Prospects for real-time physics-based thermosphere ionosphere models for neutral density specification and forecast Tim Fuller-Rowell, Mariangel Fedrizzi,

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Presentation transcript:

Prospects for real-time physics-based thermosphere ionosphere models for neutral density specification and forecast Tim Fuller-Rowell, Mariangel Fedrizzi, Mihail Codrescu, Tomoko Matsuo, and Catalin Negrea Sept 25-26th, 2012 NADIR MURI

2007 CHAMP/CTIPe Orbit Average Comparisons Main purpose of this study is to simulate the model response to short-period variations in geomagnetic activity during the year. To accommodate this goal the semi- annual variation of neutral density in CTIPe has been removed by introducing a semi-annual variation in electric field small-scale variability. Electric fields can directly change Joule heating by varying the ion convection at high-latitudes (Deng and Ridley, 2007). An increase in Joule heating raises the neutral temperature, which enhances the neutral density at constant heights. Electric field variability changes the distribution of Joule heating significantly, and can introduce interhemispheric asymmetries (Codrescu et al., 1995, 2000). 400 km New CTIPe run including seasonal variation in the E-field small scale variability R= 0.88 RMSE= 0.17 BIAS= -0.017 SD= 0.17 Sept 25-26th, 2012 NADIR MURI

Coupled Thermosphere Ionosphere Plasmasphere Model with self-consistent Electrodynamics Global thermosphere 80 - 500 km, solves momentum, energy, composition, etc. Vx, Vy, Vz, Tn, O, O2, N2, …. High latitude ionosphere 80 - 10,000 km, solves continuity, momentum, energy, etc. O+, H+, O2+, NO+, N2+, N+, Vi, Ti, …. Plasmasphere, and mid and low latitude ionosphere Self-consistent electrodynamics Forcing: solar UV and EUV, Weimer electric field, TIROS/NOAA auroral precipitation, tidal forcing Sept 25-26, 2012 NADIR MURI

Magnetospheric Forcing of CTIPe ACE solar wind data defines magnetospheric sources Weimer electric field patterns: Auroral precipitation pattern: NADIR MURI

Real-time CTIPe at NOAA Space Weather Prediction Center Implemented in 2010 in test operational mode Automated scripts extract solar wind data from operational database ACE measurements of IMF, solar wind (SW) velocity and density, and either solar F10.7 or EUV flux to force the global circulation model Due to the 30 minute propagation time of SW to the nose of the magnetosphere it provides a 10-20 minute forecast Web page shows neutral temperature, electron density, mean molecular mass, nmF2, hmF2, TEC, and model inputs in a quick look format Runs 100 times faster than real time (run once, sample 3-D density field) Can use SRPM EUV solar radiation forecast and WSA-ENLIL geomagnetic activity forecast for 5-day prediction updates every 6 hours Automated validation and comparison with GAIM, US-TEC, DLR, etc. Extensive other validation Can provide Joule heating index for JB2008 http://helios.swpc.noaa.gov/ctipe/CTIP.html

NmF2 and hmF2 against MH ionosonde O/N2 ratio compared with TIMED-GUVI SRPM (Fontenla et al., ) EUV proxy (F10.7, F10.781 day)

Relationship between CTIPe Joule Heating and neutral density: Joule heating index Fedrizzi et al. (Space Weather, 2012) INPUT (Joule heating) IMPULSE RESPONSE (shaping filter) OUTPUT (Joule heating index) Convolution of CTIPe Joule heating with the shaping filter results in a new parameter (Joule heating index) representing the integral of the product of the two functions.

Bruce Bowman Sept 25-26th, 2012 NADIR MURI

Sept 25-26th, 2012 NADIR MURI

Real-time CTIPe Summary CTIPe running at SWPC in real-time in test operational mode Joule heating index can be provided as test operational index Available at CCMC and used by ISS operations Provided to AFRL High vertical resolution version being validated (improved tidal propagation, MTM, etc.) Sept 25-26th, 2012 NADIR MURI

Robust and Practical Assimilative Methods Tomoko Matsuo Sept 25-26th, 2012 NADIR MURI

Assimilative Method I Optimal interpolation using CTIPe with maximum-likelihood covariance estimate of the neutral density improves the density specification up to 40-50 % in comparison to CTIPe predictions [Matsuo et al., SW, 2012]. Low-dimensional covariance is built with EOFs to describe large-scale correlation succinctly [Matsuo and Forbes, JGR, 2010; Lei et al., JGR, 2012]. Currently, the analysis is limited to 400km. Application to real-time CTIPe (STTR)

Assimilative Method II EnKF using NCAR-TIEGCM [Matsuo et al., JGR, 2012; Lee et al., JGR, 2012; Matsuo and Araujo-Pradere, RS, 2011] EnKF is capable of improving the neutral density specification by assimilating CHAMP/GRACE in-situ neutral density and COSMIC Ne profiles. DART/TIEGCM is open to the community. Assimilation of HASDM data to TIEGCM (AFRL small univ) Data Assimilation Research Testbed (http://www.image.ucar.edu/DARes/DART) TIEGCM 1.94 (http://www.hao.ucar.edu/modeling/tgcm)