Abstract. The VHF electromagnetic noise intensity data at several stations in the Tohoku area of Japan during the period of a rather large (with magnitude of 7.2) earthquake (Miyagi-ken oki earthquake) taken place on 16 August 2005, are analyzed by means of different fractal analysis methods, including (1) spectral slope estimation, (2) multi-fractal detrended fluctuation analysis and (3) multi-fractal wavelet transform modulus maxima method. It seems to the authors that there is no definite analysis method for the analysis of any seismogenic phenomenon, so that the only way we have to take, is to apply different methods to the same data for the detailed comparison of the results. This comparison enables us to deduce the properties commonly observed by the above methods. Because the most important feature common to these three methods, is that significant changes in fractal scaling characteristics are observed just during the earthquake (mainly before the earthquake) only at one station of Kunimi. Finally, we can come to the definite conclusion on the self-organization of VHF emissions only at one station in the present case.
Uncertainty in ocean analysis methods and deficiencies in the observing system are major obstacles for the reliable reconstruction of the past ocean climate. The variety of existing ocean reanalyses is exploited in a multi-reanalysis ensemble to improve the ocean state estimation and to gauge uncertainty levels. The ensemble-based analysis of signal-to-noise ratio allows the identification of ocean characteristics for which the estimation is robust (such as tropical mixed-layer-depth,upper ocean heat content), and where large uncertainty exists (deep ocean, Southern Ocean, sea-ice thickness, salinity), providing guidance for future enhancement of the observing and data assimilation systems. ; This work has been partially funded by the European Commission funded projects MyOcean, MyOcean2 and COMBINE; by the GEMINA project-funded bythe Italian Ministry for Environment; by the NERC-funded VALOR project; by the NERC-funded NCEO program; by the Research Program on Climate Change adaptation of the Ministry of Education, Culture, Sports, Science and Technology of the Japanese government; by the Joint UK DECC/Defra Met Office Hadley Centre Climate Programme (GA01101); by NASA's Modeling Analysis and Prediction Program under WBS 802678.02.17.01.25 and by the NASA Physical Oceanography Program; by the NOAA's Climate Observation Division (COD); by the LEFE/GMMC French national program. ; Published ; s80-s97 ; 4A. Clima e Oceani ; JCR Journal ; open