CD4 – Open Validation of Space Weather Models Throughout the Heliosphere: Challenges and Future Directions
Talks
CD4 Fri 8/11 09:00-10:15, room C2D – Almedina
Author(s): Christina Kay
JHU/APL
Abstract: Coronal mass ejections (CMEs) drive space weather effects at Earth and through the rest of the heliosphere. Predicting their arrival is a major part of space weather forecasting. In 2013, the Community Coordinated Modeling Center started collecting predictions from the community, developing an Arrival Time Scoreboard (ATSB). Riley et al. (2018) analyzed the first 5 years of the ATSB, finding a bias of a few hours and uncertainty of order 15 hr. These metrics have been routinely quoted since 2018, but have not been updated despite the availability of continued predictions. We revise analysis of the ATSB using a sample 3.5 times the size of that in the original study. We find generally the same overall metrics, a bias of -2.5 hr, mean absolute error of 13.2 hr, and standard deviation of 17.4 hr, with only a slight improvement comparing between the previously-used and new sets. The most well-established, frequently-submitted model results tend to outperform those from seldomly-contributed models. These “best” models show a slight improvement over the 11 year span, with more scatter between the models during early times and a convergence toward the same error metrics in recent years. We find little evidence of any correlations between the arrival time errors and any other properties. The one noticeable exception is a tendency for late predictions for short transit times and vice versa. We propose that any model-driven systematic errors may be washed out by the uncertainties in CME reconstructions or in characterization of the background solar wind, and suggest that improving these may be the key to better predictions.
Author(s): Nathaniel Edward-Inatimi, Prof. Mathew Owens, Dr. Luke Barnard, Dr. Matthew Lang, Dr. Harriet Turner, Dr. Mike Marsh, Dr. Siegfried Gonzi
University of Reading; University of Reading; University of Reading; British Antarctic Survey; University of Reading; UK Met Office; UK Met Office
Abstract: In this study, we have adapted established meteorological methods to a solar-wind ensemble, with the goal of producing a calibrated probabilistic forecast. This is motivated by the need to improve the characterisation of the ambient wind conditions that are crucial to the understanding of space physics and space weather, through impact on coronal mass ejection propagation to Earth. A series of hindcasts were generated over Solar cycle 24: the Magnetohydrodynamic Algorithm outside a Sphere (MAS) coronal model, constrained by the observed photospheric magnetic field, is used to provide an estimate of solar wind conditions at 30 solar radii, which are then propagated to near-Earth space using the Heliospheric Upwind eXtrapolation with time dependence (HUXt) solar wind model. An ensemble of initial conditions to the HUXt model is produced by making spatial perturbations to the MAS output. We evaluated the impact of latitudinal and longitudinal variances; the scale parameters for the spatial perturbations which effectively control spread of the initial conditions to HUXt. Optimal scale parameters were found to improve ensemble distribution as evaluated by rank histogram and reliability diagram, latitudinal and longitudinal variances of 20 and 10 degrees respectively produced the best distributed ensemble. These methods attempt to quantitatively link the forecast uncertainty to the ensemble spread. Calibrated ensembles showed an average increase in skill of 9% towards lower Brier score and a 2.5% increase in Receiver Operating Characteristic (ROC) score. The improvements were small but score distributions indicated a consistent and systematic uptick in skill. Cost/Loss analysis also found that the calibrated probabilistic forecast provides a more actionable forecast at high cost/loss ratios, where the applications of the forecast are more sensitive to false-alarms. Platt-scaling, a statistical post-processing method, was used to correct for an over-confidence bias seen in the reliability diagrams. Cost/Loss for the Platt-scaled probabilistic forecast showed a further promising improvement in forecast skill. This work marks a first attempt at formally calibrating solar-wind ensemble forecasts.
