WEATHER FORECAST PERCEPTIONS OF SAUDI ARABIAN CITIZENS: INITIAL STEPS TOWARDS BUILDING EXTREME WEATHER FORECASTING COMMUNICATION TECHNOLOGY

2021 ◽  
Author(s):  
Abdulrahman Khamaj ◽  
Amin G. Alhashim ◽  
Vincent T. Ybarra ◽  
Azham Hussain
Keyword(s):  
Weather Forecasting ◽  
Middle Eastern ◽  
Protective Action ◽  
Weather Forecast ◽  
Weather Data ◽  
Cross Sectional ◽  
Daily Lives ◽  
Weather Forecasts ◽  
The Public ◽  
Public Perspective

AbstractCommunicating weather forecasts from the public perspective is essential for meeting people’s needs and enhancing their overall experiences. Due to the lack of cited work on the public’s behavior and perception of weather data and delivery sources in Middle Eastern countries such as Saudi Arabia (KSA), this study employs a cross-sectional questionnaire to fill the gap and apply the Protective Action Decision Model to non-Western individuals. The questionnaire examined respondents’ opinions about 1) the importance of weather forecast accessibility, 2) crucial weather features, and 3) available features on existing smartphone weather applications (apps) in KSA. The results showed that nearly all participants reported that their decisions of daily lives and activities were highly dependent on weather forecasts. Most participants thought weather forecast features are necessary. Though the most commonly used source for weather forecasts in KSA was smartphone apps, many participants responded that these apps were lacking specific weather functionalities (e.g., giving weather alerts to their exact location). Regression analyses found that KSA individuals who do not believe that weather forecasts are important are predicted by 1) not wanting any new features added to weather applications and 2) that weather forecasts do not impact lives nor property. This study’s findings can guide governmental and private weather agencies in KSA and other Middle Eastern or developing countries to better understand how to meet and communicate people’s weather needs.

Visualizing Uncertainty in Weather Forecasts

2020 ◽  
Vol 64 (1) ◽  
pp. 1064-1068
Author(s):  
Qinyu Ding ◽  
Barbara Millet
Keyword(s):  
Weather Forecasting ◽  
Weather Forecast ◽  
Inclusion Criteria ◽  
Design Features ◽  
Uncertainty Visualization ◽  
Weather Forecasts ◽  
The Public ◽  
Design Attributes ◽  
Initial Basis ◽  
Expression Of Uncertainty

Uncertainty bears an inherent relationship to weather forecasting. Even with advances in technology and mathematical modeling improving weather forecasts, communicating risks to the public is still challenging. This systematic review investigates design attributes that influence the expression of uncertainty visualization in weather forecasts. A total of 14 publications met the inclusion criteria. This review revealed six categories of design features that can inform how viewers interpret the uncertainty conveyed in weather forecast displays. These design features also provide us with an initial basis for developing guidelines. We discuss how the features might be used and the importance of doing so.

scholarly journals A novel weather parameters prediction scheme and their effects on crops

2022 ◽  
Vol 12 (1) ◽  
pp. 639
Author(s):  
Naveen Lingaraju ◽  
Hosaagrahara Savalegowda Mohan
Keyword(s):  
Weather Forecasting ◽  
Fitness Function ◽  
Research Work ◽  
Geographical Location ◽  
Weather Forecast ◽  
Forecast Model ◽  
Weather Data ◽  
Prediction Scheme ◽  
Weather Parameters ◽  
Technological World

Weather forecast is significantly imperative in today’s smart technological world. A precise forecast model entails a plentiful data in order to attain the most accurate predictions. However, a forecast of future rainfall from historical data samples has always been challenging and key area of research. Hence, in modern weather forecasting a combo of computer models, observation, and knowledge of trends and patterns are introduced. This research work has presented a fitness function based adaptive artificial neural network scheme in order to forecast rainfall and temperature for upcoming decade (2021-2030) using historical weather data of 20 different districts of Karnataka state. Furthermore, effects of these forecasted weather parameters are realized over five major crops of Karnataka namely rice, wheat, jowar, maize, and ragi with the intention of evaluation for efficient crop management in terms of the passing relevant messages to the farmers and alternate measures such as suggesting other geographical locations to grow the same crop or growing other suitable crops at same geographical location. A graphical user interface (GUI) application has been developed for the proposed work in order to ease out the flow of work.

scholarly journals The communicative process of weather forecasts issued in the probabilistic form

2009 ◽  
Vol 08 (01) ◽  
pp. A03
Author(s):  
Alessio Raimondi
Keyword(s):  
Human Activities ◽  
Weather Forecasting ◽  
Weather Forecast ◽  
Bottom Line ◽  
Weather Forecasts ◽  
Depth Analysis ◽  
Communicative Process ◽  
Hurricane Charley ◽  
Informative Content ◽  
Effective Use

