Search results for: weather factors

Authors: N. A. Parvin, E. B. Ferranti, L. A. Chapman, C. A. Pfrang

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This study intends to investigate the effects of the Urban Heat Island on public health in Birmingham. Birmingham is located at the center of the West Midlands and its weather is Highly variable due to geographical factors. Residential developments, road networks and infrastructure often replace open spaces and vegetation. This transformation causes the temperature of urban areas to increase and creates an "island" of higher temperatures in the urban landscape. Extreme heat in the urban area is influencing public health in the UK as well as in the world. Birmingham is a densely built-up area with skyscrapers and congested buildings in the city center, which is a barrier to air circulation. We will investigate the city regarding heat and cold-related human mortality and other impacts. We are using primary and secondary datasets to examine the effect of population shift and land-use change on the UHI in Birmingham. We will also use freely available weather data from the Birmingham Urban Observatory and will incorporate satellite data to determine urban spatial expansion and its effect on the UHI. We have produced a temperature map based on summer datasets of 2020, which has covered 25 weather stations in Birmingham to show the differences between diurnal and nocturnal summer and annual temperature trends. Some impacts of the UHI may be beneficial, such as the lengthening of the plant growing season, but most of them are highly negative. We are looking for various effects of urban heat which is impacting human health and investigating mitigation options.

Keywords: urban heat, public health, climate change

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Authors: Martin Kittel, Alexander Roth

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The continuous integration of variable renewable energy sources (VRE) in the power sector is required for decarbonizing the European economy. Power sectors become increasingly exposed to weather variability, as the availability of VRE, i.e., mainly wind and solar photovoltaic, is not persistent. Extreme events, e.g., long-lasting periods of scarce VRE availability (‘VRE droughts’), challenge the reliability of supply. Properly accounting for the severity of VRE droughts is crucial for designing a resilient renewable European power sector. Energy system modeling is used to identify such a design. Our analysis reveals the sensitivity of the optimal design of the European power sector towards VRE droughts. We analyze how VRE droughts impact optimal power sector investments, especially in generation and flexibility capacity. We draw upon work that systematically identifies VRE drought patterns in Europe in terms of frequency, duration, and seasonality, as well as the cross-regional and cross-technological correlation of most extreme drought periods. Based on their analysis, the authors provide a selection of relevant historical weather years representing different grades of VRE drought severity. These weather years will serve as input for the capacity expansion model for the European power sector used in this analysis (DIETER). We additionally conduct robustness checks varying policy-relevant assumptions on capacity expansion limits, interconnections, and level of sector coupling. Preliminary results illustrate how an imprudent selection of weather years may cause underestimating the severity of VRE droughts, flawing modeling insights concerning the need for flexibility. Sub-optimal European power sector designs vulnerable to extreme weather can result. Using relevant weather years that appropriately represent extreme weather events, our analysis identifies a resilient design of the European power sector. Although the scope of this work is limited to the European power sector, we are confident that our insights apply to other regions of the world with similar weather patterns. Many energy system studies still rely on one or a limited number of sometimes arbitrarily chosen weather years. We argue that the deliberate selection of relevant weather years is imperative for robust modeling results.

Keywords: energy systems, numerical optimization, variable renewable energy sources, energy drought, flexibility

Procedia PDF Downloads 45

Authors: Ojetunde Ojewola, Mark Morgan, Sonja Wilhelm-Stanis

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State parks and historic sites are vulnerable to extreme weather events which can affect visitor experiences, management priorities, and legislative requests for disaster relief funds. Recently, global attention has been focused on the perceptions of global warming and how the presence of extreme weather events might impact protected areas, both now and in the future. The effects of climate change are not equally distributed across the United States, leading to varied perceptions based on personal experience with extreme weather events. This study describes employee perceptions of vulnerability and resilience in Missouri State Parks & Historic Sites due to extreme weather events that occur across the state but grouped according to physiographic provinces. Using a four-point rating scale, perceptions of vulnerability and resilience were divided into high and low sub-groups, thus allowing researchers to construct a two by two typology of employee responses. Subsequently, this data was used to develop a three-point continuum of environmental concern (higher scores meant more concern). Employee scores were then compared against a statewide assessment which combined social, economic, infrastructural and environmental indicators of vulnerability and resilience. State park employees thought the system was less vulnerable and more resilient to climate change than data found in statewide assessment This result was also consistent in three out of five physiographic regions across Missouri. Implications suggest that Missouri state park should develop a climate change adaptation strategy for emergency preparedness.

Keywords: extreme weather events, resilience, state parks, vulnerability

Procedia PDF Downloads 100

Authors: Hoyoung Lee, Dong-Kyu Kim, Seung-Young Kho, R. Eddie Wilson

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This study quantifies a decrement in freeway capacity during rainfall. Traffic and rainfall data were gathered from Highway Agencies and Wunderground weather service. Three inter-urban freeway sections and its nearest weather stations were selected as experimental sites. Capacity analysis found reductions of maximum and mean pre-breakdown flow rates due to rainfall. The Kruskal-Wallis test also provided some evidence to suggest that the variance in the pre-breakdown flow rate is statistically insignificant. Potential application of this study lies in the operation of real time traffic management schemes such as Variable Speed Limits (VSL), Hard Shoulder Running (HSR), and Ramp Metering System (RMS), where speed or flow limits could be set based on a number of factors, including rainfall events and their intensities.

