Operational Space Weather Research Articles

Statistical comparison of seasonal variations in the GUMICS‐4 global MHD model ionosphere and measurements

AbstractUnderstanding the capability of a simulation to reproduce observed features is a requirement for its use in operational space weather forecasting. We compare statistically ionospheric seasonal variations in the Grand Unified Magnetosphere‐Ionosphere Coupling Simulation (GUMICS‐4) global magnetohydrodynamic model with measurements. The GUMICS‐4 data consist of a set of runs that was fed with real solar wind measurements and cover the period of 1 year. Ionospheric convection measurements are from the Super Dual Auroral Radar Network (SuperDARN) radars, and electric currents are derived from the magnetic field measured by the CHAMP satellite. Auroral electrojet indices are used to examine the disturbance magnetic field on ground. The signatures of electrodynamic coupling between the magnetosphere and ionosphere extend to lower latitudes in GUMICS‐4 than in observations, and key features of the auroral ovals—the Region 2 field‐aligned currents, electrojets, Harang discontinuity, and ring of enhanced conductivity—are not properly reproduced. The ground magnetic field is even at best about 5 times weaker than measurements, which can be a problem for forecasting geomagnetically induced currents. According to the measurements, the ionospheric electrostatic potential does not change significantly from winter to summer but field‐aligned currents enhance, whereas in GUMICS‐4, the electrostatic potential weakens from winter to summer but field‐aligned currents do not change. This could be a consequence of the missing Region 2 currents: the Region 1 current has to close with itself across the polar cap, which makes it sensitive to solar UV conductivity. Precipitation energy and conductance peak amplitudes in GUMICS‐4 agree with observations.

Forecasting propagation and evolution of CMEs in an operational setting: What has been learned

AbstractOne of the major types of solar eruption, coronal mass ejections (CMEs) not only impact space weather, but also can have significant societal consequences. CMEs cause intense geomagnetic storms and drive fast mode shocks that accelerate charged particles, potentially resulting in enhanced radiation levels both in ions and electrons. Human and technological assets in space can be endangered as a result. CMEs are also the major contributor to generating large amplitude Geomagnetically Induced Currents (GICs), which are a source of concern for power grid safety. Due to their space weather significance, forecasting the evolution and impacts of CMEs has become a much desired capability for space weather operations worldwide. Based on our operational experience at Space Weather Research Center at NASA Goddard Space Flight Center (http://swrc.gsfc.nasa.gov), we present here some of the insights gained about accurately predicting CME impacts, particularly in relation to space weather operations. These include: 1. The need to maximize information to get an accurate handle of three‐dimensional (3‐D) CME kinetic parameters and therefore improve CME forecast; 2. The potential use of CME simulation results for qualitative prediction of regions of space where solar energetic particles (SEPs) may be found; 3. The need to include all CMEs occurring within a ~24 h period for a better representation of the CME interactions; 4. Various other important parameters in forecasting CME evolution in interplanetary space, with special emphasis on the CME propagation direction. It is noted that a future direction for our CME forecasting is to employ the ensemble modeling approach.

The Anemomilos prediction methodology for Dst

AbstractThis paper describes new capabilities for operational geomagnetic Disturbance storm time (Dst) index forecasts. We present a data‐driven, deterministic algorithm called Anemomilos for forecasting Dst out to a maximum of 6 days for large, medium, and small storms, depending upon transit time to the Earth. This capability is used for operational satellite management and debris avoidance in Low Earth Orbit (LEO). Anemomilos has a 15 min cadence, 1 h time granularity, 144 h prediction window (+6 days), and up to 1 h latency. A new finding is that nearly all flare events above a certain irradiance threshold, occurring within a defined solar longitude/latitude region and having sufficient estimated liftoff velocity of ejected material, will produce a geoeffective Dst perturbation. Three solar observables are used for operational Dst forecasting: flare magnitude, integrated flare irradiance through time, and event location. Magnitude is a proxy for ejecta quantity or mass and, combined with speed derived from the integrated flare irradiance, represents the kinetic energy. Speed is estimated as the line‐of‐sight velocity for events within 45° radial of solar disk center. Storms resulting from high‐speed streams emanating from coronal holes are not modeled or predicted. A new result is that solar disk, not limb, observable features are used for predictive techniques. Comparisons between Anemomilos predicted and measured Dst for every hour over 25 months in three continuous time frames between 2001 (high solar activity), 2005 (low solar activity), and 2012 (rising solar activity) are shown. The Anemomilos operational algorithm was developed for a specific customer use related to thermospheric mass density forecasting. It is an operational space weather technology breakthrough using solar disk observables to predict geomagnetically effective Dst up to several days at 1 h time granularity. Real‐time forecasts are presented at http://sol.spacenvironment.net/~sam_ops/index.html?

