Recent Additions

This page includes the documents that were newly added to the repository within the last 30 days.

All these words:

This exact word or phrase:

Any of these words:

None of these words:

Language:

Publication Date Range:

Visit our Help Page for additional assistance

Select a Range:

Select a Format:

Custom Search Builder:

Custom Search Box

Visit our Help Page for additional assistance

Showing 1 - 20 of 313 results

Show Me and What Will I Remember? Exploring Recall in Response to NWS Tornado Warning Graphics

Fischer, Laura Morgan ;

Orton, Ginger

2022 | Journal of Applied Communications, 106(3) | pdf

It is critical that organizations deliver timely, effective communication about potential risks and life-saving information. The National Weather Service (NWS) developed a suite of messages known as “experimental graphic products” to be automatically distributed through their local official Twitter accounts at the onset of fast-moving, severe weath ...

04/24/2026

Title : Show Me and What Will I Remember? Exploring Recall in Response to NWS Tornado Warning Graphics Personal Author(s) : Fischer, Laura Morgan;Orton, Ginger;Sutton, Jeannette;Wallace, Madison; Published Date : 2022 Source : Journal of Applied Communications, 106(3) DOI : https://doi.org/10.4148/1051-0834.2440 Journal Title : Journal of Applied Communications Fischer, Laura Morgan et al. (2022). Show Me and What Will I Remember? Exploring Recall in Response to NWS Tornado Warning Graphics. 106(3). https://doi.org/10.4148/1051-0834.2440 Fischer, Laura Morgan et al. "Show Me and What Will I Remember? Exploring Recall in Response to NWS Tornado Warning Graphics" 106, no. 3 (2022), https://doi.org/10.4148/1051-0834.2440 Fischer, Laura Morgan et al. "Show Me and What Will I Remember? Exploring Recall in Response to NWS Tornado Warning Graphics" vol. 106, no. 3, 2022, https://doi.org/10.4148/1051-0834.2440 Export RIS Citation Information. TY - AU - Fischer, Laura Morgan AU - Orton, Ginger AU - Sutton, Jeannette AU - Wallace, Madison AB - It is critical that organizations deliver timely, effective communication about potential risks and life-saving information. The National Weather Service (NWS) developed a suite of messages known as “experimental graphic products” to be automatically distributed through their local official Twitter accounts at the onset of fast-moving, severe weather events such as tornadoes. However, recent research has suggested messages need to be carefully constructed for audiences to place attention to the content, remember the content, and later act in response to the content. The purpose of this study is to explore what people recall of the NWS Twitter message. We used an online survey instrument, distributed via Qualtrics, to investigate participant responses to three open-ended questions about the message. We performed a quantitative analysis to summarize the frequency of message features recorded by participants, and a qualitative analysis to identify themes that provide a deeper description of what was recalled. We found that participants encoded the hazard type, the time the message was sent and would expire, and the types of impacts that might occur. Graphic design cues elicited attention as they “stood out” to the participants. When asked about importance and what they would tell others, respondents described protective action, indicating participants may have activated prior knowledge of the threat, as it was not included in the message. Risk, disaster, and science communicators can draw guidance about communicating during a disaster. It provides a lens for researching message construction, and the importance of communicating protective action guidance during severe weather events. AN - noaa:73143 DO - https://doi.org/10.4148/1051-0834.2440 IS - 3 J2 - Journal of Applied Communications PB - Kansas State University PY - 2022 T2 - Journal of Applied Communications T2 - Journal of Applied Communications, 106(3) TI - Show Me and What Will I Remember? Exploring Recall in Response to NWS Tornado Warning Graphics VL - 106 UR - https://repository.library.noaa.gov/view/noaa/73143 ER -
Message Design Matters: An Experiment on Portrayal of Protective Action Guidance in Warning Messages for Three Hazards

Orton, Ginger ;

Fischer, Laura Morgan

2025 | Journal of Applied Communications, 109(1) | pdf

Risk communicators play a crucial role in informing individuals about approaching hazards and guiding them on how to respond effectively during different phases of disaster communication. Protective action guidance has been defined as the information people need to inform them of what to do to protect themselves in the face of a hazardous situation ...

04/24/2026

Title : Message Design Matters: An Experiment on Portrayal of Protective Action Guidance in Warning Messages for Three Hazards Personal Author(s) : Orton, Ginger;Fischer, Laura Morgan;Sutton, Jeannette;Huntsman, David; Published Date : 2025 Source : Journal of Applied Communications, 109(1) DOI : https://doi.org/10.4148/1051-0834.2550 Journal Title : Journal of Applied Communications Orton, Ginger et al. (2025). Message Design Matters: An Experiment on Portrayal of Protective Action Guidance in Warning Messages for Three Hazards. 109(1). https://doi.org/10.4148/1051-0834.2550 Orton, Ginger et al. "Message Design Matters: An Experiment on Portrayal of Protective Action Guidance in Warning Messages for Three Hazards" 109, no. 1 (2025), https://doi.org/10.4148/1051-0834.2550 Orton, Ginger et al. "Message Design Matters: An Experiment on Portrayal of Protective Action Guidance in Warning Messages for Three Hazards" vol. 109, no. 1, 2025, https://doi.org/10.4148/1051-0834.2550 Export RIS Citation Information. TY - AU - Orton, Ginger AU - Fischer, Laura Morgan AU - Sutton, Jeannette AU - Huntsman, David AB - Risk communicators play a crucial role in informing individuals about approaching hazards and guiding them on how to respond effectively during different phases of disaster communication. Protective action guidance has been defined as the information people need to inform them of what to do to protect themselves in the face of a hazardous situation. However, many social media messages disseminated by the National Weather Service do not include protective action guidance. Scholars have called for more research on the portrayal of protective action guidance in a message to prove which design best imparts protective action knowledge. To answer this call, a researcher-developed conceptual framework was used to explore how four portrayals of protective action guidance influence knowledge of protective actions (i.e., protective action literacy). We first describe individuals' perceptions of the appropriate protective actions to take when either a dust storm, snow squall, or tornado is approaching. Then, we report on changes in protective action literacy after exposure to a series of hazard warning messages with varying portrayals of protective action guidance. The study's results reveal important insights regarding the influence of protective action guidance portrayal in warning messages on participants’ protective action literacy. Participants' understanding of appropriate protective actions varied across hazards and was influenced by message type. This research highlights the importance of evidence-based message design, the need for comprehensive guidance for all hazards, and the role of agricultural communication in disaster preparedness. The study's findings can inform more effective disaster communication strategies and guide future research. AN - noaa:73142 DO - https://doi.org/10.4148/1051-0834.2550 IS - 1 J2 - Journal of Applied Communications PB - Kansas State University PY - 2025 T2 - Journal of Applied Communications T2 - Journal of Applied Communications, 109(1) TI - Message Design Matters: An Experiment on Portrayal of Protective Action Guidance in Warning Messages for Three Hazards VL - 109 UR - https://repository.library.noaa.gov/view/noaa/73142 ER -
Linking Survivor Stories to Forensic Engineering: How an Interscience Approach Reveals Opportunities for Reducing Tornado Vulnerability in Residential Structures

LaDue, Daphne S.

;

Roueche, David

2024 | Bulletin of the American Meteorological Society, 105(8), E1521-E1541 | pdf

When a tornado strikes a permanent or mobile/manufactured home, occupants are at risk of injury and death from blunt force trauma caused by debris-loaded winds and failure of the structure. Mechanisms for these failures have been studied for the past few decades and identified common weaknesses in the structural load path. Also under study in recen ...

