Rainfall frequency analysis using a mixed GEV distribution: a case study for annual maximum rainfalls in South Korea

Extreme rainfalls in South Korea result mainly from convective storms and typhoon storms during the summer. A proper way for dealing with the extreme rainfalls in hydrologic design is to consider the statistical characteristics of the annual maximum rainfall from two different storms when determining design rainfalls. Therefore, this study introduced a mixed generalized extreme value (GEV) distribution to estimate the rainfall quantile for 57 gauge stations across South Korea and compared the rainfall quantiles with those from conventional rainfall frequency analysis using a single GEV distribution. Overall, these results show that the mixed GEV distribution allows probability behavior to be taken into account during rainfall frequency analysis through the process of parameter estimation. The resulting rainfall quantile estimates were found to be significantly smaller than those determined using a single GEV distribution. The difference of rainfall quantiles was found to be closely correlated with the occurrence probability of typhoon and the distribution parameters.     

Comparison of primary productivity algorithms for Korean waters

This study compares five primary productivity algorithms for Korean waters. Five algorithms are in the form of vertical generalized production models: One algorithm is for gross primary production and four are for net primary production. The five algorithms were evaluated using 117 in situ primary production datasets observed by 20 cruises from 1994 to 2011 in Korean waters (East Sea, Yellow Sea, East China Sea, and Yeosu Bay). The results show that the regionally-tuned variants give better results than the original formulation. We recommend, among the tested algorithms, YSVGPM (Yellow Sea Vertically Generalized Productivity Model) for gross primary productivity algorithm and Kameda-Ishizaka algorithm for net primary productivity algorithm for estimating primary production in Korean waters.     

Morphology and molecular characterization of the epiphytic dinoflagellate Prorocentrum cf. rhathymum in temperate waters off Jeju Island, Korea

Prorocentrum spp. are planktonic and/or benthic species. Benthic Prorocentrum species are of primary concern to scientists and the public because some of them are toxic. We established clonal cultures of 3 strains of Prorocentrum species that were collected from the thalli of a macroalga in the coastal waters off Jeju Island, located at the southern end of Korea. The Korean strains of P. cf. rhathymum, which are morphologically almost identical to the Virgin Island strain of P. rhathymum, were different from P. mexicanum because the former dinoflagellate has one simple collar-like spine in the periflagellar area, while the latter dinoflagellate has a 2- or 3-horned spine. In addition, the sequences of the small subunit (SSU) rDNA of the Korean strains were identical to those of the Malaysian and Floridian strains of P. rhathymum, while the sequences of the large subunit (LSU) rDNA of the Korean strains were 0.1–0.9% different from those of the Iranian and Malaysian strains of P. rhathymum. In phylogenetic trees based on the SSU rDNA sequences, the Korean strains of P. rhathymum formed a clade with the Malaysian and Floridian strains of P. rhathymum and the Vietnamese and Polynesian strains of P. mexicanum. However, in phylogenetic trees based on the LSU rDNA sequences, the Korean strains of P. rhathymum formed a clade with the Iranian strain of P. rhathymum and the Spanish and Mexican strains of P. mexicanum. Therefore, the molecular characterization of the Korean strains does not allow us to clearly classify them as P. rhathymum, nor P. mexicanum, although their morphology has so far been reported to be closer to that of P. rhathymum than P. mexicanum and thus we designated them as P. cf. rhathymum.     

Inter-station correlation and estimation errors of areal average rain rate

In this study an equation for estimating the error involved in the areal average rain rate considering the inter-station correlation was derived and applied for two cases: the first compared two storm events with different inter-station correlations, and the second evaluated the seasonal variation of estimation error of monthly rainfall. Similar cases, but without considering the rainfall seasonality, were also investigated for the comparison. This study was applied to the Geum River Basin with 28 rain gauge measurements, each having more than 30 years of rainfall data. A summary of the application results follows: (1) When considering the inter-station correlation, the estimation error involved in the areal average rain rate became significantly decreased proportional to the inter-station correlation. (2) The estimation error of monthly areal average rainfall showed strong seasonality with high ones during the wet season and lower ones during the dry season. (3) The estimation error was well proportional to the areal average rain rate as well as to its standard deviation. The ratio of estimation error to the areal average rain rate itself was estimated to be about 0.1 for the case of assuming no inter-station correlations, but decreased to 0.06 for the case of considering the inter-station correlations between measurements. (4) The relation between the standard deviation of areal average rain rate and the estimation error became much stronger than that between the areal average rain rate itself and the estimation error. The ratio of estimation error to the standard deviations of rain rate amount was estimated to be about 0.2 for the case of assuming no inter-station correlations, but decreased to 0.1 for the case of considering the inter-station correlations. This relation was found to be valid for any case of accumulation time such as in daily, monthly, or annual rainfall data.     

Influence of climate variation on seasonal precipitation in the Colorado River Basin

This study analyzed the influence of large-scale climate pattern on precipitation in the Colorado River Basin. Large-scale climatic oscillations, like ENSO, PDO, NAO, and the global warming trend are associated with regional hydrologic variation. Ten types of climate indices were gathered and analyzed to investigate their influence on seasonal precipitation variation in the basin based on a linear correlation analysis and an influence index analysis. The influence index was developed in this study to measure the effect of climate variation on the seasonal precipitation in the basin. The statistical evidence achieved in this study confirms that the Colorado River Basin is subjected to the phase of climate variation. The strength of the seasonal response of precipitation to the climate variation varies in different localities in the basin. The methods of analysis used in this study were proposed in the hope that progress in understanding and modeling dynamic climatic systems can result in developing a valuable long-term forecasting model for water resources management.     

