scholarly journals Integrating geologic fault data into tsunami hazard studies

2013 ◽  
Vol 13 (4) ◽  
pp. 1025-1050 ◽  
Author(s):  
R. Basili ◽  
M. M. Tiberti ◽  
V. Kastelic ◽  
F. Romano ◽  
A. Piatanesi ◽  
...  
Keyword(s):  
Epistemic Uncertainty ◽  
Hazard Analysis ◽  
Regional Scale ◽  
Tsunami Hazard ◽  
Central Mediterranean ◽  
Data Set ◽  
Systematic Classification ◽  
Crustal Earthquakes ◽  
Starting Point ◽  
The Impact

Abstract. We present the realization of a fault-source data set designed to become the starting point in regional-scale tsunami hazard studies. Our approach focuses on the parametric fault characterization in terms of geometry, kinematics, and assessment of activity rates, and includes a systematic classification in six justification levels of epistemic uncertainty related with the existence and behaviour of fault sources. We set up a case study in the central Mediterranean Sea, an area at the intersection of the European, African, and Aegean plates, characterized by a complex and debated tectonic structure and where several tsunamis occurred in the past. Using tsunami scenarios of maximum wave height due to crustal earthquakes (Mw=7) and subduction earthquakes (Mw=7 and Mw=8), we illustrate first-order consequences of critical choices in addressing the seismogenic and tsunamigenic potentials of fault sources. Although tsunamis generated by Mw=8 earthquakes predictably affect the entire basin, the impact of tsunamis generated by Mw=7 earthquakes on either crustal or subduction fault sources can still be strong at many locales. Such scenarios show how the relative location/orientation of faults with respect to target coastlines coupled with bathymetric features suggest avoiding the preselection of fault sources without addressing their possible impact onto hazard analysis results.

scholarly journals A Reappraisal of the Prebisch-Singer Hypothesis Using Wavelets Analysis

2021 ◽  
Vol 14 (7) ◽  
pp. 319
Author(s):  
Hany Fahmy
Keyword(s):  
International Trade ◽  
Structural Breaks ◽  
Developing Economies ◽  
Commodity Prices ◽  
Commodity Price ◽  
Data Set ◽  
Price Series ◽  
Long Run ◽  
Starting Point ◽  
The Impact

The Prebisch-Singer (PS) hypothesis, which postulates the presence of a downward secular trend in the price of primary commodities relative to manufacturers, remains at the core of a continuing debate among international trade economists. The reason is that the results of testing the PS hypothesis depend on the starting point of the technical analysis, i.e., stationarity, nonlinearity, and the existence of structural breaks. The objective of this paper is to appraise the PS hypothesis in the short- and long-run by employing a novel multiresolution wavelets decomposition to a unique data set of commodity prices. The paper also seeks to assess the impact of the terms of trade (also known as Incoterms) on the test results. The analysis reveals that the PS hypothesis is not supported in the long run for the aggregate commodity price index and for most of the individual commodity price series forming it. Furthermore, in addition to the starting point of the analysis, the results show that the PS test depends on the term of trade classification of commodity prices. These findings are of particular significance to international trade regulators and policymakers of developing economies that depend mainly on primary commodities in their exports.

Analysis, estimation and prediction criteria for damage from geo-hydrological events: a top-down approach

2020 ◽  
Author(s):  
Ilaria Boschini ◽  
Federica Zambrini ◽  
Givanni Menduni ◽  
Daniela Molinari ◽  
Daniele Bignami
Keyword(s):  
Emergency Management ◽  
Rural Areas ◽  
Regional Scale ◽  
Flood Damage ◽  
Research Field ◽  
Economic Damage ◽  
Data Set ◽  
Commercial Activities ◽  
Intrinsic Complexity ◽  
The Impact

