NOAA National Weather Service

Heavy precipitation in Colorado (CO) is key to water resources, and the presence or absence of a few strong storms can make or break the yearly snowpack that delivers water to four major river basins. However, predicting precipitation in CO is challenging because it has high spatial and temporal variability. Atmospheric rivers (ARs) are one type of storm that results in a large fraction of extreme precipitation in the western U.S. and lends itself to improved forecasts over the region. Extensive knowledge of AR frequency, intensity, impacts, and key meteorological processes has been developed for U.S. West Coast landfalling ARs; however, relatively limited research has examined AR characteristics further inland, particularly for Colorado (CO), where high and complex topography, as well as the distance from the coast, complicate attempts to track ARs, AR-derived moisture, and AR-related impacts. Previous research efforts attributing precipitation to ARs based on their spatial footprint have yielded less than 30% of cool-season precipitation in CO as related to ARs. However, a large volume of anecdotal evidence suggests that ARs play a larger role in CO precipitation. To quantify this, we used trajectory-based methods to quantify the contribution of landfalling ARs to top-decile precipitation in subbasins throughout CO. Moisture sourced from landfalling ARs penetrates inland along relatively low-elevation corridors through the Interior West, and exhibits substantial geographic and interannual variability. Using the backward trajectory approach, we found that landfalling ARs contribute 21–78% of western CO’s top-decile cool season precipitation. Most of the AR-related precipitation across western CO during the cool-season is sourced from landfalling ARs near Southern California, the Baja Peninsula, and the Pacific Northwest. These results indicate a larger role for ARs in CO weather and hydroclimate than previous research suggests and highlight the importance of AR representation in forecast models to improve predictability of precipitation in CO.

Extreme rainfall events can trigger flash floods that pose serious risks to communities, infrastructure, and critical services, particularly in arid and rapidly urbanizing environments. In the Kingdom of Saudi Arabia, short hydrological response times, strong spatial variability of precipitation, complex topography, and limited observational data significantly challenge flood early warning capabilities, which affect emergency management at the national scale. Addressing these challenges requires integrated and scalable hydro-meteorological forecasting systems capable of operating across large spatial domains while resolving convective weather events and associated localized flood impacts in urban/suburban areas.This study presents a nationwide, operational flash flood early warning system developed for the Kingdom of Saudi Arabia. The system is designed to provide consistent coverage across the country while capturing fine-scale weather, hydrological and hydrodynamic processes relevant to flash flooding in arid environments. It operates over 137 hydrological domains, representing more than 6,000 outlets, delivering 2D flood simulations at a spatial resolution of 30 m nationwide, with enhanced resolution of up to 2.5 m in selected urban areas.The forecasting framework is structured as an end-to-end modeling chain that links atmospheric forcing, hydrological response, hydraulic flood propagation, and infrastructure impacts. High-resolution numerical weather predictions generated by the Weather Research and Forecasting (WRF) model are combined with real-time radar and rain gauge observations to produce hourly ensemble weather and precipitation forecasts and hindcasts. These meteorological inputs drive a distributed hydrological model (CREST), which simulates runoff generation across arid catchments using spatially explicit information on topography, land cover, soil properties, and drainage networks. A reservoir management module is fully integrated within the modeling chain, allowing the system to account for reservoir storage dynamics, controlled releases, and spillway operations, and to assess the influence of dam infrastructure on downstream flood evolution.Hydrological outputs are used as boundary conditions to a two-dimensional hydrodynamic model, which simulates floodplain dynamics, water depths, and inundation extents.All model components are coupled within a WebGIS-based operational platform that displays deterministic and ensemble weather and hydrologic forecasts, probabilistic flood warnings, and real-time nowcasting products. Flood hazard information is delivered through interactive maps, warning levels, and time series, to support decision- making by civil protection authorities and emergency managers at national and local scales.The functionality and operational performance of the system are demonstrated through its application on a recent extreme rainfall and flash flood events that affected the entire region of Saudi Arabia in the period of December 9-16, 2025. The system successfully captured the timing, spatial extent, and severity of flooding across multiple domains, providing useful lead times and high-resolution inundation maps. This case study highlights the robustness, scalability, and operational value of the framework, demonstrating its potential to enhance flood preparedness through early warning, and risk management across the Kingdom of Saudi Arabia under increasing hydro- meteorological extremes.

