Search NASA⌕ Search

SEARCH · Search NASA

Results for “DCC”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Status of the GSICS VIS/NIR DCC Calibration Efforts

This year's goals for the GSICS VIS/NIR group is to finalize the VIS/NIR demonstration product requirements and to process the product for public dissemination provided on the GSICS web page. The GSICS VIS/NIR group members have been working on a unified calibration approach among various agencies. Two calibration methods have been chosen for the visible bands, deep convective clouds (DCC) and lunar invariant targets. To come to consensus across the agencies, each step of the DCC process will be outlined. Brief discussions are to follow to determine any outstanding issues. The presentation will review the DCC calibration process implemented by the CERES calibration team. CERES has already implemented the DCC method across 18 geostationary satellites. The various agencies have taken the framework and optimized the method for their particular geostationary satellite. Several new improvements will be discussed, such as deseasonalization of the DCC reflectances, impact of the bidirectional model, and update frequency.

David Doelling↗
NASA NTRSDate not supplied

Inter-Calibrating the CERES SW Instrument Fluxes Using Deep Convective Clouds(DCC) Within the Same Sun-Synchronous Orbit

The NASA CERES EBAF product provides the scientific community observed TOA fluxes to monitor the Earth’s energy imbalance and to validate climate models. To provide a seamless EBAF 24-year record, the CERES instrument calibration must be stable and consistent across satellite records. Once the Terra and Aqua spacecraft are decommissioned at the end of 2025, the CERES project will rely on CERES instrument observations on the SNPP and NOAA-20 1:30 PM sun-synchronous orbits. The SNPP and NOAA-20 satellite orbit placement will prevent any time matched observations for inter-calibration efforts. The future Libera instrument, which will continue the CERES record and scheduled for launch in 2028 onboard the NOAA-22 satellite, will also need to be inter-calibrated without the aid of time-matched observations. Deep convective clouds (DCC) are the most Lambertian, brightest, tropical Earth invariant targets located at the tropopause making them ideal to radiometrically scale the CERES SW observed radiance to a common reference. The SNPP, NOAA-20 and future NOAA-22 satellites are in the same 16-day repeatable orbits, allowing the DCC targets to be observed with the same angular configuration. The empirically derived SNPP CERES SW channel Bidirectional Reflectance Distribution Function (BRDF) can be easily be applied to the NOAA-20 CERES SW channel radiances since they observe the nearly the same DCC systems. The DCC BRDF corrected radiances are analyzed collectively into radiance probability distribution functions (PDF). By comparing the PDF statistics, the SNPP and NOAA-20 CERES SW channel can be inter-calibrated. The inter-calibration coefficients are validated with the CERES instrument calibration team coefficients to optimize the methodology.

David Doelling↗
DOE OSTI2024

Modular Staged Pressurized Oxy-Combustion (SPOC) Power Plant for Coal and Biomass – Integration of Combustor Boiler and DCC

Utilities and grid operators worldwide are under significant pressure to incorporate intermittent renewable sources while strategizing on how to maintain the necessary stability and reliability of the grid. The development of a power plant which will be capable of flexible operation to meet the needs of the grid as more intermittent sources like wind and solar energy are incorporated is key to maintain the reliability of the grid. Through the use of innovative and cutting-edge technologies that improve efficiency and reduce carbon emissions, and being small compared to today's conventional utility-scale power plants, the modular Staged, Pressurized Oxy-Combustion (SPOC) process envisioned by and under development at Washington University in St. Louis (WUSTL) has the potential to achieve these goals. Specifically, the process offers: 1) a modular plant design that allows for better operational flexibility; 2) the utilization of fuel-staging and pressurized oxy-combustion, resulting in smaller plant size, improved plant efficiency, and reduced costs for pollutant and CO2 removal compared to traditional power plants with post-combustion capture technology; and 3) the use of small modular boilers and pollutant removal units that can be constructed off-site leading to reduced capital costs for the plant. WUSTL is advancing the development of the critical components for the SPOC power plant, including the integrated combustor-boiler system and the direct contact cooler. To demonstrate the boiler convective section and to obtain critical data for commercial-scale pressurized boiler design, a simulated convective heat transfer boiler test section was designed and integrated with the combustor (radiant section). A direct contact cooler (DCC) was integrated with the combustor-boiler to demonstrate the dynamic operation of the integrated system and the performance of the DCC, including the efficiency for simultaneous removal of NOx and SOx. This talk will present an update on the evaluation of the critical components for system integration, including heat transfer data from the simulated boiler, scrubbing efficiency for the DCC under different operating conditions, and CFD modeling and validation for burner and boiler development.

