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DOE OSTI2023

Towards Lightweight Data Integration Using Multi-Workflow Provenance and Data Observability

Modern large-scale scientific discovery requires multidisciplinary collaboration across diverse computing facilities, including High Performance Computing (HPC) machines and the Edge-to-Cloud continuum. Integrated data analysis plays a crucial role in scientific discovery, especially in the current AI era, by enabling Responsible AI development, FAIR, Reproducibility, and User Steering. However, the heterogeneous nature of science poses challenges such as dealing with multiple supporting tools, cross-facility environments, and efficient HPC execution. Building on data observability, adapter system design, and provenance, we propose MIDA: an approach for lightweight runtime Multi-workflow Integrated Data Analysis. MIDA defines data observability strategies and adaptability methods for various parallel systems and machine learning tools. With observability, it intercepts the dataflows in the background without requiring instrumentation while integrating domain, provenance, and telemetry data at runtime into a unified database ready for user steering queries. We conduct experiments showing end-to-end multi-workflow analysis integrating data from Dask and MLFlow in a real distributed deep learning use case for materials science that runs on multiple environments with up to 276 GPUs in parallel. We show near-zero overhead running up to 100,000 tasks on 1,680 CPU cores on the Summit supercomputer.

Santos Souza, Renan↗

NASA NTRS2002

Experimental Investigation of Water Droplet Impingement on Airfoils, Finite Wings, and an S-duct Engine Inlet

Validation of trajectory computer codes, for icing analysis, requires experimental water droplet impingement data for a wide range of aircraft geometries as well as flow and icing conditions. This report presents improved experimental and data reduction methods for obtaining water droplet impingement data and provides a comprehensive water droplet impingement database for a range of test geometries including an MS(1)-0317 airfoil, a GLC-305 airfoil, an NACA 65(sub 2)-415 airfoil, a commercial transport tail section, a 36-inch chord natural laminar flow NLF(1)-0414 airfoil, a 48-inch NLF(1)-0414 section with a 25 percent chord simple flap, a state-of-the-art three-element high lift system, a NACA 64A008 finite span swept business jet tail, a full-scale business jet horizontal tail section, a 25 percent-scale business jet empennage, and an S-duct turboprop engine inlet. The experimental results were obtained at the NASA Glenn Icing Research Tunnel (IRT) for spray clouds with median volumetric diameter (MVD) of 11, 11.5, 21, 92, and 94 microns and for a range of angles of attack. The majority of the impingement experiments were conducted at an air speed of 175 mph corresponding to a Reynolds number of approximately 1.6 million per foot. The maximum difference of repeated tests from the average ranged from 0.24 to 12 percent for most of the experimental results presented. This represents a significant improvement in test repeatability compared to previous experimental studies. The increase in test repeatability was attributed to improvements made to the experimental and data reduction methods. Computations performed with the LEWICE-2D and LEWICE-3D computer codes for all test configurations are presented in this report. For the test cases involving median volumetric diameters of 11 and 21 microns, the correlation between the analytical and experimental impingement efficiency distributions was good. For the median volumetric diameters of 92 and 94-micron cases, however, the analysis produced higher impingement efficiencies and larger impingement limits than the experiment. It is speculated that this discrepancy is due to droplet splashing and breakup experienced by large droplets during impingement.

