Atmospheric Sciences Research Articles

An Iterative Approach toward Development of Ensemble Visualization Techniques for High-Impact Winter Weather Hazards: Part II: Product Evaluation

Abstract We developed five prototype convection-allowing model ensemble visualization products with the goal of improving depictions of the timing of winter weather hazards. These products are interactive, web-based plots visualizing probabilistic onset times and durations of intense snowfall rates, probabilities of heavy snow at rush hour, periods of heightened impacts, and mesoscale snowband probabilities. Prototypes were evaluated in three experimental groups coordinated by the Weather Prediction Center (WPC) Hydrometeorological Testbed (HMT), with a total of 53 National Weather Service (NWS) forecasters. Forecasters were asked to complete a simple forecast exercise for a snowfall event, with a control group using the Storm Prediction Center’s (SPC) High-Resolution Ensemble Forecast (HREF) system viewer, and an experimental group using both the HREF viewer and the five experimental graphics. Forecast accuracy was similar between the groups, but the experimental group exhibited smaller mean absolute error for snowfall duration forecasts. A series of Likert-scale questions saw participants respond favorably to all of the products and indicated that they would use them in operational forecasts and in communicating information to core partners. Forecasters also felt that the new products improved their comprehension of ensemble spread and reduced the time required to complete the forecasting exercise. Follow-up plenary discussions reiterated that there is a high demand for ensemble products of this type, though a number of potential improvements, such as greater customizability, were suggested. Ultimately, we demonstrated that social science methods can be effectively employed in the atmospheric sciences to yield improved visualization products.

A hydrogenated amorphous silicon detector for Space Weather applications

The characteristics of a hydrogenated amorphous silicon (a-Si:H) detector are presented here for monitoring in space solar flares and the evolution of strong to extreme energetic proton events. The importance and the feasibility to extend the proton measurements up to hundreds of MeV is evaluated. The a-Si:H presents an excellent radiation hardness and finds application in harsh radiation environments for medical purposes, for particle beam characterization and, as we propose here, for space weather science applications. The critical flux detection limits for X rays, electrons and protons are discussed.

Differences Evaluation among Three Global Remote Sensing SDL Products

At present, a variety of global remote sensing surface downwelling longwave radiation (SDL) products are used for atmospheric science research; however, there are few studies on the quantitative evaluation of differences among different SDL products. In order to evaluate the differences among different SDL products quantitatively, we have selected three commonly used SDL products—Clouds and the Earth’s Radiant Energy System-Synoptic Radiative Fluxes and Clouds (CERES-SYN), the European Centre for Medium Range Weather Forecasts-Surface Radiation Budget (ECMWF-SRB) and the Global Energy and Water Exchanges Project-Surface Radiation Budget (GEWEX-SRB)—to comprehensively study in this paper. The results show that there are significant differences among the three SDL products in some areas, such as in the Arctic, the Antarctic, the Sahara, the Tibet Plateau, and Greenland. The maximum absolute root mean square error (RMSEab) in these areas is greater than 20 Wm−2, the maximum relative root mean square error (RMSEre) is greater than 20%, the maximum and minimum absolute mean bias error (MBEab) are about 20 Wm−2 and −20 Wm−2, respectively, and the maximum and minimum relative mean bias error (MBEre) are about 10% and −10%, respectively. Among the three SDL products, the difference between the ECMWF-SRB and GEWEX-SRB is the most significant. In addition, this paper also analyzed the differences among different SDL products based on three aspects. Firstly, the differences among the three SDL products show that there is significant seasonality, and the differences among different months may vary greatly. However, the differences are not sensitive to years. Secondly, there are some differences in cloud-forcing radiative fluxes (CFRFs) of different SDL products, which is also an important factor affecting the difference between different SDL products. Finally, in the process of converting high temporal resolution SDL products into monthly SDL products, data processing also affects the difference between different SDL products.

Design and Development of an Ultraviolet All-Sky Imaging System.

