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NASA NTRS1989

Heterodyne spectroscopy of the J = 17-16 CO line in Orion

We have obtained high-resolution spectra of the 153 micrometers J = 17-16 CO line in the BN-KL region of Orion using a laser heterodyne spectrometer. The line shows broad wings (30 km s-1 FWHM at BN) characteristic of the plateau emission as well as a narrower component probably associated with the quiescent gas in the molecular ridge. From an analysis of the plateau emission together with that observed in lower J CO transitions, we derive an excitation temperature of 180 +/- 50 K and minimum column density of 1 x 10(18) cm-2 for CO in this component, which constitutes 80% of the total integrated intensity of the J = 17-16 line near BN. The peak intensity of the narrower component observed at 0.8 km s-1 resolution increases relative to that of the plateau component toward theta 1C and away from BN, while the width decreases from 10 to 4 km s-1 (FWHM).

NASA Discipline Number 52-60↗

NASA NTRS2004

Hurricane Forecasting with the High-resolution NASA Finite-volume General Circulation Model

A high-resolution finite-volume General Circulation Model (fvGCM), resulting from a development effort of more than ten years, is now being run operationally at the NASA Goddard Space Flight Center and Ames Research Center. The model is based on a finite-volume dynamical core with terrain-following Lagrangian control-volume discretization and performs efficiently on massive parallel architectures. The computational efficiency allows simulations at a resolution of a quarter of a degree, which is double the resolution currently adopted by most global models in operational weather centers. Such fine global resolution brings us closer to overcoming a fundamental barrier in global atmospheric modeling for both weather and climate, because tropical cyclones and even tropical convective clusters can be more realistically represented. In this work, preliminary results of the fvGCM are shown. Fifteen simulations of four Atlantic tropical cyclones in 2002 and 2004 are chosen because of strong and varied difficulties presented to numerical weather forecasting. It is shown that the fvGCM, run at the resolution of a quarter of a degree, can produce very good forecasts of these tropical systems, adequately resolving problems like erratic track, abrupt recurvature, intense extratropical transition, multiple landfall and reintensification, and interaction among vortices.

Atlas, R.↗

NASA NTRS2001

Pulse Detonation Engine Modeled

Pulse Detonation Engine Technology is currently being investigated at Glenn for both airbreathing and rocket propulsion applications. The potential for both mechanical simplicity and high efficiency due to the inherent near-constant-volume combustion process, may make Pulse Detonation Engines (PDE's) well suited for a number of mission profiles. Assessment of PDE cycles requires a simulation capability that is both fast and accurate. It should capture the essential physics of the system, yet run at speeds that allow parametric analysis. A quasi-one-dimensional, computational-fluid-dynamics-based simulation has been developed that may meet these requirements. The Euler equations of mass, momentum, and energy have been used along with a single reactive species transport equation, and submodels to account for dominant loss mechanisms (e.g., viscous losses, heat transfer, and valving) to successfully simulate PDE cycles. A high-resolution numerical integration scheme was chosen to capture the discontinuities associated with detonation, and robust boundary condition procedures were incorporated to accommodate flow reversals that may arise during a given cycle. The accompanying graphs compare experimentally measured and computed performance over a range of operating conditions for a particular PDE. Experimental data were supplied by Fred Schauer and Jeff Stutrud from the Air Force Research Laboratory at Wright-Patterson AFB and by Royce Bradley from Innovative Scientific Solutions, Inc. The left graph shows thrust and specific impulse, Isp, as functions of equivalence ratio for a PDE cycle in which the tube is completely filled with a detonable hydrogen/air mixture. The right graph shows thrust and specific impulse as functions of the fraction of the tube that is filled with a stoichiometric mixture of hydrogen and air. For both figures, the operating frequency was 16 Hz. The agreement between measured and computed values is quite good, both in terms of trend and magnitude. The error is under 10 percent everywhere except for the thrust value at an equivalence ratio of 0.8 in the left figure, where it is 14 percent. The simulation results shown were made using 200 numerical cells. Each cycle of the engine, approximately 0.06 sec, required 2.0 min of CPU time on a Sun Ultra2. The simulation is currently being used to analyze existing experiments, design new experiments, and predict performance in propulsion concepts where the PDE is a component (e.g., hybrid engines and combined cycles).