04/24/2026

Title : Linking Survivor Stories to Forensic Engineering: How an Interscience Approach Reveals Opportunities for Reducing Tornado Vulnerability in Residential Structures Personal Author(s) : LaDue, Daphne S.;Roueche, David;Lombardo, Frank;Mayeux, Lara; Published Date : 2024 Source : Bulletin of the American Meteorological Society, 105(8), E1521-E1541 DOI : https://doi.org/10.1175/BAMS-D-23-0036.1 Journal Title : Bulletin of the American Meteorological Society LaDue, Daphne S. et al. (2024). Linking Survivor Stories to Forensic Engineering: How an Interscience Approach Reveals Opportunities for Reducing Tornado Vulnerability in Residential Structures. 105(8). https://doi.org/10.1175/BAMS-D-23-0036.1 LaDue, Daphne S. et al. "Linking Survivor Stories to Forensic Engineering: How an Interscience Approach Reveals Opportunities for Reducing Tornado Vulnerability in Residential Structures" 105, no. 8 (2024), https://doi.org/10.1175/BAMS-D-23-0036.1 LaDue, Daphne S. et al. "Linking Survivor Stories to Forensic Engineering: How an Interscience Approach Reveals Opportunities for Reducing Tornado Vulnerability in Residential Structures" vol. 105, no. 8, 2024, https://doi.org/10.1175/BAMS-D-23-0036.1 Export RIS Citation Information. TY - AU - LaDue, Daphne S. AU - Roueche, David AU - Lombardo, Frank AU - Mayeux, Lara AB - When a tornado strikes a permanent or mobile/manufactured home, occupants are at risk of injury and death from blunt force trauma caused by debris-loaded winds and failure of the structure. Mechanisms for these failures have been studied for the past few decades and identified common weaknesses in the structural load path. Also under study in recent decades, much has been learned about how people receive and understand warnings and determine how, when, and if they will shelter in advance. Recent research, for example, shows most people do not shelter until close to impact, after seeing, hearing, or feeling the approaching tornado. To advance beyond these innovations, a new, multidisciplinary approach was fielded in nine southeast U.S. tornadoes between 2019 and 2022. For each tornado, 1) wind engineering assessments documented near-surface wind fields, 2) structural engineering assessments documented the primary wind load path for each structure, and 3) social science interviews captured the survivor’s narrative and asked several follow-up questions to assure key items of interest were addressed in each interview. When possible, the team was multidisciplinary during the interview, enabling survivors to ask questions and better understand their experiences. Most survivors became aware of the approaching tornado with at least a few minutes of lead time, and most were able to reach a place of refuge. Most survivors recalled sensory experiences during the tornado, and about half could describe the direction or temporal sequences of damage. A case study of the Cookeville, Tennessee, tornado of 3 March 2020 illustrates the power of the integrated data assessment. AN - noaa:73141 DO - https://doi.org/10.1175/BAMS-D-23-0036.1 IS - 8 J2 - Bulletin of the American Meteorological Society PB - American Meteorological Society PY - 2024 T2 - Bulletin of the American Meteorological Society T2 - Bulletin of the American Meteorological Society, 105(8), E1521-E1541 TI - Linking Survivor Stories to Forensic Engineering: How an Interscience Approach Reveals Opportunities for Reducing Tornado Vulnerability in Residential Structures VL - 105 UR - https://repository.library.noaa.gov/view/noaa/73141 ER -
The Impact of the Brief Vulnerability Overview Tool on NWS and EM Operations and Communication in the Hazardous Weather Testbed

Saunders, Michelle E.

;

LaDue, Daphne S.

2025 | Weather and Forecasting, 40(11), 2425-2441 | pdf

A new impact-based decision support tool, the Brief Vulnerability Overview Tool (BVOT), was created to improve National Weather Service (NWS) meteorologists’ spatial situational awareness and prompt timely communication with core partners such as emergency managers (EMs). While inspired by observations of operations and NWS–EM communication, the to ...

04/24/2026

Title : The Impact of the Brief Vulnerability Overview Tool on NWS and EM Operations and Communication in the Hazardous Weather Testbed Personal Author(s) : Saunders, Michelle E.;LaDue, Daphne S.;Friedman, Jack R.;Marmo, Alex N.;Fenske, Daniel L.; Published Date : 2025 Source : Weather and Forecasting, 40(11), 2425-2441 DOI : https://doi.org/10.1175/WAF-D-24-0250.1 Journal Title : Weather and Forecasting Saunders, Michelle E. et al. (2025). The Impact of the Brief Vulnerability Overview Tool on NWS and EM Operations and Communication in the Hazardous Weather Testbed. 40(11). https://doi.org/10.1175/WAF-D-24-0250.1 Saunders, Michelle E. et al. "The Impact of the Brief Vulnerability Overview Tool on NWS and EM Operations and Communication in the Hazardous Weather Testbed" 40, no. 11 (2025), https://doi.org/10.1175/WAF-D-24-0250.1 Saunders, Michelle E. et al. "The Impact of the Brief Vulnerability Overview Tool on NWS and EM Operations and Communication in the Hazardous Weather Testbed" vol. 40, no. 11, 2025, https://doi.org/10.1175/WAF-D-24-0250.1 Export RIS Citation Information. TY - AU - Saunders, Michelle E. AU - LaDue, Daphne S. AU - Friedman, Jack R. AU - Marmo, Alex N. AU - Fenske, Daniel L. AB - A new impact-based decision support tool, the Brief Vulnerability Overview Tool (BVOT), was created to improve National Weather Service (NWS) meteorologists’ spatial situational awareness and prompt timely communication with core partners such as emergency managers (EMs). While inspired by observations of operations and NWS–EM communication, the tool merited study to understand how increased knowledge of vulnerabilities might impact the creation and delivery of NWS products and decision support, and how EMs would interpret and use the resulting forecasts and decision support. This next-generation approach to integrating meteorological innovations with a deeper understanding of societal needs and vulnerabilities was tested over eight experiment weeks in the NOAA Hazardous Weather Testbed from 2021 through 2022. Participants worked through weather cases in simulated operational environments, engaged in discussions, and completed surveys. Each of eight cases involved three time periods: 24–48 h before a severe weather event, 6–12 h before, and a 35-min period of active severe weather. BVOT was used most during active severe weather operations, where meteorologists used it as a situational awareness tool that enabled them to provide messaging about the threat of weather to specific vulnerabilities that were of concern to EMs. Meteorologists’ use of BVOT helped EMs do their jobs more effectively by giving them greater lead time to relay information, plan, respond, and recover. AN - noaa:73140 DO - https://doi.org/10.1175/WAF-D-24-0250.1 IS - 11 J2 - Weather and Forecasting PB - American Meteorological Society PY - 2025 T2 - Weather and Forecasting T2 - Weather and Forecasting, 40(11), 2425-2441 TI - The Impact of the Brief Vulnerability Overview Tool on NWS and EM Operations and Communication in the Hazardous Weather Testbed VL - 40 UR - https://repository.library.noaa.gov/view/noaa/73140 ER -
Redrawing Risks: How Professional Users Interpret and Use an Iteratively Redesigned Hurricane Threats and Impacts Graphic

Prestley, Robert

;

Morss, Rebecca

2025 | Weather, Climate, and Society, 17(4), 997-1010 | pdf

The National Weather Service and other weather industry partners increasingly use Hurricane Threats and Impacts (HTI) graphics to communicate the breadth of hazards and impacts associated with tropical cyclones. However, HTI graphics are often poorly designed and difficult to access, inhibiting their wider use during high-impact tropical cyclone ev ...

04/24/2026

Title : Redrawing Risks: How Professional Users Interpret and Use an Iteratively Redesigned Hurricane Threats and Impacts Graphic Personal Author(s) : Prestley, Robert;Morss, Rebecca;Majumdar, Sharanya J.;McNoldy, Brian;Millet, Barbara;Cairo, Alberto;Evans, Scotney D.; Published Date : 2025 Source : Weather, Climate, and Society, 17(4), 997-1010 DOI : https://doi.org/10.1175/WCAS-D-25-0069.1 Journal Title : Weather, Climate, and Society Prestley, Robert et al. (2025). Redrawing Risks: How Professional Users Interpret and Use an Iteratively Redesigned Hurricane Threats and Impacts Graphic. 17(4). https://doi.org/10.1175/WCAS-D-25-0069.1 Prestley, Robert et al. "Redrawing Risks: How Professional Users Interpret and Use an Iteratively Redesigned Hurricane Threats and Impacts Graphic" 17, no. 4 (2025), https://doi.org/10.1175/WCAS-D-25-0069.1 Prestley, Robert et al. "Redrawing Risks: How Professional Users Interpret and Use an Iteratively Redesigned Hurricane Threats and Impacts Graphic" vol. 17, no. 4, 2025, https://doi.org/10.1175/WCAS-D-25-0069.1 Export RIS Citation Information. TY - AU - Prestley, Robert AU - Morss, Rebecca AU - Majumdar, Sharanya J. AU - McNoldy, Brian AU - Millet, Barbara AU - Cairo, Alberto AU - Evans, Scotney D. AB - The National Weather Service and other weather industry partners increasingly use Hurricane Threats and Impacts (HTI) graphics to communicate the breadth of hazards and impacts associated with tropical cyclones. However, HTI graphics are often poorly designed and difficult to access, inhibiting their wider use during high-impact tropical cyclone events. In this study, we evaluated HTI graphics with broadcast meteorologists and emergency managers to understand how these professional users use and access HTI information. Additionally, we examine how these users perceive and use a prototype redesigned HTI graphic, created by our research team as part of a novel user-driven iterative design process that incorporates feedback from numerous stakeholders, best practices in visual design, and our team’s various interdisciplinary expertise. We demonstrate that professional users find HTI usable and actionable for their decision-making during tropical threats. Further, we find that these users appreciated the prototype redesigned HTI intuitively for its more “modern” feel, ease of use, and broader accessibility. However, these professional users also disagreed over aspects of the prototype HTI graphic’s design, such as the colors used, hazards represented, and the amount of text included in the graphic, suggesting that there is no “one-size-fits-all” approach to designing effective tropical cyclone risk visualizations. We thus suggest continued investment in user-driven iterative design approaches to understand and meet the needs of the weather industry’s various stakeholders when developing new or existing graphical products. AN - noaa:73139 DO - https://doi.org/10.1175/WCAS-D-25-0069.1 IS - 4 J2 - Weather, Climate, and Society PB - American Meteorological Society PY - 2025 T2 - Weather, Climate, and Society T2 - Weather, Climate, and Society, 17(4), 997-1010 TI - Redrawing Risks: How Professional Users Interpret and Use an Iteratively Redesigned Hurricane Threats and Impacts Graphic VL - 17 UR - https://repository.library.noaa.gov/view/noaa/73139 ER -
Subjective attribution, experiences, behaviors, and climate policy support during increasingly risky storms

Wong-Parodi, Gabrielle

;

Ng, Michelle

2026 | Cell Reports Sustainability, 3(3), 100628 | pdf

Subjective attribution—the perception that an extreme weather event is caused by climate change—is an important but understudied precursor to intended climate action. Our project advances understanding of how subjective attribution changes in response to exposure to specific extreme weather events, negative experiences that arise from that exposure ...

