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NASA NTRS2007

An Experimental System for a Global Flood Prediction: From Satellite Precipitation Data to a Flood Inundation Map

Floods impact more people globally than any other type of natural disaster. It has been established by experience that the most effective means to reduce the property damage and life loss caused by floods is the development of flood early warning systems. However, advances for such a system have been constrained by the difficulty in estimating rainfall continuously over space (catchment-. national-, continental-. or even global-scale areas) and time (hourly to daily). Particularly, insufficient in situ data, long delay in data transmission and absence of real-time data sharing agreements in many trans-boundary basins hamper the development of a real-time system at the regional to global scale. In many countries around the world, particularly in the tropics where rainfall and flooding co-exist in abundance, satellite-based precipitation estimation may be the best source of rainfall data for those data scarce (ungauged) areas and trans-boundary basins. Satellite remote sensing data acquired and processed in real time can now provide the space-time information on rainfall fluxes needed to monitor severe flood events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models, which can be parameterized by a tailored geospatial database. An example that is a key to this progress is NASA's contribution to the Tropical Rainfall Measuring Mission (TRMM), launched in November 1997. Hence, in an effort to evolve toward a more hydrologically-relevant flood alert system, this talk articulates a module-structured framework for quasi-global flood potential naming, that is 'up to date' with the state of the art on satellite rainfall estimation and the improved geospatial datasets. The system is modular in design with the flexibility that permits changes in the model structure and in the choice of components. Four major components included in the system are: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM, topography-derived hydrologic parameters such as flood direction. flow accumulation, basin, and river network etc.; 3) spatially distributed hydrological models to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay thc input data to the models and display the flood inundation results to the users and decision-makers. Early results appear reasonable in terms of location and frequency of events. Case studies of this experimental system are evaluated with surface runoff data and other river monitoring systems. such as Dartmouth Flood Observatory's "Surface Water Watch" array of river reaches that are measured daily via other satellite remote sensing data. A major outcome of this progress will be the availability of a global overview of flood alerts that should consequently improve the performance of Decision Support System. We expect these developments in utilization of satellite remote sensing technology to offer a practical solution to the challenge of building a cost-effective early warning system for data scarce and under-developed areas.

Adler, Robert↗

NASA NTRS2019

Analysis Ready Data in Analytics Optimized Data Stores for Analysis of Big Earth Data in the Cloud

Cloud computing offers the possibility of making the analysis of Big Data approachable for a wider community due to affordable access to computing power, an ecosystem of usable tools for parallel processing, and migration of many large datasets to archives in the cloud, allowing data-proximal computing. Generally, data analysis acceleration in the cloud comes from running multiple nodes in a split-combine-apply strategy. Data systems such as the Earth Observing System Data and Information System are in a position to "pre-split" the data by storing them in a data store that is optimized for data parallel computing, i.e., an Analytics-Optimized Data Store (AODS). A variety of approaches to AODS are possible, from highly scalable databases to scalable filesystems to data formats optimized for cloud access (e.g., zarr and cloud-optimized datasets), with the optimal choice dependent on both the types of analysis and the geospatial structure of the data. A key question is how much preprocessing of the data to do, both before splitting and as the first part of the apply step. Again, the geospatial structure of the data and the analysis type influence the decision, with the added complexity of the user type. Trans-disciplinary users who are not well-versed in the nuances of quality-filtering and georeferencing of remote sensing orbit/swath/scene data tend to ask for more highly processed data, relying on the data provider to make sensible decisions on preprocessing parameters. (This accounts for the popularity of "Level 3" gridded data, despite the lower spatial resolution it provides.) In this case, data can be preprocessed before the split, resulting in higher performance in the rest of the "apply" step, which can be transformative for use cases such as interactive data exploration at scale. Discipline researchers who are experienced with remote sensing data often prefer more flexibility in customizing the preprocessing data into Analysis Ready Data, resulting in more need for on-the-fly preprocessing.

