prepared by ncar auto-nowcaster prepared for the wmo nowcasting workshop in conjunction with the...

Prepared by

NCAR Auto-nowcaster

Prepared for the WMO Nowcasting Workshop

in conjunction with the

World Weather Research Program

Sydney 2000 Field Demonstration

Program

30 Oct. -10 Nov.

Jim Wilson, Rita Roberts, Cindy Muellerand Tom Saxen

National Center for Atmospheric ResearchBoulder, Colorado, USA

• Science of Nowcasting Thunderstorms

•NCAR Thunderstorm Auto-nowcaster

• Auto-nowcaster Example for 22 September 1999 from Sydney

Workshop Outline

The material is divided into three sections:

Science of Nowcasting Thunderstorms

• Thunderstorm Lifetime, Evolution and Characteristics • Boundary Influences on Thunderstorm Evolution• Stability Influences on Thunderstorm Evolution• Forecast Parameters

The following are discussed:


• Thunderstorm Lifetime, Evolution and Characteristics

Thunderstorm Lifetime, Evolution and Characteristics

Single cell storms live < 30 min

Thunderstorm Lifetime

Single cell storms live < 30 min Multi-cell storm systems live > 30 min

(Henry 1993; Battan 1953; Foote and Mohr 1979)


Conve

ctiv

e St

orm

Sys

tem

Sing

le-c

ell T

hund

ersto

rm

TIME (hr)

SIZ

E

1 2 3 4 5

There are frequent and rapid changes in storm size and intensity.

Example Evolution of a Single Cell and a Convective Systems


Thunderstorm Characteristics:

Radar can provide time trends of thunderstorm movement, size, height,intensity, height of the rain mass centroid, and vertically integratedliquid water equivalent.

Beyond ~ 15 min these parametersby themselves are of only limitedforecast value. This is becausephysical processes that dictate changes in storms are not necessarily observable in the pasthistory of the storm but are oftendriven by boundary layer eventssuch as convergence and stability.

(Tsonis and Austin 1981, Bellon and Austin1978, Browning et al. 1982, Collier 1989)


The vast majority of storms have short lifetimes and/or frequent rapid changes in storm intensity and size thus - forecasts by extrapolation alone are generally insufficient. Need to forecast initiation, growth and dissipation. Mature supercells and large squall lines are often exceptions. Extrapolation alone for these systems is often sufficient for periods up to at least 2 hr.


Adapted from Browning (1980),Doswell (1986) and Austin et al. (1987)

Accuracy of Time and Place Specific Forecasts of Convective Storms

As can be seen in the figureto the left the accuracy of the forecasts decreases very rapidly during the first hour. Large scale numerical models can not even makeforecasts on this short timescale. Forecasts with explicit storm numericalmethods are in their infancy.The approach used here is an expert system which is based on the heavy use of observations and theory.


• Thunderstorm Lifetime, Evolution and Characteristics • Boundary Influences on Thunderstorm Evolution

Boundary Influences on Thunderstorm Evolution

1. Satellite cloud imagery.Note the N-S line ofcumulus associated witha sea breeze along theFlorida east coast.

Boundary layer convergence lines (boundaries) frequently influence the evolution of thunderstorms. These boundaries can often be observed in:

2. Clear-air radar features.Note enhanced N-S lineof reflectivity associated with a boundary. Redarrows are wind directionfrom surface stations.


• Example of Storm Initiation Behind a Moving Boundary

This first picture shows convergingwinds in the Doppler velocity data.Brown and red colors representvelocities away from the radar whilegreens are towards.

The following time lapse pictures areradar reflectivity. Note the storminitiation as the boundary movessoutheast (click once).


Thunderstorm initiationFrequently occurs nearboundary layerconvergence lines.

Thunderstorm Initiation Locations

(Purdom 1973, 1976 1982; Wilson and Schreiber 1986)

The figure to the right shows theinitiation of thunderstorms relative to boundaries for a summer in Colorado. 80% of the storms initiated in close proximity to a boundary. This region is referred to as the liftingzone.


~20 km

lifting zone

~10 km

The lifting zone is the most likely region for storm initiation and storm growth. It is positionedabout the boundary based on theboundary speed of movement.

(Wilson and Mueller 1993)


• Colliding Boundaries Often Initiate Intense Storms

Colliding boundaries are frequentlyresponsible for storm initiation andsignificant increase in the intensityand size of existing storms.

