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Results for “functional principal component analysis”

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.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

CELCAP: A Computer Model for Cogeneration System Analysis

A description of the CELCAP cogeneration analysis program is presented. A detailed description of the methodology used by the Naval Civil Engineering Laboratory in developing the CELCAP code and the procedures for analyzing cogeneration systems for a given user are given. The four engines modeled in CELCAP are: gas turbine with exhaust heat boiler, diesel engine with waste heat boiler, single automatic-extraction steam turbine, and back-pressure steam turbine. Both the design point and part-load performances are taken into account in the engine models. The load model describes how the hourly electric and steam demand of the user is represented by 24 hourly profiles. The economic model describes how the annual and life-cycle operating costs that include the costs of fuel, purchased electricity, and operation and maintenance of engines and boilers are calculated. The CELCAP code structure and principal functions of the code are described to how the various components of the code are related to each other. Three examples of the application of the CELCAP code are given to illustrate the versatility of the code. The examples shown represent cases of system selection, system modification, and system optimization.

Source record↗
DOE OSTI2022

Non-intrusive reduced order modeling of natural convection in porous media using convolutional autoencoders: Comparison with linear subspace techniques

Natural convection in porous media is a highly nonlinear multiphysical problem relevant to many engineering applications (e.g., the process of CO 2 sequestration). Here, we extend and present a non-intrusive reduced order model of natural convection in porous media employing deep convolutional autoencoders for the compression and reconstruction and either radial basis function (RBF) interpolation or artificial neural networks (ANNs) for mapping parameters of partial differential equations (PDEs) on the corresponding nonlinear manifolds. To benchmark our approach, we also describe linear compression and reconstruction processes relying on proper orthogonal decomposition (POD) and ANNs. Further, we present comprehensive comparisons among different models through three benchmark problems. The reduced order models, linear and nonlinear approaches, are much faster than the finite element model, obtaining a maximum speed-up of 7 × 10 6 because our framework is not bound by the Courant–Friedrichs–Lewy condition; hence, it could deliver quantities of interest at any given time contrary to the finite element model. Our model’s accuracy still lies within a relative error of 7% in the worst-case scenario. We illustrate that, in specific settings, the nonlinear approach outperforms its linear counterpart and vice versa. We hypothesize that a visual comparison between principal component analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE) could indicate which method will perform better prior to employing any specific compression strategy.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1989

Model-based quantification of image quality

In 1982, Park and Schowengerdt published an end-to-end analysis of a digital imaging system quantifying three principal degradation components: (1) image blur - blurring caused by the acquisition system, (2) aliasing - caused by insufficient sampling, and (3) reconstruction blur - blurring caused by the imperfect interpolative reconstruction. This analysis, which measures degradation as the square of the radiometric error, includes the sample-scene phase as an explicit random parameter and characterizes the image degradation caused by imperfect acquisition and reconstruction together with the effects of undersampling and random sample-scene phases. In a recent paper Mitchell and Netravelli displayed the visual effects of the above mentioned degradations and presented subjective analysis about their relative importance in determining image quality. The primary aim of the research is to use the analysis of Park and Schowengerdt to correlate their mathematical criteria for measuring image degradations with subjective visual criteria. Insight gained from this research can be exploited in the end-to-end design of optical systems, so that system parameters (transfer functions of the acquisition and display systems) can be designed relative to each other, to obtain the best possible results using quantitative measurements.

Hazra, Rajeeb↗
NASA NTRSDate not supplied

Rapid Development of Instrument Thermal Models: Perspectives and Guidelines from NASA Goddard’s Instrument Design Laboratory

The Instrument Design Laboratory (IDL), part of NASA Goddard Space Flight Center’s Integrated Design Center (IDC), is a concurrent and collaborative environment which allows for rapid development of science instrumentation concepts within the span of less than two weeks. Science goals set by a Principal Investigator from government, industry or academia are translated into engineering requirements, from which a team of engineers spanning multiple disciplines use an established study process and a suite of analysis tools to work towards an instrument point design. As part of this process, a staff thermal engineer is tasked with designing a thermal control system which meets all incoming thermal requirements, while iterating real-time with other subsystems to ensure compatibility and functionality as a completed system. Thermal engineers on spaceflight projects typically have weeks or months to develop thermal models. However, the severe time limitation in this conceptual study setting makes thermal design particularly difficult, as rapid thermal modeling solely over the span of a few days is required to develop the instrument thermal design and understand the performance over its intended mission, especially if the instrument concept contains multiple thermal challenges such as dynamic environments or high heat dissipating components. In this paper, the authors provide a condensed guide for the most efficient ways to develop thermal models and conduct thermal analysis within the span of one-to-two weeks, as informed by decades of design experience and best practices in the IDL. The authors also focus on quick methods for determining worst-case thermal environments, deciding which modeling details are essential at this early phase, and quantifying the engineering resources necessary for thermal control. This paper concludes with specific thermal design tips for different instrument types across the electromagnetic spectrum.

