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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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NASA NTRS2006

Satellite-Based Assessment of Possible Dust Aerosols Semi-Direct Effect on Cloud Water Path over East Asia

The semi-direct effects of dust aerosols are analyzed over eastern Asia using 2 years (June 2002 to June 2004) of data from the Clouds and the Earth s Radiant Energy System (CERES) scanning radiometer and MODerate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite, and 18 years (1984 to 2001) of International Satellite Cloud Climatology Project (ISCCP) data. The results show that the water path of dust-contaminated clouds is considerably smaller than that of dust-free clouds. The mean ice water path (IWP) and liquid water path (LWP) of dusty clouds are less than their dust-free counterparts by 23.7% and 49.8%, respectively. The long-term statistical relationship derived from ISCCP also confirms that there is significant negative correlation between dust storm index and ISCCP cloud water path. These results suggest that dust aerosols warm clouds, increase the evaporation of cloud droplets and further reduce cloud water path, the so-called semi-direct effect. The semi-direct effect may play a role in cloud development over arid and semi-arid areas of East Asia and contribute to the reduction of precipitation.

Huang, Jianping↗
NASA NTRSDate not supplied

Implications of using MERRA-2 cloud water in aerosol wet scavenging for Pb-210 surface concentrations and vertical profiles in GEOS-Chem

Precipitation scavenging is the dominant loss process for a whole suite of aerosols but model parameterizations of this process are highly uncertain, substantially contributing to large uncertainties in the simulated loadings and radiative forcing of aerosols. Lead-210 (210Pb, radioactive half-life of 22.3 years) is produced by radioactive decay of soil-emitted gaseous 222Rn. It attaches to ambient submicron aerosols and is subject to precipitation scavenging processes. Liu et al. [2001] estimated the global mean lifetime of tropospheric 210Pb aerosols to be ~9 days using the GEOS-Chem model. Luo et al. [2019, 2020] provided an option to use MERRA-2 cloud water in the model aerosol scavenging scheme. In this study, we examine the impact of this revision on 210Pb simulations and compare results with climatological observations of 210Pb surface and UT/LS concentrations, as well as aircraft profile measurements from eleven NASA field missions.

Bo Zhang↗
NASA NTRS2021

Joint cloud water path and rainwater path retrievals from airborne ORACLES observations

This study presents a new algorithm that combines W-band reflectivity measurements from the Airborne Precipitation Radar – third generation (APR-3) passive radiometric cloud optical depth and effective radius retrievals from the Research Scanning Polarimeter (RSP) to estimate total liquid water path in warm clouds and identify the contributions from cloud water path (CWP) and rainwater path (RWP). The resulting CWP estimates are primarily determined by the optical depth input, although reflectivity measurements contribute ∼10 %–50 % of the uncertainty due to attenuation through the profile. Uncertainties in CWP estimates across all conditions are 25 % to 35 %, while RWP uncertainty estimates frequently exceed 100 %. Two-thirds of all radar-detected clouds observed during the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign that took place from 2016–2018 over the southeast Atlantic Ocean have CWP between 41 and 168 g/sq. m and almost all CWPs (99 %) between 6 to 445 g/sq. m. RWP, by contrast, typically makes up a much smaller fraction of total liquid water path (LWP), with more than 70 % of raining clouds having less than 10 g/sq. m of rainwater. In heavier warm rain (i.e., rain rate exceeding 40 mm/h or 1000 mm/d), however, RWP is observed to exceed 2500 g/sq. m. CWP (RWP) is found to be approximately 30 g/sq. m (7 g/sq. m) larger in unstable environments compared to stable environments. Surface precipitation is also more than twice as likely in unstable environments. Comparisons against in situ cloud microphysical probe data spanning the range of thermodynamic stability and meteorological conditions encountered across the southeast Atlantic basin demonstrate that the combined APR-3 and RSP dataset enable a robust joint cloud–precipitation retrieval algorithm to support future ORACLES precipitation susceptibility and cloud–aerosol–precipitation interaction studies.

algorithm↗
NASA NTRS1990

A scheme for parameterizing ice-cloud water content in general circulation models

The optical properties of ice clouds are a primary issue for climate and climate change. Evaluating these optical properties in three-dimensional models for studying climate will require a method to calculate the ice water content of such clouds. A procedure is developed to parameterize ice water content as a function of large-scale meteorological characteristics for use in circulation models in which the ice water content is not calculated by means of a three-dimensional prognostic equation for condensed water. The technique identifies large-scale flows in which ice clouds exist and calculates their ice water content by reconstructing the trajectory associated with cloud formation. As the cloud forms, its ice content changes both by deposition of ice from water vapor and by ice removal by sedimentation. The sedimentation process is found to modify significantly the ice water content expected from deposition alone. Ice water contents predicted by the parameterization are compared with aircraft observations collected in the middle latitudes and the tropics, and show reasonable agreement over four orders-of-magnitude of ice water content. A parameterization for the sublimation of ice crystals settling into ice-subsaturated environments is also presented.

