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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
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↗
NASA NTRS2002

Mesoscale Convective Systems During SCSMEX: Simulations with a Regional Climate Model and a Cloud-Resolving Model

The South China Sea Monsoon Experiment (SCSMEX) was conducted in May-June 1998. One of its major objectives is to better understand the key physical processes for the onset and evolution of the summer monsoon over Southeast Asia and southern China (Lau et al. 2000). Multiple observation platforms (e.g., soundings, Doppler radar, ships, wind seafarers, radiometers, etc.) during SCSMEX provided a first attempt at investigating the detailed characteristics of convection and circulation changes, associated with monsoons over the South China Sea region. SCSMEX also provided precipitation derived from atmospheric budgets (Johnson and Ciesielski 2002) and comparison to those obtained from the Tropical Rainfall Measuring Mission (TRMM). In this paper, a regional climate model and a cloud-resolving model are used to perform multi-day integrations to understand the precipitation processes associated with the summer monsoon over Southeast Asia and southern China. The regional climate model is used to understand the soil - precipitation interaction and feedback associated with a flood event that occurred in and around China's Atlantic River during SCSMEX. Sensitivity tests on various land surface models, cumulus parameterization schemes (CASE), sea surface temperature (SST) variations and midlatitude influences are also performed to understand the processes associated with the onset of the monsoon over the S. China Sea during SCSMEX. Cloud-resolving models (CRMs) use more sophisticated and physically realistic parameterizations of cloud microphysical processes with very fine spatial and temporal resolution. One of the major characteristics of CRMs is an explicit interaction between clouds, radiation and the land/ocean surface. It is for this reason that GEWEX (Global Energy and Water Cycle Experiment) has formed the GCSS (GEWEX Cloud System Study) expressly for the purpose of improving the representation of the moist processes in large-scale models using CRMs. The Goddard Cumulus Ensemble (GCE) model is a CRM and is used to simulate convective systems associated with the onset of the South China Sea monsoon in 1998. The BRUCE model includes the same land surface model, cloud physics, and radiation scheme used in the regional climate model. A comparison between the results from the GCE model and regional climate model is performed.

Tao, W. K.↗
NASA NTRS2003

Large-eddy Simulation of Stratocumulus-topped Atmospheric Boundary Layers with Dynamic Subgrid-scale Models

The objective of the present study is to evaluate the dynamic procedure in LES of stratocumulus topped atmospheric boundary layer and assess the relative importance of subgrid-scale modeling, cloud microphysics and radiation modeling on the predictions. The simulations will also be used to gain insight into the processes leading to cloud top entrainment instability and cloud breakup. In this report we document the governing equations, numerical schemes and physical models that are employed in the Goddard Cumulus Ensemble model (GCEM3D). We also present the subgrid-scale dynamic procedures that have been implemented in the GCEM3D code for the purpose of the present study.

Senocak, Inane↗
NASA NTRS2008

Application of the NASA A-Train to Evaluate Clouds Simulated by the Weather Research and Forecast Model

The CloudSat Mission, part of the NASA A-Train, is providing the first global survey of cloud profiles and cloud physical properties, observing seasonal and geographical variations that are pertinent to evaluating the way clouds are parameterized in weather and climate forecast models. CloudSat measures the vertical structure of clouds and precipitation from space through the Cloud Profiling Radar (CPR), a 94 GHz nadir-looking radar measuring the power backscattered by clouds as a function of distance from the radar. One of the goals of the CloudSat mission is to evaluate the representation of clouds in forecast models, thereby contributing to improved predictions of weather, climate and the cloud-climate feedback problem. This paper highlights potential limitations in cloud microphysical schemes currently employed in the Weather Research and Forecast (WRF) modeling system. The horizontal and vertical structure of explicitly simulated cloud fields produced by the WRF model at 4-km resolution are being evaluated using CloudSat observations in concert with products derived from MODIS and AIRS. A radiative transfer model is used to produce simulated profiles of radar reflectivity given WRF input profiles of hydrometeor mixing ratios and ambient atmospheric conditions. The preliminary results presented in the paper will compare simulated and observed reflectivity fields corresponding to horizontal and vertical cloud structures associated with midlatitude cyclone events.

