Evaluation of a Prototype Broadband Water-Vapour Profiling Differential Absorption Lidar at Cardington, UK

Gaffard, C.; Li, Zhihong; Harrison, Dawn; Lehtinen, Raisa; Roininen, Reijo

doi:10.3390/atmos12111521

Cited by 8 publications

(5 citation statements)

References 23 publications

(46 reference statements)

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“…The Raman LiDAR presented comparable results with a slightly higher uncertainty estimated at 9.2%. Using a similar technique, Gaffard et al [49] evaluated a Dial LiDAR and reported an uncertainty between 5% and 10%, suggesting similar performances. When comparing the Meteodrone to the Raman LiDAR, similar results were obtained with an RMS of 9.02%.…”

Section: Wmo Requirementsmentioning

confidence: 96%

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Evaluation of an Automatic Meteorological Drone Based on a 6-Month Measurement Campaign

Hervo,

Romanens,

Martucci

et al. 2023

Atmosphere

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From December 2021 to May 2022, MeteoSwiss and Meteomatics conducted a proof of concept to demonstrate the capability of automatic drones to provide data of sufficient quality and reliability on a routine operational basis. Over 6 months, Meteodrones MM-670 were operated automatically eight times per night at Payerne, Switzerland. In total, 864 meteorological profiles were measured and compared to co-located standard measurements, including radiosoundings and remote sensing instruments. To our knowledge, this is the first time that Meteodrone’s atmospheric profiles have been evaluated in such an extensive campaign. The paper highlights two case studies that showcase the performance and challenges of measuring temperature, humidity, and wind with a Meteodrone. It also focuses on the overall quality of the drone measurements. Throughout the campaign, the availability of Meteodrone measurements was 75.7%, with 82.2% of the flights reaching the nominal altitude of 2000 m above sea level. The quality of the measurements was assessed against the WMO’s (World Meteorological Organization) requirements. The temperature measurements gathered by the Meteodrone met the “breakthrough” target, while the humidity and wind profiles met the “threshold” target for high-resolution numerical weather prediction. The temperature measurement quality was comparable to that of a microwave radiometer, and the humidity quality was similar to that obtained from a Raman LiDAR. However, the wind measurements gathered by a Doppler LiDAR were more accurate than the estimation provided by the Meteodrone. This campaign marks a significant step towards the operational use of automatic drones for meteorological applications.

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Section: Wmo Requirementsmentioning

confidence: 96%

“…These WMO requirements were recently used by Gaffard et al [49] to evaluate novel measurements like a DIAL LiDAR. This study aims to evaluate whether Meteodrones fulfill these requirements.…”

Section: Wmo Requirements and Quality Analysismentioning

confidence: 99%

Evaluation of an Automatic Meteorological Drone Based on a 6-Month Measurement Campaign

Hervo,

Romanens,

Martucci

et al. 2023

Atmosphere

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“…The DIAL underwent initial testing in Helsinki and Toronto before being deployed to Iqaluit (Mariani et al, 2020b). This new system and its predecessor were extensively evaluated in different climates and demonstrated excellent agreement with independent water vapour profile observations from co-located radiosondes, radiometers, UAV's, and Raman lidars (Newsom et al, 2020;Gaffard et al, 2021).…”

Section: Dial and Raman Water Vapour Lidarsmentioning

confidence: 99%

Enhanced automated meteorological observations at the Canadian Arctic weather science (CAWS) supersites

Mariani

Huang²,

Crawford³

et al. 2022

Preprint

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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 are completely automated (no on-site operator) and operate 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, data collection methods, and example case studies of HIW events are discussed. CAWS data are publically 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.

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“…Consequently, we have removed this altitude region from our diurnal analysis. Most recently, Gaffard et al (2021) conducted a 1 month validation of a second preproduction version at the UK Met Office testing site in Cardington. They found biases of similar range and magnitude to the previous studies.…”

Section: Vaisala Differential Absorption Lidarmentioning

confidence: 99%

“…In this study, we address both the need for higher vertical resolution and higher latitude observations of water vapour profiles. In 2018, Environment and Climate Change Canada (ECCC) deployed a preproduction Vaisala lidar (Mariani et al, 2020; Newsom et al, 2020; Gaffard et al, 2021; Mariani et al, 2021) and installed it at the Iqaluit, Nunavut supersite (Joe et al, 2020). The lidar is a differential absorption lidar (DIAL) capable of producing specific humidity profiles from 90 m to 3 km altitude above ground level (depending on the meteorological conditions) at 100–300 m vertical resolution (in the first 1.5 km altitude) at a temporal frequency of 20 min.…”

Section: Introductionmentioning

confidence: 99%

An assessment of Arctic diurnal water‐vapour cycles in Canada's weather forecast model and ERA5

Hicks–Jalali

Mariani

Casati

et al. 2023

Quart J Royal Meteoro Soc

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The diurnal water‐vapour cycle is a critical component of the hydrological cycle, yet it is one of the hardest components to accurately reproduce in forecast and climate models. Previous studies have shown that both forecast and climate models underrepresent the diurnal water‐vapour cycle, which leads to errors in precipitation, cloud, and radiative transfer parameters. Most diurnal cycle studies were conducted in the Tropics, and very few model evaluations of this process exist for the Arctic. Additionally, the majority of studies focus on total column water‐vapour cycles; almost none use height‐resolved measurements. In this study, we evaluate the diurnal water‐vapour cycles in Environment and Climate Change Canada's Global Environmental Multiscale–High Resolution Deterministic Prediction System (GEM–HRDPS) numerical weather forecast model and the European Centre for Medium‐Range Weather Forecasts Reanalysis v5 (ERA5) using a Vaisala preproduction differential absorption lidar (DIAL) and a co‐located Global Positioning System (GPS) located in Iqaluit, Nunavut (63.75° N, 68.55° W). Both numerical products reproduce the phase of the diurnal cycle well below 1 km year‐round. However, ERA5's diurnal amplitudes are significantly smaller than the DIAL and GPS amplitudes. GEM–HRDPS amplitudes are consistently larger in the first few hundred metres but smaller above 1 km; it also underrepresents the amplitude of the total column diurnal cycle. Neither ERA5 nor GEM–HRDPS accurately reproduce the 12‐hr component of the diurnal cycle in either the height‐resolved or total column cycles. The inability to accurately reproduce the 12‐hr component in both numerical products suggests that the representation of some underlying process is incomplete, which can impact the accuracy of precipitation and radiative transfer algorithms. In conclusion, we find that the numerical products are able to reproduce the general behaviour and shape of the cycle but still require improvement at certain altitudes.

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Evaluation of a Prototype Broadband Water-Vapour Profiling Differential Absorption Lidar at Cardington, UK

Cited by 8 publications

References 23 publications

Evaluation of an Automatic Meteorological Drone Based on a 6-Month Measurement Campaign

Evaluation of an Automatic Meteorological Drone Based on a 6-Month Measurement Campaign

Enhanced automated meteorological observations at the Canadian Arctic weather science (CAWS) supersites

An assessment of Arctic diurnal water‐vapour cycles in Canada's weather forecast model and ERA5

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