• Title/Summary/Keyword: NCAR CAM

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Impact of IODM and ENSO on the East Asian Monsoon: Simulations through NCAR Community Atmospheric Model (동아시아 몬순 지역에서 IODM과 ENSO의 영향 : NCAR Community Atmospheric Model을 이용한 모의 실험)

  • Oh J.-H.;Chaudhari H. S.;Kripalani R. H.
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.7 no.4
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    • pp.240-249
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    • 2005
  • The normal Indian Ocean is characterized by warmer waters over the eastern region and cooler waters over the western region. Changes in sea surface temperature (SST) over the western and eastern Indian Ocean give birth to a phenomenon now referred to as the Indian Ocean Dipole Mode (IODM). The positive phase of this mode is characterized by positive SST anomalies over the western Indian Ocean and negative anomalies over the southeastern Indian Ocean, while the negative phase is characterized by a reversed SST anomaly pattern. On the other hand, the normal Pacific Ocean has warm (cool) waters over the western (eastern) parts. Positive (negative) SST anomalies over the central/eastern (western) Pacific Ocean characterize the E1 Nino phenomenon. The reverse situation leads to the La Nina phenomenon. The coupled ocean-atmosphere phenomenon over the Pacific is referred to as the E1 Nino Southern Oscillation (ENSO) phenomenon. In this study the impact of IODM and ENSO on the East Asian monsoon variability has been studied using observational data and using the Community Atmospheric Model (CAM) of the National Center for Atmospheric Research (NCAR). Five sets of model experiments were performed with anomalous SST patterns associated with IODM/ENSO superimposed on the climatological SSTs. The empirical and dynamic approaches reveal that it takes about 3-4 seasons fur the peak IODM mode to influence the summer monsoon activity over East Asia. On the other hand, the impact of ENSO on the East Asian monsoon could occur simultaneously. Further, the negative (positive) phase of IODM and E1 Nino (La Nina) over the Pacific enhances (suppresses) monsoon activity over the Korea-Japan Sector. Alternatively, IODM appears to have no significant impact on monsoon variability over China. However, El Nino (La Nina) suppresses (enhances) monsoon activity over China. While the IODM appears to influence the North Pacific subtropical high, ENSO appears to influence the Aleutian low over the northwest Pacific. Thus, the moisture supply towards East Asia from the Pacific is determined by the strengthening/weakening of the subtropical high and the Aleutian low.

Optimization of the Vertical Localization Scale for GPS-RO Data Assimilation within KIAPS-LETKF System (KIAPS 앙상블 자료동화 시스템을 이용한 GPS 차폐자료 연직 국지화 규모 최적화)

  • Jo, Youngsoon;Kang, Ji-Sun;Kwon, Hataek
    • Atmosphere
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    • v.25 no.3
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    • pp.529-541
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    • 2015
  • Korea Institute of Atmospheric Prediction System (KIAPS) has been developing a global numerial prediction model and data assimilation system. We has implemented LETKF (Local Ensemble Transform Kalman Filter, Hunt et al., 2007) data assimilation system to NCAR CAM-SE (National Center for Atmospheric Research Community Atmosphere Model with Spectral Element dynamical core, Dennis et al., 2012) that has cubed-sphere grid, known as the same grid system of KIAPS Integrated Model (KIM) now developing. In this study, we have assimilated Global Positioning System Radio Occultation (GPS-RO) bending angle measurements in addition to conventional data within ensemble-based data assimilation system. Before assimilating bending angle data, we performed a vertical unit conversion. The information of vertical localization for GPS-RO data is given by the unit of meter, but the vertical localization method in the LETKF system is based on pressure unit. Therefore, with a clever conversion of the vertical information, we have conducted experiments to search for the best vertical localization scale on GPS-RO data under the Observing System Simulation Experiments (OSSEs). As a result, we found the optimal setting of vertical localization for the GPS-RO bending angle data assimilation. We plan to apply the selected localization strategy to the LETKF system implemented to KIM which is expected to give better analysis of GPS-RO data assimilation due to much higher model top.