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#publicsafety — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #publicsafety, aggregated by home.social.

  1. The Past, Present & Future Of Dams In The Southeastern U.S.
    --
    doi.org/10.1007/s00267-026-025 <-- shared paper
    --
    H/T @UF Water Institute
    “[The authors are] helping build a foundation for better water policy, planning, and resilience. By diving into the into the history, present status, and future of dams in the southeastern region, [they are] filling a research gap of an under-examined area..”
    --
    “Dams and reservoirs have played a central role in the industrialization and economic development of the United States, providing hydropower, flood control, navigation, water supply, and recreation. Yet they have also transformed river systems, displaced communities, and contributed to major ecological change. This paper presents an exploratory review of the history, present status, and future of dams in the Southeastern United States, focusing on U.S. Geological Survey hydrologic regions 3 (South Atlantic-Gulf) and 6 (Tennessee). Using data from the National Inventory of Dams, historical archives, and interdisciplinary literature, the study examines temporal trends in dam construction, societal and ecological impacts, hazard conditions, and emerging trends in dam management. The Southeastern U.S. contains some of the nation’s highest dam densities and storage capacities, with more than 19,000 inventoried dams as of 2026. Many dams were constructed during the mid-twentieth century through the New Deal and postwar infrastructure programs led by the Tennessee Valley Authority and the U.S. Army Corps of Engineers. This aging infrastructure, in combination with inconsistent regulation, and increasing exposure to extreme weather raises growing safety concerns, particularly for the many high-hazard dams in poor or unrated conditions in the region. The paper also explores future trajectories, including hydropower modernization, pumped storage expansion, and dam removal efforts aimed at balancing renewable energy production, ecological restoration, and public safety…”

  2. #MorningJoe on #MSNOW showed a video of #ICE agents punching two American citizens who were teenage boys traveling to enlist (join) the United States Marine Corps. Trump's recklessly brutal #ICE is out of control.
    #PublicSafety #HumanRights #politics

  3. "Firefighters battling enormous wildfires in the United States say the federal government (the Trump Administration) is failing them at a time when supercharged blazes have made their jobs exponentially more dangerous":
    theguardian.com/us-news/2026/s
    #Trump #WorstPresidentEver #PublicSafety copy: @renewedresistance #WildFires

  4. "Firefighters battling enormous wildfires in the United States say the federal government (the Trump Administration) is failing them at a time when supercharged blazes have made their jobs exponentially more dangerous":
    theguardian.com/us-news/2026/s
    #Trump #WorstPresidentEver #PublicSafety copy: @renewedresistance #WildFires

  5. Reuters: Indian police to query Google over 500,000 fake Gmail IDs linked to bomb hoax. “Indian police will question Google over a lack ​of safeguards after smashing a criminal network that set up and managed more than ‌500,000 fake Gmail accounts to send hoax bomb threats to government offices, a police official told Reuters on Tuesday.”

    https://rbfirehose.com/2026/09/15/reuters-indian-police-to-query-google-over-500000-fake-gmail-ids-linked-to-bomb-hoax/
  6. Reuters: Indian police to query Google over 500,000 fake Gmail IDs linked to bomb hoax. “Indian police will question Google over a lack ​of safeguards after smashing a criminal network that set up and managed more than ‌500,000 fake Gmail accounts to send hoax bomb threats to government offices, a police official told Reuters on Tuesday.”

    https://rbfirehose.com/2026/09/15/reuters-indian-police-to-query-google-over-500000-fake-gmail-ids-linked-to-bomb-hoax/
  7. Reuters: Indian police to query Google over 500,000 fake Gmail IDs linked to bomb hoax. “Indian police will question Google over a lack ​of safeguards after smashing a criminal network that set up and managed more than ‌500,000 fake Gmail accounts to send hoax bomb threats to government offices, a police official told Reuters on Tuesday.”

    https://rbfirehose.com/2026/09/15/reuters-indian-police-to-query-google-over-500000-fake-gmail-ids-linked-to-bomb-hoax/
  8. Reuters: Indian police to query Google over 500,000 fake Gmail IDs linked to bomb hoax. “Indian police will question Google over a lack ​of safeguards after smashing a criminal network that set up and managed more than ‌500,000 fake Gmail accounts to send hoax bomb threats to government offices, a police official told Reuters on Tuesday.”

