Related papers: pwv_kpno: A Python Package for Modeling the Atmosp…
Time-variable absorption by water vapor in Earth's atmosphere presents an important source of systematic error for a wide range of ground-based astronomical measurements, particularly at near-infrared wavelengths. We present results from…
We retrieved the total content of the atmospheric water vapor (or Integrated Water Vapor, IWV) from extensive sets of photometric data obtained since 1995 at Lindenberg Meteorological Observatory with star and sun photometers. Different…
The spread of PM2.5 pollutants that endanger health is difficult to predict because it involves many atmospheric variables. These micron particles can spread rapidly from their source to residential areas, increasing the risk of respiratory…
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…
We report precipitable water vapor (PWV) measurements made at Las Campanas Observatory using optical spectra of H2O lines obtained with the Magellan echelle spectrograph, and calculated using a robust technique that is accurate to 5-10%.…
Atmospheric mean temperature T_m, is a vital parameter in the evaluation of precipitable water vapor (PWV) through the analysis of GPS signal, it is, therefore, important to have a good way of evaluation of T_m for the eventual accurate…
Photovoltaic (PV) energy grows at an unprecedented pace, which makes it difficult to maintain up-to-date and accurate PV registries, which are critical for many applications such as PV power generation estimation. This lack of qualitative…
We describe here a new algorithm to model the water contents of the atmosphere from GNSS slant wet delays relative to a single receiver. We first make the assumption that the water vapor contents are mainly governed by a scale height…
The simulation of atmospheric showers through Monte-Carlo processes as well as their projection into Imaging Atmospheric Cherenkov Telescopes (IACT) is long and very computing intensive. As these simulations are the most advanced ones from…
Accurate assessment of atmospheric nitrogen dioxide (NO$_2$) and sulfur dioxide (SO$_2$) is essential for understanding climate-air quality interactions, supporting environmental policy, and protecting public health. Traditional monitoring…
We present the easy-to-use, publicly available, Python package petitRADTRANS, built for the spectral characterization of exoplanet atmospheres. The code is fast, accurate, and versatile; it can calculate both transmission and emission…
After 30 years since the beginning of the Global Positioning System (GPS), or, more generally, Global Navigation Satellite System (GNSS) meteorology, this technique has proven to be a reliable method for retrieving atmospheric water vapor;…
This work presents a proposal for a wireless sensor network for participatory sensing, with IoT sensing devices developed especially for monitoring and predicting air quality, as alternatives of high cost meteorological stations. The…
Aims: We studied the precipitable water vapour (PWV) content near Cerro Armazones and discuss the potential use of our technique of modelling the telluric absorbtion lines for the investigation of other molecular layers. The site is…
Cosmic-ray observatories necessarily rely on Monte Carlo simulations for their design, calibration and analysis of their data. Detailed simulations are very demanding computationally. We present a python-based package called ShowerModel to…
The variability induced by precipitable water vapour (PWV) can heavily affect the accuracy of time-series photometric measurements gathered from the ground, especially in the near-infrared. We present here a novel method of modelling and…
Context. Interest in the use of the Chajnantor area for millimeter and submillimeter astronomy is increasing because of its excellent atmospheric conditions. Knowing the general site annual variability in precipitable water vapor (PWV) can…
Environmental sensors are crucial for monitoring weather conditions and the impacts of climate change. However, it is challenging to place sensors in a way that maximises the informativeness of their measurements, particularly in remote…
Fine-grained air pollution forecasting is crucial for urban management and the development of healthy buildings. Deploying portable sensors on mobile platforms such as cars and buses offers a low-cost, easy-to-maintain, and wide-coverage…
In many problem settings that require spatio-temporal forecasting, the values in the time-series not only exhibit spatio-temporal correlations but are also influenced by spatial diffusion across locations. One such example is forecasting…