04/24/2026

Title : Subjective attribution, experiences, behaviors, and climate policy support during increasingly risky storms Personal Author(s) : Wong-Parodi, Gabrielle;Ng, Michelle;Herbert, Natalie;Prestley, Robert;Walpole, Hugh;Schumacher, Andrea;Morss, Rebecca;L. Demuth, Julie; Published Date : 2026 Source : Cell Reports Sustainability, 3(3), 100628 DOI : https://doi.org/10.1016/j.crsus.2025.100628 Journal Title : Cell Reports Sustainability Wong-Parodi, Gabrielle et al. (2026). Subjective attribution, experiences, behaviors, and climate policy support during increasingly risky storms. 3(3). https://doi.org/10.1016/j.crsus.2025.100628 Wong-Parodi, Gabrielle et al. "Subjective attribution, experiences, behaviors, and climate policy support during increasingly risky storms" 3, no. 3 (2026), https://doi.org/10.1016/j.crsus.2025.100628 Wong-Parodi, Gabrielle et al. "Subjective attribution, experiences, behaviors, and climate policy support during increasingly risky storms" vol. 3, no. 3, 2026, https://doi.org/10.1016/j.crsus.2025.100628 Export RIS Citation Information. TY - AU - Wong-Parodi, Gabrielle AU - Ng, Michelle AU - Herbert, Natalie AU - Prestley, Robert AU - Walpole, Hugh AU - Schumacher, Andrea AU - Morss, Rebecca AU - L. Demuth, Julie AB - Subjective attribution—the perception that an extreme weather event is caused by climate change—is an important but understudied precursor to intended climate action. Our project advances understanding of how subjective attribution changes in response to exposure to specific extreme weather events, negative experiences that arise from that exposure, and how changes in attribution importantly relate to climate action. Our findings suggest that people process information about their exposure to events and quickly determine what they attribute that event to, as well as how that attribution may inform their decisions to adapt to or mitigate climate change. Our findings suggest possible pathways for interventions to improve people’s responses to intensifying extreme weather events, including using these events as an opportunity to discuss climate change and ways that people can respond. AN - noaa:73138 DO - https://doi.org/10.1016/j.crsus.2025.100628 IS - 3 J2 - Cell Reports Sustainability PB - Elsevier BV PY - 2026 T2 - Cell Reports Sustainability T2 - Cell Reports Sustainability, 3(3), 100628 TI - Subjective attribution, experiences, behaviors, and climate policy support during increasingly risky storms VL - 3 UR - https://repository.library.noaa.gov/view/noaa/73138 ER -
Properties of Cold Pools from PERiLS 2022–23

Silcott, Miranda K. ;

Parker, Matthew D.

2025 | Monthly Weather Review, 153(10), 2085-2106 | pdf

Cold pools play a range of important roles in quasi-linear convective systems (QLCSs), including maintenance via the development of new convective cells as well as baroclinic generation of horizontal vorticity. Although a number of QLCS cold pools have been characterized in the literature using one or a few sensors, their variability (both internal ...

04/24/2026

Title : Properties of Cold Pools from PERiLS 2022–23 Personal Author(s) : Silcott, Miranda K.;Parker, Matthew D.;Kosiba, Karen A.;Nesbitt, Stephen W.;Trapp, Robert J.;Wurman, Joshua;Weiss, Christopher C.; Published Date : 2025 Source : Monthly Weather Review, 153(10), 2085-2106 DOI : https://doi.org/10.1175/MWR-D-24-0280.1 Journal Title : Monthly Weather Review Silcott, Miranda K. et al. (2025). Properties of Cold Pools from PERiLS 2022–23. 153(10). https://doi.org/10.1175/MWR-D-24-0280.1 Silcott, Miranda K. et al. "Properties of Cold Pools from PERiLS 2022–23" 153, no. 10 (2025), https://doi.org/10.1175/MWR-D-24-0280.1 Silcott, Miranda K. et al. "Properties of Cold Pools from PERiLS 2022–23" vol. 153, no. 10, 2025, https://doi.org/10.1175/MWR-D-24-0280.1 Export RIS Citation Information. TY - AU - Silcott, Miranda K. AU - Parker, Matthew D. AU - Kosiba, Karen A. AU - Nesbitt, Stephen W. AU - Trapp, Robert J. AU - Wurman, Joshua AU - Weiss, Christopher C. AB - Cold pools play a range of important roles in quasi-linear convective systems (QLCSs), including maintenance via the development of new convective cells as well as baroclinic generation of horizontal vorticity. Although a number of QLCS cold pools have been characterized in the literature using one or a few sensors, their variability (both internally and across a range of environments) has still not been widely studied. This gap in knowledge extends particularly to high-shear low-CAPE (HSLC) convective environments common to the cool season in the southeastern United States, where the Propagation, Evolution, and Rotation in Linear Storms (PERiLS) field campaign was focused. PERiLS specifically targeted environmental and storm-scale processes in QLCSs, including their cold pools. Our analysis focuses on the heterogeneity and temporal variability of cold pools across short time and spatial scales using numerous surface and sounding observations across five PERiLS QLCSs. The PERiLS cold pools are generally weaker than those previously studied in warm-season, midlatitude QLCSs, likely due to the lower CAPE and higher relative humidity values common to HSLC environments during PERiLS. Nevertheless, the distributions of most PERiLS cold pool variables at least partially overlap with those of previously studied QLCSs. The median PERiLS measurement reveals a cold pool that is ≈2.5 km deep, having a surface temperature decrease of ≈−6°C, and a peak outflow wind gust of ≈13 m s−1. In the spirit of a “cold pool audit,” we present the internal and case-to-case variability of these particularly well-observed QLCSs. AN - noaa:73137 DO - https://doi.org/10.1175/MWR-D-24-0280.1 IS - 10 J2 - Monthly Weather Review PB - American Meteorological Society PY - 2025 T2 - Monthly Weather Review T2 - Monthly Weather Review, 153(10), 2085-2106 TI - Properties of Cold Pools from PERiLS 2022–23 VL - 153 UR - https://repository.library.noaa.gov/view/noaa/73137 ER -
Snow-to-Liquid Ratio Prediction over the Contiguous United States Using Machine Learning

Pletcher, Michael D.

;

Veals, Peter G.

2026 | Weather and Forecasting, 41(2), 317-338 | pdf

Winter storms have widespread impacts across the contiguous United States (CONUS), resulting in travel and economic disruptions, loss of life, and damage to property and infrastructure. Snow-to-liquid ratio (SLR), the ratio of new (i.e., freshly fallen) snow to liquid precipitation equivalent, is used operationally to forecast snowfall amount durin ...