    https://rbfirehose.com/2026/09/15/reuters-indian-police-to-query-google-over-500000-fake-gmail-ids-linked-to-bomb-hoax/
  9. Reuters: Indian police to query Google over 500,000 fake Gmail IDs linked to bomb hoax. “Indian police will question Google over a lack ​of safeguards after smashing a criminal network that set up and managed more than ‌500,000 fake Gmail accounts to send hoax bomb threats to government offices, a police official told Reuters on Tuesday.”

    https://rbfirehose.com/2026/09/15/reuters-indian-police-to-query-google-over-500000-fake-gmail-ids-linked-to-bomb-hoax/
  10. WeatherNext – [An] AI Model Achieves Breakthrough In Forecasting Cyclones
    --
    deepmind.google/blog/weatherne <-- shared technical Google DeepMind blog post
    --
    doi.org/10.1038/s41586-026-109 <-- shared paper
    --
    deepmind.google/science/weathe <-- shared data
    --
    github.com/google-deepmind/wea <-- shared GitHub repository
    --
    H/T @juliet Rothenberg | Product Director of Earth & Resilience AI at Google
    [this post should not be considered an endorsement of a particular organisation or their approach]
    “[The Google WeatherNext AI team] are showing how the WeatherNext AI model from Google DeepMind and Google Research has achieved state-of-the-art accuracy in predicting a cyclone's track, intensity, and wind structure. On average, the WeatherNext Cyclones model gives forecasters an extra day’s worth of predictive accuracy- delivering an advance equivalent to roughly a decade of historical meteorological progress 🌀
    Here is how WeatherNext is transforming cyclone forecasting:
    • Gaining an Extra Day of Advanced Warning: WN 3-day forecasts are as good as what prior models were able to provide for 2-day forecasts, giving critical time for emergency response.
    • Overcoming Traditional Trade-offs: WN bridges the gap between massive global atmospheric currents (which steer a cyclone's path) and fine-grained thermodynamic processes around its core (which drive its intensity) into a single AI model.
    • Unprecedented Ensemble Scale: Using Functional Generative Networks (FGNs), WN now generates 1,000-member ensembles in less than a minute on a TPU to capture rare, consequential tail-risks like sudden rapid intensification – which means forecasters can see a broader range of possible scenarios.
    • Real-World Impact: During the 2025 Atlantic hurricane season, the WN model helped the National Hurricane Center (NHC) make a historic forecast for Hurricane Melissa by predicting rapid intensification and landfall five days in advance.
    [The] teams are open sourcing the operationalized models (WeatherNext Cyclones and WeatherNext 2), alongside a compact version (WeatherNext 2-mini) that can run on a single TPU in a free public Colab notebook – all with a goal of empowering local organizations worldwide.
    Weather affects everyone. By combining advanced AI with the real-world expertise of human forecasters, we can build a collaborative ecosystem that saves lives and helps communities adapt to a changing climate…”
    #Google #DeepMind #GoogleResearch #AI #ensembles #FunctionalGenerativeNetworks #WeatherNext #cyclone #operationalised #model #modeling #forecasting #spatialanalyis #spatiotemporal #track #intensity #windstructure #hurricane #weather #climate #metrology #cyclonetrack #risk #hazard #emergencyresponse #planning #tool #earlywarning #scale #magnitude #path #track #thermodynamic #scenarios #opensource #impacts #tropicalcyclones #WeatherNextCyclones #weathermodel #atmospheric #predictions #mitigation #warning #robust #publicsafety #infrastructure
    @Google | @WeatherNext