Cross-sections to the right show alarge increase in vertical velocity(3 m/s to 12 m/s) as twoboundaries (red lines) collide.

(Mahoney 1988)

Storm Initiation often follows a boundary intercepting Cumulus clouds


In the radar images to theright an east-west orientedgust front is moving southintercepting a north-southhorizontal convective roll.The cumulus clouds along the roll grow into thunderstorms once thegust front passes under them.

Wilson and Mueller 1993


Storm merger and intensification frequently follows aboundary intercepting existing storms.

Note in the images tothe right the merger and growth of thestorms in advance ofthe gust front (represented by thered line) as they are intercepted by thegust front (toggleforward and back).

Boundary Influences on Thunderstorm EvolutionBoundary Characteristics That Influence Storm Evolution

• Boundary Relative Cell Speed (Ub)

(Moncrieff and Miller 1976, Weisman and Klemp 1986, Wilson and Megenhardt 1997)

cell velocity

boundaryvelocity

cell velocity

Boundary velocity

Ub large

Ub is the rate at which a cell ismoving away from a boundary.For values >~4 m/s the storm will move away from the boundary and likely dissipate. For smallervalues the storm will remain nearthe boundary and likely live.

Ub near zero


• Low-level Shear Relative to Boundary

(Thorpe et al. 1982, Rotunno et al., 1988, Weisman and Klemp 1986)

The low-level shear is the vector difference, normal to the boundary,of the surface wind minus the 2.5 km wind. It can vary considerable along the boundary.

This parameter is indicative of howtilted the updrafts will be. Values< -8 m/s favor erect updraftsand thus more intense and longlived storms.


• Convergence Magnitude and Depth

Obviously strong low-levelconvergence and deep updraftshave greater potential for developing intense thunderstorms.

(Sun and Crook 1994, 1997)

The picture to the right shows anexample of wind vectors and convergence magnitude at a heightof 200 m as retrieved from singleDoppler radar. The yellow line isthe position of a gust front. The yellows and reds represent the strongest convergence.


• Thunderstorm Nowcasting Requires Close Monitoring of Boundaries, Storms and Clouds to Anticipate When They Will Intercept Each Other


• Thunderstorm Lifetime, Evolution and Characteristics • Boundary Influences on Thunderstorm Evolution• Stability Influences on Thunderstorm Evolution

Stability Influences on Thunderstorm Evolution

Static Stability is a Critical Parameter for ForecastingThunderstorms.

Unfortunately they are widelyspaced and observations are infrequent thus of limited use for thunderstorm nowcasting purposes.

Traditionally radiosondes areused to measure stability.

Stability Influences on Thunderstorm EvolutionSoundings are of limited use for thunderstorm nowcasting

because of small-scale variability in water vapor.Convergence lines modify the water vapor field

In this example threesimultaneous soundingsshow there are largevariations in the convective availablepotential energy (orange area) overshort distances in thevicinity of a convergence line.

Wilson et al., 1992

Stability Influences on Thunderstorm EvolutionSoundings are of limited use for thunderstorm nowcasting

because of small-scale variability in water vapor.

Horizontal Convective Rolls modify the water vapor field

Weckwerth et al, 1996

The highest moisture istypically in the updraftportion of horizontalconvective rolls. Thus ifthe sounding does not goup in the updraft thepotential for thunderstormsis likely underestimated.

Stability Influences on Thunderstorm EvolutionSatellite Cloud Imagery Used to Monitor Stability

The presence of cumulus cloudsindicates instability although of unknown magnitude and depth. The use of satellite visible and

infrared imagery to monitor thelocation and development ofcumulus clouds serves as a useful proxy for stability.

Stability Influences on Thunderstorm Evolution

The picture to the right is a radarestimated rainfall accumulationfield for the past hour. Thiscan be used as an indicator of where rain may have caused localcooling. Thus this area may bemore stable and less likely tosupport further convection. Thisfield is more useful in weaklyforced synoptic situations whereboundary layer instability playsa primary role.

Accumulated Precipitation Field Used to Monitor Stability


• Thunderstorm Lifetime, Evolution and Characteristics • Boundary Influences on Thunderstorm Evolution• Stability Influences on Thunderstorm Evolution• Forecast Parameters

Forecast Parameters

Factors Associated With Storm Initiation:• Presence of convergence line (Boundary)• Lifted index < 0 in lifting zone• Cu in lifting zone• Rapid growth of Cu in lifting zone• Colliding boundaries• Low boundary relative cell speeds

Based on our present knowledge of storm evolution the followingparameters are used to forecast storm initiation, growth and dissipation.

