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NASA NTRS1984

Application of VISSR Atmospheric Sounder (VAS) data in weather analysis

A technique which analyzes irregularly spaced satellite data is described. An experiment with rawinsonde and VISSR Atmospheric Sounder (VAS) radiance measurements collected on March 6-7, 1982 is conducted to reveal the applicability of the technique. The rawinsonde data are analyzed on a 16 x 12 grid using the two pass analysis scheme of Barnes (1973). A scheme similar to the Barnes (1973) procedure is employed to produce gridded analysis of VAS data over a 200 x 15000 km region in central part of the U.S. The use of a correction pass on the initial gridded field is described; the technique is extremely effective on uniformly spaced observations. The incorporation of the limited fine mesh model to the scheme to analyze data in sparse and cloudy regions is examined. A comparison of rawinsonde data with VAS data is provided. The technique proves effective for studying cloudy and sparse areas with VAS data and produces a four-dimensional data set with significant mesoscale structure.

Jedlovec, G. J.↗

NASA NTRS1981

An objective isobaric/isentropic technique for upper air analysis

An objective meteorological analysis technique is presented whereby both horizontal and vertical upper air analyses are performed. The process used to interpolate grid-point values from the upper-air station data is the same as for grid points on both an isobaric surface and a vertical cross-sectional plane. The nearby data surrounding each grid point are used in the interpolation by means of an anisotropic weighting scheme, which is described. The interpolation for a grid-point potential temperature is performed isobarically; whereas wind, mixing-ratio, and pressure height values are interpolated from data that lie on the isentropic surface that passes through the grid point. Two versions (A and B) of the technique are evaluated by qualitatively comparing computer analyses with subjective handdrawn analyses. The objective products of version A generally have fair correspondence with the subjective analyses and with the station data, and depicted the structure of the upper fronts, tropopauses, and jet streams fairly well. The version B objective products correspond more closely to the subjective analyses, and show the same strong gradients across the upper front with only minor smoothing.

Mancuso, R. L.↗

NASA NTRS1990

On modelling the pressure-strain correlations in wall bounded flows

Turbulence models for the pressure-strain term of the Reynolds-stress equations in the vicinity of a moving wall are evaluated for a high Reynolds number flow using decaying grid turbulence as a model problem. The data of Thomas and Hancock are used as a base for evaluating the different turbulence models. In particular, the Rotta model for return-to-isotropy is evaluated both in its inclusion into the Reynolds-stress equation model and in comparison to a nonlinear model advanced by Sarkar and Speziale. Further, models for the wall correction to the transfer term advanced by Launder et al., Shir, and Shih and Lumley are compared. Initial data using the decaying grid turbulence experiment as a base suggests that the coefficients proposed for these models are high perhaps by as much as an order of magnitude. The Shih and Lumley model which satisfies realizability constraints, in particular, seems to hold promise in adequately modeling the Reynolds stress components of this flow. Extensions of this work are to include testing the homogeneous transfer model by Shih and Lumley and the testing of the wall transfer models using their proposed coefficients and the coefficients chosen from this work in a flow with mean shear component.

Peltier, L. J.↗

NASA NTRS2011

A Real-Time MODIS Vegetation Composite for Land Surface Models and Short-Term Forecasting

The NASA Short-term Prediction Research and Transition (SPoRT) Center is producing real-time, 1- km resolution Normalized Difference Vegetation Index (NDVI) gridded composites over a Continental U.S. domain. These composites are updated daily based on swath data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the polar orbiting NASA Aqua and Terra satellites, with a product time lag of about one day. A simple time-weighting algorithm is applied to the NDVI swath data that queries the previous 20 days of data to ensure a continuous grid of data populated at all pixels. The daily composites exhibited good continuity both spatially and temporally during June and July 2010. The composites also nicely depicted high greenness anomalies that resulted from significant rainfall over southwestern Texas, Mexico, and New Mexico during July due to early-season tropical cyclone activity. The SPoRT Center is in the process of computing greenness vegetation fraction (GVF) composites from the MODIS NDVI data at the same spatial and temporal resolution for use in the NASA Land Information System (LIS). The new daily GVF dataset would replace the monthly climatological GVF database (based on Advanced Very High Resolution Radiometer [AVHRR] observations from 1992-93) currently available to the Noah land surface model (LSM) in both LIS and the public version of the Weather Research and Forecasting (WRF) model. The much higher spatial resolution (1 km versus 0.15 degree) and daily updates based on real-time satellite observations have the capability to greatly improve the simulation of the surface energy budget in the Noah LSM within LIS and WRF. Once code is developed in LIS to incorporate the daily updated GVFs, the SPoRT Center will conduct simulation sensitivity experiments to quantify the impacts and improvements realized by the MODIS real-time GVF data. This presentation will describe the methodology used to develop the 1-km MODIS NDVI composites and show sample output from summer 2010, compare the MODIS GVF data to the AVHRR monthly climatology, and illustrate the sensitivity of the Noah LSM within LIS and/or the coupled LIS/WRF system to the new MODIS GVF dataset.