Abstract Snow squalls remain a dangerous meteorological hazard, particularly to highway drivers. While snow squalls do not cause significant amounts of total snowfall, their rapid onset and intense nature create an environment conducive to roadway fatalities. In particular, the near-zero visibility and slick roadways caused by snow squalls can catch drivers by surprise, leading to multi-vehicle pileups. Though the US National Weather Service began issuing Snow Squall Warnings to mobile phones in 2018, many individuals remain unaware of the risks posed by this hazard. Additionally, extra cultural and language barriers exist when using traditional text-based warnings and guidance to communicate risks to Spanish-speaking groups with Limited English Proficiency. To enhance more traditional methods of risk communication, especially among non-native English-speaking groups, we created a virtual reality (VR) snow squall driving simulation. The simulation provides an open-ended environment in which users drive through a simulated snow squall. We conducted a user study in which 216 individuals tested the simulation and completed a survey. In total, 146 of the participants used the simulation and answered the survey questions in English, while the other 70 participants used the simulation and completed the survey in Spanish. Using the results, we compared the effectiveness of the VR simulation across the two survey cohorts. We found the VR simulation to be an effective communication tool across both groups, with participants finding the experience enjoyable and reporting intent for behavior change if faced with a real snow squall.

Abstract This workshop aims to improve the competence of elementary school teachers using digital learning media, in particular, Wordwall, Pickerwhell and Ahaslides. This activity is a Community Service Program of the Elementary School Teacher Education Lecturer Team of Universitas Pelita Bangsa which was carried out online involving 2 Principals, 15 Elementary School Teachers, and 79 Students spread across regions in Indonesia, especially Bekasi, West Java. The workshop was carried out through three stages, namely preparation, material delivery, and evaluation. In the preparation stage, the service team prepared an online workshop by inviting the cooperation of several schools and involving students. In the implementation stage, workshop participants participated in the presentation of theory and practice in the use of digital platforms through Zoom Meetings and then the evaluation was carried out through the help of Google Form after the implementation. The results of the evaluation showed that 82% of participants gave a very useful, solution, and innovative assessment of the implementation of the workshop, while 56.1% of participants rated YouTube as the easiest platform to use, followed by Wordwall at 34.1%. Overall, this workshop received an average satisfaction of 4.88 out of 5. Thus, this digital learning workshop is effective in improving teachers' competence in smartphone-based digital learning. It is hoped that there will be no more limitations for teachers to implement digital learning by utilizing gadgets owned by all groups, namely smartphones. Keywords: Workshop; Digital Learning; Elementary School Teachers; Smartphone Abstrak Workshop ini bertujuan meningkatkan kompetensi Guru SD memanfaatkan media pembelajaran digital, khususnya, Wordwall, Pickerwhell dan Ahaslides. Kegiatan ini merupakan Program Pengabdian Masyarakat Tim Dosen Pendidikan Guru Sekolah Dasar Universitas Pelita Bangsa yang dilaksanakan secara daring dengan melibatkan 2 Kepala Sekolah, 15 Guru SD, dan 79 Mahasiswa yang tersebar di wilayah di Indonesia khususnya Bekasi, Jawa Barat. Workshop dilaksanakan melalui tiga tahapan, yaitu persiapan, penyampaian materi, dan evaluasi. Pada tahap persiapan tim pengabdian mempersiapkan workshop secara daring dengan mengajak kerjasama beberapa sekolah dan melibatkan mahasiswa. Tahap implementasi, peserta workshop mengikuti pemaparan teori dan praktik dalam penggunaan platform digital melalui Zoom Meeting kemudian pada evaluasi dilaksanakan melalui bantuan Google Form usai pelaksanaan. Hasil evaluasi menunjukkan 82% peserta memberikan penilaian sangat Bermanfaat, Solutif, dan Inovatif terhadap pelaksanan workshop, sementara 56,1% peserta menilai YouTube sebagai platform yang paling mudah digunakan dan disusul Wordwall 34,1%. Keseluruhan, workshop ini mendapatkan rata-rata kepuasan 4,88 dari 5. Dengan demikian workshop pembelajaran digital ini efektif meningkatkan kompetensi guru dalam pembelajaran digital berbasis smartphone. Diharapkan tidak ada lagi keterbatasan guru mengimplementasikan pembelajaran digital dengan memanfaatkan gawai yang dimiliki semua kalangan yaitu Smartphone. Kata kunci: Workshop; Pembelajaran Digital;Guru SD; Smartphone

