Status Report from IPT-SWeISS TT-SCI

Transcription

1 WORLD METEOROLOGICAL ORGANIZATION COMMISION FOR AERONAUTICAL METEOROLOGY COMMISSION FOR BASIC SYSTEMS/OPEN PROGRAMME AREA GROUP ON DATA-PROCESSING AND FORECASTING SYSTEM INTER-PROGRAMME TEAM ON SPACE WEATHER INFORMATION, SYSTEM AND SERVICES SECOND SESSION TOKYO, JAPAN, MAY 2018 IPT-SWEISS-2/Doc. 2.x/3.x/4.x (dd.mm.2018) Original: ENGLISH Status Report from IPT-SWeISS TT-SCI (Submitted by Mamoru Ishii) ABSTRACT This document present the current status of Task Team Science (TT-SCI), IPT- SWeISS. Status Report 1 Agree membership Closed on July 31, Agree ToRs Closed on Sep 30, Agree workplan Closed on Sep 30, Share lessons-learned in the usage of space weather models in daily forecasting activities In progress: Iwona prepared draft of questioner. After reviewing the format, TT-SCI sent the format to the chair of ISES, Terry Onsager on April 24, Define skill scores and other verification techniques to assess the potential value of existing research models for user-oriented services In progress: CCMC has similar activities for discussing verification of existing research models. We should have contact to Marsha. ISES also has 6 Workshops on space weather impacts on Essential Climate Variables (e.g., ESWW2018 EGU ) In progress: 7 Workshops to evaluate the benefit of whole atmosphere models (from the surface to the top of the thermosphere) used in conjunction with other space weather models(e.g., SWW2018, ESWW2018, URSI/AP-RASC 28May- 1Jun,2018)

2 In progress: David Jackson arranges the session in Whole Atmosphere Modelling workshop held in madrid, June 13-15, Workshops on data-assimilation capabilities for Sun-Earth system models to improve forecast skill (e.g., PSTEP-3, 2018) In progress: 9 Workshops on evaluating solar flare forecast models for operational space weather forecast In progress: ACTION PROPOSED The Meeting is invited to note the information contained in this document when discussing how it organises its work and formulates its actionss or decision using the proposed template. References: (if any) Appendix 1: Membership of TT-SCI Sergio DASSO (Argentina) sdasso@at.fcen.uba.ar Andries JESSE (Belgium) Jesse.Andries@oma.be Clezio Marcos De NARDIN (Brazil) clezio.denardin@inpe.br Jens BERDERMANN (Germany) jens.berdermann@dlr.de Clara YATIN I (Indonesia) clara@lapan.go.id Mamoru ISHII (Japan) mishii@nict.go.jp Jangsuk Choi (KSWC, Korea) dyne1225@korea.kr, portion@korea.kr Craig RODGER (New Zealand) craig.rodger@otago.ac.nz Iwona STANISLAWSKA (Poland) stanis@cbk.waw.p Margit HABERREITER (Switzerland) margit.haberreiter@pmodwrc.ch David JACKSON (UK) david.jackson@metoffice.gov.uk Juha Pekka Luntama (ESA) Pekka.Luntama@esa.int Elsayed Talaat (CGMS/SWxTT) elsayed.talaat@noaa.gov

3 Appendix 2; TT-SCI Terms of Reference Inter-Programme Team on Space Weather Information Systems and Services (IPT-SWeISS) Task Team on Space Weather Science (TT-SCI) Terms of Reference Objective The objective of the Task Team on Space Weather Science (TT-SCI) is to support the development of space weather services through discussing, adopting and evaluating space weather forecast and verification methods and models, interaction with climate, and transition from research to operations in communication with partner organizations, CGMS and ISES Activities The activities of the TT-SCI should include, as a minimum: i) Share lessons-earned in the usage of space weather models in daily forecasting activities for coordination and consultation between warning centres, working collaboratively with ISES; ii) Define skill scores and other verification techniques to assess the potential value of existing research models for comparing the results provided by warning centres and for improving the forecasting skill of whole space weather forecast information providers; iii) iv) Identify gaps in the scientific space weather measurements and communicate with relevant entities (space agencies, ground based measurement system operators, etc.) to promote new measurements that will enable progress in space weather forecasting methods and models; and Keep abreast of, and encourage, scientific developments which can lead to future improvements in space weather forecasts. To assist this process, the TT-SCI shall aim to perform the following tasks: Reporting a. Arrange Workshops on space weather impacts on Essential Climate Variables for discussing the precise estimation of extreme space weather event to the climate; b. Evaluate the benefit of whole atmosphere models (from the surface to the top of the thermosphere) used in conjunction with other space weather models; and c. Arrange Workshops on data-assimilation capabilities for Sun-Earth system models to improve forecast skill. TT-SCI is a task team of the Inter-Programme Team on Space Weather Information Systems and Services (IPT-SWeISS) under the Commission for Basic Systems (CBS) and Commission for Aeronautical Meteorology (CAeM).

4 TT-SCI will report to IPT-SWeISS on a routine basis through its designated rapporteur (see Composition). Coordination The TT-SCI should ensure necessary coordination as a minimum with: IPT-SWeISS and its other task teams; Relevant expert teams of WMO technical commissions; and Partner organisations including ITU, ISES and CGMS Working methodology TT-SCI should establish and maintain a work programme, comprising deliverables with deadlines, to support the efficient and effective progress of work. The TT-SCI work programme should be reviewed and, as necessary, updated by the task team at least annually. TT-SCI should work, to the greatest extent, through electronic correspondence and virtual meetings, thereby minimizing the need for physical meetings. Composition TT-SCI should establish, from amongst its membership, a rapporteur to coordinate its activities and report to IPT-SWeISS on a routine basis (see Reporting). Secretariat support Secretariat support to TT-SCI will be provided by the Data-processing and Forecasting Division (DPFS) of the Weather and Disaster Risk Reduction Service Department (WDS) and the Space-based Observing System Division (SBOS) of the Observing and Information System Department (OBS).

