Overview of the KMA's Space Weather Service and R&D Program

Transcription

1 Overview of the KMA's Space Weather Service and R&D Program Jiyoung Kim

2 Contributors of this presentation: Jinha Lee, Hyesook Lee, Jaehoon Noh, Wonhyeong Yi, Dong-Hee Lee, Daehyeon Oh, Jaegwang Won, and Hoon Park, who are my colleague of the KMA/NMSC

3 Outline Background of KMA s Space Weather Service Current Status of the Operational Service Monitoring, Models, and Forecasts Research and Development Activities Operational System Construction Space Weather Payload (KSEM) Development Weather Impact Studies Space Weather Policy of KMA KSEM Launch, R&D Enhancement, and Partnerships International Collaborations

4 Background Why KMA interested in the Space Weather? Increased needs of space weather information due to the expansion of human activities to the SPACE More stable operations of the meteorological satellites (current COMS and the following GK-2A) Climate change study by natural solar forcing as well as solar impacts on terrestrial weather phenomena [The National Weather Act 14. 2] KMA has to provide the forecast (including warning) service on various weather- and climate-related impacts due to physical causes from the SPACE

5 Operational Space Weather Service (monitoring, models, and forecast) Poster Presentation: Wonhyeong Yi et al.

6 Monitoring Solar Activities Solar Flares GOES-Primary: X-ray Flux Coronal Hole (CH) SDO AIA: Images in channes of 193A and 211A Coronal Mass Ejection (CME) SOHO LASCO2 and LASCO3 Interplanetary Space Interplanetary Magnetic Field (IMF) Solar Wind Speed, Density, and Temperature ACE was replaced by DSCOVR (as of July 27, 2016) Neat-Earth Environment Geomagnetic Storm and Proton/Electron Flux Kp Index and Dst Index

7 Operational Monitoring System Space Weather Monitoring by SDO Images, Radiation and Particle Fluxes

8 Operational Monitoring System Radiation Dose for each Polar Airway based on KREAM and CARI-6 models

9 Operational Monitoring System Satellite Operation by Magnetopause Position, Electron and Proton Fluxes

10 Models Flare Prediction (AMOS) Automatic McIntosh-based Occurrence probability of Solar activity (AMOS) Input Flare occurrence probability by each sunspot group McIntosh sunspot classification Sunspot area Sunspot area change Output Flare occurrence probability over C class within 24 hours References Lee et al., 2012: Solar Flare Occurrence Rate and Probability in Terms of the Sunspot Classification Supplemented with Sunspot Area and Its Changes, Solar Physics, 281, 639~650. Gallagher et al., 2002: Active-Region Monitoring and Flare Forecasting I. D ata Processing and First Results, Solar Physics, 209, 171~183. Solar Proton Event (SPE) Prediction Input Flare flux Flare position Arrival time of the maximum flare flux Output Probability of SPE occurrence (%) References Cane et al., 1986: Two classes of solar energetic particle events associated with impulsive and long-duration soft X-ray flares, Astrophys J, 301, 448~45 9. Reames, 1999: Particle acceleration at the Sun and in the heliosphere, Spac e Sci. Rev., 90, 413~491. Kallenrode, 2003: Current views on impulsive and gradual solar energetic p article events, J.Phys. G Nucl. Phys, 29, 965~981.

11 Models Kp Index Prediction Model Input Solar wind dynamic pressure Velocity Density IMF Output Predicted Kp index References Takahashi et al., 2001: An automated procedur e for near-real-time Kp estimates, J. Geophys. R es., 106, 21017~ Wing et al., 2005: Kp forecast models, J. Geoph ys. Res., 110, A04203, doi: /2004ja Magnetopause Prediction Model Input Solar wind dynamic pressure Velocity Density Meridional component of MF (Bz) Output Position of magnetopause Reference Shue et al. 1998: Magnetopause location under extreme solar wind conditions, J. Geophys. Res., 103, A8, 17691~ Dst Index Prediction Model Input Solar wind dynamic pressure IMF Output Predicted Dst index References Burton et al., 1975: An empirical relations hip between interplanetary conditions and Dst, J. Geophys. Res., 80, 4204~4214. Temerin and Li, 2002: A new model for the prediction of Dst on the basis of the solar wind, J. Geophys. Res., 107(A12), 1472, doi: /2001JA Temerin and Li, 2006: Dst model for , J. Geophys. Res., 111, A04221, doi: /2005JA Wang, C. B., J. K. Chao, and C. H. Lin (2003 ), Influence of the solar wind dynamic pres sure on the decay and injection of the ring current, J. Geophys. Res., 108(A9), 1341, do i: /2003ja

12 Models KREAM Korean Radiation Exposure Assessment Model for aviation route dose (KREAM) GEANT4 model+ NRLMSIS00 model Input Sunspot Number GOES Proton Flux Output Radiation dose with latitude, longitude and altitude Reference Hwang et al., 2015: Heliocentric Potential (HCP) Prediction Model for Nowc ast of Aviation Radiation Dose, JASS 32, 39~44. CARI-6M Input Predicted Heliocentric Potential (HCP) Output Radiation dose Reference Hwang et al., 2015: Heliocentric Potential (HCP) Prediction Model for Nowc ast of Aviation Radiation Dose, JASS 32, 39~44. For more advanced version of KREAM mode, please refer to HWANG et al. presentation!