One of the main purposes of weather forecasting is that of protecting weather-sensitive human activities. Forecasts issued in the probabilistic form have a higher informative content, as opposed to deterministic one, since they bear information that give also a measure of their own uncertainty. However, in order to make an appropriate and effective use of this kind of forecasts in an operational setting, communication becomes significatively relevant.The present paper, after having briefly examined the weather forecasts concerning Hurricane Charley (August 2004), tackles the issue of the communicative process in detail.The bottom line of this study is that for the weather forecast to achieve its best predictive potential, an in-depth analysis of communication issues is necessary.

scholarly journals The Met Office Weather Game: investigating how different methods for presenting probabilistic weather forecasts influence decision-making

2019 ◽  
Vol 2 (2) ◽  
pp. 101-116 ◽  
Author(s):  
Elisabeth M. Stephens ◽  
David J. Spiegelhalter ◽  
Ken Mylne ◽  
Mark Harrison
Keyword(s):  
Decision Making ◽  
Weather Forecasting ◽  
Weather Forecast ◽  
Online Game ◽  
Weather Forecasts ◽  
Probabilistic Forecasts ◽  
Presentation Formats ◽  
The Uk ◽  
Mass Participation ◽  
The Impact

Abstract. To inform the way probabilistic forecasts would be displayed on their website, the UK Met Office ran an online game as a mass participation experiment to highlight the best methods of communicating uncertainty in rainfall and temperature forecasts, and to widen public engagement in uncertainty in weather forecasting. The game used a hypothetical “ice-cream seller” scenario and a randomized structure to test decision-making ability using different methods of representing uncertainty and to enable participants to experience being “lucky” or “unlucky” when the most likely forecast scenario did not occur. Data were collected on participant age, gender, educational attainment, and previous experience of environmental modelling. The large number of participants (n>8000) that played the game has led to the collation of a unique large dataset with which to compare the impact on the decision-making ability of different weather forecast presentation formats. This analysis demonstrates that within the game the provision of information regarding forecast uncertainty greatly improved decision-making ability and did not cause confusion in situations where providing the uncertainty added no further information.

Real-Time Weather Analytics

2020 ◽  
Vol 17 (4) ◽  
pp. 15-31
Author(s):  
Lavanya K. ◽  
Sathyan Venkatanarayanan ◽  
Anay Anand Bhoraskar
Keyword(s):  
Data Storage ◽  
Weather Forecasting ◽  
Modern Science ◽  
Weather Forecast ◽  
Forecast Model ◽  
Data Availability ◽  
Third Party ◽  
Weather Data ◽  
Storage Devices ◽  
Weather Forecast Model

Weather forecasting is one of the biggest challenges that modern science is still contending with. The advent of high-power computing, technical advancement of data storage devices, and incumbent reduction in the storage cost have accelerated data collection to turmoil. In this background, many artificial intelligence techniques have been developed and opened interesting window of opportunity in hitherto difficult areas. India is on the cusp of a major technology overhaul with millions of people's data availability who were earlier unconnected with the internet. The country needs to fast forward the innovative use of available data. The proposed model endeavors to forecast temperature, precipitation, and other vital information for usability in the agrarian sector. This project intends to develop a robust weather forecast model that learns automatically from the daily feed of weather data that is input through a third-party API source. The weather feed is sourced from openweathermap, an online service that provides weather data, and is streamed into the forecast model through Kafka components. The LSTM neural network used by the forecast model is designed to continuously learn from predictions and perform actual analysis. The model can be architected to be implemented across very large applications having the capability to process large volumes of streamed or stored data.

Some Interim Results of the Study

1982 ◽  
Vol 35 (3) ◽  
pp. 502-516
Author(s):  
R. Monk
Keyword(s):  
North Atlantic ◽  
Weather Forecast ◽  
Air Traffic ◽  
Weather Data ◽  
Weather Forecasts ◽  
Additional Information ◽  
European Cities ◽  
The North ◽  
The North Atlantic ◽  
To Receive

We are still in the process of collecting and developing ways of studying and analysing air traffic routes across the North Atlantic. The results presented in this paper must therefore be recognized as provisional. The data comprise some twelve examples of North Atlantic weather forecasts issued from Bracknell; they are sent to us regularly for the 2nd and 15th day of each month. We have also made arrangements to receive notification from the Heathrow Meteorological Office of any days in which there were significant changes in the weather forecast, so that we can request the additional information from Bracknell. Each set of weather data contains the ‘analysis weather’, that is the best estimate of the actual weather at 1200 GMT, and therefore applicable to the time when aircraft are making westerly departures across the North Atlantic from European cities, and also the weather forecasts issued for 12 and 24 hours before this time.

scholarly journals Next-Day Prediction of Hourly Solar Irradiance Using Local Weather Forecasts and LSTM Trained with Non-Local Data

Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5258 ◽  
Author(s):  
Byung-ki Jeon ◽  
Eui-Jong Kim
Keyword(s):  
Solar Irradiance ◽  
Short Term Memory ◽  
Predictive Performance ◽  
Weather Forecast ◽  
Weather Data ◽  
Local Data ◽  
Weather Forecasts ◽  
Proposed Model ◽  
International Data ◽  
Limited Input Data

