Item 1. Apologies

Apologies were received from Stephen Burt & Dave Bullock. Item 2. Agreement of agenda The agenda was agreed. Item 3. Minutes of last meeting The minutes of the committee meeting & AGM held on 12 th September 2014 were agreed as being correct. Item 4. Items arising Actions from the previous committee meeting were considered and the following matters were discussed: Rain gauge raffle – At the 2013 RMetS Amateur Meteorologist Symposium, MD organised a SIG stand where he raffled an EML rain gauge, signed-up 29 new members & raised £145. MD was thanked for his hard work. New committee member – MD has contacted, but not yet had a reply from, Mark Wilkinson (James Hutton Institute, Aberdeen) to invite him to join the SIG committee. The SIG has offered to pay travel expenses for Mark for one trip/year to attend a SI

Space Weather Modeling Capabilities Assessment: Auroral Precipitation and Highâ Latitude Ionospheric Electrodynamics

As part of its International Capabilities Assessment effort, the Community Coordinated Modeling Center initiated several working teams, one of which is focused on the validation of models and methods for determining auroral electrodynamic parameters, including particle precipitation, conductivities, electric fields, neutral density and winds, currents, Joule heating, auroral boundaries, and ion outflow. Auroral electrodynamic properties are needed as input to space weather models, to test and validate the accuracy of physical models, and to provide needed information for space weather customers and researchers. The working team developed a process for validating auroral electrodynamic quantities that begins with the selection of a set of events, followed by construction of ground truth databases using all available data and assimilative data analysis techniques. Using optimized, predefined metrics, the ground truth data for selected events can be used to assess model performance and improvement over time. The availability of global observations and sophisticated data assimilation techniques provides the means to create accurate ground truth databases routinely and accurately.Key PointsA working team has been established to develop a process for validation of auroral precipitation and electrodynamics modelsValidation of auroral electrodynamic parameters requires generation of ground truth data sets for selected eventsCurrent observations and data assimilation techniques continue to improve the accuracy of global auroral electrodynamic specificationPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148365/1/swe20815_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148365/2/swe20815.pd

Model Evaluation Guidelines for Geomagnetic Index Predictions

Geomagnetic indices are convenient quantities that distill the complicated physics of some region or aspect of near‐Earth space into a single parameter. Most of the best‐known indices are calculated from ground‐based magnetometer data sets, such as Dst, SYM‐H, Kp, AE, AL, and PC. Many models have been created that predict the values of these indices, often using solar wind measurements upstream from Earth as the input variables to the calculation. This document reviews the current state of models that predict geomagnetic indices and the methods used to assess their ability to reproduce the target index time series. These existing methods are synthesized into a baseline collection of metrics for benchmarking a new or updated geomagnetic index prediction model. These methods fall into two categories: (1) fit performance metrics such as root‐mean‐square error and mean absolute error that are applied to a time series comparison of model output and observations and (2) event detection performance metrics such as Heidke Skill Score and probability of detection that are derived from a contingency table that compares model and observation values exceeding (or not) a threshold value. A few examples of codes being used with this set of metrics are presented, and other aspects of metrics assessment best practices, limitations, and uncertainties are discussed, including several caveats to consider when using geomagnetic indices.Plain Language SummaryOne aspect of space weather is a magnetic signature across the surface of the Earth. The creation of this signal involves nonlinear interactions of electromagnetic forces on charged particles and can therefore be difficult to predict. The perturbations that space storms and other activity causes in some observation sets, however, are fairly regular in their pattern. Some of these measurements have been compiled together into a single value, a geomagnetic index. Several such indices exist, providing a global estimate of the activity in different parts of geospace. Models have been developed to predict the time series of these indices, and various statistical methods are used to assess their performance at reproducing the original index. Existing studies of geomagnetic indices, however, use different approaches to quantify the performance of the model. This document defines a standardized set of statistical analyses as a baseline set of comparison tools that are recommended to assess geomagnetic index prediction models. It also discusses best practices, limitations, uncertainties, and caveats to consider when conducting a model assessment.Key PointsWe review existing practices for assessing geomagnetic index prediction models and recommend a “standard set” of metricsAlong with fit performance metrics that use all data‐model pairs in their formulas, event detection performance metrics are recommendedOther aspects of metrics assessment best practices, limitations, uncertainties, and geomagnetic index caveats are also discussedPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147764/1/swe20790_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147764/2/swe20790.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147764/3/swe20790-sup-0001-2018SW002067-SI.pd

