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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.

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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Comparison of cloud microphysical parameters derived from surface and satellite measurements during FIRE phase 2

Cloud microphysical properties are an important component in climate model parameterizations of water transport, cloud radiative exchange, and latent heat processes. Estimation of effective cloud particle size, liquid or ice water content, and optical depth from satellite-based instrumentation is needed to develop a climatology of cloud microphysical properties and to better understand and model cloud processes in atmospheric circulation. These parameters are estimated from two different surface data sets taken at Coffeyville, Kansas, during the First ISCCP Regional Experiment (FIRE) Phase-2 Intensive Field Observation (IFO) period (November 13 - December 7, 1991). Satellite data can also provide information about optical depth and effective particle size. This paper explores the combination of the FIRE-2 surface and satellite data to determine each of the cloud microphysical properties.

Young, David F.↗
DOE OSTI2016

On the relationships among cloud cover, mixed‐phase partitioning, and planetary albedo in GCMs

Abstract In this study, it is shown that CMIP5 global climate models (GCMs) that convert supercooled water to ice at relatively warm temperatures tend to have a greater mean‐state cloud fraction and more negative cloud feedback in the middle and high latitude Southern Hemisphere. We investigate possible reasons for these relationships by analyzing the mixed‐phase parameterizations in 26 GCMs. The atmospheric temperature where ice and liquid are equally prevalent (T5050) is used to characterize the mixed‐phase parameterization in each GCM. Liquid clouds have a higher albedo than ice clouds, so, all else being equal, models with more supercooled liquid water would also have a higher planetary albedo. The lower cloud fraction in these models compensates the higher cloud reflectivity and results in clouds that reflect shortwave radiation (SW) in reasonable agreement with observations, but gives clouds that are too bright and too few. The temperature at which supercooled liquid can remain unfrozen is strongly anti‐correlated with cloud fraction in the climate mean state across the model ensemble, but we know of no robust physical mechanism to explain this behavior, especially because this anti‐correlation extends through the subtropics. A set of perturbed physics simulations with the Community Atmospheric Model Version 4 (CAM4) shows that, if its temperature‐dependent phase partitioning is varied and the critical relative humidity for cloud formation in each model run is also tuned to bring reflected SW into agreement with observations, then cloud fraction increases and liquid water path (LWP) decreases with T5050, as in the CMIP5 ensemble.

58 GEOSCIENCES↗
NASA NTRS2011

Remote Sensing the Vertical Profile of Cloud Droplet Effective Radius, Thermodynamic Phase, and Temperature

Cloud-aerosol interaction is a key issue in the climate system, affecting the water cycle, the weather, and the total energy balance including the spatial and temporal distribution of latent heat release. Information on the vertical distribution of cloud droplet microphysics and thermodynamic phase as a function of temperature or height, can be correlated with details of the aerosol field to provide insight on how these particles are affecting cloud properties and their consequences to cloud lifetime, precipitation, water cycle, and general energy balance. Unfortunately, today's experimental methods still lack the observational tools that can characterize the true evolution of the cloud microphysical, spatial and temporal structure in the cloud droplet scale, and then link these characteristics to environmental factors and properties of the cloud condensation nuclei. Here we propose and demonstrate a new experimental approach (the cloud scanner instrument) that provides the microphysical information missed in current experiments and remote sensing options. Cloud scanner measurements can be performed from aircraft, ground, or satellite by scanning the side of the clouds from the base to the top, providing us with the unique opportunity of obtaining snapshots of the cloud droplet microphysical and thermodynamic states as a function of height and brightness temperature in clouds at several development stages. The brightness temperature profile of the cloud side can be directly associated with the thermodynamic phase of the droplets to provide information on the glaciation temperature as a function of different ambient conditions, aerosol concentration, and type. An aircraft prototype of the cloud scanner was built and flew in a field campaign in Brazil.

