Latest news with #ERA5
Hindustan Times
26-06-2025
- Science
- Hindustan Times
Weather Bee: First half of 2025 likely to breach 1.5°C warming threshold
With data for nearly half of 2025 in, there is both good news and bad news for global temperature. The bad news is that the first half of the year is the second warmest in 2025 and more than 1.5°C warmer than the pre-industrial average, a threshold that global leaders agreed to keep long-term warming under in the 2015 Paris Agreement. The good news is that June warming is likely to end up below the 1.5°C threshold, the second consecutive month to do so. This is likely to keep the probability of 2025 ending as the warmest year lower than it was earlier in the year. PREMIUM File photo Global temperature data from the ERA5 dataset produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) is now available up to June 23. With just a week of data to be factored in for June, the trends for half of the year seen right now should not change by a big margin by the end of the month. This shows that the average warming in the first 174 days of 2025 is 1.53°C. This makes the first half of the year the second warmest on record in 2025, after 2024, which experienced 1.62°C in the first 174 days. 2025 is also only the second year when the first half of the year has breached the 1.5°C threshold. Chart 1 HT photo To be sure, while the first six months of the year average a warming of more than 1.5°C, this is because of the warming up to April. All of the first four months of 2025 averaged a warming of more than 1.5°C, but May averaged a warming of 1.39°C and June so far is only 1.31°C warmer than the pre-industrial average. If the trends seen so far carry on until the month's end, June will only be only the second consecutive month and third month since July 2023 (apart from July 2024 and May 2025) that does not average a warming of more than 1.5°C. The level of warming in May and June, however, should not be taken as a sign that the world is still far away from breaching the 1.5°C threshold in long-term averages. The reason for this is the recent trend in global warming. The 2015-2024 averages of warming in each month show that June warming was the least and May warming is ranked fourth lowest. In fact, as the accompanying chart shows, warming has been generally lower in the middle of the year, when the northern hemisphere experiences its summer. May, June, and July are also the only months that have crossed the 1.5°C threshold only once (either in 2023 or 2024). Chart 2 HT photo Clearly, the lower level of warming in May and June is not out of the ordinary in a world headed towards long-term 1.5°C warming. In fact, even the rest of the year needs to average only 1.47°C for 2025 to breach the threshold on average. For becoming the second-warmest year on record – a record currently held by 2023, which averaged 1.48°C warming in the ERA5 dataset – the rest of the year needs to average a warming of only 1.44°C. However, May and June averaging a warming below 1.5°C has helped in one way. An unprecedented 1.66°C warming will be required in the rest of the year for 2025 to beat the 2024 record and become the warmest year on record. The previous record for the June 24-December 31 period is currently held by 2023, when the period averaged 1.65°C warming. The lower level of warming in May is also why the probability for 2025 ending up as the warmest year on record was drastically decreased by Berkeley Earth (another organization that publishes a global temperature dataset updated monthly) in their May update compared to their April update: from 18% to 6%. However, Berkeley's earth forecast for the year ending up 1.5°C warmer in their record is still 43%, a relatively small reduction compared to the 52% forecast in the April update. This is why the global temperature trends in the first half of the year are a mixed bag.
The Verge
12-06-2025
- Science
- The Verge
Google has a new AI model and website for forecasting tropical storms
Google is using a new AI model to forecast tropical cyclones and working with the US National Hurricane Center (NHC) to test it out. Google DeepMind and Google Research launched a new website today called Weather Lab to share AI weather models that Google is developing. It says its new, experimental AI-based model for forecasting cyclones — also called typhoons or hurricanes when they reach a certain strength — can generate 50 different scenarios for a storm's possible track, size, and intensity up to 15 days in advance. The NHC is working with Google to evaluate the effectiveness of the model. The collaboration comes after the Trump administration and DOGE slashed the National Weather Service's staff and capacity for federal climate and weather research. Other companies and weather agencies are also exploring whether AI can improve forecasts, but technological advances so far don't eliminate the need for traditional weather models. Google released a research paper today, which has yet to be peer-reviewed, on how its tropical cyclone model works. It claims that its model's predictions are at least as accurate as those of traditional physics-based models. We'll have to see what the National Hurricane Center's rating of it is as the Atlantic hurricane season churns through November. For now, the aim is to strengthen NHC's forecasting in order to give people more accurate warnings and time to prepare for a storm. According to Google, its model's five-day predictions for cyclone tracks in the North Atlantic and East Pacific were 87 miles (140 km) closer, on average, to the storm's actual track than predictions from the European Center for Medium-Range Weather Forecasts (ECMWF) in 2023 and 2024. Weather Lab's interactive website lets people see how AI models compare to the ECMWF's physics-based models. But Google is emphasizing that its website is just a research tool for now — not something the public should rely on for forecasts. Google's cyclone model is trained on data from Europe's ERA5 archive, which includes hundreds of millions of observations collected by weather agencies around the world combined with predictions from a traditional weather model. The company also used ERA5 to train its previous AI weather prediction model GenCast. That model outperformed one of ECMWF's