A method for precision measurement of synchronization errors in tracking-station clocks
Precision measurement of synchronization error in tracking station clocks, to obtain selenodetic data on Lunar Orbiter mission
Borncamp, F.↗
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TROPOMI Methane Validation in the GeoCarb Domain
Objective: GeoCarb validation •Purpose: •Do the four TCCON sites in the GeoCarb domain characterize satellite validation? •Method: •Assess the error estimates globally vs. in the GeoCarb domain •Assess the use of GML/DOE aircraft for CH4 validation •Systematic error estimate (from Kulawik, 2016): •+ regional bias (stdevof average bias versus validation at each station) •+ correlated error (stdev of daily average versus validation) •-co-location error (above quantities for model@satelliteminus model@valid) •-validation error (systematic error of validation estimates, e.g. model extension) Aircraft validation error •CH4 profile extension error estimate: 7 ppb •Extend aircraft observations to the top of the atmosphere with different model configurations •CAMS, scaling to stratosphere, then taking stratosphere •Extend by repeating top aircraft value to the troposphere, then taking CAMS •Extend with GEOS-Chem run (from 2010). •Difference CAMS-Scale vs. CAMS-Tropo: •3.6 +-5.5 ppb •Systematic error: 6.6 ppb •Extending aircraft to tropopause is blatantly wrong, but these two have the same stratosphere. •Difference CAMS-Scale vs. GEOS-Scale: •6.2 +-8.7 ppb •Do not consider bias since model is 10 years off. Systematic error ~8.7 ppb. •Estimate of systematic error from profile extension (possibly underestimated, resulting in possibly higher TROPOMI error estimate) •7 ppb •Would likely vary some by season, site, other conditions •Aircraft measurement error: 1 ppb •1 ppb from measurement error3
TROMPOMI↗
Multiphenomenology explosion monitoring (MultiPEM): a general framework for data interpretation and yield estimation
SUMMARY An underground nuclear explosion (UNE) couples mechanical energy into crustal rock, which propagates as seismic and acoustic waves. These different physical phenomena transport, by different pathways, to standoff detectors at varying distances. The transport pathways attenuate the original signal but in different ways. Enabled by correct statistical weighting, signal attenuation models can be used to combine these disparate sensor data to estimate the yield of an UNE. Contemporaneous statistical models, used in yield estimation, can be improved with an advanced partition of error for these physical signal propagation models. We present an advanced multivariate approach to error modelling of multiphenomenology physical signatures. In addition to measurement error, our error model represents physical model biases as random with a physics-based covariance structure. To illustrate this proposed framework, we demonstrate the estimation of explosion yield using openly available seismic and acoustic data from chemical single-point explosions.
Williams, Brian J.↗
Error Analysis of the Shuttle Reaction Control System Propellant Gaging Module
An investigation of the Shuttle Reaction Control System (RCS) propellant gaging module has revealed that the gaging errors due to the combined effects of random instrumentation measurement errors and propellant loading uncertainties are non-linear over the range of the propellant quantity gage (0-100%), with the largest error occurring at the zero point. When the RCS propellant tanks are filled to contain 100% of the maximum usable propellant, the largest gaging error was determined to be 3.9% for the fuel and 5.4% for the oxidizer. When the RCS propellant tanks initially contain 50% of the maximum usable propellant, the largest gaging error increases to 4.0% for the fuel and 5.6% for the oxidizer.
Duhon, D. D.↗
Error Analysis of the Shuttle Orbital Maneuvering System P-V-T Propellant Gaging Module. Mission Planning, Mission Analysis and Software Formulation
An investigation of the shuttle orbital maneuvering system (OMS) pressure-volume-temperature (P-V-T) propellant gaging module has revealed that the gaging errors due to the combined effects of random instrumentation measurement errors, propellant loading uncertainties, and simplifying assumptions in the software are non-linear over the range of the usable propellant quantity gage (0-100%), with the largest error being at the zero point. When the OMS propellant tanks in the orbiter vehicle pods are filled to contain 100% of the maximum usable propellant, the gaging error at the zero point was determined to be 9.5% for the fuel and 9.5% for the oxidizer. When the OMS propellant tanks initially contain 50% of the maximum usable propellant, the largest gaging error is still 9.5% for the fuel and 9.5% for the oxidizer.
