Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “drizzle”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Utilizing a Storm-Generating Hotspot to Study Convective Cloud Transitions: The CACTI Experiment

The Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign was designed to improve understanding of orographic cloud life cycles in relation to surrounding atmospheric thermodynamic, flow, and aerosol conditions. The deployment to the Sierras de Córdoba range in north-central Argentina was chosen because of very frequent cumulus congestus, deep convection initiation, and mesoscale convective organization uniquely observable from a fixed site. The C-band Scanning Atmospheric Radiation Measurement (ARM) Precipitation Radar was deployed for the first time with over 50 ARM Mobile Facility atmospheric state, surface, aerosol, radiation, cloud, and precipitation instruments between October 2018 and April 2019. An intensive observing period (IOP) coincident with the RELAMPAGO field campaign was held between 1 November and 15 December during which 22 flights were performed by the ARM Gulfstream-1 aircraft. A multitude of atmospheric processes and cloud conditions were observed over the 7-month campaign, including numerous orographic cumulus and stratocumulus events; new particle formation and growth producing high aerosol concentrations; drizzle formation in fog and shallow liquid clouds; very low aerosol conditions following wet deposition in heavy rainfall; initiation of ice in congestus clouds across a range of temperatures; extreme deep convection reaching 21-km altitudes; and organization of intense, hail-containing supercells and mesoscale convective systems. These comprehensive datasets include many of the first ever collected in this region and provide new opportunities to study orographic cloud evolution and interactions with meteorological conditions, aerosols, surface conditions, and radiation in mountainous terrain.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Convective Transition Statistics over Tropical Oceans for Climate Model Diagnostics: GCM Evaluation

To assess deep convective parameterizations in a variety of GCMs and examine the fast-time-scale convective transition, a set of statistics characterizing the pickup of precipitation as a function of column water vapor (CWV), PDFs and joint PDFs of CWV and precipitation, and the dependence of the moisture–precipitation relation on tropospheric temperature is evaluated using the hourly output of two versions of the GFDL Atmospheric Model, version 4 (AM4), NCAR CAM5 and superparameterized CAM (SPCAM). The 6-hourly output from the MJO Task Force (MJOTF)/GEWEX Atmospheric System Study (GASS) project is also analyzed. Contrasting statistics produced from individual models that primarily differ in representations of moist convection suggest that convective transition statistics can substantially distinguish differences in convective representation and its interaction with the large-scale flow, while models that differ only in spatial–temporal resolution, microphysics, or ocean–atmosphere coupling result in similar statistics. Most of the models simulate some version of the observed sharp increase in precipitation as CWV exceeds a critical value, as well as that convective onset occurs at higher CWV but at lower column RH as temperature increases. While some models quantitatively capture these observed features and associated probability distributions, considerable intermodel spread and departures from observations in various aspects of the precipitation–CWV relationship are noted. For instance, in many of the models, the transition from the low-CWV, nonprecipitating regime to the moist regime for CWV around and above critical is less abrupt than in observations. Additionally, some models overproduce drizzle at low CWV, and some require CWV higher than observed for strong precipitation. For many of the models, it is particularly challenging to simulate the probability distributions of CWV at high temperature.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

An evaluation of size-resolved cloud microphysics scheme numerics for use with radar observations Part II: Condensation and evaporation

Accurate numerical modeling of clouds and precipitation is essential for weather forecasting and climate change research. While size-resolved (bin) cloud microphysics models predict particle size distributions without imposing shapes, results are subject to artificial size distribution broadening owing to numerical diffusion associated with various processes. Whereas Part I of this study addressed collision–coalescence, here we investigate numerical diffusion that occurs in solving condensation and evaporation. In a parcel model framework, all of the numerical schemes examined converge to one solution of condensation and evaporation as the mass grid is refined, and the advection-based schemes are recommended over the reassigning schemes. Including Eulerian vertical advection in a column limits the convergence to some extent, but that limitation occurs at a sufficiently fine mass grid, and the number of iterations in solving vertical advection should be minimized to reduce numerical diffusion. Insubstantial numerical diffusion in solving condensation can be amplified if collision–coalescence is also active, which in turn can be substantially diminished if turbulence effects on collision are incorporated. Here, large-eddy simulations of a drizzling stratocumulus field reveal that changes in moments of Doppler spectra obtained using different mass grids are consistent with those obtained from the simplified framework, and that spectral moments obtained using a mass grid designed to effectively reduce numerical diffusion are generally closer to observations. Notable differences between the simulations and observations still exist, and our results suggest a need to consider whether factors other than numerical diffusion in the fundamental process schemes employed can cause such differences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Ice Multiplication by Fragmentation during Quasi-Spherical Freezing of Raindrops: A Theoretical Investigation