Author(s): Christian Möstl, Eva Weiler, Emma E. Davies, Ute V. Amerstorfer, Hannah T. Rüdisser, Andreas J. Weiss, Tanja Amerstorfer, Justin Le Louëdec, Maike Bauer, Veronika Haberle, Satabdwa Majumdar, Timothy S. Horbury, Noé Lugaz
Austrian Space Weather Office, GeoSphere Austria, Graz, Austria; Austrian Space Weather Office, GeoSphere Austria, Graz, Austria; Institute of Physics, University of Graz, Graz, Austria; Austrian Space Weather Office, GeoSphere Austria, Graz, Austria; Austrian Space Weather Office, GeoSphere Austria, Graz, Austria; Austrian Space Weather Office, GeoSphere Austria, Graz, Austria; Institute of Physics, University of Graz, Graz, Austria; NASA Postdoctoral Program Fellowship, NASA Goddard Space Flight Center, Greenbelt, MD, USA; Austrian Space Weather Office, GeoSphere Austria, Graz, Austria; Austrian Space Weather Office, GeoSphere Austria, Graz, Austria; Austrian Space Weather Office, GeoSphere Austria, Graz, Austria; Institute of Physics, University of Graz, Graz, Austria; Conrad Observatory, GeoSphere Austria, Vienna, Austria; Austrian Space Weather Office, GeoSphere Austria, Graz, Austria; Imperial College London, South Kensington Campus, London, UK; Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA
Abstract: With solar cycle 25 at maximum and the lingering potential for more super-geomagnetic storms in the upcoming years, an inconvenient truth in space weather research and operations is that we are still not very good at predicting the geomagnetic storm magnitude of incoming coronal mass ejections (CMEs). I will deliver a concise summary of the current status of the field regarding prediction methods, validation and modeling of CME speeds and southward Bz magnetic fields, for single and interacting events, and point out possible avenues in order to improve the situation. Metrics are discussed that should measure the progress of the field quantitatively. Current abilities of Bz prediction models should be assessed, and provide a benchmark against which new developments can be compared, and infrastructure should be developed to track the progress we are making.
Advances are being made now with Solar Orbiter acting as the first far upstream monitor, stationed occasionally near the Sun-Earth line and delivering data of incoming CMEs in real time. Closer to L1, STEREO-A has drifted towards and away from the Sun-Earth line in 2023 and 2024, and observed the May 2024 superstorm. Both spacecraft allow for the first time to test mission concepts for how the accuracy and prediction lead time could be improved using spacecraft in situ data, something already on the horizon with the HENON mission. Progress is also possible with only L1 data. First steps towards validation have also been made with the usage of all these types of in situ observations.
Innovative developments in analytical and numerical models add new possibilities to the picture. The PUNCH mission will pioneer polarized heliospheric imaging, which could improve the situation on deriving the type of magnetic flux ropes fields of incoming CMEs from remote observations. We propose that the combination of distant retrograde mission concepts like MIIST and HENON, that routinely sample CMEs at spatial separations of 1-10° and 0.01 to 0.1 AU in the 2030s, when also ESA Vigil is expected to start operations, may have the potential to bring space weather forecasting to a level in the public eye that is not too far away anymore from terrestrial weather forecasting.
Author(s): Zhenguang Huang, Gabor Toth, Nishtha Sachdeva, Bartholomeus van der Holst
University of Michigan; University of Michigan; University of Michigan; University of Michigan
Abstract: An accurate solar wind background is critical for space weather applications, which includes correctly modeling and predicting the arrival of Corotating Interaction Regions (CIRs), Coronal Mass Ejections (CMEs), and Solar Energetic Particles (SEPs). Currently, no global 3-D numerical first-principles models are used, primary because of two reasons: 1. high computational cost; 2. the uncertainty of the input parameters. In this presentation, we will propose a novel approach to empirically prescribe the model parameters of the Alfvén Wave Solar Model (AWSoM) that is developed at the University of Michigan. Our results illustrate that AWSoM can reasonably predict the solar wind distribution at Earth orbit using the new method, which will improve space weather predictions when 3-D first-principles models are applied.