Lynnes, Christopher↗

NASA NTRSDate not supplied

Overview of NASA’s Science Mission Directorate Small Satellites Programs and Advances in Transformative Science Measurements with Small Satellites

Small satellites have become an accepted platform for enabling high-quality science measurements and observations. NASA missions have leveraged advances in sensor miniaturization, technology innovations, and new small satellite mission architectures to support high spatial and temporal measurements, continuity measurements, and constellations in response to science objectives described in NASA’s Decadal Surveys. Across six divisions of the Science Mission Directorate (SMD), over 12 years, SMD has funded 88 CubeSat/ SmallSat Missions and 59 Studies to date. Currently, SMD has 53 small spacecraft science missions (87spacecraft) in implementation or formulation. This paper provides the background of efforts to promote the implementation of small satellites within NASA as a balanced portfolio for the agency’s science, technology, and exploration goals. We include analysis of SmallSat awards and trends funded by SMD through Research Opportunities in Space and Earth Sciences (ROSES), Small Innovative Missions for Planetary Exploration (SIMPLEx), and Small Explorer (SMEX) and Medium Explorer (MIDEX) calls over the last 12years. The data source of this assessment is a subset of the NASA SmallSat Coordination Group Database, a collection of all known funded NASA SmallSat and CubeSat missions and studies. This paper also provides an overview of small satellite programs and selected missions from SMD’s divisions: Astrophysics, Heliophysics, Earth Science, and Planetary Science, and describes SMD’s efforts in fostering an incremental and continuous path to achieve high-priority science through transformative science measurements. This paper recognizes the latest observations and trends of the NASA CubeSat / SmallSat Science missions with masses ranging between 1kg to 500kg.

Small Satellites, SMD SmallSat, CubeSat,↗

NASA NTRSDate not supplied

Advances in Transformative Science Measurements with Small Satellites

Small satellites have become an accepted platform for enabling high-quality science measurements and observations. NASA missions have leveraged advances in sensor miniaturization, technology innovations, and new small satellite mission architectures to support high spatial and temporal measurements, continuity measurements, and constellations in response to science objectives described in NASA’s Decadal Surveys. Across six divisions of the Science Mission Directorate (SMD), over 12 years, SMD has funded 88 CubeSat/ SmallSat Missions and 59 Studies to date. Currently, SMD has 53 small spacecraft science missions (87spacecraft) in implementation or formulation. This paper provides the background of efforts to promote the implementation of small satellites within NASA as a balanced portfolio for the agency’s science, technology, and exploration goals. We include analysis of SmallSat awards and trends funded by SMD through Research Opportunities in Space and Earth Sciences (ROSES), Small Innovative Missions for Planetary Exploration (SIMPLEx), and Small Explorer (SMEX) and Medium Explorer (MIDEX) calls over the last 12years. The data source of this assessment is a subset of the NASA SmallSat Coordination Group Database, a collection of all known funded NASA SmallSat and CubeSat missions and studies. This paper also provides an overview of small satellite programs and selected missions from SMD’s divisions: Astrophysics, Heliophysics, Earth Science, and Planetary Science, and describes SMD’s efforts in fostering an incremental and continuous path to achieve high-priority science through transformative science measurements. This presentation recognizes the latest observations and trends of the NASA CubeSat / SmallSat Science missions with masses ranging between 1kg to 500kg.

Small Satellites, SMD SmallSat, CubeSat↗

NASA NTRS2010

Advances in Landslide Hazard Forecasting: Evaluation of Global and Regional Modeling Approach

A prototype global satellite-based landslide hazard algorithm has been developed to identify areas that exhibit a high potential for landslide activity by combining a calculation of landslide susceptibility with satellite-derived rainfall estimates. A recent evaluation of this algorithm framework found that while this tool represents an important first step in larger-scale landslide forecasting efforts, it requires several modifications before it can be fully realized as an operational tool. The evaluation finds that the landslide forecasting may be more feasible at a regional scale. This study draws upon a prior work's recommendations to develop a new approach for considering landslide susceptibility and forecasting at the regional scale. This case study uses a database of landslides triggered by Hurricane Mitch in 1998 over four countries in Central America: Guatemala, Honduras, EI Salvador and Nicaragua. A regional susceptibility map is calculated from satellite and surface datasets using a statistical methodology. The susceptibility map is tested with a regional rainfall intensity-duration triggering relationship and results are compared to global algorithm framework for the Hurricane Mitch event. The statistical results suggest that this regional investigation provides one plausible way to approach some of the data and resolution issues identified in the global assessment, providing more realistic landslide forecasts for this case study. Evaluation of landslide hazards for this extreme event helps to identify several potential improvements of the algorithm framework, but also highlights several remaining challenges for the algorithm assessment, transferability and performance accuracy. Evaluation challenges include representation errors from comparing susceptibility maps of different spatial resolutions, biases in event-based landslide inventory data, and limited nonlandslide event data for more comprehensive evaluation. Additional factors that may improve algorithm performance accuracy include incorporating additional triggering factors such as tectonic activity, anthropogenic impacts and soil moisture into the algorithm calculation. Despite these limitations, the methodology presented in this regional evaluation is both straightforward to calculate and easy to interpret, making results transferable between regions and allowing findings to be placed within an inter-comparison framework. The regional algorithm scenario represents an important step in advancing regional and global-scale landslide hazard assessment and forecasting.