Molthan, Andrew L.↗
NASA NTRS2005

The Impact of Surface Albedo on the Retrievals of Low-Level Stratus Cloud Properties: An Updated Parameterization

An updated version of Dong et al. (1998, hereafter D98) parameterization is developed from a total of 40 hours of data with a broad range of surface albedos (0.1-0.8) during the 2000-2002 winter seasons at the DOE ARM SGP site. The updated parameterization includes the impact of surface albedo on the retrievals of stratus cloud microphysical and radiative properties, and has a significant improvement over D98 when surface albedo is high. Comparing the retrievals, the cloud-droplet effective radii (r(sub e)) calculated from the updated parameterization have a higher correlation coefficient (0.733) and lower Root-Mean-Square (RMS) error (1.74 m or 17.4%) than those (0.602, 4.0 m or 40%) from the D98. The cloud albedos also have a much higher correlation coefficient (0.983) and lower RMS (3%) than those 0.465, 26%) from the D98. The upper limit of surface albedo is 0.3 in applying the D98.

Dong, Xiquan↗
NASA NTRS2009

Radiative Effects of African Dust and Smoke Observed from CERES and CALIOP Data

Cloud and aerosol effects have a significant impact on the atmospheric radiation budget in the Tropical Atlantic because of the spatial and temporal extent of desert dust and smoke from biomass burning in the atmosphere. The influences of African dust and smoke aerosols on cloud radiative properties over the Tropical Atlantic Ocean were analyzed for the month of July for three years (2006-2008) using collocated data collected by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Clouds and the Earth s Radiant Energy System (CERES) instruments on the CALIPSO and Aqua satellites. Aerosol layer height and type can be more accurately determined using CALIOP data, through parameters such as cloud and aerosol layer height, optical depth and depolarization ratio, than data from atmospheric imagers used in previous cloud-aerosol interaction studies. On average, clouds below 5 km had a daytime instantaneous shortwave (SW) radiative flux of 270.2 +/- 16.9 W/sq m and thin cirrus clouds had a SW radiative flux of 208.0 +/- 12.7 W/sq m. When dust aerosols interacted with clouds below 5 km, as determined from CALIPSO, the SW radiative flux decreased to 205.4 +/- 13.0 W/sq m. Similarly, smoke aerosols decreased the SW radiative flux of low clouds to a value of 240.0 +/- 16.6 W/sq m. These decreases in SW radiative flux were likely attributed to the aerosol layer height and changes in cloud microphysics. CALIOP lidar observations, which more accurately identify aerosol layer height than passive instruments, appear essential for better understanding of cloud-aerosol interactions, a major uncertainty in predicting the climate system.

Yorks, John E.↗
NASA NTRS2015

Cloud Properties of CERES-MODIS Edition 4 and CERES-VIIRS Edition 1

The Clouds and Earth's Radiant Energy System (CERES) analyzes MODerate-resolution Imaging Spectroradiometer (MODIS) data and Visible Infrared Imaging Radiometer Suite (VIIRS) to derive cloud properties that are combine with aerosol and CERES broadband flux data to create a multi-parameter data set for climate study. CERES has produced over 15 years of data from Terra and over 13 years of data from Aqua using the CERES-MODIS Edition-2 cloud retrieval algorithm. A recently revised algorithm, CERESMODIS Edition 4, has been developed and is now generating enhanced cloud data for climate research (over 10 years for Terra and 8 years for Aqua). New multispectral retrievals of properties are included along with a multilayer cloud retrieval system. Cloud microphysical properties are reported at 3 wavelengths, 0.65, 1.24, and 2.1 microns to enable better estimates of the vertical profiles of cloud water contents. Cloud properties over snow are retrieved using the 1.24-micron channel. A new CERES-VIIRS cloud retrieval package was developed for the VIIRS spectral complement and is currently producing the CERES-VIIRS Edition 1 cloud dataset. The results from CERES-MODIS Edition 4 and CERES-VIIRS Edition 1 are presented and compared with each other and other datasets, including CALIPSO, CloudSat and the CERES-MODIS Edition-2 results.

