• Title/Summary/Keyword: meteorological instrument

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Intercomparing the Aerosol Optical Depth Using the Geostationary Satellite Sensors (AHI, GOCI and MI) from Yonsei AErosol Retrieval (YAER) Algorithm (연세에어로졸 알고리즘을 이용하여 정지궤도위성 센서(AHI, GOCI, MI)로부터 산출된 에어로졸 광학두께 비교 연구)

  • Lim, Hyunkwang;Choi, Myungje;Kim, Mijin;Kim, Jhoon;Go, Sujung;Lee, Seoyoung
    • Journal of the Korean earth science society
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    • v.39 no.2
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    • pp.119-130
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    • 2018
  • Aerosol Optical Properties (AOPs) are retrieved using the geostationary satellite instruments such as Geostationary Ocean Color Imager (GOCI), Meteorological Imager (MI), and Advanced Himawari Imager (AHI) through Yonsei AErosol Retrieval algorithm (YAER). In this study, the retrieved aerosol optical depths (AOD)s from each instrument were intercompared and validated with the ground-based sunphotometer AErosol Robotic NETwork (AERONET) data. As a result, the four AOD products derived from different instruments showed consistent results over land and ocean. However, AODs from MI and GOCI tend to be overestimated due to cloud contamination. According to the comparison results with AERONET, the percentage within expected errors (EE) are 36.3, 48.4, 56.6, and 68.2% for MI, GOCI, AHI-minimum reflectivity method (MRM), and AHI-estimated surface reflectance from shortwave Infrared (ESR) product, respectively. Since MI AOD is retrieved from a single visible channel, and adopts only one aerosol type by season, EE is relatively lower than other products. On the other hand, the AHI ESR is more accurate than the minimum reflectance method as used by GOCI, MI, and AHI MRM method in May and June when the vegetation is relatively abundant. These results are explained by the RMSE and the EE for each AERONET site. The ESR method result show to be better than the other satellite product in terms of EE for 15 out of 22 sites used for validation, and they are better than the other product for 13 sites in terms of RMSE. In addition, the error in observation time in each product is found by using characteristics of geostationary satellites. The absolute median biases at 00 to 06 Universal Time Coordinated (UTC) are 0.05, 0.09, 0.18, 0.18, 0.14, 0.09, and 0.10. The absolute median bias by observation time has appeared in MI and the only 00 UTC appeared in GOCI.

The Variations of Stratospheric Ozone over the Korean Peninsula 1985~2009 (한반도 상공의 오존층 변화 1985~2009)

