scholarly journals Weather Forecasting in Brazil: A Concise Historical Review

2021 ◽  
Vol 44 ◽  
Author(s):  
Valdo Da Silva Marques ◽  
Claudine Dereczynski
Keyword(s):  
Weather Forecasting ◽  
Technological Development ◽  
Historical Review ◽  
Weather Forecast ◽  
Weather Forecasts ◽  
Weather Forecasters ◽  
Survey Results ◽  
Formation And Evolution ◽  
Climate Studies ◽  
And Training

The main objective of this article is to describe the factors and issues responsible for the evolution of the weather forecast in Brazil.This is done based on a historical review of the formation and evolution of the national meteorological services in the last 170 yearsand on the development of weather forecasting methods. Changes in the routines of weather forecasting services in two centenaryBrazilian institutions, the National Institute of Meteorology and the Brazilian Navy, since the creation of the first subjective forecaststo the present day, are highlighted. Information about the 14 undergraduate courses in Meteorology in Brazil is given, which supportthe technological development of this science, through scientific research and training of human resources. The introduction ofmeteorological radar in the 1970s, and its current networks, as well as the elaboration of the first numerical weather predictions (NWP)by the Center for Weather Forecasting and Climate Studies (Centro de Previsão do Tempo e Estudos Climáticos do Instituto Nacionalde Pesquisas Espaciais – CPTEC/INPE), in 1995, are also described. To complement, a survey is presented, showing the currentworking conditions of weather forecasters. The survey results reveal that 45% of the 102 meteorologists interviewed use the CzechRepublic Windy application to prepare their weather forecasts operationally and almost 60% use the Wyoming University website toobtain data from radiosondes launched in Brazil. It is important to highlight that, since the introduction of NWP by CPTEC/INPE, at theend of the 1990s, there has been a great advance in the field of weather forecasting. Moreover, observational networks have undergonea great expansion, with a significant increase in the number of weather stations in recent decades. Despite all the progress achieved,there is still a need for the integration of observational networks and databases of various institutions. Finally, the development ofapplications that meet the demand of young meteorologists in the operational centers is advisable.

scholarly journals Maintaining the Role of Humans in the Forecast Process: Analyzing the Psyche of Expert Forecasters

2007 ◽  
Vol 88 (12) ◽  
pp. 1893-1898 ◽  
Author(s):  
Neil A. Stuart ◽  
David M. Schultz ◽  
Gary Klein
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Weather Forecasting ◽  
Time Constraints ◽  
Learning Gap ◽  
Weather Forecasters ◽  
The Future ◽  
Mental Modeling ◽  
And Training

The Second Forum on the Future Role of the Human in the Forecast Process occurred on 2–3 August 2005 at the American Meteorological Society's Weather Analysis and Forecasting Conference in Washington, D.C. The forum consisted of three sessions. This paper discusses the second session, featuring three presentations on the cognitive and psychological aspects of expert weather forecasters. The first presentation discussed the learning gap between students (goal seekers) and teachers (knowledge seekers)—a similar gap exists between forecasters and researchers. In order to most effectively train students or forecasters, teachers must be able to teach across this gap using some methods described within. The second presentation discussed the heuristics involved in weather forecasting and decision making under time constraints and uncertainty. The final presentation classified the spectrum of forecasters from intuitive scientists to the disengaged. How information technology can best be adapted so as not to inhibit intuitive scientists from their mental modeling of weather scenarios is described. Forecasters must continuously refine their skills through education and training, and be aware of the heuristic contributions to the forecast process, to maintain expertise and have the best chance of ensuring a dynamic role in the future forecast process.

