Seon Ki Park

Systematic Variation of Summertime Tropical Cyclone Activity in the Western North Pacific in Relation to the Madden–Julian Oscillation

Abstract The variability of observed tropical cyclone (TC) activity (i.e., genesis, track, and landfall) in the western North Pacific (WNP) is examined in relation to the various categories of the Madden–Julian oscillation (MJO) during summer (June–September) for the period 1979–2004. The MJO categories are defined based on the empirical orthogonal function analysis of outgoing longwave radiation data. The number of TCs increases when the MJO-related convection center is located in the WNP. The axis of a preferable genesis region systematically shifts like a seesaw in response to changes in the large-scale environments associated with both the eastward and northward propagation of the MJO and the intraseasonal variability of the WNP subtropical high. Furthermore, the authors show that the density of TC tracks in each MJO category depends on the systematic shift in the main genesis regions at first order. Also, the shift is affected by the prevailing large-scale steering flows in each MJO category. When th...

Dipole Structure of Interannual Variations in Summertime Tropical Cyclone Activity over East Asia

Abstract The present study examines variations in summertime (July–September) tropical cyclone (TC) activity over East Asia during the period 1951–2003. To represent TC activity, a total of 853 TC best tracks for the period were converted to TC passage frequencies (TPFs) within 5° × 5° latitude–longitude grids; TPFs are defined as the percentage values obtained by dividing the number of TC appearances in each grid box by the total number of TCs each year. Empirical orthogonal function analysis of the TPF showed three leading modes: two tropical modes that represent the long-term trend and the relationship with ENSO and one midlatitude mode that oscillates between south of Korea and southeast of Japan with an interannual time scale. The latter proved to be the most remarkable climatic fluctuation of summertime TC activity in the midlatitudes and is referred to as the East Asian dipole pattern (EADP) in this paper. Anomalous atmospheric flows directly connected to the EADP are an enhanced anticyclonic (cycl...

Nonlinearity and predictability of convective rainfall associated with water vapor perturbations in a numerically simulated storm

Predictability of convective rainfall in a numerically simulated storm is assessed in conjunction with nonlinearity imposed by systematic perturbations in water vapor using a three-dimensional cloud model (ARPS). Nonlinearity is explicitly quantified using the tangent linear approximation, and predictability is measured by the noise-to-signal ratio. It is found that the behavior of nonlinearity at an early period of error insertion exerts strong influence on error dynamics and predictability in the future. The rate of increase in nonlinearity is larger for perturbations with larger magnitude and positive direction. Although dynamics of individual storms are sensitive to specified perturbations, the predictability limits generally go beyond 140 min after perturbations are introduced. The major contribution to the total error in the domain-integrated accumulated rainfall fields comes from the phase error rather than the amplitude error, especially under the region of secondary storms. The location and general behavior of the main storm (supercell) is predictable in a longer timescale than suggested by Lorenzs theoretical analysis. On the basis of the results from this study, some implications for practical storm-scale predictability are discussed.

Soil Surface Energy and Water Budgets during a Monsoon Season in Korea

Abstract In this study, attention has been focused on the climatology of some variables linked to the turbulent exchanges of heat and water vapor in the surface layer during a summer monsoon in Korea. In particular, the turbulent fluxes of sensible and latent heat, the hydrologic budget, and the soil temperatures and moistures have been analyzed. At large scale, because the measurements of those data are not only fragmentary and exiguously available but also infeasible for the execution of climatologic analyses, the outputs of a land surface scheme have been used as surrogate of observations to analyze surface layer processes [this idea is based on the methodology Climatology of Parameters at the Surface (CLIPS)] in the Korean monsoonal climate. Analyses have been made for the summer of 2005. As a land surface scheme, the land surface process model (LSPM) developed at the University of Torino, Italy, has been employed, along with the data collected from 635 Korean meteorological stations. The LSPM predict...

An improved parameterization of the allocation of assimilated carbon to plant parts in vegetation dynamics for Noah‐MP

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 developed scheme is implemented in the augmented Noah land surface model with multiple parameterization options (Noah-MP) along with other biophysical processes related to variations in photosynthetic capacity. The scheme and the augmented biophysical processes are evaluated against tower measurements of vegetation from four forest sites in various regions — two for the deciduous broadleaf and two for the needleleaf evergreen forest. Results from the augmented Noah-MP showed good agreement with the observations and demonstrated improvements in representing the seasonality of leaf area index (LAI), gross primary production (GPP), ecosystem respiration (ER), and latent heat flux. In particular, significant improvements are found in simulating amplitudes and phase shift timing in the LAI seasonal cycle, the amount of GPP and ER in the growing season. Furthermore, the augmented Noah-MP performed reasonably well in simulating the spatial distributions of LAI, GPP and NPP in East Asia, consistent with the satellite observations.

