Satellite-based thunderstorm tracking, monitoring and nowcasting over South Africa

Similar documents
Overview on project activities with regard to thunderstorms

Nowcasting of Severe Weather from Satellite Images (for Southern

Satellite-based Convection Nowcasting and Aviation Turbulence Applications

Improving real time observation and nowcasting RDT. E de Coning, M Gijben, B Maseko and L van Hemert Nowcasting and Very Short Range Forecasting

Satellite-Based Detection of Fog and Very Low Stratus

Cb-LIKE: thunderstorm forecasts up to 6 hrs with fuzzy logic

Keywords: weather information for ATC, nowcasting, forecasting, severe weather

RDT-CW: TOWARD A MULTIDIMENSIONAL DESCRIPTION OF CONVECTION

Thunderstorm Nowcast and Forecast for Aviation Safety and Efficiency

OPERATIONAL USE OF METEOSAT-8 SEVIRI DATA AND DERIVED NOWCASTING PRODUCTS. Nataša Strelec Mahović

Page 1/8 Long duration validation of PGE11. SAF - Nowcasting Product Assessment Review Worshop (Madrid ctober 2005

CHARACTERISATION OF STORM SEVERITY BY USE OF SELECTED CONVECTIVE CELL PARAMETERS DERIVED FROM SATELLITE DATA

REPORT ON THE ACTIVITIES OF THE EUMETSAT-ESSL CONVECTION WORKING GROUP

MSG FOR NOWCASTING - EXPERIENCES OVER SOUTHERN AFRICA

METEOSAT CONVECTIVE INITIATION PRODUCT WITH AND WITHOUT CLOUD TRACKING - EXPERIENCES

Judit Kerényi. OMSZ - Hungarian Meteorological Service, Budapest, Hungary. H-1525 Budapest, P.O.Box 38, Hungary.

Hail nowcast exploiting radar and satellite observations

Cb-TRAM: Tracking and monitoring severe convection from onset over rapid development to mature phase using multi-channel Meteosat-8 SEVIRI data

NOWCASTING AND FORECASTING THUNDERSTORMS FOR AIR TRAFFIC WITH AN INTEGRATED FORECAST SYSTEM BASED ON OBSERVATIONS AND MODEL DATA

RGB Experts and Developers Workshop 2017 Tokyo, Japan

Validation Report for Precipitation products from Cloud Physical Properties (PPh-PGE14: PCPh v1.0 & CRPh v1.0)

PRECONVECTIVE SOUNDING ANALYSIS USING IASI AND MSG- SEVIRI

NOWCASTING THUNDERSTORM HAZARDS FOR FLIGHT OPERATIONS: THE CB WIMS APPROACH IN FLYSAFE

Early detection of thunderstorms using satellite, radar and

Meteosat Third Generation (MTG): Lightning Imager and its products Jochen Grandell

A statistical approach for rainfall confidence estimation using MSG-SEVIRI observations

MSGVIEW: AN OPERATIONAL AND TRAINING TOOL TO PROCESS, ANALYZE AND VISUALIZATION OF MSG SEVIRI DATA

AN INTEGRATED USER-ORIENTED WEATHER FORECAST SYSTEM FOR AIR TRAFFIC USING REAL-TIME OBSERVATIONS AND MODEL DATA

Rapidly Developing Thunderstorm (RDT)

Application of automated CB/TCU detection based on radar and satellite data

1. FY10 GOES-R3 Project Proposal Title Page

NEFODINA: A TOOL FOR AUTOMATIC DETECTION OF SEVERE CONVECTIVE PHENOMENA

Judit Kerényi. OMSZ-Hungarian Meteorological Service P.O.Box 38, H-1525, Budapest Hungary Abstract

MSG system over view

Atmospheric Motion Vectors: Product Guide

Detailed flow, hydrometeor and lightning characteristics of an isolated, hail producing thunderstorm during COPS

"Experiences with use of EUMETSAT MPEF GII product for convection/storm nowcasting"

USE OF THE EUROPEAN SEVERE WEATHER DATABASE TO VERIFY SATELLITE-BASED STORM DETECTION OR NOWCASTING

Czech Hydrometeorological Institute, Na Šabatce 17, CZ Praha 4, Czech Republic. 3

DNICast Direct Normal Irradiance Nowcasting Methods for Optimized Operation of Concentrating Solar Technologies

SATELLITE MONITORING OF THE CONVECTIVE STORMS

Improvement of thunderstorm hazard information for pilots through a ground based weather information and management system

COLD-RING AND COLD-U/V SHAPED STORMS

Global Instability Index: Product Guide

Research on Lightning Nowcasting and Warning System and Its Application

QUALITY OF MPEF DIVERGENCE PRODUCT AS A TOOL FOR VERY SHORT RANGE FORECASTING OF CONVECTION

COMBINED USE OF AN INSTABILITY INDEX AND SEVIRI WATER VAPOR IMAGERY TO DETECT UNSTABLE AIR MASSES

For the operational forecaster one important precondition for the diagnosis and prediction of

NOWCASTING PRODUCTS BASED ON MTSAT-1R RAPID SCAN OBSERVATION. In response to CGMS Action 38.33

