ATMOSPHERIC EMITTED RADIANCE INTERFEROMETER - CURRENT AND FUTURE TROPOSPHERIC APPLICATIONS

1. ATMOSPHERIC EMITTED RADIANCE INTERFEROMETER - CURRENT AND FUTURE TROPOSPHERIC APPLICATIONS W. F. Feltz, #D. Turner, H. B. Howell, R. Dedecker, *W. L. Smith and H. Woolf 6th ISTP Leipzig, Germany 14-20 September 2003 University of Wisconsin CIMSS/SSEC *NASA LaRC, # Pacific Northwest National Laboratory

2. OVERVIEW • Instrument Overview • Some current AERI Applications • Advancements in Temperature and Moisture Retrieval (IHOP and CRYSTAL-FACE) • Conclusions

3. INSTRUMENT OVERVIEW IR Detector Dewar with Cooler Cold Finger ABB Stirling Cooler Compressor HBB Bomem Interferometer

4. AERI SPECIFICATIONS • Spectral Resolution better than 1 cm-1 wavenumber from 520-3000 cm-1 (3 - 20 um) • Calibrated to 1% ambient radiance (better than 1 K ambient temperature) • Automated and environmentally hardened • Time resolution: 6 - 10 minutes (adjustable) • Ground-based and portable • Surface viewing mode and uplooking mode

6. UW AERI - 2 (AERIBAGO, SSEC) DOE AERI - 8 (Kansas/Oklahoma, Alaska, S. Pacific) U-Miami M-AERI - 3 (Florida) Bomem AERI -8 (Italy, California, Maryland, Canada) U Idaho P-AERI - 1 (Antarctica)

8. AERI APPLICATIONS

9. Real-time Thermodynamic Retrievals Six AERI systems (including Madison, WI) are currently processing PBL retrievals in near real-time, allowing “on the fly” validation:

10. AERI Cloud Phase Detection: Sample Results Credits: Dr. David Turner Pacific Northwest National Laboratories

11. INTERCOMPARISON OF TWO MARINE AERIS MEASURING SST 16 Day Cruise Hawaii Largest Daily Mean Difference: 0.020 K Ten Day Mean Difference: 0.005 K New Zealand Track of the R/V Roger Revelle 28 Sept. - 14 Oct. 1997 Credits: Dr. Peter Minnett U of Miami RSMAS

12. Marine-AERI Cruises Conducted by U of Miami Since 1996 to Obtain Ocean Surface Skin Temperature and Emissivity

13. AERI THERMODYNAMIC RETRIEVAL SPECTRAL REGIONS

14. AERI Thermodynamic Retrieval Flow Chart Radiosonde Climatology Regression Data Base T,Q Surface to 3 Km AERI Radiance Cloud Base Height (if present) Hybrid First Guess Physical Retrieval NWP Model/Satellite T,Q Profile 2 Km - Tropopause Temperature/ Moisture Profile Surface Moisture

15. AERIplus Retrieval Description • Two step retrieval, construct optimal first guess than conduct physical retrieval • Statistical retrieval is a combined regression and NWP profile • Physical retrieval used is iterative onion peel technique • Temperature and water vapor mixing ratio profiles retrieved from high resolution AERI spectra up to 3 km • Temporal resolution ~ ten minutes (increasing to < 1 minute) • Vertical resolution improved in lowest kilometer from 100 m to 50 m • Fast model update based on LBLRTM with HITRAN 2000 trans. coeffs • Constraints: AERI retrieval only possible in clear sky or below cloud base to 3 kilometers

16. AERIplus, RUC, GOE-8 Profile Statistics

17. Examples of the updated AERIplus temperature retrieval improvement during the IHOP field experiment. The red profile was calculated with old algorithm while the green profile uses the new LBLRTM based fast model with improved vertical resolution and spectroscopy as compared to radiosonde (thick black line) Double inversion resolved with new algorithm

18. IHOP AERIplus Retrieval RMS Statistics

19. AERI THERMODYNAMIC RETRIEVALS

20. IHOP AERIplus Retrieval RMS Statistics

21. Hillsboro 3 June 0230 UTC Vici Lamont Morris Purcell

22. AERI West – East AERI water vapor cross sections during IHOP

23. Total Precipitable Water

24. AERIPLUS COUPLED WITH NOAA WIND PROFILER MOISTURE DIVERGENCE/ADVECTION Storm Reports from 30 April 2003 Moisture Divergence Calculation Credits: Robin Tanamachi U of Oklahoma

25. Example: Crystal Rapid-sampling AERI data

26. Applications of High Temporal Resolution AERI Data: Boundary Layer Roll Detection during CRYSTAL 40-s Profiles: 17-21 UTC 20 g/kg 2.0 15 1.5 Altitude (km) Mixing Ratio (g/kg) 1.0 10 0.5 315 m 0 5 17 21 Time (UTC) 5 AERI WV (g/kg) Perturbations: 315 m 0 40 s Perturbation 5 min. Running Mean -5 17 Time (UTC) 21

