Short-Term Weather Forecasting for Probabilistic Wake-Vortex Prediction
|
|
- Jean Payne
- 6 years ago
- Views:
Transcription
1 Short-Term Weather Forecasting for Probabilistic Wake-Vortex Prediction Frank Holzäpfel Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany Summary of WakeNet3-Europe-Workshop 10 and 11 May 2010 Institut für Physik der Atmosphäre DLR, Oberpfaffenhofen, Germany... and previous activities
2 Short-Term Weather Forecasting for Probabilistic Wake-Vortex Prediction SESAR WP 11.2 Meteorological Services challenges of weather prediction requirements, uncertainties and methods of probabilistic wake vortex prediction nowcasting methods numerical weather prediction methods deterministic predictions ensemble prediction methods feasibility and priorities thanks to: George Craig (LMU), Matthias Steiner (NCAR), M. Raschendorfer (DWD), Daniel Sacher (MeteoSolutions), Klaus Dengler (DLR), Kirstin Kober (DLR)
3 SESAR WP 11 SWP 11.1 Flight and Wing Operations Centre SWP 11.2 Meteorological Services EUMETNET Consortium 11 Meteorological Services AustroControl BelgoControl DLR NLR
4 High Level Strategy of SWP 11.2 Identify sensitivities of the flight life cycle to meteorology Understand how these sensitivities will change as ATM, aircraft, airport and meteorological systems evolve Provide proof-of-concepts Developing dedicated & innovative MET services Integrate these MET services into future ATM system in an optimal way.
5 Project Management & Coordination Consolidation of Operational Requirements Consolidation of Technical Requirements Pre Operational Validation Capabilities, integration, Feasibility & Options Integration with SWIM Technical Infrastructure Prototype(s) Development & Verification MET Transverse Support, Consultancy & Advice GIE/EIG EUMETNET, Registered Number RPM Bruxelles 5
6 dealing with probabilities is daily life... (Hagedorn 2009) Nothing is certain in this world there is nothing certain but death and taxes. (Benjamin Franklin) In many situations, decisions have to be based on probabilities the theory of probabilities is at bottom only common sense reduced to calculus. (Pierre-Simon, Marquis de Laplace) Interpretation of probabilities is sometimes not straightforward math is hard, let s go shopping. (Barbie) Appropriate presentation can help to make the right decisions solving a problem simply means representing it so as to make the solution transparent. (Herbert A. Simon) Training Course 2009 NWP-PR: How to Communicate Uncertainties 6/33
7 weather is a chaotic phenomenon... Lorenz attractor (1963), the prototype chaotic model.. (Palmer 2009) u t uu 2Ωu 1 0 p g k 0 F
8 time & space scales of atmospheric motion (The Remote Sensing Tutorial, NASA) - wind and turbulence scenarios depend on phenomena with a wide range of characteristic length and time scales - predictability may largely depend on the prevailing weather situation
9 (time-lagged ensemble Klaus Dengler, DLR) ultimate goal minimization, knowledge, and use of uncertainties of meteo parameters on average, more compact probabilistic wake vortex predictions
10 Requirements for meteo input parameters vertical profiles of: crosswind, headwind/tailwind, TKE, EDR, potential temperature in height ranges where WV develop vertical resolution: 20 m - 50 m prediction horizon: 2 min - 6 min - 20 min - 1 hour - 6 hours + appropriate probability density distributions (averages, standard deviations)
11 Prediction Skill deterministic scoring results (P2P) lateral transport: most important, easy to model, largest uncertainty RMS 5 15 / 0 RMS z / b 0 RMS y / b 0 best median factor 2-4 worst median worst median 86 m²/s 17 m 34 m
12 Probabilistic Methods Probabilistic Methods - Systematic Systematic Monte Carlo Simulation (PVM) ) ( ) ( ) TKE( ) ( ) ( ) ( ) (, ) (, ),TKE( ) (, ) (, ) ( z z z z w z v z u z z z w z z v z u...,,,,, b z y x b z y x consider uncertainties of initial, environmental, (model) parameters: difficulties: - specification of uncertainties - computation times - intrinsic wake vortex variability / deformation
13 Probabilistic Methods - Hybrid (empirical) Probabilistic Two-Phase Wake Vortex Model P2P fixed uncertainties: variation of decay parameters uncertainty allowances ( 2, u,0.8t 2 );( 2, l,1.2 T b, ) dynamic uncertainties: uncertainty allowances y 2 C q C v ( ), z ( ) y, z ( ) dt u l u l q sh sh 2 model calibration with measurement data: uncertainty allowances
14 probabilistic short-term term weather prediction methods survey - nowcasting methods (extrapolation of observed values in space and time) - persistence assumption - Lagrangian approaches - simple physical or statistical models - numerical weather prediction models (NWP) - deterministic NWP (uncertainty estimates from subgrid scale models) - ensemble prediction method - multi model, initialization, perturbation ensemble - time-lagged ensemble - spatial ensemble - combinations of the above
