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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.↗

NASA NTRS1995

Cloud Properties Derived From GOES-7 for Spring 1994 ARM Intensive Observing Period Using Version 1.0.0 of ARM Satellite Data Analysis Program

This document describes the initial formulation (Version 1.0.0) of the Atmospheric Radiation Measurement (ARM) program satellite data analysis procedures. Techniques are presented for calibrating geostationary satellite data with Sun synchronous satellite radiances and for converting narrowband radiances to top-of-the-atmosphere fluxes and albedos. A methodology is documented for combining geostationary visible and infrared radiances with surface-based temperature observations to derive cloud amount, optical depth, height, thickness, temperature, and albedo. The analysis is limited to two grids centered over the ARM Southern Great Plains central facility in north-central Oklahoma. Daytime data taken during 5 Apr. - 1 May 1994, were analyzed on the 0.3 deg and 0.5 deg latitude-longitude grids that cover areas of 0.9 deg x 0.9 deg and 10 deg x 14 deg, respectively. Conditions ranging from scattered low cumulus to thin cirrus and thick cumulonimbus occurred during the study period. Detailed comparisons with hourly surface observations indicate that the mean cloudiness is within a few percent of the surface-derived sky cover. Formats of the results are also provided. The data can be accessed through the World Wide Web computer network.

Minnis, Patrick↗

NASA NTRS1983

An interactive system for compositing digital radar and satellite data

This paper describes an approach for compositing digital radar data and GOES satellite data for meteorological analysis. The processing is performed on a user-oriented image processing system, and is designed to be used in the research mode. It has a capability to construct PPIs and three-dimensional CAPPIs using conventional as well as Doppler data, and to composite other types of data. In the remapping of radar data to satellite coordinates, two steps are necessary. First, PPI or CAPPI images are remapped onto a latitude-longitude projection. Then, the radar data are projected into satellite coordinates. The exact spherical trigonometric equations, and the approximations derived for simplifying the computations are given. The use of these approximations appears justified for most meteorological applications. The largest errors in the remapping procedure result from the satellite viewing angle parallax, which varies according to the cloud top height. The horizontal positional error due to this is of the order of the error in the assumed cloud height in mid-latitudes. Examples of PPI and CAPPI data composited with satellite data are given for Hurricane Frederic on 13 September 1979 and for a squall line on 2 May 1979 in Oklahoma.

Heymsfield, G. M.↗

NASA NTRSDate not supplied

Understanding and Utilizing PBL Height Data from Multiple Observing Systems in the GEOS System