  • Park, Sang Seo;Kim, Jhoon;Cho, Nayeong;Lee, Yun Gon;Cho, Hi Ku
    • Atmosphere
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    • v.21 no.4
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    • pp.349-359
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    • 2011
  • The climatology in stratospheric ozone over the Korean Peninsula, presented in previous studies (e.g., Cho et al., 2003; Kim et al., 2005), is updated by using daily and monthly data from satellite and ground-based data through December 2009. In addition, long-term satellite data [Total Ozone Mapping Spectrometer (TOMS), Ozone Monitoring Instrument (OMI), 1979~2009] have been also analyzed in order to deduce the spatial distributions and temporal variations of the global total ozone. The global average of total ozone (1979~2009) is 298 DU which shows a minimum of about 244 DU in equatorial latitudes and increases poleward in both hemispheres to a maximum of about 391 DU in Okhotsk region. The recent period, from 2006 to 2009, shows reduction in total ozone by 6% relative to the values for the pre-1980s (1979~1982). The long-term trends were estimated by using a multiple linear regression model (e.g., WMO, 1999; Cho et al., 2003) including explanatory variables for the seasonal variation, Quasi-Biennial Oscillation (QBO) and solar cycle over three different time intervals: a whole interval from 1979 to 2009, the former interval from 1979 to 1992, and the later interval from 1993 to 2009 with a turnaround point of deep minimum in 1993 is related to the effect of Mt. Pinatubo eruption. The global trend shows -0.93% $decade^{-1}$ for the whole interval, whereas the former and the later interval trends amount to -2.59% $decade^{-1}$ and +0.95% $decade^{-1}$, respectively. Therefore, the long-term total ozone variations indicate that there are positive trends showing a recovery sign of the ozone layer in both North/South hemispheres since around 1993. Annual mean total ozone (1985~2009) is distributed from 298 DU for Jeju ($33.52^{\circ}N$) to 352 DU for Unggi ($42.32^{\circ}N$) in almost zonally symmetric pattern over the Korean Peninsula, with the latitudinal gradient of 6 DU $degree^{-1}$. It is apparent that seasonal variability of total ozone increases from Jeju toward Unggi. The annual mean total ozone for Seoul shows 323 DU, with the maximum of 359 DU in March and the minimum of 291 DU in October. It is found that the day to day variability in total ozone exhibits annual mean of 5.7% in increase and -5.2% in decrease. The variability as large as 38.4% in increase and 30.3% in decrease has been observed, respectively. The long-term trend analysis (e.g., WMO, 1999) of monthly total ozone data (1985~2009) merged by satellite and ground-based measurements over the Korean Peninsula shows increase of 1.27% $decade^{-1}$ to 0.80% $decade^{-1}$ from Jeju to Unggi, respectively, showing systematic decrease of the trend magnitude with latitude. This study also presents a new analysis of ozone density and trends in the vertical distribution of ozone for Seoul with data up to the end of 2009. The mean vertical distributions of ozone show that the maximum value of the ozone density is 16.5 DU $km^{-1}$ in the middle stratospheric layer between 24 km and 28 km. About 90.0% and 71.5% of total ozone are found in the troposphere and in the stratosphere between 15 and 33 km, respectively. The trend analysis reconfirms the previous results of significant positive ozone trend, of up to 5% $decade^{-1}$, in the troposphere and the lower stratosphere (0~24 km), with negative trend, of up to -5% $decade^{-1}$, in the stratosphere (24~38 km). In addition, the Umkehr data show a positive trend of about 3% $decade^{-1}$ in the upper stratosphere (38~48 km).

Measurement and Quality Control of MIROS Wave Radar Data at Dokdo (독도 MIROS Wave Radar를 이용한 파랑관측 및 품질관리)

  • Jun, Hyunjung;Min, Yongchim;Jeong, Jin-Yong;Do, Kideok
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.32 no.2
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    • pp.135-145
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    • 2020
  • Wave observation is widely used to direct observation method for observing the water surface elevation using wave buoy or pressure gauge and remote-sensing wave observation method. The wave buoy and pressure gauge can produce high-quality wave data but have disadvantages of the high risk of damage and loss of the instrument, and high maintenance cost in the offshore area. On the other hand, remote observation method such as radar is easy to maintain by installing the equipment on the land, but the accuracy is somewhat lower than the direct observation method. This study investigates the data quality of MIROS Wave and Current Radar (MWR) installed at Dokdo and improve the data quality of remote wave observation data using the wave buoy (CWB) observation data operated by the Korea Meteorological Administration. We applied and developed the three types of wave data quality control; 1) the combined use (Optimal Filter) of the filter designed by MIROS (Reduce Noise Frequency, Phillips Check, Energy Level Check), 2) Spike Test Algorithm (Spike Test) developed by OOI (Ocean Observatories Initiative) and 3) a new filter (H-Ts QC) using the significant wave height-period relationship. As a result, the wave observation data of MWR using three quality control have some reliability about the significant wave height. On the other hand, there are still some errors in the significant wave period, so improvements are required. Also, since the wave observation data of MWR is different somewhat from the CWB data in high waves of over 3 m, further research such as collection and analysis of long-term remote wave observation data and filter development is necessary.