Paxson, Daniel E.↗

NASA NTRS2006

Introduction to MODIS Cloud Products

The Earth's radiative energy balance and hydrological cycle are fundamentally coupled with the distribution and properties of clouds. Therefore, the ability to remotely infer cloud properties and their variation in space and time is crucial for establishing climatologies as a reference for validation of present-day climate models and in assessing future climate change. Remote cloud observations also provide data sets useful for testing and improving cloud model physics, and for assimilation into numerical weather prediction models. The MODerate Resolution Imaging Spectroradiometer (MODIS) imagers on the Terra and Aqua Earth Observing System (EOS) platforms provide the capability for globally retrieving these properties using passive solar reflectance and infrared techniques. In addition to providing measurements similar to those offered on a suite of historical operational weather platforms such as the Advanced Very High Resolution Radiometer (AVHRR), the High-resolution Infrared Radiation Sounder (HIRS), and the Geostationary Operational Environmental Satellite (GOES), MODIS provides additional spectral and/or spatial resolution in key atmospheric bands, along with on-board calibration, to expand the capability for global cloud property retrievals. The core MODIS operational cloud products include cloud top pressure, thermodynamic phase, optical thickness, particle size, and water path, and are derived globally at spatial resolutions of either 1- or 5-km (referred to as Level-2 or pixel-level products). In addition, the MODIS atmosphere team (collectively providing cloud, aerosol, and clear sky products) produces a combined gridded product (referred to as Level-3) aggregated to a 1 equal-angle grid, available for daily, eight-day, and monthly time periods. The wealth of information available from these products provides critical information for climate studies as well as the continuation and improved understanding of existing satellite-based cloud climatologies derived from heritage instruments. This chapter provides an overview of the MODIS Level-2 and -3 operational cloud products.

Baum, Bryan A.↗

NASA NTRS2009

Parametric Optimization of Ares I Propellant Slosh Characteristics Using Frequency Response Criteria

A novel technique for developing propellant slosh damping requirements with respect to the stability characteristics of large flexible launch vehicles is presented. A numerical algorithm is devised which allows an automated software program to rapidly converge to pseudo-optimal solutions that minimize required propellant slosh damping for multiple tanks while maintaining constraints on the frequency response characteristics of a particular open-loop plant transfer function. An implementation of the algorithm using a high-order linear model of the Ares I plant dynamics considers all relevant dynamic interactions of flexible body modes, propellant slosh, and nozzle inertia effects. A high-resolution propellant damping requirements table is produced that can be used for baffle design. The method is demonstrated to provide exceptional speed and accuracy when compared with the alternative human-in-the-loop approach.

Orr, Jeb S.↗

NASA NTRS2010

A Modeling and Verification Study of Summer Precipitation Systems Using NASA Surface Initialization Datasets

One of the most challenging weather forecast problems in the southeastern U.S. is daily summertime pulse-type convection. During the summer, atmospheric flow and forcing are generally weak in this region; thus, convection typically initiates in response to local forcing along sea/lake breezes, and other discontinuities often related to horizontal gradients in surface heating rates. Numerical simulations of pulse convection usually have low skill, even in local predictions at high resolution, due to the inherent chaotic nature of these precipitation systems. Forecast errors can arise from assumptions within parameterization schemes, model resolution limitations, and uncertainties in both the initial state of the atmosphere and land surface variables such as soil moisture and temperature. For this study, it is hypothesized that high-resolution, consistent representations of surface properties such as soil moisture, soil temperature, and sea surface temperature (SST) are necessary to better simulate the interactions between the surface and atmosphere, and ultimately improve predictions of summertime pulse convection. This paper describes a sensitivity experiment using the Weather Research and Forecasting (WRF) model. Interpolated land and ocean surface fields from a large-scale model are replaced with high-resolution datasets provided by unique NASA assets in an experimental simulation: the Land Information System (LIS) and Moderate Resolution Imaging Spectroradiometer (MODIS) SSTs. The LIS is run in an offline mode for several years at the same grid resolution as the WRF model to provide compatible land surface initial conditions in an equilibrium state. The MODIS SSTs provide detailed analyses of SSTs over the oceans and large lakes compared to current operational products. The WRF model runs initialized with the LIS+MODIS datasets result in a reduction in the overprediction of rainfall areas; however, the skill is almost equally as low in both experiments using traditional verification methodologies. Output from object-based verification within NCAR s Meteorological Evaluation Tools reveals that the WRF runs initialized with LIS+MODIS data consistently generated precipitation objects that better matched observed precipitation objects, especially at higher precipitation intensities. The LIS+MODIS runs produced on average a 4% increase in matched precipitation areas and a simultaneous 4% decrease in unmatched areas during three months of daily simulations.

