#mitigation — Public Fediverse posts

https://www.theguardian.com/environment/2026/aug/20/ministers-are-in-denial-about-the-scale-of-the-crises-we-face. This #letter writer, Dr Amy McDonnell, wants the #Government to start getting its act together on #climate #adaptation - which is all well & good, & doubtless necessary, but that same Government needs to act with far greater #urgency on climate #mitigation, too - & there must be absolutely NO more talk about further #drilling for #oil & #gas in the #NorthSea!

Let me start a thread on nature restoration, rewilding, reforestation 🧵

#adaptation #mitigation #carbon #carbonSinks #restoration #rewilding #reforestation #land #wetlands #rewetting #deterrence #prevention #drought #droughts #wildfires #heatwaves #landSink

Let me start a thread on nature restoration, rewilding, reforestation 🧵

#adaptation #mitigation #carbon #carbonSinks #restoration #rewilding #reforestation #land #wetlands #rewetting #deterrence #prevention #drought #droughts #wildfires #heatwaves #landSink

This one is a "could" but with well-sifted risk data >>

Future Projections of Burned Area in Europe Highlight the Importance of Human Action

https://onlinelibrary.wiley.com/doi/10.1111/gcb.71043 #wildfires #climate #mitigation

Every Model Cheats

https://dreadnode.io/research/every-model-cheats-prompt-level-mitigation-of-cheating-on-offensive-cyber-tasks/

Comments: https://news.ycombinator.com/item?id=49374635

#HackerNews #EveryModelCheats #CyberSecurity #AIResearch #OffensiveTasks #Mitigation

WeatherNext – [An] AI Model Achieves Breakthrough In Forecasting Cyclones
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https://deepmind.google/blog/weathernext-ai-model-achieves-breakthrough-in-forecasting-cyclones/ <-- shared technical Google DeepMind blog post
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https://doi.org/10.1038/s41586-026-10953-2 <-- shared paper
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https://deepmind.google/science/weatherlab/ <-- shared data
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https://github.com/google-deepmind/weathernext <-- shared GitHub repository
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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

The idea that you can mitigate climate change is….

[supply your own completion.
I can’t think of suitable words
- along the lines of “stupid”]

#climateChange #mitigation

I just now have decided to:
• keep climate science and carbon management here and
• write about social adaptation to climate risks there: @eric

So I research #climatePolicy at both accounts:
• #mitigation of climate forcing, #decoupling here and
• #adaptation to climate drift there: @eric

So there is the continuation of a thread on an institutional preparation to a future climate: https://social.coop/@eric/117058523359266590

https://www.theguardian.com/society/2026/aug/05/nhs-must-prepare-for-annual-summer-heat-pressures-says-yvette-cooper. "Don't even think about #mitigation of the #climate #emergency, because we're going to go on extracting & burning #fossilfuels, chopping & burning down #forests & destroying #wetlands - just #adapt to it." That's this #Labour #Government all over, & the #Tories & #ReformUK as well!

From Fragmentation To Integration - A Review Of Data–Model Integration In Land Subsidence Research
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https://doi.org/10.1016/j.ancene.2026.100567 <-- shared paper
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H/T @manonzero current drought conditions, increasing pressure on ecosystems, and ongoing climate adaptation challenges, land subsidence is receiving growing attention worldwide.
For anyone wanting to learn more about land subsidence, or get a refresher, [the authors] provide an overview of the processes involved, the ways it can be measured or estimated, the models used to simulate it, and how observations and models can be combined, [their] new [#openaccess] review paper [link above] may be of interest!
A central message of the paper is that understanding and managing land subsidence requires bringing these different sources of information together…”
--
“HIGHLIGHTS:
• Presents a comprehensive synthesis that unifies all major elements of integral land-subsidence research.
• Defines the methodological steps needed for full integration and positions them within the broader challenges posed by subsidence.
• Brings together and distills the key components of data, modelling, and integration into a coherent framework.
ABSTRACT: Land subsidence, the sinking of the Earth’s surface, is a multi-faceted hazard driven by both natural and anthropogenic factors, and poses significant risk to environments, ecosystems, and society. Despite decades of growing research output, substantial gaps persist between investigations on the diversity of causes, reflected in data and model insufficiency. These gaps hinder the understanding of the issue and impede the effectiveness of mitigation measures. Many studies have urged to include all identified subsidence processes acting in a single area in an integral framework, for which a complex analysis has not systematically been outlined before. Therefore, [they] focus here on bridging the gaps between various technical research disciplines involved. [They] stress the urgency for an integral approach that combines observations with subsurface information of all known subsidence processes in an area, and [they] appeal for utilizing them in physics-guided data integrations. Only then can all subsidence drivers be understood, and effective mitigation measures designed. [They] outline the elements for an integral approach in categorical tables and schematized figures, and [they] discuss the main opportunities and challenges in a stepwise workflow. Leveraging these opportunities naturally leads to more robust, scalable, and policy-relevant solutions and fosters a more sustainable future…”
#Land #subsidence #processes #Verticallandmotion #SLR #sealevel #sealevelrise #relativesealevelrise #modeling #data #model #InSAR #elevation #holistic #GIS #spatial #mapping #climate #drought #extremeweather #climatechange #climateadaption #ecosystems #measurement #monitoring #research #review #framework #overview #risk #hazard #anthropogenic #mitigation #engineering #water #hydrology #policy #planning #design #remotesensing #spatialanalysis #spatiotemporal