Kan Yang↗
DOE OSTI2026

Quantifying Temperature Dependence of Pu(IV) Absorbance Spectra for Advanced Online Monitoring of Nuclear Processes

This article presents a systematic study of Pu(IV) absorbance spectral features as a function of temperature to develop an understanding of this parameter’s effect on chemometric models that can be used as online monitoring tools to support nuclear processing. The descriptive and predictive models that provide real-time feedback of these processes are usually constructed with data collected in conditions typical of a laboratory environment, which can differ drastically from a processing environment. To assess the impact of temperature on Pu(IV) absorbance spectra, 11 samples of Pu(IV) were synthesized with varying HNO 3 concentrations ranging from 0.6 to 9.5 M and heated between 15 and 45 °C. Ultraviolet (UV)–visible (vis)–near-infrared (NIR) absorption spectra collected at different HNO 3 concentrations and temperatures revealed that features associated with Pu(IV) are sensitive to temperature at all HNO 3 concentrations and that changes in features depend on HNO 3 concentration. The contributions of temperature and HNO 3 concentration to variation in Pu(IV) spectral features were evaluated using the principal component analysis of spectra that were baseline-corrected with an asymmetric least-squares method. Furthermore, predictive modeling for HNO 3 concentration with partial least-squares regression of UV–vis–NIR spectra highlighted the importance of accounting for temperature in the calibration set to optimize model performance. This methodology constitutes a new, systematic approach to account for the effect of temperature on the absorption spectra of metal ions and is useful for process monitoring applications in many industries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Reionization effective likelihood from Planck 2018 data

We release relike (reionization effective likelihood), a fast and accurate effective likelihood code based on the latest Planck 2018 data that allows one to constrain any model for reionization between 6 < z < 30 using five constraints from the CMB reionization principal components (PC). We tested the code on two example models which showed excellent agreement with sampling the exact Planck likelihoods using either a simple Gaussian PC likelihood or its full kernel density estimate. This code enables a fast and consistent means for combining Planck constraints with other reionization data sets, such as kinetic Sunyaev-Zeldovich effects, line-intensity mapping, luminosity function, star formation history, quasar spectra, etc., where the redshift dependence of the ionization history is important. Since the PC technique tests any reionization history in the given range, we also derive model-independent constraints for the total Thomson optical depth τ PC = $0.0619$$^{+0.0056}_{–0.0068}$ and its 15 ≤ z ≤ 30 high redshift component τ PC (15,30) < 0.020 (95% C.L.). Furthermore, the upper limits on the high-redshift optical depth is a factor of ~3 larger than those reported in the Planck 2018 cosmological parameter paper using the FlexKnot method and we validate our results with a direct analysis of a two-step model which permits this small high-z component.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Characterization of Caenorhabditis elegans sphingomyelin synthases through heterologous expression

Sphingomyelin (SM) is a major component of mammalian cell membranes and particularly abundant in the myelin sheath that surrounds nerve fibers. Its production is catalyzed by SM synthases SMS1 and SMS2, which interconvert phosphatidylcholine and ceramide to diacylglycerol and SM in the Golgi and at the plasma membrane, respectively. As the lipids participating in this reaction fulfill both structural and signaling functions, SMS enzymes have considerable potential to influence diverse important cellular processes. The nematode Caenorhabditis elegans is an attractive model for studying both animal development and human disease. The organism contains five SMS homologues but none of these have been characterized in any detail. Here, we carried out the first systematic analysis of SMS family members in C. elegans . Using heterologous expression systems, genetic ablation, metabolic labeling and lipidome analyses, we show that C. elegans harbors at least three distinct SM synthases and one ceramide phosphoethanolamine (CPE) synthase. Moreover, C. elegans SMS family members have partially overlapping but also unique sub-cellular distributions and together occupy all principal compartments of the secretory pathway. Our findings shed light on crucial aspects of sphingolipid metabolism in a valuable animal model and opens avenues for exploring the role of SM and its metabolic intermediates in organismal development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Novel principal component analysis tool based on python for analysis of complex spectra of time-of-flight secondary ion mass spectrometry