Papadakis, Michael↗

NASA NTRS2015

The I4 Online Query Tool for Earth Observations Data

The NASA Earth Observation System Data and Information System (EOSDIS) delivers an average of 22 terabytes per day of data collected by orbital and airborne sensor systems to end users through an integrated online search environment (the Reverb/ECHO system). Earth observations data collected by sensors on the International Space Station (ISS) are not currently included in the EOSDIS system, and are only accessible through various individual online locations. This increases the effort required by end users to query multiple datasets, and limits the opportunity for data discovery and innovations in analysis. The Earth Science and Remote Sensing Unit of the Exploration Integration and Science Directorate at NASA Johnson Space Center has collaborated with the School of Earth and Space Exploration at Arizona State University (ASU) to develop the ISS Instrument Integration Implementation (I4) data query tool to provide end users a clean, simple online interface for querying both current and historical ISS Earth Observations data. The I4 interface is based on the Lunaserv and Lunaserv Global Explorer (LGE) open-source software packages developed at ASU for query of lunar datasets. In order to avoid mirroring existing databases - and the need to continually sync/update those mirrors - our design philosophy is for the I4 tool to be a pure query engine only. Once an end user identifies a specific scene or scenes of interest, I4 transparently takes the user to the appropriate online location to download the data. The tool consists of two public-facing web interfaces. The Map Tool provides a graphic geobrowser environment where the end user can navigate to an area of interest and select single or multiple datasets to query. The Map Tool displays active image footprints for the selected datasets (Figure 1). Selecting a footprint will open a pop-up window that includes a browse image and a link to available image metadata, along with a link to the online location to order or download the actual data. Search results are either delivered in the form of browse images linked to the appropriate online database, similar to the Map Tool, or they may be transferred within the I4 environment for display as footprints in the Map Tool. Datasets searchable through I4 (http://eol.jsc.nasa.gov/I4_tool) currently include: Crew Earth Observations (CEO) cataloged and uncataloged handheld astronaut photography; Sally Ride EarthKAM; Hyperspectral Imager for the Coastal Ocean (HICO); and the ISS SERVIR Environmental Research and Visualization System (ISERV). The ISS is a unique platform in that it will have multiple users over its lifetime, and that no single remote sensing system has a permanent internal or external berth. The open source I4 tool is designed to enable straightforward addition of new datasets as they become available such as ISS-RapidSCAT, Cloud Aerosol Transport System (CATS), and the High Definition Earth Viewing (HDEV) system. Data from other sensor systems, such as those operated by the ISS International Partners or under the auspices of the US National Laboratory program, can also be added to I4 provided sufficient access to enable searching of data or metadata is available. Commercial providers of remotely sensed data from the ISS may be particularly interested in I4 as an additional means of directing potential customers and clients to their products.

Stefanov, William L.↗

DOE OSTI2015

THE 2014 KIDA NETWORK FOR INTERSTELLAR CHEMISTRY

Chemical models used to study the chemical composition of the gas and the ices in the interstellar medium are based on a network of chemical reactions and associated rate coefficients. These reactions and rate coefficients are partially compiled from data in the literature, when available. We present in this paper kida.uva.2014, a new updated version of the kida.uva public gas-phase network first released in 2012. In addition to a description of the many specific updates, we illustrate changes in the predicted abundances of molecules for cold dense cloud conditions as compared with the results of the previous version of our network, kida.uva.2011.

astrochemistry↗

DOE OSTI2020

Constraining the destruction rate of K 40 in stellar nucleosynthesis through the study of the Ar 40 ( p , n ) K 40 reaction

Background: We present that K 40 plays a significant role in the radiogenic heating of Earth-like exoplanets, which can affect the development of a habitable environment on their surfaces. The initial amount of K 40 in the interior of these planets depends on the composition of the interstellar clouds from which they formed. Within this context, nuclear reactions that regulate the production of K 40 during stellar evolution can play a critical role. Purpose: In this study, we constrain for the first time the astrophysical reaction rate of K 40 ( n , p ) Ar 40 , which is responsible for the destruction of K 40 during stellar nucleosynthesis. We provide to the nuclear physics community high-resolution data on the cross section and angular distribution of the Ar 40 ( p , n ) K 40 reaction. These are important to various applications involving Ar 40 . The associated reaction rate of the Ar 40 ( p , n ) K 40 process addresses a reaction rate gap in the Joint Institute for Nuclear Astrophysics REACLIB database in the region of intermediate-mass isotopes. Methods: We performed differential cross-section measurements on the Ar 40 ( p , n ) K 40 reaction, for six energies in the center-of-mass system between 3.2 and 4.0 MeV and various angles between 0 ° and 135 ° . The experiment took place at the Edwards Accelerator Laboratory at Ohio University using the beam swinger target location and a standard neutron time-of-flight technique. We extracted total and partial cross sections by integrating the double differential cross sections we measured. Results: The total and partial cross sections varied with energy due to the contribution from isobaric analog states and Ericson type fluctuations. The energy-averaged neutron angular distributions were symmetrical relative to 90 ° . Based on the experimental data, local transmission coefficients were extracted and were used to calculate the astrophysical reaction rates of Ar 40 ( p , n ) K 40 and K 40 ( n , p ) Ar 40 reactions. The new rates were found to vary significantly from the theoretical rates in the REACLIB library. We implemented the new rates in network calculations to study nucleosynthesis via the slow neutron capture process, and we found that the produced abundance of K 40 is reduced by up to 10% compared to calculations with the library rates. At the same time, the above result removes a significant portion of the previous theoretical uncertainty on the K 40 yields from stellar evolution calculations. Conclusions: Our results support a destruction rate of K 40 in massive stars via the K 40 ( n , p ) Ar 40 reaction that is larger compared to previous estimates. The rate of K 40 destruction via the K 40 ( n , p ) Ar 40 reaction now has a dramatically reduced uncertainty based on our measurement. Lastly, this result directly affects the predicted stellar yields of K 40 from nucleosynthesis, which is a critical input parameter for the galactic chemical evolution models that are currently employed for the study of significant properties of exoplanets.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Global ocean dimethyl sulfide climatology estimated from observations and an artificial neural network

