Improved whistler inversion method for monitoring the electron density in the plasmasphere János Lichtenberger[1,2]; Dávid Koronczay [1,2]; Csaba Ferencz [1]; Péter Steinbach [3]; Mark Clilverd [4]; Craig Rodger [5]; Dmitry Sannikov [6]; and Nina Cherneva [6] [1] Department of Geophysics and Space Sciences, Eötvös University, Budapest, Hungary, [2] Geodetic and Geophysical Institute, RCAES, Sopron, Hungary, [3] MTA-ELTE Research Group for Geology, Geophysics and Space Sci., Budapest, Hungary, [4] British Antarctic Survey, Cambridge, United Kingdom, [5] Department of Physics, University of Otago, Dunedin, New Zealand, [6] Institute of Cosmophysical Research and Radio Wave Propagation, Paratunka, Russia In the PLASMON FP7-Space project (http://plasmon.elte.hu, Lichtenberger et al., 2013], a new whistler inversion algorithm [Lichtenberger, 2009] was implemented using Virtual Trace Transformation [Lichtenberger et al., 2010]. The accuracy of the parameters inverted by the algorithm – that is basically it works well – depends on their initial values, how close or how far are they from the real values. These initial values are more or less based on – sometimes ad hoc – estimations. Instead of the estimation, a new procedure has been developed based on papers of Dowden and Allcock [1971] and Park [1972], as well as on model calculation. The Virtual Trace Transformation used in the Automatic Whistler Analyzer algorithm is applied to a cleaned reassigned spectrogram and its applicability highly depends on the effectivity of the spectrogram cleaning step. A new approach has been developed for ground based whistlers based on ‘de-chirping’ [Jacobson et al., 2011] or ‘reduction-to-sferic’ method that compensates the signal phase from the time of the recording back to the sferic. The phase calculated for a frequency is based on the whistler inversion algorithm mentioned above. The result of the inversion using phase reduction is more reliable than the one obtained by VTT. This paper we present the two enhanced algorithm as well as some preliminary results based on the new methods. References: Dowden, R. L., and G. M. Allcock (1971): Determination of nose frequency of non-nose whistlers, J. Atmos. Terr. Phys., 33, 1125-1129. Jacobson, A. R., R. H. Holzworth, R. F. Pfaff, and M. P. McCarthy (2011), Study of oblique whistlers in the low-latitude ionosphere, jointly with the C/NOFS satellite and the World-Wide Lightning Location Network, Annales Geophysicae, 29, 851-863, Lichtenberger, J. (2009): A new whistler inversion method. Journal of Geophysical Research,114, A07222, doi: 10.1029/2008JA013799 Lichtenberger, J., Ferencz, Cs., Hamar, D., Steinbach, P., Rodger, C.J., Clilverd, M.A. and Collier, A.B. (2010): Automatic Whistler Detector and Analyzer system: Implementation of the analyzer algorithm. Journal of Geophysical Research 115, A12214, doi: 10.1029/2010JA015931. Lichtenberger, J., Clilverd, M.A., Heilig, B., Vellante, M., Manninen, J., Rodger, C.J., Collier, A.B., Jorgensen, A.M., Reda, J., Holzworth, R.H., Friedel, R. and Simon-Wedlund, M. (2013): The plasmasphere during a space weather event: first results from the PLASMON project. Journal of Space Weather and Space Climate, 3, A23, doi:10.1051/swsc/2013045. Park, C.G. (1972): Methods to determine electron concentration in the magnetosphere from nose whistlers, Technical report 3454-1, Radioscience Laboratory, Stanford Electronics Laboratories, Stanford University, Stanford, California..