Multi-decadal scenario simulation over Korea using a one-way double-nested regional climate model system. Part 1: recent climate simulation (1971–2000)

We present an analysis of a high resolution multi-decadal simulation of recent climate (1971–2000) over the Korean Peninsula with a regional climate model (RegCM3) using a one-way double-nested system. Mean climate state as well as frequency and intensity of extreme climate events are investigated at various temporal and spatial scales, with focus on surface air temperature and precipitation. The mother intermediate resolution model domain encompasses the eastern regions of Asia at 60 km grid spacing while the high resolution nested domain covers the Korean Peninsula at 20 km grid spacing. The simulation spans the 30-year period of January 1971 through December 2000, and initial and lateral boundary conditions for the mother domain are provided from ECHO-G fields based on the IPCC SRES B2 scenario. The model shows a good performance in reproducing the climatological and regional characteristics of surface variables, although some persistent biases are present. Main results are as follows: (1) The RegCM3 successfully simulates the fine-scale structure of the temperature field due to topographic forcing but it shows a systematic cold bias mostly due to an underestimate of maximum temperature. (2) The frequency distribution of simulated daily mean temperature agrees well with the observed seasonal and spatial patterns. In the summer season, however, daily variability is underestimated. (3) The RegCM3 simulation adequately captures the seasonal evolution of precipitation associated to the East Asia monsoon. In particular, the simulated winter precipitation is remarkably good, clearly showing typical precipitation patterns that occur on the northwestern areas of Japan during the winter monsoon. Although summer precipitation is underestimated, area-averaged time series of precipitation over Korea show that the RegCM3 agrees better with observations than ECHO-G both in terms of seasonal evolution and precipitation amounts. (4) Heavy rainfall phenomena exceeding 300 mm/day are simulated only at the high resolution of the double nested domain. (5) The model shows a tendency to overestimate the number of precipitation days and to underestimate the precipitation intensities. (6) A CSEOF analysis reveals that the model captures the strength of the annual cycle and the surface warming trend throughout the simulated period.     

Present and future climatologies in the phase I CREMA experiment

We provide an overall assessment of the surface air temperature and precipitation present day (1976–2005) and future (2070–2099) ensemble climatologies in the Phase I CREMA experiment. This consists of simulations performed with different configurations (physics schemes) of the ICTP regional model RegCM4 over five CORDEX domains (Africa, Mediterranean, Central America, South America, South Asia), driven by different combinations of three global climate models (GCMs) and two greenhouse gas (GHG) representative concentration pathways (RCP8.5 and RCP4.5). The biases (1976–2005) in the driving and nested model ensembles compared to observations show a high degree of spatial variability and, when comparing GCMs and RegCM4, similar magnitudes and more similarity for precipitation than for temperature. The large scale patterns of change (2070–2099 minus 1976–2005) are broadly consistent across the GCM and RegCM4 ensembles and with previous analyses of GCM projections, indicating that the GCMs selected in the CREMA experiment are representative of the more general behavior of current GCMs. The RegCM4, however, shows a lower climate sensitivity (reduced warming) than the driving GCMs, especially when using the CLM land surface scheme. While the broad patterns of precipitation change are consistent across the GCM and RegCM4 ensembles, greater differences are found at sub-regional scales over the various domains, evidently tied to the representation of local processes. This paper serves to provide a reference view of the behavior of the CREMA ensemble, while more detailed and process-based analysis of individual domains is left to companion papers of this special issue.     

Analysis of the liquefaction phenomena in the village of Vittorito (L��Aquila)

This paper describes a case-history of liquefaction occurred near the village of Vittorito after the April 6, 2009 L’Aquila earthquake (moment magnitude M_w = 6.3), approximately 45 km far from the epicentre. In the document, first, an estimation of the seismic motion in the area has been made. Thereafter, the performed geotechnical investigation is described, followed by the application of some fast assessment criteria for the occurrence of liquefaction, recently proposed by the new Italian Building Code. A careful assessment of all the parameters involved in conventional Seed and Idriss (1971) liquefaction analyses is considered. The cyclic resistance ratio CRR is evaluated by cone penetration tests CPT and by in situ seismic dilatometer tests SMDT; in the latter case CRR is evaluated by different empirical correlations with shear wave velocity V_s and horizontal stress index K_D. Analytical data confirmed the observed occurrence of the liquefaction in Vittorito, even if the acceleration field in the area, produced by the L’Aquila earthquake, was very low.     