Case, Jonathan L.↗

NASA NTRS2012

Projections of Declining Surface-Water Availability for the Southwestern United States

16 of the CMIP5 models had all the data needed for this work for at least one simulation that was continuous from 1950 to 2040. Details of the models analyzed here are provided in Table S1. The model data analyzed here are available at http://strega.ldeo.columbia.edu:81/expert/home/.naomi/.AR5/.v2/.historical:rcp85/.mmm16/ a. Assessing the climatology of the models Despite increases in horizontal resolution of many models compared to their CMIP3 counterparts none of these models can adequately resolve the topography of the south west United States, such as the Sierra Nevada and Rocky Mountains and the associated orographic precipitation. This requires that caution be used when interpreting the results presented here. To assess the ability of the models to simulate the current hydroclimate, in Figure S1 we show the observed (from the Global Precipitation Climatology Centre gridded rain gauge data, (1)) monthly climatology of precipitation and the same for all the models and the multimodel mean for the California-Nevada, Colorado headwaters and Texas regions. The GPCC data uses rain gauges only and interpolates to regular grids of which we used the 1◦ by 1◦ one. Details of the data set can be found in (2). While the models apparently overestimate precipitation in California and Nevada the seasonal cycle with wet winters and dry summers is very well represented. It is also possible that the rain gauge observations are biased low by inadequately sampling the higher mountain regions. How ever the models might also be expected to underestimate orographic precipitation due to inadequate horizontal resolution. The 25 models are also too wet in the Colorado headwaters region but correctly represent the quite even distribution though the year. The bimodal distribution of precipitation in Texas, with peaks in May and September, and the absolute amounts, are well modeled but with the September peak too weak. The positive precipitation bias translates into a positive runoff bias for the Colorado headwaters as also shown in Figure S1. Here the observed runoff values are taken from simulations of the Variable Infiltration Capacity (VIC) land surface-hydrology model (3) forced by observed meteorology (5) that were conducted as part of the North American Land Data Assimilation System project phase 2 ( (NLDAS-2), http://www.emc.ncep.noaa.gov/mmb/nldas/. Runoff for California-Nevada is better simulated but there is a positive bias over Texas despite no strong precipitation bias. To check whether regional climate models better simulate P and runoff in these regions we analyzed the historical simulation with the Regional Climate Model version 3 driven by the National Centers for Environmental Prediction-Department of Energy Reanalysis 2 available from the North American Regional Climate Change Assessment Program (http://www.narccap.ucar.edu). This model configuration retained these biases in P and runoff although they were reduced in amplitude. Given these varying biases we plot P and P − E changes in actual values but apply the simplest bias correction possible to the runoff and soil moisture values and show the modeled changes in terms of percentages of the 20th Century model climatologies. A thorough assessment of the simulation of North American climate in CMIP5 models is conducted in Sheffield at al. (North American Climate in CMIP5 Experiments. Part I: Evaluation of 20th Century Continental and Regional Climatology, manuscript submit ted to J. Climate, available at http://www.climate.noaa.gov/index.jsp?pg=./cpo pa/ mapp/cmip5 publications.html). Sheffield et al. analyze the climatology of precipitation, surface air temperature, low level winds, moisture fluxes, runoff etc. and conclude that the main features of the hydrological cycle, including characteristics of the atmospheric moisture balance and its seasonality, are captured in the CMP5 models subject to biases in total precipitation amounts. We chose to use all available models instead of selecting some and rejecting others based on an assessment of model realism. This is in accord with the suggestions of Mote et al. for CMIP3 (4) but future work needs to revisit this matter for the case of the CMIP5 ensemble.

