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The detection and parameterization of molecular clumps are the first step in studying them. We propose a method based on the Local Density Clustering algorithm while physical parameters of those clumps are measured using the Multiple Gaussian Model algorithm. One advantage of applying the Local Density Clustering to the clump detection and segmentation, is the high accuracy under different signal-to-noise levels. The Multiple Gaussian Model is able to deal with overlapping clumps whose parameters can reliably be derived. Using simulation and synthetic data, we have verified that the proposed algorithm could accurately characterize the morphology and flux of molecular clumps. The total flux recovery rate in 13CO (J = 1−0) line of M16 is measured as 90.2%. The detection rate and the completeness limit are 81.7% and 20 K km s−1 in 13CO (J = 1−0) line of M16, respectively.

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The ratio of penumbral to umbra area of sunspots plays a crucial role in the solar physics fields, especially for understanding the origin and evolution of the solar activity cycle. By analyzing the recently digitized sunspot drawings observed from Yunnan Observatories (1957-2021), we investigate the long-term variation of the penumbral to umbra area ratio of sunspots. An automatic extraction method, based on the maximum between-class variance and the morphological discrimination, is used to accurately extract penumbra and umbra and to calculate the ratio over six solar cycles (cycle 19-24). The expected value of the ratio of penumbra to umbra area is found to be 6.63 ± 0.98, and it does not exhibit any systematic variation with sunspot latitudes and phases. The average ratio fluctuates from 5 to 7.5 per year and the overall trend has decreased after 1999 compared to the previous. The ratio of sunspot penumbra to umbra area satisfies the log-normal distribution, implying its variation is related to the evolution of the photospheric magnetic field. Our results are consistent with previous works.

Sunspots are the most striking and easily observed magnetic structures of the Sun, and statistical analysis of solar historical data could reveal a wealth of information on the long-term variation of solar activity cycle. The hand-drawn sunspot records of Yunnan Observatories, Chinese Academy of Sciences have been accumulating for more than 60 years, and nearly 16 000 images have been preserved. In the future, the observation mode of recording sunspots by hand-drawing will be replaced inevitably by digital images observed either at ground or in space. To connect the hand-drawn sunspot data and the purely digital sunspot data in future, it is necessary to analyze the systematic errors of the data which are observed by the two observation modes in the period of transition. In this paper, we choose 268 round sunspots (H-type in modified Zurich sunspot classification) from the drawing of Yunnan Observatories to compare their positions and areas with the CCD observations made by Helioseismic and Magnetic Imager (HMI) on board Solar Dynamic Observatory (SDO) and Global Oscillation Network Group (GONG). We find that the latitude and longitude accuracy of hand-drawn sunspot are within −0.127 and 2.29 degree respectively, and the area accuracy is about 16.36 sunspot unit (μHem). Systematic errors apparently decrease with large sunspot.