Keywords: capacity randomness, flow breakdown, freeway capacity, rainfall

Procedia PDF Downloads 356

Authors: Nasser A. Al-Azri

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The effectiveness of passive cooling techniques is assessed based on bioclimatic charts that require the typical meteorological year (TMY) for a specified location for their development. However, TMYs are not always available; mainly due to the scarcity of records of solar radiation which is an essential component used in developing common TMYs intended for general uses. Since solar radiation is not required in the development of the bioclimatic chart, this work suggests developing TMYs based solely on the relevant parameters. This approach improves the accuracy of the developed TMY since only the relevant parameters are considered and it also makes the development of the TMY more accessible since solar radiation data are not used. The presented paper will also discuss the development of the TMY from the raw data available at the NOAA-NCDC archive of world weather data and the construction of the bioclimatic charts for some randomly selected locations around the world.

Keywords: bioclimatic charts, passive cooling, TMY, weather data

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Authors: Helene Thieblemont, Fariborz Haghighat

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Energy storage systems play a crucial role in decreasing building energy consumption during peak periods and expand the use of renewable energies in buildings. To provide a high building thermal performance, the energy storage system has to be properly controlled to insure a good energy performance while maintaining a satisfactory thermal comfort for building’s occupant. In the case of passive discharge storages, defining in advance the required amount of energy is required to avoid overheating in the building. Consequently, anticipatory supervisory control strategies have been developed forecasting future energy demand and production to coordinate systems. Anticipatory supervisory control strategies are based on some predictions, mainly of the weather forecast. However, if the forecasted hourly outdoor temperature may be found online with a high accuracy, solar radiations predictions are most of the time not available online. To estimate them, this paper proposes an advanced approach based on the forecast of weather conditions. Several methods to correlate hourly weather conditions forecast to real hourly solar radiations are compared. Results show that using weather conditions forecast allows estimating with an acceptable accuracy solar radiations of the next day. Moreover, this technique allows obtaining hourly data that may be used for building models. As a result, this solar radiation prediction model may help to implement model-based controller as Model Predictive Control.

Keywords: anticipatory control, model predictive control, solar radiation forecast, thermal storage

Procedia PDF Downloads 248

Authors: Taufik Nugroho, Firsty Dzainuurahmana, Tika Widiastuti

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The polemic about the salt crisis re-emerged, this is a classic problem in Indonesia and is still a homework that is not finished yet. This salt crisis occurs due to low productivity of salt commodities that have not been able to meet domestic demand and lack of salt productivity caused by several factors. One of the biggest factors of the crisis is the weather anomaly that disrupts salt production, less supportive technology and price stability. This study will try to discuss the salt scarcity and crisis solution in Islamic view. As for the conclusion of this study is the need for equilibrium or balancing between demand and supply, need to optimize the role of the government as Hisbah to maintain the balance of market mechanisms and prepare the stock system of salt stock by buying farmers products at reasonable prices then storing them.

Keywords: crisis, Islamic solution, scarcity, salt

Procedia PDF Downloads 258

Authors: Roikhan Mochamad Aziz

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This study aims to analze the interdependence of several variables simultaneously in order to simplify the form of the relationship between some of the variables studied a number of factors less than the variable studied which means it can also describe the data structure of a research. Based 100 respondents from the public, such as the people of South Tangerang, this study used factor analysis tool. The results of this study indicate that the studied variables being formed into nine factors, namely faith factors, community factors, factors of social care, confidence factor, factor income, educational factors, self-satisfaction factors, factors work, and knowledge factor. Total variance of the 9 factors is 67,30% means that all nine of these factors are factors that can contribute too paying zakat of muzakki consciousness of 67,30% while the remaining 32,70% is supported by other factors outside the 9 factors.

Keywords: zakat, analysis factor, faith, education, knowledge

Procedia PDF Downloads 247

Authors: Samaneh Poormohammadi, Farid Golkar, Vahideh Khatibi Sarabi

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Climate change and consecutive droughts have increased the importance of using rainwater harvesting methods. One of the methods of rainwater harvesting and, in other words, the management of atmospheric water resources is the use of weather modification technologies. Weather modification (also known as weather control) is the act of intentionally manipulating or altering the weather. The most common form of weather modification is cloud seeding, which increases rain or snow, usually for the purpose of increasing the local water supply. Cloud seeding operations in Iran have been married since 1999 in central Iran with the aim of harvesting rainwater and reducing the effects of drought. In this research, we analyze the results of cloud seeding operations in the Simindashtplain in northern Iran. Rainwater harvesting with the help of cloud seeding technology has been evaluated through its effects on surface water and underground water. For this purpose, two different methods have been used to estimate runoff. The first method is the US Soil Conservation Service (SCS) curve number method. Another method, known as the reasoning method, has also been used. In order to determine the infiltration rate of underground water, the balance reports of the comprehensive water plan of the country have been used. In this regard, the study areas located in the target area of each province have been extracted by drawing maps of the influence coefficients of each area in the GIS software. It should be mentioned that the infiltration coefficients were taken from the balance sheet reports of the country's comprehensive water plan. Then, based on the area of each study area, the weighted average of the infiltration coefficient of the study areas located in the target area of each province is considered as the infiltration coefficient of that province. Results show that the amount of water extracted from the rain with the help of cloud seeding projects in Simindasht is as follows: an increase in runoff 63.9 million cubic meters (with SCS equation) or 51.2 million cubic meters (with logical equation) and an increase in ground water resources: 40.5 million cubic meters.

