AIRS (Atmospheric Infrared Sounder)Regression Retrieval (Level 2)

Level 0 to Level 2Level 0: raw data

Level 1A: geolocated radiance in counts

Level 1B: calibrated radiance in physical units

Level 2: retrieved physical variables (temperature, humidity and ozone profiles, surface skin temperature, total precipitable water, total ozone content, cloud top height . . .)

Regression Model

Regression Retrieval (1)

Regression Retrieval (2)

Principal Components (PC) Regression Retrieval1. Calculate Regression Coefficients

The TrainingsetXtr . . . Representative set of atmospheric variables including temperature, moisture, ozone, surface pressure, surface skin temperature and surface skin emissivities

Ytr . . . Corresponding set of simulated radiances, calculated by a fast RT (radiative transfer) forward model

Radiance received by AIRS

Fast Radiative Transfer Forward Model Fast Model Regression : - Computation of line-by-line Transmittance for FM training data set - Convolve with AIRS SRF (spectral response function) - Solve regression scheme = AC for coefficients C using predictors A (predictors are functions of T, p, absorber amount, scanang )

Calculate transmittance for any other profile

Solve RTE to get radiance R

IMAPP AIRS Regression Retrieval Results:

Comparison with co-located radiosonde observations (RAOBs)

Co-located RAOB / AIRS single profile retrieval (RTV)Temperature (pixel 1259)residual = observed minus calculated spectrum Brightness Temperature (BT) residual

Co-located RAOB / AIRS single profile retrieval (RTV)Humidity (pixel 1516)Brightness Temperature (BT) residualresidual = observed minus calculated spectrum

Co-located RAOB / AIRS retrieval statistics (1899 profiles)

Co-located RAOB / AIRS retrieval statistics (1899 profiles)Radiosonde ObservationsAIRS Retrieval

IMAPP AIRS Regression Retrieval Results:

Global (240 granules) retrievals and retrievals over the CIMSS direct broadcast area

Globally Retrieved Temperature at 850 mbarWith CloudmaskWithout CloudmaskAscending GransDescending Grans

Globally Retrieved Moisture at 850 mbarAscending GransDescending GransWith CloudmaskWithout Cloudmask

CIMSS Direct Broadcast area: AIRS measurements (10-23-2003)Brightness Temperature [K] at 1000 cm-1 (no cloudmask)

Temperature [K] at 700 mbar (no cloudmask)Humidity [g/kg] at 700 mbar (no cloudmask)CIMSS Direct Broadcast area: IMAPP AIRS Retrieval (10-23-2003)

CIMSS Direct Broadcast area: IMAPP AIRS Retrieval (10-23-2003)

CIMSS Direct Broadcast area: IMAPP AIRS Retrieval (10-23-2003)

CIMSS Direct Broadcast area: IMAPP AIRS Retrieval (10-23-2003)

IMAPP AIRS Regression Retrieval Results:

Comparison with ECMWF analysis fields

AIRS RTV vs. ECMWF Analysis: Temperature at 700 mbar (G192, 09-02-2003)

AIRS RTV vs. ECMWF Analysis: Temperature at 500 mbar and at selected pixel

AIRS RTV vs. ECMWF Analysis: Humidity at 750 mbar and at selected pixel

AIRS RTV vs. ECMWF Analysis: Humidity along scanline 65 (without cloudmask)IMAPP AIRS RetrievalECMWF Analysis

AIRS RTV vs. ECMWF Analysis: Humidity along scanline 65 (with cloudmask)IMAPP AIRS RetrievalECMWF Analysis

RMS and STDEV of ECMWF minus AIRS RTV(G192, 09-02-2003, 4758 clear pixels)Humidity Temperature

AIRS RTV vs. ECMWF Analysis: Spatial mean of Brightness Temperature (BT) residualIMAPP AIRS RetrievalECMWF Analysis

AIRS RTV vs. ECMWF Analysis: Spectral mean of Brightness Temperature (BT) residualAIRS RTVECMWF AnalysisMean Long WaveMean Short WaveMean Mid Wave

