The Experts below are selected from a list of 259389 Experts worldwide ranked by ideXlab platform
Zhongshi Zhang - One of the best experts on this subject based on the ideXlab platform.
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do Climate simulations support the existence of east asian monsoon Climate in the late eocene
Palaeogeography Palaeoclimatology Palaeoecology, 2018Co-Authors: Xiangyu Li, Zhongshi Zhang, Ran ZhangAbstract:Abstract Early synthesis of geologic evidence demonstrated that a zonal Climate pattern once dominated China in the Paleogene. The zonal Climate pattern is very different from the non-zonal modern monsoon Climate pattern. It has been hypothesized that the transition from a zonal to non-zonal pattern is related to the initiation of the East Asian monsoon. The earliest timing of East Asian monsoon initiation is suggested to be the Late Eocene, although this is still the subject of hot debate. Here, we use the low-resolution Norwegian Earth System Model (NorESM-L) and the high-resolution Community Atmosphere Model version 4 (CAM4) to simulate the Climate in China for the Early and Late Eocene and further evaluate the Climate Effect of topography and sea-surface temperature (SST) on East Asian regional Climate. Our simulations supported a zonal/zonal-like arid desert/steppe Climate band appearance in China in the Early Eocene, but the zonal band very likely disappeared in the Late Eocene due to increased precipitation over East China. The increased precipitation is caused by intensified summer southerlies, associated with the westward extension of the western Pacific subtropical high (WPSH) in the Late Eocene. However, the disappearance of a zonal Climate band does not sufficiently indicate formation of an East Asian monsoon Climate in the Late Eocene: simulated wind and precipitation seasonality is still much weaker in the Late Eocene and should be distinguished from the modern monsoonal seasonality.
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do Climate simulations support the existence of east asian monsoon Climate in the late eocene
Palaeogeography Palaeoclimatology Palaeoecology, 2018Co-Authors: Xiangyu Li, Zhongshi Zhang, Ran ZhangAbstract:Abstract Early synthesis of geologic evidence demonstrated that a zonal Climate pattern once dominated China in the Paleogene. The zonal Climate pattern is very different from the non-zonal modern monsoon Climate pattern. It has been hypothesized that the transition from a zonal to non-zonal pattern is related to the initiation of the East Asian monsoon. The earliest timing of East Asian monsoon initiation is suggested to be the Late Eocene, although this is still the subject of hot debate. Here, we use the low-resolution Norwegian Earth System Model (NorESM-L) and the high-resolution Community Atmosphere Model version 4 (CAM4) to simulate the Climate in China for the Early and Late Eocene and further evaluate the Climate Effect of topography and sea-surface temperature (SST) on East Asian regional Climate. Our simulations supported a zonal/zonal-like arid desert/steppe Climate band appearance in China in the Early Eocene, but the zonal band very likely disappeared in the Late Eocene due to increased precipitation over East China. The increased precipitation is caused by intensified summer southerlies, associated with the westward extension of the western Pacific subtropical high (WPSH) in the Late Eocene. However, the disappearance of a zonal Climate band does not sufficiently indicate formation of an East Asian monsoon Climate in the Late Eocene: simulated wind and precipitation seasonality is still much weaker in the Late Eocene and should be distinguished from the modern monsoonal seasonality.
Simons D.g. - One of the best experts on this subject based on the ideXlab platform.