Magalhaes, Duarte↗
NASA NTRS2017

Non-Intrusive Velocity Measurements with MTV During DCC Event in the HTTF

Velocity profiles are measured using molecular tagging velocimetry (MTV) in the high temperature test facility (HTTF) at Oregon State University during a depressurized conduction cooldown (DCC) event. The HTTF is a quarter scale electrically heated nuclear reactor simulator designed to replicate various accident scenarios. During a DCC, a double ended guillotine break results in the reactor pressure vessel (RPV) depressurizing into the reactor cavity and ultimately leading to air ingress in the reactor core (lock-exchange and gas diffusion). It is critical to understand the resulting buoyancy-driven flow to characterize the reactor self-cooling capacity through natural circulation. During tests conducted at ambient pressure and temperature, the RPV containing helium is opened (via the hot and cold legs) to a large vessel filled with nitrogen to simulate the atmosphere. The velocity profile on the hot leg pipe centerline is recorded at 10 Hz with MTV based on NO tracers. The precision of the velocimetry was measured to be 0.02 m/s in quiescent flow prior to the tests. A helium flow from the RPV is initially observed in the top quarter of the pipe. During the first 20 seconds of the event, helium flows out of the RPV with a maximum velocity below 2 m/s. The velocity profile transitions from parabolic to linear in character and decays slowly over the rest of the recording; peak velocities of 0.2 m/s are observed after 30 min. A counter-flow of nitrogen is also observed intermittently, which occurs at lower velocities (>0.1 m/s).

Andre, M. A.↗
NASA NTRSDate not supplied

The Impact of Pixel Size on the Characterization of Deep Convective Clouds for Calibration

The NASA CERES project provides the scientific community the observed TOA SW and LW fluxes for climate monitoring and climate model validation. CERES utilizes hourly geostationary imager derived broadband fluxes, which rely on the channel radiances and associated cloud retrievals, are used to estimate the broadband fluxes between CERES observations. This requires stable and consistent cross-platform imager visible channel calibration. The CERES project utilizes deep convective clouds (DCC) as an invariant Earth target to both monitor the stability of sensors and for radiometric scaling. GSICS, an international collaboration, is also evaluating and implementing the DCC invariant target calibration methodology to provide consistent calibration coefficients across geostationary imagers anchored to the AquaMODIS or the NOAA-20 VIIRS calibration reference. Tropical DCC are the brightest, coldest, most Lambertian, top of the atmosphere Earth targets. The DCC invariant target calibration methodology relies on a large ensemble of tropical D CC-identified pixel-level reflectances, which are aggregated as probability density functions (PDF). By assuming the monthly PDF shape is otherwise consistent in time excepting shifts in reflectance caused by changes in the sensor calibration, the imager stability is monitored. Radiometric scaling is accomplished by ratioing the sensor pair DCC PDF reflectance values. The success of the DCC methodology relies on consistent PDF distributions. The goal of this study is to determine the impact of pixel resolution on the DCC reflectance distribution. Single SNPP-VIIRS 750-m and Landsat 8 OLI 30-m granules are aggregated to degrade the pixel resolution from the native level. The DCC pixels are identified using a BT threshold. Most of the brightest DCC pixels are also the coldest, although there are exceptions. It was found that increasing the BT threshold exponentially increased the number of darker pixels. The pixel resolution did not seem to impact the DCC reflectance PDF distribution for pixel resolutions less than 3 km, which suggests that imagers of varying pixel resolutions may be radiometrically scaled to each other using DCC targets.

DCC↗
NASA NTRSDate not supplied

Deep Convective Cloud Calibration Sensitivity Studies in Support of Radiometrically Scaling GEO Imagers With VIIRS

