towards improved operational space weather forecasts ......heliospheric da rmse in near-earth solar...

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David Jackson Suzy Bingham, Emily Down, Siegfried Gonzi, Dan Griffin, Edmund Henley, James Manners, Mike Marsh Towards Improved Operational Space Weather Forecasts challenges in modelling and observations European Space Weather Week, Leuven, Belgium, 5-9 November 2018 @MetOfficeSpace

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Page 1: Towards Improved Operational Space Weather Forecasts ......Heliospheric DA RMSE in near-Earth solar wind speed Blue = prior state, from the MAS ensemble. Green = posterior state, from

David Jackson

Suzy Bingham, Emily Down, Siegfried Gonzi, Dan Griffin, Edmund Henley, James Manners, Mike Marsh

Towards Improved Operational Space Weather Forecasts – challenges in modelling and observations

European Space Weather Week, Leuven, Belgium, 5-9 November 2018@MetOfficeSpace

Page 2: Towards Improved Operational Space Weather Forecasts ......Heliospheric DA RMSE in near-Earth solar wind speed Blue = prior state, from the MAS ensemble. Green = posterior state, from

© Crown copyright Met Office

• Met Office strategic goal for operational space weather forecasts:

• coupled Sun to Earth modelling system. Physics-based, constrained by DA.

• In reality, still far away : no coupled system, only some DA, use of empirical (not physics-based) models remains commonplace.

• Gaps in this ideal future S2E system.

• List of scientific and technical challenges to be met

• Examples of ways to start to address the problems – heliosphere DA, development of whole atmosphere model

• Gaps in observation network – use WMO requirements to address this

• Helped guide design for new operational L1 and L5 solar / heliosphere missions

• Can be used in the design of a new observation network for the thermosphere.

2

Outline

Page 3: Towards Improved Operational Space Weather Forecasts ......Heliospheric DA RMSE in near-Earth solar wind speed Blue = prior state, from the MAS ensemble. Green = posterior state, from

•Photosphere(solar surface)

•Corona(solar atmosphere)

•Solar wind(interplanetary space)

•Magnetosphere•Radiation belts

• Ionosphere

•Thermosphere

• Middle and Lower atmosphere

Toward Sun-Earth coupled modelling

GOAL: Coupled Sun-to-Earth models with DA for much-enhanced forecast capacity

Page 4: Towards Improved Operational Space Weather Forecasts ......Heliospheric DA RMSE in near-Earth solar wind speed Blue = prior state, from the MAS ensemble. Green = posterior state, from

•CME prediction

•coronal magnetic field modelling

•What ARs shall be eruptive?

•Flare prediction, AR tracking

•CH and filament identification

•SEP initiation

•Ionosphericscintillation

•Thermosphere modelling

•Thermo / ionosphere coupling

•Upper / lower atmosphere coupling (whole atmosphere model)

•Aviation radiation

•Strength of storms / substorms

•No magnetosphere model !

•Radiation belt forecasts only at Geo

Opinion of MOSWOC Scientists, Forecasters, Managers

----------------------------------------------- No coupling ! ------------------------------------------

Sun-to-Earth modellingWhat’s missing?

•Bz prediction

•DA / IPS data

•SEP propagation

Page 5: Towards Improved Operational Space Weather Forecasts ......Heliospheric DA RMSE in near-Earth solar wind speed Blue = prior state, from the MAS ensemble. Green = posterior state, from

Solar / Heliosphere ChallengesProblem Next Step Physics? DA?

Coupling?

CME prediction - P?

Coronal magnetic field modelling

NLFFF magnetofriction

P, C

What ARS shall be eruptive?

- P?

Flare prediction, AR tracking

Ensembles,SMART

CH / filament identification

CHIMERA (CH)

SEP initialisation SPARX P

Bz prediction Faraday rotn?

DA / IPS data DA prototype, IPS Enlil

P, D, C(?),

SEP propagation SPARX P

Automated CH methods (CHIMERA: Tadhg Garton, TCD)

Lack of physical understanding and insufficient data??

Need more data?

• Heavy reliance on SEL, photosphericmagnetic field

• IPS and L5 operational mission good additions

• Parker SP and SO no good for ops but good for research => future opern. missions

Do more with existing data?

