The Relative Importance of Factors Influencing Tropical Cyclone Rapid Intensity Changes

2019 ◽  
Vol 46 (4) ◽  
pp. 2282-2292 ◽  
Author(s):  
Saiprasanth Bhalachandran ◽  
Ziad S. Haddad ◽  
Svetla M. Hristova‐Veleva ◽  
F. D. Marks Jr.
Keyword(s):  
Tropical Cyclone ◽  
Relative Importance ◽  
Factors Influencing ◽  
Intensity Changes

scholarly journals Precipitation Properties Observed during Tropical Cyclone Intensity Change

2015 ◽  
Vol 143 (11) ◽  
pp. 4476-4492 ◽  
Author(s):  
George R. Alvey III ◽  
Jonathan Zawislak ◽  
Edward Zipser
Keyword(s):  
Tropical Cyclone ◽  
Passive Microwave ◽  
Intensity Change ◽  
Rapid Intensification ◽  
Relative Importance ◽  
Tropical Cyclone Intensity ◽  
Cyclone Intensity ◽  
East Pacific ◽  
Intensity Changes ◽  
Strong Convection

Abstract Using a 15-yr (1998–2012) multiplatform dataset of passive microwave satellite data [tropical cyclone–passive microwave (TC-PMW)] for Atlantic and east Pacific storms, this study examines the relative importance of various precipitation properties, specifically convective intensity, symmetry, and area, to the spectrum of intensity changes observed in tropical cyclones. Analyses are presented not only spatially in shear-relative quadrants around the center, but also every 6 h during a 42-h period encompassing 18 h prior to onset of intensification to 24 h after. Compared to those with slower intensification rates, storms with higher intensification rates (including rapid intensification) have more symmetric distributions of precipitation prior to onset of intensification, as well as a greater overall areal coverage of precipitation. The rate of symmetrization prior to, and during, intensification increases with increasing intensity change as rapidly intensifying storms are more symmetric than slowly intensifying storms. While results also clearly show important contributions from strong convection, it is concluded that intensification is more closely related to the evolution of the areal, radial, and symmetric distribution of precipitation that is not necessarily intense.

scholarly journals Socioeconomic Risks and Their Impacts on Ecological River Health in South Korea: An Application of the Analytic Hierarchy Process

2021 ◽  
Vol 13 (11) ◽  
pp. 6287
Author(s):  
Suyeon Kim ◽  
Sang-Woo Lee ◽  
Se-Rin Park ◽  
Yeeun Shin ◽  
Kyungjin An
Keyword(s):  
South Korea ◽  
Socioeconomic Factors ◽  
Ecosystem Health ◽  
Relative Importance ◽  
River Ecosystem ◽  
River Health ◽  
Analytic Hierarchy ◽  
Factors Affecting ◽  
Factors Influencing ◽  
Hierarchy Process

It is imperative to develop a methodology to identify river impairment sources, particularly the relative impact of socioeconomic sources, to enhance the efficiency of various river restoration schemes and policies and to have an internal diagnosis system in place. This study, therefore, aims to identify and analyze the relative importance of the socioeconomic factors affecting river ecosystem impairment in South Korea. To achieve this goal, we applied the Analytical Hierarchy Process (AHP) to evaluate expert judgement of the relative importance of different socioeconomic factors influencing river ecosystem impairment. Based on a list of socioeconomic factors influencing stream health, an AHP questionnaire was prepared and administered to experts in aquatic ecology. Our analysis reveals that secondary industries form the most significant source of stream ecosystem impairment. Moreover, the most critical socioeconomic factors affecting stream impairment are direct inflow pollution, policy implementation, and industrial wastewater. The results also suggest that the AHP is a rapid and robust approach to assessing the relative importance of different socioeconomic factors that affect river ecosystem health. The results can be used to assist decision makers in focusing on actions to improve river ecosystem health.

scholarly journals Tropical Cyclone Intensity Change Prediction Based on Surrounding Environmental Conditions with Deep Learning

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2685
Author(s):  
Xin Wang ◽  
Wenke Wang ◽  
Bing Yan
Keyword(s):  
Deep Learning ◽  
Tropical Cyclone ◽  
Environmental Conditions ◽  
Environmental Variables ◽  
Intensity Change ◽  
Prediction Algorithm ◽  
Hybrid Features ◽  
Distribution Features ◽  
Intensity Changes ◽  
Change Prediction

Tropical cyclone (TC) motion has an important impact on both human lives and infrastructure. Predicting TC intensity is crucial, especially within the 24 h warning time. TC intensity change prediction can be regarded as a problem of both regression and classification. Statistical forecasting methods based on empirical relationships and traditional numerical prediction methods based on dynamical equations still have difficulty in accurately predicting TC intensity. In this study, a prediction algorithm for TC intensity changes based on deep learning is proposed by exploring the joint spatial features of three-dimensional (3D) environmental conditions that contain the basic variables of the atmosphere and ocean. These features can also be interpreted as fused characteristics of the distributions and interactions of these 3D environmental variables. We adopt a 3D convolutional neural network (3D-CNN) for learning the implicit correlations between the spatial distribution features and TC intensity changes. Image processing technology is also used to enhance the data from a small number of TC samples to generate the training set. Considering the instantaneous 3D status of a TC, we extract deep hybrid features from TC image patterns to predict 24 h intensity changes. Compared to previous studies, the experimental results show that the mean absolute error (MAE) of TC intensity change predictions and the accuracy of the classification as either intensifying or weakening are both significantly improved. The results of combining features of high and low spatial layers confirm that considering the distributions and interactions of 3D environmental variables is conducive to predicting TC intensity changes, thus providing insight into the process of TC evolution.

