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News - IPCC Report Shows Desperation, Not Climate Catastrophe
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Coral reefs are a natural habitat for many species, as well as being of high economic and touristic significance. However, they represent an extremely sensitive ecosystem with a narrow ecological limit: prolonged high temperatures can lead to bleaching, in which corals expel their symbiotic algae and eventually corals will degrade and die. This work investigates the potential threat of rising temperatures to coral reefs in Southeast Asian Seas through a case study of the UNESCO Cu Lao Cham – Hoi An Biosphere Reserve. We assessed the risk caused by both rising sea surface temperature (SST) and occurrence of more extreme El Niño events. Using outputs from a regionally-downscaled climate model, we found that by the decades 2041-2050 and 2051-2060, whether with RCP 4.5 or RCP 8.5, the environmental temperature will change beyond the coral capacity threshold. Of particular concern is RCP 8.5, where the number of weeks per decade in which SST exceeds the threshold of coral reef bleach
Why do we need sharper weather and climate models?
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Clouds study finds that low climate sensitivity is ‘extremely unlikely’
It is “very likely” that the way clouds change as the world warms will drive further temperature rise, a new study finds.
The response of clouds to a change in global temperature – known as the “cloud feedback” – plays a crucial role in how much the planet will warm. However, estimates of cloud feedback are uncertain. The new study, published in Proceedings of the National Academy of Sciences, uses global satellite observations to reduce this uncertainty.
Taking their findings into account, the authors produce a central estimate of equilibrium climate sensitivity (ECS) – the global temperature change resulting from a doubling of atmospheric CO2 – of 3.2C. They add that low ECS values below 2C are “extremely unlikely”.
Skillful near-term climate predictions of rainfall over the Tibetan Plateau (TP), the Asian water tower, benefit billions of people. On the basis of the state-of-the-art decadal prediction models, we showed evidence that although the raw model outputs show low predicted ability for the summer Inner TP (ITP) rainfall due to low signal-to-noise ratios in models, we can produce realistic predictions by extracting the predictable signal from large ensemble predictions along with a postprocessing procedure of variance adjustment. The results indicate that the summer ITP rainfall is highly predictable on multiyear time scales. The predictability of ITP rainfall originates from the Silk Road pattern driven by sea surface temperature over the subpolar gyre region in North Atlantic. Real-time forecasts suggest that the ITP will become wetter, with 12.8% increase in rainfall during 2020–2027 relative to 1986–2005. Our results will help the water resources management in the surrounding region
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