Aviation Hazards: Thunderstorms and Deep Convection

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1 Aviation Hazards: Thunderstorms and Deep Convection TREND Empirical thunderstorm forecasting techniques

2 Contents Necessary conditions for convection: Instability Low-level moisture Trigger mechanism Forecasting thunderstorms for aviation: Analysis and diagnosis Symbiosis with other forecasting The thunderstorm forecasting paradox 2

3 Thunderstorm Fundamentals Composite Analysis of Concurrence of the Three Necessary Conditions The Three Necessary Conditions i. Instability ii. Low-level moisture iii. Lifting mechanism ( trigger ) 3

4 Concurrence of the three necessary conditions Low-level moisture Instability Concurrence of All 3 conditions TS? Low-level convergence 4

5 Thermodynamic Instability a) Parcel Theory: Instability categorisation via aerological diagram / comparing environment and parcel Dry / Saturated Adiabatic Lapse Rate slopes (ELRs and DALR & SALR) b) Lifted Index, Li, a fairly universal standard of thermodynamic instability? Thermodynamic instability indices reference: Severe Weather Indices, by Ryan Knutsvig, Grand Forks, North Dakota, USA: 5

6 a) Parcel Theory Instability categorisation via an aerological diagram Compare Environment (ELR) to: Parcel s Dry / Saturated Adiabatic Lapse Rate (DALR) slope Parcel s Saturated Adiabatic Lapse Rate (SALR) slope 6

7 Stability of atmospheric layers with differing E.L.Rs to small parcel displacements ELR (B) SALR ELR (C) isotherm DALR ELR (D) ELR(A) Absolutely unstable Conditionally stable/unstable Absolutely stable 7

8 b) Lifted Index LI = T500 - TP500 Where LI ( C) is the lifted index, T500 is the 500hPa environmental temperature ( C), TP500 is the 500hPa temperature ( C) which a parcel will achieve if it is lifted dry-adiabatically from the surface to its lifted condensation level (LCL) and then, moist-adiabatically to 500hPa. (In the lifting process, the lower 1 km mean mixing ratio is used as well as the observed/forecast surface temperature.) 8

9 Interpreting Lifted Index For Li < -2.0 Thunderstorms are possible Note that local conditions may qualify this threshold The need for a climatological study to determine meaningful threshold of Li 9

10 Skew-T / LogP Diagram: 23 UTC 17/01/01 Li = -5.2º C (Severe) Thunderstorms are indicated 10

11 Tropical conditional instability Tropics are generally conditionally unstable Upper air divergence enhances low-level convergence Land Daytime surface heating Increased instability Peak of thunderstorm activity in late afternoon Ocean Night-time cloud-top cooling Increased instability Peak of thunderstorm activity in early morning 11

12 Low-level moisture Picture next page: climatology of thunderstorms in Australia Isobronts lines of equal occurrence of thunderstorms Observation: Concentration of TS near coasts, in tropics Molecular weight comparison: H20 < [Dry Air] average ρ [moist air] < ρ [dry air] moist air is more buoyant than dry air! moist air enhances convection Dew-point temperature (in º C) is a common measurement of moisture content Low-level dew-point analysis by way of isodrosotherms 12

13 Australian thunder-day climatology 13

14 What low-level flow characteristics will enhance localised ascent? Preferred instigators of thunderstorm activity Orography (e.g., mountains) Interacting thunderstorm out-flows Convergence of synoptic and local scale winds Discontinuities i. ii. iii. Front Dry line: a sharp gradient in low-level moisture Water vapour dry / moist boundary Trough line: associated with low-level cyclonic flow and ascent Tropical Cyclone: large scale low-level convergence 14

15 Mountains and Convection 15

16 Interacting thunderstorm out-flows 16

17 Sea-breeze front and sea breeze convergence over an island 17

18 Cold and Warm Fronts Temperature discontinuities on a synoptic scale 18

19 Example: Cold Front 19

20 Trough line A trough of low pressure is associated with low-level convergence Cyclonic flow is associated with low-level convergence Especially on eastward side / pole-ward flow 20

21 Prefrontal Trough 21

22 Convection along a Trough Line 22

23 Moisture Discontinuities Dry Line e.g., in northern Australia Isodrosotherm gradient becomes intense Indicates moisture / dry air boundary Moist air is more buoyant than dry air Sets up local circulation Can initiate convection Water Vapour Dry / Moist Boundary Moist air is more buoyant than dry air Sets up local circulation Can initiate convection Often associated with severe thunderstorms 23

24 Forecasting Thunderstorms for Aviation Observations Analyses Public Weather / Severe Weather / Aviation Weather interactions Thunderstorm Diagnostics Thunderstorm Forecasting Methodologies Time Scales and Thunderstorm Forecasting The Thunderstorm Forecasting Paradox 24

25 Observations Observations Satellite Data RADAR Imagery Upper winds / Temperature sondes Surface observations METARs / SPECIs and Synoptic Observations AMDARs Alerts derived from Observations Input into Weather Watch Do Aviation products require amendment or not? 25

26 Analyses Hand-analysis of synoptic plots Every 3 hours, say Enormous amount of information is inculcated, particularly changes to weather fields, each time the chart is newly analysed Synoptic scale analyses (NWP or hand-drawn) are the forecaster s bread and butter 26

27 Thunderstorm Diagnostics Thunderstorm Forecasting Methodologies - Expert Systems or Decision Trees Example - Refer to the article J.R. Colquhoun. 1987: A Decision Tree Method of Forecasting Thunderstorms, Severe Thunderstorms and Tornadoes. Weather and Forecasting: Vol. 2, No. 4, pp

28 Time Scales and Thunderstorm Forecasting Thunderstorm Climatology A description of thunderstorm behaviour, and so provides an expectation of thunderstorms Setting of local thresholds e.g,, Lifted Index Aviation Forecasts Short-term forecast period (e.g., TAFs) Now-casting Weather watch e.g., tracking storms with RADAR Outlook Period: Supported by NWP guidance Provides heightened anticipation of thunderstorm activity 28

29 Forecast Symbiosis Aviation weather forecasting can benefit from interactions with Public and Marine Weather Severe Weather And, vice versa Consider time / space scales Are they inclusive? Do they overlap? 29

30 Public Weather, Severe Weather, Aviation Weather Interactions Public & Marine Forecasting Severe Weather Aviation 30

31 Public Weather Severe Weather Aviation Weather Symbiosis Public & Marine Forecasting Aviation Forecasting Severe Weather Forecasting 31

32 The thunderstorm forecasting paradox The forecaster intends not to miss a thunderstorm event, if it relates to an Aviation product for which he or she is responsible This generally leads to over-forecasting thunderstorms: a high false alarm rate The aim is then, with experience, to endeavour not to forecast thunderstorms, when ostensibly overwhelming evidence points to a thunderstorm event! 32

33 Summary Thunderstorm Forecasting: A skill which requires practice Largely experience based Often false-alarm rate high Shared data with Severe Weather specialists / Public Weather forecasters Optimum net value from team effort 33

34 Forward to NWP guidance for thunderstorm forecasting 34

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