Author(s): Miguel Reis Orcinha, Nicola Tomassetti, Bruna Bertucci, Fernando Barão, David Pelosi, Francesco Faldi, Emanuele Fiandrini, Pauli Väisänen
INFN – Istituto Nazionale di Fisica Nucleare; Università degli Studi di Perugia & INFN; Università degli Studi di Perugia & INFN; University of Lisbon & Laboratório de Instrumentação e Física Experimental de Partículas; Università degli Studi di Perugia & INFN; Università degli Studi di Perugia & INFN; Università degli Studi di Perugia & INFN; INFN Perugia & University of Perugia & University of Oulu & Sodankylä Geophysical Observatory
Abstract: The intensity and energy spectrum of energetic charged radiation in the heliosphere are significantly influenced by solar activity. This phenomenon is known as solar modulation of cosmic rays.
As interplanetary travel becomes a reality, missions in low-earth orbit become longer and more frequent. In order to accurately assess the radiation hazard experienced by astronauts during space missions, there is an emergent need for accurately depicting the space radiation environment and predicting the cosmic-ray flux in the heliosphere.
Here we present a new effective and predictive model of solar modulation which incorporates fundamental physics processes of particle transport such as diffusion, drift, convection, and adiabatic cooling to compute the energy spectrum; and temporal evolution of cosmic radiation in the inner heliosphere. Calibration and validation of our model were performed using the most recent cosmic-ray data from space-based experiments, such as AMS-02 on the International Space Station, along with multichannel observations of solar activity and interplanetary parameters.
This model enables us to not only capture the temporal evolution of the fluxes of different cosmic-ray particles, but also predict the cosmic-ray flux by relating it to solar activity.
Empowered by this model and a time-dependent effective description of the geomagnetic field, we will show our estimates of the dose rates experienced by astronauts over time, as they orbit Earth onboard the International Space Station and while traveling through interplanetary space.
By providing a robust framework for understanding cosmic ray variations and their implications for space travel, our research contributes to advancing the safety and effectiveness of space exploration endeavours.
Author(s): Adam Kubaryk, Tzu-Wei Fang, Tim Fuller-Rowell, Zhuxiao Li, Astrid Maute, George Millward
CIRES, NOAA/SWPC; NOAA/SWPC; CIRES, NOAA/SWPC; CIRES, NOAA/SWPC; CIRES, NOAA/SWPC; CIRES, NOAA/SWPC
Abstract: The coupled Whole Atmosphere Model-Ionosphere Plasmasphere Electrodynamics (WAM-IPE) Forecast System (WFS) has been operational at the NOAA Space Weather Prediction Center since 2021. Near real-time validation of the modeling system and its output represents a chief ongoing challenge in assessing the value the model can provide to users, whether in the form of a nowcast or multiple-day forecasts.
Significant gaps still exist with respect to near real-time validation for the WFS, particularly in the neutral upper atmosphere. The May 2024 G5 Storm will be discussed as a critical case study in pushing the physical limits of the operational WFS, and the lessons rapidly learned and applied to the operational model system will be highlighted, demonstrating validation against observationally-informed datasets of both the neutral atmosphere and global ionosphere.
Additionally, the availability of a tool for more open validation and general use of the operational WFS specification of neutral density will be discussed, as well as highlighting WAM-IPE’s availability for Runs on Request at NASA’s Community Coordinated Modeling Center.
Posters
Posters II Display Thu 7/11 – Fri 8/11, room C1A – Aeminium
Authors in attendance: Thu 7/11 10:15–11:30, 15:15-16:15; Fri 8/11 10:15–11:30
Author(s): Florin-Ioan Constantin, Eugeniu Mihnea Popescu, Gabriel Chiritoi, Florin Adrian Popescu, Eduad Ilie Nastase, Alexandra Muntean, Georgiana Simionescu, Diana Ioana Cosac
Institute of Space Science – subsidiary of INFLPR; Institute of Space Science – subsidiary of INFLPR; Institute of Space Science – subsidiary of INFLPR; Institute of Space Science – subsidiary of INFLPR; National Institute for Earth Physics; National Institute for Earth Physics; Institute of Space Science – subsidiary of INFLPR; Institute of Space Science – subsidiary of INFLPR
Abstract: The solar magnetic activity cycle is currently approaching its maximum values, producing the greatest solar flares seen in the past decade. These intense solar flares have resulted in the occurrence of aurora borealis even in latitudes as low as 45 degrees. This heightened solar activity provides a unique opportunity to test and evaluate the performance of mapping techniques employed by the Ionospheric Monitoring Service to produce Total Electron Content (TEC) maps over the territory of Romania. In this study, we assess the accuracy and reliability of our mapping techniques under conditions of increased ionospheric disturbances, such as the storm that produced aurora borealis over Romania in November 2023 and in May 2024, as the TEC maps generated during this period of elevated solar activity are crucial for understanding the impact of geomagnetic storms on communication and navigation systems. The results have been compared to maps produced by the International GNSS Service (IGS), as well as the German Aerospace Center (DLR).
