TAMDAR AERIBAGO Validation Experiment (TAVE) - Memphis Wayne Feltz, Erik Olson, John Short, Sarah Bedka, Kristopher Bedka, Tim Wagner, and Scott Cultice University of Wisconsin - Madison SSEC/CIMSS

TAVE OUTLINE TAVE Experiment Description TAVE Dataset Overview Preliminary Validation Results Future Analysis and Deployment Preliminary RUC vs Aircraft Validation

TAVE LOGISTICS Location: Memphis airport at Air National Guard Dates/Timing: 23 February - 08 March 2005 Weather: Dry, cool, two periods of rainfall, very little in the way of high dewpoint events/convection Data: Made available in near real-time, netcdf format from anonymous ftp server  Radiosondes - 49 total launches  12 Tail Numbers with TAMDAR instrumentation (excluding the 3 with bad sensors) Web site:

Memphis Airport Location

Memphis ANG Deployment

AERIBAGO Details Size: 28 ft in length, Height 17 ft (tower) Power: Full power, 3 phase, 60 Amp Hubble all weather connection, we need to contract electrician for wiring Internet Accessibility: LAN already installed, phone line need (voice/data/cellphone), ethernet preferable but not necessary Grounding

AERIBAGO INSTRUMENTATION Vaisala DigiCORA III RS-92 GPS Sounding System Atmospheric Emitted Radiance Interferometer (AERI) GPS Receiver VAISALA Surface PTU Station VAISALA 25K Ceilometer

Instrument Summary Radiosondes - Vertical temperature and water vapor, Vaisala RS-92 radiosondes, 20 preparation time, 1 1/2 hour flight time, realtime monitoring capability Surface Station - Vaisala sensors, one minute, p, t, q, v, u, tested and calibrated for accuracy at SSEC AERI - Vertical temperature and water vapor profiles to three kilometers at ten minute resolution within PBL GPS - Integrated total water vapor at half hourly time resolution must be at a stationary location for at least ten days Vaisala Ceilometer - Cloud base heights every ten seconds

TAVE AERIBAGO SETUP

Vaisala DigiCORA-III Receiver RS-92SGP Capable

Radiosonde Profile vs TAMDAR

GPS Receiver

Vaisala Surface Station

Vaisala Ceilometer

Atmospheric Emitted Radiance Interferometer (AERI)

AERI Thermodynamic Retrievals

Other Datasets Collected TAMDAR/ACARS Profiles from MADIS and converted to netcdf over Memphis RUC Analysis Profiles over Memphis Satellite, radar, and surface imagery GOES pwv, profiles All Available at: ftp://ftp.ssec.wisc.edu/validation/exper/tamdar/data/

Preliminary TAMDAR Thermodynamic Validation

TAVE Validation Datasets

Radiosonde Schedule Saab 340s arrive / depart in the following groups (local time): 7:35 - 7:55 Arrive 9:20 - 9:55 Depart 12:36 - 1:15 Arrive 14: :00 Depart 17: :00 Arrive 19: :50 Depart TAVE Radiosonde Launch Time Slots: 8:30, 10:15, 14:15, 17:00, and 19:00 Local time Up to 5 Launches per day Careful attention was paid to keep the radiosonde out of sun and allowing sensor to acclimate to outside environment for several minutes before launch

Radiosonde Launch Procedure

Radiosonde Ascent Rate 5,000 ft, reached 5 minutes after launch ft/min ascent rate. 10,000 ft, reached 12 minutes after launch. 800 ft/min ascent rate. 24,000 ft, reached 30 minutes after launch. 700 ft/min ascent rate. 30,000 ft, reached 43 minutes after launch. 500 ft/min ascent rate. These balloons are smaller and lighter than the ones the NWS launches at 00Z and 12Z at numerous sites across the US.

Profiles Comparison Examples

Excluded Tail Numbers Tail numbers: 5580, bad relative humidity information bad temperature information

Radiosonde vs TAMDAR Trajectories Dashed - Descending Solid - Ascending Black lines - State Boundaries

Profile Examples

Statistics for Ascent/Descent Temperature

Statistics for Ascent/Descent Relative Humidity

Statistics for All Matches

Future Validation Improvements Validation quality of radiosonde water vapor measurements by correlating with Bago surface sensor and AERI radiance intercomparison TAMDAR sensor QC should be looked at with more scrutiny, maybe rh1 or rh2 should be used instead of rh once consensus between TAMDAR sensor indicates good rh1 or rh2 data Validation matches should be screened in the vertical as a function of horizontal distance between sensor to help account for horizontal variability of the water vapor

Future Validation Improvements Continued Temperature from ACARS measurements within +/- 30 minutes should be included on rms/bias plots Time criteria can be tightened with more matches from future deployment Wind validation using GPS winds from radiosondes vs TAMDAR/ACARS measurements

Wet Bias

PBL Comparisons TAMDAR/AERI/RUC

TAVE Summary Preliminary Validation is underway TAVE Data Available: More extensive validation will be presented at Virginia meeting in September Next Deployment possible in May or July/August in Memphis

Comparison of TAMDAR and non-TAMDAR with RUC 1 hr forecast Source statistical data provided by Bill Moninger – FSL Data from weekly ‘fit’ statistics from Mid-January - Mid-March 2005 Ralph Petersen CIMSS

Comparison of TAMDAR and non-TAMDAR with RUC 1 hr forecast Bias Temperature ( o C) Standard Deviation Source statistical data provided by Bill Moninger - FSL WMO Temperature Requirements for Regional NWP (RMS) o C, Minimum Acceptable 3.0 o C Data from Mid-January - Mid-March 2005

Comparison of TAMDAR and non-TAMDAR with RUC 1 hr forecast Bias Speed (m s -1 ) Standard Deviation Source statistical data provided by Bill Moninger - FSL WMO Wind Requirements for Regional NWP (RMS) - 1 m s -1, Minimum Acceptable 5 m s -1 Data from Mid-January - Mid-March 2005

Comparison of TAMDAR and non-TAMDAR with RUC 1 hr forecast Bias Relative Humidity (%) Standard Deviation Source statistical data provided by Bill Moninger - FSL WMO Moisture Requirements for Regional NWP (RMS) - 5%, Minimum Acceptable 20% Data from Mid-January - Mid-March 2005

Summary of Comparison of TAMDAR and non-TAMDAR with RUC 1 hr forecast Evaluations performed between TAMDAR and all other aircraft - Need to separate reports from similar parts of atmosphere - Need to view in combination with Rawinsonde Co-Locations - Need to have more Q/C information - WMO criteria used here to exclude outliers - May have been too conservative Two data sets show notably different characteristics - Temperature - More TAMDAR outliers (> WMO Specs) and different (cold) bias - Wind - More TAMDAR outliers and Bias ( 3x ) and Standard Deviation larger - Moisture - No WVSS-II comparison made yet - Bias increases as RH increases - RMS near WMO limits (careful since we are comparing to model forecast/analysis) Issue – Who will manage, maintain and distribute TAMDAR Q/C info? - Currently, WMO requires NWS to do this for other aircraft data.