A day of warning may be enough to break up an incoming asteroid, simulations suggest

Follow us and never miss a story.

https://1ban.news/nt1-short-warning-mitigation-2026-08-04/

#1ban #nt1 #short #warning #mitigation #space

Flood And Landslide Susceptibility Assessment And Multi Hazard Interaction Mapping Using Machine Learning And GIS For Sustainable Settlement Planning In Nepal
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https://doi.org/10.1007/s44288-026-00670-8 <-- shared paper
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H/T @Narayan Thapa | Earth Data Modeling
“Nepal lies within an active seismic zone and is influenced by most dynamic climatic systems in the world. It faces compounding floods and landslide threats. Impacts are worst where multi-hazard interactions create spatially linked corridors. Despite frequent co-occurrence, national-scale assessments remain limited. This study presents machine learning and GIS-based approach to map nationwide susceptibility to floods, landslides, and identify their potential interaction zones, and delineate critical multi-hazard flow zones through spatial adjacency analysis. Using Google Earth Engine, the Random Forest model integrates topographic, climatic, environmental, and hydrological datasets to overcome subjective expert-driven methods. The model achieved strong predictive accuracy (AUC: 0.84 for floods, 0.85 for landslides). The results showed 19% of Nepal’s lowlands are medium to very highly susceptible to inundation, threatening approximately 900,000 people and over 3.4 million buildings; whilst in the hilly terrains, 40% is susceptible to slope-failure endangering 200,000 people and about 0.6 million buildings. K-means clustering followed by spatial adjacency analysis identified four spatial zonation: 81% of national area as low-hazard zone, 9% as flood-only zone, 5% as landslide-only zone, and 5% as interaction zones. Critical multi-hazard flow zone covering 7,588 km² represents spatially connected corridors linking interaction zones to downstream flood-prone populated areas, affecting 88 km² built-up land and 1,722 km² cropland. These zones represent susceptibility-based spatial connectivity rather than physically simulated cascading processes. These findings support recommendations for risk-informed land-use planning, resilient infrastructure development and climate adaptation aligned to sustainable development and investment risk screening…”
#GIS #spatial #mapping #GoogleEarthEngine #MachineLearning #RemoteSensing #GeospatialAI #DisasterRiskReduction #MultiHazard #ClimateAdaptation #climatechange #extremeweather #LandUsePlanning #SustainableDevelopment #InfrastructurePlanning #RiskAssessment #NaturalHazards #Nepal #EarthObservation #HinduKushHimalaya #HKH #HinduKush #Himalayas #risk #hazard #assessment #national #regional #spatialanalysis #spatiotemporal #massmovement #landslide #assessment #mitigation #water #hydrology #flood #flooding #sustainability