<p>A rapid evaluation of flood damage is strategic for the good success of emergency management activities after a natural disaster. A method for the estimation of economic damage is developed considering the impact of hydrogeological phenomena with meteoclimatic forcing over settlements, industrial and rural areas and commercial activities.</p><p>Damage estimation is a very current research field, but the available methods are far from being effective in the period immediately following the event. This is due particularly to the intrinsic complexity and variability of the damage process and the lack of reliable and consistent damage measures across areas at least at the regional scale.</p><p>This work proposes a national scale first approximation correlation between vulnerated area and expected damage. The relationship, expressed in terms of power law, is calibrated on a huge number of single damage records collected by the Italian government all through the country during flood and landslide events in the last 6 years. Data have been grouped following the type of flood. Records come from official data provided by government commissioners in charge of emergency management, according to the national law. Validation, carried out on an independent data set, is quite encouraging and provides indications for further developments.</p>

scholarly journals Parameterization of oceanic whitecap fraction based on satellite observations

2015 ◽  
Vol 15 (15) ◽  
pp. 21219-21269 ◽  
Author(s):  
M. F. M. A. Albert ◽  
M. D. Anguelova ◽  
A. M. M. Manders ◽  
M. Schaap ◽  
G. de Leeuw
Keyword(s):  
Wind Speed ◽  
Regional Scale ◽  
Regional Analysis ◽  
Global Scale ◽  
Sea Spray ◽  
Emission Rates ◽  
Data Set ◽  
Scale Assessment ◽  
Starting Point ◽  
Speed Dependence

Abstract. In this study the utility of satellite-based whitecap fraction (W) values for the prediction of sea spray aerosol (SSA) emission rates is explored. More specifically, the study is aimed at improving the accuracy of the sea spray source function (SSSF) derived by using the whitecap method through the reduction of the uncertainties in the parameterization of W by better accounting for its natural variability. The starting point is a dataset containing W data, together with matching environmental and statistical data, for 2006. Whitecap fraction W was estimated from observations of the ocean surface brightness temperature TB by satellite-borne radiometers at two frequencies (10 and 37 GHz). A global scale assessment of the data set to evaluate the wind speed dependence of W revealed a quadratic correlation between W and U10, as well as a relatively larger spread in the 37 GHz data set. The latter could be attributed to secondary factors affecting W in addition to U10. To better visualize these secondary factors, a regional scale assessment over different seasons was performed. This assessment indicates that the influence of secondary factors on W is for the largest part imbedded in the exponent of the wind speed dependence. Hence no further improvement can be expected by looking at effects of other factors on the variation in W explicitly. From the regional analysis, a new globally applicable quadratic W(U10) parameterization was derived. An intrinsic correlation between W and U10 that could have been introduced while estimating W from TB was determined, evaluated and presumed to lie within the error margins of the newly derived W(U10) parameterization. The satellite-based parameterization was compared to parameterizations from other studies and was applied in a SSSF to estimate the global SSA emission rate. The thus obtained SSA production for 2006 of 4.1 × 1012 kg is within previously reported estimates. While recent studies that account for parameters other than U10 explicitly could be suitable to improve predictions of SSA emissions, we promote our new W(U10) parameterization as an alternative approach that implicitly accounts for these different parameters and helps to improve SSA emission estimates equally well.

scholarly journals Extrapolating regional probability of drying of headwater streams using discrete observations and gauging networks

2017 ◽  
Author(s):  
Aurélien Beaufort ◽  
Nicolas Lamouroux ◽  
Hervé Pella ◽  
Thibault Datry ◽  
Eric Sauquet
Keyword(s):  
Headwater Streams ◽  
Regional Scale ◽  
National Level ◽  
Ephemeral Streams ◽  
Field Observations ◽  
Discrete Observations ◽  
Data Set ◽  
Intermittent Rivers ◽  
The Impact ◽  
Flow Intermittence

