Observing the Energetic Effects of High Clouds: Applications to “Hot Towers”, Convective Lifecycles, and Cloud Feedbacks
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Radiative diffusivity factors in cirrus and stratocumulus clouds: Application to two-stream models
A diffusion-like description of radiative transfer in clouds and the free atmosphere is often used. The two stream model is probably the best known example of such a description. The main idea behind the approach is that only the first few moments of radiance are needed to describe the radiative field correctly. Integration smooths details of the angular distribution of specific intensity and it is assumed that the closure parameters of the theory (diffusivity factors) are only weakly dependent on the distribution. The diffusivity factors are investigated using the results obtained from both Stratocumulus and Cirrus phases of FIRE experiment. A new theoretical framework is described in which two (upwards and downwards) diffusivity factors are used and a detailed multistream model is used to provide further insight about both the diffusivity factors and their dependence on scattering properties of clouds.
Stephens, Graeme L.↗
A general model for Io's neutral gas clouds. II - Application to the sodium cloud
A previously developed neutral cloud model is applied to the neutral sodium cloud produced by Io. Past models for the cloud are reviewed and the motivation for developing better models is discussed. The interactions of sodium in the plasma torus are discussed. It is shown how the new model can be used to provide a consistent physical explanation for the basic physical characteristics of the spatially extended Io sodium cloud and for the east-west intensity asymmetry observed very near Io. This leads to definite conclusions regarding the flux distribution and density of sodium in Io's exosphere, the level of the collisional exobase in the atmosphere, the nature of the interaction of the corotating plasma torus and the satellite atmosphere/corona, and the presence of an east-west electric field in the planetary system.
Smyth, W. H.↗
Using spatial coherence to retrieve cloud properties - ERBE experience and CERES applications
Cloud properties for individual ERBE scanner fields of view are obtained from simultaneous, collocated imagery data. The cloud properties are used to assess the performance of the ERBE maximum likelihood estimate of cloud conditions which ultimately influences estimates of the radiative fluxes at the top of the atmosphere. During EOS the analysis of MODIS observations within the fields of view of the CERES instruments promises to yield, in addition, estimates of surface radiative fluxes as well as the vertical distribution of radiative heating within the atmosphere.
Coakley, James A., Jr.↗
The effect of moonlight on observation of cloud cover at night, and application to cloud climatology
Ten years of nighttime weather observations from the Northern Hemisphere in December were classified according to the illuminance of moonlight or twilight on the cloud tops, and a threshold level of illuminance was determined, above which the clouds are apparently detected adequately. This threshold corresponds to light from a full moon at an elevation angle of 6 deg, light from a partial moon at higher elevation, or twilight from the sun less than 9 deg bvelow the horizon. It permits the use of about 38% of the observations made with the sun below the horizon. The computed diurnal cycles of total cloud cover are altered considerably when this moonlight criterion is imposed. Maximum cloud cover over much of the ocean is now found to be at night or in the morning, whereas computations obtained without benefit of the moonlight criterion, as in our published atlases, showed the time of maximum to be noon or early afternoon in many regions. The diurnal cycles of total cloud cover we obtain are compared with those of the International Satellite Cloud Climatology Project (ISCCP) for a few regions; they are generally in better agreement if the moonlight criterion is imposed on the surface observations. Using the moonlight criterion, we have analyzed 10 years (1982-91) of surface weather observations over land and ocean, worldwide, for total cloud cover and for the frequency of occurrence of clear sky, fog, and precipitation. The global average cloud cover (average of day and night) is about 2% higher if the moonlight criterion is imposed than if all observations are used. The difference is greater in winter than in summer, because of the fewer hours of darkness in summer. The amplitude of the annual cycle of total cloud cover over the Arctic Ocean and at the South Pole is diminished by a few percent when the moonlight criterion is imposed. The average cloud cover for 1982-91 is found to be 55% for Northern Hemisphere land, 53% for Southern Hemisphere land, 66% for Northern Hemisphere ocean, and 70% for Southern Hemisphere ocean, giving a global average of 64%. The global average for daytime is 64.6%; for nighttime 63.3%.
