Christoph Ritter

Understanding the role of water vapor in Arctic amplification requires a detailed evaluation of its spatio‐temporal variability. In this work, we use an integrated water vapor (IWV) data set from a ground‐based microwave radiometer at Ny‐Ålesund, Svalbard, covering 2012–2024, to characterize temporal IWV variability. We also identify extreme atmospheric moistening and drying events based on a new detection method and relate them to large‐scale circulation patterns and airmass pathways. IWV exhibits a pronounced annual cycle with values ranging from 0.6 to 33 kg . While absolute IWV variability within a month is smaller in winter than in summer, relative variability is nearly twice as large. We identified 352 extreme moistening and 371 extreme drying events, accounting for 20% of the study period. Extreme drying occurs primarily through continuous drying, whereas extreme moistening events include a higher fraction of consecutive moistening episodes and therefore last longer. Most events occur on synoptic time scales of 1–3 days. Extreme moistening events are linked to large‐scale circulation patterns that facilitate the advection of moist airmasses toward Svalbard from southeasterly to westerly directions, which account for 52% of all moistening events. Extreme drying occurs under similar circulation patterns, but is mainly linked to a reduction in the poleward moisture transport due to an eastward shift of the prevailing pressure centers. 45% of extreme drying events follow directly after an extreme moistening event. Given the comprehensive ground‐based observations available at Ny‐Ålesund, the identified events provide a useful framework to study their impact on clouds, precipitation, radiation, and surface conditions.

In this work, we present a case study mainly from Raman lidar observations and radiosonde data for a site in the European Arctic to analyse how aerosol grows into a purely water-containing fog. We use a relatively high resolution (85 s, 7.5 m) for the lidar evaluation and use an inversion technique to derive aerosol size distributions before fog formation, in the fog and directly after fog disintegration. We find predominantly accumulation-size particles before and after the fog event. In the fog layer, this mode splits up into two branches: one is hydrophobic, and the other roughly doubles its size within 85 s but does not grow into typical cloud droplet sizes. We find very high lidar ratios > 100 sr for 532 nm. We use Mie calculations to confirm that such high lidar ratios are to be expected for micron-sized droplets if the imaginary part of the refractive index is not negligible. Further, we analyse how lidar ratio and colour ratio change as a function of cloud optical depth and derive that the formation and disintegration of several short-lived fog events at the same altitude seem to be symmetrical. Finally, we employ Koehler theory to show that the droplets should have grown into super-micron sizes. As this has not been observed clearly, the time for particle growth into cloud regime under low turbulence conditions takes longer than 85 s.

In this work, we revise the retrieval of extinction coefficient profiles from Raman Lidar. This is an ill-posed problem, and we show that methods like Levenberg–Marquardt or Tikhonov–Phillips can be applied. We test these methods for a synthetic Lidar profile (known solution) with different noise realizations. Further, we apply these methods to three different cases of data from the Arctic: under daylight (Arctic Haze), under daylight with a high and vertically extended aerosol layer, and at nighttime with high extinction. We show that our methods work and allow a trustful derivation of extinction up to clearly higher altitudes (at about half a signal-to-noise ratio) compared with the traditional, non-regularized Ansmann solution. However, these new methods are not trivial and require a choice of parameters, which depend on the noise of the data. As the Lidar signal quality quickly decreases with range, a separation of the profile into several sub-intervals seems beneficial.

The climate impact of Arctic aerosols, like the Arctic Haze, and their origin are not fully understood. Therefore, long-term aerosol observations in the Arctic are performed. In this study, we present a homogenised data set from a sun and star photometer operated in the European Arctic, in Ny-Ålesund, Svalbard, of the 20 years from 2004–2023. Due to polar day and polar night, it is crucial to use observations of both instruments. Their data is evaluated in the same way and follows the cloud-screening procedure of AERONET. Additionally, an improved method for the calibration of the star photometer is presented. We found out, that autumn and winter are generally more polluted and have larger particles than summer. While the monthly median Aerosol Optical Depth (AOD) decreases in spring, the AOD increases significantly in autumn. A clear signal of large particles during the Arctic Haze can not be distinguished from large aerosols in winter. With autocorrelation analysis, we found that AOD events usually occur with a duration of several hours. We also compared AOD events with large-scale processes, like large-scale oscillation patterns, sea ice, weather conditions, or wildfires in the Northern Hemisphere but did not find one single cause that clearly determines the Arctic AOD. Therefore the observed optical depth is a superposition of different aerosol sources.