Marine dimethyl sulfide (DMS) is important to climate due to the ability of DMS to alter Earth's radiation budget. Knowledge of the global-scale distribution, seasonal variability, and sea-to-air flux of DMS is needed in order to improve understanding of atmospheric sulfur, aerosol/cloud dynamics, and albedo. Here we examine the use of an artificial neural network (ANN) to extrapolate available DMS measurements to the global ocean and produce a global climatology with monthly temporal resolution. A global database of 82 996 ship-based DMS measurements in surface waters was used along with a suite of environmental parameters consisting of latitude–longitude coordinates, time of day, time of year, solar radiation, mixed layer depth, sea surface temperature, salinity, nitrate, phosphate, and silicate. Linear regressions of DMS against the environmental parameters show that on a global-scale mixed layer depth and solar radiation are the strongest predictors of DMS. These parameters capture ~9 % and ~7 % of the raw DMS data variance, respectively. Multilinear regression can capture more of the raw data variance (~39 %) but strongly underestimates DMS in high-concentration regions. In contrast, the artificial neural network captures ~66 % of the raw data variance in our database. Like prior climatologies our results show a strong seasonal cycle in surface ocean DMS with the highest concentrations and sea-to-air fluxes in the high-latitude summertime oceans. We estimate a lower global sea-to-air DMS flux (20.12±0.43 Tg S yr –1 ) than the prior estimate based on a map interpolation method when the same gas transfer velocity parameterization is used. Our sensitivity test results show that DMS concentration does not change unidirectionally with each of the environmental parameters, which emphasizes the interactions among these parameters. The ANN model suggests that the flux of DMS from the ocean to the atmosphere will increase with global warming. Given that larger DMS fluxes induce greater cloud albedo, this corresponds to a negative climate feedback.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1995

Estimation of polar stratospheric cloud infrared extinction climatology using visible satellite observations

Polar stratospheric clouds (PSC's) provide surfaces for heterogeneous processes which can dramatically alter the normal partitioning of odd nitrogen and chlorine families in the winter polar stratospheres, setting up conditions for significant ozone depletion as manifested in the springtime Antarctic ozone hole. The spatial and temporal distribution of PSC's is important for parameterizing PSC occurrence in multidimensional photochemical models whose use is essential for fully understanding observed Antarctic ozone losses as well as for accessing the possibility of a similar phemonenon occurring in the future in the Arctic. The Stratospheric Aerosol Measurement (SAM) 2 sensor, a single-channel (1mu m) photometer launched into a Sun-synchronous orbit aboard the Nimbus 7 satellite in October 1978, provided a unique database to establish the climatology of PSC's. Poole and Pitts (1994) used the record of high-latitude aerosol extinction obtained by SAM II from 1979-1989 to establish the climatology of PSC occurrences in the Arctic and Antarctic. Unfortunately, little information about PSC composition or type was detectable from the single-wavelength SAM II data.