Author(s): Ronish Mugatwala, Simone Chierichini, Gregoire Francisco, Robertus Erdélyi, Dario Del Moro
University of Rome Tor Vergata; University of Sheffield; University of Rome Tor Vergata; University of Sheffield; University of Rome Tor Vergata
Abstract: An accurate assessment of our current space weather modelling is necessary due to progress in space weather research. Any validation framework needs suitable qualitative data for consistent validation procedures. The qualitative data also contributes to the refinement of the model and hence better forecasting ability. In alignment with this objective specifically for CME events, we present a newly prepared dataset of CME-ICME lineup events. This dataset includes in-situ observations from various spacecraft like Messenger, Venus Express, Maven, Stereo-A/B, Solar Orbiter, Bepi Colombo, Parker Solar Probe, Wind, etc, with detailed CME analysis from the NASA CCMC platform. Apart from CME-ICME information, the dataset also possesses the necessary information about Probabilistic Drag Based Model (P-DBM) quantities. The dataset is publicly available to provide a valuable resource for model validation and to compare the performance with other available CME propagation models.
Our work offers a unique opportunity to refine CME propagation models, as ICMEs have been observed at multiple targets across a wide range of heliocentric distances. By utilising this dataset, researchers can better understand the dynamics of CME propagation and improve the forecasting methods.
Author(s): Tinatin Baratashvili, Benjamin Grison, Brigitte Schmieder, Pascal Demoulin, Stefaan Poedts
Centre for Mathematical Plasma Astrophysics, Dept. of Mathematics, KU Leuven, 3001 Leuven, Belgium; Institute of Atmospheric Physics CAS, Dept of Space Physics, 14100 Prague, Czech Republic; Centre for Mathematical Plasma Astrophysics, Dept. of Mathematics, KU Leuven, 3001 Leuven, Belgium ,LESIA, Observatoire de Paris, 5 place Jules Janssen, 92190 Meudon, France, SUPA, School of Physics & Astronomy, University of Glasgow, G12 8QQ, UK; LESIA, Observatoire de Paris, 5 place Jules Janssen, 92190 Meudon, France; Centre for Mathematical Plasma Astrophysics, Dept. of Mathematics, KU Leuven, 3001 Leuven, Belgium, Institute of Physics, University of Maria Curie-Skłodowska, Pl. M. Curie-Skłodowska 5, 20-031 Lublin, Poland
Abstract: Coronal Mass Ejections (CMEs) are the main drivers of interplanetary shocks and space weather disturbances. Strong CMEs directed towards Earth can severely impact our planet, and their timely prediction can enable us to mitigate (part of) the damage they cause. One of the key parameters determining a CME’s geo-effectiveness is its internal magnetic configuration.
The novel heliospheric wind and CME propagation model Icarus (Verbeke et al. 2022), implemented within the framework of MPI-AMRVAC (Xia et al., 2018), introduces new capabilities for better and faster space weather forecasts. Advanced numerical techniques are implemented, such as solution adaptive mesh refinement (AMR) and radial grid stretching. The user controls the different refinement and coarsening conditions and thresholds. These techniques result in optimised computer memory usage and a significant execution speed-up, which is crucial for forecasting.