Sun-Mack, Sunny↗
DOE OSTI2020

Confronting the Challenge of Modeling Cloud and Precipitation Microphysics

In the atmosphere, microphysics refers to the microscale processes that affect cloud and precipitation particles and is a key linkage among the various components of Earth’s atmospheric water and energy cycles. The representation of microphysical processes in models continues to pose a major challenge leading to uncertainty in numerical weather forecasts and climate simulations. In this paper, the problem of treating microphysics in models is divided into two parts: i) how to represent the population of cloud and precipitation particles, given the impossibility of simulating all particles individually within a cloud, and ii) uncertainties in the microphysical process rates owing to fundamental gaps in knowledge of cloud physics. The recently-developed Lagrangian particle-based method is advocated as a way to address several conceptual and practical challenges of representing particle populations using traditional bulk and bin microphysics parameterization schemes. For addressing critical gaps in cloud physics knowledge, sustained investment for observational advances from laboratory experiments, new probe development, and next-generation instruments in space is needed. Greater emphasis on laboratory work, which has apparently declined over the past several decades relative to other areas of cloud physics research, is argued to be an essential ingredient for improving process-level understanding. More systematic use of natural cloud and precipitation observations to constrain microphysics schemes is also advocated. Because it is generally difficult to quantify individual microphysical process rates from these observations directly, this presents an inverse problem that can be viewed from the standpoint of Bayesian statistics. Following this idea, a probabilistic framework is proposed that combines elements from statistical and physical modeling. Besides providing rigorous constraint of schemes, there is an added benefit of quantifying uncertainty systematically. Finally, a broader hierarchical approach is proposed to accelerate improvements in microphysics schemes, leveraging the advances described in this paper related to process modeling (using Lagrangian particle-based schemes), laboratory experimentation, cloud and precipitation observations, and statistical methods.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2009

Cold Season QPF: Sensitivities to Snow Parameterizations and Comparisons to NASA CloudSat Observations

As operational numerical weather prediction is performed at increasingly finer spatial resolution, precipitation traditionally represented by sub-grid scale parameterization schemes is now being calculated explicitly through the use of single- or multi-moment, bulk water microphysics schemes. As computational resources grow, the real-time application of these schemes is becoming available to a broader audience, ranging from national meteorological centers to their component forecast offices. A need for improved quantitative precipitation forecasts has been highlighted by the United States Weather Research Program, which advised that gains in forecasting skill will draw upon improved simulations of clouds and cloud microphysical processes. Investments in space-borne remote sensing have produced the NASA A-Train of polar orbiting satellites, specially equipped to observe and catalog cloud properties. The NASA CloudSat instrument, a recent addition to the A-Train and the first 94 GHz radar system operated in space, provides a unique opportunity to compare observed cloud profiles to their modeled counterparts. Comparisons are available through the use of a radiative transfer model (QuickBeam), which simulates 94 GHz radar returns based on the microphysics of cloudy model profiles and the prescribed characteristics of their constituent hydrometeor classes. CloudSat observations of snowfall are presented for a case in the central United States, with comparisons made to precipitating clouds as simulated by the Weather Research and Forecasting Model and the Goddard single-moment microphysics scheme. An additional forecast cycle is performed with a temperature-based parameterization of the snow distribution slope parameter, with comparisons to CloudSat observations provided through the QuickBeam simulator.

