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NASA NTRS2016

A Satellite Data-Driven, Client-Server Decision Support Application for Agricultural Water Resources Management

Water cycle extremes such as droughts and floods present a challenge for water managers and for policy makers responsible for the administration of water supplies in agricultural regions. In addition to the inherent uncertainties associated with forecasting extreme weather events, water planners need to anticipate water demands and water user behavior in a typical circumstances. This requires the use decision support systems capable of simulating agricultural water demand with the latest available data. Unfortunately, managers from local and regional agencies often use different datasets of variable quality, which complicates coordinated action. In previous work we have demonstrated novel methodologies to use satellite-based observational technologies, in conjunction with hydro-economic models and state of the art data assimilation methods, to enable robust regional assessment and prediction of drought impacts on agricultural production, water resources, and land allocation. These methods create an opportunity for new, cost-effective analysis tools to support policy and decision-making over large spatial extents. The methods can be driven with information from existing satellite-derived operational products, such as the Satellite Irrigation Management Support system (SIMS) operational over California, the Cropland Data Layer (CDL), and using a modified light-use efficiency algorithm to retrieve crop yield from the synergistic use of MODIS and Landsat imagery. Here we present an integration of this modeling framework in a client-server architecture based on the Hydra platform. Assimilation and processing of resource intensive remote sensing data, as well as hydrologic and other ancillary information occur on the server side. This information is processed and summarized as attributes in water demand nodes that are part of a vector description of the water distribution network. With this architecture, our decision support system becomes a light weight 'app' that connects to the server to retrieve the latest information regarding water demands, land use, yields and hydrologic information required to run different management scenarios. Furthermore, this architecture ensures all agencies and teams involved in water management use the same, up-to-date information in their simulations.

Agricultural↗

NASA NTRS1995

Measurement of the spectral absorption of liquid water in melting snow with an imaging spectrometer

Melting of the snowpack is a critical parameter that drives aspects of the hydrology in regions of the earth where snow accumulates seasonally. New techniques for measurement of snow melt over regional scales offer the potential to improve monitoring and modeling of snow-driven hydrological processes. We present the results of measuring the spectral absorption of liquid water in a melting snowpack with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). AVIRIS data were acquired over Mammoth Mountain, in east central California on 21 May 1994 at 18:35 UTC. The air temperature at 2926 m on Mammoth Mountain at site A was measured at 15-minute intervals during the day preceding the AVIRIS data acquisition. At this elevation, the air temperature did not drop below freezing the night of May 20 and had risen to 6 degrees Celsius by the time of the overflight on May 21. These temperature conditions support the presence of melting snow at the surface as the AVIRIS data were acquired.

Green, Robert O.↗

NASA NTRS2002

A Solar Model with g-Modes

Good evidence is assembled showing that the Suit's core arid surface vary on time scales from a month to a decade arid that a number of scales are similar. The most plausible source for numerous long time scales and periodicities is long-lived global oscillations. This suggests g-modes (oscillations restored mainly by buoyancy) because they particularly affect the core and base of the convective envelope, which then indirectly modulates the surface. Also, standing g-modes have rotational properties that match many observed periodicities. But the standard solar model (SSM) has a static core and excites few if any g-modes. making new interior structures worth exploring. The model outlined here assumes two well mixed shells near 0.18 and 0.68 R, (13 = solar radius) where sound speed data shows sharp deviations from the SSM. Mixing is sustained by flows driven by the oscillations. The shells form a cavity that excludes g-modes from their main damping region below 0.1 R, assisting their net excitation and increasing their oscillation periods by at least a factor of two and probably much more. In terms of the solar luminosity L, the modes transport up through the cavity a power approx. 0.004 L as a lower limit and 0.11 L as all upper limit. The modes dissipate energy in the outer shell and cool the inner shell, asymmetrically in each case, and this stimulates occasional convective events whose response time is typically 0.8 years longer near the inner shell. Such events cool the core and reduce neutrino flux while heating the envelope and increasing solar activity. This gives a physical basis for a well mixed Sun with low neutrino flux and basis for the observed anticorrelation and lag of neutrino behind surface activity.