15 Forecast Skill of Nowcasting and NWP - Theory: theoretical limit of predictability (chaos) - Nowcasting Methods: very high initial skill followed by rapid decrease - NWP Models: skill over a longer period since dynamical processes simulated (after Kober 2009) Lin et al, 2005; Golding, 1998
16 Forecast Skill of Nowcasting and NWP WV prediction: crossover time ~ 1 hour precipitation prediction: blending of Nowcasting and NWP improves predictability NWP nowcasting blended Frech M., Holzäpfel F., J. Aircraft Kirstin Kober, DLR
17 Example: Short-term term Prediction of Wind and Temperature Profiles based on WTR data for the Wake Vortex Warning System at Frankfurt Airport measurements + fits prediction of trend + confidence interval Daniel Sacher
18 NWP: microscale (deterministic) approach deterministic numerical weather predictions, including assimilation of observations taken in the airport environment, might well capture the average state of the atmosphere subgrid scale variability of weather parameters makes the dominant contribution to the overall uncertainty currently, the turbulence parameterization of the COSMO model is being augmented: Improved EDR forecasts considering effects of horizontal shear, mountain blocking, and convection M. Raschendorfer, DWD
19 ensemble prediction (mesoscale( mesoscale) ) approaches (M. Steiner, NCAR)
20 Multi model, initialization, perturbation ensembles Example: Hurricane track & intensity prediction Hurricanes can cause huge societal impacts Focus on storm track, timing, & intensity (both precipitation & wind) Translation of hurricane track, size & intensity ensemble into probabilistic evacuation area, storm surge, damage, disruption of services, economic impact, etc. Ensemble of Hurricane Tracks M. Steiner, NCAR M. Steiner, NCAR
21 Multi model, initialization, perturbation ensembles Example: Hurricane track & intensity prediction Hurricanes can cause huge societal impacts Focus on storm track, timing, & intensity (both precipitation & wind) Translation of hurricane track, size & intensity ensemble into probabilistic evacuation area, storm surge, damage, disruption of services, currently too costly for wake vortex applications economic impact, etc. initiative to install common European-wide, high-resolution ensemble prediction systems (Chiara Marsigli, Servizio Idro-Meteo-Clima, Bologna) Ensemble of Hurricane Tracks M. Steiner, NCAR M. Steiner, NCAR
22 Example: Time-lagged ensemble K. Dengler, DLR COSMO NWP model with assimilation of SYN, TEMP, AMDAR, Radar, RASS
23 Use of Time-Lagged Ensembles for Probabilistic WV Predictions extension of P2P envelope of 3 4 runs: fast decay: 2, u, 0.8T 2, N 2 N, 2 intermediate (det.) decay: slow decay: 2,T, mean 2 2, l, 1.2T 2, N 2 N, 2 3 runs wind envelopes: u 2 u, v 2 v 4 runs uncertainty allowances: 0.2, 0 0.5b 0 y u( l), z u( l) y, z ( ) 2 C q C v q sh sh 2 dt
24 Use of Time-Lagged Ensembles for Probabilistic WV Predictions preliminary findings mean and median of TLE superior to deterministic predictions ensemble spread only partially encloses observations need to establish new skill scores (single skill score not sufficient) spread-skill correlation coefficient only slightly positive SSC = v, TLE v, TLE y y ensemble spread RMS y / b0
25 Summary nowcasting methods preferable if measurement instrumentation available added value from spatial ensembles based on measurements (Radar, Lidar, suite of instruments) possibly enhanced by 4D data analysis NWP necessary, if air volumes cannot be covered by instrumentation data assimilation increases forecast skill economical approach: time-lagged ensembles + data assimilation schemes + spatial ensembles alternative: uncertainties from subgrid scale variability of deterministic pred. blending of nowcasting and NWP bridges gap & improves prediction quality all types of NWP may benefit from improved boundary layer physics, parameterizations, and initial conditions weather prediction products can be enhanced by careful calibration
26 presentations and minutes available on
Probabilistic Weather Prediction
Probabilistic Weather Prediction George C. Craig Meteorological Institute Ludwig-Maximilians-Universität, Munich and DLR Institute for Atmospheric Physics Oberpfaffenhofen Summary (Hagedorn 2009) Nothing
More informationProbabilistic Wake Vortex Decay Model Predictions Compared with Observations of Four Field Measurement Campaigns