Weather Forecasting by Humans—Heuristics and Decision Making

2004 ◽  
Vol 19 (6) ◽  
pp. 1115-1126 ◽  
Author(s):  
Charles A. Doswell
Keyword(s):  
Decision Making ◽  
Cognitive Psychology ◽  
Multidisciplinary Approach ◽  
Weather Forecasting ◽  
Judgment And Decision Making ◽  
Human Cognition ◽  
Weather Forecasts ◽  
Weather Forecasters ◽  
Insight Into ◽  
Considerable Insight

Abstract The decision-making literature contains considerable information about how humans approach tasks involving uncertainty using heuristics. Although there is some reason to believe that weather forecasters are not identical in all respects to the typical subjects used in judgment and decision-making studies, there also is evidence that weather forecasters are not so different that the existing understanding of human cognition as it relates to making decisions is entirely inapplicable to weather forecasters. Accordingly, some aspects of cognition and decision making are reviewed and considered in terms of how they apply to human weather forecasters, including biases introduced by heuristics. Considerable insight into human forecasting could be gained by applying available studies of the cognitive psychology of decision making. What few studies exist that have used weather forecasters as subjects suggest that further work might well be productive in terms of helping to guide the improvement of weather forecasts by humans. It is concluded that a multidisciplinary approach, involving disciplines outside of meteorology, needs to be developed and supported if there is to be a future role for humans in forecasting the weather.

scholarly journals Generating Probabilistic Next-Day Severe Weather Forecasts from Convection-Allowing Ensembles Using Random Forests

2020 ◽  
Vol 35 (4) ◽  
pp. 1605-1631
Author(s):  
Eric D. Loken ◽  
Adam J. Clark ◽  
Christopher D. Karstens
Keyword(s):  
Random Forests ◽  
Weather Forecast ◽  
Severe Weather ◽  
Decision Makers ◽  
Limited Information ◽  
Weather Forecasts ◽  
Skill Scores ◽  
Weather Forecasters ◽  
Forecast Data ◽  
Better Than

AbstractExtracting explicit severe weather forecast guidance from convection-allowing ensembles (CAEs) is challenging since CAEs cannot directly simulate individual severe weather hazards. Currently, CAE-based severe weather probabilities must be inferred from one or more storm-related variables, which may require extensive calibration and/or contain limited information. Machine learning (ML) offers a way to obtain severe weather forecast probabilities from CAEs by relating CAE forecast variables to observed severe weather reports. This paper develops and verifies a random forest (RF)-based ML method for creating day 1 (1200–1200 UTC) severe weather hazard probabilities and categorical outlooks based on 0000 UTC Storm-Scale Ensemble of Opportunity (SSEO) forecast data and observed Storm Prediction Center (SPC) storm reports. RF forecast probabilities are compared against severe weather forecasts from calibrated SSEO 2–5-km updraft helicity (UH) forecasts and SPC convective outlooks issued at 0600 UTC. Continuous RF probabilities routinely have the highest Brier skill scores (BSSs), regardless of whether the forecasts are evaluated over the full domain or regional/seasonal subsets. Even when RF probabilities are truncated at the probability levels issued by the SPC, the RF forecasts often have BSSs better than or comparable to corresponding UH and SPC forecasts. Relative to the UH and SPC forecasts, the RF approach performs best for severe wind and hail prediction during the spring and summer (i.e., March–August). Overall, it is concluded that the RF method presented here provides skillful, reliable CAE-derived severe weather probabilities that may be useful to severe weather forecasters and decision-makers.

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.

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.

International competency requirements for public weather forecasters /

2021 ◽  
Vol 3 ◽  
pp. 161-171
Author(s):  
E.V. Vasil’ev ◽  
Keyword(s):  
Satellite Data ◽  
Weather Forecasting ◽  
World Meteorological Organization ◽  
Competency Assessment ◽  
Further Training ◽  
Knowledge And Skills ◽  
Weather Forecasts ◽  
Weather Forecasters ◽  
The World

Competency requirements for public weather forecasters, as well as knowledge and skills necessary for their implementation, that were developed and recommended for practical use by the World Meteorological Organization, are presented. Basic skills of working with radar and satellite data are described. The importance of the weather forecaster competency compliance with the presented requirements is emphasized, as well as a need for proper competency assessment and, if necessary, further training in order to improve the quality of weather forecasts and storm warnings. Keywords: competency, weather forecasters, weather forecasting, knowledge and skills, competency assessment, training

Weather forecasting and communication in the upper Great Ruaha catchment area.