Solar irradiance prediction is significant for maximizing energy-saving effects in the predictive control of buildings. Several models for solar irradiance prediction have been developed; however, they require the collection of weather data over a long period in the predicted target region or evaluation of various weather data in real time. In this study, a long short-term memory algorithm–based model is proposed using limited input data and data from other regions. The proposed model can predict solar irradiance using next-day weather forecasts by the Korea Meteorological Administration and daily solar irradiance, and it is possible to build a model with one-time learning using national and international data. The model developed in this study showed excellent predictive performance with a coefficient of variation of the root mean square error of 12% per year even if the learning and forecast regions were different, assuming that the weather forecast was correct.

scholarly journals Eye Tracking: Evaluating the Impact of Gesturing during Televised Weather Forecasts

2015 ◽  
Vol 96 (3) ◽  
pp. 387-392 ◽  
Author(s):  
Robert Drost ◽  
Jay Trobec ◽  
Christy Steffke ◽  
Julie Libarkin
Keyword(s):  
Eye Tracking ◽  
Weather Forecast ◽  
Weather Forecasts ◽  
The Public ◽  
Weather Information ◽  
Study Results ◽  
Physical Gestures ◽  
Areas Of Interest ◽  
The Second Variation ◽  
The Impact

Abstract Televised media is one of the most frequently accessed sources of weather information. The local weathercaster is the link between weather information and the public, and as such weathercaster characteristics, from vocal cadence to physical appearance, can impact viewer understanding. This study considers the role of weathercaster gesturing on viewer attention during weather forecasts. Two variations of a typical weather forecast were viewed by a total of 36 students during an eye tracking session. The first forecast variation contained physical gestures toward forecast text by the newscaster (Gesture condition) while the second variation contained minimal gesturing (No Gesture condition). Following each eye tracking session, students completed a retention survey related to the forecast. These data were used to identify areas of interest to which students attended during viewing and to ascertain how well the forecast was retained across the gesturing treatments. Study results suggest that the weathercaster’s gesturing during forecasts may have induced confusion among participants, but did not affect retention of the weather information investigated in the study. Gesturing diverted attention from other areas of interest within the forecast by encouraging participants to focus on the weathercaster’s hands. This study indicates that minor modifications to weathercaster behavior can produce significant changes in viewer behavior.

scholarly journals Resolution of Probabilistic Weather Forecasts with Application in Disease Management

2017 ◽  
Vol 107 (2) ◽  
pp. 158-162 ◽  
Author(s):  
G. Hughes ◽  
N. McRoberts ◽  
F. J. Burnett
Keyword(s):  
Disease Management ◽  
Mutual Information ◽  
Disease Risk ◽  
Information Gain ◽  
Weather Forecast ◽  
Weather Data ◽  
Specific Information ◽  
Information Theoretic ◽  
Weather Forecasts ◽  
Measuring Change

Predictive systems in disease management often incorporate weather data among the disease risk factors, and sometimes this comes in the form of forecast weather data rather than observed weather data. In such cases, it is useful to have an evaluation of the operational weather forecast, in addition to the evaluation of the disease forecasts provided by the predictive system. Typically, weather forecasts and disease forecasts are evaluated using different methodologies. However, the information theoretic quantity expected mutual information provides a basis for evaluating both kinds of forecast. Expected mutual information is an appropriate metric for the average performance of a predictive system over a set of forecasts. Both relative entropy (a divergence, measuring information gain) and specific information (an entropy difference, measuring change in uncertainty) provide a basis for the assessment of individual forecasts.

Knowing Their Place: The Blue Hill Observatory and the Value of Local Knowledge in an Era of Synoptic Weather Forecasting, 1884–1894

2016 ◽  
Vol 29 (3) ◽  
pp. 305-346 ◽  
Author(s):  
James Bergman
Keyword(s):  
Local Knowledge ◽  
Weather Forecasting ◽  
Scale Up ◽  
Weather Forecast ◽  
Weather Forecasts ◽  
Synoptic Weather ◽  
Observation Network ◽  
Meteorological Observatory ◽  
History Of ◽  
The U.S

ArgumentThe history of meteorology has focused a great deal on the “scaling up” of knowledge infrastructures through the development of national and global observation networks. This article argues that such efforts to scale up were paralleled by efforts to define a place for local knowledge. By examining efforts of the Blue Hill Meteorological Observatory, near Boston, Massachusetts, to issuelocalweather forecasts that competed with the centralized forecasts of the U.S. Signal Service, this article finds that Blue Hill, as a user of the Signal Service's observation network, developed a new understanding of local knowledge by combining local observations of the weather with the synoptic maps afforded by the nationwide telegraph network of the U.S. Signal Service. Blue Hill used these forecasts not only as a service, but also as evidence of the superiority of its model of local forecasting over the Signal Service's model, and in the process opened up larger questions about the value of a weather forecast and the value of different kinds of knowledge in meteorology.

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