Duhon, D. D.↗
Application of HCMM data to regional geologic analysis for mineral and energy resource evaluation
A more accurate algorithm was developed to compute thermal inertia from temperature difference and albedo information. The error of this algorithm is about 1/3 of the measurement error in HCMM as opposed to the current algorithm which can have an error 5 times larger. A northeast trending lineament was discovered in southwestern Arizona on enhanced thermal inertia images.
Watson, K.↗
Error-Based Design Space Windowing
Windowing of design space is considered in order to reduce the bias errors due to low-order polynomial response surfaces (RS). Standard design space windowing (DSW) uses a region of interest by setting a requirement on response level and checks it by a global RS predictions over the design space. This approach, however, is vulnerable since RS modeling errors may lead to the wrong region to zoom on. The approach is modified by introducing an eigenvalue error measure based on point-to-point mean squared error criterion. Two examples are presented to demonstrate the benefit of the error-based DSW.
Papila, Melih↗
Orion Optical Navigation for Loss of Communication Lunar Return Contingencies
The Orion Crew Exploration Vehicle (CEV) will replace the Space Shuttle and serve as the next-generation spaceship to carry humans back to the Moon for the first time since the Apollo program. For nominal lunar mission operations, the Mission Control Navigation team will utilize radiometric measurements to determine the position and velocity of Orion and uplink state information to support Lunar return. However, in the loss of communications contingency return scenario, Orion must safely return the crew to the Earth's surface. The navigation design solution for this loss of communications scenario is optical navigation consisting of lunar landmark tracking in low lunar orbit and star- horizon angular measurements coupled with apparent planetary diameter for Earth return trajectories. This paper describes the optical measurement errors and the navigation filter that will process those measurements to support navigation for safe crew return.
Getchius, Joel↗
Synthetic ozone deposition and stomatal uptake at flux tower sites
Abstract. We develop and evaluate a method to estimate O 3 deposition and stomatal O 3 uptake across networks of eddy covariance flux tower sites where O 3 concentrations and O 3 fluxes have not been measured. The method combines standard micrometeorological flux measurements, which constrain O 3 deposition velocity and stomatal conductance, with a gridded dataset of observed surface O 3 concentrations. Measurement errors are propagated through all calculations to quantify O 3 flux uncertainties. We evaluate the method at three sites with O 3 flux measurements: Harvard Forest, Blodgett Forest, and Hyytiälä Forest. The method reproduces 83 % or more of the variability in daily stomatal uptake at these sites with modest mean bias (21 % or less). At least 95 % of daily average values agree with measurements within a factor of 2 and, according to the error analysis, the residual differences from measured O 3 fluxes are consistent with the uncertainty in the underlying measurements. The product, called synthetic O 3 flux or SynFlux, includes 43 FLUXNET sites in the United States and 60 sites in Europe, totaling 926 site years of data. This dataset, which is now public, dramatically expands the number and types of sites where O 3 fluxes can be used for ecosystem impact studies and evaluation of air quality and climate models. Across these sites, the mean stomatal conductance and O 3 deposition velocity is 0.03–1.0 cm s -1 . The stomatal O 3 flux during the growing season (typically April–September) is 0.5–11.0 nmol O 3 m -2 s -1 with a mean of 4.5 nmol O 3 m -2 s -1 and the largest fluxes generally occur where stomatal conductance is high, rather than where O 3 concentrations are high. The conductance differences across sites can be explained by atmospheric humidity, soil moisture, vegetation type, irrigation, and land management. These stomatal fluxes suggest that ambient O 3 degrades biomass production and CO 2 sequestration by 20 %–24 % at crop sites, 6 %–29 % at deciduous broadleaf forests, and 4 %–20 % at evergreen needleleaf forests in the United States and Europe.