Heymsfield, Andrew J.↗
NASA NTRSDate not supplied

Remote Sensing of Clouds, Water Vapor, and Near-Surface Winds Under Various Aerosol Conditions During CAMP2Ex

The Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) field campaign took place from August – October 2019. CAMP2Ex science objectives include understanding aerosol-cloud interaction under various Meteorological conditions, and how these Meteorological phenomena affect aerosol distribution in the atmosphere. Numerous instruments were flown on the National Aeronautics and Space Administration (NASA) P-3 aircraft during 19 CAMP2Ex science flights, including the Advanced Microwave Precipitation Radiometer (AMPR) the Airborne Third Generation Precipitation Radar (APR-3), and the High Spectral Resolution Lidar 2 (HSRL2). Geophysical retrieval equations for cloud liquid water, columnar water vapor, and near-surface wind speed using AMPR brightness temperatures have been derived and tested using CAMP2Ex data. Water vapor and wind speed retrievals have been validated using in situ observations, such as dropsondes and shipborne instruments. This presentation will demonstrate these AMPR-based retrievals during CAMP2Ex, including discussions of retrieval uncertainties. Specific CAMP2Ex flights will be presented in greater detail, including inferences of other Meteorological phenomena in clear air and around precipitating and non-precipitating clouds, such as background wind speeds and potential identification of gust fronts. These analyses will be supplemented with APR-3 reflectivity and Doppler velocity data to infer microphysical processes occurring within and around selected clouds of interest. In cases where multiple remote-sensing measurements were obtained for the same cloud, a time-evolution analysis of these features may be performed. Throughout these analyses, HSRL2 data will be used to quantify aerosol properties beneath the P-3, and variations in the AMPR/APR-3 observations with respect to various aerosol conditions will be discussed.

Corey Amiot↗
NASA NTRS1994

Simulations of the effects of water vapor, cloud liquid water, and ice on AMSU moisture channel brightness temperatures

Radiative transfer simulations are performed to determine how water vapor and nonprecipitating cloud liquid water and ice particles within typical midlatitude atmospheres affect brightness temperatures T(sub B)'s of moisture sounding channels used in the Advanced Microwave Sounding Unit (AMSU) and AMSU-like instruments. The purpose is to promote a general understanding of passive top-of-atmosphere T(sub B)'s for window frequencies at 23.8, 89.0, and 157.0 GHz, and water vapor frequencies at 176.31, 180.31, and 182.31 GHz by documenting specific examples. This is accomplished through detailed analyses of T(sub B)'s for idealized atmospheres, mostly representing temperate conditions over land. Cloud effects are considered in terms of five basic properties: droplet size distribution, phase, liquid or ice water content, altitude, and thickness. Effects on T(sub B) of changing surface emissivity also are addressed. The brightness temperature contribution functions are presented as an aid to physically interpreting AMSU T(sub B)'s. Both liquid and ice clouds impact the T(sub B)'s in a variety of ways. The T(sub B)'s at 23.8 and 89 GHz are more strongly affected by altostratus liquid clouds than by cirrus clouds for equivalent water paths. In contrast, channels near 157 and 183 GHz are more strongly affected by ice clouds. Higher clouds have a greater impact on 157- and 183-GHz T(sub B)'s than do lower clouds. Clouds depress T(sub B)'s of the higher-frequency channels by suppressing, but not necessarily obscuring, radiance contributions from below. Thus, T(sub B)'s are less closely associated with cloud-top temperatures than are IR radiometric temperatures. Water vapor alone accounts for up to 89% of the total attenuation by a midtropospheric liquid cloud for channels near 183 GHz. The Rayleigh approximation is found to be adequate for typical droplet size distributions; however, Mie scattering effects from liquid droplets become important for droplet size distribution functions with modal radii greater than 20 micrometers near 157 and 183 GHz, and greater than 30-40 micrometers at 89 GHz. This is due mainly to the relatively small concentrations of droplets much larger than the mode radius. Orographic clouds and tropical cumuli have been observed to contain droplet size distributions with mode radii in the 30-40 micrometers range. Thus, as new instruments bridge the gap between microwave and infrared to frequencies even higher than 183 GHz, radiative transfer modelers are cautioned to explicitly address scattering characteristics of such clouds.