  11. WeatherNext – [An] AI Model Achieves Breakthrough In Forecasting Cyclones
    --
    deepmind.google/blog/weatherne <-- shared technical Google DeepMind blog post
    --
    doi.org/10.1038/s41586-026-109 <-- shared paper
    --
    deepmind.google/science/weathe <-- shared data
    --
    github.com/google-deepmind/wea <-- shared GitHub repository
    --
    H/T @juliet Rothenberg | Product Director of Earth & Resilience AI at Google
    [this post should not be considered an endorsement of a particular organisation or their approach]
    “[The Google WeatherNext AI team] are showing how the WeatherNext AI model from Google DeepMind and Google Research has achieved state-of-the-art accuracy in predicting a cyclone's track, intensity, and wind structure. On average, the WeatherNext Cyclones model gives forecasters an extra day’s worth of predictive accuracy- delivering an advance equivalent to roughly a decade of historical meteorological progress 🌀
    Here is how WeatherNext is transforming cyclone forecasting:
    • Gaining an Extra Day of Advanced Warning: WN 3-day forecasts are as good as what prior models were able to provide for 2-day forecasts, giving critical time for emergency response.
    • Overcoming Traditional Trade-offs: WN bridges the gap between massive global atmospheric currents (which steer a cyclone's path) and fine-grained thermodynamic processes around its core (which drive its intensity) into a single AI model.
    • Unprecedented Ensemble Scale: Using Functional Generative Networks (FGNs), WN now generates 1,000-member ensembles in less than a minute on a TPU to capture rare, consequential tail-risks like sudden rapid intensification – which means forecasters can see a broader range of possible scenarios.
    • Real-World Impact: During the 2025 Atlantic hurricane season, the WN model helped the National Hurricane Center (NHC) make a historic forecast for Hurricane Melissa by predicting rapid intensification and landfall five days in advance.
    [The] teams are open sourcing the operationalized models (WeatherNext Cyclones and WeatherNext 2), alongside a compact version (WeatherNext 2-mini) that can run on a single TPU in a free public Colab notebook – all with a goal of empowering local organizations worldwide.
    Weather affects everyone. By combining advanced AI with the real-world expertise of human forecasters, we can build a collaborative ecosystem that saves lives and helps communities adapt to a changing climate…”
    #Google #DeepMind #GoogleResearch #AI #ensembles #FunctionalGenerativeNetworks #WeatherNext #cyclone #operationalised #model #modeling #forecasting #spatialanalyis #spatiotemporal #track #intensity #windstructure #hurricane #weather #climate #metrology #cyclonetrack #risk #hazard #emergencyresponse #planning #tool #earlywarning #scale #magnitude #path #track #thermodynamic #scenarios #opensource #impacts #tropicalcyclones #WeatherNextCyclones #weathermodel #atmospheric #predictions #mitigation #warning #robust #publicsafety #infrastructure
    @Google | @WeatherNext

  12. WeatherNext – [An] AI Model Achieves Breakthrough In Forecasting Cyclones
    --
    deepmind.google/blog/weatherne <-- shared technical Google DeepMind blog post
    --
    doi.org/10.1038/s41586-026-109 <-- shared paper
    --
    deepmind.google/science/weathe <-- shared data
    --
    github.com/google-deepmind/wea <-- shared GitHub repository
    --
    H/T @juliet Rothenberg | Product Director of Earth & Resilience AI at Google
    [this post should not be considered an endorsement of a particular organisation or their approach]
    “[The Google WeatherNext AI team] are showing how the WeatherNext AI model from Google DeepMind and Google Research has achieved state-of-the-art accuracy in predicting a cyclone's track, intensity, and wind structure. On average, the WeatherNext Cyclones model gives forecasters an extra day’s worth of predictive accuracy- delivering an advance equivalent to roughly a decade of historical meteorological progress 🌀
    Here is how WeatherNext is transforming cyclone forecasting:
    • Gaining an Extra Day of Advanced Warning: WN 3-day forecasts are as good as what prior models were able to provide for 2-day forecasts, giving critical time for emergency response.
    • Overcoming Traditional Trade-offs: WN bridges the gap between massive global atmospheric currents (which steer a cyclone's path) and fine-grained thermodynamic processes around its core (which drive its intensity) into a single AI model.
    • Unprecedented Ensemble Scale: Using Functional Generative Networks (FGNs), WN now generates 1,000-member ensembles in less than a minute on a TPU to capture rare, consequential tail-risks like sudden rapid intensification – which means forecasters can see a broader range of possible scenarios.
    • Real-World Impact: During the 2025 Atlantic hurricane season, the WN model helped the National Hurricane Center (NHC) make a historic forecast for Hurricane Melissa by predicting rapid intensification and landfall five days in advance.
    [The] teams are open sourcing the operationalized models (WeatherNext Cyclones and WeatherNext 2), alongside a compact version (WeatherNext 2-mini) that can run on a single TPU in a free public Colab notebook – all with a goal of empowering local organizations worldwide.
    Weather affects everyone. By combining advanced AI with the real-world expertise of human forecasters, we can build a collaborative ecosystem that saves lives and helps communities adapt to a changing climate…”
    #Google #DeepMind #GoogleResearch #AI #ensembles #FunctionalGenerativeNetworks #WeatherNext #cyclone #operationalised #model #modeling #forecasting #spatialanalyis #spatiotemporal #track #intensity #windstructure #hurricane #weather #climate #metrology #cyclonetrack #risk #hazard #emergencyresponse #planning #tool #earlywarning #scale #magnitude #path #track #thermodynamic #scenarios #opensource #impacts #tropicalcyclones #WeatherNextCyclones #weathermodel #atmospheric #predictions #mitigation #warning #robust #publicsafety #infrastructure
    @Google | @WeatherNext