Jonathan L. Case↗

NASA NTRS2008

Weather Research and Forecasting Model Wind Sensitivity Study at Edwards Air Force Base, CA

NASA prefers to land the space shuttle at Kennedy Space Center (KSC). When weather conditions violate Flight Rules at KSC, NASA will usually divert the shuttle landing to Edwards Air Force Base (EAFB) in Southern California. But forecasting surface winds at EAFB is a challenge for the Spaceflight Meteorology Group (SMG) forecasters due to the complex terrain that surrounds EAFB, One particular phenomena identified by SMG is that makes it difficult to forecast the EAFB surface winds is called "wind cycling". This occurs when wind speeds and directions oscillate among towers near the EAFB runway leading to a challenging deorbit bum forecast for shuttle landings. The large-scale numerical weather prediction models cannot properly resolve the wind field due to their coarse horizontal resolutions, so a properly tuned high-resolution mesoscale model is needed. The Weather Research and Forecasting (WRF) model meets this requirement. The AMU assessed the different WRF model options to determine which configuration best predicted surface wind speed and direction at EAFB, To do so, the AMU compared the WRF model performance using two hot start initializations with the Advanced Research WRF and Non-hydrostatic Mesoscale Model dynamical cores and compared model performance while varying the physics options.

Watson, Leela R.↗

NASA NTRS2010

A Simple Technique for Creating Regional Composites of Sea Surface Temperature from MODIS for Use in Operational Mesoscale NWP

This paper describes a simple technique for creating regional, high-resolution, daytime and nighttime composites of sea surface temperature (SST) for use in operational numerical weather prediction (NWP). The composites are based on observations from NASA s Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua and Terra. The data used typically are available nearly in real time, are applicable anywhere on the globe, and are capable of roughly representing the diurnal cycle in SST. The composites resolution is much higher than that of many other standard SST products used for operational NWP, including the low- and high-resolution Real-Time Global (RTG) analyses. The difference in resolution is key because several studies have shown that highly resolved SSTs are important for driving the air sea interactions that shape patterns of static stability, vertical and horizontal wind shear, and divergence in the planetary boundary layer. The MODIS-based composites are compared to in situ observations from buoys and other platforms operated by the National Data Buoy Center (NDBC) off the coasts of New England, the mid-Atlantic, and Florida. Mean differences, mean absolute differences, and root-mean-square differences between the composites and the NDBC observations are all within tenths of a degree of those calculated between RTG analyses and the NDBC observations. This is true whether or not one accounts for the mean offset between the skin temperatures of the MODIS dataset and the bulk temperatures of the NDBC observations and RTG analyses. Near the coast, the MODIS-based composites tend to agree more with NDBC observations than do the RTG analyses. The opposite is true away from the coast. All of these differences in point-wise comparisons among the SST datasets are small compared to the 61.08C accuracy of the NDBC SST sensors. Because skin-temperature variations from land to water so strongly affect the development and life cycle of the sea breeze, this phenomenon was chosen for demonstrating the use of the MODIS-based composite in an NWP model. A simulated sea breeze in the vicinity of New York City and Long Island shows a small, net, but far from universal improvement when MODIS-based composites are used in place of RTG analyses. The timing of the sea breeze s arrival is more accurate at some stations, and the near-surface temperature, wind, and humidity within the breeze are more realistic.

