SIGMET Analysis

7/29/2019 SIGMET Analysis

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Executions and Techniques onSIGMET Consulting Information

April, 2011 Beijing

Qiang Xuemin


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Main topic

To briefly introduce the executions

and techniques on SIGMET information

which have been successfully applied inaeronautic significant weather forecasts .


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Data used in this work:

Conventional telegram report

Output products from the globalmid-term numerical weatherforecast model

Satellite data


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4 Phenomenaof SIGMETConsultingInformation

Contents

Thunderstorm

Aircraft Bumps

Aircraft Icing

SevereLee Waves


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Executions and Techniques onThunder Storm1 Diagnostics on stabilization index of the

atmosphere

Multi-factor-overlapping techniques on

thunder storm area

Classification and extrapolation of satellite

data for convective weather

Integrated forecast techniques on thunder

storm area

Thunder

Storm


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Active convections is in favor of a thunder storm.

favorable conditions

I. conditionally unstable stratification in the atmosphere

II. abundant in water vapor

III. a kind of dynamic trigger mechanism

Characteristics

meso-scale system / short lifetime / strong convective weather

Forecast

Yes or No before 0-6 hours

About Thunder Storm


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1-1 Diagnostics on stabilization index of the atmosphere

Potential Forecast

for

Convective Weather

Diagnostics

Thresholdfor these index

Index characterizing instability of the atmosphere

Outputproducts from NWF


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1

2

3

4 4. Energy Index

1. Thermal Index

2. Humidity

Index

3. Dynamical

Index

Diagnosticson stabilizationindex of the atmosphere


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1 Thermal Index

A---index

Air mass index---K

Potential instability index---I

Showalter Index---SI

Simplified Showalter Index---SSI

Yamazaki index---KYI

Bejerknese Index---BI

Diagnostic on convective instability


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A---index

)(500

85 0

500850 dttttA

---- to describe the vertical humidity condition in the whole

volume

t500 / t850 : temperatue at 500 / 850 hPa

td : dew-point

When A 0, probability of a thunderstrom is 90%


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1 Thermal Index

A---index

Air mass index---K








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Air mass index---K

K t t t t td d 850 500 850 700( )or

500700850850 )()(2 TTTTTTK dd

---- the bigger the K index is, the more unstable in the air will be.

K 20oC, no thunderstorm20oCK25oC, single thunderstorm25oC K30oC, sporadic thunderstorms30o C K35o C, scattered thunderstorms35o C K , massive thunderstorms


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1 Thermal Index

A---index

Air mass index---K








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700

700925200

925300 01.02

dthhh

hhI

h : geopential height

---- favorable condition : colder in the upper air, warmer in lower

---- the bigger I index is, the more instable of the stratification will be

K 2.79, no thunderstorm

K2.79, yes


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1 Thermal Index

A---index

Air mass index---K








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500 SSI T T ----temperature difference between the stratification curve and the statecurve, describing air mass at 850hPa rising along dry-adiabatic curve

till to the condensation level then rising along wet-adiabatic curve till

to 500hPa (with temperature Ts). T500 is the environmental

temperature at 500hPa.

---- positive: rising air mass with high temperature

negative: with low temperature

Value of SI Index Possibility of thunderstorm event

3

o

Clittle or not

3oCSI0oC Shower be possible

0oCSI-3oC Thunderstorm be possible

-3oCSI-6oC Strong thunderstorm be possible

-6oCSI Severe convective weather be possible


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1 Thermal Index

A---index

Air mass index---K





Bjerknes Index---BI



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'

500 STTSSI ---- Ts

: air mass at 850hPa rising along dry-adiabatic curve till to

500hPa (with temperature Ts). T500 is the environmental

temperature at 500hPa.

---- usually, SSI 0.

---- The smaller the SSI is, the stable the air would be.