Keywords: rainwater harvesting, ground water, atmospheric water resources, weather modification, cloud seeding

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Authors: Yuqing Chen, Ying Xu, Renfa Li

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The development of matrix completion theory provides new approaches for data gathering in Wireless Sensor Networks (WSN). The existing matrix completion algorithms for WSN mainly consider how to reduce the sampling number without considering the real-time performance when recovering the data matrix. In order to guarantee the recovery accuracy and reduce the recovery time consumed simultaneously, we propose a new ALM algorithm to recover the weather monitoring data. A lot of experiments have been carried out to investigate the performance of the proposed ALM algorithm by using different parameter settings, different sampling rates and sampling models. In addition, we compare the proposed ALM algorithm with some existing algorithms in the literature. Experimental results show that the ALM algorithm can obtain better overall recovery accuracy with less computing time, which demonstrate that the ALM algorithm is an effective and efficient approach for recovering the real world weather monitoring data in WSN.

Keywords: wireless sensor network, matrix completion, singular value thresholding, augmented Lagrange multiplier

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Authors: Vito Telesca, Giuseppina A. Giorgio

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The earth system is subject to a wide range of human activities that have changed the ecosystem more rapidly and extensively in the last five decades. These global changes have a large impact on human health. The relationship between extreme weather events and mortality are widely documented in different studies. In particular, a number of studies have investigated the relationship between climatological variations and the cardiovascular and respiratory system. The researchers have become interested in the evaluation of the effect of environmental variations on the occurrence of different diseases (such as infarction, ischemic heart disease, asthma, respiratory problems, etc.) and mortality. Among changes in weather conditions, the heat waves have been used for investigating the association between weather conditions and cardiovascular events and cerebrovascular, using thermal indices, which combine air temperature, relative humidity, and wind speed. The effects of heat waves on human health are mainly found in the urban areas and they are aggravated by the presence of atmospheric pollution. The consequences of these changes for human health are of growing concern. In particular, meteorological conditions are one of the environmental aspects because cardiovascular diseases are more common among the elderly population, and such people are more sensitive to weather changes. In addition, heat waves, or extreme heat events, are predicted to increase in frequency, intensity, and duration with climate change. In this context, are very important public health and climate change connections increasingly being recognized by the medical research, because these might help in informing the public at large. Policy experts claim that a growing awareness of the relationships of public health and climate change could be a key in breaking through political logjams impeding action on mitigation and adaptation. The aims of this study are to investigate about the importance of interactions between weather variables and your effects on human health, focusing on Italy. Also highlighting the need to define strategies and practical actions of monitoring, adaptation and mitigation of the phenomenon.

Keywords: climate change, illness, Italy, temperature, weather

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Authors: Ákos Tótin

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In crop production the most modern hybrids are available for us, therefore the yield and yield stability is determined by the agro-technology. The purpose of the experiment is to adapt the modern agrotechnology to the new type of hybrids. The long-term experiment was set up in 2015-2016 on chernozem soil in the Hajdúság (eastern Hungary). The plots were set up in 75 thousand ha-1 plant density. We examined some mainly use hybrids of Hungary. The conducted studies are: germination dynamic, growing dynamic and the effect of annual weather for the yield. We use three different sowing date as early, average and late, and measure how many plant germinated during the germination process. In the experiment, we observed the germination dynamics in 6 hybrid in 4 replication. In each replication, we counted the germinated plants in 2m long 2 row wide area. Data will be shown in the average of the 6 hybrid and 4 replication. Growing dynamics were measured from the 10cm (4-6 leaf) plant highness. We measured 10 plants’ height in two weeks replication. The yield was measured buy a special plot harvester - the Sampo Rosenlew 2010 – what measured the weight of the harvested plot and also took a sample from it. We determined the water content of the samples for the water release dynamics. After it, we calculated the yield (t/ha) of each plot at 14% of moisture content to compare them. We evaluated the data using Microsoft Excel 2015. The annual weather in each crop year define the maize germination dynamics because the amount of heat is determinative for the plants. In cooler crop year the weather is prolonged the germination. At the 2015 crop year the weather was cold in the beginning what prolonged the first sowing germination. But the second and third sowing germinated faster. In the 2016 crop year the weather was much favorable for plants so the first sowing germinated faster than in the previous year. After it the weather cooled down, therefore the second and third sowing germinated slower than the last year. The statistical data analysis program determined that there is a significant difference between the early and late sowing date growing dynamics. In 2015 the first sowing date had the highest amount of yield. The second biggest yield was in the average sowing time. The late sowing date has lowest amount of yield.