• Empirical CME / SEP prediction?

• Flares done to death but no step change –need a paradigm shift e.g more physics-based

models

Page 6: Towards Improved Operational Space Weather Forecasts ......Heliospheric DA RMSE in near-Earth solar wind speed Blue = prior state, from the MAS ensemble. Green = posterior state, from

Challenges nearer to EarthProblem Next Step Physics? DA? Coupling?

Strength of storms / substorms

No / SWMF P, C

No magnetospheremodel

SWMF P, C

Rad belt f/casts only at Geo

BAS model P, (C)

Ionosphericscintillation

-

Thermosphere modelling

DTM

Thermo / ionosphere modelling

UM / TIEGCM P, D, C

Upper / lower atmosphere coupling

UM (WA version)

P, (D), C

Aviation radiation MAIRE P

More physics-based models and DA

• Simple fact that ionosphere and quite a lot of the magnetosphere is fairly well observed?

• Still need model developments. Eg MHD->PiC for substorms, ionosphere / thermosphere / lower atmosphere coupling

• But still need more obs e.g away from Geo, whole of thermosphere. Scintillation, aviation-level radiation

Page 7: Towards Improved Operational Space Weather Forecasts ......Heliospheric DA RMSE in near-Earth solar wind speed Blue = prior state, from the MAS ensemble. Green = posterior state, from

© Crown copyright Met Office

Examples of ways we are addressing these gaps

Page 8: Towards Improved Operational Space Weather Forecasts ......Heliospheric DA RMSE in near-Earth solar wind speed Blue = prior state, from the MAS ensemble. Green = posterior state, from

Heliospheric DA

RMSE in near-Earth solar wind speed Blue = prior state, from the MAS ensemble. Green = posterior state, from DA of STEREO A and B .

• Need data ahead of Earth to improve forecasts at Earth

• But need to run model back in time to update inner boundary –otherwise information gets swept out beyond 1 AU by solar wind

•Lang et al (2017) showed that EnKF can’t work with Enlil for this reason

•Applying 4D-Var to 2D solar wind model (Riley & Lionello) much more successful (Lang et al, 2018) since adjoint updates previous model state

•Window = 27 days. Simple linear model (NWP = 6 hrs). What about for an MHD model? Matt Lang (Paris), Matt Owens

(Reading)

Page 9: Towards Improved Operational Space Weather Forecasts ......Heliospheric DA RMSE in near-Earth solar wind speed Blue = prior state, from the MAS ensemble. Green = posterior state, from

• One model from the Earth’s surface to exobase

• Important role of lower level driving in thermos / ionosphericstate

A Whole Atmosphere model

Extend UM from 85 km upto the thermosphere

• Its non-hydrostatic formulation will make the UM unique amongst surface to thermosphere-spanning models.

Chartier et al, 2013

Focus on upward extension to ~170 km first

• physics & chemistry schemes in development

• In meantime, relaxation to T climatology gives stable testbed (100 km lid; 120 km lid being worked on)

• Modify GW parametrization to work in MLT

• Molecular viscosity for realistic wave damping in thermosphere – enables lid > 130 km

Matt Griffith (Bath), Chris Kelly (Leeds)

Page 10: Towards Improved Operational Space Weather Forecasts ......Heliospheric DA RMSE in near-Earth solar wind speed Blue = prior state, from the MAS ensemble. Green = posterior state, from

© Crown copyright Met Office

WMO observations requirements and data gaps

Page 11: Towards Improved Operational Space Weather Forecasts ......Heliospheric DA RMSE in near-Earth solar wind speed Blue = prior state, from the MAS ensemble. Green = posterior state, from

WMO Space Weather Observing

Requirements

•Rolling requirements – observations for operational SpWXhttp://www.wmo-sat.info/oscar/applicationareas/view/25

• "threshold" – min.

requirement for

useful data

•"goal" - ideal

•"breakthrough" -

intermediate level.

An optimum, from

cost-benefit POV,

when planning or

designing obs

systems.