IMAPP AIRS Regression Retrieval Results:

Comparison with ECMWF analysis fields and L2 operational product

AIRS RTV vs. ECMWF Analysis vs. Operational Product: Temperature at 500 mbar (G192, 04-04-2004)

AIRS RTV vs. ECMWF Analysis vs. Operational Product: Temperature at selected pixel

AIRS RTV vs. ECMWF Analysis vs. Operational Product: Humidity at 600 mbar (G192, 04-04-2004)

AIRS RTV vs. ECMWF Analysis vs. Operational Product: Humidity at selected pixel

IMAPP AIRS Regression Retrieval Results:

Comparison with MODIS and GOES retrievals

MODIS RTV vs. AIRS RTV vs. GOES RTV:Temperature and Humidity at 620 mbar (G192, 09-02-2003)AIRS RTVGOES RTVMODIS RTVTemperature @620Humidity @620

Accurate atmospheric sounding and cloud variability observations provide an understanding of atmospheric dynamic and cloud-radiation processes that need to be included in climate models. Furthermore they are critical for initializing storm scale models for the prediction of severe weather events.

This requires an algorithm whichfully utilizes the information about the atmospheric state inherent in single field-of-view hyperspectral radiances (e.g. AIRS, IASI, CrIS) is fast to be useful for real-time applicationsprovides T, H2O, O3 profiles, as well as surface temperature, surface emissivity, cloud top pressure, cloud optical thickness, CO2 concentration simultaneously under all weather conditions at single-FOV resolutionaccounts for the non-linearity between radiances and cloud parameters and atmospheric moistureaccounts for the annual change of CO2

Improved Profile and Cloud Top Height Retrieval by Using Dual RegressionElisabeth Weisz & others

Dual Regression Retrieval Algorithm Part 1Clear trained EOF regression results

The Training SetsClear TrainingSet (SeeBorV5.0 clear-sky global training database)15704 globally distributed profiles of T, H2O, O3 at 101 levels taken from NOAA-88, ECMWF and TIGR-3 data sets, including radiosondes and ozonesondes. Quality and saturation checks have been applied.Tskin has been assigned using a relationship between Tskin and Tairs derived for the SGP ARM site.Surface Emissivity was assigned using a global land surface emissivity data base and the standard sea water emissivity spectrum. A few eigenvector coefficients are used in the regression, which are reconstructed to full spectrum after the retrieval.CO2 concentration is assigned as a random normally distributed value ranging from 360 and 400 ppmv

Cloudy TrainingSet 19948 globally distributed profiles, with 7969 from the clear set. CTP pressure was determined from the relative humidity structure of the profileRandomly distributed COTH ranging from 0.01 and 10 Randomly distributed CPS ranging from 5 to 35 for water droplets and 10 to 50 for ice crystals Tskin has been assigned from Tair by adding a random numberSurface Emissivities as in the clear setCO2 concentration as in the clear set

The Classifications Class Tb@920 cm-1 Tb@920 cm-1 (training) (observations)

1 Tb 260 K Tb 255 K 2 250 Tb 270 K 255 Tb 265 K 3 260 Tb 280 K 265 Tb 275 K 4 270 Tb 290 K 275 Tb 285 K 5 280 Tb 300 K 285 Tb 295 K 6 290 Tb 295 TbScanning angle classification: 11 sets ranging from 0 to 49. BT classification (for the clear set only)

Cloud Height classification (for the cloudy set only): 8 overlapping classes between 100 and 1000 hPa (200 hPa range each). CTOP is determined iteratively until the optimal cloud category is selected.CO2 classification: 5 sets defined by overlapping periods from 2002 to 2013. Annual mean values from ftp:://ftp.cmdl.noaa.gov/ccg/co2/trends/co2_annmean_gl.txt or via 370+2(year-2000).

yearsAnn mean CO2 [ppmv]12002-2005375.722004-2007379.832006-2009383.742008-2011387.952010-2013392.6

Cloud Height classification (for the cloudy set only): 8 overlapping classes between 100 and 1000 hPa (200 hPa range each) i.e. 100-300 hPa, 200-400 hPa, .800-1000 hPa. CTOP is determined iteratively until the optimal cloud category is selected.

