@Article{GalkinFRHKNBKFLWDGB:2022:GlMoIo,
               author = "Galkin, Ivan and Fr{\'o}n, Adam and Reinisch, Bodo and 
                         Hern{\'a}ndez-Pajares, Manuel and Krankowski, Andrzej and Nava, 
                         Bruno and Bilitza, Dieter and Kotulak, Kacper and Flisek, Pawel 
                         and Liz, Zishen and Wang, Ningbo and Dollase, David Roma and 
                         Garc{\'{\i}}a-Rigo, Alberto and Batista, Inez Staciarini",
          affiliation = "{University of Massachusetts Lowell} and {University of Warmia and 
                         Mazury in Olsztyn} and {Lowell Digisonde International} and 
                         {Universitat Polit{\`e}cnica de Catalunya} and {University of 
                         Warmia and Mazury in Olsztyn} and {The Abdus Salam International 
                         Centre for Theoretical Physics} and {George Mason University} and 
                         {University of Warmia and Mazury in Olsztyn} and {University of 
                         Warmia and Mazury in Olsztyn} and {Chinese Academy of Sciences 
                         (CAS)} and {Chinese Academy of Sciences (CAS)} and {Universitat 
                         Polit{\`e}cnica de Catalunya} and {Universitat Polit{\`e}cnica 
                         de Catalunya} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)}",
                title = "Global Monitoring of Ionospheric Weather by GIRO and GNSS Data 
                         Fusion",
              journal = "Atmosphere",
                 year = "2022",
               volume = "13",
               number = "3",
                pages = "e371",
                month = "Mar.",
             keywords = "GIRO, GNSS, Ionosonde, Ionospheric weather.",
             abstract = "Prompt and accurate imaging of the ionosphere is essential to 
                         space weather services, given a broad spectrum of applications 
                         that rely on ionospherically propagating radio signals. As the 3D 
                         spatial extent of the ionosphere is vast and covered only 
                         fragmentarily, data fusion is a strong candidate for solving 
                         imaging tasks. Data fusion has been used to blend models and 
                         observations for the integrated and consistent views of 
                         geosystems. In space weather scenarios, low latency of the sensor 
                         data availability is one of the strongest requirements that limits 
                         the selection of potential datasets for fusion. Since remote 
                         plasma sensing instrumentation for ionospheric weather is complex, 
                         scarce, and prone to unavoidable data noise, conventional 3D-var 
                         assimilative schemas are not optimal. We describe a novel 
                         substantially 4D data fusion service based on near-real-time data 
                         feeds from Global Ionosphere Radio Observatory (GIRO) and Global 
                         Navigation Satellite System (GNSS) called GAMBIT (Global 
                         Assimilative Model of the Bottomside Ionosphere with Topside 
                         estimate). GAMBIT operates with a few-minute latency, and it 
                         releases, among other data products, the anomaly maps of the 
                         effective slab thickness (EST) obtained by fusing GIRO and GNSS 
                         data. The anomaly EST mapping aids understanding of the vertical 
                         plasma restructuring during disturbed conditions.",
                  doi = "10.3390/atmos13030371",
                  url = "http://dx.doi.org/10.3390/atmos13030371",
                 issn = "2073-4433",
             language = "en",
           targetfile = "galkin_2022.pdf",
        urlaccessdate = "25 jun. 2024"
}