Modeling Viking Era Water Ice Clouds
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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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Passive microwave techniques for sensing the Earth's atmosphere provide powerful tools for understanding and monitoring its dynamics.
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The dust cycle is critically important for the current climate of Mars. The radiative effects of dust impact the thermal and dynamical state of the atmosphere [1,2,3]. Although dust is present in the Martian atmosphere throughout the year, the level of dustiness varies with season. The atmosphere is generally the dustiest during northern fall and winter and the least dusty during northern spring and summer [4]. Dust particles are lifted into the atmosphere by dust storms that range in size from meters to thousands of kilometers across [5]. Regional storm activity is enhanced before northern winter solstice (Ls~200 degrees - 240 degrees), and after northern solstice (Ls~305 degrees - 340 degrees ), which produces elevated atmospheric dust loadings during these periods [5,6,7]. These pre- and post- solstice increases in dust loading are thought to be associated with transient eddy activity in the northern hemisphere with cross-equatorial transport of dust leading to enhanced dust lifting in the southern hemisphere [6]. Interactive dust cycle studies with Mars General Circulation Models (MGCMs) have included the lifting, transport, and sedimentation of radiatively active dust. Although the predicted global dust loadings from these simulations capture some aspects of the observed dust cycle, there are marked differences between the simulated and observed dust cycles [8,9,10]. Most notably, the maximum dust loading is robustly predicted by models to occur near northern winter solstice and is due to dust lifting associated with down slope flows on the flanks of the Hellas basin. Thus far, models have had difficulty simulating the observed pre- and post- solstice peaks in dust loading.
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.
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A field campaign at Siple Dome in West Antarctica during the austral summer 2019-2020 offers an opportunity to evaluate climate model performance, particularly cloud microphysical simulation. Over Antarctic ice sheets and ice shelves, clouds are a major regulator of the surface energy balance, and in the warm season their presence occasionally induces surface melt that can gradually weaken an ice shelf structure. This dataset from Siple Dome, obtained using transportable and solar-poweredequipment, includes surface energy balance measurements, meteorology and cloud remote sensing. To demonstrate how these data can be used to evaluate model performance, comparisons are made with meteorological reanalysis known to give generally good performance over Antarctica (ERA5). Surface albedo measurements show expected variability with observed cloud amount, and can be used to evaluate a model's snowpack parameterization. One case study discussed involves a squall with northerly winds, during which ERA5 fails to produce cloud cover throughout one of the days. A second case study illustrates how shortwave spectroradiometer measurements that encompass the 1.6-micron atmospheric window reveal cloud phase transitions associated with cloud lifecycle. Here, continuously precipitating mixed-phase clouds become mainly liquid water clouds from local morning through the afternoon, not reproduced by ERA5. We challenge researchers to run their various regional or global models in a manner that has the large-scale meteorology follow the conditions of this field campaign, compare cloud and radiation simulations with this Siple Dome dataset, and potentially investigate why cloud microphysical simulations or other model components might produce discrepancies with these observations.
The inaugural calibration of the ice crystal and supercooled liquid water clouds generated in NASA Glenn's engine altitude test facility, the Propulsion Systems Lab (PSL) is reported herein. This calibration was in support of the inaugural engine ice crystal validation test. During the Fall of 2012 calibration effort, cloud uniformity was documented via an icing grid, laser sheet and cloud tomography. Water content was measured via multi-wire and robust probes, and particle sizes were measured with a Cloud Droplet Probe and Cloud Imaging Probe. The environmental conditions ranged from 5,000 to 35,000 ft, Mach 0.15 to 0.55, temperature from +50 to -35 F and relative humidities from less than 1 percent to 75 percent in the plenum.
