Forecast Office Research Articles

Leveraging Collaborative Partnerships to Enhance NWS and Emergency Management Communications through Exercising

Abstract Tabletop exercises examining weather-related hazards are not uncommon but are often built around somewhat generic scenarios that only touch on the meteorological communication environment at a very shallow level. A recent exercise in central Oklahoma sought to change that. A local emergency manager, personnel from a National Weather Service (NWS) forecast office, and a severe weather researcher with a background in exercise design and facilitation worked together to create and deliver a realistic severe weather simulation. Exercise participants were exposed to detailed forecast information via NWSChat—a dedicated communication tool used to connect NWS forecasters, emergency managers, and media members for real-time information sharing. NWS forecasters were able to both actively play in the exercise due to the use of NWSChat and observe how local decision-makers interpreted and utilized the impact-based decision support service (IDSS) graphics and short-term forecast updates. The collaborative approach of developing a detailed scenario with numerous real-world IDSS graphics, along with the use of NWSChat for real-time delivery, resulted in overwhelmingly positive feedback from the participants. The local emergency management office identified numerous areas for improvement in communicating real-time forecast information across their jurisdiction, along with gaps in current plans and resources. Meanwhile, the NWS forecast office had the opportunity to experiment with using the new NWSChat platform in a high-impact severe weather environment before a real-world event took place. Forecasters also gained insight into current IDSS graphic interpretation, noting areas for improved messaging to end users, such as adding storm motion to existing severe weather graphics.

Analysis and Prediction of Summer Rainfall over Southwestern Utah

Abstract While many studies have examined intense rainfall and flash flooding during the North American monsoon (NAM) in Arizona, Nevada, and New Mexico, less attention has focused on the NAM’s extension into southwestern Utah. This study relates flash flood reports and Multi-Radar Multi-Sensor (MRMS) precipitation across southwestern Utah to atmospheric moisture content and instability analyses and forecasts from the High-Resolution Rapid Refresh (HRRR) model during the 2021–23 monsoon seasons. MRMS quantitative precipitation estimates over southwestern Utah during the summer depend largely on the areal coverage from the KICX WSR-88D radar near Cedar City, Utah. Those estimates are generally consistent with the limited number of precipitation gauge reports in the region except at extended distances from the radar. A strong relationship is evident between days with widespread precipitation and afternoons with above-average precipitable water (PWAT) and convective available potential energy (CAPE) estimated from HRRR analyses across the region. Time-lagged ensembles of HRRR forecasts (initialization times from 0300 to 0600 UTC) that are 13–18 h prior to the afternoon period when convection is initiating (1800–2100 UTC) are useful for situational awareness of widespread precipitation events after adjusting for underprediction of afternoon CAPE. Improved skill is possible using random forest classification relying only on PWAT and CAPE to predict days experiencing excessive (upper quartile) precipitation. Such HRRR predictions may be useful for forecasters at the Salt Lake City National Weather Service Forecast Office to assist in issuing flash flood potential statements for visitors to national parks and other recreational areas in the region. Significance Statement Summer flash floods in southwestern Utah are a risk to area residents and millions of visitors annually to the region’s national parks, monuments, and recreational areas. The likelihood of flash floods within the region’s catchments depends on the intense afternoon and early evening convection initiated by lift and instability primarily due to terrain–flow interactions over elevated plateaus and mountains. Forecasts at lead times of 13–18 h of moisture and instability from the operational High-Resolution Rapid Refresh model have the potential to predict summer afternoons that are likely to have increased risks for higher rainfall amounts across southwestern Utah, although they are not expected to predict the likelihood of flash floods in any specific locale.

