SEARCH · Engineering Papers

Results for “variable importance”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 631 records · Page 35

All sources NASA NTRS DOE OSTI

NASA NTRS2016

Modeling Antarctic Subglacial Lake Filling and Drainage Cycles

The growth and drainage of active subglacial lakes in Antarctica has previously been inferred from analysis of ice surface altimetry data. We use a subglacial hydrology model applied to a synthetic Antarctic ice stream to examine internal controls on the filling and drainage of subglacial lakes. Our model outputs suggest that the highly constricted subglacial environment of our idealized ice stream, combined with relatively high rates of water flow funneled from a large catchment, can combine to create a system exhibiting slow-moving pressure waves. Over a period of years, the accumulation of water in the ice stream onset region results in a buildup of pressure creating temporary channels, which then evacuate the excess water. This increased flux of water beneath the ice stream drives lake growth. As the water body builds up, it steepens the hydraulic gradient out of the overdeepened lake basin and allows greater flux. Eventually this flux is large enough to melt channels that cause the lake to drain. Lake drainage also depends on the internal hydrological development in the wider system and therefore does not directly correspond to a particular water volume or depth. This creates a highly temporally and spatially variable system, which is of interest for assessing the importance of subglacial lakes in ice stream hydrology and dynamics.

drainage↗

NASA NTRS2022

Idaho Wildfires II: Assessing the Relationship Between Drought Indicators and Wildfire Risk to Enhance Hazard Modeling and Inform Mitigation Planning

The western United States has experienced twenty years of increased and prolonged drought which have exacerbated wildfire hazards. These jeopardize population centers through increased risks to ecosystem services, local economies, and livelihoods. The Idaho Office of Emergency Management, Water Resources, and Department of Lands are seeking methods to dynamically monitor these conditions and update models that inform hazard mitigation planning and resource allocation. Towards this, these agencies partnered with NASA DEVELOP to produce drought-enhanced wildfire hazard models. Part of a two-term project, the two teams revised the state’s static wildfire hazard model with refined data layers and remotely-sensed data to reflect dynamic ecosystem responses to drought conditions and wildfire potential. Our team distinguished between rangeland and forestland ecosystems, and investigated relationships between drought metrics and vegetation condition using TerrSet Earth Trends Modeler. This analysis determined that total precipitation at a 5-month lag interval (r 2 = 0.72) along with the Evaporative Stress Index (r 2 = 0.69); and precipitation at a 5-month interval (r 2 = 0.42) were important drivers in rangeland and forestland, respectively. These driver variables were incorporated into a temporally dynamic wildfire hazard map. Our team used linear regression to correlate hazard ratings with wildfire frequency. For the year 2020, neither the enhanced hazard model (p < 0.10, r 2 = 0.01) nor the state’s static model (p < 0.05, r 2 = 0.03) were strongly correlated with actual wildfire frequency as they expressed an inverse relationship between wildfire hazard and frequency. This suggests wildfire occurrence is complex and not necessarily driven by the variables used.

Wildfire↗

NASA NTRSDate not supplied

Maintaining the Continuity of the Global Climate Data Record of Lightning from Space