Instruments on the Galileo probe measured composition, cloud properties, thermal structure. winds, radiative energy balance, and electrical properties of the Jovian atmosphere. As expected the probe results confirm some expectations about Jupiter's atmosphere, refute others, and raise new questions which still remain unanswered. This talk will concentrate on those aspects of the probe observations which either raised new questions or remain unresolved. The Galileo probe observations of composition and clouds provided some of the biggest surprises of the mission. Helium abundance measured by the probe differed significantly from the remote sensing derivations from Voyager. discrepancy between the Voyager helium abundance determinations for Jupiter and the Galileo probe value have now led to a considerably increased helium determination for Saturn. Global abundance of N in the form of ammonia was observed to be supersolar by approximately the same factor as carbon, in contrast to expectations that C/N would be significantly larger than solar. This has implications for the formation and evolution of Jupiter. The cloud structure was not what was generally anticipated, even though most previous remote sensing results below the uppermost cloud referred to 5 micron hot spots, local regions with reduced cloud opacity. The Galileo probe descended in one of these hot spots. Only a tenuous, presumed ammonium hydrosulfide, cloud was detected, and no significant water cloud or super-solar water abundance was measured. The mixing ratios as a function of depth for the condensibles ammonia, hydrogen sulfide, and water, exhibited no apparent correlation with either condensation levels or with each other, an observation that is still a puzzle, although there are now dynamical models of hot spots which show promise in being able to explain such behavior. Probe tracked zonal winds show that wind magnitude increases with depth to pressures of about 4 bars, with the winds extending to at least as deep as the probe made measurements, 22 bars. Models of hot spot dynamics raise the possibility that the variation with depth of the probe measured zonal winds between 0.4 and 4 bars reflect the dynamics of the hot spot rather than the global wind pattern. Galileo upper atmosphere measurements established that there is a sharp temperature rise with altitude between about 350 and 800 km above the 1 bar pressure level, with the upper atmosphere reaching, temperatures near 900 K. The energy sources for this upper atmosphere heating are not clearly established, but various mechanisms have been proposed. These and other aspects of the Galileo probe data will be discussed.
Instruments on the Galileo probe measured composition, cloud properties, thermal structure, winds, radiative energy balance, and electrical properties of the Jovian atmosphere. As expected the probe results confirm some expectations about Jupiter's atmosphere, refute others, and raise new questions which still remain unanswered. This talk will concentrate on those aspects of the probe observations which either raised new questions or remain unresolved. The Galileo probe observations of composition and clouds provided some of the biggest surprises of the mission. Helium abundance measured by the probe differed significantly from the remote sensing derivations from Voyager. Discrepancy between the Voyager helium abundance determinations for Jupiter and the Galileo probe value have now led to a considerably increased helium determination for Saturn. Global abundance of N in the form of ammonia was observed to be super-solar by approximately the same factor as carbon, in contrast to expectations that C/N would be significantly larger than solar. This has implications for the formation and evolution of Jupiter. The cloud structure was not what was generally anticipated, even though most previous remote sensing results below the uppermost cloud referred to 5 micron hot spots, local regions with reduced cloud opacity. The Galileo probe descended in one of these hot spots. Only a tenuous, presumed ammomium hydrosulfide, cloud was detected, and no significant water cloud or super-solar water abundance was measured. The mixing ratios as a function of depth for the condensibles ammonia, hydrogen sulfide, and water, exhibited no apparent correlation with either condensation levels or with each other, an observation that is still a puzzle, although there are now dynamical models of hot spots which show promise in being able to explain such behavior. Probe tracked zonal winds show that wind magnitude increases with depth to pressures of about 4 bars, with the winds extending to at least as deep as the probe made measurements, 22 bars. Models of hot spot dynamics raise the possibility that the variation with depth of the probe measured zonal winds between 0.4 and 4 bars reflect the dynamics of the hot spot rather than the global wind pattern. Galileo upper atmosphere measurements established that there is a sharp temperature rise with altitude between about 350 and 800 km above the 1 bar pressure level, with the upper atmosphere reaching temperatures near 900 K. The energy sources for this upper atmosphere heating are not clearly established, but various mechanisms have been proposed. These and other aspects of the Galileo probe data will be discussed.
The effects of an initially overlying layer of solar-absorbing aerosol on the transition of stratocumulus to trade cumulus clouds are examined using large-eddy simulations. For lightly drizzling cloud the transition is generally hastened, resulting mainly from increased cloud droplet number concentration (Nc) induced by entrained aerosol. The increased Nc slows sedimentation of cloud droplets and shortens their relaxation time for diffusional growth, both of which accelerate entrainment of overlying air and thereby stratocumulus breakup. However, the decrease in albedo from cloud breakup is more than offset by redistributing cloud water over a greater number of droplets, such that the diurnal-average shortwave forcing at the top of the atmosphere is negative. The negative radiative forcing is enhanced by sizable longwave contributions, which result from the greater cloud breakup and a reduced boundary layer height associated with aerosol heating. A perturbation of moisture instead of aerosol aloft leads to a greater liquid water path and a more gradual transition. Adding absorbing aerosol to that atmosphere results in substantial reductions in liquid water path (LWP) and cloud cover that lead to positive short-wave and negative longwave forcings on average canceling each other. Only for heavily drizzling clouds is the breakup delayed, as inhibition of precipitation overcomes cloud water loss from enhanced entrainment. Considering these simulations as an imperfect proxy for biomass burning plumes influencing Namibian stratocumulus, we expect regional indirect plus semi-direct forcings to be substantially negative to negligible at the top of the atmosphere, with its magnitude sensitive to background and perturbation properties.