13 Space Weather Alert/Warning Satellite Operation (SO) Radio Blackout (R) Solar Radiation Storm (S) Geomagnetic Storm (G) Magnetopause Position (MP) NOAA Scale SO R SO S Criterion : 6.6 R E (Geostationary Orbit) IW RD RD Radiation Dose for Polar Airways (RD) Radio Blackout (R) Solar Radiation Storm (S) SO SO Ionospheric Weather (IW) Radio Blackout (R) Solar Radiation Storm (S) Geomagnetic Storm (G) IW G RD MP

14 Space Weather Alert/Warning When R, S, G are expected to be above 4th level When R, S, G are expected to be 3rd level sample of forecast statement Warning Advisory Mediumrange FCST Daily FCST 1700KST Every Tuesday 1600KST Everyday

15 Space Weather R&D Activities

16 Space Weather R&D (2014~16) Space Weather Data Analysis and Application Study Radiation Dose for Polar Routes and Telecommunication Impact Study Development of Space Weather Forecast Models and Construction of the Integrated Forecast System Stable Operation of the Integrated Operational Model and Assessment for the Forecast Skill Operation of the KREAM model with its Service Improvement

17 Space Weather R&D (2014~16) Weather and Climate Impact Study of Space Weather Lightning impact study of high speed stream - Detected the enhancement of lightning rate in Korea - Expansion of study area over Northern Hemisphere - More detailed explanation of the physical mechanism Poster presentation: Dong-Hee Lee et al. Near real-time estimation of local K-index (Cheongyang) - Basic study for estimating local K-index over Korea - Relationship between Kp index and local K index(c.c. 0.8) - Comparison study of K index with latitudinal station data

18 Space Weather Payload (KSEM) Geo-KOMPSAT-2A To be launched in 2018 In orbit of 128.2E Sensors Requirements Application Fields Particle Detector - Electron energy range : 100keV ~ 2 MeV - Proton energy range : 100keV ~ 20 MeV - Angular Resolution (pitch angle): 60 at least Global Electron Distribution Particle Distribution Magnetometer - Measurement range : ± 64,000nT (in 3 axes) - Field Resolution : 1nT at least (on orbit) Dst and Kp Prediction Satellite Monitor Charging - Current range: ± 3pA/cm 2 - Measurement Resolution : 0.001pA/cm 2 Satellite Charging Index

19 KSEM Development Milestone Design and Review Module Set Testing for Launch Launch/IOT/Ops. Launch OPERATION /SERVICE PROJECT START SYSTEM REQUIREM ENT PRELIMIN ARY DESIGN DETAILED DESIGN ENV TEST ENV TEST TEST/LAUNCH TEST TEST/ LAUNCH TEST LAUNCH AND IOT SYSTEM REQUIREMENT DESIGNING MODEL ENV TEST TEST/ LAUNCH TEST LAUNCH AND IOT Poster presentation: Daehyeon Oh et al.

20 COMS Operation Events Summary: Temporal disruption of COMS meteorological mission on August 31, 2016(0600UTC~0900UTC) SEU might be one of reasons (KARI report) SEU: a change of state or transient induced by an energetic particle such as a cosmic ray or proton in a device. SEUs are soft errors, and non-destructive. They normally appear as transient pulses in logic or support circuitry, or as bitflips in memory cells or registers (Source: Data Analysis: - GOES data: X-ray flux, Proton Flux(>10Mev), Electron Flux(>2MeV)* - ACE data: IMF, Solar wind data - Ground-based data: Kp index, Dst index - Models: position of magnetopause

21 Characteristics of Space Weather August 19 ~ September 2, 2016 August 5 ~ 19, 2015 SEU event (Aug. 31, 2016) SEU event (Aug. 12, 2015) Characteristics: Daily maximum electron flex(>2mev) over 10 3 pfu: 4 days continued 34 times since Dec. 2013(33 months). Once a month

22 SW Impact on Satellite Operation Internal Charging: >100 kev electron (due to high energy electrons) Surface Charging: 0~100 kev electron (due to low energy electron) SEU/Burnout/Latchup: >5MeV proton (due to high energy proton) Drag Effect (satellite drag due to increase of neutral atmosphere on the satellite orbit) Although it is not easy to reveal the cause of satellite disruption, continued research, support and collaboration in the community are needed (may give a feedback to the spacecraft design)

23 KMA s Space Weather Policy Successful Operation of Space Weather Payload (KSEM) The first space-borne measurement of space weather in the geostationary eastern orbit Development of data production, validation, and application technology R&D Investment for Improving the SW Service Strengthening the government, academic, and private partnerships Close and open communication with SW users International Collaboration with WMO and Others IPT-SWISS(Inter-Program Team on Space Weather Information, System and Services) Collaborations with Asia and Oceania countries, U.S., and ESA

24 KMA s Space Weather Policy To better understand complex system between solar and terrestrial physics, so more close collaborations are needed. Meteorology Climate Sciences Chemistry Dynamics Radiative Transfer Electrodynamics Plasma Physics Space Weather

25 Space is too wide and deep for us, and many questions are still waiting for us Thank you for your attention!