Collaborative Exploration of Storm-Scale Probabilistic Guidance for NWS Forecast Operations

Abstract The operational utility of the NOAA National Severe Storm Laboratory’s storm-scale probabilistic Warn-on-Forecast System (WoFS) was examined across the watch-to-warning time frame in a virtual NOAA Hazardous Weather Testbed (HWT) experiment. Over four weeks, 16 NWS forecasters from local Weather Forecast Offices, the Storm Prediction Center, and the Weather Prediction Center participated in simulated forecasting tasks and focus groups. Bringing together multiple NWS entities to explore new guidance impacts on the broader forecast process is atypical of prior NOAA HWT experiments. This study therefore provides a framework for designing such a testbed experiment, including methodological and logistical considerations necessary to meet the needs of both local office and national center NWS participants. Furthermore, this study investigated two research questions: 1) How do forecasters envision WoFS guidance fitting into their existing forecast process? and 2) How could WoFS guidance be used most effectively across the current watch-to-warning forecast process? Content and thematic analyses were completed on flowcharts of operational workflows, real-time simulation interactions, and focus group activities and discussions. Participants reported numerous potential applications of WoFS, including improved coordination and consistency between local offices and national centers, enhanced hazard messaging, and improved operations planning. Challenges were also reported, including the knowledge and training required to incorporate WoFS guidance effectively and forecasters’ trust in new guidance and openness to change. The solutions identified to these challenges will take WoFS one step closer to transition, and in the meantime, improve the capabilities of WoFS for experimental use within the operational community. Significance Statement A first-of-its-kind experiment brought together forecasters from local weather forecast offices and national centers to examine the experimental Warn-on-Forecast System’s (WoFS’s) potential applications across watch-to-warning scales. This experiment demonstrated that WoFS can provide great benefit to forecasters, though a few challenges remain. Benefits provided by WoFS frequently overlap roles and responsibilities at local and national scales, suggesting the potential for enhanced cross-office collaboration. The challenges anticipated for WoFS operational use are far fewer than the benefits, and some solutions to these challenges are now being implemented. Finally, the mixed-methods experimental framework described herein also provides guidance for future collaborative experiments in testbed research that examine impacts of new technologies across NWS entities.

Tweeting the Heat: An Analysis of the National Weather Service’s Approach to Extreme Heat Communication on Twitter

Abstract Heat communication interventions are an essential way that public safety organizations can reduce extreme heat consequences for at-risk groups. Although the aim of these interventions is typically behavior change, these organizations commonly assume that providing information about heat risks, impacts, vulnerable populations, and protective actions will lead individuals to protect themselves. However, behavior change is a complex process whereby messages must be crafted in ways that increase their persuasive effects. To examine the extent to which key assumptions about behavior change are present in public safety organizations’ heat communication interventions, we examine 250 heat-related tweets sent by seven National Weather Service (NWS) weather forecast offices (WFOs) in 2021. We find that these NWS WFOs use technical language or “jargon” to communicate about heat risks and impacts. In addition, we find that information about vulnerable populations and protective actions is not presented in a way that conforms to theory on behavior change. Based on these results, we offer recommendations to increase the persuasiveness of NWS WFO communication interventions that encourage the public to protect themselves during extreme heat events. Significance Statement Heat is the leading cause of death among all weather-related hazards. How heat is communicated to the public can help mitigate heat-related morbidity and mortality. However, heat communication interventions are often developed with several embedded assumptions about behavior change that negatively impact their effectiveness. By examining how a key public safety organization communicates about heat on social media, and the extent to which these assumptions are present, we offer recommendations to increase the persuasiveness of NWS heat communication on social media.

Evaluation of Probabilistic Snow Forecasts for Winter Weather Operations at Intermountain West Airports

Abstract This work set out to assess the performance of four forecast systems [the Short-Range Ensemble Forecast (SREF), High-Resolution Rapid Refresh Ensemble (HRRRE), the National Blend of Models (NBM), and the Probabilistic Snow Accumulation product (PSA) from the National Weather Service (NWS) Boulder, Colorado, Weather Forecast Office] when predicting snowfall events around the Intermountain West to advise winter weather decision-making processes at Denver International Airport. The goal was to provide airport personnel and the Boulder NWS Forecast Office with operationally relevant verification results on the timing and severity of these events so they are able to make better-informed decisions to minimize negative impacts of storms. Forecasts of snow events using various probability thresholds and a climatological snow-to-liquid ratio of 15:1 were evaluated against Meteorological Aerodrome Reports (METARs) for 24-h periods following four decision-making times spaced equally throughout the day. For the ensembles, a frequentist approach was used: the forecast probability equaled the percentage of ensemble members that predicted a snow event. The results show that the NBM had the best timing of snow events out of the products, while all the products tended to overforecast snow amount. Additionally, NBM had fewer snow events and rarely had high probabilities of snow, unlike the other forecast products.