Modeling Flood Susceptibility Utilizing Advanced Ensemble Machine Learning Techniques in the Marand Plain [Iran]
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https://doi.org/10.3390/geosciences15030110 <-- shared paper
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H/T @Geosciences MDPI
“This study applies advanced machine learning algorithms to map flood susceptibility in northwest Iran. The results demonstrate strong predictive performance, with the Locally Weighted Linear model delivering the highest accuracy and providing valuable guidance for flood-risk management and disaster mitigation…”
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“Flooding is one of the most significant natural hazards in Iran, primarily due to the country’s arid and semi-arid climate, irregular rainfall patterns, and substantial changes in watershed conditions. These factors combine to make floods a frequent cause of disasters. In this case study, flood susceptibility patterns in the Marand Plain, located in the East Azerbaijan Province in northwest Iran, were analyzed using five machine learning (ML) algorithms: M5P model tree, Random SubSpace (RSS), Random Forest (RF), Bagging, and Locally Weighted Linear (LWL). The modeling process incorporated twelve meteorological, hydrological, and geographical factors affecting floods at 485 identified flood-prone points. The data were analyzed using a geographic information system, with the dataset divided into 70% for training and 30% for testing to build and validate the models. An information gain ratio and multicollinearity analysis were employed to assess the influence of various factors on flood occurrence, and flood-related variables were classified using quantile classification. The frequency ratio method was used to evaluate the significance of each factor. Model performance was evaluated using statistical measures, including the Receiver Operating Characteristic (ROC) curve. All models demonstrated robust performance, with an area under the ROC curve (AUROC) exceeding 0.90. Among the models, the LWL algorithm delivered the most accurate predictions, followed by RF, M5P, Bagging, and RSS. The LWL-generated flood susceptibility map classified 9.79% of the study area as highly susceptible to flooding, 20.73% as high, 38.51% as moderate, 29.23% as low, and 1.74% as very low. The findings of this research provide valuable insights for government agencies, local authorities, and policymakers in designing strategies to mitigate flood-related risks. This study offers a practical framework for reducing the impact of future floods through informed decision-making and risk management strategies…”
#FloodSusceptibility #FloodRisk #MachineLearning #GIS #NaturalHazards #DisasterManagement #FloodModeling #Hydrology #EnvironmentalMonitoring #RiskAssessment #GeospatialAnalysis #ClimateResilience #GIS #spatial #mapping #Iran #MarandPlain #EastAzerbaijan #machinelearning #AI #floodhazard #floodvulnerability #flood #flooding #water #hydrography #hydrology #model #modeling #risk #hazard #rainfall #precipitation #extremeweather #spatialanalysis #spatiotemporal #modelperformance #policy #planning #mitigation #design #riskmanagement

🚨How should Europe deal with #climaterisks? Climate #mitigation #adaptation is becoming essential. 🎙️Watch the latest EEA 'climate and environment' podcast pisode or 🎧wherever you download your podcasts 🔗https://www.youtube.com/watch?v=vbJhUyCqi4Y

🚨How should Europe deal with #climaterisks?
Climate #mitigation #adaptation is becoming essential.
🎙️Watch the latest EEA 'climate and environment' podcast pisode or 🎧wherever you download your podcasts
🔗piped.video/watch?v=vbJhUyCq…
---
https://nitter.net/EUEnvironment/status/2084560419302072606#m

Tackling Climate Change means tackling poverty at the same time.

It is said that “poverty is always with us”. However as the UN rapporteur on extreme poverty said, “Poverty is not inevitable, it is manufactured”.

We are responsible for many of the issues holding developing countries back. We can and must do things differently in order to improve our chances of dealing with Climate Change, for all our sakes.

https://agrandmothersdream.com/we-cant-solve-climate-change-without-fixing-poverty/