The NASA CERES SYN1deg product provides the scientific community regional hourly TOA and surface broadband fluxes and clouds. For consistent geostationary (GEO) derived fluxes and clouds the GEO imagers are radiometrically scaled to the Aqua-MODIS calibration reference. The CERES project utilizes GEO and MODIS or VIIRS analogous channel coincident, collocated, and co-angled radiance pairs as the primary method to inter-calibrate the GEO imagers. Tropical deep convective clouds (DCC) are bright, near Lambertian, top of atmosphere pseudo invariant Earth targets that do not rely on coincident ray-matched radiance pairs to radiometrically scale sensors to a common calibration reference. The DCC invariant target (DCC-IT) methodology collectively analyzes all tropical DCC identified pixel radiances by way of probability density function (PDF) distributions. Perfectly inter-calibrated sensor pairs should reveal nearly identical PDF distributions given the same DCC identification criterion. The PDF median, mean, mode, and inflection point statistics were tested as a function of DCC identification criterion using SNPP-VIIRS and Himawari-8 AHI 0.65μm channel radiances during January 2019. It was found that the PDF inflection point provided inter-calibration factors within 0.25% that were nearly independent of DCC identification criterion. The PDF median provided inter-calibration factors within 0.25% for the coldest BT and most stringent homogeneity factors. The PDF mean and mode statistics were inadequate under any DCC conditions. It is critical for the DCC pixel radiances to be anisotropically corrected. The DCC-IT methodology will also be tested for other visible and SWIR bands.

DCC↗
NASA NTRS2010

The Characterization of Deep Convective Cloud Albedo as a Calibration Target Using MODIS Reflectances

There are over 25 years of historical satellite data available to climate analysis. The historical satellite data needs to be well calibrated, especially in the visible, where there is no onboard calibration on operational satellites. The key to the vicarious calibration of historical satellites relies on invariant targets, such as the moon, Dome C, and deserts. Deep convective clouds (DCC) also show promise of being a stable invariant or predictable target viewable by all satellites, since they behave as solar diffusers. However DCC have not been well characterized for calibration. Ten years of well-calibrated MODIS is now available. DCC can easily be identified using IR thresholds, where the IR calibration can be traced to the onboard black-bodies. The natural variability of DCC albedo will be analyzed geographically and seasonally, especially difference of convection initiated over land or ocean. Functionality between particle size and ozone absorption with DCC albedo will be examined. Although DCC clouds are nearly Lambertion, the angular distribution of reflectances will be sampled and compared with theoretical models. Both Aqua and Terra MODIS DCC angular models will be compared for consistency. Normalizing angular geostationary DCC reflectances, which were calibrated against MODIS, with SCIAMACHY spectral reflectances and comparing them to MODIS DCC reflectances will inspect the usage of DCC albedos as an absolute calibration target.

Doelling, David R.↗
NASA NTRSDate not supplied

The Impact of Pixel Size on the Characterization of Deep Convective Clouds for Calibration

The NASA CERES project provides the scientific community the observed TOA SW and LW fluxes for climate monitoring and climate model validation. CERES utilizes hourly geostationary imager derived broadband fluxes, which rely on the channel radiances and associated cloud retrievals, to estimate the broadband fluxes between CERES observations. This requires stable imager visible channel calibration, which the CERES project verifies by utilizing deep convective clouds (DCC) as an invariant Earth target. GSICS, which is an international collaboration, is also evaluating the DCC invariant target calibration methodology to provide consistent calibration coefficients across geostationary imagers anchored to the Aqua-MODIS calibration reference. Tropical DCC are the brightest, coldest, most Lambertian, top of the atmosphere Earth targets. The DCC invariant target calibration methodology relies on a large ensemble of tropical DCC-identified pixel-level reflectances, which are histogrammed to find the mode reflectance of the probability density function (PDF). The imager stability is monitored by tracking the monthly DCC PDF mode reflectance over time. Radiometric scaling is accomplished by ratioing the GEO and VIIRS DCC mode reflectance values. The PDF shape and mode dependency on sensor pixel resolution, which varies among sensors, is unknown. This study will characterize the impact of pixel resolution on the DCC PDFs by aggregating Landsat 30-m pixel reflectances into various coarser pixel resolutions ranging from 100-m to 4-km, and comparing the corresponding PDF statistics. This analysis will assist in improving the uncertainty in a DCC-based intercalibration between instruments with different pixel resolutions.