Hahn, Carole J.↗
Near-Real Time Satellite-Retrieved Cloud and Surface Properties for Weather and Aviation Safety Applications
Cloud properties determined from satellite imager radiances provide a valuable source of information for nowcasting and weather forecasting. In recent years, it has been shown that assimilation of cloud top temperature, optical depth, and total water path can increase the accuracies of weather analyses and forecasts. Aircraft icing conditions can be accurately diagnosed in near-‐real time (NRT) retrievals of cloud effective particle size, phase, and water path, providing valuable data for pilots. NRT retrievals of surface skin temperature can also be assimilated in numerical weather prediction models to provide more accurate representations of solar heating and longwave cooling at the surface, where convective initiation. These and other applications are being exploited more frequently as the value of NRT cloud data become recognized. At NASA Langley, cloud properties and surface skin temperature are being retrieved in near-‐real time globally from both geostationary (GEO) and low-‐earth orbiting (LEO) satellite imagers for weather model assimilation and nowcasting for hazards such as aircraft icing. Cloud data from GEO satellites over North America are disseminated through NCEP, while those data and global LEO and GEO retrievals are disseminated from a Langley website. This paper presents an overview of the various available datasets, provides examples of their application, and discusses the use of the various datasets downstream. Future challenges and areas of improvement are also presented.
Minnis, Patrick↗
Microphysical Timescales in Clouds and their Application in Cloud-Resolving Modeling
Computational phenomena (i.e., spurious supersaturation and negative mixing ratio of cloud water) usually exist in cloud-resolving models when the time step for explicit integration is larger than a microphysical timescale in clouds. In this paper, the microphysical timescales in clouds are studied, showing that the timescale of water vapor condensation (or cloud water evaporation) is smaller than 10 s - the order of a typical time step for cloud-resolving models. To avoid spurious computational phenomena in cloud-resolving modeling, it is suggested that moist entropy be used as a prognostic thermodynamic variable, and temperature be diagnosed from that and other prognostic variables. A simple numerical model with moist entropy as a prognostic variable, for example, is presented to show that spurious computational phenomena are removed when moist entropy is used as a prognostic variable.
Zeng, Xi-Ping↗
Microphysical Timescales in Clouds and their Application in Cloud-Resolving Modeling
Independent prognostic variables in cloud-resolving modeling are chosen on the basis of the analysis of microphysical timescales in clouds versus a time step for numerical integration. Two of them are the moist entropy and the total mixing ratio of airborne water with no contributions from precipitating particles. As a result, temperature can be diagnosed easily from those prognostic variables, and cloud microphysics be separated (or modularized) from moist thermodynamics. Numerical comparison experiments show that those prognostic variables can work well while a large time step (e.g., 10 s) is used for numerical integration.
Zeng, Xiping↗
Polarization Difference - The Scientific Story Behind One Variable and Its Practical Applications
Cloud ice and snow microphysical characteristics play an important role in determining cloud radiative effect. They are also closely connected to the details of surface precipitation characteristics. Ice orientation is one microphysical property that is traditionally believed to have trivial impact on the weather systems/climate, and it is hard to measure from space. In this presentation, I will show how many scientific stories can be told from one variable – the brightness temperature difference between vertically-polarized and horizontally-polarized 166 GHz measurements from the Global Precipitation Measurement Microwave Imager (GPM-GMI). Through scrutinizing collocated CloudSat, GMI and GPM radar observations together with the aid of radiative transfer model simulations, we can not only tell apart the particle size, shape and orientation, but also understand the precipitation regime as well as the life stage of a a precipitation system. In the second half of my talk, I will showcase how this variable can be used for predicting precipitation flags and separating mixed-phase cloud from liquid and ice with the powerful machine learning/artificial intelligence (ML/AI) technique.
cloud ice and snow microphysical characteristics↗
Evaluation and Applications of Cloud Climatologies from CALIOP
Clouds have a major impact on the Earth radiation budget and differences in the representation of clouds in global climate models are responsible for much of the spread in predicted climate sensitivity. Existing cloud climatologies, against which these models can be tested, have many limitations. The CALIOP lidar, carried on the CALIPSO satellite, has now acquired over two years of nearly continuous cloud and aerosol observations. This dataset provides an improved basis for the characterization of 3-D global cloudiness. Global average cloud cover measured by CALIOP is about 75%, significantly higher than for existing cloud climatologies due to the sensitivity of CALIOP to optically thin cloud. Day/night biases in cloud detection appear to be small. This presentation will discuss detection sensitivity and other issues associated with producing a cloud climatology, characteristics of cloud cover statistics derived from CALIOP data, and applications of those statistics.
