Atmospheric stability indicates whether air vertical motion is dumped or amplified. This is important for wind energy applications as it affects wind turbine wakes and thus the yield of wind parks. The paper provides an assessment of stability metrics measured by ground-based microwave radiometers in different climatological conditions and instrument types, onshore and offshore. Results indicate that special precaution may be required offshore to achieve typical onshore performances.

Europe frequently experiences compound events, with major impacts. We investigate these events’ interactions, characteristics, and changes over time, focusing on socio-economic impacts in Germany and central Europe. Highlighting 2018’s extreme events, this study reveals impacts on water, agriculture, and forests and stresses the need for impact-focused definitions and better future risk quantification to support adaptation planning.

The German federal state of Brandenburg is particularly prone to soil moisture droughts. To support the management of related risks, we introduce a novel soil moisture and drought monitoring network based on cosmic-ray neutron sensing technology. This initiative is driven by a collaboration of research institutions and federal state agencies, and it is the first of its kind in Germany to have started operation. In this brief communication, we outline the network design and share first results.

We compared wind measurements using different lidar setups at various heights. The triple Doppler lidar, sonic anemometer, and two single Doppler lidars were tested. Overall, the lidar methods showed good agreement with the sonic anemometer. The triple Doppler lidar performed better than single Doppler lidars, especially at higher altitudes. We also developed a new filtering approach for virtual tower scanning strategies. Single Doppler lidars provide reliable wind data over flat terrain.

Little noise in radial velocity Doppler lidar measurements can contribute to large errors in retrieved turbulence variables. In order to distinguish between plausible and erroneous measurements we developed new filter techniques that work independently of the choice of a specific threshold for the signal-to-noise ratio. The performance of these techniques is discussed both by means of assessing the filter results and by comparing retrieved turbulence variables versus independent measurements.

Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.

This publication describes the microwave radiometric measurements performed during the EUREC⁴A campaign at Barbados Cloud Observatory (BCO) and aboard RV Meteor and RV Maria S Merian. We present retrieved integrated water vapor (IWV), liquid water path (LWP), and temperature and humidity profiles as a unified, quality-controlled, multi-site data set on a 3 s temporal resolution for a core period between 19 January 2020 and 14 February 2020.

This paper uses the tail pairwise dependence matrix (TPDM) proposed by Cooley and Thibaud (2019), which we extend to the description of common extremes in two variables. We develop an extreme pattern index (EPI), a pattern-based aggregation to describe spatially extended weather extremes. Our results show that the EPI is suitable for describing heat waves.  We extend the EPI to describe extremes in two variables and obtain an index to describe compound precipitation deficits and heat waves.

In this study, measurement uncertainties from microwave radiometers and their impact on temperature profiling are analyzed. These measurement uncertainties include horizontal inhomogeneities of the atmosphere, pointing errors or tilts of the instrument, physical obstacles which are in the line of sight of the radiometer, and radio frequency interferences. Impacts on temperature profiles from these uncertainties are usually small in real-life scenarios and when obstacles are far enough away.

The present study used several different datasets, conducted a field survey, and paired the data with three different machine learning algorithms to construct spatial maps for areas at risk of land degradation for the Lut watershed in Iran. According to the land degradation map, almost the entire study region is at risk. A large fraction of 43 % of the area is prone to both high wind-driven and water-driven soil erosion.

Sensitivity analyses for wind direction effects upon an ENVI-met microclimate model were performed for a heterogeneous urban study area. Significant temperature differences were found when forcing the model with constant N/E/S/W wind direction data. Best model performance was observed using measured wind direction forcing data. The results demonstrate that cooling effects of park areas are largely directional which is important for urban planning and design of climate change adaptation measures.

In this study we performed high-resolution climate model simulations for the hyper-arid Atacama Desert for the mid-Pliocene (3.2 Ma). The aim is to uncover the atmospheric processes that are involved in the enhancement of strong rainfall events during this period. We find that strong upper-level moisture fluxes (so-called moisture conveyor belts) originating in the tropical eastern Pacific are the main driver for increased rainfall in the mid-Pliocene.

Marine stratocumulus clouds of the eastern Pacific play an essential role in the Earth's climate. These clouds form the major source of water to parts of the extreme dry Atacama Desert at the northern coast of Chile. For the first time these clouds are observed over a whole year with three remote sensing instruments. It is shown how these clouds are influenced by the land–sea wind system and the distribution of ocean temperatures.

This work analyses a meteorological event, called nocturnal low-level jets (NLLJs), defined as high wind speeds relatively close to the surface. There were positive and negative impacts from NLLJs. While NLLJs increased the mean power production, they also increased the variability in the wind with height. Our results imply that long NLLJ events are also larger, affecting many wind turbines at the same time. Short NLLJ events are more local, having stronger effects on power variability.

Lidars can measure the wind profile in the lower part of the atmosphere, provided that the wind field is horizontally uniform and does not change during the time of the measurement. These requirements are mostly not fulfilled in reality, and the lidar wind measurement will thus hold a certain error. We investigate different strategies for lidar wind profiling using a lidar simulator implemented in a numerical simulation of the wind field. Our findings can help to improve wind measurements.

When insects fill the lower kilometers of the atmosphere, they get caught in the convergent parts of the wind field. Their concentration visualizes the otherwise invisible circulation on radar images. This study shows how clear-air radar data can be compared to simulated wind fields in terms of scale, anisotropy, and direction. Despite known difficulties with simulating these near-surface wind systems, we find decent agreement between a long-term simulation and the German radar mosaic.

Stationary, long-lasting blocked weather patterns can lead to extreme conditions. Within this study the temporal evolution of the occurrence probability is analyzed, and the onset, decay and transition probabilities of blocking within the past 30 years are modeled. Using Markov models combined with logistic regression, we found large changes in summer, where the probability of transitions to so-called Omega blocks increases strongly, while the unblocked state becomes less probable.

Lockdowns to avoid the spread of COVID-19 have created an unprecedented reduction in human emissions. We can estimate the changes in emissions at a country level, but to make predictions about how this will affect our climate, we need more precise information about where the emissions happen. Here we combine older estimates of where emissions normally occur with very recent estimates of sector activity levels to enable different groups to make simulations of the climatic effects of lockdown.

A fleet of quadrotors is presented as a system to measure the spatial distribution of atmospheric boundary layer flow. The big advantage of this approach is that multiple and flexible measurement points in space can be sampled synchronously. The algorithm to calculate the horizontal wind is based on the principle of aerodynamic drag and the related quadrotor dynamics. The validation reveals that an average accuracy of < 0.3 m s⁻¹ for the wind speed and < 8° for the wind direction was achieved.

Temperature and humidity profiles in the lowest couple of kilometers near the surface are very important for many applications. Passive spectral radiometers are commercially available, and observations from these instruments have been used to get these profiles. However, new active lidar systems are able to measure partial profiles of water vapor. This paper investigates how the derived profiles of water vapor and temperature are improved when the active and passive observations are combined.

We find that increased temperatures affect aerosols and reactive gases by changing natural emissions and their rates of removal from the atmosphere. Changing the composition of these species in the atmosphere affects the radiative budget of the climate system and therefore amplifies or dampens the climate response of climate models of the Earth system. This study found that the largest effect is a dampening of climate change as warmer temperatures increase the emissions of cooling aerosols.