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NASA NTRS1987

Objective method for analysis and tracking of convective cells as seen by radar

A special method has been developed for the study of cells that are embedded in convective rain systems. This method consists of a package of computer programs that use pattern recognition techniques on three-dimensional digital radar data to identify the rain cells, track them with time, and calculate their properties. The product of the computations is a comprehensive database of physically meaningful properties of rain cells, which can be used to infer the internal structure and the dynamics of convective rain systems. The cell-tracking method has been applied to the summer convective clouds of south Florida for the following purposes: (1) derivation of the relationship between the echo top height and the precipitation characteristics (e.g., area, water yield, rain intensity and duration of the rain cells); (2) study of the microphysical behaviorof cumulus clouds in relation to their cell properties; (3) evaluation of the effect of seeding on cumulus clouds on the cell scale; and (4) examination of cloud-to-ground lightning discharges in relation to convective cell intensity. The cell-tracking method is also currently being used in rain enhancement projects in Texas, Israel, and South Africa. The cell-tracking method, its products and their use in meteorological research are described in this paper.

Rosenfeld, Daniel↗

NASA NTRSDate not supplied

Bimodal SLD Ice Accretion on Swept NACA 0012 Airfoil Models

An ice shape database has been created to document ice accretions on a swept 15-inch chord NACA0012 model and a swept 36-inch chord NACA0012 airfoil model resulting from an exposure to a Supercooled Large Drop (SLD) icing cloud with a bimodal drop size distribution. The ice shapes created were documented with photographs, laser scanned surface measurements over a section of the model span, and measurement of the ice mass over the same section of each accretion. The icing conditions were based on a series of reference conditions that were previously used to generate ice shapes on these models. Drop distribution effects were evaluated by using the same IRT icing conditions except with either monomodal or bimodal drop distributions. Ice shapes resulting from the bimodal distribution as well as from equivalent monomodal drop size distributions were obtained and compared. Results indicate that the ice shapes and mass values from the monomodal and bimodal drop size distributions were the same within the range of repeatability for the conditions tested in this campaign.

Icing↗

NASA NTRS2011

Towards an Improved High Resolution Global Long-Term Solar Resource Database

This paper presents an overview of an ongoing project to develop and deliver a solar mapping processing system to the National Renewable Energy Laboratory (NREL) using the data sets that are planned for production at the National Climatic Data Center (NCDC). NCDC will be producing a long-term radiance and cloud property data set covering the globe every three hours at an approximate resolution of 10 x 10 km. NASA, the originators of the Surface meteorology and Solar Energy web portal are collaborating with SUNY-Albany to develop the production system and solar algorithms. The initial result will be a global long-term solar resource data set spanning over 25 years. The ultimate goal of the project is to also deliver this data set and production system to NREL for continual production. The project will also assess the impact of providing these new data to several NREL solar decision support tools.

Stackhouse, Paul W.↗

NASA NTRS2011

Flight Planning in the Cloud

This new interface will enable Principal Investigators (PIs), as well as UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar) members to do their own flight planning and time estimation without having to request flight lines through the science coordinator. It uses an all-in-one Google Maps interface, a JPL hosted database, and PI flight requirements to design an airborne flight plan. The application will enable users to see their own flight plan being constructed interactively through a map interface, and then the flight planning software will generate all the files necessary for the flight. Afterward, the UAVSAR team can then complete the flight request, including calendaring and supplying requisite flight request files in the expected format for processing by NASA s airborne science program. Some of the main features of the interface include drawing flight lines on the map, nudging them, adding them to the current flight plan, and reordering them. The user can also search and select takeoff, landing, and intermediate airports. As the flight plan is constructed, all of its components are constantly being saved to the database, and the estimated flight times are updated. Another feature is the ability to import flight lines from previously saved flight plans. One of the main motivations was to make this Web application as simple and intuitive as possible, while also being dynamic and robust. This Web application can easily be extended to support other airborne instruments.