Conor Haney↗
NASA NTRSDate not supplied

Seasonal, Spectral, and Regional Characterization of Deep Convective Clouds Top-of-Atmosphere Bidirectional Reflectance for Improved Satellite Intercalibration

The NASA CERES project provides the scientific community with regional broadband fluxes designed for long-term climate monitoring. The CERES climate quality dataset requires that the CERES instrument, as well as the MODIS and VIIRS imager records to be radiometrically stable over time. Deep Convective Clouds (DCCs) are spectrally uniform, near-Lambertian natural diffusers offering high signal-to-noise ratio and stable radiometric response in the VIS-NIR spectrum. For shortwave infrared (SWIR) wavelengths greater than 1.2µm, the DCC response is significantly influenced by cloud particle size and atmospheric absorption. Previous studies improved the characterization of the SWIR band DCC radiance, by using channel specific monthly empirical BRDFs as well as using the probability density function mean statistic to track the SWIR band stability. Also, that the DCC radiance is greater over land than over ocean and that the TWP DCC radiance has the lowest tropical DCC radiance. This study confirms and improves upon the previous studies. The study stratified the tropics regionally into land and ocean domains and applied their respective ocean-only and land-only empirical monthly BRDFs and normalized the land DCC BRDF corrected radiances with their ocean counterpart. This approach provided the most stable DCC response. The DCC BRDF corrected radiance monthly standard error was 0.24%, 0.62%, 0.59%, and 0.43% for the 1.24µm, 1.37µm, 1.61µm, and 2.25µm SWIR bands, which reduced the standard error 20%, 13%, 24%, and 26%, respectively when compared with the all-surface approach. The same approach was attempted over the Tropical Western Pacific and found not to be an improvement over the tropical domain. Further stratification of the tropical domain will need to balance sufficient sampling while accounting for regional DCC radiance differences.

Prathana Khakurel↗
NASA NTRS2006

AIRS Observations of Deep Convective Clouds

Large thunderstorms can be identified in the AIRS data as areas where the brightness temperature of the 1231 cm-1 atmospheric window channel in non-polar areas is less than 210 K. Each day about 6000 large thunderstorms are identified, almost exclusively within 30 degrees of the equator. Since the size of the AIRS footprint at nadir is 13.5 km, a brightness temperature of less than 210 K indicates that the top of the anvil of the thunderstorm protrudes well into the tropopause. Such objects are commonly referred to as Deep Convective Clouds (DCC). Our interest in DCC was motivated by the question 'Are severe weather events increasing due to global warming'. Each DCC is a severe weather event, although not on the scale of the much less frequent hurricanes, which can be identified in the AIRS data as clusters of several hundred DCC. The number of DCC per day has been fairly stable over the past four years for the mean of the tropical oceans, but a significant increase can be seen day and night in the Atlantic Ocean. The number of DCC per day shows a strong seasonal and latitudinal dependence, with the peak count lagging the solstice of the latitude zone by about 2 months. The most prominent features in brightness temperature spectra of DCC are due to stratospheric CO2, Ozone and Methane. In the channels with weighting functions below the stratosphere the brightness temperature is typically 205 K, with a characteristic 1 to 2.5 K drop between 1000 and 750 cm-1, equivalent to a 2-4 % drop in emissivity. This is likely due to the presence of cirrus (ice) particles. Some of this analysis of DCC can be extended using past and future operational sounders in polar orbit.

temperature↗
NASA NTRSDate not supplied

Deep Convective Cloud Calibration Sensitivity Studies in Support of Radiometrically Scaling GEO Imagers With VIIRS

The NASA CERES SYN1deg product provides the scientific community regional hourly TOA and surface broadband fluxes and clouds. For consistent geostationary (GEO) derived fluxes and clouds the GEO imagers are radiometrically scaled to the Aqua-MODIS calibration reference. The CERES project utilizes GEO and MODIS analogous channel coincident, collocated, and co-angled radiance pairs as the primary method to inter-calibrate the GEO imagers. Deep convective clouds (DCC) are bright tropical, near Lambertian, top of atmosphere pseudo invariant Earth targets that do not rely on coincident radiance pairs to radiometrically scale sensors to a common calibration reference. DCC pixels are identified by cold IR window channel brightness temperatures (BT). Successful DCC inter-calibration relies on sufficient sampling of comparable identified DCC pixels between sensors. The DCC identification thresholds, pixel resolution, local time, and geographical sampling should be consistent between sensors. Over 20 GEO imagers during the span of the CERES record have various visible and IR pixel resolutions. Unlike the MODIS and VIIRS imagers, where the visible and IR pixel resolutions are similar, the GEO visible pixel resolution is much finer than the IR pixel resolution. The study will examine the pixel resolution impact on the DCC calibration methodology. The resulting DCC calibration coefficients can be validated against the sensor pair calibration methodology. Accounting for the DCC calibration imager resolution differences will allow the CERES project to utilize the future CLARREO observations as the calibration reference for all GEO, MODIS, and VIIRS imagers across the CERES record.

