NOAA/NCEP Space Weather Prediction Center Space Weather Prediction Testbed: Transitioning Satellite Data to Operations Rodney Viereck Director, Space Weather Prediction Testbed Presentation to the Satellite Science Meeting 24 February, 2015 Outline: SWPC and SWPT Models and Products IDEA GOLD

Space Weather Prediction Center Operations – Space Weather Forecast Office R & D – Space Weather Prediction Testbed Transitioning models into operations Research-to-Operations Applied Research Model Development Model Test/Evaluation Model Transition Operations Support Operations-to-Research Customer Requirements Observation Requirements Research Requirements Putting out daily forecast since 1965. Specifications; Current conditions Forecast; Conditions tomorrow Watches; Conditions are favorable for storm Warnings; Storm is imminent with high probability Alerts; observed conditions meeting or exceeding storm thresholds 24 February 2015

Modeling at NOAA – A Sun to Earth Modeling Partnerships with the Space Weather Research Community Sun: WSA Operational Solar Wind: Enlil Operational Aurora: OVATION Operational Magnetosphere: U. Michigan SWMF Operational in 2016 Ionosphere: IPE Operational in 2017 Thermosphere: WAM Operational in 2017 Ground: E-Field Operational in 2016 Note: a vast majority of customers are concerned only about the near-Earth ionosphere 24 February 2015

Primary Space Weather Satellites White: Currently Operating Red: Future Missions STEREO (Ahead) SOHO (NASA/ESA) Solar EUV Images Solar Corona (CMEs) ACE (NASA) Solar wind composition, speed, and direction Magnetic field strength and direction GOES (NOAA) Energetic Particles Magnetic Field Solar X-ray Flux Solar X-Ray Images SOHO ACE DSCOVR COSMIC II (Taiwan/NOAA) Ionospheric Electron Density Profiles Ionospheric Scintillation L1 DSCOVR (NOAA/NASA/DOD) Solar wind composition, speed, and direction Magnetic field strength and direction GOES SDO SDO (NASA) Solar EUV Images Solar Magnetograms Solar EUV spectra POES METOP COSMIC II STEREO (NASA) CME Direction and Shape Solar wind composition, speed, and direction Magnetic field strength and direction POES (NOAA) METOP (EUMETSAT) High Energy Particles Total Energy Deposition Solar UV Flux STEREO (Behind) 24 February 2015

Relativistic Electron Forecast Model Current SWPC Products Synoptic Drawings Solar X-ray Flux US-TEC Relativistic Electron Forecast Model WSA-Enlil HF Com Absorption CME Analysis Tool WSA Aurora Forecast Model - 30 Minute Forecast Wing Kp Forecast Satellite Environment Model 24 February 2015

Models Under Development Ionosphere/Plasmasphere/ Electrodynamics Model Global TEC Assimilative Model Solar Flare Forecast Whole Atmosphere Model Far-side Analysis ROTI GPS Product Geospace Model Space weather is caused by a series of interconnected events, beginning at the Sun and ending in the near-Earth space environment. Our ability to predict conditions and events in space depends on our understanding of these connections, and more importantly, our ability to predict details. More accurate products with improved lead time requires modeling multiple domains of the Sun-Earth system and understanding the complex couplings between the components of the system. We have embarked on an important initiative to introduce into the operational environment, a modeling framework that captures critical domains of the Sun-Earth system, beginning on the Sun and ending at the Earth’s surface. Using the Enlil model we will understand the structure of the solar wind as it propagates from the Sun to Earth; the geospace Space Weather Modeling Framework will help us understand the geomagnetic response to the changes in the solar wind structure, and provide regional predictions of the rapid time rate of change of the Earth’s magnetic field; the Whole Atmosphere Model will help us understand critical details in the mesosphere, the exosphere, and in particular the ionosphere, helping us to understand the complex and dynamical links between the lower atmosphere and the upper atmosphere; and through our new understanding of ground conductivity across North America, we will characterize and predict the regional electric field and the associated currents that can cause havoc to the electric power grid. Solar EUV Irradiance Model Specification Forecast Aurora Forecast Model - 3-Day Forecast Electric Field Model 24 February 2015

Models Under Development Integrated Dynamics in Earth’s Atmosphere IDEA Integrated Dynamics in Earth’s Atmosphere Ionosphere/Plasmasphere/ Electrodynamics Model Global TEC Assimilative Model Solar Flare Forecast Whole Atmosphere Model Far-side Analysis ROTI GPS Product Geospace Model Space weather is caused by a series of interconnected events, beginning at the Sun and ending in the near-Earth space environment. Our ability to predict conditions and events in space depends on our understanding of these connections, and more importantly, our ability to predict details. More accurate products with improved lead time requires modeling multiple domains of the Sun-Earth system and understanding the complex couplings between the components of the system. We have embarked on an important initiative to introduce into the operational environment, a modeling framework that captures critical domains of the Sun-Earth system, beginning on the Sun and ending at the Earth’s surface. Using the Enlil model we will understand the structure of the solar wind as it propagates from the Sun to Earth; the geospace Space Weather Modeling Framework will help us understand the geomagnetic response to the changes in the solar wind structure, and provide regional predictions of the rapid time rate of change of the Earth’s magnetic field; the Whole Atmosphere Model will help us understand critical details in the mesosphere, the exosphere, and in particular the ionosphere, helping us to understand the complex and dynamical links between the lower atmosphere and the upper atmosphere; and through our new understanding of ground conductivity across North America, we will characterize and predict the regional electric field and the associated currents that can cause havoc to the electric power grid. Solar EUV Irradiance Model Specification Forecast Aurora Forecast Model - 3-Day Forecast Electric Field Model 24 February 2015