Probabilistic Wake Vortex Decay Model Predictions Compared with Observations of Four Field Measurement Campaigns Frank Holzäpfel Institut für Physik der Atmosphäre,, DLR Oberpfaffenhofen,, Germany P2P
More informationSESAR 1 & SESAR Deployment Meteorological Services for Aviation
SESAR 1 & SESAR Deployment Meteorological Services for Aviation EUMETNET EIG Rosalind Lapsley Eurocontrol Agency Research Team Workshop on Weather and Atmosphere, London, 25 April 2017 Context of MET in
More informationAircraft Wake Vortex State-of-the-Art & Research Needs
WakeNet3-Europe EC Grant Agreement No.: ACS7-GA-2008-213462 Compiled by:... F. Holzäpfel (DLR) et al. Date of compilation:... (for a complete list of contributors see page 3) Dissemination level:... Public
More informationProbabilistic Winter Weather Nowcasting supporting Total Airport Management
Probabilistic Winter Weather Nowcasting supporting Total Airport Management Jaakko Nuottokari* Finnish Meteorological Institute *With Heikki Juntti, Elena Saltikoff, Harri Hohti, Seppo Pulkkinen, Alberto
More informationAdvances in weather and climate science
Advances in weather and climate science Second ICAO Global Air Navigation Industry Symposium (GANIS/2) 11 to 13 December 2017, Montreal, Canada GREG BROCK Scientific Officer Aeronautical Meteorology Division
More informationCharacterization of Forecast Uncertainty by Means of Ensemble Techniques
Characterization of Forecast Uncertainty by Means of Ensemble Techniques Matthias Steiner National Center for Atmospheric Research Boulder, Colorado, USA Email: msteiner@ucar.edu Short-Term Weather Forecasting
More informationWWRP Implementation Plan Reporting AvRDP
WWRP Implementation Plan Reporting AvRDP Please send you report to Paolo Ruti (pruti@wmo.int) and Sarah Jones (sarah.jones@dwd.de). High Impact Weather and its socio economic effects in the context of
More informationDATA FUSION NOWCASTING AND NWP
DATA FUSION NOWCASTING AND NWP Brovelli Pascal 1, Ludovic Auger 2, Olivier Dupont 1, Jean-Marc Moisselin 1, Isabelle Bernard-Bouissières 1, Philippe Cau 1, Adrien Anquez 1 1 Météo-France Forecasting Department
More informationMeteorology in Continuous Descent Operations
Meteorology in Continuous Descent Operations Rosalind Lapsley, EUMETNET EIG SESAR WP11.2 Leader 19 March 2013 Contents a) Why is meteorology important to CDO? b) What MET information is currently available?
More informationSESAR vs MET. Bart Nicolai CAeM ET-ISA Core Expert Geneva, 23 May 2017
SESAR vs MET Bart Nicolai CAeM ET-ISA Core Expert Geneva, 23 May 2017 1 SESAR context Source: European Commission 2 SESAR ATM evolution Planned position dependent on wind and influenced by (expected) location
More informationTurbulence Measurements. Turbulence Measurements In Low Signal-to-Noise. Larry Cornman National Center For Atmospheric Research
Turbulence Measurements In Low Signal-to-Noise Larry Cornman National Center For Atmospheric Research Turbulence Measurements Turbulence is a stochastic process, and hence must be studied via the statistics
More informationDeutscher Wetterdienst
WakeNet3-Greenwake Workshop Wake Vortex & Wind Monitoring Sensors in all weather conditions DWD s new Remote Wind Sensing Equipment for an Integrated Terminal Weather System (ITWS) Frank Lehrnickel Project
More informationAircraft Wake Vortex State-of-the-Art & Research Needs
WakeNet3-Europe EC Grant Agreement No.: ACS7-GA-2008-213462 Aircraft Wake Vortex Compiled by:... F. Holzäpfel (DLR) et al. Date of compilation:... (for a complete list of contributors see page 3) Dissemination
More informationConsortium for Small- Scale Modelling
Consortium for Small- Scale Modelling Michał Ziemiański 37 th EWGLAM and 22 nd SRNWP meeting 5 October 2015, Belgrade COSMO Governance: General: New COSMO Science Plan was approved by the STC in March
More informationEvolving Meteorological Services for the Terminal Area
Evolving Meteorological Services for the Terminal Area Towards an new participatory approach in ATM H. Puempel Chief, Aeronautical Meteorology Division Weather and Disaster Risk Reduction Dept. WMO The
More informationMeteorological Services for Aviation SWIM & MET-GATE EUMETNET EIG. Rosalind Lapsley & Bart Nicolai World ATM Congress 2017 EUROCONTROL SWIM Workshop
Meteorological Services for Aviation SWIM & MET-GATE EUMETNET EIG Rosalind Lapsley & Bart Nicolai World ATM Congress 2017 EUROCONTROL SWIM Workshop Context of MET in SESAR1 & Deployment The most significant
More informationWake vortex severity assessment a core element of the safety case. German Aerospace Center DLR
Wake vortex severity assessment a core element of the safety case German Aerospace Center DLR Carsten Schwarz, Klaus-Uwe Hahn - Institute of Flight Systems Frank Holzäpfel, Thomas Gerz - Institute of Atmospheric
