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At least 109 records · Page 6

Optical Extinction Measurements of Laser Side-Scatter During Tropical Storm Colin

A side-scatter imaging (SSI) technique using a 447 nm, 500 mW laser and a Nikon D80 camera was tested at Kennedy Space Center, Florida during the passing of a rain band associated with Tropical Storm Colin. The June 6, 2016, 22:00 GMT rain event was intense but short-lived owing to the strong west-to-east advection of the rain band. An effort to validate the optical extinction measurement was conducted by setting up a line of three tipping rain gauges along an 80 m east-west path and below the laser beam. Differences between tipping bucket measurements were correlated to the extinction coefficient profile along the lasers path, as determined by the SSI measurement. In order to compare the tipping bucket to the optical extinction data, a Marshall-Palmer DSD model was assumed. Since this was a daytime event, the laser beam was difficult to detect in the camera images, pointing out an important limitation of SSI measurements: the practical limit of DSD density that can be effectively detected and analyzed under daylight conditions using this laser and camera, corresponds to a fairly moderate rainfall rate on the order of 20 mmh (night measurements achieve a much improved sensitivity). The SSI analysis model under test produced promising results, but in order to use the SSI method for routine meteorological studies, improvements to the math model will be required.

optical extinction↗

Impact of Scattering Model on Disdrometer Derived Attenuation Scaling

NASA Glenn Research Center (GRC), the Air Force Research Laboratory (AFRL), and the Politecnico di Milano (POLIMI) are currently entering the third year of a joint propagation study in Milan, Italy utilizing the 20 and 40 GHz beacons of the Alphasat TDP5 Aldo Paraboni scientific payload. The Ka- and Q-band beacon receivers were installed at the POLIMI campus in June of 2014 and provide direct measurements of signal attenuation at each frequency. Collocated weather instrumentation provides concurrent measurement of atmospheric conditions at the receiver; included among these weather instruments is a Thies Clima Laser Precipitation Monitor (optical disdrometer) which records droplet size distributions (DSD) and droplet velocity distributions (DVD) during precipitation events. This information can be used to derive the specific attenuation at frequencies of interest and thereby scale measured attenuation data from one frequency to another. Given the ability to both predict the 40 GHz attenuation from the disdrometer and the 20 GHz timeseries as well as to directly measure the 40 GHz attenuation with the beacon receiver, the Milan terminal is uniquely able to assess these scaling techniques and refine the methods used to infer attenuation from disdrometer data.In order to derive specific attenuation from the DSD, the forward scattering coefficient must be computed. In previous work, this has been done using the Mie scattering model, however, this assumes a spherical droplet shape. The primary goal of this analysis is to assess the impact of the scattering model and droplet shape on disdrometer derived attenuation predictions by comparing the use of the Mie scattering model to the use of the T-matrix method, which does not assume a spherical droplet. In particular, this paper will investigate the impact of these two scattering approaches on the error of the resulting predictions as well as on the relationship between prediction error and rain rate.

statistics↗

Comparison of Raindrop Size Distribution between NASA’s S-Band Polarimetric Radar and Two-Dimensional Video Disdrometers

The ground-based-radar-derived raindrop size distribution (DSD) parameters—mass-weighted drop diameter Dmass and normalized intercept parameter NW—are the sole resource for direct validation of the National Aeronautics and Space Administration (NASA) Global Precipitation Measurement (GPM) mission Core Observatory satellite-based retrieved DSD. Both Dmass and NW are obtained from radar-measured reflectivity ZH and differential reflectivity ZDR through empirical relationships. This study uses existing relationships that were determined for the GPM ground validation (GV) program and directly compares the NASA S-band polarimetric radar (NPOL) observables of ZH and ZDR and derivedDmass and NW with those calculated by two-dimensional video disdrometer (2DVD). The joint NPOL and 2DVD datasets were acquired during three GPM GV field campaigns conducted in eastern Iowa, southern Appalachia, and western Washington State. The comparative study quantifies the level of agreement for ZH, ZDR, Dmass, and log(NW) at an optimum distance (15–40 km) from the radar as well as at distances greater than 60 km from radar and over mountainous terrain. Interestingly, roughly 10%–15% of the NPOL ZH–ZDR pairs were well outside the envelope of 2DVD-estimated ZH–ZDR pairs. The exclusion of these pairs improved the comparisons noticeably.

