atmospheric characterization made easy by modeling, measuring and forecasting
We enable direct to Earth optical Comms with improved climate understanding
Optical communications are easily blocked by clouds and scattered by turbulence. Only through site diversity and redundancy can the continuity of service be ensured. Unlike fiber optics, the atmosphere is an ever changing propagation medium inducting bandwidth variation from 0 to 100% of the theoretical link capacity.

an easy access to critical data
we offer
Atmospherical characterization
Modeling, measuring and forecasting of all relevant parameters including cloud cover, turbulence and absorption.
Survey potential sites with laser communication optical ground station
The guarantee to choose the best path.

modeling
real-time, continuous atmospheric monitoring
We want to ensure that our clients can get critical information to optimize their infrastructure or improve their decision making.
Miratlas offers its clients real-time and continuous monitoring of atmospheric turbulence. The data collected allows us to mitigate by anticipating and minimizing the impact of the atmosphere on the propagation of light.
modeling
Forecasting the atmospheric turbulence
The prediction of atmospheric conditions is the purpose of the services offered by Miratlas.
In particular, the measurement and prediction of atmospheric turbulence has an important scientific value, and an important economic value as it guarantees Satcom operators an optimization of their optical telecommunication infrastructures.
To predict these disturbances, we use machine learning, which is central to the extrapolation and interpretation of data from our instrument network.
The quality of short-term forecasts of atmospheric disturbances depends on the quality of the data collected, but also on its quantity.
This quantity is increasing as our network is deployed and offers the diversity of observation sites necessary to study different climates. The data also accumulated over time and the continuity of the measurements over several years makes it possible to obtain the necessary seasonal variations.
an important asset
modeling the atmosphere

disruptive and innovative
our technology
Miratlas is committed to using disruptive and innovative technologies to achieve its mission.
To predict these disturbances, Miratlas uses machine learning, which is central to the extrapolation and interpretation of data from our instrument network.
The quality of short-term forecasts of atmospheric disturbances depends on the quality of the data collected, but also on its quantity.
This quantity is increasing as our network is deployed and offers the diversity of observation sites necessary to study different climates. The data also accumulate over time and the continuity of the measurements over several years makes it possible to obtain the necessary seasonal variations.
empowering your decision making
Discover how atmospheric knowledge will help your organisation
Sat Com/Telecom operators
Number and locations of Optical Ground Station sites.
Space situational awareness
Robotic telescope site selection and operations optimization
Telecom equipment manufacturers
Optical Ground Station design and cost
Astronomy
Telescope safety and observation optimisation
Atmospheric pollution and climatology
Improved atmospheric modelling for pollutant dispersion and climate studies.
Airport traffic monitoring
Real-time turbulence measurement for runways.