Flores, Sarah L.↗

DOE OSTI2023

Simulated sulfur K-edge X-ray absorption spectroscopy database of lithium thiophosphate solid electrolytes

X-ray absorption spectroscopy (XAS) is a premier technique for materials characterization, providing key information about the local chemical environment of the absorber atom. In this work, we develop a database of sulfur K-edge XAS spectra of crystalline and amorphous lithium thiophosphate materials based on the atomic structures reported in Chem. Mater., 34, 6702 (2022). The XAS database is based on simulations using the excited electron and core-hole pseudopotential approach implemented in the Vienna Ab initio Simulation Package. Our database contains 2681 S K-edge XAS spectra for 66 crystalline and glassy structure models, making it the largest collection of first-principles computational XAS spectra for glass/ceramic lithium thiophosphates to date. This database can be used to correlate S spectral features with distinct S species based on their local coordination and short-range ordering in sulfide-based solid electrolytes. The data is openly distributed via the Materials Cloud, allowing researchers to access it for free and use it for further analysis, such as spectral fingerprinting, matching with experiments, and developing machine learning models.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Bimodal SLD Ice Accretion on a CRM Midspan Wing Section Model

An ice shape database has been created to document ice accretions on a 65 per cent scale version of the mid-span section of the Common Research Model resulting from an exposure to a Supercooled Large Drop (SLD) icing cloud with a bimodal drop size distribution. The ice shapes created were documented with photographs, laser scanned surface measurements over a section of the model span, and measurement of the ice mass over the same section of each accretion. Drop distribution effects were evaluated by using the same IRT icing conditions except with either monomodal or bimodal drop distributions. Ice shapes resulting from the bimodal distribution as well as from equivalent monomodal drop size distributions were obtained and compared. Results indicate that the ice shapes resulting from the monomodal and bimodal drop size distributions had equivalent mass and volume, as expected with this approach. Note: No audio portion for this record, additionally slide 9 has a playable video but must be downed in order to view.

Icing↗

DOE OSTI2022

Scalability Testing Approach for Internet of Things for Manufacturing SQL and NoSQL Database Latency and Throughput

The proliferation of low-cost sensors and industrial data solutions has continued to push the frontier of manufacturing technology. Machine learning and other advanced statistical techniques stand to provide tremendous advantages in production capabilities, optimization, monitoring, and efficiency. The tremendous volume of data gathered continues to grow, and the methods for storing the data are critical underpinnings for advancing manufacturing technology. This work aims to investigate the ramifications and design tradeoffs within a decoupled architecture of two prominent database management systems (DBMS): sql and NoSQL. A representative comparison is carried out with Amazon Web Services (AWS) DynamoDB and AWS Aurora MySQL. The technologies and accompanying design constraints are investigated, and a side-by-side comparison is carried out through high-fidelity industrial data simulated load tests using metrics from a major US manufacturer. The results support the use of simulated client load testing for comparing the latency of database management systems as a system scales up from the prototype stage into production. As a result of complex query support, MySQL is favored for higher-order insights, while NoSQL can reduce system latency for known access patterns at the expense of integrated query flexibility. Here, by reviewing this work, a manufacturer can observe that the use of high-fidelity load testing can reveal tradeoffs in IoTfM write/ingestion performance in terms of latency that are not observable through prototype-scale testing of commercially available cloud DB solutions.

AWS↗

NASA NTRS1988

Long-term changes in reflectivity and large scale motions in the atmosphere of Jupiter and Saturn

A systematic photographic program, utilizing broad-band UV, blue, green, red and near IR pass-bands were carried out at the 60 cm. Tortugas Mountain Telescope. This is part of an ongoing program that spans two Jovian years (25 yrs). The purpose of this program is to provide an ongoing database to characterize high resolution data from spacecraft and earth-orbiting observatories. The standard observing program was maintained and support was given to other investigators who are carrying out complementary observing programs. The general aspect of the cloud decks were monitored, and reveal an interval that shows little variation in the general aspect of the clouddeck of Jupiter since 1981, when the North Temperature Belt darkened. A charge coupled device (CCD) camera was adapted for low cost operation, utilizing an IBM-AT clone for data acquisition. An RCA frame grabber was modified for encoding the archival images.