5 Appendix 3: TT-SCI workplan Task Priority Deliverable Date Due Lead Current status Agree membership High 31/07/17 Mamoru Ishii closed Agree TORs High 1. Produce Draft TORs 1. 31/08/17 closed 2. Agree TORs 2. 30/09/17 Mamoru Ishii Agree work plan High Draft work plan updated & 30/09/17 Mamoru Ishii closed agreed Share lessons-learned in the usage of space weather models in daily forecasting activities High 1. 31/01/ /03/ /05/18 Andries Jesse, Iwona Stanislawska Define skill scores and other verification techniques to assess the potential value of existing research models for useroriented services Workshops on space weather impacts on Essential Climate Variables (e.g., ESWW2018 EGU ) Workshops to evaluate the benefit of whole atmosphere models (from the surface to the top of the thermosphere) used in conjunction with other space weather models High Lower Lower 1. Prepare the format of questioner to be provided to ISES RWCs 2. With ISES agree the present usage of space weather models to be researched 3. Complete a document from collected questioner 1. Fix the roadmap to complete this task with ISES 2. Complete the assessment of skill score using existing dataset 3. Discussion of the results and prepare the conclusions 1. Fix abstract and potential speakers coordinated with ESWW 2. Fix the speakers 3. Logistical actions 1. Fix abstract and potential speakers coordinated with SWPC 2. Fix the speakers 3. Logistical actions 1. 31/12/ /05/ /12/ /04/ /07/ /10/ /12/ /02/ /04/18 David Jackson Juha-Pekka Luntama Margit Haberreiter Jens Berdermann David Jackson Iwona stanislawska In progress Waiting the answer from ISES In progress David, Jussi, Margit and Jens plan to submit a workshop on EGU2019 In progress Margit and Jens plan to submit a workshop on EGU2019 In progress David and Iwona arrange Whole atmosphere modelling

6 (e.g., SWW2018, ESWW2018, URSI/AP-RASC 28May- 1Jun,2018) Workshops on data-assimilation capabilities for Sun-Earth system models to improve forecast skill (e.g., PSTEP-3, 2018) Workshops on evaluating solar flare forecast models for operational space weather forecast Lower Lower 1. Fix abstract and potential speakers coordinated with PSTEP 2. Fix the speakers 3. Logistical actions 1. Searching flare forecast models 2. Fix the speakers 3. Logistical actions 1. 31/12/ /02/ /04/ /06/ /12/ /05/19 Mamoru Ishii Mamoru Ishii workshop on June 13-15, 2018 in Madrid Mamoru plans to submit a workshop on EGU2019 Mamoru plans to submit a workshop on EGU2019

7 Appendix 4 Questionnaire Please input some details of your forecasting / nowcasting model: 1. Name of the model: 2. Developer name\contact person: 3. Affiliation: 4. Characterize your model with respect to the lead-time of forecasting: nowcast (up to 1 hour ahead): short-term forecasting (1 hour to 3 days ahead): mid- and long-term forecasting (1 week to 1 month/or more). 5. Backgrounds (1 page maximum), describing: i) is the model: theoretical (using e.g. differential equations to calculate physical laws) empirical (expressions, input parameters) extrapolation of past measurements (simple, weighted) Neural Network (or other machine learning techniques) ii) period(s) of forecasting (lead time) iii) model error(s): percentage error, other error estimates Comment [j1]: The 1 hour boundary is a bit arbitrary: I think whether we consider a 1 hour forecast a nowcast or a forecast may depend on which process / quantity we talk about,. E.g. for K indices which have timeresolution of 3 hours, anything within 3 hours is probably to be classified as nowcast. Should we avoid such pedantic discussion? 6. Is the model operational? If yes a) Since when? b) Is the output publically available? 7. Does the model run in some continuous manner or is it event triggered? If event triggered: Does it require a human operator to provide input parameters and run the model? If human inputs are required: Do you have specific instructions for the operators about how to set input parameters to optimize the results? If yes: Please list. 8. How does the model output influence forecast / nowcast products other than the (raw) model output itself? Does this include an intermediate (or final) step involving human interpretation or humanly driven analysis of the model output? If yes: Do you have specific instructions for the operators about how to interpret the output in order to optimize the results of downstream processes / products? If yes: Please list. 9. References

8 ISSUES AND PROPOSED ACTION/RECOMMENDATION OR DECISION Issue #1 Rationale for the proposed action or decision Proposed action Share lessons-learned in the usage of space weather models in daily forecasting activities What By whom Deadline Proposed decision What To whom Time frame

9 Issue #1 Rationale for the proposed action or decision Proposed action What By whom Deadline Proposed decision What To whom Time frame

10 Issue #1 Rationale for the proposed action or decision Proposed action What By whom Deadline Proposed decision What To whom Time frame

11 Issue #1 Rationale for the proposed action or decision Proposed action What By whom Deadline Proposed decision What To whom Time frame

12 Issue #1 Rationale for the proposed action or decision Proposed action What By whom Deadline Proposed decision What To whom Time frame

13 Issue #1 Rationale for the proposed action or decision Proposed action What By whom Deadline Proposed decision What To whom Time frame