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NASA NTRS2009

Gaussian and Lognormal Models of Hurricane Gust Factors

A document describes a tool that predicts the likelihood of land-falling tropical storms and hurricanes exceeding specified peak speeds, given the mean wind speed at various heights of up to 500 feet (150 meters) above ground level. Empirical models to calculate mean and standard deviation of the gust factor as a function of height and mean wind speed were developed in Excel based on data from previous hurricanes. Separate models were developed for Gaussian and offset lognormal distributions for the gust factor. Rather than forecasting a single, specific peak wind speed, this tool provides a probability of exceeding a specified value. This probability is provided as a function of height, allowing it to be applied at a height appropriate for tall structures. The user inputs the mean wind speed, height, and operational threshold. The tool produces the probability from each model that the given threshold will be exceeded. This application does have its limits. They were tested only in tropical storm conditions associated with the periphery of hurricanes. Winds of similar speed produced by non-tropical system may have different turbulence dynamics and stability, which may change those winds statistical characteristics. These models were developed along the Central Florida seacoast, and their results may not accurately extrapolate to inland areas, or even to coastal sites that are different from those used to build the models. Although this tool cannot be generalized for use in different environments, its methodology could be applied to those locations to develop a similar tool tuned to local conditions.

Merceret, Frank↗

NASA NTRS1977

An information theory approach to the density of the earth

Information theory can develop a technique which takes experimentally determined numbers and produces a uniquely specified best density model satisfying those numbers. A model was generated using five numerical parameters: the mass of the earth, its moment of inertia, three zero-node torsional normal modes (L = 2, 8, 26). In order to determine the stability of the solution, six additional densities were generated, in each of which the period of one of the three normal modes was increased or decreased by one standard deviation. The superposition of the seven models is shown. It indicates that current knowledge of the torsional modes is sufficient to specify the density in the upper mantle but that the lower mantle and core will require smaller standard deviations before they can be accurately specified.

Graber, M. A.↗

NASA NTRS1998

Modelling and Estimation of Dynamic Ocean Topography Within Global Geopotential Solutions

In this poster, we will present a report on the ongoing investigation "Improved Gravitational and Dynamic Height Models Through the use of Oceanographic Data." we have used a two year mean (1993-1994) of the Dynamic ocean Topography (DOT) field implied by the Semtner and Chervin POCM_4B model, and developed normal equations in surface spherical harmonics to degree and order 30. These normal equations, were combined with normal equations derived from TOPEX and ERS-1 altimeter data over the same time period. Combination solutions (based on satellite tracking data, altimeter data, surface gravity data and OCM data) were were developed Test solutions were obtained estimating the DOT field to 2Ox2O and 3ox3O. These solutions were tested with independent DOT values computed over 38 WOCE hydrographic sections, which contained a total of 3072 stations and represented 216000 km of travelled lines. The weighted standard deviation of the differences between the DOT obtained from the hydrographic data and and the field estimated from the joint combination solutions was computed for each of the test models, the weighted standard deviation for the baseline combination solution excluding the POCM4_B data was 9.7 cm for a DOT solution to 30x30, where introducing the POCM4_B data into the combination model reduced the standard deviation to 9.2 cm, indicating the the introduction of oceanographic information benefits the solution for the dynamic ocean topography. We will discuss the weighting schemes applied and the method of solution. Another aspect of our investigation involves testing alternate parametric representations of the dynamic height field. We looked at the alternative representations in terms of the Proudman functions (PF), and compared these to the use of spherical harmonics (SH) to represent the dynamic ocean topography, using once again the 1993 and 1994 output of the POCM4_B OCM as the reference model. A significant advantage of PF's over SH's is that the former require no "fill-in" values over areas where the DOT is undefined. We show that the PF and SH results using equal number of parameters agree quite well in overall content. In addition, PFs appear better suited for representation of high frequency signals close to the signal boundary. The development of the PF solutions for the DOT will be described and the statistics of the comparisons will be presented.