Beebe, Reta↗

NASA NTRS2006

Quantifying Global Uncertainties in a Simple Microwave Rainfall Algorithm

While a large number of methods exist in the literature for retrieving rainfall from passive microwave brightness temperatures, little has been written about the quantitative assessment of the expected uncertainties in these rainfall products at various time and space scales. The latter is the result of two factors: sparse validation sites over most of the world's oceans, and algorithm sensitivities to rainfall regimes that cause inconsistencies against validation data collected at different locations. To make progress in this area, a simple probabilistic algorithm is developed. The algorithm uses an a priori database constructed from the Tropical Rainfall Measuring Mission (TRMM) radar data coupled with radiative transfer computations. Unlike efforts designed to improve rainfall products, this algorithm takes a step backward in order to focus on uncertainties. In addition to inversion uncertainties, the construction of the algorithm allows errors resulting from incorrect databases, incomplete databases, and time- and space-varying databases to be examined. These are quantified. Results show that the simple algorithm reduces errors introduced by imperfect knowledge of precipitation radar (PR) rain by a factor of 4 relative to an algorithm that is tuned to the PR rainfall. Database completeness does not introduce any additional uncertainty at the global scale, while climatologically distinct space/time domains add approximately 25% uncertainty that cannot be detected by a radiometer alone. Of this value, 20% is attributed to changes in cloud morphology and microphysics, while 5% is a result of changes in the rain/no-rain thresholds. All but 2%-3% of this variability can be accounted for by considering the implicit assumptions in the algorithm. Additional uncertainties introduced by the details of the algorithm formulation are not quantified in this study because of the need for independent measurements that are beyond the scope of this paper. A validation strategy for these errors is outlined.

Kummerow, Christian↗

NASA NTRS2017

Remote Sensing of Crystal Shapes in Ice Clouds

Ice crystals in clouds exist in a virtually limitless variation of geometries. The most basic shapes of ice crystals are columnar or plate-like hexagonal prisms with aspect ratios determined by relative humidity and temperature. However, crystals in ice clouds generally display more complex structures owing to aggregation, riming and growth histories through varying temperature and humidity regimes. Crystal shape is relevant for cloud evolution as it affects microphysical properties such as fall speeds and aggregation efficiency. Furthermore, the scattering properties of ice crystals are affected by their general shape, as well as by microscopic features such as surface roughness, impurities and internal structure. To improve the representation of ice clouds in climate models, increased understanding of the global variation of crystal shape and how it relates to, e.g., location, cloud temperature and atmospheric state is crucial. Here, the remote sensing of ice crystal macroscale and microscale structure from airborne and space-based lidar depolarization observations and multi-directional measurements of total and polarized reflectances is reviewed. In addition, a brief overview is given of in situ and laboratory observations of ice crystal shape as well as the optical properties of ice crystals that serve as foundations for the remote sensing approaches. Lidar depolarization is generally found to increase with increasing cloud height and to vary with latitude. Although this variation is generally linked to the variation of ice crystal shape, the interpretation of the depolarization remains largely qualitative and more research is needed before quantitative conclusions about ice shape can be deduced. The angular variation of total and polarized reflectances of ice clouds has been analyzed by numerous studies in order to infer information about ice crystal shapes from them. From these studies it is apparent that pristine crystals with smooth surfaces are generally inconsistent with the data and thus crystal impurity, distortion or surface roughness is prevalent. However, conclusions about the dominating ice shapes are often inconclusive and contradictory and are highly dependent on the limited selection of shapes included in the investigations. Since ice crystal optical properties are mostly determined by the aspect ratios of the crystal components and their microscale structure, it is advised that remote sensing applications focus on the variation of these ice shape characteristics, rather than on the macroscale shape or habit. Recent studies use databases with nearly continuous ranges of crystal component aspect ratio and-or roughness levels to infer the variation of ice crystal shape from satellite and airborne remote sensing measurements. Here, the rationale and results of varying strategies for the remote sensing of ice crystal shape are reviewed. Observed systematic variations of ice crystal geometry with location, cloud height and atmospheric state suggested by the data are discussed. Finally, a prospective is given on the future of the remote sensing of ice cloud particle shapes.

clouds↗

DOE OSTI2023

Department of Energy’s Atmospheric System Research (ASR) Program’s Workshop on the Future of Atmospheric Large Eddy Simulation (LES): Workshop Report