Abstract. Headwater streams represent a substantial proportion of river systems and have frequently flows intermittence due to their upstream position in the network. These intermittent rivers and ephemeral streams have recently seen a marked increase in interest, especially to assess the impact of drying on aquatic ecosystems. The objective of this paper is to quantify how discrete (in space and time) field observations of flow intermittence help to extrapolate the daily probability of drying at the regional scale. Two empirical models based on linear or logistic regressions have been developed to predict the daily probability of intermittence at the regional scale across France. Explanatory variables were derived from available daily discharge and groundwater level data of a dense gauging/piezometer network, and models were calibrated using discrete series of field observations of flow intermittence. The robustness of the models was tested using (1) an independent, dense regional data set of intermittence observations, (2) observations of the year 2017 excluded from the calibration. The resulting models were used to simulate the regional probability of drying in France: (i) over the period 2011–2017 to identify the regions most affected by flow intermittence; (ii) over the period 1989–2017, using a reduced input dataset, to analyze temporal variability of flow intermittence at the national level. The two regressions models performed equally well between 2011 and 2017. The accuracy of predictions depended on the number of continuous gauging/piezometer stations and intermittence observations available to calibrate the regressions. Regions with the highest performance were located in sedimentary plains, where the monitoring network was dense and where the regional probability of drying was the highest. Conversely, worst performances were obtained in mountainous regions. Finally, temporal projections (1989–2016) suggested highest probabilities of intermittence (> 35 %) in 1989–1991, 2003 and 2005. A high density of intermittence observations improved the information provided by gauging stations and piezometers to extrapolate the spatial distribution of intermittent rivers and ephemeral streams.

scholarly journals Parameterization of oceanic whitecap fraction based on satellite observations

2016 ◽  
Vol 16 (21) ◽  
pp. 13725-13751 ◽  
Author(s):  
Monique F. M. A. Albert ◽  
Magdalena D. Anguelova ◽  
Astrid M. M. Manders ◽  
Martijn Schaap ◽  
Gerrit de Leeuw
Keyword(s):  
Wind Speed ◽  
Regional Scale ◽  
Global Scale ◽  
Sea Spray ◽  
Emission Rates ◽  
Data Set ◽  
Starting Point ◽  
Different Seasons ◽  
Sea Spray Aerosol ◽  
Intrinsic Correlation

Abstract. In this study, the utility of satellite-based whitecap fraction (W) data for the prediction of sea spray aerosol (SSA) emission rates is explored. More specifically, the study aims at evaluating how an account for natural variability of whitecaps in the W parameterization would affect SSA mass flux predictions when using a sea spray source function (SSSF) based on the discrete whitecap method. The starting point is a data set containing W data for 2006 together with matching wind speed U10 and sea surface temperature (SST) T. Whitecap fraction W was estimated from observations of the ocean surface brightness temperature TB by satellite-borne radiometers at two frequencies (10 and 37 GHz). A global-scale assessment of the data set yielded approximately quadratic correlation between W and U10. A new global W(U10) parameterization was developed and used to evaluate an intrinsic correlation between W and U10 that could have been introduced while estimating W from TB. A regional-scale analysis over different seasons indicated significant differences of the coefficients of regional W(U10) relationships. The effect of SST on W is explicitly accounted for in a new W(U10, T) parameterization. The analysis of W values obtained with the new W(U10) and W(U10, T) parameterizations indicates that the influence of secondary factors on W is for the largest part embedded in the exponent of the wind speed dependence. In addition, the W(U10, T) parameterization is able to partially model the spread (or variability) of the satellite-based W data. The satellite-based parameterization W(U10, T) was applied in an SSSF to estimate the global SSA emission rate. The thus obtained SSA production rate for 2006 of 4.4  ×  1012 kg year−1 is within previously reported estimates, however with distinctly different spatial distribution.