Lightning is a natural hazard, an indicator of changes in convective storm behavior across multiple spatial and temporal scales, and a major influence on climate-affecting chemicals such as ozone and methane. Lightning also has substantial impacts on the near-space environment. As such, the World Meteorological Organization (WMO) has designated lightning as an Essential Climate Variable (ECV); that is, a measurement that is really important for understanding Earth’s climate. Spaceborne lightning observations are the gold standard for measuring global lightning, as the detection efficiency is more spatially uniform compared to ground-based lightning measurements. In addition, spaceborne is the only practical method for measuring total lightning (i.e., both intracloud and cloud-to-ground) at the global scale, as ground-based networks have limited ability to detect intracloud lightning at long distances (e.g., over oceans, far from land-based sensors). Since 1995, with only a two-year gap (2015-2017), lightning has been observed globally using a combination of Optical Transient Detector (OTD) and Lightning Imaging Sensor (LIS) instruments. However, the year 2023 is the planned end for the International Space Station (ISS) LIS mission, and there is no designated low-Earth orbit (LEO) successor yet identified. Since 2017, geostationary (GEO) observations of lightning have become increasingly available. These include the U.S. Geostationary Lightning Mappers (GLMs), China’s Lightning Mapping Imager (LMI), and Europe’s Lightning Imager (LI). While GEO provides continuous, quasi-hemispheric coverage of lightning and thunderstorms, there are current gaps preventing global coverage, particularly in portions of Asia and the western Pacific, as well as high-latitude regions. Moreover, integration of the GEO constellation into a Climate Data Record (CDR) of lightning is a major challenge only recently begun to be addressed by the WMO. Furthermore, recent work has demonstrated some deficiencies in the global record of lightning from space. For example, small lightning flashes are very common in severe weather, but are difficult to observe using the present set of spaceborne lightning imagers. Moreover, some types of lightning are best observed using frequencies other than the commonly used near-infrared (777-nm), including ultraviolet and the radio spectrum. Finally, it is not possible to assess the vertical distribution of lightning globally, even though this measurement is highly relevant to thunderstorm behavior as well as lightning’s effects on greenhouse gases and the near-space environment. This presentation will provide a current assessment of lightning measurements from space, will identify significant current and future gaps in these observations, and will evaluate potential solutions for improving the overall CDR of global lightning.

Timothy Lang↗

NASA NTRS2015

Global Ocean Evaporation: How Well Can We Estimate Interannual to Decadal Variability?

Evaporation from the world's oceans constitutes the largest component of the global water balance. It is important not only as the ultimate source of moisture that is tied to the radiative processes determining Earth's energy balance but also to freshwater availability over land, governing habitability of the planet. Here we focus on variability of ocean evaporation on scales from interannual to decadal by appealing to three sources of data: the new MERRA-2 (Modern-Era Retrospective analysis for Research and Applications -2); climate models run with historical sea-surface temperatures, ice and atmospheric constituents (so-called AMIP experiments); and state-of-the-art satellite retrievals from the Seaflux and HOAPS (Hamburg Ocean-Atmosphere Parameters and Fluxes from Satellite) projects. Each of these sources has distinct advantages as well as drawbacks. MERRA-2, like other reanalyses, synthesizes evaporation estimates consistent with observationally constrained physical and dynamical models-but data stream discontinuities are a major problem for interpreting multi-decadal records. The climate models used in data assimilation can also be run with lesser constraints such as with SSTs and sea-ice (i.e. AMIPs) or with additional, minimal observations of surface pressure and marine observations that have longer and less fragmentary observational records. We use the new ERA-20C reanalysis produced by ECMWF embodying the latter methodology. Still, the model physics biases in climate models and the lack of a predicted surface energy balance are of concern. Satellite retrievals and comparisons to ship-based measurements offer the most observationally-based estimates, but sensor inter-calibration, algorithm retrieval assumptions, and short records are dominant issues. Our strategy depends on maximizing the advantages of these combined records. The primary diagnostic tool used here is an analysis of bulk aerodynamic computations produced by these sources and uses a first-order Taylor series analysis of wind speed, SST, near-surface stability and relative humidity variations around climatology to gauge the importance of these components. We find that the MERRA-2 evaporation record is strongly influenced by the availability of wind speed and humidity from passive microwave imagers beginning in the late 1980s as well as by the SST record. The trend over the period 1980 to present is nearly 10%. AMIP or the ERA-20C trends are much smaller. We find that ENSO-related signals involving both wind speed and thermodynamic variability remain the primary signal in the latter and are confirmed by satellite retrievals. We present uncertainty estimates based on the various data sources and discuss the implications for GEWEX water and energy budget science challenges.