Wolff, Charles L.↗

NASA NTRS2015

Relative Contributions of Mean-State Shifts and ENSO-Driven Variability to Precipitation Changes in a Warming Climate

El Niño-Southern Oscillation (ENSO) is an important driver of regional hydroclimate variability through far-reaching teleconnections. This study uses simulations performed with coupled general circulation models (CGCMs) to investigate how regional precipitation in the twenty-first century may be affected by changes in both ENSO-driven precipitation variability and slowly evolving mean rainfall. First, a dominant, time-invariant pattern of canonical ENSO variability (cENSO) is identified in observed SST data. Next, the fidelity with which 33 state-of-the-art CGCMs represent the spatial structure and temporal variability of this pattern (as well as its associated precipitation responses) is evaluated in simulations of twentieth-century climate change. Possible changes in both the temporal variability of this pattern and its associated precipitation teleconnections are investigated in twenty-first-century climate projections. Models with better representation of the observed structure of the cENSO pattern produce winter rainfall teleconnection patterns that are in better accord with twentieth-century observations and more stationary during the twenty-first century. Finally, the model-predicted twenty-first-century rainfall response to cENSO is decomposed into the sum of three terms: 1) the twenty-first-century change in the mean state of precipitation, 2) the historical precipitation response to the cENSO pattern, and 3) a future enhancement in the rainfall response to cENSO, which amplifies rainfall extremes. By examining the three terms jointly, this conceptual framework allows the identification of regions likely to experience future rainfall anomalies that are without precedent in the current climate.

Simulation↗

NASA NTRS1976

Test data report: Low speed wind tunnel tests of a full scale, fixed geometry inlet, with engine, at high angles of attack

A full scale inlet test was to be done in the NASA-ARC 40' X 80' WT to demonstrate satisfactory inlet performance at high angles of attack. The inlet was designed to match a Hamilton-Standard 55 inch, variable pitch fan, driven by a Lycoming T55-L-11A gas generator. The test was installed in the wind tunnel on two separate occasions, but mechanical failures in the fan drive gear box early in each period terminated testing. A detailed description is included of the Model, installation, instrumentation and data reduction procedures.

Shain, W. M.↗

NASA NTRS2016

Spatial and Temporal Uncertainty of Crop Yield Aggregations

The aggregation of simulated gridded crop yields to national or regional scale requires information on temporal and spatial patterns of crop-specific harvested areas. This analysis estimates the uncertainty of simulated gridded yield time series related to the aggregation with four different harvested area data sets. We compare aggregated yield time series from the Global Gridded Crop Model Inter-comparison project for four crop types from 14 models at global, national, and regional scale to determine aggregation-driven differences in mean yields and temporal patterns as measures of uncertainty. The quantity and spatial patterns of harvested areas differ for individual crops among the four datasets applied for the aggregation. Also simulated spatial yield patterns differ among the 14 models. These differences in harvested areas and simulated yield patterns lead to differences in aggregated productivity estimates, both in mean yield and in the temporal dynamics. Among the four investigated crops, wheat yield (17% relative difference) is most affected by the uncertainty introduced by the aggregation at the global scale. The correlation of temporal patterns of global aggregated yield time series can be as low as for soybean (r = 0.28).For the majority of countries, mean relative differences of nationally aggregated yields account for10% or less. The spatial and temporal difference can be substantial higher for individual countries. Of the top-10 crop producers, aggregated national multi-annual mean relative difference of yields can be up to 67% (maize, South Africa), 43% (wheat, Pakistan), 51% (rice, Japan), and 427% (soybean, Bolivia).Correlations of differently aggregated yield time series can be as low as r = 0.56 (maize, India), r = 0.05∗Corresponding (wheat, Russia), r = 0.13 (rice, Vietnam), and r = −0.01 (soybean, Uruguay). The aggregation to sub-national scale in comparison to country scale shows that spatial uncertainties can cancel out in countries with large harvested areas per crop type. We conclude that the aggregation uncertainty can be substantial for crop productivity and production estimations in the context of food security, impact assessment, and model evaluation exercises.

