Assessing characteristics of Mediterranean explosive cyclones for different data resolution

Understanding the drivers of wildfire occurrence is of great value for fire prevention and management, but due to the variation in research methods, data sources, and data resolution of those studies, it is challenging to conduct a large-scale comprehensive comparative qualitative analysis on the topic. China has diverse vegetation types and topography, and has undergone rapid economic and social development, but experiences a high frequency of wildfires, making it one of the ideal locations for wildfire research. We applied the Random Forests modelling approach to explore the main types of wildfire drivers (climate factors, landscape factors and human factors) in three high wildfire density regions (Northeast (NE), Southwest (SW), and Southeast (SE)) of China. The results indicate that climate factors were the main driver of wildfire occurrence in the three regions. Precipitation and temperature significantly impacted the fire occurrence in the three regions due to the direct influence on the moisture content of forest fuel. However, wind speed had important influence on fire occurrence in the SE and SW. The explanation power of the landscape and human factors varied significantly between regions. Human factors explained 40% of the fire occurrence in the SE but only explained less than 10% of the fire occurrence in the NE and SW. The density of roads was identified as the most important human factor driving fires in all three regions, but railway density had more explanation power on fire occurrence in the SE than in the other regions. The landscape factors showed nearly no influence on fire occurrence in the NE but explained 46.4% and 20.6% in the SE and SW regions, respectively. Amongst landscape factors, elevation had the highest average explanation power on fire occurrence in the three regions, particularly in the SW. In conclusion, this study provides useful insights into targeted fire prediction and prevention, which should be more precise and effective under climate change and socio-economic development.

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Co-Simulation Framework for Optimal Allocation and Power Management of DGs in Power Distribution Networks Based on Computational Intelligence Techniques

Electronics ◽

10.3390/electronics10141648 ◽

2021 ◽

Vol 10 (14) ◽

pp. 1648

Author(s):

Marinko Barukčić ◽

Toni Varga ◽

Vedrana Jerković Jerković Štil ◽

Tin Benšić

Keyword(s):

Power System ◽

Power Management ◽

Computational Intelligence ◽

Input Data ◽

Optimization Problem ◽

Optimal Allocation ◽

Distribution Networks ◽

Distributed Generations ◽

Data Resolution ◽

The Impact

The paper researches the impact of the input data resolution on the solution of optimal allocation and power management of controllable and non-controllable renewable energy sources distributed generation in the distribution power system. Computational intelligence techniques and co-simulation approach are used, aiming at more realistic system modeling and solving the complex optimization problem. The optimization problem considers the optimal allocation of all distributed generations and the optimal power control of controllable distributed generations. The co-simulation setup employs a tool for power system analysis and a metaheuristic optimizer to solve the optimization problem. Three different resolutions of input data (generation and load profiles) are used: hourly, daily, and monthly averages over one year. An artificial neural network is used to estimate the optimal output of controllable distributed generations and thus significantly decrease the dimensionality of the optimization problem. The proposed procedure is applied on a 13 node test feeder proposed by the Institute of Electrical and Electronics Engineers. The obtained results show a huge impact of the input data resolution on the optimal allocation of distributed generations. Applying the proposed approach, the energy losses are decreased by over 50–70% by the optimal allocation and control of distributed generations depending on the tested network.

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Tomographic resolution limits for diffraction imaging

Interpretation ◽

10.1190/int-2014-0079.1 ◽

2015 ◽

Vol 3 (1) ◽

pp. SF15-SF20 ◽

Cited By ~ 3

Author(s):

Yunsong Huang ◽

Dongliang Zhang ◽

Gerard T. Schuster

Keyword(s):

Numerical Simulations ◽

Diffraction Data ◽

Signal To Noise Ratio ◽

Signal To Noise ◽

Specular Reflections ◽

Data Resolution ◽

Resolution Limits ◽

Diffraction Imaging ◽

Noise Ratio

We derived formulas for the tomographic resolution limits [Formula: see text] of diffraction data. Resolution limits exhibited that diffractions can provide twice or more the tomographic resolution of specular reflections and therefore led to more accurate reconstructions of velocities between layers. Numerical simulations supported this claim in which the tomogram inverted from diffraction data was noticeably more resolved compared to that inverted from specular data. The specular synthetics were generated by sources on the surface, and the diffraction data were generated by buried diffractors. However, this advantage is nullified if the intensity and signal-to-noise ratio of the diffractions are much less than those of the pervasive specular reflections.

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Rossby wave-breaking analysis of explosive cyclones in the Euro-Atlantic sector

Quarterly Journal of the Royal Meteorological Society ◽

10.1002/qj.2190 ◽

2013 ◽

Vol 140 (680) ◽

pp. 738-753 ◽

Cited By ~ 32

Author(s):

Iñigo Gómara ◽

Joaquim G. Pinto ◽

Tim Woollings ◽

Giacomo Masato ◽

Pablo Zurita-Gotor ◽

...

