Spectral wave modeling of tsunami waves in Pohang New Harbor (South Korea) and Paradip Port (India)

Ocean Dynamics - A coupled numerical model is developed based on the spectral element method (SEM) and boundary element method (BEM) to predict the characteristics of tsunami wave response on...     

Critical influence of the pattern of Tropical Ocean warming on remote climate trends

Evidence is presented that the recent trend patterns of surface air temperature and precipitation over the land masses surrounding the North Atlantic Ocean (North America, Greenland, Europe, and North Africa) have been strongly influenced by the warming pattern of the tropical oceans. The current generation of atmosphere–ocean coupled climate models with prescribed radiative forcing changes generally do not capture these regional trend patterns. On the other hand, even uncoupled atmospheric models without the prescribed radiative forcing changes, but with the observed oceanic warming specified only in the tropics, are more successful in this regard. The tropical oceanic warming pattern is poorly represented in the coupled simulations. Our analysis points to model error rather than unpredictable climate noise as a major cause of this discrepancy with respect to the observed trends. This tropical error needs to be reduced to increase confidence in regional climate change projections around the globe, and to formulate better societal responses to projected changes in high-impact phenomena such as droughts and wet spells.     

Spectral Density Analysis for Wave Characteristics in Pohang New Harbor

The Pohang New Harbor (PNH), located at the Yongil bay in the northeastern part of Pohang city, South Korea, has experienced extreme wave hazards of about 3.0–5.0 m in elevation due to the seasonal swell from the far ocean. In this paper, both analytical and numerical studies are performed to investigate the wave-induced oscillations in an arbitrary shaped harbor with corner point consideration. By taking the consideration of the actual topography and bathymetry data, the boundary of PNH is constructed. Our theoretical model is based on the assumptions of inviscid, irrotational fluid, infinitesimal wave amplitude, and finally, the Helmholtz equation and its Weber’s solution. The numerical simulations are conducted to analyze the spectral density of the standing waves in PNH at eight respective synthetic record points. The simulation results are validated with real-time measurement data, which is obtained by wave heights and tide gauges at the specified record points within and outside the PNH. To improve the harbor’s design, a tactic such as building the breakwater at the entrance of the harbor is implemented and then spectral density is estimated in the modified geometry of the PNH. The consequential effects are proposed at the same time, suggesting the feasibility of the improvement measures.     

Seasonal ensemble generator for radar rainfall using copula and autoregressive model

Uncertainty analysis of radar rainfall enables stakeholders and users have a clear knowledge of the possible uncertainty associated with the rainfall products. Long-term empirical modeling of the relationship between radar and gauge measurements is an efficient and practical method to describe the radar rainfall uncertainty. However, complicated variation of synoptic conditions makes the radar-rainfall uncertainty model based on historical data hard to extend in the future state. A promising solution is to integrate synoptic regimes with the empirical model and explore the impact of individual synoptic regimes on radar rainfall uncertainty. This study is an attempt to introduce season, one of the most important synoptic factor, into the radar rainfall uncertainty model and proposes a seasonal ensemble generator for radar rainfall using copula and autoregressive model. We firstly analyze the histograms of rainfall-weighted temperature, the radar-gauge relationships, and Box and Whisker plots in different seasons and conclude that the radar rainfall uncertainty has strong seasonal dependence. Then a seasonal ensemble generator is designed and implemented in a UK catchment under a temperate maritime climate, which can fully model marginal distribution, spatial dependence, temporal dependence and seasonal dependence of radar rainfall uncertainty. To test its performance, 12 typical rainfall events (4 for each season) are chosen to generate ensemble rainfall values. In each time step, 500 ensemble members are produced and the values of 5th to 95th percentiles are used to derive the uncertainty bands. Except several outliers, the uncertainty bands encompass the observed gauge rainfall quite well. The parameters of the ensemble generator vary considerably for each season, indicating the seasonal ensemble generator reflects the impact of seasons on radar rainfall uncertainty. This study is an attempt to simultaneously consider four key features of radar rainfall uncertainty and future study will investigate their impacts on the outputs of hydrological models with radar rainfall as input or initial conditions.     

Bianchi type V universe with bulk viscous matter and time varying gravitational and cosmological constants

We consider spatially homogeneous and anisotropic Bianchi type V space- time with a bulk viscous fluid source, and time varying gravitational constant G and cosmological term Λ. The coefficient of bulk viscosity ζ is assumed to be a simple linear function of the Hubble parameter H (i.e. ζ = ζ 0 + ζ 1 H , where ζ 0 and ζ 1 are constants). The Einstein field equations are solved explicitly by using a law of variation for the Hubble parameter, which yields a constant value of the deceleration parameter. Physical and kinematical parameters of the models are discussed. The models are found to be compatible with the results of astronomical observations.     

Evaluation of TRMM rainfall for soil moisture prediction in a subtropical climate

The Tropical Rainfall Measuring Mission (TRMM) is a joint space mission between NASA and the Japan Aerospace Exploration Agency (JAXA) designed to monitor and study tropical rainfall. In this study, the daily rainfall from TRMM has been utilized to simulate the soil moisture content up to 30 cm vertical soil profile of at an interval depth of 15 cm by using the HYDRUS 1D numerical model for the three plots. The simulated soil moisture content using ground-based rainfall and TRMM-derived rainfall measurements indicate an agreeable goodness of fit between the both. The Nash–Sutcliffe efficiency using ground-based and TRMM-derived rainfall was found in the range of 0.90–0.68 and 0.70–0.40, respectively. The input data sensitivity analysis of precipitation combined with different irrigation treatment indicates a high dependency of soil moisture content with rainfall input. The overall analysis reveals that TRMM rainfall is promising for soil moisture prediction in absence of ground-based measurements of soil moisture.