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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

The Vertical Distribution of Thin Features Over the Arctic Analysed from CALIPSO Observations: Optically Thin Clouds - Part 1

Clouds play a crucial role in the Arctic climate system. Therefore, it is essential to accurately and reliably quantify and understand cloud properties over the Arctic. It is also important to monitor and attribute changes in Arctic clouds. Here, we exploit the capability of the CALIPSO-CALIOP instrument and provide comprehensive statistics of tropospheric thin clouds, otherwise extremely difficult to monitor from passive satellite sensors.We use 4 yr of data (June 2006.May 2010) over the circumpolar Arctic, here defined as 67-82 deg. N, and characterize probability density functions of cloud base and top heights, geometrical thickness and zonal distribution of such cloud layers, separately for water and ice phases, and discuss seasonal variability of these properties. When computed for the entire study area, probability density functions of cloud base and top heights and geometrical thickness peak at 200-400, 1000-2000 and 400-800 m, respectively, for thin water clouds, while for ice clouds they peak at 6-8, 7-9 and 400-1000 m, respectively. In general, liquid clouds were often identified below 2 km during all seasons, whereas ice clouds were sensed throughout the majority of the upper troposphere and also, but to a smaller extent, below 2 km for all seasons.

DeVasthale, Abhay↗
NASA NTRS2005

A Climatology of Midlatitude Continental Clouds from the ARM SGP Site: Low-Level Cloud Macrophysical, Microphysical, and Radiative Properties - Part I

A record of single-layer and overcast low cloud (stratus) properties has been generated using approximately 4000 hours of data collected from January 1997 to December 2002 at the Atmospheric Radiation Measurement (ARM) Southern Great Plains Central Facility (SCF). The cloud properties include liquid-phase and liquid-dominant, mixed-phase, low cloud macrophysical, microphysical, and radiative properties including cloud-base and -top heights and temperatures, and cloud physical thickness derived from a ground-based radar and lidar pair, and rawinsonde sounding; cloud liquid water path (LWP) and content (LWC), and cloud-droplet effective radius (r(sub e)) and number concentration (N) derived from the macrophysical properties and radiometer data; and cloud optical depth (tau), effective solar transmission (gamma), and cloud/top-of-atmosphere albedos (R(sub cldy)/R(sub TOA)) derived from Eppley precision spectral pyranometer measurements. The cloud properties were analyzed in terms of their seasonal, monthly, and hourly variations. In general, more stratus clouds occur during winter and spring than in summer. Cloud-layer altitudes and physical thicknesses were higher and greater in summer than in winter with averaged physical thicknesses of 0.85 km and 0.73 km for day and night, respectively. The seasonal variations of LWP, LWC, N. tau, R(sub cldy), and R(sub TOA) basically follow the same pattern with maxima and minima during winter and summer, respectively. There is no significant variation in mean r(sub e), however, despite a summertime peak in aerosol loading, Although a considerable degree of variability exists, the 6-yr average values of LWP, LWC, r(sub e), N, tau, gamma, R(sub cldy) and R(sub TOA) are 150 gm(exp -2) (138), 0.245 gm(exp -3) (0.268), 8.7 micrometers (8.5), 213 cm(exp -3) (238), 26.8 (24.8), 0.331, 0.672, 0.563 for daytime (nighttime). A new conceptual model of midlatitude continental low clouds at the ARM SGP site has been developed from this study. The low stratus cloud amount monotonically increases from midnight to early morning (0930 LT), and remains large until around local noon, then declines until 1930 LT when it levels off for the remainder of the night. In the morning, the stratus cloud layer is low, warm, and thick with less LWC, while in the afternoon it is high, cold, and thin with more LWC. Future parts of this series will consider other cloud types and cloud radiative forcing at the ARM SCF.

