1. 1 NEW OBSERVING SYSTEMS, NAOS, AND TARGETED OBSERVATIONS Presentation at the COMAP Symposium on Numerical Weather Prediction, NCAR, Boulder, CO 17-21 May 1999 by Tom Schlatter NOAA Forecast Systems Laboratory

2. 2 OUTLINE How does this talk relate to NWP? What observations are only recently being assimilated into operational U.S. models? What you need to know about automated aircraft reports and profiler data with regard to NWP and nowcasting in the WFO The North American Atmospheric Observing System (NAOS) program - What problems does it tackle? Targeted observations

3. 3 How does this talk relate to NWP? Observations feed prediction models. For short forecasts, accuracy of initial state is more of an issue than realism of model. Observations used to gauge accuracy of evolving forecast, to formulate the nowcast (30-90 minute extrapolation). ACARS and profiler observations, separately and together, have led to improvements in tropospheric predictions of temperature and wind. New products from these sources can also help you improve your nowcast. NAOS strives to put logic behind the proliferation of observing systems. What observing strategies are best for NWP? Targeted observations: put them where they make the most difference in downstream forecast accuracy.

4. 4 What observations are only recently being assimilated into operational U.S. models? Note: Listed data sources are being assimilated into at least one of these three NCEP models: global spectral, Eta, and RUC-2. VAD winds from WSR-88D raw radiances from NOAA satellites precipitable water vapor estimates from GOES and NOAA satellites scatterometer data (to infer winds at sea surface) ACARS en route and ascent/descent data boundary-layer profilers of opportunity Radio Acoustic Sounding System high density cloud-drift winds from GOES

5. 5 Coming Soon raw radiances from GOES satellite radial winds from WSR-88D water vapor drift winds from GOES precipitable water vapor estimates from GPS receivers on the ground This lecture focuses on those observation sources highlighted in red.

6. 6 What’s new with ACARS? More reports More airlines participating in data collection Increasing percentage of ascent / descent reports Web page available to WFOs Water Vapor Sensing System

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9. 9 Nominal contribution of different airlines to the total daily number of ACARS reports American11% Delta 23% Federal Express 4% Northwest 7% United26% United Parcel Service29% (for 17 June 1998)

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12. 12 Water Vapor Sensing System (WVSS) Status Report as of May 1999 WVSS refers to a water vapor sensor installed on commercial aircraft that delivers relative humidity values along with wind and temperature as part of the ACARS/MDCRS report.

13. 13 Progress As of January 1999, 104 aircraft-weeks of WVSS reports (~190,000) had been collected. Two different aircraft obtained the measurements. With careful calibration, the WVSS delivers good humidity information under a wide variety of conditions, including in the high troposphere. Errors range from ~4% in mid-troposphere at low Mach numbers to ~17% in the high, cold troposphere at high Mach numbers. 5 UPS aircraft now equipped with WVSS NOAA owns 60 total systems; within ~12 months, about half should be installed on UPS and the other half on American jets.

14. 14 Problems UPS has been very slow to add new sensors to its fleet. Other airlines have expressed interest but have not yet agreed to install the sensors on their aircraft. Some airlines prefer a single probe for temperature and humidity rather than two separate probes, as is the case now. This is prompting a redesign of the WVSS and requires new FAA approval--a lengthy process.

15. 15 Three methods of measuring moisture by aircraft are viable today: Thin-film capacitor (polymer) Chilled mirror Near-infrared laser diode Fast response time is critical. Best bet: near-infrared laser diode

16. 16 Near-Infrared Laser Diode (Indium, Galium, Arsenic, Phosphorus Absorption Spectroscopy The transmission of light through an absorbing gas is described by I = I o exp (-  nl) I = intensity at the detector I o = initial intensity  = molecular absorption cross section (depends upon wavelength, temperature and pressure) n = number density of absorbing species l = optical path length Courtesy of Rex Fleming

17. 17 Requirements for detecting 1% RH at 40,000 ft p = 187 mb T = 225 K r sat = 2.5 x 10 -4 r 1%RH = 2.5 x 10 -6 where r is the mixing ratio in grams of water vapor per gram of dry air. Let r mol = ratio of number of water vapor molecules to number of dry air molecules. r mol = (29/18) r 1%RH = 4 x 10 -6 Ideal gas law:p = nkT where p = pressure (Pascals  Newton m -2 ) n = number density of molecules T = temperature (Kelvin) n = p/(kT) = 1.87 x 10 4 [Newton m -2 ] 1.38 x 10 -23 [J molecule -1 K -1 ] 225 [K] Noting that a Joule [J] is a Newton meter, we obtain n = 6.02 x 10 24 molecules m -3 ~ 6 x 10 18 molecules cm -3 (number density of air) Courtesy of Rex Fleming

18. 18 Requirements for detecting 1% RH at 40,000 ft (continued) Thereforen (H 2 O) = (4 x 10 -6 fraction of molecules that are H 2 O)  (6 x 10 18 air molecules cm -3 ) n (H 2 O) = 24 x 10 12 molecules cm -3 Detectors can be built that are sensitive to tiny depletions in the initial intensity, that is, to one part in 10 -5. Thus an intensity ratio I / I o = 0.99999 is measurable. The laser diode in question operates at a wavelength of 1.36  m (near infrared). At this wavelength, the absorption cross section for water vapor is  = 1.8 x 10 -19 cm 2 molecule -1. We can solve for the path length (to estimate the size of the instrument) by means of ln (I / I o ) = –  nl ln (0.99999) = – (1.8 x 10 -19 ) (24 x 10 12 ) l l = 10 -5 / (4.32 x 10 -6 ) l ~ 2.3 cm path length Conclusion: The instrument can be small! Courtesy of Rex Fleming

