NASA’s SPHEREx telescope has measured the atmospheric chemistry of nearby brown dwarfs, exposing gaps in how scientists model their atmospheres. The findings give astronomers a way to test predictions about objects whose temperatures and sizes can be misjudged by those models. In its October 8, 2026, announcement, NASA said the study, also available on arXiv, has been published in The Astrophysical Journal.
Brown dwarfs form when gas clouds collapse, but lack enough mass to keep hydrogen fusion going as stars do. Their atmospheres share traits with giant planets such as Jupiter and Saturn. SPHEREx detected water, methane, carbon dioxide and carbon monoxide in the study’s sample, NASA said.
Where the models fall short
The researchers compared observations of 37 nearby brown dwarfs with several atmospheric models. The toughest cases included objects passing through a cooling stage when clouds change and methane becomes more prominent. Models broadly reproduced the chemical trends, but struggled to match different parts of the same object’s light spectrum simultaneously, with particularly large discrepancies around carbon dioxide and carbon monoxide features.
That distinction matters: detecting familiar molecules doesn’t mean scientists can yet explain the whole atmosphere. Lead author Zafar Rustamkulov put the variation plainly in NASA’s announcement: “Even at the same temperature, their spectra look quite distinct.”
SPHEREx’s advantage is its view from above Earth’s atmosphere, where water blocks some of the wavelengths astronomers need. It measures brightness across 102 wavelength bands, letting researchers identify molecules through the light they absorb. The study reports that its measurements capture more than 80% of most brown dwarfs’ total emitted light, providing a substantial check on theoretical predictions.
The team says thousands more brown dwarfs are being analyzed. Researchers hope that larger sample will show how widely clouds and atmospheric chemistry vary as these objects cool, giving them more observations to test and improve the models.
Sources
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