Interpretation of mean‐field bias correction of radar rain rate using the concept of linear regression

In this study, the correction problem of mean‐field bias of radar rain rate was investigated using the concept of linear regression. Three different relationships were reviewed for their slopes to be used as the bias correction factor: Relationship 1 (R1) is based on the conventional linear regression, relationship 2 (R2) is forced to pass the origin and relationship 3 (R3) is the line whose slope is the G/R ratio. In other words, R1 is the regression line connecting the intercept and the mass centre of measurement pairs, R2 is the regression line forced to pass the origin, and R3 is the line connecting the origin and the mass centre. The slopes of all three relationships were reviewed analytically to compare them, and thereby, the effect of zero measurements could be evaluated. Additionally, the effect of using switched independent and dependent variables on the derived slopes was also evaluated. The theoretically derived results were then verified by analysing the rainfall event on 10–11 August 2010 in Korea. Finally, the difference between the bias‐corrected radar rain rate and the rain gauge rain rate was quantified by root mean square error and mean error so that it could be used as a measure for the evaluation of bias correction factors. In conclusion, the slope of R2 was found to be the best for the bias correction factor. However, when deciding the slope of this R2, the radar rain rate should be used as the independent variable in the low rain rate region, and the rain gauge rain rate in the high rain rate region above a certain threshold. Copyright © 2013 John Wiley & Sons, Ltd.     

Late Quaternary glaciation in the Nun‐Kun massif,northwestern India

The late Quaternary glacial history of the Nun‐Kun massif, located on the boundary between the Greater Himalaya and the Zanskar range in northwestern India, was reconstructed. On the basis of morphostratigraphy and ¹⁰Be dating of glacial landforms (moraines and glacial trimlines), five glacial stages were recognized and defined, namely: (i) the Achambur glacial stage dated to Marine Oxygen Isotope Stage 3 to 4 (38.7–62.7 ka); (ii) the Tongul glacial stage dated to the early part of the Lateglacial (16.7–17.4 ka); (iii) the Amantick glacial stage dated to the later part of the Lateglacial (14.3 ka, 11.7–12.4 ka); (iv) the Lomp glacial stage dated to the Little Ice Age; and (v) the Tanak glacial stage, which has the youngest moraines, probably dating to the last few decades or so. Present and former equilibrium‐line altitudes (ELAs) were calculated using the standard area accumulation ratio method. The average present‐day ELA of ～4790 m above sea level in the Greater Himalaya is lower than those in the Ladakh and Zanskar ranges, namely 5380 and ～5900 m a.s.l., respectively. The ELA in the Zanskar range is higher than in the Ladakh range, possibly due to the higher peaks in the Ladakh range that are able to more effectively capture and store snow and ice. ELA depressions decrease towards the Ladakh range (i.e. inner Plateau). Peat beds interbedded with aeolian deposits that cap the terminal moraine of Tarangoz Glacier suggest millennial‐time‐scale climate change throughout the Holocene, with soil formation times at c. 1.5, c. 3.4 and c. 5.2 ka, probably coinciding with Holocene abrupt climate change events. Given the style and timing of glaciation in the study area, it is likely that climate in the Nun‐Kun region is linked to Northern Hemisphere climate oscillations with teleconnections via the mid‐latitude westerlies.     

Development and application of a methodology for vulnerability assessment of climate change in coastal cities

This research is based on the need to develop methodology for climate change vulnerability assessment in coastal cities. While there have been some studies on the development of methodologies for vulnerability assessment on a national scale, there have been few attempts to develop a method for local vulnerability assessment with application to coastal cities. The objective of this study was to develop a general methodology to assess vulnerability to climate change and to apply it to the metropolitan coastal city of Busan in South Korea. We followed the conceptual framework for assessing climate change vulnerability provided by the Intergovernmental Panel on Climate Change (IPCC), which is composed of climate exposure, sensitivity, and adaptive capacity. Sea level rises of 0.5 m, 1 m, 2 m, and 3 m were considered as the climate exposure. Sensitivity to sea level rise was measured based on the percentage of flooded area calculated using flood simulation with a GIS tool. The population density and the population at age 65 years and over were also included in the calculation of sensitivity index. Sensitivities to heat wave and heavy rainstorm were quantified using the expert opinions from the Delphi survey and information on land use classification. Adaptive capacity was assessed in three sections: economic capability, infrastructure, and institutional capabilities. By combining the adaptive capacity and three different sensitivities, vulnerability to sea level rise (SLR-V), vulnerability to heavy rainstorm (HR-V), and vulnerability to heat wave (HW-V) were separately evaluated in 16 counties of Busan. Using cluster analysis, we could classify four major groups of counties based on SLR-V, HR-V, HW-V, and reported damage cost. For clustered groups, different adaptation strategies were suggested based on the different vulnerability patterns. Application of our methodology to Busan indicated that our methodology is easy to use and provides concrete policy implications when setting up adaptation strategies. The methodology developed in this study could also be used in mainstreaming climate change into Integrated Coastal Management (ICM).     

Integration of Information Technology into Geotechnical Engineering Practice: Concept and Development

Information Technology (IT) has been extensively used to predict, visualize, and analyze physical parameters in order to expedite routine geotechnical design procedures. This paper presents an example of the combined technique of IT and numerical analysis for routine geotechnical design projects. The proposed approach involves the development of ANN(s) using a calibrated finite element model(s) for use as a prediction tool and implementation of the developed ANN(s) into a GIS platform for visualization and analysis of spatial distribution of predicted results. A novel feature of the proposed approach is an ability to expedite a routine geotechnical design process that otherwise requires significant time and effort in performing numerical analyses for different design scenarios. A knowledge-based underground excavation design system that utilizes artificial neural networks (ANNs) as prediction tools is also introduced. Practical implications of the use of IT in geotechnical design are discussed in great detail.     

