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At least 37 records · Page 2

Ice processes in Antarctica: identification via multi-wavelength active and passive measurements and model evaluation (Final Report)

This project is based on new multi-frequency radar observations collected during the AWARE field campaign in 2016 at McMurdo Station by the ARM Mobile facility. Three scientific goals have been achieved. We have developed ice and mixed-phase cloud microphysics retrievals from multi-wavelength radar observations and ancillary observations, generally applicable at ARM sites. These technique generally better characterize the size of the ice crystals, their equivalent water content and the degree of riming better than using single wavelength techniques. We have characterized ice microphysical properties and ice processes via multi-frequency signatures. We have identified a unique mode in the McMurdo dataset appearing at quite cold temperature that we have attributed to riming processes. Triple frequency radar measurements unfortunately were available only for a short period but our work lays the foundation for building climatological and testing their replicability in models. Simultaneously case studies from the AWARE campaign have been exploited to evaluate and improve the NASA GISS ModelE3 climate model, including selection of case studies for combined goals of (i) running side-by-side using large-eddy simulation (LES) and ModelE3 in single-column model (SCM) mode and (ii) fingerprinting cloud processes in multi-wavelength radar observations. The different components of this work have contributed to 15 published papers with two currently under review.

54 ENVIRONMENTAL SCIENCES↗

CSAPR2 Optimized Convective Cell Tracking Data during TRACER

One of the challenges in analyzing convective cell properties is to observe the quick evolution of individual convective cells. While the operational radar data provide a volumetric data set to analyze radar observables of convective precipitation clouds, previous studies also suggested the quick evolution of cell life cycle that might not be captured by conventional radar volume scan strategies that take ~5-7 minutes. Aiming at enhancing our understanding of the links between convective cloud kinematic and microphysical processes as well as life cycles, the Tracking Aerosol Convection Interactions ExpeRiment (TRACER; Jensen et al. 2019) was conducted at Houston, Texas, in 2022. The TRACER campaign deployed the 2nd generation C-band Scanning ARM Precipitation Radar (CSAPR2), which performed frequent updates of range height indicator (RHI) and sector plan position indicator (PPI) scans to track individual convective cells every < 2 minutes, guided by a new cell tracking framework, Multisensor Agile Adaptive Sampling (MAAS; Kollias et al. 2020). This allows for capturing fast-evolving radar observables. We provide the processed CSAPR2 cell tracking data in CfRadial format collected during the TRACER field campaign from June to September 2022. The data files include processed radar variables: noise-masked reflectivity and differential reflectivity corrected for rain attenuation and systematic biases, noise-masked dealiased radial velocity, specific differential phase, locations of target cells (latitude, longitude, radar range), and radar-echo classification. Figure 1 provides an example of a 3D image of CSAPR2 reflectivity from the lowest PPI scan and an RHI scan after data processing.

54 ENVIRONMENTAL SCIENCES↗

Improving parameterization of ice microphysical processes in Arctic clouds using a synergistic modeling and observational approach (Final Report)

The primary goals of the project were to: 1) Improve the fundamental quantitative models of ice growth processes using ARM radar observations. 2) Better understand the growth of ice particle populations through vapor deposition, riming, and aggregation in Arctic clouds using a new particle-property microphysical model. 3) Robustly estimate and constrain key unknown model parameters using ARM radar observations combined with the particle-property model to develop an improved parameterization of ice growth processes for traditional bulk parameterizations used in cloud and climate models.