04/24/2026

Title : Snow-to-Liquid Ratio Prediction over the Contiguous United States Using Machine Learning Personal Author(s) : Pletcher, Michael D.;Veals, Peter G.;Chase, Randy J.;Hilberg, Steven D.;Newman, Noah;Rosenow, Andrew A.;Steenburgh, W. James; Published Date : 2026 Source : Weather and Forecasting, 41(2), 317-338 DOI : https://doi.org/10.1175/WAF-D-25-0124.1 Journal Title : Weather and Forecasting Pletcher, Michael D. et al. (2026). Snow-to-Liquid Ratio Prediction over the Contiguous United States Using Machine Learning. 41(2). https://doi.org/10.1175/WAF-D-25-0124.1 Pletcher, Michael D. et al. "Snow-to-Liquid Ratio Prediction over the Contiguous United States Using Machine Learning" 41, no. 2 (2026), https://doi.org/10.1175/WAF-D-25-0124.1 Pletcher, Michael D. et al. "Snow-to-Liquid Ratio Prediction over the Contiguous United States Using Machine Learning" vol. 41, no. 2, 2026, https://doi.org/10.1175/WAF-D-25-0124.1 Export RIS Citation Information. TY - AU - Pletcher, Michael D. AU - Veals, Peter G. AU - Chase, Randy J. AU - Hilberg, Steven D. AU - Newman, Noah AU - Rosenow, Andrew A. AU - Steenburgh, W. James AB - Winter storms have widespread impacts across the contiguous United States (CONUS), resulting in travel and economic disruptions, loss of life, and damage to property and infrastructure. Snow-to-liquid ratio (SLR), the ratio of new (i.e., freshly fallen) snow to liquid precipitation equivalent, is used operationally to forecast snowfall amount during winter storms. However, no clear best prediction method for SLR has been established, and some operational SLR prediction methods were developed for specific regions, potentially limiting their utility for CONUS-wide applications. Using Community Collaborative Rain, Hail and Snow Network (CoCoRaHS) snowfall observations, station geographic information, and fifth generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis (ERA5) vertical profiles of atmospheric variables, we developed a random forest (RF)-based algorithm for predicting SLR across the CONUS. SLR forecasts and quantitative snowfall forecasts (QSFs) based on this algorithm were then derived from the NOAA High-Resolution Rapid Refresh (HRRR). The resulting RF SLR mean absolute error (MAE) was 2.92 across the CONUS compared to MAEs for current operational methods of 3.51–4.76. Improvements were also seen in QSF. Additionally, the RF outperformed operational SLR methods within individual regional snow climates. Despite these improvements, there were situations when the RF struggled, such as high (>20) and low (<5) SLR events that featured relatively cold and calm and warm and windy environments, respectively, in the eastern CONUS. The use of CoCoRaHS observations for training provides a template for improving snowfall forecasts at a CONUS-wide scale with the RF providing an algorithm for improving SLR prediction for operational applications. AN - noaa:73136 DO - https://doi.org/10.1175/WAF-D-25-0124.1 IS - 2 J2 - Weather and Forecasting PB - American Meteorological Society PY - 2026 T2 - Weather and Forecasting T2 - Weather and Forecasting, 41(2), 317-338 TI - Snow-to-Liquid Ratio Prediction over the Contiguous United States Using Machine Learning VL - 41 UR - https://repository.library.noaa.gov/view/noaa/73136 ER -
Assessing the Impact of the Valid-Time-Shifting Method on the EnVar Analysis of the Storm Environment for Convection Initiation Cases

Li, Tsung-Han

;

Gasperoni, Nicholas

2025 | Weather and Forecasting, 40(10), 2003-2022 | pdf

The valid-time-shifting (VTS) method was implemented to increase the background ensemble size for assimilating conventional in situ observations within a convection-allowing ensemble-variational (EnVar) analysis and forecast system. The focus of the study is to examine the impact of VTS on the analysis of the storm environment for convection initia ...

04/24/2026

Title : Assessing the Impact of the Valid-Time-Shifting Method on the EnVar Analysis of the Storm Environment for Convection Initiation Cases Personal Author(s) : Li, Tsung-Han;Gasperoni, Nicholas;Wang, Xuguang;Wang, Yongming; Published Date : 2025 Source : Weather and Forecasting, 40(10), 2003-2022 DOI : https://doi.org/10.1175/WAF-D-24-0096.1 Journal Title : Weather and Forecasting Li, Tsung-Han et al. (2025). Assessing the Impact of the Valid-Time-Shifting Method on the EnVar Analysis of the Storm Environment for Convection Initiation Cases. 40(10). https://doi.org/10.1175/WAF-D-24-0096.1 Li, Tsung-Han et al. "Assessing the Impact of the Valid-Time-Shifting Method on the EnVar Analysis of the Storm Environment for Convection Initiation Cases" 40, no. 10 (2025), https://doi.org/10.1175/WAF-D-24-0096.1 Li, Tsung-Han et al. "Assessing the Impact of the Valid-Time-Shifting Method on the EnVar Analysis of the Storm Environment for Convection Initiation Cases" vol. 40, no. 10, 2025, https://doi.org/10.1175/WAF-D-24-0096.1 Export RIS Citation Information. TY - AU - Li, Tsung-Han AU - Gasperoni, Nicholas AU - Wang, Xuguang AU - Wang, Yongming AB - The valid-time-shifting (VTS) method was implemented to increase the background ensemble size for assimilating conventional in situ observations within a convection-allowing ensemble-variational (EnVar) analysis and forecast system. The focus of the study is to examine the impact of VTS on the analysis of the storm environment for convection initiation (CI) cases. The VTS method increases the background ensemble size cost-effectively by shifting the background ensemble initialized at the same time but valid at different times. Three CI cases in May 2019 were chosen. Three sets of experiments were designed to reveal the impact of VTS, all compared to the same 36-member ensemble experiments without VTS (noVTS-36). The first two sets of VTS experiments triples the background ensembles to 108 (VTS36x3) and triples the background members to 36 on a reduced-base 12-member EnVar (VTS12x3). The third VTS experiment is designed to have the same computational cost as noVTS-36 (VTS24x3). Objective results from all three cases show that VTS12x3 achieves similar analysis accuracy and statistically indistinguishable conventional observation variable forecast errors and reflectivity forecast skill for light/medium thresholds compared to noVTS-36, at 73% of the computational cost. Tripling the base ensemble size (VTS36x3) achieves the highest forecast improvement throughout the 9-h evaluation period compared to noVTS-36, at a fraction of the added costs (89%). With a computational cost nearly the same as noVTS-36, VTS24x3 achieves improved environmental analyses, significantly lower forecast error of conventional observation variables, and noteworthy subjective forecast improvements with slight objective skill improvements at light and medium reflectivity thresholds. AN - noaa:73135 DO - https://doi.org/10.1175/WAF-D-24-0096.1 IS - 10 J2 - Weather and Forecasting PB - American Meteorological Society PY - 2025 T2 - Weather and Forecasting T2 - Weather and Forecasting, 40(10), 2003-2022 TI - Assessing the Impact of the Valid-Time-Shifting Method on the EnVar Analysis of the Storm Environment for Convection Initiation Cases VL - 40 UR - https://repository.library.noaa.gov/view/noaa/73135 ER -
Improving CFSv2 Snow Water Equivalent Forecasts in the Colorado River Basin with Generalized Analog Regression Downscaling

Ratterman, Cody

;

Zhang, Wei

2025 | Weather and Forecasting, 40(11), 2381-2389 | pdf

Snowpack is the most important water resource for the Colorado River basin (CRB), along with the Great Salt Lake (GSL) basin. Predicting snowpack in this region months ahead presents grand challenges to scientific and operational communities due to a lack of methods and products for snowpack forecasts in the Colorado River basin. Here, we apply the ...

04/24/2026

Title : Improving CFSv2 Snow Water Equivalent Forecasts in the Colorado River Basin with Generalized Analog Regression Downscaling Personal Author(s) : Ratterman, Cody;Zhang, Wei;Affram, Grace;Bean, Brennan; Published Date : 2025 Source : Weather and Forecasting, 40(11), 2381-2389 DOI : https://doi.org/10.1175/WAF-D-23-0196.1 Journal Title : Weather and Forecasting Ratterman, Cody et al. (2025). Improving CFSv2 Snow Water Equivalent Forecasts in the Colorado River Basin with Generalized Analog Regression Downscaling. 40(11). https://doi.org/10.1175/WAF-D-23-0196.1 Ratterman, Cody et al. "Improving CFSv2 Snow Water Equivalent Forecasts in the Colorado River Basin with Generalized Analog Regression Downscaling" 40, no. 11 (2025), https://doi.org/10.1175/WAF-D-23-0196.1 Ratterman, Cody et al. "Improving CFSv2 Snow Water Equivalent Forecasts in the Colorado River Basin with Generalized Analog Regression Downscaling" vol. 40, no. 11, 2025, https://doi.org/10.1175/WAF-D-23-0196.1 Export RIS Citation Information. TY - AU - Ratterman, Cody AU - Zhang, Wei AU - Affram, Grace AU - Bean, Brennan AB - Snowpack is the most important water resource for the Colorado River basin (CRB), along with the Great Salt Lake (GSL) basin. Predicting snowpack in this region months ahead presents grand challenges to scientific and operational communities due to a lack of methods and products for snowpack forecasts in the Colorado River basin. Here, we apply the generalized analog regression downscaling (GARD) method to snow water equivalent in the Climate Forecast System, version 2 (CFSv2), model of NOAA (∼100-km atmosphere component) along with the benchmarking 4-km National Snow and Ice Data Center (NSIDC) snow water equivalent (SWE) data. We train GARD with CFSv2 hindcasts, followed by testing the model using the most recent water years 2020–21. The forecasting results based on GARD outperform CFSv2 in terms of common evaluation metrics such as seasonal bias and root-mean-square error across lead months 1–4, especially in the high-elevation areas of the CRB including the Wasatch, Uinta, and Rocky Mountain ranges. The research findings are valuable for decision-makers in these regions for managing water resources and protecting the Colorado River and the Great Salt Lake. AN - noaa:73134 DO - https://doi.org/10.1175/WAF-D-23-0196.1 IS - 11 J2 - Weather and Forecasting PB - American Meteorological Society PY - 2025 T2 - Weather and Forecasting T2 - Weather and Forecasting, 40(11), 2381-2389 TI - Improving CFSv2 Snow Water Equivalent Forecasts in the Colorado River Basin with Generalized Analog Regression Downscaling VL - 40 UR - https://repository.library.noaa.gov/view/noaa/73134 ER -
Application of a Two-Step Space–Time EOF Statistical Postprocessing Algorithm to Mitigate Subseasonal 200-hPa Geopotential Height Forecast Error

Stikeleather, William D.

