Weather-related Information Research Articles

원주이씨 해남문중의 『용하도록』과 지역사 정보

In this article, we analyzed the 『Yonghadorok(用下都錄)』 owned by WonjuLee clan(原州李氏) and examined the area of Durak(斗落) in the Haenam region , the problem of place names, the opening of Mokpo Port and the rice crop house, and the drought in the Haenam region during the Japanese colonial period. The average area of 1 durak in 『Yonghadorok』 is 214 pyeong(坪), which is larger than the average of 200 pyeong in Haenam Country. And out of the 12 places analyzed, there are as many as 4 places that deviate from 200 pyeong to 10% error of 180~220 pyeong, and among them, 2 places are close to 300 pyeong. Thus, it can be seen that even within the same municipality there was a great deviation in the area of 1 durak. 『Yonghadorok』 conveys micro-place names that have not been recorded in the existing research. Accordingly, the analysis of Yonghagi(用下記) can be said to be local history information that can supplement the study of place names at dong(洞) levels. On the other hand, if you look at the 『Yonghadorok』, the same place name is written in different Chinese characters depending on the writer, which shows that even the local literate class was not well versed in the origin of the place names in their own region. The Haenam(海南) area belongs to the Mokpo cultural area, where Mokpo Port can be easily accessed by ship. With the opening of the port of Mokpo Port, the price of rice skyrocketed. Specifically, the price of rice in Haenam and Yeongam(靈巖) region soared 2 times and 2.42 times, respectively. The crop status of Yonghagi is an indirect data that can grasp the drought at the city and county level as a time series. As a result of the analysis, through in 1901, 1912, 1938, and 1942~1943, when droughts occurred in Jeolla Province(全羅道), in Haenam region the average or abundant crops were harvested. As a result, it was possible to specifically observe that the weather-related information at the Province(道) level cannot be applied to the city and county level as it is.

Agriculture data analysis using parallel k-nearest neighbour classification algorithm

A cost-effective and effective agriculture management system is created by utilizing data analytics (DA), internet of things (IoT), and cloud computing (CC). Geographic information system (GIS) technology and remote sensing predictions give users and stakeholders access to a variety of sensory data, including rainfall patterns and weather-related information (such as pressure, humidity, and temperatures). They have unstructured format for sensory data. The current systems do a poor job of analysing such data since they cannot effectively balance speed and memory usage. An effective categorization model (ECM) on agriculture management system is proposed to address this research difficulty. First, a classification technique called priority-based k-nearest neighbour (KNN) is provided to categorize unstructured multi-dimensional data into a structured form. Additionally, the Hadoop MapReduce (HMR) framework is used to do classification utilizing a parallel approach. Data from real-time IoT sensors used in agriculture is the subject of experiments. The suggested approach significantly outperforms previous approaches that are computing time, memory efficiency, model accuracy, and speedup.

Reducing consequences of extreme heat: The role of weather information access

This study investigates the impact of weather information sources on consequences associated with extreme heat events, employing a cross-sectional survey conducted on hospitalized individuals who have experienced heat stress in Central Vietnam. Multiple information channels, including official agencies and social media, were found to significantly reduce the Cost of Illness (COI) associated with heat-related ailments. Social media, in particular, emerged as a potent tool for climate adaptation. Improving the clarity and accessibility of weather information through official channels is crucial, especially for households with varying income levels. Demographic factors such as age and gender should be considered when fine-tuning communication strategies, with special attention given to individuals with underlying medical conditions, who are particularly susceptible to extreme heat effects. These findings underscore the need to maximize the reach of weather-related information and reduce economic burdens on affected populations. This provides valuable insights for policymakers aiming to bolster climate resilience in vulnerable regions like Vietnam, emphasizing the significance of diverse information sources and tailored communication in climate change adaptation.

