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Non‐linear Error Compensation Technique with Associative Restoration (NECTAR) is a novel approach to the assimilation of fragmentary sensor data to produce a global nowcast of the near‐Earth space weather. NECTAR restores missing information by iteratively transforming ("morphing") an underlying global climatology model into agreement with currently available sensor data. The morphing procedure benefits from analysis of the inherent multiscale diurnal periodicity of the geosystems by processing 24‐hr time histories of the differences between measured and climate‐expected values at each sensor site. The 24‐hr deviation time series are used to compute and then globally interpolate the diurnal deviation harmonics. NECTAR therefore views the geosystem in terms of its periodic planetary‐scale basis to associate observed fragments of the activity with the grand‐scale weather processes of the matching variability scales. Such approach strengthens the restorative capability of the assimilation, specifically when only a limited number of observatories is available for the weather nowcast. Scenarios where the NECTAR concept works best are common in planetary‐scale near‐Earth weather applications, especially where sensor instrumentation is complex, expensive, and therefore scarce. To conduct the assimilation process, NECTAR employs a Hopfield feedback recurrent neural network commonly used in the associative memory architectures. Associative memories mimic human capability to restore full information from its initial fragments. When applied to the sparse spatial data, such a neural network becomes a nonlinear multiscale interpolator of missing information. Early tests of the NECTAR morphing reveal its enhanced capability to predict system dynamics over no‐data regions (spatial interpolation). Key Points: A novel technique is presented for assimilating fragmentary sensor data to produce a global‐scale space weather nowcastThe technique iteratively transforms ("morphs") an underlying global climatology model into agreement with available sensor dataThe technique senses the inherent multiscale diurnal periodicity of geosystems to restore missing information over no‐data regions [ABSTRACT FROM AUTHOR]

Ionospheric data are valuable records of the behavior of the ionosphere, solar activity, and the entire Sun‐Earth system. The data are critical for both societally important services and scientific investigations of upper atmospheric variability. This work investigates some of the difficulties and pitfalls in maintaining long‐term records of geophysical measurements. This investigation focuses on the ionospheric parameters contained in the historical data sets within the National Oceanic and Atmospheric Administration National Geophysical Data Center and Space Physics Interactive Data Resource databases. These archives include data from approximately 100 ionosonde stations worldwide, beginning in the early 1940s. Our study focuses on the quality and consistency of ionosonde data accessible via the primary Space Physics Interactive Data Resource node located within the National Oceanic and Atmospheric Administration National Geophysical Data Center and the World Data Center for Solar‐Terrestrial Physics located in Boulder, Colorado. We find that, although the Space Physics Interactive Data Resource archives contained an impressive amount of high‐quality data, specific problems existed involving missing and noncontiguous data sets, long‐term variations or changes in methodologies and analysis procedures used, and incomplete documentation. The important lessons learned from this investigation are that the data incorporated into an archive must have clear traceability back to the primary source, including scientific validation by the contributors, and that the historical records must have associated metadata that describe relevant nuances in the observations. Although this report only focuses on historical ionosonde data in National Oceanic and Atmospheric Administration databases, we feel that these findings have general applicability to environmental scientists interested in using long‐term geophysical data sets for climate and global change research. Key Points: This work describes problems found within long‐term ionospheric records, likely caused by distributed storage systemThe problems found still persist, and there is no appearance of reparationIonospheric data are valuable records of the behavior of the ionosphere, solar activity, and the entire Sun‐Earth system [ABSTRACT FROM AUTHOR]

To address challenges of assessing space weather modeling capabilities, the Community Coordinated Modeling Center is leading a newly established International Forum for Space Weather Modeling Capabilities Assessment. This paper presents preliminary results of validation of modeled foF2 (F2 layer critical frequency) and TEC (total electron content) during the first selected 2013 March storm event (17 March 2013). In this study, we used eight ionospheric models ranging from empirical to physics‐based, coupled ionosphere‐thermosphere and data assimilation models. The quantities we considered are TEC and foF2 changes and percentage changes compared to quiet time background, and the maximum and minimum percentage changes. In addition, we considered normalized percentage changes of TEC. We compared the modeled quantities with ground‐based observations of vertical Global Navigation Satellite System TEC (provided by Massachusetts Institute of Technology Haystack Observatory) and foF2 data (provided by Global Ionospheric Radio Observatory) at the 12 locations selected in middle latitudes of the American and European‐African longitude sectors. To quantitatively evaluate the models' performance, we calculated skill scores including correlation coefficient, root‐mean square error (RMSE), ratio of the modeled to observed maximum percentage changes (yield), and timing error. Our study indicates that average RMSEs of foF2 range from about 1 MHz to 1.5 MHz. The average RMSEs of TEC are between ~5 and ~10 TECU (1 TEC Unit = 1016 el/m2). dfoF2[%] RMSEs are between 15% and 25%, which is smaller than RMSE of dTEC[%] ranging from 30% to 60%. The performance of the models varies with the location and metrics considered. Key Points: foF2/TEC and foF2/TEC changes during a storm predicted by eight ionosphere models were compared with GIRO foF2 and GPS TEC measurementsSkill scores (e.g., correlation coefficient, RMSE, yield, and timing error) were calculatedModel performance strongly depends on the quantities considered, the type of metrics used, and the location considered [ABSTRACT FROM AUTHOR]

