Modification of a linear regression-based multi-model super-ensemble technique and its application in forecasting of wave height during extreme weather conditions

2018 ◽  
Vol 11 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Swarnali Majumder ◽  
T. M. Balakrishnan Nair ◽  
K. G. Sandhya ◽  
P. G. Remya ◽  
P. Sirisha
Keyword(s):  
Linear Regression ◽  
Wave Height ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Ensemble Technique

scholarly journals ANALISA TITIK KRITIS GERAKAN ROLL KAPAL TRIMARAN UNTUK DIAPLIKASI PADA KAPAL IKAN PURSE SEINE

2021 ◽  
Vol 4 ◽  
pp. 44-50
Author(s):  
Fella Gaspersz ◽  
Richard B. Luhulima
Keyword(s):  
Critical Point ◽  
Wave Height ◽  
Inclination Angle ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Roll Motion ◽  
Fishing Vessel ◽  
Fishing Vessels ◽  
Wave Heights ◽  
Wave Angle

The marine fisheries catching and processing industry are considered vulnerable to the effects of extreme weather at sea. Global warming effects and El Nino and La Nina have a significant impact on the upwelling process, which impacts the lifestyle and environment of marine biota, including pelagic fish, which is one of the most important contributors to the shipping industry. Extreme weather conditions, with wave heights ranging from 1 to 5 meters, dominate the waters of Maluku. In extreme sea conditions, most fishers choose not to go fishing, not because there are no fish at the fishing grounds, but to avoid mishaps at sea. This research aimed to analyze the critical point of ship roll motion and ship stability. The hull shape employed in this study was a monohull fishing vessel and a trimaran fishing vessel with the same displacement of 21,1 tons. In extreme weather conditions, the Maxsurf software was used to analyze the ship's response, especially the critical point of the ship's roll motion. The I.M.O. Standard was utilized to calculate the ship's stability. The operational speed of the ship was v = 3 knots, with fluctuations in wave angle of incidence between 00 - 1800. Wave heights of 1,0; 2,0; 3,0, and 0,4 meters represent extreme weather conditions in Maluku waters' fishing grounds. The findings revealed that the trimaran hull type had better stability where the inclination angle of trimaran vessel stability was 480 while the monohull was 410. The trimaran fishing vessel was able to withstand a wave height of 3 meters with an inclination angle of 32,560. In comparison, the monohull fishing vessel was able to survive at a wave height of 2 meters with an inclination angle of 24,690. Monohull fishing vessel had a maximum limit of roll motion at wave directions 82 and 99 with a wave height of 3 m, and it reached at the critical point at angles of 43 and 138, at the height of 4 m. Meanwhile, the trimaran fishing vessel had a critical point at a wave angle of 760 and 1000 with a wave height of 4 meters. In the area between those two angles, monohull and trimaran fishing vessels will lose the balance (stability) of the roll motion, resulting in capsize.

scholarly journals NONLINEAR CHARACTERISTICS OF WAVE HEIGHT IN AN EXTREME WEATHER CONDITIONS

2015 ◽  
Vol 71 (2) ◽  
pp. I_457-I_462
Author(s):  
Nobuhito MORI ◽  
Yusuke TAKAGI ◽  
Hajime MASE ◽  
Tomohiro YASUDA ◽  
Hiroaki SHIMADA
Keyword(s):  
Wave Height ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Nonlinear Characteristics

scholarly journals Bayesian hierarchical modelling of North Atlantic windiness

2013 ◽  
Vol 13 (3) ◽  
pp. 545-557 ◽  
Author(s):  
E. Vanem ◽  
O. N. Breivik
Keyword(s):  
Climate Change ◽  
Wave Height ◽  
North Atlantic ◽  
Environmental Conditions ◽  
Significant Wave Height ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Bayesian Hierarchical ◽  
Significant Wave