Knievel, Jason C.↗

NASA NTRS2011

SPoRT's Participation in the GOES-R Proving Ground Activity

The next generation geostationary satellite, GOES-R, will carry two new instruments with unique atmospheric and surface observing capabilities, the Advanced Baseline Imager (ABI) and the Geostationary Lightning Mapper (GLM), to study short-term weather processes. The ABI will bring enhanced multispectral observing capabilities with frequent refresh rates for regional and full disk coverage to geostationary orbit to address many existing and new forecast challenges. The GLM will, for the first time, provide the continuous monitoring of total lightning flashes over a hemispherical region from space. NOAA established the GOES-R Proving Ground activity several years ago to demonstrate the new capabilities of these instruments and to prepare forecasters for their day one use. Proving Ground partners work closely with algorithm developers and the end user community to develop and transition proxy data sets representing GOES-R observing capabilities. This close collaboration helps to maximize refine algorithms leading to the delivery of a product that effectively address a forecast challenge. The NASA Short-term Prediction Research and Transition (SPoRT) program has been a participant in the NOAA GOES-R Proving Ground activity by developing and disseminating selected GOES-R proxy products to collaborating WFOs and National Centers. Established in 2002 to demonstrate the weather and forecasting application of real-time EOS measurements, the SPoRT program has grown to be an end-to-end research to operations activity focused on the use of advanced NASA modeling and data assimilation approaches, nowcasting techniques, and unique high-resolution multispectral data from EOS satellites to improve short-term weather forecasts on a regional and local scale. Participation in the Proving Ground activities extends SPoRT s activities and taps its experience and expertise in diagnostic weather analysis, short-term weather forecasting, and the transition of research and experimental data to operational decision support systems like NAWIPS, AWIPS, AWIPS2, and Google Earth. Recent SPoRT Proving Ground activities supporting the development and use of a pseudo GLM total lightning product and the transition of the AWG s Convective Initiation (CI) product, both of which were available in AWIPS and AWIPS II environments, by forecasters during the Hazardous Weather Testbed (HWT) Spring Experiment. SPoRT is also providing a suite of SEVIRI and MODIS RGB image products, and a high resolution composite SST product to several National Centers for use in there ongoing demonstration activities. Additionally, SPoRT has involved numerous WFOs in the evaluation of a GOES-MODIS hybrid product which brings ABI-like data sets in front of the forecaster for everyday use. An overview of this activity will be presented at the conference.

Jedlovec, Gary↗

NASA NTRS2012

A Robust Multi-Scale Modeling System for the Study of Cloud and Precipitation Processes

During the past decade, numerical weather and global non-hydrostatic models have started using more complex microphysical schemes originally developed for high resolution cloud resolving models (CRMs) with 1-2 km or less horizontal resolutions. These microphysical schemes affect the dynamic through the release of latent heat (buoyancy loading and pressure gradient) the radiation through the cloud coverage (vertical distribution of cloud species), and surface processes through rainfall (both amount and intensity). Recently, several major improvements of ice microphysical processes (or schemes) have been developed for cloud-resolving model (Goddard Cumulus Ensemble, GCE, model) and regional scale (Weather Research and Forecast, WRF) model. These improvements include an improved 3-ICE (cloud ice, snow and graupel) scheme (Lang et al. 2010); a 4-ICE (cloud ice, snow, graupel and hail) scheme and a spectral bin microphysics scheme and two different two-moment microphysics schemes. The performance of these schemes has been evaluated by using observational data from TRMM and other major field campaigns. In this talk, we will present the high-resolution (1 km) GeE and WRF model simulations and compared the simulated model results with observation from recent field campaigns [i.e., midlatitude continental spring season (MC3E; 2010), high latitude cold-season (C3VP, 2007; GCPEx, 2012), and tropical oceanic (TWP-ICE, 2006)].