Weather effects on natural surface trail use in an urban wilderness multi-use trail system

Previous research has concluded weather conditions can influence physical activity (PA) on trails. However, these studies focused primarily on mixed-use paved surface trails. Many recreational areas use natural surface trails for mountain biking, trail running, and walking. The purpose of this study was to analyze the association between weather conditions and the use of natural surface trails for PA. In addition, this investigation sought to determine if the type of trail surface material, gravel vs. dirt, impacted PA differently by weather factors. Infrared trail counters were used to measure hourly trail use within Knoxville's Urban Wilderness in Knoxville, TN. An onsite weather station was used to obtain hourly weather variables. Negative binomial regression models were used to analyze the relationship between trail use and weather conditions. Both trail locations experienced bi-modal peaks in usage with Spring and Fall months showing the highest usage. As temperature increased, so did trail use (β = 0.115, p = 0.00); however, gravel trail use began to decrease at temperatures above 86 °F. Precipitation negatively impacted trail use on both gravel (β = −3.114, p = 0.00) and dirt (β = −2.281, p = 0.00) trails. Relative humidity and had a negative relationship with trail use on both trails. UVRI (β = −0.036) was only significantly associated with dirt trail use. The direction of the effect of weather measures on natural surface trail use is similar to previous studies on paved trails; however, the magnitude of the effect varies. Gravel trail use was more sensitive to temperature and precipitation, while relative humidity, absolute pressure, and UVRI had a greater impact on dirt trail use. The variations in the magnitude of the effect may be a function of the activity performed on the different trail surfaces. Trail surface material should be considered to fully understand the impact weather has on trail use. Management implicationsBy understanding the behaviors of natural surface trail users in response to various weather conditions, managers can adapt their trail planning (i.e., type of trail, surface material), maintenance, and funding for various projects. Managers could collect weather-related information in conjunction with trail surface conditions to inform users of more user-friendly trails during adverse weather events. This could decrease trail maintenance by shifting users to trails that can tolerate more use in poor weather. Additionally, this information would enable managers to develop programs more effectively (e.g., special events, learning clinics) and thus engage more people in outdoor recreation.

Farmers’ Awareness and Perception about Climate Change in the Indo-Gangetic Plain Region of India

Climate change is negatively impacting agriculture productivity worldwide. Accordingly, it becomes necessary to know the level of farmers’ awareness about climate change. The study was conducted in the year 2023 to examine farmers’ awareness and perceptions about nature, and the impact of changes in climate patterns on agriculture in India’s Indo Gangetic Plain (IGP) region. The study is based on a survey of 400 farmers, selected conveniently from five districts of Uttar Pradesh, a prominent province of the IGP region. The weighted average mean and chi-square test were applied to analyze the primary data. The findings indicate that farmers of the sampled area were aware of the problem, they get weather-related information from multiple sources like television, newspapers, etc. Almost half of the respondents in the sampled area strongly consider climate change as anthropogenic as well as naturogenic. Farmers perceived that reduced crop yields as the premier ultimatum of climate change in agriculture. The results unveil that the contrasting income groups have different levels of awareness of climate change similarly youth and educated farmers rely on their specific sources of weather-related information.

Who Cares about the Weather? Inferring Weather Conditions for Weather-Aware Object Detection in Thermal Images

Deployments of real-world object detection systems often experience a degradation in performance over time due to concept drift. Systems that leverage thermal cameras are especially susceptible because the respective thermal signatures of objects and their surroundings are highly sensitive to environmental changes. In this study, two types of weather-aware latent conditioning methods are investigated. The proposed method aims to guide two object detectors, (YOLOv5 and Deformable DETR) to become weather-aware. This is achieved by leveraging an auxiliary branch that predicts weather-related information while conditioning intermediate layers of the object detector. While the conditioning methods proposed do not directly improve the accuracy of baseline detectors, it can be observed that conditioned networks manage to extract a weather-related signal from the thermal images, thus resulting in a decreased miss rate at the cost of increased false positives. The extracted signal appears noisy and is thus challenging to regress accurately. This is most likely a result of the qualitative nature of the thermal sensor; thus, further work is needed to identify an ideal method for optimizing the conditioning branch, as well as to further improve the accuracy of the system.

Experimental Methodology to Optimize Power Flow in Utility Grid with Integrated Renewable Energy and Storage Devices Using Hidden Markov Model

A continuous energy supply to the load side is required by modern power systems. This calls for a sound understanding of how to forecast load demand in the present and the future with the least degree of inaccuracy. Typically, a sequential method with two steps—forecasting and optimization—is used to derive judgments from data. For achieving this goal, optimized power flow is focused in this paper through load forecasting, mode selection, and optimization of power forecasting. Firstly, load forecasting is implemented using time series, and economic and weather-related information for the different consumer’s load. Then mode selection is implemented using Hidden Markov Model that determines the requested load for grid-connected or RES mode. When composite RES is developed, the percentage of serviced load rises as more renewable energy sources are added. Following the implementation of the consumer load and mode selection, optimization is used to improve the power flow. The empirical findings show enhanced prescriptive performance when compared to answers found in single- and multi-household contexts. Also, we offer insightful information on how explaining performance is described.