Keywords: germination, maize, sowing date, yield

Procedia PDF Downloads 206

Authors: M. Bokhtiar Hasan, M. Delowar Hossain, Abu N. M. Wahid

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The principal aim of the study is to find out a way to effectively manage the agricultural risks like price volatility, weather risks, and fund shortage. To hedge price volatility, farmers sometimes make contracts with agro-traders but fail to protect themselves effectively due to not having legal framework for such contracts. The study extensively reviews existing literature and find evidence that the majority studies either deal with price volatility or weather risks. If we could address these risks through a single model, it would be more useful to both the farmers and traders. Intrinsically, the authors endeavor in this regard, and the key contribution of this study basically lies in it. Initially, we conduct a small survey aspiring to identify the shortcomings of existing contracts. Later, we propose a model encompassing forward and insurance contracts together where forward contract will be used to hedge price volatility and insurance contract will be used to protect weather risks. Contribution/Originality: The study adds to the existing literature through proposing an integrated model comprising of forward contract and crop insurance which will support both farmers and traders to cope with the agricultural risks like price volatility, weather hazards, and fund shortage. JEL Classifications: O13, Q13

Keywords: agriculture, forward contract, insurance contract, risk management, model

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Authors: Kiyanoush Ghalavand

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Aquaculture production is inherently a risky business, and farmers face a variety of weather, pest, disease, inptut supply, and market related risks. There are many factors out farmers control and unpredictable. Insurance has an important role in aquaculture production and is a tool to support farmers against threats. Investigation of factors affecting aquaculture farmers' adoption of aquaculture insurance strategy was the objective of this study. The purpose of this study was determining the related factors to adoption of insurance by aquaculture farmers in Khuzestan province, Iran. The research design was a descriptive and correlation surveying method. Aquaculture farmers in Khuzestan province were the target population for this study. A random sample of aquaculture selected (N=1830, n =139). The main result of the study reveled that exist correlation between the level of education, knowledge about purpose of insurance, participation in extension course, visit with insurance organization, and contact with extension agents to the adoption of insurance by aquaculture farmers were significantly positive. By using Bartlett's test and KMO test, determine whether research variables are appropriate for factor analysis (Sig = 0.000, Bartlett test = 0.9724, KMO = 0.74). The number of factors was determined using a split plot, eigenvalue, and percent of variance. An examination of the items and their factors loadings was used to understand the nature of the nine factors. To reduce subjectivity, items with factor loading equal to or greater than 0.5 were considered most important when factors were labeled. The nine factors were labeled (1) Extension and education activities, (2) Economical characteristics, (3) Governmental support, (4) communicational channel, (5) local leaders, (6) Facilitate in given damage (7) Motivation establishing, (8) Given damage in appropriate methods and (9) Appropriate activities by insurance organization. The results obtained from the factors analysis reveal that the nine factors explain percentage75 of the variation of the adoption of insurance of the adoption of insurance by aquaculture farmers in Khuzestan province.

Keywords: aquaculture farmers, insurance, factorial analysis, Khuzestan province, risks

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Authors: David N. Prihoda

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This paper charts the history of the English word Tempest from its origins in Proto-Indo European to its modern usage as a term for storms, both literal and metaphorical. It does so by way of considering the word’s morphology, semiotics, and phonetics. It references numerous language studies and dictionaries to chronicle the word’s many steps along that path, from demarcation of measurement to assessment of time, all the way to an observation about the weather or the human psyche. The conclusive findings show that tempest has undergone numerous changes throughout its history, and these changes interestingly parallel its connotations as a symbol for both chaotic weather and the chaos of the human spirit

Keywords: Tempest, etymology, language origins, English

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Authors: Yonghun Ro, Joo-Wan Cha, Sanghee Chae, Areum Ko, Woonseon Jung, Jong-Chul Ha

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National Institute of Meteorological Science (NIMS) in South Korea has performed the cloud seeding to support the field of cloud physics. This is to determine the precipitation occurrence analyzing the changes in the microphysical schemes of clouds. NIMS conducted 12 times of cloud seeding in the lower height of the troposphere at Kangwon and Kyunggi provinces throughout 2018. The change in the reflectivity of the weather radar was analyzed to verify the enhancement of precipitation according to the cloud seeding in this study. First, the natural system in the near of the target area was separated to clear the seeding effect. The radar reflectivity in the point of ground gauge station was extracted in every 10 minutes and the increased values during the reaction time of cloud particles and seeding materials were estimated as a seeding effect considering the cloud temperature, wind speed and direction, and seeding line that the aircraft had passed by. The radar reflectivity affected by seeding materials was showed an increment of 5 to 10 dBZ, and enhanced precipitation cloud was also detected in the 11 cases of cloud seeding experiments.

