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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

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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

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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.

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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

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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.

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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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Content of ACARS Reports

TimeLatitute / LongitudeFlight levelTemperatureWind speed / direction

Future Additions

Water vapor - Water Vapor Sensing System (WVSS)Turbulence

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Accuracy of ACARS Reports

Temperature RMS observation error < 0.5oCWind RMS vector wind error < 3 m s-1

Error rates: < 0.5% of all reports in 19891-2% in 1994(30% error rate for voice reports)

Frequency of ACARS Reports

Cruise: ~ every 7½ minAscent/descent: ~ every 2000 ft (notfixed)Number of participating aircraft:500-600

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Nominal contribution of different airlines to the total daily number of ACARS reports

American 11%

Delta 23%

Federal Express 4%

Northwest 7%

United 26%

United Parcel Service 29%

(for 17 June 1998)

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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.

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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.

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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.

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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

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Near-Infrared Laser Diode

(Indium, Galium, Arsenic, Phosphorus

Absorption Spectroscopy

The transmission of light through an absorbing gas is described by

I = Io exp (- nl)

I = intensity at the detector

Io = 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

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Requirements for detecting 1% RH at 40,000 ft

p = 187 mb T = 225 K rsat = 2.5 x 10-4 r1%RH = 2.5 x 10-6

where r is the mixing ratio in grams of water vapor per gram of dry air.

Let rmol = ratio of number of water vapor molecules to number of dry air molecules.

rmol = (29/18) r1%RH = 4 x 10-6

Ideal gas law: p = nkTwhere p = pressure (Pascals Newton m-2)

n = number density of moleculesT = temperature (Kelvin)

n = p/(kT) = 1.87 x 104 [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 1024 molecules m-3 ~ 6 x 1018 molecules cm-3 (number density of air)Courtesy of Rex Fleming

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Requirements for detecting 1% RH at 40,000 ft(continued)

Therefore n (H2O) = (4 x 10-6 fraction of molecules that are H2O) (6 x 1018 air molecules cm-3)

n (H2O) = 24 x 1012 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 / Io = 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

cm2 molecule-1. We can solve for the path length (to estimate the size of theinstrument) by means of

ln (I / Io) = – nl ln (0.99999) = – (1.8 x 10-19) (24 x 1012) 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

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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

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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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V E R T IC A LE A S T

R a d a r B e a m s

Equipment Shelter

GPS Water VaporAntennafor PWV

Profiler SurfaceObserving

System(PSOS)

Wind Profiler Radar Antenna

RASS TemperatureSounder

7 .5 0 k m

1 6 .2 5 k m

L O WM O D E

H e ig h tR e s o l u t i o n

3 2 0 m

H e ig h tR e s o l u t i o n

9 0 0 m

H IG HM O D E

N O R T H

9 .2 5 k m

7 .5 0 k m

0 .5 0 k m

H e ig h t s M e a s u r e d

NOAA Profiler Network (NPN) Site Sketch

V E R T IC A LE A S T

R a d a r B e a m s

Equipment Shelter

GPS Water VaporAntennafor PWV

Profiler SurfaceObserving

System(PSOS)

Wind Profiler Radar Antenna

RASS TemperatureSounder

7 .5 0 k m

1 6 .2 5 k m

L O WM O D E

H e ig h tR e s o l u t i o n

3 2 0 m

H e ig h tR e s o l u t i o n

9 0 0 m

H IG HM O D E

N O R T H

9 .2 5 k m

7 .5 0 k m

0 .5 0 k m

H e ig h t s M e a s u r e d

NOAA Profiler Network (NPN) Site Sketch

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Vandenberg

Jayton

Medicine Bow

Platteville

Vandenberg

Jayton

Medicine Bow

Platteville

Haskell

Neodesha

Lathrop

Bloomfield

Merriman

McCook Fairbury

Wood Lake

Blue River

Winchester

DeQueenOkolona

Winnfield

ProfilerControl Center

Aztec

Tucumcari

White Sands

Granada

Vici

Haviland

Hillsboro

Lamont

SlaterNeligh

Conway

Purcell

Palestine

Syracuse

NOAA Profiler Network

Talkeetna Glennallen

Central

Wolcott

404 MHz Profiler

449 MHz Profiler

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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 Tv through

c = ( Rtv)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.