More informationMontréal, 7 to 18 July 2014
INTERNATIONAL CIVIL AVIATION ORGANIZATION WORLD METEOROLOGICAL ORGANIZATION 6/5/14 Meteorology (MET) Divisional Meeting (2014) Commission for Aeronautical Meteorology Fifteenth Session Montréal, 7 to 18
More informationA SMART SYSTEM FRAMEWORK ENABLING AN INNOVATIVE WEATHER AWARENESS SYSTEM FOR AIRPORTS AND BEYOND
A SMART SYSTEM FRAMEWORK ENABLING AN INNOVATIVE WEATHER AWARENESS SYSTEM FOR AIRPORTS AND BEYOND Christian Schiefer, Sebastian Kauczok, Andre Weipert WSN16 WMO WWRP 4th International Symposium on Nowcasting
More informationRecent advances in Tropical Cyclone prediction using ensembles
Recent advances in Tropical Cyclone prediction using ensembles Richard Swinbank, with thanks to Many colleagues in Met Office, GIFS-TIGGE WG & others HC-35 meeting, Curacao, April 2013 Recent advances
More informationStrategic Radar Enhancement Project (SREP) Forecast Demonstration Project (FDP) The future is here and now
Strategic Radar Enhancement Project (SREP) Forecast Demonstration Project (FDP) The future is here and now Michael Berechree National Manager Aviation Weather Services Australian Bureau of Meteorology
More informationCharacterizing the role of diabatic processes for the modification of mid-latitude Rossby waves and Jetstream winds
Characterizing the role of diabatic processes for the modification of mid-latitude Rossby waves and Jetstream winds Andreas Schäfler 1, George Craig 2, Andreas Dörnbrack 1, Florian Harnisch 4, Uwe Marksteiner
More informationWMO Aviation Research Demonstration Project (AvRDP) and Seamless Trajectory Based Operation (TBO) PW Peter Li
WMO Aviation Research Demonstration Project (AvRDP) and Seamless Trajectory Based Operation (TBO) PW Peter Li Hong Kong Observatory Chair, AvRDP SSC New Era of Aviation Industry WMO Congress XVI recognized
More informationFLORA: FLood estimation and forecast in complex Orographic areas for Risk mitigation in the Alpine space
Natural Risk Management in a changing climate: Experiences in Adaptation Strategies from some European Projekts Milano - December 14 th, 2011 FLORA: FLood estimation and forecast in complex Orographic
More informationCb-LIKE: thunderstorm forecasts up to 6 hrs with fuzzy logic
Cb-LIKE: thunderstorm forecasts up to 6 hrs with fuzzy logic Martin Köhler DLR Oberpfaffenhofen 15th EMS/12th ECAM 07 11 September, Sofia, Bulgaria Long-term forecasts of thunderstorms why? -> Thunderstorms
More informationCurrent best practice of uncertainty forecast for wind energy
Current best practice of uncertainty forecast for wind energy Dr. Matthias Lange Stochastic Methods for Management and Valuation of Energy Storage in the Future German Energy System 17 March 2016 Overview
More informationSTEPS-BE: an ensemble radar rainfall nowcasting system for urban hydrology in Belgium
STEPS-BE: an ensemble radar rainfall nowcasting system for urban hydrology in Belgium Loris Foresti 1,2, Maarten Reyniers 2, Lesley De Cruz 2, Alan Seed 3 and Laurent Delobbe 2 with contributions from
More informationConvective Structures in Clear-Air Echoes seen by a Weather Radar
Convective Structures in Clear-Air Echoes seen by a Weather Radar Martin Hagen Deutsches Zentrum für Luft- und Raumfahrt Oberpfaffenhofen, Germany Weather Radar Weather radar are normally used to locate
More informationNOAA s Severe Weather Forecasting System: HRRR to WoF to FACETS
NOAA s Severe Weather Forecasting System: HRRR to WoF to FACETS David D NOAA / Earth System Research Laboratory / Global Systems Division Nowcasting and Mesoscale Research Working Group Meeting World Meteorological
More informationApplication and verification of the ECMWF products Report 2007
Application and verification of the ECMWF products Report 2007 National Meteorological Administration Romania 1. Summary of major highlights The medium range forecast activity within the National Meteorological
More informationEMADDC. towards operational collection of Mode-S EHS observations in Europe
EMADDC towards operational collection of Mode-S EHS observations in Europe Jan Sondij MBA Programme Manager EMADDC Senior Advisor Aviation Meteorology KNMI Content About EMADDC History of Mode-S EHS research
More informationNowcasting for the London Olympics 2012 Brian Golding, Susan Ballard, Nigel Roberts & Ken Mylne Met Office, UK. Crown copyright Met Office
Nowcasting for the London Olympics 2012 Brian Golding, Susan Ballard, Nigel Roberts & Ken Mylne Met Office, UK Outline Context MOGREPS-UK AQUM Weymouth Bay models Summary Forecasting System Generic Products
More informationThe document was not produced by the CAISO and therefore does not necessarily reflect its views or opinion.