Weather information and agricultural outcomes: Evidence from a pilot field experiment in Benin

Weather conditions are an important determinant of agricultural factor input, particularly labor allocation. The availability of weather forecasts can therefore lead to efficiency gains in the form of cost decreases and productivity increases. We test the practical feasibility, the uptake, and the effect of providing basic weather forecasts in the rainy season on the labor productivity of smallholder farmers. For this purpose, we conducted a Randomized Controlled Trial as a pilot with monthly data collections involving 331 farmers across six villages in northern Benin. We find that most farmers subscribe to the intervention and report satisfaction with the service. The impact estimates indicate positive and economically significant intention-to-treat and local average treatment effects in terms of reduced relative labor costs, increased yield and, in turn, increased labor productivity for maize and cotton cultivation. These benefits come at relatively low cost, suggesting that weather-related information via mobile phone outreach holds promise for helping smallholder farmers to better adapt to changing weather.

Factors affecting adoption intensity of climate change adaptation practices: A case of smallholder rice producers in Chitwan, Nepal

This study examines how smallholder rice producers' adoption intensity for climate change adaptation practices (i.e., improved varieties, irrigation practices, direct seeded rice, integrated pest management, and adjustment in crop calendar) is influenced by access to Extension services, training, weather-related information, and membership in farmer groups or cooperatives (referred to as “institutional resources”). We use survey data collected from 359 smallholder rice producers in the Chitwan district of Nepal in 2019. The results indicate that: (1) access to institutional resources significantly enhance the likelihood of adoption of more climate change adaptation practices; (2) high intensity climate change adaptation practice measured by the adoption of three, four, and five practices significantly increases with access to institutional resources; (3) intensity of adoption of climate change adaptation practices is reduced with greater adaptation alternatives available to rice producers; and (4) lack of information and technical knowledge are the most important reasons for non-adoption of climate change adaptation practices by smallholder rice producers. The results are valuable for policy makers and planners to prioritize training opportunities and allocate scarce resources to enhance climate change adaptation and improve sustainability of rice production practices.

Do You See What I See? How Media Choice and Visual Tornado Cues Influence Individual Storm Preparation

Abstract When a tornado hits, there is little time to think through mental checklists for needed items. This study attempted to understand what information sources those in the path of tornados utilized for preparation and how those sources influence people to act. Results from the study indicate that television and radio are the top two information sources, and that some visual graphics—gauged via heat maps to understand higher levels of severe weather preparation—were reported as useful. Contrary to meteorological intentions, results showed that participants were less likely to prepare for impending weather when radar displayed tornado locations and intensity. In addition, those who identified as having more interest in weather-related information in the study were significantly more likely to prepare, along with those who fear future tornadoes. Each variable explored is underpinned by the theory of planned behavior and the risk information seeking and processing (RISP) model to better understand behavioral intentions and actions. This study offers two new concepts of general weather that have not previously been explored: interest and general versus specific storm preparation. Significance Statement The purpose of this work is to learn more about how individuals gather information and obtain weather warnings, primarily during tornado events. In particular, the study seeks to understand how individuals view and interpret visual graphics with information about the location and details about the event. Further, results suggest some differences between those who generally prepare for storm season versus those who only prepare for a specific event. Researchers may also be interested to know how weather enthusiasts may differ in their preparatory activities in comparison with nonweather enthusiasts. All of this information will help meteorologists and media professionals to better target their messages during severe weather.

