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MTG Lightning Imager Proxy Data

Presentation to the Convection Working Group. Zagreb, Croatia 9 April 2014. MTG Lightning Imager Proxy Data. Jochen Grandell. Topics. Putting the MTG Lightning Imager (LI) into context MTG LI status update MTG LI products Heritage products from LEO experiences Accumulated products

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MTG Lightning Imager Proxy Data

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  1. Presentation to the Convection Working Group Zagreb, Croatia 9 April 2014 MTG Lightning Imager Proxy Data Jochen Grandell

  2. Topics • Putting the MTG Lightning Imager (LI) into context • MTG LI status update • MTG LI products • Heritage products from LEO experiences • Accumulated products • Proxy data basics • LINET-based proxy data • L2 Prototype processor • L2 accumulated (proxy) product examples • Summary

  3. Lightning Imager Science Team & Mission Advisory Group • The LI activities have been supported by the Lightning Imager Science Team (LIST) in 2009-2013 • Due to program evolution, a new team (Mission Advisory Group) has been set up in early 2014. • First meeting took place on 18-19 Feb 2014

  4. Topics • Putting the MTG Lightning Imager (LI) into context • MTG LI status update • MTG LI products • Heritage products from LEO experiences • Accumulated products • Proxy data basics • LINET-based proxy data • L2 Prototype processor • L2 accumulated (proxy) product examples • Summary

  5. MTG to Secure Continuity and Evolution of EUMETSAT Services 2018/2019 and 2021 2002 1977 MOP/MTP MSG MSG MOP/MTP MTG-I and MTG-S Observation missions: - Flex.Comb. Imager: 16 channels - Infra-Red Sounder - Lightning Imager - UVN 3-axis stabilised satellites Twin Sat configuration Class 3.6-ton • Observation missions: • - SEVIRI: 12 channels • GERB • Spinning satellite • Class 2-ton • Observation mission: • MVIRI: 3channels • Spinning satellite • Class 800 kg Implementation of the EUMETSAT Mandate for the Geostationary Programme Atmospheric Chemistry Mission (UVN-S4): via GMES Sentinel 4 (Ultraviolet Visible Near-infrared spectrometer)

  6. Lightning Detection from Space – from LEO to GEO Feasibility of lightning detection from space by optical sensors has been proven by NASA instruments since 1995 on low earth orbits (LEO) OTD (1995-2000) Results from LIS/OTD: Global lightning distribution Annual flash density LIS (1997-present)

  7. Geostationary lightning imaging – objectives and benefits The LI on MTG measures Total Lightning: Cloud-to-Cloud Lightning (IC) and Cloud-to-Ground Lightning (CG) Main benefit from GEO observations: homogeneous and continuous observations delivering information on location and strength of lightning flashes to the users with a timeliness of 30 seconds • Main objectives are to detect, monitor, track and extrapolate in time: • Development of active convective areas and storm lifecycle • Lightning climatology • Chemistry (NOx production)

  8. Lightning Detection from Space – from LEO to GEO GEO lightning missions in preparation by several agencies (in USA, Europe, China) for this decade... ...all of these are building on LIS/OTD heritage Geostationary Lightning Imager (GLI) on FY-4 (China) Geostationary Lightning Mapper (GLM) on GOES-R (USA) Lightning Imager (LI) on MTG (Europe) 2015  2018  2015/2016

  9. Topics • Putting the MTG Lightning Imager (LI) into context • MTG LI status update • MTG LI products • Heritage products from LEO experiences • Accumulated products • Proxy data basics • LINET-based proxy data • L2 Prototype processor • L2 accumulated (proxy) product examples • Summary

  10. Lightning Imager (LI) main characteristics CMOS Back-thinned backside illuminated detectors with integrated ADCs The baseline for the LI is a 4-camera solution 1170 x 1000 pixels per camera. Coverage close to visible disc

  11. Lightning Imager (LI) Status Update • LI instrument and mission prime contractor is Selex ES from Italy, which includes the: • Development of the LI instrument • ...and also the L0-L1b data processing software • MTG LI Phase B2 has been kicked off in 2012 • SRR (System Requirements Review) done in two parts, finished in spring 2013 • PDR (Preliminary Design Review) started towards end of 2013 at instrument level – Mission level PDR in late spring 2014.