A rigorous computation of the electromagnetic field scattered from an atmospheric liquid water cloud is proposed. The recent development of a fast recursive algorithm (Chew algorithm) for computing the fields scattered from numerous scatterers now makes a rigorous computation feasible. A method is presented for adapting this algorithm to a general case where there are an extremely large number of scatterers. It is also proposed to extend a new binary PAM channel coding technique (El-Khamy coding) to multiple levels with non-square pulse shapes. The Chew algorithm can be used to compute the transfer function of a cloud channel. Then the transfer function can be used to design an optimum El-Khamy code. In principle, these concepts can be applied directly to the realistic case of a time-varying cloud (adaptive channel coding and adaptive equalization). A brief review is included of some preliminary work on cloud dispersive effects on digital communication signals and on cloud liquid water spectra and correlations.
The ndrop_mfrsr value-added product (VAP) provides an estimate of the cloud droplet number concentration of overcast water clouds retrieved from cloud optical depth from the multi-filter rotating shadowband radiometer (MFRSR) instrument and liquid water path (LWP) retrieved from the microwave radiometer (MWR). When cloud layer information is available from vertically pointing lidar and radars in the Active Remote Sensing of Clouds (ARSCL) product, the VAP also provides estimates of the adiabatic LWP and an adiabatic parameter (beta) that indicates how divergent the LWP is from the adiabatic case. quality control (QC) flags (qc_drop_number_conc), an uncertainty estimate (drop_number_conc_toterr), and a cloud layer type flag (cloud_base_type) are useful indicators of the quality and accuracy of any given value of the retrieval. Examples of these major input and output variables are given in sample plots in section 6.0.
Measurements of temperature, water vapor, cloud liquid water, and lidar cloud height taken by the National Center for Aeronautical Research (NCAR) Electra are analyzed for two days of the First ISCCP Regional Experiment (FIRE) stratocumulus field program. Examination of instrument time series, correlations between sensors, soundings through the layer, and lidar measurements of cloud base height are used to correct sensor offset problems, check for probe wetting, and choose the most accurate measurements of temperature, humidity, and cloud liquid water.
The need to understand the complementarity of the radar and radiometer is important not only to the Tropical Rain Measuring Mission (TRMM) program but to a growing number of multi-instrumented airborne experiment that combine single or dual-frequency radars with multichannel radiometers. The method of analysis used in this study begins with the derivation of dual-wavelength radar equations for the estimation of a two-parameter drop size distribution (DSD). Defining a "storm model" as the set of parameters that characterize snow density, cloud water, water vapor, and features of the melting layer, then to each storm model there will usually correspond a set of range-profiled drop size distributions that are approximate solutions of the radar equations. To test these solutions, a radiative transfer model is used to compute the brightness temperatures for the radiometric frequencies of interest. A storm model or class of storm models is considered optimum if it provides the best reproduction of the radar and radiometer measurements. Tests of the method are made for stratiform rain using simulated storm models as well as measured airborne data. Preliminary results show that the best correspondence between the measured and estimated radar profiles usually can be obtained by using a moderate snow density (0.1-0.2 g/cu cm), the Maxwell-Garnett mixing formula for partially melted hydrometeors (water matrix with snow inclusions), and low to moderate values of the integrated cloud liquid water (less than 1 kg/sq m). The storm-model parameters that yield the best reproductions of the measured radar reflectivity factors also provide brightness temperatures at 10 GHz that agree well with the measurements. On the other hand, the correspondence between the measured and modeled values usually worsens in going to the higher frequency channels at 19 and 34 GHz. In searching for possible reasons for the discrepancies, It is found that changes in the DSD parameter Mu, the radar constants, or the path-integrated attenuation can affect the high frequency channels significantly. In particular, parameters that cause only modest increases in the median mass diameter of the snow, and which have a minor effect on the radar returns or the low frequency brightness temperature, can produce a strong cooling of the 34 GHz brightness temperature.
The ways in which radio signals are affected by meteorological parameters are described, as are methods for interpreting the signals, the state-of-the-art in instrumentation, the current state of development of the field, and some problems and prospects for the future. It is shown that the temperature profile of the atmosphere, water vapor and ozone distribution, cloud water content, and certain surface properties can be measured with sufficient accuracy to provide useful meteorological information.