Kirschbaum, Dalia B.↗

NASA NTRS2011

Spatial Distribution of Volcanic Hotspots and Paterae on Io: Implications for Tidal Heating Models and Magmatic Pathways

Io, the innermost of Jupiter's Galilean satellites, is the most volcanically active body in the Solar. System. Io's global mean heat flow is approximately 2 W/square m, which is approximately 20 times larger than on Earth. High surface temperatures concentrate within "hotspots" and, to date, 172 Ionian hotspots have been identified by spacecraft and Earth-based telescopes. The Laplace resonance between Io, Europa, and Ganymede maintains these satellites in noncircular orbits and causes displacement of their tidal bulges as the overhead position of Jupiter changes for each moon. Gravitational interactions between Jupiter and Io dominate the orbital evolution of the Laplacian system and generate enormous heat within to as tidal energy is dissipated. If this energy were transferred out of Io at the same rate as it is generated, then the associated surface heat flux would be 2.24 +/- 0.45 W/square m. This estimate is in good agreement with observed global heat flow, but to better constrain tidal dissipation mechanisms and infer how thermal energy is transferred to Io's surface, it is critical to closely examine the spatial distribution of volcanic features. End-member tidal dissipation models either consider that heating occurs completely in the mantle, or completely in the asthenosphere. Mixed models typically favor one-third mantle and two-thirds asthenosphere heating. Recent models also consider the effects of mantle-asthenosphere boundary permeability and asthenospheric instabilities. Deep-mantle heating models predict maximum surface heat flux near the poles, whereas asthenosphere heating models predict maxima near the equator-particularly in the Sub-Jovian and Anti-Jovian hemispheres, with smaller maxima occurring at orbit tangent longitudes. Previous studies have examined the global distribution of Ionian hotspots and patera (i.e., irregular or complex craters with scalloped edges that are generally interpreted to be volcanic calderas), but in this study, we combine a new geospatial analysis technique with an improved hotspot and paterae database .

Hamilton, C. W.↗

NASA NTRS2014

Analysis of Inter-Moss Loops in the Solar Region with IRIS and SDO AIA: Automatic Event Detection and Characterization

The Interface Region Imaging Spectrograph (IRIS), launched in the summer of 2013, is designed specifically to observe and investigate the transition region and adjacent layers of the solar atmosphere, obtaining images in high spatial, temporal, and spectral resolution. Our particular work is focused on the evolution of inter-moss loops, which have been detected in the lower corona by the Atmospheric Imaging Assembly (AIA) and the High-Resolution Coronal Imager (Hi- C), but are known to have foot points below the transition region. With the high-resolution capabilities of IRIS and its Si IV pass band, which measures activity in the upper chromosphere, we can study these magnetic loops in detail and compare their characteristic length and time scales to those obtained from several AIA image sets, particularly the 171, 193, and 211 pass bands. By comparing the results between these four data sets, one can potentially establish a measure of the ionization equilibrium for the location in question. To explore this idea, we found a large, sit-and-stare observation within the IRIS database that fit our specifications. This data set contained a number of well-defined inter-moss loops (by visual inspection) with a cadence less than or equal to that of AIA (approximately 12 seconds). This particular data set was recorded on October 23, 2013 at 07:09:30, lasting for 3219 seconds with a field of view of 120.6 by 128.1 arcseconds, centered on -53.9 by 59.1 arcseconds from disk center. For ease of comparison, the AIA data has been interpolated to match the IRIS cadence and resolution. In the main portion of the poster, we demonstrate the detection of events, the information collected, and the immediate results to the right, showing the progress of an event with green as the start, blue as the peak, and red as the end. Below here, we demonstrate how pixels are combined to form groups. The 3D results are shown to the right.