---- SSI has outstanding exhibition in forecasting strong convective

weather, such as tornadoes, hailstones, and so on


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1 Thermal Index

A---index

Air mass index---K





Bjerknes Index---BI



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KYIT S

T T

A

d

( )850

humidity condition at low level

stabilization of the air

temperature advection

at 500hpa While: =1, =1105s0 (statistically)S -----(T-Td)850 ----- ( units)T ----- 10-5s-1

8501 ( )

0{A

A

d

A

T ST S

T T

T SKYI

1

2

3

KYI

pay attention

possibility is high

in all likelihood


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1 Thermal Index

A---index

Air mass index---K





Bjerknes Index---BI



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Bjerknes Index---BI

200 TZBI

Z: thickness from 1000-700hPa (unit: gpm)

T: temperature at 700hPa (unit: K)200: empirical coefficient

BI 94, a thunderstorm might occur.

When BI is used in a frontal circumstance, the correct rate

would be more than 81%.


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1 Thermal Index

A---index

Air mass index---K





Bjerknes Index---BI



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0

0

0

se

p

stable

neutral or

instable

0

0

0

se

z

stable

neutral

instable

se: pseudo-equivalent potential temperature

This method usually is used in diagnosing weather systems with

systematical updraft flows.


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1

2

3

4 4. Energy Index

1. Thermal Index

2. Humidity

Index

3. Dynamical

Index



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2 Humidity Index

difference between air temperature and dew-point temperature

divergence of the water vapor flux

dTTTTD

simple, but useful

When TTd=0 saturated.

Based on the NWF products, we can get TTD at each grid points.


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2 Humidity Index

difference between air temperature and dew-point temperature



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Water vapor flux, depicting the strength and direction of thetransportation of the moisture.

FH: flux on horizontal

FZ: flux on vertical

horizontal wind speed vertical speed

specific humidity density of the air

HF V q g

qFz

V

q

( ) ( ) ( )V q g uq g vq g x y

positive: outcome or lost of the water vapor

negative: income or convergence of the water vapor


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1

2

3

4 4. Energy Index

1. Thermal Index

2. Humidity

Index

3. Dynamical

Index


Dynamical Index


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Dynamical Index3

vorticity

divergence

vertical velocity

yu

xvV

D Vu

x

v

y

unit: 10-6s-1

unit: 10-5s-1

752

1

925925 D

unit: 10-3hPas-1

at 925hPa

PDDkkkk

)(

21

11k level


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1

2

3

4 4. Energy Index

1. Thermal Index

2. Humidity

Index

3. Dynamical

Index


Energy Index


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Energy Index4

convective available potential energy CAPE

modified CAPE MCAPE

normalized CAPE NCAPE

downdraft CAPE DCAPE

convective inhibitation CIN


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convective available potential energyCAPE

( )EL

LFC

Zvp ve

veZ

T TCAPE g dZ

T

Tv pseudo temperature

subscript mark

e ---- environment air

p --- air parcel

LFC level of free convectionLCL level of condensation

EL equilibrium level

EAL equivalent area level

dry adiabatic curve

wet adiabatic curve

state curve

stratification curve


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convective available potential energyCAPE

Two aspects noticeable in computing CAPE

corrections for Tv)1(

1

/1rT

r

rTT

v

height of LCLsurface / h850 / h925 /

height with the biggest wet-bulb temperature from 1000 to800hPa


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modified CAPE MCAPE

---- re and ri stand for the mixing ratio of water vapor in

liquid and solid state, respectively.

---- g (re + ri ) stands for the dragging function caused by

the water component in the air

[ ( ) ]EL

LFC

Z

e i pZ

Tvp TveMCAPE g r r dZ

Tve


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normalized CAPE NCAPE

FCL EL LFC

CAPE CAPE CAPE

H Z Z

----designed to consider the effect on the vertical velocity

caused by the vertical distribution of the floating force


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downdraft CAPE DCAPE

In the body of a storm, when precipitation, ice water or crystalvaporizes in the unsaturated air or melts at the frozen layer, downdraft

occurs.

