Executions and Techniques on SIGMET Consulting Information

Transcription

1 Executions and Techniques on SIGMET Consulting Information Qiang Xuemin April, 2011 Beijing

2 Main topic To briefly introduce the executions and techniques on SIGMET information which have been successfully applied in aeronautic significant weather forecasts.

3 Data used in this work: Conventional telegram report Output products from the global mid-term numerical weather forecast model Satellite data

4 Contents Thunderstorm 4 Phenomena of SIGMET Consulting Information Aircraft Bumps Aircraft Icing Severe Lee Waves

5 Thunder Storm 1 Diagnostics on stabilization index of the atmosphere Executions and Techniques on Thunder Storm Multi-factor-overlapping techniques on thunder storm area Classification and extrapolation of satellite data for convective weather Integrated forecast techniques on thunder storm area

6 About Thunder Storm 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

7 1-1 Diagnostics on stabilization index of the atmosphere Output products from NWF Index characterizing instability of the atmosphere Threshold for these index Potential Forecast for Convective Weather Diagnostics

8 1. Thermal Index Energy Index 2. Humidity Index 2 Diagnostics on stabilization index of the atmosphere 3. Dynamical Index 3

9 1 Thermal Index ⅰ A---index ⅴ Simplified Showalter Index---SSI ⅱ Air mass index---k ⅵ Yamazaki index---kyi ⅲ Potential instability index---i ⅶ Bejerknese Index---BI ⅳ Showalter Index---SI ⅷ Diagnostic on convective instability

10 ⅰ A---index A 500 t850 t 500 ( t to describe the vertical humidity condition in the whole volume td t 500 / t 850 : temperatue at 500 / 850 hpa t d : dew-point ) When A 0, probability of a thunderstrom is 90%

12 ⅱ or Air mass index---k K t t t ( t t ) K d850 d 700 2T T 850 ( T Td ) 850 ( T Td ) the bigger the K index is, the more unstable in the air will be. K < 20 o C, no thunderstorm 20 o C < K <25 o C, single thunderstorm 25 o C < K <30 o C, sporadic thunderstorms 30 o C < K <35 o C, scattered thunderstorms 35 o C < K, massive thunderstorms

14 ⅲ Potential instability index---i I h 200 h 300 h 925 h 925 2h t d 700 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 K <2.79, yes

16 ⅳ Showalter Index---SI SI T T 500 S ---- temperature difference between the stratification curve and the state curve, 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 T s ). T 500 is the environmental temperature at 500hPa positive: rising air mass with high temperature negative: with low temperature Value of SI Index >3 o C Possibility of thunderstorm event little or not 3 o C >SI >0 o C Shower be possible 0 o C >SI >-3 o C Thunderstorm be possible -3 o C >SI >-6 o C Strong thunderstorm be possible -6 o C >SI Severe convective weather be possible

17 1 Thermal Index ⅰ A---index ⅴ Simplified Showalter Index---SSI ⅱ Air mass index---k ⅵ Yamazaki index---kyi ⅲ Potential instability index---i ⅶ Bjerknes Index---BI ⅳ Showalter Index---SI ⅷ Diagnostic on convective instability

18 ⅴ Simplified Showalter Index---SSI SSI T T ' 500 S ---- T s : air mass at 850hPa rising along dry-adiabatic curve till to 500hPa (with temperature Ts ). T 500 is the environmental temperature at 500hPa usually, SSI 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

20 ⅵ Yamazaki index---kyi stabilization of the air temperature advection KYI T A S ( T Td ) 850 at 500hpa While: α=1, β= s,γ=0 (statistically) S (T-T d ) ( units) T A s -1 KYI TA S 1 ( TTd ) { T T A A S S humidity condition at low level KYI pay attention possibility is high in all likelihood

22 ⅶ Bjerknes Index---BI BI Z T 200 Z: thickness from hPa (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%.

24 ⅷ Diagnostic on convective instability se p stable neutral instable or se z stable neutral instable θ se : pseudo-equivalent potential temperature This method usually is used in diagnosing weather systems with systematical updraft flows.

25 1. Thermal Index Energy Index 2. Humidity Index 2 Diagnostics on stabilization index of the atmosphere 3. Dynamical Index 3

26 2 Humidity Index ⅰ TTD T T d difference between air temperature and dew-point temperature ⅱ simple, but useful divergence of the water vapor flux When T-T d =0 saturated. Based on the NWF products, we can get TTD at each grid points.