Version No. 1.0 Version Date 2/25/2008 Externally-authored document cover sheet Effective Date: 4/03/2008 The purpose of this cover sheet is to provide attribution and background information for documents
More informationRadar/Lidar Sensors for Wind & Wake-Vortex Monitoring on Airport: First results of SESAR P XP0 trials campaign at Paris CDG Airport
www.thalesgroup.com Radar/Lidar Sensors for Wind & Wake-Vortex Monitoring on Airport: First results of SESAR P12.2.2 XP0 trials campaign at Paris CDG Airport F. Barbaresco, Thales Air Systems 2 / Synthesis
More informationTranslating Ensemble Weather Forecasts into Probabilistic User-Relevant Information
Translating Ensemble Weather Forecasts into Probabilistic User-Relevant Information Matthias Steiner with contributions from Robert Sharman, Thomas Hopson, Yubao Liu, Mike Chapman, and Mary Hayden Email:
More informationCatalysing Innovation in Weather Science - the role of observations and NWP in the World Weather Research Programme
Catalysing Innovation in Weather Science - the role of observations and NWP in the World Weather Research Programme Estelle de Coning, Paolo Ruti, Julia Keller World Weather Research Division The World
More informationMulti-Model Ensemble Wake Vortex Prediction
Multi-Model Ensemble Wake Vortex Prediction Stephan Körner *, Frank Holzäpfel *, Nash'at Ahmad+ * German Aerospace Center (DLR) Institute of Atmospheric Physics + NASA Langley Research Center WakeNet 2015,
More informationRecommendations on trajectory selection in flight planning based on weather uncertainty
Recommendations on trajectory selection in flight planning based on weather uncertainty Philippe Arbogast, Alan Hally, Jacob Cheung, Jaap Heijstek, Adri Marsman, Jean-Louis Brenguier Toulouse 6-10 Nov
More informationAVIATION APPLICATIONS OF A NEW GENERATION OF MESOSCALE NUMERICAL WEATHER PREDICTION SYSTEM OF THE HONG KONG OBSERVATORY
P452 AVIATION APPLICATIONS OF A NEW GENERATION OF MESOSCALE NUMERICAL WEATHER PREDICTION SYSTEM OF THE HONG KONG OBSERVATORY Wai-Kin WONG *1, P.W. Chan 1 and Ivan C.K. Ng 2 1 Hong Kong Observatory, Hong
More informationCAS & CAeM Aviation Research and Demonstration Project Paris-CDG airport
World Meteorological Organization Working together in weather, climate and water WMO CAS & CAeM Aviation Research and Demonstration Project Paris-CDG airport WMO www.wmo.int Paris-CDG airport Mid-latitude
More informationSeamless Probabilistic Forecasts for Civil Protection: from week to minutes
Seamless Probabilistic Forecasts for Civil Protection: from week to minutes Yong Wang, Clemens Wastl, Andre Simon, Mihaly Szűcs ZAMG and HMS An EU project Bridging of Probabilistic Forecasts and Civil
More informationWind-Based Robust Trajectory Optimization using Meteorological Ensemble Probabilistic Forecasts
Wind-Based Robust Trajectory Optimization using Meteorological Ensemble Probabilistic Forecasts Daniel González Arribas, Manuel Soler, Manuel Sanjurjo Rivo Area of Aerospace Engineering Universidad Carlos
More informationA Stochastic Parameterization for Deep Convection
A Stochastic Parameterization for Deep Convection EGU Assembly 7th April 2006 Bob Plant 1, George Craig 2 and Christian Keil 2 1: Department of Meteorology, University of Reading, UK 2: DLR-Institut fuer
More informationEn-route aircraft wake vortex encounter analysis in a high density air traffic region
En-route aircraft wake vortex encounter analysis in a high density air traffic region Ulrich Schumann 1) and Robert Sharman 2) 1) Institut für Physik der Atmosphäre, DLR, Oberpfaffenhofen 2) Research Applications
More informationLAM EPS and TIGGE LAM. Tiziana Paccagnella ARPA-SIMC
DRIHMS_meeting Genova 14 October 2010 Tiziana Paccagnella ARPA-SIMC Ensemble Prediction Ensemble prediction is based on the knowledge of the chaotic behaviour of the atmosphere and on the awareness of
More informationState of the art of wind forecasting and planned improvements for NWP Helmut Frank (DWD), Malte Mülller (met.no), Clive Wilson (UKMO)
State of the art of wind forecasting and planned improvements for NWP Helmut Frank (DWD), Malte Mülller (met.no), Clive Wilson (UKMO) thanks to S. Bauernschubert, U. Blahak, S. Declair, A. Röpnack, C.