  12. Lightning Imager (LI) main characteristics • LI main characteristics: • Measurements at 777.4 nm • Coverage close to visible disc • Continuous measurements of (lightning) triggered events – in addition, background images typically once every minute • Ground sample distance at SSP ~4.5 km => 4.7 million pixels • Integration time per frame 1 ms (parameterised) • Background subtraction and event detection in on-board electronics • Data rate <30 Mbps; Mass < 110Kg; Power < 320W

  13. Topics • Putting the MTG Lightning Imager (LI) into context • MTG LI status update • MTG LI products • Heritage products from LEO experiences • Accumulated products • Proxy data basics • LINET-based proxy data • L2 Prototype processor • L2 accumulated (proxy) product examples • Summary

  14. L2 Flashes/Groups/Events • Product Terminology: • Events:what the instrument measures, a triggered pixel in the detector grid • Groups:collection of neighbouring triggered events in the same integration period (1-2 ms), representing roughly a lightning stroke in nature • Flashes:a collection of groups in temporal and spatial vicinity (XX km, YY ms), representing a “geophysical” flash.

  15. L2 Flashes/Groups/Events The “Flash tree” combining the events and the groups into one flash Triggered event #1 Group #1.1 Flash A Triggered event #2 Triggered event #3 Triggered event #4 Group #1.2 Triggered event #5 Triggered event #6

  16. Groups and Flashes – LIS approach followed Example/Conceptual representation of a L2 processing sequence: “Groups” “Flashes” “Events”

  17. Topics • Putting the MTG Lightning Imager (LI) into context • MTG LI status update • MTG LI products • Heritage products from LEO experiences • Accumulated products • Proxy data basics • LINET-based proxy data • L2 Prototype processor • L2 accumulated (proxy) product examples • Summary

  18. L2 Accumulated Products • Accumulated products: • Collecting samples from a 30 second buffer • Resampled to the 2-km FCI-IR grid for simple visualising with FCI data • Events define the extent in the products • Flashes define the values in the products • For a longer temporal accumulation, the 30 second products can be stacked • Three products in all: • Accumulated flashes • Accumulated flash index • Accumulated flash radiance

  19. Topics • Putting the MTG Lightning Imager (LI) into context • MTG LI status update • MTG LI products • Heritage products from LEO experiences • Accumulated products • Proxy data basics • LINET-based proxy data • L2 Prototype processor • L2 accumulated (proxy) product examples • Summary

  20. Proxy data basics (1) • MTG LI is without heritage in GEO orbit, and the closest comparison is the Lightning Imaging Sensor (LIS) on TRMM – currently still in operation • However, LIS flying on LEO orbit can only monitor storms for less than 2 minutes at a time • In addition, coverage is limited to +/- 35 deg Lat => Europe is excluded • Use of ground-based Lightning Location System (LLS) networks as a source of proxy data is not straightforward, as they are based on RF observations of lightning and are sensitive to different parts of the lightning process • “apples and oranges”

  21. Proxy data basics (2) • The best compromise is to use ground-based lightning data, but converted to optical pulses based on case study comparisons with LIS data. • One of the networks in operation in Europe (LINET) is currently the main source of such proxy data for the LI activities. • LINET data has been compared in measurement campaigns to other ground-based systems and to LIS • As an outcome, a model for transforming the LINET stroke data into optical emission (“pulses”) has been created

  22. Thunderstorm ElectrificationLightning and its Emissions • VHF – Very High Frequency, (V)LF – (Very) Low Frequency

  23. Topics • Putting the MTG Lightning Imager (LI) into context • MTG LI status update • MTG LI products • Heritage products from LEO experiences • Accumulated products • Proxy data basics • LINET-based proxy data • L2 Prototype processor • L2 accumulated (proxy) product examples • Summary

  24. LINET network coverage Central Europe well covered (2008 data) Sensor baselines highly varying across the network (= distance between sensors)

  25. Modeling of MTG-LI Optical SignalsStrategy for Proxy Data Generation Transformation of LINET RF stroke data into optical groupsby modeling of cloud top optical emission: • Simulation of the number of optical groups per stroke (depending on LINET detection efficiency, i.e. sensor baseline, in the area) If this number is ≥ 1: • Generation of one direct coincident optical group per LINET stroke • Random generation of additional optical groups per LINET stroke according to a log-normal model for radiance, footprint and time Generation of optical events from RF stroke data

  26. Topics • Putting the MTG Lightning Imager (LI) into context • MTG LI status update • MTG LI products • Heritage products from LEO experiences • Accumulated products • Proxy data basics • LINET-based proxy data • L2 Prototype processor • L2 accumulated (proxy) product examples • Summary

  27. L2 prototype processor A prototype L2 processor in Matlab The main objectives of the prototype processor are: Implementation, testing and verification of the L2 algorithms. Verification and validation of the proxy data Flash/group clustering parameters easily set for each individual run

  28. Topics • Putting the MTG Lightning Imager (LI) into context • MTG LI status update • MTG LI products • Heritage products from LEO experiences • Accumulated products • Proxy data basics • LINET-based proxy data • L2 Prototype processor • L2 accumulated (proxy) product examples • Summary