Toward Operational Real-Time Identification of Frontal Boundaries Using Machine Learning

Abstract We present and evaluate a deep learning first-guess front-identification system that identifies cold, warm, stationary, and occluded fronts. Frontal boundaries play a key role in the daily weather around the world. Human-drawn fronts provided by the National Weather Service’s Weather Prediction Center, Ocean Prediction Center, Tropical Analysis and Forecast Branch, and Honolulu Forecast Office are treated as ground-truth labels for training the deep learning models. The models are trained using ERA5 data with variables known to be important for distinguishing frontal boundaries, including temperature, equivalent potential temperature, and wind velocity and direction at multiple heights. Using a 250-km neighborhood over the contiguous U.S. domain, our best models achieve critical success index scores of 0.60 for cold fronts, 0.43 for warm fronts, 0.48 for stationary fronts, 0.45 for occluded fronts, and 0.71 using a binary classification system (front/no front), whereas scores over the full unified surface analysis domain were lower. For cold and warm fronts and binary classification, these scores significantly outperform prior baseline methods that utilize 250-km neighborhoods. These first-guess deep learning algorithms can be used by forecasters to locate frontal boundaries more effectively and expedite the frontal analysis process. Significance Statement Fronts are boundaries that affect the weather that people experience daily. Currently, forecasters must identify these boundaries through manual analysis. We have developed an automated machine learning method for detecting cold, warm, stationary, and occluded fronts. Our automated method provides forecasters with an additional tool to expedite the frontal analysis process.

Conceptualizing Confidence: A Multisited Qualitative Analysis in a Severe Weather Context

Abstract Confidence is a concept important to weather prediction, shaping how risk information is created, shared, understood, and acted upon. For forecasters in the National Weather Service (NWS) and their partners in public safety, confidence is central to their work, appearing frequently during their decision support services. While confidence has been examined in a variety of literatures, it is often addressed simplistically or as one of many variables in a study. It is rarely the object of study in and of itself, even less so in a naturalistic setting like an operational environment. To build a more robust knowledge of confidence and its many dimensions, we conducted a multisited ethnography of three interrelated sites central to tornado prediction and information dissemination, leading up to and during a cool-season tornado event. In partnership with collaborators from the NWS and emergency management, we simultaneously deployed to a National Center, a local Weather Forecast Office, and an emergency management office. This article explicates confidence from multiple social science theories, considering the scientific, data-based roots of confidence, as well as its affective, relational, and procedural origins. Our results show that confidence emerges in varied and complex ways and at different scales. Confidence can indicate one’s assessment of evidence and agreement (or lack) of it, beliefs about partners’ future behavior based on past experiences, and ritual interactions between offices that create patterned expectations. We argue for a more robust interdisciplinary analysis of confidence given how it shapes weather-related policies and practices, technologies, and communication strategies.

Determining the Location of the 22 May 1855 Chicago Area Tornado

Abstract The number and location of tornadoes in the greater Chicago area is a topic of frequent interest among the media, public, and local government agencies served by the National Weather Service (NWS) Chicago Forecast Office. While accounts of tornadoes over the last several decades are generally clear, tornadoes occurring prior to 1950—especially those considered to be weak—are often more difficult to discern owing to limited corresponding detailed reports. As part of an effort to review and update all tornadoes known to have occurred within the modern-day boundaries of Chicago, NWS Chicago staff reviewed the 22 May 1855 tornado, which is regarded as the first to impact the city of Chicago. Multiple sources reported that the tornado occurred near the town of Jefferson, which eventually became the Jefferson Park neighborhood of Chicago. However, after reviewing multiple historical records, newspaper articles, property maps, and genealogical information, the actual location of the tornado was determined to have been in present-day Des Plaines. Confusion over the name “Jefferson” likely led to the misunderstanding that, until now, has been perpetuated through numerous reports and media accounts.