( ) ln

1 ( )

n

i

i

n

p

d e pp

Z

ve vpZ

ve

DCAPE R T T d p

g T T dZT

---- Pi / Zi pressure or height where downdraft begins

---- Pn / Zn pressure or height when downdraft reaches the ground

Approximatively, the maximum down speed can be written as:

max 2W DCAPE


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convective inhibition CIN

dry adiabatic curve

wet adiabatic curve

state curve

stratification curve

LFC

i

Z e p

ZB

T TCIN g dz

T

TB mean temperature at ABL

(atmospheric boundary layer)

subscript mark

e ---- environment air

p --- air parcel

ZLFC level of free convection

Zi original level2

CINW CIN


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Executions and Techniques on Thunder Storm1

Diagnostics on stabilization index of

the atmosphere

Multi-factor-overlapping techniqueson thunder storm area

Classification and extrapolation of

satellite data for convective weather

Integrated forecast techniques on

thunder storm area

Thunder

Storm


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1-2 Multi-factor-overlapping method on thunderstorm area

=0

=0

trough

SW airflow

chart for multi-factor-overlapping method


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indices selection

stability indices

0se

p

K>35

SI0

KYI1

BI94

TI>0

I2.79

water vapor indices850 850

2.0d

T T

850( ) 0qV

850 850 925 925( ) ( ) 5.0d dT T T T

850 700( ) ( ) 0qV qV

momentum indices

and

or

700 5000W W

850( ) 0V

5000V

850 700( ) ( ) 0V V and

energy indices CAPE>200

convective precipitation RC>3mm


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Multi-factor-overlapping method in forecast thunderstorm

Step-wise

decreasing FAR

Executions of

indices

overlapping

Integrated

judgment on

severe weather

850 850 925 925( ) ( ) 25d dT T T T

15K

500 700 850 92530

se se se se K

To judge whether 15

indices meet the

requirements or not. If it

is true, NP+1.

If NP>8 and CAPE>800

Or NP>11

Or CAPE>2000

Or Rc>5mm

Then there will be a thunderstorm

within the forecast area.


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the atmosphere


Classification and extrapolation of


Integrated forecast techniques on

thunder storm area

Thunder

Storm

1-3 classification and extrapolation of satellite data for convective


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1 3 classification and extrapolation of satellite data for convective

weather

including:

quality control on Satellite data

classification and extraction ofconvectivecloud,jet stream cloud, frontal cloud and

cloud systems related with Lee waves

obtaining live information ofsandstorm

1-3 Identification and extrapolation of satellite data for convective


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1 3 Identification and extrapolation of satellite data for convective

weather

threshold technique

space correlation technique

bi-channel dynamic threshold technique

dynamic clustering technique

brightness temperature technique


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the atmosphere


Identification and extrapolation of


Integrated forecasting techniques on

thunder storm areas

Thunder

Storm

1 4 I t t d f t t h i th d t


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1-4 Integrated forecast techniques on thunder storm area

Regression integrated technique is used to forecast thethunder storm rainfall area.

Basic principle:

n

i

iiYbbY

1

0

b0 mean of the forecast objective

bi coefficient, reflecting the relationship between forecasts(actually, they represents the variety forecast measures)

1 4 I t t d f t t h i th d t


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Steps:

a variety methods forecasting thunderstorms are used tocompute inversely the history samples

Use MOS method, output of the forecasts are treated as differentfactors

Set up a forecast model by using the regressive integratedtechnique

Substitute results of the various methods to the model and drawthe final forecast conclusion.

1-4 Integrated forecast techniques on thunder storm area

C t t


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Contents

Thunderstorm

Aircraft Bumps

Aircraft Icing

Severe Lee Wave


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Executions and Techniques onAircraft Bumps2

2 1 Aircraft Bumps and The Turbulences


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Bumping is a kind of phenomenon that a flying aircraft goes up and

down and sways from the right to the left badly, or its body

shakes violently. It is caused mainly by the turbulences in the

atmosphere.