;

Roundy, Paul E.

2024 | Weather and Forecasting, 39(11), 1621-1634 | pdf

The time-extended empirical orthogonal function (EEOF) patterns of error developed in a companion paper are applied in this study for model data postprocessing. Projecting forecast anomalies from the model seasonal cycle from GEFSv12 outputs onto these EEOF patterns reconstructs the error principal components (PCs) in a manner that can be applied i ...

04/24/2026

Title : Application of a Two-Step Space–Time EOF Statistical Postprocessing Algorithm to Mitigate Subseasonal 200-hPa Geopotential Height Forecast Error Personal Author(s) : Stikeleather, William D.;Roundy, Paul E.; Published Date : 2024 Source : Weather and Forecasting, 39(11), 1621-1634 DOI : https://doi.org/10.1175/WAF-D-23-0168.1 Journal Title : Weather and Forecasting Stikeleather, William D. and Roundy, Paul E. (2024). Application of a Two-Step Space–Time EOF Statistical Postprocessing Algorithm to Mitigate Subseasonal 200-hPa Geopotential Height Forecast Error. 39(11). https://doi.org/10.1175/WAF-D-23-0168.1 Stikeleather, William D. and Roundy, Paul E. "Application of a Two-Step Space–Time EOF Statistical Postprocessing Algorithm to Mitigate Subseasonal 200-hPa Geopotential Height Forecast Error" 39, no. 11 (2024), https://doi.org/10.1175/WAF-D-23-0168.1 Stikeleather, William D. and Roundy, Paul E. "Application of a Two-Step Space–Time EOF Statistical Postprocessing Algorithm to Mitigate Subseasonal 200-hPa Geopotential Height Forecast Error" vol. 39, no. 11, 2024, https://doi.org/10.1175/WAF-D-23-0168.1 Export RIS Citation Information. TY - AU - Stikeleather, William D. AU - Roundy, Paul E. AB - The time-extended empirical orthogonal function (EEOF) patterns of error developed in a companion paper are applied in this study for model data postprocessing. Projecting forecast anomalies from the model seasonal cycle from GEFSv12 outputs onto these EEOF patterns reconstructs the error principal components (PCs) in a manner that can be applied in real time. When these reconstructed error anomalies are compared with the original GEFSv12 200-hPa geopotential height (Z200) reforecast error anomalies, the projected and validation error signals tend to align temporally. When distributed globally, projection and validation error anomalies have statistically significant positive Pearson correlation coefficients with each other at most grid points outside of the tropics. Categorical Heidke skill score (HSS) analysis reaffirms that by lead day 16 of a forecast, the algorithm skillfully predicts systematic errors for locations outside of the tropics. Hemispheric winter demonstrates that the highest magnitude HSS values are in the high latitudes, illustrating the underlying seasonality of Z200 behavior and predictability. On average, wintertime HSS values hover around 20%, with high-latitude locations exceeding mean values of 40%. Comparatively, summertime values generally exceed 10% improvement outside of the tropics. High-latitude storm-track regions, such as the North Atlantic, North Pacific, and South Pacific, contain the most Z200 variance in the globe and the highest HSS values. This algorithm will be applied to real-time forecasts and additional variables in future work, with the end goal of implementation into the NOAA-CPC subseasonal forecasts. AN - noaa:73133 DO - https://doi.org/10.1175/WAF-D-23-0168.1 IS - 11 J2 - Weather and Forecasting PB - American Meteorological Society PY - 2024 T2 - Weather and Forecasting T2 - Weather and Forecasting, 39(11), 1621-1634 TI - Application of a Two-Step Space–Time EOF Statistical Postprocessing Algorithm to Mitigate Subseasonal 200-hPa Geopotential Height Forecast Error VL - 39 UR - https://repository.library.noaa.gov/view/noaa/73133 ER -
Development of a Two-Step EOF Statistical Postprocessing Algorithm to Identify Patterns of Systematic Error and Variance within GEFSv12 Reforecasts

Stikeleather, William D.

;

Roundy, Paul E.

2024 | Weather and Forecasting, 39(11), 1605-1620 | pdf

Analysis of seasonally varying signals of model error biases, as well as the diagnosis of space–time patterns of synoptic error, here is accomplished through the development of a statistical postprocessing algorithm based on time-extended empirical orthogonal functions (EEOFs) built on patterns of variance. This work analyzes GEFSv12 200-hPa geopot ...

04/24/2026

Title : Development of a Two-Step EOF Statistical Postprocessing Algorithm to Identify Patterns of Systematic Error and Variance within GEFSv12 Reforecasts Personal Author(s) : Stikeleather, William D.;Roundy, Paul E.; Published Date : 2024 Source : Weather and Forecasting, 39(11), 1605-1620 DOI : https://doi.org/10.1175/WAF-D-23-0167.1 Journal Title : Weather and Forecasting Stikeleather, William D. and Roundy, Paul E. (2024). Development of a Two-Step EOF Statistical Postprocessing Algorithm to Identify Patterns of Systematic Error and Variance within GEFSv12 Reforecasts. 39(11). https://doi.org/10.1175/WAF-D-23-0167.1 Stikeleather, William D. and Roundy, Paul E. "Development of a Two-Step EOF Statistical Postprocessing Algorithm to Identify Patterns of Systematic Error and Variance within GEFSv12 Reforecasts" 39, no. 11 (2024), https://doi.org/10.1175/WAF-D-23-0167.1 Stikeleather, William D. and Roundy, Paul E. "Development of a Two-Step EOF Statistical Postprocessing Algorithm to Identify Patterns of Systematic Error and Variance within GEFSv12 Reforecasts" vol. 39, no. 11, 2024, https://doi.org/10.1175/WAF-D-23-0167.1 Export RIS Citation Information. TY - AU - Stikeleather, William D. AU - Roundy, Paul E. AB - Analysis of seasonally varying signals of model error biases, as well as the diagnosis of space–time patterns of synoptic error, here is accomplished through the development of a statistical postprocessing algorithm based on time-extended empirical orthogonal functions (EEOFs) built on patterns of variance. This work analyzes GEFSv12 200-hPa geopotential height (Z200) model error against ERA5 reanalysis data. The mean-square error variance between GEFSv12 reforecast and ERA5 grows rapidly after day 7 of a forecast and continues to increase through the end of the 16-day forecast period. At lead time 16, the largest variance occurs in mid- to high-latitude oceanic storm tracks. Variance is highest during hemispheric winter when baroclinic energy is abundant. The seasonal cycle of error shows largest anomalies in the high latitudes during hemispheric winter. After running the titular two-step, space–time EEOF algorithm, a standardized spatial eigenspectrum shows that eigenvalues increase at longer lead times after decreasing in the medium range, demonstrating that the algorithm extracts large-scale signals of systematic error in the long range. Leading wintertime space–time eigenmode pairs include high-latitude blocking structures and Rossby wave trains. Results suggest that the large-scale systematic errors in GEFSv12 Z200 initiate in part from inaccurate representations of phase speeds of atmospheric waves in the polar jet. AN - noaa:73132 DO - https://doi.org/10.1175/WAF-D-23-0167.1 IS - 11 J2 - Weather and Forecasting PB - American Meteorological Society PY - 2024 T2 - Weather and Forecasting T2 - Weather and Forecasting, 39(11), 1605-1620 TI - Development of a Two-Step EOF Statistical Postprocessing Algorithm to Identify Patterns of Systematic Error and Variance within GEFSv12 Reforecasts VL - 39 UR - https://repository.library.noaa.gov/view/noaa/73132 ER -
Direct Assimilation of GOES-16 ABI All-Sky Radiances in HAFS Self-Cycled Dual-Resolution 3DEnVar System: System Description and a Case Study of Hurricane Laura (2020)

Yang, Yue

;

Wang, Xuguang

2026 | Weather and Forecasting, 41(1), 187-203 | pdf

Compared to utilizing temperature and mixing ratios of water vapor and hydrometeors as state variables (Standard_state), the direct assimilation of GOES-16 Advanced Baseline Imager (ABI) channel-10 all-sky radiances is advanced by additionally including brightness temperature (BT) as a state variable (BT_state) within the Hurricane Analysis and For ...