H-SAF future developments on Convective Precipitation Retrieval

1.29 LIFE CYCLE OF CONVECTIVE CELLS WITH RAPID SCAN SATELLITE AND RADAR DATA IN THE EASTERN ALPINE REGION

Nowcasting thunderstorms for aeronautical end-users

Cloud analysis from METEOSAT data using image segmentation for climate model verification

Update on CoSPA Storm Forecasts

The importance of satellite data for nowcasting in the WWRP strategy

The water vapour channels of SEVIRI (Meteosat). An introduction

Assimilation of MSG visible and near-infrared reflectivity in KENDA/COSMO

METEOSAT THIRD GENERATION

Applications of multi-spectral satellite data

Comparison of cloud statistics from Meteosat with regional climate model data

INTERPRETATION OF MSG IMAGES, PRODUCTS AND SAFNWC OUTPUTS FOR DUTY FORECASTERS

H-SAF VSA Programme HSAF_ CDOP2_VS14_03

SNOW COVER MAPPING USING METOP/AVHRR AND MSG/SEVIRI

Utilising Radar and Satellite Based Nowcasting Tools for Aviation Purposes in South Africa. Erik Becker

Numerical modelling of the interaction of soil moisture with planetary boundary layer features and convection over West Africa

Detection and Monitoring Convective Storms by. Using MSG SEVIRI Image. Aydın Gürol ERTÜRK. Contents

Volcanic, Weather and Climate Effects on Air Transport

EUMETSAT products and services for monitoring storms - New missions, more data and more meteorological products

USE OF SATELLITE INFORMATION IN THE HUNGARIAN NOWCASTING SYSTEM

Assimilating cloud information from satellite cloud products with an Ensemble Kalman Filter at the convective scale

EUMETSAT Satellite Programmes Use of McIDAS at EUMETSAT

VWG.01 EUMETSAT Corporate Slide Collection (EUM/CIS/VWG/14/743878) Version 1, January 2014 MONITORING WEATHER AND CLIMATE FROM SPACE

GEOMETRIC CLOUD HEIGHTS FROM METEOSAT AND AVHRR. G. Garrett Campbell 1 and Kenneth Holmlund 2

Remote Sensing Seminar 8 June 2007 Benevento, Italy. Lab 5 SEVIRI and MODIS Clouds and Fires

An illustration of the practical use in aviation of operational real-time geostationary satellite data

2.2 Concatenating Weather Monitoring and Forecast: the WxFUSION Concept. The Concept of Combining Weather Observation and Prediction Data

Combined and parallel use of MSG composite images and SAFNWC/MSG products at the Hungarian Meteorological Service

GENERATION OF HIMAWARI-8 AMVs USING THE FUTURE MTG AMV PROCESSOR

OVERSHOOTING TOPS CHARACTERISTICS AND PROPERTIES

Nerushev A.F., Barkhatov A.E. Research and Production Association "Typhoon" 4 Pobedy Street, , Obninsk, Kaluga Region, Russia.

CHARACTERISTICS OF EMBEDDED WARM AREAS AND SURROUNDING COLD RINGS AND COLD-US

Verification and performance measures of Meteorological Services to Air Traffic Management (MSTA)

Tracking and nowcasting of convective cells using remote sensing data from radar and satellite

Probabilistic Quantitative Precipitation Forecasts for Tropical Cyclone Rainfall

THE IMPACT OF NEFODINA CONVECTIVE CLOUDS IDENTIFICATION IN THE RAIN RATE RETRIEVAL OF H-SAF

MSG Indian Ocean Data Coverage (IODC) Jochen Grandell & Sauli Joro

Figure 5: Comparison between SAFIR warning and radar-based hail detection for the hail event of June 8, 2003.

MAIN ATTRIBUTES OF THE PRECIPITATION PRODUCTS DEVELOPED BY THE HYDROLOGY SAF PROJECT RESULTS OF THE VALIDATION IN HUNGARY

EUMETSAT NEWS. Marianne König.

Performance of a Probabilistic Cloud-to-Ground Lightning Prediction Algorithm

RGB Experts and Developers Workshop - Introduction Tokyo, Japan 7-9 Nov 2017

Scientific and Validation Report for the Extrapolated Imagery Processor of the NWC/GEO

COMPARISON OF AMV HEIGHT ASSIGNMENT BIAS ESTIMATES FROM MODEL BEST-FIT PRESSURE AND LIDAR CORRECTIONS

VALIDATION RESULTS OF THE OPERATIONAL LSA-SAF SNOW COVER MAPPING

7.2 A TECHNIQUE FOR FORECASTING AND TRACKING ACTIVE CONVECTIVE CELLS : AN APPLICATION TO MESOSCALE CONVECTIVE SYSTEMS OVER DEL PLATA BASIN

EUMETSAT PLANS. K. Dieter Klaes EUMETSAT Darmstadt, Germany

Near Real-time Cloud Classification, Mesoscale Winds, and Convective Initiation Fields from MSG Data