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An object-based image analysis approach using bathymetry and bathymetric derivatives to classify the seafloor
'MDPI AG', 2021Co-Authors: Koop L., Snellen M., Simons D.g.Abstract:In this paper, object-based image analysis classification methods are developed that do not rely on backscatter in order to classify the seafloor. Instead, these methods make use of bathymetry, bathymetric derivatives, and grab samples for classification. The classification is performed on image object statistics. One of the methods utilizes only texture-based features, that is, features that are related to the spatial arrangement of image characteristics. The second method is similar, but relies on a wider set of image object features. The methods were developed and tested using a dataset from Norwegian waters, specifically the Røstbanken area off the coast of Lofoten. The classification results were compared to backscatter-based classification and to grab sample ground-reference data. The algorithm that performed the best was then also applied to a dataset from the Borkumer Stones area close to the island of Schiermonnikoog in Dutch waters. This allowed testing the applicability of the algorithm for different datasets. Because the algorithms that were developed do not require backscatter, the availability of which is much more scarce than bathymetry, and because of the low computational requirements, they could be applied to any area where high-resolution bathymetry and grab samples are available.Aircraft Noise and Climate Effect
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Assessing the performance of the multi-beam echo-sounder bathymetric uncertainty prediction model
'MDPI AG', 2020Co-Authors: Mohammadloo, Tannaz H., Snelle M., Simons D.g.Abstract:Realistic predictions of the contribution of the various sources affecting the quality of the bathymetric measurements prior to a survey are of importance to ensure sufficient accuracy of the soundings. To this end, models predicting these contributions have been developed. The objective of the present paper is to assess the performance of the bathymetric uncertainty prediction model for modern Multi-Beam Echo-Sounder (MBES) systems. Two datasets were acquired at water depths of 10m and 30m with three pulse lengths equaling 27 μs, 54 μs, and 134 μs in the Oosterschelde estuary (The Netherlands). The comparison between the bathymetric uncertainties derived from the measurements and those predicted using the current model indicated a relatively good agreement except for the most outer beams. The performance of the uncertainty prediction model improved by accounting for the most recent insights into the contributors to the MBES depth uncertainties, i.e., the Doppler Effect, baseline decorrelation (accounting for the pulse shape), and the signal-to-noise ratio.Aircraft Noise and Climate Effect
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Multi-approach study of nose landing gear noise
'American Institute of Aeronautics and Astronautics (AIAA)', 2020Co-Authors: Merino Martinez R., Simons D.g., Snellen M., Kennedy John, Neri Eleonora, Bennett, Gareth J.Abstract:The noise emissions of a full-scale nose landing gear (NLG), measured in a wind tunnel and obtained from computational simulations, are compared with those of three regional aircraft types recorded in flyover measurements. A comparison is made with the noise prediction models of Fink, Guo, and German Aerospace Center (DLR). A good agreement was found between all the spectra. The noise emissions up to 1.2 kHz were found to scale with the sixth power of the flow velocity, as usual; however, the spectra at higher frequencies collapsed better when scaled to the seventh power, confirming the fact that high-frequency noise is radiated from the turbulent flow surrounding small features of the NLG. Microphone arrays showed that the main noise sources were located in the middle of the wheel axle. For the flyovers and computational simulations, strong tonal peaks (at around 2200 Hz) were found, which are likely to be caused by open cavities in the NLG. This phenomenon is not accounted for in prediction models. Removing these tones would result in noise reductions of up to 2 dB. Thus, it is highly recommended to include cavity-noise estimations in the current prediction models, or to simply eliminate such cavities where possible with the use of cavity caps.Aircraft Noise and Climate Effect
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Monitoring underwater nourishments using multibeam bathymetric and backscatter time series
'Elsevier BV', 2020Co-Authors: Gaida T.c., Snellen M., Van Dijk T.a.g.p., Vermaas Tommer, Mesdag Chris, Simons D.g.Abstract:Natural and man-induced coastal erosion endanger life and environment in coastal areas worldwide. For sedimentary barrier coasts, beach and underwater nourishments are an efficient coastal protection strategy. To optimize nourishments and to understand their impact on the marine environment, monitoring strategies are required. In this study, we investigate the potential of multibeam echosounder (MBES) data, providing both bathymetry and backscatter (BS), for monitoring the evolution of the nourished sediment and morphodynamics over time. A time series of seven MBES measurements, as well as two sets of box cores, vibrocores and seismic data were acquired of a channel-side nourishment near the Wadden Sea island Ameland (The Netherlands), between April 2017 and May 2019. In general, a high confidence of the acoustic reliability of the BS time series measurements is demonstrated. The unsupervised Bayesian classification method, supported by ground-truthing, is employed to produce a time series of sediment maps, revealing sediments ranging from sandy mud to sand with varying amounts of shell fragments. Based on the sediment maps, the nourished sediment could be distinguished from the natural sediment. Within one year, the shell-rich pre-nourishment seabed is recreated by washing out finer sediments, which are deposited towards the main tidal channel. Using the seismic data and vibrocores, the shell-rich pre-nourishment seabed could be identified in the subsurface after being buried by the nourishments, supporting the general findings. Furthermore, a rapid development of steep bedforms with increasing sediment sorting is observed in parts of the nourished areas. This study shows that high-resolution sediment maps obtained from a time series of MBES BS together with bathymetry reveal morphodynamic and sedimentary processes of nourishment evolution and can advance underwater nourishment strategies.Aircraft Noise and Climate Effect
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Using Alternatives to Determine the Shallowest Depth for Bathymetric Charting: Case Study
'American Society of Civil Engineers (ASCE)', 2019Co-Authors: Haji Mohammadloo T., Snelle M., Simons D.g., Dierik E, Icknese SimoAbstract:Methods for gridding multibeam echo sounder (MBES) measurements to equidistant grids are proposed as alternatives to the shallowest measured depth, which is affected by outliers. The approaches considered use a combination of mean and standard deviation of soundings and the regression coefficient from the best fitted plane. These methods along with mean and shallowest depths were applied to two surveyed areas. Two issues were found to be of importance, that is, a proper distribution of soundings and low uncertainties in the depth measurements. Improper sampling excludes using the method employing regression coefficients. For flat areas, the shallowest measured depth was found to be highly influenced by measurement uncertainties, counteracted when using the mean depth. However, the mean depth underestimates the shallowest depth for areas with slopes. When correcting the mean depth for standard deviation, the Effect of slopes is accounted for while the influence of measurement uncertainties is decreased compared to shallowest measured depth. Since the uncertainties are dependent on beam angle, depth, and measurement equipment, these issues need to be accounted for in survey planning.Aircraft Noise and Climate Effect
Jianping Huang - One of the best experts on this subject based on the ideXlab platform.