Knowledge Sharing Motivation

2020 ◽  
pp. 171-200
Author(s):  
Nelly Todorova ◽  
Annette M. Mills
Keyword(s):  
Knowledge Management ◽  
Knowledge Sharing ◽  
Integrated Model ◽  
Motivational Factors ◽  
Relative Importance ◽  
Model Based ◽  
Factors Influencing ◽  
Extrinsic Motivators ◽  
Reward Programs ◽  
Social Behaviours

Organisations invest heavily in knowledge management technologies and initiatives which are entirely dependent on the willingness of employees to share their knowledge. Educational and reward programs need to be informed by an understanding of what motivates people to share their knowledge at work. Prior research based on motivational theories suggests the importance of intrinsic and extrinsic motivators to encourage voluntary pro-social behaviours such as knowledge sharing. However, the literature on motivation in the context of knowledge sharing is still emerging and fragmented. This chapter therefore proposes an integrated model that brings together theoretical insights from motivational research to explain the influence of key intrinsic and extrinsic motivators on knowledge sharing. The chapter reports the results of the assessment of the model based on data collected across 10 organisations. The discussion of results contributes to the understanding of motivational factors influencing attitude and intention to share knowledge and their relative importance.

The relative importance of biotic and abiotic factors influencing aspen recruitment in Arizona

2019 ◽  
Vol 441 ◽  
pp. 32-41 ◽  
Author(s):  
Matthew J. Clement ◽  
Larisa E. Harding ◽  
Richard W. Lucas ◽  
Esther S. Rubin
Keyword(s):  
Abiotic Factors ◽  
Relative Importance ◽  
Biotic And Abiotic Factors ◽  
Factors Influencing

scholarly journals Experience is Key: Examining the Relative Importance of Factors Influencing Individuals’ Water Conservation

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1870 ◽  
Author(s):  
Derrick Holland ◽  
Kristina Janét ◽  
Asheley Landrum
Keyword(s):  
Water Scarcity ◽  
Water Conservation ◽  
Message Framing ◽  
Policy Decision ◽  
Decision Makers ◽  
Individual Factors ◽  
Relative Importance ◽  
Attitudes And Behaviors ◽  
Factors Influencing ◽  
Resource Managers

Conservation of our global natural resources is one of the most pressing concerns facing our international society. One of these crucial resources is water. The current study sought to understand how individual factors such as experience with water scarcity, message framing, and ideology can impact perceptions, attitudes, and behaviors related to water conservation. Through the utilization of an online experiment, the current findings suggest that higher levels of experience with water scarcity predict more concern, more positive credibility perceptions of water conservation messages, and a higher likelihood of conserving water in the future. Message framing, specifically gain frames, predicted more concern and more positive perceptions of message credibility, and ideology only predicted perceptions of message credibility. Implications for global communities, resource managers, and policy decision-makers are discussed.

scholarly journals Performance of a New Convective Parameterization Scheme on Model Convergence in Simulations of a Tropical Cyclone at Grey-Zone Resolutions

2014 ◽  
Vol 71 (6) ◽  
pp. 2078-2088 ◽  
Author(s):  
Yuan Sun ◽  
Lan Yi ◽  
Zhong Zhong ◽  
Yao Ha
Keyword(s):  
Tropical Cyclone ◽  
Radial Pressure ◽  
Cumulus Parameterization ◽  
Parameterization Scheme ◽  
Convective Heating ◽  
Finite Limit ◽  
Grey Zone ◽  
Gray Zone ◽  
Grid Spacing ◽  
Intensity Changes

Abstract The latest version of the Weather Research and Forecasting model (WRFV3.5) is used to evaluate the performance of the Grell and Freitas (GF13) cumulus parameterization scheme on the model convergence in simulations of a tropical cyclone (TC) at gray-zone resolutions. The simulated TC intensity converges to a finite limit as the grid spacing varies from 7.5 to 1 km. The reasons for the model convergence are investigated from perspectives of subgrid-scale processes and thermodynamic and dynamic structures. It is found that the impacts of above factors are notably different with varying model resolutions. The convective heating and drying increase as the grid spacing decreases, which inhibits the explicit microphysical parameterization preventing the simulated TC from overly intensifying. As the grid spacing decreases from 7.5 to 5 km, the TC intensity increases because of a stronger secondary circulation, a larger magnitude and proportion of strong eyewall updraft, and a greater amount of latent heating in the eyewall. As the grid spacing decreases from 5 to 3 km, the radius of maximum wind (RMW) decreases and the radial pressure gradient increases leading to an increase in TC intensity. The simulated TC intensity changes slightly as the grid spacing decreases from 3 to 1 km since the RMW and the storm structure both change little. The slight changes in the simulated TC intensity at such high resolutions indicate a great model convergence. Therefore, the GF13 presents an appropriate option that increases the model convergence in the TC intensity simulation at gray-zone resolution.

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