Nowcasting Development and Users Need in Aviation

Transcription

1 Nowcasting Development and Users Need in Aviation Ping-Wah Peter LI Aviation Weather Services Branch, Hong Kong Observatory Working Group in Nowcasting Research Geneva, WMO 8-10 February 2011

2 Outline The challenge MSTA objective Guiding principles MSTA initial concepts Outstanding questions Next Steps Other special requirement

3 The challenge ICAO Annex 3 stipulates MET Services in support of aerodrome operations Aerodrome Forecast (TAF) Trend-type Landing Forecast (TREND) Aerodrome Warnings in support of FIR, regional, global operations AIRMET/SIGMET WAFC charts Most in highly-condensed, coded, textual format Current Practice: TAF VHHH Z 0606/ KT 7000 FEW040 TX22/0607Z TX23/0707Z TN16/0623Z TEMPO 0606/ HZ BECMG 0608/ KT BECMG 0703/ KT TEMPO 0704/ HZ BECMG 0708/ KT=

4 An aircraft report (21/11/2006( 21/11/2006)

5

6 Weather radar showing intense echoes

7 FTHK31 VHHH AAB TAF AMD VHHH Z 0816/ KT 7000 FEW020 SCT060 TX33/0906Z TN26/0816Z TEMPO 0816/ G40KT 2000 TSRA +SHRA FEW008 SCT012CB BKN050 BECMG 0818/ KT TEMPO 0822/ HZ SHRA TEMPO 0908/ G30KT 2000 TSRA +SHRA FEW008 SCT015CB BKN050 BECMG 0909/0911 VRB05KT=

8 The challenge These Services do not meet the needs of today s aircraft operators Not specific enough Nothing between aerodrome and FIR/global scale No info on important parameters (location and movement of convection, crosswind, headwind, winter conditions such as snow fall rate) The problem has been recognized by ICAO MET services required by ATM to optimize traffic flow in the enroute and terminal areas Various Member states are developing new MET services to address their needs

9 What the WMO is doing An expert team was established by the Commission for Aeronautical Meteorology (CAeM) of the WMO at its 13th Session in 2006, and re-constituted at its 14th Session in 2010 Name changed from New Terminal Forecast (NTF) to Meteorological Services for the Terminal Area (MSTA) to reflect that the new Services will supplement the TAF, not replace it Supported by a Task Team on User Needs (TT-UN) to liaise with ICAO groups and aviation stakeholders Aerodrome Meteorological Observation and Forecast Study Group (AMOFSG) and its Ad Hoc Working Group Air Traffic Management Requirements and Performance Panel (ATMRPP) IFALPA, IFATCA, IATA, etc.

10 MSTA objective to address these new and evolving ATM user needs and to avoid the costly parallel development of similar weather products of varying and confusing data formats to develop a detailed MSTA proposal, supported by ICAO and the aviation user communities, ready for endorsement by the next Conjoint ICAO MET/AIM Divisional Meeting/WMO CAeM Session (currently scheduled for 2014) and reflected in ICAO Annex 3 (in 2016) Focussing effort on a particular need: the terminal area 10

11 Guiding principles (1) For effective CDM (Collaborative Decision Making), the need to have a common picture Ease of use ( high glance value ) is paramount Others (States, organizations) are working on creating the databases, including NextGen Wx and SESAR. MSTA s role is to define the service that will be driven by the data The general approach is nowcasting and NWP However, a key role for the human in the process do QC, provide interpretation. A need to focus human intervention where it s most effective

12 Guiding principles (2) Follow needs as identified by ICAO including elements, type of guidance (deterministic or probabilistic), attainable accuracy Have some questions re the ability to meet some of the targets Go beyond basic MET parameters to also consider their impact on ATM; i.e. bridge the gap, e.g. Support to the determination of the active runway Guidance for whether flights need to change the route Focus on operations in and around aerodromes, including airport operations, e.g. de-icing, runway maintenance, ramp operations