Large-eddy simulation (LES) is used as a tool to understand physical processes such as turbulence, aerosols, clouds, precipitation, radiation, the interactions among all these, and their interactions with the underlying surface. Over the next 10 years, LES will drive fundamental progress in open scientific questions in these areas as LES is increasingly used to gain understanding of complex interacting physical processes involving atmospheric turbulence. This growth will be driven both by scientific demand and the expansion of computational resources needed to conduct LES, and the form that the growth takes will largely be determined by how computational resources are leveraged for scientific gain. In particular, we suggest that computational resources are likely to be leveraged in two separate but not necessarily distinct ways. On one hand, growth in computational resources will allow LES to be made more routine, that is, performed more frequently, while on the other hand, the computational expense (measured in total floating point operations) afforded to individual LES will expand dramatically, allowing simulations to increase in both domain size and resolution as well as physical detail. Current U.S. Department of Energy (DOE) projects such as LES ARM Symbiotic Simulation and Observation Activity (LASSO) are leading the way in conducting routine LES, building large, public databases that are accessible for data science, sensitivity studies, and training for machine learning. LES will also become more routine as it becomes more accessible for individual researchers to address their scientific questions of interest. Scientific questions addressed by LES over the next 10 years are likely to include cloud organization and aggregation; aerosol cloud interactions and atmospheric chemistry (including geo-engineering); urban-scale LES; atmospheric extreme events, ranging from small-scale severe weather to wildfires; and ocean-wave-atmosphere interactions. Further LES-related research will likely grow significantly in areas related to societal impact studies of air quality and extreme weather events, applications to renewable energy forecasting and resource assessment, and aid in decision-making processes. The growth in the use of LES in atmospheric science research will drive the need for better physical process representations (e.g., cloud aerosol microphysics, radiation, and atmospheric chemistry) at the scales resolved by LES. To date, many of the process representations used by LES have been taken directly from coarser-resolution models. Promising methods for LES process representations include superdroplet and quadrature methods for microphysics, 3D approaches for radiation, and better representation of chemistry and aerosol processes. At LES resolution, land-atmosphere interactions for complex terrains, land cover/types, biogeochemistry, and plant canopy models are needed as an improvement beyond traditional and widely used Monin-Obuhkov similarity theory.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Department of Energy’s Atmospheric System Research (ASR) Program’s Workshop on the Future of Atmospheric Large Eddy Simulation (LES) (Workshop Report)

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Using gap-filled MAIAC AOD and WRF-Chem to estimate daily PM 2.5 concentrations at 1 km resolution in the Eastern United States

To link short-term exposures of air pollutants to health outcomes, scientists must use high temporal and spatial resolution estimates of PM 2.5 concentrations. We develop a daily PM 2.5 product at 1 × 1 km 2 spatial resolution across the eastern United States (east of 90° W) with the aid of 1 × 1 km 2 MAIAC aerosol optical depth (AOD) data, 36 × 36 km 2 WRF-Chem output, 1 × 1 km 2 land-use type from the National Land Cover Database, and 0.125° × 0.125° ERA-Interim re-analysis meteorology. A gap-filling technique is applied to MAIAC AOD data to construct robust daily estimates of AOD when the satellite data are missing (e.g., areas obstructed by clouds or snow cover). The input data are incorporated into a multiple-linear regression model trained to surface observations of PM 2.5 from the EPA Air Quality System (AQS) monitoring network. The model generates a high-fidelity estimate (r 2 = 0.75 using a 10-fold random cross-validation) of daily PM 2.5 throughout the eastern United States. Of the inputs to the statistical model, WRF-Chem output (r 2 = 0.66) is the most important contributor to the skill of the model. MAIAC AOD is also a strong contributor (r 2 = 0.52). Daily PM 2.5 output from our statistical model can be easily integrated into county-level epidemiological studies. The novelty of this project is that we are able to simulate PM 2.5 in a computationally efficient manner that is constrained to ground monitors, satellite data, and chemical transport model output at high spatial resolution (1 × 1 km 2 ) without sacrificing the temporal resolution (daily) or spatial coverage (>2,000,000 km 2 ).

47 OTHER INSTRUMENTATION↗

DOE OSTI2018

Modeling and Simulation of High-Frequency Solar Irradiance

As the use of solar power as a source of electricity is increasing, so is the interest in modeling radiation at high temporal resolutions. High-dimensional remote sensing data products depend on cloud cover variability, atmosphere aerosol levels, and other atmospheric parameters. Because of weather fronts and aerosols, it is difficult to quantify solar power variability based on distributed solar networks. The global horizontal irradiance (GHI) component in the National Solar Radiation Database (NSRDB) is available at a 30-min time resolution. The algorithm proposed in this paper produces 1-min-resolution GHI samples at locations where NSRDB data are available. The synthetic irradiance datasets are produced using log-additive non-Gaussian mixture models and resampling techniques. The model is trained over historical data, and predicted values are compared with in situ data. This approach allows for estimating the solar irradiance at subhourly temporal resolutions, while featuring variability for locations where measurements are otherwise not available.