Seager, Richard↗

NASA NTRS1990

Statistical prediction of satellite magnetic anomalies

Computationally rapid statistical procedures are presented for satellite altitude normalizations and the gridding of magnetic anomaly data, as an alternative to the more commonly used but computationally expensive equivalent-source inversion procedures. The statistical predictions of Magsat observations over South America have demonstrated the great computational advantages of collocation over equivalent source inversion in gridding magnetic anomally data; in general, three-dimensional collocation is an efficient and cost-effective approach for obtaining altitude-normalized anomally grids from orbital or arbitrarily distributed data.

Goyal, H. K.↗

NASA NTRSDate not supplied

FUN3D Analyses of the 5th AIAA Propulsion Aerodynamics Workshop Inlet Test Case

This work presents the results of FUN3D analyses that were performed for the 5th AIAA Propulsion Aerodynamics Workshop. The workshop was separated into two sections that focused on inlet and nozzle flows. This paper focuses on the inlet section of the workshop, which considered an axisymmetric inlet in close-proximity to the ground and subjected to a crosswind. Four levels of grid refinement were provided by the workshop committee. Participants were asked to perform simulations for three crosswind velocities on a minimum of three levels of grid refinement, for a total of nine required cases. This work employed an updated set of grids provided by the committee after completion of the workshop based on feedback from participants. The updated grids featured a larger computational domain and increased refinement near the ground vortex region. This work employed the three coarsest grid levels from the updated grid set. Note that an additional extension downstream of the inlet was added to the provided grids for this work to mitigate observed convergence issues. Additionally, a limited turbulence model study was performed for the highest value of crosswind velocity and the finest grid. The results show that grid convergence was only achieved for the case with the lowest value of crosswind velocity. However, the results were generally observed to improve, relative to the experimental data, with increasing grid refinement. The FUN3D predictions were observed to agree qualitatively with the provided experimental data. However, FUN3D exhibited a tendency to underpredict the minimum value of the radially averaged total pressure at the Aerodynamic Interface Plane, which is consistent with the general findings from the workshop. Overall, FUN3D was found to perform well relative to its peers for the PAW5 workshop inlet test case.

PAI↗

NASA NTRSDate not supplied

FUN3D Analyses of the 5th AIAA Propulsion Aerodynamics Workshop Inlet Test Case

PAI↗

NASA NTRS2018

Numerical Simulations of a Quiet SuperSonic Technology (QueSST) Aircraft Preliminary Design

Reynolds Averaged Navier-Stokes (RANS) simulations were performed on a Lockheed Martin Quiet SuperSonic Technology (QueSST) aircraft preliminary design to assess inlet performance. The FUN3D flow solver and its adjoint-based grid refinement capability were used for the simulations in hopes of determining internal "best practices" for predicting inlet performance on top-aft-mounted inlets. Several parameters were explored including tetrahedral vs. pentahedral cells in/around the boundary-layer regions, an engine axis-aligned linear pressure sensor vs. a pressure box objective as the grid adaptation metric, and the number of grid adaptation cycles performed. Additional simulations were performed on manually refined grids for comparison with the adjoint-based adapted grids. Results showed poor agreement in predicted inlet performance on the refined grids compared to experimental data. This was true regardless of whether the refinement was adjoint-based or manual, the cell type in/near the boundary-layer regions, or the grid adaptation metric used. In addition, the 40-probe total pressure recovery was shown to decrease asymptotically as the number of adaptation cycles is increased. Solutions on the unadapted grids generally had better agreement with experimental data than their refined grid counterparts.

