Zen Mariani

The planetary boundary layer height (PBLh) is a key parameter in atmospheric modeling and observational applications, but is inconsistently defined in the literature and lacks a large, global ensemble of observations. Doppler lidar observational datasets, with high temporal resolution and deployability, provide an opportunity for long-term, high vertical and temporal resolution PBLh estimates to improve our understanding of atmospheric mixing. Using data collected by the Southern Ontario LIDar (SOLID) Mesonet, a network of Doppler lidar sites spanning 500 km across Southern Ontario, Canada, we present three methods for estimating the PBLh from Doppler lidar vertical wind speed and aerosol backscatter observations. We perform comparisons with PBLh estimates from the Global Environment Multiscale (GEM) model, the ECMWF Reanalysis 5 (ERA5), and nearby radiosonde flights at the Buffalo International Airport, New York, USA. We identify the vertical wind variance threshold method to be the estimate with the highest consistency with expected PBLh values and variation, comparisons to numerical and radiosonde measurement-derived estimates, and least sensitivity to noise in observations. However, each of the methods presented here show a general consistency with theoretical expectations and comparisons in appropriate conditions, affirming the validity of Doppler lidar-derived PBLh estimates in Southern Ontario.

We present a first-principles density-matrix simulation of blackbody-radiation (BBR)–induced decoherence in cesium Rydberg electromagnetically induced transparency (EIT). The model incorporates spontaneous emission, blackbody-stimulated transitions, collisional broadening, transit-time–limited decoherence, and Doppler averaging across a truncated but converged Rydberg manifold within a Lindblad master-equation framework. From the steady-state solution, we extract both the temperature-dependent Rydberg coherence decay rate and the corresponding probe absorption coefficient. We show that the experimentally observed modification of probe transmission reported by Kaur et al (2026) arises predominantly from BBR-induced decoherence of the Rydberg coherence, rather than from population redistribution among Rydberg levels. The model reproduces the observed temperature-dependent trends in probe absorption with quantitative accuracy. By employing a fully m j -resolved transition network, we establish a direct connection between microscopic decoherence processes and macroscopic optical observables. The decoherence effect on the optical response is sufficiently well-defined to serve as a measurable signal, enabling potential applications in Rydberg-based thermometry and radiometry. These results provide a self-consistent microscopic description of BBR-limited performance in thermal-vapor Rydberg EIT and establish a quantitative link between Rydberg-state decoherence and measurable changes in optical susceptibility, with direct relevance to radio-frequency-based sensing platforms.

The EarthCARE Commissioning Calibration and Validation Campaign in Ottawa (ECALOT) was a dedicated airborne and surface-based campaign designed to support the calibration and validation of Level 1 and Level 2 products from the EarthCARE satellite mission. The campaign was conducted between October 2024 and March 2025 in eastern Canada, primarily in the regions surrounding Ottawa and Montreal. Airborne observations were carried out using the National Research Council Canada (NRC) Convair-580 research aircraft, equipped with remote sensing instruments analogous to those flown on EarthCARE, including a nadir/zenith/side-looking 94 GHz cloud radar system with Doppler capability and zenith/nadir-pointing 355 nm elastic lidars, together with a comprehensive suite of in situ cloud and aerosol probes. Complementary surface-based observations were obtained at a primary site at the Ottawa Macdonald-Cartier International Airport and two additional climate sentinel stations in the Montreal region, providing continuous ground-based reference measurements of surface radiation, atmospheric thermodynamic profiles, precipitation, and other meteorological variables. A total of seven research flights were conducted, sampling a range of mid-latitude continental cloud conditions, including stratocumulus, multilayer cloud systems, and nimbostratus associated with liquid- or solid-phase precipitation. The ECALOT sampling strategy was designed to integrate airborne and surface-based in situ and remote-sensing observations collected along and offset from EarthCARE’s ground track, while accounting for temporal offsets relative to the satellite overpass. Together, the ECALOT campaign provides coordinated multi-platform observations that enable evaluation of active sensor measurements, radar-lidar-imager synergy, representation of liquid, ice and mixed-phase clouds, three-dimensional scene construction, and radiative closure across EarthCARE’s data processing chain, while also providing observational constraints for improving the representation of mixed-phase clouds and their radiative effects in numerical models.

