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Context. Solar observations of carbon monoxide (CO) indicate the existence of lower-temperature gas in the lower solar chromosphere. We present an observation of pores, and quiet-Sun, and network magnetic field regions with CO 4.66 μm lines by the Cryogenic Infrared Spectrograph (CYRA) at Big Bear Solar Observatory. Aims. We used the strong CO lines at around 4.66 μm to understand the properties of the thermal structures of lower solar atmosphere in different solar features with various magnetic field strengths. Methods. Different observations with different instruments were included: CO 4.66 μm imaging spectroscopy by CYRA, Atmospheric Imaging Assembly (AIA) 1700 Å images, Helioseismic and Magnetic Imager (HMI) continuum images, line-of-sight (LOS) magnetograms, and vector magnetograms. The data from 3D radiation magnetohydrodynamic (MHD) simulation with the Bifrost code are also employed for the first time to be compared with the observation. We used the Rybicki-Hummer (RH) code to synthesize the CO line profiles in the network regions. Results. The CO 3-2 R14 line center intensity changes to be either enhanced or diminished with increasing magnetic field strength, which should be caused by different heating effects in magnetic flux tubes with different sizes. We find several “cold bubbles” in the CO 3-2 R14 line center intensity images, which can be classified into two types. One type is located in the quiet-Sun regions without magnetic fields. The other type, which has rarely been reported in the past, is near or surrounded by magnetic fields. Notably, some are located at the edge of the magnetic network. The two kinds of cold bubbles and the relationship between cold bubble intensities and network magnetic field strength are both reproduced by the 3D MHD simulation with the Bifrost and RH codes. The simulation also shows that there is a cold plasma blob near the network magnetic fields, causing the observed cold bubbles seen in the CO 3-2 R14 line center image. Conclusions. Our observation and simulation illustrate that the magnetic field plays a vital role in the generation of some CO cold bubbles. 

Context. The magnetic field is the underlying cause of solar activities. Spectropolarimetric Stokes inversions have been routinely used to extract the vector magnetic field from observations for about 40 years. In contrast, the photospheric continuum images have an observational history of more than 100 years. Aims. We suggest a new method to quickly estimate the unsigned radial component of the magnetic field, | B r |, and the transverse field, B t , just from photospheric continuum images ( I ) using deep convolutional neural networks (CNN). Methods. Two independent models, that is, I versus | B r | and I versus B t , are trained by the CNN with a residual architecture. A total of 7800 sets of data ( I , B r and B t ) covering 17 active region patches from 2011 to 2015 from the Helioseismic and Magnetic Imager are used to train and validate the models. Results. The CNN models can successfully estimate | B r | as well as B t maps in sunspot umbra, penumbra, pore, and strong network regions based on the evaluation of four active regions (test datasets). From a series of continuum images, we can also detect the emergence of a transverse magnetic field quantitatively with the trained CNN model. The three-day evolution of the averaged value of the estimated | B r | and B t from continuum images follows that from Stokes inversions well. Furthermore, our models can reproduce the nonlinear relationships between I and | B r | as well as B t , explaining why we can estimate these relationships just from continuum images. Conclusions. Our method provides an effective way to quickly estimate | B r | and B t maps from photospheric continuum images. The method can be applied to the reconstruction of the historical magnetic fields and to future observations for providing the quick look data of the magnetic fields.