Forecast Parameters

Factors Associated With Storm Growth:• Boundary motion = storm motion• Convergence strong and deep• Erect updrafts• Merging of storms• Boundary intercepting cumulus and storms

Forecast Parameters

Factors Associated With Storm Dissipation:• Boundary moving away from storms • Boundary moving into a stable region• Storm decreasing in size and intensity and no boundary present

ReferencesAustin G. L., A. Bellon, P. Dionne and M. Roch, 1987: On the interaction between radar and satellite image nowcasting systems and mesoscale numerical models. Proceedings, Mesoscale Analysis & Forecasting, European Space Agency SP-282, Vancover, Canada, 225-228.

Battan, L. J., 1953: Duration of convective radar cloud units, Bull. Amer. Meteor. Soc., 34, 227- 228.

Bellon, A., and G. L. Austin, 1978: The evaluation of two years of real time operation of a short- term precipitation forecasting procedure (SHARP), J. Appl. Meteor., 17, 1778-1787.

Browning, K. A., 1980: Local weather forecasting, Proc. R. Soc. London Ser., A371, 179-211.

Browning, K. A., C. G Collier, P.R. Larke, P. Menmuir, G. A. Monk, and R. G. Owens, 1982: On the

forecasting of frontal rain using a weather radar network. Mon. Wea. Rev., 110, 534-552.

Collier, C.G., 1989: Applications of Weather Radar Systems, Wiley and Sons, 294 pp.

Doswell,C.A., 1986: Short-range forecasting. Mesoscale Meteorology and Forecasting, P.Ray, Ed. Amer. Meteor. Soc., Boston, 793 pp.

Foote, G. B., and C. G. Mohr, 1979: Results of a randomized hail suppression experiment in northeast Colorado. Part VI: Post hoc stratification by storm type and intensity. J. Appl. Meteor., 18, 1589-1600.

ReferencesHenry, S. G., 1993: Analysis of thunderstorm lifetime as a function of size and intensity. Preprints. 26th Conference on Radar Meteorology, Norman OK, Amer. Meteor. Soc., 138-140.

Mahoney, W.P. III, 1988: Gust front characteristics and the kinematics associated with interacting thunderstorm outflows, Mon. Wea. Rev, 116, 1474-1491.

Mueller, C.K., and J.W. Wilson, 1989: Evaluation of the TDWR nowcasting experiment. Preprints, 24th Conf. on Radar Meteorology, Tallahassee, Amer. Meteor. Soc., Boston, 224-227.

Moncrieff, M.W., and M.J. Miller, 1976: The dynamics and simulation of tropical cumulonimbus and squall lines. Quart. J. Roy. Meteor. Soc., 102, 373-394.

Purdom J.F.W., 1973: Satellite imagery and the mesoscale convective forecast problem, Preprints, 8th Conference on Severe Local Storms, Denver, Amer. Meteor. Soc. 244-251.

Purdom, J. F. W., 1976: Some uses of high resolution GOES imagery in the mesoscale forecasting of convection and its behavior. Mon. Wea Rev., 104, 1474-1483.

Purdom, J.F.W., 1982: Subjective interpretations of geostationary satellite data for nowcasting. Nowcasting, K. Browning (Ed.), Academic Press, London, 149-166.

Rotunno, R., J.B. Klemp and M.L. Weisman, 1988: A theory for strong, long-lived squall lines. J. Atmos. Sci., 45, 463-485.

ReferencesSun,J and A. Crook, 1994: Wind and thermodynamic retrievalfrom single-Doppler measurements of a gust front observed during Phoenix II. Mon. Wea. Rev,122, 1075-1091.

Sun, J. and N.A. Crook, 1997: Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint: Part I: model development and simulated data experiments. J. Atmos. Sci, 54, 1642-1661.

Thorpe, A. J., M. J. Miller and M. W. Moncrieff, 1982: Two-dimensional convection in nonconstant shear: a model of midlatitude squall lines. Quart. J. Roy. Meteor. Soc., 108, 739-762.

Tsonis, A. A., and G. L. Austin, 1981: An evaluation of extrapolation techniques for the short- term prediction of rain amounts. Atmos.-Ocean, 19, 54-65.