27 2 Humidity Index ⅰ difference between air temperature and dew-point temperature ⅱ divergence of the water vapor flux

28 ⅱ divergence of the water vapor flux Water vapor flux, depicting the strength and direction of the transportation of the moisture. F H : flux on horizontal F Z : flux on vertical FH V q g F z q V q horizontal wind speed specific humidity vertical speed density of the air ( 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

29 Dynamical Index 1. Thermal Index Energy Index 2. Humidity Index 2 Diagnostics on stabilization index of the atmosphere 3. Dynamical Index 3

30 3 Dynamical Index ⅰ vorticity V v x u y unit: 10-6 s -1 ⅱ divergence D u V x v y unit: 10-5 s -1 ⅱ vertical velocity k 1 D ( D 2 D k 1 k k1) 75 P at 925hPa k level unit: 10-3 hpas -1

31 Energy Index 1. Thermal Index Energy Index 2. Humidity Index 2 Diagnostics on stabilization index of the atmosphere 3. Dynamical Index 3

32 4 Energy Index ⅰ convective available potential energy CAPE ⅱ modified CAPE MCAPE ⅲ normalized CAPE NCAPE ⅳ downdraft CAPE DCAPE ⅴ convective inhibitation CIN

33 ⅰ convective available potential energy CAPE ZEL Tvp Tve CAPE g ( ) dz T Z LFC ve T v pseudo temperature subscript mark e ---- environment air p --- air parcel LFC level of free convection LCL level of condensation EL equilibrium level EAL equivalent area level wet adiabatic curve stratification curve dry adiabatic curve state curve

34 ⅰ convective available potential energy CAPE Two aspects noticeable in computing CAPE 1corrections for T v T v T 1 r / T(1 r) 1 r 2height of LCL surface / h 850 / h 925 / height with the biggest wet-bulb temperature from 1000 to 800hPa

35 ⅱ modified CAPE MCAPE ZEL Tvp Tve MCAPE g [ ( re ri ) p] dz ZLFC Tve ---- r e and r i stand for the mixing ratio of water vapor in liquid and solid state, respectively g (r e + r i ) stands for the dragging function caused by the water component in the air

36 ⅲ normalized CAPE NCAPE CAPE CAPE CAPE H Z Z FCL EL LFC ----designed to consider the effect on the vertical velocity caused by the vertical distribution of the floating force

37 ⅳ downdraft CAPE DCAPE In the body of a storm, when precipitation, ice water or crystal vaporizes in the unsaturated air or melts at the frozen layer, downdraft occurs. p n DCAPE R ( T T ) d ln p p i d e p Zi 1 g ( Tve Tvp ) dz Zn T ---- P i / Z i pressure or height where downdraft begins ve ---- P n / Z n pressure or height when downdraft reaches the ground Approximatively, the maximum down speed can be written as: W max 2 DCAPE

38 ⅴ convective inhibition CIN Z T T LFC e p CIN g dz Zi T B wet adiabatic curve T B mean temperature at ABL (atmospheric boundary layer) subscript mark e ---- environment air p --- air parcel Z LFC Z i level of free convection original level stratification curve dry adiabatic curve WCIN state curve 2CIN

39 1 Executions and Techniques on Thunder Storm Diagnostics on stabilization index of the atmosphere Thunder Storm Multi-factor-overlapping techniques on thunder storm area Classification and extrapolation of satellite data for convective weather Integrated forecast techniques on thunder storm area

40 1-2 Multi-factor-overlapping method on thunderstorm area trough =0 SW airflow =0 chart for multi-factor-overlapping method

41 indices selection stability indices K>35 SI<0 A>0 KYI 1 BI 94 TI>0 I 2.79 se p 0 water vapor indices T T d ( qv ) and or ( T T ) ( T T ) d d925 ( qv ) ( qv ) momentum indices W W ( V ) and ( V ) ( V) V energy indices CAPE>200 convective precipitation RC>3mm

42 Multi-factor-overlapping method in forecast thunderstorm Step-wise decreasing FAR Executions of indices overlapping Integrated judgment on severe weather To judge whether If 15 NP>8 and CAPE>800 indices meet the Or NP>11 requirements or not. If it Or CAPE>2000 is true, NP+1. K Or Rc>5mm ( T T ) ( T T ) d d925 K 15 se500 se700 se850 se Then there will be a thunderstorm within the forecast area.