Muller, Bradley M.↗
NASA NTRS1992

Estimation of liquid water cloud height and fraction using simulated AMSU-A and MHS data

The rms retrieval errors in cloud top pressure for fully overcast conditions over both land and water surfaces are shown for AMSU-A oxygen channel pair 3 and 5 and MHS water vapor channel pair 4 and 5. For both pairs, the decrease of retrieval skill from high cloud is evident for almost all liquid water contents. For high cloud and medium cloud, the water vapor pair outperforms the oxygen pair. Retrieval accuracy is the best for high and middle clouds and degrades as the cloud top is lower in the atmosphere.

Huang, Hung-Lung↗
NASA NTRS2000

A New Neural Network Approach Including First-Guess for Retrieval of Atmospheric Water Vapor, Cloud Liquid Water Path, Surface Temperature and Emissivities Over Land From Satellite Microwave Observations

The analysis of microwave observations over land to determine atmospheric and surface parameters is still limited due to the complexity of the inverse problem. Neural network techniques have already proved successful as the basis of efficient retrieval methods for non-linear cases, however, first-guess estimates, which are used in variational methods to avoid problems of solution non-uniqueness or other forms of solution irregularity, have up to now not been used with neural network methods. In this study, a neural network approach is developed that uses a first-guess. Conceptual bridges are established between the neural network and variational methods. The new neural method retrieves the surface skin temperature, the integrated water vapor content, the cloud liquid water path and the microwave surface emissivities between 19 and 85 GHz over land from SSM/I observations. The retrieval, in parallel, of all these quantities improves the results for consistency reasons. A data base to train the neural network is calculated with a radiative transfer model and a a global collection of coincident surface and atmospheric parameters extracted from the National Center for Environmental Prediction reanalysis, from the International Satellite Cloud Climatology Project data and from microwave emissivity atlases previously calculated. The results of the neural network inversion are very encouraging. The r.m.s. error of the surface temperature retrieval over the globe is 1.3 K in clear sky conditions and 1.6 K in cloudy scenes. Water vapor is retrieved with a r.m.s. error of 3.8 kg/sq m in clear conditions and 4.9 kg/sq m in cloudy situations. The r.m.s. error in cloud liquid water path is 0.08 kg/sq m . The surface emissivities are retrieved with an accuracy of better than 0.008 in clear conditions and 0.010 in cloudy conditions. Microwave land surface temperature retrieval presents a very attractive complement to the infrared estimates in cloudy areas: time record of land surface temperature will be produced.

Aires, F.↗
NASA NTRS2006

Optically Thin Liquid Water Clouds: Their Importance and Our Challenge

Many of the clouds important to the Earth's energy balance, from the tropics to the Arctic, are optically thin and contain liquid water. Longwave and shortwave radiative fluxes are very sensitive to small perturbations of the cloud liquid water path (LWP) when the liquid water path is small (i.e., < g/sq m) and, thus, the radiative properties of these clouds must be well understood to capture them correctly in climate models. We review the importance of these thin clouds to the Earth's energy balance, and explain the difficulties in observing them. In particular, because these clouds are optically thin, potentially mixed-phase, and often (i.e., have large 3-D variability), it is challenging to retrieve their microphysical properties accurately. We describe a retrieval algorithm intercomparison that was conducted to evaluate the issues involved. The intercomparison included eighteen different algorithms to evaluate their retrieved LWP, optical depth, and effective radii. Surprisingly, evaluation of the simplest case, a single-layer overcast cloud, revealed that huge discrepancies exist among the various techniques, even among different algorithms that are in the same general classification. This suggests that, despite considerable advances that have occurred in the field, much more work must be done, and we discuss potential avenues for future work.