Ice multiplication by fragmentation during collision–freezing of supercooled rain or drizzle is investigated. A zero-dimensional dynamical system describes the time evolution of number densities of supercooled drops and ice crystals in a mixed-phase cloud. The characteristic time scale for this collision–freezing ice fragmentation is controlled by the collision efficiency, the number of ice fragments per freezing event, and the available number concentration of supercooled drops. The rate of the process is proportional to the number of supercooled drops available. Thus, ice may multiply extensively, even when the fragmentation number per freezing event is relatively small. The ratio of total numbers of ice particles to those from the first ice, namely, the “ice-enhancement factor,” is controlled both by the number of fragments per freezing event and by the available number concentration of supercooled drops in a similar manner. Especially, when ice fragmentation by freezing of supercooled drops is considered in isolation, the number of originally existing supercooled drops multiplied by the fragmentation number per freezing event yields the eventual number of ice crystals. When supercooled drops are continuously generated by coalescence, ice crystals from freezing fragmentation also continuously increase asymptotically at a rate equal to the generation rate of supercooled drops multiplied by the fragmentation number per freezing event. All these results are expressed by simple analytical forms, thanks to the simplicity of the theoretical model. These parameters can practically be used as a means for characterizing observed mixed-phase clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Advanced Two-Moment Bulk Microphysics for Global Models. Part II: Global Model Solutions and Aerosol–Cloud Interactions*

A modified microphysics scheme is implemented in the Community Atmosphere Model, version 5 (CAM5). The new scheme features prognostic precipitation. The coupling between the microphysics and the rest of the model is modified to make it more flexible. Single-column tests show the new microphysics can simulate a constrained drizzling stratocumulus case. Substepping the cloud condensation (macrophysics) within a time step improves single-column results. Simulations of mixed-phase cases are strongly sensitive to ice nucleation. The new microphysics alters process rates in both single-column and global simulations, even at low (200 km) horizontal resolution. Thus, prognostic precipitation can be important, even in low-resolution simulations where advection of precipitation is not important. Accretion dominates as liquid water path increases in agreement with cloud-resolving model simulations and estimates from observations. The new microphysics with prognostic precipitation increases the ratio of accretion over autoconversion. Additionally, the change in process rates appears to significantly reduce aerosol–cloud interactions and indirect radiative effects of anthropogenic aerosols by up to 33% (depending on substepping) to below 1 W m-2 of cooling between simulations with preindustrial (1850) and present-day (2000) aerosol emissions.

58 GEOSCIENCES↗
DOE OSTI2018

An Evaluation of Marine Boundary Layer Cloud Property Simulations in the Community Atmosphere Model Using Satellite Observations: Conventional Subgrid Parameterization versus CLUBB