Lemoine, Frank G.↗

NASA NTRS2017

Earth Global Reference Atmospheric Model (GRAM) Overview and Updates: DOLWG Meeting

What is Earth-GRAM (Global Reference Atmospheric Model): Provides monthly mean and standard deviation for any point in atmosphere - Monthly, Geographic, and Altitude Variation; Earth-GRAM is a C++ software package - Currently distributed as Earth-GRAM 2016; Atmospheric variables included: pressure, density, temperature, horizontal and vertical winds, speed of sound, and atmospheric constituents; Used by engineering community because of ability to create dispersions in atmosphere at a rapid runtime - Often embedded in trajectory simulation software; Not a forecast model; Does not readily capture localized atmospheric effects.

White, Patrick↗

NASA NTRS2021

Precipitable water vapor over oceans from the Maritime Aerosol Network: Evaluation of global models and satellite products under clear sky conditions

We present results from an evaluation of precipitable water vapor (W) over remote oceanic areas as derived from global reanalysis models and from satellites against observations from the Maritime Aerosol Network (MAN) for cloudless skies during the period of 2004–2017. They cover polar, mid latitude and tropical oceanic regions and represent a first effort to use MAN observations for such evaluation. The global reanalysis model products evaluated in this study are from the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2), the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA I), and the Climate Forecast System Reanalysis (CFSR) model. The satellite products evaluated are from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Polarization and Directionality of the Earth's Reflectances (POLDER), the Global Ozone Monitoring Experiment (GOME-2), the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), and the Atmospheric Infra-red Sounder (AIRS). Satellite retrievals of W are based on the attenuation of solar reflected light by water vapor absorption bands, except those from AIRS that rely on brightness temperature measurements. A very good agreement is observed between the model estimates and MAN, with mean differences of ~5% and standard deviations of ~15%. These results are within the uncertainties associated with the models and the measurements, indicating the skill of the reanalysis models to estimate W over oceans under clear sky conditions. Mean differences of W between the satellite and MAN products are ~11, 6.7, 12, −7, and 3% for MODIS, POLDER, GOME-2, SCIAMACHY and AIRS respectively, while their standard deviations are 31, 29, 28, 20 and 17%. These differences reveal the need to address inconsistencies among different satellite sensors and ground-based measurements to reduce the uncertainties associated with the retrievals.

Daniel Pérez-Ramírez↗

NASA NTRS1989

The effects of seasonal and latitudinal earth infrared radiance variations on ERBS attitude control

Analysis performed in the Flight Dynamics Facility by the Earth Radiation Budget Satellite (ERBS) Attitude Determination Support team illustrates the pitch attitude control motion and roll attitude errors induced by Earth infrared (IR) horizon radiance variations. IR scanner and inertial reference unit (IRU) pitch and roll flight data spanning 4 years of the ERBS mission are analyzed to illustrate the changes in the magnitude of the errors on time scales of the orbital period, months, and seasons. The analysis represents a unique opportunity to compare prelaunch estimates of radiance-induced attitude errors with flight measurements. As a consequence of this work the following additional information is obtained: an assessment of an average model of these errors and its standard deviation, a measurement to determine and verify previously proposed corrections to the current Earth IR radiance data base, and the possibility of a mean motion model derived from flight data in place of IRU data for ERBS fine attitude determination.

Phenneger, M. C.↗

NASA NTRS1990

The effects of seasonal and latitudinal earth infrared radiance variations on ERBS attitude control

Phenneger, M.↗

NASA NTRS2006

A New Empirical Thermospheric Density Model JB2006 using New Solar Indices

A new empirical atmospheric density model is developed using the CIRA72 (Jacchia 71) model as the basis for the diffusion equations. New solar indices based on orbit based sensor data are used for the solar irradiances in the extreme and far ultraviolet wavelengths. New exospheric temperature and semiannual density equations are employed to represent the major thermospheric density variations. Temperature correction equations are also developed for diurnal and latitudinal effects, and finally density correction factors are used for model corrections required at high altitude (1500-4000 km). The new model, Jacchia-Bowman 2006, is validated through comparisons of accurate daily density drag data previously computed for numerous satellite. For 400 km altitude the standard deviation of 16% for the standard Jacchia model is reduced to 10% for the new JB2006 model for periods of low geomagnetic storm activity.