#climatechange
#mitigation
#poverty

Unraveling The Drivers Of Water Shortage Across Spatial Scales And Sectors In Colorado's West Slope River Basins
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https://doi.org/10.1029/2026EF008137 <-- shared paper
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['sorry' about your Kentucky Bluegrass, almonds, etc... /s]
H/T Sai Veena Sunkara | Postdoctoral Associate
“…Colorado’s West Slope basins provide nearly 70% of the inflows to Lake Powell and are also essential to communities, agriculture, industry, hydropower, and downstream Colorado River users.
To examine the wide range of possible futures, [they] simulated 2.1 million years, defining 20,000 plausible scenarios applying changes to streamflow, snowmelt timing, drought persistence, and agricultural, municipal, and industrial water demand.
A key finding is that there is 𝗻𝗼 𝘀𝗶𝗻𝗴𝗹𝗲 𝗰𝗮𝘂𝘀𝗲 𝗼𝗳 𝗳𝘂𝘁𝘂𝗿𝗲 𝘄𝗮𝘁𝗲𝗿 𝘀𝗵𝗼𝗿𝘁𝗮𝗴𝗲𝘀. The most influential drivers vary by basin, sector, and water user. In some areas, shortages are driven primarily by persistent low-flow conditions or changing snowmelt timing. In others, increasing municipal, industrial, or irrigation demand plays a larger role. This suggests that adaptation strategies must be tailored to specific basins and users rather than relying on a single, system-wide solution. Other major findings are
• West Slope deliveries to Lake Powell could fall more than 50% below the current median baseline
• Storage in major West Slope reservoirs could decline 40–55% below historical medians
These results underscore the need for water-planning approaches that account for deep uncertainty, persistent drought, shifting snowmelt patterns, and sector-specific demand…”
#Colorado #waterallocation #StateMod #USWest #USA #WesternSlope #waterresources #watersecurity #watershortage #drought #snowmelt #rainfall #precipitation #riverbasin #water #hydrography #hydrology #reasons #agriculture #industry #hydropower #streamflow #surfacewater #municipal #irrigation #adaptationstrategies #planning #policy #mitigation #ColoradoRiver #basins #climatechange #extremeweather #populationpressure #waterdemand #waterrights #model #modeling #HiddenMarkovModel #stochastic #projecteddemand #ColoradoRiverBasin #wateruse #spatial #mapping #spatialanalysis #spatiotemporal #strategy

Quantifying UK Coastal Flood Exposure Under Future Sea-Level Rise To [2100 and] 2300
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https://doi.org/10.1038/s41467-026-74982-1 <-- shared paper
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https://www.theguardian.com/environment/2026/jul/21/millions-long-term-coastal-flooding-risk-uk-climate-action <-- shared media article
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H/T @University of Bristol School of Geographical Sciences
“🌊 New research on long-term coastal flooding as a result of climate inaction 🌊
… The researchers found:
🔷 By 2100 at least an additional 0.5 million people exposed to the 1-in-200 year undefended flood extent - a 25% increase compared to present day.
🔷 Under the most pessimistic storyline by 2300 involving significant ice-sheet instability, an additional 13 million people could be exposed to the 1-in-200 year undefended flood event.
🔷 Under some scenarios there is a need for large-scale movement of populations and settlements away from the coast in the coming centuries…”
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“Up to 13 million people in the UK face the long-term risk of coastal flooding due to the climate crisis, scientists have warned, with a ‘reasonable worst-case scenario’ suggesting the need for the large-scale movement of populations away from a dramatically reshaped coast…
Sea level has risen by about 20cm around the UK in the last century and is accelerating. A further 40cm to 60cm by 2100 is already baked in, meaning about half a million more people will be at risk of their homes being flooded, on top of the 2.5 million already in danger near the coasts. Lincolnshire and the Humber estuary are most in danger…”
--
“The latest Intergovernmental Panel on Climate Change assessment report highlighted the potential for more than 15 metres of global sea-level rise by 2300. In this study, [the authors] explore the implications for UK coastal flood exposure by combining national-scale flood modelling with physically-based storylines of UK sea-level rise. By 2100 all storylines show broadly similar results with at least an additional ½ million people exposed to the 1-in-200 year undefended flood extent, which represents a 25% increase compared to present day. Under the most pessimistic storyline by 2300 involving significant ice-sheet instability, an additional 13 million people could be exposed to the 1-in-200 year undefended flood event. This would imply the potential need for large-scale movement of populations and settlements away from the coast in the coming centuries. Given current global emissions pledges, exposure increases by 1.7 million people by 2300, however up to 1 million could be avoided if Paris Agreement targets for greenhouse gas emissions are met…”
#coast #coastal #innundation #climatechange #global #sealevel #sealevelrise #SLR #flood #flooding #climatechange #population #infrastructure #UK #England #Scotland #Wales #NorthernIreland #Lincolnshire #Humber #estuary #settlement #city #urban #mitigation #planning #policy #infrastructure #risk #hazard #humanimpacts #spatialanalysis #spatiotemporal #GIS #spatial #mapping #coastalflooding #climatecrisis #model #modeling #elevation #DEM

