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Abstract
The accurate interpretation of hurricane risk graphics is expected to benefit public decision-making. To investigate public interpretation and suggest improvements to graphical designs, an interdisciplinary, mixed-methods approach is being undertaken. Drawing on a series of focus groups with Miami residents that focused on understanding interpretations of the National Hurricane Center’s track forecast cone or “Cone of Uncertainty”, we developed an online survey targeting a much larger sample of Florida residents (n=2,847). The findings from this survey are the primary focus of this short article. We attempt to answer three questions: 1) What are the most frequent and trusted sources of information that Florida residents use when they learn that a hurricane is coming their way? 2) How accurately are Florida residents able to interpret risk based on the NHC Cone of Uncertainty graphic? 3) What is the relationship, if any, between the number of correct interpretations and income, age, education, housing location, housing type, or “most trusted” sources of information? Unlike previous public surveys that focused more on evacuation decisions, forecast usage, and perception of hurricane risk, our approach specifically pays attention to the details of design elements of the forecast graphics with the long-term goal of minimizing misinterpretation of future graphics. Our analysis suggests that many residents have difficulty interpreting several aspects, suggesting a rethink on how to graphically communicate aspects such as uncertainty; the size of the storm; areas of likely damage; watches and warnings; and wind intensity categories. Graphical communication strategies need to be revised to better support the different ways in which people understand forecast products, and these strategies should be tested for validity in real world settings.
Abstract
The accurate interpretation of hurricane risk graphics is expected to benefit public decision-making. To investigate public interpretation and suggest improvements to graphical designs, an interdisciplinary, mixed-methods approach is being undertaken. Drawing on a series of focus groups with Miami residents that focused on understanding interpretations of the National Hurricane Center’s track forecast cone or “Cone of Uncertainty”, we developed an online survey targeting a much larger sample of Florida residents (n=2,847). The findings from this survey are the primary focus of this short article. We attempt to answer three questions: 1) What are the most frequent and trusted sources of information that Florida residents use when they learn that a hurricane is coming their way? 2) How accurately are Florida residents able to interpret risk based on the NHC Cone of Uncertainty graphic? 3) What is the relationship, if any, between the number of correct interpretations and income, age, education, housing location, housing type, or “most trusted” sources of information? Unlike previous public surveys that focused more on evacuation decisions, forecast usage, and perception of hurricane risk, our approach specifically pays attention to the details of design elements of the forecast graphics with the long-term goal of minimizing misinterpretation of future graphics. Our analysis suggests that many residents have difficulty interpreting several aspects, suggesting a rethink on how to graphically communicate aspects such as uncertainty; the size of the storm; areas of likely damage; watches and warnings; and wind intensity categories. Graphical communication strategies need to be revised to better support the different ways in which people understand forecast products, and these strategies should be tested for validity in real world settings.
Abstract
Advances in science literacy documented in an undergraduate course on Climate and Climate Change at the University of Wisconsin-Madison (UW) in 2020 begged the question: does the new climate knowledge translate into behavior change? Traditionally a “knowledge-action gap” has undermined educators’ efforts to galvanize actions towards mitigating climate change. Through a survey focused on carbon footprint and civic engagement and testimonials gleaned from students’ capstone elevator speeches, this study presents an encouraging update on young adults’ response to the climate crisis. By comparing responses to a similar survey distributed to UW students in another undergraduate course in 2021, we show that the course focused on Climate and Climate Change motivated behavior modifications that lighten carbon footprint to a greater degree than a traditional introductory meteorology course.
Abstract
Advances in science literacy documented in an undergraduate course on Climate and Climate Change at the University of Wisconsin-Madison (UW) in 2020 begged the question: does the new climate knowledge translate into behavior change? Traditionally a “knowledge-action gap” has undermined educators’ efforts to galvanize actions towards mitigating climate change. Through a survey focused on carbon footprint and civic engagement and testimonials gleaned from students’ capstone elevator speeches, this study presents an encouraging update on young adults’ response to the climate crisis. By comparing responses to a similar survey distributed to UW students in another undergraduate course in 2021, we show that the course focused on Climate and Climate Change motivated behavior modifications that lighten carbon footprint to a greater degree than a traditional introductory meteorology course.