43 1 Executions and Techniques on Thunder Storm Diagnostics on stabilization index of the atmosphere Thunder Storm Multi-factor-overlapping techniques on thunder storm area Classification and extrapolation of satellite data for convective weather Integrated forecast techniques on thunder storm area

44 1-3 classification and extrapolation of satellite data for convective weather including: quality control on Satellite data classification and extraction of convective cloud, jet stream cloud, frontal cloud and cloud systems related with Lee waves obtaining live information of sandstorm

45 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

46 1 Executions and Techniques on Thunder Storm Diagnostics on stabilization index of the atmosphere Thunder Storm Multi-factor-overlapping techniques on thunder storm area Identification and extrapolation of satellite data for convective weather Integrated forecasting techniques on thunder storm areas

47 1-4 Integrated forecast techniques on thunder storm area Regression integrated technique is used to forecast the thunder storm rainfall area. Basic principle: b 0 b i Y b 0 n i1 b i Y i mean of the forecast objective coefficient, reflecting the relationship between forecasts (actually, they represents the variety forecast measures)

48 1-4 Integrated forecast techniques on thunder storm area Steps: 1 a variety methods forecasting thunderstorms are used to compute inversely the history samples ; 2 Use MOS method, output of the forecasts are treated as different factors; 3 Set up a forecast model by using the regressive integrated technique; 4 Substitute results of the various methods to the model and draw the final forecast conclusion.

49 Contents Thunderstorm 4 Phenomena of SIGMET Consulting Information Aircraft Bumps Aircraft Icing Severe Lee Wave

50 2 Executions and Techniques on Aircraft Bumps

51 2-1 Aircraft Bumps and The Turbulences 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

52 2-2 Mechanism of the Turbulences: Loading coefficient n Y G a W ρ V K S Y G ascending force gravity acceleration n WVK 2G S vertical wind speed of the gust density of the air speed of the aircraft coefficient of slope area of the airfoil n increment of n n Y G ma mg a g 1 Y VSKW 2

53 2-3 Diagnose and Forecast on Aircraft Bumps ⅰ Richardson Index ⅴ L Index ⅱ Ellrod Index ⅵ Integrated Diagnose ⅲ Ti Index ⅳ E Index

54 ⅰ Richardson Index---a classical method Ri ( g / )( / z) v / z 2 1static stability of the layer 2vertical sheer of the layer The 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 R i is helpful in figuring out the layer on which the aircraft bumps might take place.

56 Ellrod Index ⅱ In Practical, [ ] TI VWS DEF CVG y u x v y v x u DEF y v x u CVG z V VWS negative of divergence wind shear on vertical direction flow field deformation made by stretch in horizontal and shear in vertical TI VWS DEF unit: 10-7 s -2

57 Table for Bump and TI Degree of bump Value of TI light TI 4 Light-medium 4<TI 8 medium 8<TI<16 severe TI 16

58 ⅲ T i Index----applied in NMC, U.S.A V V V Cp V Ti 2 ( ) V T V V wind vector potential temperature The bigger Ti index is, the stronger the bumps will be. Ti >5.1 a medium Bump might occurs. Ti <1.7 no bumps.

60 ⅳ E Index----Dutton (1989) E h 0.25 v 10.5 h wind shear in horizontal unit: m/s/100km v wind shear in vertical unit: m/s/1000km Table3 relationship between E index and the probability of a medium CAT in 100Km-averaged flight test E P(%)

62 ⅴ L Index method----a probability method Step 1 compute L index u T u L z n n 2.52 u n u x 2 v y 2 wind shear in horizontal unit: m/s/100km u z u z 2 v z 2 wind shear in vertical unit: m/s/1000km T n T x 2 T y 2 temperature shear in horizontal unit: /s/100km

63 ⅴ L Index method----a probability method Step 2 get the probability------p p 0. 59L 1 e 1 generally, 86%>P 75% light CAT forecast output %>P 86% moderate CAT forecast output P 96% svevere CAT forecast output --- 3

64 ⅵ integrated diagnose on CAT areas 5 i i i1 F k f k f k f k f k f k f k i f i weight output for 5 forecasts

65 Contents Thunderstorm 4 Phenomena of SIGMET Consulting Information Aircraft Bumps Aircraft Icing Severe Lee Wave

66 3 Executions and Techniques on Aircraft Icing

67 3-1 Aircraft Icing

68 3-1 Aircraft Icing

69 3-2 Factors affecting Aircraft Icing I weather conditions temperature 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

70 3-3 Arithmetic on Aircraft Icing

71 3-3-1 Icing computation scheme 1 step1. computations on LWC L c 0.95 Ph ( Qc Qh ) /(2.87Th ) ( for cumulous cloud ) L n f E( T c T h ) /( T( T 36) quantities at the flight level t k : temperature( ) P h : pressure f: relative humidity T h : temperature (K) Q h : saturated specific humidity quantities at the cloud bottom E T c : temperature Qc: saturated specific humidity 2 ) ( for stratus cloud ) 7.5t /(237.5 h ) 6 h t.1110 T c T T h 2

72 Table4 Levels for liquid water content (LWC) value L <L <L <L <L 1.0 L 1.0 rank L1 L2 L3 L4 L5 L6

73 step2. diameter of moderate cloud droplet Table 5 diameters of moderate water droplets for different clouds cloud St Sc Ns As Ac Cu Cb D MV unit: μm Table 6 classification for D mv D MV >50 rank D1 D2 D3 D4 D5