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a powerful surface analysis tool, which can simultaneously provide elemental, isotopic, and molecular information with part per million (ppm) sensitivity. However, each spectrum may be composed of hundreds of ion signals, which makes the spectra data complex. Principal component analysis (PCA) is a multivariate analysis technique that has been widely used to figure out the variances among samples in ToF-SIMS spectra data analysis and is showing great success in the explanation of complex ToF-SIMS spectra. So far, several software tools have been developed for PCA of ToF-SIMS spectra; however, none of them are freely available. Such a situation leads to some difficulties in extending applications of PCA to various research fields. More importantly, it has long been challenging for common researchers to understand PCA plots and extract chemical differences among samples. In this work, we developed a new and flexible software tool (named “advanced spectra pca toolbox”) based on python for PCA of complex ToF-SIMS spectra along with an easy-to-read manual. It can generate data analysis reports automatically to explain chemical differences among samples, allowing less experienced researchers to easily understand tricky PCA results. Moreover, it is expandable and compatible with artificial intelligence/machine learning functions. Pure goethite and different lignin adsorbed goethite samples were used as a model system to demonstrate our new software tool, proving that our software tool can be readily used in complex spectra data processing. Our new software tool is open-source, convenient, flexible, and expandable. We expect this open-source tool will benefit the ToF-SIMS community.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Toward Better Understanding of Microphysical Processes and Resulting Precipitation Physics: A Merger Of Observations and Cloud Models (Final Report)

A large database of global disdrometer observations and a diverse set of simulations from the Regional Atmospheric Modeling System (RAMS) were compared using principal component analysis (PCA) in order to better understand warm and ice-based precipitation processes. The analysis demonstrated that six distinct precipitation groups (PGs) with common characteristics were revealed in both the observations and model simulations. These PGs were defined by similar co-variability of rain parameters. However, the model showed large concentrations of drops with a given size compared to the observations. Detailed investigations determined the parameterization of drop breakup was forcing the drops to an equilibrium size with a stronger constraint than was indicated by the observations. A series of sensitivity studies permutating the rain shape parameter in the RAMS 2-moment bulk scheme demonstrated how the assumed shape of the rain distribution influences the microphysics as well as precipitation characteristics. Results were compared to the same simulations performed with a bin microphysics scheme where the rain shape parameter is freely evolving. In the bin scheme, a wide range of shape parameters were found, with horizontal and vertical variability, in addition to being a function of storm lifetime. The results of this study highlight the limitations of a fixed assumed rain distribution in 2-moment microphysics schemes. Model simulations were used to probe the microphysical origins of the six PGs. Rain budgets from a supercell case showed that several of the groups hypothesized to be associated with strong ice microphysical processes had significant contributions from melting hail, but the complexity of ice and warm-rain processes in the supercell precluded definitive determination of microphysical origins for many of the PGs. A case study from the Mid-latitude Continental Convection and Clouds Experiment (MC3E) compared the model PGs to disdrometer observations, and demonstrated the spatial and temporal variability of the PGs which is not possible from disdrometer point measurements alone. The analyses performed during this project demonstrated how statistical analysis can provide a robust method for comparing model simulations and observations, which ultimately resulted identification of limitations in some current microphysics parameterizations as well as insights into precipitation variability which ultimately benefits both observations and modeling efforts.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

Results of a Deep Chandra Observation of the Crab Nebula and Pulsar

The Crab Nebula and pulsar were observed for a total of 150 ksec with the LETG/HRC-S combination aboard the Chandra X-Ray Observatory in 2000, January. One of the principal aims of the experiment was to study the emission of from the pulsar as a function of pulse phase. Neutron stars are believed to be formed with core temperatures of 10(exp 11). As the pulsar is the youngest known neutron star with an age of only 940 yrs, it should be possible to observe thermal emission from the hot stellar surface which in turn constrains equations of state. The pulsar, on the other hand, is a powerful non-thermal emitter, powering an X-ray bright synchrotron nebula which, in Einstein and ROSAT observations, overshadowed the fainter thermal surface emission. Making use of the high angular resolution provided by Chandra we were able to detect X-rays from the Crab-pulsar at all pulse phases. We discuss whether this detection is indeed of thermal emission or of a faint synchrotron component of the pulsed emission from the magnetosphere. We further report on dynamical effects observed in the pulsar-wind outflow and the analysis of the LETG spectral data, especially near the oxygen edge. The results of the spectral analysis has interesting implications for the composition of the interstellar medium.