Tao, Wei-Kuo↗

NASA NTRS2012

Evaluating the Contribution of NASA Remotely-Sensed Data Sets on a Convection-Allowing Forecast Model

The Short-term Prediction Research and Transition (SPoRT) Center is a collaborative partnership between NASA and operational forecasting partners, including a number of National Weather Service forecast offices. SPoRT provides real-time NASA products and capabilities to help its partners address specific operational forecast challenges. One challenge that forecasters face is using guidance from local and regional deterministic numerical models configured at convection-allowing resolution to help assess a variety of mesoscale/convective-scale phenomena such as sea-breezes, local wind circulations, and mesoscale convective weather potential on a given day. While guidance from convection-allowing models has proven valuable in many circumstances, the potential exists for model improvements by incorporating more representative land-water surface datasets, and by assimilating retrieved temperature and moisture profiles from hyper-spectral sounders. In order to help increase the accuracy of deterministic convection-allowing models, SPoRT produces real-time, 4-km CONUS forecasts using a configuration of the Weather Research and Forecasting (WRF) model (hereafter SPoRT-WRF) that includes unique NASA products and capabilities including 4-km resolution soil initialization data from the Land Information System (LIS), 2-km resolution SPoRT SST composites over oceans and large water bodies, high-resolution real-time Green Vegetation Fraction (GVF) composites derived from the Moderate-resolution Imaging Spectroradiometer (MODIS) instrument, and retrieved temperature and moisture profiles from the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI). NCAR's Model Evaluation Tools (MET) verification package is used to generate statistics of model performance compared to in situ observations and rainfall analyses for three months during the summer of 2012 (June-August). Detailed analyses of specific severe weather outbreaks during the summer will be presented to assess the potential added-value of the SPoRT datasets and data assimilation methodology compared to a WRF configuration without the unique datasets and data assimilation.

Zavodsky, Bradley T.↗

NASA NTRS2014

Range-Specific High-Resolution Mesoscale Model Setup: Data Assimilation

Mesoscale weather conditions can have an adverse effect on space launch, landing, and ground processing at the Eastern Range (ER) in Florida and Wallops Flight Facility (WFF) in Virginia. During summer, land-sea interactions across Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) lead to sea breeze front formation, which can spawn deep convection that can hinder operations and endanger personnel and resources. Many other weak locally driven low-level boundaries and their interactions with the sea breeze front and each other can also initiate deep convection in the KSC/CCAFS area. Some of these other boundaries include the Indian River breeze front, Banana River breeze front, outflows from previous convection, horizontal convective rolls, convergence lines from other inland bodies of water such as Lake Okeechobee, the trailing convergence line from convergence of sea breeze fronts due to the shape of Cape Canaveral, frictional convergence lines from the islands in the Bahamas, convergence lines from soil moisture differences, convergence lines from cloud shading, and others. All these subtle weak boundary interactions often make forecasting of operationally important weather very difficult at KSC/CCAFS during the convective season (May-Oct). These convective processes often build quickly, last a short time (60 minutes or less), and occur over small distances, all of which also poses a significant challenge to the local forecasters who are responsible for issuing weather advisories, watches, and warnings. Surface winds during the transition seasons of spring and fall pose the most difficulties for the forecasters at WFF. They also encounter problems forecasting convective activity and temperature during those seasons. Therefore, accurate mesoscale model forecasts are needed to aid in their decision making. Both the ER and WFF would benefit greatly from high-resolution mesoscale model output to better forecast a variety of unique weather phenomena. Global and national scale models cannot properly resolve important local-scale weather features at each location due to their horizontal resolutions being much too coarse. Therefore, a properly tuned model at a high resolution is needed to provide improved capability. This task is a multi-year effort in which the Applied Meteorology Unit (AMU) will tune the Weather Research and Forecasting (WRF) model individually for each range. The goal of the first year, the results of which are in this report, was to tune the WRF model based on the best model resolution and run time while using reasonable computing capabilities. To accomplish this, the ER and WFF supported the tasking of the AMU to perform a number of sensitivity tests in order to determine the best model configuration for operational use at each of the ranges to best predict winds, precipitation, and temperature (Watson 2013). This task is a continuation of that work and will provide a recommended local data assimilation (DA) and numerical forecast model design optimized for the ER and WFF to support space launch activities. The model will be optimized for local weather challenges at both ranges.