Martins, J. V.↗
NASA NTRS2020

A Machine Learning-Based Cloud Detection and Thermodynamic Phase Classification Algorithm using Passive Spectral Observations

We trained two Random Forest (RF) machine-learning models for cloud mask and cloud thermodynamic phase detection using spectral observations from VIIRS on Suomi NPP (SNPP). Observations from CALIOP were carefully selected to provide reference labels. The two RF models were trained for all-day and daytime-only conditions using a 4-year collocated VIIRS/CALIOP dataset from 2013 to 2016. Due to the orbit difference, the collocated CALIOP and SNPP VIIRS training samples cover a broad viewing zenith angle range, which is a great benefit to overall model performance. The all-day model uses 3 VIIRS infrared (IR) bands (8.6,11, and 12 μm) and the daytime model uses 5 Near-IR (NIR) and Shortwave-IR (SWIR) bands (0.86, 1.24, 1.38, 1.64 and 2.25 μm) together with the 3 IR bands to detect clear, liquid water, and ice cloud pixels. Up to 7 surface types, namely, ocean/water, forest, cropland, grassland, snow/ice, barren/desert, and shrubland, were considered separately to enhance performance for both models. Detection of cloudy pixels and thermodynamic phase with the two RF models were compared against collocated CALIOP products from 2017. It is shown that, with a conservative screening process that excludes the most challenging cloudy pixels for passive remote sensing, the two RF models have high accuracy rates in comparison with the CALIOP reference for both cloud detection and thermodynamic phase. Other existing SNPP VIIRS and Aqua MODIS cloud mask and phase products are also evaluated, with results showing that the two RF models and the MODIS MYD06 optical property phase product are the top 3 algorithms with respect to lidar observations during the daytime. During the nighttime, the RF all-day model works best for both cloud detection and phase, in particular for pixels over snow/ice surfaces. The present RF models can be extended to other similar passive instruments if training samples can be collected from CALIOP or other lidars. However, the quality of reference labels and potential sampling issues that may impact model performance would need further attention.

cloud detection↗
NASA NTRS1983

Aqueous-phase source of formic acid in clouds

The coupled gas- and aqueous-phase cloud chemistry of HCOOH were examined for controlling factors in the acidity of cloud and rainwater. Attention was given to the aqueous OH/HO2 system that yields an OH species that is highly reactive with other species, notably SO2 and the formaldehyde/formic acid complex. A numerical model was developed to simulate the cloud chemistry in the remote troposphere, with considerations given to CH4-CO-NO(x)-O3-H(x)O(y) system. It was determined that aqueous phase OH radicals can produce and destroy formic acid droplets in daylight conditions, as well as control formic acid levels in rainwater. It is sugested that the same types of reactions may be involved in the control of acetic acid and other organic acids.

Chameides, W. L.↗
NASA NTRS1986

The single scattering phase functions of Jupiter's clouds

The determination of the single scattering phase functions of Jupiter's clouds and a thin upper haze by Tomasko et al. was refined and extended to seven latitudes in blue and red light. The phase function is well-constrained by the Pioneer 10 and 11 photometric data sets. Multiple scattering models were computed to match the limb darkening at each latitude at up to 15 phase angles from 12 deg to 151 deg. Ground-based observations were used for absolute calibration and to extend the data to lower phase angles. The phase functions were parameterized using the double Henyey-Greenstein function. The three Henyey-Greenstein parameters and the single scattering albedo were determined using a non-linear least squares method for the haze and the clouds below. The phase functions derived for the northen zone and belt are remarkably similar to the phase functions of the corresponding regions in the south, with most of the differences in brightness of the northern and southern features resulting from minor differences in single scattering albedo. Analysis of the Equatorial Region is complicated by the presence of numerous small features, but the phase function required is generally similar to that seen in the more homogeneous regions. Details of the phase functions of the haze and clouds are presented, and the differences between the cloud phase functions at low and high latitudes in red and blue light are discussed.

Doose, L. R.↗
DOE OSTI2024

Dependence of Cloud Macrophysical Properties and Phase Distributions on Environmental Conditions Over the North Atlantic and Southern Ocean: Results From COMBLE and MARCUS