Weckwerth, T.M., J.W. Wilson, and R.M. Wakimoto, 1996: Thermodynamic variability within the convective boundary layer due to horizontal convective rolls. Mon. Wea. Rev., 124, 769-784.

Weisman M.L., and J.B. Klemp, 1986: Characteristics of isolated convective storms, Chapter 15. Mesoscale Meteorology and Forecasting, P.S.Ray, Ed., Amer. Meteor. Soc., 763 pp.

Wilson, J.W., and W.E. Schreiber, 1986: Initiation of convective storms by radar-observed boundary layer convergent lines. Mon. Wea. Rev., 114, 2516-2536.

Wilson, J.W., G.B. Foote, J.C. Fankhauser, N.A. Crook, C.G. Wade, J.D. Tuttle, C.K. Mueller, S.K. Krueger, 1992: The role of boundary layer convergence zones and horizontal rolls in the initiation of thunderstorms: a case study. Mon. Wea. Rev., 120, 1758-1815.

ReferencesWilson, J. W., and C. K. Mueller, 1993: Nowcasts of thunderstorm initiation and evolution. Wea. Forecasting., 8, 113-131.

Wilson, J. W., and D. L. Megenhardt, 1997: Thunderstorm initiation, organization and lifetime associated with Florida boundary layer convergence lines. Mon. Wea. Rev., 125, 1507-1525

END


NCAR Thunderstorm Auto-nowcaster• Produces 0-2 hr time and place specific forecast of thunderstorm• Expert system utilizing fuzzy logic• Ingests multiple data sets• Extrapolates radar echoes• Forecasts storm initiation,

growth and decay• Algorithms derive forecast

parameters based on the

characteristics of;– Boundaries, – Storms and – Clouds

NCAR Thunderstorm Auto-nowcaster

• Data Sets• Nowcasting Parameters• Methodology for Combining Forecast Parameters• Nowcaster Examples• Nowcaster Implementations and Statistics• Implementation, Statistics, and Summary

The following are discussed


• Data Sets

• Radar (primary data set)

ReflectivityVelocity

Ingests Multiple Data Sets

Satellite


Visible Infrared


Surface Stations overlaid on topography

Soundings


Numerical Weather Prediction Output

Sounding 2.5 km winds


Winds Retrieved From Radar (Adjoint Winds)

200 m height windsoverlaid on reflectivity

200 m height winds overlaid on convergence


• Data Sets• Nowcasting Parameters

Nowcasting ParametersParameters Which Characterize Boundaries:

• Convergence Line (Boundary) Detection

Boundaries can be detected byalgorithms and/or entered by humans.

Parameters which characterizethe boundaries are the principleparameters for forecasting storminitiation, growth and dissipation.

Nowcasting Parameters

Parameters Which Characterize Boundaries:

• Boundary Lifting Area

Here the boundary is represented bythe green line and the lifting area isthe color coded region around the boundary. The colors represent theboundary speed of motion. Thewidth of the lifting area is based on the speed of motion. Storm initiation and growth are most likely inside the lifting area.



• Vertical velocity along boundary.

The vertical velocity within the boundary layer is computed fromthe retrieved horizontal wind fields. Higher values are favorable for storm initiation and intense storms.



The assumption is that the mean wind in a layer between about 2 and4 km approximates the cell motion. The brown colors ( 4 m/s) areregions where the boundary and storms should remain together andthe purple and red colors where the boundary is likely to move awayfrom the storms.

• Boundary Relative Steering Flow

This parameter is used in lieu of the boundary relative cell speed.


• Boundary Relative Low-level Shear

The boundary relative low-level shear is the vector difference, normalto the boundary, of the surface wind minus the 2.5 km wind. Profiler or sounding winds are used for the 2.5 km wind.The surface wind is based onthe single Doppler retrieved winds.

The dark green and blue colors represent regions where the updraftsare likely more erect and the brown regions where they are tilted.


Boundary collision zones are determined from the extrapolation of individual boundaries. The blue lines indicate the original location of the boundaries and the yellow the extrapolated positions. The solid red region indicates where the boundaries will collideduring the forecast period. This is the region where storm initiation is most likely.

• Boundary Collisions


Parameters Which Characterize Storms:

• Storm Extrapolation

Initial Radar Reflectivity Field

Extrapolated radar reflectivityfield based on past motion

Filter applied to removenon-convective echo.


• Storm Size and Growth

Storm size is color coded(m2). Large storms tend tolive longer.

Parameters Which Characterize Storms:

Trend in growth size iscolored coded (m2/hr).