All-sky cameras capture a panoramic view of the full sky from horizon to horizon to generate a wide-angle image of the observable sky. State-of-the-art all-sky imagers are limited to imaging in the visible and infrared spectrum and cannot image in the UV spectrum. This article describes the development of an all-sky imaging system capable of capturing 130° wide-angle sky images from horizon to horizon in the UV-AB spectrum. The design of the UV all-sky imaging system is based on low-cost, accessible, and scalable components to develop multiple images that can be deployed over a wider geographical area. The spectral response of the camera system has been validated in the UV spectrum (280-420 nm) using a monochromatic UV beam with an average power output of 22 nW. UV all-sky imaging systems complement existing infrared and visible all-sky cameras. They have wide applications in astronomy, meteorology, atmospheric science, vulcanology, meteors and auroral monitoring, and the defence sector.

Visual analysis of model parameter sensitivities along warm conveyor belt trajectories using Met.3D (1.6.0-multivar1)

Abstract. Numerical weather prediction models rely on parameterizations for subgrid-scale processes, e.g., for cloud microphysics, which are a well-known source of uncertainty in weather forecasts. Via algorithmic differentiation, which computes the sensitivities of prognostic variables to changes in model parameters, these uncertainties can be quantified. In this article, we present visual analytics solutions to analyze interactively the sensitivities of a selected prognostic variable to multiple model parameters along strongly ascending trajectories, so-called warm conveyor belt (WCB) trajectories. We propose a visual interface that enables us to (a) compare the values of multiple sensitivities at a single time step on multiple trajectories, (b) assess the spatiotemporal relationships between sensitivities and the trajectories' shapes and locations, and (c) find similarities in the temporal development of sensitivities along multiple trajectories. We demonstrate how our approach enables atmospheric scientists to interactively analyze the uncertainty in the microphysical parameterizations and along the trajectories with respect to the selected prognostic variable. We apply our approach to the analysis of WCB trajectories within extratropical Cyclone Vladiana, which occurred between 22–25 September 2016 over the North Atlantic. Peaks of sensitivities that occur at different times relative to a trajectory's fastest ascent reveal that trajectories with their fastest ascent in the north are more susceptible to rain sedimentation from above than trajectories that ascend further south. In contrast, large sensitivities to cloud condensation nuclei (CCN) activation and cloud droplet collision in the south indicate a local rain droplet formation. These large sensitivities reveal considerable uncertainty in the shape of clouds and subsequent rainfall. Sensitivities to cloud droplets' formation and subsequent conversion to rain droplets are also more pronounced along convective ascending trajectories than for slantwise ascents. The slantwise ascending trajectories are characterized by periods of slower ascent and even descent, during which the sensitivities to the formation of cloud droplets and rain droplets alternate. This alternating pattern leads to large-scale precipitation patterns, whereas convective ascending trajectories do not exhibit this pattern. Thus the primary source for uncertainty in large-scale precipitation patterns stems from slantwise ascents. The strong ascent of convective trajectories leads to large sensitivities of rain mass density to riming and freezing parameters at high altitudes, which are barely present in slantwise ascending trajectories. These sensitivities correspond to uncertainties concerning graupel and hail formation in convective ascents.

Review article: Scaling, dynamical regimes, and stratification. How long does weather last? How big is a cloud?

