Search results for: meteorological events

Authors: Ihejirika Chinedu Emeka, Njoku John Didacus, Obenade Moses

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This study was aimed at determining the impact of meteorological events (seasonal variations) and sand excavation activities on turbidity and Total Suspended Solids (TSS) of Imo River, Southeastern Nigeria. In-situ measurements of the parameters were carried out at the peaks of two consecutive seasons–dry and rainy season at seven major points of sand excavation along the river, under standard analytical methods. There were significant variations in seasons (P<0.05) for turbidity and TSS at all locations. The average turbidity concentration of locations were 36.71 NTU, during the rainy season, and 17 NTU in a dry season, while the average TSS concentration were 27.14 mg/L, during the rainy season, and 8.86mg/L in a dry season. Turbidity correlated positively (strongly) with TSS (r=0.956) at R–Square=0.91. Turbidity and TSS values were higher during the rainy season than the dry season. Turbidity increased when Total Suspended Solids increased. Sand excavation increased turbidity and TSS values of Imo River. The river had moderate water quality during the rainy season and unimpaired water quality during a dry season. The river was not very clear in both seasons, but clearer in a dry season than in rainy season. The increase in turbidity and TSS can lead to the destruction of aquatic biodiversity and stagnation of ecosystem processes. Exposure of aquatic animals to the recorded turbidity level in a rainy season can lead to stress.

Keywords: biodiversity destruction, meteorological events, pollution, sand excavation

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Authors: Linta Rose, Prasad K. Bhaskaran

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Water-level information along the coast is very important for disaster management, navigation, planning shoreline management, coastal engineering and protection works, port and harbour activities, and for a better understanding of near-shore ocean dynamics. The water-level variation along a coast attributes from various factors like astronomical tides, meteorological and hydrological forcing. The study area is the Head Bay of Bengal which is highly vulnerable to flooding events caused by monsoons, cyclones and sea-level rise. The study aims to explore the extent to which wind and surface pressure can influence water-level elevation, in view of the low-lying topography of the coastal zones in the region. The ADCIRC hydrodynamic model has been customized for the Head Bay of Bengal, discretized using flexible finite elements and validated against tide gauge observations. Monthly mean climatological wind and mean sea level pressure fields of ERA Interim reanalysis data was used as input forcing to simulate water-level variation in the Head Bay of Bengal, in addition to tidal forcing. The output water-level was compared against that produced using tidal forcing alone, so as to quantify the contribution of meteorological forcing to water-level. The average contribution of meteorological fields to water-level in January is 5.5% at a deep-water location and 13.3% at a coastal location. During the month of July, when the monsoon winds are strongest in this region, this increases to 10.7% and 43.1% respectively at the deep-water and coastal locations. The model output was tested by varying the input conditions of the meteorological fields in an attempt to quantify the relative significance of wind speed and wind direction on water-level. Under uniform wind conditions, the results showed a higher contribution of meteorological fields for south-west winds than north-east winds, when the wind speed was higher. A comparison of the spectral characteristics of output water-level with that generated due to tidal forcing alone showed additional modes with seasonal and annual signatures. Moreover, non-linear monthly mode was found to be weaker than during tidal simulation, all of which point out that meteorological fields do not cause much effect on the water-level at periods less than a day and that it induces non-linear interactions between existing modes of oscillations. The study signifies the role of meteorological forcing under fair weather conditions and points out that a combination of multiple forcing fields including tides, wind, atmospheric pressure, waves, precipitation and river discharge is essential for efficient and effective forecast modelling, especially during extreme weather events.

Keywords: ADCIRC, head Bay of Bengal, mean sea level pressure, meteorological forcing, water-level, wind

Procedia PDF Downloads 194

Authors: Nina Miklavčič, Urška Kugovnik, Natalia Galkina, Primož Ribarič, Rudi Vončina

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Today, the need for weather predictions is deeply rooted in the everyday life of people as well as it is in industry. The forecasts influence final decision-making processes in multiple areas, from agriculture and prevention of natural disasters to air traffic regulations and solutions on a national level for health, security, and economic problems. Namely, in Slovenia, alongside other existing forms of application, weather forecasts are adopted for the prognosis of electrical current transmission through powerlines. Meteorological parameters are one of the key factors which need to be considered in estimations of the reliable supply of electrical energy to consumers. And like for any other measured value, the knowledge about measurement uncertainty is also critical for the secure and reliable supply of energy. The estimation of measurement uncertainty grants us a more accurate interpretation of data, a better quality of the end results, and even a possibility of improvement of weather forecast models. In the article, we focused on the estimation of measurement uncertainty of the diagnostic microscale meteorological model CALMET. For the purposes of our research, we used a network of meteorological stations spread in the area of our interest, which enables a side-by-side comparison of measured meteorological values with the values calculated with the help of CALMET and the measurement uncertainty estimation as a final result.

