Time Series Machine Learning Methods for Surface PM2.5 Estimations Using Geostationary Satellites and Numerical Weather Models
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A recently developed method for estimating transonic aircraft aerodynamics to high angles of attack which is especially suited to computerized aircraft design and optimization studies is described. Following theoretical and empirical guidelines, explicit nonlinear equations are formulated for subsonic, transonic, and supersonic speeds; new algorithms are used for assessing compressibility effects and for analyzing transonic, shock-dominated flows which adhere to Laitone's limit Mach-number criterion. Viscous dominated flows are not analyzed. The transonic influence of viscosity is indirectly accommodated by assigning designated inputs rather than extracted solutions for the chordwise locations of shock and separation. The method is extended to complete aircraft configurations by including accounts for nose lift, the wing downwash field, and tail lift. Several comparisons of experiment and estimate are included.
We present a general method for making cross comparable estimates of the benefits of NASA-developed decision support technologies for air traffic management, and we apply a specific implementation of the method to estimate benefits of three decision support tools (DSTs) under development in NASA's advanced Air Transportation Technologies Program: Active Final Approach Spacing Tool (A-FAST), Expedite Departure Path (EDP), and Conflict Probe and Trial Planning Tool (CPTP). The report also reviews data about the present operation of the national airspace system (NAS) to identify opportunities for DST's to reduce delays and inefficiencies.
A simple method of estimating moisture content (W) of a bare soil from the observed brightness temperature (T sub B) at 1.4 GHz is discussed. The method is based on a radiative transfer model calculation, which has been successfully used in the past to account for many observational results, with some modifications to take into account the effect of surface roughness. Besides the measured T sub B's, the three additional inputs required by the method are the effective soil thermodynamic temperature, the precise relation between W and the smooth field brightness temperature T sub B and a parameter specifying the surface roughness characteristics. The soil effective temperature can be readily measured and the procedures of estimating surface roughness parameter and obtaining the relation between W and smooth field brightness temperature are discussed in detail. Dual polarized radiometric measurements at an off-nadir incident angle are sufficient to estimate both surface roughness parameter and W, provided that the relation between W and smooth field brightness temperature at the same angle is known. The method of W estimate is demonstrated with two sets of experimental data, one from a controlled field experiment by a mobile tower and the other, from aircraft overflight. The results from both data sets are encouraging when the estimated W's are compared with the acquired ground truth of W's in the top 2 cm layer. An offset between the estimated and the measured W's exists in the results of the analyses, but that can be accounted for by the presently poor knowledge of the relationship between W and smooth field brightness temperature for various types of soils. An approach to quantify this relationship for different soils and thus improve the method of W estimate is suggested.
A method for estimating the heat and moisture fluxes of coastal waters using the cloud free path, the sea surface temperature, and the saturation water vapor mixing ratio is presented. Generalized nomograms for the surface sensible and latent heat fluxes are developed using the Stage and Businger (1981) mixed-layer model. The fluxes are found to be slightly dependent on wind speed. The results are found to be applicable to any path within the cloud-free region, with heat fluxes obtainable by multiplication of the mean heating by the mean wind speed in the boundary layer. Higher stability causes lowered heating. It is shown that the latent heat flux is linear. Applications of the method to lake-effect snowstorms and for verification of boundary-layer models are indicated.
The validity of integrating over discrete wavelength bands is examined to estimate total shortwave bidirectional reflectance of vegetated and bare soil surfaces. Methods for estimating albedo from multiple angle, discrete wavelength band radiometer measurements are studied. These methods include a numerical integration technique and the integration of an empirically derived equation for bidirectional reflectance. It is concluded that shortwave albedos estimated through both techniques agree favorably with the independent pyranometer measurements. Absolute rms errors are found to be 0.5 percent or less for both grass sod and bare soil surfaces.
Methods and systems for converting an image contrast evolution of an object to a temperature contrast evolution and vice versa are disclosed, including methods for assessing an emissivity of the object; calculating an afterglow heat flux evolution; calculating a measurement region of interest temperature change; calculating a reference region of interest temperature change; calculating a reflection temperature change; calculating the image contrast evolution or the temperature contrast evolution; and converting the image contrast evolution to the temperature contrast evolution or vice versa, respectively.
