1. Utilizing Scientific Advances in Operational Systems
Terry Onsager, Tom Berger, and Howard Singer
NOAA, Space Weather Prediction Center

2. Main Points • Operational Sun-to-Earth Modeling Suite
• Elements of a Research-to-Operations Effort
• Elements of an Operations-to-Research Effort
• Challenges in Utilizing Research in Operations

3. Components of NOAA’s Numerical Space Weather Modeling Effort
Magnetosphere/
Ionosphere
Atmosphere/
Ionosphere
Solar /Solar Wind
L1 Satellite Location – ACE and now DSCOVR

4. SWPC Operational Model Suite Tracking solar storms from “Sun to Mud”
GMU/AFRL WSA/Enlil
U. Michigan Geospace
NOAA/CIRES WAM-IPE
USGS/NOAA E-field
Inputs:
GONG solar magnetic field data
SOHO/LASCO coronagraph CME images from L1
Validation:
DSCOVR solar wind character at L1
GOES magnetometer shock arrival
Inputs:
DSCOVR solar wind density, temp, speed, mag field at L1
Solar F10.7 radio flux measurements
Validation:
GOES vector magnetic field
USGS magnetometer network
Inputs:
GFS Tropospheric weather model inputs
GOES Solar EUV flux
COSMIC-2 RO electron density
Geomagnetic storm data from Geospace
Validation:
GPS receiver network TEC measurements
Inputs:
USGS lithospheric conductivity model
USGS magnetometer network
Validation:
USGS geoelectric field measurements.
Operational
Operational FY16
Operational FY17-19
Operational FY17
Note: all models developed with NASA and/or NSF funding at some level.

5. Four Stages of Utilizing Scientific Advances in Operations
WSA-Enlil
1. Demonstrate model value – Value to customers must exceed cost to transition and to run model operationally
2. Develop operational software from research model
3. Implement model and product generation on operational computer
4. Continuously improve and upgrade operational model
Geospace

6. Establishing Value toward Operational Services is a Necessary Condition
• Demonstrate model value – Value to customers must exceed cost to transition and to run model operationally
Strategic Importance
Operational Significance
Implementation Readiness
Cost to Operate, Maintain, and Improve
• The need for performance metrics has long been well known
• However, we still do not know how quantitatively good or bad our current scientific or operational capabilities are (metrics)

7. Establishing Operational Value is a Necessary Condition
• Demonstrate model value – Value to customers must exceed cost to transition and to run model operationally
Enil/Cone Shock Arrival Time Errors:
+/- 5.9 hours
WSA-Enlil
Taktakishvili et al., 2009

8. Establishing Operational Value is a Necessary Condition
• Demonstrate model value – Value to customers must exceed cost to transition and to run model operationally
Geospace models evaluated: Regional K and dB/dt
CCMC, modelers, SWPC, and science community
Distribution of observed mid-latitude K values for modeled K values of 4, 6, and 8
Observed K (Newport Station)
K = 4
K = 6
K = 8
Modeled K
Univ. of Michigan SWMF

9. Operational Evolution – “Operations-to-Research”
Continuous improvement of operational models is an unmet need
• Forecasters and customers gain experience and provide feedback
• Scientific advances improve model quality
• However, mechanisms do not exist to enable scientists to use, evaluate, and participate in the improvement of operational models

10. Operational Evolution – “Operations-to-Research”
National Space Weather Action Plan (2015):
Action 5.6.2: DOC and DOD, in collaboration with NASA and NSF, will develop a plan (which may include a center) that will ensure the improvement, testing, and maintenance of operational forecasting models.
Operations-to-Research Workshop held August 16-17, 2016
Building a culture of research-operations coordination was recognized as a key factor

11. Areas with Good Awareness
- Agencies recognize the need to address both space weather research and operations
- There have been many success where operational capabilities have been significantly enhanced;
- The major user needs for operational forecasts and specifications are well known;
- The need to improve our operational products and services from our research understanding is well known;
- The need for performance metrics is well known.

12. Areas in Need of Improvement
- We do not know how to predict what we know needs to be predicted (i.e., solar eruptions, IMF at 1 AU, etc.)
- We do not have quantitative scientific or operational metrics
- Funding to address topics of operational relevance is lacking
- Scientists are unable to use, evaluate, and participate in the improvement of operational models, e.g., community models
- The research environment fosters the advancement of fundamental scientific understanding, not the improvement of operational products.

13. Applied Research in Meteorology
- Research to improve the accuracy of forecasts and warnings
- Collaborative between operational forecasters and academic institutions
- Applied research of interest to operational meteorology community
- Apply scientific knowledge to operational products and services

14. Summary • Elements of using scientific tools in operations:
- Demonstrate operational value;
- Develop operational software;
- Implement on operational computer;
- Continuously improve operational capability.
• Performance metrics are important to determine operational value and to measure improvement.
• A key challenge is to have scientists actively participate in the use, evaluation, and improvement of operational products.
• If community models are required, how can we establish a path to develop them?