Keywords: uncertancy, meteorological model, meteorological measurment, CALMET

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Authors: Joo-Heon Lee, Seo-Yeon Park, Chanyang Sur, Ho-Won Jang

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Satellite-based remote sensing technique has been widely used in the area of drought and environmental monitoring to overcome the weakness of in-situ based monitoring. There are many advantages of remote sensing for drought watch in terms of data accessibility, monitoring resolution and types of available hydro-meteorological data including environmental areas. This study was focused on the applicability of drought monitoring based on satellite imageries by applying to the historical drought events, which had a huge impact on meteorological, agricultural, and hydrological drought. Satellite-based drought indices, the Standardized Precipitation Index (SPI) using Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM); Vegetation Health Index (VHI) using MODIS based Land Surface Temperature (LST), and Normalized Difference Vegetation Index (NDVI); and Scaled Drought Condition Index (SDCI) were evaluated to assess its capability to analyze the complex topography of the Korean peninsula. While the VHI was accurate when capturing moderate drought conditions in agricultural drought-damaged areas, the SDCI was relatively well monitored in hydrological drought-damaged areas. In addition, this study found correlations among various drought indices and applicability using Receiver Operating Characteristic (ROC) method, which will expand our understanding of the relationships between hydro-meteorological variables and drought events at global scale. The results of this research are expected to assist decision makers in taking timely and appropriate action in order to save millions of lives in drought-damaged areas.

Keywords: drought monitoring, moderate resolution imaging spectroradiometer (MODIS), remote sensing, receiver operating characteristic (ROC)

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Authors: I. Szer, J. Szer, M. Pieńko, A. Robak, P. Jamińska-Gadomska

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Work at height, such as construction works on scaffoldings, is associated with a considerable risk. Scaffolding workers are usually exposed to changing weather conditions what can additionally increase the risk of dangerous situations. Therefore, it is very important to foresee the risk of adverse conditions to which the worker may be exposed. The data from meteorological stations may be used to asses this risk. However, the dependency between weather conditions on a scaffolding and in the vicinity of meteorological station, should be determined. The paper presents an analysis of two selected environmental parameters which have influence on the behavior of workers – air temperature and wind speed. Measurements of these parameters were made between April and November of 2016 on ten scaffoldings located in different parts of Poland. They were compared with the results taken from the meteorological stations located closest to the studied scaffolding. The results gathered from the construction sites and meteorological stations were not the same, but statistical analyses have shown that they were correlated.

Keywords: scaffolding, health and safety at work, temperature, wind velocity

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Authors: Alper Serdar Anli

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Analysis of temporal variation of reference evapotranspiration (ET0) is important in arid and semi-arid regions where water resources are limited. In this study, temporal variation of reference evapotranspiration (ET0) and meteorological drought analysis through SPEI (Standardized Precipitation Evapotranspiration Index) method have been carried out in provinces of Central Anatolia Region, Turkey. Reference evapotranspiration of concerning provinces in the region has been estimated using Penman-Monteith method and one calendar year has been split up four periods as r1, r2, r3 and r4. Temporal variation of reference evapotranspiration according to four periods has been analyzed through parametric Dickey-Fuller test and non-parametric Mann-Whitney U test. As a result, significant increasing trends for reference evapotranspiration have been detected and according to SPEI method used for estimating meteorological drought in provinces, mild drought has been experienced in general, and however there have been also a significant amount of events where moderate and severely droughts occurred.

Keywords: central Anatolia region, drought index, Penman-Monteith, reference evapotranspiration, temporal variation

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Authors: Charlotte Dreger, Erik Bollaert

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This paper presents two environmentally-friendly coastal structures realized on the Lake of Neuchâtel. Both structures reflect current environmental issues of concern on the lake and have been strongly affected by extreme meteorological conditions between their period of design and their actual operational period. The Lake of Neuchatel is one of the biggest Swiss lakes and measures around 38 km in length and 8.2 km in width, for a maximum water depth of 152 m. Its particular topographical alignment, situated in between the Swiss Plateau and the Jura mountains, combines strong winds and large fetch values, resulting in significant wave heights during storm events at both north-east and south-west lake extremities. In addition, due to flooding concerns, historically, lake levels have been lowered by several meters during the Jura correction works in the 19th and 20th century. Hence, during storm events, continuous erosion of the vulnerable molasse shorelines and sand banks generate frequent and abundant littoral transport from the center of the lake to its extremities. This phenomenon does not only cause disturbances of the ecosystem, but also generates numerous problems at natural or man-made infrastructures located along the shorelines, such as reed plants, harbor entrances, canals, etc. A first example is provided at the southwestern extremity, near the city of Yverdon, where an ensemble of 11 small islands, the Iles des Vernes, have been artificially created in view of enhancing biological conditions and food availability for bird species during their migration process, replacing at the same time two larger islands that were affected by lack of morphodynamics and general vegetalization of their surfaces. The article will present the concept and dimensioning of these islands based on 2D numerical modelling, as well as the realization and follow-up campaigns. In particular, the influence of several major storm events that occurred immediately after the works will be pointed out. Second, a sediment retention dike is discussed at the northeastern extremity, at the entrance of the Canal de la Broye into the lake. This canal is heavily used for navigation and suffers from frequent and significant sedimentation at its outlet. The new coastal structure has been designed to minimize sediment deposits around the exutory of the canal into the lake, by retaining the littoral transport during storm events. The article will describe the basic assumptions used to design the dike, as well as the construction works and follow-up campaigns. Especially the huge influence of changing meteorological conditions on the littoral transport of the Lake of Neuchatel since project design ten years ago will be pointed out. Not only the intensity and frequency of storm events are increasing, but also the main wind directions alter, affecting in this way the efficiency of the coastal structure in retaining the sediments.