14 SOLAR ENERGY↗

DOE OSTI2021

Version 4 CALIPSO Imaging Infrared Radiometer ice and liquid water cloud microphysical properties – Part I: The retrieval algorithms

Following the release of the version 4 Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data products from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, a new version (version 4; V4) of the CALIPSO Imaging Infrared Radiometer (IIR) Level 2 data products has been developed. The IIR Level 2 data products include cloud effective emissivities and cloud microphysical properties such as effective diameter and ice or liquid water path estimates. Dedicated retrievals for water clouds were added in V4, taking advantage of the high sensitivity of the IIR retrieval technique to small particle sizes. This paper (Part I) describes the improvements in the V4 algorithms compared to those used in the version 3 (V3) release, while results will be presented in a companion (Part II) paper. The IIR Level 2 algorithm has been modified in the V4 data release to improve the accuracy of the retrievals in clouds of very small (close to 0) and very large (close to 1) effective emissivities. To reduce biases at very small emissivities that were made evident in V3, the radiative transfer model used to compute clear-sky brightness temperatures over oceans has been updated and tuned for the simulations using Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) data to match IIR observations in clear-sky conditions. Furthermore, the clear-sky mask has been refined compared to V3 by taking advantage of additional information now available in the V4 CALIOP 5 km layer products used as an input to the IIR algorithm. After sea surface emissivity adjustments, observed and computed brightness temperatures differ by less than ±0.2 K at night for the three IIR channels centered at 08.65, 10.6, and 12.05 µm, and inter-channel biases are reduced from several tens of Kelvin in V3 to less than 0.1 K in V4. We have also improved retrievals in ice clouds having large emissivity by refining the determination of the radiative temperature needed for emissivity computation. The initial V3 estimate, namely the cloud centroid temperature derived from CALIOP, is corrected using a parameterized function of temperature difference between cloud base and top altitudes, cloud absorption optical depth, and CALIOP multiple scattering correction factor. As shown in Part II, this improvement reduces the low biases at large optical depths that were seen in V3 and increases the number of retrievals. As in V3, the IIR microphysical retrievals use the concept of microphysical indices applied to the pairs of IIR channels at 12.05 and 10.6 µm and at 12.05 and 08.65 µm. The V4 algorithm uses ice look-up tables (LUTs) built using two ice habit models from the recent “TAMUice2016” database, namely the single-hexagonal-column model and the eight-element column aggregate model, from which bulk properties are synthesized using a gamma size distribution. Four sets of effective diameters derived from a second approach are also reported in V4. Here, the LUTs are analytical functions relating microphysical index applied to IIR channels 12.05 and 10.6 µm and effective diameter as derived from in situ measurements at tropical and midlatitudes during the Tropical Composition, Cloud, and Climate Coupling (TC4) and Small Particles in Cirrus Science and Operations Plan (SPARTICUS) field experiments.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2004

Globe Teachers Guide and Photographic Data on the Web

The task of managing the GLOBE Online Teacher s Guide during this time period focused on transforming the technology behind the delivery system of this document. The web application transformed from a flat file retrieval system to a dynamic database access approach. The new methodology utilizes Java Server Pages (JSP) on the front-end and an Oracle relational database on the backend. This new approach allows users of the web site, mainly teachers, to access content efficiently by grade level and/or by investigation or educational concept area. Moreover, teachers can gain easier access to data sheets and lab and field guides. The new online guide also included updated content for all GLOBE protocols. The GLOBE web management team was given documentation for maintaining the new application. Instructions for modifying the JSP templates and managing database content were included in this document. It was delivered to the team by the end of October, 2003. The National Geophysical Data Center (NGDC) continued to manage the school study site photos on the GLOBE website. 333 study site photo images were added to the GLOBE database and posted on the web during this same time period for 64 schools. Documentation for processing study site photos was also delivered to the new GLOBE web management team. Lastly, assistance was provided in transferring reference applications such as the Cloud and LandSat quizzes and Earth Systems Online Poster from NGDC servers to GLOBE servers along with documentation for maintaining these applications.

Kowal, Dan↗

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 NTRS2006

NASA-Langley Web-Based Operational Real-time Cloud Retrieval Products from Geostationary Satellites

At NASA Langley Research Center (LaRC), radiances from multiple satellites are analyzed in near real-time to produce cloud products over many regions on the globe. These data are valuable for many applications such as diagnosing aircraft icing conditions and model validation and assimilation. This paper presents an overview of the multiple products available, summarizes the content of the online database, and details web-based satellite browsers and tools to access satellite imagery and products.

Palikonda, Rabindra↗