With and Without Lower Atmosphere: Typical iono-thermosphere model: Driven by Solar EUV and Geomagnetic Storms. Global maps show little fine structure Ionosphere-thermosphere model coupled to the lower atmosphere: Global maps show structure relevant to GPS accuracy and availability HF Comm. The temperature structure from a stand-alone thermosphere ionosphere plasmasphere model (e.g., CTIPe) is similar to the MSIS empirical model. The Whole Atmosphere Model (WAM) drives variability from the chaotic lower atmosphere which introduces a whole spectrum of variability. 24 February 2015

IDEA (Integrated Dynamics in Earth’s Atmosphere) Whole Atmosphere Model (WAM = Extended GFS) Ionosphere Plasmasphere Electrodynamics (IPE) Integrated Dynamics in Earth’s Atmosphere (IDEA = WAM+IPE) Specification and Multi-day forecasts for GPS/GNSS Navigation HF radio communication Satellite communication Ionosphere Model WAM Neutral Atmosphere 0 – 600 km GFS 0 – 60 km Whole Atmosphere Model Thermosphere Mesosphere Stratosphere Troposphere 24 February 2015

IDEA ionospheric forecast Daytime ExB vertical drift at Jicamarca. A precursor to ionospheric scintillation which blocks GPS Observed Forecast with IDEA Observed 14 Day Forecast with IDEA Total Electron Content. Directly related to GPS Error 24 February 2015

2009 Sudden Strat. Warm Event: WAM vs GFS Forecast Raising the top of the GFS model improves forecast lead time WAM forecasts the Strat-Warm 2 days before GFS January 13 Forecast January 15 Forecast The full impact of WAM on tropospheric forecasts needs to be evaluated 24 February 2015

IDEA Task List Complete the coupling of WAM to IPE Improve WAM (and GFS) Improve stratospheric ozone and water vapor chemistry Improve gravity wave parameterization to include non-orographic gravity waves Test higher resolution Implement “Deep Atmosphere” gridding Non-hydrostatic core Expand data and data assimilation up to 100 km Develop data and data assimilation for 100-200 km 24 February 2015

WAM – IPE Data List Stratosphere and Mesosphere Extend analysis of SSMIS to ~80-100 km altitude for temperature. Extend use of AIRS, IASI, CRIS, AMSUA for temperature. MLS for ozone and temperature to 85 km Thermosphere and Ionosphere Ionospheric radio occultation e.g., COSMIC-II Line of site Total Electron Content, Scintillation Indices ( Accelerometer data for neutral density e.g., GOCE, GRACE, SWARM Ground-based dual frequency GPS receivers Global network of Ionosondes/Dynasondes Incoherent Scatter Radars (MH, Arecibo, Jicamarca, AMISR, etc.) Solar flux, GOES-EUV, NASA SDO Solar Wind: ACE/DSCOVR Missing Data: High spatial and temporal resolution global coverage of… Neutral Temperature Neutral Densities Electron Densities 24 February 2015

Capturing Global Phenomena Ionospheric Total Electron Content Observation FORMOSAT-3/COSMIC: Accumulation of a months worth of data taken between 20:00 and 22:00 local time TIMED GUVI (similar to DMSP SSUSI): 6 orbits of data Capturing the spatial and temporal variations in the ionosphere is very difficult from LEO orbit. 24 February 2015

4/17/2017 Global-scale Observations of the Limb and Disk (GOLD) NASA Instrument of Opportunity Instrument Summary Mass 34 kg Power 61 W Size 42×42×70 cm Observations: Hemispheric maps of… Neutral temperature O/N2 ratio (composition) Electron density Limb scans of temperature Imaging Spectrograph: Two independent, identical channels Wavelength range: 132 – 160 nm Target Launch: October 2017 Hosted Payload on geostationary commercial satellite Florida Space Institute (FSI) University of Central Florida PI: Richard Eastes Project Coordinator: Andrey Krywonos Laboratory for Atmospheric and Space Physics (LASP) University of Colorado Deputy PI: William McClintock Project Manager: Mark Lankton NOAA SWPC Collaborator: Mihail Codrescu 155 nm? 24 February 2015

Data Assimilation Challenge The Ionosphere-Thermosphere system is a strongly driven system Order of magnitude electron density changes… Driven by order of magnitude changes in solar EUV and Geomagnetic activity. Occur on timescales of minutes. Data assimilation is challenging Adjusting ionospheric conditions to match observations does not work. The ionosphere returns to its original state in the next few time steps. Not sure which DA scheme is best Extended GSI/hybrid (3D EnVar) Extended 4D hybrid (4D EnVar) Separate Iono-Thermo ensemble Kalman Filter Assimilate Data 24 February 2015

Summary The Space Weather Prediction Testbed provides new models and products to the Forecast Center and to Customers Nearly every space weather model/product depends on real-time satellite data IDEA: The coupled Whole Atmosphere Model and Ionosphere Plasmasphere Electrodynamics Model represents a significant advance in space weather modeling Need to expand existing data and data assimilation in the 60-100 km region Need new data and data assimilation techniques in the 200 – 600 km region. The GOLD mission will provide new data critical for space weather modeling Global (hemispheric) continuous real-time data Both ionosphere and neutral atmosphere data 24 February 2015