13 What will it be A web-based graphical service Fed by a database that will support other services such as charts and a simplified version (text or object) for uplink to the cockpit The gridded/object data would be available for direct integration into users decision-support systems (DSTs) Integrate the most important info in an easy-to-use fashion, and colour-coded Red : High impact on ATFM (action recommended) Yellow : Possible impact to ATFM (manageable) Green (Blue?) : Chance of impact is low but cannot be excluded Detailed weather scenario/conditions/threshold determined by MET Authority and user

14 What will it be A "recommended practice, not a regulatory service; i.e. optional for a State to offer this service, but if it does, then it will define how A flexible framework. focussing on a few basic parameters now (convection, winds, low visibility, winter weather) Expandable to include other parameters as techniques become available

15 MSTA timeframe Three timeframes (3-tier) to support differing needs Nowcast (0 to 1-2 hours) High-resolution, rapid update Supports tactical decision-making Short-term forecast (up to 6 hours) Lower resolution, covers greater area Supports tactical decision-making Outlook (up to 2 days ahead) Even coarser resolution nowcasting blending with NWP NWP Supports pre-tactical (or strategic) decision-making 15

16 graphics MSTA initial concept on convection (nowcast) tabular TAF VHHH Z 0300/ FEW020 SCT040 TX28/0306Z TN22/0223Z TEMPO 0305/ TSRA +SHRA FEW008 SCT012CB= Significant weather forecast for the next 24 hours ( UTC) Intense thunderstorms and CB associated with a trough of low pressure will move northeast away from NTF region gradually within the next 6 hours. Visibility will drop to around 1500m in heavy showers. There will be high chance of gusts (80%) reaching 40 knots at VHHH during UTC Outlook for hours ( UTC) Typhoon Ketsana is expected to enter the South China Sea. Embedded CB and isolated thunderstorms will start to affect the southeastern part of NTF region from around UTC. The chance of northerly crosswinds reaching 20 kt with significant low level turbulence will become medium to high (60-80%) at VHHH during UTC. Live demo of sample Integrated Display available at: TAF Textual description 16

17 MSTA initial concept on convection (Short Term Forecast) 17

18 MSTA initial concept on convection (outlook) 18

19 Japanese Met Agency initiative Wind (Alert Metric) Crosswind comp with pcpn Vsby CIG Convec tion Snowfall rate Wind shear Red >=40 >=30 >=25, MDT to HVY <500m <200 ft TS overhead >= 1cm/h >=30 at sfc. >=50 blw 5000 Yellow >=30, gust to >=50 >=25 >=20, MDT to HVY TS in vcnty MDT or HVY Blue TS in TAF Criteria are terminal specific

20 Tabular format sample Japanese Met Agency initiative Graphical format (sample)

21 International Trend Automated Thunderstorm Alert Service (Australia) 21

22 International Trend Météo-France Thunderstorm detection and forecast for Air Traffic Control Application de Signalisation et Prévision des Orages pour le Contrôle Aérien (ASPOC) Convection monitoring based on weather radar and lightning data 4 intensity (dbz) levels relevant to ATC operations. 30-min forecast Trial ASPOC-3D, based on wx radar, lightning data and satellite imagery (cloud top, Zmax) 22

23 International Trend MIT Lincoln Lab Route Availability Planning Tool (RAPT) Operational at New York. Integrated into FAA Integrated Terminal Weather System (ITWS) An automated tool intended to help ATC and airline dispatchers determine the specific departure routes and departure times that will be affected by significant convective weather TAF VHHH Z 1418/ KT 7000 FEW010 SCT025 BKN060 TX29/1506Z TN24/1422Z TEMPO 1418/1421 VRB20G30KT 2500 TSRA +SHRA FEW008 SCT012CB BKN040 TEMPO 1421/ SHRA= 23

24 Validation and Verification (V&V) process People are most comfortable with deterministic answers (i.e. yes/no, specific values). However, people also request uncertainty information at times When predicting the occurrence of a thunderstorm at a specific point (a specific circle of 5 km radius), skill currently is limited to about 30 minutes Thus longer-term predictions need to be presented using a larger circle, reducing the accuracy targets, or taking a different approach (i.e. probabilistic) A challenge to create probabilistic guidance that s meaningful. Also the need to incorporate a measure of confidence in the forecast