WMO Statement of Guidance: assessment of adequacy of

observations to fulfill requirements; suggests areas of progress

towards improved observing systems.

http://www.wmo.int/pages/prog/www/OSY/SOG/SoG-SW.pdf

Page 12: Towards Improved Operational Space Weather Forecasts ......Heliospheric DA RMSE in near-Earth solar wind speed Blue = prior state, from the MAS ensemble. Green = posterior state, from

Future L1 and L5 Missions

• WMO / Met Office requirements fed into

ESA Phase 0, and Phase 1 / 2A studies

• CME

Detection

strongly

dependent on

STEREO and

SOHO (L1)

c/graphs

• Way past

their planned

lifetimes

Observation Instrument Priority

Coronal imagery (CME detection) Coronagraph M(andatory)

Imaging of transients on SEL Heliospheric Imager M

Photospheric full disk

magnetograms

Magnetograph M

EUV imaging of coronal structures

and solar activity

EUV Imager M

Solar wind plasma measurement Plasma analyser M

IMF vector measurements Magnetometer M

X-ray flux measurement X-ray flux meter M

Radio burst detection Radio receivers S(econdary)

Energetic particles Proton and electron

detector

S

Proposed Instrument Baseline for L5 Mission

Page 13: Towards Improved Operational Space Weather Forecasts ......Heliospheric DA RMSE in near-Earth solar wind speed Blue = prior state, from the MAS ensemble. Green = posterior state, from

WMO Statement of Guidance & Gap Assessment

Lower thermosphere ρ - Less than Marginal / Marginal – (limb

sounding UV) SSUSI and SSULI may meet reqs, but no info available

on accuracy, obs cycle and timeliness

Upper thermosphere ρ - Marginal – Swarm meets some reqs (not

timeliness, uncertainty, vert. res.). Partly addressed by new missions

eg GRACE follow-on? SSUSI/SSULI may meet reqs.

Wind: Lower and upper thermosphere - Poor – Only a few sparse FPI

observations. Poor timeliness. Awaiting ICON mission in 2017.

Accelerometer wind errors too large.

T: Lower Thermosphere - Marginal – OSIRIS data are available, but they

do not cover whole vertical range and have poor timeliness. Upper

Thermosphere - Poor – just FPI

Layer U/certainty Hor res Vert res Ob cycle Timeliness

ρ Hi Thermo 10/15/20 % 100/200/500

km

20/50/100

km

5s / 5 min

/ 30 min

30/45/60 min

ρ Lower

Thermo

5/7/10 % 100/200/500

km

5/10/25

km

5s / 60 s /

5 min

5/20/60 min

Page 14: Towards Improved Operational Space Weather Forecasts ......Heliospheric DA RMSE in near-Earth solar wind speed Blue = prior state, from the MAS ensemble. Green = posterior state, from

Possible solution: Fill gaps with smallsat

constellations (after QB50)

QB50 Objective: to carry out atmospheric research within the

lower thermosphere, between 200 - 380km altitude.

Instruments include Ion-Neutral Mass Spectrometer (INMS): T, ρ

Constellation designed

to be closer to WMO

vertical resolution

requirements

•Use nanoracks to launch

cubesat batches (ISS,

415km) 60 days apart =>

leads to separation in

altitude of O(10) km

•Also 8 Cubesats at 500

km

To be addressed in future mission

•Timeliness poor (no QB50 data reception budget)

•Maintaining full coverage – initial orbits, replenishing

constellation, small onboard propulsion systemsSee Caspi et al, submitted to Space Weather

Page 15: Towards Improved Operational Space Weather Forecasts ......Heliospheric DA RMSE in near-Earth solar wind speed Blue = prior state, from the MAS ensemble. Green = posterior state, from

© Crown copyright Met Office

• Met Office strategic goal for operational space weather forecasts:

• Big gaps between state of the art and where we want to be

• Further model and DA developments are required. Some being worked on (heliospheric DA, whole atmosphere modelling)

• Progress is also being held back by lack of sufficient observations

• WMO space weather team have provided observations requirements and analysed gaps

• Guide design for new operational L1 and L5 solar / heliosphere missions and new observations for the thermosphere.

• Greater publicity of WMO activities and interaction with other relevant groups (Smallsat researchers, CGMS, etc, etc) vital

• Maybe have an observations R2O workshop?

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Conclusions