The accurate representation of Cold Air Outbreaks (CAOs) and affiliated mixed-phase boundary layer (BL) clouds in models is challenging. How BL cloud properties evolve during CAOs and their dependence on meteorological conditions is not well understood but is important for the simulation of Earth's energy budgets. Here the properties of polar BL clouds over the North Atlantic (NA) and Southern Ocean (SO) are compared using observations from the Measurements of Aerosol Radiation and CloUds over the SO (MARCUS) and CAOs in the Marine BL Experiment (COMBLE) conducted over the NA. MARCUS observations show a stronger BL inversion than COMBLE, with a higher mean EIS (estimated inversion strength)/LTS (lower tropospheric stability) of -0.03 K/13 K compared to COMBLE’s -3.2 K/9.3 K. 39% of CAOs observed during COMBLE were intense with M > 5 K, while MARCUS only had 1.3%. 78%/72% of clouds sampled in CAOs during COMBLE/MARCUS had cloud top heights <4 km. The mean BL cloud top height was over 400 m higher, and the BL was over 500 m deeper for M of 10 K compared to 0 K for both regions. MARCUS observed a 27% moister BL structure than COMBLE when M > 5 K due to stronger BL inversion trapping more moisture within the BL. Under the same LTS, EIS, and M conditions, MARCUS observed a 12% drier BL structure, and clouds were 46% more turbulent than COMBLE. During CAOs, 54% of single-layer BL clouds sampled during MARCUS had liquid-dominated bases compared to 39% during COMBLE.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

The use of an airborne lidar for mapping cirrus clouds in FIRE, phase 2

The Univ. of Washington (UW) and Georgia Tech have recently built a dual wavelength airborne lidar for operation on the UW's Convair C-131A research aircraft. This lidar was used in studying aerosols and clouds. These studies demonstrated the utility of airborne lidar in a variety of atmospheric research and prompt the suggestion that this facility be included in the next FIRE cirrus experiment. The vertically pointing airborne lidar would be used as a complement to ground based lidars. The airborne lidar would ensure extended coverage of IFO cases that develop upwind of the surface lidars or which miss the ground based lidars while still being the focus of satellite and aircraft in situ studies. The airborne lidar would help assure that cirrus clouds were simultaneously viewed by satellite, sampled by aircraft, and structurally characterized by lidar. System specifications are listed and a schematic is shown of the lidar system aboard the C-131A.

Radke, Lawrence F.↗
DOE OSTI2018

(GO) 2 -SIM: a GCM-oriented ground-observation forward-simulator framework for objective evaluation of cloud and precipitation phase

General circulation model (GCM) evaluation using ground-based observations is complicated by inconsistencies in hydrometeor and phase definitions. Here we describe (GO) 2 -SIM, a forward simulator designed for objective hydrometeor-phase evaluation, and assess its performance over the North Slope of Alaska using a 1-year GCM simulation. For uncertainty assessment, 18 empirical relationships are used to convert model grid-average hydrometeor (liquid and ice, cloud, and precipitation) water contents to zenith polarimetric micropulse lidar and Ka-band Doppler radar measurements, producing an ensemble of 576 forward-simulation realizations. Sensor limitations are represented in forward space to objectively remove from consideration model grid cells with undetectable hydrometeor mixing ratios, some of which may correspond to numerical noise. Phase classification in forward space is complicated by the inability of sensors to measure ice and liquid signals distinctly. However, signatures exist in lidar–radar space such that thresholds on observables can be objectively estimated and related to hydrometeor phase. The proposed phase-classification technique leads to misclassification in fewer than 8 % of hydrometeor-containing grid cells. Such misclassifications arise because, while the radar is capable of detecting mixed-phase conditions, it can mistake water- for ice-dominated layers. However, applying the same classification algorithm to forward-simulated and observed fields should generate hydrometeor-phase statistics with similar uncertainty. Alternatively, choosing to disregard how sensors define hydrometeor phase leads to frequency of occurrence discrepancies of up to 40 %. So, while hydrometeor-phase maps determined in forward space are very different from model reality they capture the information sensors can provide and thereby enable objective model evaluation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

(GO)2-SIM: a GCM-Oriented Ground-Observation Forward-Simulator Framework for Objective Evaluation of Cloud and Precipitation Phase