74 step3. classification for environmental temperature Table 7 classification for environmental temperature value T>0-5<T 0-10<T -5-20<T -10 T<-20 rank T1 T2 T3 T4 T5

75 step4. index matrix for severe icing I index T1: T>0, I=0

76 T2:-5 <T 0 Index I D1 D2 D3 D4 D5 L L L L L L

77 T3:-10 <T -5 index I D1 D2 D3 D4 D5 L L L L L L

78 T4:-20 <T -10 index I D1 D2 D3 D4 D5 L L L L L L

79 T5:T -20 指数 I D1 D2 D3 D4 D5 L L L L L L

80 3-3-2 Icing computation scheme 2 criterions on Icing -8 <t<0 and t-td <t -8 and t-td <t -16 and t-td 4.0 Table 8 rank for Icing Advection of Temperature (AT) Property of AT cold advection neutral cloud type strong cumulus cumuliform stratus rainfall yes no yes no yes no rank of icing severe moderate moderate light moderate light little

81 3-3-3 Icing computation scheme 3 rank for Icing: 0-no icing 1-trace rime icing(trc-rim) 2-light mixed icing(lgt-mxd) 3-light rime icing(lgt-rim) 4-light clear icing(lgt-clr) 5-modetate mixed icing(mdt-mxd) 6-moderate rime icing(mdt-rim) 7-moderate clear icing(mdt-clr) Define T-T d =ddp

82 Table 9 RAOB Icing Project wet layer temperature(t: ) -8<t<=0-16<t<=-8-22<t -16 t td =ddp ddp 1 1<ddp 3 ddp 1 1<ddp 3 ddp 4 Vertical decendi ng rate stable unstable stable unstable stable unstable stable unstable 2 >2 2 >2 2 >2 2 >2 type of icing LGT-RIM MDT-CLR TRC-RIM LGT-CLR MDT-RIM MDT-MXD LGT-RIM LGT-MXD LGT-RIM

83 3-3-3 Icing computation scheme 4 Rap Icing Project ( Forbs and Thompson, 1986 ) (1) stratum icing -12 <t 0, f 85% with t<-12, f<85% at upper level (2) ice rain icing t 0, f 80% with t>0,f=80% at upper level (3) unstable condition icing -20 <t 0, f 56% at lower unstable level (4) common icing -16 <t 0, f 63%

84 3-3-3 Icing computation scheme 5 VV Index ( Wang Xinwei, 2002) II [( RH 50) 2] [ T ( T 14) /( 49)]/10 RH: relative humidity T: temperature Final criterions: 4 > II 0 and ω -0.2pa/s light icing VV=1 7 > II 4 and ω -0.2pa/s moderate icing VV=2 II 7 and ω -0.2pa/s severe icing VV=3

85 3-3-4 integrated icing forecast 5 indices integration of overlapping technique icing area weighted averaging method rank of icing none light moderate severe

86 Contents Thunderstorm 4 Phenomena of SIGMET Consulting Information Aircraft Bumps Aircraft Icing Severe Lee Waves

87 4 Executions and Techniques on Severe Lee Waves

88 4 Executions and Techniques on Severe Lee Waves Properties wave length 1.8 ~ 70Km, most is in the range of 5~20Km. Changes with the height and the wind speed. amplitude several hundred meters ~ 2Km. Most is 0.3~0.5Km. vertical speed 2~6 ms -1 The taking place of Lee Waves depends on two terms: static stability of the air wind speed

89 4-1 Scorer Parameter Used in Lee Waves Theory l g 2 u 2 1 u 2 z u 2 ( Scorer, 1949 ) u T g γ d γ wind speed upright to the mountain ridge environmental temperature gravity acceleration adiabatic vertical temperature descending rate of dry air vertical temperature descending rate of the environment 1 ( ) T

90 4-1 Scorer Parameter Used in Lee Waves Theory l g 2 u 2 1 u 2 z u 2 ( Scorer, 1949 ) l 2 g 2 u When there is wave fluctuations at the lee of the mountain, l 2 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, l 2 at upper levels usually are smaller than that at lower levels. The smaller l 2 is changed with the height, the possibility of Lee waves is larger.

91 4-2 arithmetic 2 in forecasting Lee Waves 1 favorable situation for Lee waves : 2 ln N g z 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 6 2 N layer with N 2 descending below 500hPa apparent wave fluctuations with wave length of 10-70Km maximum vertical speed at mid-level, small vertical speed at low and high X Y Z 3 consistency in wind direction at low and high 4 vertical section of wind speed

92 4-3 integration in forecasting Lee Waves 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.

93 Thanks for your attention!