Keywords: cloud seeding, reflectivity, weather radar, seeding effect

Procedia PDF Downloads 139

Authors: Al-Juhaishi Mohammed, Mikael Motelica-Heino, Fabrice Muller, Audrey Guirimand-Dufour, Christian Défarge

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This study aims at improving the urban hydrological cycle of the Orléans agglomeration (France) and understanding the relationship between physical and chemical parameters of urban surface runoff and the hydrological conditions. In particular water quality parameters such as pH, conductivity, total dissolved solids, major dissolved cations and anions, and chemical and biological oxygen demands were monitored for three types of urban water discharges (wastewater treatment plant output (WWTP), storm overflow and stormwater outfall) under two hydrologic scenarii (dry and wet weather). The first results were obtained over a period of five months.Each investigated (Ormes and l’Egoutier) outfall represents an urban runoff source that receives water from runoff roads, gutters, the irrigation of gardens and other sources of flow over the Earth’s surface that drains in its catchments and carries it to the Loire River. In wet weather conditions there is rain water runoff and an additional input from the roof gutters that have entered the stormwater system during rainfall. For the comparison the results La Chilesse is a storm overflow that was selected in our study as a potential source of waste water which is located before the (WWTP).The comparison of the physical-chemical parameters (total dissolved solids, turbidity, pH, conductivity, dissolved organic carbon (DOC), concentration of major cations and anions) together with the chemical oxygen demand (COD) and biological oxygen demand (BOD) helped to characterize sources of runoff waters in the different watersheds. It also helped to highlight the infiltration of wastewater in some stormwater systems that reject directly in the Loire River. The values of the conductivity measured in the outflow of Ormes were always higher than those measured in the other two outlets. The results showed a temporal variation for the Ormes outfall of conductivity from 1465 µS cm-1 in the dry weather flow to 650 µS cm-1 in the wet weather flow and also a spatial variation in the wet weather flow from 650 µS cm-1 in the Ormes outfall to 281 μS cm-1 in L’Egouttier outfall. The ultimate BOD (BOD28) showed a significant decrease in La Corne outfall from 210 mg L-1 in the wet weather flow to 75 mg L-1 in the dry weather flow because of the nutrient load that was transported by the runoff.

Keywords: BOD, COD, the Loire River, urban hydrology, urban dry and wet weather discharges, macronutrients

Procedia PDF Downloads 241

Authors: Federica Di Marcantonio, Antoine Leblois, Wolfgang Göbel, Hervè Kerdiles

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Weather-related shocks can threaten the ability of farmers to maintain their agricultural output and food security levels. Informal coping mechanisms (i.e. migration or community risk sharing) have always played a significant role in mitigating the negative effects of weather-related shocks in Ethiopia, but they have been found to be an incomplete strategy, particularly as a response to covariate shocks. Particularly, as an alternative to the traditional risk pooling products, an innovative form of insurance known as Index-based Insurance has received a lot of attention from researchers and international organizations, leading to an increased number of pilot initiatives in many countries. Despite the potential benefit of the product in protecting the livelihoods of farmers and pastoralists against climate shocks, to date there has been an unexpectedly low uptake. Using information from current pilot projects on index-based insurance in Ethiopia, this paper discusses the determinants of uptake that have so far undermined the scaling-up of the products, by focusing in particular on weather data availability, price affordability and willingness to pay. We found that, aside from data constraint issues, high price elasticity and low willingness to pay represent impediments to the development of the market. These results, bring us to rethink the role of index insurance as products for enhancing smallholders’ response to covariate shocks, and particularly for improving their food security.

Keywords: index-based insurance, willingness to pay, satellite information, Ethiopia

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Authors: Francisco Toledo-Castillo, María Josefa Sospedra-Baeza, Sergio Hidalgo-Fuentes

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Motorcycles constitute about 9% of all motorized vehicles in Spain and are generally overrepresented in traffic accidents, accounting for 21% of total accidents. Six years of motorcycle accident data were obtained through the national accident database of Spain (Dirección General de Tráfico). Some of the studied factors are age, gender, helmet wearing, alcohol consumption, speeding, subject’s driving license and for how long it has been held, the trip purpose, and the presence of a passenger on the vehicle. Key findings show helmet use, unsafe speed, the trip purpose, weather, distraction, collision type and other variables play significant roles in crash-injury outcomes. Finally, we examine evolution of mortality and severity from 2006 to 2011.

Keywords: motorcycle accidents, risk factors, statistics, Spain

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Authors: Tatiana G. Smirnova, Stan G. Benjamin

