1. CISM solar wind metrics M.J. Owens and the CISM Validation and Metrics Team Boston University, Boston MA Abstract. The Center for Space-Weather Modeling (CISM) has developed a coupled model of the whole Sun-to- Earth system, from the solar photosphere to the terrestrial thermosphere, which is undergoing continual refinement. Validation of the component models is critical, both throughout their individual development and their integration in the coupled system. The first routinely available in situ observations along the solar-terrestrial chain are of solar wind just upstream of Earth. Thus coronal and heliospheric models are often considered in tandem for the purpose of validation. In this study we calculate performance metrics for empirical, hybrid empirical/physics-based and full physics-based coronal-heliospheric models. Simple point-by-point analysis techniques, such as mean-square-error and correlation coefficients, indicate that the empirical scheme currently gives the best forecast of solar wind speed at 1 AU. However, a more detailed analysis shows the errors in the physics-based schemes are predominantly due to small timing errors, and that the large-scale features of the solar wind are actually well modeled: We suggest that additional ``tuning'' of the coupling between the coronal and heliospheric physics-based models could lead to a significant improvement of their accuracy. Furthermore, we note that the physics-based models accurately capture dynamic effects, such as magnetic field compression, flow deflection and density build-up at solar wind stream interaction regions, which the empirical schemes do not. 1. Component models 2. Coupled models 3. Solar wind speed at L1 4. High Speed Enhancements (HSEs) 5. Conclusions Corona WSA The Wang-Sheeley-Arge model of the corona uses a photospheric field observations to constrain a modified magnetostatic potential field source surface (PFSS) model of the corona. Solar wind speed at the WSA outer boundary is determined by the expansion of magnetic flux tubes. MAS The MAS solution to the corona is given by the time-dependent MHD equations, with finite resistivity and viscosity, in spherical geometry, using photospheric field observations as the inner boundary condition. Heliosphere Ballistic projection The solar wind speed from the outer boundary of the coronal model is ballistically projected to 1 AU, accounting for stream interactions. ENLIL ENLIL is a three-dimensional, ideal MHD simulation of the solar wind that uses the radial field and speed from the coronal model as its inner boundary condition. Component models can be coupled together to produce different configurations of coronal/heliospheric models. Baseline – WSA coronal model using NSO magnetograms, ballistically propagated to 1 AU. WENLIL – WSA coronal model using NSO magnetograms, used to initiate the ENLIL model of the heliosphere. CORHEL – MAS model of the corona with NSO magnetograms, used to initiate the ENLIL model of the heliosphere. A High Speed Enhancements (HSE) is defined as any region of the solar, 2 days or longer, in which the net solar wind speed increase is 100 km/s or more. Compare the number of hit, missed and falsely predicted streams: MHD models can capture structure resulting from dynamic effects at stream interaction regions: Magnetic field compression Plasma flow deflections Density enhancement Underestimate in CORHEL slow wind speed As density is determined by mass flux, over estimate in density Both CORHEL and WENLIL underestimate B at 1 AU Baseline model explicitly sets B at 1 AU to 5nT Comparisons of 8 years of solar wind speed prediction with observations from ACE/Wind (black lines) All three coupled models track the overall structure very well. Mean square error (MSE) for this whole period suggests the baseline is the best prediction Can compute a “skill” by comparing the MSE of a model with the MSE of the baseline Drop in “skill” in 1997, is associated with a very low baseline MSE, due to the low variability of the observed solar wind being well captured. Skill of CORHEL remains low due to slight under prediction of slow solar wind speed We have tested the predictive capability of three coupled models by comparison to 8-years of solar wind data. The baseline empirical model current gives the best solar wind speed prediction (at least in terms of MSE). Timing and magnitude of high speed enhancements is well predicted by CORHEL. WENLIL probably needs further tuning of the WSA – ENLIL coupling. Solar wind features formed by dynamic interaction in the heliosphere are well captured by the physics-based models Physics-based approach to solar wind forecasting needs further work to “beat” the empirical schemes, but it looks very promising. Synthetic data: Can also compare the difference in the observed and model HSE arrival time (dT) and maximum speed (dV). All models show a slight underestimate of the maximum speed (which may be expected due to lack of fast ICMEs) Arrival time of HSEs is well matched by the baseline and CORHEL MSE(A) < MSE(B)