Carl John Henney

Forecasting F10.7 with solar magnetic flux transport modeling

Abstract : A new method is presented here to forecast the solar 10.7 cm (2.8 GHz) radio flux, abbreviated F10.7, utilizing advanced predictions of the global solar magnetic field generated by a flux transport model. Using indices derived from the absolute value of the solar magnetic field, we find good correlation between the observed photospheric magnetic activity and the observed F10.7 values. Comparing magnetogram data observed within 6 hours of the F10.7 measurements during the years 1993 through 2010, the Spearman correlation coefficient, rs, for an empirical model of F10.7 is found to be 0.98. In addition, we find little change in the empirical model coefficients and correlations between the first and second 9 year intervals of the 18 year period investigated. By evolving solar magnetic synoptic maps forward 1 7 days, this new method provides a realistic estimation of the Earth-side solar magnetic field distribution used to forecast F10.7. Spearman correlation values of approximately 0.97, 0.95, and 0.93 are found for 1 day, 3 day, and 7 day forecasts, respectively. The method presented here can be expanded to forecast other space weather parameters, e.g., total solar irradiance and extreme ultraviolet flux. In addition, nearterm improvements to the F10.7 forecasting method, e.g., including far-side magnetic data with solar magnetic flux transport, are discussed.

Solar Wind Forecasting with Coronal Holes

An empirical model for forecasting solar wind speed related geomagnetic events is presented here. The model is based on the estimated location and size of solar coronal holes. This method differs from models that are based on photospheric magnetograms (e.g., Wang–Sheeley model) to estimate the open field line configuration. Rather than requiring the use of a full magnetic synoptic map, the method presented here can be used to forecast solar wind velocities and magnetic polarity from a single coronal hole image, along with a single magnetic full-disk image. The coronal hole parameters used in this study are estimated with Kitt Peak Vacuum Telescope He I 1083 nm spectrograms and photospheric magnetograms. Solar wind and coronal hole data for the period between May 1992 and September 2003 are investigated. The new model is found to be accurate to within 10% of observed solar wind measurements for its best 1-month period, and it has a linear correlation coefficient of ∼0.38 for the full 11 years studied. Using a single estimated coronal hole map, the model can forecast the Earth directed solar wind velocity up to 8.5 days in advance. In addition, this method can be used with any source of coronal hole area and location data.

Data Assimilation in the ADAPT Photospheric Flux Transport Model

Global maps of the solar photospheric magnetic flux are fundamental drivers for simulations of the corona and solar wind and therefore are important predictors of geoeffective events. However, observations of the solar photosphere are only made intermittently over approximately half of the solar surface. The Air Force Data Assimilative Photospheric Flux Transport (ADAPT) model uses localized ensemble Kalman filtering techniques to adjust a set of photospheric simulations to agree with the available observations. At the same time, this information is propagated to areas of the simulation that have not been observed. ADAPT implements a local ensemble transform Kalman filter (LETKF) to accomplish data assimilation, allowing the covariance structure of the flux-transport model to influence assimilation of photosphere observations while eliminating spurious correlations between ensemble members arising from a limited ensemble size. We give a detailed account of the implementation of the LETKF into ADAPT. Advantages of the LETKF scheme over previously implemented assimilation methods are highlighted.

Modeling the corona and solar wind using ADAPT maps that include far-side observations

As the primary input to nearly all coronal and solar wind models, global estimates of the solar photospheric magnetic field distribution are critical for reliable modeling of the corona and heliosphere. Over the last several years the Air Force Research Laboratory (AFRL), in collaboration with Los Alamos National Laboratory (LANL) and the National Solar Observatory (NSO), has developed a model that produces more realistic estimates of the instantaneous global photospheric magnetic field distribution than those provided by traditional photospheric field synoptic maps. The Air Force Data Assimilative Photospheric flux Transport (ADAPT) model is a photospheric flux transport model, originally developed at NSO, that makes use of data assimilation methodologies developed at LANL. The flux transport model evolves the observed solar magnetic flux using relatively well understood transport processes when measurements are not available and then updates the modeled flux with new observations using data assimilation methods that rigorously take into account model and observational uncertainties. ADAPT originally only made use of Earth-side magnetograms, but the code has now been modified to assimilate helioseismic far-side active region data such as those available from the Global Oscillation Network Group. As a preliminary test, a helioseismically detected active region that first emerged on the far-side of the Sun in early July 2010 is incorporated into maps produced by ADAPT and then used in the Wang-Sheeley-Arge (WSA) model to simulate the corona and solar wind. The WSA model results, with and without far-side data included in the ADAPT global maps, are compared here with coronal EUV and in situ solar wind observations available from STEREO. We find that the observed and modeled values are in better agreement when including the far-side detection.

The Open Flux Problem

The heliospheric magnetic field is of pivotal importance in solar and space physics. The field is rooted in the Suns photosphere, where it has been observed for many years. Global maps of the solar magnetic field based on full disk magnetograms are commonly used as boundary conditions for coronal and solar wind models. Two primary observational constraints on the models are (1) the open field regions in the model should approximately correspond to coronal holes observed in emission, and (2) the magnitude of the open magnetic flux in the model should match that inferred from in situ spacecraft measurements. In this study, we calculate both MHD and PFSS solutions using fourteen different magnetic maps produced from five different types of observatory magnetograms, for the time period surrounding July, 2010. We have found that for all of the model/map combinations, models that have coronal hole areas close to observations underestimate the interplanetary magnetic flux, or, conversely, for models to match the interplanetary flux, the modeled open field regions are larger than coronal holes observed in EUV emission. In an alternative approach, we estimate the open magnetic flux entirely from solar observations by combining automatically detected coronal holes for Carrington rotation 2098 with observatory synoptic magnetic maps. This approach also underestimates the interplanetary magnetic flux. Our results imply that either typical observatory maps underestimate the Suns magnetic flux, or a significant portion of the open magnetic flux is not rooted in regions that are obviously dark in EUV and X-ray emission.

