A copula-based multivariate analysis of Canadian RCM projected changes to flood characteristics for northeastern Canada

In the present work, climate change impacts on three spring (March–June) flood characteristics, i.e. peak, volume and duration, for 21 northeast Canadian basins are evaluated, based on Canadian regional climate model (CRCM) simulations. Conventional univariate frequency analysis for each flood characteristic and copula based bivariate frequency analysis for mutually correlated pairs of flood characteristics (i.e. peak–volume, peak–duration and volume–duration) are carried out. While univariate analysis is focused on return levels of selected return periods (5-, 20- and 50-year), the bivariate analysis is focused on the joint occurrence probabilities P1 and P2 of the three pairs of flood characteristics, where P1 is the probability of any one characteristic in a pair exceeding its threshold and P2 is the probability of both characteristics in a pair exceeding their respective thresholds at the same time. The performance of CRCM is assessed by comparing ERA40 (the European Centre for Medium-Range Weather Forecasts 40-year reanalysis) driven CRCM simulated flood statistics and univariate and bivariate frequency analysis results for the current 1970–1999 period with those observed at selected 16 gauging stations for the same time period. The Generalized Extreme Value distribution is selected as the marginal distribution for flood characteristics and the Clayton copula for developing bivariate distribution functions. The CRCM performs well in simulating mean, standard deviation, and 5-, 20- and 50-year return levels of flood characteristics. The joint occurrence probabilities are also simulated well by the CRCM. A five-member ensemble of the CRCM simulated streamflow for the current (1970–1999) and future (2041–2070) periods, driven by five different members of a Canadian Global Climate Model ensemble, are used in the assessment of projected changes, where future simulations correspond to A2 scenario. The results of projected changes, in general, indicate increases in the marginal values, i.e. return levels of flood characteristics, and the joint occurrence probabilities P1 and P2. It is found that the future marginal values of flood characteristics and P1 and P2 values corresponding to longer return periods will be affected more by anthropogenic climate change than those corresponding to shorter return periods but the former ones are subjected to higher uncertainties.     

A dissection of the surface temperature biases in the Community Earth System Model

Based upon the climate feedback-responses analysis method, a quantitative attribution analysis is conducted for the annual-mean surface temperature biases in the Community Earth System Model version 1 (CESM1). Surface temperature biases are decomposed into partial temperature biases associated with model biases in albedo, water vapor, cloud, sensible/latent heat flux, surface dynamics, and atmospheric dynamics. A globally-averaged cold bias of ?1.22 K in CESM1 is largely attributable to albedo bias that accounts for approximately ?0.80 K. Over land, albedo bias contributes ?1.20 K to the averaged cold bias of ?1.45 K. The cold bias over ocean, on the other hand, results from multiple factors including albedo, cloud, oceanic dynamics, and atmospheric dynamics. Bias in the model representation of oceanic dynamics is the primary cause of cold (warm) biases in the Northern (Southern) Hemisphere oceans while surface latent heat flux over oceans always acts to compensate for the overall temperature biases. Albedo bias resulted from the model’s simulation of snow cover and sea ice is the main contributor to temperature biases over high-latitude lands and the Arctic and Antarctic region. Longwave effect of water vapor is responsible for an overall warm (cold) bias in the subtropics (tropics) due to an overestimate (underestimate) of specific humidity in the region. Cloud forcing of temperature biases exhibits large regional variations and the model bias in the simulated ocean mixed layer depth is a key contributor to the partial sea surface temperature biases associated with oceanic dynamics. On a global scale, biases in the model representation of radiative processes account more for surface temperature biases compared to non-radiative, dynamical processes.     

R/V Isabu-Based First Ultraclean Seawater Sampling for Ocean Trace Elements in Korea

Ocean Science Journal - Trace elements (Mn, Fe, Co, Ni, Cu, Zn, etc.) are essential micronutrients for marine organisms and are thus related to major issues in the ocean, such as climate change,...     