Temporal and spatial characteristics of fog occurrence over the Korean Peninsula

[1] In this study, fogs are classified based on the spatial and temporal characteristics over South Korea using the visibility data and the empirical orthogonal function (EOF) and wavelet analyses. With fog defined in terms of visibility (<1 km), the EOF analysis is performed to extract spatial distribution characteristics via dimension reduction, whereas the space‐time wavelet expansion is applied to the EOF time series to specify the fog characteristics in the space of time versus scale (i.e., period in this study). The first EOF mode occupies 48.9% of total variance and shows the fog distribution covering almost entire areas of South Korea with one sign (+), except at the eastern coast and western part of the southern coast. The wavelet analysis reveals that this fog occurs based on meteorological conditions of various scales from daily to seasonal, thus classified as mixed fog. The second EOF mode, which occupies 19.5% of total variance, shows distinct separation of spatial distribution of fog, with a negative (�) sign in winter over northwestern coastal/inland, western coastal, and south central mountain areas of South Korea and a positive (+) sign in other seasons elsewhere. With cycles of 1–2 weeks and 1–2 months being dominant in the wavelet analysis, this fog is considered to be strongly affected by synoptic scale weather systems and monsoon. Fog over the positive area is mostly affected by monsoon and/or cyclonic frontal systems, thus classified as frontal fog, whereas that over the negative area is affected by the cold‐core anticyclones moving over warm sea surface in winter or by radiative cooling, thus classified as steam fog (coastal/ sea) or radiation fog (inland), respectively. The mountain area may have upslope fog because of orographic lifting. The third EOF mode, occupying 6.7% of total variance, depicts distinct spatial separation of fog distribution around the coastal areas with a negative (�) sign and in the inland areas with a positive (+) sign. The former, with a dominant 1–2 week cycle, is classified as sea fog affected by migratory anticyclones and monsoon in late spring and summer, while the latter, with a dominant diurnal variation, represents radiation fog under clear sky in autumn. It turns out that the combined EOF and wavelet analyses are useful to assess the detailed spatial and temporal characteristics of various types of fog occurrence in South Korea.

Soil temperature response in Korea to a changing climate using a land surface model

The land surface processes play an important role in weather and climate systems through its regulation of radiation, heat, water and momentum fluxes. Soil temperature (ST) is one of the most important parameters in the land surface processes; however, there are few extensive measurements of ST with a long time series in the world. According to the CLImatology of Parameters at the Surface (CLIPS) methodology, the output of a trusted Soil-Vegetation- Atmosphere Transfer (SVAT) scheme can be utilized instead of observations to investigate the regional climate of interest. In this study, ST in South Korea is estimated in a view of future climate using the output from a trusted SVAT scheme — the University of TOrino model of land Process Interaction with Atmosphere (UTOPIA), which is driven by a regional climate model. Here characteristic changes in ST are analyzed under the IPCC A2 future climate for 2046-2055 and 2091-2100, and are compared with those under the reference climate for 1996-2005. The UTOPIA results were validated using the observed ST in the reference climate, and the model proved to produce reasonable ST in South Korea. The UTOPIA simulations indicate that ST increases due to environmental change, especially in air temperature (AT), in the future climate. The increment of ST is proportional to that of AT except for winter. In wintertime, the ST variations are different from region to region mainly due to variations in snow cover, which keeps ST from significant changes by the climate change.

Parameter Estimation Using an Evolutionary Algorithm for QPF in a Tropical Cyclone

In this study the quantitative precipitation forecast (QPF) related to a tropical cyclone is performed using a high-resolution mesoscale model and an evolutionary algorithm. For this purpose two parameters of the Kain-Fritsch convective parameterization scheme, in the Weather Research and Forecasting (WRF) model, are optimized using the micro-genetic algorithm (GA). The auto-conversion rate (c) and the convective time scale (T c ) are target parameters. The fitness function is based on a QPF skill score. Typhoon Rusa (2002) is simulated in a grid spacing of 25 km. The default value of c is 0. 03 s− 1 while that of T c is limited to a range between 1800 s and 3600 s as a function of grid resolution. To produce the best QPF skill, at least for this tropical cyclone case, c is optimized to 0. 0004 s− and T c to 1922s. Our results indicate that parameters of subgrid-scale physical processes need to be adjusted to produce better QPF in a tropical cyclone, sometimes to values far different from the default values in a numerical model. Such adjustment may be dependent on the characteristics of weather systems as well as geographical locations.