The accuracy of PBL height simulation is a key issue in many applications including forecasting near surface meteorology and air quality, however, it is a very challenging problem due to the lack of not only comprehensive, global Planetary Boundary Layer (PBL) observations but also a strategy and infrastructure to utilize PBL height data from a variety of sensors. Following the designation of PBL as an incubation class observable in the 2017 Decadal Survey, the PBL Incubation Study Team Report [14] made clear that “a future global PBL observing system requires modeling and data assimilation as essential components.” There is an urgent need for global modeling development in order to utilize Program of Record (POR) observations, assess their impacts, and identify gaps to be filled by future PBL missions. Our overall objective is to develop PBL data assimilation capabilities in the NASA Global Earth Observing System (GEOS), focusing on PBL height from multiple observing systems, to support the assessment and use of future PBL observations. The NASA GEOS system is composed of the GEOS global atmospheric general circulation model (AGCM) and the atmospheric data assimilation system (ADAS). The PBL parameterizations include the “Lock” K-profile scheme driven by surface and cloud-top buoyancy fluxes ([4]), and the “Louis” local scheme for stable conditions based on the Richardson number ([5]). Above the mixed layer defined by the Lock surface plume, shallow cumulus convection is represented by the mass flux scheme of [9]. Additional parameterizations are summarized in [1]. The ADAS employs the hybrid 4D Ensemble- Variational (EnVar) configuration ([15]), with the ensemble providing flow-dependent background error covariance information. The resultant analysis increments are fed back to the forecast model through the 4D incremental analysis update (IAU) approach ([11]). In this study, PBL height data are being or have been generated from radiosondes, GNSS RO, satellite (CATS, CALIPSO and ICESat-2) and ground-based (MPLNET) lidars, and wind profiler. Investigations have been conducted to specify quality marks for PBL height retrievals for the data assimilation purpose. These PBL height data have different strengths and weaknesses ([2], [3], [6], [7], [8], [10]), and the satellite PBL height data provide better global coverage and complement in-situ PBL height data. Radiosondes offer high accuracy and in situ measurement of temperature and humidity profiles, but with poor spatio-temporal sampling. The in-situ observing systems like MPLNET and wind profiler provide long history of PBL height records at each station. The GNSS RO based PBL height is retrieved based on the sharp gradients in refractivity profile that represent the fine vertical structure of temperature and moisture changes above the PBL. However, not all RO refractivity profiles reach the surface depending on location and regime, and RO refractivity retrievals can be negatively biased below 2km. The PBL height data from satellite lidars provide high resolution along track PBL height retrievals, but over land they are affected by previous day convective PBL aerosol and strongly associated with mixing layer and retrievals cannot be made below thick, attenuating clouds. A successful assimilation of PBL height data requires a thorough understanding of the observing method and the retrieval algorithm for each observing system in order to use the PBL height data from multiple observing systems properly. Due to the sensitivity of PBL height data to the observing method and choice of algorithm, it is important to use a model definition appropriate for each observation type to compute differences between PBL height data and model PBL height (OmFs). The GEOS model currently includes two PBL height definitions suitable for direct comparison with observed PBL height, and additional definitions are being added in this study. Evaluation of different model PBL height definitions is underway. Meanwhile, efforts have been made in the GEOS data assimilation system to develop PBL height data assimilation capability. PBL height data can be assimilated using two different approaches. The traditional approach is to construct an observation operator and its tangent linear and adjoint, which link control variables to PBL height data from each observing system. This observation operator can be very complicated, e.g., the lidar-based PBL height observation operator includes the backscatter lidar forward observation operator, the algorithm to derive PBL height from attenuated total backscatter, interpolation, and calculations handling the mismatch between observed and model scales. The other approach is to augment PBL height to the control variable vector, and it is adopted in this study. The latter approach was also used in previous studies, e.g., the assimilation of PBL height data from radiosonde and aircraft in the Real Time Mesoscale Analysis (RTMA) system for a dispersion modelling study ([13]); the PBL height assimilation study using lidar PBL height data at Greensburg, Kansas for a field campaign ([12]). The PBL height assimilation from multiple observing systems in this study allows us to take advantage of the diverse PBL height data that provide much better global coverage collectively under different meteorological conditions and with different temporal and spatial scales. As all the PBL heights are tightly coupled with the PBL thermodynamic variables, the strong correlations, which are provided by the 4D ensemble forecast, enable PBL height data from various sources to interact and combine coherently and provide additional information for PBL temperature and moisture fields. The results of comparisons among PBL height data from different sources and the evaluation of the model PBL height definitions with the PBL height data will be presented, and the PBL height data synergy strategies and preliminary results will also be discussed at the conference.

Y. Zhu↗

NASA NTRS2015

An Empirical Non-TNT Approach to Launch Vehicle Explosion Modeling

In an effort to increase crew survivability from catastrophic explosions of Launch Vehicles (LV), a study was conducted to determine the best method for predicting LV explosion environments in the near field. After reviewing such methods as TNT equivalence, Vapor Cloud Explosion (VCE) theory, and Computational Fluid Dynamics (CFD), it was determined that the best approach for this study was to assemble all available empirical data from full scale launch vehicle explosion tests and accidents. Approximately 25 accidents or full-scale tests were found that had some amount of measured blast wave, thermal, or fragment explosion environment characteristics. Blast wave overpressure was found to be much lower in the near field than predicted by most TNT equivalence methods. Additionally, fragments tended to be larger, fewer, and slower than expected if the driving force was from a high explosive type event. In light of these discoveries, a simple model for cryogenic rocket explosions is presented. Predictions from this model encompass all known applicable full scale launch vehicle explosion data. Finally, a brief description of on-going analysis and testing to further refine the launch vehicle explosion environment is discussed.