Keywords: meteorological evolution, sediment transport, lake of Neuchatel, numerical modelling, environmental measures

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Authors: Domingos Viegas, Miguel Almeida, Carmen Rocha, Ilda Novo, Yolanda Luna

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Forest fires along the more than 1200km of the Spanish-Portuguese border are more and more frequent, currently achieving around 2000 fire events per year. Some of these events develop to large international wildfire requiring concerted operations based on shared information between the two countries. The fire event of Valencia de Alcantara (2003) causing several fatalities and more than 13000ha burnt, is a reference example of these international events. Currently, Portugal and Spain have a specific cross-border cooperation protocol on wildfires response for a strip of about 30km (15 km for each side). It is recognized by public authorities the successfulness of this collaboration however it is also assumed that this cooperation should include more functionalities such as the development of a common risk information system for transboundary fire events. Since Portuguese and Spanish authorities use different approaches to determine the fire risk indexes inputs and different methodologies to assess the fire risk, sometimes the conjoint firefighting operations are jeopardized since the information is not harmonized and the understanding of the situation by the civil protection agents from both countries is not unique. Thus, a methodology aiming the harmonization of the fire risk calculation and perception by Portuguese and Spanish Civil protection authorities is hereby presented. The final results are presented as well. The fire risk index used in this work is the Canadian Fire Weather Index (FWI), which is based on meteorological data. The FWI is limited on its application as it does not take into account other important factors with great effect on the fire appearance and development. The combination of these factors is very complex since, besides the meteorology, it addresses several parameters of different topics, namely: sociology, topography, vegetation and soil cover. Therefore, the meaning of FWI values is different from region to region, according the specific characteristics of each region. In this work, a methodology for FWI calibration based on the number of fire occurrences and on the burnt area in the transboundary regions of Portugal and Spain, in order to assess the fire risk based on calibrated FWI values, is proposed. As previously mentioned, the cooperative firefighting operations require a common perception of the information shared. Therefore, a common classification of the fire risk for the fire events occurred in the transboundary strip is proposed with the objective of harmonizing this type of information. This work is integrated in the ECHO project SpitFire - Spanish-Portuguese Meteorological Information System for Transboundary Operations in Forest Fires, which aims the development of a web platform for the sharing of information and supporting decision tools to be used in international fire events involving Portugal and Spain.

Keywords: data harmonization, FWI, international collaboration, transboundary wildfires

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Authors: Naci Büyükkaracığan, Hasan Uzun

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Flood is the event which damage to the surrounding lands, residential places, infrastructure and vibrant, because of the streams overflow events from its bed for several reasons. Flood is a natural formation which develops due to its region's climatic conditions, technical and topographical characteristics. However, factors causing floods with global warming caused by human activity are events such as uncontrolled urbanization. Floods in Turkey are natural disasters which cause huge economic losses after the earthquake. At the same time, the flood disaster is one of the most observed hydrometeorological disasters, compared to 30%, in Turkey. Every year, there are around 200 flood-flood disasters and the disaster as a result of financial losses of $ 100 million per year are reported to occur in public institutions. The amount allocated for carrying out investment-project activities for reducing and controlling of flood damage control are around US $ 30 million per year. The existence of a linear increase in the number of flood disasters is noteworthy due to various reasons in the last 50 years of observation. In this study, first of all, big events of the flood in Turkey and their reasons were examined. And then, the information about the work to be done in order to prevent flooding by government was given with examples. Meteorological early warning systems, flood risk maps and regulation of urban development studies are described for this purpose. As a result, recommendations regarding in the event of the occurrence of floods disaster management were issues raised.

Keywords: flood, disaster, disaster management, Türkiye

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Authors: Christian N. Chibo

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Imo River Basin is located in South Eastern Nigeria comprising of 11 states of Imo, Abia, Anambra, Ebonyi, Enugu, Edo, Rivers, Cross river, AkwaIbom, Bayelsa, Delta, and Bayelsa states. The basin has a fluvial erosional system dominated by powerful rivers coming down from steep slopes in the area. This research investigated various hazards associated with flood, the vulnerable areas, elements at risk of flood and various adaptation strategies adopted by local inhabitants to cope with the hazards. The research aim is to identify, examine and assess flood hazards, vulnerability and adaptations in the Upper Imo River Basin. The study identified the role of elevation in cause of flood, elements at risk of flood as well as examine the effectiveness or otherwise of the adaptation strategies for coping with the hazards. Data for this research is grouped as primary and secondary. Their various methods of generation are field measurement, questionnaire, library websites etc. Other types of data were generated from topographical, geological, and Digital Elevation model (DEM) maps, while the hydro meteorological data was sourced from Nigeria Meteorological Agency (NIMET), Meteorological stations of Geography and Environmental Management Departments of Imo State University and Alvan Ikoku Federal College of Education. 800 copies of questionnaire were distributed using systematic sampling to 8 locations used for the pilot survey. About 96% of the questionnaire were retrieved and used for the study. 13 flood events were identified in the study area. Their causes, years and dates of events were documented in the text, and the damages they caused were evaluated. The study established that for each flood event, there is over 200mm of rain observed on the day of the flood and the day before the flood. The study also observed that the areas that situate at higher elevation (See DEM) are less prone to flood hazards while areas at low elevations are more prone to flood hazards. Elements identified to be at risk of flood are agricultural land, residential dwellings, retail trading and related services, public buildings and community services. The study thereby recommends non settlement at flood plains and flood prone areas and rearrangement of land use activities in the upper Imo River Basin among others

