Detection of mean-field bias of the radar rain rate using rain gauges available within a small portion of radar umbrella: a case study of the Donghae (East Sea) radar in Korea

Observation of a storm approaching from the ocean to the in-land area is very important for the flood forecasting. Radar is generally used for this purpose. However, as rain gauges are mostly located within the in-land area, detection of the mean-field bias of radar rain rate cannot be easily made. This problem is obviously different from that with evenly-spaced rain gauges over the radar umbrella. This study investigated the detection problem of mean-field bias of radar rain rate when rain gauges are available within a small portion of radar umbrella. To exactly determine the mean-field bias, i.e. the difference between the radar rain rate and the rain gauge rain rate, the variance of the difference between two observations must be small; thus, a sufficient number of observations are indispensable. Therefore, the problem becomes determining the number of rain gauges that will satisfy the given accuracy, that being the variance of the difference between two observations. The dimensionless error variance derived by dividing the expected value of the error variance by the variance of the areal average rain rate was introduced as a criteria to effectively detect the mean field bias. Here, the variance of the areal average rain rate was assumed to be the climatological one and the expectation for the error variance could be changed depending one the sampling characteristics. As an example, this study evaluated the rainfall observation over the East Sea by the Donghae radar. About 6.8 % of the entire radar umbrella covered in-land areas, where the rain gauges were available. It was found that, to limit the dimensionless error variance to 2 %, a total of 26 rain gauges are required for the entire radar umbrella; whereas, a total of 24 rain gauges would be required within the in-land area with available for the rain gauge data.     

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.     

Giant gas bubbles in a rheomorphic vent fill at the Las Cañadas caldera,Tenerife (Canary Islands)

During rheomorphism subsequent to fallout deposition, a portion of the densely welded fallout of the La Grieta Member flowed back into the vent from where it was erupted, while the rest of it flowed down the outer slopes of the Las Cañadas caldera in Tenerife. The welded fallout and conduit-vent structure are physically connected and constitute a rare example of this type of deposits rooted to its feeder conduit and exposed in the caldera wall. The lower part of the vent-filling rheomorphic rocks shows gas bubbles and cavities that increase in size (up to 4 m) down vent. Bubbles are deformed against other bubbles, against the steep vent walls, flattened parallel to the flow foliation planes, and elongated parallel to the flow lineation and flow fold axes. The preservation of such giant bubbles, rather than their formation, seems to be a pretty unique feature of the phonolitic products investigated here and it is likely the result of the combination of factors that acted to preserve, in the surrounding of the glass transition interval, the sealing and the late stage cooling of a pressurized system. In addition, strain drop at the base of the vent-filling rheomorphic flow caused by flow stopping against vertical vent walls may have promoted rapid gas exsolution and the formation of large bubbles.     

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.     

Potential increase of flood hazards in Korea due to global warming from a high-resolution regional climate simulation

Because of the importance of the changes in the hydrologic cycle, accurate assessment of precipitation characteristics is essential to understand the impact of climate change due to global warming. This study investigates the changes in extreme precipitation with sub-daily and daily temporal scales. For a fine-scale climate change projection focusing on the Korean peninsula (20 km), we performed the dynamical downscaling of the global climate scenario covering the period 1971?C2100 (130-year) simulated by the Max-Planck-Institute global climate model, ECHAM5, using the latest version of the International Centre for Theoretical Physics (ICTP) regional climate model, RegCM3. While annual mean precipitation exhibits a pronounced interannual and interdecadal variability, with the increasing or decreasing trend repeated during a certain period, extreme precipitation with sub-daily and daily temporal scales estimated from the generalized extreme value distribution shows consistently increasing pattern. The return period of extreme precipitation is significantly reduced despite the decreased annual mean precipitation at the end of 21^st century. The decreased relatively weak precipitation is responsible for the decreased total precipitation, so that the decreased total precipitation does not necessarily mean less heavy precipitation. Climate change projection based on the ECHAM5-RegCM3 model chain clearly shows the effect of global warming in increasing the intensity and frequency of extreme precipitation, even without significantly increased total precipitation, which implies an increased risk for flood hazards.     

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.