terminal / transitional en route convective weather forecast … · 2004. 8. 4. · ncwf (4 km)...

MIT Lincoln LaboratoryJEE/000028- 1

jee 5/26/00

Terminal / Transitional En Route ConvectiveWeather Forecast

(TCWF)

Marilyn Wolfson

MIT Lincoln Laboratory

(presented by Jim Evans)


jee 5/26/00

Outline

• User needs

• Weather phenomenology

– Cells

– Organized systems

• TCWF

– Methodology

– Scoring / Little Rock example

– Current Status

• Current research

• Summary


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Summary of User Needs and Current Capabilities

Not Needed or Not SuitableHighly Desired

Suitable, Though Less Highly Desired Most Highly Desired, When Available

Users

Terminal ATCSupervisors, CTAS,TMCs, Pilots, FSS

Terminal(TRACON)

SpatialExtent

Forecast Lead Time Accuracy

Regional(ARTCC)

National

Automation systems,TMUs, CWSUs,

Pilots, FSS

Airline DispatchersCommand Center

Pilots, FSS

50 nm

100-200 nm

>200 nm

0.5 - 1 hr 1 - 2 hr 2 - 6+ hr >30 - 50% >50 - 70% >70 - 90%

TCWF 1-hr 0.5-hr

TCWFNCWF

1-hr

NCWF 1-hr

0.5-hr

CCFP


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April 16, 2000 - New York Delay Case

Fo

reca

st A

ccu

racy

Mesoscale model(POP)

Expert system

Extrapolation

Forecast Period (hrs)1 2 3 4 5 6

Modified from Browning, 1980

Local explicit cloud model

Qualitative Assessment ofForecast AccuracyConvective precipitation for

spatial scale of a few kilometers

CCFP (twice a day)Expert system = ForecasterForecast area >> Storm area

Tactical StrategicTRACON ARTCC National

FY02-03 Automated Products - Demonstration (5-10 min update)Forecast Area = Storm Area

Automated Products (5-10 min update)TCWF (1km) and NCWF (4 km)Forecast Area = Storm Area

Forecaster Products (60 min update)Convective SIGMETForecast Area > Storm Area


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Models of Convective Weather

0 5 10 15 20 25 30 35

12

9

6

3

Hei

gh

t (km

)

Time (min)

0 10 20 km"Dissipating""Mature""Cumulus"

14

12

10

8

6

4

20 –18 –16 –14 –12 –10 –8 –6 –4 –2 0 2 4 6

Distance Ahead of Outflow Boundary (km)

Storm Motion –40°C

–20°C

–0°C

SN

Hei

ght

(km

)

Model of Storm TypeAppearance in

Radar Data Storm Life Cycle

Time

Wat

er C

on

ten

t

0 10 20 30 min

Time

Wat

er C

on

ten

t

0 2 4 6 8 hr

Multi-cell or “Line” Storms

Isolated or “Airmass” Storms

• Diurnal forcing• Short-lived• Largely disorganized

• Large scale forcing• Long-lived• Highly organized


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ITWS Storm Cell Information


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ITWS Storm Motion and ExtrapolatedPosition Products

• Storm Motion

– Black arrow indicatingdirection and numeralindicating speed in knots

• Storm Extrapolated Position

– blue solid line for currentposition and blue dashed linesindicating position in minutes

• Products computed fromunderlying precipitationproduct; one for eachprecipitation product


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Terminal/Transitional En Route Forecast Algorithm Architecture

Radar data Scale separation

Track vectors Product display

Real-timeScoring

NEXRAD radar


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Terminal/Transitional En RouteConvective Weather Forecast Product

-30 -20 -10 CurrentWeather

+10+20

+30+40

+50

+60 min Forecast

Key features:Real time scoring of past performanceUpdates every 5-6 minutesUses NEXRAD dataSuccessful operational use at Dallas,Orlando, New York in 1998-99

Technology development funded by FAA AviationWeather Research Program (AWR)


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Scoring Forecast Performance

• Users require +/- 5 nm accuracy for 1-hour forecast

- Compare forecast with truth in 5x5 neighborhood- False pixel is “hit” if truth pixel found- Miss pixel is “hit” if forecast pixel found


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CSI Scoring Metric

RedFalseAlarm

GreenHit

BlueMiss

Dashed rectangle: Forecast StormSolid rectangle: Actual Storm

Probability of detection (POD) = HitsHits + Misses

Probability of false alarm (PFA) = False alarmsHits + False Alarms

HitsHits + Misses + False AlarmsCritical Success Index (CSI) =

EXAMPLE

50 misses250 hits50 false alarms

POD = 83%PFA = 17%

CSI = 71%

CSI gives credit forhits and penalizesboth misses andfalse alarms in onestatistic.