event detection↗

NASA NTRS2016

Analysis of Inter-Moss Loops in the Solar Region with IRIS and SDO AIA: Automatic Event Detection and Characterization

IRIS↗

NASA NTRS2007

Methods for Characterizing Fine Particulate Matter Using Satellite Remote-Sensing Data and Ground Observations: Potential Use for Environmental Public Health Surveillance

This study describes and demonstrates different techniques for surfacing daily environmental / hazards data of particulate matter with aerodynamic diameter less than or equal to 2.5 micrometers (PM2.5) for the purpose of integrating respiratory health and environmental data for the Centers for Disease Control and Prevention (CDC s) pilot study of Health and Environment Linked for Information Exchange (HELIX)-Atlanta. It described a methodology for estimating ground-level continuous PM2.5 concentrations using B-Spline and inverse distance weighting (IDW) surfacing techniques and leveraging National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectrometer (MODIS) data to complement The Environmental Protection Agency (EPA) ground observation data. The study used measurements of ambient PM2.5 from the EPA database for the year 2003 as well as PM2.5 estimates derived from NASA s satellite data. Hazard data have been processed to derive the surrogate exposure PM2.5 estimates. The paper has shown that merging MODIS remote sensing data with surface observations of PM2.5 not only provides a more complete daily representation of PM2.5 than either data set alone would allow, but it also reduces the errors in the PM2.5 estimated surfaces. The results of this paper have shown that the daily IDW PM2.5 surfaces had smaller errors, with respect to observations, than those of the B-Spline surfaces in the year studied. However the IDW mean annual composite surface had more numerical artifacts, which could be due to the interpolating nature of the IDW that assumes that the maxima and minima can occur only at the observation points. Finally, the methods discussed in this paper improve temporal and spatial resolutions and establish a foundation for environmental public health linkage and association studies for which determining the concentrations of an environmental hazard such as PM2.5 with good accuracy levels is critical.

Al-Hamdan, Mohammad Z.↗

NASA NTRSDate not supplied

Kalman Filtering and RTS Smoothing for Arc-Jet Sample Edge Tracking

Accurate and temporally consistent measurements of test-article recession are required to characterize material response during arc-jet ablation experiments. However, image-based boundary measurements are often affected by segmentation noise, brightness variations, and frame-to-frame variability. This work extends arcjetCV [1] with filtering methods for tracking the evolving boundaries of hemispherical and ISO-Q test articles. Two boundary-tracking approaches based on Kalman filtering [2] were implemented. The first applies a point-wise Kalman filter followed by a Rauch–Tung–Striebel smoother [3] to individual boundary-point locations. The second applies the same filtering and smoothing framework to a reduced set of geometry-dependent shape parameters. The point-wise method reduces local frame-to-frame fluctuations while preserving spatial details along the detected boundary. The shape-parameter method provides a compact and geometrically constrained estimate of the sample contour. Figure 1 illustrates the two approaches for a hemispherical test article. Both methods improve temporal consistency and support more robust estimation of surface recession from arc-jet imagery. The two filtering approaches provide complementary representations of boundary evolution and improve the reliability of image-based recession measurements during arc-jet experiments.

recession measurement↗

NASA NTRS2004

Effect of aerosols and clouds on the retrieval of infrared sea surface temperatures

Comparisons are performed between spatially averaged sea surface temperatures (ASST2) as derived from the second Along-Track Scanning Radiometer (ATSR-2) on board the second European Remote Sensing Satellite (ERS-2) and the NOAA–NASA Advanced Very High Resolution Radiometer (AVHRR) Oceans Pathfinder dataset (MPFSST). Difference maps, MPFSST 2 ASST2, along with the application of a simple statistical regression model to aerosol and cloud data from the Total Ozone Mapping Spectrometer (TOMS), are used to examine the impact of possible aerosol and cloud contamination. Differences varied regionally, but the largest biases were seen off western Africa. Nighttime and daytime differences off western Africa were reduced from 20.58 to 20.28C and from 20.18 to 08C, respectively. Significant cloud flagging, based on the model, occurred in the Indian Ocean, the equatorial Pacific, and in the vicinity of the Gulf Stream. Comparisons of the MPFSST and the ASST2 with in situ data from the 2002 version of the World Oceanic Database (WOD02) off western Africa show larger mean differences for the MPFSST. The smallest mean differences occurred for nighttime ASST2 2 WOD02 with a value of 0.08 6 0.48C.