Bowman, Bruce R.↗

NASA NTRS2010

Design and Development of a Model to Simulate 0-G Treadmill Running Using the European Space Agency's Subject Loading System

Develop a model that simulates a human running in 0 G using the European Space Agency s (ESA) Subject Loading System (SLS). The model provides ground reaction forces (GRF) based on speed and pull-down forces (PDF). DESIGN The theoretical basis for the Running Model was based on a simple spring-mass model. The dynamic properties of the spring-mass model express theoretical vertical GRF (GRFv) and shear GRF in the posterior-anterior direction (GRFsh) during running gait. ADAMs VIEW software was used to build the model, which has a pelvis, thigh segment, shank segment, and a spring foot (see Figure 1).the model s movement simulates the joint kinematics of a human running at Earth gravity with the aim of generating GRF data. DEVELOPMENT & VERIFICATION ESA provided parabolic flight data of subjects running while using the SLS, for further characterization of the model s GRF. Peak GRF data were fit to a linear regression line dependent on PDF and speed. Interpolation and extrapolation of the regression equation provided a theoretical data matrix, which is used to drive the model s motion equations. Verification of the model was conducted by running the model at 4 different speeds, with each speed accounting for 3 different PDF. The model s GRF data fell within a 1-standard-deviation boundary derived from the empirical ESA data. CONCLUSION The Running Model aids in conducting various simulations (potential scenarios include a fatigued runner or a powerful runner generating high loads at a fast cadence) to determine limitations for the T2 vibration isolation system (VIS) aboard the International Space Station. This model can predict how running with the ESA SLS affects the T2 VIS and may be used for other exercise analyses in the future.

Caldwell, E. C.↗

NASA NTRS1981

On the internal target model in a tracking task

An optimal control model for predicting operator's dynamic responses and errors in target tracking ability is summarized. The model, which predicts asymmetry in the tracking data, is dependent on target maneuvers and trajectories. Gunners perception, decision making, control, and estimate of target positions and velocity related to crossover intervals are discussed. The model provides estimates for means, standard deviations, and variances for variables investigated and for operator estimates of future target positions and velocities.

Caglayan, A. K.↗

NASA NTRS2010

Verify MesoNAM Performance

The AMU conducted an objective analysis of the MesoNAM forecasts compared to observed values from sensors at specified KSC/CCAFS wind towers by calculating the following statistics to verify the performance of the model: 1) Bias (mean difference), 2) Standard deviation of Bias, 3) Root Mean Square Error (RMSE), and 4) Hypothesis test for Bias = O. The 45 WS LWOs use the MesoNAM to support launch weather operations. However, the actual performance of the model at KSC and CCAFS had not been measured objectively. The analysis compared the MesoNAM forecast winds, temperature and dew point to the observed values from the sensors on wind towers. The data were stratified by tower sensor, month and onshore/offshore wind direction based on the orientation of the coastline to each tower's location. The model's performance statistics were then calculated for each wind tower based on sensor height and model initialization time. The period of record for the data used in this task was based on the operational start of the current MesoNAM in mid-August 2006 and so the task began with the first full month of data, September 2006, through May 2010. The analysis of model performance indicated: a) The accuracy decreased as the forecast valid time from the model initialization increased, b) There was a diurnal signal in T with a cool bias during the late night and a warm bias during the afternoon, c) There was a diurnal signal in Td with a low bias during the afternoon and a high bias during the late night, and d) The model parameters at each vertical level most closely matched the observed parameters at heights closest to those vertical levels. The AMU developed a GUI that consists of a multi-level drop-down menu written in JavaScript embedded within the HTML code. This tool allows the LWO to easily and efficiently navigate among the charts and spreadsheet files containing the model performance statistics. The objective statistics give the LWOs knowledge of the model's strengths and weaknesses and the GUI allows quick access to the data which will result in improved forecasts for operations.

