© Crown copyright Met Office 1 ISES Forecast Verification Workshop Saturday 11 th April 2015 Millennium Harvest House, th Street, Boulder, Colorado 80302, USA Agenda 09:00 – 09:15Summary of European Space Weather Week verification session. Verification at the UK Met Office. Suzy Bingham, Met Office, UK. 09:15 – 09:30Introduction to NICT ’ s evaluation of the space weather forecasts provided by Japan, US, Belgium, Australia and China. Mamoru Ishii, NICT, Japan. 09:30 – 09:45Verification at RWC Belgium. Jesse Andries & Andy Devos. 09:45 – 10:00The verification of solar proton event probability forecasts at SEPC. China SEPC. 10:00 – 10:30State-of-the-art in weather forecast verification, and available tools and resources in the weather community. Barbara Brown, NCAR, USA. 10:30 – 10:45Coffee break. 10:45 – 12:15Discussion focus 1. Global product: flare forecasts. Discussion lead by Jesse Andries & Andy Devos. 12:15 – 13:15Lunch. 13:15 – 13:30Gathering GNSS data for making TEC maps and the effort of spreading GTEX format for easy exchange of GNSS data. Mamoru Ishii, NICT, Japan. 13:30 – 13:45TEC maps over Canada, Robyn Fiori, Canada. 13:45 – 15:00Discussion focus 2. Regional product: TEC nowcasts. Discussion lead by: Mihail Codrescu 15:00 – 15:15Coffee break. 15:15 – 16:30Discussion on other verification topics.

© Crown copyright Met Office 2 Discussion topics Product information & current verification by different centres. Relevant quantities/values for verification. Exact interpretation of communicated values. Standardisation. User-driven metrics. ‘Truth’, true measurements to verify against. Verification techniques to allow consistency & best-practices in order to compare verification of local products. Coordination & collaboration. Alignment with WIS Pilot Project. Common products & exact descriptions of each so that verification results are comparable. Future milestones/targets of verification. Discussion on other verification topics (15: :00) Operational Enlil output composite plot

© Crown copyright Met Office European Space Weather Week verification session summary ISES Verification Workshop 11 th April 2015 Suzy Bingham Met Office, UK 3

© Crown copyright Met Office ‘Space weather metrics, verification & validation’ splinter session 4 Minutes available:

© Crown copyright Met Office ESWW presentations 5 Liege Andy Devos, ROB. Solar Terrestrial Centre of Excellence (STCE) ( Evaluate: flare probability, Kp index, 10.7cm radio flux & proton events. Peter Wintoft, Swedish Institute of Space Physics. Perspectives on extreme events: science, statistics & user perspectives. The use of particular skill scores for rare/extreme events. Alexi Glover, ESA. Space Weather European Network (SWENET) ( Space weather services & data portal with simple metrics already being used.

© Crown copyright Met Office ESWW presentations 6 Manoulis Georgoulis, Academy of Athens, Greece. Solar flare prediction methods. Use of different skill scores & test in different parts of solar cycle. Sean Elvidge, University of Birmingham, UK. Taylor Diagrams: visualising stats & different parameters & models on 1 diagram. “On the use of modified Taylor diagrams to compare ionospheric assimilation models,” Radio Science, Suzy Bingham, Met Office, UK. Translating terrestrial met verification methods to space weather. Real-time verification/validation is important for forecasters. Maria Kuznetsova, CCMC, USA. Model validation activities include: TEC, Dst index & regional K. Can calculate skill scores on the CCMC system.

© Crown copyright Met Office Challenges for verification/validation 7 (1) Confusion: many forecasts from many centres so difficult to understand what data to use. (2) Variety of techniques required: due to varied nature of forecasts (e.g. probabilistic forecasts, binary forecasts, time-series predictions, 2-d 3-d matrices of predictions, single value predictions). (3) What to compare: local/global forecasts, max/average values. How forecast windows & lead times will impact on forecast accuracy. (4) Terminology: how to compare with varying terminology between centres, e.g ‘unsettled’ Kp & ‘eruptive flaring’ can be different between centres. (5) Forecasting of extremes/rare events: raises problems for many skill scores.