Abstract. Extreme weather conditions represent serious natural hazards to ship operations and may be the direct cause or contributing factor to maritime accidents. Such severe environmental conditions can be taken into account in ship design and operational windows can be defined that limits hazardous operations to less extreme conditions. Nevertheless, possible changes in the statistics of extreme weather conditions, possibly due to anthropogenic climate change, represent an additional hazard to ship operations that is less straightforward to account for in a consistent way. Obviously, there are large uncertainties as to how future climate change will affect the extreme weather conditions at sea and there is a need for stochastic models that can describe the variability in both space and time at various scales of the environmental conditions. Previously, Bayesian hierarchical space-time models have been developed to describe the variability and complex dependence structures of significant wave height in space and time. These models were found to perform reasonably well and provided some interesting results, in particular, pertaining to long-term trends in the wave climate. In this paper, a similar framework is applied to oceanic windiness and the spatial and temporal variability of the 10-m wind speed over an area in the North Atlantic ocean is investigated. When the results from the model for North Atlantic windiness is compared to the results for significant wave height over the same area, it is interesting to observe that whereas an increasing trend in significant wave height was identified, no statistically significant long-term trend was estimated in windiness. This may indicate that the increase in significant wave height is not due to an increase in locally generated wind waves, but rather to increased swell. This observation is also consistent with studies that have suggested a poleward shift of the main storm tracks.

Analysis of the moisture content of maize kernels in over-ripe plants

2006 ◽  
Vol 54 (4) ◽  
pp. 425-430
Author(s):  
T. Árendás ◽  
L. C. Marton ◽  
P. Bónis ◽  
Z. Berzsenyi
Keyword(s):  
Linear Regression ◽  
Moisture Content ◽  
Grain Yield ◽  
Equilibrium Moisture Content ◽  
Weather Conditions ◽  
Positive Correlation ◽  
Maize Grain Yield ◽  
Maize Grain ◽  
Maize Kernels

The effect of varying weather conditions on the moisture content of the maize grain yield was investigated in Martonvásár, Hungary from late August to late September, and from the 3rd third of September to the 1st third of Novemberbetween 1999 and 2002. In every year a close positive correlation (P=0.1%) could be observed between the moisture content in late September and the rate of drying down in October. Linear regression was used each year to determine the equilibrium moisture content, to which the moisture content of kernels returned if they contained less than this quantity of water in late September and harvesting was delayed. In the experimental years this value ranged from 15.24-19.01%.

scholarly journals Precipitation Modeling for Extreme Weather Based on Sparse Hybrid Machine Learning and Markov Chain Random Field in a Multi-Scale Subspace

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1241
Author(s):  
Ming-Hsi Lee ◽  
Yenming J. Chen
Keyword(s):  
Machine Learning ◽  
Markov Chain ◽  
Random Field ◽  
Long Range ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Prediction Algorithm ◽  
Learning Method ◽  
Multi Scale ◽  
Hybrid Machine

This paper proposes to apply a Markov chain random field conditioning method with a hybrid machine learning method to provide long-range precipitation predictions under increasingly extreme weather conditions. Existing precipitation models are limited in time-span, and long-range simulations cannot predict rainfall distribution for a specific year. This paper proposes a hybrid (ensemble) learning method to perform forecasting on a multi-scaled, conditioned functional time series over a sparse l1 space. Therefore, on the basis of this method, a long-range prediction algorithm is developed for applications, such as agriculture or construction works. Our findings show that the conditioning method and multi-scale decomposition in the parse space l1 are proved useful in resisting statistical variation due to increasingly extreme weather conditions. Because the predictions are year-specific, we verify our prediction accuracy for the year we are interested in, but not for other years.