Keywords: flood hazard, flood plain, geomorphology, Imo River Basin

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Authors: Özlem Küçükakça

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The world population is rapidly growing. In the last few decades, environmental protection and climate change have been remarked as a global concern. All events have their own ecological footprint. Therefore, all participants who take part in the events, from event organizer to audience should be responsible for reducing carbon emissions. Currently, there is a literature gap which investigates the relationship between events and environment. Hence, this study is conducted to investigate how to implement environmental sustainability in the event management. Therefore, a wide literature and also the UK festivals database have been investigated. Finally, environmental effects and the solution of reducing impacts at events were discussed.

Keywords: ecological footprint, environmental sustainability, events, sustainability

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Authors: Nebila Lichiheb, LaToya Myles, William Pendergrass, Bruce Hicks, Dawson Cagle

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Atmospheric transport of hazardous materials in urban areas is increasingly under investigation due to the potential impact on human health and the environment. In response to health and safety concerns, several dispersion models have been developed to analyze and predict the dispersion of hazardous contaminants. The models of interest usually rely on meteorological information obtained from the meteorological models of NOAA’s National Weather Service (NWS). However, due to the complexity of the urban environment, NWS forecasts provide an inadequate basis for dispersion computation in urban areas. A dense meteorological network in Washington, DC, called DCNet, has been operated by NOAA since 2003 to support the development of urban monitoring methodologies and provide the driving meteorological observations for atmospheric transport and dispersion models. This study focuses on the comparison of wind observations from the DCNet station on the U.S. Department of Commerce Herbert C. Hoover Building against the North American Mesoscale (NAM) model outputs for the period 2017-2019. The goal is to develop a simple methodology for modifying NAM outputs so that the dispersion requirements of the city and its urban area can be satisfied. This methodology will allow us to quantify the prediction errors of the NAM model and propose adjustments of key variables controlling dispersion model calculation.

Keywords: meteorological data, Washington D.C., DCNet data, NAM model

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Authors: Juergen Junk, Franz Ronellenfitsch, Michael Eickermann

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An appropriate weed management in autumn is a prerequisite for an economically successful harvest in the following year. In Luxembourg oilseed rape, wheat and barley is sown from August until October, accompanied by a chemical weed control with soil active herbicides, depending on the state of the weeds and the meteorological conditions. Based on regular ground and surface water-analysis, high levels of contamination by transformation products of respective herbicide compounds have been found in Luxembourg. The most ideal conditions for incorporating soil active herbicides are single rain events. Weed control may be reduced if application is made when weeds are under drought stress or if repeated light rain events followed by dry spells, because the herbicides tend to bind tightly to the soil particles. These effects have been frequently reported for Luxembourg throughout the last years. In the framework of a multisite long-term field experiment (EFFO) weed monitoring, plants observations and corresponding meteorological measurements were conducted. Long-term time series (1947-2016) from the SYNOP station Findel-Airport (WMO ID = 06590) showed a decrease in the number of days with precipitation. As the total precipitation amount has not significantly changed, this indicates a trend towards rain events with higher intensity. All analyses are based on decades (10-day periods) for September and October of each individual year. To assess the future meteorological conditions for Luxembourg, two different approaches were applied. First, multi-model ensembles from the CORDEX experiments (spatial resolution ~12.5 km; transient projections until 2100) were analysed for two different Representative Concentration Pathways (RCP8.5 and RCP4.5), covering the time span from 2005 until 2100. The multi-model ensemble approach allows for the quantification of the uncertainties and also to assess the differences between the two emission scenarios. Second, to assess smaller scale differences within the country a high resolution model projection using the COSMO-LM model was used (spatial resolution 1.3 km). To account for the higher computational demands, caused by the increased spatial resolution, only 10-year time slices have been simulated (reference period 1991-2000; near future 2041-2050 and far future 2091-2100). Statistically significant trends towards higher air temperatures, +1.6 K for September (+5.3 K far future) and +1.3 K for October (+4.3 K), were predicted for the near future compared to the reference period. Precipitation simultaneously decreased by 9.4 mm (September) and 5.0 mm (October) for the near future and -49 mm (September) and -10 mm (October) in the far future. Beside the monthly values also decades were analyzed for the two future time periods of the CLM model. For all decades of September and October the number of days with precipitation decreased for the projected near and far future. Changes in meteorological variables such as air temperature and precipitation did already induce transformations in weed societies (composition, late-emerging etc.) of arable ecosystems in Europe. Therefore, adaptations of agronomic practices as well as effective weed control strategies must be developed to maintain crop yield.

