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South-Coast Cyclone in Japan During El Niño-Caused Warm Winters
Hiroaki Ueda,Yuusuke Amagai,Masamitsu Hayasaki 한국기상학회 2017 Asia-Pacific Journal of Atmospheric Sciences Vol.53 No.2
La Niña conditions during boreal winter sometimes brings excessive snowfall in Japan, especially on the East Sea/Sea of Japan coastal and mountain areas through intensified northwesterly cold winds caused by La-Niña related atmospheric teleconnection. Meanwhile, snowfall events also increase in the Pacific coast area of Japan during the El Niño state due to extratropical cyclones passing along the south coast of Japan (hereafter referred to as South-coast cyclone). In the present study, we investigated year-to-year snowfall/ rainfall variations based on meteorological station data and cyclone tracks identified by using the Japanese 55-year Reanalysis. The result clearly indicates increase of the South-coast cyclone during El Niño-developing winters, which is consistent with excessive snowfall in the northern part of the Pacific coast. Strong subtropical jet hampers cyclogenesis due to less vertical interaction through the trapping of upper-level eddies. During El Niño-developing winters, the subtropical jet is weakened over East Asia, indicating dynamic linkage to increased cyclone frequency. In addition to this, both the deepening of the upper-tropospheric trough over East Asia and anomalous low-tropospheric northwest anticyclones extending from the Philippines toward Japan are also consistent with the enhancement of cyclogenesis over the East China Sea as well as warm winter in Japan.
Aerosol model evaluation using two geostationary satellites over East Asia in May 2016
Goto, Daisuke,Kikuchi, Maki,Suzuki, Kentaroh,Hayasaki, Masamitsu,Yoshida, Mayumi,Nagao, Takashi M.,Choi, Myungje,Kim, Jhoon,Sugimoto, Nobuo,Shimizu, Atsushi,Oikawa, Eiji,Nakajima, Teruyuki Elsevier 2019 Atmospheric research Vol.217 No.-
<P><B>Abstract</B></P> <P>This study newly applies measurements from two geostationary satellites, the Advanced Himawari Imager (AHI) onboard the geostationary satellite Himawari-8 and the Geostationary Ocean Color imager (GOCI) onboard the geostationary satellite COMS, to evaluate a unique regional aerosol-transport model coupled to a non-hydrostatic icosahedral atmospheric model (NICAM) at a high resolution without any nesting technique and boundary conditions of the aerosols. Taking advantage of the unique capability of these geostationary satellites to measure aerosols with unprecedentedly high temporal resolution, we focus on a target area (115°E-155°E, 20°N-50°N) in East Asia in May 2016, which featured the periodic transport of industrial aerosols and a very heavy aerosol plume from Siberian wildfires. The aerosol optical thickness (AOT) fields are compared among the AHI, GOCI, MODIS, AERONET and NICAM data. The results show that both AHI- and GOCI-retrieved AOTs were generally comparable to the AERONET-retrieved ones, with high correlation coefficients of approximately 0.7 in May 2016. They also show that NICAM successfully captured the detailed horizontal distribution of AOT transported from Siberia to Japan on the most polluted day (18 May 2016). The monthly statistical metrics, including correlation between the model and either AHI or GOCI, are estimated to be >0.4 in 42–49% of the target area. With the aid of sensitivity model experiments with and without Siberian wildfires, it was found that a long-range transport of aerosols from Siberian wildfires (from as far as 3000 km) to Japan influenced the monthly mean aerosol levels, accounting for 7–35% of the AOT, 26–49% of the surface PM2.5 concentrations, and 25–66% of the aerosol extinction above 3 km in height over Japan. Therefore, the air pollutants from Siberian wildfire cannot be ignored for the spring over Japan.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A high resolution model generally produces an observed aerosol distribution. </LI> <LI> Next-generation geostationary satellites are applied for aerosol model evaluation. </LI> <LI> Multiple measurement helped to understand the 4-dimensional aerosol structure. </LI> <LI> Siberian wildfires strongly affected the aerosol levels over Japan in May 2016. </LI> </UL> </P>