Assessing models for ionospheric weather specifications over Australia during the 2004 Climate and Weather of the Sun‐Earth‐System (CAWSES) campaign

Abstract

[1] The Utah State University (USU) Global Assimilation of Ionospheric Measurements (GAIM) program is developing assimilation models to specify ionospheric weather. In this study the Gauss Markov Kalman Filter (GMKF) GAIM model was used. The period 20 March through 19 April 2004, which spanned the Climate and Weather of the SunEarth-System (CAWSES) first study period, has been extensively studied to validate the performance of the GAIM model. Although the USU-GAIM model has both regional and global capabilities and can assimilate data from a wide variety of ionospheric observations, for this study the GMKF model was run in a global mode using data only from 162 ground-based GPS slant total electron content (TEC) stations and in situ measurements from three satellites. Using measurements from the 11 ionosonde stations of the Australian Department of Defence sounder network as an independent bottomside ground-truth, the International Reference Ionosphere (IRI), Ionospheric Forecast Model (IFM), and GMKF were compared for (1) monthly mean climatology and (2) the day-to-day weather during the 31 day period. A skill score was developed for the day-to-day weather by defining the IRI as the reference model. IFM is found to be a 10% improvement, while the GMKF is 39% more capable to capture weather variability. However, the study also identifies that this global version of GMKF has difficulty around sunrise, during which time the GMKF performance can be poorer than IRI. Excluding this interval from the skill score analysis increases the GMKF ability to track weather to 48%. The use of more data and different data types should further increase the GMKF's ability to capture weather variations.

Tomography Reconstruction of Ionospheric Electron Density with Empirical Orthonormal Functions Using Korea GNSS Network

“…in Icheon and about 1.8×10 6 cm -3 in Jeju ionosonde stations, respectively. Similar upper limit can be also found in previous studies (Sojka et al 2007;Yu et al 2013;Ratovsky et al 2015;Ratovsky et al 2017). The upper limit is obviously the limitation of the empirical model and is not realistic.…”

The PFISR IPY observations of ionospheric climate and weather

“…The long-term IPY data set could potentially become the basis for a comprehensive skill score analysis for real-time ionospheric models. Sojka et al (2007b) used 1 month of ionosonde observations in Australia to study how a skill score could be developed using ionospheric specifications generated by the USU-GAIM-Gauss Markov. Their study found that even 1 month of observations does not clearly establish the climate baseline to which weather either adds or detracts.…”

USU Gauss-Markov Model: High Resolution Regional Capability and Support for AFWA

“…Both the Gauss-Markov (GM) data assimilation model and the background Ionosphere Forecast Model (IFM) were validated using measurements from 11 ionosonde stations that are associated with the Australian Department of Defense sounder network (Sojka et al, 2006). The ionosondes provide bottomside electron density profiles that can be compared to those calculated by the two models.…”