Pitts, Michael C.↗

NASA NTRS2020

The interactive global fire module pyrE (v1.0)

Fires affect the composition of the atmosphere and Earth’s radiation balance by emitting a suite of reactive gases and particles. An interactive fire module in an Earth system model (ESM) allows us to study the natural and anthropogenic drivers, feedbacks, and interactions of open fires. To do so, we have developed pyrE, the NASA GISS (Goddard Institute for Space Studies) interactive fire emissions *module. The pyrE module is driven by environmental variables like flammability and cloud-to-ground lightning, calculated by the GISS ModelE ESM, and parameterized by anthropogenic impacts based on population density data. Fire emissions are generated from the flaming phase in pyrE (active fires). Using pyrE, we examine fire occurrence, regional fire suppression, burned area, fire emissions, and how it all affects atmospheric composition. To do so, we evaluate pyrE by comparing it to satellite-based datasets of fire count, burned area, fire emissions, and aerosol optical depth (AOD). We demonstrate pyrE’s ability to simulate the daily and seasonal cycles of open fires and resulting emissions. Our results indicate that interactive fire emissions are biased low by 32 %–42 %, depending on emitted species, compared to the GFED4s (Global Fire Emissions Database) inventory. The bias in emissions drives underestimation in column densities, which is diluted by natural and anthropogenic emissions sources and production and loss mechanisms. Regionally, the resulting AOD of a simulation with interactive fire emissions is underestimated mostly over Indonesia compared to a simulation with GFED4s emissions and to MODIS AOD. In other parts of the world pyrE’s performance in terms of AOD is marginal to a simulation with prescribed fire emissions.

Fires↗

DOE OSTI2025

Statistical Analysis of Trans‐Ionospheric Pulse Pairs and Inferences on Their Characteristics

Trans-ionospheric pulse pairs (TIPPs), first observed in 1993, are signatures of in-cloud lightning discharges observed by satellite-based broadband very high frequency (VHF) receivers. It has been definitively shown that TIPPs are the space-based signatures of compact intracloud discharges (CIDs), and that the associated pair of pulses that comprise a TIPP result from the direct VHF pulse from the discharge, followed by a pulse reflected from the Earth's surface. However, the ratio of the peak amplitudes of these two pulses can vary widely, with the second pulse often having considerably higher peak amplitude than the first. This observation has not been satisfactorily explained. Using data collected from geostationary orbit by the Radio Frequency Sensor (RFS) and matched to locations reported by the Global Lightning Dataset (GLD360), we assemble the largest database to date of 76,348 TIPPs with associated location, altitude, and amplitude ratio of the two pulses in the TIPP. We show that the amplitude ratio of TIPPs is strongly correlated to the altitude of the associated discharges and the geometry of the source location with respect to the Earth's surface and the receiver. These observations strongly suggest that the difference in amplitude of the two pulses is driven by a nondipole radiated beam pattern that is dependent on the polarity of the CID, velocity of the current wavefront, and viewing angle.

58 GEOSCIENCES↗

NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth independence and autonomy of mission operations. Here we present an overview of AI/ML architecture to support deep space mission goals, developed with leaders in the field. First, we focus on the fundamental biological research that supports our understanding of physiological responses to spaceflight, and we describe current efforts to support AI/ML research including data standardization and data engineering through maximally open and FAIR (findable, accessible, interoperable, reusable) databases and the generation of AI-ready datasets for reuse and analysis. We also discuss remote data management frameworks for research data as well as environmental and health data that are generated during deep space missions. We highlight several research projects that leverage data standardization and management for fundamental biological discovery to uncover the complex effects of space travel on living systems. Next, we provide an overview of cutting-edge AI/ML approaches that can be integrated to support remote monitoring and analysis during deep space missions, including generative models and large language models to learn the underlying biomedical patterns and predict outcomes or answer questions during off world medical scenarios. We also describe current AI/ML methods to support this research and monitoring through automated cloud-based labs which enable limited human intervention and closed-loop experimentation in remote settings. These labs could support mission autonomy by analyzing environmental data streams, and would be facilitated through in situ analytics capabilities to avoid sending large raw data files through low bandwidth communications. Finally, in the context of deep space missions with limited communications or access to medical advice from Earth, we describe a solution for integrated, real-time mission biomonitoring across hierarchical levels from continuous environmental monitoring, to wearables and point-of-care devices, to molecular and physiological monitoring. We introduce a precision space health system that will ensure that the future of space health is predictive, preventative, participatory and personalized.