Turner, D. D.↗
NASA NTRS2005

Observed Land Impacts on Clouds, Water Vapor, and Rainfall at Continental Scales

How do the continents affect large-scale hydrological cycles? How important can one continent be to the climate system? To address these questions, 4-years of National Aeronautics and Space Administration (NASA) Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations, Tropical Rainfall Measuring Mission (TRMM) observations, and the Global Precipitation Climatology Project (GPCP) global precipitation analysis, were used to assess the land impacts on clouds, rainfall, and water vapor at continental scales. At these scales, the observations illustrate that continents are integrated regions that enhance the seasonality of atmospheric and surface hydrological parameters. Specifically, the continents of Eurasia and North America enhance the seasonality of cloud optical thickness, cirrus fraction, rainfall, and water vapor. Over land, both liquid water and ice cloud effective radii are smaller than over oceans primarily because land has more aerosol particles. In addition, different continents have similar impacts on hydrological variables in terms of seasonality, but differ in magnitude. For example, in winter, North America and Eurasia increase cloud optical thickness to 17.5 and 16, respectively, while in summer, Eurasia has much smaller cloud optical thicknesses than North America. Such different land impacts are determined by each continent s geographical condition, land cover, and land use. These new understandings help further address the land-ocean contrasts on global climate, help validate global climate model simulated land-atmosphere interactions, and help interpret climate change over land.

Jin, Menglin↗
NASA NTRS2005

Observed Land Impacts on Clouds, Water Vapor, and Rainfall at Continental Scales

How do the continents affect large-scale hydrological cycles? How important can one continent be to the climate system? To address these questions, five years of National Aeronautics and Space Administration (NASA) Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations, Tropical Rainfall Measuring Mission (TRMM) observations, and the Global Precipitation Climatology Project (GPCP) global precipitation analysis, were used to assess the land impacts on clouds, ~ainfall, and water vapor at continental scales. At these scales, Empirical Orthogonal Function (EOF) and continentally averaged analyses illustrate that continents as integrated regions enhance the seasonality of atmospheric and surface hydrological parameters. Specifically, the continents of Eurasia and North America enhance the seasonality of cloud optical thickness, cirrus fraction, rainfall, and water vapor. Over land, both liquid water and ice cloud effective radii are smaller than over oceans, primarily because land has more aerosol particles. In addition, different continents have similar impacts on hydrological variables in terms of seasonality, but differ in magnitude. For example, in winter, North America and Eurasia increase cloud optical thickness to 17.5 and 16, respectively, while in summer, Eurasia has much smaller cloud optical thicknesses than North An1erica. Such different land impacts are determined by each continent's geographical condition, land cover, and land use. These new understandings help further address the land-ocean contrasts on global climate, help validate global climate model simulated land-atmosphere interactions, and shed light on interpreting climate change over land.

Jin, Menglin↗
NASA NTRS1989

A scheme for parameterizing ice cloud water content in general circulation models

A method for specifying ice water content in GCMs is developed, based on theory and in-cloud measurements. A theoretical development of the conceptual precipitation model is given and the aircraft flights used to characterize the ice mass distribution in deep ice clouds is discussed. Ice water content values derived from the theoretical parameterization are compared with the measured values. The results demonstrate that a simple parameterization for atmospheric ice content can account for ice contents observed in several synoptic contexts.

Heymsfield, Andrew J.↗
NASA NTRS1986

Lightning in the Jovian water cloud

The vertical location of the lightning superbolts seen on the Voyager images of Jupiter has been determined using a comparison between the measured spot sizes for single flashes with the intensity distributions calculated from various assumptions about the altitude of the flash. A Monte Carlo model was used to describe the light scattering in the clouds, aerosols, and gases of the Jupiter atmosphere. Best agreement between the measurements and the model predictions was obtained when the lightning activity was assumed to occur in a lower cloud centered at the 5-bar pressure level, whereas the width predicted for lightning in the ammonia cloud was much smaller than the measured widths. The results imply that the lightning observed by the Voyager must be in a cloud much deeper than the ammonia cloud. The lower cloud is expected to be composed of water or a mixture of water and ammonium hydrosulfide.