Keywords: CORDEX projections, dry spells, ensembles, weed management

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Authors: Luis Gimeno, Rosmeri da Rocha, Raquel Nieto, Tercio Ambrizzi, Alex Ramos, Anita Drumond

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The transport of moisture from oceanic sources to the continents represents the atmospheric branch of the water cycle, forming the connection between evaporation from the ocean and precipitation over the continents. In this regard two large scale dynamical/meteorological structures appear to play a key role, namely Low Level Jet (LLJ) systems and Atmospheric Rivers (ARs). The former are particularly important in tropical and subtropical regions; the latter is mostly confined to extratropical regions. A key question relates to the anomalies in the transport of moisture observed during natural hazards related to extremes of precipitation (i.e., drought or wet spells). In this study we will be focused on these two major atmospheric moisture transport mechanisms (LLJs and ARs) and its role in precipitation extreme events (droughts and wet spells) in the Amazonia paying particular attention to i) intensification (decreasing) of moisture transport by them and its role in wet spells (droughts), and ii) changes in their positions and occurrence with associated flooding and wet spells.

Keywords: droughts, wet spells, amazonia, LLJs, atmospheric rivers

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Authors: L. Krpalkova, N. O' Mahony, A. Carvalho, S. Campbell, S. Harapanahalli, J. Walsh

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The objective of this study was to determine the effects of environmental stressors on the performance of lactating dairy cows and discuss some future trends. There exists a relationship between the meteorological data and milk yield prediction accuracy in pasture-based dairy systems. New precision technologies are available and are being developed to improve the sustainability of the dairy industry. Some of these technologies focus on welfare of individual animals on dairy farms. These technologies allow the automatic identification of animal behaviour and health events, greatly increasing overall herd health and yield while reducing animal health inspection demands and long-term animal healthcare costs. The data set consisted of records from 489 dairy cows at two dairy farms and temperature measured from the nearest meteorological weather station in 2018. The effects of temperature on milk production and behaviour of animals were analyzed. The statistical results indicate different effects of temperature on milk yield and behaviour. The “comfort zone” for animals is in the range 10 °C to 20 °C. Dairy cows out of this zone had to decrease or increase their metabolic heat production, and it affected their milk production and behaviour.

Keywords: behavior, milk yield, temperature, precision technologies

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Authors: Charline David, Alexandre Blondin Massé, Arnaud Zinflou

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In 2016, Clements, Hurn, and Li proposed a multiple equation time series approach for the short-term load forecasting, reporting an average mean absolute percentage error (MAPE) of 1.36% on an 11-years dataset for the Queensland region in Australia. We present an adaptation of their model to the electrical power load consumption for the whole Quebec province in Canada. More precisely, we take into account two additional meteorological variables — cloudiness and wind speed — on top of temperature, as well as the use of multiple meteorological measurements taken at different locations on the territory. We also consider other minor improvements. Our final model shows an average MAPE score of 1:79% over an 8-years dataset.

Keywords: short-term load forecasting, special days, time series, multiple equations, parallelization, clustering

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Authors: Chakrit Chotamonsak

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In this study, the Weather Research and Forecasting (WRF) model was used as regional climate model to dynamically downscale the ECHAM5 Global Climate Model projection for the regional climate change impact on air quality–related meteorological conditions in the upper northern Thailand. The analyses were focused on meteorological variables that potentially impact on the regional air quality such as sea level pressure, planetary boundary layer height (PBLH), surface temperature, wind speed and ventilation. Comparisons were made between the present (1990–2009) and future (2045–2064) climate downscaling results during majority air pollution season (dry season, January-April). Analyses showed that the sea level pressure will be stronger in the future, suggesting more stable atmosphere. Increases in temperature were obvious observed throughout the region. Decreases in surface wind and PBLH were predicted during air pollution season, indicating weaker ventilation rate in this region. Consequently, air quality-related meteorological variables were predicted to change in almost part of the upper northern Thailand, yielding a favorable meteorological condition for pollutant accumulation in the future.

Keywords: climate change, climate impact, air quality, air pollution, Thailand

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Authors: Chiang Wei, Hui-Chung Yeh, Yen-Chang Chen

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The objective of this study is to estimate the rainfall using the new generation Himawari-8 meteorological satellite with multi-band, high-bit format, and high spatiotemporal resolution, ground rainfall data at the Chen-Yu-Lan watershed of Joushuei River Basin (443.6 square kilometers) in Central Taiwan. Accurate and fine-scale rainfall information is essential for rugged terrain with high local variation for early warning of flood, landslide, and debris flow disasters. 10-minute and 2 km pixel-based rainfall of Typhoon Megi of 2016 and meiyu on June 1-4 of 2017 were tested to demonstrate the new generation Himawari-8 meteorological satellite can capture rainfall variation in the rugged mountainous area both at fine-scale and watershed scale. The results provide the valuable rainfall information for early warning of future disasters.