Parameter Estimation Using the Genetic Algorithm in Terms of Quantitative Precipitation Forecast

In this study, the optimal parameter estimation is performed for both physical and computational parameters in a mesoscale meteorological model, and its impact on the quantitative precipitation forecasting (QPF) is assessed for a heavy rainfall case occurred at the Korean peninsula in June 2005. Experiments are carried out using the PSU/NCAR MM5 model and the genetic algorithm (GA) for two parameters: the reduction rate of the convective available potential energy in the Kain-Fritsch (KF) scheme for cumulus parameterization, and the Asselin filter parameter for numerical stability. The fitness function is defined based on a QPF skill score. It turns out that each optimized parameter significantly improves the QPF skill. Such improvement is maximized when two optimized parameters are used simultaneously. Our results indicate that optimizations of computational parameters as well as physical parameters and their adequate applications are essential in improving model performance.

Korean Global Data Assimilation and Prediction System

The Korea Meteorological Administration (KMA) first started global Numerical Weather Prediction (NWP) in the late 1990’s, for which the global data assimilation and prediction system had been adopted from the Japan Meteorological Agency (JMA). Having some difficulties in sustaining forecast skill, which was probably due to a system software issue in porting across computer platforms during the first several years of the 2000s, the KMA decided to adopt the United Kingdom Met Office’s Unified Model (UM), and this has been operational since 2011 (Park et al., 2017). The UM-based numerical weather prediction system is a major component for providing daily weather forecasts in Korea. At the same time, the KMA launched a mission to develop major components of the model autonomously and established the Korea Institute of Atmospheric Prediction Systems (KIAPS) in 2011. Educative experience at KMA from using foreign NWP systems has shown limitations in improving the forecast performance, especially incorporating changes to allow for suggestions and evaluations by the KMA forecasters; thus, necessitating the development of KMA’s own NWP system. This special issue highlights the fully-fledged efforts in the development of the new Korean global data assimilation and prediction system. As of February 2018, the 12-km Korean Integrated Model (KIM) system has been launched in a real-time forecast framework, with a spectral-element non-hydrostatic dynamical core on a cubed sphere grid and a state-of-the-art physics parameterization package. The initial conditions are obtained via an advanced method of hybrid four-dimensional ensemble variational data assimilation (4DEnVar) over its native grid. In their 2017 report, the Science Advisory Committee (SAC)* stated that they believe KIAPS addresses with great professionalism and creativity all the important aspects of NWP: dynamical core, coupled systems, physics, and data assimilation, at all time and space scales relevant to regional and global atmospheric forecasts. The SAC continues to encourage the team to collaborate and communicate with other major operational centers and to release KIM in the public domain in the long run, especially to share physics schemes or other software allowing for open discussion in scientific and technical publications. Through this sharing, KIAPS can leverage its limited resources to benefit from contributions by international scientists with similar interests. In this manner, the KIAPS team aim eventually to attain the full maturity of a NWP R&D group having a high international reputation and to achieve recognition on their own merits. This issue is composed of eleven papers written by the KIAPS staff. S. Hong et al. overviews the development strategy and ongoing efforts of KIM, along with the evolution of its performance. S. Choi analyzes the structure of eigenvalues of the KIM dynamic core to clarify the issue of numerical stability. J. Kang et al. and I. Kwon et al. summarize the data processing and quality control, and the benefits of 4DEnVar, respectively. H. Song et al. and S. Shin et al. document the advanced technologies required for 4DEnVar over the cubed-sphere grid. Hong and Jang describe the impact of shallow convection processes on a simulated climatology. E. Lee et al. document the turbulent mixing in stratocumulus-topped boundary layer of NWP models. H. Choi et al. document the effects of spectral non-orographic gravity wave drag on weather and climate modeling. J. Kim et al. and K. Kim et al. present the scalability and computational efficiency issues of KIM. We hope that the papers in this issue will stimulate further development of the KIM NWP system, and promote confidence in its use as a tool for further improving our scientific knowledge of weather and climate.