Blackwood, James M.↗

NASA NTRS1974

Interpretation of the polarization of Venus

The linear polarization of sunlight reflected by Venus is analyzed by comparing observations with extensive multiple scattering computations. The analysis establishes that Venus is veiled by a cloud or haze layer of spherical particles. The refractive index of the particles is about 1.44 at 0.55 microns with a normal dispersion, the refractive index decreasing from about 1.46 at 0.365 microns to 1.43 at 0.99 microns. The cloud particles have a narrow size distribution with a mean radius of about 1 micron; specifically, the effective radius of the size distribution is approximately 1.05 microns and the effective variance is about 0.07. The particles exist at a high level in the atmosphere, with the optical thickness unity occurring where the pressure is about 50 mb. The particle properties deduced from the polarization eliminate all but one of the cloud compositions which have been proposed for Venus. A concentrated solution of sulfuric acid provides good agreement with the polarization data.

Hansen, J. E.↗

NASA NTRS2016

Multi-Sensor Cloud and Aerosol Retrieval Simulator and Remote Sensing from Model Parameters : Aerosols - Part 2

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a simulated radiance product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers. This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled. In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model sub grid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to operational remote-sensing algorithms. Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (MOYD04). TheMOYD04 product is of course normally produced from MOYD021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a MOYD021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source. We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

aerosol retrieval↗

NASA NTRS2021

Dense 3D-Reconstruction from Monocular Image Sequences for Computationally Constrained UAS

The ability to find safe landing sites over complex 3D terrain is an essential safety feature for fully autonomous small unmanned aerial systems (UAS), which requires on-board perception for 3D reconstruction and terrain analysis if the overflown terrain is unknown. This is a challenge for UAS that are limited in size, weight and computational power, such as small rotorcrafts executing autonomous missions on Earth, or in planetary applications such as the Mars Helicopter. For such a computationally constraint system, we propose a structure from motion approach that uses inputs from a single downward facing camera to produce dense point clouds of the overflown terrain in real time. In contrast to existing approaches, our method uses metric pose information from a visual-inertial odometry algorithm as camera pose priors, which allows deploying a fast pose refinement step to align camera frames such that a conventional stereo algorithm can be used for dense 3D reconstruction. We validate the performance of our approach with extensive evaluations in simulation, and demonstrate the feasibility with data from UAS flights.

Brockers, Roland↗

NASA NTRS1990

FIRE extended time/limited area observations at Palisades, New York

Downwelling shortwave and longwave irradiation are being continuously monitored at Palisades, New York as part of the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE) Extended Time/Limited Area Initiative. In addition, fisheye (180 degree) sky photographs are taken at the times of NOAA 9 and LANDSAT satellite overpasses on select days, particularly when cirrus clouds are present. Measurements of incoming shortwave (0.28 to 2.80 microns) hemispheric and diffuse, hemispheric near infrared (0.7 to 2.80 microns), and downwelling hemispheric infrared (4.0 to 50.0 microns) irradiation have been made from a rooftop location on the grounds of the Lamont-Doherty Geological Observatory since December 1986. The three Eppley Precision Spectral Pyranometers and the Eppley Pyrgeometer used to measure these variables were calibrated with Colorado State University instruments at Madison, Wisconsin as part of the FIRE Intensive Laboratory. Pyrgeometer output contains an adjustment for body temperature but not for dome temperature. Data are transmitted to a Campbell CR-21 Digital Recorder, where one minute averages of ten second samples are stored and subsequently dumped to a cassette recorder. Using a Campbell C-20 Cassette Interface, these data are transferred to an Apple Macintosh computer for analysis and for archiving on floppy disks. In addition to the raw irradiances collected, variables derived from these data are generated and stored. These include: the ratio of near infrared irradiation to visible irradiation and the fraction of the full shortwave irradiation which is diffuse; and will soon include: shortwave transmissivity and optical depth in the shortwave. Sky photographs are taken with an Olympus OM2-N 35 mm camera and are timed to be coincident with overpassing NOAA and LANDSAT satellites. Palisades is within the field of view of the NOAA 9 daily in the middle to late afternoon. The satellite viewing angle is within 45 degrees of nadir over Palisades on approximately half of the passes.

