1. 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 Mueller and Tom Saxen National Center for Atmospheric Research Boulder, Colorado, USA

2. 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:

3. 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:

4. Science of Nowcasting Thunderstorms Thunderstorm Lifetime, Evolution and Characteristics

5. 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)

6. Thunderstorm Lifetime, Evolution and Characteristics Convective Storm System Single-cell Thunderstorm TIME (hr) SIZE 12345 There are frequent and rapid changes in storm size and intensity. Example Evolution of a Single Cell and a Convective Systems

7. Thunderstorm Lifetime, Evolution and Characteristics Thunderstorm Characteristics: Radar can provide time trends of thunderstorm movement, size, height, intensity, height of the rain mass centroid, and vertically integrated liquid water equivalent. Beyond ~ 15 min these parameters by themselves are of only limited forecast value. This is because physical processes that dictate changes in storms are not necessarily observable in the past history of the storm but are often driven by boundary layer events such as convergence and stability. (Tsonis and Austin 1981, Bellon and Austin 1978, Browning et al. 1982, Collier 1989)

8. Thunderstorm Lifetime, Evolution and Characteristics 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.

9. Thunderstorm Lifetime, Evolution and Characteristics 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 figure to the left the accuracy of the forecasts decreases very rapidly during the first hour. Large scale numerical models can not even make forecasts on this short time scale. Forecasts with explicit storm numerical methods are in their infancy. The approach used here is an expert system which is based on the heavy use of observations and theory.

10. Science of Nowcasting Thunderstorms Thunderstorm Lifetime, Evolution and Characteristics Boundary Influences on Thunderstorm Evolution

11. 1. Satellite cloud imagery. Note the N-S line of cumulus associated with a sea breeze along the Florida 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 line of reflectivity associated with a boundary. Red arrows are wind direction from surface stations.

12. Boundary Influences on Thunderstorm Evolution Example of Storm Initiation Behind a Moving Boundary This first picture shows converging winds in the Doppler velocity data. Brown and red colors represent velocities away from the radar while greens are towards. The following time lapse pictures are radar reflectivity. Note the storm initiation as the boundary moves southeast (click once).

13. Boundary Influences on Thunderstorm Evolution Thunderstorm initiation Frequently occurs near boundary layer convergence lines. Thunderstorm Initiation Locations (Purdom 1973, 1976 1982; Wilson and Schreiber 1986) The figure to the right shows the initiation 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 lifting zone.

14. Boundary Influences on Thunderstorm Evolution ~20 km lifting zone ~10 km The lifting zone is the most likely region for storm initiation and storm growth. It is positioned about the boundary based on the boundary speed of movement. (Wilson and Mueller 1993)

15. Boundary Influences on Thunderstorm Evolution Colliding Boundaries Often Initiate Intense Storms Colliding boundaries are frequently responsible for storm initiation and significant increase in the intensity and size of existing storms. Cross-sections to the right show a large increase in vertical velocity (3 m/s to 12 m/s) as two boundaries (red lines) collide. (Mahoney 1988)

16. Storm Initiation often follows a boundary intercepting Cumulus clouds Boundary Influences on Thunderstorm Evolution In the radar images to the right an east-west oriented gust front is moving south intercepting a north-south horizontal convective roll. The cumulus clouds along the roll grow into thunderstorms once the gust front passes under them. Wilson and Mueller 1993

17. Boundary Influences on Thunderstorm Evolution Storm merger and intensification frequently follows a boundary intercepting existing storms. Note in the images to the right the merger and growth of the storms in advance of the gust front (represented by the red line) as they are intercepted by the gust front (toggle forward and back).

18. Boundary Influences on Thunderstorm Evolution Boundary Characteristics That Influence Storm Evolution Boundary Relative Cell Speed (U b ) (Moncrieff and Miller 1976, Weisman and Klemp 1986, Wilson and Megenhardt 1997) cell velocity boundary velocity cell velocity Boundary velocity U b large U b is the rate at which a cell is moving away from a boundary. For values >~4 m/s the storm will move away from the boundary and likely dissipate. For smaller values the storm will remain near the boundary and likely live. U b near zero

19. Boundary Influences on Thunderstorm Evolution Boundary Characteristics That Influence Storm Evolution 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 how tilted the updrafts will be. Values < -8 m/s favor erect updrafts and thus more intense and long lived storms.