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Rapid Update Cycle (RUC) land surface model (LSM) was a land-surface component in several generations of operational weather prediction models at the National Center for Environment Prediction (NCEP) at the National Oceanic and Atmospheric Administration (NOAA). It was designed for short-range weather predictions with an emphasis on severe weather and originally was intentionally simple to avoid uncertainties from poorly known parameters. Nevertheless, the RUC LSM, when coupled with the hourly-assimilating atmospheric model, can produce a realistic evolution of time-varying soil moisture and temperature, as well as the evolution of snow cover on the ground surface. This result is possible only if the soil/vegetation/snow component of the coupled weather prediction model has sufficient skill to avoid long-term drift. RUC LSM was first implemented in the operational NCEP Rapid Update Cycle (RUC) weather model in 1998 and later in the Weather Research Forecasting Model (WRF)-based Rapid Refresh (RAP) and High-resolution Rapid Refresh (HRRR). Being available to the international WRF community, it was implemented in operational weather models in Austria, New Zealand, and Switzerland. Based on the feedback from the US weather service offices and the international WRF community and also based on our own validation, RUC LSM has matured over the years. Also, a sea-ice module was added to RUC LSM for surface predictions over the Arctic sea-ice. Other modifications include refinements to the snow model and a more accurate specification of albedo, roughness length, and other surface properties. At present, RUC LSM is being tested in the regional application of the Unified Forecast System (UFS). The next generation UFS-based regional Rapid Refresh FV3 Standalone (RRFS) model will replace operational RAP and HRRR at NCEP. Over time, RUC LSM participated in several international model intercomparison projects to verify its skill using observed atmospheric forcing. The ESM-SnowMIP was the last of these experiments focused on the verification of snow models for open and forested regions. The simulations were performed for ten sites located in different climatic zones of the world forced with observed atmospheric conditions. While most of the 26 participating models have more sophisticated snow parameterizations than in RUC, RUC LSM got a high ranking in simulations of both snow water equivalent and surface temperature. However, ESM-SnowMIP experiment also revealed some issues in the RUC snow model, which will be addressed in this paper. One of them is the treatment of grid cells partially covered with snow. RUC snow module computes energy and moisture budgets of snow-covered and snow-free areas separately by aggregating the solutions at the end of each time step. Such treatment elevates the importance of computing in the model snow cover fraction. Improvements to the original simplistic threshold-based approach have been implemented and tested both offline and in the coupled weather model. The detailed description of changes to the snow cover fraction and other modifications to RUC soil and snow parameterizations will be described in this paper.

Keywords: land-surface models, weather prediction, hydrology, boundary-layer processes

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Authors: Rebecca A. Deek

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There is evidence that erratic and extreme weather is becoming a common occurrence, and even predictions that this will become even more frequent and more severe. It also appears that the severity of earthquakes is intensifying. Some observers believe that human conduct has given reasons for such change; others attribute this to environmental and geological cycles. However, as some physicists, environmental scientists, politicians, and others continue to debate the connection between weather events, seismic activities, and climate change, other scientists, engineers, and urban planners are exploring how can our habitat become more responsive and resilient to such phenomena. There are a number of recent instances of nature’s destructive events that provide basis for the development of defensive measures.

Keywords: biomimicry, natural disasters, protection of human lives, resilient infrastructures

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Authors: Bikis Muhammed, Sehra Sedigh Sarvestani, Ali R. Hurson, Lasanthi Gamage

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Vehicular traffic events have overly complex spatial correlations and temporal interdependencies and are also influenced by environmental events such as weather conditions. To capture these spatial and temporal interdependencies and make more realistic vehicular traffic predictions, graph neural networks (GNN) based traffic prediction models have been extensively utilized due to their capability of capturing non-Euclidean spatial correlation very effectively. However, most of the already existing GNN-based traffic prediction models have some limitations during learning complex and dynamic spatial and temporal patterns due to the following missing factors. First, most GNN-based traffic prediction models have used static distance or sometimes haversine distance mechanisms between spatially separated traffic observations to estimate spatial correlation. Secondly, most GNN-based traffic prediction models have not incorporated environmental events that have a major impact on the normal traffic states. Finally, most of the GNN-based models did not use an attention mechanism to focus on only important traffic observations. The objective of this paper is to study and make real-time vehicular traffic predictions while incorporating the effect of weather conditions. To fill the previously mentioned gaps, our prediction model uses a real-time driving distance between sensors to build a distance matrix or spatial adjacency matrix and capture spatial correlation. In addition, our prediction model considers the effect of six types of weather conditions and has an attention mechanism in both spatial and temporal data aggregation. Our prediction model efficiently captures the spatial and temporal correlation between traffic events, and it relies on the graph attention network (GAT) and Bidirectional bidirectional long short-term memory (Bi-LSTM) plus attention layers and is called GAT-BILSTMA.

Keywords: deep learning, real time prediction, GAT, Bi-LSTM, attention

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Authors: Nadine Ayasha

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Hail happened in Sukabumi (August 23, 2020), Sekadau (August 22, 2020), and Bogor (September 23, 2020), where this extreme weather phenomenon occurred in the dry season. This study uses the ERA5 reanalysis model data, it aims to examine the vertical velocity impact on the hail occurrence in the dry season, as well as its relation to other weather parameters such as relative humidity, streamline, and wind velocity. Moreover, HCAI product satellite data is used as supporting data for the convective cloud development analysis. Based on the results of graphs, contours, and Hovmoller vertical cut from ERA5 modeling, the vertical velocity values in the 925 Mb-300 Mb layer in Sukabumi, Sekadau, and Bogor before the hail event ranged between -1.2-(-0.2), -1.5-(-0.2), -1-0 Pa/s. A negative value indicates that there is an upward motion from the air mass that trigger the convective cloud growth, which produces hail. It is evidenced by the presence of Cumulonimbus cloud on HCAI product when the hail falls. Therefore, the vertical velocity has significant effect on the hail event. In addition, the relative humidity in the 850-700 Mb layer is quite wet, which ranges from 80-90%. Meanwhile, the streamline and wind velocity in the three regions show the convergence with slowing wind velocity ranging from 2-4 knots. These results show that the upward motion of the vertical velocity is enough to form the wet atmospheric humidity and form a convergence for the growth of the convective cloud, which produce hail in the dry season.