Category of the Turbulences:

Dynamical Turbulences

Thermal Turbulences

Wind Shear Turbulences

Wake Vortex Turbulences

2-1 Aircraft Bumps and The Turbulences

2 2 Mechanism of the Turbulences:


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2-2 Mechanism of the Turbulences:

G

Yn

SG

VKWn

2

g

a

mg

ma

G

Yn

VSKWY 2

1

Loading coefficient

Y ascending force

G gravity

a acceleration

W vertical wind speed of the gust

density of the air

V speed of the aircraft

K coefficient of slope

S area of the airfoil

n increment of n

2 3 Di d F t Ai ft B


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2-3 Diagnose and Forecast on Aircraft Bumps

Richardson Index

Ellrod Index

Ti Index

E Index

L Index

Integrated Diagnose


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Richardson Index---a classical method

2( / )( / ) /Ri g z v z

static stability of the layer vertical sheer of the layerThe index operates well in two circumstances:

areas closing to a jet stream

areas with gales near the ground surface and

unstable air at the bottom

A Vertical section of Ri is helpful in figuring out the layer on

which the aircraft bumps might take place.

2 3 Di d F t Ai ft B


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Richardson Index

Ellrod Index

Ti Index

E Index

L Index

Integrated Diagnose


56/93

Ellrod Index

In Practical,

[ ]TI VWS DEF CVG

21

22

y

u

x

v

y

v

x

uDEF

y

v

x

uCVG

z

VVWS

negative of divergence

wind shear on vertical direction

flow field deformation made

by stretch in horizontal and

shear in vertical

TI VWS DEF unit: 10-7s-2


57/93

Degree of bump Value of TI

light TI4

Light-medium 4


58/93

Ti Index----applied in NMC, U.S.A

V

The bigger Ti index is, the stronger the bumps will be.

Ti >5.1 a medium Bump might occurs.

Ti


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Richardson Index

Ellrod Index

Ti Index

E Index

L Index

Integrated Diagnose


60/93

E Index----Dutton (1989)

v

h wind shear in horizontal

unit: m/s/100Kmwind shear in vertical

unit: m/s/1000Km

21.25 0.25 10.5

h vE

E 5 7.5 10 15 20 25 30

P(%) 0.0 0.95 1.55 2.2 2.8 4.2 7.5

Table3 relationship between E index and the probability of a

medium CAT in 100Km-averaged flight test



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Richardson Index

Ellrod Index

Ti Index

E Index

L Index

Integrated Diagnose


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L Index method----a probability method

wind shear in horizontal unit: m/s/100Km

wind shear in vertical unit: m/s/1000Km

52.2133.0718.0268.7

n

u

n

T

z

uL

Step 1 compute L index

22

z

v

z

u

z

u

22

y

v

x

u

n

u

22

yT

xT

nT temperature shear in horizontal unit: /s/100Km


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L Index method----a probability method

Step 2 get the probability------P

Lep

59.01

1

generally,

86%>P75% light CAT forecast output --- 1

95%>P86% moderate CAT forecast output --- 2

P96% svevere CAT forecast output --- 3


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integrated diagnose on CAT areas

5

1 1 2 2 3 3 4 4 5 5

1

i i

i

F k f k f k f k f k f k f

ki weightfi output for 5 forecasts

Contents


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Contents

Thunderstorm

Aircraft Bumps

Aircraft Icing

SevereLee Wave


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Executions and Techniques onAircraft Icing3

3-1 Aircraft Icing


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3 1 Aircraft Icing

3-1 Aircraft Icing


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3 1 Aircraft Icing

3-2 Factors affecting Aircraft Icing


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3 2 Factors affecting Aircraft Icing

I weather conditionstemperature ----- TAT (total air temperature)

LWC and the scales of the water droplets

cloud phase state

II flight parameters

including flight speed, aircraft shape and type and other

parameters

3-3 Arithmetic on Aircraft Icing


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3 3 Arithmetic on Aircraft Icing

3-3-1 Icing computation scheme 1


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3 3 c g co putat o sc e e

step1. computations on LWC

)87.2/()(95.0 hhchc TQQPL ( for cumulous cloud )

))36(/()(1025.0 24 TTTTEfLhcn ( for stratus cloud )

quantities at the flight level tk: temperature()Ph : pressure f: relative humidity Th: temperature (K)