More informationNew Meteorological Services Supporting ATM
New Meteorological Services Supporting ATM Meteorological Services in the Terminal Area (MSTA)...providing MET services to support a move from Air Traffic Control (ATC) to more integrated and collaborative
More informationProgress in Aviation Weather Forecasting for ATM Decision Making FPAW 2010
Progress in Aviation Weather Forecasting for ATM Decision Making FPAW 2010 Jim Evans Marilyn Wolfson 21 October 2010-1 Overview (1) Integration with storm avoidance models and ATC route usage models (2)
More informationMesoscale meteorological models. Claire L. Vincent, Caroline Draxl and Joakim R. Nielsen
Mesoscale meteorological models Claire L. Vincent, Caroline Draxl and Joakim R. Nielsen Outline Mesoscale and synoptic scale meteorology Meteorological models Dynamics Parametrizations and interactions
More informationHow to shape future met-services: a seamless perspective
How to shape future met-services: a seamless perspective Paolo Ruti, Chief World Weather Research Division Sarah Jones, Chair Scientific Steering Committee Improving the skill big resources ECMWF s forecast
More informationA study on the spread/error relationship of the COSMO-LEPS ensemble
4 Predictability and Ensemble Methods 110 A study on the spread/error relationship of the COSMO-LEPS ensemble M. Salmi, C. Marsigli, A. Montani, T. Paccagnella ARPA-SIMC, HydroMeteoClimate Service of Emilia-Romagna,
More informationMeasuring In-cloud Turbulence: The NEXRAD Turbulence Detection Algorithm
Measuring In-cloud Turbulence: The NEXRAD Turbulence Detection Algorithm John K. Williams,, Greg Meymaris,, Jason Craig, Gary Blackburn, Wiebke Deierling,, and Frank McDonough AMS 15 th Conference on Aviation,
More informationDeutscher Wetterdienst
Deutscher Wetterdienst Limited-area ensembles: finer grids & shorter lead times Susanne Theis COSMO-DE-EPS project leader Deutscher Wetterdienst Thank You Neill Bowler et al. (UK Met Office) Andras Horányi
More informationWeather Information for Europe 3 May 2018
Weather Information for Europe 3 May 2018 Weatherproofing the network A collaborative approach Jaakko Nuottokari EUMETNET WG AVIMET Chair Head of Aviation and Defence Finnish Meteorological Institute Jaakko.Nuottokari@fmi.fi
More information<Operational nowcasting systems in the framework of the 4-D MeteoCube>
Background Nowcasting is applicable
More informationProtocol of the 1 st COPS Meeting
Protocol of the 1 st COPS Meeting Meeting Dates: September 13-14, 2004 Preparation date: September 30, 2004 Place: University of Hohenheim Authors: Volker Wulfmeyer and Andreas Behrendt, IPM, UHOH List
More informationHave a better understanding of the Tropical Cyclone Products generated at ECMWF
Objectives Have a better understanding of the Tropical Cyclone Products generated at ECMWF Learn about the recent developments in the forecast system and its impact on the Tropical Cyclone forecast Learn
More informationWMO Aeronautical Meteorology Scientific Conference 2017
Session 1 Science underpinning meteorological observations, forecasts, advisories and warnings 1.3 Aerodrome throughput 1.3.1 Wake vortex detection and prediction Frequent-output sub-kilometric NWP models
More informationGenerating probabilistic forecasts from convectionpermitting. Nigel Roberts
Generating probabilistic forecasts from convectionpermitting ensembles Nigel Roberts Context for this talk This is the age of the convection-permitting model ensemble Met Office: MOGREPS-UK UK 2.2km /12
More informationProbabilistic Weather Forecasting and the EPS at ECMWF
Probabilistic Weather Forecasting and the EPS at ECMWF Renate Hagedorn European Centre for Medium-Range Weather Forecasts 30 January 2009: Ensemble Prediction at ECMWF 1/ 30 Questions What is an Ensemble
More informationUpdate on CoSPA Storm Forecasts
Update on CoSPA Storm Forecasts Haig August 2, 2011 This work was sponsored by the Federal Aviation Administration under Air Force Contract No. FA8721-05-C-0002. Opinions, interpretations, conclusions,
More informationTropical Storm List
Tropical Storm Email List http://tstorms.org/ tropical-storms@tstorms.org Tropical-Storms is a mailing list only for those who are professionally active in either the research or forecasting of tropical
More information0-6 hour Weather Forecast Guidance at The Weather Company. Steven Honey, Joseph Koval, Cathryn Meyer, Peter Neilley The Weather Company
1 0-6 hour Weather Forecast Guidance at The Weather Company Steven Honey, Joseph Koval, Cathryn Meyer, Peter Neilley The Weather Company TWC Forecasts: Widespread Adoption 2 0-6 Hour Forecast Details 3
More informationWMO AMDAR Programme Overview
WMO AMDAR Programme Overview Bryce Ford - presenting on behalf of WMO and NOAA FPAW Nov 1, 2012 The WMO AMDAR Program AMDAR Programme Current Status WMO World Meteorological Organization (http://www.wmo.int)
More informationNHC Ensemble/Probabilistic Guidance Products
NHC Ensemble/Probabilistic Guidance Products Michael Brennan NOAA/NWS/NCEP/NHC Mark DeMaria NESDIS/STAR HFIP Ensemble Product Development Workshop 21 April 2010 Boulder, CO 1 Current Ensemble/Probability