leading physics-based models 97.2 percent of the time, according to research published in the journal Nature in December 2024. Animation showing the Google model's prediction for Cyclone Alfred when it was a Category 3 cyclone in the Coral Sea. The model's ensemble mean prediction (bold blue line) correctly anticipated Cyclone Alfred's rapid weakening to tropical storm status and eventual landfall near Brisbane, Australia, seven days later, with a high probability of landfall somewhere along the Queensland coast. Credit: Google The company says it's also working with the Cooperative Institute for Research in the Atmosphere at Colorado State University and other researchers in the UK and Japan to improve its AI weather models. The importance of real-world observations and older weather models in developing these new kinds of tools is one reason why AI is so far only poised to assist traditional weather forecasting instead of replacing it. Adjusting to a changing climate will also hinge on the ability to collect and analyze new data on increasingly extreme and erratic weather events. How well the US can keep up with this kind of research, however, is a growing concern under the Trump administration. DOGE's rampage through the federal government has taken its toll at the federal agency that houses the NHC and the National Weather Service, the National Oceanic and Atmospheric Administration (NOAA). The National Weather Service reduced the number of weather balloon launches after staffing cuts, and NOAA is increasingly relying on weather balloon data from private companies. Project 2025 called for dismantling NOAA — which leads climate research on top of providing weather forecasts — and privatizing much of its services. Some advocates are raising alarm over the prospect of turning weather forecasts into a paid product instead of a free service available to anyone and everyone. 'For a long time, weather has been viewed as a public good, and I think, you know, most of us agree with that … Hopefully we can contribute to that, and that's why we're trying to kind of partner with the public sector,' Peter Battaglia, a research scientist at Google DeepMind, said in a press call when The Verge asked about concerns surrounding privatizing weather services. Tellingly, Google's announcement today doesn't mention the climate crisis like the company has in previous launches for this kind of program. 'As climate change drives more extreme weather events, accurate and trustworthy forecasts are more essential than ever,' it said in a December 4 announcement for GenCast.
IOL News
12-06-2025
- Climate
- IOL News
Floods and climate resilience: key findings from South Africa's weather-related disasters study
File image of damages caused by the April 2024 flash flood in Margate on the KZN South Coast. Image: Johan Steyn As the death toll rises to 67 from the recent floods in the Eastern Cape, Dr Mary-Jane Bopape., Managing Director of the South African Environmental Observation Network (NRF-SAEON), along with her research collaborators, just released a comprehensive analysis of weather-related disasters in South Africa from 1980 to 2023. The research, utilising data from respected sources such as the Emergency Events Database (EM-DAT) and synoptic charts provided by the South African Weather Service, offers critical insights that are set to transform our understanding of climate resilience and disaster management. The study, which draws on sophisticated meteorological reanalyses such as the fifth generation European Centre for Medium Range Weather Forecasting reanalysis (ERA5) and data from the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), identifies floods and storms as the most recurrent weather-related disasters faced in South Africa. Notably, KwaZulu-Natal (KZN) province is highlighted as the most affected region, with the eThekwini Metropolitan Municipality emerging as the area with the highest number of recorded disaster events across the entire country. Remarkably, while KZN is known for its high rainfall, the research indicates that eThekwini does not necessarily experience more rainfall compared to other districts within the province. This surprising outcome suggests that human factors tied to urbanisation may exacerbate the impacts of weather-related disasters in these metropolitan areas. Video Player is loading. Play Video Play Unmute Current Time 0:00 / Duration -:- Loaded : 0% Stream Type LIVE Seek to live, currently behind live LIVE Remaining Time - 0:00 This is a modal window. Beginning of dialog window. Escape will cancel and close the window. Text Color White Black Red Green Blue Yellow Magenta Cyan Transparency Opaque Semi-Transparent Background Color Black White Red Green Blue Yellow Magenta Cyan Transparency Opaque Semi-Transparent Transparent Window Color Black White Red Green Blue Yellow Magenta Cyan Transparency Transparent Semi-Transparent Opaque Font Size 50% 75% 100% 125% 150% 175% 200% 300% 400% Text Edge Style None Raised Depressed Uniform Dropshadow Font Family Proportional Sans-Serif Monospace Sans-Serif Proportional Serif Monospace Serif Casual Script Small Caps Reset restore all settings to the default values Done Close Modal Dialog End of dialog window. Advertisement Next Stay Close ✕ The Managing Director of the South African Environmental Observation Network (NRF- SAEON), Dr Mary-Jane Bopape Image: Supplied "With these insights, we can better inform climate resilience strategies and proactive disaster management efforts. This important contribution to the field paves the way for more effective responses to climate challenges and disaster preparedness in our communities," says Dr Bopape. Her vision is clear: to leverage this study's findings for the benefit of future policies and community safety. Across South Africa, the research highlights that major urban centres, particularly the eThekwini, Johannesburg, Ekurhuleni, and Cape Town metropolises, report significant occurrences of weather-related disasters. Notably, Johannesburg has been identified as a hotspot for floods, while Ekurhuleni leads in storm incidents within Gauteng province. However, urbanisation patterns may play a pivotal role in shaping disaster outcomes, with Gauteng noted for reporting the fewest droughts, likely due to its urban character.