Dong, Xiquan↗
DOE OSTI2025

Baltimore Social-Environmental Collaborative (BSEC) Doppler Lidar & Derived Products

This repository contains all processed Doppler‐lidar outputs from the PSU lidar deployed for the Baltimore Social‐Environmental Collaborative (BSEC) project. Vertical Stare Scans (fixed‐beam, vertical profiling): 1 Hz backscatter intensity (m⁻¹ sr⁻¹), signal‐to‐noise ratio (unitless), and Doppler vertical‐velocity (m s⁻¹) on ~30 m range gates, stored as CF-compliant NetCDF. Wind Profiles (horizontal‐wind retrieval): daily NetCDF outputs of retrieved horizontal wind speed (m s⁻¹) and direction (degrees), computed from the angled‐scan returns. Profile Statistics (summary statistics on the vertical velocity): 15 min windows (default) of mean, variance, skewness, kurtosis, high-frequency variance, etc., as a function of height; saved as CF-compliant NetCDF files. Boundary Layer Height (BLH) (fuzzy-logic output): 15 min BLH estimates (m), with lower/upper fuzzy bounds (m) and a quality flag (0–4) indicating data status (e.g., no data, good, below range, ran out of signal, cloud-topped). Cloud Base Height (Haar-gradient detection): 15 min estimates of cloud-base height (m) with a cloud-detection quality flag (0–3: none, low, moderate, high). All five product streams are organized by year and date under their own top-level folders (01_Vertical_Stare_Scans/ through 05_Cloud_Height/). Each folder contains a data_ /YYYY/ subdirectory with daily CF-compliant NetCDF outputs (96 windows per day at 15 min intervals). Global attributes in each file include creation history, version (2.0.0), institution, and source. Instrument & MeasurementsThe PSU Doppler Lidar samples aerosol backscatter (m⁻¹ sr⁻¹), signal-to-noise ratio, and radial velocity at ~1 Hz. Vertical stare scans point the beam straight up; after collecting angled scans through multiple elevation angles, the "Wind Profiles" product contains the fully retrieved horizontal wind speed and direction. Data were collected continuously at ~30 m range resolution, with a typical height ceiling of ~12 km. How to Use Open any NetCDF with Python's xarray, MATLAB, or similar CF-compliant tools. Stare scans and angled-scan retrievals (Wind Profiles) are CF-compliant daily NetCDF files. Profile-Statistics, BLH, and Cloud Height files are daily 15 min summaries (96 time steps per file). Inspect the included variables (e.g., vertical_velocity_variance, wind_speed, BLH, cloud_base_height) for your analyses. Use the quality flags (BLH_flag, cloud_flag) to filter out poor-quality retrievals. For more information or questions about processing methods, please contact:Nicholas E. Prince ⟨nec5299@psu.edu⟩Penn State Department of Meteorology & Atmospheric Science

Air Quality↗
NASA NTRS1990

A study of marine stratocumulus using lidar and other FIRE aircraft observations

The National Center for Atmospheric Research (NCAR) airborne infrared lidar system (NAILS) used in the 1987 First ISCCP Regional Experiment (FIRE) off the coast of California is a 10.6 microns wavelength carbon dioxide lidar system constructed by Ron Schwiesow and co-workers at NCAR. The lidar is particularly well suited for detailed observations of cloud shapes; i.e., height of cloud top (when flying above cloud and looking down) and cloud base (when flying below cloud and looking up) along the flight path. A brief summary of the lidar design characteristics is given. The lidar height resolution of plus or minus 3 m allows for the distance between the aircraft and cloud edge to be determined with this accuracy; however, the duration of the emitted pulse is approximately 3 microseconds, which corresponds to a 500 m pulse length. Therefore, variations in backscatter intensities within the clouds can normally not be resolved. Hence the main parameter obtainable from the lidar is distance to cloud; in some cases the cloud depth can also be determined. During FIRE the lidar was operational on 7 of the 10 Electra flights, and data were taken when the distance between cloud and aircraft (minimum range) was at least 500 m. The lidar was usually operated at 8 Hz, which at a flight speed of 100 m s(-1) translates into a horizontal resolution of about 12 m. The backscatter as function of time (equivalent to distance) for each laser pulse is stored in digital form on magnetic tape. Currently, three independent variables are available to the investigators on the FIRE Electra data tapes: lidar range to cloud, strength of return (relative power), and pulse width of return, which is related to penetration depth.