20. Boundary Influences on Thunderstorm Evolution Boundary Characteristics That Influence Storm Evolution Convergence Magnitude and Depth Obviously strong low-level convergence and deep updrafts have greater potential for developing intense thunderstorms. (Sun and Crook 1994, 1997) The picture to the right shows an example of wind vectors and convergence magnitude at a height of 200 m as retrieved from single Doppler radar. The yellow line is the position of a gust front. The yellows and reds represent the strongest convergence.

21. Boundary Influences on Thunderstorm Evolution Boundary Characteristics That Influence Storm Evolution Thunderstorm Nowcasting Requires Close Monitoring of Boundaries, Storms and Clouds to Anticipate When They Will Intercept Each Other

22. Science of Nowcasting Thunderstorms Thunderstorm Lifetime, Evolution and Characteristics Boundary Influences on Thunderstorm Evolution Stability Influences on Thunderstorm Evolution

23. Static Stability is a Critical Parameter for Forecasting Thunderstorms. Unfortunately they are widely spaced and observations are infrequent thus of limited use for thunderstorm nowcasting purposes. Traditionally radiosondes are used to measure stability.

24. Stability Influences on Thunderstorm Evolution Soundings 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 three simultaneous soundings show there are large variations in the convective available potential energy (orange area) over short distances in the vicinity of a convergence line. Wilson et al., 1992

25. Stability Influences on Thunderstorm Evolution Soundings 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 is typically in the updraft portion of horizontal convective rolls. Thus if the sounding does not go up in the updraft the potential for thunderstorms is likely underestimated.

26. Stability Influences on Thunderstorm Evolution Satellite Cloud Imagery Used to Monitor Stability The presence of cumulus clouds indicates instability although of unknown magnitude and depth. The use of satellite visible and infrared imagery to monitor the location and development of cumulus clouds serves as a useful proxy for stability.

27. Stability Influences on Thunderstorm Evolution The picture to the right is a radar estimated rainfall accumulation field for the past hour. This can be used as an indicator of where rain may have caused local cooling. Thus this area may be more stable and less likely to support further convection. This field is more useful in weakly forced synoptic situations where boundary layer instability plays a primary role. Accumulated Precipitation Field Used to Monitor Stability

28. Science of Nowcasting Thunderstorms Thunderstorm Lifetime, Evolution and Characteristics Boundary Influences on Thunderstorm Evolution Stability Influences on Thunderstorm Evolution Forecast Parameters

29. 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 following parameters are used to forecast storm initiation, growth and dissipation.

30. 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

31. 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

32. References Austin 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.

33. References Henry, 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.

34. References Sun,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.

35. References Wilson, 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

36. END Science of Nowcasting Thunderstorms

37. 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

38. 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

39. NCAR Thunderstorm Auto-nowcaster Data Sets

40. Radar (primary data set) Reflectivity Velocity Ingests Multiple Data Sets

41. Satellite Ingests Multiple Data Sets VisibleInfrared

42. Ingests Multiple Data Sets Surface Stations overlaid on topography Soundings

43. Ingests Multiple Data Sets Numerical Weather Prediction Output Sounding 2.5 km winds

44. Ingests Multiple Data Sets Winds Retrieved From Radar (Adjoint Winds) 200 m height winds overlaid on reflectivity 200 m height winds overlaid on convergence

45. NCAR Thunderstorm Auto-nowcaster Data Sets Nowcasting Parameters

46. Parameters Which Characterize Boundaries: Convergence Line (Boundary) Detection Boundaries can be detected by algorithms and/or entered by humans. Parameters which characterize the boundaries are the principle parameters for forecasting storm initiation, growth and dissipation.

47. Nowcasting Parameters Parameters Which Characterize Boundaries: Boundary Lifting Area Here the boundary is represented by the green line and the lifting area is the color coded region around the boundary. The colors represent the boundary speed of motion. The width of the lifting area is based on the speed of motion. Storm initiation and growth are most likely inside the lifting area.

48. Nowcasting Parameters Parameters Which Characterize Boundaries: Vertical velocity along boundary. The vertical velocity within the boundary layer is computed from the retrieved horizontal wind fields. Higher values are favorable for storm initiation and intense storms.

