Measuring the shape of clouds helps scientists understand how the Earth will continue to respond to climate change. Satellites measure clouds in different ways. One way is to take pictures of clouds from multiple angles and to use the differences between the pictures to measure cloud structure. However, doing this accurately can be challenging. We propose a way to use machine learning to recover the shape of clouds from multi-angle satellite data.

This paper presents a design of a UV wind lidar, made with a UV fiber laser and a Quadri Mach-Zehnder interferometer as a spectral analyzer, used to measure the wind in front of future low-consumption aircraft. The article details the optimization of the different elements of the instrument with simulations. This paper also presents a method to optimize laser angles for determining wind direction and strength and shows a 50 % improvement over the current angles used.

Methane leaks into houses that use natural gas from appliances, pipes, and fittings. We measured methane emitted from a manufactured house under different ventilation conditions using indoor and outdoor concentration measurements. We injected methane at prescribed rates into the house and then measured the emissions using our method. We report the error in the calculation based on these tests. We also describe the method and provide guidance on conducting this type of experiment.

The imbalance between the energy the Earth absorbs from the Sun and the energy the Earth emits back into space gives rise to climate change, but measuring the small imbalance is challenging. We simulate satellites in various orbits to investigate how well they sample the imbalance and find that the best option is to combine at least two satellites that see complementary parts of the Earth and cover the daily and annual cycles. This information is useful when planning future satellite missions.