Analysis of lower atmospheric data for diffusion studies
Mathematical diffusion models and meteorological inputs for estimating toxic fuel hazards at Kennedy Space Center
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Mathematical diffusion models and meteorological inputs for estimating toxic fuel hazards at Kennedy Space Center
Two flight prototype solid propellant pulsed plasma microthruster propulsion systems for the SMS satellite were fabricated, assembled and tested. The propulsion system is a completely self contained system requiring only three electrical inputs to operate: a 29.4 volt power source, a 28 volt enable signal and a 50 millsec long command fire signal that can be applied at any rate from 50 ppm to 110 ppm. The thrust level can be varied over a range 2.2 to 1 at constant impulse bit amplitude. By controlling the duration of the 28 volt enable either steady state thrust or a series of discrete impulse bits can be generated. A new technique of capacitor charging was implemented to reduce high voltage stress on energy storage capacitors.
The feasibility of extended and long range weather prediction by physical and dynamical methods was investigated in the following research projects: (1) spectral energy balance; (2) annual cycles of surface heat balance and temperature over North America; and (3) atmospheric response to sea surface temperature anomalies.
The author has identified the following significant results. Large area LANDSAT yield estimates were generated. These results were compared with estimates computed using a meteorological yield model (CCEA). Both of these estimates were compared with Kansas Crop and Livestock Reporting Service (KCLRS) estimates of yield, in an attempt to assess the relative and absolute accuracy of the LANDSAT and CCEA estimates. Results were inconclusive. A large area direct wheat prediction procedure was implemented. Initial results have produced a wheat production estimate comparable with the KCLRS estimate.
Large-area relations between satellite spectral data and end-of-season crop yield were investigated. Green Index Number (GIN) values from Landsat MSS data of sample segments throughout the U.S. Great Plains winter wheat belt in 1978 were correlated to county USDA-SRS reported yields. A linear relation between GIN and yield appeared to exist up to GIN values of 40 or 50, covering cases of severe to moderate stress. In a test on 1978 Texas winter wheat at the county level, GIN values for sample segments in the counties were used in conjunction with an agronomic-meteorological yield model. The combined fit explained significantly more of the observed yield variation at the county level than the agromet model alone.
The first systematic account of the climate of Mars, based upon observations was produced. Cloud data were used to determine spatially and temporally varying near-surface wind direction, relative wind speed, static stability, and humidity conditions on a global scale. Existing models of meteorological processes were critically reexamined in light of the data, and more stringent constraints were set on global processes. Several discoveries were made, including the large extent and seasonal variability of the Mars equatorial Hadley cell, the failure of high latitude winds to reverse direction in early northern spring, the change in meridional wind component in southern midautum, and the almost constant cloud cover in the northern hemisphere, during spring and summer primarily by condensate clouds and in fall and winter by condensates and dust. The implications of these observations are discussed.
Observing systems simulation experiments (OSSE's) provide a powerful tool to assess the impact of proposed satellite borne observing systems on meteorological applications models. We describe the results of an OSSE conducted to assess the impact of data from a low power lidar wind sensor on the forecast accuracy of a global spectral numerical weather prediction (NWP) model, the Air Force Geophysics Laboratory Global Data Assimilation System. The instrument would be operating at near-infrared wavelengths thereby increasing the backscatter signal relative to comparable infrared lidar.
The impact of a large forest fire smoke plume on atmospheric processes is studied through a numerical model of meteorology, aerosols, and radiative transfer. The simulated smoke optical depths at 0.63-micron wavelength are in agreement with analyses of satellite data and show values as high as 1.8. The smoke has an albedo of 35 percent, or more than double the clear-sky value, and cools the surface by as much as 5 K. An imaginary refractive index, n sub im, of 0.01 yields results which closely match the observed cooling, single scattering albedo, and the Angstrom wavelength exponent. An n exp im of 0.1, typical of smoke from urban fires, produces 9 K cooling. Coagulation causes the geometric mean radius by number to increase from the initial value of 0.08 micron to a final value of 0.15 micron, while the specific extinction and absorption increase by 40 and 25 percent, respectively.