58 GEOSCIENCES↗

CSAPR2 cell-tracking data collected during TRACER

One of the challenges of analyzing convective cell properties is quick evolution of the individual convective cells. While the operational radar data provide great a data set to analyze the evolution of radar observables of convective precipitation clouds statistically, previous studies also suggested that, because of the quick evolution of cell life cycle, conventional radar volume scan strategies taking ~5-7 minutes might not capture the detailed evolution. The TRACER campaign deployed CSAPR2, which performed frequent update of RHI and sector PPI scans to track convective cells every < 2 minutes guided by a new cell-tracking framework, Multisensor Agile Adaptive Sampling (MAAS; Kollias et al. 2020). This allows for capturing fast-evolving radar observables. The submitted data files are CSAPR2 data in CfRadial format collected during the TRACER field campaign from June to September 2020. The data files include processed radar variables including: noise-masked reflectivity and differential reflectivity corrected for rain attenuation and systematic biases, noise-masked dealiased radial velocity, specific differential phase, locations of target cells (latitude, longitude, radar range), and radar-echo classification.

54 ENVIRONMENTAL SCIENCES↗

A radar view of ice microphysics and turbulence in Arctic cloud systems

Ice microphysical processes are inherently complex because of their sensitivity to temperature and humidity, the diversity of ice crystal habits, and their interaction with supercooled liquid water (SCL) and turbulence. Long-term surface-based radar observations have been systematically used to unravel the different processes that affect ice particle growth. In this study, we present a statistical analysis of 6.5 years of Ka-band radar observations in Arctic cloud systems, combined with thermodynamic profiles derived from radiosonde measurements. For the first time, ice particle growth and sublimation – diagnosed from vertical gradients of radar reflectivity and mean Doppler velocity – are systematically mapped across a broad range of temperature and moisture conditions. These vertical gradients correspond closely to saturation levels relative to ice and exhibit a strong temperature dependence in supersaturated regions. Notably, distinct signatures near −15 °C are indicative of dendritic growth. Turbulence, quantified via the eddy dissipation rate (EDR), is most frequently observed in regions containing SCL. The co-occurrence of SCL and elevated turbulence results in significantly enhanced ice particle growth compared to conditions in which either is present alone. This work provides new observational constraints that are critical for improving the representation of ice microphysics in atmospheric models.

54 ENVIRONMENTAL SCIENCES↗

Highly supercooled riming and unusual triple-frequency radar signatures over McMurdo Station, Antarctica

Abstract. Riming of ice crystals by supercooled water droplets is an efficient ice growth process, but its basic properties are still poorly known. While it has been shown to contribute significantly to surface precipitation at mid-latitudes, little is known about its occurrence at high latitudes. In Antarctica, two competing effects can influence the occurrence of riming: (i) the scarcity of supercooled liquid water clouds due to the extremely low tropospheric temperatures and (ii) the low aerosol concentration, which may lead to the formation of fewer and larger supercooled drops potentially resulting in an enhanced riming efficiency. In this work, by exploiting the deployment of an unprecedented number of multiwavelength remote sensing systems (including triple-frequency radar measurements) in West Antarctica, during the Atmospheric Radiation Measurements West Antarctic Radiation Experiment (AWARE) field campaign, we evaluate the riming incidence at McMurdo Station and find that riming occurs at much lower temperatures when compared to previous results in the mid-latitudes. This suggests the possible occurrence of a common atmospheric state over Antarctica that includes a rather stable atmosphere inhibiting turbulent mixing, and a high riming efficiency driven by large cloud droplets. We then focus on a peculiar case study featuring a persistent layer with a particularly pronounced riming signature in triple-frequency radar data but only a relatively modest amount of supercooled liquid water. In-depth analysis of the radar observations suggests that such signatures can only be explained by the combined effects of moderately rimed aggregates or similarly shaped florid polycrystals and a narrow particle size distribution (PSD). Simulations of this case study performed with a one-dimensional bin model indicate that similar triple-frequency radar observations can be reproduced when narrow PSDs are simulated. Such narrow PSDs can in turn be explained by two key factors: (i) the presence of a shallow homogeneous droplet or humidified aerosol freezing layer aloft seeding an underlying supercooled liquid layer, and (ii) the absence of turbulent mixing throughout a stable polar atmosphere that sustains narrow PSDs, as hydrometeors grow from the nucleation region aloft to ice particles of several millimeters in size, by vapor deposition and then riming.