CSI is just like PODbut with penalty forfalse alarms in denominator.


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30-min Binary Forecast Performance6-level Precip

11:52 local time

Convective Forecast PerformanceFor Little Rock Accident - 6/1/99


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Convective Forecast PerformanceFor Little Rock Accident - 6/1/99

60-min Binary Forecast Performance6-level Precip

11:52 local time


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2 June 99 Forecast Performance


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Terminal Convective Weather Forecast

• Algorithm redesign based on ‘99 Orlando tests

– 1 km resolution for all calculations (was 4 km)

– 2 km resolution for 200 nm product (was 4 km)

– 1 km scoring to match previous 4-km “user” scoring

– Separate scores for TRACON and 200 nm products

Dallas

MemphisNew York *

Orlando

* Funded by Port Authority of NY & NJ

24 March 00

29 April 00

8 May 00

26 April 00


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New TCWF Display

• Integrated with ITWS Situation Display• Allows full pan/zoom/overlay capability for TCWF

TCWFITWS

Air Traffic Users

TCWF

ITWS

Other Dedicated Users

TCWF

Web Users

• TRACONs

– MEM

– DFW

– MCO

– NYC

• ARTCC TMUs

and CWSUs

– ZME

– ZFW

– ZJX

– ZNY

– Command Center– Northwest– NW Airlink– FedEx– American– American Eagle– Delta– United– Southwest– FAA Tech Center

– CDM-Net

– Airlines

– Sponsors

– Researchers


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Improving TCWF Forecasts

• TCWF (and NCWF) only extrapolate

• Need explicit growth and decay for:

– line storm growth and decay phases

– airmass storms

• Extend lead time (w/ accuracy) to 2 hrs

TimeW

ater

Co

nte

nt

0 10 20 30 min

Useful 30 min forecasts

Isolated or “Airmass” Storms

Time

Wat

er C

on

ten

t

0 2 4 6 8 hr

Good 60min forecasts in “steady” stage

Multi-cell or “Line” Storms


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Convective Weather PDT Research Priorities

Enroute Airspace

TRACON

2

3

6

41

5

2. New growth on runways3. “Pop-ups” at arrival gate

6. “Pop-ups” enroute

4. Organized air mass storm

1. Line storm (width, length, and tops)

5. Gap in line

Terminal(TRACON)0.5-1 hour

Regional(ARTCC)1-2 hours

National2-6 hours

Storm Type

Moderate 4Hard

Near Impossible

Very Hard Hard

Very Hard

Air Mass Storms Organized Storms

Low Priority

High Priority

Medium Priority


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Meteorology of Storm Evolution

Large-scale (synoptic) environment– Stability– Vertical wind shear– Mid-level moisture– Large-scale forcing (winds)

Boundary Layer Structure– Convergence line position– Strength of the convergence– Low-level shear– Stability

Cloud Characteristics– Type– Growth

Storm Characteristics– Position– Growth rate – storm structure– Storm merger– Storm boundary interaction


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Current Science Initiatives

• Large-scale Environment– RUC2, satellite and radar

• Boundary Layer Structure– Advanced gust front detection (MIGFA)– VDRAS– ITWS terminal winds (uses multiple Doppler analyses)

• Cloud Characteristics

– Integration of satellite and radar data for cloud type and growth -important for moisture and stability

• Storm Characteristics– Tracking - Done– Probablistic Growth and Decay– Storm merger and boundary-storm merger interest fields

• Explicit forecasting– Numerical models– Expert systems


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Satellite Cloud Growth Detection

2153 2210 2222 2233

Radar

Visible

Cloud IR

Dallas/Ft.Worth TRACON - June 4, 1998


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Performance Comparison

TCWF TCWF + radar/satellite growth


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Summary

• Need forecasts of convective cells and storm systems forautomation and traffic flow management

• TCWF is a major advance in “tactical” TFM

– Rapid updates with high spatial and time resolution

– Scoring so user has sense for uncertainty in weatherpredictability in that area at that time

• Research underway to predict new growth in areas with nosignificant radar returns and, storm dissipation

– Satellite data will be very important

– Dense sensor coverage (especially Doppler radar) in and nearmajor terminals will be a major asset in improvingperformance

• ATM system designers will need to account for substantiveuncertainty in exact locations of future significant weather

terminal / transitional en route convective weather forecast … · 2004. 8. 4. · ncwf (4 km)...

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