Conor Haney↗
NASA NTRS2012

The Characterization of Deep Convective Clouds as an Invariant Calibration Target and as a Visible Calibration Technique

Deep convective clouds (DCCs) are ideal visible calibration targets because they are bright nearly isotropic solar reflectors located over the tropics and they can be easily identified using a simple infrared threshold. Because all satellites view DCCs, DCCs provide the opportunity to uniformly monitor the stability of all operational sensors, both historical and present. A collective DCC anisotropically corrected radiance calibration approach is used to construct monthly probability distribution functions (PDFs) to monitor sensor stability. The DCC calibration targets were stable to within 0.5% and 0.3% per decade when the selection criteria were optimized based on Aqua MODerate Resolution Imaging Spectroradiometer 0.65-micrometer-band radiances. The Tropical Western Pacific (TWP), African, and South American regions were identified as the dominant DCC domains. For the 0.65-micrometer band, the PDF mode statistic is preferable, providing 0.3%regional consistency and 1%temporal uncertainty over land regions. It was found that the DCC within the TWP had the lowest radiometric response and DCC over land did not necessarily have the highest radiometric response. For wavelengths greater than 1 micrometer, the mean statistic is preferred, and land regions provided a regional variability of 0.7%with a temporal uncertainty of 1.1% where the DCC land response was higher than the response over ocean. Unlike stratus and cirrus clouds, the DCC spectra were not affected by water vapor absorption.

Doelling, David R.↗
NASA NTRSDate not supplied

Overview of Advanced Stirling Convertor Dual Convertor Controller Development and Testing at NASA Glenn Research Center

For over two decades, NASA Glenn Research Center (GRC) has been supporting the development of Radioisotope Power Systems (RPS). NASA desires higher conversion efficiency RPS options that are reliable and robust with long life design. Dynamic conversion, such as Stirling offer the potential for higher conversion efficiencies than current RPS but have yet to be demonstrated in a flight application. GRC developed a non-nuclear representation of a RPS consisting of a pair of Advanced Stirling Convertors (ASC), a Dual Convertor Controller (DCC), and associated support equipment. The DCC was designed by the Johns Hopkins University/Applied Physics Laboratory (JHU/APL) to actively control a pair of ASCs. Based on lessons learned, three generations of DCCs were developed over the past decade. After each generation of the DCC was completed, tests were performed to verify functionality. These tests include acceptance testing, fault testing, characterization testing, and testing with the Radioisotope Power System Systems Integration Laboratory (RSIL). Acceptance testing verifies that the DCC can control a pair of ASCs to produce full convertor power output. The fault testing verifies that the DCC can maintain control of the ASCs during either internal or external faults. Characterization testing verifies the functionality of the DCC over a range of bus voltage values. RSIL provides insight into the electrical interactions between a representative radioisotope power generator, its associated control schemes, and realistic electric system loads. The DCC design, development, lessons learned, test results, and future work are presented in this paper.

Stirling↗
NASA NTRSDate not supplied

Consistent Pixel Resolution Characterization of Deep Convective Clouds for Calibration

The NASA CERES project provides global TOA shortwave and longwave fluxes for climate monitoring and validation that spans over 20 years. CERES utilizes broadband fluxes derived from geostationary (GEO) imagers to estimate broadband fluxes between the CERES observations. In order for these fluxes to be viable, the GEO imager calibration must be stable over time. One such calibration method used by CERES is to evaluate ensemble sets of deep convective clouds (DCC) as invariant targets (IT) over time. DCC targets can also provide radiometric scaling between sensors. An international collaboration through GSICS is also evaluating the DCC-IT calibration methodology to provide consistent calibration coefficients across geostationary sensors. Tropical DCC are the coldest, brightest, and most Lambertian TOA Earth targets identified using a window channel brightness temperature threshold. The DCC-IT technique involves a large ensemble of TOA pixel-level reflectances, which are binned into probability density functions (PDF). The PDF structure dependency on sensor pixel resolution, which can vary greatly among sensors, is not well known. This study will identify the impact of pixel resolution on the DCC PDFs by aggregating VIIRS and Landsat OLI/TIRS pixel resolutions into various coarser pixel resolutions and comparing the shape and statistics of the resulting PDFs. This study should assist in mitigating the pixel resolution dependency in the DCC-IT approach for providing scaling factors between sensors.

Conor Haney↗