Robertson, Franklin R.↗

NASA NTRS2008

Chandra X-ray Grating Spectrometry of Eta Carinae near X-ray Minimum: I. Variability of the Sulfur and Silicon Emission Lines

We report on variations in important X-ray emission lines in a series of Chandra grating spectra of the supermassive colliding wind binary star eta Car, including key phases around the X-ray minimum/periastron passage in 2003.5. The X-rays arise from the collision of the slow, dense wind of eta Car with the fast, low-density wind of an otherwise hidden companion star. The X-ray emission lines provide the only direct measure of the flow dynamics of the companion's wind along the wind-wind collision zone. We concentrate here on the silicon and sulfur lines, which are the strongest and best resolved lines in the X-ray spectra. Most of the line profiles can be adequately fit with symmetric Gaussians with little significant skewness. Both the silicon and sulfur lines show significant velocity shifts and correlated increases in line widths through the observations. The R = forbidden-to-intercombination ratio from the Si XIII and S XV triplets is near or above the low-density limit in all observations, suggesting that the line-forming region is > 1.6 stellar radii from the companion star, and that the emitting plasma may be in a non-equilibrium state. We show that simple geometrical models cannot simultaneously fit both the observed centroid variations and changes in line width as a function of phase. We show that the observed profiles can be fitted with synthetic profiles with a reasonable model of the emissivity along the wind-wind collision boundary. We use this analysis to help constrain the line formation region as a function of orbital phase, and the orbital geometry. Subject headings: X-rays: stars -stars: early-type-stars: individual (q Car)

Henley, D. B.↗

NASA NTRS1984

The effects of Cr, Co, Al, Mo and Ta on the cyclic oxidation behavior of a prototype cast Ni-base superalloy based on a 2(5) composite statistically designed experiment

A series of cast Ni-base superalloys were systematically varied at selected levels of Co, Cr, Mo, Ta, and Al. The elemental levels varied were Mo, 0 to 4 percent; Cr, 6 to 18 percent; Co, 0 to 20 percent, Ta, 0 to 8 percent; and Al, 3.25 to 6.25 percent. The cyclic oxidation resistance was determined from specific weight change data as a function of time for 1 hr cycles in static air at 1100 C. The significant terms in decreasing order of their importance were Al, Ta, Cr2, Al-Cr, Cr-Co, Co2, Al-Mo, Cr-Mo, Al-Al, and Mo-Ta. The Al term alone accounted for close to 82 percent of the explained variability. The estimating equation showed that the Al level was the most important and should be at its 6.25 wt % maximum value. The Mo and Ta levels should also be at their maximum 4 and 8 wt % respectively. The cobalt composition should be as low as possible, i.e., 0 wt%. The Cr level optimum varies depending on the other 4 levels. The X-ray diffaction results indicate the most protective scales are alumina/aluminate spinel stabilizized with a tri-rutile oxide high in Ta and Mo.

Barrett, C. A.↗

NASA NTRS1994

Probability techniques for reliability analysis of composite materials

Traditional design approaches for composite materials have employed deterministic criteria for failure analysis. New approaches are required to predict the reliability of composite structures since strengths and stresses may be random variables. This report will examine and compare methods used to evaluate the reliability of composite laminae. The two types of methods that will be evaluated are fast probability integration (FPI) methods and Monte Carlo methods. In these methods, reliability is formulated as the probability that an explicit function of random variables is less than a given constant. Using failure criteria developed for composite materials, a function of design variables can be generated which defines a 'failure surface' in probability space. A number of methods are available to evaluate the integration over the probability space bounded by this surface; this integration delivers the required reliability. The methods which will be evaluated are: the first order, second moment FPI methods; second order, second moment FPI methods; the simple Monte Carlo; and an advanced Monte Carlo technique which utilizes importance sampling. The methods are compared for accuracy, efficiency, and for the conservativism of the reliability estimation. The methodology involved in determining the sensitivity of the reliability estimate to the design variables (strength distributions) and importance factors is also presented.