More informationJ1.2 Short-term wind forecasting at the Hong Kong International Airport by applying chaotic oscillatory-based neural network to LIDAR data
J1.2 Short-term wind forecasting at the Hong Kong International Airport by applying chaotic oscillatory-based neural network to LIDAR data K.M. Kwong Hong Kong Polytechnic University, Hong Kong, China
More informationConsolidated Storm Prediction for Aviation (CoSPA) Overview
Consolidated Storm Prediction for Aviation (CoSPA) Overview Ray Moy (FAA), Bill Dupree (MIT LL Lead), and Matthias Steiner (NCAR Lead) 27 September 2007 NBAA User Panel Review - 1 Consolidated Storm Prediction
More informationThe impact of airborne wind and water vapour lidar measurements on ECMWF analyses and forecasts
The impact of airborne wind and water vapour lidar measurements on ECMWF analyses and forecasts Martin Weissmann, Andreas Dörnbrack, Gerhard Ehret, Christoph Kiemle, Roland Koch, Stephan Rahm, Oliver Reitebuch
More informationReport of the Scientific Project Manager
Report of the Scientific Project Manager G. Doms, DWD, 4th COSMO General Meeting, Warsaw, Poland Status of the LM LM Version 2.13 (18 January 2002) - Option for use of Wind profiler/rass reports - Adjustments
More informationMotivation & Goal. We investigate a way to generate PDFs from a single deterministic run
Motivation & Goal Numerical weather prediction is limited by errors in initial conditions, model imperfections, and nonlinearity. Ensembles of an NWP model provide forecast probability density functions
More informationAviation Weather Hazards Nowcasting Based on Remote Temperature Sensing Data
Aviation Weather Hazards Nowcasting Based on Remote Temperature Sensing Data Mikhail Kanevsky*, Evgeny Miller**, Nikolay Baranov*** *International Aeronavigation Systems, kanevsky@ians.aero, **RPO ATTEX,
More informationReport on EN6 DTC Ensemble Task 2014: Preliminary Configuration of North American Rapid Refresh Ensemble (NARRE)
Report on EN6 DTC Ensemble Task 2014: Preliminary Configuration of North American Rapid Refresh Ensemble (NARRE) Motivation As an expansion of computing resources for operations at EMC is becoming available
More informationFLYSAFE meteorological hazard nowcasting driven by the needs of the pilot
FLYSAFE meteorological hazard nowcasting driven by the needs of the pilot R. W. Lunnon, Met Office, Exeter, EX1 3PB, United Kingdom., Thomas Hauf, Thomas Gerz, and Patrick Josse. 1. Introduction The FLYSAFE
More informationOutline. Research Achievements
Taiwan Typhoon and Flood Research Institute, National Applied Research Laboratories 11F., No.97, Sec. 1, Roosevelt Rd., Zhongzheng Dist., Taipei City 10093, Taiwan (R.O.C.) http://www.ttfri.narl.org.tw/eng/index.html
More informationBehind the Climate Prediction Center s Extended and Long Range Outlooks Mike Halpert, Deputy Director Climate Prediction Center / NCEP
Behind the Climate Prediction Center s Extended and Long Range Outlooks Mike Halpert, Deputy Director Climate Prediction Center / NCEP September 2012 Outline Mission Extended Range Outlooks (6-10/8-14)
More informationWMO Aeronautical Meteorology Scientific Conference 2017
Session 2 Integration, use cases, fitness for purpose and service delivery 2.4 Trajectory-based operations (TBO), flight planning and user-preferred routing Recommendations on trajectory selection in flight
More informationWeather Forecasting: Lecture 2
Weather Forecasting: Lecture 2 Dr. Jeremy A. Gibbs Department of Atmospheric Sciences University of Utah Spring 2017 1 / 40 Overview 1 Forecasting Techniques 2 Forecast Tools 2 / 40 Forecasting Techniques
More informationOverview on project activities with regard to thunderstorms
Overview on project activities with regard to thunderstorms Arnold Tafferner Co-workers: C. Forster, H. Mannstein, T. Zinner, M. Hagen, T. Gerz, DLR Institut für Physik der Atmosphäre (IPA) Wetter&Fliegen
More informationMode-S EHS data usage in the meteorological domain:
Mode-S EHS data usage in the meteorological domain: derivation of Wind and Temperature observations; and assimilation of these observations in a numerical weather prediction model. Jan Sondij, MBA Senior
More informationJ8.4 NOWCASTING OCEANIC CONVECTION FOR AVIATION USING RANDOM FOREST CLASSIFICATION
J8.4 NOWCASTING OCEANIC CONVECTION FOR AVIATION USING RANDOM FOREST CLASSIFICATION Huaqing Cai*, Cathy Kessinger, David Ahijevych, John Williams, Nancy Rehak, Daniel Megenhardt and Matthias Steiner National
More informationOptimal combination of NWP Model Forecasts for AutoWARN
ModelMIX Optimal combination of NWP Model Forecasts for AutoWARN Tamas Hirsch, Reinhold Hess, Sebastian Trepte, Cristina Primo, Jenny Glashoff, Bernhard Reichert, Dirk Heizenreder Deutscher Wetterdienst
More informationThe benefits and developments in ensemble wind forecasting
The benefits and developments in ensemble wind forecasting Erik Andersson Slide 1 ECMWF European Centre for Medium-Range Weather Forecasts Slide 1 ECMWF s global forecasting system High resolution forecast