Examining complementary relationships among climate change adaptation practices of rice producers in Chitwan, Nepal

ABSTRACT This study examines how the complementary relationships among multiple climate change adaptation strategies (improved varieties, irrigation practices and direct-seeded rice, referred to as ‘DSR’) are influenced by access to Extension services, training related to farming practices and weather-related information (referred to as ‘institutional factors’). This study hypothesizes the influence of institutional factors and the resulting effects on their joint adoption using survey data collected from 359 rice producers in Chitwan district of Nepal in 2019. The results indicate: (1) adoption of all the three climate change adaptation practices are complementary to each other; (2) all three institutional factors enhance the likelihood of the adoption of variety, access to Extension and training enhances the likelihood of the adoption of improved irrigation, and information enhances the likelihood of the adoption of DSR and (3) access to Extension and training enhance the complementarities among all three pairs of adaptation practices (variety and irrigation; variety and DSR and irrigation and DSR), while information enhances the complementarity between variety and DSR only. The impact of complementary relationships among multiple climate change adaptation strategies influenced by the institutional factors is particularly valuable for policy makers and government agencies to allocate and prioritize resources.

Quantifying the Effect of Rainfall and Visibility Conditions on Road Traffic Travel Time Reliability

Abstract This research explores a data-driven methodological framework to quantify the effect of rainfall and visibility on travel time reliability (TTR) by considering selected road segments in North Carolina. The framework includes capturing, processing, and integrating weather-related information and travel time data for the selected road segments. Various TTR indices were computed for the selected road segments under different rainfall and visibility ranges by day of the week (DOW) and time of the day (TOD). The TTR indices were computed for one week before and after (same DOW and TOD) under the normal weather condition and compared with those obtained under different intensities of rainfall and visibility. The variability in travel time patterns due to other events is expected to be marginal when considering the same DOW and TOD for comparison purposes. The results indicate that poor visibility with different rainfall intensities has the maximum adverse effect on the TTR. The outcomes from the data-driven methodological framework help the transportation planners in developing weather-responsive traffic management strategies and assessing their effectiveness using TTR indices. Significance Statement Travel time reliability (TTR) generally refers to the level of consistency or dependability in transportation service. It is considered as a measure of road operational performance. Ensuring higher levels of reliability is critical for efficient transportation system management along with mobility and accessibility needs. However, factors such as weather condition have a negative effect on the TTR. A data-driven methodological framework is proposed by integrating weather information and travel time data to quantify the effect of common weather conditions like rainfall and visibility on the TTR. The results indicated that heavy rain and poor visibility have an adverse effect on the TTR. These results are useful for agencies to better manage the traffic under different weather conditions.

8 - The Impact of Short Message Services (SMS) Weather Forecasts on Cost, Yield and Income in Maize Production: Evidence from a Pilot Randomised Controlled Trial in Bembèrèkè, North Benin

In this study we analyse the impact of weather forecasts provided to smallholder maize farmers through mobile phone short message service on self-reported labour costs, crop yield and income. We conducted a pilot field experiment, involving 331 randomly selected eligible farmers in six villages. Randomisation was done at the village level. We used three regression specifications to estimate the impacts: Ordinary Least Squares (OLS), Generalised Estimating Equations (GEE) with a small sample correction and Randomisation Inference (RI). We found that the treatment and control groups were well balanced. Farmers in the treatment group recorded lower labour costs but higher crop yield and income levels. Both the direction and the magnitude of the impact estimates were consistent across the three regression specifications, but significant with the RI model only (for labour costs and yield) or the RI and GEE models (for income). Weather forecasts can have an impact on smallholder farmers’ labour, yield and income. These findings are strong evidence of the possibility of using weather-related information and mobile phones to build smallholder farmers’ resilience to climate variability. Yet more research is required to build a solid evidence base to inform agricultural policies. Rosaine N. Yegbemey, Laboratoire d’Analyse et de Recherches sur les Dynamiques Economiques et Sociales (LARDES), Faculté d’Agronomie, Université de Parakou, Bénin. Email: ynerice@gmail.com; rosaine.yegbemey@fa-up.bj Aline M. Aloukoutou, Bureau de Recherche et de Développement en Agriculture (Breda-ONG). Email: alma_aline@yahoo.com Ghislain B. D. Aïhounton, Laboratoire d’Analyseet de Recherches sur les Dynamiques Economiques et Sociales (LARDES), Faculté d’Agronomie, Université de Parakou, Bénin. Email: aihountong@gmail.com

6 - Impact Pathways of Weather Information for Smallholder Farmers: A Qualitative ex ante Analysis