Probabilistic forecasting of ionospheric scintillation and GNSS receiver signal tracking performance at high latitudes

<p>At high latitudes, phase scintillation occurs predominantly on the dayside in the ionospheric footprint of the magnetospheric cusp, and in the nightside auroral oval. A new technique of probabilistic forecasting of phase scintillation occurrence relative to the arrival time of high-speed solar wind from coronal holes and interplanetary coronal mass ejections has recently been proposed [Prikryl et al. 2012]. Cumulative probability distribution functions for the phase-scintillation occurrence that are obtained can be specified for low (below-median) and high (above-median) values of various solar wind plasma parameters. Recent advances in modeling of high-speed solar wind and coronal mass ejections, combined with the probabilistic forecasting of scintillation, will lead to improved operational space weather forecasting applications. Scintillation forecasting and mitigation techniques need to be developed to avoid potential costly failures of technology-based Global Navigation Satellite Systems in the near future, in particular during the upcoming solar maximum. The Global Navigation Satellite Systems receiver-tracking performance during severe scintillation conditions can be assessed by the analysis of receiver phase-locked-loop jitter. Tracking jitter maps [Sreeja et al. 2011] offers a potentially useful tool to provide users with expected tracking conditions, if based on scintillation predictions as proposed above. Scintillation indices are obtained from L1 GPS data collected with the Canadian High Arctic Ionospheric Network. Combined with high rate amplitude and phase data, they can be used as input to receiver tracking models to develop scintillation mitigation techniques.</p>

The SCORE Scale: A Coronal Mass Ejection Typification System Based On Speed

Key PointsA simple new category system for CMEs based on frequency of detection and speedApplicable in space weather operations and research

New Ages of Operational Space Weather Forecast in Japan

Key PointsIntroducing current activities of Japanese space weather forecastFuture direction of Japanese operational space weather researchHistorical background of Japanese space weather forecast

Using SDO EVE data as a proxy for GOES XRS B 1–8 angstrom

AbstractSolar soft X‐ray irradiance measured by the GOES X‐Ray Sensor (XRS) is a critical measurement for space weather operations. At present, there is a primary GOES XRS operating with a second XRS in storage on orbit. This configuration results in gaps in critical observational coverage when the primary XRS is nonoperational such as during satellite maneuvers and during the spring and fall eclipse seasons. EUV Variability Experiment (EVE) on NASA's Solar Dynamics Observatory provides near–real‐time measurements of the solar soft X‐ray irradiances at wavelengths similar to XRS. This study examines the accuracy in using EVE data as a proxy for GOES XRS. Using EVE data, we develop three different solar irradiance index models, which are then tested to determine how well they predict the XRS irradiances and magnitude (GOES class) of solar flares. The best performing index model has been implemented in Version 3 of EVE data and is publicly available within minimal latency through the EVE Science Processing and Operations Center.

Solar thematic maps for space weather operations

Thematic maps are arrays of labels, or “themes,” associated with discrete locations in space and time. Borrowing heavily from the terrestrial remote sensing discipline, a numerical technique based on Bayes' theorem captures operational expertise in the form of trained theme statistics, then uses this to automatically assign labels to solar image pixels. Ultimately, regular thematic maps of the solar corona will be generated from high‐cadence, high‐resolution SUVI images, the solar ultraviolet imager slated to fly on NOAA's next‐generation GOES‐R series of satellites starting ∼2016. These thematic maps will not only provide quicker, more consistent synoptic views of the sun for space weather forecasters, but digital thematic pixel masks (e.g., coronal hole, active region, flare, etc.), necessary for a new generation of operational solar data products, will be generated. This paper presents the mathematical underpinnings of our thematic mapper, as well as some practical algorithmic considerations. Then, using images from the Solar Dynamics Observatory (SDO) Advanced Imaging Array (AIA) as test data, it presents results from validation experiments designed to ascertain the robustness of the technique with respect to differing expert opinions and changing solar conditions.