54 ENVIRONMENTAL SCIENCES↗

Tropical Cyclone Wind Shear-Relative Asymmetry in Reanalyses

Abstract While tropical cyclones (TCs) are axisymmetric vortices to the first order, they often exhibit noteworthy structural asymmetries. These often result from environmental vertical wind shear, which tilts the vortex and induces a wavenumber 1 pattern in the circulation and precipitation fields. Reanalyses and climate models have improved in representing the TC structure and climatology, but their relatively coarse resolution and dependence on parameterized physics cast doubt on their ability to capture the asymmetric TC structure. We perform the most comprehensive process-oriented assessment of TC asymmetry to date in reanalyses. Specifically, we analyze the composite shear-relative TC structure in ERA5 and Climate Forecast System Reanalysis (CFSR), which vary in their resolutions, physical parameterization suites, and data assimilation techniques. These structures are compared with aircraft reconnaissance radar observations. In agreement with the observations, the strongest tangential winds are usually found left-of-shear, while inner core rainfall, ascent, vortex tilt, and low-level inflow are favored directly downshear or in the downshear-left quadrant. Outer rainband convection generally peaks in the downshear-right quadrant. Thermodynamic asymmetries are also apparent, with anomalous low-level moisture right-of-shear, midlevel warmth in the upshear-right quadrant (uptilt), and cloud properties suggestive of a realistic precipitation life cycle from growth to fallout. We also decompose rainfall contributions from the convective parameterization and large-scale cloud schemes and highlight the roles of vorticity advection, buoyancy advection, and diabatic processes in driving asymmetric vertical motions in the inner core and outer rainband regions. Our results suggest that process-level studies of TC asymmetry and TC–wind shear interaction under future warming are viable using climate models. Significance Statement Asymmetries are common in tropical cyclones (TCs), influencing their intensity, track, and hazards. Vertical wind shear often plays a leading-order role in causing these asymmetries. It is uncertain how well asymmetric structures and processes are captured in reanalyses and global climate models (GCMs) with grid spacings of 0.25° and coarser. In this study, we first evaluate TC asymmetry in reanalyses, which have the benefit of being forced by observations. This helps to assess whether the resolutions associated with GCMs sufficiently capture asymmetric structures and processes and motivates upcoming work with free-running GCMs to study how TC asymmetry may change in a warming climate.

Carstens, Jacob D.↗

Refractivity Observations from Radar Phase Measurements: The 22 May 2002 Dryline Case during IHOP Project

The dryline, often associated with the development of severe storms in the Southern Great Plains of the United States of America, is a boundary layer phenomenon that occurs when a warm and moist air mass from the Gulf of Mexico meets a hot and dry air mass from the southwest desert area. An accurate knowledge of the water vapor spatio-temporal variability in the lower part of the atmosphere is crucial for a better understanding of the evolution of the dryline. The tropospheric refractivity, directly related to water vapor content, is a proxy for the water vapor content of the troposphere. It has already been demonstrated that the refractivity and the refractivity vertical gradient can be jointly estimated from radar phase measurements. In fact, it has been shown that using kriging interpolation techniques, accurate refractivity maps within the coverage area of the radar can be obtained with high temporal resolution. In this paper, a detailed analysis of the time series of radar-based refractivity maps obtained during a dryline that occurred on the afternoon of 22 May 2002 during the International H 2 O Project is presented. Comparisons between the time series of radar refractivity maps, obtained with the NCAR S-Pol radar, and the refractivity measurements derived from automatic ground-based weather stations and the AERI instrument, placed at different locations within the coverage area of the NCAR S-Pol radar, demonstrate the accuracy of radar refractivity estimates even for highly variable conditions, both in time and space, in the troposphere. Correlation coefficients higher than 0.95 are obtained in all weather station locations. Regarding the RMSE, errors less than 6 N-units are obtained for all cases, being even as low as 2.92 N-units at some locations.