Keyword(s):

Rossby Wave ◽

Wave Breaking ◽

Atlantic Sector ◽

Rossby Wave Breaking ◽

Explosive Cyclones

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The concurrence of Atmospheric Rivers and explosive cyclogenesis in the North Atlantic and North Pacific basins

10.5194/esd-2017-76 ◽

2017 ◽

Author(s):

Jorge Eiras-Barca ◽

Alexandre M. Ramos ◽

Joaquim G. Pinto ◽

Ricardo M. Trigo ◽

Margarida L. R. Liberato ◽

...

Keyword(s):

North Atlantic ◽

North Pacific ◽

Reanalysis Data ◽

Water Vapour Flux ◽

Atmospheric Rivers ◽

The North ◽

Explosive Cyclones ◽

The North Atlantic ◽

Characteristic Features ◽

Western Side

Abstract. The explosive cyclogenesis of extra-tropical cyclones and the occurrence of atmospheric rivers are characteristic features of baroclinic atmospheres, and are both closely related to extreme hydrometeorological events in the mid-latitudes, particularly on coastal areas on the western side of the continents. The potential role of atmospheric rivers in the explosive cyclone deepening has been previously analysed for selected case studies, but a general assessment from the climatological perspective is still missing. Using ERA-Interim reanalysis data for 1979–2011, we analyse the concurrence of atmospheric rivers and explosive cyclogenesis over the North Atlantic and North Pacific Basins for the extended winter months (ONDJFM). Atmospheric rivers are identified for almost 80 % of explosive deepening cyclones. For non-explosive cyclones, atmospheric rivers are found only in roughly 40 % of the cases. The analysis of the time evolution of the high values of water vapour flux associated with the atmospheric river during the cyclone development phase leads us to hypothesize that the identified relationship is the fingerprint of a mechanism that raises the odds of an explosive cyclogenesis occurrence and not merely a statistical relationship. This insight can be helpful for the predictability of high impact weather associated with explosive cyclones and atmospheric rivers.

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Application of UAV-SfM photogrammetry and aerial lidar to a disastrous flood: repeated topographic measurement of a newly formed crevasse splay of the Kinu River, central Japan

Natural Hazards and Earth System Science ◽

10.5194/nhess-17-1505-2017 ◽

2017 ◽

Vol 17 (9) ◽

pp. 1505-1519 ◽

Cited By ~ 11

Author(s):

Atsuto Izumida ◽

Shoichiro Uchiyama ◽

Toshihiko Sugai

Keyword(s):

Lidar Data ◽

High Definition ◽

Central Japan ◽

Aerial Photos ◽

Data Resolution ◽

Disastrous Flood ◽

Surface Models ◽

Elevation Changes ◽

Aerial Vehicle ◽

Crevasse Splay

Abstract. Geomorphic impacts of a disastrous crevasse splay that formed in September 2015 and its post-formation modifications were quantitatively documented by using repeated, high-definition digital surface models (DSMs) of an inhabited and cultivated floodplain of the Kinu River, central Japan. The DSMs were based on pre-flood (resolution: 2 m) and post-flood (resolution: 1 m) aerial light detection and ranging (lidar) data from January 2007 and September 2015, respectively, and on structure-from-motion (SfM) photogrammetry data (resolution: 3.84 cm) derived from aerial photos taken by an unmanned aerial vehicle (UAV) in December 2015. After elimination of systematic errors among the DSMs and down-sampling of the SfM-derived DSM, elevation changes on the order of 10−1 m – including not only topography but also growth of vegetation, vanishing of flood waters, and restoration and repair works – were detected. Comparison of the DSMs showed that the volume eroded by the flood was more than twice the deposited volume in the area within 300–500 m of the breached artificial levee, where the topography was significantly affected. The results suggest that DSMs based on a combination of UAV-SfM and lidar data can be used to quantify, rapidly and in rich detail, topographic changes on floodplains caused by floods.

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SIR2004: an improved tool for crystal structure determination and refinement

Journal of Applied Crystallography ◽

10.1107/s002188980403225x ◽

2005 ◽

Vol 38 (2) ◽

pp. 381-388 ◽

Cited By ~ 2020

Author(s):

Maria C. Burla ◽

Rocco Caliandro ◽

Mercedes Camalli ◽

Benedetta Carrozzini ◽

Giovanni L. Cascarano ◽

...

