The Andean Geostationary Sentinel: How a Satellite Finds Windows in the Clouds ✎

Original: "Identification of Potential Sites for Astronomical Observations in Northern South-America"
arXiv:1504.06033 · 2015-04-23 · arXiv non-exclusive · independent analysis · 3 min
Five years of satellite infrared images have revealed twelve sites in the northern Andes where the sky opens for telescopes more than 30% of dry nights.

Every night, an invisible sentinel hangs over the Andes. The GOES-12 satellite, and later its successor GOES-13, watches Earth from an altitude of 36,000 kilometers, recording how the mountains breathe clouds. For five straight years, it tracked where the sky stayed clear and where it got wrapped in cotton. From those night images grew a map that shows where to place a telescope so that stars don't hide behind the clouds.

For an astronomer, clouds are not just a nuisance; they are the main enemy. A telescope needs hours of clear sky, and the more, the better. But in the tropical Andes, weather stations are scarce, and the mountains create their own microclimates: rain on one slope, dryness on the other. So scientists from Colombia and Venezuela decided not to hike from peak to peak with instruments, but instead to teach a satellite to distinguish clouds by their thermal radiation. Every cloud has its own temperature, and the satellite sees it in the infrared range, just as a thermal camera sees hot pipes behind a wall.

The threshold temperature for clouds at 4000 meters altitude in the Andes can drop to 0–2 °C, while in the Magdalena River valley it exceeds 20 °C. This means that the same infrared patch on a satellite image indicates a cloud over the summit but clear sky over the lowland.

To tell a cloud from clear sky, you need a reference. That reference came from 63 weather stations that have recorded ground temperatures for years. The scientists took the average temperature for each month and subtracted three standard deviations, yielding a threshold: if the satellite sees a temperature below that, then a cloud is over that spot. For high atmospheric layers, thresholds were calculated from radiosondes that rise twice a day from Bogotá and the Caribbean coast. All together, this produced a map with a resolution of 28 by 18 kilometers, enough to discern individual mountain ranges.

The result was generous. Over five years, twelve sites stood out where, during the dry season, the fraction of clear spectroscopic nights exceeds 30%. The absolute record holder is a spot in the Venezuelan Andes at 3480 meters altitude: 67.0 ± 10.7% clear nights in the dry season and 53.5 ± 12.2% in the wet season, giving 220 ± 42 spectroscopic nights per year. For comparison, the operating Llano del Hato Observatory shows only 132 ± 25 such nights. In Colombia, the best regions are the Sierra Nevada de Santa Marta (126 ± 34 nights) and the Serranía del Perijá (111 ± 27 nights). Near the equator, at Nudo de los Pastos, two sites yield 105 ± 36 and 101 ± 42 nights, with minimal seasonal differences there, just 1–4%.

Year-by-year analysis revealed a dip in clear nights during the wet seasons of 2010 and 2011, coinciding with positive values of the Southern Oscillation Index, that is, with La Niña.

Before this work, no clear-sky maps existed for the northern Andes. Ground stations were insufficient, and atmospheric models often miss the mark in mountains. Now any university can open a satellite archive and, within a few weeks, assess whether it is worth hauling a telescope to a distant peak. The method was validated against the observing logs of the Llano del Hato Observatory: satellite estimates matched the actual records of astronomers. This means that the sentinel over the Andes tells the truth, and it can be trusted.

The threshold temperature for clouds at an altitude of 4000 meters in the Andes can drop to 0–2 °C, while in the Magdalena River valley it exceeds 20 °C. This means that the same infrared spot on a satellite image indicates a cloud over a peak but clear sky over a lowland.

Concepts
lsst very large telescope alma sdss Oceanic Niño index Niño 3.4 region NOAA CPC act vera rubin observatory lhaaso zwicky transient facility askap Niño 4 Niño 1+2 sky survey