No Arabic abstract
Context: The winter seeing at Concordia is essentially bimodal, excellent or quite poor, with relative proportions that depend on altitude above the snow surface. This paper studies the temporal behavior of the good seeing sequences. Aims: An efficient exploitation of extremely good seeing with an adaptive optics system needs long integrations. It is then important to explore the temporal distribution of the fraction of time providing excellent seeing. Methods: Temporal windows of good seeing are created by a simple binary process. Good or bad. Their autocorrelations are corrected for those of the existing data sets, since these are not continuous, being often interrupted by technical problems in addition to the adverse weather gaps. At the end these corrected autocorrelations provide the typical duration of good seeing sequences. This study has to be a little detailed as its results depend on the season, summer or winter. Results: Using a threshold of 0.5 arcsec to define the good seeing, three characteristic numbers are found to describe the temporal evolution of the good seeing windows. The first number is the mean duration of an uninterrupted good seeing sequence: it is $tau_0=7.5$ hours at 8 m above the ground (15 hours at 20 m). These sequences are randomly distributed in time, with a negative exponential law of damping time $tau_1=29$ hours (at elevation 8 m and 20 m). The third number is the mean time between two 29 hours episodes. It is T=10 days at 8 m high (5 days at 20 m).
Atmospheric emission is a dominant source of disturbance in ground-based astronomy at mm wavelengths. The Antarctic plateau is recognized to be an ideal site for mm and sub-mm observations, and the French/Italian base of Dome C is among the best sites on Earth for these observations. In this paper we present measurements, performed using the BRAIN-pathfinder experiment, at Dome C of the atmospheric emission in intensity and polarization at 150GHz, one of the best observational frequencies for CMB observations when considering cosmic signal intensity, atmospheric transmission, detectors sensitivity, and foreground removal. Careful characterization of the air-mass synchronous emission has been performed, acquiring more that 380 elevation scans (i.e. skydip) during the third BRAIN-pathfinder summer campaign in December 2009/January 2010. The extremely high transparency of the Antarctic atmosphere over Dome Concordia is proven by the very low measured optical depth: <tau_I>=0.050 pm 0.003 pm 0.011 where the first error is statistical and the second is systematic error. Mid term stability, over the summer campaign, of the atmosphere emission has also been studied. Adapting the radiative transfer atmosphere emission model am to the particular conditions found at Dome C, we also infer the level of the PWV content of the atmosphere, notoriously the main source of disturbance in millimetric astronomy (<PWV>=0.77 +/- 0.06 + 0.15 - 0.12 mm). Upper limits on the air-mass correlated polarized signal are also placed for the first time. The degree of circular polarization of atmospheric emission is found to be lower than 0.2% (95%CL), while the degree of linear polarization is found to be lower than 0.1% (95%CL). These limits include signal-correlated instrumental spurious polarization.
In this article, we present a detailed analysis of the statistical properties of seeing for the Muztagh-ata site which is the candidate site for hosting future Chinese Large Optical/infrared Telescope (LOT) project. The measurement was obtained with Differential Image Motion Monitor (DIMM) from April 2017 to November 2018 at different heights during different periods. The median seeing at 11 meters and 6 meters are very close but different significantly from that on the ground. We mainly analyzed the seeing at 11 meters monthly and hourly, having found that the best season for observing was from late autumn to early winter and seeing tended to improve during the night only in autumn. The analysis of the dependence on temperature inversion, wind speed, direction also was made and the best meteorological conditions for seeing is given.
We present seeing measurements at OAUNI site gathered on 2016 and 2017 campaigns using V and R broadband filters. In order to quantify the seeing we used the full-width-at-half-maximum from stellar profiles on photometric sequences during the observational windows of our supernovae program. A typical median seeing of 1.8 arcsec was found on 2016 and a worst value of 2.0 arcsec on 2017. The last one was probably affected by anomalous conditions related to the 2017 extreme climatic phenomena. The monthly first quartile analysis indicates that best seeing conditions can be achieved at a level of 1.5 arcsec. In general, our results indicate a reasonable sky quality for the OAUNI site.
Seeing, the angular size of stellar images blurred by atmospheric turbulence, is a critical parameter used to assess the quality of astronomical sites. Median values at the best mid-latitude sites are generally in the range of 0.6--0.8,arcsec. Sites on the Antarctic plateau are characterized by comparatively-weak turbulence in the free-atmosphere above a strong but thin boundary layer. The median seeing at Dome C is estimated to be 0.23--0.36 arcsec above a boundary layer that has a typical height of 30,m. At Dome A and F, the only previous seeing measurements were made during daytime. Here we report the first direct measurements of night-time seeing at Dome A, using a Differential Image Motion Monitor. Located at a height of just 8,m, it recorded seeing as low as 0.13,arcsec, and provided seeing statistics that are comparable to those for a 20,m height at Dome C. It indicates that the boundary layer was below 8,m 31% of the time. At such times the median seeing was 0.31,arcsec, consistent with free-atmosphere seeing. The seeing and boundary layer thickness are found to be strongly correlated with the near-surface temperature gradient. The correlation confirms a median thickness of approximately 14,m for the boundary layer at Dome A, as found from a sonic radar. The thinner boundary layer makes it less challenging to locate a telescope above it, thereby giving greater access to the free-atmosphere.
AI for good (AI4G) projects involve developing and applying artificial intelligence (AI) based solutions to further goals in areas such as sustainability, health, humanitarian aid, and social justice. Developing and deploying such solutions must be done in collaboration with partners who are experts in the domain in question and who already have experience in making progress towards such goals. Based on our experiences, we detail the different aspects of this type of collaboration broken down into four high-level categories: communication, data, modeling, and impact, and distill eleven takeaways to guide such projects in the future. We briefly describe two case studies to illustrate how some of these takeaways were applied in practice during our past collaborations.