Jensen, Jorgen B.↗
DOE OSTI2020

Aerosol Impacts on Mesoscale Convective Systems Forming Under Different Vertical Wind Shear Conditions

Following our previous study of wind shear effect on mesoscale convective system (MCS) organization under a clean atmospheric condition using the Weather Research and Forecasting model coupled with Spectral-Bin Microphysics, we conduct sensitivity simulations by increasing cloud condensation nuclei (CCN) concentration and investigate aerosol impacts on MCSs forming under different wind shear conditions. We find that, aerosols induce stronger updrafts and downdrafts in all MCSs. The stronger updrafts and enlarged convective core area contribute to larger vertical mass fluxes and enhance precipitation, indicating convective invigoration. Increased updraft speed below 8-km altitude mainly results from enhanced condensational heating, and increased water loading effect is not large enough to overcome the increase in thermal buoyancy. Interestingly, above 8-km altitude we see reduced updraft speed by the increased aerosols due to reduced vertical pressure perturbation gradient force, and weakened depositional growth due to competition of water vapor by enhanced condensation. The accumulated rainfall and mean rain rate are increased, with an increased occurrence frequency of heavy rain. The increase of rain rate is seen in both convective and stratiform regions, with a more significant increase in convective rain rate. In general, we see a higher frequency of deep convective cloud in the polluted condition because of invigorated convection, and more stratiform/anvil clouds, but a lower frequency of shallow warm clouds. The unanimously invigorated MCSs by aerosols under various wind shear conditions revealed by this study has an important implication in weather and climate at warm and humid regions that are influenced by pollution.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1986

Planetary optical and infrared imaging

Images were acquired of a circumstellar disk of orbiting material around the nearby star beta Pictoris. This material is believed to be associated with the formation of planets and provides a first look at a planetary system much younger than our own. Preliminary work was also done to acquire multicolor photometric data and polarimetry on the beta Pictoris disk as well. A coronagraphic search for other proto-planetary systems is also underway. Coronagraphic imaging provided the first clear images and a determination of the geometric albedo of the rings of Uranus. A search for material around the asteroid Amphitrite showed that the region around the asteroid was free of particles larger than 500 meters in radius or diffuse material with an optical depth larger than .000001. NASA IRTF infrared images of Jupiter and Saturn are providing information on the relative heights and cloud top temperatures of atmospheric features.

Terrile, R. J.↗
NASA NTRS1990

Air-sea interaction during an extreme cold air outbreak from the eastern coast of the United States

An aircraft investigation of boundary layer mean and turbulent structure is reported, and the Lagrangian budgets of temperature and moisture in the subcloud layer following a streamline during an extreme cold air outbreak are evaluated. The maximum sea-air temperature difference was 23 K. Two aircraft were used: the NCAR Electra, which measured turbulent fluxes and investigated subcloud layer conditions, and the NASA Electra, which measured the height of cloud tops using lidar. A stratocumulus overcast was found from about 60 km offshore to the Gulf Stream core with cloud top rising downstream. East of the Gulf Stream cumulus congestus and snow showers were observed. Cloud base decreased downstream and numerous steam plumes filled the subcloud layer. Temperature cross sections show most warming, and moistening of the subcloud layer occurred before the Gulf Stream core. Windspeeds increased downstream and maxima were observed near cloud top (inversion) and in the subcloud layer. Lagrangian budgets showed most warming, and moistening of the layer between 70 m and about 100 m below mean cloud base was due to turbulent flux divergence.

Grossman, Robert L.↗
NASA NTRS1993

Comparison of cloud boundaries measured with 8.6 mm radar and 10.6 micrometer lidar

One of the most basic cloud properties is location; the height of cloud base and the height of cloud top. The glossary of meteorology defines cloud base (top) as follows: 'For a given cloud or cloud layer, that lowest (highest) level in the atmosphere at which the air contains a perceptible quantity of cloud particles.' Our studies show that for a 8.66 mm radar, and a 10.6 micrometer lidar, the level at which cloud hydrometers become 'perceptible' can vary significantly as a function of the different wavelengths, powers, beamwidths and sampling rates of the two remote sensors.

