Weather Forecasting in Brazil: A Concise Historical Review

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.

Discounting Under Severe Weather Threat

The human and economic costs of severe weather damage can be mitigated by appropriate preparation. Despite the benefits, researchers have only begun to examine if known decision-making frameworks apply to severe-weather-related decisions. Using experiments, we found that a hyperbolic discounting function accurately described participant decisions to prepare for, and respond to, severe weather, although only delays of 1 month or longer significantly changed decisions to evacuate, suggesting that severe weather that is not imminent does not affect evacuation decisions. In contrast, the probability that a storm would impact the participant influenced evacuation and resource allocation decisions. To influence people’s evacuation decisions, weather forecasters and community planers should focus on disseminating probabilistic information when focusing on short-term weather threats (e.g., hurricanes); delay information appears to affect people’s evacuation decision only for longer-term threats, which may hold promise for climate-change warnings.

Physical and synoptic predictors and their optimal values leading to the formation of heavy rainfall

The physical and synoptic predictors are presented, which allow refining the automated forecasts of heavy precipitation implemented in the Hydrometeorological Center of Russia on the recommendation of the Roshydromet Central Methodological Forecasting Commission, as well as hydrodynamic forecasts of precipitation and forecasts of weather forecasters. The physical substantiation of the considered predictors is given. Their optimal values for the formation of heavy precipitation are determined. The parameters of convection and the intensity of the convective phenomenon diagnosed on the basis of radar data further expand the possibilities of refining forecasts of heavy and very heavy precipitation and, if necessary, allow issuing a storm warning with a sufficient lead time or refining a storm warning. Keywords: heavy precipitation, physical and synoptic predictors, diagnosed convection parameters, DMRL-C data

International competency requirements for public weather forecasters /

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

International competency requirements for public weather forecasters

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

Anticipatory Culture in the Bering Sea: Weather, Climate and Temporal Dissonance

A major implication of climate change is the declining capacity for communities to anticipate future conditions and scenarios. In the Bering Sea region of Western Alaska, this situation is acute and holds manifold consequences, particularly for the region’s primarily Indigenous residents. Based upon interviews and fieldwork in two Bering Sea communities and among regional weather forecasters, this paper explores the intertwined temporalities of weather, climate, and social life. I demonstrate that anticipatory culture, which otherwise structures anticipatory practices regarding climate, local weather, and social life, is beset by temporal dissonance across three timescales. First, dramatic climatic and ecosystem shifts reshape how Indigenous Peoples envision themselves as culturally inhabiting a long-range history and future. Second, changes in weather patterns, ecological cycles, and sea ice dynamics upset evaluations of seasonality, leading to a pervasive sense of unpredictability. Third, on the everyday timescale, social and technological change complicates mariners’ evaluations of risk and economic (commercial and subsistence) decision-making. I conclude by connecting these three socio-environmental temporalities to the temporal frames that primarily characterize weather and climate services, with an emphasis on the US National Weather Service. The paper discusses how such services may further orient toward engaging socially embedded practices of anticipation in addition to formal prediction. Such an orientation can help to shape an anticipatory culture that more closely aligns meteorological and social patterns.