© Crown copyright Met Office Challenges for verification/validation continued 8 (6) Solar cycle: differences in activity depending on where you are in the solar cycle. (7) Thresholds: for probabilistic forecasts, e.g. set threshold to maximise the skill score. But how would this work with inter- model comparisons? (8) Errors in validation process: can arise from models, validation data & post-processing. So need to make sure other forms of inaccuracy aren’t passed on to model/forecast. (9) Fear of loss of funding: if researchers fear a loss of funding when they don’t do well in a validation activity then this discourages participation. Activity has to be representative & unbiased. (10) Flow of information between centres/modellers: it’s important for info to flow between them so that centres can present appropriate metrics to users, & models are tested against metrics which can be translated into user requirements.

© Crown copyright Met Office Requirements for verification/validation (1)fix timescales / lead times, (2)common parameters, (3)common fomat, (4)common terminology, (5)provide data access, (6)use metrics which are adequate, easy to interpret & easily reproducible, (7)if there are multiple lead times, use appropriate weightings, (8)agreed a list of events for validation exercises. 9

© Crown copyright Met Office Suggested analysis (1)Error analysis. (2)ROC curve (Relative Operating Characteristic). False Alarm Rate v Probability of Detection. (3)Reliability plots (e.g. for flare probability forecasts). (4)Brier skill scores (e.g. flare probability forecast). (5)Extremal Dependence Index (EDI)- independent of the rarity of events. Has been applied to ground dB/dt forecasts at the Swedish SpWx Center. (6)Equitable skill scores with weighting for rare events. (6)Taylor diagrams to combine different synoptic metrics such as correlation, bias, etc, in a single plot. Potentially useful for inter- model comparisons but not likely to be used for a non-specialist service end-user. 10

© Crown copyright Met Office To aid verification/validation (1)More transparency between forecasts. (2)Communication/coordination between centres & users. (3)Different approaches need different domains. (5)Agencies can provide an unbiased platform. (6)Agencies can encourage participation in community wide initiatives. (7)Agencies could provide computing resources/manpower to do independent tests. (8)Agencies could provide dedicated workshops & campaigns. (9)There’re established lists of products, which vary depending on community, e.g. WMO, ‐ sat.info/oscar/applicationareas/view/25 ESA, ‐ SWE/SSA ‐ SWE ‐ RS ‐ SSD ‐ 0001_i1r3.pdf 11

© Crown copyright Met Office Overview of Met Office verification plans ISES Verification Workshop 11 th April 2015 Suzy Bingham Met Office, UK 12

© Crown copyright Met Office Met Office models 13 Enlil: predicts solar wind speed & density between Sun & Earth for next few days. REFM: 3-day forecast of high-energy electrons at GEO orbit. D-RAP: Global map of real-time D region absorption predictions. MIDAS/Bernese: Nowcasting Total Electron Content in ionosphere.

© Crown copyright Met Office Verification requirements Probabilistic forecasts, 1-4 days ahead, produced twice daily: o High energy proton flux (2 levels). o High energy electron fluence (2 levels). o Geomagnetic storms (4 levels). o X-ray flares (2 levels). Spatial: o MIDAS/Bernese (TEC) o DRAP Deterministic: o CME arrival time (time at Earth) o REFM (daily fluence) 14 Examples of probability forecasts

© Crown copyright Met Office 15 Would like to verify: 1.CME arrival times at Earth. 1.Enlil output from the four centres running Enlil operationally, against observed data from ACE (composite plot). 1.Real-time solar wind speed on forecaster bench, against ACE (later DSCOVR) & STEREO A &B. Enlil verification ENLIL output on the forecaster visualisation suite

© Crown copyright Met Office CME forecast verification 16 Overview of results for 2014 and 2015 (2013 still to be done). Accuracy proportion correct ~ 0.75 Threat Score ~ 0.67 Bias ~0.9 Reliability False Alarm Ratio ~ 0.15 Discrimination Hit rate ~ 0.76 False Alarm Rate ~ 0.36 Skill Heidke ~ 0.36 Peirce ~ 0.4 Equitable Threat Score ~ 0.2