Abstract
Hurricane Ida recently became one of the strongest hurricanes to hit Louisiana on record, with an estimated landfalling maximum sustained wind of 130 kt. Although Hurricane Ida made landfall at a similar time of year and landfall location as Hurricane Katrina (2005), Ida’s postlandfall decay rate was much weaker than Hurricane Katrina. This manuscript includes a comparative analysis of pre- and post-landfall synoptic conditions for Hurricane Ida and other historical major landfalling hurricanes (Category 3+ on the Saffir-Simpson Hurricane Wind Scale) along the Gulf Coast since 1983, with a particular focus on Hurricane Katrina.
Abundant precipitation in southeastern Louisiana prior to Ida’s landfall increased soil moisture. This increased soil moisture along with extremely weak overland steering flow likely slowed the storm’s weakening rate post-landfall. Offshore environmental factors also played an important role, particularly anomalously high nearshore sea surface temperatures and weak vertical wind shear that fueled the rapid intensification of Ida just before landfall. Strong nearshore vertical wind shear weakened Hurricane Katrina before landfall, and moderate northward steering flow caused Katrina to move inland relatively quickly, aiding in its relatively fast weakening rate following landfall.
The results of this study improve our understanding of critical factors influencing the evolution of the nearshore intensity of major landfalling hurricanes in the Gulf of Mexico. This study can help facilitate forecasting and preparation for inland hazards resulting from landfalling hurricanes with nearshore intensification and weak post-landfall decay.
Abstract
Hurricane Ida recently became one of the strongest hurricanes to hit Louisiana on record, with an estimated landfalling maximum sustained wind of 130 kt. Although Hurricane Ida made landfall at a similar time of year and landfall location as Hurricane Katrina (2005), Ida’s postlandfall decay rate was much weaker than Hurricane Katrina. This manuscript includes a comparative analysis of pre- and post-landfall synoptic conditions for Hurricane Ida and other historical major landfalling hurricanes (Category 3+ on the Saffir-Simpson Hurricane Wind Scale) along the Gulf Coast since 1983, with a particular focus on Hurricane Katrina.
Abundant precipitation in southeastern Louisiana prior to Ida’s landfall increased soil moisture. This increased soil moisture along with extremely weak overland steering flow likely slowed the storm’s weakening rate post-landfall. Offshore environmental factors also played an important role, particularly anomalously high nearshore sea surface temperatures and weak vertical wind shear that fueled the rapid intensification of Ida just before landfall. Strong nearshore vertical wind shear weakened Hurricane Katrina before landfall, and moderate northward steering flow caused Katrina to move inland relatively quickly, aiding in its relatively fast weakening rate following landfall.
The results of this study improve our understanding of critical factors influencing the evolution of the nearshore intensity of major landfalling hurricanes in the Gulf of Mexico. This study can help facilitate forecasting and preparation for inland hazards resulting from landfalling hurricanes with nearshore intensification and weak post-landfall decay.
Abstract
The Arctic environment is changing, increasing the vulnerability of local communities and ecosystems, and impacting its socio-economic landscape. In this context, weather and climate prediction systems can be powerful tools to support strategic planning and decision-making at different time horizons. This article presents several success stories from the H2020 project APPLICATE on how to advance Arctic weather and seasonal climate prediction, synthesizing the key lessons learned throughout the project and providing recommendations for future model and forecast system development.
Abstract
The Arctic environment is changing, increasing the vulnerability of local communities and ecosystems, and impacting its socio-economic landscape. In this context, weather and climate prediction systems can be powerful tools to support strategic planning and decision-making at different time horizons. This article presents several success stories from the H2020 project APPLICATE on how to advance Arctic weather and seasonal climate prediction, synthesizing the key lessons learned throughout the project and providing recommendations for future model and forecast system development.