A Comparison of Flare Forecasting Methods. III. Systematic Behaviors of Operational Solar Flare Forecasting Systems

A workshop was recently held at Nagoya University (31 October – 02 November 2017), sponsored by the Center for International Collaborative Research, at the Institute for Space-Earth Environmental Research, Nagoya University, Japan, to quantitatively compare the performance of today’s operational solar flare forecasting facilities. Building upon Paper I of this series (Barnes et al. 2016), in Paper II (Leka et al. 2019) we described the participating methods for this latest comparison effort, the evaluation methodology, and presented quantitative comparisons. In this paper we focus on the behavior and performance of the methods when evaluated in the context of broad implementation differences. Acknowledging the short testing interval available and the small number of methods available, we do find that forecast performance: 1) appears to improve by including persistence or prior flare activity, region evolution, and a human “forecaster in the loop”; 2) is hurt by restricting data to disk-center observations; 3) may benefit from long-term statistics, but mostly when then combined with modern data sources and statistical approaches. These trends are arguably weak and must be viewed with numerous caveats, as discussed both here and in Paper II. Following this present work, we present in Paper IV a novel analysis method to evaluate temporal patterns of forecasting errors of both types (i.e., misses and false alarms; Park et al. 2019). Hence, most importantly, with this series of papers we demonstrate the techniques for facilitating comparisons in the interest of establishing performance-positive methodologies

Summary of the plenary sessions at European Space Weather Week 15: space weather users and service providers working together now and in the future

During European Space Weather Week 15 two plenary sessions were held to review the status of operational space weather forecasting. The first session addressed the topic of working with space weather service providers now and in the future, the user perspective. The second session provided the service perspective, addressing experiences in forecasting development and operations. Presentations in both sessions provided an overview of international efforts on these topics, and panel discussion topics arising in the first session were used as a basis for panel discussion in the second session. Discussion topics included experiences during the September 2017 space weather events, cross domain impacts, timeliness of notifications, and provision of effective user education. Users highlighted that a severe space weather event did not necessarily lead to severe impacts for each individual user across the different sectors. Service providers were generally confident that timely and reliable information could be provided during severe and extreme events, although stressed that more research and funding were required in this relatively new field of operational space weather forecasting, to ensure continuation of capabilities and further development of services, in particular improved forecasting targeting user needs. Here a summary of the sessions is provided followed by a commentary on the current state-of-the-art and potential next steps towards improvement of services

Verification of Flare Forecasts at the Met Office Space Weather Operations Centre

Presentation at European Meteorological Society Annual Meeting, 2017 September 6, DCU, Dublin, Irelan

Frequency of eating and concentrations of serum cholesterol in the Norfolk population of the European prospective investigation into cancer (EPIC-Norfolk): cross-sectional study

OBJECTIVES: To examine the relation between self reported eating frequency and serum lipid concentrations in a free living population. DESIGN: Cross sectional population based study. SETTING: Norfolk, England. PARTICIPANTS: 14 666 men and women aged 45-75 years from the Norfolk cohort of the European prospective investigation into cancer (EPIC-Norfolk). MAIN OUTCOME MEASURES: Concentrations of blood lipids. RESULTS: Mean concentrations of total cholesterol and low density lipoprotein cholesterol decreased in a continuous relation with increasing daily frequency of eating in men and women. No consistent relation was observed for high density lipoprotein cholesterol, body mass index, waist to hip ratio, or blood pressure. Mean cholesterol concentrations differed by about 0.25 mmol/l between people eating more than six times a day and those eating once or twice daily; this difference was reduced to 0.15 mmol/l after adjustment for possible confounding variables, including age, obesity, cigarette smoking, physical activity, and intake of energy and nutrients (alcohol, fat, fatty acids, protein, and carbohydrate). CONCLUSIONS: Concentrations of total cholesterol and low density lipoprotein cholesterol are negatively and consistently associated with frequency of eating in a general population. The effects of eating frequency on lipid concentrations induced in short term trials in animals and human volunteers under controlled laboratory conditions can be observed in a free living general population. We need to consider not just what we eat but how often we eat