General circulation model (GCM) evaluation using ground-based observations is complicated by inconsistencies in hydrometeor and phase definitions. Here we describe (GO)2-SIM, a forward simulator designed for objective hydrometeor-phase evaluation, and assess its performance over the North Slope of Alaska using a 1-year GCM simulation. For uncertainty assessment, 18 empirical relationships are used to convert model grid-average hydrometeor (liquid and ice, cloud, and precipitation) water contents to zenith polarimetric micropulse lidar and Ka-band Doppler radar measurements, producing an ensemble of 576 forward-simulation realizations. Sensor limitations are represented in forward space to objectively remove from consideration model grid cells with undetectable hydrometeor mixing ratios, some of which may correspond to numerical noise.Phase classification in forward space is complicated by the inability of sensors to measure ice and liquid signals distinctly. However, signatures exist in lidar–radar space such that thresholds on observables can be objectively estimated and related to hydrometeor phase. The proposed phase-classification technique leads to misclassification in fewer than 8% of hydrometeor-containing grid cells. Such misclassifications arise because, while the radar is capable of detecting mixed-phase conditions, it can mistake water- for ice-dominated layers. However, applying the same classification algorithm to forward-simulated and observed fields should generate hydrometeor-phase statistics with similar uncertainty. Alternatively, choosing to disregard how sensors define hydrometeor phase leads to frequency of occurrence discrepancies of up to 40%. So, while hydrometeor-phase maps determined in forward space are very different from model "reality" they capture the information sensors can provide and thereby enable objective model evaluation.

Lamer, K.↗
NASA NTRS1986

MIE Lidar proposed for the German Space Shuttle Mission D2

Firm plans for a second German Spacelab mission (D2-mission), originally scheduled for late 1988 is basically a zero-g mission, but will also include earth observation experiments. On board the D2-facility will allow performance of a number of different measurements with the goal to obtain performance data (cloud top heights, height of the planetary boundary layer, optical thickness, and cloud base height of thin and medium thick clouds, ice/water phase discriminatin for clouds, tropopause height, tropaspheric height, tropospheric aerosols, and stratospheric aerosols.

Renger, W.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-20489-DND

Using CALIPSO cloud observations from 2008 to 2014, this study investigate the correlation between changes in galactic cosmic ray and cloud properties (cloud cover, cloud thermodynamic phase, and water cloud droplet number concentration) globally and regionally.

Yongxiang Hu↗
NASA NTRS2019

Strong Dependence of Atmospheric Feedbacks on Mixed-Phase Microphysics and Aerosol-Cloud Interactions in HadGEM3

We analyze the atmospheric processes that explain the large changes in radiative feed-backs between the two latest climate configurations of the Hadley Centre Global Environmental model. We use a large set of atmosphere-only climate-change simulations (amip and amip-p4K) to separate the contributions to the differences in feedback parameter from all the atmospheric model developments between the two latest model configurations. We show that the differences are mostly driven by changes in the shortwave cloud radiative feedback in the midlatitudes, mainly over the Southern Ocean. Two new schemes explain most of the differences: the introduction of a new aerosol scheme; and the development of a new mixed-phase cloud scheme. Both schemes reduce the strength of the pre-existing shortwave negative cloud feedback in the midlatitudes. The new aerosol scheme dampens a strong aerosol-cloud interaction, and it also suppresses a negative clear-sky shortwave feedback. The mixed-phase scheme increases the amount of cloud liquid water path (LWP) in the present-day, thereby reducing the radiative effciency of the increase of LWP in the warmer climate. It also enhances a strong, pre-existing, positive cloud fraction feedback. We assess the realism of the changes by comparing present-day simulations against observations, and discuss avenues that could help constrain the relevant processes.

HadGEM3↗
NASA NTRS1978

The phase function of Venus cloud particles from Mariner 10 data

Mariner 10 images of Venus taken at several phase angles were photometrically reduced. The analysis shows that the phase function of the cloud particles is not isotropic, as had been deduced earlier from the brightness distribution on spacecraft images taken at a single phase angle, but has a broad minimum near 60 deg and is forward-scattering. The scattering properties are in quantitative agreement with previous deductions from earth-based polarization measurements by Hansen and his associates.

Hapke, B.↗
DOE OSTI2025

Developing a Lagrangian Frame Transformation on Satellite Data to Study Cloud Microphysical Transitions in Arctic Marine Cold Air Outbreaks

Abstract Arctic marine cold air outbreaks (CAOs) generate distinct and dynamic cloud regimes due to intense air‐sea interactions. To understand the temporal evolution of CAO cloud properties and compare different CAO events, a Lagrangian perspective is particularly useful. We developed a novel technique that enables the conversion of inherently Eulerian satellite data into a Lagrangian framework, combining the broad spatiotemporal coverage of satellite observations with the advantages of Lagrangian tracking. This technique was applied to eight CAO cases associated with a recent field campaign. Our results reveal a striking contrast among the cases in terms of cloud‐top phase transitions, providing new insights into the evolution of CAO cloud properties.

Lagrangian analysis↗