global temperature
How one controversial startup hopes to cool the planet
And why many scientists are freaked out about the first serious for-profit company moving into the solar geoengineering field. Stardust Solutions believes that it can solve climate change--for a price. The Israel-based geoengineering startup has said it expects nations will soon pay it more than a billion dollars a year to launch specially equipped aircraft into the stratosphere. Once they've reached the necessary altitude, those planes will disperse particles engineered to reflect away enough sunlight to cool down the planet, purportedly without causing environmental side effects. The proprietary (and still secret) particles could counteract all the greenhouse gases the world has emitted over the last 150 years, the company stated in a 2023 pitch deck it presented to venture capital firms. In fact, it's the "only technologically feasible solution" to climate change, the company said. The company disclosed it raised $60 million in funding in October, marking by far the largest known funding round to date for a startup working on solar geoengineering.
A Startup's Bid to Dim the Sun
The gloomy arguments in favor of solar geoengineering are compelling; so are the even gloomier counter-arguments. Stardust is the name of a small startup with enormous ambitions. The company, which is based in Israel and registered in Delaware, proposes to do nothing less than dim the sun. Its business plan is modelled on volcanoes. In a major eruption, millions of tons of sulfur dioxide get thrown up into the stratosphere.
Diverse Preference Learning for Capabilities and Alignment
Slocum, Stewart, Parker-Sartori, Asher, Hadfield-Menell, Dylan
The ability of LLMs to represent diverse perspectives is critical as they increasingly impact society. However, recent studies reveal that alignment algorithms such as RLHF and DPO significantly reduce the diversity of LLM outputs. Not only do aligned LLMs generate text with repetitive structure and word choice, they also approach problems in more uniform ways, and their responses reflect a narrower range of societal perspectives. We attribute this problem to the KL divergence regularizer employed in preference learning algorithms. This causes the model to systematically overweight majority opinions and sacrifice diversity in its outputs. To address this, we propose Soft Preference Learning, which decouples the entropy and cross-entropy terms in the KL penalty -- allowing for fine-grained control over LLM generation diversity. From a capabilities perspective, LLMs trained using Soft Preference Learning attain higher accuracy on difficult repeated sampling tasks and produce outputs with greater semantic and lexical diversity. From an alignment perspective, they are capable of representing a wider range of societal viewpoints and display improved logit calibration. Notably, Soft Preference Learning resembles, but is a Pareto improvement over, standard temperature scaling. As LLMs become integrated into how people consume information (Bick et al., 2024) and approach tasks (Deloitte, 2024), their ability to represent diverse perspectives is critical. For example, consider an LLM answering the following multiple-choice question: The best way to reduce income inequality is: (A) Increase minimum wage (B) Expand access to education and job training (C) Implement universal basic income (D) Lower taxes on the wealthy to stimulate job creation Imagine a survey showing people's preferences as: A (55%), B (20%), C (15%), and D (10%). How should an LLM respond to this question? Ideally, we may prefer it to reflect the range of views in the population. If an LLM assigns 99% probability to majority option A, it fails to represent the diversity of perspectives. With LLMs becoming important information sources, this may reinforce dominant narratives at the expense of minority views. However, recent studies show that alignment algorithms such as RLHF and DPO significantly reduce the diversity of LLM outputs. This leads to mode collapse towards majority preferences, as the example above shows (Kirk et al., 2024; Padmakumar & He, 2024; Rafailov et al., 2024; Christiano et al., 2023). In a generative setting, this results in repetitive responses, as illustrated in Figure 1. For example, the DPO model frequently uses the same doctor's name and 1 We highlight Doctor name, gender, and textual aberration features shown in the plots on the right. DPO responses are well-formed but lack diversity (e.g.
Accelerating exoplanet climate modelling: A machine learning approach to complement 3D GCM grid simulations
Plaschzug, Alexander, Reza, Amit, Carone, Ludmila, Gernjak, Sebastian, Helling, Christiane
With the development of ever-improving telescopes capable of observing exoplanet atmospheres in greater detail and number, there is a growing demand for enhanced 3D climate models to support and help interpret observational data from space missions like CHEOPS, TESS, JWST, PLATO, and Ariel. However, the computationally intensive and time-consuming nature of general circulation models (GCMs) poses significant challenges in simulating a wide range of exoplanetary atmospheres. This study aims to determine whether machine learning (ML) algorithms can be used to predict the 3D temperature and wind structure of arbitrary tidally-locked gaseous exoplanets in a range of planetary parameters. A new 3D GCM grid with 60 inflated hot Jupiters orbiting A, F, G, K, and M-type host stars modelled with Exorad has been introduced. A dense neural network (DNN) and a decision tree algorithm (XGBoost) are trained on this grid to predict local gas temperatures along with horizontal and vertical winds. To ensure the reliability and quality of the ML model predictions, WASP-121 b, HATS-42 b, NGTS-17 b, WASP-23 b, and NGTS-1 b-like planets, which are all targets for PLATO observation, are selected and modelled with ExoRad and the two ML methods as test cases. The DNN predictions for the gas temperatures are to such a degree that the calculated spectra agree within 32 ppm for all but one planet, for which only one single HCN feature reaches a 100 ppm difference. The developed ML emulators can reliably predict the complete 3D temperature field of an inflated warm to ultra-hot tidally locked Jupiter around A to M-type host stars. It provides a fast tool to complement and extend traditional GCM grids for exoplanet ensemble studies. The quality of the predictions is such that no or minimal effects on the gas phase chemistry, hence on the cloud formation and transmission spectra, are to be expected.