Molthan, A. L.↗
DOE OSTI2018

Comparisons of Ice Water Path in Deep Convective Systems Among Ground-Based, GOES, and CERES-MODIS Retrievals

Retrievals of convective cloud microphysical properties based on passive satellite imagery are difficult. To help quantify their uncertainties, ice water paths (IWPs) retrieved from the NASA Clouds and the Earth's Radiant Energy System project using Geostationary Operational Environmental Satellite (GOES) and Terra/Aqua MODerate-resolution Imaging Spectroradiometer observations are compared with IWPs retrieved from Next-Generation Radar (NEXRAD) observations over a large domain (32°N to 40°N and 105°W to 91°W) during the 2011 Midlatitude Continental Convective Clouds Experiment field campaign. Based on comparisons of pixel-level (4 km × 4 km) daytime IWP retrievals from NEXRAD and GOES, it is found that NEXRAD- and GOES-retrieved mean IWPs are 2.03 and 1.83 kg m -2 , respectively, for ice-phase cloud in thick anvil area. Their mean difference of 0.20 kg m -2 (with 95% confidence interval: 0.14-0.26 kg m -2 ) is within the uncertainty of NEXRAD retrievals. However, the low correlation between pixel-to-pixel comparisons indicates a large variation in GOES-retrieved IWP. For mixed-phase clouds in thick anvil areas, in addition to IWPs, total water paths (TWPs, sum of ice and liquid water path) are estimated with aid of aircraft measurements for NEXRAD retrievals and corrected using a TWP parameterization for GOES retrievals. The mean values of estimated TWPs from NEXRAD (corrected using aircraft in situ measurements) and GOES are similar. GOES and Clouds and the Earth's Radiant Energy System-MODerate-resolution Imaging Spectroradiometer-retrieved IWPs/TWPs generally do not exceed 5 kg m - 2. Large differences and low correlations exist between satellite and NEXRAD retrievals in stratiform rain areas. Possible reasons for the differences between retrievals are discussed.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

A further study of cumulus interactions and mergers - Three-dimensional simulations with trajectory analysis

Cumulus processes involved in the interaction and merging of clouds under the influence of different imposed conditions (including large-scale lifting forcing, environmental wind shear, and cloud microphysical processes) were studied using simulations with a three-dimensional model. The design of the study was to generate several convective clouds randomly inside the model domain, and then to observe and analyze the interactions and merging between the simulated clouds. Ten merged clouds were identified. Seven of these, each involving two previously separated clouds, generally lie along a line parallel to the initial environmental wind shear vector, while one (also a two-cloud system) lies along a line perpendicular to the wind shear vector prior to merging. The remaining two merging systems involve three parent clouds each; they are a combination of parallel and perpendicular cells. The merging mechanisms associated with three-cloud merging cases are studied by examining the temperature, pressure, and wind fields prior to, during, and following the merging.

Tao, Wei-Kuo↗
NASA NTRS1990

The effects of van der Waals attractions on cloud droplet growth by coalescence

The inclusion of van der Waals attractions in the interaction between cloud droplets has been recently shown to significantly increase the collision efficiencies of the smaller droplets. In the current work, these larger values for the collision efficiencies are used in a population dynamics model of the droplet size distribution evolution with time, in hopes of at least partially resolving the long-standing paradox in cloud microphysics that predicted rates of the onset of precipitation are generally much lower than those which are observed. Evolutions of several initial cloud droplet spectra have been tracked in time. Size evolutions are compared as predicted from the use of collision efficiencies computed using two different models to allow for droplet-droplet contact: one which considers slip flow effects only, and one which considers the combined effects of van der Waals forces and slip flow. The rate at which the droplet mass density function shifts to larger droplet sizes is increased by typically 20-25 percent, when collision efficiencies which include van der Waals forces are used.

Rogers, Jan R.↗
DOE OSTI2022

Relationships between Cloud Droplet Spectral Relative Dispersion and Entrainment Rate and Their Impacting Factors

