• Atmosphere
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• v.27 no.3
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• pp.277-290
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• 2017

Characteristics of precipitation in South Korea during the 2016 Changma period (6/18~7/30) are analyzed in great details. El $Ni{\tilde{n}}o$-induced tropical Indian Ocean (IO) basin-wide warming lasts from spring to early summer and induces the western North Pacific subtropical high (WNPSH) circulation anomaly through an equatorial Kelvin wave during the 2016 Changma period. Along the northern edge of the WNPSH, strong precipitation occurred, in particular, over eastern China and southern Japan. During the Changma period, South Korea had the near-normal mean precipitation amount (~332 mm). However, about 226 mm of rain fell in South Korea during 1 July to 6 July, which amounts to 67% of total Changma precipitation in that year. Upper-level synoptic migratory lows and low-level moisture transport played an essential role, especially from 1 July to 3 July, in triggering an abrupt development of fronts over the Korean Peninsula and the eastern continent China. The front over the eastern China migrates progressively eastward, which results in heavy rainfall over the Korean peninsula from 1 to 3 July. In contrast, from 4 to 6 July, the typhoon (NEPARTAK) affected an abrupt northward advance of the North Pacific subtropical high (NPSH). The northward extension of the NPSH strengthens the Changma front and induces the southerly flows toward the Korean peninsula, giving rise to an increase in heavy rainfall. The NEPARTAK is generated due to interaction of the Madden-Julian Oscillation (MJO), equatorial Rossby wave and Kelvin waves.

• Atmosphere
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• v.28 no.3
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• pp.263-272
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• 2018

The high-resolution ocean surface wind vector produced by scatterometer was assimilated within the Local Ensemble Transform Kalman Filter (LETKF) in Korea Institute of Atmospheric Prediction Systems (KIAPS). The Advanced Scatterometer (ASCAT) on Metop-A/B wind data was processed in the KIAPS Package for Observation Processing (KPOP), and a module capable of processing surface wind observation was implemented in the LETKF system. The LETKF data assimilation cycle for evaluating the performance improvement due to ASCAT observation was carried out for approximately 20 days from June through July 2017 when Typhoon Nepartak was present. As a result, we have found that the performance of ASCAT wind vector has a clear and beneficial effect on the data assimilation cycle. It has reduced analysis errors of wind, temperature, and humidity, as well as analysis errors of lower troposphere wind. Furthermore, by the assimilation of the ASCAT wind observation, the initial condition of the model described the typhoon structure more accurately and improved the typhoon track prediction skill. Therefore, we can expect the analysis field of LETKF will be improved if the Scatterometer wind observation is added.