Bauman, William H., III↗

NASA NTRS1991

Theoretical computation of trace gases retrieval random error from measurements of high spectral resolution infrared sounder

The purpose of this paper is to demonstrate the trace gas profiling capabilities of future passive high spectral resolution (1 cm(exp -1) or better) infrared (600 to 2700 cm(exp -1)) satellite tropospheric sounders. These sounders, such as the grating spectrometer, Atmospheric InfRared Sounders (AIRS) (Chahine et al., 1990) and the interferometer, GOES High Resolution Interferometer Sounder (GHIS), (Smith et al., 1991) can provide these unique infrared spectra which enable us to conduct this analysis. In this calculation only the total random retrieval error component is presented. The systematic error components contributed by the forward and inverse model error are not considered (subject of further studies). The total random errors, which are composed of null space error (vertical resolution component error) and measurement error (instrument noise component error), are computed by assuming one wavenumber spectral resolution with wavenumber span from 1100 cm(exp -1) to 2300 cm(exp -1) (the band 600 cm(exp -1) to 1100 cm(exp -1) is not used since there is no major absorption of our three gases here) and measurement noise of 0.25 degree at reference temperature of 260 degree K. Temperature, water vapor, ozone and mixing ratio profiles of nitrous oxide, carbon monoxide and methane are taken from 1976 US Standard Atmosphere conditions (a FASCODE model). Covariance matrices of the gases are 'subjectively' generated by assuming 50 percent standard deviation of gaussian perturbation with respect to their US Standard model profiles. Minimum information and maximum likelihood retrieval solutions are used.

Huang, Hung-Lung↗

NASA NTRS2020

Studies in Astronomical Time Series Analysis: VII. An Enquiry Concerning Non-Linearity, the RMS-Mean Flux Relation, and log-Normal Flux Distributions

A broad and widely used class of stationary, linear, additive time series models can have statistical properties which many authors have asserted imply that the underlying process must be non-linear, non-stationary, multiplicative, or inconsistent with shot noise. This result is demonstrated with exact and numerical evaluation of the model flux distribution function and dependence of flux standard deviation on mean flux (here and in the literature called the rms-flux relation). These models can: (1) exhibit normal, log-normal or other flux distributions; (2) show linear or slightly non-linear rms-mean flux dependencies; as well as (3) match arbitrary second order statistics of the time series data. Accordingly the above assertions cannot be made on the basis of statistical time series analysis alone. Also idscussed are ambiguities in the meaning of terms relevant to this study – linear, stationary and multiplicative – and functions that can transform observed fluxes to a normal distribution as well or better than the logarithm.

Jeffrey D Scargle↗

NASA NTRS2012

Comparison of Predictive Modeling Methods of Aircraft Landing Speed

Expected increases in air traffic demand have stimulated the development of air traffic control tools intended to assist the air traffic controller in accurately and precisely spacing aircraft landing at congested airports. Such tools will require an accurate landing-speed prediction to increase throughput while decreasing necessary controller interventions for avoiding separation violations. There are many practical challenges to developing an accurate landing-speed model that has acceptable prediction errors. This paper discusses the development of a near-term implementation, using readily available information, to estimate/model final approach speed from the top of the descent phase of flight to the landing runway. As a first approach, all variables found to contribute directly to the landing-speed prediction model are used to build a multi-regression technique of the response surface equation (RSE). Data obtained from operations of a major airlines for a passenger transport aircraft type to the Dallas/Fort Worth International Airport are used to predict the landing speed. The approach was promising because it decreased the standard deviation of the landing-speed error prediction by at least 18% from the standard deviation of the baseline error, depending on the gust condition at the airport. However, when the number of variables is reduced to the most likely obtainable at other major airports, the RSE model shows little improvement over the existing methods. Consequently, a neural network that relies on a nonlinear regression technique is utilized as an alternative modeling approach. For the reduced number of variables cases, the standard deviation of the neural network models errors represent over 5% reduction compared to the RSE model errors, and at least 10% reduction over the baseline predicted landing-speed error standard deviation. Overall, the constructed models predict the landing-speed more accurately and precisely than the current state-of-the-art.