Ali Tokay↗

Development and Evaluation of the Raindrop Size Distribution Parameters for the NASA Global Precipitation Measurement Mission Ground Validation Program

The National Aeronautics and Space Administration Global Precipitation Measurement (GPM) mission ground validation program uses dual-polarization radar moments to estimate raindrop size distribution (DSD) parameters, the mass-weighted mean drop diameter Dmass, and normalized intercept parameter NW, to validate the GPM Core Observatory–derived DSD parameters. The disdrometer-based Dmass and NW are derived through empirical relationships between Dmass and differential reflectivity ZDR, and between NW, reflectivity ZH, and Dmass. This study employs large datasets collected from two-dimensional video disdrometers (2DVD) during six different field studies to derive the requisite empirical relationships. The uncertainty of the derived Dmass(ZDR) relationship is evaluated through comparisons of 2DVD-calculated and ZDR-estimated Dmass, where ZDR is calculated directly from 2DVD observations. Similarly, the uncertainty of the NW(ZH, Dmass) relationship is evaluated through 2DVD-calculated and Dmass and ZH-estimated NW, where Dmass and ZH are directly calculated from 2DVD observations. This study also presents the sensitivity of Dmass(ZDR) relationships to climate regime and to disdrometer type after developing three additional Dmass(ZDR) relationships from second-generation Particle Size Velocity (PARSIVEL2) disdrometer (P2) observations collected in the Pacific Northwest, in Iowa, and at Kwajalein Atoll in the tropical Pacific Ocean. The application of P2-derived Dmass(ZDR) relationship based on precipitation in the northwestern United States to P2 observations collected over the tropical ocean resulted in the highest error among comparisons of the three datasets.

Ali Tokay↗

Comparison of Raindrop Size Distribution between NASA's S-Band Polarimetric Radar and Two-Dimensional Video Disdrometers

The ground-based-radar-derived raindrop size distribution (DSD) parameters—mass-weighted drop diameter D mass and normalized intercept parameter NW—are the sole resource for direct validation of the National Aeronautics and Space Administration (NASA) Global Precipitation Measurement (GPM ) mission Core Observatory satellite-based retrieved DSD. Both D mass and NW are obtained from radar-measured reflectivity Z Hand differential reflectivity ZDR through empirical relationships. This study uses existing relationships that were determined for the GPM ground validation (GV) program and directly compares the NASA S-band polarimetric radar (NPOL) observables of Z Hand Z DR and derived D mass and NW with those calculated by two-dimensional video disdrometer (2DVD). The joint NPOL and 2DVD datasets were acquired during three GPM GV field campaigns conducted in eastern Iowa, southern Appalachia, and western Washington State. The comparative study quantifies the level of agreement for ZH, ZDR, D mass, and log (NW) at an optimum distance (15–40 km) from the radar as well as at distances greater than 60 km from radar and over mountainous terrain. Interestingly, roughly 10%–15% of the NPOLZH–Z DR pairs were well outside the envelope of 2DVD-estimatedZH–Z DR pairs. The exclusion of these pairs improved the comparisons noticeably.

Ali Tokay↗

Drop Size Distribution Measurements in Outer Rainbands of Hurricane Dorian at the NASA Wallops Precipitation-Research Facility

Hurricane rainbands are very efficient rain producers, but details on drop size distributions are still lacking. This study focuses on the rainbands of hurricane Dorian as they traversed the densely instrumented NASA precipitation-research facility at Wallops Island, VA, over a period of 8 h. Drop size distribution (DSD) was measured using a high-resolution meteorological particle spectrometer (MPS) and 2D video disdrometer, both located inside a double-fence wind shield. The shape of the DSD was examined using double-moment normalization, and compared with similar shapes from semiarid and subtropical sites. Dorian rainbands had a superexponential shape at small normalized diameter values similar to those of the other sites. NASA’s S-band polarimetric radar performed range height-indicator (RHI) scans over the disdrometer site, showing some remarkable signatures in the melting layer (bright-band reflectivity peaks of 55 dBZ, a dip in the copolar correlation to 0.85 indicative of 12–15 mm wet snow, and a staggering reflectivity gradient above the 0 °C level of −10 dB/km, indicative of heavy aggregation). In the rain layer at heights < 2.5 km, polarimetric signatures indicated drop break-up as the dominant process, but drops as large as 5 mm were detected during the intense bright-band period.

