Clouds substantially affect Earth's energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts. Here we show that several independent, empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. These results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.
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http://dx.doi.org/10.1038/nature18273 | DOI Listing |
Biotechnol Biofuels Bioprod
January 2025
Botany and Microbiology Department, Faculty of Science, Tanta University, Tanta, 31527, Egypt.
Background: Phaeodactylum tricornutum is a versatile marine microalga renowned for its high-value metabolite production, including omega-3 fatty acids and fucoxanthin, with emerging potential for integrated biorefinery approaches that encompass biofuel and bioproduct generation. Therefore, in this study we aimed to optimize the cultivation conditions for boosting biomass, lipid, and fucoxanthin production in P. tricornutum, focusing on the impacts of different nutrient ratios (nitrogen, phosphorus, silicate), glycerol supplementation, and light regimes.
View Article and Find Full Text PDFJAMA Netw Open
January 2025
Interdepartmental Neuroscience Program, Yale University, New Haven, Connecticut.
Importance: Opioid use disorder (OUD) impacts millions of people worldwide. Prior studies investigating its underpinning neural mechanisms have not often considered how brain signals evolve over time, so it remains unclear whether brain dynamics are altered in OUD and have subsequent behavioral implications.
Objective: To characterize brain dynamic alterations and their association with cognitive control in individuals with OUD.
Interv Neuroradiol
January 2025
Neuroradiology, The Royal London Hospital, Barts NHS Trust, London, UK.
Background And Purpose: We report short- and intermediate-term effects on headaches with intra-arterial injection of lidocaine in the middle meningeal artery in patients with severe headaches associated with subarachnoid hemorrhage.
Methods: We treated seven patients with intra-arterial lidocaine in doses up to 50 mg in each middle meningeal artery via a microcatheter bilaterally (except in one patient). We recorded the maximum intensity of headache (graded by 11-point numeric rating scale) prior to procedure and every day for the next 10 days or discharge, whichever came first.
Nature
January 2025
Department of Atmospheric and Oceanic Sciences, McGill University, Montreal, Quebec, Canada.
Clouds greatly influence the Earth's energy balance. Observationally constraining cloud radiative feedback, a notably uncertain climate feedback mechanism, is crucial for improving predictions of climate change but, so far, remains an elusive objective, and the feedback may be different over the ocean versus over land. Here we show a local negative surface longwave cloud feedback over land at the southern Great Plains site, constrained by direct long-term observation of spectrally resolved downwelling longwave radiance.
View Article and Find Full Text PDFSci Data
January 2025
Department of Earth and Environment, Boston University, Boston, MA, 02215, USA.
The Fraction of Absorbed Photosynthetically Active Radiation (FPAR) is essential for assessing vegetation's photosynthetic efficiency and ecosystem energy balance. While the MODIS FPAR product provides valuable global data, its reliability is compromised by noise, particularly under poor observation conditions like cloud cover. To solve this problem, we developed the Spatio-Temporal Information Composition Algorithm (STICA), which enhances MODIS FPAR by integrating quality control, spatio-temporal correlations, and original FPAR values, resulting in the High-Quality FPAR (HiQ-FPAR) product.
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