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Eleven years of dual-polarization weather radar data, complemented by satellite and lidar observations, were used to investigate the origin of areas of localized intensification of precipitation spotted in the vicinity of Helsinki-Vantaa airport. It was observed that existing precipitation is enhanced locally on spatial scales from a few kilometers to several tens of kilometers. The precipitation intensity in these localized areas was 6-14 times higher than the background large-scale precipitation rate. Surface observations and dual-polarization radar data indicate that snowflakes within the ice portion of the falling precipitation in the intensification regions are larger and more isotropic than in the surrounding precipitation. There appears to be an increase in the ice particle number concentration within the intensification region. The observed events were linked to arriving or departing air traffic. We advocate that the mechanism responsible for intensification is aircraft-produced ice particles boosting the aggregation growth of snowflakes. Plain Language Summary: By analyzing 11 years of dual-polarization weather radar observations in the Helsinki region, we have discovered that airplanes landing in or departing from the Helsinki-Vantaa airport could locally increase precipitation rate by as much as 14 times. The observed phenomenon is related to the hole-punch clouds, which are also forming with the help of airplanes. The reported observations allow us to have a better understanding of precipitation formation processes that take place in ice and mixed phase clouds. They show that falling ice crystals from upper clouds could seed lower clouds and therefore increase rain or snowfall intensity through the process called snowflake aggregation. During snowflake aggregation bigger faster falling particles are formed by ice particles colliding and sticking together.

This study presents analysis of in situ measurements conducted over the period 2005–2014 in the Indian Himalayas to give a thorough overview of the factors and causes that drive aerosol properties. Aerosol extensive properties (namely, particle number concentration, scattering coefficient, equivalent black carbon, PM2.5, and PM10) have 1.5–2 times higher values in the early to late afternoon than during the night, and a strong seasonality. The interannual variability is ±20% for both PM2.5 and total particle number concentration. Analysis of the data shows statistically significant decreasing trends of −2.3 μg m−3 year−1 and −2.7 μg m−3 year−1 for PM2.5 and PM10, respectively, over the study period. The mountainous terrain site (Mukteshwar, MUK) is primarily under the influence of air from the plains. This is due to convective transport processes that are enhanced by local and mesoscale topography, leading to pronounced valley/mountain winds and consequently to atmospheric boundary layer air lifting from the plains below. The transport from plains is evident in seasonal‐diurnal patterns observed at MUK. The timing of the patterns corresponds with changes in turbulence and water vapor (q). According to our analysis, using these as proxies is a viable method for examining boundary layer influence in the absence of direct atmospheric boundary layer height measurements. Comparing the measurements with climate models shows that even regional climate models have problems capturing the orographic influence accurately at MUK, highlighting the importance of long‐term direct measurements at multiple points to understand aerosol behavior in mountainous areas.

We have extensively evaluated the response of cloud base drizzle rate (Rcb; mm d−1) in warm clouds to liquid water path (LWP; g m−2) and to cloud condensation nuclei (CCN) number concentration (NCCN; cm−3), an aerosol proxy. This evaluation is based on a 19 month long data set of Doppler radar, lidar, microwave radiometers, and aerosol observing systems from the Atmospheric Radiation Measurement (ARM) Mobile Facility deployments at the Azores and in Germany. Assuming 0.55% supersaturation to calculate NCCN, we found a power law Rcb=0.0015±0.0009⋅LWP1.68±0.05NCCN−0.66±0.08, indicating that Rcb decreases by a factor of 2–3 as NCCN increases from 200 to 1000 cm−3 for fixed LWP. Additionally, the precipitation susceptibility to NCCN ranges between 0.5 and 0.9, in agreement with values from simulations and aircraft measurements. Surprisingly, the susceptibility of the probability of precipitation from our analysis is much higher than that from CloudSat estimates but agrees well with simulations from a multiscale high-resolution aerosol-climate model. Although scale issues are not completely resolved in the intercomparisons, our results are encouraging, suggesting that it is possible for multiscale models to accurately simulate the response of LWP to aerosol perturbations.

Accurate observations of cloud microphysical properties are needed for evaluating and improving the representation of cloud processes in climate models and better estimate of the Earth radiative budget. However, large differences are found in current cloud products retrieved from ground-based remote sensing measurements using various retrieval algorithms. Understanding the differences is an important step to address uncertainties in the cloud retrievals. In this study, an in-depth analysis of nine existing ground-based cloud retrievals using ARM remote sensing measurements is carried out. We place emphasis on boundary layer overcast clouds and high level ice clouds, which are the focus of many current retrieval development efforts due to their radiative importance and relatively simple structure. Large systematic discrepancies in cloud microphysical properties are found in these two types of clouds among the nine cloud retrieval products, particularly for the cloud liquid and ice particle effective radius. Note that the differences among some retrieval products are even larger than the prescribed uncertainties reported by the retrieval algorithm developers. It is shown that most of these large differences have their roots in the retrieval theoretical bases, assumptions, as well as input and constraint parameters. This study suggests the need to further validate current retrieval theories and assumptions and even the development of new retrieval algorithms with more observations under different cloud regimes.

[1] Supercooled liquid water clouds can occur in the form of thin layers that have a much larger radiative impact than ice clouds of the same water content because of their smaller particle size, yet they are poorly represented in climate models. Such clouds may be easily distinguished from ice by their high lidar backscatter coefficient and sharp backscatter gradient at cloud top. In this paper, data from the Lidar In-space Technology Experiment (LITE), which flew on the space shuttle in 1994, are used to estimate the fraction of clouds that contain supercooled liquid water over the latitude range ±60°. Around 20% of clouds between −10°C and −15°C were found to contain liquid water, falling with temperature to essentially zero below −35°C. Even from this limited dataset some clear latitudinal clear trends were evident, with a distinctly more frequent occurrence of supercooled water in clouds associated with mid-latitude weather systems in the southern hemisphere, as well as in tropical clouds warmer than around −15°C. The results between 40 and 60°N agree well with the distribution previously found at Chilbolton in Southern England (51°N), implying that the forthcoming long-term lidar observations from space will be able to infer the global distribution of mixed-phase clouds with much greater accuracy and vertical resolution than has been possible until now.