Performance of response spectral models against New Zealand data

2017 ◽  
Vol 50 (1) ◽  
pp. 21-38 ◽  
Author(s):  
Chris Van Houtte
Keyword(s):  
New Zealand ◽  
Seismic Hazard ◽  
Ground Motion ◽  
Epistemic Uncertainty ◽  
Hazard Analysis ◽  
Strong Motion ◽  
Seismic Hazard Assessment ◽  
Crustal Earthquakes ◽  
Spectral Models ◽  
Strong Motion Database

An important component of seismic hazard assessment is the prediction of the potential ground motion generated by a given earthquake source. In New Zealand seismic hazard studies, it is commonplace for analysts to only adopt one or two models for predicting the ground motion, which does not capture the epistemic uncertainty associated with the prediction. This study analyses a suite of New Zealand and international models against the New Zealand Strong Motion Database, both for New Zealand crustal earthquakes and earthquakes in the Hikurangi subduction zone. It is found that, in general, the foreign models perform similarly or better with respect to recorded New Zealand data than the models specifically derived for New Zealand application. Justification is given for using global models in future seismic hazard analysis in New Zealand. Although this article does not provide definitive model weights for future hazard analysis, some recommendations and guidance are provided.

Classification of 3-DOF 3-UPU Translational Parallel Mechanisms Based on Constraint Singularity Loci Using Gröbner Cover

2021 ◽  
Author(s):  
Xianwen Kong
Keyword(s):  
Parallel Mechanism ◽  
Polynomial Systems ◽  
Coordinate Frame ◽  
Parallel Mechanisms ◽  
Systematic Classification ◽  
Starting Point ◽  
Moving Platform ◽  
Singular Configuration ◽  
The Impact

Abstract A 3-UPU translational parallel mechanism (TPM) is one of typical TPMs. Several types of 3-UPU TPMs have been proposed in the literature. Despite comprehensive studies on 3-UPU TPMs in which the joint axes on the base and the moving platform are coplanar, only a few 3-UPU TPMs with a skewed base and moving platform have been proposed. However, the impact of link parameters on singularity loci of such TPMs has not been systematically investigated. The advances in computing CGS (comprehensive Gröbner system) or Gröbner cover of parametric polynomial systems provide an efficient tool for solving this problem. This paper presents a systematic classification of 3-UPU TPMs, especially those with a skewed base and moving platform, based on constraint singularity loci. First, the constraint singularity equation of a 3-UPU TPM is derived. To simplify this equation, the coordinate frame on the base (or moving platform) is set up such that the centers of three U joints are located on different coordinate axes. Using Gröbner Cover, the 3-UPU TPMs are classified into 20 types based on the constraint singularity loci. Finally, a novel 3-UPU TPM is proposed. Unlike most of existing 3-UPU TPMs which can transit to two or more 3-DOF operation modes at a constraint singular configuration, the proposed 3-UPU TPM can only transit to one general 3-DOF operation mode in a constraint singular configuration. The singularity locus divides the workspace of this 3-UPU TPM into two constraint singularity-free regions. This work provides a solid foundation for the design of 3-UPU TPMs and a starting point for the classification of a general 3-UPU parallel mechanism.

Representation of emissions from European major population centeres in MECO(n) - Lessons learned from EMeRGe-EU

2020 ◽  
Author(s):  
Mariano Mertens ◽  
Astrid Kerkweg ◽  
Patrick Jöckel ◽  
Markus Kilian ◽  
Lisa Eirenschmalz ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Potential Model ◽  
Climate Model ◽  
Regional Scale ◽  
Good Representation ◽  
Data Set ◽  
Mixing Ratios ◽  
Extensive Evaluation ◽  
Sensitivity Studies ◽  
The Impact