More informationFive years of limited-area ensemble activities at ARPA-SIM: the COSMO-LEPS system
Five years of limited-area ensemble activities at ARPA-SIM: the COSMO-LEPS system Andrea Montani, Chiara Marsigli and Tiziana Paccagnella ARPA-SIM Hydrometeorological service of Emilia-Romagna, Italy 11
More informationWG4: interpretation and applications
Federal Department of Home Affairs FDHA Federal Office of Meteorology and Climatology MeteoSwiss WG4: interpretation and applications Pierre Eckert MeteoSwiss, Geneva Topics FIELDEXTRA presentation by
More informationSIXTH INTERNATIONAL WORKSHOP on TROPICAL CYCLONES. Working Group: Phillipe Caroff, Jeff Callaghan, James Franklin, Mark DeMaria
WMO/CAS/WWW Topic 0.1: Track forecasts SIXTH INTERNATIONAL WORKSHOP on TROPICAL CYCLONES Rapporteur: E-mail: Lixion A. Avila NOAA/National Hurricane Center 11691 SW 17th Street Miami, FL 33165-2149, USA
More informationReport from the PDP working group
Report from the PDP working group Craig Bishop, Pat Harr, Shuhei Maeda, John Methven, Mark Rodwell, Istvan Szunyogh, Olivier Talagrand, Heini Wernli ICSC11 Meeting July 2013 PDP mission Main task of the
More informationConvection-Resolving NWP with WRF. Section coordinator Ming Xue University of Oklahoma
Convection-Resolving NWP with WRF Section coordinator Ming Xue University of Oklahoma Convection-resolving NWP Is NWP that explicitly treats moist convective systems ranging from organized MCSs to individual
More informationTHE WAKE VORTEX PREDICTION & MONITORING SYSTEM WSVBS
THE WAKE VORTEX PREDICTION & MONITORING SYSTEM WSVBS PART II: PERFORMANCE AND ATC INTEGRATION AT FRANKFURT AIRPORT T. Gerz 1, F. Holzäpfel 1, W. Gerling 2, A. Scharnweber 2, M. Frech 1, A. Wiegele 1, K.
More informationGROUND-BASED AND AIR-BORNE LIDAR FOR WAKE VORTEX DETECTION AND CHARACTERISATION
GROUND-BASED AND AIR-BORNE LIDAR FOR WAKE VORTEX DETECTION AND CHARACTERISATION A. Wiegele, S. Rahm, I. Smalikho Institut für Physik der Atmosphäre Deutsches Zentrum für Luft- und Raumfahrt (DLR), Oberpfaffenhofen,
More informationNowcasting thunderstorms for aeronautical end-users
Nowcasting thunderstorms for aeronautical end-users Jean-Marc Moisselin Météo-France, Nowcasting Department co-authors: Céline Jauffret (Météo-France) Overview Introduction SAT RADAR NWP image crédit:
More informationWWRP RDP COPS Coordination Structure Science Questions Status Outlook
WWRP RDP COPS Volker Wulfmeyer Institute of Physics and Meteorology University of Hohenheim Stuttgart, Germany, the COPS International Science Steering Committee, and the D-PHASE Steering Committee Coordination
More informationIn-Flight Wake Encounter Prediction with the Wake Encounter Avoidance and Advisory System (WEAA)
In-Flight Wake Encounter Prediction with the Wake Encounter Avoidance and Advisory System (WEAA) Tobias Bauer, Fethi Abdelmoula Institute of Flight Systems, German Aerospace Center (DLR) WakeNet-Europe
More informationEnvironment Canada s Regional Ensemble Kalman Filter
Environment Canada s Regional Ensemble Kalman Filter May 19, 2014 Seung-Jong Baek, Luc Fillion, Kao-Shen Chung, and Peter Houtekamer Meteorological Research Division, Environment Canada, Dorval, Quebec
More informationCombining Deterministic and Probabilistic Methods to Produce Gridded Climatologies
Combining Deterministic and Probabilistic Methods to Produce Gridded Climatologies Michael Squires Alan McNab National Climatic Data Center (NCDC - NOAA) Asheville, NC Abstract There are nearly 8,000 sites
More informationFirst THORPEX International Science Symposium, Montreal
Courtesy of Mel Shapiro Ladies and Gentlemen, The Rossby wave train you can find in the Thorpex Science Plan reached Europe on August 11, 2002. An upper level trough induced the development of a low pressure
More informationWeather Analysis and Forecasting
Weather Analysis and Forecasting An Information Statement of the American Meteorological Society (Adopted by AMS Council on 25 March 2015) Bull. Amer. Meteor. Soc., 88 This Information Statement describes
More informationFernando Prates. Evaluation Section. Slide 1
Fernando Prates Evaluation Section Slide 1 Objectives Ø Have a better understanding of the Tropical Cyclone Products generated at ECMWF Ø Learn the recent developments in the forecast system and its impact
More informationVerification and performance measures of Meteorological Services to Air Traffic Management (MSTA)
Verification and performance measures of Meteorological Services to Air Traffic Management (MSTA) Background Information on the accuracy, reliability and relevance of products is provided in terms of verification
More informationFig. F-1-1. Data finder on Gfdnavi. Left panel shows data tree. Right panel shows items in the selected folder. After Otsuka and Yoden (2010).
F. Decision support system F-1. Experimental development of a decision support system for prevention and mitigation of meteorological disasters based on ensemble NWP Data 1 F-1-1. Introduction Ensemble
More information