This paper presents a satellite-observation-based evaluation of the marine boundary layer (MBL) cloud properties from two Community Atmosphere Model, version 5 (CAM5), simulations, one with the standard parameterization schemes (CAM5–Base) and the other with the Cloud Layers Unified by Binormals scheme (CAM5–CLUBB). When comparing the direct model outputs, the authors find that CAM5–CLUBB produces more MBL clouds, a smoother transition from stratocumulus to cumulus, and a tighter correlation between in-cloud water and cloud fraction than CAM5–Base. In the model-to-observation comparison using the COSP satellite simulators, the authors find that both simulations capture the main features and spatial patterns of the observed cloud fraction from MODIS and shortwave cloud radiative forcing (SWCF) from CERES. However, CAM5–CLUBB suffers more than CAM5–Base from a problem that can be best summarized as “undetectable” clouds (i.e., a significant fraction of simulated MBL clouds are thinner than the MODIS detection threshold). This issue leads to a smaller COSP–MODIS cloud fraction and a weaker SWCF in CAM5–CLUBB than the observations and also CAM5–Base in the tropical descending regions. Finally, the authors compare modeled radar reflectivity with CloudSat observations and find that both simulations, especially CAM5–CLUBB, suffer from an excessive drizzle problem. Further analysis reveals that the subgrid precipitation enhancement factors in CAM5–CLUBB are unrealistically large, which makes MBL clouds precipitate too excessively, and in turn results in too many undetectable thin clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Merged Cloud and Precipitation Dataset from the HIAPER GV for the Cloud System Evolution in the Trades (CSET) Campaign

The Cloud System Evolution in the Trades (CSET) aircraft campaign was conducted in the summer of 2015 in the northeast Pacific to observe the transition from stratocumulus to cumulus cloud regime. Fourteen transects were made between Sacramento, California, and Kona, Hawaii, using the NCAR's High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) Gulfstream V (GV) aircraft. The HIAPER W-band Doppler cloud radar (HCR) and the high-spectral-resolution lidar (HSRL), in their first deployment together on board the GV, provided crucial cloud and precipitation observations. The HCR recorded the raw in-phase (I) and quadrature (Q) components of the digitized signal, from which the Doppler spectra and its first three moments were calculated. HCR/HSRL data were merged to develop a hydrometeor mask on a uniform georeferenced grid of 2-Hz temporal and 20-m vertical resolutions. The hydrometeors are classified as cloud or precipitation using a simple fuzzy logic technique based on the HCR mean Doppler velocity, HSRL backscatter, and the ratio of HCR reflectivity to HSRL backscatter. This is primarily applied during zenith-pointing conditions under which the lidar can detect the cloud base and the radar is more sensitive to clouds. The microphysical properties of below-cloud drizzle and optically thin clouds were retrieved using the HCR reflectivity, HSRL backscatter, and the HCR Doppler spectrum width after it is corrected for the aircraft speed. These indicate that as the boundary layers deepen and cloud-top heights increase toward the equator, both the cloud and rain fractions decrease.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Rain Drop Size Distributions Estimated from NOAA Snow-Level Radar Data

Using NOAA’s S-band High-Power Snow-Level Radar (HPSLR), a technique for estimating the rain drop size distribution (DSD) above the radar is presented. This technique assumes the DSD can be described by a four parameter, generalized gamma distribution (GGD). Using the radar’s measured average Doppler velocity spectrum and a value (assumed, measured, or estimated) of the vertical air motion w, an estimate of the GGD is obtained. Four different methods can be used to obtain w. One method that estimates a mean mass-weighted raindrop diameter D m from the measured reflectivity Z produces realistic DSDs compared to prior literature examples. These estimated DSDs provide evidence that the radar can retrieve the smaller drop sizes constituting the “drizzle” mode part of the DSD. Here, this estimation technique was applied to 19 h of observations from Hankins, North Carolina. Results support the concept that DSDs can be modeled using GGDs with a limited range of parameters. Further work is needed to validate the described technique for estimating DSDs in more varied precipitation types and to verify the vertical air motion estimates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

High temporal resolution estimates of Arctic snowfall rates emphasizing gauge and radar-based retrievals from the MOSAiC expedition

