Thunderstorm Forecasting - WMO Commission for Aeronautical

Transcription

Aviation Hazards:
Thunderstorms and Deep
Convection
TREND
Empirical thunderstorm
forecasting techniques
© Copyright Commonwealth of Australia 2006,
Bureau of Meteorology
Contents
¾ Necessary conditions for convection:
¾ Instability
¾ Low-level moisture
¾ Trigger mechanism
¾ Forecasting thunderstorms for aviation:
¾ Analysis and diagnosis
¾ Symbiosis with other forecasting
¾ The thunderstorm forecasting paradox
2
Thunderstorm Fundamentals
¾
¾
Composite Analysis of Concurrence of
the Three Necessary Conditions
The Three Necessary Conditions
i. Instability
ii. Low-level moisture
iii. Lifting mechanism (“trigger”)
3
Concurrence of the three
necessary conditions
Low-level moisture
Instability
Concurrence
of All 3
conditions
TS ?
Low-level convergence
4
Thermodynamic Instability
¾ a) Parcel Theory: Instability categorisation via
aerological diagram / comparing environment and
parcel Dry / Saturated Adiabatic Lapse Rate
slopes (ELRs and DALR & SALR)
¾ b) Lifted Index, Li, a fairly universal standard of
thermodynamic instability?
¾ Thermodynamic instability indices reference:
¾ Severe Weather Indices, by Ryan Knutsvig, Grand Forks,
North Dakota, USA:
¾ http://www.geocities.com/weatherguyry/swx2.html
5
a) Parcel Theory
¾ Instability categorisation via an
aerological diagram …
¾ Compare Environment (ELR) to:
¾ Parcel’s Dry / Saturated Adiabatic Lapse Rate
(DALR) slope
¾ Parcel’s Saturated Adiabatic Lapse Rate
(SALR) slope
6
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
b) Lifted Index
¾ LI = T500 - TP500
¾ 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.
¾ (In the lifting process, the lower 1 km mean
mixing ratio is used as well as the
observed/forecast surface temperature.)
8
Interpreting Lifted Index
¾ For Li < -2.0
¾ Thunderstorms are possible
¾ Note that local conditions may qualify this
threshold
¾ The need for a climatological study to
determine meaningful threshold of Li
9
Skew-T / LogP Diagram:
23 UTC 17/01/01
Li = -5.2º C ⇒ (Severe)
Thunderstorms are indicated
10
Tropical conditional instability
¾ Tropics are generally conditionally
unstable
¾ Upper air divergence enhances low-level
convergence
¾ Land
¾ Daytime surface heating
¾ Increased instability
¾ Peak of thunderstorm activity in late afternoon
¾ Ocean
¾ Night-time cloud-top cooling
¾ Increased instability
¾ Peak of thunderstorm activity in early morning
11
Low-level moisture
¾ Picture next page: climatology of thunderstorms
in Australia
¾ Isobronts – lines of equal occurrence of thunderstorms
¾ Observation: Concentration of TS near coasts, in tropics
¾ Molecular weight comparison:
¾
¾
¾
¾
H20 < [Dry Air] average
⇒ ρ [moist air] < ρ [dry air]
⇒ moist air is more buoyant than dry air!
⇒ moist air enhances convection
¾ Dew-point temperature (in º C) is a common
measurement of moisture content
¾ Low-level dew-point analysis by way of isodrosotherms
12
Australian thunder-day
climatology
13
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
Mountains and
Convection
15
Interacting thunderstorm out-flows
16
Sea-breeze front and sea breeze
convergence over an island
17
Cold and Warm Fronts
¾ Temperature discontinuities on a synoptic
scale
18
Example: Cold Front
19
Trough line
¾ A trough of low pressure is associated
with low-level convergence
¾ Cyclonic flow is associated with low-level
convergence
¾ Especially on eastward side / pole-ward flow