Methods and systems for converting an image contrast evolution of an object to a temperature contrast evolution and vice versa are disclosed, including methods for assessing an emissivity of the object; calculating an afterglow heat flux evolution; calculating a measurement region of interest temperature change; calculating a reference region of interest temperature change; calculating a reflection temperature change; calculating the image contrast evolution or the temperature contrast evolution; and converting the image contrast evolution to the temperature contrast evolution or vice versa, respectively.
A method is presented for estimating the crack-extension resistance curve (R-curve) from residual-strength (maximum load against original crack length) data for precracked fracture specimens. The method allows additional information to be inferred from simple test results, and that information can be used to estimate the failure loads of more complicated structures of the same material and thickness. The fundamentals of the R-curve concept are reviewed first. Then the analytical basis for the estimation method is presented. The estimation method has been verified in two ways. Data from the literature (involving several materials and different types of specimens) are used to show that the estimated R-curve is in good agreement with the measured R-curve. A recent predictive blind round-robin program offers a more crucial test. When the actual failure loads are disclosed, the predictions are found to be in good agreement.
A method for estimating the integrated precipitable water (IPW) content of the atmosphere using measurements of indicated infrared zenith sky temperature was validated over east-central Florida. The method uses inexpensive, commercial off the shelf, hand-held infrared thermometers (IRT). Two such IRTs were obtained from a commercial vendor, calibrated against several laboratory reference sources at KSC, and used to make IR zenith sky temperature measurements in the vicinity of KSC and Cape Canaveral Air Force Station (CCAFS). The calibration and comparison data showed that these inexpensive IRTs provided reliable, stable IR temperature measurements that were well correlated with the NOAA IPW observations.
In this work, we augmented existing methods for estimating pilot workload ratings with deep neural networks trained using data from simulated flight tests in the Vertical Motion Simulator (VMS). We used an existing method, Spare Capacity Operations Estimator (SCOPE), along with a recurrent neural network and conducted comparison studies between the two methods individually, and when used together. We found that using both methods together can improve the result over using either approach alone. In our first test case, we achieved an improved linear correlation coefficient of 0.409 over that of SCOPE alone at 0.352 on the training dataset. Through cross validation, we also found that the results may be dependent on the split of training vs. validation data, and that further investigation should be conducted to understand what additional inputs to the neural network model should be made.
Calculational methods for estimation of dose from external proton exposure of arbitrary convex bodies are briefly reviewed. All the necessary information for the estimation of dose in soft tissue is presented. Special emphasis is placed on retaining the effects of nuclear reaction, especially in relation to the dose equivalent. Computer subroutines to evaluate all of the relevant functions are discussed. Nuclear reaction contributions for standard space radiations are in most cases found to be significant. Many of the existing computer programs for estimating dose in which nuclear reaction effects are neglected can be readily converted to include nuclear reaction effects by use of the subroutines described herein.
Three reports describe research on proposed method for estimating crop yields by combining meteorological data with satellite measurements of reflected radiation to estimate crop-absorbed radiation. Concept, when tested over large areas, forms basis for evaluating crop conditions and estimating yields over regions where ground observations too costly or too difficult.
A method to estimate raindrop size distribution (DSD) parameters from a combined Zm profile and path-integrated attenuation is shown, and a test result of the method using the data from an aircraft experiment is presented. The 'semi' dual-parameter (SDP) measurement is employed to estimate DSD parameters using the data obtained from an aircraft experiment conducted by Communications Research Laboratory, Tokyo, in conjunction with NASA. The validity of estimated DSD parameters is examined using measured Ka-band radar reflectivities. The estimated path-averaged N(0) is consistent with the Ka/X Ze ratio, and the use of estimated DSD shows excellent agreement between the rain rates estimated from the X-band and K-band Zes. The feasibility of estimating DSD parameters from space is confirmed.
Two estimators developed by Jeffreys (1940, 1968) are described and used in conjunction with polar-motion data to determine the frequency (Fc) and quality factor (Qc) of the Chandler wobble. Data are taken from a monthly polar-motion series, satellite laser-ranging results, and optical astrometry and intercompared for use via interpolation techniques. Maximum likelihood arguments were employed to develop the estimators, and the assumption that polar motion relates to a Gaussian random process is assessed in terms of the accuracies of the estimators. The present results agree with those from Jeffreys' earlier study but are inconsistent with the later estimator; a Monte Carlo evaluation of the estimators confirms that the 1968 method is more accurate. The later estimator method shows good performance because the Fourier coefficients derived from the data have signal/noise levels that are superior to those for an individual datum. The method is shown to be valuable for general spectral-analysis problems in which isolated peaks must be analyzed from noisy data.