The Second Annual Space Weather Community Operations Workshop: Advancing Operations Into the Next Decade

How can we continue to advance the space weather operational community from lessons already learned when it comes to data reliability, maintainability, accessibility, dependability, safety, and quality? How can we make space weather more easily accessible to each other and outside users? Representatives from operational, commercial, academic, and government organizations weighed in on these important questions at the second annual Space Weather Community Operations Workshop, held 22–23 March 2012 in Park City, Utah, with the unofficial workshop motto being Don’t Reinvent the Wheel. The workshop, hosted by the Space Weather Center (SWC) at Utah State University (USU), had an objective of building on preexisting distributed space weather networks. W. Kent Tobiska, director of USU SWC, introduced this objective by pointing to the operations-level information exchange already occurring between 11 organizations: NOAA Space Weather Prediction Center (SWPC); NASA Community Coordinated Modeling Center; Laboratory for Atmospheric and Space Physics; Atmospheric and Environmental Research; Center for Space Plasma and Aeronomic Research; Exploration Physics International; Rice Space Institute; U.S. Geological Survey (USGS); Space Environment Center; Space Environment Technologies; and the event host, USU SWC. The workshop brought together two dozen core commercial, agency, and university space weather operational personnel to promote a robust data exchange capacity within the space weather enterprise. This data exchange focuses on sharing common operational problems and solutions as well as working toward developing best practices that will eventually become standards for space weather operations. Each participant discussed mission assurance best practices in terms of reliability, maintainability, accessibility, dependability, safety, and quality. For example, recommendations for reliability best practices would be to maintain redundancy by creating several channels for data access making systems more reliable by allowing data customers multiple access points and relieving strain on systems. Unreliable source data are detrimental to space weather products when downstream users are unable to ingest data. Looking at maintainability, simple practices such as consistent, intuitive file-naming conventions; maintainable software; documentation (e.g., user guides and test plans); and attention to other best practices in software development are vital. Structural and descriptive metadata are key players in accessibility. Following the simple outline of Who, What, Where, When, Why, How, and Whose is recommended for creating and developing meaningful metadata that will benefit the end user. Dependability of data and systems becomes a main focus for data producers and maintainers. The direct access servers (non-Web) such as the External Space Weather Data Store used by NOAA SWPC and Earthworm used by USGS are examples of different systems used to bolster dependability of data access for users. Finally, safety and quality of products and data can be tested against several different challenges, including Geospace Environment Modeling (GEM) Metrics, Coupling, Energetics, and Dynamics of Atmospheric Regions (CEDAR) Electrodynamics Thermosphere Ionosphere (ETI), GEMCEDAR (Dst), and Solar Heliosphere and Interplanetary Environment (SHINE) program (see http://ccmc.gsfc.nasa.gov/ support/CETI2010/). Quality products will help improve the safety of the same products, fostering a community perception of trustworthy space weather data providers. Topics of coronal mass ejection forecasts and ensemble modeling, high-latitude energy inputs, and products and services were discussed in breakout sessions. These sessions generated ideas for creating accessible data distribution systems, ensuring reliability in operational data systems, building dependable data networks, establishing and implementing operational space weather best practices, and developing maintainable operational systems. The 2012 workshop concluded with action items for improving common space weather operations. The success of the first Space Weather Community Operations Workshop in 2011 led to sponsorship of the second workshop by the Amer-

The US‐UK Space Weather Workshop

The US‐UK Space Weather Workshop

Multi-mode Ensemble Visualization Demo System for Space Weather

空间天气模式集成是空间天气预报业务化的基础, 空间天气模式集成可视化演示软件系统是其中重要的研究内容之一. 空间天气模式种类繁多, 要素多样, 模型复杂, 且各模式可视化形式及方法具有差异性. 本文综合当前中国空间天气模式的特点, 构建了一套空间天气模式集成可视化演示系统. 该系统兼容性好、可扩展性高, 能够集成当前中国空间天气中大多数模式. 讨论了空间数据管理方法, 基于Visual C++ 软件平台和OpenGL可视化软件模块,以动态加载方式初步实现了多个空间天气模式的可视化集成.