Weisskopf, M. C.↗
NASA NTRS2015

Assessing Wetland Hydroperiod and Soil Moisture With Remote Sensing: A Demonstration for the NASA Plum Brook Station Year 2

Primary Goal: Assist with the evaluation and measuring of wetlands hydroperiod at the PlumBrook Station using multi-source remote sensing data as part of a larger effort on projecting climate change-related impacts on the station's wetland ecosystems. MTRI expanded on the multi-source remote sensing capabilities to help estimate and measure hydroperiod and the relative soil moisture of wetlands at NASA's Plum Brook Station. Multi-source remote sensing capabilities are useful in estimating and measuring hydroperiod and relative soil moisture of wetlands. This is important as a changing regional climate has several potential risks for wetland ecosystem function. The year two analysis built on the first year of the project by acquiring and analyzing remote sensing data for additional dates and types of imagery, combined with focused field work. Five deliverables were planned and completed: 1) Show the relative length of hydroperiod using available remote sensing datasets 2) Date linked table of wetlands extent over time for all feasible non-forested wetlands 3) Utilize LIDAR data to measure topographic height above sea level of all wetlands, wetland to catchment area radio, slope of wetlands, and other useful variables 4) A demonstration of how analyzed results from multiple remote sensing data sources can help with wetlands vulnerability assessment 5) A MTRI style report summarizing year 2 results. This report serves as a descriptive summary of our completion of these our deliverables. Additionally, two formal meetings were held with Larry Liou and Amanda Sprinzl to provide project updates and receive direction on outputs. These were held on 2/26/15 and 9/17/15 at the Plum Brook Station. Principal Component Analysis (PCA) is a multivariate statistical technique used to identify dominant spatial and temporal backscatter signatures. PCA reduces the information contained in the temporal dataset to the first few new Principal Component (PC) images. Some advantages of PCA include the ability to filter out temporal autocorrelation and reduce speckle to the higher order PC images. A PCA was performed using ERDAS Imagine on a time series of PALSAR dates. Hydroperiod maps were created by separating the PALSAR dates into two date ranges, 2006-2008 and 2010, and performing an unsupervised classification on the PCAs.

Brooks, Colin↗
NASA NTRS2011

Full-Scale Turbofan-Engine Turbine-Transfer Function Determination Using Three Internal Sensors

Existing NASA/Honeywell EVNERT full-scale static engine test data is analyzed by using source-separation techniques in order to determine the turbine transfer of the currently sub-dominant combustor noise. The results are used to assess the combustor-noise prediction capability of the Aircraft Noise Prediction Program (ANOPP). Time-series data from three sensors internal to the Honeywell TECH977 research engine is used in the analysis. The true combustor-noise turbine-transfer function is educed by utilizing a new three-signal approach. The resulting narrowband gain factors are compared with the corresponding constant values obtained from two empirical acoustic-turbine-loss formulas. It is found that a simplified Pratt & Whitney formula agrees better with the experimental results for frequencies of practical importance. The 130 deg downstream-direction far-field 1/3-octave sound-pressure levels (SPL) results of Hultgren & Miles are reexamined using a post-correction of their ANOPP predictions for both the total noise signature and the combustion-noise component. It is found that replacing the standard ANOPP turbine-attenuation function for combustion noise with the simplified Pratt & Whitney formula clearly improves the predictions. It is recommended that the GECOR combustion-noise module in ANOPP be updated to allow for a user-selectable switch between the current transmission-loss model and the simplified Pratt & Whitney formula. The NASA Fundamental Aeronautics Program has the principal objective of overcoming today's national challenges in air transportation. The Subsonic Fixed Wing Project's Reduce-Perceived-Noise Technical Challenge aims to develop concepts and technologies to dramatically reduce the perceived aircraft noise outside of airport boundaries. The reduction of aircraft noise is critical to enabling the anticipated large increase in future air traffic.