  13. WeatherNext – [An] AI Model Achieves Breakthrough In Forecasting Cyclones
    --
    deepmind.google/blog/weatherne <-- shared technical Google DeepMind blog post
    --
    doi.org/10.1038/s41586-026-109 <-- shared paper
    --
    deepmind.google/science/weathe <-- shared data
    --
    github.com/google-deepmind/wea <-- shared GitHub repository
    --
    H/T @juliet Rothenberg | Product Director of Earth & Resilience AI at Google
    [this post should not be considered an endorsement of a particular organisation or their approach]
    “[The Google WeatherNext AI team] are showing how the WeatherNext AI model from Google DeepMind and Google Research has achieved state-of-the-art accuracy in predicting a cyclone's track, intensity, and wind structure. On average, the WeatherNext Cyclones model gives forecasters an extra day’s worth of predictive accuracy- delivering an advance equivalent to roughly a decade of historical meteorological progress 🌀
    Here is how WeatherNext is transforming cyclone forecasting:
    • Gaining an Extra Day of Advanced Warning: WN 3-day forecasts are as good as what prior models were able to provide for 2-day forecasts, giving critical time for emergency response.
    • Overcoming Traditional Trade-offs: WN bridges the gap between massive global atmospheric currents (which steer a cyclone's path) and fine-grained thermodynamic processes around its core (which drive its intensity) into a single AI model.
    • Unprecedented Ensemble Scale: Using Functional Generative Networks (FGNs), WN now generates 1,000-member ensembles in less than a minute on a TPU to capture rare, consequential tail-risks like sudden rapid intensification – which means forecasters can see a broader range of possible scenarios.
    • Real-World Impact: During the 2025 Atlantic hurricane season, the WN model helped the National Hurricane Center (NHC) make a historic forecast for Hurricane Melissa by predicting rapid intensification and landfall five days in advance.
    [The] teams are open sourcing the operationalized models (WeatherNext Cyclones and WeatherNext 2), alongside a compact version (WeatherNext 2-mini) that can run on a single TPU in a free public Colab notebook – all with a goal of empowering local organizations worldwide.
    Weather affects everyone. By combining advanced AI with the real-world expertise of human forecasters, we can build a collaborative ecosystem that saves lives and helps communities adapt to a changing climate…”
    #Google #DeepMind #GoogleResearch #AI #ensembles #FunctionalGenerativeNetworks #WeatherNext #cyclone #operationalised #model #modeling #forecasting #spatialanalyis #spatiotemporal #track #intensity #windstructure #hurricane #weather #climate #metrology #cyclonetrack #risk #hazard #emergencyresponse #planning #tool #earlywarning #scale #magnitude #path #track #thermodynamic #scenarios #opensource #impacts #tropicalcyclones #WeatherNextCyclones #weathermodel #atmospheric #predictions #mitigation #warning #robust #publicsafety #infrastructure
    @Google | @WeatherNext