Winker, David↗
Cloud Computing Applications in Support of Earth Science Activities at Marshall Space Flight Center
Currently, the NASA Nebula Cloud Computing Platform is available to Agency personnel in a pre-release status as the system undergoes a formal operational readiness review. Over the past year, two projects within the Earth Science Office at NASA Marshall Space Flight Center have been investigating the performance and value of Nebula s "Infrastructure as a Service", or "IaaS" concept and applying cloud computing concepts to advance their respective mission goals. The Short-term Prediction Research and Transition (SPoRT) Center focuses on the transition of unique NASA satellite observations and weather forecasting capabilities for use within the operational forecasting community through partnerships with NOAA s National Weather Service (NWS). SPoRT has evaluated the performance of the Weather Research and Forecasting (WRF) model on virtual machines deployed within Nebula and used Nebula instances to simulate local forecasts in support of regional forecast studies of interest to select NWS forecast offices. In addition to weather forecasting applications, rapidly deployable Nebula virtual machines have supported the processing of high resolution NASA satellite imagery to support disaster assessment following the historic severe weather and tornado outbreak of April 27, 2011. Other modeling and satellite analysis activities are underway in support of NASA s SERVIR program, which integrates satellite observations, ground-based data and forecast models to monitor environmental change and improve disaster response in Central America, the Caribbean, Africa, and the Himalayas. Leveraging SPoRT s experience, SERVIR is working to establish a real-time weather forecasting model for Central America. Other modeling efforts include hydrologic forecasts for Kenya, driven by NASA satellite observations and reanalysis data sets provided by the broader meteorological community. Forecast modeling efforts are supplemented by short-term forecasts of convective initiation, determined by geostationary satellite observations processed on virtual machines powered by Nebula.
Molthan, Andrew L.↗
Radio recombination lines from fast shocks in molecular clouds, with application to bipolar flows
Detailed shock calculations are presented which demonstrate that fast dissociative shocks in molecular clouds produce detectable radio recombination lines and continuum lines, in addition to optical and infrared recombination lines. The theoretical results are applied to outflows from young stellar objects; bipolar flows are treated as massive, radiative winds. The calculations support Hasegawa and Akabane's (1984) interpretation of the H51-alpha line from Orion-KL as being due to a shock, and are consistent with the two-shock model of Chernoff, Hollenbach, and McKee (1982).
Mckee, Christopher F.↗
Multidimensional Data Aggregation in the Cloud with Application to Geostationary Satellite-based Air Quality Monitoring
Scientists use satellite data for studying Earth's systems, and the remote sensing data that these satellites collect are typically separated into files of a size small enough for efficient network transfer and storage. However, researchers usually prefer to analyze the data based on real-world dimensions like time, space, or elevation. To help with this, NASA's Atmospheric Science Data Center (ASDC) developed a new cloud-based tool that combines these smaller data chunks into larger, more useful datasets. The tool works on Network Common Data Form (netCDF4) and some HDF5 formatted files, and it is available as a service in NASA's Earthdata Cloud. In this presentation, we showcase this service using data from the Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument. By combining TEMPO's continuous observations over time, we create longer and more informative analysis-ready time series to facilitate the study of air quality patterns. Insights gained will provide a more comprehensive understanding of pollution sources, transport patterns, and their effects on the environment and human health.
Daniel Kaufman↗
Application of Cloude's target decomposition theorem to polarimetric imaging radar data
In this paper we applied Cloude's decomposition to imaging radar polarimetry. We show in detail how the decomposition results can guide the interpretation of scattering from vegetated areas. For multifrequency polarimetric radar measurements of a clear-cut area, the decomposition leads us to conclude that the vegetation is probably thin compared to even the C-band radar wavelength of 6 cm. For a frosted area, we notice an increased amount of even number of reflection scattering at P-band and L-band, probably the result of penetration through the coniferous canopy resulting in trunk-ground double reflection scattering. However, the scattering for the forested area is still dominated by scattering from randomly oriented cylinders. It is found that these cylinders are thicker than in the case of clear-cut areas, leading us to conclude that scattering from the branches probably dominates in this case.
Vanzyl, Jakob J.↗
Application of Cloude's target decomposition theorem to polarimetric imaging radar data
We apply Cloude's decomposition to imaging radar polarimetry. We derive the general expressions for the eigenvalues and eigenvectors for the case of terrain with reflection symmetry, and show in detail how the decomposition results can guide the interpretation of scattering from vegetated areas. For multi-frequency polarimetric radar measurements of a clear-cut area, the decomposition leads us to conclude that the vegetation is probably thin compared to even the C-band radar wavelength of 6 cm. For a forested area, we notice an increased amount of even number of reflection scattering at P-band and L-band, probably the result of penetration through the coniferous canopy resulting in trunk-ground double reflection scattering. The scattering for the forested area is still dominated by scattering from randomly oriented cylinders, however. It is found that these cylinders are thicker than in the case of clear-cut areas, leading us to conclude that scattering from the branches probably dominate in this case.