Merhala Thurai↗

A Possible Explanation for the Z-R Parameter Inconsistency when Comparing Stratiform and Convective Rainfall

The well-known Z-R power law Z A R(sup b) uses two parameters, A and b, in order to relate rainfall rate R to measured weather radar reflectivity Z. A common method used by researchers is to compute Z and R from disdrometer data and then extract the A-b parameter pair from a log-linear line fit to a scatter plot of Z-R pairs. Even though it may seem far more truthful to extract the parameter pair from a fit of radar Z(sub R) versus gauge rainfall rate R(sub G), the extreme difference in spatial and temporal sampling volumes between radar and rain gauge creates a slew of problems that can generally only be solved by using rain gauge arrays and long sampling averages. Disdrometer derived A-b parameters are easily obtained and can provide information for the study of stratiform versus convective rainfall. However, an inconsistency appears when comparing averaged A-b pairs from various researchers. Values of b range from 1.26 to 1.51 for both stratiform and convective events. Paradoxically the values of A fall into three groups: 150 to 200 for convective; 200 to 400 for stratiform; and 400 to 500 again for convective. This apparent inconsistency can be explained by computing the A-b pair using the gamma DSD coupled with a modified drop terminal velocity model, v(D) alpha D(sup beta) - w, where w is a somewhat artificial constant vertical velocity of the air above the disdrometer. This model predicts three regions of A, corresponding to w less than 0, w = 0, and w greater than 0, which approximately matches observed data.

gamma DSD↗

A New Parametrization of the Rain Drop Size Distribution

This paper revisits the problem of finding a parametric form for the rain drop size distribution (DSD) which 1) is an appropriate model for tropical rainfall, and 2) involves statistically independent parameters. Using TOGA/COARE data, we derive a parametrization which meets these criteria. This new parametrization is an improvement on the one that was derived in [3] using TRMM ground truth data from Darwin, Australia. The new COARE data allows us to verify that the spatial variability fo the two

rain↗

Pathway for decarbonizing residential building operations in the US and China beyond the mid-century

With global carbon budget targets looming, residential buildings in top economies must become carbon neutral as soon as possible to reserve more emission space for emerging carbon-emitting economies. This study is the first to compare the operational decarbonization process of China’s and the United States (US) residential buildings from 2000 to 2060 by combining the end-use emission model with the decomposing structural decomposition (DSD) method and Monte Carlo simulation. The results show that from 2001 to 2020 China decarbonized 1544 mega-tons of carbon dioxide (MtCO 2 ) and the US decarbonized 1848 MtCO 2 . In the business-as-usual scenario, China will hit its emission peak in 2031 (±3) with 934 (±61) MtCO 2 , while the US will maintain a lock-in level of 736 (±133) MtCO 2 since the 2030s. In the decarbonization scenario, operational carbon neutrality for residential buildings in 2060 is promoted by an increase in clean power generation proportion, building-integrated power generation level, building electrification level, and a reduction in end-use energy intensity, which will contribute 34.4 %, 21.4 %, 14.3 %, and 29.9 % in China and 32.9 %, 33.1 %, 8.2 %, and 25.8 % in the US, respectively. Especially, building-integrated power generation in China only costs about 40 % of what it costs in the US. Besides, high-decarbonization strategies for residential building operations are proposed as references for governments to formulate targeted climate policies. Overall, this study offers data benchmarks for buildings’ carbon neutrality of top economies to further promote synergistic carbon neutrality with the buildings of emerging economies in the age of Post COP27.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Density Functionals for Hydrogen Storage: Defining the H2Bind275 Test Set with Ab Initio Benchmarks and Assessment of 55 Functionals