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a robust low level cloud and clutter discrimination method for ground based millimeter wavelength cloud radar
Atmospheric Measurement Techniques, 2021Co-Authors: Jianping HuangAbstract:Abstract. Low-level clouds play a key role in the energy budget and hydrological cycle of the Climate system. The accurate long-term observation of low-level clouds is essential for understanding their Climate Effect and model constraints. Both ground-based and spaceborne millimeter-wavelength cloud radars can penetrate clouds but the detected low-level clouds are always contaminated by clutter, which needs to be removed. In this study, we develop an algorithm to accurately separate low-level clouds from clutter for ground-based cloud radar using multi-dimensional probability distribution functions along with the Bayesian method. The radar reflectivity, linear depolarization ratio, spectral width, and their dependence on the time of the day, height, and season are used as the discriminants. A low-pass spatial filter is applied to the Bayesian undecided classification mask by considering the spatial correlation difference between clouds and clutter. The final feature mask result has a good agreement with lidar detection, showing a high probability of detection rate (98.45 % ) and a low false alarm rate (0.37 % ). This algorithm will be used to reliably detect low-level clouds at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) site for the study of their Climate Effect and the interaction with local abundant dust aerosol in semi-arid regions.
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a robust low level cloud and clutter discrimination method for ground based millimeter wavelength cloud radar
Atmospheric Measurement Techniques Discussions, 2020Co-Authors: Jianping HuangAbstract:Abstract. Low-level clouds play a key role in the energy budget and hydrological cycle of the Climate system. The long-term and accurate observation of low-level clouds is essential for understanding their Climate Effect and model constraints. Both ground-based and spaceborne millimeter-wavelength cloud radars can penetrate clouds but the detected low-level clouds are always contaminated by clutters, which needs to be removed. In this study, we develop an algorithm to accurately separate low-level clouds from clutters for ground-based cloud radar using multi-dimensional probability distribution functions along with the Bayesian method. The radar reflectivity, linear depolarization ratio, spectral width and their dependences on the time of the day, height and season are used as the discriminants. A low pass spatial filter is applied to the Bayesian undecided classification mask, considering the spatial correlation difference between clouds and clutters. The resulting feature mask shows a good agreement with lidar detection, which has a high probability of detection rate (98.45 %) and a low false alarm rate (0.37 %). This algorithm will be used to reliably detect low-level clouds at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) site, to study their Climate Effect and the interaction with local abundant dust aerosol in semi-arid region.
L Borselli - One of the best experts on this subject based on the ideXlab platform.
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a robust algorithm for estimating soil erodibility in different Climates
Catena, 2012Co-Authors: L Borselli, Dino Torri, P IaquintaAbstract:Abstract The analysis of global soil erodibility data by Salvador Sanchis et al. (2008) showed that there is a significant Climate Effect on soil erodibility which allows for a split of the data into two subsets, one for prevailing cool conditions and another for prevailing warm conditions (defined using the Koppen Climate classification). Despite the recognition of this new dichotomous variable, prediction of soil erodibility values remained very poor. This paper presents a new technique for dealing with such a variability by calculating probability density functions of soil erodibility K values when the user knows a set of textural parameters and the climatic classification of the site. Finally the user has the possibility to decide, on the basis of local knowledge, which K value to use. The procedure has been implemented in a freeware software named KUERY available for the scientific community. Finally, as an illustration, the methodology is applied to a catchment in south Italy.