Keywords: hail, extreme weather, vertical velocity, relative humidity, streamline

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Authors: Siripen Yiamjanya, Kevin Wongleedee

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This research paper aims to identify travel motivation by push and pull factors that affected decision making of international tourists in selecting Thailand as their destination choice. A total of 200 international tourists who traveled to Thailand during January and February, 2014 were used as the sample in this study. A questionnaire was employed as a tool in collecting the data, conducted in Bangkok. The list consisted of 30 attributes representing both psychological factors as “push- based factors” and destination factors as “pull-based factors”. Mean and standard deviation were used in order to find the top ten travel motives that were important determinants in the respondents’ decision making process to select Thailand as their destination choice. The finding revealed the top ten travel motivations influencing international tourists to select Thailand as their destination choice included [i] getting experience in foreign land; [ii] Thai food; [iii] learning new culture; [iv] relaxing in foreign land; [v] wanting to learn new things; [vi] being interested in Thai culture, and traditional markets; [vii] escaping from same daily life; [viii] enjoying activities; [ix] adventure; and [x] good weather. Classification of push- based and pull- based motives suggested that getting experience in foreign land was the most important push motive for international tourists to travel, while Thai food portrayed its highest significance as pull motive. Discussion and suggestions were also made for tourism industry of Thailand.

Keywords: decision making, destination choice, international tourist, pull factor, push factor, Thailand, travel motivation

Procedia PDF Downloads 363

Authors: P. Intaracharoen, P. Chantraket, C. Detyothin, S. Kirtsaeng

Abstract:

Radar reflectivity data from Phimai weather radar station of DRRAA (Department of Royal Rainmaking and Agricultural Aviation) were used to analyzed the rainstorm characteristics via Thunderstorm Identification Tracking Analysis and Nowcasting (TITAN) algorithm. The Phimai weather radar station was situated at Nakhon Ratchasima province, northeastern Thailand. The data from 277 days of rainstorm events occurring from May 2016 to May 2017 were used to investigate temporal distribution characteristics of convective individual rainclouds. The important storm properties, structures, and their behaviors were analyzed by 9 variables as storm number, storm duration, storm volume, storm area, storm top, storm base, storm speed, storm orientation, and maximum storm reflectivity. The rainstorm characteristics were also examined by separating the data into two periods as wet and dry season followed by an announcement of TMD (Thai Meteorological Department), under the influence of southwest monsoon (SWM) and northeast monsoon (NEM). According to the characteristics of rainstorm results, it can be seen that rainstorms during the SWM influence were found to be the most potential rainstorms over northeastern region of Thailand. The SWM rainstorms are larger number of the storm (404, 140 no./day), storm area (34.09, 26.79 km²) and storm volume (95.43, 66.97 km³) than NEM rainstorms, respectively. For the storm duration, the average individual storm duration during the SWM and NEM was found a minor difference in both periods (47.6, 48.38 min) and almost all storm duration in both periods were less than 3 hours. The storm velocity was not exceeding 15 km/hr (13.34 km/hr for SWM and 10.67 km/hr for NEM). For the rainstorm reflectivity, it was found a little difference between wet and dry season (43.08 dBz for SWM and 43.72 dBz for NEM). It assumed that rainstorms occurred in both seasons have same raindrop size.

Keywords: rainstorm characteristics, weather radar, TITAN, Northeastern Thailand

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Authors: Ilham S. M. Elsayed

Abstract:

The purpose of this study is to investigate Alahsa Governorate status and its vulnerability to generate urban heat islands. Alahsa Governorate is a famous oasis in the Arabic Peninsula including several oil centers. Extensive literature review was done to collect previous relative data on the urban heat island of Alahsa Governorate. Data used for the purpose of this research were collected from authorized bodies who control weather station networks over Alahsa Governorate, Eastern Province, Saudi Arabia. Although, the number of weather station networks within the region is very limited and the analysis using GIS software and its techniques is difficult and limited, the data analyzed confirm an increase in temperature for more than 2 °C from 2004 to 2014. Such increase is considerable whenever human health and comfort are the concern. The increase of temperature within one decade confirms the availability of urban heat islands. The study concludes that, Alahsa Governorate is vulnerable to create urban heat islands and more attention should be drawn to strategic planning of the governorate that is developing with a high pace and considerable increasing levels of urbanization.

Keywords: Alahsa Governorate, population density, Urban Heat Island, weather station

Procedia PDF Downloads 219

Authors: Olumuyiwa Idowu Ojo, Oluwatobi Peter Olowo

Abstract:

The study developed a Geographical Information Systems (GIS) database and mapped inter-annual changes in crop yields of cassava, cowpea, maize, rice, melon and yam as a response to inter-annual rainfall and temperature variability in Southwest, Nigeria. The aim of this project is to study the comparative analysis of the weather variability impact of six crops yield (Rice, melon, yam, cassava, Maize and cowpea) in South Western States of Nigeria (Oyo, Osun, Ekiti, Ondo, Ogun and Lagos) from 1991 – 2007. The data was imported and analysed in the Arch GIS 9 – 3 software environment. The various parameters (temperature, rainfall, crop yields) were interpolated using the kriging method. The results generated through interpolation were clipped to the study area. Geographically weighted regression was chosen from the spatial statistics toolbox in Arch GIS 9.3 software to analyse and predict the relationship between temperature, rainfall and the different crops (Cowpea, maize, rice, melon, yam, and cassava).