Aggregation uncertainty↗

NASA NTRS2001

Properties of the Water Column and Bottom Derived from AVIRIS Data

Using AVIRIS data as an example, we show in this study that the optical properties of the water column and bottom of a large, shallow area can be adequately retrieved using a model-driven optimization technique. The simultaneously derived properties include bottom depth, bottom albedo, and water absorption and backscattering coefficients, which in turn could be used to derive concentrations of chlorophyll, dissolved organic matter, and suspended sediments. The derived bottom depths were compared with a bathymetry chart and a boat survey and were found to agree very well. Also, the derived bottom-albedo image shows clear spatial patterns, with end members consistent with sand and seagrass. The image of absorption and backscattering coefficients indicates that the water is quite horizontally mixed. These results suggest that the model and approach used work very well for the retrieval of sub-surface properties of shallow-water environments even for rather turbid environments like Tampa Bay, Florida.

Lee, Zhong-Ping↗

NASA NTRS2010

CFD Models of a Serpentine Inlet, Fan, and Nozzle

Several computational fluid dynamics (CFD) codes were used to analyze the Versatile Integrated Inlet Propulsion Aerodynamics Rig (VIIPAR) located at NASA Glenn Research Center. The rig consists of a serpentine inlet, a rake assembly, inlet guide vanes, a 12-in. diameter tip-turbine driven fan stage, exit rakes or probes, and an exhaust nozzle with a translating centerbody. The analyses were done to develop computational capabilities for modeling inlet/fan interaction and to help interpret experimental data. Three-dimensional Reynolds averaged Navier-Stokes (RANS) calculations of the fan stage were used to predict the operating line of the stage, the effects of leakage from the turbine stream, and the effects of inlet guide vane (IGV) setting angle. Coupled axisymmetric calculations of a bellmouth, fan, and nozzle were used to develop techniques for coupling codes together and to investigate possible effects of the nozzle on the fan. RANS calculations of the serpentine inlet were coupled to Euler calculations of the fan to investigate the complete inlet/fan system. Computed wall static pressures along the inlet centerline agreed reasonably well with experimental data but computed total pressures at the aerodynamic interface plane (AIP) showed significant differences from the data. Inlet distortion was shown to reduce the fan corrected flow and pressure ratio, and was not completely eliminated by passage through the fan

Chima, R. V.↗

NASA NTRS2014

A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-Cloud Aerosols Using CALIOP and MODIS Data

This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It addresses the overlap of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure while also accounting for subgrid-scale variations of aerosols. The method is computationally efficient because of its use of grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table based on radiative transfer calculations. We verify that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous (approximately 1:30PM local time) shortwave DRE of above cloud aerosol (ACA) that generally agrees with more rigorous pixel-level computation within 4 percent. We also estimate the impact of potential CALIOP aerosol optical depth (AOD) retrieval bias of ACA on DRE. We find that the regional and seasonal mean instantaneous DRE of ACA over southeast Atlantic Ocean would increase, from the original value of 6.4 W m(-2) based on operational CALIOP AOD to 9.6 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 1.5 (Meyer et al., 2013) and further to 30.9 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 5 as suggested in (Jethva et al., 2014). In contrast, the instantaneous ACA radiative forcing efficiency (RFE) remains relatively invariant in all cases at about 53 W m(-2) AOD(-1), suggesting a near linear relation between the instantaneous RFE and AOD. We also compute the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global oceans based on 4 years of CALIOP and MODIS data. We find that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds. While we demonstrate our method using CALIOP and MODIS data, it can also be extended to other satellite data sets, as well as climate model outputs.

CALIOP and MODIS↗

NASA NTRS2015

Simulations of Cloud-Radiation Interaction Using Large-Scale Forcing Derived from the CINDY/DYNAMO Northern Sounding Array

The recently completed CINDY/DYNAMO field campaign observed two Madden-Julian oscillation (MJO) events in the equatorial Indian Ocean from October to December 2011. Prior work has indicated that the moist static energy anomalies in these events grew and were sustained to a significant extent by radiative feedbacks. We present here a study of radiative fluxes and clouds in a set of cloud-resolving simulations of these MJO events. The simulations are driven by the large-scale forcing data set derived from the DYNAMO northern sounding array observations, and carried out in a doubly periodic domain using the Weather Research and Forecasting (WRF) model. Simulated cloud properties and radiative fluxes are compared to those derived from the S-PolKa radar and satellite observations. To accommodate the uncertainty in simulated cloud microphysics, a number of single-moment (1M) and double-moment (2M) microphysical schemes in the WRF model are tested. The 1M schemes tend to underestimate radiative flux anomalies in the active phases of the MJO events, while the 2M schemes perform better, but can overestimate radiative flux anomalies. All the tested microphysics schemes exhibit biases in the shapes of the histograms of radiative fluxes and radar reflectivity. Histograms of radiative fluxes and brightness temperature indicate that radiative biases are not evenly distributed; the most significant bias occurs in rainy areas with OLR less than 150 W/ cu sq in the 2M schemes. Analysis of simulated radar reflectivities indicates that this radiative flux uncertainty is closely related to the simulated stratiform cloud coverage. Single-moment schemes underestimate stratiform cloudiness by a factor of 2, whereas 2M schemes simulate much more stratiform cloud.