Robinson, David A.↗

NASA NTRS1994

A statistical equilibrium analysis of interstellar CO toward zeta Ophiuchi as recorded by the Goddard High Resolution Spectrograph

High-resolution and high signal-to-noise ratio echelle observations made by the Goddard High Resolution Spectrograph (GHRS), aboard the Hubble Space Telescope, of molecular (12)C(16)O and (13)C(16)O in the absorbing gas toward zeta Oph are reported. A statistical equilibrium model, incorporating a different way of dealing with the radiation field in the interstellar clouds, is presented. Based upon previous observations, two velocity components of the gas at V(sub LSR) = - 0.79 and 0.39 km/s, corresponding to solar velocity = -14.6 and -13.4 km/s, together with three different sets of velocity dispersions are adopted in our models. The ratios of the computed emergent intensities (I(sub em)) resulting from the emission lines in the lowest transitions (J = 1 goes to 0, 2 goes to 1, 3 goes to 2) of ground state of CO are presented. The ratios for the two velocity components, (I(sub em)(1 goes to 0)(sub 1))/(I(sub em)(1 goes to 0)(sub 2)), and (I(sub em)(2 goes to 1)(sub 1))/I(sub em)(1 goes to 0)(sub 1)) are comparable to the observed corrected antenna temperature ratios. From the solutions to the statistical equilibrium equations including the six lowest rotational transitions of CO and from multiple Voigt profile fits, the observed (12)CO and (13)CO UV abroption features are successfully reproduced. Profile fitting and double cloud curve-of-growth analysis using the GHRS and Copernicus data indicate that the abundance of CO is (1.8 +/- 0.2) x 10(exp 15)/sq cm. The most recently measured wavelength of the (6 goes to 0) (13)CO band by Haridass & Huber (R(0) = 1370.616 A) shows that the tentative (13)CO features in the GHRS data are unquestionably identified. If there is no blending from any other unknown interstellar species, the isotope ratio of (12)CO/(13)CO is approximately 82 +/- 25. This result is close to the terrestrial value of 90 and implies that the CO is not substantially fractionated, and (12)C(16)O experiences little preferential self-shielding through the selective isotopic photodissociation process. This conclusion differs strongly with that of Sheffer et al. Other implications of the results are discussed.

Lyu, Cheng-Hsuan↗

NASA NTRS1997

Microphysical Retrievals Over Stratiform Rain Using Measurements from an Airborne Dual-Wavelength Radar-Radiometer

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.

Meneghini, Robert↗

NASA NTRSDate not supplied

Implementing Atmospheric Infrared Sounder (AIRS) and Cross-Track Infrared Sounder (CrIS) Cloud-Clearing Algorithm into the NASA GEOS: Focus on the 2017 Atlantic Tropical Cyclone Season

Numerical Weather Prediction (NWP) centers assimilate cloud-free infrared (IR) radiances because the assimilation of all-sky IR radiances is not yet operationally achievable. The cloud-clearing procedure offers a simpler, but effective strategy that produces cloud-affected radiances suitable for assimilation in partially cloudy regions. Several studies conducted by this team have demonstrated that IR Cloud-Cleared Radiances (CCRs), if thinned more aggressively than clear-sky radiances, can improve analysis and forecasts, particularly in meteorologically active areas. However, CCRs are not used by operational centers due partly to the thought that the process of cloud-clearing may affect latency and introduce difficult-to-control external dependencies. This study presents the results of implementing an Atmospheric Infrared Sounder (AIRS) and Cross-Track Infrared Sounder (CrIS) cloud-clearing procedure into the NASA Goddard Earth Observing System (GEOS) to demonstrate the portability of the procedure. The AIRS and CrIS cloud-clearing algorithms have been deprived of external dependencies, made customizable to any specific model, and the computational efficiency has been improved via parallelization. The revised AIRS and CrIS cloud-clearing algorithms allow a customized choice of channel selection, the use of a user-specified model's fields as first guess, and can perform in real time. Data assimilation experiments with the hybrid 4DEnVar GEOS system were successfully performed for the 2017 tropical cyclones (TC) season with a focus on three major hurricanes (Harvey, Irma, and Maria). This study shows that assimilation of locally-generated CCRs have a positive impact on both global skill and TC representation, compared to the assimilation of AIRS and CrIS clear-sky radiances, and a comparable or slightly improved impact compared to assimilation of CCRs produced by external sources, such as NASA's Distributed Active Archive Centers and NOAA’s Comprehensive Large Array-data Stewardship System. The customization and computational efficiency of the revised procedure would enable its usability in a real-time forecast context.

