Earth’s tropical sky is filled with shallow cumulus clouds, which are organised into intricate patterns. In this project, we develop, for the first time, a systematic understanding of the processes responsible for creating and dissolving these patterns, across the tropical ocean and rainforest. We develop this understanding by extracting new conceptual pictures from new, extremely high-resolution simulations and observations of the full tropics. Because cloud patterns cool the planet by reflecting sunlight, we then use this new understanding to project how the patterns react to and influence global warming – helping to meet one of climate science’s greatest challenges.

The power grid in the Netherlands has to accommodate more and more production of solar energy. Due to the erratic nature of incoming solar radiation, fluctuations in the grid arise that could cause instability. In Every Ray Counts (a collaboration between Wageningen University and Alliander), we have worked on better integrating meteorological knowledge into grid management in order to help the energy transition. We have shown that the largest peaks in solar energy production occur on scales shorter than the 15-minutes of the energy market operates and we have worked on better predictions of these peaks based on KNMI forecasts.

Global temperatures are rising due to anthropogenic greenhouse gas emissions, leading to widespread, rapid changes in the climate system. Atmospheric carbon dioxide (CO2) is the main greenhouse gas contributing to climate forcing, and only thanks to uptake by natural sinks in the biosphere and oceans its rise in the atmosphere is slowed down by around 56%. To understand atmospheric CO2 levels, it is therefore not only crucial to know the rates of anthropogenic CO2 emissions, but also how much CO2 is taken up by these natural sinks. In this program, I will build a team that uses atmospheric oxygen (O2) to contribute to two fundamental challenges in carbon cycle research: understanding the gross drivers of biosphere CO2 exchange –photosynthesis and respiration– and separating the anthropogenic and natural components in the atmospheric CO2 signal. Atmospheric O2 and CO2 are directly coupled in the carbon cycle and connected through their so-called exchange ratios which are at the heart of my program. My team will augment novel laboratory experiments of O2/CO2 exchange under controlled climatic conditions with measurements at two locations in the Netherlands: the Loobos forest site and the Rotterdam urban site. I aim to derive new estimates for the spatial-temporal variability of the biosphere O2/CO2 exchange ratio and provide new estimates of photosynthesis and respiration fluxes of CO2 and O2 at leaf-, plant- and ecosystem-scale. For the anthropogenic component, I will provide near real-time estimates of CO2 fossil fuel emissions based on new measurements, using unique exchange ratios per fuel type to “fingerprint” the signals and attribute them to different emission sources. Together with the development of a regional CarbonTracker-O2 modelling framework, this offers an exciting possibility to better quantify the European CO2 landscape. This is highly relevant for the energy transition towards achieving pledged CO2 emission reductions.

The main objective of the proposed study was to assess to what extent we could use satellite observations to detect the ecosystem-scale impact of the air pollutant ozone on plant photosynthesis. Current estimates of this impact are mainly based on laboratory experiments. Alternatively, we studied this by combining satellite observations with an European-scale air quality model. This included use of satellite observations of gases such as nitrogen dioxide that result in the formation of ozone. However, the study also revealed that apparently the quality of current ecosystem-scale vegetation products is not yet sufficient to allow detection of this ozone impact.

Cloud shadows drive strong variability in surface solar irradiance. With solar power as the fastest growing energy source worldwide, this variability poses an increasing threat to the stability of the electrical grid, because it drives strong local fluctuations in voltage. Due to the complex nature of cloud formation, a thorough understanding of the spatial extent, duration, and intensity of solar irradiance variability is lacking, and consequently weather forecasts of this variability are poor. This project will address this knowledge gap, by performing a novel field experiment, and by improving the next-generation of weather models guided by the outcome of the experiment. We will set up a spatial grid (1 km2, 50 m spacing) of hundreds of newly-designed sensors and measure surface solar irradiance at 12 wavelengths during one year. This experiment will be embedded into the new Ruisdael Observatory, which will deliver complementary cloud and aerosol observations. We will elucidate the poorly understood links between surface solar irradiance variability and the optical and geometrical properties of clouds. We will further corroborate the findings of our experiment with 3D large-eddy simulation (LES) as a virtual laboratory. This simulation technique permits models to resolve individual clouds and is therefore able to explicitly simulate the 3D interactions between clouds and radiation. While LES enables understanding of cloud-radiation interactions beyond what is possible from field experiments, using it for forecasting remains problematic due to the large computational costs associated with 3D radiation computations. Building upon my experience in LES and GPU computing and guided by the field experiment, I aim to remove this barrier by developing the first LES setup with 3D radiation fast enough for forecasting. This setup will be put to the test and validated against weather station and solar panel production data.