Seoul National University · 環境科学
Professor Kwang-Yul Kim's research lab specializes in atmospheric and climate sciences, with a focus on understanding large-scale climate variability, Arctic amplification, and air quality dynamics. The lab employs advanced statistical and dynamical methods—particularly cyclostationary empirical orthogonal function (CSEOF) analysis—to investigate seasonal and interannual variations in meteorological systems such as the Asian monsoon, the western North Pacific subtropical high, and Arctic sea ice loss. Research also emphasizes the physical mechanisms linking climate change, sea ice reduction, and atmospheric heat fluxes, as well as the impacts of human activities on urban air pollution. The lab integrates reanalysis data and long-term observational records to uncover climate-weather-air quality linkages in East Asia and the Arctic.
Figures are computed from collected data and may differ slightly.
Natural variability is an essential component of observations of all geophysical and climate variables. In principal component analysis (PCA), also called empirical orthogonal function (EOF) analysis, a set of orthogonal eigenfunctions is found from a spatial covariance function. These empirical basis functions often lend useful insights into physical processes in the data and serve as a useful tool for developing statistical methods. The underlying assumption in PCA is the stationarity of the d
Variation of the western North Pacific subtropical high (WNPSH) is an important meteorological factor for determining summertime rainfall and temperature over East Asia. Here, three major modes of summertime WNPSH variability are identified and corresponding environmental changes are investigated using cyclostationary empirical orthogonal function analysis. The leading mode exhibits a clear reinforcement of WNPSH associated with global warming. The second and third modes are characterized by int
Sea ice reduction is accelerating in the Barents and Kara Seas. Several mechanisms are proposed to explain the accelerated loss of Arctic sea ice, which remains to be controversial. In the present study, detailed physical mechanism of sea ice reduction in winter (December-February) is identified from the daily ERA interim reanalysis data. Downward longwave radiation is an essential element for sea ice reduction, but can primarily be sustained by excessive upward heat flux from the sea surface ex
The principal mode of the seasonal variation of the Asian summer monsoon (ASM) and the temporal and spatial evolution of the corresponding synoptic fields are investigated via cyclostationary EOF analysis. This study uses the 21-yr (1979-99) Xie-Arkin precipitation pentad data and National Centers for Environmental Prediction daily reanalysis data focusing on the period 21 May to 28 August, which covers the prominent life cycle of the ASM. The first mode, representing the seasonal cycle, explain
In this study, the CSEOF technique is used to investigate the physical and chemical mechanisms associated with the weekly PM<sub>10</sub> variation in South Korea. For this end, 9 years of hourly measurements of PM<sub>10</sub> in South Korea is used together with other gaseous contaminants (NO<sub>2</sub>, SO<sub>2</sub>, CO and O<sub>3</sub>) and traffic counts at the toll gates. The diurnal variation of PM<sub>10</sub> concentrations indicates a significant correlation with human activities;
This paper considers the geographical distribution of various second moment statistics from a noise‐forced energy balance climate model and compares them to the same fields derived from a 40‐year data set. The variable considered is the surface temperature field over the Earth. The energy balance model is a standardized one used in several previous studies which emphasized the geographical distribution of the seasonal cycle. It treats two‐dimensional geography explicitly by using a different (un
Human activities have been suggested to result in weekly changes of meteorological variables, called the “weekend effect.” Recent debates on its statistical significance, however, reveal that there still remain huge uncertainties as to the anthropogenic origin of the weekend effect. We show that atmospheric Rossby waves induce the “natural” weekend effect, which is much stronger than the “anthropogenic” weekend effect. The “natural” weekend effect does not completely disappear even with averagin
Simple one‐dimensional ocean models have been used to make projections of future temperature trends due to a greenhouse warming, aerosols, or emission reduction. This paper considers the seasonal cycle and the second‐moment statistics of a two‐dimensional energy balance model with a deep ocean. The surface component, a typical surface energy balance model including the ocean mixed layer, is coupled to an infinite‐depth ocean which is characterized by uniform vertical diffusion and upwelling. The
Climate change in the Southern Hemisphere has exerted impact on the primary production in the Southern Ocean (SO). Using a recently released reanalysis dataset on global biogeochemistry, a comprehensive analysis was conducted on the complex biogeochemical seasonal cycle and the impact of climate change with a focus in areas within the meridional excursion of the sea ice boundary-coastal and continental shelf zone (CCSZ) and seasonal sea ice zone (SIZ). The seasonal cycles of primary production a
Despite the on-going global warming, recent winters in Eurasian mid-latitudes were much colder than average. In an attempt to better understand the physical characteristics for cold Eurasian winters, major sources of variability in surface air temperature (SAT) are investigated based on cyclostationary EOF analysis. The two leading modes of SAT variability represent the effect of Arctic amplification (AA) and the Arctic oscillation (AO), respectively. These two modes are distinct in terms of the
Abstract The first three principal modes of wintertime surface temperature variability in Seoul, South Korea (37.33°N, 126.59°E), are extracted from the 1979–2008 observed records via cyclostationary EOF (CSEOF) analysis. The first mode represents the seasonal cycle, the principle physical mechanism of which is associated with the continent–ocean sea level pressure contrast. The second mode mainly describes the overall wintertime warming or cooling. The third mode depicts subseasonal fluctuation
Extensive studies claimed that the central equatorial Pacific (CP) El Niño has occurred more frequently and strongly than the eastern equatorial Pacific El Niño in recent years. To explain this phenomenon, spatial patterns and principal component time series from several sea surface temperature (SST) data sets in the tropical Pacific are analyzed for the period of 1951–2010. Cyclostationary empirical orthogonal function analysis separates two modes of SST variability, which explain about 50% and
This paper presents quasi‐analytical solutions to a class of coupled atmosphere‐ocean models for time‐dependent ramp‐ and step‐forced climate changes. The model consists of a conventional two‐dimensional energy balance model of the atmosphere with an oceanic mixed layer coupled to a deep ocean having vertical heat transports due to horizontally uniform vertical diffusion and upwelling. The solution is partitioned into the particular or asymptotic part and the homogeneous or transient part. This
The structures of the two principal modes of sea surface temperature (SST) variability were extracted by conducting cyclostationary EOF (CSEOF) analysis and regression analysis on several key variables. The CSEOF analysis extracts two dominant modes of SST variability that are distinct in nature. The first CSEOF is stochastic in nature and represents a standing mode of SST variability associated with a basinwide change in the surface wind. The second CSEOF exhibits a strong deterministic compone
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