Indian Ocean↗

NASA NTRS2019

Numerical Investigation and Optimization of a Flushwall Injector for Scramjet Applications at Hypervelocity Flow Conditions

An investigation utilizing Reynolds-averaged simulations (RAS) was performed in order to find optimal designs for an interdigitated flushwall injector suitable for scramjet applications at hypervelocity conditions. The flight Mach number, duct height, spanwise width, and injection angle were the design variables selected to maximize two objective functions: the thrust potential and combustion efficiency. A Latin hypercube sampling design-of-experiments method was used to select design points for RAS. A methodology was developed that automated building geometries and generating grids for each design. The ensuing RAS analysis generated the performance database from which the two objective functions of interest were computed using a one-dimensional performance utility. The data were fitted using four surrogate models: an artificial neural network (ANN) model, a cubic polynomial, a quadratic polynomial, and a Kriging model. Variance-based decomposition showed that both objective functions were primarily driven by changes in the duct height. Multiobjective design optimization was performed for all four surrogate models via a genetic algorithm method. Optimal solutions were obtained at the upper and lower bounds of the flight Mach number range. The Kriging model obtained an optimal solution set that predicted high values for both objective functions. Additionally, three challenge points were selected to assess the designs on the Pareto fronts. Further sampling among the designs of the Pareto fronts are required in order to lower the errors and perform more accurate surrogate-based optimization. sed optimization.

Shenoy, Rajiv R.↗

NASA NTRS2019

Numerical Investigation and Optimization of a Flushwall Injector for Scramjet Applications at Hypervelocity Flow Conditions

An investigation utilizing Reynolds-averaged simulations (RAS) was performed in order to demonstrate the use of design and analysis of computer experiments (DACE) methods in Sandia’s DAKOTA software package for surrogate modeling and optimization. These methods were applied to a flow- path fueled with an interdigitated flushwall injector suitable for scramjet applications at hyper- velocity conditions and ascending along a constant dynamic pressure flight trajectory. The flight Mach number, duct height, spanwise width, and injection angle were the design variables selected to maximize two objective functions: the thrust potential and combustion efficiency. Because the RAS of this case are computationally expensive, surrogate models are used for optimization. To build a surrogate model a RAS database is created. The sequence of the design variables comprising the database were generated using a Latin hypercube sampling (LHS) method. A methodology was also developed to automatically build geometries and generate structured grids for each design point. The ensuing RAS analysis generated the simulation database from which the two objective functions were computed using a one-dimensionalization (1D) of the three-dimensional simulation data. The data were fitted using four surrogate models: an artificial neural network (ANN), a cubic polynomial, a quadratic polynomial, and a Kriging model. Variance-based decomposition showed that both objective functions were primarily driven by changes in the duct height. Multiobjective design optimization was performed for all four surrogate models via a genetic algorithm method. Optimal solutions were obtained at the upper and lower bounds of the flight Mach number range. The Kriging model predicted an optimal solution set that exhibited high values for both objective functions. Additionally, three challenge points were selected to assess the designs on the Pareto fronts. Further sampling among the designs of the Pareto fronts may be required to lower the surrogate model errors and perform more accurate surrogate-model-based optimization.