Global and national scale models↗

NASA NTRS2014

GRAIL Refinements to Lunar Seismic Structure

Gravity field measurements are perhaps the most numerous of the indirect observations relevant to the Moon's internal structure. Multiple recent missions have mapped the global lunar gravity field, each one improving upon the resolution of the last. The details of the Moon's deepest structure, including the parameters that define the lunar core, however, were still largely unaddressed by pre-GRAIL gravity measurements, which were not high enough resolution to resolve the tidal coefficients at a sufficient degree of accuracy. Current constraints on core size and state arise from other indirect measurements, including lunar laser ranging, magnetic induction studies, and analyses of elemental abundances in depth-derived mare basalts. These inferences vary widely, but when considered together with structure models derived from the seismic data gathered during the Apollo missions, a schematic of the lunar interior containing a partially molten deepest mantle layer overlying molten outer and solid inner core layers was obtained. Seismology provides the most direct constraints on the variables that govern the dynamic properties of the body. However, the GRAIL mission's high-resolution measurements of the lunar gravity field are being used to constrain the interior structure of the Moon using a "crust to core" approach. GRAIL's constraints on crustal thickness, mantle structure, core radius and stratification, and core state (solid vs. molten) therefore complement seismic investigations. This work focuses on expanding our knowledge of the Moon's internal structure using joint gravity and seismic analyses, which will improve constraints on the deep lunar mantle and core.

Weber, Renee C.↗

NASA NTRS2015

A High Performance Computing Approach to Tree Cover Delineation in 1-m NAIP Imagery Using a Probabilistic Learning Framework

Tree cover delineation is a useful instrument in deriving Above Ground Biomass (AGB) density estimates from Very High Resolution (VHR) airborne imagery data. Numerous algorithms have been designed to address this problem, but most of them do not scale to these datasets, which are of the order of terabytes. In this paper, we present a semi-automated probabilistic framework for the segmentation and classification of 1-m National Agriculture Imagery Program (NAIP) for tree-cover delineation for the whole of Continental United States, using a High Performance Computing Architecture. Classification is performed using a multi-layer Feedforward Backpropagation Neural Network and segmentation is performed using a Statistical Region Merging algorithm. The results from the classification and segmentation algorithms are then consolidated into a structured prediction framework using a discriminative undirected probabilistic graphical model based on Conditional Random Field, which helps in capturing the higher order contextual dependencies between neighboring pixels. Once the final probability maps are generated, the framework is updated and re-trained by relabeling misclassified image patches. This leads to a significant improvement in the true positive rates and reduction in false positive rates. The tree cover maps were generated for the whole state of California, spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles. The framework produced true positive rates of around 88% for fragmented forests and 74% for urban tree cover areas, with false positive rates lower than 2% for both landscapes. Comparative studies with the National Land Cover Data (NLCD) algorithm and the LiDAR canopy height model (CHM) showed the effectiveness of our framework for generating accurate high-resolution tree-cover maps.

Segments↗

NASA NTRS2016

Multi-Sensor Cloud and Aerosol Retrieval Simulator and Remote Sensing from Model Parameters : Aerosols - Part 2

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a simulated radiance product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers. This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled. In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model sub grid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to operational remote-sensing algorithms. Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (MOYD04). TheMOYD04 product is of course normally produced from MOYD021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a MOYD021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source. We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

aerosol retrieval↗

NASA NTRS2015

Spatiotemporal Prediction of Fine Particulate Matter Using High-Resolution Satellite Images in the Southeastern US 2003-2011

Numerous studies have demonstrated that fine particulate matter (PM(sub 2.5), particles smaller than 2.5 micrometers in aerodynamic diameter) is associated with adverse health outcomes. The use of ground monitoring stations of PM(sub 2.5) to assess personal exposure, however, induces measurement error. Land-use regression provides spatially resolved predictions but land-use terms do not vary temporally. Meanwhile, the advent of satellite-retrieved aerosol optical depth (AOD) products have made possible to predict the spatial and temporal patterns of PM(sub 2.5) exposures. In this paper, we used AOD data with other PM(sub 2.5) variables, such as meteorological variables, land-use regression, and spatial smoothing to predict daily concentrations of PM(sub 2.5) at a 1 sq km resolution of the Southeastern United States including the seven states of Georgia, North Carolina, South Carolina, Alabama, Tennessee, Mississippi, and Florida for the years from 2003 to 2011. We divided the study area into three regions and applied separate mixed-effect models to calibrate AOD using ground PM(sub 2.5) measurements and other spatiotemporal predictors. Using 10-fold cross-validation, we obtained out of sample R2 values of 0.77, 0.81, and 0.70 with the square root of the mean squared prediction errors of 2.89, 2.51, and 2.82 cu micrograms for regions 1, 2, and 3, respectively. The slopes of the relationships between predicted PM2.5 and held out measurements were approximately 1 indicating no bias between the observed and modeled PM(sub 2.5) concentrations. Predictions can be used in epidemiological studies investigating the effects of both acute and chronic exposures to PM(sub 2.5). Our model results will also extend the existing studies on PM(sub 2.5) which have mostly focused on urban areas because of the paucity of monitors in rural areas.