Wetherhold, Robert C.↗

NASA NTRS1998

A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model: Overview - Part 1

Knowledge of the amount of water in the soil is of great importance to many earth science disciplines. Soil moisture is a key variable in controlling the exchange of water and energy between the land surface and the atmosphere. Thus, soil moisture information is valuable in a wide range of applications including weather and climate, runoff potential and flood control, early warning of droughts, irrigation, crop yield forecasting, soil erosion, reservoir management, geotechnical engineering, and water quality. Despite the importance of soil moisture information, widespread and continuous measurements of soil moisture are not possible today. Although many earth surface conditions can be measured from satellites, we still cannot adequately measure soil moisture from space. Research in soil moisture remote sensing began in the mid 1970s shortly after the surge in satellite development. Recent advances in remote sensing have shown that soil moisture can be measured, at least qualitatively, by several methods. Quantitative measurements of moisture in the soil surface layer have been most successful using both passive and active microwave remote sensing, although complications arise from surface roughness and vegetation type and density. Early attempts to measure soil moisture from space-borne microwave instruments were hindered by what is now considered sub-optimal wavelengths (shorter than 5 cm) and the coarse spatial resolution of the measurements. L-band frequencies between 1 and 3 GHz (10-30 cm) have been deemed optimal for detection of soil moisture in the upper few centimeters of soil. The Electronically Steered Thinned Array Radiometer (ESTAR), an aircraft-based instrument operating a 1,4 GHz, has shown great promise for soil moisture determination. Initiatives are underway to develop a similar instrument for space. Existing space-borne synthetic aperture radars (SARS) operating at C- and L-band have also shown some potential to detect surface wetness. The advantage of radar is its much higher resolution than passive microwave systems, but it is currently hampered by surface roughness effects and the lack of a good algorithm based on a single frequency and single polarization. In addition, its repeat frequency is generally low (about 40 days). In the meantime, two new radiometers offer some hope for remote sensing of soil moisture from space. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), launched in November 1997, possesses a 10.65 GHz channel and the Advanced Microwave Scanning Radiometer (AMSR) on both the ADEOS-11 and Earth Observing System AM-1 platforms to be launched in 1999 possesses a 6.9 GHz channel. Aside from issues about interference from vegetation, the coarse resolution of these data will provide considerable challenges pertaining to their application. The resolution of TMI is about 45 km and that of AMSR is about 70 km. These resolutions are grossly inconsistent with the scale of soil moisture processes and the spatial variability of factors that control soil moisture. Scale disparities such as these are forcing us to rethink how we assimilate data of various scales in hydrologic models. Of particular interest is how to assimilate soil moisture data by reconciling the scale disparity between what we can expect from present and future remote sensing measurements of soil moisture and modeling soil moisture processes. It is because of this disparity between the resolution of space-based sensors and the scale of data needed for capturing the spatial variability of soil moisture and related properties that remote sensing of soil moisture has not met with more widespread success. Within a single footprint of current sensors at the wavelengths optimal for this application, in most cases there is enormous heterogeneity in soil moisture created by differences in landcover, soils and topography, as well as variability in antecedent precipitation. It is difficult to interpret the meaning of 'mean' soil moisture under such conditions and even more difficult to apply such a value. Because of the non-linear relationships between near-surface soil moisture and other variables of interest, such as surface energy fluxes and runoff, mean soil moisture has little applicability at such large scales. It is for these reasons that the use of remote sensing in conjunction with a hydrologic model appears to be of benefit in capturing the complete spatial and temporal structure of soil moisture. This paper is Part I of a four-part series describing a method for intermittently assimilating remotely-sensed soil moisture information to improve performance of a distributed land surface hydrology model. The method, summarized in section II, involves the following components, each of which is detailed in the indicated section of the paper or subsequent papers in this series: Forward radiative transfer model methods (section II and Part IV); Use of a Kalman filter to assimilate remotely-sensed soil moisture estimates with the model profile (section II and Part IV); Application of a soil hydrology model to capture the continuous evolution of the soil moisture profile within and below the root zone (section III); Statistical aggregation techniques (section IV and Part II); Disaggregation techniques using a neural network approach (section IV and Part III); and Maximum likelihood and Bayesian algorithms for inversely solving for the soil moisture profile in the upper few cm (Part IV).