In order to assess current modeling capability of reproducing storm impacts on total electron content (TEC), we considered quantities such as TEC, TEC changes compared to quiet time values, and the maximum value of the TEC and TEC changes during a storm. We compared the quantities obtained from ionospheric models against ground-based GPS TEC measurements during the 2006 AGU storm event (14-15 December 2006) in the selected eight longitude sectors. We used 15 simulations obtained from eight ionospheric models, including empirical, physics-based, coupled ionosphere-thermosphere, and data assimilation models. To quantitatively evaluate performance of the models in TEC prediction during the storm, we calculated skill scores such as RMS error, Normalized RMS error (NRMSE), ratio of the modeled to observed maximum increase (Yield), and the difference between the modeled peak time and observed peak time. Furthermore, to investigate latitudinal dependence of the performance of the models, the skill scores were calculated for five latitude regions. Our study shows that RMSE of TEC and TEC changes of the model simulations range from about 3 TECU (total electron content unit, 1 TECU = 1016 el m−2) (in high latitudes) to about 13 TECU (in low latitudes), which is larger than latitudinal average GPS TEC error of about 2 TECU. Most model simulations predict TEC better than TEC changes in terms of NRMSE and the difference in peak time, while the opposite holds true in terms of Yield. Model performance strongly depends on the quantities considered, the type of metrics used, and the latitude considered. [ABSTRACT FROM AUTHOR]

When the Committee on Space Research (COSPAR) initiated the International Reference Ionosphere (IRI) project in 1968 it wisely selected K. Rawer as its first Chairperson. With a solid footing and good contacts in both the ground-based and space-based ionospheric communities he was ideally suited to pull together colleagues and data from both communities to help build the first version of the IRI. He assembled a team of 20+ international ionospheric experts in the IRI Working Group and chaired and directed the group from 1968 to 1984. The working group has now grown to 63 members and the IRI model has undergone many revisions as new data became available and new modeling techniques were applied. This paper was presented during a special session of the Kleinheubach Tagung 2013 in honor of K. Rawer's 100th birthday. It will review the current status of the IRI model and project and the international recognition it has achieved. It is quite fitting that this year we not only celebrate K. Rawer's 100th birthday but also the exciting news that his favorite science endeavor, IRI, has been internationally recognized as an ISO (International Standardization Organization) standard. The IRI homepage is at http://irimodel.org. [ABSTRACT FROM AUTHOR]

This presentation is given in honor of Prof. Karl Rawer's 90th birthday. It looks back at 35 years of research and development in the framework of the International Reference Ionosphere (IRI) project. K. Rawer initiated this international modeling effort and was the first Chairman of the IRI Working Group. IRI is a joint project of the Committee on Space Research (COSPAR) and the International Union of Radio Science (URSI) whose goal it is to establish an international standard model for the ionospheric densities, temperatures and drifts. This year we are celebrating Karl Rawer's 90th birthday and also the 35-year anniversary of the IRI effort. My talk will review the close involvement of Karl Rawer in all stages of the development and improvement of this international standard from early on and his still very active participation in this effort. [ABSTRACT FROM AUTHOR]

The IRI standard model of relative ion composition assumes a constant SHAPE="SOL" ALIGN="C" STYLE="S">n(H+n(He+) ratio of 9. We study the light ion ratio with Atmosphere Explorer C (AE-C) and ACTIVE satellite data for low and high solar activity. Based on the AE-C data a model is presented that described the light ion ratio in terms of latitude for day and night conditions. [Copyright &y& Elsevier]