South Korea's renewed focus on space weather

South Korea's renewed focus on space weather

Total electron content models and their use in ionosphere monitoring

In Global Navigation Satellite Systems (GNSS) using L band frequencies, the ionosphere causes signal delays that correspond to link‐related range errors of up to 100 m. Whereas this error can be corrected in dual‐frequency measurements by a linear combination of L1 and L2 phases, in single‐frequency measurements, additional information is needed to mitigate the ionospheric error which is proportional to the total electron content (TEC) of the ionosphere. This information can be provided by TEC maps deduced from corresponding GNSS measurements or from model values. Besides direct range error correction in navigation and remote sensing applications, TEC or electron density models play a key role in ionospheric monitoring and forecasting. In this paper we discuss the development and use of TEC models for calibrating TEC, reconstructing reliable TEC maps, and forecasting TEC behavior based on GNSS measurements. European and global TEC maps and corresponding 1 h ahead forecasts are distributed via the operational space weather and ionosphere data service (http://swaciweb.dlr.de) to the international community. The Neustrelitz TEC Model is a basic approach for a family of regional and global TEC models used in different types of applications. The model approximates typical TEC variations depending on the location, time, and level of solar activity with only a few coefficients.

Industry and Government Space Weather Experts Meet

The fifth annual NOAA Space Weather Prediction Center (SWPC)-Commercial Space Weather Interest Group (CSWIG) Summit was held on 28 April 2011 in Boulder, Colo., in association with the 2011 Space Weather Workshop. Interest was high, in the United States and internationally, in potential space weather impacts on many aspects of everyday life because of the increased vulnerability of technological systems and the possibility that a major space weather event may occur as the twenty-fourth solar cycle begins to progress toward solar maximum. Industry and government space weather experts participated in the summit. Devrie Intriligator (Carmel Research Center, Inc.) and W. Kent Tobiska (Space Environment Technologies (SET)) served as cochairs. Tom Bogdan, Director of SWPC, summarized SWPC’s current fiscal situation and future plans. SWPC has been successful in educating members of the executive branch and other government officials about space weather. President Obama’s proposed fiscal year (FY) 2012 budget includes Department of Defense and NOAA funding for the Deep Space Climate Observatory (DSCOVR), the replacement for the Advanced Composition Explorer (ACE) spacecraft, which warns of approaching interplanetary disturbances from the Sun. It is crucial for Congress to appropriate this funding if DSCOVR is to be launched on schedule in 2014. The Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC-2) mission is also in the proposed FY 2012 budget. Starting in early fall 2011, SWPC is planning to have two forecasters on duty 24 hours a day, 7 days a week. SWPC’s top operational priorities include an improved WangSheeleyArge (WSA) model of the Sun/solar wind interface and a Ground Induced Current regional model. A high priority is improved forecasting of the interplanetary magnetic field characteristics of a coronal mass ejection that hits Earth. David Bouwer (SET) summarized SWPC’s External Space Weather Data Store (E-SWDS) and other data/model sources. E-SWDS is the most reliable data source with the fewest changes/interruptions in service, format, and parameters. CSWIG looks forward to when E-SWDS also will include improved model outputs (e.g., ENLIL, WSA, etc.). Intriligator summarized concerns on the quality and quantity of future data including those from ACE and National Polar-Orbiting Operational Environmental Satellite System (NPOESS) replacements, the Geostationary Operational Environmental Satellite (GOES), etc. Space weather research, operations, and forecasts are data limited, and longterm monitoring of solar, interplanetary, and near-Earth regions is crucial. NOAA is tasked with this monitoring. Stable funding of long-term spacecraft lines (e.g., GOES) is needed. Michael Bonadonna (Office of the Federal Coordinator for Meteorology (OFCM)) updated the group on the National Space Weather Program (NSWP) and OFCM activities. One of the near-term priorities of OFCM is to improve its ability to work with the commercial sector. At present, there is no mechanism for the commercial sector to participate in the NSWP Council or other high-level NSWP activities. The Office of Science and Technology Policy has requested that NSWP assess U.S. space weather capabilities now and 10 years in the future. Tobiska discussed CSWIG participation in software test beds and Small Business Innovative Research opportunities as ways of leveraging funding. He also discussed moving toward space weather common practices and a quality assurance program including standards as developed by the American Institute of Aeronautics and Astronautics (http://spacewx.com, see the “Standards” link under “Resources”). Geoff Crowley (Atmospheric and Space Technology Research Associates) reported on the American Commercial Space Weather Association (ACSWA), the space weather association that was unanimously formed last year at the SWPCCSWIG Summit. The ACSWA executive committee (Crowley, Intriligator, Robert Schunk, and Tobiska) had earlier drafted the mission statement for ACSWA and established a Web site (http://sw01.spaceweather.usu.edu/ACSWA/ landing.html), which was unveiled at the summit meeting. Bonadonna and Bogdan enthusiastically supported ACSWA. Genene Fisher