49. Nowcasting Parameters Parameters Which Characterize Boundaries: The assumption is that the mean wind in a layer between about 2 and 4 km approximates the cell motion. The brown colors (  4 m/s) are regions where the boundary and storms should remain together and the purple and red colors where the boundary is likely to move away from the storms. Boundary Relative Steering Flow This parameter is used in lieu of the boundary relative cell speed.

50. Nowcasting Parameters Parameters Which Characterize Boundaries: Boundary Relative Low-level Shear The boundary relative low-level shear is the vector difference, normal to 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 on the single Doppler retrieved winds. The dark green and blue colors represent regions where the updrafts are likely more erect and the brown regions where they are tilted.

51. Nowcasting Parameters Parameters Which Characterize Boundaries: 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 collide during the forecast period. This is the region where storm initiation is most likely. Boundary Collisions

52. Nowcasting Parameters Parameters Which Characterize Storms: Storm Extrapolation Initial Radar Reflectivity Field Extrapolated radar reflectivity field based on past motion Filter applied to remove non-convective echo.

53. Nowcasting Parameters Storm Size and Growth Storm size is color coded (m 2 ). Large storms tend to live longer. Parameters Which Characterize Storms: Trend in growth size is colored coded (m 2 /hr).

54. Based on the visible and IR data clouds are automatically classified by type. Note color classification table on the right of the picture. Toggle with the visible picture to check classifications The difference in infrared cloud top temperatures between time periods is used to estimate if the cumulus clouds are growing or not. This picture indicates that the NW-SE line of cumulus is cooling (blue and green colors) and thus growing. Parameters Which Characterize Clouds: Nowcasting Parameters

55. NCAR Thunderstorm Auto-nowcaster Data Sets Nowcasting Parameters Methodology for Combining Forecast Parameters

56. Methodology for Combining Nowcast Parameters Forecast Parameters are Combined using Fuzzy Logic Concepts. Each Forecast Parameter is converted to a number between -1 and 1 which relates to likelihood of storm initiation, growth and dissipation (-1 very unlikely and 1 very likely). Example given for boundary relative low-level shear. Low-level shear Membership function (converts low-level shear to thunderstorm likelihood) Likelihood

57. 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/decay likelihood field to the amount of area to grow or dissipate each radar reflectivity value. Final Likelihood 0-.5.5 Grow Dissipate

58. Example of Combining Individual Likelihood Fields to Produce Forecasts of Thunderstorm Location Likelihood associated with boundary-relative steering flow along two boundaries Steering flow likelihood field after weighting

59. Likelihood associated with collision of two boundaries Example of Combining Individual Likelihood Fields to Produce Forecasts of Thunderstorm Location Collision likelihood field weighted and overlaid on previous field

60. Likelihood associated with advected radar cumulus field Example of Combining Individual Likelihood Fields to Produce Forecasts of Thunderstorm Location Radar cumulus likelihood field weighted and overlaid on previous fields

61. 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

62. NCAR Thunderstorm Auto-nowcaster Data Sets Nowcasting Parameters Methodology for Combining Forecast Parameters Nowcaster examples

63. Nowcaster Examples 60 min Forecast Verification Sterling, VA The red contours represent the nowcasts for >35 dBZ (yellow and red). The thin yellow lines are boundaries (gust front and bay breeze) Colliding Boundaries Initiate a Squall Line

64. Nowcaster Examples Storm Initiation Along a Stationary Boundary 30 min forecast Verification

65. Nowcaster Examples Storm Dissipation 30 min forecast Verification Storm dissipation occurs as the boundary (yellow line) moves north leaving the storms behind. Note storms immediately south of boundary are forecast to dissipate.

66. NCAR Thunderstorm Auto-nowcaster Data Sets Nowcasting Parameters Methodology for Combining Forecast Parameters Nowcaster Examples Nowcaster Implementations and Statistics Implementation, Statistics, and Summary

67. 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

68. FAR (False Alarm Ratio) Red is the Auto-nowcast forecast Blue is extrapolation forecast Forecast Time 100% 0% 100% 0% 100% 0% Some Accuracy Statistics Example statistics for 60 min forecasts of the case shown from Sterling VA. Verification is performed on a 1 km grid. POD (Probability of detection) CSI (Critical Success Ratio)

69. 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 SterlingWSMR

70. 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

71. END Auto-nowcaster Description

72. Auto-nowcaster examples from the Sydney Field Trials on 22 September 1999 During the evening of 22 September two hail storms passed 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.