Niama Boukachaba↗

NASA NTRS2019

Federated Cloud Challenges in NASA's Earth Science Data Systems (Why So Difficult?)

NASA is presented with a number of opportunities and challenges in federating its Earth Science Data Systems in the burgeoning world of cloud computing. Cloud hosting of Earth Science data provides a new way of bringing data together, at least from a virtual location sense, and is one of the main motives for NASA to host data there. However, NASA is also faced with a Big Data Variety challenge, brought on by the variety of the EO datasets in its archives. This diversity requires many diverse science archives to service the different science communities. As a result, nearly every major function in the Earth Observing System Data and Information System (EOSDIS) must also be federated across its data centers. This pattern is repeated with many of the outside agencies and organizations that EOSDIS federates with, such as the Committee for Earth Observing Satellites, leading to pioneering work on "deep federation" in a joint project with the European Space Agency to develop a Multi-Mission Algorithm and Analysis Platform.

Lynnes, Christopher↗

NASA NTRSDate not supplied

Ice Shape Analysis of an eVTOL Propeller in Forward Flight at the NASA Glenn Icing Research Tunnel

Advanced Air Mobility (AAM) introduces many novel electric vertical takeoff and landing (eVTOL) aircraft configurations for which the effect of icing is not well understood. While icing computational tools have often aided in the design and certification of conventional aircraft, experimental data is needed to support the development and validation of such tools for eVTOL applications. To investigate the icing phenomenon relevant to eVTOL aircraft, NASA Glenn Research Center developed a general-purpose propeller test stand for conducting fundamental icing research on electrically driven propellers in the Icing Research Tunnel (IRT). A 10-day test entry in the IRT was completed in March, 2023, with the goal of generating ice accretions on a non-proprietary propeller geometry under well-characterized conditions. Three carbon fiber propellers of diameters 0.610, 0.711, and 0.914 m (24, 28, and 36 in) were used during the test. Various parametric sweeps of cloud and operating conditions were performed to evaluate the sensitivity of the parameters on the resulting ice accretion characteristics such as ice thickness, mass, location (impingement limits), and type (glaze vs rime). Ice shapes were reviewed for their repeatability, correctness of trends, and sensitivity to parameter variations. The data from the test is being used to support the development of the ice accretion solver, GlennICE.

Icing↗

NASA NTRS2024

Ice Shape Analysis of an eVTOL Propeller in Forward Flight at the NASA Glenn Icing Research Tunnel

Icing↗

NASA NTRS2005

Principal Component-Based Radiative Transfer Model (PCRTM) for Hyperspectral Sensors: Theoretical Concept - Part I

Modern infrared satellite sensors such as Atmospheric Infrared Sounder (AIRS), Cosmic Ray Isotope Spectrometer (CrIS), Thermal Emission Spectrometer (TES), Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) and Infrared Atmospheric Sounding Interferometer (IASI) are capable of providing high spatial and spectral resolution infrared spectra. To fully exploit the vast amount of spectral information from these instruments, super fast radiative transfer models are needed. This paper presents a novel radiative transfer model based on principal component analysis. Instead of predicting channel radiance or transmittance spectra directly, the Principal Component-based Radiative Transfer Model (PCRTM) predicts the Principal Component (PC) scores of these quantities. This prediction ability leads to significant savings in computational time. The parameterization of the PCRTM model is derived from properties of PC scores and instrument line shape functions. The PCRTM is very accurate and flexible. Due to its high speed and compressed spectral information format, it has great potential for super fast one-dimensional physical retrievals and for Numerical Weather Prediction (NWP) large volume radiance data assimilation applications. The model has been successfully developed for the National Polar-orbiting Operational Environmental Satellite System Airborne Sounder Testbed - Interferometer (NAST-I) and AIRS instruments. The PCRTM model performs monochromatic radiative transfer calculations and is able to include multiple scattering calculations to account for clouds and aerosols.

