The current atmospheric observing systems fail to provide a satisfactory amount of spatially and temporally resolved observations of temperature and humidity in the planetary boundary layer (PBL) despite their potential positive impact on numerical weather prediction (NWP). This is particularly critical for humidity, which exhibits a very high variability in space and time or for the vertical distribution of temperature, determining the atmosphere’s stability. Novel ground-based lidar remote sensing technologies and in situ measurements from unmanned aerial vehicles can fill this observational gap, but operational maturity was so far lacking. Only recently, commercial lidar systems for temperature and humidity profiling in the lower troposphere and automated observations on board of drones have become available. Raman lidar can provide profiles of temperature and humidity with high temporal and vertical resolution in the troposphere. Drones can provide high-quality in situ observations of various meteorological variables with high temporal and vertical resolution, but flights are complicated in high-wind situations, icing conditions, and can be restricted by aviation activity. Both observation systems have shown to considerably improve analyses and forecasts of high-impact weather, such as thunderstorms and fog in an operational, convective-scale NWP framework. The results of this study demonstrate the necessity for and the value of additional, high-frequency PBL observations for NWP and how lidar and drone observations can fill the gap in the current operational observing system.

Abstract. Cirrus cloud thinning (CCT) is a relatively new radiation management proposal to counteract anthropogenic climate warming by targeting Earth's terrestrial radiation balance. The efficacy of this method was presented in several general circulation model (GCM) studies that showed widely varied radiative responses, originating in part from the differences in the representation of cirrus ice microphysics between the different GCMs. The recent implementation of a new, more physically based ice microphysics scheme (Predicted Particle Properties, P3) that abandons ice hydrometeor size class separation into the ECHAM-HAM GCM, coupled to a new approach for calculating cloud fractions that increases the relative humidity (RH) thresholds for cirrus cloud formation, motivated a reassessment of CCT efficacy. In this study, we first compared CCT sensitivity between the new cloud fraction approach and the original ECHAM-HAM cloud fraction approach. Consistent with previous approaches using ECHAM-HAM, with the P3 scheme and the higher RH thresholds for cirrus cloud formation, we do not find a significant cooling response in any of our simulations. The most notable response from our extreme case is the reduction in the maximum global-mean net top-of-atmosphere (TOA) radiative anomalies from overseeding by about 50 %, from 9.9 W m−2 with the original cloud fraction approach down to 4.9 W m−2 using the new cloud fraction RH thresholds that allow partial grid-box coverage of cirrus clouds above ice saturation, unlike the original approach. Even with this reduction with the updated cloud fraction approach, the TOA anomalies from overseeding far exceed those reported in previous studies. We attribute the large positive TOA anomalies to seeding particles overtaking both homogeneous nucleation and heterogeneous nucleation on mineral dust particles within cirrus clouds to produce more numerous and smaller ice crystals. This effect is amplified by longer ice residence times in clouds due to the slower removal of ice via sedimentation in the P3 scheme. In an effort to avoid this overtaking effect of seeding particles, we increased the default critical ice saturation ratio (Si,seed) for ice nucleation on seeding particles from the default value of 1.05 to 1.35 in a second sensitivity test. With the higher Si,seed we drastically reduce overseeding, which suggests that Si,seed is a key factor to consider for future CCT studies. However, the global-mean TOA anomalies contain high uncertainty. In response, we examined the TOA anomalies regionally and found that specific regions only show a small potential for targeted CCT, which is partially enhanced by using the larger Si,seed. Finally, in a seasonal analysis of TOA responses to CCT, we find that our results do not confirm the previous finding that high-latitude wintertime seeding is a feasible strategy to enhance CCT efficacy, as seeding in our model enhances the already positive cirrus longwave cloud radiative effect for most of our simulations. Our results also show feedbacks on lower-lying mixed-phase and liquid clouds through the reduction in ice crystal sedimentation that reduces cloud droplet depletion and results in stronger cloud albedo effects. However, this is outweighed by stronger longwave trapping from cirrus clouds with more numerous and smaller ice crystals. Therefore, we conclude that CCT is unlikely to act as a feasible climate intervention strategy on a global scale.

CapsuleSmall weather-sensing Uncrewed Aircraft Systems are becoming reliable and accurate enough to be considered as a cost-effective solution for filling observational gaps that could enhance National Meteorological and Hydrological Services around the world.

