The JWST Weather Report: retrieving temperature variations, auroral heating, and static cloud coverage on SIMP-0136

TL;DR

This paper exploits JWST time-resolved spectroscopy of SIMP-0136 with NIRSpec/PRISM and MIRI/LRS to map atmospheric state changes across a full rotation. By extending the petitRADTRANS retrieval framework to time-resolved spectra, the authors infer a persistent stratospheric temperature inversion—likely driven by auroral heating—and quantify variations in temperature, chemistry, and clouds. They find a ~5 K hemispheric effective-temperature variation and phase-linked CO$_2$ and H$_2$S abundances, while CH$_4$, CO, and H$_2$O remain largely homogeneous; silicate clouds are required but show little longitudespread variability, suggesting magnetic/thermodynamic drivers over clouds as the dominant variability mechanism. The results challenge simple 1D cloud-variability pictures for L–T transition objects and highlight the need for 3D modeling (including auroral, magnetic, and dynamical processes) to interpret high-precision, broad-wavelength observations.

Abstract

SIMP-0136 is a T2.5 brown dwarf whose young age ($200\pm50$~Myr) and low mass ($15\pm3$~M$_{\rm Jup}$) make it an ideal analogue for the directly imaged exoplanet population. With a 2.4 hour period, it is known to be variable in both the infrared and the radio, which has been attributed to changes in the cloud coverage and the presence of an aurora respectively. To quantify the changes in the atmospheric state that drive this variability, we obtained time-series spectra of SIMP-0136 covering one full rotation with both NIRSpec/PRISM and the MIRI/LRS on board JWST. We performed a series of time-resolved atmospheric retrievals using petitRADTRANS in order to measure changes in the temperature structure, chemistry, and cloudiness. We inferred the presence of a ~250 K thermal inversion above 10 mbar of SIMP-0136 at all phases, and propose that this inversion is due to the deposition of energy into the upper atmosphere by an aurora. Statistical tests were performed in order to determine which parameters drive the observed spectroscopic variability. The primary contribution was due to changes in the temperature profile at pressures deeper than 10 mbar, which resulted in variation of the effective temperature from 1243 K to 1248 K. This changing effective temperature was also correlated to observed changes in the abundances of CO2 and H2S, while all other chemical species were consistent with being homogeneous throughout the atmosphere. Patchy silicate clouds were required to fit the observed spectra, but the cloud properties were not found to systematically vary with longitude. This work paints a portrait of an L/T transition object where the primary variability mechanisms are magnetic and thermodynamic in nature, rather than due to inhomogeneous cloud coverage.

Figures (22)

• Figure 1: NIRSpec/PRISM (left) and MIRI/LRS (right) observations of SIMP-0136. Top: Emission spectra in 15$^{\circ}$ rotation bins. Each binned NIRSpec spectrum is averaged over 90 s of integration, while each LRS spectrum is averaged over 38 s integrations to ensure that the overall signal to noise of the input spectra for the retrievals is proportional to the emitted flux. Centre: Uncertainties calculated by the JWST pipeline for each spectrum in blue. Standard deviation of the 90s (115s for the LRS) intervals in red, demonstrating that the pipeline uncertainties accurately reflect the underlying statistical distribution of the noise. Bottom: Binned variability maps, also known as dynamic spectra. These variability maps are aligned in phase, as the MIRI observations were taken after the NIRSpec observations and are binned to highlight the wavelength dependence of the variability. The 24 phase bins used in these maps correspond to the binned spectra used as inputs for the retrievals.
• Figure 2: Best-fit model from the fiducial retrieval to the observed spectrum at 0$^{\circ}$ phase, whose uncertainties are smaller than the displayed line width. This model assumed a fixed mass and radius of 10.381 M$_{\rm Jup}$ and 0.9329 R$_{\rm Jup}$ respectively. Also shown for visual reference are the log opacities at the 1 bar level of the primary absorbers in each wavelength range. The CH$_{4}$ abundance was allowed to vary as a function of altitude. The reduced $\chi^{2}$ of the fit is poor at 295, due to the photometric precision of JWST. However, the model clearly matches the key absorption features of H$_{2}$O, CH$_{4}$, CO, and CO$_{2}$, as well as additional species such as H$_{2}$S and NH$_{3}$.
• Figure 3: Emission contribution function for SIMP-0136 at 0$^{\circ}$ phase. The emission contribution is shown in square-root colour scale to highlight subtle variations. Significant contributions are present across four decades in pressure, bounded by a cloud layer near 10 bar and by methane absorption up to 10$^{-3}$ bar.
• Figure 4: Retrieved temperature profiles for each phase bin. Temperature profiles are given as 90% confidence intervals. In grey is the emission contribution function, averaged over wavelength. We show the square root of the contribution to highlight that there is small, but significant emission from the upper atmosphere, coincident with the location of the temperature inversion. In black lines are condensation curves for enstatite, forsterite, and iron, showing that the retrieved cloud base pressure for the silicate cloud is coincident with the expected condensation location. We also show the temperature profile from a self-consistent ExoRem model ($\log g = 4.5$, [M/H]$=0$, C/O$=0.55$, T$_{\rm eff}=1000$ K) as a red dotted line.
• Figure 5: Volume mixing ratio profiles of gas-phase species for all phases. The shaded regions indicate 68% confidence intervals, taken from the set of median abundances measured at each phase. The measured precision for a single phase is typically an order of magnitude smaller than the variation between phases.