The EarthCARE Commissioning Calibration and Validation Campaign in Ottawa (ECALOT) was a dedicated airborne and surface-based campaign designed to support the calibration and validation of Level 1 and Level 2 products from the EarthCARE satellite mission. The campaign was conducted between October 2024 and March 2025 in eastern Canada, primarily in the regions surrounding Ottawa and Montreal. Airborne observations were carried out using the National Research Council Canada (NRC) Convair-580 research aircraft, equipped with remote sensing instruments analogous to those flown on EarthCARE, including a nadir/zenith/side-looking 94 GHz cloud radar system with Doppler capability and zenith/nadir-pointing 355 nm elastic lidars, together with a comprehensive suite of in situ cloud and aerosol probes. Complementary surface-based observations were obtained at a primary site at the Ottawa Macdonald-Cartier International Airport and two additional climate sentinel stations in the Montreal region, providing continuous ground-based reference measurements of surface radiation, atmospheric thermodynamic profiles, precipitation, and other meteorological variables. A total of seven research flights were conducted, sampling a range of mid-latitude continental cloud conditions, including stratocumulus, multilayer cloud systems, and nimbostratus associated with liquid- or solid-phase precipitation. The ECALOT sampling strategy was designed to integrate airborne and surface-based in situ and remote-sensing observations collected along and offset from EarthCARE’s ground track, while accounting for temporal offsets relative to the satellite overpass. Together, the ECALOT campaign provides coordinated multi-platform observations that enable evaluation of active sensor measurements, radar-lidar-imager synergy, representation of liquid, ice and mixed-phase clouds, three-dimensional scene construction, and radiative closure across EarthCARE’s data processing chain, while also providing observational constraints for improving the representation of mixed-phase clouds and their radiative effects in numerical models.

This study presents the implementation of prognostic aerosols within the Predicted Particle Properties (P3) microphysics scheme to improve the physical consistency of aerosol–cloud–precipitation interactions. Two new prognostic number mixing ratios representing "water-friendly" (CCN) and "ice-friendly" (INP) aerosols are added. Aerosols then evolve dynamically and interact with hydrometeors via nucleation, scavenging, evaporation, and sublimation. The impacts of the modified scheme are investigated using convection-permitting (1-km horizontal grid spacing) simulations of an Arctic mixed-phase cloud case observed on 19–20 January 2026 near Inuvik, Canada. Simulations are compared against "in situ" observations, ground-based radar measurements, and retrievals from the EarthCARE satellite. Results show that the inclusion of prognostic aerosols significantly affects cloud microphysical properties and phase partitioning. The prognostic aerosol simulation produces systematically fewer but larger ice particles, leading to increased reflectivity and enhanced riming. It also results in higher liquid water content and lower ice water content compared to the simulation without prognostic aerosols, thereby favoring the persistence of supercooled liquid layers and improving agreement with retrievals. Sensitivity experiments demonstrate that the choice of ice nucleation parameterization plays a dominant role in controlling the cloud phase. Aerosol-dependent formulations produce lower ice crystal concentrations and more persistent liquid water than the original temperature-dependent scheme, thereby enhancing mixed-phase cloud occurrence. The new prognostic aerosol framework improves the representation of aerosol-cloud indirect effects in P3 and provides a pathway toward more accurate simulations of clouds and precipitation, which are critical for radiative balance and weather prediction in polar regions and elsewhere.