Inlet Performance↗

NASA NTRS2000

BOREAS TE-1 Soils Data Over The SSA Tower Sites in Raster Format

The BOREAS TE-1 team collected various data to characterize the soil-plant systems in the BOREAS SSA. This data set was gridded from vector layers of soil maps that were received from Dr. Darwin Anderson (TE-1), who did the original soil mapping in the field during 1994. The vector layers were gridded into raster files that cover approximately 1 square kilometer over each of the tower sites in the SSA. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗

NASA NTRS2017

Global Gridded Crop Model Evaluation: Benchmarking, Skills, Deficiencies and Implications.

Crop models are increasingly used to simulate crop yields at the global scale, but so far there is no general framework on how to assess model performance. Here we evaluate the simulation results of 14 global gridded crop modeling groups that have contributed historic crop yield simulations for maize, wheat, rice and soybean to the Global Gridded Crop Model Intercomparison (GGCMI) of the Agricultural Model Intercomparison and Improvement Project (AgMIP). Simulation results are compared to reference data at global, national and grid cell scales and we evaluate model performance with respect to time series correlation, spatial correlation and mean bias. We find that global gridded crop models (GGCMs) show mixed skill in reproducing time series correlations or spatial patterns at the different spatial scales. Generally, maize, wheat and soybean simulations of many GGCMs are capable of reproducing larger parts of observed temporal variability (time series correlation coefficients (r) of up to 0.888 for maize, 0.673 for wheat and 0.643 for soybean at the global scale) but rice yield variability cannot be well reproduced by most models. Yield variability can be well reproduced for most major producing countries by many GGCMs and for all countries by at least some. A comparison with gridded yield data and a statistical analysis of the effects of weather variability on yield variability shows that the ensemble of GGCMs can explain more of the yield variability than an ensemble of regression models for maize and soybean, but not for wheat and rice. We identify future research needs in global gridded crop modeling and for all individual crop modeling groups. In the absence of a purely observation-based benchmark for model evaluation, we propose that the best performing crop model per crop and region establishes the benchmark for all others, and modelers are encouraged to investigate how crop model performance can be increased. We make our evaluation system accessible to all crop modelers so that other modeling groups can also test their model performance against the reference data and the GGCMI benchmark.

wheat↗

NASA NTRS2017

Assessing Uncertainties in Gridded Emissions: A Case Study for Fossil Fuel Carbon Dioxide (FFCO2) Emission Data

Fossil fuel carbon dioxide (CO2) emissions (FFCO2) are the largest input to the global carbon cycle on a decadal time scale. Because total emissions are assumed to be reasonably well constrained by fuel statistics, FFCO2 often serves as a reference in order to deduce carbon uptake by poorly understood terrestrial and ocean sinks. Conventional atmospheric CO2 flux inversions solve for spatially explicit regional sources and sinks and estimate land and ocean fluxes by subtracting FFCO2. Thus, errors in FFCO2 can propagate into the final inferred flux estimates. Gridded emissions are often based on disaggregation of emissions estimated at national or regional level. Although national and regional total FFCO2 are well known, gridded emission fields are subject to additional uncertainties due to the emission disaggregation. Assessing such uncertainties is often challenging because of the lack of physical measurements for evaluation. We first review difficulties in assessing uncertainties associated with gridded FFCO2 emission data and present several approaches for evaluation of such uncertainties at multiple scales. Given known limitations, inter-emission data differences are often used as a proxy for the uncertainty. The popular approach allows us to characterize differences in emissions, but does not allow us to fully quantify emission disaggregation biases. Our work aims to vicariously evaluate FFCO2 emission data using atmospheric models and measurements. We show a global simulation experiment where uncertainty estimates are propagated as an atmospheric tracer (uncertainty tracer) alongside CO2 in NASA's GEOS model and discuss implications of FFCO2 uncertainties in the context of flux inversions. We also demonstrate the use of high resolution urban CO2 simulations as a tool for objectively evaluating FFCO2 data over intense emission regions. Though this study focuses on FFCO2 emission data, the outcome of this study could also help improve the knowledge of similar gridded emissions data for non-CO2 compounds with similar emission characteristics.