Abstract
Making decisions about the appropriate action to take when presented with uncertain information is difficult, particularly in an emergency response situation. Decision makers can be influenced by factors such as how information is framed, their risk sensitivity and the impact of false alarms. Uncertainty arising from limited knowledge of the current state or future outcome of an event is unavoidable when making decisions. However, there is no universally agreed method on the design and presentation of uncertainty information. The aim of this article is to demonstrate that decision theory can be applied to an ensemble of plausible realisations of a situation to build a transparent framework which can then be used to determine the optimal action by assigning losses to different decision outcomes. The optimal action is then visualized, enabling the uncertainty information to be presented in a condensed manner suitable for decision makers. The losses are adaptable depending on the hazard and the individual operational model of the decision maker. To illustrate this approach, decision theory will be applied to an ensemble of volcanic ash simulations used for the purpose of airline flight planning, focussing on the 2019 eruption of Russian volcano Raikoke. Three idealised scenarios are constructed to show the impact of different loss models on the optimal action. In all cases, applying decision theory can significantly alter the regions, and therefore potential flight tracks, identified as potentially hazardous. Thus we show that different end users would and should make different decisions when presented with the same probabilistic information based on their individual user requirements.
Abstract
Making decisions about the appropriate action to take when presented with uncertain information is difficult, particularly in an emergency response situation. Decision makers can be influenced by factors such as how information is framed, their risk sensitivity and the impact of false alarms. Uncertainty arising from limited knowledge of the current state or future outcome of an event is unavoidable when making decisions. However, there is no universally agreed method on the design and presentation of uncertainty information. The aim of this article is to demonstrate that decision theory can be applied to an ensemble of plausible realisations of a situation to build a transparent framework which can then be used to determine the optimal action by assigning losses to different decision outcomes. The optimal action is then visualized, enabling the uncertainty information to be presented in a condensed manner suitable for decision makers. The losses are adaptable depending on the hazard and the individual operational model of the decision maker. To illustrate this approach, decision theory will be applied to an ensemble of volcanic ash simulations used for the purpose of airline flight planning, focussing on the 2019 eruption of Russian volcano Raikoke. Three idealised scenarios are constructed to show the impact of different loss models on the optimal action. In all cases, applying decision theory can significantly alter the regions, and therefore potential flight tracks, identified as potentially hazardous. Thus we show that different end users would and should make different decisions when presented with the same probabilistic information based on their individual user requirements.
Abstract
A series of webinars and panel discussions were conducted on the topic of the evolving role of humans in weather prediction and communication, in recognition of the 100th anniversary of the founding of the AMS. One main theme that arose was the inevitability that new tools using artificial intelligence will improve data analysis, forecasting, and communication. We discussed what tools are being created, how they are being created, and how the tools will potentially affect various duties for operational meteorologists in multiple sectors of the profession. Even as artificial intelligence increases automation, humans will remain a vital part of the forecast process as that process changes over time. Additionally, both university training and professional development must be revised to accommodate the evolving forecasting process, including addressing the need for computing and data skills (including artificial intelligence and visualization), probabilistic and ensemble forecasting, decision support, and communication skills. These changing skill sets necessitate that both the U.S. Government’s Meteorologist General Schedule 1340 requirements and the AMS standards for a bachelor’s degree need to be revised. Seven recommendations are presented for student and forecaster preparation and career planning, highlighting the need for students and operational meteorologists to be flexible lifelong learners, acquire new skills, and be engaged in the changes to forecast technology in order to best serve the user community throughout their careers. The article closes with our vision for the ways that humans can maintain an essential role in weather prediction and communication, highlighting the interdependent relationship between computers and humans.