Keywords: estimation, Himawari-8, rainfall, satellite imagery

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Authors: Milan Joshi, Harsh Agrawal, Pallaw Mishra, Sanand Sule

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Predicting electricity usage is a crucial aspect of organizing and controlling sustainable energy systems. The task of forecasting electricity load is intricate and requires a lot of effort due to the combined impact of social, economic, technical, environmental, and cultural factors on power consumption in communities. As a result, it is important to create strong models that can handle the significant non-linear and complex nature of the task. The objective of this study is to create and compare three machine learning techniques for predicting electricity load for both the day ahead and intraday, taking into account various factors such as meteorological data and social events including holidays and festivals. The proposed methods include a LightGBM, FBProphet, combination of FBProphet and LightGBM for day ahead and Motifs( Stumpy) based on Mueens algorithm for similarity search for intraday. We utilize these techniques to predict electricity usage during normal days and social events in the Himachal Region. We then assess their performance by measuring the MSE, RMSE, and MAPE values. The outcomes demonstrate that the combination of FBProphet and LightGBM method is the most accurate for day ahead and Motifs for intraday forecasting of electricity usage, surpassing other models in terms of MAPE, RMSE, and MSE. Moreover, the FBProphet - LightGBM approach proves to be highly effective in forecasting electricity load during social events, exhibiting precise day ahead predictions. In summary, our proposed electricity forecasting techniques display excellent performance in predicting electricity usage during normal days and special events in the Himachal Region.

Keywords: feature engineering, FBProphet, LightGBM, MASS, Motifs, MAPE

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Authors: Muhammad Abid

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In this study, we performed the comparative exergetic and exergoeconomic analyses of a wind turbine over a period of twelve months from 1st January to 30th December 2011. The turbine is part of a wind-PV hybrid system with hydrogen storage, located on the roof of Mechanical Engineering Department, King Saud University, Riyadh, Saudi Arabia. The rated power output from this turbine is 1.7 W with a rated wind speed of 12 m/s and cut-in/cut-out wind speeds of 3/14 m/s. We utilize a wide range of experimental data in the analysis and assessment. We determine exergy efficiencies and their relation with meteorological variables, such as temperature and density. We also calculate exergoeconomic parameter R ̇_ex and its dependence on the temperature, using the average values for twelve months of the year considered for comparison purposes. The exergy efficiency changes from 0.12 to 0.31 while the density varies between 1.31 and 1.2 kg/m3 for different temperature values. The R ̇_ex has minimum and maximum values of 0.02 and 0.81, respectively, while the temperature is in the range of 8-24°C for various wind velocity values.

Keywords: exergy, efficiency, renewable energy, wind energy, meteorological variables

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Authors: J. Junk, M. Eickermann

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The Small Hive Beetle, Aethina tumida (Coleoptera: Nitidulidae) is a parasite for honey bee colonies, Apis mellifera, and was recently introduced to the European continent, accidentally. Based on the literature, a model was developed by using regional meteorological variables (daily values of minimum, maximum and mean air temperature as well as mean soil temperature at 50 mm depth) to calculate the time-point of hive invasion by A. tumida in springtime, the development duration of pupae as well as the number of generations of A. tumida per year. Luxembourg was used as a test region for our model for 2005 to 2013. The model output indicates a successful surviving of the Small Hive Beetle in Luxembourg with two up to three generations per year. Additionally, based on our meteorological data sets a first migration of SHB to apiaries can be expected from mid of March up to April. Our approach can be transferred easily to other countries to estimate the risk potential for a successful introduction and spreading of A. tumida in Western Europe.

Keywords: Aethina tumida, air temperature, larval development, soil temperature

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Authors: Goksel Ezgi Guzey, Bihrat Onoz

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The scarcity of streamflow gauging stations and the increasing effects of global warming cause designing water management systems to be very difficult. This study is a significant contribution to assessing regional regression models for estimating streamflow. In this study, simulated meteorological data was related to the observed streamflow data from 1971 to 2020 for 33 stream gauging stations of the Euphrates-Tigris Basin. Ordinary least squares regression was used to predict flow for 2020-2100 with the simulated meteorological data. CORDEX- EURO and CORDEX-MENA domains were used with 0.11 and 0.22 grids, respectively, to estimate climate conditions under certain climate scenarios. Twelve meteorological variables simulated by two regional climate models, RCA4 and RegCM4, were used as independent variables in the ordinary least squares regression, where the observed streamflow was the dependent variable. The variability of streamflow was then calculated with 5-6 meteorological variables and watershed characteristics such as area and height prior to the application. Of the regression analysis of 31 stream gauging stations' data, the stations were subjected to a clustering analysis, which grouped the stations in two clusters in terms of their hydrometeorological properties. Two streamflow equations were found for the two clusters of stream gauging stations for every domain and every regional climate model, which increased the efficiency of streamflow estimation by a range of 10-15% for all the models. This study underlines the importance of homogeneity of a region in estimating streamflow not only in terms of the geographical location but also in terms of the meteorological characteristics of that region.

Keywords: hydrology, streamflow estimation, climate change, hydrologic modeling, HBV, hydropower

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Authors: K. D. Sharma, M. Parida, S. S. Jain, Anju Saini, V. K. Katiyar

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Air quality models form one of the most important components of an urban air quality management plan. Various statistical modeling techniques (regression, multiple regression and time series analysis) have been used to predict air pollution concentrations in the urban environment. These models calculate pollution concentrations due to observed traffic, meteorological and pollution data after an appropriate relationship has been obtained empirically between these parameters. Artificial neural network (ANN) is increasingly used as an alternative tool for modeling the pollutants from vehicular traffic particularly in urban areas. In the present paper, an attempt has been made to model traffic air pollution, specifically CO concentration using neural networks. In case of CO concentration, two scenarios were considered. First, with only classified traffic volume input and the second with both classified traffic volume and meteorological variables. The results showed that CO concentration can be predicted with good accuracy using artificial neural network (ANN).