This article presents the results of snowfall rate and accumulation estimates from a vertically pointing 35-GHz radar and other sensors deployed during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. The radar-based retrievals are the most consistent in terms of data availability and are largely immune to blowing snow. The total liquid-equivalent accumulation during the snow accumulation season is around 110 mm, with more abundant precipitation during spring months. About half of the total accumulation came from weak snowfall with rates less than approximately 0.2 mmh–1. The total snowfall estimates from a Vaisala optical sensor aboard the icebreaker are similar to those from radar retrievals, though their daily and monthly accumulations and instantaneous rates varied significantly. Compared to radar retrievals and the icebreaker optical sensor data, measurements from an identical optical sensor at an ice camp are biased high. Blowing snow effects, in part, explain differences. Weighing gauge measurements significantly overestimate snowfall during February–April 2020 as compared to other sensors and are not well suited for estimating instantaneous snowfall rates. The icebreaker optical disdrometer estimates of snowfall rates are, on average, relatively little biased compared to radar retrievals when raw particle counts are available and appropriate snowflake mass-size relations are used. These counts, however, are not available during periods that produced more than a third of the total snowfall. While there are uncertainties in the radar-based retrievals due to the choice of reflectivity-snowfall rate relations, the major error contributor is the uncertainty in the radar absolute calibration. The MOSAiC radar calibration is evaluated using comparisons with other radars and liquid water cloud–drizzle processes observed during summer. Overall, this study describes a consistent, radar-based snowfall rate product for MOSAiC that provides significant insight into Central Arctic snowfall and can be used for many other purposes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

MAGIC Cloud Properties from Zenith Radiance Data Final Campaign Summary

Cloud droplet size and optical depth are the most fundamental properties for understanding cloud formation, dissipation and interactions with aerosol and drizzle. They are also a crucial determinant of Earth’s radiative and water-energy balances. However, these properties are poorly predicted in climate models. As a result, the response of clouds to climate change is one of the major sources of uncertainty in climate prediction.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Parsivel Disdrometer Support for MAGIC Field Campaign Report

In the Marine ARM GPCI Investigation of Clouds (MAGIC) field campaign, the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s second Mobile Facility (AMF2) was deployed on the Horizon Lines cargo ship Spirit traversing a route between Los Angeles, California and Honolulu, Hawaii for one full year. The transect for this deployment was chosen specifically because it crosses the stratocumulus-to-cumulus transition of the North-East Pacific, a region of great climatic interest and a close approximation to the transect used for several focused model intercomparison efforts. The cloud type and cover along this transect vary from low marine stratocumulus with high areal coverage near the California coast to isolated shallow cumulus with much lower areal coverage in the trade wind regime near Hawaii. The low marine stratocumulus decks, with their high albedo, exert a major influence on the shortwave radiation budget in the ocean environment, and thus provide an extremely important forcing of Earth’s climate. The trade cumulus clouds play a large role in the global surface evaporation and also in Earth’s albedo. One of the important science drivers of the MAGIC campaign was to measure the properties of clouds and precipitation, specifically cloud type, fractional coverage, base height, physical thickness, liquid water path (LWP), optical depth, and drizzle and precipitation frequency, amount, and extent. Retrievals of cloud and precipitation properties during the MAGIC campaign relied critically on the calibration of the AMF2 radar systems. For MAGIC this included the KAZR and M-WACR, both fixed zenith-pointing systems, and the 1290 MHz beam steerable wind profiler.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Collaborative Research: Reducing tropical precipitation biases in CESM — Tests of unified parameterizations with ARM observations

In state-of-the-art climate models, each cloud type is treated using its own separate cloud parameterization and its own separate microphysics parameterization. This use of separate schemes for separate cloud regimes is undesirable because it is theoretically unfounded, it hampers interpretation of results, and it leads to the temptation to overtune parameters. In this grant, we are creating a climate model that contains a unified cloud parameterization and a unified microphysics parameterization. This model will be used to address the problems of excessive frequency of drizzle in climate models and excessively early onset of deep convection in the Tropics over land. The resulting model will be compared with ARM observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Improving Mixed-phase Cloud Parameterization in Climate Model with the ACRF Measurements