Borucki, W. J.↗
NASA NTRS2020

Sensitivity of Multispectral Imager Liquid Water Cloud Microphysical Retrievals to the Index of Refraction

A cloud property retrieved from multispectral imagers having spectral channels in the shortwave infrared (SWIR) and/or midwave infrared (MWIR) is the effective particle radius (CER), a radiatively relevant weighting of the cloud particle size distribution. The physical basis of the CER retrieval is the dependence of SWIR/MWIR cloud reflectance on the cloud particle single scattering absorption, which in turn depends on the complex index of refraction of bulk liquid water (or ice) in addition to the cloud particle size. There is a general consistency in the choice of the liquid water index of refraction by the cloud remote sensing community, largely due to the few available independent datasets and compilations. Here we examine the sensitivity of CER retrievals to the available laboratory index of refraction datasets in the SWIR and MWIR using the retrieval software package that produces NASA’s standard MODIS/VIIRS continuity cloud products. The sensitivity study incorporates two laboratory index of refraction datasets that include measurements at supercooled water temperatures, one in the SWIR [Kou et al., 1993] and one in the MWIR [Wagner et al., 2005]. Neither has been broadly utilized in the cloud remote sensing community. It is shown that these two new datasets can significantly change CER retrievals (e.g., 1-2 μm) relative to common datasets used by the community. Further, index of refraction data for a 265 K water temperature results in more consistent retrievals between the two spectrally distinct 2.2 μm atmospheric window channels on MODIS and VIIRS. As a result, the 265 K values from the SWIR and MWIR index of refraction datasets were adopted for use in the production version of the continuity cloud product. The results indicate the need to better understand temperature-dependent bulk water absorption and uncertainties in these spectral regions.

MODIS↗
NASA NTRS1999

Optical Thickness and Effective Radius Retrievals of Liquid Water Clouds over Ice and Snow Surface

Cloud optical thickness and effective radius retrievals from solar reflectance measurements traditionally depend on a combination of spectral channels that are absorbing and non-absorbing for liquid water droplets. Reflectances in non-absorbing channels (e.g., 0.67, 0.86 micrometer bands) are largely dependent on cloud optical thickness, while longer wavelength absorbing channels (1.6, 2.1, and 3.7 micrometer window bands) provide cloud particle size information. Retrievals are complicated by the presence of an underlying ice/snow surface. At the shorter wavelengths, sea ice is both bright and highly variable, significantly increasing cloud retrieval uncertainty. However, reflectances at the longer wavelengths are relatively small and may be comparable to that of dark open water. Sea ice spectral albedos derived from Cloud Absorption Radiometer (CAR) measurements during April 1992 and June 1995 Arctic field deployments are used to illustrate these statements. A modification to the traditional retrieval technique is devised. The new algorithm uses a combination of absorbing spectral channels for which the snow/ice albedo is relatively small. Using this approach, preliminary retrievals have been made with the MODIS Airborne Simulator (MAS) imager flown aboard the NASA ER-2 during FIRE-ACE. Data from coordinated ER-2 and University of Washington CV-580 aircraft observations of liquid water stratus clouds on June 3 and June 6, 1998 have been examined. Size retrievals are compared with in situ cloud profile measurements of effective radius made with the CV-580 PMS FSSP probe, and optical thickness retrievals are compared with extinction profiles derived from the Gerber Scientific "g-meter" probe. MAS retrievals are shown to be in good agreement with the in situ measurements.

Platnick, S.↗
NASA NTRS2022

On the Effects of Cloud Water Content on Passive Microwave Snowfall Retrievals

The Bayesian passive microwave retrievals of snowfall often rely on mathematical matching of the observed vectors of brightness temperature with an a priori database of precipitation profiles and their corresponding brightness temperatures. Mathematical proximity does not necessarily lead to consistent retrievals due to limited information content of passive microwave observations. This paper defines imposter (genuine) vectors of brightness temperature as those that are mathematically close but physically inconsistent (consistent) and characterizes them through the Silhouette Coefficient (SC) analysis. The Neyman–Pearson (NP) hypothesis testing is used to separate the imposter and genuine brightness temperatures based on their associated values of cloud ice (IWP) and liquid water path (LWP), given by coincidences of CloudSat Profiling Radar (CPR) and the Global Precipitation Measurement (GPM) Microwave Imager (GMI). The study determines thresholds for IWP and LWP that allow optimal identification of imposter brightness temperatures of non-snowing and snowing clouds, which can mislead the passive microwave retrieval algorithms to falsely detect or miss the snowfall events. It is demonstrated that emission signal of supercooled liquid water in snowing clouds can lead to improved passive microwave retrieval of snowfall and conditioning the retrievals to the cloud IWP and LWP can result in marginal correction of the snowfall detection probability; however, reduce the probability of false alarm by 6%–8% over sea ice and open oceans.

Snowfall↗