Collaboration among Forecasters to Issue Severe Weather Hazard Information and Warnings Using the Hazard Services–Probabilistic Hazard Information (HS-PHI) Tool

Abstract This project tested software capabilities and operational implications related to interoffice collaboration during NWS severe weather warning operations within a proposed paradigm, Forecasting A Continuum of Environmental Threats (FACETs). Current NWS policy of each forecast office issuing warnings for an exclusive area of responsibility may result in inconsistent messaging. In contrast, the FACETs paradigm, with object-based, moving probabilistic and deterministic hazard information, could provide seamless information across NWS County Warning Areas (CWAs). An experiment was conducted that allowed NWS forecasters to test new software that incorporates FACETs-based hazard information and potential concepts of operation to improve messaging consistency between adjacent WFOs. Experiment scenarios consisted of a variety of storm and office border interactions, fictional events requiring nowcasts, and directives that mimicked differing inter-WFO warning philosophies. Surveys and semi-structured interviews were conducted to gauge forecasters’ confidence and workload levels, and to discuss potential solutions for interoffice collaboration and software issues. We found that forecasters were able to adapt quickly to the new software and concepts and were comfortable with collaborating with their neighboring WFO in warning operations. Although forecasters felt the software’s collaboration tools enabled them to communicate in a timely manner, adding this collaboration increased their workload when compared to their workload during current warning operations.

Spatial Analysis of United States National Weather Service Excessive Heat Warnings and Heat Advisories

Abstract Public heat alerts are important risk communication tools, but there has been no systematic analysis of how frequently they are issued or how patterns in alert frequency relate to regional climatology or heat–health impacts. We compiled and analyzed all excessive heat warnings and heat advisories (collectively, heat alerts) issued by the U.S. National Weather Service for 2010–19. Heat alert frequency was correlated to climatological indicators derived from reanalysis data aggregated to Weather Forecast Office (WFO) polygons and to estimates of heat-attributable mortality for 134 metropolitan areas. The type of heat alerts used and the frequency with which they were issued were highly variable. Across 77% of the country, heat advisories were the primary product issued. The median location experienced 2.3 heat alert days per year. Regions with the highest frequency (approaching 25 heat alert days per year) included the southern Midwest and Great Plains, as well as the desert Southwest. The 95th-percentile daily maximum heat index was the climatological indicator most strongly correlated with heat alert frequency across all WFOs (r = 0.71). Locations that issued heat alerts more frequently than would be expected based on climatology were primarily located along the Pacific coast; those that issued heat alerts less frequently than expected were in southern Texas and southern Florida, the latter of which includes multiple cities with high rates of heat-attributable mortality. Our results suggest that the public may be receiving mixed signals about the severity of the heat hazard, with some hotter locations particularly underserved by heat risk messaging.

Creating a Communication Framework for FACETs: How Probabilistic Hazard Information Affected Warning Operations in NOAA’s Hazardous Weather Testbed

Abstract Scientists at NOAA are testing a new tool that allows forecasters to communicate estimated probabilities of severe hazards (tornadoes, severe wind, and hail) as part of the Forecasting a Continuum of Environmental Threats (FACETs) framework. In this study, we employ the embedded systems theory (EST)—a communication framework that analyzes small group workplace practices as products of group, organizational, and local dynamics—to understand how probabilistic hazard information (PHI) is produced and negotiated among multiple NWS weather forecast offices in an experimental setting. Gathering feedback from NWS meteorologists who participated in the 2020 Hazard Services (HS)-PHI Interoffice Collaboration experiment, we explored implications of local and interoffice collaboration while using this experimental tool. By using a qualitative thematic analysis, it was found that differing probability thresholds, forecasting styles, social dynamics, and workload will be social factors that developers should consider as they bring PHI toward operational readiness. Warning operations in this new paradigm were also implemented into the EST model to create a communication ecosystem for future weather hazard communication research. Significance Statement Meteorologists are currently exploring how to use probabilities to communicate life-saving information. From tornadoes to hail, a new type of probabilistic hazard information could fundamentally change the way that NWS meteorologists collaborate with one another when issuing weather products, especially near and along the boundaries of County Warning Areas. To explore potential collaboration challenges and solutions, we applied a communication framework and explored perceptions that NWS meteorologists had while using this new tool in an experimental setting. NWS meteorologists expressed that differing ways of communicating hazard information between each office, along with forecasting styles and workload, would change the way they go about producing critical hazard information to the public.