Keywords: air quality management, artificial neural network, meteorological variables, statistical modeling

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Authors: Parvin Ghafarian, Mohammadreza Mohammadpur Panchah, Mehri Fallahi

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Synoptic patterns from surface up to tropopause are very important for forecasting the weather and atmospheric conditions. There are many tools to prepare and analyze these maps. Reanalysis data and the outputs of numerical weather prediction models, satellite images, meteorological radar, and weather station data are used in world forecasting centers to predict the weather. The forecasting extreme precipitating on the southern coast of the Caspian Sea (CS) is the main issue due to complex topography. Also, there are different types of climate in these areas. In this research, we used two reanalysis data such as ECMWF Reanalysis 5th Generation Description (ERA5) and National Centers for Environmental Prediction /National Center for Atmospheric Research (NCEP/NCAR) for verification of the numerical model. ERA5 is the latest version of ECMWF. The temporal resolution of ERA5 is hourly, and the NCEP/NCAR is every six hours. Some atmospheric parameters such as mean sea level pressure, geopotential height, relative humidity, wind speed and direction, sea surface temperature, etc. were selected and analyzed. Some different type of precipitation (rain and snow) was selected. The results showed that the NCEP/NCAR has more ability to demonstrate the intensity of the atmospheric system. The ERA5 is suitable for extract the value of parameters for specific point. Also, ERA5 is appropriate to analyze the snowfall events over CS (snow cover and snow depth). Sea surface temperature has the main role to generate instability over CS, especially when the cold air pass from the CS. Sea surface temperature of NCEP/NCAR product has low resolution near coast. However, both data were able to detect meteorological synoptic patterns that led to heavy rainfall over CS. However, due to the time lag, they are not suitable for forecast centers. The application of these two data is for research and verification of meteorological models. Finally, ERA5 has a better resolution, respect to NCEP/NCAR reanalysis data, but NCEP/NCAR data is available from 1948 and appropriate for long term research.

Keywords: synoptic patterns, heavy precipitation, reanalysis data, snow

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Authors: Nadia Nisar

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Background: In the temperate regions Influenza activities occur sporadically all year round with peaks coinciding during cold months. Meteorological and environmental conditions play significant role in the transmission of influenza globally. In this study, we assessed the relationship between meteorological parameters and influenza activity in two geographical areas of Pakistan. Methods: Influenza data were collected from Islamabad (north) and Multan (south) regions of national influenza surveillance system during 2010-2015. Meteorological database was obtained from National Climatic Data Center (Pakistan). Logistic regression model with a stepwise approach was used to explore the relationship between meteorological parameters with influenza peaks. In statistical model, we used the weekly proportion of laboratory-confirmed influenza positive samples to represent Influenza activity with metrological parameters as the covariates (temperature, humidity and precipitation). We also evaluate the link between environmental conditions associated with seasonal influenza epidemics: 'cold-dry' and 'humid-rainy'. Results: We found that temperature and humidity was positively associated with influenza in north and south both locations (OR = 0.927 (0.88-0.97)) & (OR = 0.1.078 (1.027-1.132)) and (OR = 1.023 (1.008-1.037)) & (OR = 0.978 (0.964-0.992)) respectively, whilst precipitation was negatively associated with influenza (OR = 1.054 (1.039-1.070)) & (OR = 0.949 (0.935-0.963)). In both regions, temperature and humidity had the highest contribution to the model as compared to the precipitation. We revealed that the p-value for all of climate parameters is <0.05 by Independent-sample t-test. These results demonstrate that there were significant relationships between climate factors and influenza infection with correlation coefficients: 0.52-0.90. The total contribution of these three climatic variables accounted for 89.04%. The reported number of influenza cases increased sharply during the cold-dry season (i.e., winter) when humidity and temperature are at minimal levels. Conclusion: Our findings showed that measures of temperature, humidity and cold-dry season (winter) can be used as indicators to forecast influenza infections. Therefore integrating meteorological parameters for influenza forecasting in the surveillance system may benefit the public health efforts in reducing the burden of seasonal influenza. More studies are necessary to understand the role of these parameters in the viral transmission and host susceptibility process.

Keywords: influenza, climate, metrological, environmental

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Authors: Babak Kamrani, Nozar Kishi

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Stochastic catalog represents the events module of the earthquake loss estimation models. It includes series of events with different magnitudes and corresponding frequencies/probabilities. For the development of the stochastic catalog, random or uniform sampling methods are used to sample the events from the seismicity model. For covering all the Magnitude Frequency Distribution (MFD), a huge number of events should be generated for the above-mentioned methods. Characteristic Event (CE) method chooses the events based on the interest of the insurance industry. We divide the MFD of each source into bins. We have chosen the bins based on the probability of the interest by the insurance industry. First, we have collected the information for the available seismic sources. Sources are divided into Fault sources, subduction, and events without specific fault source. We have developed the MFD for each of the individual and areal source based on the seismicity of the sources. Afterward, we have calculated the CE magnitudes based on the desired probability. To develop the stochastic catalog, we have introduced uncertainty to the location of the events too.