20
Prefrontal Trough
21
Convection along a Trough Line
22
Moisture Discontinuities
¾ Dry Line
¾ e.g., in northern Australia
¾ Isodrosotherm gradient becomes intense
¾ Indicates moisture / dry air boundary
¾ Moist air is more buoyant than dry air
¾ Sets up local circulation
¾ Can initiate convection
¾ Water Vapour Dry / Moist Boundary
¾ Moist air is more buoyant than dry air
¾ Sets up local circulation
¾ Can initiate convection
¾ Often associated with severe thunderstorms
23
Forecasting Thunderstorms for
Aviation
¾ Observations
¾ Analyses
¾ Public Weather / Severe Weather / Aviation
Weather interactions
¾ Thunderstorm Diagnostics
¾ Thunderstorm Forecasting Methodologies
¾ Time Scales and Thunderstorm Forecasting
¾ The Thunderstorm Forecasting Paradox
24
Observations
¾ Observations
¾Satellite Data
¾RADAR Imagery
¾Upper winds / Temperature sondes
¾Surface observations
¾ METARs / SPECIs and Synoptic Observations
¾AMDARs
¾Alerts derived from Observations
¾ Input into Weather Watch
¾Do Aviation products require amendment or not?
25
Analyses
¾ Hand-analysis of synoptic plots
¾ Every 3 hours, say
¾ Enormous amount of information is inculcated,
particularly changes to weather fields, each time the
chart is newly analysed
¾ Synoptic scale analyses (NWP or hand-drawn)
are the forecaster’s bread and butter
26
Thunderstorm Diagnostics
¾ Thunderstorm Forecasting Methodologies
- Expert Systems or Decision Trees
¾ Example - Refer to the article
¾ J.R. Colquhoun. 1987: A Decision Tree Method of
Forecasting Thunderstorms, Severe Thunderstorms
and Tornadoes. Weather and Forecasting: Vol. 2, No.
4, pp. 337–345
¾ And, also after John Colquhoun’s work:
Figures 1a and 1b >>>
27
Time Scales and Thunderstorm
Forecasting
¾ Thunderstorm Climatology
¾ A description of thunderstorm behaviour, and so
provides an expectation of thunderstorms
¾ Setting of local thresholds e.g,, Lifted Index
¾ Aviation Forecasts
¾ Short-term forecast period (e.g., TAFs)
¾ Now-casting – Weather watch
¾ e.g., tracking storms with RADAR
¾ Outlook Period: Supported by NWP guidance
¾ Provides heightened anticipation of thunderstorm
activity
32
Forecast Symbiosis
¾ Aviation weather forecasting can benefit
from interactions with
¾ Public and Marine Weather
¾ Severe Weather
¾ And, vice versa
¾ Consider time / space scales
¾ Are they inclusive? Do they overlap?
33
Public Weather, Severe Weather,
Aviation Weather Interactions
Public & Marine Forecasting
Severe
Weather
Aviation
34
Public Weather – Severe Weather
– Aviation Weather Symbiosis
Public & Marine Forecasting
Aviation Forecasting
Severe Weather Forecasting
35
The thunderstorm forecasting
paradox
¾ The forecaster intends not to miss a
thunderstorm event, if it relates to an
Aviation product for which he or she is
responsible
¾ This generally leads to over-forecasting
thunderstorms: a high “false alarm rate”
¾ The aim is then, with experience, to
endeavour not to forecast thunderstorms,
when ostensibly overwhelming evidence
points to a thunderstorm event!
36
Summary
¾ Thunderstorm Forecasting:
¾ A skill which requires practice
¾ Largely experience based
¾ Often false-alarm rate high
¾ Shared data with Severe Weather specialists /
Public Weather forecasters
⇒ Optimum net value from team effort
37
Forward to
NWP guidance for thunderstorm forecasting
38

Thunderstorm Forecasting - WMO Commission for Aeronautical

Transcription

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