Shinji Kadokura

Anomalous Weather Patterns in Relation to Heavy Precipitation Events in Japan during the Baiu Season

AbstractAnomalous weather patterns (WPs) in relation to heavy precipitation events during the baiu season in Japan are investigated using a nonlinear classification technique known as the self-organizing map (SOM). The analysis is performed on daily time scales using the Japanese 55-year Reanalysis Project (JRA-55) to determine the role of circulation and atmospheric moisture on extreme events and to investigate interannual and interdecadal variations for possible linkages with global-scale climate variability. SOM is simultaneously employed on four atmospheric variables over East Asia that are related to baiu front variability, whereby anomalous WPs that dominated during the 1958–2011 period are obtained. Our analysis extracts seven typical WPs, which are linked to frequent occurrences of heavy precipitation events. Each WP is associated with regional variations in the probability of extreme precipitation events. On interannual time scales, El Nino–Southern Oscillation (ENSO) affects the frequency of the...

Radiometric calibration for the airborne interferometric monitor for greenhouse gases simulator

The Advanced Earth Observation Satellite (ADEOS), launched in the summer of 1996, has a high-resolution infrared Fourier transform spectrometer, with the interferometric monitor for greenhouse gases (IMG) onboard. The IMG has a high spectral resolution of 0.1 cm(-1) for the purpose of retrieving greenhouse gas profile maps of the Earth. To meet the requirements of the retrieval algorithms for greenhouse gas profiles, atmospheric emission spectra must be calibrated to better than 1 K accuracy. Prior to the launch of the ADEOS with the IMG, we developed an airborne simulator called the tropospheric infrared interferometric sounder (TIIS). We explain the calibration procedure for the TIIS, which determines the points with the same optical path difference on interferograms for complex Fourier transformation, using the retained phase term on the calibrated spectrum. The downward atmospheric radiation, measured with the TIIS, was well calibrated using this algorithm. Furthermore, calibration of the spectra obtained from the IMG initial checkout mission observation was carried out.

Rainfall downscaling of weekly ensemble forecasts using self-organising maps

This study presents an application of self-organising maps (SOMs) to downscaling medium-range ensemble forecasts and probabilistic prediction of local precipitation in Japan. SOM was applied to analyse and connect the relationship between atmospheric patterns over Japan and local high-resolution precipitation data. Multiple SOM was simultaneously employed on four variables derived from the JRA-55 reanalysis over the area of study (south-western Japan), and a two-dimensional lattice of weather patterns (WPs) was obtained. Weekly ensemble forecasts can be downscaled to local precipitation using the obtained multiple SOM. The downscaled precipitation is derived by the five SOM lattices based on the WPs of the global model ensemble forecasts for a particular day in 2009–2011. Because this method effectively handles the stochastic uncertainties from the large number of ensemble members, a probabilistic local precipitation is easily and quickly obtained from the ensemble forecasts. This downscaling of ensemble forecasts provides results better than those from a 20-km global spectral model (i.e. capturing the relatively detailed precipitation distribution over the region). To capture the effect of the detailed pattern differences in each SOM node, a statistical model is additionally concreted for each SOM node. The predictability skill of the ensemble forecasts is significantly improved under the neural network-statistics hybrid-downscaling technique, which then brings a much better skill score than the traditional method. It is expected that the results of this study will provide better guidance to the user community and contribute to the future development of dam-management models.

IMG: precursor of the high-resolution FTIR on the satellite

The Interferometric Monitor for Greenhouse gases (IMG) was the precursor of the high-resolution sensor of Fourier transform infrared spectroscopy (FTIR) boarded on the satellite for Earth observation. The IMG was boarded on the Advanced Earth Observing Satellite (ADEOS) launched by the National Space Development Agency of Japan (NASDA) on Aug. 17, 1996. The IMG sensor operated for only 8 months, however, the obtained high-resolution thermal infrared spectra provided abundant information on global atmospheric phenomena, and the first global maps of greenhouse gases were retrieved from these spectra.

The first view of the global map of greenhouse gases by the interferometric monitor for greenhouse gases (IMG)

Abstract The interferometric monitor for greenhouse gases (IMG), was the precursor for the high resolution FTIR boarded on the satellite for Earth observation. The IMG sensor was able to obtain only 8 months of radiation spectra, however, the retrieved greenhouse gases global maps have certified that the high resolution spectrometer in the space is a very effective tool for the atmospheric science.