Tailoring weather information for specific users

<p>In June 2018 at Slovenian Environmental Agency (ARSO) the internal project SPOMIN was started. In Slovenia, weather forecasters have only one operational shift per day, which lasts 12 hours, and only one weather forecaster is mostly responsible for general forecasts for the entire country. Dedicated forecasts for special users are fragmented and delegated to teams across the Agency; in most cases there is only one person responsible for each specific topic, and some forecasts for specific activities are not even produced, for example for leisure activities, skiing, surfing, etc. Therefore, the aim of SPOMIN project was to harmonize operational meteorological information and forecasts and collect their production in one team.</p><p>For the SPOMIN proposes, we issued a questionnaire addressed to our users and received more than 1000 answers, many of them were descriptive. Many of our users are familiar with our special products for users, but they are missing additional graphic representation or explanatory text or more details related to their activity. There are also some of users who are unaware of our products as they are not easy to find on our websites. Our users know what kind of information and forecasts they are missing, and they provided us with a lot of ideas how to improve our products and which new products should we develop in future. Thus, the project team suggested some new products and upgrade of existing ones. While the project was finished in 2020, the conclusions and results were conveyed to the newly formed team for specific forecasts.</p><p>At present, we are not able to enrich the content of our web site with new kinds of information, because the web site is currently under renovation. To overcome this situation, we have started adding more information to the social network where we have over 20,000 followers, recording podcasts with highly relevant topics, producing lots of interesting infographics, and so on. Our plans for the future include production of videos with forecasts and meteorological educational content. Of course, we will upgrade and implement the ideas developed in SPOMIN project and integrate them on our new website which will be much more user oriented as it is the current one.</p><p>Selected examples of tailored information for users published on our social media will be presented.</p><p> </p>

Drag-Based Ensemble Model (DBEM) to predict the heliospheric propagation of CMEs

<p><span>The Drag-based Model (DBM) is an analytical model for heliospheric propagation of Coronal Mass Ejections (CMEs) that predicts the CME arrival time and speed at Earth or any other given target in the solar system. It is based on the equation of motion and depends on initial CME parameters, background solar wind speed, w and the drag parameter γ. A very short computational time of DBM (< 0.01s) allowed us to develop the Drag-Based Ensemble Model (DBEM) that considers the variability of model input parameters by making an ensemble of n different input parameters to calculate the distribution and significance of the DBM results. Using such an approach, we apply DBEM to determine the most likely CME arrival times and speeds, quantify the prediction uncertainties and calculate the confidence intervals. Recently, a new DBEMv3 version was developed including the various improvements and Graduated Cylindrical Shell (GCS) option for the CME geometry input as well as the CME propagation visualizations. Thus, we compare the DBEMv3 with previous DBEM versions (e.g. DBEMv2), evaluate it and determine the DBEMv3 performance and errors by using various CME-ICME lists. Compared to the previous versions, the DBEMv3 provides very similar results for all calculated output parameters with slight improvement in the performance. Based on the evaluation performed for 146 CME-ICME pairs, the DBEMv3 performance with mean error (ME) of -11.3 h, mean absolute error (MAE) of 17.3 h was obtained, similar to previous DBM and DBEM evaluations. Fully operational DBEMv3 web application was integrated as one of the ESA Space Situational Awareness portal services (https://swe.ssa.esa.int/current-space-weather) providing an important tool for space weather forecasters.</span></p>

Signatures of Oceanic Wind Events in Geostationary Cloud Top Temperature and Lightning Data

Thirteen ocean-based wind events from 2018, detected by buoys and Coastal-Marine Automated Network (C-MAN) stations, were analyzed using 1 min mesoscale sector Advanced Baseline Imager (ABI) cloud top brightness temperature (CTTB) data, as well as 1 min Geostationary Lightning Mapper (GLM) lightning data. The ABI and GLM instruments are located on the Geostationary Operational Environmental Satellite (GOES)-16 satellite. An oceanic wind event was defined as a buoy or C-MAN station-recorded peak wind gust of at least 14 m s−1, associated with a convective storm. The wind gust was required to exceed the wind speed by at least 4 m s−1 at the time of the event, but not exceed the corresponding wind speed by at least 4 m s−1 for more than 30 min. This study hypothesized that prior to a wind event, there should be unique signatures in ABI CTTB and GLM lightning datasets. The presumption was that the minimum CTTB and maximum flash rate should occur near the same time and prior to the event. The minimum CTTB occurred an average of 10.5 min and a median of 7 min prior to events, with a range from 29 min prior to 1 min after the event. Changes in CTTB were often subtle. A maximum flash rate occurred within 5 min of the minimum CTTB for 11 of the 12 events with lightning, and did not exceed 11 fl min−1 for nine of the 12 events with lightning. Operational weather forecasters might use CTTB and lightning trends to help identify storms capable of producing significant oceanic wind events.