Hultgren, Lennart S.↗
NASA NTRS2001

Results of a Deep Chandra Observation of the Crab Nebula and Pulsar

The Crab Nebula and pulsar were observed for a total of 150 ksec with the LETG/HRC-S combination aboard the Chandra X-Ray Observatory in 2000, January and February. One of the principal aims of the experiment was to study the emission from the pulsar as a function of pulse phase. Neutron stars are believed to be formed with core temperatures of 10(exp 11) K. As the pulsar is the best studied of the young known neutron stars with an age of only 940 yrs, it should be possible to observe thermal emission from the hot stellar surface which in turn constrains equations of state. The pulsar, on the other hand, is a powerful non-thermal emitter, powering an X-ray bright synchrotron nebula which, in Einstein and ROSAT observations, overshadowed the fainter thermal surface emission. Making use of the high angular resolution provided by Chandra we were able to detect X-rays from the Crab-pulsar at all pulse phases. We discuss whether this detection is indeed of thermal emission or of a faint synchrotron component of the pulsed emission from the magnetosphere. We further comment on dynamical effects observed in the pulsar-wind outflow and the analysis of the LETG spectral data, especially near the oxygen edge.

Weisskopf, M. C.↗
NASA NTRS1944

On the general theory of thin airfoils for nonuniform motion

General thin-airfoil theory for a compressible fluid is formulated as boundary problem for the velocity potential, without recourse to the theory of vortex motion. On the basis of this formulation the integral equation of lifting-surface theory for an incompressible fluid is derived with the chordwise component of the fluid velocity at the airfoil as the function to be determined. It is shown how by integration by parts this integral equation can be transformed into the Biot-Savart theorem. A clarification is gained regarding the use of principal value definitions for the integral which occur. The integral equation of lifting-surface theory is used a s the starting point for the establishment of a theory for the nonstationary airfoil which is a generalization of lifting-line theory for the stationary airfoil and which might be called "lifting-strip" theory. Explicit expressions are given for section lift and section moment in terms of the circulation function, which for any given wing deflection is to be determined from an integral equation which is of the type of the equation of lifting-line theory. The results obtained are for airfoils of uniform chord. They can be extended to tapered airfoils. One of the main uses of the results should be that they furnish a practical means for the analysis of the aerodynamic span effect in the problem of wing flutter. The range of applicability of "lifting-strip" theory is the same as that of lifting-line theory so that its results may be applied to airfoils with aspect ratios as low as three.

BIBLIOGRAPHY-WINGS↗
NASA NTRS2000

Results of a Deep Chandra Observation of the Crab Nebula and Pulsar

The Crab Nebula and pulsar were observed for a total of 150 ksec with the LETG/HRC-S combination aboard the Chandra X-Ray Observatory in 2000, January. One of the principal aims of the experiment was to study the emission of from the pulsar as a function of pulse phase. Neutron stars are believed to be formed with core temperatures of T(sub c) approx. 10(sup 11) K. As the pulsar is the youngest known neutron star with an age of only 940 yrs, it should be possible to observe thermal emission from the hot stellar surface which in turn constrains equations of state. The pulsar, on the other hand, is a powerful non-thermal emitter, powering an X-ray bright synchrotron nebula which, in Einstein and ROSAT observations, overshadowed the fainter thermal surface emission. Making use of the high angular resolution provided by Chandra we were able to detect X-rays from the Crab-pulsar at all pulse phases. We discuss whether this detection is indeed of thermal emission or of a faint synchrotron component of the pulsed emission from the magnetosphere. We further report on dynamical effects observed in the pulsar-wind outflow and the analysis of the LETG spectral data, especially near the oxygen edge. The results of the spectral analysis has interesting implications for the composition of the interstellar medium.(c) 2000.: American Astronomical Society. All rights reserved

Weisskopf, M. C.↗
DOE OSTI2023

DFTT report for Signal Analysis (2023)

The Detection Framework Testbed and Toolkit (DFTT) is a database and associated java programs intended to facilitate the development and testing of algorithms for operating suites of correlation and subspace detectors. This framework is a generalization of the system described in Harris and Dodge (2011) and Dodge and Harris (2016). DFTT allows retrospective processing of sequences of data using various system configurations. Results are saved in a database, so it is easy to compare the results obtained using different configurations of the system. The principal software components of DFTT are the ConfigCreator, the framework_runner and the Builder program. ConfigCreator assembles the files necessary to define a particular configuration used for processing. The framework_runner operates suites of detectors and saves the results in an Oracle™ database. Builder allows visual examination of templates and detected signals and allows editing and creation of detectors. In addition, there are tools for importing continuous data into the database. DFTT is licensed under the MIT license and has LLNL release number LLNL-CODE-801881. In the current fiscal year DFTT has been used in two different projects. The first (NTL-funded) project investigates the feasibility of screening nuisance detections using correlation detectors. The second (GNEM-funded) project seeks to extend the results of Harris and Dodge (2021) to 3- D sources and multiple stations. Each of these efforts required that additional functionality be added to DFTT. In this report I will summarize the enhancements to DFTT in the context of the relevant research effort.