Over the past half century since 1975, the development and improvement of meteorological geostationary (GEO) satellites have played a pivotal role in observing cloud dynamics and subsequently in advancing spaceborne precipitation estimation. Infrared (IR) observation from GEO satellites offers unique advantages, such as broad spatial coverage, high temporal resolution, and long-term consistency, motivating extensive research to unlock the potential of GEO IR-based data for capturing precipitation structure and dynamics. This article reviews the major developments and milestone achievements of GEO IR-based precipitation estimation over the past five decades and summarizes the future prospects, including potential directions and remaining challenges. By examining the history of global GEO satellites and more than 100 references in this domain, we categorize the development of GEO IR-based precipitation estimation methodology and technology into three distinct stages: 1) the Exploration Phase (1975 to ca. 1995), 2) the Growth Phase (ca. 1995 to ca. 2015), and 3) the Exploitation Phase (ca. 2015 to the present). As we transition into an emerging new stage, these efforts collectively point toward multispectral retrievals, lifecycle-aware machine learning (ML), smart sensing, and advanced multisource integration as key directions shaping the future of GEO IR-based precipitation estimation. In summary, GEO IR-based precipitation estimation has made substantial contributions over the past half century and will play an increasingly important role with great potential in future precipitation science.

Extreme hydrometeorological events replenish water resources but can also trigger catastrophic flash floods, infrastructure damage, and loss of life. In California, landfalling atmospheric rivers account for ~85% of the most intense rainfall and flood

Mexican-origin families often face economic hardship due to systemic oppression, increasing the likelihood of adolescent marijuana use. While the family stress model provides insight into the mechanism of the association between family economic hardship and adolescent marijuana use, resilience factors are relatively unknown. The present study uses a three-wave longitudinal data set of Mexican immigrant families in the United States (Wave 1-adolescents: Mage = 12.29, SD = 0.93; mothers: Mage = 38.57, SD = 5.71) to investigate the mechanism underlying the association between family income and adolescents' likelihood of marijuana use, guided by the family stress model. The protective role of adolescent executive function (shifting task performance and working memory), which has been widely linked to adolescent marijuana use in prior research, was tested as a key resilience factor supporting behavioral regulation and adaptive coping in negative family environments. The results revealed the long-term detrimental influence of early adolescents' family income on the likelihood of using marijuana in late adolescence through family economic pressure, maternal internalizing symptoms, maternal hostility toward partner, and maternal hostility toward adolescent. The downstream link is buffered by adolescents' longer reaction times in shifting tasks and longer digit span by attenuating the influence of maternal hostility toward adolescent on the likelihood of adolescent marijuana use. Revealing the mechanism and identifying resilience factors for the association between family economic hardship and adolescent's marijuana use in Mexican-origin families shed light on the targets of interventions to help adolescents thrive and overcome economic disadvantage in Mexican-origin communities. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

OP 14: Health Services 3, B302 (FCSH), September 3, 2025, 17:00 - 18:00Cultural mediators (CMs) play a crucial role in facilitating migrants’ access to healthcare services in Turkey. Many CMs are migrants themselves, providing essential support in navigating complex healthcare systems. A three-day training program was designed in May 2019 to enhance their health-related knowledge, with a particular focus on maternal and child health. One of the primary challenges was conveying complex health concepts to individuals from diverse linguistic and cultural backgrounds.To address this, creative drama was employed as a pedagogical technique, fostering curiosity through improvisational scenarios involving both trainers and trainees. A key aspect of this approach was integrating participants’ lived experiences into the learning process, thereby enhancing engagement and retention. The training scenario depicted a migrant woman fleeing conflict, seeking refuge in Turkey, and navigating various healthcare facilities while experiencing multiple health challenges.To evaluate the program’s effectiveness, pre- and post-training surveys?comprising 11 open-ended questions were administered. The results indicated a significant improvement in knowledge, with correct responses increasing by 60%. Initially, only four of the 17 participants correctly identified the legal timeframe for abortion, increasing to ten in the post-test. Similarly, none of the participants?initially answered correctly regarding child vaccination policies in Turkey, whereas ten provided the correct response afterward.Following the training, participants conducted health-related presentations for both their organizations’ staff and the migrant communities they serve. As a result, 10 CMs successfully delivered sessions, reaching 70 migrants and 107 civil society workers. These findings highlight the essential role of CMs in improving healthcare access for migrant populations. Given the increasing migration trends, strengthening CMs’ health knowledge is vital for improving healthcare outcomes. Creative drama emerges as an effective, engaging and innovative pedagogical technique for enhancing learning in healthcare training programs.