Diallo, Ousmane H.↗

NASA NTRS2022

Soil Carbon Losses Reduce Soil Moisture in Global Climate Model Simulations

Most agricultural soils have experienced substantial soil organic carbon losses in time. These losses motivate recent calls to restore organic carbon in agricultural lands to improve biogeochemical cycling and for climate change mitigation. Declines in organic carbon also reduce soil infiltration and water holding capacity, which may have important effects on regional hydrology and climate. To explore the regional hydroclimate impacts of soil organic carbon changes, we conduct new global climate model experiments with NASA Goddard Institute for Space Studies ModelE that include spatially explicit soil organic carbon concentrations associated with different human land management scenarios. Compared to a “no land use” case, a year 2010 soil degradation scenario, in which organic carbon content (OCC; weight %) is reduced by a factor of ∼0.12 on average across agricultural soils, resulted in soil moisture losses between 0.5 and 1 temporal standard deviations over eastern Asia, northern Europe, and the eastern United States. In a more extreme idealized scenario where OCC is reduced uniformly by 0.66 across agricultural soils, soil moisture losses exceed one standard deviation in both hemispheres. Within the model, these soil moisture declines occur primarily due to reductions in porosity (and to a lesser extent infiltration) that overall soil water holding capacity. These results demonstrate that changes in soil organic carbon can have meaningful, large-scale effects on regional hydroclimate and should be considered in climate model evaluations and developments. Further, this also suggests that soil restoration efforts targeting the carbon cycle are likely to have additional benefits for improving drought resilience.

Atmosphere-land interaction↗

NASA NTRS1988

The GISS global climate-middle atmosphere model. II - Model variability due to interactions between planetary waves, the mean circulation and gravity wave drag

The variability which arises in the GISS Global Climate-Middle Atmosphere Model on two time scales is reviewed: interannual standard deviations, derived from the five-year control run, and intraseasonal variability as exemplified by statospheric warnings. The model's extratropical variability for both mean fields and eddy statistics appears reasonable when compared with observations, while the tropical wind variability near the stratopause may be excessive possibly, due to inertial oscillations. Both wave 1 and wave 2 warmings develop, with connections to tropospheric forcing. Variability on both time scales results from a complex set of interactions among planetary waves, the mean circulation, and gravity wave drag. Specific examples of these interactions are presented, which imply that variability in gravity wave forcing and drag may be an important component of the variability of the middle atmosphere.

Rind, D.↗

NASA NTRS1989

Angular radiation models for earth-atmosphere system. Volume 2: Longwave radiation

The longwave angular radiation models that are required for analysis of satellite measurements of Earth radiation, such as those from the Earth Radiation Budget Experiment (ERBE) are presented. The models contain limb-darkening characteristics and mean fluxes. Limb-darkening characteristics are the longwave anisotropic factor and the standard deviation of the longwave radiance. Derivation of these models from the Nimbus 7 ERB (Earth Radiation Budget) data set is described. Tabulated values and computer-generated plots are included for the limb-darkening and mean-flux models.

Suttles, J. T.↗

NASA NTRS2010

A Comparison of Tropical Storm (TS) and Non-TS Gust Factors for Assessing Peak Wind Probabilities at the Eastern Range

Peak wind speed is an important forecast element to ensure the safety of personnel and flight hardware at Kennedy Space Center (KSC) and the Cape Canaveral Air Force Station (CCAFS) in East-Central Florida. The 45th Weather Squadron (45 WS), the organization that issues forecasts for the KSC/CCAFS area, finds that peak winds are more difficult to forecast than mean winds. This difficulty motivated the 45 WS to request two independent studies. The first (Merceret 2009) was the development of a reliable model for gust factors (GF) relating the peak to the mean wind speed in tropical storms (TS). The second (Lambert et al. 2008) was a climatological study of non-TS cool season (October-April) mean and peak wind speeds by the Applied Meteorology Unit (AMU; Bauman et al. 2004) without the use of GF. Both studies presented their statistics as functions of mean wind speed and height. Most of the few comparisons of TS and non-TS GF in the literature suggest that non-TS GF at a given height and mean wind speed are smaller than the corresponding TS GF. The investigation reported here converted the non-TS peak wind statistics calculated by the AMU to the equivalent GF statistics and compared them with the previous TS GF results. The advantage of this effort over all previously reported studies of its kind is that the TS and non-TS data were taken from the same towers in the same locations. This eliminates differing surface attributes, including roughness length and thermal properties, as a major source of variance in the comparison. The goal of this study is two-fold: to determine the relationship between the non-TS and TS GF and their standard deviations (GFSD) and to determine if models similar to those developed for TS data in Merceret (2009) could be developed for the non-TS environment. The results are consistent with the literature, but include much more detailed, quantitative information on the nature of the relationship between TS and non-TS GF and GFSD as a function of height and mean wind speed.

Merceret, Francis J.↗