DIAL and GNSS observations of the diurnal water‐vapour cycle above Iqaluit, Nunavut

Quart J Royal Meteoro Soc

Casati

et al. 2023

Self Cite

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.

Section: Data and Data Processingmentioning

confidence: 95%

“…(2014), and Hicks‐Jalali et al . (2021). Hence, in this study we use the first method and follow the least‐squares fitting procedure as in Dai et al .…”

Section: The Diurnal Cyclementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Hicks–Jalali

Quart J Royal Meteoro Soc

Casati

et al. 2023

Self Cite

“…Estimates of the uncertainty in the water vapour profile and maximum effective range are provided by the DIAL's quality control algorithm (Newsom et al, 2020). The DIAL's unique 24 h continuous water vapour observations enable detailed model inter-comparison studies and measurements of height-resolved diurnal water vapour cycles (Hicks-Jalali et al, 2021). The DIAL stopped collecting observations on 20 June 2020 in order to perform repairs; it will be redeployed to the Toronto area.…”

Section: Differential Absorption Lidar (Dial) and Raman Water Vapour ...mentioning

confidence: 99%

Enhanced automated meteorological observations at the Canadian Arctic Weather Science (CAWS) supersites

Huang²,

Crawford³

et al. 2022

Earth Syst. Sci. Data

Self Cite

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.

“…Estimates of the uncertainty in the water vapor profile and maximum effective range are provided by the DIAL's quality control algorithm (Newsom et al, 2020). The DIAL's unique 24 hr continuous water vapour observations enable detailed model inter-comparison studies and measurements of height-resolved diurnal water vapour cycles (Hicks-Jalali et al, 2021).…”

Section: Dial and Raman Water Vapour Lidarsmentioning

confidence: 99%

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

Huang²,

Crawford³

et al. 2022

Preprint

Self Cite

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.