Shenoy, Rajiv R.↗

NASA NTRS2015

Simulated Transmission of the Dengue Virus Across the US-Mexico Border Using Remotely Sensed and Ground Based Weather Data

Incidence of dengue fever, caused by a mosquito transmitted virus, have increased in the Americas during recent decades. In the US, local transmission has been reported in southern Texas and Florida. However, despite its close proximity to dengue endemic areas in Mexico and the presence of a primary mosquito vector, there are no reports of local transmission in Arizona. Many studies have demonstrated that weather influences dengue virus transmission by regulating vector development rates, vector habitat availability, and the duration of the virus extrinsic incubation period (EIP). The EIP, the period between mosquito infection and the ability for it to retransmit the virus, is especially important given its high sensitivity to temperature and the short lifespan of mosquitoes. Other studies, however, have suggested that human related factors such as socioeconomic status and herd immunity may explain much of the disparity in dengue incidence in the US‐Mexico border region. Using a meteorologically driven model of vector population dynamics and virus transmission we compare simulations of dengue fever cases in southern Arizona and northern Mexico. A Monte Carlo approach is employed to select parameter values by evaluating simulations in Hermosillo Mexico with reported dengue fever case data. Simulations that replicate the case data best are retained and rerun using remotely sensed climate data from other Arizona and Mexico locations to determine the relative influence of weather on virus transmission. Although human and environmental factors undoubtedly influence dengue transmission in the US‐Mexico border regions, weather is a major facilitator of the transmission process.

Dengue↗

NASA NTRS2025

Integrating the Interconnections Between Groundwater and Land Surface Processes Through the Coupled NASA Land Information System and ParFlow Environment

Understanding the interactions between the atmosphere, the land, and the subsurface is fundamental to hydrology and is critical for a better assessment of the impacts of climate change and human management on hydrological systems. However, many land surface models simplify the subsurface hydrology and thereby these interactions. In this study, we couple the land surface model Noah-MP included in the NASA Land Information System (LIS) with the integrated hydrologic model ParFlow (ParFlow-LIS) using the Earth System Modeling Framework (ESMF) and the National United Operational Prediction Capability (NUOPC). This coupling improves the simulation of water and energy cycle processes by adding the three-dimensional variably saturated and heterogeneous flow in the subsurface using sophisticated and nonlinear physics-based equations as well as the advances in satellite remote sensing-based data assimilation of the land surface, thereby benefiting the integrated hydrologic modeling and data assimilation community. We use the High Plains aquifer, located in the central United States, as a testbed to evaluate the coupled ParFlow-LIS system. The new ParFlow-LIS system accounts for the effects of topographically driven flows on the land surface, producing more fine-scale patterns of land surface states and fluxes than standalone LIS. In addition, ParFlow-LIS enables the consideration of the effect of subsurface water storage on evapotranspiration. This is particularly important in areas and times with dry soils, such as during drought conditions or in the presence of a cone of depression due to pumping.

land surface modeling↗

NASA NTRS1999

Study of Magnetic Damping Effect on Convection and Solidification Under G-Jitter Conditions

As shown by NASA resources dedicated to measuring residual gravity (SAMS and OARE systems), g-jitter is a critical issue affecting space experiments on solidification processing of materials. This study aims to provide, through extensive numerical simulations and ground based experiments, an assessment of the use of magnetic fields in combination with microgravity to reduce the g-jitter induced convective flows in space processing systems. We have so far completed asymptotic analyses based on the analytical solutions for g-jitter driven flow and magnetic field damping effects for a simple one-dimensional parallel plate configuration, and developed both 2-D and 3-D numerical models for g-jitter driven flows in simple solidification systems with and without presence of an applied magnetic field. Numerical models have been checked with the analytical solutions and have been applied to simulate the convective flows and mass transfer using both synthetic g-jitter functions and the g-jitter data taken from space flight. Some useful findings have been obtained from the analyses and the modeling results. Some key points may be summarized as follows: (1) the amplitude of the oscillating velocity decreases at a rate inversely proportional to the g-jitter frequency and with an increase in the applied magnetic field; (2) the induced flow approximately oscillates at the same frequency as the affecting g-jitter, but out of a phase angle; (3) the phase angle is a complicated function of geometry, applied magnetic field, temperature gradient and frequency; (4) g-jitter driven flows exhibit a complex fluid flow pattern evolving in time; (5) the damping effect is more effective for low frequency flows; and (6) the applied magnetic field helps to reduce the variation of solutal distribution along the solid-liquid interface. Work in progress includes numerical simulations and ground-based measurements. Both 2-D and 3-D numerical simulations are being continued to obtain further information on g-jitter driven flows and magnetic field effects. A physical model for ground-based measurements is completed and some measurements of the oscillating convection are being taken on the physical model. The comparison of the measurements with numerical simulations is in progress. Additional work planned in the project will also involve extending the 2-D numerical model to include the solidification phenomena with the presence of both g-jitter and magnetic fields.

