Evaluation of space-based observation capabilities in OSCAR in support of Gap Analysis 12th European...
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Transcript of Evaluation of space-based observation capabilities in OSCAR in support of Gap Analysis 12th European...
Evaluation of space-based observation capabilities in OSCAR
in support of Gap Analysis
12th European Space Weather Week,Ostend, 23-27 November 2015
Jérôme Lafeuille (WMO)
WMO; Name of Department (ND)
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Acknowledgements
Biz. Bizzarri analysed 900 instruments and developed 1800 rules !
Nils Hettich, Edward Akerboom, Timo Proescholdt developed the OSCAR software
Alain Hilgers and several of his ESTEC colleagues provided guidance on rules and properties for space weather sensors
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Outline
1. Motivation2. OSCAR operational version3. New features (Version currently in test)4. Application of the expert system to space weather
sensors5. Perspectives
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Motivation WMO Congress agreed to support space weather operational activities
(May 2015). This requires a comprehensive, global observing system, with global data sharing and cooperation
There are hundreds of space-based sensors but who knows which sensors are actually available or planned ? Which ones are relevant for “my” applications ?
A synoptic view of current and future capabilities is needed toperform a Gap Analysis and tosupport global planning and evolveto a true global observing “system”
WMO thus developed OSCAR“Observing System CapabilityAnalysis and Review” database
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OSCAR/Space operational version (www.wmo.int/oscar)
• >900 instrument models• ~ 1000 visits/day• Worldwide users : space agencies, main operational centres,
application development centres, consultants, researchers, students…• Used for reports, application planning, gap analysis, socio-economic
benefit studies, frequency management, etc. in Earth Observation. • The Space weather part is not validated.
Factual information content Name, purpose Mass, power Orbit (type, alt, ECT, lon) Launch date, end date, status Data access, telecom frequencies
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Satellite
Programme
Agency
Instrument • Name, purpose• Mass, power• Type, description, scan mode• Resolution FOV, coverage• Status• Spectral & other characteristics
Satellite payload• Detailed status, dates• Link to calibration• Link to event log
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Mapping instruments to variables
Basis of the gap analysis
Which instruments can measure a given variable?
Which variables can be measured with a given instrument?
Two sides of the same question
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Measurement Timeline for Solar EUV flux
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Outline
1. Motivation2. OSCAR operational version3. New features (Version currently in test)4. Application of the expert system to space weather
sensors5. Perspectives
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Instruments searchable by properties New !
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Instruments searchable by properties
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Instruments searchable by properties
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Instruments searchable by properties New !
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New instrument-variable mapping
Two independent approaches will be available in OSCAR:
A simplified (trivial) approach :- for each sensor we record the «Mission objectives» stated by the instrument provider (measurements that the sensor has been specified to measure): primary, secondary, and opportunity objectives
An expert system based on physics-based objective rules- concept presented initially at ESWW-11 - implemented in the new version of OSCAR (currently in test)- validated for Earth Observation instruments only
New instrument-variable mapping principle
Instrument design requirements e.g: Energy bands Spectral
channels Aperture Resolution Dynamics No of channels Polarization Etc..
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XXX
X
X
XXXX
X
X
XX
XXX
Variable 3
Variable x
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Variable 2
Variable 4
Variable y
Variable 1
XXX
X
X
XXXX
X
X
XX
XXX
Science-based rules
Objective assessment
Algorithm summary
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Type 1Type 2
Each instrument type has a set of properties which define a particular metrics
Instrument has a profile P in this metrics __________
Variable U
Variable V
Variable W
For a given variable we look at all rules applying to this variable and test the applicable instruments against these rules
For an instrument, the rule providing the best score defines the relevance of this instrument for the considered variable.
RuleRule
RuleRule
Enables objective comparison of potential performance of different classes of sensors Performance drivers are defined objectively on the basis of
physical measuring principles Each instrument is characterized by fully objective features
«Rules» are purely declarative – can be updated independently of the software itself - facilitating scientific maintenance
Transparent: the rules can be submitted to external reviews
Proved very efficient for the 600+ Earth Observation instruments (~ 1800 Rules for 120 variables)
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Benefit of this expert system approach
Outline
1. Motivation2. OSCAR operational version3. New features (Version currently in test)4. Application of the expert system to space weather
sensors5. Perspectives
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Applying this approach to space weather sensors
• Step 1: Define an instrument typology • Step 2: For each type of sensor, identify the «properties», i.e.
the key specifications driving the performance • Step 3: For each variable, develop rules quantifying the
potential relevance of a sensor to measure a variable, as a function of the properties
• Step 4: Enter the applicable properties of each actual sensor
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Work in progress !