54 ENVIRONMENTAL SCIENCES↗

Giant Cloud Condensation Nuclei Facilitate Drizzle Formation in Stratocumulus—Insights From a Combined Observation‐Modeling Framework

The mechanism for initiating drizzle drop remains a gap in the current understanding of warm rain formation. One prevalent hypothesis suggests that the presence of Giant Cloud Condensation Nuclei (GCCN) generates drizzle‐sized drops necessary to trigger the Collision‐Coalescence (C‐C) process. Here, in this study, this hypothesis is investigated using a novel framework that integrates in situ observations, remote sensing measurements, and idealized models. Results show that GCCN can efficiently generate drizzle drops through condensation, producing a broad Droplet Size Distribution (DSD) comparable to in situ observations. The large drizzle drop and broad DSD strongly facilitate C‐C, further accelerating drizzle initiation. To compare with observation, the model‐generated DSDs are used to generate radar Doppler spectra where radar reflectivity and Doppler skewness is estimated. The simulated radar quantities correspond well with radar observations, providing critical evidence for the GCCN‐induced drizzle initiation mechanism.

54 ENVIRONMENTAL SCIENCES↗

A riming‐dependent parameterization of scattering by snowflakes using the self‐similar Rayleigh–Gans approximation

Abstract Riming is a key process of precipitation formation in ice‐containing clouds, but quantifying riming from observations is challenging, limiting our ability to evaluate the riming process in numerical weather models. One challenge for radar observations is that riming changes both the physical properties (mass, area cross‐section) and scattering properties of ice particles. These changes need to be implemented consistently as a function of riming in radar forward operators, which are required for retrievals and model evaluation in observation space. In this study, mass–size, cross‐section area–size, and backscattering cross‐section relations are developed as a function of the normalized rime mass for aggregates composed of various monomer types (columns, dendrites, needles, plates, and rosettes). The proposed framework allows us to simulate scattering properties of aggregated ice particles consistently as a function of riming in retrievals and radar forward operators. The parameterizations are developed from a large data set of simulated rimed aggregates of different sizes and monomer crystal types. The backscattering cross‐section parameterization (the “riming‐dependent parameterization”) is evaluated for radar frequencies of 35.6 and 94.0 GHz and is based on the Self‐Similar Rayleigh–Gans approximation (SSRGA), which is increasingly used to calculate microwave scattering of ice crystals and snowflakes. Compared with parameterizations from the literature that do not consider riming, the riming‐dependent parameterization leads to significantly smaller biases in terms of backscattering cross‐section. When using the particle masses and scattering properties of the individual particles simulated by the aggregation and riming model as a reference, the bias of our parameterization is below 1 dB when integrating over an exponential particle size distribution with sizes from 0.1–10 mm.

54 ENVIRONMENTAL SCIENCES↗

Investigation of Arctic Cloud Properties and Surface Radiation Based on MOSAiC Shipborne Observations

The Arctic is rapidly changing due to changes of the Earth system. This study investigates cloud fraction, phase partition, cloud type, and their relationships with surface radiation based on yearlong shipborne observations in the Arctic regions. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign provided lidar and radar observations of cloud microphysical properties and surface shortwave (SW) and longwave (LW) radiation. Cloud and radiative properties were examined at daily and monthly resolutions in four seasons. Low clouds were found to be most prevalent throughout the year, followed by deep clouds. The ice phase is the dominant phase except for summer (June–August). Liquid and mixed phases show more significant monthly and annual mean radiative effects in SW and LW than the ice phase. The clouds show net warming effects due to LW heating in most months, while the SW cooling effects of clouds become more dominant for July and August. The cloud and radiation observations from MOSAiC were used to evaluate simulations of the atmospheric component of the Energy Exascale Earth System Model version 2. The simulations show large overestimations of the liquid and mixed phases in the Arctic regions from February to September. The simulations also underestimate the percentages of low clouds and overestimate the percentages of deep clouds throughout the year. Altogether, this work provides a unique analysis of cloud and radiation properties based on high-resolution shipborne observations, which can be used to assist future model evaluation and development.

58 GEOSCIENCES↗