Space Weather Model Moves Into Prime Time

Space Weather Model Moves Into Prime Time

ESA Soon to Unveil Space Weather Services

ESA Soon to Unveil Space Weather Services

New Chains of Space Weather Monitoring Stations in China

To develop an understanding of near-Earth space’s response to solar activities and to eventually enhance the success of space weather predictions, it is crucial to make synergetic observations of the entire environment from the Sun to the Earth as a system. Since the beginning of the space era, direct observations by satellites have become a much needed means toward this end. However, ground-based observations also have advantages and serve as a counterpart to those made in space. For example, instruments on the ground are much less expensive and easier to repair than those on satellites. Groundbased observations provide continuous highresolution data not subject to the limitation of the downlink data rate from satellites to ground receiving stations. Also, because some observations have been made from Earth for hundreds of years, society has long and continuous records of quantities such as geomagnetic field variations, measurements of relative ionospheric opacity, and sunspot observations. Data from spacecraft, on the other hand, go back only a few decades. China has a total land area of about 9,600,000 square kilometers, with geomagnetic locations covering middle to low latitudes. The first geomagnetic observatory in China was constructed in Beijing in 1870 by Russians, but it ceased working in 1882. China briefly participated in the International Geophysical Year (1957–1958) and started to explore the upper atmosphere using rockets and balloons in the 1960s. Though research at government institutions and universities picked up in the late twentieth century, the ability to monitor the geospace environment and capture the evolution and characteristics of the weather in geospace above China is still insufficient today. Not only is China’s large population increasingly reliant on space-based technologies, but there are also not enough locations across the country where space weather conditions are monitored. This limits Chinese scientists’ understanding of the basic physical processes in geospace and their ability to make accurate predictions of adverse space weather for their country’s citizens. To acknowledge the needs of both basic science and useful space weather operations, a ground-based program to monitor China’s geospace environment is currently under way. Called the Meridian Space Weather Monitoring Project (or Chinese Meridian Project), the effort consists of a chain of 15 ground-based observatories located roughly along 120°E longitude and 30°N latitude. Each observatory is equipped with multiple instruments to measure key parameters such as the baseline and timevarying geomagnetic field, as well as the middle and upper atmosphere and ionosphere from about 20 to 1000 kilometers. Starting in 2011, the project will collect data for at least 11 years, providing the wide-range, continuous, and multiparameter data sets needed to guide model developments, which in turn will better describe and predict the characteristics and dynamics of the geospace environment.

Distributed networks enable advances in US space weather operations

Space weather, the shorter-term variable impact of the Sun’s photons, solar wind particles, and interplanetary magnetic field upon the Earth’s environment, adversely affects our technological systems. These technological systems, including their space component, are increasingly being seen as a way to help solve 21st Century problems such as climate change, energy access, fresh water availability, and transportation coordination. Thus, the effects of space weather on space systems and assets must be mitigated and operational space weather using automated distributed networks has emerged as a common operations methodology. The evolution of space weather operations is described and the description of distributed network architectures is provided, including their use of tiers, data objects, redundancy, and time domain definitions. There are several existing distributed networks now providing space weather information and the lessons learned in developing those networks are discussed along with the details of examples for the Solar Irradiance Platform (SIP), Communication Alert and Prediction System (CAPS), GEO Alert and Prediction System (GAPS), LEO Alert and Prediction System (LAPS), Radiation Alert and Prediction System (RAPS), and Magnetosphere Alert and Prediction System (MAPS).