Based on the visible and IR dataclouds are automatically classifiedby type. Note color classificationtable on the right of the picture.Toggle with the visible picture to check classifications

The difference in infrared cloud toptemperatures between time periodsis used to estimate if the cumulus clouds are growing or not. This picture indicates that the NW-SE line of cumulus is cooling (blue andgreen colors) and thus growing.

Parameters Which Characterize Clouds:



• Data Sets• Nowcasting Parameters• Methodology for Combining Forecast Parameters

Methodology for Combining Nowcast Parameters

Forecast Parameters are Combined using Fuzzy LogicConcepts. Each Forecast Parameter is converted to anumber between -1 and 1 which relates to likelihood of storm initiation, growth and dissipation (-1 very unlikelyand 1 very likely).

Example given for boundary relative low-level shear.

Low-level shear Membership function(converts low-level shear to thunderstorm likelihood)

Likelihood

Methodology for Combining Nowcast Parameters

Each likelihood field is multiplied by a numerical weight relative to its importance. These fields are then summed to provide the final likelihood field. This process is done separately for the likelihood of storm initiation and likelihood of growth/decay for existing echoes.

The membership functions and weights are defined by the forecaster and can be easily modified.

The graph is an example of a membership function that converts the final growth/decaylikelihood field to the amount of area to grow or dissipate eachradar reflectivity value.

Final Likelihood0- .5 .5

Gro

wD

issi

pat e

Example of Combining IndividualLikelihood Fields to ProduceForecasts of Thunderstorm Location

Likelihood associated withboundary-relative steeringflow along two boundaries

Steering flow likelihood field after weighting

Likelihood associated withcollision of two boundaries

Example of Combining IndividualLikelihood Fields to ProduceForecasts of Thunderstorm Location

Collision likelihood field weighted and overlaid on previous field

Likelihood associated withadvected radar cumulusfield

Example of Combining Individual Likelihood Fields to Produce Forecasts of Thunderstorm Location

Radar cumulus likelihood field weighted and overlaid on previous fields

Likelihood fields are summed,

Example of Combining Individual Likelihood Fields to Produce Forecasts of Thunderstorm Location

threshold and contoured

to produce final forecast

Forecast verification


• Data Sets• Nowcasting Parameters• Methodology for Combining Forecast Parameters• Nowcaster examples

Nowcaster Examples

60 min Forecast

Verification

Sterling, VA

The red contours represent the nowcastsfor >35 dBZ (yellow and red). The thin yellowlines are boundaries (gustfront and bay breeze)

Colliding Boundaries Initiate a Squall Line

Nowcaster Examples

Storm Initiation Along a Stationary Boundary

30 min forecast Verification

Nowcaster Examples

Storm Dissipation

30 min forecastVerification

Storm dissipation occurs as the boundary (yellow line) moves north leaving the storms behind. Note storms immediately south of boundary are forecast to dissipate.


• Data Sets• Nowcasting Parameters• Methodology for Combining Forecast Parameters• Nowcaster Examples• Nowcaster Implementations and Statistics• Implementation, Statistics, and Summary

Auto-nowcaster Implementations

• White Sands Missile Range, New Mexico 1998, 1999, 2000

• National Weather Service Sterling VA 1997,1998, 1999, 2000

• Bureau of Meteorology, Sydney Australia 1999, 2000

• Redstone Arsenal, Huntsville AL 1999, 2000

0%

20%

40%

60%

80%

100%

Forecast Time (UTC)

FA

R (

%)

GF_FAR

AN_FAR

0%

20%

40%

60%

80%

100%

Forecast Time (UTC)

CS

I (%

)

GF_CSI

AN_CSI

28 Aug ust 19 9 7 (6 0 Minute Forecast)

0%

20%

40%

60%

80%

100%

Forecast Time (UTC)

PO

D (

%)

GF_POD

AN_POD

FAR FAR (False Alarm Ratio)(False Alarm Ratio)

Red is the Auto-nowcast forecastBlue is extrapolation forecast

Forecast Time

100%

0%

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0%

Some Accuracy Statistics

Example statistics for 60 min forecasts of the case shown fromSterling VA. Verification is performed on a 1 km grid.