  14. WeatherNext – [An] AI Model Achieves Breakthrough In Forecasting Cyclones
    --
    deepmind.google/blog/weatherne <-- shared technical Google DeepMind blog post
    --
    doi.org/10.1038/s41586-026-109 <-- shared paper
    --
    deepmind.google/science/weathe <-- shared data
    --
    github.com/google-deepmind/wea <-- shared GitHub repository
    --
    H/T @juliet Rothenberg | Product Director of Earth & Resilience AI at Google
    [this post should not be considered an endorsement of a particular organisation or their approach]
    “[The Google WeatherNext AI team] are showing how the WeatherNext AI model from Google DeepMind and Google Research has achieved state-of-the-art accuracy in predicting a cyclone's track, intensity, and wind structure. On average, the WeatherNext Cyclones model gives forecasters an extra day’s worth of predictive accuracy- delivering an advance equivalent to roughly a decade of historical meteorological progress 🌀
    Here is how WeatherNext is transforming cyclone forecasting:
    • Gaining an Extra Day of Advanced Warning: WN 3-day forecasts are as good as what prior models were able to provide for 2-day forecasts, giving critical time for emergency response.
    • Overcoming Traditional Trade-offs: WN bridges the gap between massive global atmospheric currents (which steer a cyclone's path) and fine-grained thermodynamic processes around its core (which drive its intensity) into a single AI model.
    • Unprecedented Ensemble Scale: Using Functional Generative Networks (FGNs), WN now generates 1,000-member ensembles in less than a minute on a TPU to capture rare, consequential tail-risks like sudden rapid intensification – which means forecasters can see a broader range of possible scenarios.
    • Real-World Impact: During the 2025 Atlantic hurricane season, the WN model helped the National Hurricane Center (NHC) make a historic forecast for Hurricane Melissa by predicting rapid intensification and landfall five days in advance.
    [The] teams are open sourcing the operationalized models (WeatherNext Cyclones and WeatherNext 2), alongside a compact version (WeatherNext 2-mini) that can run on a single TPU in a free public Colab notebook – all with a goal of empowering local organizations worldwide.
    Weather affects everyone. By combining advanced AI with the real-world expertise of human forecasters, we can build a collaborative ecosystem that saves lives and helps communities adapt to a changing climate…”

    @Google | @WeatherNext

  15. The Register: US Navy won’t torpedo hurricane forecast satellite feed after all . “The US Navy has announced plans to continue distributing satellite data needed for hurricane forecasting, months after authorities said the data stream was to be turned off. The U-turn comes after protests from weather forecasters and an alternative approach from amateur satellite enthusiasts, which showed users […]

    https://rbfirehose.com/2025/08/05/the-register-us-navy-wont-torpedo-hurricane-forecast-satellite-feed-after-all/

  16. The Register: US Navy won’t torpedo hurricane forecast satellite feed after all . “The US Navy has announced plans to continue distributing satellite data needed for hurricane forecasting, months after authorities said the data stream was to be turned off. The U-turn comes after protests from weather forecasters and an alternative approach from amateur satellite enthusiasts, which showed users […]

    https://rbfirehose.com/2025/08/05/the-register-us-navy-wont-torpedo-hurricane-forecast-satellite-feed-after-all/

  17. The Register: US Navy won’t torpedo hurricane forecast satellite feed after all . “The US Navy has announced plans to continue distributing satellite data needed for hurricane forecasting, months after authorities said the data stream was to be turned off. The U-turn comes after protests from weather forecasters and an alternative approach from amateur satellite enthusiasts, which showed users […]

    https://rbfirehose.com/2025/08/05/the-register-us-navy-wont-torpedo-hurricane-forecast-satellite-feed-after-all/

  18. The Register: US Navy won’t torpedo hurricane forecast satellite feed after all . “The US Navy has announced plans to continue distributing satellite data needed for hurricane forecasting, months after authorities said the data stream was to be turned off. The U-turn comes after protests from weather forecasters and an alternative approach from amateur satellite enthusiasts, which showed users […]

    https://rbfirehose.com/2025/08/05/the-register-us-navy-wont-torpedo-hurricane-forecast-satellite-feed-after-all/

  19. The Register: US Navy won’t torpedo hurricane forecast satellite feed after all . “The US Navy has announced plans to continue distributing satellite data needed for hurricane forecasting, months after authorities said the data stream was to be turned off. The U-turn comes after protests from weather forecasters and an alternative approach from amateur satellite enthusiasts, which showed users […]

    https://rbfirehose.com/2025/08/05/the-register-us-navy-wont-torpedo-hurricane-forecast-satellite-feed-after-all/