FFCO↗

NASA NTRS1998

A TRMM Rainfall Estimation Method Applicable to Land Areas

Utilizing multi-spectral, dual-polarization Special Sensor Microwave Imager (SSM/I) radiometer measurements, we have developed in this study a method to retrieve average rain rate, R(sub f(sub R)), in a mesoscale grid box of 2deg x 3deg over land. The key parameter of this method is the fractional rain area, f(sub R), in that grid box, which is determined with the help of a threshold on the 85 GHz scattering depression 0 deduced from the SSM/I data. In order to demonstrate the usefulness of this method, nine-months of R(sub f(sub R))are retrieved from SSM/I data over three grid boxes in the Northeastern United States. These retrievals are then compared with the corresponding ground-truth-average rain rate, R(sub g), deduced from 15-minute rain gauges. Based on nine months of rain rate retrievals over three grid boxes, we find that R(sub f(sub R)can explain about 64 % of the variance contained in R(sub g). A similar evaluation of the grid-box-average rain rates R(sub GSCAT) and R(sub SRL), given by the NASA/GSCAT and NOAA/SRL rain retrieval algorithms, is performed. This evaluation reveals that R(sub GSCAT) and R(sub SRL) can explain only about 42 % of the variance contained in R(sub g). In our method, a threshold on the 85 GHz scattering depression is used primarily to determine the fractional rain area in a mesoscale grid box. Quantitative information pertaining to the 85 GHz scattering depression in the grid box is disregarded. In the NASA/GSCAT and NOAA/SRL methods on the other hand, this quantitative information is included. Based on the performance of all three methods, we infer that the magnitude of the scattering depression is a poor indicator of rain rate. Furthermore, from maps based on the observations made by SSM/I on land and ocean we find that there is a significant redundancy in the information content of the SSM/I multi-spectral observations. This leads us to infer that observations of SSM/I at 19 and 37 GHz add only marginal information to that given by 85 GHz scattering depression. As with other methods, the area-average rain retrieval method developed in this study needs tuning with radar and/or rain gauge observations. In the TRMM mission, the microwave radiometer rain retrieval algorithm can be tuned with TRMM radar observations. Since the radiometer has about 3.5 times wider spatial coverage compared to the radar in the TRMM mission, such an algorithm can be useful to extend geographically the rain information provided by the TRMM Precipitation Radar.

Prabhakara, C.↗

NASA NTRS1989

The implementation of the graphics of program EAGLE: A numerical grid generation code on NASA Langley SNS computer system

Program EAGLE (Eglin Arbitrary Geometry Implicit Euler) Numerical Grid Generation System is a composite (multi-block) algebraic or elliptic grid generation system designed to discretize the domain in and/or around any arbitrarily shaped three dimensional regions. This system combines a boundary conforming surface generation scheme and includes plotting routines designed to take full advantage of the DISSPLA Graphics Package (Version 9.0). Program EAGLE is written to compile and execute efficiently on any Cray machine with or without solid state disk (SSD) devices. Also, the code uses namelist inputs which are supported by all Cray machines using the FORTRAN compiler CFT77. The namelist inputs makes it easier for the user to understand the inputs and operation of Program EAGLE. EAGLE's numerical grid generator is constructed in the following form: main program, EGG (executive routine); subroutine SURFAC (surface generation routine); subroutine GRID (grid generation routine); and subroutine GRDPLOT (grid plotting routines). The EAGLE code was modified to use on the NASA-LaRC SNS computer (Cray 2S) system. During the modification a conversion program was developed for the output data of EAGLE's subroutine GRID to permit the data to be graphically displayed by IRIS workstations, using Plot3D. The code of program EAGLE was modified to make operational subroutine GRDPLOT (using DI-3000 Graphics Software Packages) on the NASA-LaRC SNS Computer System. How to implement graphically, the output data of subroutine GRID was determined on any NASA-LaRC graphics terminal that has access to the SNS Computer System DI-300 Graphics Software Packages. A Quick Reference User Guide was developed for the use of program EAGLE on the NASA-LaRC SNS Computer System. One or more application program(s) was illustrated using program EAGLE on the NASA LaRC SNS Computer System, with emphasis on graphics illustrations.