Abstract. Until the 1980s, scaling notions were restricted to self-similar homogeneous special cases. I review developments over the last decades, especially in multifractals and generalized scale invariance (GSI). The former is necessary for characterizing and modelling strongly intermittent scaling processes, while the GSI formalism extends scaling to strongly anisotropic (especially stratified) systems. Both of these generalizations are necessary for atmospheric applications. The theory and some of the now burgeoning empirical evidence in its favour are reviewed. Scaling can now be understood as a very general symmetry principle. It is needed to clarify and quantify the notion of dynamical regimes. In addition to the weather and climate, there is an intermediate “macroweather regime”, and at timescales beyond the climate regime (up to Milankovitch scales), there is a macroclimate and megaclimate regime. By objectively distinguishing weather from macroweather, it answers the question “how long does weather last?”. Dealing with anisotropic scaling systems – notably atmospheric stratification – requires new (non-Euclidean) definitions of the notion of scale itself. These are needed to answer the question “how big is a cloud?”. In anisotropic scaling systems, morphologies of structures change systematically with scale even though there is no characteristic size. GSI shows that it is unwarranted to infer dynamical processes or mechanisms from morphology. Two “sticking points” preventing more widespread acceptance of the scaling paradigm are also discussed. The first is an often implicit phenomenological “scalebounded” thinking that postulates a priori the existence of new mechanisms, processes every factor of 2 or so in scale. The second obstacle is the reluctance to abandon isotropic theories of turbulence and accept that the atmosphere's scaling is anisotropic. Indeed, there currently appears to be no empirical evidence that the turbulence in any atmospheric field is isotropic. Most atmospheric scientists rely on general circulation models, and these are scaling – they inherited the symmetry from the (scaling) primitive equations upon which they are built. Therefore, the real consequence of ignoring wide-range scaling is that it blinds us to alternative scaling approaches to macroweather and climate – especially to new models for long-range forecasts and to new scaling approaches to climate projections. Such stochastic alternatives are increasingly needed, notably to reduce uncertainties in climate projections to the year 2100.

Editorial for the Special Issue “Atmospheric Dispersion and Chemistry Models: Advances and Applications”

Atmospheric dispersion and chemical transport models (CTMs) are a key tool in both atmospheric chemistry and environmental sciences [...]

Assessing the spatial spread–skill of ensemble flood maps with remote-sensing observations

Abstract. An ensemble of forecast flood inundation maps has the potential to represent the uncertainty in the flood forecast and provide a location-specific likelihood of flooding. Ensemble flood map forecasts provide probabilistic information to flood forecasters, flood risk managers and insurers and will ultimately benefit people living in flood-prone areas. Spatial verification of the ensemble flood map forecast against remotely observed flooding is important to understand both the skill of the ensemble forecast and the uncertainty represented in the variation or spread of the individual ensemble-member flood maps. In atmospheric sciences, a scale-selective approach has been used to evaluate a convective precipitation ensemble forecast. This determines a skilful scale (agreement scale) of ensemble performance by locally computing a skill metric across a range of length scales. By extending this approach through a new application, we evaluate the spatial predictability and the spatial spread–skill of an ensemble flood forecast across a domain of interest. The spatial spread–skill method computes an agreement scale at every grid cell between each unique pair of ensemble flood maps (ensemble spatial spread) and between each ensemble flood map with a SAR-derived flood map (ensemble spatial skill; SAR: synthetic aperture radar). These two are compared to produce the final spatial spread–skill performance. These methods are applied to the August 2017 flood event on the Brahmaputra River in the Assam region of India. Both the spatial skill and spread–skill relationship vary with location and can be linked to the physical characteristics of the flooding event such as the location of heavy precipitation. During monitoring of flood inundation accuracy in operational forecasting systems, validation and mapping of the spatial spread–skill relationship would allow better quantification of forecast systematic biases and uncertainties. This would be particularly useful for ungauged catchments where forecast streamflows are uncalibrated and would enable targeted model improvements to be made across different parts of the forecast chain.

The influence of phenanthrene on the adsorption and conversion of SO2 on the hydroxylated {001} surface of α-quartz: A DFT study

One of the major challenges in environmental and atmospheric science is understanding the effects of mineral dust’s surface physiochemical properties and pre-adsorbed volatile organic compounds on the conversion of atmospheric pollutants. However, the process of adsorption and conversion of polluting gases on typical mineral dust surface is not fully understood. In this study, we systematically investigated the impact of surficial hydroxyl groups on the α-quartz {001} surface, oxidizers, and adsorbed phenanthrene (Phe) on the adsorption and oxidation process of SO2 by using density functional theory. Our findings indicate that the presence of hydroxyl groups on the α-quartz {001} surface increases SO2 adsorption whereas the presence of Phe decreases the SO2 capture capabilities. On pristine α-quartz {001} surfaces, SO2 tends to form dissociative SO42- groups and adsorb SO3. While surficial hydroxylation of α-quartz {001} facilitates the desorption of SO3, resulting in fewer dissociative SO42- groups and HSO3- salt. These results are consistent with our heterogeneous reaction of SO2 and α-quartz. In addition, O3 is more effective than O2 in the oxidation of SO2. Meanwhile, Phe inhibits the adsorption of HSO3- salt on hydroxylated α-quartz {001} surfaces. This study not only highlights the process surficial hydroxyl groups and adsorbed Phe regulate the evolution of adsorbed SO2 on α-quartz {001}, but also revealed the formation mechanism of the sulfur-containing aerosols.