Radio occultation techniques for probing the ionosphere

GPS radio occultation measurements establish the basis for a new remote sensing technique for vertical profile information on the electron density of the entire ionosphere from satellite orbit heights down to the bottomside. No other profiling technique such as vertical sounding or incoherent scatter, unifies vertical profiling through the entire ionosphere with global coverage. Inversion methods are described both for vertical profiling as well as for tree dimensional electron density reconstructions of the ionosphere. In three dimensional electron density reconstructions using signals from Global Navigation Satellite Systems (GNSS), the Ionospheric Radio Occultation (IRO) measurements provide vertical information which is complementary to the information obtained by ground based measurements. Assessment of achievable accuracy and spatial resolution are addressed by simulation studies. IRO measurements have been carried out onboard the German CHAMP satellite since 11 April 2001 on a routine basis. Assuming a spherically layered ionosphere, up to about 150 Electron Density Profiles (EDPs) per day are retrieved within a latency of 3 h. Validation results obtained by using independent data sources are reported. The validation with vertical sounding data in mid-latitudes indicates a small positive bias in the plasma frequency of up to about 0.5 MHz throughout the entire profile. Averages of the numerous EDPs show wellknown ionospheric phenomena such as the equatorial anomaly, the winter anomaly and the expansion of the profile with increasing solar energy input. It is concluded that CHAMP-IRO measurements have the potential to establish global data sets of vertical electron density profiles for developing and improving global ionospheric models and to provide operational space weather information.

Operational Space Weather Entering a New Era

U.S. operational space weather maturing because of two competing factors. On one hand, directed agency funding at about $1 billion for model development over the past decade has brought modeling maturity to !ve broad Sun-toEarth domains, i.e., Sun, heliosphere, magnetosphere, ionosphere, and thermosphere. On the other hand, agency funding for transitioning these models into operations has been a small fraction of the level provided for model development. is situation has le# implementation of operational space weather largely unfunded and woefully undirected, with the exception of a few U.S. Air Force Weather Agency projects. A new vision needed so that operational space weather can help solve 21st-century challenges. e current paradigm for operational space weather began in the 1990s, when the idea was to build complete systems at single facilities. ese rapid prototyping centers were envisioned as a means for implementing new operational systems, but this path was unsuccessful. Although increased funding for operational space weather would have bene!ted the community, this did not happen, and in the lopsided funding pro!le, operational space weather was forced to develop an unusual but robust architecture. is architecture consists of distributed networks—automated systems of models, data streams, and algorithms at multiple, geographically dispersed facilities linked by operational servers. A central server manages the network and uses a database enabling remote nodes to deposit output data and access input data at their geophysical or measurement cadences and latencies. e emergence of distributed networks represents a paradigm shi# from 1995, when the National Space Weather Program (NSWP) strategic plan was !rst published. At that time, very few models existed that could be even considered for use in operations. Model development increased due to the funding surge, and by 2000 seventy-three models characterizing 15 space environment domains were listed in the NSWP implementation plan (2nd edition). During the past decade some of these models were implemented operationally and became important components of distributed networks. Early examples were the Magnetospheric Spec!cation Model (MSM; 2000), SOLAR2000 (S2K; 2001), and High Accuracy Satellite Drag Model (HASDM; 2004). More recently, systems of coupled models and data streams have been created, including Global Assimilation of Ionospheric Measurements (GAIM; 2006), HakamadaAkasofuFry (HAF; 2007), and Communication Alert and Prediction System (CAPS; 2008). Coupled model/ data systems that are currently being implemented include the JacchiaBowman 2008 (JB2008), the Nowcast of Atmospheric Ionizing Radiation for Aviation Safety (NAIRAS), U.S. Geological Survey Dst, ENLIL with Cone, and Ionosphere Operational System (IONS; i.e., the commercial version of GAIM at the Utah Science Technology and Research (USTAR) Center for Space Weather). Of added note that the Space Weather Modeling Framework (SWMF) and the Center for Integrated Space Weather Modeling (CISM) have developed multi domain systems to represent the entire Sunto-Earth environment, in which some of the models have been running for years. e need to test coupled systems existed even without funding, and the lack of funds drove small businesses, universities, and the multiagency Community Coordinated Modeling Center to create innovative, cost-e$ective solutions. Basically, these organizations had to !nd cheaper ways to accomplish testing and operational implementation. e result was the development of distributed networks to close the Technology Readiness Level (TRL) 7–9 gap. TRL the concept used by agencies and companies to assess the maturity of evolving technologies. TRL 7 models and data can operate in stand-alone mode within the context of an operational environment. TRL 8 signi!es the completion of a fully functional system prototype, and TRL 9 describes a fully delivered, operational system. e distributed network systems at TRL 7–9 are linked in a way that allows developers to maintain versioning and proprietary control over their models, permits data streams to be integrated at their own measurement cadence, results in testing %exibility, enables rapid