This study validates a new magnetized CME model in Icarus by simulating interplanetary coronal mass ejections (ICMEs). We chose a CME event observed by MESSENGER and ACE. We identify the source region for the CME of interest, reconstruct its characteristic parameters and initiate the CME propagation inside Icarus with a spheromak CME model. We modelled two additional CMEs that interacted with the main CME of interest. The observed profiles were reconstructed only by modelling the complex interaction of the three CMEs, demonstrating the effectiveness of our approach.
Different AMR criteria are used to achieve higher spatial resolutions at propagating shock fronts and in the interiors of the ICMEs. This way, the complex structure of the magnetic field and the deformation and (plasma and magnetic flux) erosion can be simulated with higher accuracy due to the advantage of AMR. A higher resolution is especially important for the spheromak model because the internal magnetic field configuration affects the CME evolution and its interaction with the magnetized heliospheric wind significantly. Finally, the synthetic time series of plasma quantities obtained at different satellite locations are compared to the available observational data from MESSENGER and ACE. As a result, Icarus allows us to model CMEs with higher accuracy yet efficiently.
TB acknowledges support from the projects C14/19/089 (C1 project Internal Funds KU Leuven), G0B5823N and G002523N (WEAVE) (FWO-Vlaanderen), 4000134474 (SIDC Data Exploitation, ESA Prodex-12), and Belspo project B2/191/P1/SWiM.
Author(s): Maria Papailiou, Maria Abunina, Helen Mavromichalaki, Artem Abunin, Semyon Belov, Maria Gerontidou, Anatoly Belov, Nataly Shlyk, Victor Yanke, Norma Crosby, Mark Dierckxsens
National and Kapodistrian University of Athens; Pushkov Institute of Terrestrial Magnetism, Ionosphere and Radio Wave Propagation RAS (IZMIRAN); National and Kapodistrian University of Athens; Pushkov Institute of Terrestrial Magnetism, Ionosphere and Radio Wave Propagation RAS (IZMIRAN); Pushkov Institute of Terrestrial Magnetism, Ionosphere and Radio Wave Propagation RAS (IZMIRAN); National and Kapodistrian University of Athens; Pushkov Institute of Terrestrial Magnetism, Ionosphere and Radio Wave Propagation RAS (IZMIRAN); Pushkov Institute of Terrestrial Magnetism, Ionosphere and Radio Wave Propagation RAS (IZMIRAN); Pushkov Institute of Terrestrial Magnetism, Ionosphere and Radio Wave Propagation RAS (IZMIRAN); Royal Belgian Institute for Space Aeronomy; Royal Belgian Institute for Space Aeronomy
Abstract: Pre-decreases and/or pre-increases of the cosmic ray intensity usually precede large Forbush decreases and the accompanying geomagnetic storms. Such precursors could therefore forewarn of an upcoming geomagnetic disturbance. Consequently, the study of precursors can play a significant role in space research applications and contribute to the reliable prognosis of cosmic ray and geomagnetic activity. The Athens Cosmic Ray Group of the National and Kapodistrian University of Athens (NKUA) and the Cosmic Ray Group of the Pushkov Institute of Terrestrial Magnetism, Ionosphere and Radiowave Propagation of the Russian Academy of Sciences (IZMIRAN) have been studying the precursors before the start of a Forbush Decrease (FD). In this study FDs that satisfy the following criteria have been investigated: increased cosmic ray anisotropy Axyb > 0.8% 1 hour before the start of the FD; FD with magnitude > 5%; FD accompanied with geomagnetic storms (Dst < -100nT and 5 ≤ Kp-index ≤ 9). The “Forbush Effects and Interplanetary Disturbances” database provided by IZMIRAN was used to analyze the solar, interplanetary and geomagnetic conditions during each FD event. Additionally, the Ring of Stations method was applied to each event in order to plot the asymptotic longitude as function of time allowing for a visual representation of the precursors. Results revealed that the adopted threshold value of 0.8% of the cosmic ray anisotropy 1 hour before the shock arrival is successful, as the majority of the events under examination showed clear signs of precursors (either pre-decreases or pre-increases or both).