CORONAL SOURCES OF THE SOLAR F10.7 RADIO FLUX

We present results from the first solar full-disk (the radio flux at 10.7 cm, 2.8 GHz) image taken with the S-band receivers on the recently upgraded Karl G. Jansky Very Large Array in order to assess the relationship between the index and solar extreme ultraviolet (EUV) emission. To identify the sources of the observed 2.8 GHz emission, we calculate differential emission measures from EUV images collected by the Atmospheric Imaging Assembly and use them to predict the bremsstrahlung component of the radio emission. By comparing the bremsstrahlung prediction and radio observation we find that 8.1% ± 0.5% of the variable component of the flux is associated with the gyroresonance emission mechanism. Additionally, we identify optical depth effects on the radio limb which may complicate the use of time series as an EUV proxy. Our analysis is consistent with a coronal iron abundance that is four times the photospheric level.

A NEW TECHNIQUE FOR THE PHOTOSPHERIC DRIVING OF NON-POTENTIAL SOLAR CORONAL MAGNETIC FIELD SIMULATIONS

In this paper, we develop a new technique for driving global non-potential simulations of the Suns coronal magnetic field solely from sequences of radial magnetic maps of the solar photosphere. A primary challenge to driving such global simulations is that the required horizontal electric field cannot be uniquely determined from such maps. We show that an inductive electric field solution similar to that used by previous authors successfully reproduces specific features of the coronal field evolution in both single and multiple bipole simulations. For these cases, the true solution is known because the electric field was generated from a surface flux-transport model. The match for these cases is further improved by including the non-inductive electric field contribution from surface differential rotation. Then, using this reconstruction method for the electric field, we show that a coronal non-potential simulation can be successfully driven from a sequence of ADAPT maps of the photospheric radial field, without including additional physical observations which are not routinely available.

Forecasting solar extreme and far ultraviolet irradiance

A new method is presented to forecast the solar irradiance of selected wavelength ranges within the extreme ultraviolet (EUV) and far ultraviolet (FUV) bands. The technique is similar to a method recently published by Henney et al. (2012) to predict solar 10.7 cm (2.8 GHz) radio flux, abbreviated F10.7, utilizing advanced predictions of the global solar magnetic field generated by a flux transport model. In this and the previous study, we find good correlation between the absolute value of the observed photospheric magnetic field and selected EUV/FUV spectral bands. By evolving solar magnetic maps forward 1 to 7 days with a flux transport model, estimations of the Earth side solar magnetic field distribution are generated and used to forecast irradiance. For example, Pearson correlation coefficient values of 0.99, 0.99, and 0.98 are found for 1 day, 3 day, and 7 day predictions, respectively, of the EUV band from 29 to 32 nm. In the FUV, for example, the 160 to 165 nm spectral band, correlation values of 0.98, 0.97, and 0.96 are found for 1 day, 3 day, and 7 day predictions, respectively. In the previous study, the observed F10.7 signal is found to correlate well with strong magnetic field (i.e., sunspot) regions. Here we find that solar EUV and FUV signals are significantly correlated with the weaker magnetic fields associated with plage regions, suggesting that solar magnetic indices may provide an improved indicator (relative to the widely used F10.7 signal) of EUV and FUV nonflaring irradiance variability as input to ionospheric and thermospheric models.

Coronal and heliospheric modeling using flux-evolved maps

Magnetohydrodynamic (MHD) simulations are now routinely used to produce models of the solar corona and inner heliosphere for specific time periods. These models typically rely on maps of the photospheric magnetic field. Two well-known problems arise from the use of these synoptic maps. First, the Suns poles are poorly observed, which necessarily means that the polar fields in these maps must be reconstructed with a variety of interpolation/extrapolation techniques. Second, the synoptic maps contain data that is as much as 27 days old, whereas the Suns magnetic flux is always evolving. Flux evolution models can in principle alleviate both these difficulties, by providing physical approximations for the polar fields and by estimating the likely state of the field on unobserved portions of the Sun. In this study, we focus on the polar field problem, and show why typical synoptic maps may underestimate the polar magnetic fields near solar minimum. We use a map created with the Air Force Data Assimilative ...

An Empirically Driven Time-Dependent Model of the Solar Wind

We describe the development and application of a time-dependent model of the solar wind. The model is empirically driven, starting from magnetic maps created with the Air Force Data Assimilative Photospheric flux Transport (ADAPT) model at a daily cadence. Potential field solutions are used to model the coronal magnetic field, and an empirical specification is used to develop boundary conditions for an MHD model of the solar wind. The time-dependent MHD simulation shows classic features of stream structure in the interplanetary medium that are seen in steady-state models; it also shows time evolutionary features that do not appear in a steady-state approach. The model results compare reasonably well with 1 AU OMNI observations. Data gaps when SOLIS magnetograms were unavailable hinder the model performance. The reasonable comparisons with observations suggest that this modeling approach is suitable for driving long term models of the outer heliosphere. Improvements to the ingestion of magnetograms in flux transport models will be necessary to apply this approach in a time-dependent space weather model.