CO2 classification: 5 sets defined by overlapping periods from 2002 to 2013. Annual mean values from ftp:://ftp.cmdl.noaa.gov/ccg/co2/trends/co2_annmean_gl.txt or via 370+2*(year-2000).

yearsAnn mean CO2 [ppmv]12002-2005375.722004-2007379.832006-2009383.742008-2011387.952010-2013392.6

Dual Regression Retrieval Algorithm Part 1Clear trained EOF regression results

Cloud Top AltitudeLevel where Tcloudy-Tclear > 3 Kat all levels below that levelFinal Profile(clear-trained above, cloud-trained below cloud level)Clear trained EOF regression resultsCloud trained EOF regression resultsDual Regression Retrieval Algorithm Part 2General Idea

A retrieval (incl. CO2 amount) is generated by using the regression set associated with current year. The CO2 classification is refined if necessary and the retrieval is run again.

A first estimate of the CTOP from the clear-trained and cloudy-trained retrieved T profile is obtained. The cloud classification is refined if necessary (i.e. if T derived cloud class differs from cloud-trained solution).

If CTOP is close to the surface and the maximum difference between clear and cloudy retrieved Tskin

Retrieval error statistics (simulated)Unstratified (orig) vs. stratified (DR)

SurfSkinTemp [K]CTOP [mbar]COTH#/Bias/Stdev/RMSE (orig)16359/0.45/2.21/2.2616009/-25.9/177.3/79.216009/1.6/2.9/3.3#/Bias/Stdev/RMSE (DR)16359/-0.07/1.57/1.5716009/1.1/156.1/156.116009/-0.1/1.7/1.7

CTH comparison with CloudSat and Calipsotropicalpolar

T and H2O Error Statistics (comparison with radiosondes over CONUS, Dec 2009)

MODIS 1km images (1705, 1710)High Dense CirrusCirrus OutflowEyeHurricane Isabel (Sept-13, 2003)

..AIRS Temperature (at 850 hPa) and Humidity (at 700 hPa)

AIRS Temperature and Humidity (at 300 hPa)

Isabel Eye Sounding

Joplin, MO Tornado (May 22, 2011)

RH 850 hPaRH 700 hPaTemp 500 hPa Joplin

Joplin

1.5-km RHIncreased3.0-km RHDecreased5-km Temp.DecreasedIASI (at 15:40 UTC) and AIRS (at 19:45 UTC) H2O and Temperature ChangeIASI (153855Z)May 22, 2011 1540 UTC AIRS (G197)May 22, 2011 1945 UTC

IASI (1540 UTC)AIRS (1945 UTC)IASI and AIRS Temperature, Dew Point Temperature and Humidity at Joplin, MO.Dew PointSolid lines: temperatureDashed lines: dew point temperatureTempLat/Lon: 37.0/-94.6Lat/Lon: 37.1/-94.5Temperature [K]Temperature [K]

AIRS at 19:40 vs. RAOB at 18:00 for Springfield (75 mi east of Joplin, MO)Solid lines: temperatureDashed lines: dew point temperature

IASI/AIRS Stability Change (Total Totals)

The cloud height stratified dual (EOF) regression retrieval provides all-sky condition vertical temperature and moisture profiles with profiles being retrieved down to cloud level and below thin and/or scattered to broken clouds. The single FOV algorithm is capable to capture the spatial detail of the atmospheric state which will benefit various applications, in particular severe weather forecasting.Algorithm will be integrated in the UW/CIMSS IMAPP AIRS software package. Retrieval products will include TPW, TOC, Lifted Index and CAPE.Improved Profile and Cloud Top Height Retrieval by Using Dual RegressionSummary

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