Author(s): M. Levisohn, R. Mullinix, C. Wiegand, D. DeZeeuw, L. Rastaetter, M. El Alaoui, M. Kuznetsova, J. Wang, M. Reiss, Y. Zheng, J. Yue, C. Ngwira, J. Gjerloev
NASA GSFC
Abstract: The Comprehensive Assessment of Models and Events using Library Tools (CAMEL) framework developed by the Community Coordinated Modeling Center (CCMC) at NASA Goddard Space Flight Center (GSFC) is an integrated and flexible framework allowing users to seamlessly compare space weather and space science model outputs with observational data sets. The front-end interactive portion of the framework, the CAMEL Web App, provides visualization tools and calculates skill scores for each validation campaign included in the CAMEL data repository. Along with recent user experience updates to the web application, new data on ground magnetic perturbations have been added to the database and expanded visualization capabilities. These new data are essential to discovering how well models analyze the regional or even local predictions of the geomatics environment related to geomagnetically induced current (GIC). Moreover, multiple validation studies and papers have been published discussing the importance of better understanding GIC. This specific new ground magnetic perturbation study in CAMEL draws data from SuperMAG, a library of global magnetic field observations hosted by Johns Hopkins University Applied Physics Laboratory (APL), and the Space Weather Modeling Framework (SWMF), a model hosted by the CCMC Runs-On-Request (ROR) and integrated Space Weather Analysis (iSWA) tools. The new validation campaign builds upon what was done in Pulkkinen et al. [2013] by including additional models and model settings, an expanded list of storm time periods, a new strategic station selection tool, and expanded skill scores and metrics. These new capabilities allow users to better understand, visualize, and share the results of the ground magnetic perturbations studies.
Author(s): Ranadeep Sarkar, Jens Pomoell, Emilia Kilpua, Eleanna Asvestari
University of Helsinki; University of Helsinki; University of Helsinki; University of Helsinki
Abstract: One of the major challenges in space weather forecasting is to reliably predict the magnetic structure of interplanetary coronal mass ejections (ICMEs) in the near-Earth space. In the framework of global MHD modelling, several efforts have been made to model the CME magnetic field from Sun to Earth. However, it remains challenging to deduce a flux-rope solution that can reliably model the magnetic structure of a CME. Spheromaks are one of the models that are widely used to characterize the internal magnetic structure of a CME. However, recent studies show that spheromaks are prone to experience a large rotation when injected in the heliospheric domain which may affect the prediction efficacy of CME magnetic fields at 1 AU. Moreover, the fully inserted spheromaks do not have any legs attached to the Sun. In addition, due to the inherent topology of the spheromak, the in-situ signature may exhibit a double flux-rope-like profile not reproduced by standard locally cylindrical flux rope models. Aiming to study the dynamics of CMEs exhibiting different magnetic topologies, we implement a new flux-rope model in “European heliospheric forecasting information asset” (EUHFORIA). Our flux-rope model includes an initially force-free toroidal flux-rope that is embedded in the low-coronal magnetic field. The dynamics of the flux rope in the low and middle corona is solved by a non-uniform advection constrained by the observed kinematics of the event. This results in a global non-toroidal loop-like magnetic structure that locally manifests as a cylindrical structure. At heliospheric distances, the evolution is modeled as a MHD process using EUHFORIA. As proof of concept, we validate this tool for the CME event on 2013 July 7, which was sequentially detected by MESSENGER and WIND. Comparing the model results with the in-situ magnetic field configuration of the ICME at both the location of Mercury and Earth, we find that the simulated magnetic field profiles of the flux-rope are in very good agreement with the in-situ observations. We highlight that both near-Sun observations and the inner spacecraft in-situ data are very important to constrain the global MHD models, reducing the uncertainty in predicting the magnetic field profiles of CMEs.
Author(s): Fan Zhang, Michaela Brchnelova, Andrea Lani, Stefaan Poedts
University of Oslo; KU Leuven; KU Leuven; KU Leuven
Abstract: The novel fully implicit MHD model, COCONUT, has successfully modelled steady and time-evolving global solar corona and flux-rope propagation while incorporating more self-consistent physics. Such successes allow COCONUT to provide more accurate inputs for heliospheric models. In the meantime, the numerics of the model are constantly being improved for better performance in low plasma beta simulations, as solar coronal phenomena are predominantly driven by strong magnetic fields.