59 BASIC BIOLOGICAL SCIENCES↗
RF techniques - Mismatch errors on noise temperature measurements
General-case equations for application to mismatch errors in Y-factor measurements for calibration of receiver - radio frequency technique for noise temperature measurement errors
NOISE MEASUREMENT↗
Quantitative analysis of the correlations in the Boltzmann-Grad limit for hard spheres
In this contribution I consider the problem of the validity of the Boltzmann equation for a system of hard spheres in the Boltzmann-Grad limit. I briefly review the results available nowadays with a particular emphasis on the celebrated Lanford’s validity theorem. Finally I present some recent results, obtained in collaboration with S. Simonella, concerning a quantitative analysis of the propagation of chaos. More precisely we introduce a quantity (the correlation error) measuring how close a j-particle rescaled correlation function at time t (sufficiently small) is far from the full statistical independence. Roughly speaking, a correlation error of order k, measures (in the context of the BBKGY hierarchy) the event in which k tagged particles form a recolliding group.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
The TEMS Apollo-Saturn 1B tracking system error model results through the AS-205 flight test
Regression analysis of tracking system measurement errors on Apollo/Saturn 1B flight tests
Junkin, B. G.↗
Fitting program for linear regressions according to Mahon (1996)
This program takes the users' Input data and fits a linear regression to it using the prescription presented by Mahon (1996). Compared to the commonly used York fit, this method has the correct prescription for measurement error propagation. This software should facilitate the proper fitting of measurements with a simple Interface.
Trappitsch, RetoG.↗
Comments on local electron concentration determination from Doppler dispersion measurements of satellite radio beacons.
Measurement errors in ionospheric local electron concentration determination from Doppler dispersion measurements by satellite radio beacons
Da Rosa, A. V.↗
Noncontact measurement of angular deflection
Technique for measuring instantaneous angular deflection of object requires no physical contact. Technique utilizes two flat refractors, converging lens, and different photocell. Distinction of method is its combination of optical and electromechanical components into feedback system in which measurement error is made to approach zero. Application is foreseen in measurement of torsional strain.
Bryant, E. L.↗
Assimilation of Soil Moisture Observations Over Land Improves Analysis and Prediction of Tropical Cyclone Idai
Soil moisture conditions can impact the circulation and structure of a tropical cyclone (TC) when part or all of the circulation is over land. Dry land surface conditions may lead to faster dissipation of a TC over land, whereas very wet conditions may lead to a prolonged maintenance of its intensity. While this relationship is relatively well understood in theory, applications of these findings in the context of numerical weather prediction (NWP) have been limited. Here we present a case study that explores the potential of improving TC predictions through an improved soil moisture initialization in an NWP framework. Specifically, we examine the impact of assimilating observations from the NASA Soil Moisture Active Passive (SMAP) mission into the NASA Goddard Earth Observing System (GEOS) global weather model on the prediction of South-West Indian Ocean TC Idai (2019). SMAP provides accurate L-band (1.4 GHz) brightness temperatures (Tb) observations that are sensitive to soil moisture globally and at high revisit times of 2-3 days. It has previously been shown that the assimilation of SMAP Tbs significantly improves modeled land surface states. Here we evaluate: (i) forecasts initialized from an analysis that is comparable to the GEOS operational analysis (without SMAP Tb assimilation) and (ii) forecasts initialized from an analysis that additionally assimilates SMAP Tb observations. We find that in the analysis with SMAP assimilation, the TC has a better-defined, more aligned vertical structure over land relative to the control run; moreover, the analyzed TC size, as measured by the wind speed radius, better matches the observed TC size. We further find significant reductions in the forecast intensity error and the forecast along-track error, measured against observations. The largest error reductions occur at lead times of 36 to 72 hours, suggesting that the land with its longer memory gains in importance as a source of predictability at this timescale. An investigation of the underlying mechanisms leading to the skill improvements from SMAP data assimilation revealed that the assimilation of SMAP leads to wetter soil moisture conditions and an increased latent heat flux in the SMAP analysis, which results in a TC with higher column-integrated total moisture content and total energy compared to the control analysis.
Jana Kolassa↗