Multi-objective resilience enhancement program in smart grids during extreme weather conditions

2021 ◽  
Vol 129 ◽  
pp. 106824
Author(s):  
Rahman Ashrafi ◽  
Meysam Amirahmadi ◽  
Mohammad Tolou-Askari ◽  
Vahid Ghods
Keyword(s):  
Smart Grids ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Multi Objective

scholarly journals Extreme weather conditions and dengue outbreak in Guangdong, China: spatial heterogeneity based on climate variability

2021 ◽  
pp. 110900
Author(s):  
Jian Cheng ◽  
Hilary Bambrick ◽  
Laith Yakob ◽  
Gregor Devine ◽  
Francesca D. Frentiu ◽  
...  
Keyword(s):  
Climate Variability ◽  
Spatial Heterogeneity ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Dengue Outbreak

scholarly journals Overheating Risk and Energy Demand of Nordic Old and New Apartment Buildings during Average and Extreme Weather Conditions under a Changing Climate

2021 ◽  
Vol 11 (9) ◽  
pp. 3972
Author(s):  
Azin Velashjerdi Farahani ◽  
Juha Jokisalo ◽  
Natalia Korhonen ◽  
Kirsti Jylhä ◽  
Kimmo Ruosteenoja ◽  
...  
Keyword(s):  
Climate Change ◽  
Energy Demand ◽  
Energy Use ◽  
Residential Buildings ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Living Room ◽  
Extra Energy ◽  
Cooling Unit ◽  
Indoor Conditions

The global average air temperature is increasing as a manifestation of climate change and more intense and frequent heatwaves are expected to be associated with this rise worldwide, including northern Europe. Summertime indoor conditions in residential buildings and the health of occupants are influenced by climate change, particularly if no mechanical cooling is used. The energy use of buildings contributes to climate change through greenhouse gas emissions. It is, therefore, necessary to analyze the effects of climate change on the overheating risk and energy demand of residential buildings and to assess the efficiency of various measures to alleviate the overheating. In this study, simulations of dynamic energy and indoor conditions in a new and an old apartment building are performed using two climate scenarios for southern Finland, one for average and the other for extreme weather conditions in 2050. The evaluated measures against overheating included orientations, blinds, site shading, window properties, openable windows, the split cooling unit, and the ventilation cooling and ventilation boost. In both buildings, the overheating risk is high in the current and projected future average climate and, in particular, during exceptionally hot summers. The indoor conditions are occasionally even injurious for the health of occupants. The openable windows and ventilation cooling with ventilation boost were effective in improving the indoor conditions, during both current and future average and extreme weather conditions. However, the split cooling unit installed in the living room was the only studied solution able to completely prevent overheating in all the spaces with a fairly small amount of extra energy usage.

Potential Impacts of Extreme Heat and Bushfires on Dementia

2021 ◽  
Vol 79 (3) ◽  
pp. 969-978
Author(s):  
Taya L. Farugia ◽  
Carla Cuni-Lopez ◽  
Anthony R. White
Keyword(s):  
Rural Communities ◽  
Natural Disasters ◽  
Low Socioeconomic Status ◽  
Forest Fires ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Extreme Heat ◽  
Indigenous Populations ◽  
Future Research ◽  
Diagnosis Of Dementia

Australia often experiences natural disasters and extreme weather conditions such as: flooding, sandstorms, heatwaves, and bushfires (also known as wildfires or forest fires). The proportion of the Australian population aged 65 years and over is increasing, alongside the severity and frequency of extreme weather conditions and natural disasters. Extreme heat can affect the entire population but particularly at the extremes of life, and patients with morbidities. Frequently identified as a vulnerable demographic in natural disasters, there is limited research on older adults and their capacity to deal with extreme heat and bushfires. There is a considerable amount of literature that suggests a significant association between mental disorders such as dementia, and increased vulnerability to extreme heat. The prevalence rate for dementia is estimated at 30%by age 85 years, but there has been limited research on the effects extreme heat and bushfires have on individuals living with dementia. This review explores the differential diagnosis of dementia, the Australian climate, and the potential impact Australia’s extreme heat and bushfires have on individuals from vulnerable communities including low socioeconomic status Indigenous and Non-Indigenous populations living with dementia, in both metropolitan and rural communities. Furthermore, we investigate possible prevention strategies and provide suggestions for future research on the topic of Australian bushfires and heatwaves and their impact on people living with dementia. This paper includes recommendations to ensure rural communities have access to appropriate support services, medical treatment, awareness, and information surrounding dementia.

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