Armstrong, Edward M.↗

NASA NTRS2004

The Effect of Aerosols and Clouds on the Retrieval of Infrared Sea Surface Temperatures

Comparisons are performed between spatially averaged sea surface temperatures (ASST2) as derived from the second Along-Track Scanning Radiometer (ATSR-2) on board the second European Remote Sensing Satellite (ERS-2) and the NOAA-NASA Advanced Very High Resolution Radiometer (AVHRR) Oceans Pathfinder dataset (MPFSST). Difference maps, MPFSST 2 ASST2, along with the application of a simple statistical regression model to aerosol and cloud data from the Total Ozone Mapping Spectrometer ( TOMS), are used to examine the impact of possible aerosol and cloud contamination. Differences varied regionally, but the largest biases were seen off western Africa. Nighttime and daytime differences off western Africa were reduced from -0.5degrees to -0.2degreesC and from -0.1degrees to 0degreesC, respectively. Significant cloud flagging, based on the model, occurred in the Indian Ocean, the equatorial Pacific, and in the vicinity of the Gulf Stream. Comparisons of the MPFSST and the ASST2 with in situ data from the 2002 version of the World Oceanic Database (WOD02) off western Africa show larger mean differences for the MPFSST. The smallest mean differences occurred for nighttime ASST2 - WOD02 with a value of 0.0degrees +/- 0.4degreesC.

clouds↗

NASA NTRS2014

ENSO Effect on East Asian Tropical Cyclone Landfall via Changes in Tracks and Genesis in a Statistical Model

Improvements on a statistical tropical cyclone (TC) track model in the western North Pacific Ocean are described. The goal of the model is to study the effect of El Nino-Southern Oscillation (ENSO) on East Asian TC landfall. The model is based on the International Best-Track Archive for Climate Stewardship (IBTrACS) database of TC observations for 1945-2007 and employs local regression of TC formation rates and track increments on the Nino-3.4 index and seasonally varying climate parameters. The main improvements are the inclusion of ENSO dependence in the track propagation and accounting for seasonality in both genesis and tracks. A comparison of simulations of the 1945-2007 period with observations concludes that the model updates improve the skill of this model in simulating TCs. Changes in TC genesis and tracks are analyzed separately and cumulatively in simulations of stationary extreme ENSO states. ENSO effects on regional (100-km scale) landfall are attributed to changes in genesis and tracks. The effect of ENSO on genesis is predominantly a shift in genesis location from the southeast in El Nino years to the northwest in La Nina years, resulting in higher landfall rates for the East Asian coast during La Nina. The effect of ENSO on track propagation varies seasonally and spatially. In the peak activity season (July-October), there are significant changes in mean tracks with ENSO. Landfall-rate changes from genesis- and track-ENSO effects in the Philippines cancel out, while coastal segments of Vietnam, China, the Korean Peninsula, and Japan show enhanced La Nina-year increases.

