Seon Ki Park

Gb3 accumulation reduces K(Ca)3.1 channel expression by down-regulating ERK and AP-1 and up-regulating REST and the channel activity by decreasing intracellular levels of PI(3)P. Gb3 thereby evokes K(Ca)3.1 channel dysfunction, and the channel dysfunction in vascular endothelial cells may contribute to vasculopathy in Fabry disease.

A record‐breaking heavy rainfall event, with a 24‐hr accumulated rainfall of 870.5 mm, occurred in a coastal area at the foot of a mountain range in the central‐eastern part of the Korean Peninsula during the passage of Typhoon Rusa (2002). Synoptic features of this case were investigated via high‐resolution numerical analysis and forecast fields obtained from the PSU/NCAR MM5. The main causes of this localized heavy rainfall include: 1) strong low‐level convergence of moist air from the sea int

In this study a nonhydrostatic 3D cloud model, along with an automatic differentiation tool, is used to investigate the sensitivity of a supercell storm to prescribed errors (perturbations) in the water vapor field. The evolution of individual storms is strongly influenced by these perturbations, though the specific impact depends upon their location in time and space. Generally, perturbations in the rain region above cloud base have the largest impact on storm dynamics, especially for subsequen

Abstract. This study examines the uncertainty in calculating the fundamental climatological characteristics of precipitation in the East Asia region from multiple fine-resolution gridded analysis data sets based on in situ rain gauge observations and data assimilations. Five observation-based gridded precipitation data sets are used to derive the long-term means, standard deviations in lieu of interannual variability and linear trends over the 28-year period from 1980 to 2007. Both the annual an

Abstract In the land surface models predicting vegetation growth and decay, representation of the seasonality of land surface energy and mass fluxes largely depends on how to describe the vegetation dynamics. In this study, we developed a new parameterization scheme to characterize allocation of the assimilated carbon to plant parts, including leaves and fine roots. The amount of carbon allocation in this scheme depends on the climatological net primary production (NPP) of the plants. The newly

The validity of the moist tangent linear model (TLM) derived from a time-dependent 1D Eulerian cloud model is investigated by comparing TLM solutions to differences between results from a nonlinear model identically perturbed. The TLM solutions are found to be highly sensitive to the amplitude of the applied perturbation, and thus the linear approximation is valid only for a specific range of perturbations. The TLM fails to describe the evolution of perturbations when the initial variation is gi

An automatic differentiation tool (ADIFOR) is applied to a warm-rain, time-dependent 1D cloud model to study the influence of input parameter variability, including that associated with the initial state as well as physical and computational parameters, on the dynamical evolution of a deep convective storm.

Prior literature associates CEO power with agency problems and documents the negative relationship between CEO power and firm value (e.g., Bebchuk et al. , 2011). However, the 'optimal' level of CEO power may differ for every firm and for individual CEO depending on firm and CEO characteristics. In this study, we estimate the normal ('optimal') level of CEO power and show that the association between CEO power and firm value is nonmonotonic. Our results reveal that the normal level of CEO power

Data assimilation is theoretically founded on probability, statistics, control theory, information theory, linear algebra, and functional analysis. At the same time, data assimilation is a very practical subject, given its goal of estimating the posterior probability density function in realistic high-dimensional applications. This puts data assimilation at the intersection between the contrasting requirements of theory and practice. Based on over twenty years of teaching courses in data assimil

This study aims to enhance the accuracy of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) in forecasting Asian dust storms (ADSs) by using the micro-Genetic Algorithm (μGA). We developed an optimization system---the WRF-Chem-μGA system---to seek the optimal combination of the planetary boundary layer (PBL) and land surface parameterization schemes, which are crucial for numerical forecast of dust storms. The optimization was conducted concerning meteorological and a