<p>Comprehensive regional chemistry-climate or chemistry transport models are important tools to study the impact of emissions from major population centres (MPC) and/or investigate potential mitigation options for MPC emissions. Before such models can be employed it is important to investigate how well the models represent observed atmospheric conditions. This comparison helps not only in judging the performance of the models, but allows to test our understanding of chemical and physical processes in the atmosphere. A prerequisite for an extensive evaluation of models are the availability of temporally and spatially high resolved observational data. Such a data set was obtained during the EMeRGe-Europe campaign of the HALO research aircraft in July 2017, which targeted the outflow of different MPC in Europe.</p><p>We used the data of the EMeRGe-EU campaign together with ground based observations to evaluate the representation of European MPC emissions in the MECO(n) model system. MECO(n) is a global/regional chemistry-climate model which couples the regional chemistry-climate model COSMO-CLM/MESSy on-line (i.e., during runtime) with the global chemistry climate-model EMAC. The dynamics of EMAC is nudged against ERA-Interim reanalysis data. We performed three nesting steps from 300 km on the global scale to 50 km, 12 km and 7 km on the regional scale. In our evaluation we focus on tropospheric ozone (O<sub>3</sub>) and related precursors, methane (CH<sub>4</sub>) and sulphur dioxide (SO<sub>2</sub>). </p><p>Generally, the comparison between the measurements and the model results shows a good representation of European MPC emissions in MECO(n). In detail, however, the measured mixing ratios of carbon monoxide (CO) and reactive nitrogen (NO<sub>y</sub>)  are underestimated, while O<sub>3</sub> and SO<sub>2</sub> are overestimated by the model. Potential reasons for these differences are too efficient vertical mixing, and underestimation of MPC emissions. </p><p>To test hypotheses for potential model improvements we performed additional sensitivity studies with different nudging data for EMAC and an alternative anthropogenic emission inventory. The differences of the model results to the observations, however, are only slightly influenced by these changes. Accordingly, further hypotheses for potential model improvements needs to be investigated.  While the simulated mixing ratios differ only slightly between the sensitivity studies, the ozone source apportionment results (using a tagging approach) show much larger differences. This indicates the large uncertainty of  source apportionment analyses caused by uncertainties of emission inventories and model dynamics and requires further analysis in the future. </p>

scholarly journals Stream temperature prediction in ungauged basins: review of recent approaches and description of a new physics-derived statistical model

2015 ◽  
Vol 19 (9) ◽  
pp. 3727-3753 ◽  
Author(s):  
A. Gallice ◽  
B. Schaefli ◽  
M. Lehning ◽  
M. B. Parlange ◽  
H. Huwald
Keyword(s):  
Statistical Model ◽  
Regional Scale ◽  
Stream Temperature ◽  
New Physics ◽  
Model Structure ◽  
Stream Network ◽  
Ungauged Catchments ◽  
Physical Point ◽  
Data Set ◽  
The Impact

Abstract. The development of stream temperature regression models at regional scales has regained some popularity over the past years. These models are used to predict stream temperature in ungauged catchments to assess the impact of human activities or climate change on riverine fauna over large spatial areas. A comprehensive literature review presented in this study shows that the temperature metrics predicted by the majority of models correspond to yearly aggregates, such as the popular annual maximum weekly mean temperature (MWMT). As a consequence, current models are often unable to predict the annual cycle of stream temperature, nor can the majority of them forecast the inter-annual variation of stream temperature. This study presents a new statistical model to estimate the monthly mean stream temperature of ungauged rivers over multiple years in an Alpine country (Switzerland). Contrary to similar models developed to date, which are mostly based on standard regression approaches, this one attempts to incorporate physical aspects into its structure. It is based on the analytical solution to a simplified version of the energy-balance equation over an entire stream network. Some terms of this solution cannot be readily evaluated at the regional scale due to the lack of appropriate data, and are therefore approximated using classical statistical techniques. This physics-inspired approach presents some advantages: (1) the main model structure is directly obtained from first principles, (2) the spatial extent over which the predictor variables are averaged naturally arises during model development, and (3) most of the regression coefficients can be interpreted from a physical point of view – their values can therefore be constrained to remain within plausible bounds. The evaluation of the model over a new freely available data set shows that the monthly mean stream temperature curve can be reproduced with a root-mean-square error (RMSE) of ±1.3 °C, which is similar in precision to the predictions obtained with a multi-linear regression model. We illustrate through a simple example how the physical aspects contained in the model structure can be used to gain more insight into the stream temperature dynamics at regional scales.

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