Step1: space weather sensor typology
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Solar activity monitors• Solar or space imager (incl. heliospheric imagers and coronograph)• Solar magnetograph (imaging spectrometer) and velocity sensor• Solar photometer or spectrometer • Solar microwave radiometer or radio receiver• Other solar monitorsSolar wind and interplanetary monitors• Solar wind radiometer/spectrometer • Solar wind particle spectrometer• Interplanetary magnetometer • Electric field/radio/other sensors(Charge det., dosimeter, plasma density probe)Geospace monitors • Geospace radiometer/spectrometer • Magnetospheric particle spectrometer• Magnetometer • Geospace electric field/radio/other sensors (Charge det., dosimeter, plasma drift) • Aurora or special imager (including plasmasphere UV)
Step 2: Properties for several sensor types (examples)
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Solar imagers Particle spectrometers Magnetometers/Electric field sensor
Includes 17.3 nm Energy min for electron flux (keV) 3-axis magnetometer
Includes 19.3-19.5 nm Energy max for electron flux (keV) Uncertainty (nT)
Includes 28.4 nm Energy min for proton flux (keV) Resolution (nT)
Includes He-II Ly-α (30.4 nm) Energy max for proton flux (keV) Response frequency (Hz)
Includes Far UV (117-170 nm) Angular range (solid angle) in sr Measures electric field
Includes H Ly-α (121.65 nm) Angular resolution (% of 2π sr) Uncertainty (mV/m)
Includes CaII K (393.4 nm) Time resolution (s) (sampling rate) Dynamic range
Acquires White light Dynamics Is a charge detector
Has polarimetric capability Sensitivity Is a dosimeter
Has Doppler capability Is Pointing to the Sun Is a plasma drift meter
Is a Spectrometer Energy spectral resolution Is a plasma density probeIs a coronagraph Detects Electrons, protons
FoV inner/outer limit (SolarRadii) Detects alfa, heavy ions
Spatial resolution (km or arcsec) Detects neutrons
Step 3: Examples of rulesFor this Variable
With this type of instrument
If the following conditions are true Then the relevance is
Solar wind density
Particle spectrometer
Detects protons, 0-10 keVSun pointing ; Solid angle >= 2πEnergy spectral resol < 10% (resp. 20 %)Time resol < 10sDynamics 1:100,000; Sensitivity (TBD)
Excellent(resp. Very high)
Solar wind density
Particle spectrometer
Detects electrons, 0-100 eVSolid angle >= 2πEnergy spectral resol < 10% (resp. 20 %)Time resol < 10sDynamics 1:100,000; Sensitivity (TBD)
Excellent(resp. Very high)
Solar X-ray flux
Solar photometer/ spectrometer
X-Ray detector; include [0.05-0.8 nm] rangeFoV includes whole Sun; Time resol < 1 min
Excellent
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Step 4: Populating the Instrument properties
• Information gathered for OSCAR -1 needs to be converted into the «Properties» framework
• Much of the required information is missing for space weather sensors
• Input from space agencies /instrument developers is dramatically needed
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Example of Gap Analysis (on incomplete test data set)
Variable selected: Proton differential
directional flux
Method selected« Simplified » Gap Analysis
Outline
1. Motivation2. OSCAR operational version3. New features (Version currently in test)4. Application of the expert system to space weather
sensors5. Perspectives
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Discussion
• Experience with OSCAR for Earth Observation sensors suggests that OSCAR can be very useful for the SW community– Promote awareness /informed use of space-based sensors – Supports overall planning and gap analysis
• The expert system approach can become a collaborative tool– The «Rules» and properties can be reviewed by expert groups– Thus improving the evaluation, building confidence, shared ownership– Can contribute to capacity building
• Dependent on support from instrument providing agencies– Support dramatically needed to share detailed sensor characteristics
• Collaboration is welcome to the development of rules and for betatesting
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Thank you for your attention!Please visit: www.wmo.int/oscar
Your feedback is welcome
www.wmo.int