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Jin Ho Yoo
,
Andrew W. Robertson
, and
In-Sik Kang

Abstract

Intraseasonal and interannual variability of Asian summer monsoon rainfall in pentad precipitation data is examined using a hidden Markov model (HMM). The spatial patterns of discrete rainfall states derived with the HMM and the associated transition probabilities between the states are shown to represent well the principal Asian summer monsoon intraseasonal oscillation (ISO), propagating eastward and northward with a period of 40–50 days. Stochastic simulations made with the HMM reasonably reproduce the canonical ISO propagation and its observed statistics such as the frequency of ISO events.

The interannual modulation of the ISO associated with El Niño–Southern Oscillation (ENSO) is assessed by employing a nonhomogeneous HMM (NHMM) with summer-mean Niño-3.4 index prescribed as an input variable. ENSO influence on the ISO is found to manifest as preferences toward particular ISO phases depending on the ENSO condition, thus adding an asymmetry to the ISO. In the presence of seasonal mean anomalies, it is shown that the El Niño seasonal mean rainfall anomaly pattern is identified by the HMM as a distinct state, in addition to the ISO states, whereas the La Niña seasonal mean rainfall anomaly pattern does not appear distinct from the ISO states.

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Young-Mi Min
,
Suryun Ham
,
Jin-Ho Yoo
, and
Su-Hee Han
Free access
Hye-Mi Kim
,
Myong-In Lee
,
Peter J. Webster
,
Dongmin Kim
, and
Jin Ho Yoo

Abstract

The relationship between El Niño–Southern Oscillation (ENSO) and tropical storm (TS) activity over the western North Pacific Ocean is examined for the period from 1981 to 2010. In El Niño years, TS genesis locations are generally shifted to the southeast relative to normal years and the passages of TSs tend to recurve to the northeast. TSs of greater duration and more intensity during an El Niño summer induce an increase of the accumulated tropical cyclone kinetic energy (ACE). Based on the strong relationship between the TS properties and ENSO, a probabilistic prediction for seasonal ACE is investigated using a hybrid dynamical–statistical model. A statistical relationship is developed between the observed ACE and large-scale variables taken from the ECMWF seasonal forecast system 4 hindcasts. The ACE correlates positively with the SST anomaly over the central to eastern Pacific and negatively with the vertical wind shear near the date line. The vertical wind shear anomalies over the central and western Pacific are selected as predictors based on sensitivity tests of ACE predictive skill. The hybrid model performs quite well in forecasting seasonal ACE with a correlation coefficient between the observed and predicted ACE at 0.80 over the 30-yr period. A relative operating characteristic analysis also indicates that the ensembles have significant probabilistic skill for both the above-normal and below-normal categories. By comparing the ACE prediction over the period from 2003 to 2011, the hybrid model appears more skillful than the forecast from the Tropical Storm Risk consortium.

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Changhyun Yoo
,
Sungsu Park
,
Daehyun Kim
,
Jin-Ho Yoon
, and
Hye-Mi Kim

Abstract

The Madden–Julian oscillation (MJO), the dominant mode of tropical intraseasonal variability, influences weather and climate in the extratropics through atmospheric teleconnection. In this study, two simulations using the Community Atmosphere Model version 5 (CAM5)—one with the default shallow and deep convection schemes and the other with the unified convection scheme (UNICON)—are employed to examine the impacts of cumulus parameterizations on the simulation of the boreal wintertime MJO teleconnection in the Northern Hemisphere. It is demonstrated that the UNICON substantially improves the MJO teleconnection. When the UNICON is employed, the simulated circulation anomalies associated with the MJO better resemble the observed counterpart, compared to the simulation with the default convection schemes. Quantitatively, the pattern correlation for the 300-hPa geopotential height anomalies between the simulations and observation increases from 0.07 for the default schemes to 0.54 for the UNICON. These circulation anomalies associated with the MJO further help to enhance the surface air temperature and precipitation anomalies over North America, although room for improvement is still evident. Initial value calculations suggest that the realistic MJO teleconnection with the UNICON is not due to the changes in the background wind, but rather primarily to the improved tropical convective heating associated with the MJO.

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Soo-Jin Sohn
,
WonMoo Kim
,
Jin Ho Yoo
,
Yun-Young Lee
,
Sang Myeong Oh
,
Bo Ra Kim
,
Hyunrok Lee
,
Sangcheol Kim
,
Sunny Seuseu
, and
Netatua Pelesikoti

Abstract

Seasonal prediction provides critical information for the tropical Pacific region, where the economy and livelihood is highly dependent on climate variability. While the highest skills of dynamical prediction systems are usually found in the tropical Pacific, National Hydrological and Meteorological Services (NHMS) in the Pacific Islands Countries (PICs) do not take full advantage of such scientific achievements. The Republic of Korea-Pacific Islands Climate Prediction Services (ROK-PI CliPS) project aims to help PICs produce regionally tailored climate prediction information using a dynamical seasonal prediction system. The project is being jointly implemented by the APEC Climate Center (APCC) and the Secretariat of the Pacific Regional Environment Programme (SPREP), in close collaboration with NHMSs in PICs. The regionally tailored, dynamical-statistical hybrid climate prediction system uses predictors that were identified through communications with NHMSs. The predictors were selected based on the empirical physical relationship of the local climate fluctuations, indicated by multi-institutional and multimodel ensembles. This hybrid system makes full use of dynamical seasonal predictions, which have not been commonly utilized in current operation in PICs. In accordance with system development, additional efforts have been made for PIC NHMSs to build capacity by increasing their knowledge and skill needed to develop such methodologies and systems. Nonetheless, the successive and strategic efforts to sustain and further improve climate predictions in the Pacific Islands region are required.

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