Vanzyl, Jakob J.↗
Coloration Determination of Spectral Darkening Occurring on a Broadband Earth Observing Radiometer: Application to Clouds and the Earth's Radiant Energy System (CERES)
It is estimated that in order to best detect real changes in the Earth s climate system, space based instrumentation measuring the Earth Radiation Budget (ERB) must remain calibrated with a stability of 0.3% per decade. Such stability is beyond the specified accuracy of existing ERB programs such as the Clouds and the Earth s Radiant Energy System (CERES, using three broadband radiometric scanning channels: the shortwave 0.3 - 5microns, total 0.3. > 100microns, and window 8 - 12microns). It has been shown that when in low earth orbit, optical response to blue/UV radiance can be reduced significantly due to UV hardened contaminants deposited on the surface of the optics. Since typical onboard calibration lamps do not emit sufficient energy in the blue/UV region, this darkening is not directly measurable using standard internal calibration techniques. This paper describes a study using a model of contaminant deposition and darkening, in conjunction with in-flight vicarious calibration techniques, to derive the spectral shape of darkening to which a broadband instrument is subjected. Ultimately the model uses the reflectivity of Deep Convective Clouds as a stability metric. The results of the model when applied to the CERES instruments on board the EOS Terra satellite are shown. Given comprehensive validation of the model, these results will allow the CERES spectral responses to be updated accordingly prior to any forthcoming data release in an attempt to reach the optimum stability target that the climate community requires.
Matthews, Grant↗
Radiative Transfer Through Clouds and Its Applications in Support of the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) Mission
The Greenland and Antarctic ice sheets, which contain enough ice to raise sea level by about 7 and 60 m, respectively, are losing mass at an increasing rate. To acquire continuous information of the cryosphere, after the Ice, Cloud, and land Elevation Satellite (ICESat) (2003-2010), NASA is actively planning for the ICESat-2 mission. Both ICESat and ICESat-2 are space-borne lidar altimetry systems. The systems measure the time of flight of the arriving photons that are reflected by the surface to deduce the elevation of the underlying terrain. As one of NASA's top priority missions, ICESat-2 is scheduled to launch in 2016. One of the major science goals of ICESat-2 is to quantify the ice sheet mass balance to determine its contributions to the sea level change and its impacts on ocean circulation (Abdalati et al. 2010). Compared to ICESat, which operates at 40 Hz and records the reflected laser energy as a waveform, the significantly improved ICESat-2 lidar employs a 532 nm micro-pulse photon counting system that operates at a high frequency of 10kHz with single photon detectability (Yang et al. 2012). To achieve its science goals, ICESat-2 requires the ability of detecting the elevation change with an accuracy of 0.2 cm/year over the entire ice sheet. Since every photon emitted by the lidar system will travel through the atmosphere, clouds can certainly affect the flight time of the arriving photons. Forward scattering by cloud particles increases the photon path length, thus resulting in biases in ice sheet elevation measurements known as atmospheric path delay (Duta et al. 2001, Yang et al. 2010, 2011). To ensure the accuracy of ICESat-2 surface elevation measurements, it is critical to understand how clouds would affect the travel time of arriving photons. In this talk, we will first present a framework that simulates the behavior of a space-borne 532 mn micro-pulse photon counting lidar in cloudy and clear atmospheres. To investigate the process of laser propagation through clouds, a 3-D Monte Carlo radiative transfer model is used to simulate the photon path distribution and the Poisson distribution is adopted for the number of photon returns. Since the photon counting system only registers the time of the first arriving photon within the detector "dead time", the retrieved average surface elevation tends to bias towards higher values. This is known as the first photon bias. With the scenarios simulated here, the first photon bias for clear sky is about 6.5 cm. Clouds affect surface altimetry in two ways: (1) cloud attenuation lowers the average number of arriving photons and hence reduces the first photon bias; (2) cloud forward scattering increases the photon path length and makes the surface appear further away from the satellite. Compared to clear sky, the average surface elevation detected by the photon counting system for cloudy sky with optical depth 1.0 is 4.0 to 6.0 cm lower for the simulations conducted. The effect of surface roughness on the accuracy of elevation retrievals will also discussed.
Yang, Yuekui↗
Automatic classification of clouds on Meteosat imagery - Application to high-level clouds
A statistical classification method based on clustering on three-dimensional histograms is applied to the three channels of the Meteosat imagery. The results of this classification are studied for different cloud cover cases over tropical regions. For high-level cloud classes, it is shown that the bidimensional IR-water vapor histogram allows one to deduce the cloud top temperature even for semi-transparent clouds.
Desbois, M.↗