04/24/2026

Title : Direct Assimilation of GOES-16 ABI All-Sky Radiances in HAFS Self-Cycled Dual-Resolution 3DEnVar System: System Description and a Case Study of Hurricane Laura (2020) Personal Author(s) : Yang, Yue;Wang, Xuguang; Published Date : 2026 Source : Weather and Forecasting, 41(1), 187-203 DOI : https://doi.org/10.1175/WAF-D-25-0055.1 Journal Title : Weather and Forecasting Yang, Yue and Wang, Xuguang (2026). Direct Assimilation of GOES-16 ABI All-Sky Radiances in HAFS Self-Cycled Dual-Resolution 3DEnVar System: System Description and a Case Study of Hurricane Laura (2020). 41(1). https://doi.org/10.1175/WAF-D-25-0055.1 Yang, Yue and Wang, Xuguang "Direct Assimilation of GOES-16 ABI All-Sky Radiances in HAFS Self-Cycled Dual-Resolution 3DEnVar System: System Description and a Case Study of Hurricane Laura (2020)" 41, no. 1 (2026), https://doi.org/10.1175/WAF-D-25-0055.1 Yang, Yue and Wang, Xuguang "Direct Assimilation of GOES-16 ABI All-Sky Radiances in HAFS Self-Cycled Dual-Resolution 3DEnVar System: System Description and a Case Study of Hurricane Laura (2020)" vol. 41, no. 1, 2026, https://doi.org/10.1175/WAF-D-25-0055.1 Export RIS Citation Information. TY - AU - Yang, Yue AU - Wang, Xuguang AB - Compared to utilizing temperature and mixing ratios of water vapor and hydrometeors as state variables (Standard_state), the direct assimilation of GOES-16 Advanced Baseline Imager (ABI) channel-10 all-sky radiances is advanced by additionally including brightness temperature (BT) as a state variable (BT_state) within the Hurricane Analysis and Forecast System (HAFS) self-cycled dual-resolution three-dimensional ensemble–variational (3DEnVar) data assimilation (DA) system. With a focus on the rapid intensification (RI) predictions for Hurricane Laura (2020), the ABI all-sky radiances and operational observations are simultaneously assimilated during the pre-RI to RI period. Statistical comparisons across multiple DA cycles demonstrate the superiority of BT_state over Standard_state in terms of objective alignment with observations for background, analyses, and forecasts. Compared to Standard_state, the closer fit of BT_state to observations benefits from better convergence and faster variational minimization. The performances of the background, analyses, and forecasts from Standard_state and BT_state are verified subjectively against various observations. During the DA period, the background and analysis from BT_state outperform Standard_state in capturing the storm size, surrounding clear-sky areas, and the wind field structure within the storm region. Additionally, BT_state yields higher forecast skill than Standard_state for the intensity, track, and main structural features of Laura. Detailed diagnostics suggest that the enhanced thermodynamic structure analysis in BT_state facilitates the RI prediction, and the improved large-scale environment analysis in BT_state contributes to the accurate track prediction. AN - noaa:73131 DO - https://doi.org/10.1175/WAF-D-25-0055.1 IS - 1 J2 - Weather and Forecasting PB - American Meteorological Society PY - 2026 T2 - Weather and Forecasting T2 - Weather and Forecasting, 41(1), 187-203 TI - Direct Assimilation of GOES-16 ABI All-Sky Radiances in HAFS Self-Cycled Dual-Resolution 3DEnVar System: System Description and a Case Study of Hurricane Laura (2020) VL - 41 UR - https://repository.library.noaa.gov/view/noaa/73131 ER -
Flow-Dependent Evaluation and Training of Random Forest–Based Probabilistic Forecasts of Severe Weather Hazards

Shearer, Andrew

;

Johnson, Aaron

2025 | Weather and Forecasting, 40(11), 2357-2379 | pdf

There has been an increasing interest in recent years in the use of machine learning (ML) algorithms such as random forests (RFs) in the context of severe weather prediction. However, there is a need to better understand the impacts of large-scale flow patterns on RF model performance to further improve their use of multiscale information. This wor ...

04/24/2026

Title : Flow-Dependent Evaluation and Training of Random Forest–Based Probabilistic Forecasts of Severe Weather Hazards Personal Author(s) : Shearer, Andrew;Johnson, Aaron;Wang, Xuguang; Published Date : 2025 Source : Weather and Forecasting, 40(11), 2357-2379 DOI : https://doi.org/10.1175/waf-d-24-0204.1 Journal Title : Weather and Forecasting Shearer, Andrew et al. (2025). Flow-Dependent Evaluation and Training of Random Forest–Based Probabilistic Forecasts of Severe Weather Hazards. 40(11). https://doi.org/10.1175/waf-d-24-0204.1 Shearer, Andrew and Johnson, Aaron and Wang, Xuguang "Flow-Dependent Evaluation and Training of Random Forest–Based Probabilistic Forecasts of Severe Weather Hazards" 40, no. 11 (2025), https://doi.org/10.1175/waf-d-24-0204.1 Shearer, Andrew et al. "Flow-Dependent Evaluation and Training of Random Forest–Based Probabilistic Forecasts of Severe Weather Hazards" vol. 40, no. 11, 2025, https://doi.org/10.1175/waf-d-24-0204.1 Export RIS Citation Information. TY - AU - Shearer, Andrew AU - Johnson, Aaron AU - Wang, Xuguang AB - There has been an increasing interest in recent years in the use of machine learning (ML) algorithms such as random forests (RFs) in the context of severe weather prediction. However, there is a need to better understand the impacts of large-scale flow patterns on RF model performance to further improve their use of multiscale information. This work leverages real-time forecasts from convection-allowing Finite-Volume Cubed-Sphere Dynamical Core (FV3)-based ensemble forecasts produced by the University of Oklahoma Multiscale Data Assimilation and Predictability Laboratory during the Hazardous Weather Testbed (HWT) Spring Forecasting Experiments. Results show that by using an RF trained on all forecast cases, forecast cases that have relatively high importance for certain predictors have different discernible flow patterns compared to low-importance forecast cases for the same predictors through composite differences in different environmental variables. Maximum updraft helicity storm attribute predictors were associated with strong synoptic ascent, u500 had compact shortwaves within northwesterly flow, and MUCAPE was associated with forcing displaced north of the region of severe weather. RF models trained on forecast cases with similar domain-averaged CAPE/shear were statistically more skillful than the baseline model trained irrespective of CAPE/shear patterns in forecasting the occurrence of severe weather. However, selecting training forecast cases based on spatial patterns or principal components of CAPE/shear using EOF analysis did not further improve the RF ability to forecast severe weather compared to the baseline model. The benefits of training on forecast cases based on domain-averaged CAPE/shear were maintained, and some of the benefits of training based on spatial patterns of CAPE/shear were maintained as the sample size increased. AN - noaa:73130 DO - https://doi.org/10.1175/waf-d-24-0204.1 IS - 11 J2 - Weather and Forecasting PB - American Meteorological Society PY - 2025 T2 - Weather and Forecasting T2 - Weather and Forecasting, 40(11), 2357-2379 TI - Flow-Dependent Evaluation and Training of Random Forest–Based Probabilistic Forecasts of Severe Weather Hazards VL - 40 UR - https://repository.library.noaa.gov/view/noaa/73130 ER -
The effects of boundary layer vertical turbulent diffusivity on the tropical cyclone intensity

Ye, Lei ;

Li, Yubin

2023 | Atmospheric Research, 295, 106994 | pdf

The sensitivity of the simulated intensification of Typhoon Mangkhut (2018) to boundary layer turbulent diffusivity (Km) is investigated through a series of numerical simulations using the modified Km from the Yonsei-University (YSU) planetary boundary layer (PBL) scheme in the Weather Research and Forecasting (WRF) model. Two intensity metrics, na ...

