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Register a new userFrom Predicting Solar Activity to Forecasting Space Weather: Practical Examples of Research-to-Operations and Operations-to-Research
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The successful transition of research to operations (R2O) and operations to research (O2R) requires, above all, interaction between the two communities. We explore the role that close interaction and ongoing communication played in the successful fielding of three separate developments: an observation platform, a numerical model, and a visualization and specification tool. Additionally, we will examine how these three pieces came together to revolutionize interplanetary coronal mass ejection (ICME) arrival forecasts. A discussion of the importance of education and training in ensuring a positive outcome from R2O activity follows. We describe efforts by the meteorological community to make research results more accessible to forecasters and the applicability of these efforts to the transfer of space-weather research.We end with a forecaster wish list for R2O transitions. Ongoing, two-way communication between the research and operations communities is the thread connecting it all.
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The Met Office Space Weather Operations Centre produces 24/7/365 space weather guidance, alerts, and forecasts to a wide range of government and commercial end users across the United Kingdom. Solar flare forecasts are one of its products, which are issued multiple times a day in two forms; forecasts for each active region on the solar disk over the next 24 hours, and full-disk forecasts for the next four days. Here the forecasting process is described in detail, as well as first verification of archived forecasts using methods commonly used in operational weather prediction. Real-time verification available for operational flare forecasting use is also described. The influence of human forecasters is highlighted, with human-edited forecasts outperforming original model results, and forecasting skill decreasing over longer forecast lead times.
In the United States, scientific research in space weather is funded by several Government Agencies including the National Science Foundation (NSF) and the National Aeronautics and Space Agency (NASA). For commercial purposes, space weather forecast is made by the Space Weather Prediction Center (SWPC) of the National Oceanic and Atmospheric Administration (NOAA). Observations come from the network of groundbased observatories funded via various sources, as well as from the instruments on spacecraft. Numerical models used in forecast are developed in the framework of individual research projects. Later, the most promising models are selected for additional testing at SWPC. In order to increase the application of models in research and education, NASA in collaboration with other agencies created Community Coordinated Modeling Center (CCMC). In mid-1990, US scientific community presented compelling evidence for developing the National Program on Space Weather, and in 1995, such program has been formally created. In 2015, the National Council on Science and Technology issued two documents: the National Space Weather Strategy [1] and the Action Plan [2]. In the near future, these two documents will define the development of Space Weather research and forecasting activity in USA. Both documents emphasize the need for close international collaboration in area of space weather.
We study the security threats of power system operation brought by a class of data injection attacks upon load forecasting algorithms. In particular, with minimal assumptions on the knowledge and ability of the attacker, we design attack data on input features for load forecasting algorithms in a black-box approach. System operators can be oblivious of such wrong load forecasts, which lead to uneconomical or even insecure decisions in commitment and dispatch. This paper is the first attempt to bring up the security issues of load forecasting algorithms to our knowledge, and show that accurate load forecasting algorithm is not necessarily robust to malicious attacks. More severely, attackers are able to design targeted attacks on system operations strategically with additional topology information. We demonstrate the impact of load forecasting attacks on two IEEE test cases. We show our attack strategy is able to cause load shedding with high probability under various settings in the 14-bus test case, and also demonstrate system-wide threats in the 118-bus test case with limited local attacks.
We discuss the general design of the ANTARES code which is intended for simulations in stellar hydrodynamics with radiative transfer and realistic microphysics in 1D, 2D and 3D. We then compare the quality of various numerical methods. We have applied ANTARES in order to obtain high resolution simulations of solar granulation which we describe and analyze. In order to obtain high resolution, we apply grid refinement to a region predominantly occupied by an exploding granule. Strong, rapidly rotating vortex tubes of small diameter (~100 km) generated by the downdrafts and ascending into the photosphere near the granule boundaries evolve, often entering the photosphere from below in an arclike fashion. They essentially contribute to the turbulent velocity field near the granule boundaries.
In order to evaluate the quality of the scientific research, we introduce a new family of scientific performance measures, called Scientific Research Measures (SRM). Our proposal originates from the more recent developments in the theory of risk measures and is an attempt to resolve the many problems of the existing bibliometric indices. The SRM that we introduce are based on the whole scientists citation record and are: coherent, as they share the same structural properties; flexible to fit peculiarities of different areas and seniorities; granular, as they allow a more precise comparison between scientists, and inclusive, as they comprehend several popular indices. Another key feature of our SRM is that they are planned to be calibrated to the particular scientific community. We also propose a dual formulation of this problem and explain its relevance in this context.
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