• Journal of the Korean earth science society
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• v.35 no.4
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• pp.249-258
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• 2014

Despite the greenhouse gases like carbon dioxide have steadily increased in atmosphere, the overall trend of the global average surface air temperature has stalled during the last decade (2002-present). This phenomenon is often called hiatus or warming pause, which is challenging the prevailing view that anthropogenic forcing causes warming environment. Our study characterized the hiatus by analyzing the HadGEM2-AO (95 yrs) simulation data based on RCP8.5 scenario. The PC2 time series from the EOF of the zonal mean vertical ocean temperature has been defined as the index that represents the warming pause. The relationship between the hiatus, ENSO and the changes in climate system are identified by utilizing the newly defined PC2. Since the La Nina index (defined as the negative of NINO3 index) leads PC2 by about 11 months, it may be possible that the La Nina causes the warming to be interrupted. We also show that the cooling of the climate system closed tied to the heat penetration into the deep ocean, indicating the weakening the warming rate is due to the oceanic heat uptake. Finally, the global warming hiatus is characterized by the anomalous warming in Arctic region as well as the intensification of the trade wind in the equatorial Pacific.

• Atmosphere
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• v.24 no.3
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• pp.379-390
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• 2014

This study explores the long-term trends of surface air temperatures in 11 KMA stations over the period of 1960~2012. Both linear and nonlinear trends are examined for the $95^{th}$, $50^{th}$, and $5^{th}$ percentiles of daily maximum ($T_{max}$) and minimum temperatures ($T_{min}$) by using quantile regression method. It is found that in most stations linear trends of $T_{max}$ and $T_{min}$ are generally stronger in winter than in summer, and warming trend of the $5^{th}$ percentile temperature (cold extreme) is stronger than that of the $95^{th}$ percentile temperature (warm extreme) in both seasons. The nonlinear trends, which are evaluated by the second order polynomial fitting, show a strong nonlinearity in winter. Specifically, winter temperatures have increased until 2000s but slightly decreased afterward in all percentiles. This contrasts with the $95^{th}$ and $50^{th}$ percentiles of summer $T_{min}$ that show a decreasing trend until 1980s then an increasing trend. While this result is consistent with a seasonal dependence of the recent global warming hiatus, most of the nonlinear trends are statistically insignificant, making a quantitative attribution of nonlinear temperature trends challenging.

• Atmosphere
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• v.28 no.4
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• pp.415-425
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• 2018

The roles of atmospheric heating formation and distribution on the global circulation are of utmost importance, and those are directly related to not only spatial but also temporal characteristics of monsoon system. In this study, before we clarify the characteristics of apparent heat source <$Q_1$> and moisture sink <$Q_2$>, comparisons of three reanalysis datasets (NCEP2, ERA-Interim, and JRA-55) in its global or regional patterns are performed to clearly evaluate differences among datasets. Considering inter-hemispheric difference of global monsoon regions, seasonal means of June-July-August and December-January-February, which is summer (winter) and winter (summer) in the Northern (Southern) Hemisphere are employed respectively. Here we show the characteristics of eight different regional monsoon regions and find contributions of <$Q_2$> to <$Q_1$> for the regional monsoon regions. Each term in apparent heat source and moisture sink is shown to come from the ERA-Interim dataset, since the ERA-Interim could be representative of three datasets. The NCEP2 data has a different characteristic in the ratio of <$Q_2$> and <$Q_1$> because it overestimates <$Q_1$> compared to the other two different datasets. The Australia monsoon has been performing better over time, while some regional monsoons (South America, North America, and North Africa) have been showing increasing data inconsistency. In addition, the three reanalysis datasets are getting different marching with time, in particular since the early 2000s over South America, North America, and North Africa monsoon regions. The recent inconsistency among the three datasets that may be associated with the global warming hiatus remains unexplored.