Crosson, William L.↗

NASA NTRS2021

Ionization Efficiency in the Dayside Ionosphere of Mars: Structure and Variability

Ionization efficiency, the ratio between photoelectron impact ionization and primary photoionization, is an important quantity from the perspective of ionospheric energy balance and as a quantity to be parameterized for use in global simulations. We investigate ionization efficiency using MAVEN in situ measurements of solar extreme ultraviolet (EUV) flux, suprathermal electron flux, and neutral density. Its behavior with respect to pressure and solar zenith angle (SZA) is explained by ionization cross-sections and photoabsorption, plus photoelectron transport near the terminator. We find similar ionization efficiencies between the species CO 2 , O, N 2 , and CO, with Argon ∼40% higher, explained largely by its higher ionization potential. Efficiency depends positively on solar activity, increasing by ∼50–100% (depending on season) from low to moderate solar EUV levels, before flattening at higher EUV levels. EUV spectral hardening appears to be responsible for only ∼15% of this increase, the remainder best explained by variability in neutral composition. We find a negligible dependence of ionization efficiency on the strength and direction of crustal magnetic fields. Efficiencies agree poorly with the theoretical model of Nicholson et al. (2009), https://doi.org/10.1111/j.1365-2966.2009.15463.x, possibly reflecting differences in model versus measured solar EUV spectrum and neutral densities. We fit the data to the empirical parameterization of Mendillo et al. (2011), https://doi.org/10.1029/2011ja016865 but find that a single fit cannot capture ionization efficiency behavior across all dayside SZA values. We believe that an empirical model of Mars ionization efficiency will require MAVEN data and validated transport modeling to reach to sufficiently high pressures to capture Mars' photochemical peaks M1 and M2

Robert Lillis↗

NASA NTRS2001

Improving Ocean Angular Momentum Estimates Using a Model Constrained by Data

Ocean angular momentum (OAM) calculations using forward model runs without any data constraints have, recently revealed the effects of OAM variability on the Earth's rotation. Here we use an ocean model and its adjoint to estimate OAM values by constraining the model to available oceanic data. The optimization procedure yields substantial changes in OAM, related to adjustments in both motion and mass fields, as well as in the wind stress torques acting on the ocean. Constrained and unconstrained OAM values are discussed in the context of closing the planet's angular momentum budget. The estimation procedure, yields noticeable improvements in the agreement with the observed Earth rotation parameters, particularly at the seasonal timescale. The comparison with Earth rotation measurements provides an independent consistency check on the estimated ocean state and underlines the importance of ocean state estimation for quantitative. studies of the variable large-scale oceanic mass and circulation fields, including studies of OAM.

Ponte, Rui M.↗

NASA NTRS2014

Brown Dwarf Variability: What's Varying and Why?

Surveys by ground based telescopes, HST, and Spitzer have revealed that brown dwarfs of most spectral classes exhibit variability. The spectral and temporal signatures of the variability are complex and apparently defy simplistic classification which complicates efforts to model the changes. Important questions include understanding if clearings are forming in an otherwise uniform cloud deck or if thermal perturbations, perhaps associated with breaking gravity waves, are responsible. If clouds are responsible how long does it take for the atmospheric thermal profile to relax from a hot cloudy to a cooler cloudless state? If thermal perturbations are responsible then what atmospheric layers are varying? How do the observed variability timescales compare to atmospheric radiative, chemical, and dynamical timescales? I will address such questions by presenting modeling results for time-varying partly cloudy atmospheres and explore the importance of various atmospheric processes over the relevant timescales for brown dwarfs of a range of effective temperatures. Regardless of the origin of the observed variability, the complexity seen in the atmospheres of the field dwarfs hints at the variability that we may encounter in the next few years in directly imaged young Jupiters. Thus understanding the nature of variability in the field dwarfs, including sensitivity to gravity and metallicity, is of particular importance for exoplanet characterization.