simulation↗

NASA NTRS2001

Astronaut Photography of Coral Reefs

Astronaut photographs of tropical coastal areas may contain information on submerged features, including coral reefs, up to depths of about 15 m in clear waters. Previous research efforts have shown that astronaut photographs can aid in estimating coral reef locations and extent on national, regional and global scales, and allow characterization of major geomorphological rim and lagoon features (Andrefouet et al. 2000, in preparation). They can be combined with traditional satellite data to help distinguish between clouds and lagoon features such as pinnacles (Andrefouet and Robinson, in review). Furthermore, astronaut photographs may provide reef scientists and managers with information on the location and extent of river plumes and sediment run off, or facilitate identification of land cover types, including mangroves (Webb et al., in press). Photographs included in the section were selected based on several criteria. The primary consideration of the editors was that the photographs represent a worldwide distribution of coral reefs, have extremely low visual interference by cloud cover, and display a spatial scale reasonable for examining reef-related features. Once photographs were selected, they were digitized from 2nd generation copies. The color and contrast were hand corrected to an approximation of natural color (required to account for spectral differences between photographs due to the color sensitivities of films used, and differences in sun angle and exposure of the photographs). None of the photographs shown here have been georeferenced to correct them to a map projection and scale. Any distortions in features due to slightly oblique look angles when the photographs were taken through spacecraft windows remain. When feasible, near vertical photographs have been rotated so that north is toward the top. An approximate scale bar and north arrow have added using distinctive features on each photograph with reference to a 1:1,000,000 scale navigation chart. Astronaut photographs provide a unique source of moderate resolution reef remote sensing data because of their global coverage and (immediate) availability in the public domain. The database of photographs can be searched an browsed online and high-resolution digital copies of photographs in this atlas can be accessed via the Website of Earth Science and Image Analysis at NASA's Johnson Space Center:

Robinson, Julie A.↗

NASA NTRS1994

HRMA calibration handbook: EKC gravity compensated XRCF models

This document, consisting of hardcopy printout of explanatory text, figures, and tables, represents one incarnation of the AXAF high resolution mirror assembly (HRMA) Calibration Handbook. However, as we have envisioned it, the handbook also consists of electronic versions of this hardcopy printout (in the form of postscript files), the individual scripts which produced the various figures and the associated input data, the model raytrace files, and all scripts, parameter files, and input data necessary to generate the raytraces. These data are all available electronically as either ASCII or FITS files. The handbook is intended to be a living document and will be updated as new information and/or fabrication data on the HRMA are obtained, or when the need for additional results are indicated. The SAO Mission Support Team (MST) is developing a high fidelity HRMA model, consisting of analytical and numerical calculations, computer software, and databases of fundamental physical constants, laboratory measurements, configuration data, finite element models, AXAF assembly data, and so on. This model serves as the basis for the simulations presented in the handbook. The 'core' of the model is the raytrace package OSAC, which we have substantially modified and now refer to as SAOsac. One major structural modification to the software has been to utilize the UNIX binary pipe data transport mechanism for passing rays between program modules. This change has made it possible to simulate rays which are distributed randomly over the entrance aperture of the telescope. It has also resulted in a highly efficient system for tracing large numbers of rays. In one application to date (the analysis of VETA-I ring focus data) we have employed 2 x 10(exp 7) rays, a substantial improvement over the limit of 1 x 10(exp 4) rays in the original OSAC module. A second major modification is the manner in which SAOsac incorporates low spatial frequency surface errors into the geometric raytrace. The original OSAC included the ability to use Legendre-Fourier polynomials to describe deviations from the basic optical prescription. To this we have added bicubic splines to address a deficiency in the handling of the sharper deformations in the areas of mirror support pads. SAO has developed software (TRANS-FIT) to translate the most common finite element analysis models into these forms for incorporation into the raytrace program.

Tananbaum, H. D.↗

NASA NTRS2008

The NASA MSFC Earth Global Reference Atmospheric Model-2007 Version

Reference or standard atmospheric models have long been used for design and mission planning of various aerospace systems. The NASA/Marshall Space Flight Center (MSFC) Global Reference Atmospheric Model (GRAM) was developed in response to the need for a design reference atmosphere that provides complete global geographical variability, and complete altitude coverage (surface to orbital altitudes) as well as complete seasonal and monthly variability of the thermodynamic variables and wind components. A unique feature of GRAM is that, addition to providing the geographical, height, and monthly variation of the mean atmospheric state, it includes the ability to simulate spatial and temporal perturbations in these atmospheric parameters (e.g. fluctuations due to turbulence and other atmospheric perturbation phenomena). A summary comparing GRAM features to characteristics and features of other reference or standard atmospheric models, can be found Guide to Reference and Standard Atmosphere Models. The original GRAM has undergone a series of improvements over the years with recent additions and changes. The software program is called Earth-GRAM2007 to distinguish it from similar programs for other bodies (e.g. Mars, Venus, Neptune, and Titan). However, in order to make this Technical Memorandum (TM) more readable, the software will be referred to simply as GRAM07 or GRAM unless additional clarity is needed. Section 1 provides an overview of the basic features of GRAM07 including the newly added features. Section 2 provides a more detailed description of GRAM07 and how the model output generated. Section 3 presents sample results. Appendices A and B describe the Global Upper Air Climatic Atlas (GUACA) data and the Global Gridded Air Statistics (GGUAS) database. Appendix C provides instructions for compiling and running GRAM07. Appendix D gives a description of the required NAMELIST format input. Appendix E gives sample output. Appendix F provides a list of available parameters to enable the user to generate special output. Appendix G gives an example and guidance on incorporating GRAM07 as a subroutine in other programs such as trajectory codes or orbital propagation routines.