Mixed-phase cloud microphysical and dynamical processes are still poorly understood, and their representation in GCMs is a major source of uncertainties in overall cloud feedback in GCMs. Thus improving mixed-phase cloud parameterizations in climate models is critical to reducing the climate forecast uncertainties. This study aims at providing improved knowledge of mixed-phase cloud properties from the long-term ACRF observations and improving mixed-phase clouds simulations in the NCAR Community Atmosphere Model version 5 (CAM5). The key accomplishments are: 1) An improved retrieval algorithm was developed to provide liquid droplet concentration for drizzling or mixed-phase stratiform clouds. 2) A new ice concentration retrieval algorithm for stratiform mixed-phase clouds was developed. 3) A strong seasonal aerosol impact on ice generation in Arctic mixed-phase clouds was identified, which is mainly attributed to the high dust occurrence during the spring season. 4) A suite of multi-senor algorithms was applied to long-term ARM observations at the Barrow site to provide a complete dataset (LWC and effective radius profile for liquid phase, and IWC, Dge profiles and ice concentration for ice phase) to characterize Arctic stratiform mixed-phase clouds. This multi-year stratiform mixed-phase cloud dataset provides necessary information to study related processes, evaluate model stratiform mixed-phase cloud simulations, and improve model stratiform mixed-phase cloud parameterization. 5). A new in situ data analysis method was developed to quantify liquid mass partition in convective mixed-phase clouds. For the first time, we reliably compared liquid mass partitions in stratiform and convective mixed-phase clouds. Due to the different dynamics in stratiform and convective mixed-phase clouds, the temperature dependencies of liquid mass partitions are significantly different due to much higher ice concentrations in convective mixed phase clouds. 6) Systematic evaluations of mixed-phase cloud simulations by CAM5 were performed. Measurement results indicate that ice concentrations control stratiform mixed-phase cloud properties. The improvement of ice concentration parameterization in the CAM5 was done in close collaboration with Dr. Xiaohong Liu, PNNL (now at University of Wyoming).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Scanning Radar Investigations to Characterize Cloud and Precipitation Processes for ASR

The project conducted investigations in the following areas related to scanning radar retrievals: a) Development for Cloud drizzle separation studies for the ENA site based on Doppler Spectra b) Advanced radar retrieval for the SGP site c) Characterizing falling snow using multifrequency dual-polarization measurements d) BAECC field experiment. More details about these investigations can be found within each subtopic within the report.

58 GEOSCIENCES↗
DOE OSTI2017

Collaborative Research: Cloudiness transitions within shallow marine clouds near the Azores

Marine stratocumulus clouds are low, persistent, liquid phase clouds that cover large areas and play a significant role in moderating the climate by reflecting large quantities of incoming solar radiation. The deficiencies in simulating these clouds in global climate models are widely recognized. Much of the uncertainty arises from sub-grid scale variability in the cloud albedo that is not accurately parameterized in climate models. The Clouds, Aerosol and Precipitation in the Marine Boundary Layer (CAP–MBL) observational campaign and the ongoing ARM site measurements on Graciosa Island in the Azores aim to sample the Northeast Atlantic low cloud regime. These data represent, the longest continuous research quality cloud radar/lidar/radiometer/aerosol data set of open-ocean shallow marine clouds in existence. Data coverage from CAP–MBL and the series of cruises to the southeast Pacific culminating in VOCALS will both be of sufficient length to contrast the two low cloud regimes and explore the joint variability of clouds in response to several environmental factors implicated in cloudiness transitions. Our research seeks to better understand cloud system processes in an underexplored but climatologically important maritime region. Our primary goal is an improved physical understanding of low marine clouds on temporal scales of hours to days. It is well understood that aerosols, synoptic-scale forcing, surface fluxes, mesoscale dynamics, and cloud microphysics all play a role in cloudiness transitions. However, the relative importance of each mechanism as a function of different environmental conditions is unknown. To better understand cloud forcing and response, we are documenting the joint variability of observed environmental factors and associated cloud characteristics. In order to narrow the realm of likely parameter ranges, we assess the relative importance of parameter conditions based primarily on two criteria: how often the condition occurs (frequency) and to what degree varying that condition within its typically observed range affects cloud characteristics (magnitude of impact given the condition). In this manner we will be able to address the relative importance of individual factors within a multivariate range of environmental conditions. We will determine the relative roles of the thermodynamic, aerosol, and synoptic environmental factors on low cloud and drizzle formation and lifetime.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