2020 ◽  
pp. 217-234
Author(s):  
Anselm R. Mwajombe ◽  
Godwin A. Lema
Keyword(s):  
Decision Making ◽  
Water Resources ◽  
Weather Forecasting ◽  
Local Environment ◽  
Weather Forecast ◽  
Communication Technologies ◽  
End Users ◽  
Oral Traditions ◽  
Weather Forecasts ◽  
Effective Dissemination

Abstract Effective weather forecast dissemination depends on how effective dissemination channels are in informing decision making for improved management of water resources and livelihood activities, which depend on water resources in catchment areas. In this chapter, the effectiveness of the channels for weather forecast dissemination is assessed in terms of magnitude of awareness creation and versatility to end users. Our findings show that both traditional and conventional channels of weather forecasting and communication can be used to create awareness to end users in various parts of the country. For local communities, traditional weather forecasting and communicating were contingent on indigenous knowledge acquired through interaction with the local environment. Such information was accessed through indicators or signs that entail plant phenology, astronomical and meteorological events as well as mammals' behaviour. Conventional forecasting is communicated via modern communication technologies including radio, television, the Internet and posted letters. Communication of traditional weather forecasting is mainly through oral traditions. Results from our respondents revealed that 40% received weather forecasts through traditional channels, 11% through modern channels and 49% through modern and traditional channels. The majority of respondents said that weather forecasts from modern sources were not reliable to inform the decision-making process when compared with traditional sources. The study recommends synchronizing modern and traditional channels for effective weather forecast delivery.

Weather Forecasts

2020 ◽  
pp. 55-74
Author(s):  
Chris Bleakley
Keyword(s):  
Particle Physics ◽  
Weather Forecasting ◽  
Weather Forecast ◽  
Simulation Method ◽  
Monte Carlo Simulation Method ◽  
Von Neumann ◽  
Weather Forecasts ◽  
Numerical Weather Forecasting ◽  
Stanislaw Ulam ◽  
Lewis Fry Richardson

Chapter 4 tells the story of numerical weather forecasting from its inception to today’s supercomputing algorithms. In 1922, Lewis Fry Richardson proposed that, since the atmosphere is subject to the laws of physics, future weather can be predicted by means of algorithmic calculations. His attempt at forecasting a single day’s weather by means of manual calculations took several months. In the late 1940s, John von Neumann resurrected Richardson’s idea and launched a project to conduct the first weather forecast by computer. The world’s first operational electronic computer – ENIAC - completed a 24-hour forecast in just one day. It appeared that accurate forecasting simply required faster computers. In 1969, Edward Lorenz discovered that tiny errors in weather measurements can accumulate during numerical forecasting to produce large errors. The so-called Butterfly Effect was alleviated by the Monte Carlo simulation method invented by Stanislaw Ulam for particle physics.

scholarly journals Site-specific analog weather-forecast system for northwest Himalaya, India

2008 ◽  
Vol 49 ◽  
pp. 224-230 ◽  
Author(s):  
Dan Singh ◽  
Amreek Singh ◽  
Ashwagosha Ganju
Keyword(s):  
Weather Forecasting ◽  
Forecast Accuracy ◽  
Weather Forecast ◽  
Analog Model ◽  
Site Specific ◽  
Northwest Himalaya ◽  
Weather Forecasts ◽  
The Past ◽  
Weather Events ◽  
Weather Situation

AbstractIn an analog weather-forecasting procedure, recorded weather in the past analogs corresponding to the current weather situation is used to predict future weather. Consistent with the procedure, a theoretical framework is developed to predict weather at a specific site in the Pir Panjal range of the northwest Himalaya, India, using surface weather observations of the past ten winters (1991/92 to 2001/02) 3 days in advance. Weather predictions were made as snow day with quantitative snowfall category or no-snow day, for day1 through day3. As currently deployed, the procedure routinely provides a 3 day point weather forecast as guidance information to a weather and avalanche forecaster. Forecasts by analog model are evaluated by the various accuracy measures achieved for an independent dataset of three winters (2002/03 to 2004/05). The results indicate that weather forecasts by analog model are quite reliable, in that forecast accuracy corresponds closely to the relative frequencies of observed weather events. Moreover, qualitative weather (snow day or no-snow day) and quantitative categorical snowfall forecasts (quantitative snowfall category for snow day) are better than reference forecasts based on persistence and climatology for day1 predictions. Site-specific snowfall forecast guidance may play a major role in assessing avalanche danger, and accordingly formulating an avalanche forecast for a given area in advance.

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