Efficient and high-capacity storage materials are indispensable for a hydrogen-based economy. In silico tools can accelerate the process of discovery of new adsorbent materials with optimal hydrogen adsorption enthalpies. Density functional theory is well-poised to become a very useful tool for enabling high-throughput screening of potential materials. In this work, we have identified density functional approximations that provide good performance for hydrogen binding applications following a two-pronged approach. First, we have compiled a data set (H2Bind275) that comprehensively represents the hydrogen binding problem capturing the chemical and mechanistic diversity in the binding sites encountered in hydrogen storage materials. We have also computed reference interaction energies for this data set using coupled-cluster theory. Second, we have assessed the performance of 55 density functional approximations for predicting H 2 interaction energies and have identified two hybrid density functionals (ωB97X-V and ωB97M-V), two double hybrid density functionals (DSD-PBEPBE-D3(BJ) and PBE0-DH), and one semilocal density functional (B97M-V) as the best performing ones. We have recommended the addition of empirical dispersion corrections to systematically underbinding density functionals such as revPBE, BLYP, and B3LYP for improvements in performance at negligible additional cost. We have also recommended the usage of the def2-TZVPP basis set as it represents a good compromise between accuracy and cost, limiting the finite basis set errors to less than 1 kJ/mol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assessment of Performance of Density Functionals for Predicting Potential Energy Curves in Hydrogen Storage Applications

We report the availability of accurate computational tools for modeling and simulation is vital to accelerate the discovery of materials capable of storing hydrogen (H 2 ) under given parameters of pressure swing and temperature. Previously, we compiled the H2Bind275 data set consisting of equilibrium geometries and assessed the performance of 55 density functionals over this data set (Veccham, S. P.; Head-Gordon, M. J. Chem. Theory Comput. 2020, 16, 4963-4982). As it is crucial for computational tools to accurately model the entire potential energy curve (PEC), in addition to the equilibrium geometry, we extended this data set with 389 new data points to include two compressed and three elongated geometries along 78 PECs for H 2 binding, forming the H2Bind78 × 7 data set. By assessing the performance of 55 density functionals on this significantly larger and more comprehensive H2Bind78 × 7 data set, we identified the best performing density functionals for H 2 binding applications: PBE0-DH, ωB97X-V, ωB97M-V, and DSD-PBEPBE-D3(BJ). The addition of Hartree-Fock exchange improves the performance of density functionals, albeit not uniformly throughout the PEC. We recommend the usage of ωB97X-V and ωB97M-V density functionals as they offer good performance for both geometries and energies. In addition, we also identified B97M-V and B97M-rV as the best semilocal density functionals for predicting H 2 binding energy at its equilibrium geometry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Observed and Simulated Variability of Droplet Spectral Dispersion in Convective Clouds Over the Amazon

Abstract In this study, the variability of the spectral dispersion of droplet size distributions (DSDs) in convective clouds is investigated. Analyses are based on aircraft measurements of growing cumuli near the Amazon basin, and on numerical simulations of an idealized ice‐free cumulus. In cleaner clouds, the relative dispersion , defined as the ratio of the standard deviation to the mean value of the droplet diameter, is negatively correlated with the ratio of the cloud water content ( ) to the adiabatic liquid water content ( ), while no strong correlation between and is seen in polluted clouds. Bin microphysics numerical simulations suggest that these contrasting behaviors are associated with the effect of collision‐coalescence in cleaner clouds, and secondary droplet activation in polluted clouds, in addition to the turbulent mixing of parcels that experienced different paths within the cloud. Collision‐coalescence simultaneously broadens the DSDs and decreases , explaining the inverse relationship between and in cleaner clouds. Secondary droplet activation broadens the DSDs but has little direct impact on . The combination of a rather modest DSD broadening due to weak collision‐coalescence with enhanced droplet activation in both diluted and highly undiluted cloud regions may contribute to maintain a relatively uniform within polluted clouds. These findings can be useful for parameterizing the shape parameter ( ) of gamma DSDs in bulk microphysics cloud‐resolving models. It is shown that emulating the observed relationship improves the estimation of the collision‐coalescence rate in bulk microphysics simulations compared to the bin simulations.