On 20 June 1991, NASA's Boeing 737, equipped with in-situ and look-ahead wind-shear detection systems, made direct low-level penetrations (300-350 m AGL) through a microburst during several stages of its evolution. This microburst was located roughly 20 km northeast of Orlando International Airport and was monitored by a Terminal Doppler Weather Radar (TDWR) located about 10 km south of the airport. The first NASA encounter with this microburst (Event 142), at approximately 2041 UTC, was during its intensification phase. At flight level, in-situ measurements indicated a peak 1-km (averaged) F-factor of approximately 0.1. The second NASA encounter (Event 143) occurred at approximately 2046 UTC, about the time of microburst peak intensity. It was during this penetration that a peak 1-km F-factor of approximately 17 was encountered, which was the largest in-situ measurement of the 1991 summer deployment. By the third encounter (Event 144), at approximately 2051 UTC, the microburst had expanded into a macroburst. During this phase of evolution, an in-situ 1-km F-factor of 0.08 was measured. The focus of this paper is to examine this microburst via numerical simulation from an unsteady, three-dimensional meteorological cloud model. The simulated high-resolution data fields of wind, temperature, radar reflectivity factor, and precipitation are closely examined so as to derive information not readily available from 'observations' and to enhance our understanding of the actual event. Characteristics of the simulated microburst evolution are compared with TDWR and in-situ measurements.
This compendium describes aircraft data that are available from NASA's Pacific Exploratory Mission West-A (PEM West-A). PEM West is a component of the International Global Atmospheric Chemistry's (IGAC) East Asia/North Pacific Regional Study (APARE) project. The PEM- West program encompassed two expeditions to study contrasting meteorological regimes in the Pacific. Objectives of PEM West are to investigate the atmospheric chemistry of ozone over the northwest Pacific -- natural budgets and the impact of anthropogenic sources; and to investigate sulfur chemistry -- continental versus marine sulfur sources. PEM West-A was conducted in September 1991 during which the predominance of tropospheric air is from the mid-Pacific (marine) regions, but (at times) is modified/mixed with Asian continental outflow. PEM West-B was conducted during February 1994, a period characterized by maximum continental outflow. PEM-B data (not included) will become public domain during the Summer of 1995. PEM West-A flight experiments were based at Japan, Hong Kong, and Guam. This document provides a representation of NASA DC-8 aircraft data that are available from NASA Langley's Distributed Active Archive Center (DAAC), which include numerous data such as meteorological observations, modeling products, results from surface studies, satellite observations, and sonde releases.
This compendium describes aircraft data that are available from NASA's Pacific Exploratory Mission West-B (PEM West-B). PEM West is a component of the International Global Atmospheric Chemistry's (IGAC) East Asia/North Pacific Regional Study (APARE) project. Objectives of PEM West are to investigate the atmospheric chemistry of ozone over the northwest Pacific -- natural budgets and the impact of anthropogenic/continental sources; and to investigate sulfur chemistry -- continental and marine sulfur sources. The PEM West program encompassed two expeditions. PEM West-A was conducted in September 1991 during which the predominance of tropospheric air was from mid-Pacific (marine) regions, but (at times) was modified by Asian outflow. PEM West-B was conducted during February 1994, a period characterized by maximum Asian outflow. Results from PEM West-A and B are public domain. PEM West-A data are summarized in NASA TM 109177 (published February 1995). Flight experiments were based at Guam, Hong Kong, and Japan. This document provides a representation of NASA DC-8 aircraft data that are available from NASA Langley's Distributed Active Archive Center (DAAC). The DAAC includes numerous other data such as meteorological and modeling products, results from surface studies, satellite observations, and sonde releases.
During the reporting period, the PI has continued to serve on numerous review panels, task forces, and committees with the goal of providing input and guidance for the Earth Observing System Data and Information System (EOSDIS) program at NASA Headquarters and NASA Goddard Space Flight Center (GSFC). In addition, the PI has worked together with personnel at Simpson Weather Associates (SWA) to help create an on-line HDF/HDF-EOS tutorial for beginning and non-expert users of both the Hierarchical Data Format (HDF) and HDF-EOS data format and software libraries. Finally, the PI has worked together with personnel at SWA and the Information Technology and Systems Center (ITSC) at the University of Alabama in Huntsville (UAH) on a feasibility study regarding the use of data mining software to ascertain features from the gridded output from numerical meteorological forecast models. A summary of these activities is provided.
Finite volume methods are a class of discretization schemes that have proven highly successful in approximating the solution of a wide variety of conservation law systems. They are extensively used in fluid mechanics, porous media flow, meteorology, electromagnetics, models of biological processes, semi-conductor device simulation and many other engineering areas governed by conservative systems that can be written in integral control volume form. This article reviews elements of the foundation and analysis of modern finite volume methods. The primary advantages of these methods are numerical robustness through the obtention of discrete maximum (minimum) principles, applicability on very general unstructured meshes, and the intrinsic local conservation properties of the resulting schemes. Throughout this article, specific attention is given to scalar nonlinear hyperbolic conservation laws and the development of high order accurate schemes for discretizing them. A key tool in the design and analysis of finite volume schemes suitable for non-oscillatory discontinuity capturing is discrete maximum principle analysis. A number of building blocks used in the development of numerical schemes possessing local discrete maximum principles are reviewed in one and several space dimensions, e.g. monotone fluxes, E-fluxes, TVD discretization, non-oscillatory reconstruction, slope limiters, positive coefficient schemes, etc. When available, theoretical results concerning a priori and a posteriori error estimates are given. Further advanced topics are then considered such as high order time integration, discretization of diffusion terms and the extension to systems of nonlinear conservation laws.
