Sea surface wind and waves are important ocean parameters that can be continuously observed by meteorological buoys. Meteorological buoys are sparse in the ocean due to their high cost of deployment and maintenance. In contrast, low-cost compact wave buoys are suited for deployment in large numbers. Although wave buoys are not designed for wind measurement, we found that deep learning can estimate wind from wave measurements accurately, making wave buoys a good-quality data source for sea wind.

To study what is happening in the atmosphere, it is important to be able to measure the molecules and clusters present in it. In our work, we studied an artifact that happens inside a mass spectrometer, in particular the fragmentation of clusters. We were able to quantify the fragmentation and retrieve the correct concentration and composition of the clusters using our dual (experimental and theoretical) approach.

The assimilation of GNSS data in weather models has a positive impact on the forecasts. The impact is still limited due to using only the GPS zenith direction parameters. We calculate and validate more advanced tropospheric products from three satellite systems: the US American GPS, Russian GLONASS and European Galileo. The quality of all the solutions is comparable; however, combining more GNSS systems enhances the observations' geometry and improves the quality of the weather forecasts.

The central component of satellite and model validation is pointwise measurements. A point is an element of space, whereas satellite (model) pixels represent an averaged area. These two datasets are inherently different. We leveraged some geostatistical tools to transform discrete points to gridded data with quantified uncertainty, comparable to satellite footprint (and response functions). This in part alleviated some complications concerning point–pixel comparisons.

This work presents heating rates derived from aircraft observations from the 2016 and 2017 field campaigns of ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS). We separate the total heating rates into aerosol and gas (primarily water vapor) absorption and explore some of the co-variability of heating rate profiles and their primary drivers, leading to the development of a new concept: the heating rate efficiency (HRE; the heating rate per unit aerosol extinction).

The emission of biogenic volatile organic compounds (BVOCs) from plant leaves is an essential part of biosphere–atmosphere interactions. Here we demonstrate how a dynamic chamber for measuring branch-scale BVOC emissions could be characterized both in the lab for adsorptive losses and in the field for ambient–enclosure environmental differences. The results also imply emission factors for terpenes might be underestimated if measured using dynamic chambers without certified transfer efficiencies.

Air temperature from sonic temperature and air moisture has been used without an exact equation. We present an exact equation of such air temperature for closed-path eddy-covariance flux measurements. Air temperature from this equation is equivalent to sonic temperature in its accuracy and frequency response. It is a choice for advanced flux topics because, with it, thermodynamic variables in the flux measurements can be temporally synchronized and spatially matched at measurement scales.

Sunlight can pass diagonally through the atmosphere, cutting through the 3-D water vapour field in a way that smears 2-D maps of imaging spectroscopy vapour retrievals. In simulations we show how this smearing is towards or away from the Sun, so calculating across the solar direction allows sub-kilometre information about water vapour's spatial scaling to be calculated. This could be tested by airborne campaigns and used to obtain new information from upcoming spaceborne data products.

During the VAL-OUC campaign, we established a coherent Doppler lidar (CDL) network over China to verify the Level 2B (L2B) products from Aeolus. By the simultaneous wind measurements with CDLs at 17 stations, the L2B products from Aeolus are compared with those from CDLs. To our knowledge, the VAL-OUC campaign is the most extensive so far between CDLs and Aeolus in the lower troposphere for different atmospheric scenes. The vertical velocity impact on the HLOS retrieval from Aeolus is evaluated.

We present a novel approach that can be used to obtain microphysical properties of atmospheric aerosol, up to several kilometers in the atmosphere, from lidar measurements taken from the ground. Our approach provides accurate reconstructions under many different experimental conditions. Our results can contribute to the expansion of the use of remote sensing techniques for air quality monitoring and atmospheric science in general.

Radiosonde descent data could provide extra profiles of the atmosphere for forecasting and other uses. Descent data from Vaisala RS41 radiosondes have been compared with the ascent profiles and with ECMWF short-range forecasts. The agreement is mostly good. The descent rate is very variable and high descent rates cause temperature biases, especially at upper levels. Ascent winds are affected by pendulum motion; on average, the descent winds are smoother.

The Aeolus satellite observes the Earth and can vertically detect any kind of particles (aerosols or clouds) in the atmosphere below it. These observations are typically very noisy, which needs to be accounted for. This work dampens the noise in Aeolus' aerosol and cloud data, which are provided publicly by the ESA, so that the scientific community can make better use of it. This makes the data potentially more useful for weather prediction and climate research.

Carbon monoxide (CO) is produced by combustion of substances such as fossil fuels and plays an important role in atmospheric pollution and climate. We evaluated estimates of atmospheric CO derived from outgoing radiation measurements of the Atmospheric Infrared Sounder (AIRS) on a satellite orbiting the Earth against CO measurements from aircraft to show that these satellite measurements are reliable for continuous global monitoring of atmospheric CO concentrations.