POD POD (Probability of detection)(Probability of detection)

CSI CSI (Critical Success Ratio)(Critical Success Ratio)

Summary Statistics for 13 Days

Blue - Extrapolation

Maroon - Auto-nowcaster

• 50 hrs of data

– 8 Sterling days

– 5 White Sands, New Mexico (WSMR) days

• Auto-nowcaster forecasts show

consistent improvement over extrapolation forecasts

POD

FAR

CSI

0%

50%

100%

1 2 3 4 5 6 7 8 9 10 11 12 13

0%

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100%

1 2 3 4 5 6 7 8 9 10 11 12 13

0%

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1 2 3 4 5 6 7 8 9 10 11 12 13

Sterling WSMR

• Auto-nowcaster strengths: - Automated capability has been demonstrated to forecast convective storm initiation, growth and dissipation by extracting forecast parameters from multiple data sets and combining the parameters in an expert system.

- Demonstrated forecast skill over extrapolation particularly during periods of storm evolution. Potential exists for obtaining significant more improvement in skill.

• Auto-nowcaster weaknesses: - automated detection of convergence lines needs considerable improvement. - detailed stability information is not available - need to improve methods for identifying growing cumulus

Summary

ENDAuto-nowcaster Description

Auto-nowcaster examples from the Sydney Field Trials on 22 September 1999

During the evening of 22 September two hail stormspassed over the Olympic stadium between 0815 and 0945 UTC. If these storms had occurred exactly one year later they would have caused considerable problems for Olympic Game attendees.

Sydney 2000 Field Trials - Case of 22 Sep 1999

0635 UTCThe Olympic symbol indicates the location ofOlympic Park

White shapes are 30 minforecasts, Magenta colorare 60 min forecasts. Forecasts are for reflectivity >30 dBZ; note scale to right.

At this time no storms forecast in the next hourover Olympic park.


0645 UTC

Appearance of gustfront(blue line) with 30 min (brown line) and60 min (yellow line) extrapolations.

Next image a magnification for thesame time.


0645 UTC

No storms forecast overOlympic Park within the next hour.


0655 UTC

Appearance of secondgust front


0715 UTC

30 min forecast indicates a storm is nearing Olympic Parkfrom the northwest.


0715 UTC

60 min forecast indicates thunderstormover Olympic Park.


0715 UTC

Boundary relative steering flow.

Values < 4 m/s are favorable for storm initiation and long-livedstorms. That is the casein the Olympic Park area. (For more information on this parameter click here. When done return back here by clicking on .)

Factors contributing to 0715 forecast.


0715 UTC

Boundary collision

The red indicates a region where the twoboundaries are extrapolated to collide within the next 60 min.(for more informationclick here).Note Olympic Park incollision zone.



0715 UTC

Low-level retrievedwinds.

This wind data is usedto obtain low-levelshear values relative tothe boundary and vertical motion valuesalong the boundary (for more informationclick here).



0715 UTC

Boundary relative low-level shear.

Values < about - 8 m/s are favorable for intense storms. Valuesnear this are in the areaof Olympic stadium. (for more informationclick here)



0715 UTC

Vertical motion alongboundary at 1 km height. This parameter is derived from the singleDoppler wind retrieval.The vertical velocity isbetween 1.5 and 2 m/s near Olympic Park. Which is favorable for intense storms.



Verification of 30 minforecast made at 0715


Verification of 60 minforecast made at 0715


30 min forecast at 0845shows another storm approaching OlympicPark. The 20 dBZ echowest of the Park is forecast to intensify. Note this echo is on thewest extension of theboundary.

Note convergence in thewind field along the boundary.


This radar composite ofthe maximum reflectivity in a vertical column shows the 20 dBZ echo at the west end of the boundary reaches 40 dBZ aloft.

Factors contributing to0845 forecast.


25 min later at 0909 thethe vertical radar composite shows echo is still growing aloft reaching 55 dBZ.The 30 min forecast indicates a storm over Olympic Park.


Verification of the 30 min forecast.

This forecast is reasonably good.

The 60 min forecast was poor because the boundary was extrapolated to move north too fast leaving the potential new stormbehind.

New Auto-nowcaster Capability for Sydney 2000Field Demonstration

1. 30 and 60 min forecasts of reflectivity. This includes the ability toinitiate, grow and dissipate individualreflectivity values.

2. 30 and 60 minforecasts of rainfall rate.

prepared by ncar auto-nowcaster prepared for the wmo nowcasting workshop in conjunction with the...

Documents

evolution of thunderstorms

thunderstorm evolution1

example evolution

storm intensity

storm size

boundary layer eventssuch

large squall lines

accuracy of time