This article explores ex ante the impact pathways of a hypothetical intervention which consists in providing smallholder farmers with weather-related information. It uses a qualitative approach based on focus group discussions in three villages with smallholder farmers and agricultural extension officers to build a theory of change. Results suggest that providing smallholder farmers with weather-related information has the potential to help them in taking informed production decisions. In doing so, smallholder farmers can better allocate their production resources and eventually record higher yield and income. The ultimate impact is that smallholder farmers will have better lives (i.e. livelihoods). There are several types of weather-related information that can be useful for farmers. There are also several dissemination channels. Some are based on local social networks and others on information and communication technologies. Each channel has strengths and weaknesses and the best or optimal dissemination approach would probably depend on the setting of the intervention area. A number of assumptions need to be in place for an impactful intervention. For instance, weather-related information needs to be accurate, available in a timely manner and easy to use. The described possible impact pathways need to be tested rigorously through policy-oriented research.
 Rosaine N. Yegbemey, Laboratoire d’Analyse et de Recherches sur les Dynamiques Economiques et Sociales (LARDES), Faculté d’Agronomie, Université de Parakou, Bénin. Email: ynerice@gmail.com; rosaine.yegbemey@fa-up.bj
 Aline M. Aloukoutou, Bureau de Recherche et de Développement en Agriculture (Breda-ONG). Email: alma_aline@yahoo.com
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 Ghislain B. D. Aihounton, Laboratoire d’Analyse et de Recherches sur les Dynamiques Economiques et Sociales (LARDES), Faculté d’Agronomie, Université de Parakou, Bénin. Email: aihountong@gmail.com

Farmers' choices of climate-resilient strategies: Evidence from Vietnam

Farmers have a long history of adapting to changing conditions, including changing climate, towards more sustainable agricultural production. In this study, we construct a unique long-duration pseudo-panel dataset from nationally representative households in Vietnam to investigate factors behind farmer's choices to adopt soil and water conservation techniques to adapt to climatic change. Since farmers' adoption decisions are inherently dynamic, a dynamic probit model was estimated. We find that weather shocks and long-run changes in temperature are significant determinants of farmers' choices. The decision to make new investments in adaptation practices in subsequent periods is confirmed to be strongly influenced by the past adoption decision. Farmer's experience, farm size, and access to weather and output price information are also associated with households that apply conservation measures. These findings suggest that policies aiming at promoting climate-resilient strategies should pay attention to farmers' adaptation behavior and the persistence of choices in farmers' decision-making processes. Policies should target improving farmers' access to information with a special focus on market- and weather-related information to enhance farmers' adaptive capacity to better cope with ongoing climatic uncertainty.

"Farmers’ Prosperity Through ITC Based Farmers Awareness Programme: An Evidence of Gramin Krishi Mausam Sewa"

The real-time availability of weather information plays a crucial role in agricultural production, food security, and sustainable production (Haile 2005; Rathore 2013; Pandey and Singh, 2019). Thus, any slight aberration in obtaining key weather parameters by the farming community can significantly disrupt the supply chain besides jeopardizing the lives and livelihood of millions of farmers. It is well established that weather parameters influence agricultural operations farm production and productivity, while weather aberration is an important reasonor crop loss in India (Chattopadyaya et al. 2011; Rao et al. 2015; Das et al. 2018). Most of the farmers lack real-time weather-related information to make specific decisions on cropping. Further, the weather-related data for a particular crop seldom available on a single platform (Kumar et al. 2015) though the ICT is rooted firmly. It may be concluded that agriculture and its activities are mostly depend upon weather parameters. The GKMS may create an effort to help the farming community to improve its decision-making. Farmers also adopt GKMS as a tool that may help them decide regarding farming activity. This weather based agromet advisory may also help the farming community to increase the yield as well as for the reducing the cost of cultivation of crops.

Influence of Weather Features in Determining Sudden Braking

Understanding conditions and situations causing abnormal driving behaviors like sudden braking or sudden acceleration is important for preventing traffic accidents. Previous studies have used probe vehicle data to detect risky situations where sudden braking frequently occurred. However, they have mainly focused on location and vehicle-related factors. In this paper, we build models which discriminate sudden braking using a machine learning method. The models use weather-related information as well as probe data. To investigate how weather-related factors help to determine sudden braking, we conducted extensive experiments using probe data obtained from dashboard cameras and two types of weather-related information obtained from meteorological observatories (MO) and AMeDAS. Experimental results illustrate that using weather-related information improves performance in determining sudden braking and that the temporally and spatially denser characteristics of weather-related factors from AMeDAS help to compensate for insufficiencies in the model with MO data.