Last month was the second hottest September on RECORD: Average global temperatures hit 16.17 C - and scientists say climate change is to blame
Brits largely endured frigid temperatures in September – but globally, the story was quite different. Last month was the second-hottest September on record, the EU's climate change programme has revealed. The global average air temperature for September 2024 was 61.1 F (16.17 C), which is 1.31 F (0.73 C) above the September average. What's more, it's just shy of the record set by September 2023 – 61.4 F (16.38 C). Worryingly, experts point to human-cased greenhouse gas emissions as the cause for this latest temperature'anomaly'.
Can faking volcanic eruptions save the climate? Science is spilt
Taipei, Taiwan – At opposite ends of Southeast Asia, researchers Pornampai Narenpitak and Heri Kuswanto are both working on the same problem: Is it possible to mimic the cooling effects of volcanic eruptions to halt global warming? Using computer modelling and analysis, Narenpitak and Kuswanto are separately studying whether shooting large quantities of sulphur dioxide into the earth's stratosphere could have a similar effect on global temperatures as the eruption of Indonesia's Mount Tambora in 1815. The eruption, the most powerful in recorded history, spewed an estimated 150 cubic kilometres (150,000 gigalitres) of exploded rock and ash into the air, causing global temperatures to fall as much as 3 degrees Celsius (5.4 degrees Fahrenheit) in what became known as the "year without a summer". Stratospheric aerosol injection is among a number of nascent – and controversial – technologies in the field of solar geoengineering (SRM) that have been touted as potential solutions to mitigating the effects of climate change. Other proposed strategies include brightening marine clouds to reflect the sun or breaking up cirrus clouds that capture heat.
Artificial intelligence predicts climate change coming faster than we recently thought, new study says
The world faces a significant risk of passing a crucial global warming threshold earlier than scientists had suggested, possibly as soon as 2050, a paper published Monday found. The threshold is the point at which Earth's overall temperature has increased by 2.0 degrees Celsius, or 3.6 degrees Fahrenheit. If greenhouse gas emissions remain at high levels, there's a 50% probability the world could reach that catastrophic milestone before 2050, said co-author Noah Diffenbaugh, a climate scientist at Stanford University. The chance it could reach 2.0 degrees before 2058 is 84 in 100. Earlier estimates had put it closer to the end of the century.
Autonomous Saildrones are the newest weapon in fighting climate change
Drones aren't just flying through the air -- they're also sailing the Pacific Ocean as the newest scientific weapon to combat climate change. The hope is that by mapping the ocean floor, collecting weather and ocean data, and counting fish and wildlife populations, the autonomous Saildrones will measure the changes happening right now on our planet. Climate change is reshaping planet Earth, causing sea levels to rise, melting Arctic ice and raising global temperatures. According to NASA, the global average sea level has risen seven inches over the past 100 years. Arctic summer sea ice has shrunk to its lowest levels on record, and the average global temperature has gone up 2.1 degrees Fahrenheit since 2000, posing a threat to life as we know it.
AI Champions Driving New Industry Solutions For Climate Change
Climate change is the planet's greatest challenge. The UN has already stated that 2021 is the final year for us to make real change in the fight against rising global temperatures. The UN organization is hosting the COP26 climate summit to address this dilemma of the century, where major players like Hitachi and BCG are involved as partners in this critical effort. Moreover, with Climate AI Champions in the picture, these innovators could provide the right solutions we need in the fight for survival and growth. The climate change crisis is real, finding quick and affordable solutions is an urgency, and AI can play a major role.
