04301 Abstracts Collection -- Cache-Oblivious and Cache-Aware Algorithms

The Dagstuhl Seminar 04301 ``Cache-Oblivious and Cache-Aware Algorithms\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl, from 18.07.2004 to 23.07.2004. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Ensemble simulations of the 12 July 2012 Coronal Mass Ejection with the Constant Turn Flux Rope Model

Flux-rope-based magnetohydrodynamic modeling of coronal mass ejections (CMEs) is a promising tool for the prediction of the CME arrival time and magnetic field at Earth. In this work, we introduce a constant-turn flux rope model and use it to simulate the 12-July-2012 16:48 CME in the inner heliosphere. We constrain the initial parameters of this CME using the graduated cylindrical shell (GCS) model and the reconnected flux in post-eruption arcades. We correctly reproduce all the magnetic field components of the CME at Earth, with an arrival time error of approximately 1 hour. We further estimate the average subjective uncertainties in the GCS fittings, by comparing the GCS parameters of 56 CMEs reported in multiple studies and catalogs. We determined that the GCS estimates of the CME latitude, longitude, tilt, and speed have average uncertainties of 5.74 degrees, 11.23 degrees, 24.71 degrees, and 11.4% respectively. Using these, we have created 77 ensemble members for the 12-July-2012 CME. We found that 55% of our ensemble members correctly reproduce the sign of the magnetic field components at Earth. We also determined that the uncertainties in GCS fitting can widen the CME arrival time prediction window to about 12 hours for the 12-July-2012 CME. On investigating the forecast accuracy introduced by the uncertainties in individual GCS parameters, we conclude that the half-angle and aspect ratio have little impact on the predicted magnetic field of the 12-July-2012 CME, whereas the uncertainties in longitude and tilt can introduce a relatively large spread in the magnetic field predicted at Earth

The SDO/EVE Solar Irradiance Coronal Dimming Index Catalog. I. Methods and Algorithms

When a coronal mass ejection departs, it leaves behind a temporary void. That void is known as coronal dimming, and it contains information about the mass ejection that caused it. Other physical processes can cause parts of the corona to have transient dimmings, but mass ejections are particularly interesting because of their influence in space weather. Prior work has established that dimmings are detectable even in disk-integrated irradiance observations, i.e., Sun-as-a-star measurements. The present work evaluates four years of continuous Solar Dynamics Observatory Extreme Ultraviolet Experiment (EVE) observations to greatly expand the number of dimmings we may detect and characterize, and collects that information into Jamess EVE Dimming Index catalog. This paper details the algorithms used to produce the catalog, provides statistics on it, and compares it with prior work. The catalog contains 5051 potential events (rows), which correspond to all robustly detected solar eruptive events in this time period as defined by >C1 flares. Each row has a corresponding 27,349 elements of metadata and parameterizations (columns). In total, this catalog is the result of analyzing 7.6 million solar ultraviolet light curves

Implications of Different Solar Photospheric Flux-Transport Models for Global Coronal and Heliospheric Modeling

The concept of surface-flux transport (SFT) is commonly used in evolving models of the large-scale solar surface magnetic field. These photospheric models are used to determine the large-scale structure of the overlying coronal magnetic field, as well as to make predictions about the fields and flows that structure the solar wind. We compare predictions from two SFT models for the solar wind, open magnetic field footpoints, and the presence of coronal magnetic null points throughout various phases of a solar activity cycle, focusing on the months of April in even-numbered years between 2012 and 2020, inclusive. We find that there is a solar cycle dependence to each of the metrics considered, but there is not a single phase of the cycle in which all the metrics indicate good agreement between the models. The metrics also reveal large, transient differences between the models when a new active region is rotating into the assimilation window. The evolution of the surface flux is governed by a combination of large scale flows and comparatively small scale motions associated with convection. Because the latter flows evolve rapidly, there are intervals during which their impact on the surface flux can only be characterized in a statistical sense, thus their impact is modeled by introducing a random evolution that reproduces the typical surface flux evolution. We find that the differences between the predicted properties are dominated by differences in the model assumptions and implementation, rather than selection of a particular realization of the random evolution.Comment: Accepted for publication in The Astrophysical Journa