Abstract. Cirrus cloud thinning (CCT) is a relatively new radiation management proposal to counteract anthropogenic climate warming by targeting Earth’s terrestrial radiation balance. The efficacy of this method was presented in several general circulation model (GCM) studies that showed widely varied radiative responses, originating in part from the differences in the representation of cirrus ice microphysics between the different GCMs. The recent implementation of a new, more physically based ice microphysics scheme (Predicted Particle Properties, P3) that abandons ice hydrometeor size class separation into the ECHAM-HAM GCM, coupled to a new approach for calculating cloud fractions that increases the relative humidity (RH) thresholds for cirrus cloud formation, motivated a reassessment of CCT efficacy. In this study, we first compared CCT sensitivity between the new cloud fraction approach and the original ECHAM-HAM cloud fraction approach. With the P3 scheme and the higher RH thresholds for cirrus cloud formation, we find a significant cooling response of −0.36 Wm−2 only for our simulation with a seeding particle concentration of 1 L−1, due mostly to rapid cloud adjustments. The most notable response is the reduction of the maximum global-mean net top-of-atmosphere (TOA) radiative anomalies from overseeding by more than 50 %, from 9.0 Wm−2 with the original cloud fraction approach, down to 4.3 Wm−2 using the new cloud fraction RH thresholds by avoiding artificial ice-cloud expansion upon ice nucleation. We attribute the large positive TOA anomalies to seeding particles overtaking both homogeneous nucleation and heterogeneous nucleation on mineral dust particles within cirrus clouds to produce more numerous and smaller ice crystals. This effect is amplified by longer ice residence times in clouds due to the more realistic, slower removal of ice via sedimentation in the P3 scheme. In an effort to avoid this overtaking effect of seeding particles, we increased the default critical ice saturation ratio (Si,seed) for ice nucleation on seeding particles from the default value of 1.05 to 1.35 in a second sensitivity test. With the higher Si,seed we eliminate overseeding and are able to produce cooling responses over a broader range of seeding particle concentrations, with the largest cooling of −0.32 Wm−2 for a seeding particle concentration of 10 L−1, which suggests that Si,seed is a key factor to consider for future CCT studies. However, the global-mean TOA anomalies contain high uncertainty. In response, we examined the TOA responses regionally and found that specific regions only show a small potential for targeted CCT, which is partially enhanced by using the larger Si,seed. Finally, in a seasonal analysis of TOA responses to CCT, we find that our results do not support the previous finding that high-latitude wintertime seeding is a feasible strategy to enhance CCT efficacy, as seeding in our model enhances the already positive cirrus longwave cloud radiative effect. Instead, our results show that summertime cooling occurs due to adjustments of lower-lying mixed-phase and liquid clouds. Therefore, we conclude that CCT is unlikely to act as a feasible climate intervention strategy on a global scale, and should be investigated further with higher-resolution studies in potential target regions and with studies dedicated to assessing potentially realistic seeding particle materials.

<p>Wintertime stratus clouds over the Swiss Plateau can last for days.  They dissipate either due to airmass changes, absorption of solar radiation during the day, or after glaciation when a sufficiently large number of cloud droplets freezes. After formation, the ice crystals grow in an ice-supersaturated environment via vapor deposition until they are large enough to sediment from the cloud as drizzle or freezing drizzle.</p> <p>To better understand how quickly ice crystals of various habits grow in real clouds with turbulence, we conduct glaciogenic seeding experiments in wintertime stratus clouds over the Swiss Plateau in our project CLOUDLAB[1]. During these experiments, a drone releases silver iodide (AgI) particles into the cloud, upwind of our measurement site, and we use various ground-based remote sensing and in-situ cloud and aerosol instruments to detect the microphysical changes induced by seeding. Preliminary results from the first CLOUDLAB field campaign proved that our method successfully allows us to detect the seeding signal in the cloud radar. In addition to our field measurements, we conduct numerical model simulations with ICON at different horizontal resolutions and different seeding particle concentrations to understand which seeding AgI concentration is theoretically needed for partial or full glaciation of the cloud, i.e. how fast the ice crystals grow at the expense of the evaporating cloud droplets due to the Wegener-Bergeron-Findeisen process.</p> <p>First results will be presented in this talk.</p> <div><br /> <div> <p>[1] https://cloudlab.ethz.ch/</p> </div> </div>