This NESC assessment examined the accuracy of estimating buffet loads on in-line launch vehicles without booster attachments using sparse unsteady pressure measurements. The buffet loads computed using sparse sensor data were compared with estimates derived using measurements with much higher spatial resolution. The current method for estimating launch vehicle buffet loads is through wind tunnel testing of models with approximately 400 unsteady pressure transducers. Even with this relatively large number of sensors, the coverage can be insufficient to provide reliable integrated unsteady loads on vehicles. In general, sparse sensor spacing requires the use of coherence-length-based corrections in the azimuthal and axial directions to integrate the unsteady pressures and obtain reasonable estimates of the buffet loads. Coherence corrections have been used to estimate buffet loads for a variety of launch vehicles with the assumption methodology results in reasonably conservative loads. For the Space Launch System (SLS), the first estimates of buffet loads exceeded the limits of the vehicle structure, so additional tests with higher sensor density were conducted to better define the buffet loads and possibly avoid expensive modifications to the vehicle design. Without the additional tests and improvements to the coherence-length analysis methods, there would have been significant impacts to the vehicle weight, cost, and schedule. If the load estimates turn out to be too low, there is significant risk of structural failure of the vehicle. This assessment used a combination of unsteady pressure-sensitive paint (uPSP), unsteady pressure transducers, and a dynamic force and moment balance to investigate the integration schemes used with limited unsteady pressure data by comparing them with direct integration of extremely dense fluctuating pressure measurements. An outfall of the assessment was to evaluate the potential of using the emerging uPSP technique in a production test environment for future launch vehicles. The results show that modifications to the current technique can improve the accuracy of buffet estimates. More importantly, the uPSP worked remarkably well and, with improvements to the frequency response, sensitivity, and productivity, will provide an enhanced method for measuring wind tunnel buffet forcing functions (BFFs).
MIRO (Microwave Instrument for the Rosetta Orbiter) is a lightweight, uncooled, dual-frequency heterodyne radiometer. The MIRO encountered asteroid Steins in 2008, and during the flyby, MIRO used the Asteroid Mode to measure the emission spectrum of Steins. The Asteroid Mode is one of the seven modes of the MIRO operation, and is designed to increase the length of time that a spectral line is in the MIRO pass-band during a flyby of an object. This software is used to calibrate the continuum measurement of Steins emission power during the asteroid flyby. The MIRO raw measurement data need to be calibrated in order to obtain physically meaningful data. This software calibrates the MIRO raw measurements in digital units to the brightness temperature in Kelvin. The software uses two calibration sequences that are included in the Asteroid Mode. One sequence is at the beginning of the mode, and the other at the end. The first six frames contain the measurement of a cold calibration target, while the last six frames measure a warm calibration target. The targets have known temperatures and are used to provide reference power and gain, which can be used to convert MIRO measurements into brightness temperature. The software was developed to calibrate MIRO continuum measurements from Asteroid Mode. The software determines the relationship between the raw digital unit measured by MIRO and the equivalent brightness temperature by analyzing data from calibration frames. The found relationship is applied to non-calibration frames, which are the measurements of an object of interest such as asteroids and other planetary objects that MIRO encounters during its operation. This software characterizes the gain fluctuations statistically and determines which method to estimate gain between calibration frames. For example, if the fluctuation is lower than a statistically significant level, the averaging method is used to estimate the gain between the calibration frames. If the fluctuation is found to be statistically significant, a linear interpolation of gain and reference power is used to estimate the gain between the calibration frames.
Two methods of estimating surface velocity vectors from AVHRR data are applied to the same set of images and the results are compared with in situ and altimeter measurements. The first technique utilizes an automated feature-tracking algorithm and the second uses an inversion of the heat equation. The two methods were comparable in their degree of agreement with the in situ data, giving velocity magnitudes that were 30 to 50 percent less than drifter and acoustic Doppler current profiler velocities measured at 15 to 20 m depth, with rms directional differences of about 60 degrees.