Cloud microphysical properties are significantly affected by entrainment and mixing processes. However, it is unclear how the entrainment rate affects the relative dispersion of cloud droplet size distribution. Previously, the relationship between relative dispersion and entrainment rate was found to be positive or negative. To reconcile the contrasting relationships, the Explicit Mixing Parcel Model is used to determine the underlying mechanisms. When evaporation is dominated by small droplets, and the entrained environmental air is further saturated during mixing, the relationship is negative. However, when the evaporation of big droplets is dominant, the relationship is positive. Whether or not the cloud condensation nuclei are considered in the entrained environmental air is a key factor as condensation on the entrained condensation nuclei is the main source of small droplets. However, if cloud condensation nuclei are not entrained, the relationship is positive. If cloud condensation nuclei are entrained, the relationship is dependent on many other factors. High vertical velocity, relative humidity of environmental air, liquid water content, and low droplet number concentration are more likely to cause the negative relationship since new saturation is easier to achieve by evaporation of small droplets. Further, the signs of the relationship are not strongly affected by the turbulence dissipation rate, but the higher dissipation rate causes the positive relationship more significant for a larger entrainment rate. A conceptual model is proposed to reconcile the contrasting relationships. This work enhances the understanding of relative dispersion and lays a foundation for the quantification of entrainment-mixing mechanisms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

An observational study of entrainment rate in deep convection

This study estimates entrainment rate and investigates its relationships with cloud properties in 156 deep convective clouds based on in-situ aircraft observations during the TOGA-COARE (Tropical Ocean Global Atmosphere Coupled Ocean Atmosphere Response Experiment) field campaign over the western Pacific. To the authors’ knowledge, this is the first study on the probability density function of entrainment rate, the relationships between entrainment rate and cloud microphysics, and the effects of dry air sources on the calculated entrainment rate in deep convection from an observational perspective. Results show that the probability density function of entrainment rate can be well fitted by lognormal, gamma or Weibull distribution, with coefficients of determination being 0.82, 0.85 and 0.80, respectively. Entrainment tends to reduce temperature, water vapor content and moist static energy in cloud due to evaporative cooling and dilution. Inspection of the relationships between entrainment rate and microphysical properties reveals a negative correlation between volume-mean radius and entrainment rate, suggesting the potential dominance of homogeneous mechanism in the clouds examined. The entrainment rate and environmental water vapor content show similar tendencies of variation with the distance of the assumed environmental air to the cloud edges. Their variation tendencies are non-monotonic due to the relatively short distance between adjacent clouds.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1998

Tropical Oceanic Precipitation Processes over Warm Pool: 2D and 3D Cloud Resolving Model Simulations

Rainfall is a key link in the hydrologic cycle as well as the primary heat source for the atmosphere, The vertical distribution of convective latent-heat release modulates the large-scale circulations of the tropics, Furthermore, changes in the moisture distribution at middle and upper levels of the troposphere can affect cloud distributions and cloud liquid water and ice contents. How the incoming solar and outgoing longwave radiation respond to these changes in clouds is a major factor in assessing climate change. Present large-scale weather and climate models simulate cloud processes only crudely, reducing confidence in their predictions on both global and regional scales. One of the most promising methods to test physical parameterizations used in General Circulation Models (GCMS) and climate models is to use field observations together with Cloud Resolving Models (CRMs). The CRMs use more sophisticated and physically realistic parameterizations of cloud microphysical processes, and allow for their complex interactions with solar and infrared radiative transfer processes. The CRMs can reasonably well resolve the evolution, structure, and life cycles of individual clouds and cloud systems, The major objective of this paper is to investigate the latent heating, moisture and momenti,im budgets associated with several convective systems developed during the TOGA COARE IFA - westerly wind burst event (late December, 1992). The tool for this study is the Goddard Cumulus Ensemble (CCE) model which includes a 3-class ice-phase microphysical scheme, The model domain contains 256 x 256 grid points (using 2 km resolution) in the horizontal and 38 grid points (to a depth of 22 km depth) in the vertical, The 2D domain has 1024 grid points. The simulations are performed over a 7 day time period. We will examine (1) the precipitation processes (i.e., condensation/evaporation) and their interaction with warm pool; (2) the heating and moisture budgets in the convective and stratiform regions; (3) the cloud (upward-downward) mass fluxes in convective and stratiform regions; (4) characteristics of clouds (such as cloud size, updraft intensity and cloud lifetime) and the comparison of clouds with Radar observations. Differences and similarities in organization of convection between simulated 2D and 3D cloud systems. Preliminary results indicated that there is major differences between 2D and 3D simulated stratiform rainfall amount and convective updraft and downdraft mass fluxes.