Bivariate drought frequency curves and confidence intervals: a case study using monthly rainfall generation

Although water resources management practices recently use bivariate distribution functions to assess drought severity and its frequency, the lack of systematic measurements is the major hindrance in achieving quantitative results. This study aims to suggest a statistical scheme for the bivariate drought frequency analysis to provide comprehensive and consistent drought severities using observed rainfalls and their uncertainty using synthesized rainfalls. First, this study developed a multi-variate regression model to generate synthetic monthly rainfalls using climate variables as causative variables. The causative variables were generated to preserve their correlations using copula functions. This study then focused on constructing bivariate drought frequency curves using bivariate kernel functions and estimating their confidence intervals from 1,000 likely replica sets of drought frequency curves. The confidence intervals achieved in this study may be useful for making a comprehensive drought management plan through providing feasible ranges of drought severity.     

Does El Niño-Southern Oscillation affect the precipitation in Korea on seasonal time scales?

A number of studies in the past two decades have attempted to find the relationship between the precipitation in Korea and the El Niño-Southern Oscillation (ENSO) on various time scales. Comprehensive analyses of station precipitation data in Korea for the 61-year period, 1954-2014, in this study show that the effects of ENSO on the seasonal precipitation in Korea are practically negligible. The correlation between summer precipitation and ENSO is insignificant regardless of the intensity, type (e.g., eastern-Pacific or central-Pacific), and stage (e.g., developing, mature, or decaying) of ENSO. Somewhat meaningful correlation between ENSO and precipitation in Korea occurs only in the ENSO-developing fall. Because summer rainfall accounts for over half of the annual total and fall is a dry season in Korea, the overall effects of ENSO on precipitation in Korea are practically nonexistent.     

Spatial and temporal variations in nutrient and chlorophyll-a concentrations in the northern East China Sea surrounding Cheju Island

Nutrients, chlorophyll-a (Chl-a), and environmental conditions were extensively investigated in the northern East China Sea (ECS) near Cheju Island during five research cruises from 2003 to 2007. In the eastern part of the study area, surface waters were characterized only by the Tsushima Current Water (TCW) during all five cruises. However, the western surface waters changed with season and were characterized by the Yellow Sea Cold Water (YSCW) in spring, the Changjiang Diluted Water (CDW) in summer, and the Yellow Sea Mixed Water (YSMW) in autumn. In spring and autumn, relatively high concentrations of nitrate and phosphate were observed in the surface waters in the western part of the study area, where vertical mixing brought large supplies of nutrients from deep waters. Changes in wind direction occasionally varied the inflow of the Changjiang plume in summer, clearly causing the annual variation in surface nitrate and phosphate concentrations in summer. In summer, the surface distribution of nitrate and phosphate did not coincide with that of silicate in the study area, which probably resulted from the significant drop in the Si:N ratio in the Changjiang plume since construction of the Three Gorges Dam (TGD). Despite large temporal and spatial variations in surface Chl-a concentrations, depth-integrated Chl-a concentrations exhibited little variation temporally and spatially. In the study area, surface Chl-a concentration did not well reflect the standing stocks of phytoplankton. The vertical distribution of Chl-a showed large temporal and spatial variations, and the main factor controlling the vertical distribution of Chl-a in summer was the availability of nitrate. The thermohaline front may play an important role for accumulation of phytoplankton biomass in spring and autumn.     

Time-frequency characteristics of the relationships between tropical Indo-Pacific SSTs

In this study, several advanced analysis methods are applied to understand the relationships between the Nino-3.4 sea surface temperatures （SST） and the SSTs related to the tropical Indian Ocean Dipole （IOD）. By analyzing a long data record, the authors focus on the time-frequency characteristics of these relationships, and of the structure of IOD. They also focus on the seasonal dependence of those characteristics in both time and frequency domains. Among the Nino-3.4 SST, IOD, and SSTs over the tropical western Indian Ocean （WIO） and eastern Indian Ocean （EIO）, the WIO SST has the strongest annual and semiannual oscillations. While the Nino-3.4 SST has large inter-annual variability that is only second to its annual variability, the IOD is characterized by the largest semiannual oscillation, which is even stronger than its annual oscillation. The IOD is strongly and stably related to the EIO SST in a wide range of frequency bands and in all seasons. However, it is less significantly related to the WIO SST in the boreal winter and spring. There exists a generally weak and unstable relationship between the WIO and EIO SSTs, especially in the biennial and higher frequency bands. The relationship is especially weak in summer and fall, when IOD is apparent, but appears highly positive in winter and spring, when the IOD is unimportantly weak and even disappears. This feature reflects a caution in the definition and application of IOD. The Nino-3.4 SST has a strong positive relationship with the WIO SST in all seasons, mainly in the biennial and longer frequency bands. However, it shows no significant relationship with the EIO SST in summer and fall, and with IOD in winter and spring.     

Wave Data Assimilation to Modify Wind Forcing Using an Ensemble Kalman Filter

In order to improve the predictability of winter storm waves in the East Sea, this article explores the use of the ensemble Kalman filter technique for dat