Uttal, Taneil↗
NASA NTRS2019

Radiative Heating Rates Computed With Clouds Derived From Satellite‐Based Passive and Active Sensors and their Effects on Generation of Available Potential Energy

Radiative heating rates computed with cloud properties derived from passive and active sensors are investigated. Zonal monthly radiative heating rate anomalies computed using both active and passive sensors show that larger variability in longwave cooling exists near the tropical tropopause and near the top of the boundary layer between ~50°N to ~50°S. Aerosol variability contributes to increases in shortwave heating rate variability. When zonal monthly mean cloud effects on the radiative heating rate computed with both active and passive sensors and those computed with passive sensor only are compared, the latter shows cooling and heating peaks corresponding to cloud top and base height ranges used for separating cloud types. The difference of these two sets of cloud radiative effect on heating rates in the middle to upper troposphere is larger than the radiative heating rate uncertainty estimated based on the difference of two active sensor radiative heating rate profile data products. In addition, radiative heating rate contribution to generation of eddy available potential energy is also investigated. Although radiation contribution to generation of eddy available potential energy averaged over a year and the entire globe is small, radiation increases the eddy available potential energy in the northern hemisphere during summer. Two key elements that longwave radiation contribute to the generation of eddy potential energy are (1) longitudinal temperature gradient in the atmosphere associated with land and ocean surface temperatures contrasts and absorption of longwave radiation emitted by the surface and (2) cooling near the cloud top of stratocumulus clouds.

Kato, Seiji↗
DOE OSTI2025

Multiscale ACI Satellite Database

The SATELLITE_EAGLES_PNNL NetCDF dataset contains a suite of satellite- and reanalysis-derived atmospheric and surface parameters on a regular latitude–longitude grid. The dataset includes core geophysical fields such as land fraction, aerosol optical depth at multiple wavelengths (465, 550, 667, and 865 nm), sea surface temperature, estimated inversion strength, and various thermodynamic and dynamic quantities (e.g., relative humidity, vertical velocity, boundary-layer height, and surface fluxes) from both MERRA and ERA reanalysis products, provided as daily-mean and instantaneous values. A major component of the dataset consists of MODIS-retrieved cloud microphysical properties, including cloud droplet number concentration, cloud effective radius, optical thickness, and liquid water path, provided for three compositing regimes (“All,” “Q06,” and “G18”). Corresponding cloud-top parameters—temperature, height, and pressure—along with total and domain-mean cloud fraction fields are also included. The file further integrates additional satellite data from AMSR-E (for cloud water, rain water, and surface precipitation retrievals) and CERES (for top-of-atmosphere radiative fluxes, cloud fractions, and albedo). This dataset is designed to evaluate aerosol–cloud interactions in warm clouds, emphasizing the use of MODIS for deriving cloud droplet number concentration and liquid water path statistics. The complementary satellite and reanalysis fields are co-located and time-matched to the same instantaneous MODIS observations, enabling consistent comparisons between cloud properties, aerosol loading, and large-scale meteorological conditions. The dataset is recently featured in Christensen et al. (2025), Machine Learning Reveals Strong Grid-Scale Dependence in the Satellite Nd–LWP Relationship, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-3850, 2025.

Christensen, Matthew [Pacific Northwest National L↗
DOE OSTI2025

Multiscale ACI Satellite Database

The SATELLITE_EAGLES_PNNL NetCDF dataset contains a suite of satellite- and reanalysis-derived atmospheric and surface parameters on a regular latitude–longitude grid. The dataset includes core geophysical fields such as land fraction, aerosol optical depth at multiple wavelengths (465, 550, 667, and 865 nm), sea surface temperature, estimated inversion strength, and various thermodynamic and dynamic quantities (e.g., relative humidity, vertical velocity, boundary-layer height, and surface fluxes) from both MERRA and ERA reanalysis products, provided as daily-mean and instantaneous values. A major component of the dataset consists of MODIS-retrieved cloud microphysical properties, including cloud droplet number concentration, cloud effective radius, optical thickness, and liquid water path, provided for three compositing regimes (“All,” “Q06,” and “G18”). Corresponding cloud-top parameters—temperature, height, and pressure—along with total and domain-mean cloud fraction fields are also included. The file further integrates additional satellite data from AMSR-E (for cloud water, rain water, and surface precipitation retrievals) and CERES (for top-of-atmosphere radiative fluxes, cloud fractions, and albedo). This dataset is designed to evaluate aerosol–cloud interactions in warm clouds, emphasizing the use of MODIS for deriving cloud droplet number concentration and liquid water path statistics. The complementary satellite and reanalysis fields are co-located and time-matched to the same instantaneous MODIS observations, enabling consistent comparisons between cloud properties, aerosol loading, and large-scale meteorological conditions. The dataset is recently featured in Christensen et al. (2025), Machine Learning Reveals Strong Grid-Scale Dependence in the Satellite Nd–LWP Relationship, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-3850, 2025.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Investigation on cloud vertical structures based on Ka-band cloud radar observations at Wuhan in Central China