A numerical large-eddy simulation model is currently being used to quantify aircraft wake vortex behavior with meteorological observables. The model, having a meteorological framework, permits the interaction of wake vortices with environments characterized by crosswind shear, stratification, and humidity. The addition of grid-scale turbulence as an initial condition appeared to have little consequence. Results show that conventional nondimensionalizations work very well for vortex pairs embedded in stably stratified flows. However, this result is based on simple environments with constant Brunt-Vaisala frequency. Results presented here also show that crosswind profiles exert important and complex interactions on the trajectories of wake vortices. Nonlinear crosswind profiles tended to arrest the descent of wake vortex pairs. The member of the vortex pair with vorticity of same sign as the vertical change in the ambient along-track vorticity may be deflected upwards.
Assessments of the present state and future evolution of the space environment heavily relies on timely access to appropriate environmental measurements. These, near real-time (nrt), measurements provide a direct assessment of local or remote space environment conditions, they contribute to a more global description of Space Weather parameters through assimilative models, and they provide essential input into forecasting models. Unlike meteorology, however, the provision of these data is not a mainstream activity in the sense that critical space environment data are often derived from research rather than operational sensors. In addition, space research is a relatively immature field, where SUbstantial gaps in our knowledge impede our ability to optimally use available data streams. In this presentation, we provide examples of presently employed nrt data streams and their utility. We further discuss challenges and opportunities associated with the present approach to space weather forecasting. Finally, an outlook toward the future will be presented.
Vertical transport by moist sub-grid scale processes such as deep convection is a well-known source of uncertainty in CO2 source/sink inversion. However, a dynamical link between vertical transport, satellite based retrievals of column mole fractions of CO2, and source/sink inversion has not yet been established. By using the same offline transport model with meteorological fields from slightly different data assimilation systems, we examine sensitivity of frontal CO2 transport and retrieved fluxes to different parameterizations of sub-grid vertical transport. We find that frontal transport feeds off background vertical CO2 gradients, which are modulated by sub-grid vertical transport. The implication for source/sink estimation is two-fold. First, CO2 variations contained in moist poleward moving air masses are systematically different from variations in dry equatorward moving air. Moist poleward transport is hidden from orbital sensors on satellites, causing a sampling bias, which leads directly to small but systematic flux retrieval errors in northern mid-latitudes. Second, differences in the representation of moist sub-grid vertical transport in GEOS-4 and GEOS-5 meteorological fields cause differences in vertical gradients of CO2, which leads to systematic differences in moist poleward and dry equatorward CO2 transport and therefore the fraction of CO2 variations hidden in moist air from satellites. As a result, sampling biases are amplified and regional scale flux errors enhanced, most notably in Europe (0.43+/-0.35 PgC /yr). These results, cast from the perspective of moist frontal transport processes, support previous arguments that the vertical gradient of CO2 is a major source of uncertainty in source/sink inversion.
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.
We examine satellite-based measurements of chlorophyll solar-induced fluorescence (SIF) over the region impacted by the Russian drought and heat wave of 2010. Like the popular Normalized Difference Vegetation Index (NDVI) that has been used for decades to measure photosynthetic capacity, SIF measurements are sensitive to the fraction of absorbed photosynthetically-active radiation (fPAR). However, in addition, SIF is sensitive to the fluorescence yield that is related to the photosynthetic yield. Both SIF and NDVI from satellite data show drought-related declines early in the growing season in 2010 as compared to other years between 2007 and 2013 for areas dominated by crops and grasslands. This suggests an early manifestation of the dry conditions on fPAR. We also simulated SIF using a global land surface model driven by observation-based meteorological fields. The model provides a reasonable simulation of the drought and heat impacts on SIF in terms of the timing and spatial extents of anomalies, but there are some differences between modeled and observed SIF. The model may potentially be improved through data assimilation or parameter estimation using satellite observations of SIF (as well as NDVI). The model simulations also offer the opportunity to examine separately the different components of the SIF signal and relationships with Gross Primary Productivity (GPP).