NOAA’s SOLAR-1 Enters New Era Of Space Weather Monitoring
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https://www.noaa.gov/news-release/noaas-solar-1-enters-new-era-of-space-weather-monitoring <-- shared technical article
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https://www.spaceweather.gov/ <-- shared NOAA Space Weather Prediction Center (SWPC) home page
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https://www.nesdis.noaa.gov/our-satellites/future-programs/swfo/space-weather-observations-l1-advance-readiness-solar-1 <-- shared SOLAR-1 overview and details page
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https://www.nesdis.noaa.gov/our-environment/space-weather <-- shared overview of space weather and its risk, hazards & impacts
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[I was lucky enough to see the launch from the Kennedy Space Center of GOES-19/U, my first launch - and love reading about the ‘ongoing story’…]
#spaceweather #solar #monitoring #risk #hazard #impacts #humanimpacts #SOLAR1 #SOLAR-1 #SpaceWeatherPredictionCenter #NOAA #NESDIS #earlywarningsystem #monitoring #risk #hazard #mitigation #infrastructure #satellites #electric #powergrid #blackouts #brownouts #transformers #utilities #energy #aviation #nationalsecurity #defence #missileguidance #agriculture #farming #precisionagriculture #GPS #vanigation #transportation #spaceflight #LaGrange #L1 #protection #coronagraph #SWPC #NESDIS #opendata #publicgood #fedservice #fedscience
#NOAA

Странные машины: как хакеры собирают процессор из данных

Как часто нам приходится читать в бюллетенях безопасности «Уязвимость... позволяющая нарушителю выполнить произвольный код с помощью специально сформированного запроса» . Но что на самом деле скрывается за этой фразой? Что это за специальные запросы и как наша программа может выполнять чужой код, если мы досконально знаем в ней каждую строчку и каждую библиотеку? И почему Apple выстроила многоуровневую аппаратную защиту и платит до двух миллионов долларов за одну найденную уязвимость, но айфоны все равно взламывают по нажатию одной кнопки? Дело в том, что сами атаки стали другими. Когда инженеры перекрыли большинство очевидных ходов, хакерам пришлось изменить сам подход к взлому. Вместо поиска лазеек они научились заставлять программу работать против самой себя. Теперь атакующие берут легитимные вычисления программы и строят поверх них... виртуальный процессор. Хакеры умудрились обернуть против нас даже банальную функцию printf , превратив её в универсальный интерпретатор языка Brainfuck. Она обладает Тьюринг‑полнотой — а значит, внутри неё можно реализовать любой зловредный алгоритм. Перед нами — Data‑Only атаки, где наш собственный код становится оружием, а взлом превращается в программирование на «невидимом» процессоре. Процессоре, команды которого — лишь побочный эффект работы нашей собственной программы. Но обо всем по порядку. Как же мы докатились до жизни такой?

https://habr.com/ru/articles/1059800/

#hardening #харденинг #переполнение_буфера #переполнение_стека #mitigation #эксплойты

📢📝 New UBA report on international #ClimateAction: GST in NDCs - How the first Global Stocktake is reflected in the new NDCs

The Global Stocktake #GST regularly reviews the global effort towards international climate action. In their Nationally Determined Contributions #NDCs countries outline their contribution to this global effort.

In this UBA project, a multi-stage analysis was used to evaluate how #mitigation related outcomes of the first GST have been integrated into the new NDCs.

"How to Prevent #Disasters - A Cup of Tea With, #Podcast" https://uclpress.co.uk/podcast/how-to-prevent-disasters-ilan-kelman
 
#DisastersAreNotNatural #NoNaturalDisasters (avoid the phrases #NaturalDisaster #NaturalDisasters) #DRR #DisasterRiskReduction #DisasterRiskManagement #DisasterPrevention #Prevention #DisasterMitigation #Mitigation #DisasterPreparedness #Preparedness