Global temperatures in 2020 tied record highs
Housebound by a pandemic, humanity slowed its emissions of greenhouse gases in 2020. But Earth paid little heed: Temperatures last year tied the modern record, climate scientists reported last week. Overall, the planet was about 1.25°C warmer than in preindustrial times, a trend that puts climate targets in jeopardy, according to jointly reported assessments from NASA, Berkeley Earth, the U.K. Met Office, and the National Oceanic and Atmospheric Administration. The annual update of global surface temperatures—an average of readings from thousands of weather stations and ocean probes—shows 2020 essentially tied records set in 2016. But the years were nothing alike. Temperatures in 2016 were boosted by a strong El Niño, a weather pattern that warms the globe by blocking the rise of cold deep waters in the eastern Pacific Ocean. Last year, however, the Pacific entered La Niña, which has a cooling effect. That La Niña didn't provide more relief is an unwelcome surprise, says Nerilie Abram, a climate scientist at Australian National University. “It makes me worried about how quickly the global warming trend is growing.” The past 6 years are the six warmest on record, but the warming of the atmosphere is unsteady because of its chaotic nature. The ocean, which absorbs more than 90% of the heat from global warming, displays a steadier trend, and here, too, 2020 was a record year. The upper levels of the ocean contained 20 zettajoules (1021 joules) more heat than in 2019, and the rise was double the typical annual increase, scientists reported last week in Advances in Atmospheric Sciences . The subtropical Atlantic Ocean was particularly hot, fueling a record outbreak of hurricanes, says Lijing Cheng, a climate scientist at the Chinese Academy of Sciences's Institute of Atmospheric Physics who led the work. This heat, monitored down to 2000 meters by a fleet of 4000 robotic probes, is spreading deeper into the ocean while also migrating toward the poles. An extreme heat wave struck the northern Pacific, killing marine life. For the first time, warm Atlantic waters were seen penetrating into the Arctic Ocean, melting sea ice from below and reducing its extent nearly to a record low ( Science , 28 August 2020, p. [1043][1]). The warming ocean and melting ice sheets are raising sea levels by 4.8 millimeters per year, and the rate is accelerating ( Science , 20 November 2020, p. [901][2]). On land, 2020 was even more relentless, with temperatures rising 1.96°C above preindustrial levels, a clear record, Berkeley Earth reported. It was the warmest year ever in Asia and Europe and tied for the warmest in South America. Russia was particularly hot, breaking its previous record by 1.2°C, while swaths of Siberia were 7°C warmer than in preindustrial times, leading to large-scale fires and thawing permafrost that caused buildings to founder and set off oil spills ( Science , 7 August 2020, p. [612][3]). “Siberia was crazy,” says Zeke Hausfather, a climate scientist at the Breakthrough Institute and co-author of the Berkeley Earth analysis. “That heat would effectively be impossible without the warming we've seen.” In Australia, record-setting heat and drought fueled catastrophic bushfires at the start of 2020. Fires torched nearly one-quarter of southeastern Australia's forests and destroyed 3000 homes. Climate change was to blame for the country's “Black Summer,” Abram and co-authors concluded in a study published this month in Communications Earth & Environment . Meanwhile, in the United States, unprecedented heat came to the desert Southwest, which is already warming faster than the rest of the country. Phoenix wilted under its hottest summer ever, averaging 36°C. Arizona's Maricopa county, home to Phoenix, is a leader in addressing heat exposure, yet its heat deaths have hit a new record each year since 2016. In 2020, the number approached 300, a jump of some 50% over the previous year, says David Hondula, a climatologist who studies heat mortality at Arizona State University, Tempe. “It was just off the charts in terms of heat.” ![Figure][4] Turning up the heatCREDITS: (GRAPHIC) N. DESAI/ SCIENCE ; (DATA) MET OFFICE; NASA; BERKELEY EARTH; NOAA Although the global economic slowdown of the COVID-19 pandemic cut carbon dioxide (CO2) emissions by some 7%, atmospheric CO2 is long-lived, and warming from previous emissions is preordained. In any case, the drop in emissions is unlikely to last. Later this year, in May, before photosynthesis in the Northern Hemisphere draws down CO2, the U.K. Met Office predicts that levels of atmospheric CO2 will pass 417 parts per million for several weeks, 50% higher than preindustrial levels. Only dramatic action by the world's countries, far beyond existing efforts, can begin to halt this build up, Cheng says. Should the current rate of warming continue, the world will breach the targets set in the Paris climate agreement—limiting warming to 1.5°C or 2°C—by 2035 and 2065, respectively. But Hausfather says it's quite possible that warming, which has largely held steady for the past few decades at 0.19°C per decade, will actually speed up. The rate of warming over the past 14 years is well above the long-term trend. The debate now, he says, is whether that is an omen of an even darker future. [1]: https://www.sciencemag.org/content/369/6507/1043.full [2]: https://www.sciencemag.org/content/370/6519/901.full [3]: https://www.sciencemag.org/content/369/6504/612.full [4]: pending:yes