Specifically, when plasma beta is low, robustness of numerical methods is particularly challenged. Using a slope limiter or artificial viscosity, numerical diffusion can be added to improve the robustness and convergence, but accuracy will deteriorate due to the excessive numerical diffusion. It is observed that, for example, modelled coronal streamers may appear in different elongations and directions due to numerical diffusion. Such issues can be alleviated by refining the meshes, which will increase computational costs and thus hinder the effort of forecasting space weather events.
We have thus developed a new HLL-type Riemann solver within the fully implicit model. The new method has shown better robustness in primary tests while providing less diffusive results without mesh refinement. The method considers physical consistency in numerical approximations of MHD Riemann problems. Specifically, the numerically calculated magnetic field and energy are consistent, thereby avoiding the error in magnetic energy that could overwhelm the internal energy. In addition, nuances in boundary conditions and divergence cleaning approaches are addressed, as some minor changes may in fact significantly affect the overall performance, including physical accuracy. Using (synthetic) white light images, we compare numerical results and observations and show how the proposed approaches lead to changes in the resulting plasma flows and magnetic fields.
Author(s): Martin Reiss, Richard Mullinix, Chiu Wiegand, Karin Muglach, Barbara Perri, Evangelia Samara, Lutz Rastaetter
NASA CCMC; NASA CCMC; NASA CCMC; NASA GSFC; CEA, Saclay, France; NASA GSFC; NASA CCMC
Abstract: The rate at which we develop and update space science and space weather models has outpaced the rate at which we build infrastructure to enable model validation. Consequently, we end up with a bottleneck in advancing our modeling capabilities. The validation practices that rely only on selected events and time intervals, the usage of individually developed metrics, and a slow iterative process between model developers and end-users all contribute to this bottleneck. These validation practices make a complete assessment of the “state-of-the-art” in modeling difficult or even impossible. Here, we present the activities of the Ambient Solar Wind Validation Team embedded in the COSPAR ISWAT initiative. Our mission is to provide the community with an assessment of the state-of-the-art in ambient solar wind modeling at L1. To this end, we are developing an open online platform hosted at NASA’s CCMC for validating ambient solar wind models by comparing their simulation results with spacecraft measurements. The new online platform is built on the CAMEL framework and allows the community to test the quality of state-of-the-art solar wind models with unified metrics, providing an unbiased assessment of progress over time. Here, we will give a status update on our team effort, showcase the new online platform, and outline future perspectives.
Author(s): Víctor Navas-Portella, Iurii Cherniak, David Altadill, Irina Zakharenkova, Víctor de Paula, Douglas Hunt, Antoni Segarra
Observatori de l’Ebre (OE), CSIC – Universitat Ramon Llull, Roquetes, Spain; COSMIC Program Office, University Corporation for Atmospheric Research; Observatori de l’Ebre (OE), CSIC – Universitat Ramon Llull, Roquetes, Spain; COSMIC Program Office, University Corporation for Atmospheric Research; Observatori de l’Ebre (OE), CSIC – Universitat Ramon Llull, Roquetes, Spain; COSMIC Program Office, University Corporation for Atmospheric Research; Observatori de l’Ebre (OE), CSIC – Universitat Ramon Llull, Roquetes, Spain
Abstract: The knowledge about ionospheric plasma density vertical distribution within an altitudinal range of 100–500 km is critically important for the profile-based models widely used for the applications related to the trans-ionospheric radio wave propagations, satellite communication, and global navigation systems operational tasks.
The ionosondes (high frequency sounding radars) provide unbiased benchmark measurements of ionospheric plasma density due to direct relationship between sounding wave reflection and plasma frequency at a particular altitude. But due to this fact, the ground-based ionosonde operation is limited from the ionosphere lower boundary up to the F2 layer peak and does not cover the topside part of the F2 layer. The radio occultation (RO) observations from GNSS receivers onboard low-Earth-orbiting (LEO) satellites provide measurements of electron density vertical distribution also from lower boundary of ionosphere and can cover an altitudinal range up to the height of the orbit where satellites operate (about 500-700 km).