brown dwarfs↗

NASA NTRS2010

Forced and Unforced Variability of Twentieth Century North American Droughts and Pluvials

Research on the forcing of drought and pluvial events over North America is dominated by general circulation model experiments that often have operational limitations (e.g., computational expense, ability to simulate relevant processes, etc). We use a statistically based modeling approach to investigate sea surface temperature (SST) forcing of the twentieth century pluvial (1905-1917) and drought (1932-1939, 1948-1957, 1998-2002) events. A principal component (PC) analysis of Palmer Drought Severity Index (PDSI) from the North American Drought Atlas separates the drought variability into five leading modes accounting for 62% of the underlying variance. Over the full period spanning these events (1900-2005), the first three PCs significantly correlate with SSTs in the equatorial Pacific (PC 1), North Pacific (PC 2), and North Atlantic (PC 3), with spatial patterns (as defined by the empirical orthogonal functions) consistent with our understanding of North American drought responses to SST forcing. We use a large ensemble statistical modeling approach to determine how successfully we can reproduce these drought/pluvial events using these three modes of variability. Using Pacific forcing only (PCs 1-2), we are able to reproduce the 1948-1957 drought and 1905-1917 pluvial above a 95% random noise threshold in over 90% of the ensemble members; the addition of Atlantic forcing (PCs 1-2-3) provides only marginal improvement. For the 1998-2002 drought, Pacific forcing reproduces the drought above noise in over 65% of the ensemble members, with the addition of Atlantic forcing increasing the number passing to over 80%. The severity of the drought, however, is underestimated in the ensemble median, suggesting this drought intensity can only be achieved through internal variability or other processes. Pacific only forcing does a poor job of reproducing the 1932-1939 drought pattern in the ensemble median, and less than one third of ensemble members exceed the noise threshold (28%). Inclusion of Atlantic forcing improves the ensemble median drought pattern and nearly doubles the number of ensemble members passing the noise threshold (52%). Even with the inclusion of Atlantic forcing, the intensity of the simulated 1932-1939 drought is muted, and the drought itself extends too far into the southwest and southern Great Plains. To an even greater extent than the 1998-2002 drought, these results suggest much of the variance in the 1932-1939 drought is dependent on processes other than SST forcing. This study highlights the importance of internal noise and non SST processes for hydroclimatic variability over North America, complementing existing research using general circulation models.

Cook, Benjamin I.↗

NASA NTRS2015

An Assessment of Actual and Potential Building Climate Zone Change and Variability From the Last 30 Years Through 2100 Using NASA's MERRA and CMIP5 Simulations

Background: In the US, residential and commercial building infrastructure combined consumes about 40% of total energy usage and emits about 39% of total CO2 emission (DOE/EIA "Annual Energy Outlook 2013"). Building codes, as used by local and state enforcement entities are typically tied to the dominant climate within an enforcement jurisdiction classified according to various climate zones. These climate zones are based upon a 30-year average of local surface observations and are developed by DOE and ASHRAE. Establishing the current variability and potential changes to future building climate zones is very important for increasing the energy efficiency of buildings and reducing energy costs and emissions in the future. Objectives: This paper demonstrates the usefulness of using NASA's Modern Era Retrospective-analysis for Research and Applications (MERRA) atmospheric data assimilation to derive the DOE/ASHRAE building climate zone maps and then using MERRA to define the last 30 years of variability in climate zones for the Continental US. An atmospheric assimilation is a global atmospheric model optimized to satellite, atmospheric and surface in situ measurements. Using MERRA as a baseline, we then evaluate the latest Climate Model Inter-comparison Project (CMIP) climate model Version 5 runs to assess potential variability in future climate zones under various assumptions. Methods: We derive DOE/ASHRAE building climate zones using surface and temperature data products from MERRA. We assess these zones using the uncertainties derived by comparison to surface measurements. Using statistical tests, we evaluate variability of the climate zones in time and assess areas in the continental US for statistically significant trends by region. CMIP 5 produced a data base of over two dozen detailed climate model runs under various greenhouse gas forcing assumptions. We evaluate the variation in building climate zones for 3 different decades using an ensemble and quartile statistics to provide an assessment of potential building climate zone changes relative to the uncertainties demonstrated using MERRA. Findings and Conclusions: These results show that there is a statistically significant increase in the area covered by warmer climate zones and a tendency for a reduction of area in colder climate zones in some limited regions. The CMIP analysis shows that models vary from relatively little building climate zone change for the least sensitive and conservation assumptions to a warming of at most 3 zones for certain areas, particularly the north central US by the end of the 21st century.