Based on vertically pointing observations of Ka-band frequency-modulated continuous millimeter wave cloud radar (MMCR) in 2020, we investigate cloud vertical structures at Wuhan in central China. Case comparison indicates that the cloud top locations in the MMCR observation are largely consistent with those in satellite data. The precipitation has the occurrence frequency of 9.5% over the year, with the maximum value of 16.3% in July and the submaximal value of 14.7% in January, showing the significant influences of monsoons on precipitation at Wuhan. As the humid, cloudy and rainy climate, the probability of precipitation and non-precipitation clouds increases gradually from 53.9% in January to a large value of 71.5% in July. The non-precipitation clouds have the probability of 44.5% in the year, with two prominent peaks at the reflectivities of -35 to -30 dBZ around 12 km in summer and - 37– -32 dBZ around 10 km in spring. The cloud top can reach the heights of 14.49, 16.62, 13.38 and 11.73 km from spring to winter, respectively. The monthly mean cloud layer thickness is the largest (2.18 km) in May and September, and the smallest (1.36 km) in November. The seasonally averaged base and top heights and thickness of clouds have small diurnal variations. The high cloud is predominant in the warm months from May to September, and in the other cool months, the middle cloud has the most fraction. The quantitative investigation of clouds is helpful in improving the cloud parameterization in climate models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2023

The CHROMA Cloud-Top Pressure Retrieval Algorithm for the Plankton, Aerosol, Cloud, Ocean Ecosystem (PACE) Satellite Mission

This paper provides the theoretical basis and simulated retrievals for the Cloud Height Retrieval from O2 Molecular Absorption (CHROMA) algorithm. Simulations are performed for the Ocean Color Instrument (OCI), which is the primary payload on the forthcoming NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, and the Ocean Land Colour Instrument (OLCI) currently flying on the Sentinel 3 satellites. CHROMA is a Bayesian approach which simultaneously retrieves cloud optical thickness (COT), cloud-top pressure and height (CTP and CTH respectively), and (with a significant prior constraint) surface albedo. Simulated retrievals suggest that the sensor and algorithm should be able to meet the PACE mission goal for CTP error, which is ±60 mb for 65 % of opaque (COT ≥3) single-layer clouds on global average. CHROMA will provide pixel-level uncertainty estimates, which are demonstrated to have skill at telling low-error situations from high-error ones. CTP uncertainty estimates are well-calibrated in magnitude, although COT uncertainty is overestimated relative to observed errors. OLCI performance is found to be slightly better than OCI overall, demonstrating that it is a suitable proxy for the latter in advance of PACE's launch. CTP error is only weakly sensitive to correct cloud phase identification or assumed ice crystal habit/roughness. As with other similar algorithms, for simulated retrievals of multi-layer systems consisting of optically thin cirrus clouds above liquid clouds, retrieved height tends to be underestimated because the satellite signal is dominated by the optically thicker lower layer. Total (liquid plus ice) COT also becomes underestimated in these situations. However, retrieved CTP becomes closer to that of the upper ice layer for ice COT ≈3 or higher.

PACE↗
NASA NTRS1996

The effects of cloud inhomogeneities upon radiative fluxes, and the supply of a cloud truth validation dataset

The ASTER polar cloud mask algorithm is currently under development. Several classification techniques have been developed and implemented. The merits and accuracy of each are being examined. The classification techniques under investigation include fuzzy logic, hierarchical neural network, and a pairwise histogram comparison scheme based on sample histograms called the Paired Histogram Method. Scene adaptive methods also are being investigated as a means to improve classifier performance. The feature, arctan of Band 4 and Band 5, and the Band 2 vs. Band 4 feature space are key to separating frozen water (e.g., ice/snow, slush/wet ice, etc.) from cloud over frozen water, and land from cloud over land, respectively. A total of 82 Landsat TM circumpolar scenes are being used as a basis for algorithm development and testing. Numerous spectral features are being tested and include the 7 basic Landsat TM bands, in addition to ratios, differences, arctans, and normalized differences of each combination of bands. A technique for deriving cloud base and top height is developed. It uses 2-D cross correlation between a cloud edge and its corresponding shadow to determine the displacement of the cloud from its shadow. The height is then determined from this displacement, the solar zenith angle, and the sensor viewing angle.

