The continuous measuring of the vertical profile of water vapor in the boundary layer using a commercially available differential absorption lidar (DIAL) has only recently been made possible. Since September 2018, a new pre-production version of the Vaisala DIAL system has operated at the Iqaluit supersite (63.74°N, 68.51°W), commissioned by Environment and Climate Change Canada (ECCC) as part of the Canadian Arctic Weather Science project. This study presents its evaluation during the extremely dry conditions experienced in the Arctic by comparing it with coincident radiosonde and Raman lidar observations. Comparisons over a one year period were strongly correlated (r > 0.8 at almost all heights) and exhibited an average bias of +0.13 ± 0.01 g/kg (DIAL-sonde) and +0.18 ± 0.02 g/kg (DIAL-Raman). Larger differences exhibiting distinct artifacts were found between 250 and 400 m above ground level (AGL). The DIAL’s observations were also used to conduct a verification case study of operational numerical weather prediction (NWP) models during the World Meteorological Organization’s Year of Polar Prediction. Comparisons to ECCC’s global environmental multiscale model (GEM-2.5 km and GEM-10 km) indicate good agreement with an average bias < 0.16 g/kg for the higher-resolution (GEM-2.5 km) models. All models performed significantly better during the winter than the summer, likely due to the winter’s lower water vapor concentrations and decreased variability. This study provides evidence in favor of using high temporal resolution lidar water vapor profile measurements to complement radiosonde observations and for NWP model verification and process studies.

Atmospheric water vapour is the dominant gas in the greenhouse effect and its diurnal cycle is an essential component of the hydrological cycle. High-quality water-vapour measurements are critical observations for numerical weather prediction (NWP) models, which encounter difficulties in the Arctic due to its unique weather. Accurate measurements of the diurnal water-vapour cycle can improve precipitation rate and type predictions. In this study, we use a preproduction Vaisala broad-band differential absorption lidar (DIAL), installed in Iqaluit, Nunavut (63.75 • N, 68.55 • W), to calculate seasonal height-resolved diurnal water-vapour cycles from 100-1,500 m altitude. We also calculate the surface water-vapour mixing ratio and integrated water-vapour (IWV) diurnal cycles using co-located surface station and global navigation satellite system (GNSS) measurements. We find that the first 250 m of the DIAL water-vapour mixing ratio height-resolved diurnal cycle agrees within 0.02 g⋅kg −1 with the surface-station amplitudes, and within 0-2 hr in phase. DIAL diurnal-cycle R 2 values are close to 1 at the surface, and between 0.25 and 0.95 depending on the altitude and season. The phases of the diurnal cycle shift and the amplitudes increase with altitude. In the summer, all instruments observe a strong 24-hr cycle. The amplitude of the 24-hr component decreases with the solar cycle, such that the 12-hr component begins to influence the total cycle significantly by the winter. The IWV has a large 12-hr component throughout the year, which could be due to the superposition of two diurnal components at different altitudes or increasing contributions at altitudes higher than those measured by the DIAL.We have shown that using DIAL measurements to observe height-resolved diurnal cycles provides a deeper understanding of the diurnal cycle than that achieved from GNSS and surface measurements alone.

Abstract. Raman lidars have been designated as potential candidates for trend studies by the Network for the Detection of Atmospheric Composition Change (NDACC) and GCOS (Global Climate Observing System) Reference Upper Air Network (GRUAN); however, for such studies improved calibration techniques are needed as well as careful consideration of the calibration uncertainties. Trend determinations require frequent, accurate, and well-characterized measurements. However, water vapour Raman lidars produce a relative measurement and require calibration in order to transform the measurement into a mixing ratio, a conserved quantity when no sources or sinks for water vapour are present. Typically, the calibration is done using a reference instrument such as a radiosonde. We present an improved trajectory technique to calibrate water vapour Raman lidars based on the previous work of Whiteman et al. (2006), Leblanc and Mcdermid (2008), Adam et al. (2010), and Herold et al. (2011), who used radiosondes as an external calibration source and matched the lidar measurements to the corresponding radiosonde measurement. However, they did not consider the movement of the radiosonde relative to the air mass and fronts. Our trajectory method is a general technique which may be used for any lidar and only requires that the radiosonde report wind speed and direction. As calibrations can be affected by a lack of co-location with the reference instrument, we have attempted to improve their technique by tracking the air parcels measured by the radiosonde relative to the field of view of the lidar. This study uses GRUAN Vaisala RS92 radiosonde measurements and lidar measurements taken by the MeteoSwiss RAman Lidar for Meteorological Observation (RALMO), located in Payerne, Switzerland, from 2011 to 2016 to demonstrate this improved calibration technique. We compare this technique to the traditional radiosonde–lidar calibration technique which does not involve tracking the radiosonde and uses the same integration time for all altitudes. Both traditional and our trajectory methods produce similar profiles when the water vapour field is homogeneous over the 30 min calibration period. We show that the trajectory method reduces differences between the radiosonde and lidar by an average of 10 % when the water vapour field is not homogeneous over a 30 min calibration period. We also calculate a calibration uncertainty budget that can be performed on a nightly basis. The calibration uncertainty budget includes the uncertainties due to phototube paralysis, aerosol extinctions, the assumption of the Ångström exponent, and the radiosonde. The study showed that the radiosonde was the major source of uncertainty in the calibration at 4 % of the calibration value. This trajectory method showed small improvements for RALMO's calibration but would be more useful for stations in different climatological regions or when non-co-located radiosondes are the only available calibration source.