Stackhouse, Paul W., Jr.↗

NASA NTRS2011

Quantifying Spatial and Seasonal Variability in Atmospheric Ammonia with In Situ and Space-Based Observations

Ammonia plays an important role in many biogeochemical processes, yet atmospheric mixing ratios are not well known. Recently, methods have been developed for retrieving NH3 from space-based observations, but they have not been compared to in situ measurements. We have conducted a field campaign combining co-located surface measurements and satellite special observations from the Tropospheric Emission Spectrometer (TES). Our study includes 25 surface monitoring sites spanning 350 km across eastern North Carolina, a region with large seasonal and spatial variability in NH3. From the TES spectra, we retrieve a NH3 representative volume mixing ratio (RVMR), and we restrict our analysis to times when the region of the atmosphere observed by TES is representative of the surface measurement. We find that the TES NH3 RVMR qualitatively captures the seasonal and spatial variability found in eastern North Carolina. Both surface measurements and TES NH3 show a strong correspondence with the number of livestock facilities within 10 km of the observation. Furthermore, we find that TES H3 RVMR captures the month-to-month variability present in the surface observations. The high correspondence with in situ measurements and vast spatial coverage make TES NH3 RVMR a valuable tool for understanding regional and global NH3 fluxes.

Pinder, Robert W.↗

NASA NTRS2018

Impact of a Cold Pool Parameterization on the Diurnal Cycle and Intraseasonal Variability in the GEOS AGCM

A gradual transition from shallow to deep convection may be important both to the continental diurnal cycle of precipitation and to the tropical Madden-Julian Oscillation. However, many existing convection parameterizations transition too readily, with corresponding diurnal and intraseasonal biases. High entrainment rates can be used to delay deep convection, but typically produce mean state biases; this is the "entrainment dilemma." Cold pools and sub-grid organization offer a potential solution to this dilemma, and recent work shows parameterized cold pools can effectively modulate deep convection, with improvements to the diurnal cycle and intraseasonal variability. Here we investigate the effects of a simple prognostic cold pool scheme coupled to the Grell-Freitas convection parameterization, in a set of global simulations with the NASA GEOS model. Air detrained from parameterized downdrafts is maintained in vertically resolved cold pools, which evolve with simplified dynamics. We test several options for cold pool feedbacks on convection, including modifications to deep convective entrainment rates, convective source air properties, and thermodynamic profiles, based on the level of cold pool activity. Cold pool impacts on the diurnal cycle are evaluated against TRMM, and moisture and moist static energy budgets are used to understand changes in tropical intraseasonal variability. Preliminary results show delays in the diurnal cycle of precipitation.