58 GEOSCIENCES↗
DOE OSTI2023

Thermally Induced Structural Transitions in Epoxy Thermoset Polymer Networks and Their Spectroscopic Responses

The polymer network structure of epoxy thermosets plays a significant role in its final material properties. However, the effects of mild thermal exposure on these network structures are poorly studied. In this work, wide-angle X-ray scattering was used to investigate the polymer network structure of two epoxy thermosets: homopolymerized bisphenol A (BPA) epoxy resin and BPA epoxy resin cured with a polyether amine hardener (BPA/T-403). Using density functional theory and wide-angle X-ray scattering, insights into the polymer network structure were obtained. Diffraction features were determined to originate from hardener-to-hardener molecular distance, perpendicular π–π stacking of aromatic p-phenylene rings, and the average carbon–carbon distance in the polymer. Thermal exposure was found to permanently alter these structural features for both thermosets, with an increase in the π–π stacking distance. Homopolymerized BPA had an additional decrease in the hardener-to-hardener distance. These structural alterations were found to be detectable using Fourier transform infrared spectroscopy and Raman spectroscopy, with changes in the hardener-to-hardener distance having the largest variations in the resulting spectra specifically at the aromatic and ether frequencies.

36 MATERIALS SCIENCE↗
NASA NTRS2006

Bayesian Estimation of Precipitation from Satellite Passive Microwave Observations Using Combined Radar-Radiometer Retrievals

Precipitation estimation from satellite passive microwave radiometer observations is a problem that does not have a unique solution that is insensitive to errors in the input data. Traditionally, to make this problem well posed, a priori information derived from physical models or independent, high-quality observations is incorporated into the solution. In the present study, a database of precipitation profiles and associated brightness temperatures is constructed to serve as a priori information in a passive microwave radiometer algorithm. The precipitation profiles are derived from a Tropical Rainfall Measuring Mission (TRMM) combined radar radiometer algorithm, and the brightness temperatures are TRMM Microwave Imager (TMI) observed. Because the observed brightness temperatures are consistent with those derived from a radiative transfer model embedded in the combined algorithm, the precipitation brightness temperature database is considered to be physically consistent. The database examined here is derived from the analysis of a month-long record of TRMM data that yields more than a million profiles of precipitation and associated brightness temperatures. These profiles are clustered into a tractable number of classes based on the local sea surface temperature, a radiometer-based estimate of the echo-top height (the height beyond which the reflectivity drops below 17 dBZ), and brightness temperature principal components. For each class, the mean precipitation profile, brightness temperature principal components, and probability of occurrence are determined. The precipitation brightness temperature database supports a radiometer-only algorithm that incorporates a Bayesian estimation methodology. In the Bayesian framework, precipitation estimates are weighted averages of the mean precipitation values corresponding to the classes in the database, with the weights being determined according to the similarity between the observed brightness temperature principal components and the brightness temperature principal components of the classes. Because the classes are stratified by the sea surface temperature and the echo-top-height estimator, the number of classes that are considered for retrieval is significantly smaller than the total number of classes, making the algorithm computationally efficient. The radiometer-only algorithm is applied to TMI observations, and precipitation estimates are compared with combined TRMM precipitation radar (PR) TMI reference estimates. The TMI-only algorithm, supported by the empirically derived database, produces estimates that are more consistent with the reference values than the precipitation estimates from the version-6 TRMM facility TMI algorithm. Cloud-resolving model simulations are used to assign a latent heating profile to each precipitation profile in the empirically derived database, making it possible to estimate latent heating using the radiometer-only algorithm. Although the evaluation of latent heating estimates in this study is preliminary, because realistic conditional probability distribution functions are attached to latent heating structures in the algorithm s database, a generally positive impact on latent heating estimation from passive microwave observations is expected.

Grecu, Mircea↗