Keywords: stochastic catalogue, earthquake loss, uncertainty, characteristic event

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Authors: Harish Krishnamurthy, Anna Lafontant, Ren Yi

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Unidentified Flying Objects (UFOs) have been an interesting topic for most enthusiasts and hence people all over the United States report such findings online at the National UFO Report Center (NUFORC). Some of these reports are a hoax and among those that seem legitimate, our task is not to establish that these events confirm that they indeed are events related to flying objects from aliens in outer space. Rather, we intend to identify if the report was a hoax as was identified by the UFO database team with their existing curation criterion. However, the database provides a wealth of information that can be exploited to provide various analyses and insights such as social reporting, identifying real-time spatial events and much more. We perform analysis to localize these time-series geospatial events and correlate with known real-time events. This paper does not confirm any legitimacy of alien activity, but rather attempts to gather information from likely legitimate reports of UFOs by studying the online reports. These events happen in geospatial clusters and also are time-based. We look at cluster density and data visualization to search the space of various cluster realizations to decide best probable clusters that provide us information about the proximity of such activity. A random forest classifier is also presented that is used to identify true events and hoax events, using the best possible features available such as region, week, time-period and duration. Lastly, we show the performance of the scheme on various days and correlate with real-time events where one of the UFO reports strongly correlates to a missile test conducted in the United States.

Keywords: time-series clustering, feature extraction, hoax prediction, geospatial events

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Authors: Afroditi Zamanidou, Dionysios Giannakopoulos, Konstantinos Manolitsis

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A notable amount of electrical energy demand in many countries worldwide is used to cover public energy demand for road, square and other public spaces’ lighting. Renewable energy can contribute in a significant way to the electrical energy demand coverage for public lighting. This paper focuses on the sizing and design of a hybrid energy system (HES) exploiting the solar-wind energy potential to meet the electrical energy needs of lighting roads, squares and other public spaces. Moreover, the proposed HES provides coverage of the electrical energy demand for a Wi-Fi hotspot and a charging hotspot for the end-users. Alongside the sizing of the energy production system of the proposed HES, in order to ensure a reliable supply without interruptions, a storage system is added and sized. Multiple scenarios of energy consumption are assumed and applied in order to optimize the sizing of the energy production system and the energy storage system. A database with meteorological prediction data for 51 areas in Greece is developed in order to assess the possible deployment of the proposed HES. Since there are detailed meteorological prediction data for all 51 areas under investigation, the use of these data is evaluated, comparing them to real meteorological data. The meteorological prediction data are exploited to form three hourly production profiles for each area for every month of the year; minimum, average and maximum energy production. The energy production profiles are combined with the energy consumption scenarios and the sizing results of the energy production system and the energy storage system are extracted and presented for every area. Finally, the economic performance of the proposed HES in terms of Levelized cost of energy is estimated by calculating and assessing construction, operation and maintenance costs.

Keywords: energy production system sizing, Greece’s deployment potential, meteorological prediction data, wind-solar hybrid energy system, levelized cost of energy

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Authors: Sudhanshu Kumar, Raghvendra Chandrakar, Arun Chakraborty

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In the ocean, the temperature extremes have the potential to devastate marine habitats, ecosystems together with ensuing socioeconomic consequences. In recent years, these extreme events are more frequent and intense globally and their increasing trend is expected to continue in the upcoming decades. It recently attracted public interest, as well as scientific researchers, which motivates us to analyze the current marine heatwave (MHW) events in the Bay of Bengal region. we have isolated 107 MHW events (above 90th percentile threshold) in this region of the Indian Ocean and investigated the variation in duration, intensity, and frequency of MHW events during our test period (1982-2021). Our study reveals that in the study region the average of three MHW events per year with an increasing linear trend of 1.11 MHW events per decade. In the analysis, we found the longest MHW event which lasted about 99 days, which is far greater than an average MHW event duration. The maximum intensity was 5.29°C (above the climatology-mean), while the mean intensity was 2.03°C. In addition, we observed net heat flux accompanied by anticyclonic eddies to be the primary cause of these events. Moreover, we concluded that these events affect sea surface height and oceanic productivity, highlighting the adverse impact of MHWs on marine ecosystems.

Keywords: marine heatwaves, global warming, climate change, sea surface temperature, marine ecosystem

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Authors: Retius Chifurira

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Logistic regression model is the most used regression model to predict meteorological drought probabilities. When the dependent variable is extreme, the logistic model fails to adequately capture drought probabilities. In order to adequately predict drought probabilities, we use the generalized linear model (GLM) with the quantile function of the generalized extreme value distribution (GEVD) as the link function. The method maximum likelihood estimation is used to estimate the parameters of the generalized extreme value (GEV) regression model. We compare the performance of the logistic and the GEV regression models in predicting drought probabilities for Zimbabwe. The performance of the regression models are assessed using the goodness-of-fit tests, namely; relative root mean square error (RRMSE) and relative mean absolute error (RMAE). Results show that the GEV regression model performs better than the logistic model, thereby providing a good alternative candidate for predicting drought probabilities. This paper provides the first application of GLM derived from extreme value theory to predict drought probabilities for a drought-prone country such as Zimbabwe.

Keywords: generalized extreme value distribution, general linear model, mean annual rainfall, meteorological drought probabilities

Procedia PDF Downloads 161