The EarthCARE Commissioning Calibration and Validation Campaign in Ottawa (ECALOT) was a dedicated airborne and surface-based campaign designed to support the calibration and validation of Level 1 and Level 2 products from the EarthCARE satellite mission. The campaign was conducted between October 2024 and March 2025 in eastern Canada, primarily in the regions surrounding Ottawa and Montreal. Airborne observations were carried out using the National Research Council Canada (NRC) Convair-580 research aircraft, equipped with remote sensing instruments analogous to those flown on EarthCARE, including a nadir/zenith/side-looking 94 GHz cloud radar system with Doppler capability and zenith/nadir-pointing 355 nm elastic lidars, together with a comprehensive suite of in situ cloud and aerosol probes. Complementary surface-based observations were obtained at a primary site at the Ottawa Macdonald-Cartier International Airport and two additional climate sentinel stations in the Montreal region, providing continuous ground-based reference measurements of surface radiation, atmospheric thermodynamic profiles, precipitation, and other meteorological variables. A total of seven research flights were conducted, sampling a range of mid-latitude continental cloud conditions, including stratocumulus, multilayer cloud systems, and nimbostratus associated with liquid- or solid-phase precipitation. The ECALOT sampling strategy was designed to integrate airborne and surface-based in situ and remote-sensing observations collected along and offset from EarthCARE’s ground track, while accounting for temporal offsets relative to the satellite overpass. Together, the ECALOT campaign provides coordinated multi-platform observations that enable evaluation of active sensor measurements, radar-lidar-imager synergy, representation of liquid, ice and mixed-phase clouds, three-dimensional scene construction, and radiative closure across EarthCARE’s data processing chain, while also providing observational constraints for improving the representation of mixed-phase clouds and their radiative effects in numerical models.

This study presents the implementation of prognostic aerosols within the Predicted Particle Properties (P3) microphysics scheme to improve the physical consistency of aerosol–cloud–precipitation interactions. Two new prognostic number mixing ratios representing "water-friendly" (CCN) and "ice-friendly" (INP) aerosols are added. Aerosols then evolve dynamically and interact with hydrometeors via nucleation, scavenging, evaporation, and sublimation. The impacts of the modified scheme are investigated using convection-permitting (1-km horizontal grid spacing) simulations of an Arctic mixed-phase cloud case observed on 19–20 January 2026 near Inuvik, Canada. Simulations are compared against "in situ" observations, ground-based radar measurements, and retrievals from the EarthCARE satellite. Results show that the inclusion of prognostic aerosols significantly affects cloud microphysical properties and phase partitioning. The prognostic aerosol simulation produces systematically fewer but larger ice particles, leading to increased reflectivity and enhanced riming. It also results in higher liquid water content and lower ice water content compared to the simulation without prognostic aerosols, thereby favoring the persistence of supercooled liquid layers and improving agreement with retrievals. Sensitivity experiments demonstrate that the choice of ice nucleation parameterization plays a dominant role in controlling the cloud phase. Aerosol-dependent formulations produce lower ice crystal concentrations and more persistent liquid water than the original temperature-dependent scheme, thereby enhancing mixed-phase cloud occurrence. The new prognostic aerosol framework improves the representation of aerosol-cloud indirect effects in P3 and provides a pathway toward more accurate simulations of clouds and precipitation, which are critical for radiative balance and weather prediction in polar regions and elsewhere.

