-D Zonal MeanHNO3 Monthly 2-D Zonal MeanCFC12 Monthly 2-D Zonal MeanN2O5 Monthly, Diurnal 2-D Zonal MeanN2O Monthly 2-D Zonal MeanClONO2 Monthly, Diurnal 2-D Zonal MeanCH4 Monthly 2-D Zonal MeanCF4 Monthly 2-D Zonal MeanO2 Fixed 1-D ProfileAerosol Background to Volca nic 2-D Zonal MeanTemperature Monthly 2-D Zonal MeanHeight Monthly 2-D Zonal MeanA Priori Data( ) termsnoise ˆ +−+= axAIAxx• Limb-radiance is dependent on horizontal thermal and constituent mixingratio gradients• sensitivity to thermal gradients increases with decreasing wavelength (Planck functiondependence) for same opacity• optically thin channels are less sensitive to gradients• typical errors of  2-3 K in temperature for gradient of 1K/100km• Two-Pass Approach• first pass• assume horizontal homogeneity• retrieve and grid products• second pass• calculate horizontal gradients from gridded data (local or global grid)• retrieve applying LOS correction• Limb-View Geometry Approach• requires significant overlap of LOS paths for successive profiles• not applicable for standard HIRDLS global mode observations (5ºx5º)• could be applied to observation modes with finer along-track spacingLine of Sight (LOS) GradientsReferenceTan gent RayGeometricTangen t PointsNominalVerticalhψState Vector(located at referencetangent point)GeometricTange nt PointsReferenceTangen t Ray0ψGeometric Ray Paths(symmetric aboutgeometric tangentpoints)LOS Direction0ψSatellitehψState Vector(located at referencetangent point)ReferenceTange nt Ray0ψRefracted Ray Path(non-symmetric about truetangent point for n(r,ψ))LOS DirectionGeometricTangent  PointTrueTange nt PointRefracted Ray PathTemp erature, Pressure, H2O in vertical plane along LOSare used to calculate the Refractive Index of Air andderivatives.Ray Tra cing Algorithm calculates the Refracted Ray PathInterpolation of 2D fields along LOS generates the requiredLOS path quantities)(),(),( sssh ψθ[ ][ ][ ])(),()()(),()()(),()(sshVMRsVMRsshPsPsshTsTLOSLOSLOSψ=ψ=ψ=),(),(),(2 ψψψhOHhPhThdndhnhnψ∂∂ψψ,),,(2D VerticalCross-SectionAlong LOS2D LOS GeometryScience PrototypingLevel 1+CoLocAncRetrievedParametersHIRDLSLevel 2LOS GridSymbol KeyHDF EOSSwathHVSStatisticsBsel FileMLS, TES,CorrelativeDataIDL based tools and standard data formats create foundationData FormatsAdoption (as practical) of common format to minimize accessoverhead and the reinvention of wheels.HVS - (IDL-based toolkit: 2dlat, 2dlon, map, xy, cstats, coin)LIMS/HALOE heritage.Collection of comparison, statistics, plotting & contouringroutines with a simple command line interface.Reads internal format (bsel) and HIRDLS HDF-EOS Swath.Validation and VisualizationFeatures:Latitude vs P, Z color cross sectionsColor mapsCoincident profile detection andstatistics on differencesBasic line plottingFiltering based on location/time.RenderingVisualization and Validation Toolkit0 2 4 6 8H2O Mixing Ratio(ppmv)2030405060Altitude (km)HIRDLS and August Mozart 3 Model H2O Mixing RatioMeans and Differences - 3792 profiles              -10 -5 0 5 10Difference (%)2030405060Altitude (km)  -3.0-2.4-1.8-1.2-0.60.00.61.21.82.43.0Percent DifferencesHIRDLS-135 -90 -45 0 45 90 135 180-90-80-70-60-50-40-30-20-10102030405060708090-0.6-0.6-0.60.00.00.60.61.21.21.81.82.42.42.4Jan 20, 2000 09ZWater Vapor Differences (%) at 30 km3.03.33.63.94.24.54.85.15.45.76.0H2O Mixing Ratio(ppmv)HIRDLS-135 -90 -45 0 45 90 135 180-90-80-70-60-50-40-30-20-10102030405060708090Jan 19, 2000 16ZjoemciHIRDLS Water Vapor at 30km0.00.81.62.43.24.04.85.66.47.28.0 -90 -72 -54 -36 -18 0 18 36 54 72 90Latitude(Deg)30405060Altitude(km)HIRDLSAltitude(km)Mar 24, 2000 10ZHIRDLS Water Vapor Mixing Ratio0.00.81.62.43.24.04.85.66.47.28.0 -90 -72 -54 -36 -18 0 18 36 54 72 90Latitude(Deg)30405060Altitude(km)MODELAltitude(km)Mar 24, 2000 10ZModel Water Vapor Mixing RatioRadiative Transfer Models• Forward Model• Simulation of calibrated Level 1 radiances.• Spectroscopic, atmospheric, instrument parameters.• Hierarchy of models (validated against GENLN2).• LBL --> Ta bulated Coefficients --> Fast Parameterized•  Full Physics•  Benchmark Studies•  Parameter Generation GENLN3: LBL CODERadiative transfer Calculation ofChannelTransmittances Geometry &Raytracing Retrieval Interface Forward Model HierarchyHIRDLS Specific ModelAbsorption Coefficient      Look-Up Table  • Monochromatic    Calculation  • Retains Access     to PhysicsOperational Fast Model        • CG/EGA        • OPTRAN        • Correlated-kChannel / Target GasAerosol(T,p)(T,p)(T,p)(T,p)  AerosolCFC11HNO3CFC12O3O3O3AerosolN2O5N2OClONO2CH4H2OAerosolH2ONO2Gas1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21CO2AerosolO3H2ONO2CFC11HNO3CFC12N2O5N2OClONO2CH4CF4O2Spectral Channels

HIRDLS poster

http://cedadocs.ceda.ac.uk/1136/2/HIRDLS_poster_%28bottom%29.pdf

HIRDLS poster

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