THE ATMOSPHERIC MOTION VECTOR RETRIEVAL SCHEME FOR METEOSAT SECOND GENERATION. Kenneth Holmlund. EUMETSAT Am Kavalleriesand Darmstadt Germany

Using McIDAS-V for Satellite-Based Thunderstorm Research and Product Development

Warning procedures for extreme events in the Emilia-Romagna Region

Transcription:

Satellite-based thunderstorm tracking, monitoring and nowcasting over South Africa Caroline Forster 1, Estelle de Coning 2, Sebastian Diebel 1, Tobias Zinner 3 EUMETSAT Meteorological Satellite Conference Cordoba, Spain, 20 24 September 2010 1 DLR Institute of Atmospheric Physics, Oberpfaffenhofen, Germany 2 South African Weather Service 3 Meteorological Institute, University of Munich, Germany Standardfoliensatz >01.03.2007

CB-TRAM - CumuloniBus Tracking And Monitoring (Zinner, Mannstein,Tafferner, MAP, 2008) Algorithm for the detection, monitoring and nowcasting of thunderstorms from space Use of Meteosat SEVIRI Data Cb-TRAM Combination of HRV, IR10.8, IR12.0 and WV6.2 data for detecting Cb cells HRV info to localize the most active convective cells (texture in HRV image) Tracking based on pyramidal image matching algorithm Distinction of 3 development stages (1) First development of clouds (convection initiation) (2) Rapid development (strong cooling of cloud top) (3) Mature thunderstorm (reaching or exceeding the tropopause) Time resolution 15 min (or even 5 minutes with Meteosat rapid scan data) Nowcasts with extrapolation of detected features up to one hour Folie 2

CB-TRAM applied over South Africa for the first time adaption of the algorithm (e.g. to the moving HRV) convection initition (CI) Folie 3

CB-TRAM applied over South Africa for the first time adaption of the algorithm (e.g. to the moving HRV) convection initition (CI) Folie 4

CB-TRAM over South Africa convection initition (CI) pink: lightning incidents Folie 5

CB-TRAM over South Africa convection initition (CI) CB-TRAM is able to detect the most turbulent areas within the anvil pink: lightning incidents Folie 6

CB-TRAM applied over South Africa convection initition pink: lightning incidents (0-10 min after image time) Folie 7

CB-TRAM over South Africa convection initition (CI) Cb-TRAM is able to detect convection initiation before any lightning incidents occur pink: pink: lightning lightning incidents incidents (0-10 min after image time) Folie 8

CB-TRAM over South Africa convection initition (CI) pink: pink: lightning lightning incidents incidents (0-10 min after image time) grey: 15, 30, 45, 60 Min. nowcast Folie 10

CB-TRAM over South Africa convection initition (CI) Cb-TRAM is able to nowcast the development and movement of the Cb cells up to one hour pink: pink: lightning lightning incidents incidents (0-10 min after image time) grey: 15, 30, 45, 60 Min. nowcast Folie 11

Evaluation of nowcast with detected Cb TRAM cells pixel-based analysis (requires exact match of objects) hit = nowcast matches observation at a pixel miss = observation which is not nowcast at a pixel false alarm = nowcast which is not observed at a pixel object-based analysis (does not require exact match of objects) hit = nowcast object overlaps observed object miss = observed object which is not nowcast false alarm = nowcast object which is not observed + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + black: observed object at time t grey: nowcast object for time t blue: misses false alarms green :hits POD = hits / (hits + misses) FAR = false alarms / (hits + false alarms) Folie 12

Evaluation of nowcast with detected Cb TRAM cells pixel-based analysis object-based analysis (note the scale!) Folie 13

Simple evaluation of detected/nowcast Cb TRAM cells with lightning data hit = lightning incident inside of Cb-TRAM cell miss = lightning incident outside of Cb-TRAM cell false alarm = Cb-TRAM cell without lightning black contour: observed Cb object at time t green stars: lightning incidents (hits) blue stars: lighning incidents (misses) red object: object without lightning (false alarm) POD = hits / (hits + misses) FAR = false alarms / (hits + false alarms) Folie 14

Simple evaluation of detected/nowcast Cb TRAM cells with lightning data note that cells indicating CI and do (correctly) not (yet) contain lightning are also included in this analysis and are counted as false alarms also single lightning events that do not belong to lightning clusters and are typically not related to Cb-TRAM cells are included and counted as misses Folie 15

Summary and conclusions Cb-TRAM has successfully been applied over South Africa for the first time detects the most active regions within a thunderstorm is able to detect convection initiation before any lightning incident occurs is able to nowcast the movement and development of thunderstorms up to one hour The evaluation of nowcast with detected Cb-TRAM cells shows that pixel-based POD = 75%, FAR = 25% (15 min nowcast) object-based POD = 98%, FAR = 3% (15 min nowcast) POD decreases with increasing lead time, while FAR increases the nowcasting for lead times greater 30 minutes has to be improved The evaluation of Cb-TRAM detections and nowcasts with lightning data shows that Cb-TRAM agrees generally well with lightning data (POD = 80%, FAR = 5%) Cb-TRAM is a useful tool for the (early) detection, tracking and nowcasting of thunderstorms over South Africa Folie 16