PM2.5↗

NASA NTRS2017

JIGSAW-GEO (1.0): Locally Orthogonal Staggered Unstructured Grid Generation for General Circulation Modelling on the Sphere

An algorithm for the generation of non-uniform, locally orthogonal staggered unstructured spheroidal grids is described. This technique is designed to generate very high-quality staggered VoronoiDelaunay meshes appropriate for general circulation modelling on the sphere, including applications to atmospheric simulation, ocean-modelling and numerical weather prediction. Using a recently developed Frontal-Delaunay refinement technique, a method for the construction of high-quality unstructured spheroidal Delaunay triangulations is introduced. A locally orthogonal polygonal grid, derived from the associated Voronoi diagram, is computed as the staggered dual. It is shown that use of the Frontal-Delaunay refinement technique allows for the generation of very high-quality unstructured triangulations, satisfying a priori bounds on element size and shape. Grid quality is further improved through the application of hill-climbing-type optimisation techniques. Overall, the algorithm is shown to produce grids with very high element quality and smooth grading characteristics, while imposing relatively low computational expense. A selection of uniform and non-uniform spheroidal grids appropriate for high-resolution, multi-scale general circulation modelling are presented. These grids are shown to satisfy the geometric constraints associated with contemporary unstructured C-grid-type finite-volume models, including the Model for Prediction Across Scales (MPAS-O). The use of user-defined mesh-spacing functions to generate smoothly graded, non-uniform grids for multi-resolution-type studies is discussed in detail.

geophysical fluid dynamics↗

NASA NTRSDate not supplied

LES-Based Analysis of Film Cooling in a High-Pressure Turbine Rotor Including Effects of Purge and Tip Flow

Accurate modeling of coolant airflows, which form protective films over turbine blades, is essential for designing fuel-efficient and environmentally sustainable gas turbine engines. Excessive coolant reduces thermal efficiency, while insufficient coolant leads to blade overheating and causes damage. Therefore, precise prediction of flow field interactions with cooling air is critical for optimizing turbine performance. This study numerically investigates the cooling effectiveness of purge and film cooling flows within a high-pressure turbine (HPT) rotor using Large Eddy Simulation (LES). The study utilizes NASA Glenn Research Center’s Glenn-HT solver. The simulation models ethe conditions of the Penn State University START rotating rig. A high-fidelity structured mesh comprising up to 800 million cells is employed to resolve high-Reynolds number flow (Re ≈ 350,000) and to capture intricate secondary flow structures, including tip leakage and purge-induced vortices. Film cooling effectiveness computations are highly sensitive to boundary conditions at the cooling holes and to grid resolution. Even with well-resolved grids and included plena, strong mixing challenges traditional eddy viscosity models. To address this, a simplified configuration is simulated: a truncated row of shaped holes on the suction side near the leading edge and a row on the pressure side, both fed from internal plena while the purge slot and tip clearance are also modeled. Two isothermal LES cases are conducted at two distinct wall temperatures, which yield the adiabatic wall temperature and the heat transfer coefficient. The definition and means of computation of the effectiveness is discussed in this paper. The simulations reveal detailed three-dimensional unsteady flow features, including coherent vortical structures and secondary flows originating from the purge cavity. Film cooling effectiveness and Nusselt number distributions are presented for both the blade surface and tip, highlighting regions of elevated heat transfer and complex thermal behavior. These findings underscore the importance of high-resolution LES and realistic boundary conditions in capturing the dynamics of purge and film cooling, offering valuable insights for improving turbine blade design and thermal management strategies.

Secondary Flows↗