Abstract
A series of webinars and panel discussions were conducted on the topic of the evolving role of humans in weather prediction and communication, in recognition of the 100th anniversary of the founding of the AMS. One main theme that arose was the inevitability that new tools using artificial intelligence will improve data analysis, forecasting, and communication. We discussed what tools are being created, how they are being created, and how the tools will potentially affect various duties for operational meteorologists in multiple sectors of the profession. Even as artificial intelligence increases automation, humans will remain a vital part of the forecast process as that process changes over time. Additionally, both university training and professional development must be revised to accommodate the evolving forecasting process, including addressing the need for computing and data skills (including artificial intelligence and visualization), probabilistic and ensemble forecasting, decision support, and communication skills. These changing skill sets necessitate that both the U.S. Government’s Meteorologist General Schedule 1340 requirements and the AMS standards for a bachelor’s degree need to be revised. Seven recommendations are presented for student and forecaster preparation and career planning, highlighting the need for students and operational meteorologists to be flexible lifelong learners, acquire new skills, and be engaged in the changes to forecast technology in order to best serve the user community throughout their careers. The article closes with our vision for the ways that humans can maintain an essential role in weather prediction and communication, highlighting the interdependent relationship between computers and humans.
Abstract
The High-Latitude Measurement of Snowfall (HiLaMS) campaign explored variability in snowfall properties and processes at meteorologically distinct field sites located in Haukeliseter, Norway, and Kiruna, Sweden, during the winters of 2016/17 and 2017/18, respectively. Campaign activities were founded upon the sensitivities of a low-cost, core instrumentation suite consisting of Micro Rain Radar, Precipitation Imaging Package, and Multi-Angle Snow Camera. These instruments are highly portable to remote field sites and, considered together, provide a unique and complementary set of snowfall observations including snowflake habit, particle size distributions, fall speeds, surface snowfall accumulations, and vertical profiles of radar moments and snow water content. These snow-specific parameters, used in combination with existing observations from the field sites such as snow gauge accumulations and ambient weather conditions, allow for advanced studies of snowfall processes. HiLaMS observations were used to 1) successfully develop a combined radar and in situ microphysical property retrieval scheme to estimate both surface snowfall accumulation and the vertical profile of snow water content, 2) identify the predominant snowfall regimes at Haukeliseter and Kiruna and characterize associated macrophysical and microphysical properties, snowfall production, and meteorological conditions, and 3) identify biases in the HARMONIE-AROME numerical weather prediction model for forecasts of snowfall accumulations and vertical profiles of snow water content for the distinct snowfall regimes observed at the mountainous Haukeliseter site. HiLaMS activities and results suggest value in the deployment of this enhanced snow observing instrumentation suite to new and diverse high-latitude locations that may be underrepresented in climate and weather process studies.
Abstract
The High-Latitude Measurement of Snowfall (HiLaMS) campaign explored variability in snowfall properties and processes at meteorologically distinct field sites located in Haukeliseter, Norway, and Kiruna, Sweden, during the winters of 2016/17 and 2017/18, respectively. Campaign activities were founded upon the sensitivities of a low-cost, core instrumentation suite consisting of Micro Rain Radar, Precipitation Imaging Package, and Multi-Angle Snow Camera. These instruments are highly portable to remote field sites and, considered together, provide a unique and complementary set of snowfall observations including snowflake habit, particle size distributions, fall speeds, surface snowfall accumulations, and vertical profiles of radar moments and snow water content. These snow-specific parameters, used in combination with existing observations from the field sites such as snow gauge accumulations and ambient weather conditions, allow for advanced studies of snowfall processes. HiLaMS observations were used to 1) successfully develop a combined radar and in situ microphysical property retrieval scheme to estimate both surface snowfall accumulation and the vertical profile of snow water content, 2) identify the predominant snowfall regimes at Haukeliseter and Kiruna and characterize associated macrophysical and microphysical properties, snowfall production, and meteorological conditions, and 3) identify biases in the HARMONIE-AROME numerical weather prediction model for forecasts of snowfall accumulations and vertical profiles of snow water content for the distinct snowfall regimes observed at the mountainous Haukeliseter site. HiLaMS activities and results suggest value in the deployment of this enhanced snow observing instrumentation suite to new and diverse high-latitude locations that may be underrepresented in climate and weather process studies.