Fast evaluation of spherical harmonics with sphericart.

Spherical harmonics provide a smooth, orthogonal, and symmetry-adapted basis to expand functions on a sphere, and they are used routinely in physical and theoretical chemistry as well as in different fields of science and technology, from geology and atmospheric sciences to signal processing and computer graphics. More recently, they have become a key component of rotationally equivariant models in geometric machine learning, including applications to atomic-scale modeling of molecules and materials. We present an elegant and efficient algorithm for the evaluation of the real-valued spherical harmonics. Our construction features many of the desirable properties of existing schemes and allows us to compute Cartesian derivatives in a numerically stable and computationally efficient manner. To facilitate usage, we implement this algorithm in sphericart, a fast C++ library that also provides C bindings, a Python API, and a PyTorch implementation that includes a GPU kernel.

The three-dimensional structure of fronts in mid-latitude weather systems in numerical weather prediction models

Abstract. Atmospheric fronts are a widely used conceptual model in meteorology, most encountered as two-dimensional (2-D) front lines on surface analysis charts. The three-dimensional (3-D) dynamical structure of fronts has been studied in the literature by means of “standard” 2-D maps and cross-sections and is commonly sketched in 3-D illustrations of idealized weather systems in atmospheric science textbooks. However, only recently has the feasibility of the objective detection and visual analysis of 3-D frontal structures and their dynamics within numerical weather prediction (NWP) data been proposed, and such approaches are not yet widely known in the atmospheric science community. In this article, we investigate the benefit of objective 3-D front detection for case studies of extra-tropical cyclones and for comparison of frontal structures between different NWP models. We build on a recent gradient-based detection approach, combined with modern 3-D interactive visual analysis techniques, and adapt it to handle data from state-of-the-art NWP models including those run at convection-permitting kilometre-scale resolution. The parameters of the detection method (including data smoothing and threshold parameters) are evaluated to yield physically meaningful structures. We illustrate the benefit of the method by presenting two case studies of frontal dynamics within mid-latitude cyclones. Examples include joint interactive visual analysis of 3-D fronts and warm conveyor belt (WCB) trajectories, as well as identification of the 3-D frontal structures characterizing the different stages of a Shapiro–Keyser cyclogenesis event. The 3-D frontal structures show agreement with 2-D fronts from surface analysis charts and augment the surface charts by providing additional pertinent information in the vertical dimension. A second application illustrates the relation between convection and 3-D cold-front structure by comparing data from simulations with parameterized and explicit convection. Finally, we consider “secondary fronts” that commonly appear in UK Met Office surface analysis charts. Examination of a case study shows that for this event the secondary front is not a temperature-dominated but a humidity-dominated feature. We argue that the presented approach has great potential to be beneficial for more complex studies of atmospheric dynamics and for operational weather forecasting.