Liu, Xu↗

NASA NTRS2001

Microphysical Interpretation of Cirrus Measurements With Lidar

Cirrus measurements obtained with a ground-based polarization Raman lidar at 67.9 N in January 1997 reveal a strong correlation between the particle optical properties, specifically depolarization ratio delta and extinct ion-to-backscatter ratio S, for ambient cloud temperatures above approximately -45 C (delta less than approximately 40%), and an anti-correlation for colder temperatures (delta greater than approximately 40%). Over the length of the measurements (4-7.5 hours) the particle properties vary systematically: Initially, delta approximately equal to 60% and S approximately equal to 10sr are observed. Then, with decreasing delta, S first increases to approximately 27 sr(delta approximately equal to 40%) before decreasing to values around 10 sr again (delta approximately equal to 20%). The particle optical properties distinctly depend on the ambient temperature. For the microphysical analysis of the lidar observations. ray-tracing computations of particle scattering properties and a size-distribution resolving cirrus model with explicit microphysics have been used. The theoretical studies show that the optical properties and their temporal evolution can be interpreted in terms of size, shape, and growth of the cirrus particles: Near the cloud top in the early stage of the cirrus development, light scattering by small hexagonal columns with aspect ratios close to one is dominant. Over time the cloud base height extends to lower altitudes with warmer temperatures, the ice particles grow and get morphologically diverse (the scattering contributions of hexagonal columns and plates are roughly the same for large S and depolarization values of approximately 40%). In the lower ranges of the cirrus clouds, light scattering is predominantly by plate-like or complex ice particles. Mid-latitude cirrus data measured with the same instrument at 53.4 N between 1994 and 1996 follow closely the correlation between delta and S found in the warmer regions of the Arctic cirrus clouds (delta less than approximately 40%). Cirrus clouds with higher depolarization ratios are rarely observed, even for very cold ambient temperatures. Atmospheric parameters other than temperature, e.g., the availability of water vapor, are also important for the growth and the morphology of cirrus particles.

Reichardt, Jens↗

NASA NTRS2015

High Resolution Nature Runs and the Big Data Challenge

NASA's Global Modeling and Assimilation Office at Goddard Space Flight Center is undertaking a series of very computationally intensive Nature Runs and a downscaled reanalysis. The nature runs use the GEOS-5 as an Atmospheric General Circulation Model (AGCM) while the reanalysis uses the GEOS-5 in Data Assimilation mode. This paper will present computational challenges from three runs, two of which are AGCM and one is downscaled reanalysis using the full DAS. The nature runs will be completed at two surface grid resolutions, 7 and 3 kilometers and 72 vertical levels. The 7 km run spanned 2 years (2005-2006) and produced 4 PB of data while the 3 km run will span one year and generate 4 BP of data. The downscaled reanalysis (MERRA-II Modern-Era Reanalysis for Research and Applications) will cover 15 years and generate 1 PB of data. Our efforts to address the big data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS), a specialization of the concept of business process-as-a-service that is an evolving extension of IaaS, PaaS, and SaaS enabled by cloud computing. In this presentation, we will describe two projects that demonstrate this shift. MERRA Analytic Services (MERRA/AS) is an example of cloud-enabled CAaaS. MERRA/AS enables MapReduce analytics over MERRA reanalysis data collection by bringing together the high-performance computing, scalable data management, and a domain-specific climate data services API. NASA's High-Performance Science Cloud (HPSC) is an example of the type of compute-storage fabric required to support CAaaS. The HPSC comprises a high speed Infinib and network, high performance file systems and object storage, and a virtual system environments specific for data intensive, science applications. These technologies are providing a new tier in the data and analytic services stack that helps connect earthbound, enterprise-level data and computational resources to new customers and new mobility-driven applications and modes of work. In our experience, CAaaS lowers the barriers and risk to organizational change, fosters innovation and experimentation, and provides the agility required to meet our customers' increasing and changing needs

big data analysis↗