Welch, Ronald M.↗
NASA NTRS2014

The Atmospheric Infrared Sounder Version 6 Cloud Products

The version 6 cloud products of the Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) instrument suite are described. The cloud top temperature, pressure, and height and effective cloud fraction are now reported at the AIRS field-of-view (FOV) resolution. Significant improvements in cloud height assignment over version 5 are shown with FOV-scale comparisons to cloud vertical structure observed by the CloudSat 94 GHz radar and the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP). Cloud thermodynamic phase (ice, liquid, and unknown phase), ice cloud effective diameter D(sub e), and ice cloud optical thickness (τ) are derived using an optimal estimation methodology for AIRS FOVs, and global distributions for 2007 are presented. The largest values of tau are found in the storm tracks and near convection in the tropics, while D(sub e) is largest on the equatorial side of the midlatitude storm tracks in both hemispheres, and lowest in tropical thin cirrus and the winter polar atmosphere. Over the Maritime Continent the diurnal variability of tau is significantly larger than for the total cloud fraction, ice cloud frequency, and D(sub e), and is anchored to the island archipelago morphology. Important differences are described between northern and southern hemispheric midlatitude cyclones using storm center composites. The infrared-based cloud retrievals of AIRS provide unique, decadal-scale and global observations of clouds over portions of the diurnal and annual cycles, and capture variability within the mesoscale and synoptic scales at all latitudes.

infrared instruments↗
DOE OSTI2023

Convective and Turbulent Motions in Nonprecipitating Cu. Part III: Characteristics of Turbulence Motions

Velocity field in a nonprecipitating Cu under BOMEX conditions, simulated by SAM with 10-m resolution and spectral bin microphysics is separated into the convective part and the turbulent part, using a wavelet filtering. In Part II of the study properties of convective motions of this Cu were investigated. Here in Part III of the study, the parameters of cloud turbulence are calculated in the cloud updraft zone at different stages of cloud development. The main points of this study are (i) application of a fine-scale LES model of a single convective cloud allowed a direct estimation of turbulence parameters using the resolved flow in the cloud and (ii) the separation of the resolved flow into the turbulence flow and the nonturbulence flow allowed us to estimate different turbulent parameters with sufficient statistical accuracy. We calculated height and time dependences of the main turbulent parameters such as turbulence kinetic energy (TKE), spectra of TKE, dissipation rate, and the turbulent coefficient. It was found that the main source of turbulence in the cloud is buoyancy whose contribution is described by the buoyancy production term (BPT). The shear production term (SPT) increases with height and reaches its maximum near cloud top, and so does BPT. In agreement with the behavior of BPT and SPT, turbulence in the lower cloud part (below the inversion level) is weak and hardly affects the processes of mixing and entrainment. The fact that BPT is larger than SPT determines many properties of cloud turbulence. For instance, the turbulence is nonisotropic, so the vertical component of TKE is substantially larger than the horizontal components. Another consequence of the fact that BPT is larger than STP manifests itself in the finding that the turbulence spectrum largely obeys the -11/5 Bolgiano–Obukhov scaling. The classical Kolmogorov -5/3 scaling dominates for the low part of a cloud largely at the dissolving stage of cloud evolution. Using the spectra obtained we evaluated an “effective” dissipation rate which increases with height from nearly zero at cloud base up to 20 cm 2 s -3 near cloud top. The coefficient of turbulent diffusion was found to increase with height and ranged from 5 m 2 s -1 near cloud base to 25 m 2 s -1 near cloud top. In conclusion, the possible role of turbulence in the process of lateral entrainment and mixing is discussed.

54 ENVIRONMENTAL SCIENCES↗