Coronal Hole Detection and Open Magnetic Flux

Many scientists use coronal hole (CH) detections to infer open magnetic flux. Detection techniques differ in the areas that they assign as open, and may obtain different values for the open magnetic flux. We characterize the uncertainties of these methods, by applying six different detection methods to deduce the area and open flux of a near-disk center CH observed on 2010 September 19, and applying a single method to five different EUV filtergrams for this CH. Open flux was calculated using five different magnetic maps. The standard deviation (interpreted as the uncertainty) in the open flux estimate for this CH ≈ 26%. However, including the variability of different magnetic data sources, this uncertainty almost doubles to 45%. We use two of the methods to characterize the area and open flux for all CHs in this time period. We find that the open flux is greatly underestimated compared to values inferred from in situ measurements (by 2.2–4 times). We also test our detection techniques on simulated emission images from a thermodynamic MHD model of the solar corona. We find that the methods overestimate the area and open flux in the simulated CH, but the average error in the flux is only about 7%. The full-Sun detections on the simulated corona underestimate the model open flux, but by factors well below what is needed to account for the missing flux in the observations. Under-detection of open flux in coronal holes likely contributes to the recognized deficit in solar open flux, but is unlikely to resolve it

Coronal Hole Detection and Open Magnetic Flux

Many scientists use coronal hole (CH) detections to infer open magnetic flux. Detection techniques differ in the areas that they assign as open, and may obtain different values for the open magnetic flux. We characterize the uncertainties of these methods, by applying six different detection methods to deduce the area and open flux of a near-disk center CH observed on 2010 September 19, and applying a single method to five different EUV filtergrams for this CH. Open flux was calculated using five different magnetic maps. The standard deviation (interpreted as the uncertainty) in the open flux estimate for this CH approximate to 26%. However, including the variability of different magnetic data sources, this uncertainty almost doubles to 45%. We use two of the methods to characterize the area and open flux for all CHs in this time period. We find that the open flux is greatly underestimated compared to values inferred from in situ measurements (by 2.2-4 times). We also test our detection techniques on simulated emission images from a thermodynamic MHD model of the solar corona. We find that the methods overestimate the area and open flux in the simulated CH, but the average error in the flux is only about 7%. The full-Sun detections on the simulated corona underestimate the model open flux, but by factors well below what is needed to account for the missing flux in the observations. Under-detection of open flux in coronal holes likely contributes to the recognized deficit in solar open flux, but is unlikely to resolve it.Peer reviewe

Forecasting the ambient solar wind with numerical models. II. An adaptive prediction system for specifying solar wind speed near the Sun

The ambient solar wind flows and fields influence the complex propagation dynamics of coronal mass ejections in the interplanetary medium and play an essential role in shaping Earth's space weather environment. A critical scientific goal in the space weather research and prediction community is to develop, implement, and optimize numerical models for specifying the large-scale properties of solar wind conditions at the inner boundary of the heliospheric model domain. Here we present an adaptive prediction system that fuses information from in situ measurements of the solar wind into numerical models to better match the global solar wind model solutions near the Sun with prevailing physical conditions in the vicinity of Earth. In this way, we attempt to advance the predictive capabilities of well-established solar wind models for specifying solar wind speed, including the Wang–Sheeley–Arge model. In particular, we use the Heliospheric Upwind eXtrapolation (HUX) model for mapping the solar wind solutions from the near-Sun environment to the vicinity of Earth. In addition, we present the newly developed Tunable HUX (THUX) model, which solves the viscous form of the underlying Burgers equation. We perform a statistical analysis of the resulting solar wind predictions for the period 2006–2015. The proposed prediction scheme improves all the investigated coronal/heliospheric model combinations and produces better estimates of the solar wind state at Earth than our reference baseline model. We discuss why this is the case and conclude that our findings have important implications for future practice in applied space weather research and prediction