Technical note on a track-pattern-based model for predicting seasonal tropical cyclone activity over the western North Pacific

Recently, the National Typhoon Center (NTC) at the Korea Meteorological Administration launched a track-pattern-based model that predicts the horizontal distribution of tropical cyclone (TC) track density from June to October. This model is the first approach to target seasonal TC track clusters covering the entire western North Pacific (WNP) basin, and may represent a milestone for seasonal TC forecasting, using a simple statistical method that can be applied at weather operation centers. In this note, we describe the procedure of the track-pattern-based model with brief technical background to provide practical information on the use and operation of the model. The model comprises three major steps. First, long-term data of WNP TC tracks reveal seven climatological track clusters. Second, the TC counts for each cluster are predicted using a hybrid statistical-dynamical method, using the seasonal prediction of large-scale environments. Third, the final forecast map of track density is constructed by merging the spatial probabilities of the seven clusters and applying necessary bias corrections. Although the model is developed to issue the seasonal forecast in mid-May, it can be applied to alternative dates and target seasons following the procedure described in this note. Work continues on establishing an automatic system for this model at the NTC.     

Evaluation of subseasonal impacts of the MJO/BSISO in the East Asian extended summer

The Madden–Julian Oscillation (MJO)/Boreal Summer Intraseasonal Oscillation (BSISO) has been considered an important climate mode of variability on subseasonal timescales for East Asian summer. However, it is unclear how well the MJO/BSISO indices would serve as guidance for subseasonal forecasts. Using a probabilistic forecast model determined through multiple linear regression (MLR) with MJO, ENSO, and long-term trend as predictors, we examine lagged impacts of each predictor on East Asia extended summer (May–October) climate from 1982 to 2015. The forecast skills of surface air temperature (T2m) contributed by each predictor is evaluated for lead times out to five weeks. We also provide a systematic evaluation of three commonly used, real-time MJO/BSISO indices in the context of lagged temperature impacts over East Asia. It is found that the influence of the trend provides substantial summertime skill over broad regions of East Asia on subseasonal timescales. In contrast, the MJO influence shows regional as well as phase dependence outside the tropical band of the main action centers of the MJO convective anomalies. All three MJO/BSISO indices generate forecasts that yield high skill scores for week 1 forecasts. For some initial phases of the MJO/BSISO, skill reemerges over some regions for lead times of 3–5 weeks. This emergence indicates the existence of windows of opportunity for skillful subseasonal forecasts over East Asia in summer. We also explore the dynamics that contribute to the elevated skills at long lead times over Tibet and Taiwan–Philippine regions following the initial state of phases 7 and 5, respectively. The elevated skill is rooted in a wave train forced by the MJO convective heating over the Arabian Sea and feedbacks between MJO convection and SSTs in Taiwan–Philippine region. Two out of the three commonly used MJO/BSISO indices tend to identify MJO events that evolve consistently in time, allowing them to serve as reliable predictors for subseasonal forecasts for up to 5 weeks.

     

Spring phytoplankton bloom in the fronts of the East China Sea

Frontal areas between warm and saline waters of the Kuroshio currents and colder and diluted waters of the East China Sea (ECS) influenced by the Changjiang River were identified from the satellite thermal imagery and hydrological data obtained from the Coastal Ocean Process Experiment (COPEX) cruise during the period between March 1^st and 10^th, 1997. High chlorophyll concentrations appeared in the fronts of the East China Seas with the highest chlorophyll-a concentration in the southwestern area of Jeju Island (~2.9 mg/m³) and the eastern area of the Changjiang River Mouth (~2.8 mg/m³). Vertical structures of temperature, salinity and density were similar, showing the fronts between ECS and Kuroshio waters. The water column was well mixed in the shelf waters and was stratified around the fronts. It is inferred that the optimal condition for light utilization and nutrients induced both from the coastal and deep waters enhances the high phytoplankton productivity in the fronts of the ECS. In addition, the high chlorophyll-a in the fronts seems to have been associated with the water column stability as well.     

Low-Level Westerly Winds,Topography, and Tropical Cyclogenesis of Arlene (2005): Observations and Model Simulations

The evolution process of the low-level westerly winds over the eastern North Pacific is investigated to understand the tropical cyclogenesis (TCG) of Tropical Storm Arlene (2005) over the Intra-Americas Sea (IAS). Also considered are the influences of the topography of the Central American mountain region interacting with the low-level westerly winds on Arlene's TCG by comparing results from a modified-topography simulation of Arlene's TCG with those from a simulation with the original topography in the Weather Research and Forecast (WRF) model. Interactions among large-scale circulations associated with subtropical highs in both hemispheres and an anticyclone over the warm eastern North Pacific produced low-level westerly winds into the IAS. WRF model experiments with a virtually elevated terrain filling in mountain passes in Central America resulted in the delayed and suppressed development of the incipient storm. The model experiments suggest that the low-level winds and moisture fluxes from the eastern North Pacific passing through the low-level mountain passes in Central America could play a critical role in the TCG process and perhaps also sustenance of storms over the western Caribbean.