Qh: saturated specific humidity

quantities at the cloud bottom

Tc: temperature Qc: saturated specific humidity

)5.237/(5.7

1011.6hhtt

E

2

hc TTT


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value L0.01 0.01


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step2. diameter of moderate cloud droplet

cloud St Sc Ns As Ac Cu Cb

DMV 20 28 48 16 18 22 36

Table 5 diameters of moderate water droplets for different clouds

DMV 1 17 28 50 >50

rank D1 D2 D3 D4 D5

unit: m

Table 6 classification for Dmv


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step3. classification for environmental temperature

value T>0 -5


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step4. index matrix for severe icing I index

T1: T>0, I=0


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T2-5


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T3-10


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T4-20


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T5T-20

I D1 D2 D3 D4 D5

L1 0 0 0 0 5

L2 0 1 2 3 6

L3 0 2 2 3 7

L4 0 3 3 4 8

L5 0 5 5 6 9

L6 0 7 7 7 10

3-3-2 Icing computation scheme 2


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criterions on Icing

-8


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rank for Icing:

0-no icing

1-trace rime icingTRC-RIM2-light mixed icingLGT-MXD3-light rime icingLGT-RIM4-light clear icingLGT-CLR5-modetate mixed icingMDT-MXD6-moderate rime icingMDT-RIM7-moderate clear icingMDT-CLR

Define T-Td=ddp

Table 9 RAOB Icing Project


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wet layer temperaturet

-8


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Rap Icing Project ( Forbs and Thompson, 1986 )

(1) stratum icing

-12


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VV Index ( Wang Xinwei, 2002)

10/)]49/()14([]2)50[( TTRHII

RH: relative humidity T: temperature

4 > I I 0 and -0.2pa/s light icing VV=1

7 > I I 4 and -0.2pa/s moderate icing VV=2

I I 7 and -0.2pa/s severe icing VV=3

Final criterions:

3-3-4 integrated icing forecast


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icing area

rank of icing

5 indicesintegration of overlapping technique

weighted averaging method

0 1 2 3

none light moderate severe

Contents


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Thunderstorm

Aircraft Bumps

Aircraft Icing

SevereLee Waves


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Executions and Techniques onSevere Lee Waves4

4


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Executions and Techniques onSevere Lee Waves4

wave length 1.8 ~ 70Km, most is in the range of 5~20Km. Changeswith the height and the wind speed.

amplitude several hundred meters ~ 2Km. Most is 0.3~0.5Km.

vertical speed 2~6 ms-1

Properties The taking place of Lee Waves depends on two terms:

static stability of the air

wind speed

4-1 Scorer Parameter Used in Lee Waves Theory


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2

2

2

21

zu

uugl

( Scorer, 1949 )

u wind speed upright to the mountain ridge

T environmental temperature

g gravity acceleration

d adiabatic vertical temperature descending rate of

dry air

vertical temperature descending rate of theenvironment

1 ( )T

4-1 Scorer Parameter Used in Lee Waves Theory


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2

2

2

21

zu

uugl

( Scorer, 1949 )

2

2

gl

u

When there is wave fluctuations at the lee ofthe mountain, l2 is certain to decrease with the

height. As the wind speed always increases

with height and the stratification is stable or

increases only a little, l2 at upper levels usually

are smaller than that at lower levels. The

smaller l2 is changed with the height, the

possibility of Lee waves is larger.

4-2 arithmetic 2 in forecasting Lee Waves


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favorable situation for Lee waves:

stable stratification

stability at low level larger than at high level

wind direction at low level consistent with that at high level---no inversion

2 lnN gz

20N

layer with N

2

descending

below 500hPa

consistency in winddirection at low and high

vertical section of wind

speed

X

Y

Z

apparent wave fluctuations

with wave length of 10-70Km

maximum vertical speed at

mid-level, small vertical speed

at low and high

Lee

Waves

4-3 integration in forecasting Lee Waves


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As the approaches introduced previously,the integrated multi-index-overlapping

techniques will also be applied in the forecast of

the severe mountain Lee Waves areas.


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Thanks for your attention!

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