Arnold, Nathan↗

NASA NTRS2002

Process Cost Modeling for Multi-Disciplinary Design Optimization

For early design concepts, the conventional approach to cost is normally some kind of parametric weight-based cost model. There is now ample evidence that this approach can be misleading and inaccurate. By the nature of its development, a parametric cost model requires historical data and is valid only if the new design is analogous to those for which the model was derived. Advanced aerospace vehicles have no historical production data and are nowhere near the vehicles of the past. Using an existing weight-based cost model would only lead to errors and distortions of the true production cost. This report outlines the development of a process-based cost model in which the physical elements of the vehicle are costed according to a first-order dynamics model. This theoretical cost model, first advocated by early work at MIT, has been expanded to cover the basic structures of an advanced aerospace vehicle. Elemental costs based on the geometry of the design can be summed up to provide an overall estimation of the total production cost for a design configuration. This capability to directly link any design configuration to realistic cost estimation is a key requirement for high payoff MDO problems. Another important consideration in this report is the handling of part or product complexity. Here the concept of cost modulus is introduced to take into account variability due to different materials, sizes, shapes, precision of fabrication, and equipment requirements. The most important implication of the development of the proposed process-based cost model is that different design configurations can now be quickly related to their cost estimates in a seamless calculation process easily implemented on any spreadsheet tool. In successive sections, the report addresses the issues of cost modeling as follows. First, an introduction is presented to provide the background for the research work. Next, a quick review of cost estimation techniques is made with the intention to highlight their inappropriateness for what is really needed at the conceptual phase of the design process. The First-Order Process Velocity Cost Model (FOPV) is discussed at length in the next section. This is followed by an application of the FOPV cost model to a generic wing. For designs that have no precedence as far as acquisition costs are concerned, cost data derived from the FOPV cost model may not be accurate enough because of new requirements for shape complexity, material, equipment and precision/tolerance. The concept of Cost Modulus is introduced at this point to compensate for these new burdens on the basic processes. This is treated in section 5. The cost of a design must be conveniently linked to its CAD representation. The interfacing of CAD models and spreadsheets containing the cost equations is the subject of the next section, section 6. The last section of the report is a summary of the progress made so far, and the anticipated research work to be achieved in the future.

Bao, Han P.↗

NASA NTRS2002

Predicting Production Costs for Advanced Aerospace Vehicles

Bao, Han P.↗

NASA NTRS1989

Specification of parameters for development of a spatial database for drought monitoring and famine early warning in the African Sahel

Parameters were described for spatial database to facilitate drought monitoring and famine early warning in the African Sahel. The proposed system, referred to as the African Drought and Famine Information System (ADFIS) is ultimately recommended for implementation with the NASA/FEMA Spatial Analysis and Modeling System (SAMS), a GIS/Dymanic Modeling software package, currently under development. SAMS is derived from FEMA'S Integration Emergency Management Information System (IEMIS) and the Pacific Northwest Laborotory's/Engineering Topographic Laboratory's Airland Battlefield Environment (ALBE) GIS. SAMS is primarily intended for disaster planning and resource management applications with the developing countries. Sources of data for the system would include the Developing Economics Branch of the U.S. Dept. of Agriculture, the World Bank, Tulane University School of Public Health and Tropical Medicine's Famine Early Warning Systems (FEWS) Project, the USAID's Foreign Disaster Assistance Section, the World Resources Institute, the World Meterological Institute, the USGS, the UNFAO, UNICEF, and the United Nations Disaster Relief Organization (UNDRO). Satellite imagery would include decadal AVHRR imagery and Normalized Difference Vegetation Index (NDVI) values from 1981 to the present for the African continent and selected Landsat scenes for the Sudan pilot study. The system is initially conceived for the MicroVAX 2/GPX, running VMS. To facilitate comparative analysis, a global time-series database (1950 to 1987) is included for a basic set of 125 socio-economic variables per country per year. A more detailed database for the Sahelian countries includes soil type, water resources, agricultural production, agricultural import and export, food aid, and consumption. A pilot dataset for the Sudan with over 2,500 variables from the World Bank's ANDREX system, also includes epidemiological data on incidence of kwashiorkor, marasmus, other nutritional deficiencies, and synergistically-related infectious diseases.

Rochon, Gilbert L.↗