Tv = (c / 20.047) 2

when c is in m s-1 and Tv is in degrees K.

24126 127 128 129 130

1.00

2.00

3.00

4.00

5.00

GPS SatelliteConstellation

Water Vapor Observations

DataProcessing

Network of GPS Surface

Observing Systems

MeteorologicalInstruments

Receiver

Antenna

ImprovedMesoscaleForecasts

ImprovedNavigation &Positioning

SatelliteCAL/VAL

How Does GPS-IPW Work?

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115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130Julian D ay (1995)

0.00

1.00

2.00

3.00

4.00

5.00P

WV

(cm

)

0.00 1.00 2.00 3.00 4.00 5.00R aw insonde PW V (cm )

0.00

1.00

2.00

3.00

4.00

5.00

UH

/SIO

Rap

id O

rbit

PW

V (

cm)

r = 0 .984

0.00 1.00 2.00 3.00 4.00 5.00R adiom eter P W V (cm )

0.00

1.00

2.00

3.00

4.00

5.00

UH

/SIO

Rap

id O

rbit

PW

V (

cm)

r = 0 .981

RAOBSGPSWVR

Typical Water Vapor ComparisonsLamont, OK

26265 266 267 268 269 270 271 272

D ay of Year (1997)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0In

tegr

ated

Pre

cipi

tabl

e W

ater

Vap

or (

cm)

Thunderstorm

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NOAA GPS-IPW Demonstration NetworkSEAW

HKLO

NDSK

DQUA

WSMN

GDAC

VCIO

HVLK

HBRK

PRCO

WES2

AOML

KYW1

EKY1

MOB1ENG1

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

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NOAA GPS-IPW (INSTALLED) 21NOAA GPS-IPW (SCHEDULED) 19

DOT NDGPS (SCHEDULED) 66

USCG DGPS (INSTALLED) 11USCG DGPS (PENDIING) 54USCG LORAN (TENTATIVE) 20

GPS-IPW Demonstration NetworkPotential Coverage in 3-5 Years ~ 200 Stations

29-106 -104 -102 -100 -98 -96 -94 -92 -90

-106 -104 -102 -100 -98 -96 -94 -92 -90

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40

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40

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D Q U A

G D AC

H B R K

H K LO

H V LK

JTN T

LM N O

N D BC

N D SK

PA TT

PLTC

PR C O

VC IO

W N FL

W S M N

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

2.6

2.8

3.0

3.2

3.4

3.6

3.8

4.0

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

2.6

2.8

3.0

3.2

3.4

3.6

3.8

4.0

K S

O K

TX

C O

N E

-104 -102 -100 -98 -96 -94

LO N G ITU D E

-104 -102 -100 -98 -96 -94

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40

LAT

ITU

DE

3 2

3 4

3 6

3 8

4 0

K S

O K

T X

C O

N E

G P S O n l y G P S + G O E S 8

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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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

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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.

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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.

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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 site4) Average number of points in aircraft "slant” sounding5) Impact of deletions on overall uniformity of rawinsonde distribution

6) Don't touch GCOS sites.

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Match-upsRaob Airport # Ascents and

Descents / week

Salem OR Portland ~100

Oakland CA San Francisco >500

Desert Rock NV Las Vegas >100

Salt Lake City UT Salt Lake City 50-80

Santa Teresa NM White Sands profiler

Denver CO DIA ~500

Fort Worth TX Dallas/Fort Worth ~ 80

Topeka KS Kansas City (MCI) 40-70

Chanhaussen MN Minneapolis (MSP) ~ 20

Buffalo NY Toronto 25-30

Peachtree City GA Atlanta ~ 50

Slidell LA New Orleans ~ 75

Miami FL Miami (MIA) ~ 65

Upton NY New York City (JFK) >150

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Test Status for Hypothesis 1May 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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