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.     

Local outlier factor as part of a workflow for detecting and attenuating blending noise in simultaneously acquired data

A number of deblending methods and workflows have been reported in the past decades to eliminate the source interference noise recorded during a simultaneous shooting acquisition. It is common that denoising algorithms focusing on optimizing coherency and weighting down/ignoring outliers can be considered as deblending tools. Such algorithms are not only enforcing coherency but also handling outliers either explicitly or implicitly. In this paper, we present a novel approach based on detecting amplitude outliers and its application on deblending based on a local outlier factor that assigns an outlier-ness (i.e. a degree of being an outlier) to each sample of the data. A local outlier factor algorithm quantifies outlier-ness for an object in a data set based on the degree of isolation compared with its locally neighbouring objects. Assuming that the seismic pre-stack data acquired by simultaneous shooting are composed of a set of non-outliers and outliers, the local outlier factor algorithm evaluates the outlier-ness of each object. Therefore, we can separate the data set into blending noise (i.e. outlier) and signal (i.e. non-outlier) components. By applying a proper threshold, objects having high local outlier factors are labelled as outlier/blending noise, and the corresponding data sample could be replaced by zero or a statistically adequate value. Beginning with an explanation of parameter definitions and properties of local outlier factor, we investigate the feasibility of a local outlier factor application on seismic deblending by analysing the parameters of local outlier factor and suggesting specific deblending strategies. Field data examples recorded during simultaneous shooting acquisition show that the local outlier factor algorithm combined with a thresholding can detect and attenuate blending noise. Although the local outlier factor application on deblending shows a few shortcomings, it is consequently noted that the local outlier factor application in this paper obviously achieves benefits in terms of detecting and attenuating blending noise and paves the way for further geophysical applications.     

Role of Siliceous Fossil Dissolution in Downcore Variations of Grain Size and Water Content: Western Margin of Clarion-Clipperton Fracture Zone, NE Equatorial Pacific

Grain size and water content in box-core sediments from the Clarion-Clipperton fracture zone (C-C zone) in the northeast equatorial Pacific were analyzed in detail to understand the downcore variations across a hiatus between Quaternary and Tertiary layers. Grain-size distributions in the topmost core sediments show two modes: a coarse mode (peaked at 50 μm) and a fine mode (at 2-25 μm). The coarse mode disappears gradually with depth accompanied by the dissolution of siliceous fossil tests, whereas the fine mode coarsens due to the formation of authigenic minerals. Water content increases abruptly across a color boundary between an upper pale brown layer and a lower dark brown layer that is the hiatus between Quaternary and Tertiary layers. Abundant smectites and microvoid molds, which are created by the prolonged fossil dissolution in the underlying sediment, are attributed for the abrupt downcore variation of water content. Overall variations in grain size and water content in the topmost core sediments in the western C-C zone are possibly constrained by the dissolution of biogenic siliceous fossils. Variations in geotechnical properties related to these changes must be considered in the design of nodule collectors.     

The impacts of climate change on local hydrology and low flow frequency in the Geum River Basin,Korea

The climate sensitive analysis of potential climate change on streamflow has been conducted using a hydrologic model to identify hydrologic variability associated with climate scenarios as a function of perturbed climatic variables (e.g. carbon dioxide, temperature, and precipitation). The interannual variation of water resources availability as well as low flow frequency driven by monsoonal time shifts have been investigated to evaluate the likelihood of droughts in a changing climate. The results show that the timing shift of the monsoon window associated with future climate scenarios clearly affect annual water yield change of ? 12 and ? 8% corresponding to 1‐month earlier and 1‐month later monsoon windows, respectively. Also, a more severe low flow condition has been predicted at 0·03 m³/s as opposed to the historic 7Q10 flow of 1·54 m³/s given at extreme climate scenarios. Copyright © 2011 John Wiley & Sons, Ltd.