04/24/2026

Title : The effects of boundary layer vertical turbulent diffusivity on the tropical cyclone intensity Personal Author(s) : Ye, Lei;Li, Yubin;Zhu, Ping;Gao, Zhiqiu; Published Date : 2023 Source : Atmospheric Research, 295, 106994 DOI : https://doi.org/10.1016/j.atmosres.2023.106994 Journal Title : Atmospheric Research Ye, Lei et al. (2023). The effects of boundary layer vertical turbulent diffusivity on the tropical cyclone intensity. 295https://doi.org/10.1016/j.atmosres.2023.106994 Ye, Lei et al. "The effects of boundary layer vertical turbulent diffusivity on the tropical cyclone intensity" 295 (2023), https://doi.org/10.1016/j.atmosres.2023.106994 Ye, Lei et al. "The effects of boundary layer vertical turbulent diffusivity on the tropical cyclone intensity" vol. 295, 2023, https://doi.org/10.1016/j.atmosres.2023.106994 Export RIS Citation Information. TY - AU - Ye, Lei AU - Li, Yubin AU - Zhu, Ping AU - Gao, Zhiqiu AB - The sensitivity of the simulated intensification of Typhoon Mangkhut (2018) to boundary layer turbulent diffusivity (Km) is investigated through a series of numerical simulations using the modified Km from the Yonsei-University (YSU) planetary boundary layer (PBL) scheme in the Weather Research and Forecasting (WRF) model. Two intensity metrics, namely grid-point and area-averaged metrics, were employed to evaluate the simulations. The results indicate that a smaller Km tends to result in a smaller grid-point minimum central sea level pressure (MSLP), while producing a larger area-averaged MSLP and smaller area-averaged maximum 10 m wind speed (VMAX), which is consistent with a weaker radial inflow averaged over the area of a 500 km radius. Furthermore, the surface latent heat flux exhibits a nearly linear relationship with Km throughout the simulation. Overall, a larger Km tends to produce a greater diabatic heating rate, although this relationship is not as clear as that between Km and latent heat flux due to the presence of spontaneous asymmetric convective eddy features. Moreover, since a larger Km tends to result in a larger 10 m tangential wind, the size of a tropical cyclone (TC) defined by the radius at which 10 m tangential wind speed becomes 10 m s−1 shows a positive linear relationship with Km. AN - noaa:73129 DO - https://doi.org/10.1016/j.atmosres.2023.106994 J2 - Atmospheric Research PB - Elsevier BV PY - 2023 T2 - Atmospheric Research T2 - Atmospheric Research, 295, 106994 TI - The effects of boundary layer vertical turbulent diffusivity on the tropical cyclone intensity VL - 295 UR - https://repository.library.noaa.gov/view/noaa/73129 ER -
A Framework for Convective-Scale Observing System Simulation Experiments Using Ensembles

Gibbs, Jeremy A.

;

Gebauer, Joshua G.

2025 | Weather and Forecasting, 40(10), 2147-2157 | pdf

Convection-allowing models are used to predict the evolution of severe weather phenomena in the atmosphere. These models are sensitive to errors in the numerical environment used to initialize their forecast integration. Data assimilation methods can help overcome these errors but are often limited by sparse observational coverage. Numerous novel o ...

04/24/2026

Title : A Framework for Convective-Scale Observing System Simulation Experiments Using Ensembles Personal Author(s) : Gibbs, Jeremy A.;Gebauer, Joshua G.;Wicker, Louis J.;Ammon, Matthew B.;Stratman, Derek R.; Published Date : 2025 Source : Weather and Forecasting, 40(10), 2147-2157 DOI : https://doi.org/10.1175/WAF-D-24-0153.1 Journal Title : Weather and Forecasting Gibbs, Jeremy A. et al. (2025). A Framework for Convective-Scale Observing System Simulation Experiments Using Ensembles. 40(10). https://doi.org/10.1175/WAF-D-24-0153.1 Gibbs, Jeremy A. et al. "A Framework for Convective-Scale Observing System Simulation Experiments Using Ensembles" 40, no. 10 (2025), https://doi.org/10.1175/WAF-D-24-0153.1 Gibbs, Jeremy A. et al. "A Framework for Convective-Scale Observing System Simulation Experiments Using Ensembles" vol. 40, no. 10, 2025, https://doi.org/10.1175/WAF-D-24-0153.1 Export RIS Citation Information. TY - AU - Gibbs, Jeremy A. AU - Gebauer, Joshua G. AU - Wicker, Louis J. AU - Ammon, Matthew B. AU - Stratman, Derek R. AB - Convection-allowing models are used to predict the evolution of severe weather phenomena in the atmosphere. These models are sensitive to errors in the numerical environment used to initialize their forecast integration. Data assimilation methods can help overcome these errors but are often limited by sparse observational coverage. Numerous novel observation platforms are currently available that promise to close these coverage gaps, but they have not yet been widely assimilated into weather models. Observing system simulation experiments are often used to determine how best to assimilate these novel observations in space and time by using synthetic observations from a high-resolution “nature run.” However, a single deterministic nature run does not provide a measure of the flow’s intrinsic predictability within the chosen modeling system. We present a framework to provide insight into this predictability by using an ensemble of nature runs. The ensemble provides a range of likely outcomes for storm evolution and an upper limit against which forecasts are verified. We applied this framework to two events from Oklahoma in 2023: a quasi-linear convective system in February and a supercell case in April. The intrinsic predictability of the nature-run ensemble was used to calibrate each case and to verify the forecast ensembles. Results showed that the intrinsic predictability suggested by the nature-run ensemble was both field and case dependent. This framework may help guide future studies by giving researchers a better understanding of what is possible for a chosen flow problem and modeling system and how best to include and arrange novel observations. AN - noaa:73128 DO - https://doi.org/10.1175/WAF-D-24-0153.1 IS - 10 J2 - Weather and Forecasting PB - American Meteorological Society PY - 2025 T2 - Weather and Forecasting T2 - Weather and Forecasting, 40(10), 2147-2157 TI - A Framework for Convective-Scale Observing System Simulation Experiments Using Ensembles VL - 40 UR - https://repository.library.noaa.gov/view/noaa/73128 ER -
Argovis: Building a FAIR Ocean Data Service

Mills, Bill Katie-Anne

;

Giglio, Donata

2025 | Journal of Atmospheric and Oceanic Technology, 42(11), 1567-1581 | pdf

The current ecosystem of Internet-facing search and distribution tools for ocean data has limited options suitable for supporting the fast queries needed to underwrite applications that update their data frequently and on demand, such as visualization websites, interactive educational activities, and analyses constructed as living documents. These ...

04/24/2026

Title : Argovis: Building a FAIR Ocean Data Service Personal Author(s) : Mills, Bill Katie-Anne;Giglio, Donata;Scanderbeg, Megan;Purkey, Sarah;Merchant, Lynne; Published Date : 2025 Source : Journal of Atmospheric and Oceanic Technology, 42(11), 1567-1581 DOI : https://doi.org/10.1175/JTECH-D-24-0160.1 Journal Title : Journal of Atmospheric and Oceanic Technology Mills, Bill Katie-Anne et al. (2025). Argovis: Building a FAIR Ocean Data Service. 42(11). https://doi.org/10.1175/JTECH-D-24-0160.1 Mills, Bill Katie-Anne et al. "Argovis: Building a FAIR Ocean Data Service" 42, no. 11 (2025), https://doi.org/10.1175/JTECH-D-24-0160.1 Mills, Bill Katie-Anne et al. "Argovis: Building a FAIR Ocean Data Service" vol. 42, no. 11, 2025, https://doi.org/10.1175/JTECH-D-24-0160.1 Export RIS Citation Information. TY - AU - Mills, Bill Katie-Anne AU - Giglio, Donata AU - Scanderbeg, Megan AU - Purkey, Sarah AU - Merchant, Lynne AB - The current ecosystem of Internet-facing search and distribution tools for ocean data has limited options suitable for supporting the fast queries needed to underwrite applications that update their data frequently and on demand, such as visualization websites, interactive educational activities, and analyses constructed as living documents. These applications are best served by a Representational State Transfer (RESTful) application programming interface (API) with incisive search capabilities over an appropriately indexed database of ocean datasets represented with consistent encoding. For this purpose, a new Argovis API was developed and released, along with a web-facing frontend and a collection of Jupyter notebooks that leverage it and demonstrate its capabilities. This paper reviews the key engineering decisions and reference architecture used by Argovis to create a responsive, FAIR ocean data service for Argo and ship-based profiles, derived gridded fields and other products, observations from the Global drifter program, tropical cyclone track data, an atmospheric river climatology, and weekly gridded fields of sea surface temperature, sea level anomaly, and surface winds based on satellite data. We also tour some of the use cases and applications of this data service, both by the Argovis team and third-party consumers. AN - noaa:73127 DO - https://doi.org/10.1175/JTECH-D-24-0160.1 IS - 11 J2 - Journal of Atmospheric and Oceanic Technology PB - American Meteorological Society PY - 2025 T2 - Journal of Atmospheric and Oceanic Technology T2 - Journal of Atmospheric and Oceanic Technology, 42(11), 1567-1581 TI - Argovis: Building a FAIR Ocean Data Service VL - 42 UR - https://repository.library.noaa.gov/view/noaa/73127 ER -
Flood detection and mapping through multi-resolution sensor fusion: integrating UAV optical imagery and satellite SAR data

Fawakherji, Mulham ;

Hashemi-Beni, Leila

2025 | Geomatics, Natural Hazards and Risk, 16(1) | pdf

Remote sensing has advanced significantly with the increasing number of satellites in orbit and those scheduled for launch, alongside emerging proximate sensing platforms that provide data on Earth phenomena in diverse spectrums, spatial resolutions, and temporal intervals. Despite these variations, all these datasets represent the same physical en ...