新疆21世纪气候变化的高分辨率模拟

使用一个25 km高水平分辨率区域气候模式(RegCM3),嵌套MIROC3.2_hires全球气候模式结果,进行了IPCC SRES A1B情景下,东亚区域21世纪气候变化的模拟,针对新疆地区进行了分析.首先对模式模拟的当代（1981-2000年）气候进行检验,结果表明:模式对年平均气温、降水的空间分布和数值均具有较...     

Displacement prediction of step-like landslide by applying a novel kernel extreme learning machine method

Landslide displacement prediction is an essential component for developing landslide early warning systems. In the Three Gorges Reservoir area (TGRA), landslides experience step-like deformations (i.e., periods of stability interrupted by abrupt accelerations) generally from April to September due to the influence of precipitation and reservoir scheduled level variations. With respect to many traditional machine learning techniques, two issues exist relative to displacement prediction, namely the random fluctuation of prediction results and inaccurate prediction when step-like deformations take place. In this study, a novel and original prediction method was proposed by combining the wavelet transform (WT) and particle swarm optimization-kernel extreme learning machine (PSO-KELM) methods, and by considering the landslide causal factors. A typical landslide with a step-like behavior, the Baishuihe landslide in TGRA, was taken as a case study. The cumulated total displacement was decomposed into trend displacement, periodic displacement (controlled by internal geological conditions and external triggering factors respectively), and noise. The displacement items were predicted separately by multi-factor PSO-KELM considering various causal factors, and the total displacement was obtained by summing them up. An accurate prediction was achieved by the proposed method, including the step-like deformation period. The performance of the proposed method was compared with that of the multi-factor extreme learning machine (ELM), support vector regression (SVR), backward propagation neural network (BPNN), and single-factor PSO-KELM. Results show that the PSO-KELM outperforms the other models, and the prediction accuracy can be improved by considering causal factors.     

Improving basin scale shallow landslide modelling using reliable soil thickness maps

Soil thickness is a well-known factor controlling shallow landsliding. Notwithstanding, its spatial organisation over large areas is poorly understood, and in basin scale slope analyses it is often established using simple methods. In this paper, we apply five different soil thickness models in two test sites, and we use the obtained soil thickness maps to feed a slope stability model. Validation quantifies how errors in soil thickness influence the resulting factor of safety and points out which method grants the best results. In particular, in our cases, slope-derived soil thickness patterns produced the worst slope stability assessment, while the use of reliable soil thickness maps obtained by means of a more complex geomorphologically indexed model improved shallow landslides modelling.     

Increased aridity in the Mediterranean region under greenhouse gas forcing estimated from high resolution simulations with a regional climate model

We use three measures of aridity, the Köppen climate classification, the UNEP aridity index and the Budyko dryness index, to estimate the possible effects of late 21st century climate change on the Mediterranean region under increased greenhouse gas concentrations (A2 and B2 IPCC emission scenarios) as simulated with a high resolution (20 km grid interval) regional climate model (the ICTP RegCM). A basic validation of the reference simulation along with a brief discussion of the surface climate changes for the A2 and B2 scenarios is also provided. Analysis of the changes in all three aridity measures indicates that by the end of the 21st century the Mediterranean region might experience a substantial increase in the northward extension of dry and arid lands, particularly in the central and southern portions of the Iberian, Italian, Hellenic and Turkish peninsulas and in areas of southeastern Europe (e.g. Romania and Bulgaria), the Middle East, northern Africa and major Islands (Corsica, Sardinia and Sicily). Most Ice-Cap areas of the Alps are also projected to disappear. These effects are due to a large warming and pronounced decrease in precipitation, especially during the spring and summer seasons. In addition, fine scale topography and coastline features affect the aridity change signal. We identify the southern Mediterranean as a region particularly vulnerable to water stress and desertification processes under climate change conditions.     

Integrated geophysical methods for the characterisation of an archaeological site (Massenzio Basilica — Roman forum, Rome, Italy)

A geophysical study that involved different techniques was carried out with the aim to improve the knowledge of the archaeological site where the Basilica of Maxentius was founded and to discern individual covered structures (foundations).Vertical Electrical Sounding (VES), seismic refraction and Electrical Resistivity Tomography (ERT) studies were performed in the archaeological site. VES and seismic refraction allowed to characterise the main geological formations of the hill where the Basilica was built and to distinguish the concrete floor and backfilling. Electrical data were processed using different algorithms; their results were compared to appraise the inverted models' robustness.ERT inversion algorithms were used to delineate shape and size of a much more complex structure, that were originally expected from archaeological excavation plan. The results of the commercial program were used as a posteriori information to include them in the algorithm proposed by the authors; the sequential use of the programs defined a processing procedure.The integrated use of different geophysical techniques reduced a great deal the intrinsic ambiguities of each method. Direct explorations (boreholes and archaeological excavations) confirmed the geophysical results.