artificial intelligence↗

DOE OSTI2020

Navigation and Meteorological Data from Multiple Sensors on Airborne Platform (NAVMET-AIR) Value-Added Product Report

The Navigation and Meteorological Data from Multiple Sensors on Airborne Platform (NAVMET-AIR) value-added product encompasses the aafnaviwg data set in the ARM Data Center (ADC), known as the IWG file, named for the Inter-Agency Working Group for Airborne Data and Telemetry Systems (IWGADTS). Its purpose is to produce a suite of tools to promote standardization of instrument interface, data format, and data processing. This data set’s contents are navigational and meteorological state variables at 1 Hz. It also contains higher-order data flags created by ARM Aerial Facility (AAF) scientists to aid analysis such as periods when the aircraft is flying level, operating in maneuvers, or flying through cloud. Due to the nature of research flights, the payload of the aircraft consists of many duplicate and overlapping instruments to ensure, in case of instrument failure, there is a backup to record the data. Measurements from multiple instruments are consolidated into a single file. Each variable of this data set is carefully chosen from the onboard instrumentation and quality checked by AAF scientists to create this wholistic and most accurate data set for airborne research. This document is intended to be a hub towards the individual “read me” files produced for each campaign. For reference about what instrument was used for calculations on specific days, the read me files are located in the ARM IOP archive at the addresses listed, or access the IOP (intensive operational period) database at https://www.archive.arm.gov/.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2000

Laboratory Astrophysics: The Universe in the Palm of Your Hand

Polycyclic aromatic compounds (PACs), a class of organic molecules whose structures are characterized by the presence of two or more fused aromatic rings, have been the subject of astrophysical interest for nearly two decades. Large by interstellar standards (from as few as 20 to perhaps as many as several hundred atoms), it has been suggested that these species are among the most abundant interstellar molecules impacting a wide range of astrophysical phenomena including: (1) the ubiquitous family of infrared emission bands observed in an ever-increasing assortment of astronomical objects; (2) the subtle but rich array of discrete visible/near-infrared interstellar molecular absorption features known as the diffuse interstellar bands (DIBs); (3) the broad near-infrared quasi-continuum observed in a number of nebulae known as excess red emission (ERE); (4) the interstellar ultraviolet extinction curve and broad '2200 Angstrom bump'; and (5) the heating/cooling mechanisms of interstellar clouds. Nevertheless, until recently a lack of good-quality laboratory spectroscopic data on PACs under astrophysically relevant conditions (i.e. isolated, ionized molecules, ionized molecular clusters, etc.) has hindered critical evaluation and extension of this model. Fortunately, the last decade has seen an explosion of experimental and theoretical techniques aimed specifically at addressing these issues. Indeed, many of these techniques will be explored in the series of talks which constitute this forum. This talk will provide an overview of the studies of the spectroscopic properties of isolated, neutral, and ionized PACs that have been conducted in the Astrochemistry Laboratory at NASA Ames, together with a consideration of their implications for astrophysics. Particular attention will be paid to models of the interstellar infrared emission spectra generated using the available database of laboratory PAC infrared spectra and the natural ability of this database to accommodate the variations observed in the astronomical spectra. Such models provide insight into the structure, abundance, and ionization state of the interstellar PAC population and, in turn, provide direct insight into the processes of carbon nucleation, growth and evolution as matter is processed through the interstellar medium. These models will be followed by a more in depth look at some specific aspects of the interstellar infrared emission spectrum, considering both what we can learn about them and what we can learn from them. Finally, some of the limitations of the current model and the available spectroscopic dataset will be 'dered along with future experimental directions designed to address these shortcomings. Further information about this and the related areas of research currently ongoing in the Astrochemistry Laboratory can be found at our world wide web site. http://www-space.arc.nasa.gov/(tilda)astrochem