A Scale-Invariance-Based Algorithm Application For Land Surface Temperature Downscaling In Denmark
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https://doi.org/10.3390/rs18132263 <-- shared paper
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https://zenodo.org/records/20863040 <-- shared open data for downscaled LST dataset for Copenhagen
--
H/T @CLIM4cities
#urbanclimate #downscaling #landsurfacetemperature #LST #AI #machinelearning #scaleinvariance #residualcorrection #Sentinel #Landsat #satellite #remotesensing #earthobservation #CLIM4cities #UrbanClimate #ClimateServices #MachineLearning #ClimateAdaptation #heatwave #temperature #ontheground #Copenhagen #Denmark #impervioussurface #asphalt #roof #concrete #albedo #heatabsorption #mitigation #urban #urbancentre #treecover #vegetation #urbanheatisland #planning #design #hotspots #monitoring #spatialanalysis #spatiotemporal #model #modeling #usecase #operational #climatechange #extremeweather #evidencebased #adapation #sustainability #urbanplanning #climateresilience #EssentialClimateVariable #ECV
@+ATLANTIC | @Danish Meteorological Institute | @ESA Φ-lab Collaborative Innovation Network | @CLIM4cities

Brussels pivots from #climate #mitigation to #adaptation as #heatwaves expose vulnerabilities | Euronews

https://www.euronews.com/my-europe/2026/07/03/brussels-pivots-from-climate-mitigation-to-adaptation-as-heatwaves-expose-vulnerabilities

'We're going to break 50°C' — Europe's summers are about to radically change | DW News

https://piefed.social/c/europe/p/2176983/we-re-going-to-break-50degc-europe-s-summers-are-about-to-radically-change-dw-news

Schlage als #Mitigation|smaßnahme die Umbenennung von "Sommer" in "Hitzewelle" vor.

Hitzewellenferien, Hitzewellenurlaub, Dr. Hitzewelle-Team.

#Klimakrise

How Space Weather Could Bust The AI Boom
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https://spacenews.com/how-space-weather-could-bust-the-ai-boom/ <-- shared technical article
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https://futurism.com/artificial-intelligence/ai-data-centers-electric-grid-meltdown <-- shared technical article, “AI Data Centers Pushing Electric Grid Into Meltdown”
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https://doi.org/10.1146/annurev-earth-032524-012356 <-- shared 2026 paper, “Magnetic Storms and Geoelectric Hazards”
--
#AI #datcenters #infrastructure #impacts #solarstorms #spaceweather #risk #hazards #overloading #electricity #energy #powersupply #energygrid #vulnerable #transmission #energy #demand #consumers #geoelectrical #geomagnetism #blackout #damage #cost #economics #equipment #transformers #carringtonevent #NERC #grid #reliability #electricaldemand #utilities #magneticstorm #electromagneticinduction #extremeevent #historicalevent #hazardanalysis #spaceweather #history #Carrington #geoelectric #humanimpacts #risk #hazard #monitoring #network #geology #geomagnetism #impedance #rock #soil #utilities #electricaltransmission #powerlines #magnetotelluric #sensor #blackout #brownout #energy #geoelectrichazard #geoelectric #GIS #spatial #mapping #spatialanalysis #spatiotemporal #model #modeling #geomagnetism #geomagneticstorm #telecommunication #electronics #hardened #geography #mitigation #preparedness #geomorphology #geomorphometry #surfacegeology #cost #economics #disaster #impacts #technology #InternetOfThings #internet #USA #review #CONUS #numericalmodeling #realtimemonitoring #AIBoom #Bust
@North American Electric Reliability Corporation (NERC)

https://www.theguardian.com/environment/2026/jun/24/as-temperatures-soar-in-baking-britain-how-are-workers-coping-in-the-heat; https://www.theguardian.com/environment/2026/jun/23/searing-uk-heat-leaves-schools-hospitals-and-transport-networks-struggling-to-cope; https://www.theguardian.com/education/2026/jun/24/failure-to-plan-for-rising-temperatures-has-left-uks-schools-sweltering. There is a difference between #mitigation & #adaptation, which you are confusing here, @guardian. Furthermore, it isn't the #schools themselves that are to blame for the architectural #designs of #buildings that have been foisted on them, but those in #authority who insisted on those designs. You might as well blame the schools for the #climatecrisis itself!

6/
From [2]:

"#ClimateChange is [...] forecast to become the predominant pressure on #biodiversity and its ecosystem functions [...]. The interplay and feedback between the climate and biodiversity #crises call for integrated national and European policy responses. Systemic policy approaches to #pollinator stewardship,[...] also highlight the #IntegratedPolicy approach required to meet the generational challenge of #NatureRestoration and #mitigation of and #adaptation to drastic climate change"