Abstract
We introduce the Dutch East India Company “day registers” as one of the world’s longest known pre-nineteenth-century corporate chronicles (1652–1791) containing near-continuous, systematic, noninstrumental daily weather information for Cape Town, South Africa. This transcript provides the longest-known continuous seventeenth- to eighteenth-century daily weather record for Africa and the Southern Hemisphere. An 18-yr (1773–91) climate chronology from this record is presented, thus providing unique insight to the late-eighteenth-century climate of Cape Town. Extraction of daily weather information for basic statistical analysis includes precipitation, wind, sky conditions, and accounts of storms, drought, and floods. From this, we provide monthly and annual number of rain days, a rain index (relative rainfall amount), hot and cold days, and occurrence of storm-strength winds. Results show extreme weather and climate variability in Cape Town during the mid- to late 1780s.
Abstract
We introduce the Dutch East India Company “day registers” as one of the world’s longest known pre-nineteenth-century corporate chronicles (1652–1791) containing near-continuous, systematic, noninstrumental daily weather information for Cape Town, South Africa. This transcript provides the longest-known continuous seventeenth- to eighteenth-century daily weather record for Africa and the Southern Hemisphere. An 18-yr (1773–91) climate chronology from this record is presented, thus providing unique insight to the late-eighteenth-century climate of Cape Town. Extraction of daily weather information for basic statistical analysis includes precipitation, wind, sky conditions, and accounts of storms, drought, and floods. From this, we provide monthly and annual number of rain days, a rain index (relative rainfall amount), hot and cold days, and occurrence of storm-strength winds. Results show extreme weather and climate variability in Cape Town during the mid- to late 1780s.
Abstract
Probabilistic thinking underpins a wide range of scientific claims, but effectively communicating probabilistic information across audiences is challenging. In this article, we present a political–institutional approach to science that harnesses the social relationships between the people working as scientists and the public using scientific innovations. First, we show how we learned to use games and local analogies to effectively communicate probabilistic seasonal forecasts of weather and crop yields with farmers, extension workers, and water managers in Ethiopia. Second, we show how workshops—the unglamorous institutional workhorse of international development and scientific enterprises—became warmhearted events when organized around the fundamental fact of social connections between researchers and the community members and between the community members themselves. Scientists in an international scientific collaboration may not be able to become longstanding members of every community, but our approach to workshopping—and to research networks—allowed us to be engidoch (in English, guests), to tap into rich social ties to harness the humor, goodwill, and commitment that is hard to muster when scientists engage with community members as unconnected, nameless “workshop participants.”
Abstract
Probabilistic thinking underpins a wide range of scientific claims, but effectively communicating probabilistic information across audiences is challenging. In this article, we present a political–institutional approach to science that harnesses the social relationships between the people working as scientists and the public using scientific innovations. First, we show how we learned to use games and local analogies to effectively communicate probabilistic seasonal forecasts of weather and crop yields with farmers, extension workers, and water managers in Ethiopia. Second, we show how workshops—the unglamorous institutional workhorse of international development and scientific enterprises—became warmhearted events when organized around the fundamental fact of social connections between researchers and the community members and between the community members themselves. Scientists in an international scientific collaboration may not be able to become longstanding members of every community, but our approach to workshopping—and to research networks—allowed us to be engidoch (in English, guests), to tap into rich social ties to harness the humor, goodwill, and commitment that is hard to muster when scientists engage with community members as unconnected, nameless “workshop participants.”
Abstract
Conference Title: 2nd QuIESCENT (Quantifying the Indirect Effect: from Sources to Climate Effects of Natural and Transported aerosol in the Arctic) Workshop
What: Atmospheric scientists, shared and discussed recent work to understand the complex interactions between aerosols, clouds, precipitation, radiation and dynamics at northern high latitudes, as well as recent and upcoming field campaigns to improve that understanding.
When: 30 March – 1 April, 2022
Where: Tromsø, Norway
Abstract
Conference Title: 2nd QuIESCENT (Quantifying the Indirect Effect: from Sources to Climate Effects of Natural and Transported aerosol in the Arctic) Workshop
What: Atmospheric scientists, shared and discussed recent work to understand the complex interactions between aerosols, clouds, precipitation, radiation and dynamics at northern high latitudes, as well as recent and upcoming field campaigns to improve that understanding.
When: 30 March – 1 April, 2022
Where: Tromsø, Norway