Keywords: GIS, crop yields, comparative analysis, temperature, rainfall, weather variability

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Authors: S. Vavias, T. R. Brewer, T. S. Farewell

Abstract:

Coastal floods have been identified as an important natural hazard that can cause significant damage to the populated built-up areas, related infrastructure and also ecosystems and habitats. This study attempts to fill the gap associated with the development of preliminary assessments of coastal flood vulnerability for compliance with the EU Directive on the Assessment and Management of Flood Risks (2007/60/EC). In this context, a methodology has been created by taking into account three major parameters; the maximum wave run-up modelled from historical weather observations, the highest tide according to historic time series, and the sea level rise projections due to climate change. A high resolution digital terrain model (DTM) derived from LIDAR data has been used to integrate the estimated flood events in a GIS environment. The flood vulnerability map created shows potential risk areas and can play a crucial role in the coastal zone planning process. The proposed method has the potential to be a powerful tool for policy and decision makers for spatial planning and strategic management.

Keywords: coastal floods, vulnerability mapping, climate change, extreme weather events

Procedia PDF Downloads 367

Authors: Beatriz Martinez-Pastor, Maria Nogal, Alan O'Connor

Abstract:

During the last years, the number of extreme weather events has increased. A variety of extreme weather events, including river floods, rain-induced landslides, droughts, winter storms, wildfire, and hurricanes, have threatened and damaged many different regions worldwide. These events have a devastating impact on critical infrastructure systems resulting in high social, economical and environmental costs. These events have a huge impact in transport systems. Since, transport networks are completely exposed to every kind of climatological perturbations, and its performance is closely related with these events. When a traffic network is affected by a climatological hazard, the quality of its service is threatened, and the level of the traffic conditions usually decreases. With the aim of understanding this process, the concept of resilience has become most popular in the area of transport. Transport resilience analyses the behavior of a traffic network when a perturbation takes place. This holistic concept studies the complete process, from the beginning of the perturbation until the total recovery of the system, when the perturbation has finished. Many concepts are included in the definition of resilience, such as vulnerability, redundancy, adaptability, and safety. Once the resilience of a transport network can be evaluated, in this case, the methodology used is a dynamic equilibrium-restricted assignment model that allows the quantification of the concept, the next step is its improvement. Through the improvement of this concept, it will be possible to create transport networks that are able to withstand and have a better performance under the presence of climatological hazards. Analyzing the impact of a perturbation in a traffic network, it is observed that the response of the different links, which are part of the network, can be completely different from one to another. Consequently and due to this effect, many questions arise, as what makes a link more critical before an extreme weather event? or how is it possible to identify these critical links? With this aim, and knowing that most of the times the owners or managers of the transport systems have limited resources, the identification of the critical links of a transport network before extreme weather events, becomes a crucial objective. For that reason, using the available resources in the areas that will generate a higher improvement of the resilience, will contribute to the global development of the network. Therefore, this paper wants to analyze what kind of characteristic makes a link a critical one when an extreme weather event damages a transport network and finally identify them.

Keywords: critical links, extreme weather events, hazard, resilience, transport network

Procedia PDF Downloads 258

Authors: Chao-Linag Hsieh, Zheng-Wei Ye, Chen-Kang Huang, Yeun-Chung Lee, Chih-Hong Sun, Tzai-Hung Wen, Jehn-Yih Juang, Joe-Air Jiang

Abstract:

Air pollution and climate warming become more and more intensified in many areas, especially in urban areas. Environmental parameters are critical information to air pollution and weather monitoring. Thus, it is necessary to develop a suitable air pollution and weather monitoring system for urban areas. In this study, a vehicle monitoring system (VMS) based on the IoT technique is developed. Cars are selected as the research tool because it can reach a greater number of streets to collect data. The VMS can monitor different environmental parameters, including ambient temperature and humidity, and air quality parameters, including PM2.5, NO₂, CO, and O₃. The VMS can provide other information, including GPS signals and the vibration information through driving a car on the street. Different sensor modules are used to measure the parameters and collect the measured data and transmit them to a cloud server through the LoRa protocol. A user interface is used to show the sensing data storing at the cloud server. To examine the performance of the system, a researcher drove a Nissan x-trail 1998 to the area close to the Da’an District office in Taipei to collect monitoring data. The collected data are instantly shown on the user interface. The four kinds of information are provided by the interface: GPS positions, weather parameters, vehicle information, and air quality information. With the VMS, users can obtain the information regarding air quality and weather conditions when they drive their car to an urban area. Also, government agencies can make decisions on traffic planning based on the information provided by the proposed VMS.

Keywords: LoRa, monitoring system, smart city, vehicle

Procedia PDF Downloads 353