Houston, Johnny L.↗

NASA NTRS1995

Software Aids In Graphical Depiction Of Flow Data

Interactive Data Display System (IDDS) computer program is graphical-display program designed to assist in visualization of three-dimensional flow in turbomachinery. Grid and simulation data files in PLOT3D format required for input. Able to unwrap volumetric data cone associated with centrifugal compressor and display results in easy-to-understand two- or three-dimensional plots. IDDS provides majority of visualization and analysis capability for Integrated Computational Fluid Dynamics and Experiment (ICE) system. IDDS invoked from any subsystem, or used as stand-alone package of display software. Generates contour, vector, shaded, x-y, and carpet plots. Written in C language. Input file format used by IDDS is that of PLOT3D (COSMIC item ARC-12782).

Stegeman, J. D.↗

NASA NTRS1989

Merging AVHRR and SMMR data for remote sensing of ice and cloud in polar regions

Multispectral data from the Advanced Very High Resolution Radiometer (AVHRR) were digitally processed and merged with Scanning Multichannel Microwave Radiometer (SMMR) imagery. Five channels of AVHRR data, four channels of SMRR brightness temperatures and SMMR-derived ice concentration and ice type were co-registered to a polar stereographic grid. The merged data sets are currently being used in combination with meteorological information for integrated studies of clouds and sea ice.

Maslanik, J. A.↗

NASA NTRS1996

Seasonal Variations of the Earth's Gravitational Field: An Analysis of Atmospheric Pressure, Ocean Tidal, and Surface Water Excitation

Monthly mean gravitational field parameters (denoted here as C(sub even)) that represent linear combinations of the primarily even degree zonal spherical harmonic coefficients of the Earth's gravitational field have been recovered using LAGEOS I data and are compared with those derived from gridded global surface pressure data of the National meteorological center (NMC) spanning 1983-1992. The effect of equilibrium ocean tides and surface water variations are also considered. Atmospheric pressure and surface water fluctuations are shown to be the dominant cause of observed annual C(sub even) variations. Closure with observations is seen at the 1sigma level when atmospheric pressure, ocean tide and surface water effects are include. Equilibrium ocean tides are shown to be the main source of excitation at the semiannual period with closure at the 1sigma level seen when both atmospheric pressure and ocean tide effects are included. The inverted barometer (IB) case is shown to give the best agreement with the observation series. The potential of the observed C(sub even) variations for monitoring mass variations in the polar regions of the Earth and the effect of the land-ocean mask in the IB calculation are discussed.

Dong, D,↗

NASA NTRS2002

Three-Dimensional High-Order Spectral Finite Volume Method for Unstructured Grids

Many areas require a very high-order accurate numerical solution of conservation laws for complex shapes. This paper deals with the extension to three dimensions of the Spectral Finite Volume (SV) method for unstructured grids, which was developed to solve such problems. We first summarize the limitations of traditional methods such as finite-difference, and finite-volume for both structured and unstructured grids. We then describe the basic formulation of the spectral finite volume method. What distinguishes the SV method from conventional high-order finite-volume methods for unstructured triangular or tetrahedral grids is the data reconstruction. Instead of using a large stencil of neighboring cells to perform a high-order reconstruction, the stencil is constructed by partitioning each grid cell, called a spectral volume (SV), into 'structured' sub-cells, called control volumes (CVs). One can show that if all the SV cells are partitioned into polygonal or polyhedral CV sub-cells in a geometrically similar manner, the reconstructions for all the SVs become universal, irrespective of their shapes, sizes, orientations, or locations. It follows that the reconstruction is reduced to a weighted sum of unknowns involving just a few simple adds and multiplies, and those weights are universal and can be pre-determined once for all. The method is thus very efficient, accurate, and yet geometrically flexible. The most critical part of the SV method is the partitioning of the SV into CVs. In this paper we present the partitioning of a tetrahedral SV into polyhedral CVs with one free parameter for polynomial reconstructions up to degree of precision five. (Note that the order of accuracy of the method is one order higher than the reconstruction degree of precision.) The free parameter will be determined by minimizing the Lebesgue constant of the reconstruction matrix or similar criteria to obtain optimized partitions. The details of an efficient, parallelizable code to solve three-dimensional problems for any order of accuracy are then presented. Important aspects of the data structure are discussed. Comparisons with the Discontinuous Galerkin (DG) method are made. Numerical examples for wave propagation problems are presented.

Liu, Yen↗