Hudgins, Douglas M.↗

DOE OSTI2015

THE NATURE AND FREQUENCY OF OUTFLOWS FROM STARS IN THE CENTRAL ORION NEBULA CLUSTER

Recent Hubble Space Telescope images have allowed the determination with unprecedented accuracy of motions and changes of shocks within the inner Orion Nebula. These originate from collimated outflows from very young stars, some within the ionized portion of the nebula and others within the host molecular cloud. We have doubled the number of Herbig–Haro objects known within the inner Orion Nebula. We find that the best-known Herbig–Haro shocks originate from relatively few stars, with the optically visible X-ray source COUP 666 driving many of them. While some isolated shocks are driven by single collimated outflows, many groups of shocks are the result of a single stellar source having jets oriented in multiple directions at similar times. This explains the feature that shocks aligned in opposite directions in the plane of the sky are usually blueshifted because the redshifted outflows pass into the optically thick photon-dominated region behind the nebula. There are two regions from which optical outflows originate for which there are no candidate sources in the SIMBAD database.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2004

Infrared Spectroscopy of Star Formation in Galactic and Extragalactic Regions

In this program we proposed to perform a series of spectroscopic studies, including data analysis and modeling, of star formation regions using an ensemble of archival space-based data from the Infrared Space Observatory's Long Wavelength Spectrometer and Short Wavelength Spectrometer, and to take advantage of other spectroscopic databases including the first results from SIRTF. Our empha- sis has been on star formation in external, bright IR galaxies, but other areas of research have in- cluded young, low or high mass pre-main sequence stars in star formation regions, and the galactic center. The OH lines in the far infrared were proposed as one key focus of this inquiry because the Principal Investigator (H. Smith) had a full set of OH IR lines from IS0 observations. It was planned that during the proposed 2-1/2 year timeframe of the proposal other data (including perhaps from SIRTF) would become available, and we intended to be responsive to these and other such spec- troscopic data sets. Three papers are included:The Infrared Lines of OH: Diagnostics of Molecular Cloud Conditions in Infrared Bright Galaxies; The Far-Infrared Spectrum of Arp 220; andThe Far-Infrared Emission Line and Continuum Spectrum of the Seyfert Galaxy NGC 1068.

Frogel, Jay↗

DOE OSTI2019

Comparing datasets of volume servers to illuminate their energy use in data centers

As data centers proliferate, their energy intensity deserves close attention. Always-on operations and growing usage for cloud and other backend processes make servers the fundamental driver of data center energy use. Yet servers’ power draw under real-world conditions is poorly understood. This paper explores characteristics of volume servers that affect energy use, quantifying differences in power draw between higher-performing Standard Performance Evaluation Corporation (SPEC) and ENERGY STAR servers and that of a typical server. First, we establish general characteristics of the US installed base, before reporting hardware configurations from a major online retail website. We then compare idle power across three datasets (one unique to this paper) and explain their differences via the hardware characteristics to which power draw is most sensitive. We find idle server power demand to be significantly higher than benchmarks from ENERGY STAR and the industry-released SPEC database, and SPEC server configurations—and likely their power scaling—to be atypical of volume servers. Next, we examine power draw trends among high-performing servers across their load range to consider whether these trends are representative of volume servers, before inputting average idle power load values into a recent national server energy use model. Lastly, results from two surveys of IT professionals illustrate the incidence of more efficient equipment and operational practices in server rooms/closets. Future work should include server power field measurements in data centers of different sizes, accounting for variations in configurations and setting changes post-purchase, as well as investigating the linkage between time and server energy efficiency.

Fuchs, Heidi (ORCID:0000000300105411)↗

NASA NTRS2005

Combined Radar and Radiometer Analysis of Precipitation Profiles for a Parametric Retrieval Algorithm

A methodology to analyze precipitation profiles using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and precipitation radar (PR) is proposed. Rainfall profiles are retrieved from PR measurements, defined as the best-fit solution selected from precalculated profiles by cloud-resolving models (CRMs), under explicitly defined assumptions of drop size distribution (DSD) and ice hydrometeor models. The PR path-integrated attenuation (PIA), where available, is further used to adjust DSD in a manner that is similar to the PR operational algorithm. Combined with the TMI-retrieved nonraining geophysical parameters, the three-dimensional structure of the geophysical parameters is obtained across the satellite-observed domains. Microwave brightness temperatures are then computed for a comparison with TMI observations to examine if the radar-retrieved rainfall is consistent in the radiometric measurement space. The inconsistency in microwave brightness temperatures is reduced by iterating the retrieval procedure with updated assumptions of the DSD and ice-density models. The proposed methodology is expected to refine the a priori rain profile database and error models for use by parametric passive microwave algorithms, aimed at the Global Precipitation Measurement (GPM) mission, as well as a future TRMM algorithms.