The Experimental Warning Program of NOAA’s Hazardous Weather Testbed

Abstract NOAA’s Hazardous Weather Testbed (HWT) is a physical space and research framework to foster collaboration and evaluate emerging tools, technology, and products for NWS operations. The HWT’s Experimental Warning Program (EWP) focuses on research, technology, and communication that may improve severe and hazardous weather warnings and societal response. The EWP was established with three fundamental hypotheses: 1) collaboration with operational meteorologists increases the speed of the transition process and rate of adoption of beneficial applications and technology, 2) the transition of knowledge between research and operations benefits both the research and operational communities, and 3) including end users in experiments generates outcomes that are more reliable and useful for society. The EWP is designed to mimic the operations of any NWS Forecast Office, providing the opportunity for experiments to leverage live and archived severe weather activity anywhere in the United States. During the first decade of activity in the EWP, 15 experiments covered topics including new radar and satellite applications, storm-scale numerical models and data assimilation, total lightning use in severe weather forecasting, and multiple social science and end-user topics. The experiments range from exploratory and conceptual research to more controlled experimental design to establish statistical patterns and causal relationships. The EWP brought more than 400 NWS forecasters, 60 emergency managers, and 30 broadcast meteorologists to the HWT to participate in live demonstrations, archive events, and data-denial experiments influencing today’s operational warning environment and shaping the future of warning research, technology, and communication for years to come.

Communicating Probability Information in Hurricane Forecasts: Assessing Statements that Forecasters Use on Social Media and Implications for Public Assessments of Reliability

Forecasters are responsible for predicting the weather and communicating risk with stakeholders and members of the public. This study investigates the statements that forecasters use to communicate probability information in hurricane forecasts and the impact these statements may have on how members of the public evaluate forecast reliability. We use messages on Twitter to descriptively analyze probability statements in forecasts leading up to Hurricanes Harvey, Irma, Maria, and Florence from forecasters in three different groups: the National Hurricane Center, local Weather Forecast Offices, and in the television broadcast community. We then use data from a representative survey of United States adults to assess how members of the public wish to receive probability information and the impact of information format on assessments of forecast reliability. Results from the descriptive analysis indicate forecasters overwhelmingly use words and phrases in place of numbers to communicate probability information. In addition, the words and phrases forecasters use are generally vague in nature -- they seldom include rank adjectives (e.g., “low” or “high”) to qualify blanket expressions of uncertainty (e.g., “there is a chance of flooding”). Results from the survey show members of the public generally prefer both words/phrases and numbers when receiving forecast information. They also show information format affects public judgments of forecast reliability; on average, people believe forecasts are more reliable when they include numeric probability information.

The National Weather Service–North Carolina State University Internship Course: Impacts and Success over a Generation

AbstractNearly 100 North Carolina State University (NCSU) students have participated in a unique, highly structured internship course conducted by the National Weather Service (NWS) Weather Forecast Office (WFO) in Raleigh, North Carolina. Here, we explore the impact that this course has had on their professional development and career trajectories. As of this writing, the course has been running for 17 years; this paper provides an update on how the course has changed over time, and information concerning participant outcomes. Changes include a reduction in class size to allow for more individualized mentoring, and the addition of experiences outside of the WFO. The course serves as a compelling selling point in student recruiting for the Department of Marine, Earth, and Atmospheric Sciences (MEAS), and participation also helps to ensure that the curriculum is adequately preparing students for positions in the NWS. The NWS benefits from a pool of potential employees that will require less spin-up time if hired; additionally, some NCSU graduates have participated in similar student volunteer programs at their respective offices once hired.