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Climate Effects on soil erodibility
Earth Surface Processes and Landforms, 2008Co-Authors: M Salvador P Sanchis, Dino Torri, L BorselliAbstract:Soil erodibility data, calculated using measured soil loss from standard runoff plots, collected over at least one year and applying the standard requirements for calculating the soil erodibility factor (K) of the Universal Soil Loss Equation (USLE), have been analysed to investigate whether Climate affects the susceptibility of soils to water erosion. In total, more than 300 K-values extracted from the literature have been analysed. Due to the limited availability of data related to the characteristics of the soil and the location of the measuring sites, all the analysis has been carried out using only soil textural characteristics, organic matter content, rock fragment content and the some general characteristics of the climatic zone where the plots were located. The first evidence of a strong Climate Effect on soil erodibility is shown by the seasonal variation of mean monthly soil erodibility (Km). Using data collected in the USA and Italy an Effect of mean monthly air temperature on Km could be identified. Data collected in Indonesia (where mean monthly air temperature remains fairly constant throughout the year) showed comparable variations of monthly soil erodibility. However, it was impossible to explain these variations in Km as no other data than mean monthly air temperature were available. Mean annual soil erodibility shows a clear Climate Effect. Soil erodibilities can be subdivided into two large groups, one corresponding to soils in cool Climates (Df and Cf Climate according to the Koppen–Geiger Climate classification) and another to soils located in warm Climates (tropical Af and Aw Climates). Erodibilities of Mediterranean soils (found under Cs Climate) plot among the soils found in Af and Aw Climates. These subdivisions can be made for both stony and non-stony soils. Limited data suggest that soil aggregate stability is a good predictor for explaining soil erodibility variations between different Climate zones. Copyright © 2007 John Wiley & Sons, Ltd.
Xiangyu Li - One of the best experts on this subject based on the ideXlab platform.
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do Climate simulations support the existence of east asian monsoon Climate in the late eocene
Palaeogeography Palaeoclimatology Palaeoecology, 2018Co-Authors: Xiangyu Li, Zhongshi Zhang, Ran ZhangAbstract:Abstract Early synthesis of geologic evidence demonstrated that a zonal Climate pattern once dominated China in the Paleogene. The zonal Climate pattern is very different from the non-zonal modern monsoon Climate pattern. It has been hypothesized that the transition from a zonal to non-zonal pattern is related to the initiation of the East Asian monsoon. The earliest timing of East Asian monsoon initiation is suggested to be the Late Eocene, although this is still the subject of hot debate. Here, we use the low-resolution Norwegian Earth System Model (NorESM-L) and the high-resolution Community Atmosphere Model version 4 (CAM4) to simulate the Climate in China for the Early and Late Eocene and further evaluate the Climate Effect of topography and sea-surface temperature (SST) on East Asian regional Climate. Our simulations supported a zonal/zonal-like arid desert/steppe Climate band appearance in China in the Early Eocene, but the zonal band very likely disappeared in the Late Eocene due to increased precipitation over East China. The increased precipitation is caused by intensified summer southerlies, associated with the westward extension of the western Pacific subtropical high (WPSH) in the Late Eocene. However, the disappearance of a zonal Climate band does not sufficiently indicate formation of an East Asian monsoon Climate in the Late Eocene: simulated wind and precipitation seasonality is still much weaker in the Late Eocene and should be distinguished from the modern monsoonal seasonality.
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do Climate simulations support the existence of east asian monsoon Climate in the late eocene
Palaeogeography Palaeoclimatology Palaeoecology, 2018Co-Authors: Xiangyu Li, Zhongshi Zhang, Ran ZhangAbstract:Abstract Early synthesis of geologic evidence demonstrated that a zonal Climate pattern once dominated China in the Paleogene. The zonal Climate pattern is very different from the non-zonal modern monsoon Climate pattern. It has been hypothesized that the transition from a zonal to non-zonal pattern is related to the initiation of the East Asian monsoon. The earliest timing of East Asian monsoon initiation is suggested to be the Late Eocene, although this is still the subject of hot debate. Here, we use the low-resolution Norwegian Earth System Model (NorESM-L) and the high-resolution Community Atmosphere Model version 4 (CAM4) to simulate the Climate in China for the Early and Late Eocene and further evaluate the Climate Effect of topography and sea-surface temperature (SST) on East Asian regional Climate. Our simulations supported a zonal/zonal-like arid desert/steppe Climate band appearance in China in the Early Eocene, but the zonal band very likely disappeared in the Late Eocene due to increased precipitation over East China. The increased precipitation is caused by intensified summer southerlies, associated with the westward extension of the western Pacific subtropical high (WPSH) in the Late Eocene. However, the disappearance of a zonal Climate band does not sufficiently indicate formation of an East Asian monsoon Climate in the Late Eocene: simulated wind and precipitation seasonality is still much weaker in the Late Eocene and should be distinguished from the modern monsoonal seasonality.