Masunaga, Hirohiko↗

NASA NTRS1993

A regional rainfall climatology over Mexico and the southwest United States derived from passive microwave and geosynchronous infrared data

A three-year climatology of satellite-estimated rainfall for the warm season for the southwest United States and Mexico has been derived from data from the Special Sensor Microwave Imager (SSM/I). The microwave data have been stratified by month (June, July, August), year (1988, 1989, 1990), and time of day (morning and evening orbits). A rain algorithm was employed that relates 86-GHz brightness temperatures to rain rate using a coupled cloud-radiative transfer model. Results identify an early evening maximum in rainfall along the western slope of the Sierra Madre Occidental during all three months. A prominent morning rainfall maximum was found off the western Mexican coast near Mazatlan in July and August. Substantial differences between morning and evening estimates were noted. To the extent that three years constitute a climatology, results of interannual variability are presented. Results are compared and contrasted to high-resolution (8 km, hourly) infrared cloud climatologies, which consist of the frequency of occurrence of cloud colder than -38 C and -58 C. This comparison has broad implications for the estimation of rainfall by simple (cloud threshold) techniques. By sampling the infrared data to approximate the time and space resolution of the microwave, we produce ratios (or adjustment factors) by which we can adjust the infrared rain estimation schemes. This produces a combined microwave/infrared rain algorithm for monthly rainfall. Using a limited set of raingage data as ground truth, an improvement (lower bias and root-mean-square error) was demonstrated by this combined technique when compared to either method alone. The diurnal variability of convection during July 1990 was examined using hourly rain estimates from the Geostationary Operational Environmental Satellite (GOES) precipitation index and the convective stratiform technique, revealing a maximum in estimated rainfall from 1800 to 2100 local time. It is in this time period when the SSM/I evening orbit occurs. A high-resolution topographic database was available to aid in interpreting the influence of topography on the rainfall patterns.

Negri, Andrew J.↗

NASA NTRS2004

Evaluation and Application of Satellite-Based Latent Heating Profile Estimation Methods

In recent years, methods for estimating atmospheric latent heating vertical structure from both passive and active microwave remote sensing have matured to the point where quantitative evaluation of these methods is the next logical step. Two approaches for heating algorithm evaluation are proposed: First, application of heating algorithms to synthetic data, based upon cloud-resolving model simulations, can be used to test the internal consistency of heating estimates in the absence of systematic errors in physical assumptions. Second, comparisons of satellite-retrieved vertical heating structures to independent ground-based estimates, such as rawinsonde-derived analyses of heating, provide an additional test. The two approaches are complementary, since systematic errors in heating indicated by the second approach may be confirmed by the first. A passive microwave and combined passive/active microwave heating retrieval algorithm are evaluated using the described approaches. In general, the passive microwave algorithm heating profile estimates are subject to biases due to the limited vertical heating structure information contained in the passive microwave observations. These biases may be partly overcome by including more environment-specific a priori information into the algorithm s database of candidate solution profiles. The combined passive/active microwave algorithm utilizes the much higher-resolution vertical structure information provided by spaceborne radar data to produce less biased estimates; however, the global spatio-temporal sampling by spaceborne radar is limited. In the present study, the passive/active microwave algorithm is used to construct a more physically-consistent and environment-specific set of candidate solution profiles for the passive microwave algorithm and to help evaluate errors in the passive algorithm s heating estimates. Although satellite estimates of latent heating are based upon instantaneous, footprint- scale data, suppression of random errors requires averaging to at least half-degree resolution. Analysis of mesoscale and larger space-time scale phenomena based upon passive and passive/active microwave heating estimates from TRMM, SSMI, and AMSR data will be presented at the conference.

Olson, William S.↗