73. Sydney 2000 Field Trials - Case of 22 Sep 1999 0635 UTC The Olympic symbol indicates the location of Olympic Park White shapes are 30 min forecasts, Magenta color are 60 min forecasts. Forecasts are for reflectivity >30 dBZ; note scale to right. At this time no storms forecast in the next hour over Olympic park.

74. Sydney 2000 Field Trials - Case of 22 Sep 1999 0645 UTC Appearance of gust front(blue line) with 30 min (brown line) and 60 min (yellow line) extrapolations. Next image a magnification for the same time.

75. Sydney 2000 Field Trials - Case of 22 Sep 1999 0645 UTC No storms forecast over Olympic Park within the next hour.

76. Sydney 2000 Field Trials - Case of 22 Sep 1999 0655 UTC Appearance of second gust front

77. Sydney 2000 Field Trials - Case of 22 Sep 1999 0715 UTC 30 min forecast indicates a storm is nearing Olympic Park from the northwest.

78. Sydney 2000 Field Trials - Case of 22 Sep 1999 0715 UTC 60 min forecast indicates thunderstorm over Olympic Park.

79. Sydney 2000 Field Trials - Case of 22 Sep 1999 0715 UTC Boundary relative steering flow. Values < 4 m/s are favorable for storm initiation and long-lived storms. That is the case in the Olympic Park area. (For more information on this parameter click here. When done return back here by clicking on.)here Factors contributing to 0715 forecast.

80. Sydney 2000 Field Trials - Case of 22 Sep 1999 0715 UTC Boundary collision The red indicates a region where the two boundaries are extrapolated to collide within the next 60 min. (for more information click here).here Note Olympic Park in collision zone. Factors contributing to 0715 forecast.

81. Sydney 2000 Field Trials - Case of 22 Sep 1999 0715 UTC Low-level retrieved winds. This wind data is used to obtain low-level shear values relative to the boundary and vertical motion values along the boundary (for more information click here).here Factors contributing to 0715 forecast.

82. Sydney 2000 Field Trials - Case of 22 Sep 1999 0715 UTC Boundary relative low- level shear. Values < about - 8 m/s are favorable for intense storms. Values near this are in the area of Olympic stadium. (for more information click here)here Factors contributing to 0715 forecast.

83. Sydney 2000 Field Trials - Case of 22 Sep 1999 0715 UTC Vertical motion along boundary at 1 km height. This parameter is derived from the single Doppler wind retrieval. The vertical velocity is between 1.5 and 2 m/s near Olympic Park. Which is favorable for intense storms. Factors contributing to 0715 forecast.

84. Sydney 2000 Field Trials - Case of 22 Sep 1999 Verification of 30 min forecast made at 0715

85. Sydney 2000 Field Trials - Case of 22 Sep 1999 Verification of 60 min forecast made at 0715

86. Sydney 2000 Field Trials - Case of 22 Sep 1999 30 min forecast at 0845 shows another storm approaching Olympic Park. The 20 dBZ echo west of the Park is forecast to intensify. Note this echo is on the west extension of the boundary. Note convergence in the wind field along the boundary.

87. Sydney 2000 Field Trials - Case of 22 Sep 1999 This radar composite of the maximum reflectivity in a vertical column shows the 20 dBZ echo at the west end of the boundary reaches 40 dBZ aloft. Factors contributing to 0845 forecast.

88. Sydney 2000 Field Trials - Case of 22 Sep 1999 25 min later at 0909 the the vertical radar composite shows echo is still growing aloft reaching 55 dBZ. The 30 min forecast indicates a storm over Olympic Park.

89. Sydney 2000 Field Trials - Case of 22 Sep 1999 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 storm behind.

90. New Auto-nowcaster Capability for Sydney 2000 Field Demonstration 1. 30 and 60 min forecasts of reflectivity. This includes the ability to initiate, grow and dissipate individual reflectivity values. 2. 30 and 60 min forecasts of rainfall rate.

91. END