Leslie, F.W.↗

NASA NTRS1990

A neural network approach to cloud classification

It is shown that, using high-spatial-resolution data, very high cloud classification accuracies can be obtained with a neural network approach. A texture-based neural network classifier using only single-channel visible Landsat MSS imagery achieves an overall cloud identification accuracy of 93 percent. Cirrus can be distinguished from boundary layer cloudiness with an accuracy of 96 percent, without the use of an infrared channel. Stratocumulus is retrieved with an accuracy of 92 percent, cumulus at 90 percent. The use of the neural network does not improve cirrus classification accuracy. Rather, its main effect is in the improved separation between stratocumulus and cumulus cloudiness. While most cloud classification algorithms rely on linear parametric schemes, the present study is based on a nonlinear, nonparametric four-layer neural network approach. A three-layer neural network architecture, the nonparametric K-nearest neighbor approach, and the linear stepwise discriminant analysis procedure are compared. A significant finding is that significantly higher accuracies are attained with the nonparametric approaches using only 20 percent of the database as training data, compared to 67 percent of the database in the linear approach.

Lee, Jonathan↗

NASA NTRS2015

Resolving Ice Cloud Optical Thickness Biases Between CALIOP and MODIS Using Infrared Retrievals

Despite its importance as one of the key radiative properties that determines the impact of upper tropospheric clouds on the radiation balance, ice cloud optical thickness (IOT) has proven to be one of the more challenging properties to retrieve from space-based remote sensing measurements. In particular, optically thin upper tropospheric ice clouds (cirrus) have been especially challenging due to their tenuous nature, extensive spatial scales, and complex particle shapes and light scattering characteristics. The lack of independent validation motivates the investigation presented in this paper, wherein systematic biases between MODIS Collection 5 (C5) and CALIOP Version 3 (V3) unconstrained retrievals of tenuous IOT (< 3) are examined using a month of collocated A-Train observations. An initial comparison revealed a factor of two bias between the MODIS and CALIOP IOT retrievals. This bias is investigated using an infrared (IR) radiative closure approach that compares both products with MODIS IR cirrus retrievals developed for this assessment. The analysis finds that both the MODIS C5 and the unconstrained CALIOP V3 retrievals are biased (high and low, respectively) relative to the IR IOT retrievals. Based on this finding, the MODIS and CALIOP algorithms are investigated with the goal of explaining and minimizing the biases relative to the IR. For MODIS we find that the assumed ice single scattering properties used for the C5 retrievals are not consistent with the mean IR COT distribution. The C5 ice scattering database results in the asymmetry parameter (g) varying as a function of effective radius with mean values that are too large. The MODIS retrievals have been brought into agreement with the IR by adopting a new ice scattering model for Collection 6 (C6) consisting of a modified gamma distribution comprised of a single habit (severely roughened aggregated columns); the C6 ice cloud optical property models have a constant g approx. = 0.75 in the mid-visible spectrum, 5-15% smaller than C5. For CALIOP, the assumed lidar ratio for unconstrained retrievals is fixed at 25 sr for the V3 data products.This value is found to be inconsistent with the constrained (predominantly nighttime) CALIOP retrievals. An experimental data set was produced using a modified lidar ratio of 32 sr for the unconstrained retrievals (an increase of 28%), selected to provide consistency with the constrained V3 results. These modifications greatly improve the agreement with the IR and provide consistency between the MODIS and CALIOP products. Based on these results the recently released MODIS C6 optical products use the single habit distribution given above, while the upcoming CALIOP V4 unconstrained algorithm will use higher lidar ratios for unconstrained retrievals.

Cloud↗