54 ENVIRONMENTAL SCIENCES↗

A Statistical Framework for Evaluating Rain Microphysics in Model Simulations and Disdrometer Observations

Abstract Statistical analyses of a large disdrometer data set and a diverse set of model simulations for convection using the Regional Atmospheric Modeling System were conducted, with the mutual goal of providing insights into precipitation formation and microphysical processes. We demonstrate that a two‐moment bulk microphysical model successfully captures the dominant observed modes of variability in rainfall related to rainfall intensity and raindrop size distributions. The model reproduced the general distribution of observed precipitation groups (PGs) derived from Principal Component Analysis. The multi‐variable analysis also uncovered some shortcomings in the model as well as limitations of the disdrometer data. The model solutions were constrained in their predicted drop size distributions (DSDs) due to the fixed DSD parameters assumed in a two‐moment microphysics scheme. A case study from the Mid‐latitude Continental Clouds and Convection Experiment field project demonstrated how model results can be used to contextualize the disdrometer observations which are limited in sample size, spatial coherence, and detection of small drops and low drop concentrations. The case study also showed that the spatial patterns of the statistically derived PGs revealed by the model are consistent with the hypothesized microphysical processes that determine surface rain DSDs. This work demonstrates how leveraging the strengths of observations and models together can improve our understanding and representation of rain microphysical processes.

54 ENVIRONMENTAL SCIENCES↗

THz Radar Observations of Hydrometeors in a Spray Chamber

Abstract A THz radar, with its wide bandwidth, is capable of high‐resolution imaging down to the centimeter scale. In this study, a THz radar is applied to detect hydrometeors generated in a spray chamber. The observed backscattering signals show fluctuations at centimeter scales, indicating various hydrometeor distribution patterns along the radar beam. A co‐located High‐Speed Imaging (HSI) sensor is used to measure the Drop Size Distributions (DSD) in the spray chamber. The radar sampling beam is well aligned with the HSI probes, allowing an objective comparison between the remote sensing and in situ observations. In this study, the observed radar power is compared with the power estimated from the HSI measurements. Results show great consistency, with power difference smaller than 0.5 dB. This study demonstrates the feasibility and great potential of using a THz radar for ultra‐high‐resolution observations of clouds in a laboratory facility, and in the real atmosphere.

54 ENVIRONMENTAL SCIENCES↗

Impacts of Bulk Microphysics Scheme Structural Choices on Simulations of Rain Initiation Through Drop Coalescence

This study examines how different structural choices in bulk microphysics schemes impact the simulation of warm rain initiation. A single liquid category (SLC) approach prognosing up to four moments of a single drop size distribution (DSD) is compared to the traditional two-category, two-moment approach with separate DSDs for cloud and rain (four total prognostic variables). Different methods for calculating tendencies of the prognostic variables from drop collision-coalescence are also tested: a discretized numerical-integration approach, machine learning via neural networks, lookup tables, and traditional power law fits. Relative to simulations using a bin microphysics model, SLC gives smaller error overall than the two-category approach when numerical integration is used to calculate the collision-coalescence tendencies for both. Replacing the numerical integration with a pre-computed lookup table reduces computational cost with little loss of accuracy. However, using fitted power laws with SLC to represent the collision-coalescence tendencies substantially reduces accuracy and leads to an order of magnitude increase in error. It is also demonstrated that with SLC, reasonably accurate solutions are obtained using only three prognostic moments, while a two-moment SLC scheme leads to substantial error. Overall, both the choice of prognostic moments (e.g., SLC vs. two-category) and method to calculate the collision-coalescence tendencies are important to consider for minimizing errors in bulk schemes. SLC with a sufficiently detailed calculation of the collision-coalescence tendencies provides accurate solutions for a reasonable computational cost, providing a viable alternative to the traditional two-category, two-moment approach for bulk microphysics.

320 (cloud physics and chemistry)↗

Liquid ToF-SIMS revealing the oil, water, and surfactant interface evolution

Bilge water from ships is regarded as a major pollutant in the marine environment. Bilge water exists in a stable oil-in-water (O/W) emulsion form. However, little is known about the O/W liquid–liquid (l–l) interface. Traditional bulk characterization approaches are not capable of capturing the chemical changes at the O/W l–l interface. Although surfactants are deemed essential in droplet formation, their roles in bilge water stabilization have not been fully revealed. We have utilized novel in situ chemical imaging tools including in situ scanning electron microscopy (SEM) and in situ time-of-flight secondary ion mass spectrometry (ToF-SIMS) to study the evolving O/W interface using a NAVY bilge model for the first time. The droplet size distribution (DSD) does not change significantly without the addition of X-100 surfactants under static or rocking conditions. Both the oil components and the water clusters are shown to evolve over time at the O/W droplet interface by in situ liquid SIMS imaging. Of particular interest to droplet stabilization, the contribution of surfactants to the aged bilge droplets becomes more significant as the droplet size increases. The higher mass surfactant component does not appear on the droplet surface immediately while many lower mass surfactants are solvated inside the droplet. We have provided the first three-dimensional images of the evolving O/W interface and demonstrated that in situ surface chemical mapping is powerful enough to reveal the complex and dynamic l–l interface in the liquid state. Our observational insights suggest that surfactants are important in mediating droplet growth and facilitating effective separation of bilge water emulsion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assessing Raindrop Breakup Parameterizations Using Disdrometer Observations