Within the framework of the PITHIA-NRF Trans-National Access program, we investigated an opportunity to obtain the observational-based dependances of ionospheric plasma density distributions (electron density profiles, EDPs) by combining advantages of both the ionosondes and LEO RO measurements. For this task, we use high sampling rate observations from Ebro and El Arenosillo ionosonde stations and COSMIC-2 RO EDPs collocated within area of these ionosonde observations in space and time. We investigated how to combine correctly these two different techniques of the ionosphere probing and finally obtained the set of the reference EDPs that covers an altitudinal range of 100-500 km with high accuracy. In particular, to obtain accurate values of density within the entire altitudinal range, we adjust COSMIC-2 RO EDPs to the unbiased F2 layer peak density values from the ionosonde observations, like in the same technique that is applied for calibration of the plasma density profile during incoherent scatter radar measurements.
The resulted reference EDPs based only on real measurements can serve as independent data for the empirical, first principial, assimilative and machine-learning ionospheric models validation tasks.
Using the obtained reference EDPs, we estimated the accuracy of empirical profile-based models of ionosphere – International Reference Ionosphere (IRI) and NeQuick, to demonstrate model-data discrepancies, which can be improved in the future.
The results of this work are inspired the Observatori de l’Ebre and UCAR COSMIC teams to carry out in the future high sampling rate ionosonde observations with COSMIC-2 RO measurement combinations for synoptical measurements campaigns during the solstice and equinox periods of 2024-2025.
Author(s): Siegfried Gonzi, Richard Mace, Francois-Xavier Bocquet
UK Met Office; UK Met Office; UK Met Office
Abstract: The modus operandi of operational space weather forecasting of the solar wind and arrival time of coronal mass ejections (CMEs) has not changed for the last 10 years. At least not for operational centres as the likes of MOSWOC (Met Office Space Weather Operations Centre) in the UK and the SWPC (Space Weather Prediction Centre) in the USA. A GONG (Global Oscillation Network Group) magnetogram is used to calculate the boundary conditions of the background solar wind at 21.5 solar radii for a Sun to Earth model. A CME is an additional perturbation in the model and the parameters are derived with a CME Analysis Tool (CAT) by analysing coronagraph imagery. It is no secret that this process is riddled with large errors. Before we even start calculating boundary conditions, we already know that the biggest error is hidden in the synoptic map. But we also know we will never get a perfect synoptic map. A further problem is the lack of suitable measurements closer to the Sun which would help us in validating the calculated boundary conditions. This error becomes augmented by the large uncertainties of the fit of an erupting CME. We can only hope that the solar wind forecast at Earth somehow resembles the measurements at Lagrange Point 1 (L1). One way of overcoming all these problems would be the exploitation of ensembles. MOSWOC does this on a basic level with their 24-member CME forecasting system. But how ensembles are created is a completely unsolved problem in space weather forecasting. If we look over the fence to the terrestrial weather forecasting community, we will quickly realise that a modern-day forecast would be unthinkable without data assimilation. But this approach is not being used in space weather forecasting. The reason is this that there are not enough space-borne observations available. As a consequence, it could well mean a data assimilation system does not add value because of this. But this has never really been tested for realistic scenarios in an operational context. Most of the spacecrafts that make measurements of the plasma environment are located at L1, with the exception of STEREO-A. The Parker Solar Probe or the Solar Orbiter travel through the heliosphere but they are less useful for an operational data assimilation system. MOSWOC is trialling a data assimilation system for forecasting the solar wind and CMEs. The inner boundary conditions at 21.5 solar radii are updated by assimilating observations from L1. We describe in this poster the adjoint model that is used for linking the observations at L1 to the inner boundary at 21.5 solar radii. We also show first results of MOSWOC’s operational model of the 5-day forecasts of the solar wind at Earth with and without data assimilation.