Preface

Welcome to the Proceedings of the 8th International Scientific Conference of College of Science in Atmospheric Sciences (ISCCSAS-2023) May 3 – 4 2023, Mustansiriyah University, Baghdad, Iraq under the slogan “Sustainable lifestyle Development”. This is the second conference specializing in Atmospheric Sciences in Iraq. It aims to build scientific capabilities in atmospheric sciences, provide a scientific forum for researchers and specialists in the field of atmospheric sciences, and review the latest developments and research in this field. The Department of Atmospheric Sciences is the only unique department of this specialization among Iraqi universities. It has achieved many goals and contributed to the field of sustainable development and environmental systems; through the completion of the environmental park project, participation in afforestation campaigns, cultivation of green spaces, and the establishment of an educational weather observation station to monitor weather elements and an astronomical observatory followed by the Atmospheric Science Data Center (ASDC) powered by solar energy and provides data on many weather elements and aerosols for the city of Baghdad, and the introduction of higher diploma studies in climate change, and work is continuing to achieve many strategic plans and to cooperate with government institutions such as the Ministry of Water Resources / National Water Center, the Ministry of Environment, the Ministry of Transport and the Municipality of Baghdad. Today, the Department of Atmospheric Sciences concludes its achievements by holding its second specialized conference with the participation of many researchers from many Universities and research centers from inside and abroad in Iraq. All accepted papers will be published in the journal “IOP Conference Series: Earth and Environmental Science” which lies within the Scopus classification leading to improving the scientific reputation of the University. Because the conference included many participants, speakers, and researchers, from different countries of the world, some of the conference sessions were held online (virtual) using the google meet application and offline inside the halls of the Faculty of Science and the Department of Atmospheric Sciences. The conference shed light on some topics of atmospheric sciences to share views and experiences in the field of air pollution and weather events that occur all over the world due to climate change and to investigate the causes and how to adapt and mitigate them. The conference was also concerned with the use of geographic information systems (GIS) in atmospheric sciences for remote sensing, weather forecasts, and renewable energy. In conclusion, we are grateful for all the supporting, sponsoring, and supervising efforts of this conference, also we extend our gratitude to the preparatory, scientific, and electronic management committees and all the supporting committees that worked for a long time to success this conference a. Finally, we would like to thank all the researchers participated in this conference from inside and outside Iraq, wishing them success and for the conference to come up with recommendations that serve our society and country. May Allah grant everyone, peace, and Allah’s mercy and blessings be upon you. List of Editors Keynote Speakers, Scientific Committee, Organizing Committee are available in this pdf.

Space polymers erosion in simulated LEO and VLEO environments

The VLEO satellites, that are orbiting at an altitude of 200-300 km and that provide advantages for high-resolution Earth observation and atmospheric science, are becoming important not only for science, but also for agriculture, forestry, and oceans observations, for military, national security and the future of satellite businesses. We evaluated, for the first time, the performance and defined the erosion yields (Ey) for a selected number of main space hydrocarbon, fluorinated, and perfluorinated polymers in the ground-based simulator facility at conditions, imitating the LEO and VLEO environments. We also compared the results with the data for polymers erosion in LEO and with the previously established predictive model, developed for polymers and composites in LEO environment. The obtained data indicated that the predictive model can be extended and used, with some corrections for the predictions of space polymers erosion in the VLEO environment.

Interactive 3D Visual Analysis of Weather Prediction Data Reveals Midlatitude Overshooting Convection during the CIRRUS-HL Field Experiment

Abstract In summer 2021, microphysical properties and climate impact of high- and midlatitude ice clouds over Europe and the North Atlantic were studied during the Cirrus High Latitude (CIRRUS-HL) airborne field campaign. The related forecasting and flight planning tasks provided a testbed for interactive 3D visual analysis. Operational analyses and forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) were visualized with the open-source software “Met.3D.” A combination of traditional 2D displays with innovative 3D views in the interactive visualization framework facilitated rapid and comprehensive exploration of the NWP data. By this means, the benefit of interactive 3D visual forecast products in the routine flight planning procedure was evaluated. Here, we describe the use of 3D tropopause and cloud visualizations during a convective event over the Alps, which became one of the CIRRUS-HL observation targets. For the planning of the research flight on 8 July 2021, our analysis revealed that simulated strong convective updrafts locally disturb the tropopause and inject ice water across the dynamical tropopause into the lower stratosphere. The presented example provides a novel 3D perspective of convective overshooting in a global NWP model and its impact on the tropopause and lower stratosphere. The case study shall encourage the atmospheric science community to further evaluate the use of modern 3D visualization capabilities for NWP analysis.