In this work, an intercomparison of raindrop mean diameter frequency distribution (RDFD) is performed for numerical simulations of precipitating cloud systems using an array of models and microphysics schemes. This includes results from the Regional Atmospheric Modeling System (RAMS) double-moment microphysics, the Hebrew University Cloud Model bin microphysics (HUCM) interfaced to the RAMS parent model, and the Weather Research and Forecasting (WRF) Model with the Thompson, Morrison, double-moment 6-class (WDM6), and National Severe Storms Laboratory (NSSL) double-moment schemes. Simulations are examined with respect to the raindrop size distribution (DSD) volume-number mean diameter (D m ) and intercept parameter (N w ). When compared to a suite of disdrometer observations, the RDFD resulting from each microphysics scheme exhibits varying degrees of mean drop size constraints and peaks in the frequency distribution of D m . A more detailed investigation of the peaked RDFD from the RAMS simulations suggests that the parameterization of raindrop collisional breakup can impose strong limitations on the evolution of simulated drop growth. As such, a summary and comparison of the drop breakup parameterizations among the aforementioned microphysics schemes is presented. While some drop breakup parameterizations are adjusted toward the observations by modifying the threshold diameter for the onset of breakup, this study explores the use of a modified maximum breakup efficiency. This method permits the parameterization to retain its threshold breakup diameter, while limiting the strength of drop breakup and permitting a broader range of drop sizes. As a result, the simulated mean drop sizes are in better agreement with observations.

54 ENVIRONMENTAL SCIENCES↗

Warm-phase microphysical evolution in large-eddy simulations of tropical cumulus congestus: evaluating drop size distribution evolution using polarimetry retrievals, in situ measurements, and a thermal-based framework

Owing to uncertainties in convective microphysics processes, improving parameterizations in Earth system models (ESMs) can benefit from observationally constrained cases suitable for scaling between cloud-resolving models and ESMs. We propose a benchmark large-eddy simulation (LES) cumulus congestus case study from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP 2 Ex) for evaluating and improving ESMs in single-column model (SCM) mode. We seek observational constraints using novel polarimetric retrievals and in situ cloud microphysics measurements. Simulations using bulk and bin microphysics initialized with observed aerosol profiles are compared to cloud-top retrievals of cloud droplet effective radius (R eff ), effective variance (ν eff ), and number concentration (N d ) from the airborne Research Scanning Polarimeter (RSP). Both schemes reproduce characteristics of cloud-top N d and R eff that increase and decrease with altitude, respectively. Cloud-top N d is low-biased relative to RSP retrievals in both schemes, potentially due to limitations in both simulations and retrieval assumptions. Cloud-top R eff is low-biased in the bulk scheme but reasonably reproduced by the bin scheme. Profiles of N d and R eff are sensitive to the collision–coalescence process and the vertical variation in aerosol size distribution. Comparison of simulated and in situ droplet size distributions (DSDs) shows that, to first order, integrated moments are always sensitive to sizes < ~ 30 µm and can also be sensitive to larger sizes if the DSDs are sufficiently broad, with implications for the assumed maximum observed size retrieved by the RSP. The bin scheme captures the observed extended tail of the DSD, while the bulk scheme is unable to due to parametric constraints. Differences in expected relationships between in situ measurements of cloud cores and cloud-top retrievals by RSP demonstrate difficulty in constraining well the case presented herein. Finally, a thermal-tracking framework demonstrates that the dilution of N d throughout a thermal's lifetime is heavily determined by collision–coalescence and the height-varying aerosol distribution and that, in the absence of these, the impact of entrainment on diluting N d is largely offset by secondary activation. Implications for evaluating warm-phase convective microphysics schemes in ESMs and translating results for use on global, space-based polarimetry platforms are discussed.

Stanford, McKenna Wallace [Columbia Univ., New Yor↗