25 Outstanding questions A consensus for the need for probabilistic forecasts how to generate and encompass this information such that it fulfils user needs and is used appropriately? The new MET service has to be supported by a well documented and transparent validation and verification (V&V) process. What relevant verification metrics to be used to include the user perspectives in the V&V process? How to define the operationally desirable accuracy of forecasts based on user s perspective, and take into account the current/potential technological advancements in the next decade

26 MET/ATM TF2 Fukuoka, Japan, Jan 2011 Development of probabilistic forecasts Use of probabilistic forecasts in risk matrices may be considered to meet user needs. On the other hand, development of probabilistic forecasts should take into consideration the currently achievable scientific and technological capabilities, the existing limitations and constraints such as limited predictability of convective activities in the very short range Verification and validation of forecast accuracy from users perspective Time-success diagram that can be constructed based on past performance of the system. to provide a tolerance limit that defines what can be considered acceptable, and based on these definitions of a hit, a diagram can be constructed that allows to determine the likely lead time or any desired threshold of success achievable accuracy at the typical time horizon Translating weather products to user impacts scenario based (i.e. include weather elements and whether such weather element will reach certain threshold/criteria which correlates to impact. The detailed criteria and weather element to be included is to be determined as agreed between MET authority and user Where to provide the necessary standards and guidance material for MSTA

27 What WGNR can contribute Probabilistic Nowcast/forecast (PNC) research (0-6hr) Ensemble tracking approach? Tuning the parameters in numerical model? Various blending extrapolation with high resolution NWP? Linking the PNC with impacts to aircraft operations? Verification & Validation studies at airports? Collaboration with CAeM on MSTA?

28 MSTA website Prototypes and questionnaire to collect feedback 28

29 Sample Show Case #1: Advanced Aviation Nowcasting System (AANS) in Support of Air Traffic Management by Blending Radar Nowcasting Data with NWP Forecast

30 WMO/CAeM New Terminal Weather Forecast (NTF) Convective Products under development (3-tiers): Nowcast (0-1hr) Short-term (1-6hr) Outlook (6 hr 1 or 2 days)

31 Animation control Radar-based TS nowcasting System - Aviation Thunderstorm Nowcasting System (ATNS) for Select day timetactical flight (0-1 hr) planning Select REF, TOP, MAX, VIL Choose range circles Choose routes and way-points Forecast time series at waypoints Cursor values zoom/pan overlaid on googlemap Storm intensity radar 3km REF Way-points Flight route Time series forecasts of thunderstorm intensities at specific locations Colored gridded radar reflectivity Trial product has been under testing by local ATC & ATMD since 2009

32 ATNS on AMIDS

33

34 50km/hr SW lies with some embedding short waves TREC (Tracking Radar Echoes by Correlation) 3 km TREC wind of a heavy (>30mm/hr) rainstorm 23 UTC 9 August 2002 Stronger to the right, weaker to the left 3 km TREC wind of Typhoon Maria 31 August 2000

35 Short-term convective forecast (0-6 hr) Advanced Aviation Nowcasting System (AANS) Intelligently blending radar-based nowcast with NWP forecasts extrapolation effective in advective cases; dissipative cases effective in nonlinear moving; rapidly changing cases Nowcast High resolution NWP high resolution, rapidly updated seamless short-term convective forecast

36 Extending ATNS to 6 hr using modified Semi- Lagrangian Advection Robert scheme (3 iterations) Bi-cubic Lagrangian interpolation Flux limiter (local max, min constraint) One-way nested resolution 1.1km -> 0.5km Less dispersive Circulation preserved dz dt Z Z = + u t x = 0 TREC wind Forecast reflectivity TREC wind Up to 6 hr (6-min interval) Forecast reflectivity pure rotation Up to 6 hr (6-min interval)