Integrating Atmospheric Science Research in Chemical Education: Utility of Primary Research Articles in Fostering Student Interest in Meteorology

Atmospheric science research has seen significant advances in facilitating the generation of knowledge and promoting a scientific understanding of global meteorological issues and concerns with the advent of technological progress across many disciplines, including the physical and biological sciences and the breakthroughs in computational and modeling methodologies. This has resulted in a rich library of scientific literature showcasing knowledge creation and a deeper understanding of natural phenomena and their linkages to the sustenance of life embodied by the extensive systems of the hydrosphere, biosphere, and even the frontiers of outer space. This article outlines how primary research in atmospheric science can be integrated into chemical education by furnishing connections and synchronicity with chemistry, bridging the concepts, discoveries, innovations, and their immediate importance to science and society. A general overview is given on how topics or themes in general chemistry courses can utilize the power of scientific research articles on atmospheric science, fostering students' interest in meteorological concepts and related fields. A non-exhaustive list of primary research literature highlighting breakthroughs related to a specific chemistry theme serving as templates for chemical educators is provided to enable the students to see real-world applications. Integrating research into science education is an effective strategy to promote scientific thinking and literacy and should be a catalyst for the global drive for sustainability.

Exact analytical solution of the one-dimensional time-dependent radiative transfer equation with linear scattering

The radiative transfer equation (RTE) is a cornerstone for describing the propagation of electromagnetic radiation in a medium, with applications spanning atmospheric science, astrophysics, remote sensing, and biomedical optics. Despite its importance, an exact analytical solution to the RTE has remained elusive, necessitating the use of numerical approximations such as Monte Carlo, discrete ordinate, and spherical harmonics methods. In this paper, we present an exact solution to the one-dimensional time-dependent RTE. We delve into the moments of the photon distribution, providing a clear view of the transition to the diffusion regime. This analysis offers a deeper understanding of light propagation in the medium. Furthermore, we demonstrate that the one-dimensional RTE is equivalent to the Klein-Gordon equation with an imaginary mass term determined by the inverse reduced scattering length. Contrary to naive expectations of superluminal solutions, we find that our solution is strictly causal under appropriate boundary conditions, determined by the light transport problem. We validate the found solution using Monte Carlo simulations and benchmark the performance of the latter. Our analysis reveals that even for highly forward scattering, dozens of random light scatterings are required for an accurate estimate, underscoring the complexity of the problem. Moreover, we propose a method for faster convergence by adjusting the parameters of Monte Carlo sampling. We show that a Monte Carlo method sampling photon scatterings with input parameters (μs,g), where μs is the inverse scattering length and g is the scattering anisotropy parameter, is equivalent to that with (μs(1−g)/2,−1). This equivalence leads to a significantly faster convergence to the exact solution, offering a substantial improvement of the Monte Carlo method for the one-dimensional RTE. Our findings not only contribute to the theoretical understanding of the RTE but also have potential implications for improving the numerical methods used to approximate it.

Commitment to Active Allyship Is Required to Address the Lack of Hispanic and Latinx Representation in the Earth and Atmospheric Sciences

Abstract In 2021, people of Hispanic and Latinx origin made up 6% of the atmospheric and Earth sciences workforce of the United States, yet they represent 20% of the population. Motivated by this disparity in Hispanic and Latinx representation in the atmospheric and Earth science workforce, this manuscript documents the lack of representation through existing limited demographic data. The analysis presents a clear gap in participation by Hispanic and Latinx people in academic settings, with a widening gap through each education and career stage. Several factors and challenges impacting the representation disparity include the lack of funding for and collaboration with Hispanic-serving institutions, limited opportunities due to immigration status, and limited support for international research collaborations. We highlight the need for actionable steps to address the lack of representation and provide targeted recommendations to federal funding agencies, educational institutions, faculty, and potential employers. While we wait for systemic cultural change from our scientific institutions, grassroots initiatives like those proudly led by the AMS Committee for Hispanic and Latinx Advancement will emerge to address the needs of the Hispanic and Latinx scientific and broader community. We briefly highlight some of those achievements. Lasting cultural change can only happen if our leaders are active allies in the creation of a more diverse, equitable, and inclusive future. Alongside our active allies we will continue to champion for change in our weather, water, and climate enterprise.