Keyword(s):

Crystal Structure ◽

Ab Initio ◽

Structure Determination ◽

Protein Structures ◽

Medium Size ◽

Graphical Interface ◽

Asymmetric Unit ◽

Density Maps ◽

Data Resolution ◽

User Friendly

SIR2004is the evolution of theSIR2002program [Burla, Camalli, Carrozzini, Cascarano, Giacovazzo, Polidori & Spagna (2003).J. Appl. Cryst.36, 1103]. It is devoted to the solution of crystal structures by direct and Patterson methods. Several new features implemented inSIR2004make this program efficient: it is able to solveab initioboth small/medium-size structures as well as macromolecules (up to 2000 atoms in the asymmetric unit). In favourable circumstances, the program is also able to solve protein structures with data resolution up to 1.4–1.5 Å, and to provide interpretable electron density maps. A powerful user-friendly graphical interface is provided.

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Space syntax visibility graph analysis is not robust to changes in spatial and temporal resolution

Environment and Planning B Urban Analytics and City Science ◽

10.1177/2399808319897624 ◽

2020 ◽

pp. 239980831989762 ◽

Cited By ~ 1

Author(s):

Jonathan D Ericson ◽

Elizabeth R Chrastil ◽

William H Warren

Keyword(s):

Motion Tracking ◽

Space Syntax ◽

Sampling Strategies ◽

Sampled Data ◽

Spatiotemporal Resolution ◽

Data Transformations ◽

Data Resolution ◽

Environmental Geometry ◽

Visibility Graph Analysis ◽

Predictive Strength

Space syntax is an influential framework for quantifying the relationship between environmental geometry and human behavior. Although many studies report high syntactic–behavioral correlations, previous pedestrian data were collected at low spatiotemporal resolutions, and data transformations and sampling strategies vary widely; here, we systematically test the robustness of space syntax’s predictive strength by examining how these factors impact correlations. We used virtual reality and motion tracking to correlate 30 syntactic measures with high resolution walking trajectories downsampled at 10 grid resolutions and subjected to various log transformations. Overall, correlations declined with increasing grid resolution and were sensitive to data transformations. Moreover, simulations revealed spuriously high correlations (e.g. R2 = 1) with sparsely sampled data (<23 locations). These results strongly suggest that syntactic–behavioral correlations are not robust to changes in spatiotemporal resolution, and that high correlations obtained in previous studies could be inflated due to transformations, data resolution, or sampling strategies.

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The effect of input data resolution and complexity on the uncertainty of hydrological predictions in a humid vegetated watershed

Hydrology and Earth System Sciences ◽

10.5194/hess-22-5947-2018 ◽

2018 ◽

Vol 22 (11) ◽

pp. 5947-5965 ◽

Cited By ~ 1

Author(s):

Linh Hoang ◽

Rajith Mukundan ◽

Karen E. B. Moore ◽

Emmet M. Owens ◽

Tammo S. Steenhuis

Keyword(s):

Land Use ◽

Parameter Uncertainty ◽

Input Data ◽

Hydrological Modeling ◽

Assessment Tool ◽

Model Performance ◽

Data Complexity ◽

Delaware River ◽

Output Uncertainty ◽

Data Resolution

Abstract. Uncertainty in hydrological modeling is of significant concern due to its effects on prediction and subsequent application in watershed management. Similar to other distributed hydrological models, model uncertainty is an issue in applying the Soil and Water Assessment Tool (SWAT). Previous research has shown how SWAT predictions are affected by uncertainty in parameter estimation and input data resolution. Nevertheless, little information is available on how parameter uncertainty and output uncertainty are affected by input data of varying complexity. In this study, SWAT-Hillslope (SWAT-HS), a modified version of SWAT capable of predicting saturation-excess runoff, was applied to assess the effects of input data with varying degrees of complexity on parameter uncertainty and output uncertainty. Four digital elevation model (DEM) resolutions (1, 3, 10 and 30 m) were tested for their ability to predict streamflow and saturated areas. In a second analysis, three soil maps and three land use maps were used to build nine SWAT-HS setups from simple to complex (fewer to more soil types/land use classes), which were then compared to study the effect of input data complexity on model prediction/output uncertainty. The case study was the Town Brook watershed in the upper reaches of the West Branch Delaware River in the Catskill region, New York, USA. Results show that DEM resolution did not impact parameter uncertainty or affect the simulation of streamflow at the watershed outlet but significantly affected the spatial pattern of saturated areas, with 10m being the most appropriate grid size to use for our application. The comparison of nine model setups revealed that input data complexity did not affect parameter uncertainty. Model setups using intermediate soil/land use specifications were slightly better than the ones using simple information, while the most complex setup did not show any improvement from the intermediate ones. We conclude that improving input resolution and complexity may not necessarily improve model performance or reduce parameter and output uncertainty, but using multiple temporal and spatial observations can aid in finding the appropriate parameter sets and in reducing prediction/output uncertainty.

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