This study presents the implementation of prognostic aerosols within the Predicted Particle Properties (P3) microphysics scheme to improve the physical consistency of aerosol–cloud–precipitation interactions. Two new prognostic number mixing ratios representing "water-friendly" (CCN) and "ice-friendly" (INP) aerosols are added. Aerosols then evolve dynamically and interact with hydrometeors via nucleation, scavenging, evaporation, and sublimation. The impacts of the modified scheme are investigated using convection-permitting (1-km horizontal grid spacing) simulations of an Arctic mixed-phase cloud case observed on 19–20 January 2026 near Inuvik, Canada. Simulations are compared against "in situ" observations, ground-based radar measurements, and retrievals from the EarthCARE satellite. Results show that the inclusion of prognostic aerosols significantly affects cloud microphysical properties and phase partitioning. The prognostic aerosol simulation produces systematically fewer but larger ice particles, leading to increased reflectivity and enhanced riming. It also results in higher liquid water content and lower ice water content compared to the simulation without prognostic aerosols, thereby favoring the persistence of supercooled liquid layers and improving agreement with retrievals. Sensitivity experiments demonstrate that the choice of ice nucleation parameterization plays a dominant role in controlling the cloud phase. Aerosol-dependent formulations produce lower ice crystal concentrations and more persistent liquid water than the original temperature-dependent scheme, thereby enhancing mixed-phase cloud occurrence. The new prognostic aerosol framework improves the representation of aerosol-cloud indirect effects in P3 and provides a pathway toward more accurate simulations of clouds and precipitation, which are critical for radiative balance and weather prediction in polar regions and elsewhere.

Enhanced measurements of vertically resolved meteorological parameters are required to improve nowcasting of high-impact weather (HIW) and to evaluate and enhance the performance of numerical weather prediction (NWP) systems. This is particularly true in urban areas where there exists a lack of upper-air observations. To address this need, Environment and Climate Change Canada (ECCC) established the Southern Ontario Lidar (SOLID) mesoscale network (Mesonet) in and around Toronto. Eight Doppler lidars and one water vapor differential absorption lidar (DIAL) provide near-real-time observations of aerosol backscatter, cloud and planetary boundary layer (PBL) height, and vertical wind and water vapor profiles to aviation and operational weather forecasters. Combined with the neighboring New York State Mesonet, the two Mesonets provide some of the only upper-air observations in this urban area inhabited by more than 26 million people. As part of an ongoing impact analysis, this project will assess the potential of these profiling instruments to improve nowcasting operations and data assimilation efforts. Three case studies demonstrate the applications of the Mesonet’s observations, particularly for aviation nowcasting and HIW events, including passing cold fronts that result in sudden and extreme wind shifts (∼180° within 10 min) and the Delta flight 4819 plane crash investigation at Toronto’s international airport. Such real-time profiling of upper-air winds and water vapor are shown to aid forecasters and improve their ability to make storm-track adjustments with confidence, provide near-real-time analysis for automated nowcasting systems, and enable in-depth verification of NWP forecasts. Significance Statement: Providing near-real-time observations of vertical wind profiles in an urban environment is crucial to improve nowcasting, particularly during high-impact weather (HIW). The Southern Ontario Lidar (SOLID) mesoscale network (Mesonet) provides such observations at eight sites, covering several cities in Canada including London, Toronto, and Ottawa, Ontario. Combined with the neighboring New York State Mesonet, this is one of the only sources of upper-air wind observations for a region inhabited by over 26 million people. Case studies of the impact of SOLID measurements are shown for HIW events (passing cold fronts) and for the Delta flight 4819 plane crash at the Toronto airport. SOLID is shown to have a positive impact on nowcasting and aviation operations, a forecaster’s situational awareness, and for verification of weather models.

Planetary boundary layer height (PBLh), despite being key to atmospheric modelling parametrizations, remains difficult to consistently define, model, and observe. The Southern Ontario Lidar (SOLID) Mesonet, established by Environment and Climate Change Canada (ECCC) in and around Toronto beginning in 2022, provides an opportunity for high spatial and temporal resolution estimates of the PBLh in diverse atmospheric conditions. We present a Doppler lidar-derived PBLh data product using SOLID Mesonet observations, assessed in comparison to PBLh estimates from ECCC’s Global Environmental Multiscale (GEM) model, ERA5, and nearby radiosonde flights in Buffalo, NY. These comparisons highlight the uncertainties between various methods for PBLh estimation, particularly in stable atmospheric conditions such as overnight and in winter months, and give key insights into the accuracy of PBLh estimates for usage in atmospheric modelling as well as avenues for improvements.