A Multi-scale Analysis of the Atmospheric Conditions Associated with the Daytona Beach Tornado of Christmas Day, 2006

This case study describes a severe-storm event over Florida, Georgia, and South Carolina on 25 December 2006, with a particular focus on an F2 tornado that struck Daytona Beach, FL and caused over $50 million in damages. The severe weather occurred over a 12-h period and was associated with a deep upper-level trough and surface front moving through the southeastern U.S. Morning soundings over Florida showed low to moderate CAPE and strong vertical wind shear, consistent with seasonal composite tornadic soundings for the region. A quasi-linear convective system moved onshore near Tampa during the midmorning hours, the northern half of which accelerated and produced bow echoes that resulted in two tornadoes and nontornadic wind damage over Pasco, Sumter, and Lake Counties between 1620 and 1725 UTC. This portion of the line then moved into Volusia County and spawned F2 tornadoes in Deland and Daytona Beach after 1800 UTC. Data from the Melbourne National Weather Service Forecast Office’s Weather Surveillance Radar-1988D (WSR-88D), Daytona Beach International Airport (DAB) Automated Surface Observing System (ASOS), and DAB Low Level Wind Shear Alert System (LLWAS) were integrated to analyze conditions at the east end of the DAB runway 7L/25R complex, where the tornado first appeared. The LLWAS is normally used by air traffic control personnel for monitoring airport wind-shear conditions. The 10-s LLWAS wind data filled critical temporal and spatial gaps in the WSR-88D and ASOS data, and captured evidence of strong winds and cyclonic curvature nearly coincident with the locations of the radar-identified velocity couplet and tornado itself.

Total Lightning Observations of Supercells over North Central Texas

s part of a collaborative research project between Texas A&M; University and the NOAA/NWS Fort Worth/Dallas Weather Forecast Office, total lightning observations from Vaisala’s Dallas-Fort Worth (DFW) Lightning Detection and Ranging (LDAR II) network have been used to supplement Doppler radar measurements in the diagnosis of thunderstorm updraft strength and analysis of severe weather potential. More specifically, initial observations of severe convection over north-central Texas for three case dates have shown that total lightning flash extent density (FED) and gridded source density peaked prior to, or increased during reported severe weather events. Two lightning holes were observed with one supercell, and numerous FED notches were noted with other cells that likely indicated the updraft region of the thunderstorms. These signatures in the FED corresponded to weak echo regions on the KFWS WSR-88D radar reflectivity data. Additionally, lightning appendages developed for both right- and left- deviant cells prior to shifts in radar-inferred cell track, indicating a possible method for prediction of right or left hand deflections in supercell motion. A cell embedded within a linear MCS also developed a large notch in the FED data on its rear flank that persisted for over 25 min and preceded a severe wind report, indicating another potential forecasting application of total lightning data.

An Investigation of NEXRAD-Based Quantitative Precipitation Estimates in Alaska

Precipitation estimation by weather radars in Alaska is challenging. In this study, we investigate National Weather Service (NWS) precipitation products that are produced from the seven NEXRAD radar sites in Alaska. The NWS precipitation processing subsystem generates stages of data at each NEXRAD site which are then input to the weather forecast office to generate a regionwide precipitation product. Data from the NEXRAD sites and the operational rain gauges in the weather forecast region are used to produce this regionwide product that is then sent to the National Centers for Environmental Prediction (NCEP) to be included in the NCEP Stage IV distribution. The NCEP Stage IV product for Alaska has been available since 2017. We use the United States Climate Reference Network (USCRN) data from Alaska to compare to the NCEP Stage IV data. Given that the USCRN can be used in the production of the NCEP Stage IV data for Alaska, we also used the NEXRAD Digital Precipitation Array (DPA) that is generated at the site for comparison of the radar-only products. Comparing the NEXRAD-based data from Alaska to the USCRN gauge estimates using the USCRN site information on air temperature, we are able to condition the analysis based on the hourly or 6-hourly average air temperature. The estimates in the frozen phase of precipitation largely underestimate as compared to the gauge, and the correlation is low with larger errors as compared to other phases of precipitation. In the mixed phase the underestimation of precipitation improves, but the correlation is still low with relatively large errors as compared to the rain phases of precipitation. The difficulties in precipitation estimation in cold temperatures are well known and we show the evaluation for the NCEP Stage IV regional data for Alaska and the NEXRAD site specific Digital Precipitation Array (DPA) data. Results show the challenges of estimating mixed-phase and frozen precipitation. However, the DPA data shows somewhat better performance in the mixed precipitation phase, which suggests that the NWS Precipitation Processing Subsystem (PPS) is tuned to the climatology as it relates to precipitation in Alaska.