19. 19 ACARS real-time data, including ascent/descent soundings http://acweb.fsl.noaa.gov/oper/ Access restricted. If you work in a WFO, you should be able to reach this page. If you have trouble, contact Bill Moninger at moninger@fsl.noaa.gov or (303) 497-6435

20. 20 What’s new in atmospheric profiling? Potential of 6-min data Potential to infer vertical gradient of mixing ratio Loss of frequency allocation for NOAA Network Boundary-layer profiler data and RASS data available on the Web Processing GPS signals to obtain total precipitable water

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23. 23 The Radio Acoustic Sounding System (RASS) Operates in conjunction with a wind profiling radar Sound waves emitted upward from the ground When the acoustic frequency of the sound waves is just right, the profiler can sense the velocity of the sound wavesw as a function of height. The speed of sound c is related to the virtual temperature T v through c = (  Rt v ) 1/2 where  is the ratio of specific heat at constant pressure to that at constant volume for dry air, and R is the gas constant for dry air. T v = (c / 20.047) 2 when c is in m s -1 and T v is in degrees K.

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27. 27 NOAA GPS-IPW Demonstration Network SEAW HKLO NDSK DQUA WSMN GDAC VCIO HVLK HBRK PRCO WES2 AOML KYW1 EKY1 MOB1 ENG1 GAL1 ARP3 NDBC PLTC JTNT PATT CCV3 WNFL SIO3 TCUN MNP1 SHK1 900 km LMNO CHA1 FMC2 WLCI SYCN OPERATING NOAA (FSL & NGS) GPS-IPW SITES OPERATING DGPS SITES w/ GSOS EXPLANATION SCHEDULED FSL GPS-IPW SITES CENA TLKA GNAA

28. 28 DOT NDGPS (SCHEDULED)66 USCG DGPS (INSTALLED)11 USCG DGPS (PENDIING)54 USCG LORAN (TENTATIVE)20

29. 29 Addition of Calibrated GOES-8 TPW Improves the Spatial Resolution of GPS-only IPW Data. 5 NOV 1997 1500 UTC NCAR_IPWPPT

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31. 31 Web Address For comprehensive information about: NOAA Network Profilers and RASS Boundary-layer profilers Surface-based estimates of total precipitable water vapor from GPS Go to: http://www-dd.fsl.noaa.gov/profiler.html

32. 32 Introduction to NAOS NAOS - North American Atmospheric Observing System Program to make recommendations on the configuration of the upper air observing systems over North America and adjacent water areas NAOS Council has representatives from 15 agencies in U.S., Canada, and Mexico to identify issues, set priorities, coordinate work of the program, and seek financial support NAOS Test and Evaluation Working Group –Assesses potential effects of proposed observing systems and configurations on the overall efficacy of forecasting services. –Assessments involve tests of hypotheses concerning the sensitivity of forecast accuracy to specific mixes of observing systems. –Assessments must also consider utility of data to field forecasters, who use them subjectively, and to the climate community.

33. 33 Hypothesis 1 It will be possible to reduce the number of rawinsondes in the U.S. network without noticeably reducing forecast accuracy provided that the sites removed have substitute observing systems already in place. Test in two steps: Identify rawinsonde sites close to busy hub airports. At these sites withhold rawinsonde and all potential substitute observations for the periods covered by the sensitivity test. Compare forecasts generated from reduced data set with operational forecasts. Restore all substitute observations but continue to withhold rawinsondes. Compare these forecasts with operational forecasts.

34. 34 Selection criteria for matching raob sites and hub airports 1) Average number of ascents or descents per day (fewer on weekends) 2) Distance from the airport to the raob site 3) Expected similarity in climate between the airport and raob site 4) Average number of points in aircraft "slant” sounding 5) Impact of deletions on overall uniformity of rawinsonde distribution 6) Don't touch GCOS sites.

35. 35 Match-ups RaobAirport# Ascents and Descents / week Salem ORPortland~100 Oakland CASan Francisco>500 Desert Rock NVLas Vegas>100 Salt Lake City UTSalt Lake City50-80 Santa Teresa NMWhite Sandsprofiler Denver CODIA~500 Fort Worth TXDallas/Fort Worth~ 80 Topeka KSKansas City(MCI)40-70 Chanhaussen MNMinneapolis (MSP)~ 20 Buffalo NYToronto25-30 Peachtree City GAAtlanta~ 50 Slidell LANew Orleans~ 75 Miami FLMiami (MIA)~ 65 Upton NYNew York City (JFK)>150

36. 36 Test Status for Hypothesis 1 May 1999 NASA has donated computer time on its 32- processor Cray J-90. Wintertime tests (late Dec 97 until mid-Feb 98) have been completed on the J-90 computer with NCEP’s global spectral model and Eta model. Tests with the RUC-2 model are in progress.

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