3D Shortwave Radiative Kernels of Marine Boundary-layer Clouds Using Scanning Radar/Lidar and Array Spectroradiometer

This project set out to use synergetic measurements from the ARM program to observe 3D cloud field observations, and to investigate how inadequate treatment of the observed 3D characteristics of clouds in models may impact estimates of low-cloud feedback magnitude. The project comprises three components, including 1) retrieving cloud and precipitation properties, 2) developing fast radiative transfer code incorporating 3D cloud effects, and 3) estimating 3D effects/impacts on a global scale. This report documents our main research outcomes. Specifically, a novel cloud retrieval method is developed, allowing us to better characterize cloud population and sizes, drizzle properties and precipitation formation, and to better understand their interactions with aerosols. These observed 3D cloud fields were used in a fast radiative transfer code, helping discover non-negligible 3D radiative effects in the longwave spectral region. The retrieved cloud properties were also used to investigate several hypothesized cloud feedback processes.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Properties and Controlling Processes of Aerosol and Cloud Condensation Nuclei in Marine Boundary Layer Over Eastern North Atlantic (Final Report)

Remote marine low cloud systems have large spatial and temporal coverages. Because of their relatively low optical thickness and background aerosol concentrations, marine low clouds are particularly susceptible to perturbations in aerosols associated with anthropogenic emissions. Recent studies show that a large fraction of the global aerosol indirect forcing can be attributed to changes in marine low clouds, despite their relatively long distance from most anthropogenic sources. Currently, there remain large uncertainties in the magnitude of the global aerosol indirect radiative forcing. One major contribution to this large uncertainty derives from poor understanding of the aerosols under natural conditions, the perturbation by anthropogenic emissions, and the processes that drive them. In this project, we took advantage of the comprehensive, multi-dimensional characterization of meteorological parameters, trace gases, aerosol, cloud, and drizzle fields during the Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) and the long-term measurements at the Atmospheric Radiation Measurement (ARM) Eastern North Atlantic (ENA) site on Graciosa Island. By synergistically combining in situ measurements, remote sensing retrievals, and model simulations, we quantified aerosol properties in the ENA, their vertical profiles, and variations with season, synoptic state, and airmass. We investigated key aerosol processes, including entrainment of free troposphere aerosol into marine boundary layer, new particle formation, growth of Aitken mode particles, and the influences of these processes on the cloud condensation nuclei (CCN) population in marine boundary layer. The representation of key aerosol processes in the Energy Exascale Earth System Model (E3SM) was evaluated using the observations. This project has led to 26 publications, which are listed at the end of this report.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Using ARM Data to Retrieve Entrainment Rates in Stratocumulus Cloud Systems (Final Report)

A stratocumulus-topped boundary layer (STBL) is a shallow convecting layer in which both the updraft and the downdraft branches of the convective circulation are saturated (cloudy) in the upper part of the boundary layer. The convective circulation is vigorous, yet the cloud-top entrainment velocity, $w_e$, is small and difficult to measure. Differences between currently used parameterizations of $w_e$ in GCMs can lead to STBLs that differ by as much as a factor of two in climatologically important properties such as liquid water path and boundary layer depth. We have developed a new method to retrieve entrainment rates in STBLs which uses vertical velocity retrievals from surface-based cloud radar, in conjunction with other surface-based measurements. These new estimates will allow a more comprehensive evaluation of parameterizations of entrainment rate for STBLs. The new method will also provide ground-based estimates of entrainment in STBLs over long time periods. We use retrievals of vertical velocity and liquid water content profiles to estimate the turbulent liquid water flux, which is then used in combination with observed cloud-top jumps of temperature, water vapor, and calculated radiative flux profiles to estimate the entrainment rate. We present results for three days for which observational data was not significantly contaminated by drizzle. The resulting average entrainment rates are 0.58 cm/s, 1.51 cm/s, and 0.31 cm/s.

54 ENVIRONMENTAL SCIENCES↗