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Register a new userGPS Measurements of Precipitable Water Vapor Can Improve Survey Calibration: A Demonstration from KPNO and the Mayall z-band Legacy Survey
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We here show that dual-band GPS measurements of precipitable water vapor (PWV) at KPNO predict the overall per-image sensitivity of the Mayall z-band Legacy Survey (MzLS). The per-image variation in the brightness of individual stars is strongly correlated with the measured PWV and the color of the star. We use synthetic stellar spectra and TAPAS transmission models to predict the expected PWV-induced photometric errors and find good agreement with the observations. We also find that PWV absorption can be well-approximated by a linear relationship with PWV_eff and present an update on the traditional treatment in the literature. Within the range of reasonable observing conditions, the MzLS zero point varies with a standard deviation of 127 mmag. This variation is dominated by a gray secular trend with time, consistent with a gradual accumulation of contamination on optical surfaces that accounts for ~114 mmag of variation. Correcting for PWV based on a suite of stellar spectra and detailed PWV absorption models accounts for another 47 mmag of zero-point variation. The MzLS per-image sensitivity is decreased by ~40 mmag per effective mm of PWV. The difference between blue (r-z < 0.5 mag) and red (1.2 mag < r-z) stars increases by 3.25 mmag per effective mm of PWV. These results show the need for high-precision photometric surveys to simultaneously monitor PWV. We find that this GPS system provides more precise PWV measurements than using differential measurements of stars of different colors and recommend that observatories install dual-band GPS as a low-maintenance, relatively low cost, auxiliary calibration system. We extend our results of the need for well-calibrated PWV measurements by presenting calculations of the PWV photometric impact on three science cases of interest: stellar photometry, supernova cosmology, and quasar identification and variability.
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We report on the measurements of telluric water vapor made with the instrument FIFI-LS on SOFIA. Since November 2018, FIFI-LS has measured the water vapor overburden with the same measurement setup on each science flight with about 10 data points throughout the flight. This created a large sample of 469 measurements at different locations, flight altitudes and seasons. The paper describes the measurement principle in detail and provides some trend analysis on the 3 parameters. This presents the first systematic analysis with SOFIA based on in situ observations.
We present the photometric calibration of the Supernova Legacy Survey (SNLS) fields. The SNLS aims at measuring the distances to SNe Ia at (0.3<z<1) using MegaCam, the 1 deg^2 imager on the Canada-France-Hawaii Telescope (CFHT). The uncertainty affecting the photometric calibration of the survey dominates the systematic uncertainty of the key measurement of the survey, namely the dark energy equation of state. The photometric calibration of the SNLS requires obtaining a uniform response across the imager, calibrating the science field stars in each survey band (SDSS-like ugriz bands) with respect to standards with known flux in the same bands, and binding the calibration to the UBVRI Landolt standards used to calibrate the nearby SNe from the literature necessary to produce cosmological constraints. The spatial non-uniformities of the imager photometric response are mapped using dithered observations of dense stellar fields. Photometric zero-points against Landolt standards are obtained. The linearity of the instrument is studied. We show that the imager filters and photometric response are not uniform and publish correction maps. We present models of the effective passbands of the instrument as a function of the position on the focal plane. We define a natural magnitude system for MegaCam. We show that the systematics affecting the magnitude-to-flux relations can be reduced if we use the spectrophotometric standard star BD +17 4708 instead of Vega as a fundamental flux standard. We publish ugriz catalogs of tertiary standards for all the SNLS fields.
The Atacama Desert has long been established as an excellent site for submillimeter observations. Yet identifying potentially optimal locations for a new facility within this region can require long field campaigns that rely on the construction of weather stations and radiometer facilities to take data over sufficiently long timescales. Meanwhile, high-level remote sensing data products from satellites have generally only been available at >25 km resolution, limiting their utility for astronomical site selection. We aim to improve and expedite the process of site characterization and selection through the use of km-resolution satellite data. We analyze the daytime precipitable water vapor (PWV) values inferred using near-IR measurements from the MODIS Aqua and Terra satellites, comparing the level-2 satellite products to those from existing ground-based measurements from the radiometer at the Atacama Pathfinder Experiment (APEX) site. Since the APEX radiometer data has been extensively tested and compared to atmospheric transmission models, particularly in low-PWV conditions of interest for astronomy, we use these data to re-calibrate the MODIS data for the entire region, reducing systematic errors to a level of < 3%. After re-calibration, the satellite data allow mapping of the PWV across the region, and we identify several promising sites. Our findings confirm previous results, but provide a more complete and higher resolution picture, filling in key spatial and temporal information often missing from dedicated field campaigns. We also examine the seasonal trends in the ground-based data from APEX and surrounding region, finding that both data sets indicate that PWV has increased moderately over the past two decades. We demonstrate a potentially powerful method for siting new facilities such as AtLAST and extensions to global very long baseline interferometry networks like the EHT.
Long-Short-Term-Memory (LSTM) networks have been used extensively for time series forecasting in recent years due to their ability of learning patterns over different periods of time. In this paper, this ability is applied to learning the pattern of Global Positioning System (GPS)-based Precipitable Water Vapor (PWV) measurements over a period of 4 hours. The trained model was evaluated on more than 1500 hours of recorded data. It achieves a root mean square error (RMSE) of 0.098 mm for a forecasting interval of 5 minutes in the future, and outperforms the naive approach for a lead-time of up to 40 minutes.
The atmospheric water vapor content above the Roque de los Muchachos Observatory (ORM) obtained from Global Positioning Systems (GPS) is presented. GPS measurements have been evaluated by comparison with 940nm-radiometer observations. Statistical analysis of GPS measurements points to ORM as an observing site with suitable conditions for infrared (IR) observations, with a median column of precipitable water vapor (PWV) of 3.8 mm. PWV presents a clear seasonal behavior, being Winter and Spring the best seasons for IR observations. The percentage of nighttime showing PWV values smaller than 3 mm is over 60% in February, March and April. We have also estimated the temporal variability of water vapor content at the ORM. A summary of PWV statistical results at different astronomical sites is presented, recalling that these values are not directly comparable as a result of the differences in the techniques used to recorded the data.
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