This study aims to investigate the microphysical properties of Arctic, tropospheric aerosol in the transition from the Arctic Haze in spring towards the summer season in 2021. A special focus lies on the hygroscopicity of the aerosol. Therefore, a one-parameter growth curve model is applied to lidar data from the Koldewey Aerosol Raman Lidar (AWIPEV in Ny-Ålesund, Svalbard) and simultaneous radiosonde measurements. Hygroscopic growth depends on different factors like aerosol diameter and chemical composition. To detangle this dependency, three trends in hygroscopicity are additionally investigated by classifying the aerosol first by its color ratio, and then by its season and altitude. Furthermore, two special days are discussed using Mie-theory. They show on the one side the complexity of analyzing hygroscopic growth by means of lidar data, but on the other side demonstrate that it is in fact measurable with this approach. For these two case studies we calculated, that the aerosol effective radius increased from 0.16 μ m (dry) to 0.18 μ m (wet), and from 0.28 μ m to 0.32 μ m for the second case. Generally, we found two different modes of stronger or weaker hygroscopic particles and a complex altitude dependence with the least hygroscopic particles in the middle free troposphere.

The origin and climate impact of Arctic aerosols, like the Arctic Haze, are not fully understood. Therefore, long-term aerosol observations in the Arctic are performed. In this study we present a homogenised data set from sun and star photometer operated in the European Arctic, in Ny-Ålesund, Svalbard, from 2004 – 2023. Due to polar day and polar night it is crucial to use observations of both instruments. Their data is evaluated in the same way and follows the cloud-screening procedure of AERONET. Additionally, an improved method for the calibration of the star photometer is presented. We found out, that winter months are generally more polluted and have larger particles than summer. While the monthly median Aerosol Optical Depth (AOD) decreases in spring, the AOD increases significantly in autumn months. The Arctic Haze is not characterised by large particles and can not be distinguished from large aerosols in winter months. With autocorrelation analysis we found out, that AOD events usually occur with duration of several hours and are therefore caused by large-scale processes and may have a periodicity of several days. Local processes can be neglected in Ny-Ålesund but long-range transport plays a major role for the Arctic aerosol budget. We also compared AOD events with large-scale processes, like large-scale oscillation patterns, sea ice, weather conditions or wildfires on the Northern Hemisphere but did not find one single cause, which clearly determines the Arctic AOD.

An Nd:YAG-based Raman lidar provides a mature technology to derive profiles of the optical properties of aerosols over a wide altitude range. However, the derivation of micro-physical parameters is an ill-posed problem. Hence, increasing the information content of lidar data is desirable. Recently, ceilometers and wind lidar systems, both operating in the near-infrared region, have been successfully employed in aerosol research. In this study, we demonstrate that the inclusion of additional backscatter coefficients from these two latter instruments clearly improves the inversion of micro-physical parameters such as volume distribution function, effective radius, or single-scattering albedo. We focus on the Arctic aerosol and start with the typical volume distribution functions of Arctic haze and boreal biomass burning. We forward calculate the optical coefficients that the lidar systems should have seen and include or exclude the backscatter coefficients of the ceilometer (910 nm) and wind lidar data (1500 nm) to analyze the value of these wavelengths in their ability to reproduce the volume distribution function, which may be mono- or bimodal. We found that not only the coarse mode but also the properties of the accumulation mode improved when the additional wavelengths were considered. Generally, the 1500 nm wavelength has greater value in correctly reproducing the aerosol properties.

This study presented an analysis of the geometric and optical properties of cirrus clouds with data produced by Compact Cloud-Aerosol Lidar (ComCAL) over Koror, Palau (7.3°N, 134.5°E), in the Tropical Western Pacific region. The lidar measurement dataset covers April 2018 to May 2019 and includes data collected during March, July and August 2022. The results show that cirrus clouds occur approximately 47.9% of the lidar sampling time, predominantly between altitudes of 15 and 18 km. Seasonal variations in cirrus top height closely align with those of the cold point tropopause. Most cirrus clouds exhibit low cloud optical depth (COD < 0.1), with an annual mean depolarization ratio of 31 ± 19%. Convective-forming cirrus clouds during the summer monsoon season exhibit a larger size by notably lower values in terms of color ratio. Extremely thin cirrus clouds (COD < 0.005) constituting 1.6% of total cirrus occurrences are frequently observed at 1–2 km above the cold point, particularly during winter and summer, suggesting significant stratosphere–troposphere exchange. The coldest and highest tropopause over Palau is persistent during winter, and related to the pathway of tropospheric air entering the stratosphere through the cold trap. In summer, the extremely thin cirrus above the cold point is likely correlated with equatorial Kelvin waves induced by western Pacific monsoon convection.