27. Applications of High Temporal Resolution AERI Data: Boundary Layer Roll Detection during CRYSTAL AERI Boundary Layer Rolls Perturbation Power Spectrum GOES-8 1 km Visible: 1925 UTC, 7/29/02 17-25 min period at 99 % significance Boundary Layer Depth: 700 meters Roll Wavelength: ~ 5 km, Updraft Width: ~1.5 km Roll Orientation: 120°, Motion: 135° GOES Derived Roll Periodicity: 23 minutes AERI Derived Roll Periodicity: 17-25 mins Mecikalski J.M., K. M. Bedka, D. D. Turner, and W.F. Feltz: Evidence for the Presence of Roll Structures in the Convective Boundary Layer using Thermodynamic Profiling Instruments. J. Geo. Res., In Preparation

28. Future Research Plans • Updated AERIplus retrieval algorithm implemented at for DOE ARM at PNNL, all AERI data from SGP with be reprocess with RUC analysis at first guess • High temporal resolution (< 1 minute) AERI radiance measurements were collected at Crystal and Texas 2002 to test improvement in gathering cloud and thermodynamic information, all DOE ARM AERI systems will be in rapid sample mode in near future • Experimenting with SHEBA and NSA data using ECMWF analysis as first guess (no RUC available) for PBL LES (Dr J. Pinto and Dr J. Curry) • Test new physical retrieval methodology will be tested to allow error bars and error covariance matrixes to be calculated for mesoscale model assimilation (working with Dr. D. Turner PNNL)

29. Future Research Plans • A five year period of a five AERI system network with collocated with exist for study of moisture temporal and spatial gradients (students working in this direction) • New research in determination of cloud properties (starting with cloud phase) using emissivity observations derived from AERI data (Dr. D. Turner presentation) • Working with several groups outside the DOE ARM science team on PBL and atmospheric stability research using the AERI thermodynamic data • Coupled with the Raman Lidar and wind profilers at the central SGP facility near Lamont, Oklahoma there is a long-term “treasure chest” of temperature, moisture, wind, and aerosol tropospheric profile information which is underutilized for tropospheric research (See Dr. R. Ferrare presention)

30. AERI Information: • References: • Feltz, W. F., J. R. Mecikalski, 2002: Monitoring High Temporal Resolution Convective Stability Indices Using the Ground-based Atmospheric Emitted Radiance Interferometer (AERI) During the 3 May 1999 Oklahoma/Kansas Tornado Outbreak. Wea. Forecasting, 17, 445-455. • Feltz, W. F., H. B. Howell, R. O. Knuteson, H. M. Woolf, and H E. Revercomb, 2003: Near Continuous Profiling of Temperature, Moisture, and Atmospheric Stability using the Atmospheric Emitted Radiance Interferometer (AERI). J. Appl. Meteor., 42, 584-597. • Minnett, P. J., R. O. Knuteson, F. A. Best, B. J. Osborne, J. A. Hanafin, O. B. Brown, 2001: The Marine-Atmospheric Emitted Radiance Interferometer: A High-Accuracy, Seagoing Infrared Spectroradiometer. J. Atmos. Oceanic Technol, 18, 994-1013. • Tobin, D.C., and coauthors, Downwelling spectral radiance observations at the SHEBA ice station: water vapor continuum measurements from 17 to 26 um. JGR, 104, 2081-2092. • Turner, D. D., W. F. Feltz, R. Ferrare, 2000: Continuous Water Vapor Profiles from Operational Ground-based Active and Passive Sensors. Bull. Amer. Soc., 81, 1301-1317. • Turner D. D., S. A. Ackerman, B. A. Baum, H. E. Revercomb, and P. Yang, 2003: Cloud phase determination using ground-based AERI observations at SHEBA. Journal of Applied Meteorology, 42, 701-715. • AERI HOMEPAGE: http://cimss.ssec.wisc.edu/aeri/ • EMAIL: wayne.feltz@ssec.wisc.edu

31. Statistical Retrieval Description • Synthetic EOF Regression • ~1100 clear radiosondes from DOE ARM central facility near Lamont, Oklahoma for 1994-1996 • Forward calculations using 60-level fast model based on AER LBLRTM • EOF regression conducted relating each radiosonde – spectrum (562 channels) pair • Regression data set is very robust since a wide variety of weather is experiences in northern Oklahoma throughout the year

32. Hybrid First Guess • Statistical retrieval achieved during clear sky conditions (no update until a clear scene is present) • Statistical retrieval errors grow rapidly with altitude above one kilometer • Satellite profiles and NWP can be used to constrain the first guess through a simple linear interpolation between 1-2 km • This improved first guess constrains the physical retrieval and improves PBL retrieval profile • Currently combination of hourly RUC analysis/AERI statistical retrieval used over United States used to optimize the retrievals

33. Physical Retrieval Description • “Onion peel” retrieval methodology • Physical iterative recursive retrieval solution of the infrared radiative transfer equation • During each iteration the temperature and water vapor mixing ratio profile adjustments are made to minimize the difference between observed and calculated spectra • To correctly account for forward model spectroscopy and regression errors a static bias is used for water vapor (not needed for temperature retrieval spectral regions), currently bias is static but dynamic bias ties to water vapor is being considered with goal to be bias free