37 AANS Nowcasting component extended-atns 0-6 hr QPF by extending the linear extrapolation of radar echoes NWP component Non-hydrostatic Model (NHM) 0 6 hr QPF by non-hydrostatic numerical modelling

38 Non-hydrostatic Model (NHM) (adapted from JMA) Fully compressible prognostic: u, v, w, p, θ, q v, q c, q r, q i, q s, q g Data ingested: Doppler radar reflectivity & wind GPS/PWV wind profiler satellite imageries AWS TREC winds 12 hours forecasts updated every hour 141x121 grids (5km) 60 level LAPS analysis adapted from NOAA/GSD

39 Special Features (i) phase correction: to tackle the problem of spatiotemporal errors in the model precipitation forecast using variational technique (ii) calibration of intensity of model QPF: correction of the intensity of model precipitation based on radar-based quantitative precipitation estimate (QPE), and (iii) blending of calibrated model QPF with the radar nowcast, with larger weighting assigned to the nowcast component at short lead times and increasing weighting to the NWP component as lead time increases to 6 hours. (iv) converting precipitation back to reflectivity based on the latest Z-R relation

40 Blending extended-atns with NHM forecasts QPF ( t) = (1 w( t)) QPF + w( t) 1. NHM rain pattern adjustment translation, rotation, deformation ATNS QPF NHM 2. Dynamical blending hyperbolic function with varying end points adjustment β α β α w( T ) = α + T 2 { 1+ tanh[ γ (3 9)] } α, β determined dynamically by past performance

41 T+1hr Extended-ATNS AANS Radar QPE T+2hr T+3hr Not sa

42 T+4hr Extended-ATNS AANS Radar QPE T+5hr T+6hr

43 POD Performance of the extended-atns and AANS forecasts upto 6 hours ahead Forecast time (hour) CSI Forecast time (hour) ATNS AANS ATNS AANS AANS has a higher POD and CSI than the extended-atns beginning after 1-hr forecast time While the POD and CSI of the ATNS drops after 1-hr forecast time, the POD and CSI of AANS maintains at rather stable level until 5-hr forecast time

44 Sample Show Case #2: Airport Thunderstorm and Lightning Alerting System (ATLAS)

45 The Impact of Lightning Warning to the Operations of the Hong Kong International Airport RED Lightning Alert AMBER Lightning Alert Dissemination to users All ground operations have to stop and take measures to protect against lightning strikes Re-fueling, embarkment /disembarkment, baggage/cargo handling would be delayed -> major disruption to airport operations

46 Airport Thunderstorm and Lightning Alerting System (ATLAS) Lightning Location Information System (LLIS) Cloud-to-Ground (CG) lightning data Weather Radar data Doppler Weather Radars HK-GD-MC Lightning Detection Network Tate s Cairn Radar Lightning Detector Tai Mo Shan Radar

47 Weather Radar (SWIRLS) Thunderstorm movement LLIS network Cloud-to-Ground (CG) lightning location

48 ATLAS RED and AMBER Lightning Alerting Areas (HKIA 1km & 5km Regions) RED AMBER 1km 5km Lightning Alert AMBER RED

49 28 Jul :00 18:00 Longest RED Alert : 164 min, 14:42-17:25 Total CG strike : 287 in 4 hours Black Rainstorm Warning in force

50 8 Sep :30 9 Sep :30 2nd longest RED Alert : 93 min, 23:55-01:27 Total CG strikes : 1028 in 3 hours (highest in record) RED Rainstorm Warning in force

51 Airport Thunderstorm and Lightning Alerting System (ATLAS) \atlas_selected_showcase_07 28.html \atlas_selected_showcase_09 08.html

52 Time-lagged ensemble score >=N, RED (e.g., N=20) score >=1, AMBER otherwise, GREEN

53 Airport Lightning Warning Lights and Siren ALWS

54 Dedicated Web Site (AMIDS) for Airport Users

55 Webpage and Mobile Platform iphone

56 Real-time Verification System - Digital and Image Database

57 THANK YOU