Communication Structures and Decision Making Cues and Criteria to Support Effective Drought Warning in Central Malawi

Early warning systems trigger early action and enable better disaster preparedness. People-centered dissemination and communication are pivotal for the effective uptake of early warnings. Current research predominantly focuses on sudden-onset hazards, such as floods, ignoring considerable differences with slow-onset hazards, such as droughts. We identify the essential factors contributing to effective drought dissemination and communication using the people-centered approach advocated in the WMOs Multi-Hazard Early Warning System Framework (MHEWS). We use semi-structured interviews with key stakeholders and focus group discussions with small-scale farmers in the Mangochi and Salima Districts of Malawi. We show that the timely release of seasonal forecast, the tailoring of the drought warning content (and its timing) to agricultural decision making, and the provision of several dissemination channels enhance trust and improve uptake of drought warning information by farmers. Our analysis demonstrates that farmers seek, prepare, and respond to drought warning information when it is provided as advice on agricultural practices, rather than as weather-related information. The information was found to be useful where it offers advice on the criteria and environmental cues that farmers can use to inform their decisions in a timely manner. Based on our findings, we propose that by focusing on enhancing trust, improving information uptake and financial sustainability as key metrics, the MHEWS can be adapted for use in monitoring the effectiveness of early warning systems.

Utilization pattern of information sources for weather forecast among farmers of Chhattisgarh plains

There is a large deficit of information and knowledge in this vulnerable region which impedes decision making and assessment of climate related risks. The information on changing climatic conditions and its impact on agriculture and allied activities must be made available to those farmers that are far from weather stations. This study was conducted to determine utilization pattern of information sources for weather forecast among 240 farmers of Chhattisgarh Plains during 2016. The respondents were asked about the mass media sources utilized by them and it was found that almost half of respondents were having low level of use of mass media sources. Majority (55.83%) of the respondents were having low level of utilization of information sources for collecting weather information followed by 33.75 per cent of them had reported medium level of utilization. It revealed that friends/relatives/etc., newspaper, mobile and national TV channel were most credible sources of information to collect weather related information with credibility index of 76.54, 69.24, 65.48 and 60.54 per cent, respectively. National TV channel, friends/relatives/etc., newspaper and regional TV channel were most frequently used information sources for gathering weather related information with the extent of 61.46, 52.50, 49.17 and 28.13 per cent, respectively. The utility of information related to weather forecast were 39.30, 35.55 and 31.80 per cent for national TV channel, friends/relatives/etc. and news paper, respectively. It can conclusively say that friends/relatives/etc. and newspaper were more credible among the respondents. More than half of them were using those sources for gathering information but most of the respondents were not applying it in their actual practice due to irrelevancy of weather related information. Therefore, relevant and timely weather forecast is needed to build trust among the respondents so that they can change their cultivation practices according to changing climatic condition.

Assessing Weather Services for Rural Fishing and Farming Communities in Uganda.

Climate-related hazards like drought are associated with loss of life and lead to food insecurity in many parts of sub-Saharan Africa. Food insecurity, which affects more than 220 million sub-Saharan Africans, manifests as starvation that leads to more than 50% of children under the age of 5-years presenting as underweight for age in many communities on the continent. This household survey reports the means by which rural fisher folk and farming communities in Uganda gained access to early warning meteorological information. The survey covered five districts across different climatic zones in Uganda and recruited a total of 405 respondents with an average age of 41 years (SD 16). Economic activity was used to categorize each of the five districts into farming (crops and livestock) and fishing areas. The results showed that most respondents were unaware of drought as one of the climate-related hazards. Compared to respondents from the fishing communities, the respondents from farming communities were more likely to be receiving weather-related information (P-value < 0.01). There were 204/405 (50.37%) female respondents who, compared to male respondents, were less likely to have access to weather information, less willing to pay for weather information, and less likely to have and or own devices like a radio for receiving weather information. The survey demonstrated that: 1) there were gaps in the knowledge about climate-related hazards, 2) there is a need for additional interventions targeting fisher folk communities access timely weather information, and 3) introducing user paid access to weather information may increase climate-related gender-based disparities.