© Crown copyright Met Office Relativistic Electron Forecast Model (REFM) The REFM uses 30 days of solar wind speed data (currently from the ACE spacecraft) to predict the 24-hour fluence, 1-4 days ahead. Forecasters issue probability of energetic electron fluence exceeding thresholds (10 8 and 10 9 pfu), based on model output and experience. Need to assess model performance, and advisor guidance How do we verify these forecasts and identify a probability threshold for what defines a “hit”? Could use ROC curves to find the detection threshold which maximises hit rate/false alarm rate. Assess whether skill is statistically significant. 17

© Crown copyright Met Office REFM verification Use of ROC curves for evaluating forecaster probabilities has limitations: Very few observed threshold exceedences (~5 out of ~100 events). Difficult to robustly identify a probability threshold By eye, the threshold appears to be higher for shorter lead times, but this trend is unlikely to be statistically significant. 18 Use Extremal Dependence Index instead of ROC: “A probability model for verifying deterministic forecasts of extreme events”, Ferro, 2007, AMS. “Extremal Dependence Indices: Improved verification measures for deterministic forecasts of rare binary events”, Ferro & Stephenson, 2011, AMS.

© Crown copyright Met Office TEC: Multi-Instrument Data Analysis System (MIDAS) Purpose: Multi-Instrument Data Analysis System.Images ionospheric activity in real- time. Produces European region Total Electron Content (TEC) nowcast every 15 mins Input: Measurements potentially from ground- & spaced-based GPS receivers, & point estimates of local electron density. Output: TEC map over Europe every 15mins. 19

© Crown copyright Met Office TEC: Bernese model 20 European plots every 15mins, global plots every hour. TEC anomaly from previous 10 day mean. TEC change from previous hour. Output: IONEX format, 2.5km lat, 5km lon.

© Crown copyright Met Office EU H2020 FLARECAST project ( Ensemble of best methods with improved verification. Compare our human-based methods to improved automatic methods. Consistent verification methods used on consistent data sets for inter- comparison. Bringing in better methods from more mature field of numerical weather prediction. Most popular flare forecasting verification methods to use: Heidke Skill Score & True Skill Statistic. CCMC flare forecast planning page: 21 Flare forecasting

© Crown copyright Met Office 22 Probabilistic forecasts, 1-4 days ahead, produced twice daily: o High energy proton flux (2 levels). o High energy electron fluence (2 levels). o Geomagnetic storms (4 levels). o X-ray flares (2 levels). Compare against climatological/persistence models (Markov chain using transition probabilities). Use Rank Probability Score to understand accuracy. Horizon 2020 FLARECAST: may use True Skill Score or Heidke Skill Score. Spatial forecasts: o MIDAS/Bernese (TEC) o DRAP Deterministic forecasts: o CME arrival time at Earth (RMS error, FAR, etc. Composite plot.) o REFM (Use Extremal Dependence Index (EDI)). Met Office would like to provide simple metrics so that stakeholders can understand forecaster added value. Summary of Met Office verification requirements/plans

© Crown copyright Met Office Notes/guidance 23

© Crown copyright Met Office

Flexible Warning Verification System 31 Plan to translate terrestrial verification techniques to space weather, firstly using the Flexible Warning Verification System (WVS) (Mike Sharpe, Met Office). WVS is based on contingency table but gives more flexibility in space & time, i.e. gives some score to near hits. E.g. if a gale (or X-ray flare) occurs 5mins before a warning issue time then this is given some score rather than a miss. WVS provides a means for the forecaster to review events. After analysis in the WVS, suitable skill scores can be applied, e.g. Performance ROC plots & reliability plots. Useful to understand forecaster added value.

© Crown copyright Met Office Gale warning verification time Low Event threshold HIT FALSE ALARM MISS NON- EVENT Warning periodEnd time + late hit period Issue time EARLY HIT LATE HIT Event threshold EARLY LOW HIT LATE LOW HIT LOW HIT Introducing the warnings verification system 32

© Crown copyright Met Office Gale warning verification St Judes Storm October a hit! 33