Abstract. Water vapour is the strongest greenhouse gas in our atmosphere, and its strength and its dependence on temperature lead to a strong feedback mechanism in both the troposphere and the stratosphere. Raman water vapour lidars can be used to make high-vertical-resolution measurements on the order of tens of metres, making height-resolved trend analyses possible. Raman water vapour lidars have not typically been used for trend analyses, primarily due to the lack of long-enough time series. However, the Raman Lidar for Meteorological Observations (RALMO), located in Payerne, Switzerland, is capable of making operational water vapour measurements and has one of the longest ground-based and well-characterized data sets available. We have calculated an 11.5-year water vapour climatology using RALMO measurements in the troposphere. Our study uses nighttime measurements during mostly clear conditions, which creates a natural selection bias. The climatology shows that the highest water vapour specific-humidity concentrations are in the summer months and the lowest in the winter months. We have also calculated the geophysical variability of water vapour. The percentage of variability of water vapour in the free troposphere is larger than in the boundary layer. We have also determined water vapour trends from 2009 to 2019. We first calculate precipitable water vapour (PWV) trends for comparison with the majority of water vapour trend studies. We detect a nighttime precipitable water vapour trend of 1.3 mm per decade using RALMO measurements, which is significant at the 90 % level. The trend is consistent with a 1.38 ∘C per decade surface temperature trend detected by coincident radiosonde measurements under the assumption that relative humidity remains constant; however, it is larger than previous water vapour trend values. We compare the nighttime RALMO PWV trend to daytime and nighttime PWV trends using operational radiosonde measurements and find them to agree with each other. We cannot detect a bias between the daytime and nighttime trends due to the large uncertainties in the trends. For the first time, we show height-resolved increases in water vapour through the troposphere. We detect positive tropospheric water vapour trends ranging from a 5 % change in specific humidity per decade to 15 % specific humidity per decade depending on the altitude. The water vapour trends at five layers are statistically significant at or above the 90 % level.

Abstract. The changing Arctic climate is creating increased economic, transportation, and recreational activities requiring reliable and relevant weather information. However, the Canadian Arctic is sparsely observed, and processes governing weather systems in the Arctic are not well understood. There is a recognized lack of meteorological data to characterize the Arctic atmosphere for operational forecasting and to support process studies, satellite calibration/validation, search and rescue operations (which are increasing in the region), high-impact weather (HIW) detection and prediction, and numerical weather prediction (NWP) model verification and evaluation. To address this need, Environment and Climate Change Canada commissioned two supersites, one in Iqaluit (63.74∘ N, 68.51∘ W) in September 2015 and the other in Whitehorse (60.71∘ N, 135.07∘ W) in November 2017 as part of the Canadian Arctic Weather Science (CAWS) project. The primary goals of CAWS are to provide enhanced meteorological observations in the Canadian Arctic for HIW nowcasting (short-range forecast) and NWP model verification, evaluation, and process studies and to provide recommendations on the optimal cost-effective observing system for the Canadian Arctic. Both sites are in provincial/territorial capitals and are economic hubs for the region; they also act as transportation gateways to the north and are in the path of several common Arctic storm tracks. The supersites are located at or next to major airports and existing Meteorological Service of Canada ground-based weather stations that provide standard meteorological surface observations and upper-air radiosonde observations; they are also uniquely situated in close proximity to frequent overpasses by polar-orbiting satellites. The suite of in situ and remote sensing instruments at each site is completely automated (no on-site operator) and operates continuously in all weather conditions, providing near-real-time data to operational weather forecasters, the public, and researchers via obrs.ca. The two sites have similar instruments, including mobile Doppler weather radars, multiple vertically profiling and/or scanning lidars (Doppler, ceilometer, water vapour), optical disdrometers, precipitation gauges in different shielded configurations, present weather sensors, fog monitoring devices, radiation flux sensors, and other meteorological instruments. Details on the two supersites, the suites of instruments deployed, the data collection methods, and example case studies of HIW events are discussed. CAWS data are publicly accessible via the Canadian Government Open Data Portal (https://doi.org/10.18164/ff771396-b22c-4bc3-844d-38fc697049e9, Mariani et al., 2022a, and https://doi.org/10.18164/d92ed3cf-4ba0-4473-beec-357ec45b0e78, Mariani et al., 2022b); this dataset is being used to improve our understanding of synoptic and fine-scale meteorological processes in the Arctic and sub-Arctic, including HIW detection and prediction and NWP verification, assimilation, and processes.