Tao, W.- K.↗
DOE OSTI2023

What Are the Similarities and Differences in Marine Boundary Layer Cloud and Drizzle Microphysical Properties During the ACE–ENA and MARCUS Field Campaigns?

This study compares macrophysical and microphysical properties of single-layered, liquid-dominant MBL clouds from the Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) (above 60°S) and the ARM East North Atlantic (ENA) site during the Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) field campaign. A total of 1,136 (16.5% of clouds) and 6,034 5-min cloud samples are selected from MARCUS and ARM ENA in this study. MARCUS clouds have higher cloud-top heights, thicker cloud layers, larger liquid water path, and colder cloud temperatures than ENA. Thinner, warmer MBL clouds at ENA can contain higher layer-mean liquid water content due to higher cloud and ocean surface temperatures along with greater precipitable water vapor (PWV). MARCUS has a higher drizzle frequency rate (71.8%) than ENA (45.1%). Retrieved cloud and drizzle microphysical properties from each field campaign show key differences. MARCUS clouds feature smaller cloud droplets, whereas ENA clouds have larger cloud droplets, especially at the upper region of the cloud. From cloud top to cloud base, drizzle drop sizes increase while number concentrations decrease. Drizzle drop radius and number concentration decrease from cloud base to drizzle base due to net evaporation, and MARCUS' lower specific humidity leads to a higher drizzle base than ENA. In conclusion, the broader surface pressure and lower tropospheric stability (LTS) distributions during MARCUS have demonstrated that there are different synoptic patterns for selected cases during MARCUS with less PWV, while ENA is dominated by high pressure systems with nearly doubled PWV.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Radiative Energy Balance in the Tropical Tropopause Layer: An Investigation with ARM Data

The overall objective of this project is to use the ARM observational data to improve our understanding of cloud-radiation effects in the tropical tropopause layer (TTL), which is crucial for improving the simulation and prediction of climate and climate change. In last four and half years, we have been concentrating on (i) performing the comparison of the ice cloud properties from the ground-based lidar observations with those from the satellite CALIPSO lidar observations at the ARM TWP sites; (ii) analyzing TTL cirrus and its relation to the tropical planetary waves; (iii) calculating the radiative heating rates using retrieved cloud microphysical properties by combining the ground-based lidar and radar observations at the ARM TWP sites and comparing the results with those using cloud properties retrieved from CloudSat and CALIPSO observations; (iv) comparing macrophysical properties of tropical cirrus clouds from the CALIPSO satellite and from ground-based micropulse and Raman lidar observations; (v) improving the parameterization of optical properties of cirrus clouds with small effective ice particle sizes; and (vi) evaluating the enhanced maximum warming in the tropical upper troposphere simulated by the GCMs. The main results of our research efforts are reported in the 12 referred journal publications that acknowledge the DOE Grant No. DE-FG02-09ER64769.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

Cloud optical parameters as derived from the multispectral cloud radiometer

Simultaneous measurements of the liquid water content and particle size have assumed an important role in cloud physics as they help elucidate the mechanism of cloud particle formation and the mechanism of air mass-mixing in stratus clouds. Such measurements can reveal the modification of cloud air masses by anthropogenic aerosol particles (Coakley et al. 1987, Durkee 1989). Studies of the climatic impact of these modification processes on cloud microphysics seems to be urgent for understanding mechanisms of climate change. General Circulation Model (GCM) simulations can be improved by introducing a parameterization of cloud optical properties in terms of integrated liquid water content (liquid water path) and particle size (Slingo 1989). Motivated by the above mentioned circumstances, remote sensing techniques were developed for simultaneously retrieving the cloud optical thickness and effective particle radius, from which the liquid water path can be inferred. Statistical features of the cloud optical thickness (or liquid water path) and effective particle size for marine stratocumulus clouds are presented. These results were obtained during 4 days (7, 10, 13, and 16 July 1987) of observations with the Multispectral Cloud Radiometer (ER-2) and the Thematic Mapper (LANDSAT-5) during the First ISCCP Regional Experiment (FIRE).

Nakajima, Teruyuki↗