Improving Communication of Uncertainty and Risk of High-Impact Weather through Innovative Forecaster Workshops

AbstractIt is challenging to communicate uncertainty for high-impact weather events to the public and decision-makers. As a result, there is an increased emphasis and training within the National Weather Service (NWS) for “impact-based decision support.” A Collaborative Science, Technology, And Research (CSTAR) project led by Stony Brook University (SBU) in collaboration with the Alan Alda Center for Communicating Science, several NWS forecast offices, and NWS operational centers held two workshops at SBU on effective forecast communication of probabilistic information for high-impact weather. Trainers in two 1.5-day workshops helped 15–20 forecasters learn to distill their messages, engage audiences, and more effectively communicate risk and uncertainty to decision-makers, media, and the general public. The novel aspect of the first workshop focused on using improvisational techniques to connect with audiences along with exercises to improve communication skills using short, clear, conversational statements. The same forecasters participated in the second workshop, which focused on matching messages to intended audiences and stakeholder interaction. Using a recent high-impact weather event, representatives in emergency management, TV media, departments of transportation, and emergency services provided feedback on the forecaster oral presentations (2–3 min) and a visual slide. This article describes our innovative workshop approach, illustrates some of the techniques used, and highlights participant feedback.

Snowfall in the Northern Great Lakes: Lessons Learned from a Multisensor Observatory

AbstractA multisensor snowfall observational suite has been deployed at the Marquette, Michigan, National Weather Service Weather Forecast Office (KMQT) since 2014. Micro Rain Radar (MRR; profiling radar), Precipitation Imaging Package (PIP; snow particle imager), and ancillary ground-based meteorological observations illustrate the unique capabilities of these combined instruments to document radar and concomitant microphysical properties associated with northern Great Lakes snowfall regimes. Lake-effect, lake-orographic, and transition event case studies are presented that illustrate the variety of snowfall events that occur at KMQT. Case studies and multiyear analyses reveal the ubiquity of snowfall produced by shallow events. These shallow snowfall features and their distinctive microphysical fingerprints are often difficult to discern with conventional remote sensing instruments, thus highlighting the scientific and potential operational value of MRR and PIP observations. The importance of near-surface lake-orographic snowfall enhancement processes in extreme snowfall events and regime-dependent snow particle microphysical variability controlled by regime and environmental factors are also highlighted.

R2O2R Improvements Identified by United States Space Weather Forecasters

AbstractA communication deficit exists between the space weather research and forecast communities in the research‐to‐operations‐to‐research (R2O2R) pipeline. No formal, citable space exists for forecasters to communicate needs and lessons learned to the research community (O2R). This deficit was termed the “valleys of death and lost opportunities” (NRC, 2003, https://doi.org/10.17226/10658) and has resulted in advancements taking up to 20 years or more to become forecast operational. To provide this communication space, we surveyed a group of US civilian space weather forecasters on their needed improvements, use of available resources, and interactions with researchers, via a combination of questionnaire and focus group discussions. Nineteen needed improvements were identified, clustering into four categories: scientific understanding, access to data, forecast office tools, and instrumentation. Participants appeared to prefer resources with a robust data stream of high‐resolution and high‐time cadence data which suffer few technical issues. Participants want to be included in tool development more often and earlier in the process as they felt they were “seldom listened to when it comes to what [they] actually need.”