  29. L2 Accumulated products => Proxy data examples • Example animations shown for the Accumulated flash index product • Proxy data pulses  LI proxy events • L2 processor • L2 flashes + Accumulated products • The original 30 sec product stacked into several longer periods for demonstration purposes: • 15 min (= SEVIRI Full Disk Service today) • 10 min (= FCI Full Disk Scanning Service FDC) • 5 min (= FCI Rapid Scanning Service FDC/2) • 2.5 min (= FCI Rapid Scanning Service FDC/4)

  30. Preparing for a user readiness study EUM/KOEEEE Issue <No.> <Date> • Because of no heritage in orbit or business-as-usual products, feedback and comments regarding the data usage and upcoming end-products delivered by EUMETSAT are needed. • Charting the readiness of the main data users (i.e., National Meteorological and Hydrological Services, NMHS). • Ensuring that the users are able to give valuable input already before the instrument is launched. • End-users getting a first glimpse on the data before the LI instrument itself is operational. • In addition to LINET as input data, an extension of the method is in development to have a similar approach applicable to the NORDLIS/EUCLID network as well (work in progress).

  31. L2 Accumulated products • Animations: All for 20 June 2013, different accumulation times

  32. Full Domain: 150 s Accumulation Time

  33. Zoom: 150 s Accumulation Time

  34. Full Domain: 300 s Accumulation Time

  35. Zoom: 300 s Accumulation Time

  36. Full Domain: 600 s Accumulation Time

  37. Zoom: 600 s Accumulation Time

  38. Full Domain: 900 s Accumulation Time

  39. Zoom: 900 s Accumulation Time

  40. Topics • Putting the MTG Lightning Imager (LI) into context • MTG LI status update • MTG LI products • Heritage products from LEO experiences • Accumulated products • Proxy data basics • LINET-based proxy data • L2 Prototype processor • L2 accumulated (proxy) product examples • Summary

  41. Summary • Proxy data needed for product/algorithm development, system level testing, and user readiness preparation • For the Lightning Imager, being without heritage, the creation of representative proxy data has been a top priority • LINET, a ground-based system covering much of Europe has been used as a vehicle for developing the proxy data • Based on LIS-LINET comparisons, as well as comparison to other networks’ data (CHUVA campaign) • LIST activity started in 2009 and continued since through various activities • The accumulated flash product demonstration presented • User readiness study employing the proxy data in preparation

  42. Back-up slides

  43. Accumulated flashes, status at t = 10s EUM/ Issue <No.> <Date> Event count in the 30 sec buffer (still in LI grid) = Events in Flash #1 3 2 1 1 1 1 2 Flash count in the 30 sec buffer (still in LI grid) 1 1 1 1 1 1 1 Conceptual illustration

  44. Accumulated flashes, status at t = 20s EUM/ Issue <No.> <Date> Event count in the 30 sec buffer (still in LI grid) = Events in Flash #1 = Events in Flash #2 2 1 1 4 2 2 1 1 1 1 2 Flash count in the 30 sec buffer (still in LI grid) 1 1 1 1 2 1 2 1 1 1 1 Conceptual illustration

  45. Accumulated flashes, status at t = 29s EUM/ Issue <No.> <Date> Event count in the 30 sec buffer (still in LI grid) = Events in Flash #1 = Events in Flash #2 = Events in Flash #3 2 1 1 1 2 1 6 3 2 1 1 1 1 2 Flash count in the 30 sec buffer (still in LI grid) 1 1 1 1 1 1 1 3 2 2 1 1 1 1 Conceptual illustration

  46. Detection of a Lightning Optical Signal • Lightning with a background signal changing with time: • Lightning on top of a bright background is not recognised by its bright radiance, but by its transient short pulse character • For detection of lightning, a variable adapting threshold has to be used for each pixel which takes into account the change in the background radiance • (in LIS: background calculated as a moving average) Radiation energy Background Lightning signal Night Day Time

  47. From a Lightning Optical Signal to MTG LI Events From a Lightning Optical Signal to MTG LI Events • Detection of events in a nutshell: This is taking place in every 1 ms frame (1 kHz): Event detection Background scene tracking and removal Thresholding • False event filtering needed in L0-L1 processing • True lightning events (triggered by a lightning optical signal) • False events (not related to lightning)

  48. Use of proxy data within the MTG program activities • Data is being and will be used in: • Algorithm development & testing • System level testing • User readiness activities • Proxy data also shared with other agencies • NOAA GOES-R GLM team – Steve Goodman • In talks to cooperate also with CMA on proxy data

  49. LINET operating principle • LINET operating at the VLF/LF frequency range Lightning Detection Network LINET observes sfericsat VLF/LF from larger discharges Lightning Mapping Array LMA observes VHF pulses from small-scale breakdown

  50. L2 prototype processor (2) Screenshot of the prototype processor Matlab GUI - Flash/group clustering parameters easily set for each individual run

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