04/24/2026

Title : Flood detection and mapping through multi-resolution sensor fusion: integrating UAV optical imagery and satellite SAR data Personal Author(s) : Fawakherji, Mulham;Hashemi-Beni, Leila; Published Date : 2025 Source : Geomatics, Natural Hazards and Risk, 16(1) DOI : https://doi.org/10.1080/19475705.2025.2493225 Journal Title : Geomatics, Natural Hazards and Risk Fawakherji, Mulham and Hashemi-Beni, Leila (2025). Flood detection and mapping through multi-resolution sensor fusion: integrating UAV optical imagery and satellite SAR data. 16(1). https://doi.org/10.1080/19475705.2025.2493225 Fawakherji, Mulham and Hashemi-Beni, Leila "Flood detection and mapping through multi-resolution sensor fusion: integrating UAV optical imagery and satellite SAR data" 16, no. 1 (2025), https://doi.org/10.1080/19475705.2025.2493225 Fawakherji, Mulham and Hashemi-Beni, Leila "Flood detection and mapping through multi-resolution sensor fusion: integrating UAV optical imagery and satellite SAR data" vol. 16, no. 1, 2025, https://doi.org/10.1080/19475705.2025.2493225 Export RIS Citation Information. TY - AU - Fawakherji, Mulham AU - Hashemi-Beni, Leila AB - Remote sensing has advanced significantly with the increasing number of satellites in orbit and those scheduled for launch, alongside emerging proximate sensing platforms that provide data on Earth phenomena in diverse spectrums, spatial resolutions, and temporal intervals. Despite these variations, all these datasets represent the same physical environment. The challenge lies in effectively managing these diverse data sources and extracting the optimal combination of information. Data fusion offers a powerful solution for integrating and utilizing this wide array of remotely sensed data. AN - noaa:73126 DO - https://doi.org/10.1080/19475705.2025.2493225 IS - 1 J2 - Geomatics, Natural Hazards and Risk PB - Informa UK Limited PY - 2025 T2 - Geomatics, Natural Hazards and Risk T2 - Geomatics, Natural Hazards and Risk, 16(1) TI - Flood detection and mapping through multi-resolution sensor fusion: integrating UAV optical imagery and satellite SAR data VL - 16 UR - https://repository.library.noaa.gov/view/noaa/73126 ER -
Probabilistic Wave Forecast for Week 2 and beyond Based on NOAA’s Global Ensemble Forecast System

Campos, Ricardo M.

;

Figurskey, Darin

2025 | Weather and Forecasting, 40(8), 1511-1527 | pdf

In this paper, we propose a new capability for an oceanic hazards outlook containing delineations of where winds and waves are expected to have the potential of posing a hazard to either life or property at sea. This new product is based on NOAA’s Global Ensemble Forecast System, focused on developing a probabilistic forecast of 10-m wind speed (U1 ...

04/24/2026

Title : Probabilistic Wave Forecast for Week 2 and beyond Based on NOAA’s Global Ensemble Forecast System Personal Author(s) : Campos, Ricardo M.;Figurskey, Darin;Mehra, Avichal;Sienkiewicz, Joseph; Published Date : 2025 Source : Weather and Forecasting, 40(8), 1511-1527 DOI : https://doi.org/10.1175/WAF-D-24-0154.1 Journal Title : Weather and Forecasting Campos, Ricardo M. et al. (2025). Probabilistic Wave Forecast for Week 2 and beyond Based on NOAA’s Global Ensemble Forecast System. 40(8). https://doi.org/10.1175/WAF-D-24-0154.1 Campos, Ricardo M. et al. "Probabilistic Wave Forecast for Week 2 and beyond Based on NOAA’s Global Ensemble Forecast System" 40, no. 8 (2025), https://doi.org/10.1175/WAF-D-24-0154.1 Campos, Ricardo M. et al. "Probabilistic Wave Forecast for Week 2 and beyond Based on NOAA’s Global Ensemble Forecast System" vol. 40, no. 8, 2025, https://doi.org/10.1175/WAF-D-24-0154.1 Export RIS Citation Information. TY - AU - Campos, Ricardo M. AU - Figurskey, Darin AU - Mehra, Avichal AU - Sienkiewicz, Joseph AB - In this paper, we propose a new capability for an oceanic hazards outlook containing delineations of where winds and waves are expected to have the potential of posing a hazard to either life or property at sea. This new product is based on NOAA’s Global Ensemble Forecast System, focused on developing a probabilistic forecast of 10-m wind speed (U10) and significant wave height (Hs) for week 2. The methodology involves defining temporal and spatial windows to postprocess the ensemble members and analyzing the tail of the probability density function generated by the pooled dataset. Specific thresholds for U10 and Hs as well as probability levels are defined in the algorithm to generate probability maps. The performance is assessed through statistical validation using NDBC buoy data and reanalysis, followed by case studies. Results indicate that the probabilistic forecast is skillful in predicting waves up to 9 m and winds up to 48 kt (1 kt ≈ 0.51 m s−1), particularly for extratropical systems. In addition, with weaker signals and lower probabilities forecasted, extreme extratropical events associated with hurricane-force winds could be in many cases successfully detected in the week 2 forecast. Therefore, the probability maps provide valuable guidance for practical applications, helping in decision-making for maritime operations. AN - noaa:73125 DO - https://doi.org/10.1175/WAF-D-24-0154.1 IS - 8 J2 - Weather and Forecasting PB - American Meteorological Society PY - 2025 T2 - Weather and Forecasting T2 - Weather and Forecasting, 40(8), 1511-1527 TI - Probabilistic Wave Forecast for Week 2 and beyond Based on NOAA’s Global Ensemble Forecast System VL - 40 UR - https://repository.library.noaa.gov/view/noaa/73125 ER -
Initialized Seasonal Prediction with the NCAR Models in the North American Multimodel Ensemble (NMME)

Becker, Emily

;

Kirtman, Ben P.

2025 | Weather and Forecasting, 40(6), 889-900 | pdf

This study investigates the seasonal prediction capabilities of three models, all developed by the National Science Foundation (NSF) National Center for Atmospheric Research (NCAR) and implemented by the University of Miami, within the North American Multimodel Ensemble (NMME) framework. All three models, Community Climate System Model, version 3 ( ...

04/24/2026

Title : Initialized Seasonal Prediction with the NCAR Models in the North American Multimodel Ensemble (NMME) Personal Author(s) : Becker, Emily;Kirtman, Ben P.;Min, Dughong; Published Date : 2025 Source : Weather and Forecasting, 40(6), 889-900 DOI : https://doi.org/10.1175/WAF-D-24-0123.1 Journal Title : Weather and Forecasting Becker, Emily et al. (2025). Initialized Seasonal Prediction with the NCAR Models in the North American Multimodel Ensemble (NMME). 40(6). https://doi.org/10.1175/WAF-D-24-0123.1 Becker, Emily and Kirtman, Ben P. and Min, Dughong "Initialized Seasonal Prediction with the NCAR Models in the North American Multimodel Ensemble (NMME)" 40, no. 6 (2025), https://doi.org/10.1175/WAF-D-24-0123.1 Becker, Emily et al. "Initialized Seasonal Prediction with the NCAR Models in the North American Multimodel Ensemble (NMME)" vol. 40, no. 6, 2025, https://doi.org/10.1175/WAF-D-24-0123.1 Export RIS Citation Information. TY - AU - Becker, Emily AU - Kirtman, Ben P. AU - Min, Dughong AB - This study investigates the seasonal prediction capabilities of three models, all developed by the National Science Foundation (NSF) National Center for Atmospheric Research (NCAR) and implemented by the University of Miami, within the North American Multimodel Ensemble (NMME) framework. All three models, Community Climate System Model, version 3 (CCSM3), CCSM4, and Community Earth System Model, version 1 (CESM1), are initialized using the Climate Forecast System Reanalysis (CFSR) and have a common period of 1991–2018. The models’ performance in predicting key climate variables including surface temperature, precipitation, and El Niño–Southern Oscillation (ENSO) teleconnections is assessed. The models’ prediction skill is assessed using the sign test, a robust nonparametric method for comparing forecast errors. CCSM4 succeeded CCSM3 in 2014, bringing a much more accurate representation of global temperature trends and improved prediction of precipitation extremes and 2-m temperature over land. CESM1, introduced in 2023, shows further improvement relative to CCSM4 in the prediction of sea surface temperature in the tropical Pacific and precipitation extremes over land. The improvement in precipitation prediction skill is encouraging, as this field has seen little improvement over the life of the NMME. The modeled similarity to observed ENSO teleconnection patterns of 2-m temperature is somewhat less in CESM1 than in CCSM4, although precipitation teleconnection patterns are similar. CCSM4 and CESM1 show stronger surface temperature trends in the tropical Pacific and Southern Ocean than observed trends over the same period, a common problem for current state-of-the-art climate models with implications for prediction and for climate projections. AN - noaa:73124 DO - https://doi.org/10.1175/WAF-D-24-0123.1 IS - 6 J2 - Weather and Forecasting PB - American Meteorological Society PY - 2025 T2 - Weather and Forecasting T2 - Weather and Forecasting, 40(6), 889-900 TI - Initialized Seasonal Prediction with the NCAR Models in the North American Multimodel Ensemble (NMME) VL - 40 UR - https://repository.library.noaa.gov/view/noaa/73124 ER -

1 - 20 / 313

Next Page Next