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The Forecast Process. Objectives Develop a best practice scheme for the use of data in producing a forecast Produce a ‘flow chart’ illustrating this for.

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Presentation on theme: "The Forecast Process. Objectives Develop a best practice scheme for the use of data in producing a forecast Produce a ‘flow chart’ illustrating this for."— Presentation transcript:

1 The Forecast Process

2 Objectives Develop a best practice scheme for the use of data in producing a forecast Produce a ‘flow chart’ illustrating this for reference purposes

3 Forecast Process We need to develop a best practice scheme for producing a forecast From earlier lectures we know we have to take the Strengths & Weaknesses of the NWP into account We will work through a case study to illustrate the forecast process

4 Forecast Process Analysis Verification Continuity Extrapolation Development & decay NWP Climatology and experience

5 Forecast Process ANALYSIS Verification Continuity Extrapolation Development & decay NWP Climatology and experience

6 ANALYSIS – getting the start right Surface synop, metar, ship and automatic observations Upper air observations – mainly tephigrams Satellite imagery Global sferic (lightning discharge) reports Radar rainfall imagery

7 VT 1200 Z 18/10/2006

8

9 Forecast Production process AnalysisAnalysis VERIFICATION Continuity Extrapolation Development & decay NWP Climatology and experience

10 VERIFICATION - checking the analysis against: Previous forecasts NWP And then note the differences i.e. Faster or slower Bigger or smaller Stronger or weaker

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12 COTONOU VT 181200Z

13 Forecast Production process Analysis Verification CONTINUITY Extrapolation Development & decay NWP Climatology and experience

14 CONTINUITY – no change Important forecast tool in the Tropics  What happened yesterday is going to happen again today! Less so in high latitudes BUT….. Must be considered for NOWCASTING (0-6 hours ahead)  What is happening now will still be happening in 6 hours

15 Forecast Production process Analysis Verification Continuity EXTRAPOLATION Development & decay NWP Climatology and experience

16 EXTRAPOLATION – continuity of movement Thunderstorms 100 NM to east of station moving westwards at 25 KT Expected at station in 4 hours OK up to T+2 Poor forecasts by T+6

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18 Forecast Production process Analysis Verification Continuity Extrapolation DEVELOPMENT & DECAY NWP Climatology and experience

19 DEVELOPMENT AND DECAY – getting worse or better? Theoretical knowledge:  Eg Upper trough approaching making showers heavier and more frequent  Strengths & Weaknesses of NWP Effect of hills and water Diurnal effects

20 It is 1200 Z – is the upwind shower likely to develop or decay?

21 ALAM Wind forecast valid 1800 Z Low level moisture Low level convergence

22 Forecast Production process Analysis Verification Continuity Extrapolation Development & decay NWP Climatology and experience

23 NWP – model generated forecast products  MUST BE VERIFIED AT ANALYSIS STAGE FIRST Height, pressure and wind fields Humidity and precipitation fields  Most models do not advect showers  Shower signal equates to the potential for shower development Thickness fields Forecast tephigrams Severe convection indices.

24 1200 Z verification Good Poor

25 A

26 Decision time… Will there will a shower/thunderstorm at point A between 1200 and 1800? Extrapolation suggests that shower/thunderstorm will occur at 1600 Z Diurnal effects suggest that shower will develop NWP (verified well at 1200 Z) indicate potential for showers between 1200 Z and 1800 Z So what actually happened?

27 VT 1800 Z 18/10/2006

28 Poor

29 Forecast Production process Analysis Verification Continuity Extrapolation Development & decay NWP CLIMATOLOGY AND EXPERIENCE

30 CLIMATOLOGY & EXPERIENCE Climatology:  Snow in Bahamas in June?  Heatwave in Mongolia in January? Experience:  Geographical knowledge  Seen it all before!

31 NWP verification for forecast periods beyond T+36 ‘Poor man’s ensemble’  Compare model output from different centres  High forecast confidence if there is good inter- model consistency  Recent individual model ‘history’ EPS products  High forecast confidence if there is good inter- member consistency.

32 Any questions?

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