Prospects for Machine Learning Activity within the United States National Weather Service

Abstract The National Weather Service (NWS) Office of Science and Technology Integration commissioned a report to assess the status of artificial intelligence (AI) and machine learning (ML) activity within the agency with a view toward identifying existing obstacles and recommending future directions. The purpose of this essay is to communicate the steps that the NWS plans to take to realize the potential benefits of AI in operations. AI activities are growing rapidly within atmospheric sciences, and the NWS is part of this growth. However, the activity is fragmented and lacks the needed infrastructure for improved coordination of effort. Current obstacles to progress include insufficient workforce training in AI/ML, a lack of curated datasets and software that can be used for development and evaluation of these approaches, the absence of a centralized clearing house available to NWS personnel for technical expertise and consultation, limited operational compute resources, and a lack of a clear end-to-end project pathway that encompasses exploration, development, testbed/proving ground, and operational implementation. These limitations are addressable. Training materials specific to NWS interests can be developed through collaboration with existing NOAA centers. Establishing a reference library staffed with AI/ML consultants tasked with collaborating with operational units would reduce siloed efforts and enhance productivity. Establishing funding vehicles for theme-based projects with a sustainable pathway through operational implementation would help bridge the research-to-operations “valley of death.” Given the growth of AI/ML across the U.S. Weather Enterprise and the already substantial involvement of academic and private sector entities, these developments within the NWS will be of interest to the atmospheric science field.

Communicating about Extreme Heat: Results from Card Sorting and Think-Aloud Interviews with Experts from Differing Domains

Abstract Climate trends indicate that extreme heat events are becoming more common and more severe over time, requiring improved strategies to communicate heat risk and protective actions. However, there exists a disconnect in heat-related communication from experts, who commonly include heat-related jargon (i.e., technical language), to decision-makers and the general public. The use of jargon has been shown to reduce meaningful engagement with and understanding of messages written by experts. Translating technical language into comprehensible messages that encourage decision-makers to take action has been identified as a priority to enable impact-based decision support. Knowing what concepts and terms are perceived as jargon, and why, is a first step to increasing communication effectiveness. With this in mind, we focus on the mental models about extreme heat among two groups of domain experts—those trained in atmospheric science and those trained in emergency management—to identify how each group understands terms and concepts about extreme heat. We use a hybrid data collection method of open card sorting and think-aloud interviews to identify how participants conceptualize and categorize terms and concepts related to extreme heat. While we find few differences within the sorted categories, we learn that the processes leading to decisions about the importance of including, or not including, technical information differ by group. The results lead to recommendations and priorities for communicating about extreme heat. Significance Statement Effective communication between domain experts is a priority for informed decision-making under extreme weather conditions. As severe heat events increase in frequency and severity, the ability to communicate about heat and its impacts in a clear manner will become vital to life safety. The use of jargon-filled technical, scientific language can serve as a barrier to understanding and engagement, delaying decision-making and action. By identifying how extreme heat terms and concepts are understood among domain experts, risk communicators can determine where to focus on the development of plain language messaging, which improves decision support and decision-making.

What Floodplain Managers Want: Using Weather and Climate Information for Decision-Making

Abstract As a result of climate change, extreme precipitation events are likely to become more common in Oklahoma, requiring cities and municipalities to plan for managing this extra water. There are multiple types of practitioners within communities who are responsible for overseeing planning for the future, including stormwater and floodplain management. These practitioners may be able to integrate weather and climate information into their decision-making to help them prepare for heavy precipitation events and their impacts. Floodplain managers from central and eastern Oklahoma were interviewed to learn what information they currently use and how it informs their decision-making. When making decisions in the short term, floodplain managers relied on weather forecasts; for long-term decisions, other factors, such as constrained budgets or the power of county officials, had more influence than specific climate predictions or projections. On all time scales, social networks and prior experience with flooding informed floodplain managers’ decisions and planning. Overall, information about weather and climate is just one component of floodplain managers’ decision-making processes. The atmospheric science community could work more collaboratively with practitioners so that information about weather and climate is more useful and, therefore, more relevant to the types of decisions that floodplain managers make.