Li, Ben Q.↗

NASA NTRS2020

A Coupled Analysis of Atmospheric Mass Loss and Tidal Evolution in XUV Irradiated Exoplanets: The TRAPPIST-1 Case Study

Exoplanets residing close to their stars can experience evolution of both their physical structures and their orbits due to the influence of their host stars. In this work, we present a coupled analysis of dynamical tidal dissipation and atmospheric mass loss for exoplanets in X-ray and ultraviolet (XUV) irradiated environments. As our primary application, we use this model to study the TRAPPIST-1 system and place constraints on the interior structure and orbital evolution of the planets. We start by reporting on an ultraviolet continuum flux measurement (centered around ∼1900 Å) for the star TRAPPIST-1, based on 300 ks of Neil Gehrels Swift Observatory data, and which enables an estimate of the XUV-driven thermal escape arising from XUV photodissociation for each planet. We find that the X-ray flaring luminosity, measured from our X-ray detections, of TRAPPIST-1 is 5.6 × 10(exp −4) L(*), while the full flux including non-flaring periods is 6.1 × 10(exp −5) L*, when L(*) is TRAPPIST-1ʼs bolometric luminosity. We then construct a model that includes both atmospheric mass loss and tidal evolution and requires the planets to attain their present-day orbital elements during this coupled evolution. We use this model to constrain the ratio Q' = 3Q/2k2 for each planet. Finally, we use additional numerical models implemented with the Virtual Planet Simulator VPLanet to study ocean retention for these planets using our derived system parameters.

Juliette Becker↗

NASA NTRSDate not supplied

Regional and Seasonal Trends in Tropical Ozone from SHADOZ Profiles: Reference for Models and Satellite Products

Understanding lowermost stratosphere (LMS) ozone variability is an important topic in the trends and climate assessment communities because of feedbacks among changing temperature, dynamics, water vapor and ozone. LMS evaluations are usually based on satellite observations. Free tropospheric (FT) ozone assessments typically rely on profiles from commercial aircraft. Ozonesonde measurements constitute an independent dataset encompassing both LMS and FT. We used Southern Hemisphere Additional Ozonesondes (SHADOZ) data from 1998-2019 in the GSFC Multiple Linear Regression (MLR) model to analyze monthly mean FT and LMS ozone across five well-distributed tropical sites, three based on combination of nearby individual stations (Figure 1). Our findings: (1) both FT (defined as 5-15 km) and LMS (15-20 km) ozone trends exhibit marked regional and seasonal variability. (2) Stations with the largest FT ozone increases, in the equatorial Americas and western Pacific/east Indian Ocean, show these trends most strongly in February-May when there is convectively-driven wave activity. (3) LMS ozone losses are greatest in the 2nd half of the year (solid lines in Figure 2) when the losses are correlated with an increase in tropopause height (TH) as derived from SHADOZ radiosonde data. ( 4) When the upper FT and LMS are defined by tropopause-relative coordinates, the LMS ozone trend calculated by MLR becomes insignificant, as shown in the dashed lines in Figure 2. Thus, the 20-year decline in tropical LMS ozone reported in recent satellite- and model-based studies does not point to a chemical loss but is rather a signature of a tropopause that has been perturbed by a changing climate. Output based on our regional and monthly averaged FT and LMS ozone trends will be available as a reference for satellite- and model-based analyses.

Free Tropospheric (FT) ozone assessments↗

NASA NTRS1984

Scaling and modeling of three-dimensional, end-wall, turbulent boundary layers

The method of matched asymptotic expansion was employed to identify the various subregions in three dimensional, turbomachinery end wall turbulent boundary layers, and to determine the proper scaling of these regions. The two parts of the b.l. investigated are the 3D pressure driven part over the endwall, and the 3D part located at the blade/end wall juncture. Models are proposed for the 3d law of the wall and law of the wake. These models and the data of van den Berg and Elsenaar and of Mueller are compared and show good agreement between models and experiments.

Goldberg, U. C.↗