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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

A new parameterization of an empirical model for wind/ocean scatterometry

The power law form of the SEASAT A Scatterometer System (SASS) empirical backscatter-to-wind model function does not uniformly meet the instrument performance over the range 4 to 24 /ms. Analysis indicates that the horizontal polarization (H-Pol) and vertical polarization (V-Pol) components of the benchmark SASS1 model function yield self-consistent results only for a small mid-range of speeds at larger incidence angles, and for a somewhat larger range of speeds at smaller incidence angles. Comparison of SASS1 to in situ data over the Gulf of Alaska region further underscores the shortcomings of the power law form. Finally, a physically based empirical SASS model is proposed which corrects some of the deficiencies of power law models like SASS1. The new model allows the mutual determination of sea surface wind stress and wind speed in a consistent manner from SASS backscatter measurements.

Woiceshyn, P. M.↗
NASA NTRS1984

Infrared parameterization and simple climate models

The geographical distribution of the annual mean and the annual cycle in surface temperature and satellite-observed IR is examined, and the spherical harmonic representation of the data fields is exploited to demonstrate how variances and covariances are dominated by the largest space and time scales. The geographical distribution of the annual cycle in the T and IR fields is explored; the strong imprint of the continents in both is clearly evident. The influence of the cloudiness of seasonal precipitation regimes on the IR annual cycle is also quite striking, especially over the subtropics. Analysis of the data shows that the simple form IR = A+BT (with A = 204 W/sq m and B = 1.93 W/sq m/K) explains 90 percent of the area-weighted variance in the annual mean and annual cycle of the zonally averaged IR field.

Short, D. A.↗
NASA NTRS1986

The necessity for a new parameterization of an empirical model for wind/ocean scatterometry

Difficulties related to the paucity of weather observation data regarding oceans were potentially alleviated for three summer months in 1978 when NASA's Seasat telemetered data from three wind-measuring instruments. The present study is concerned with one of these instruments, the Seasat A Scatterometer System (SASS). Attention is given to an internal consistency check of the SASS 1 model, comparisons of SASS 1 and other model-predicted winds with in situ winds, and a brief summary of the principal findings. It is found that a new wind retrieval system is required if SASS wind data are to be globally applicable and, at the same time, are to meet the required performance specifications. The sum-of-squares (SOS) technique for inverting SASS NRCS (normalized radar cross section) measurements results in the discarding of valuable data in low-speed areas and for higher incidence angles.

Woiceshyn, P. M.↗
NASA NTRS2023

Role of Snowfall Versus Air Temperatures for Greenland Ice Sheet Melt-Albedo Feedbacks

The Greenland Ice Sheet is a leading contributor to global sea-level rise because climate warming has enhanced surface meltwater runoff. Melt rates are particularly sensitive to air temperatures due to feedbacks with albedo. The primary melt-albedo feedback, fluctuation of seasonal snowlines, however, is determined not only by melt but also by antecedent snowfall which could delay the onset of dark glacier ice exposure. Here we investigate the role of snowfall versus air temperatures on ice sheet melt-albedo feedbacks using satellite remote sensing and atmospheric reanalysis data. We find several lines of evidence that snowline fluctuations are driven primarily by air temperatures and that snowfall is a secondary control. First, standardized linear regressions indicate that the timing of glacier ice exposure is nearly twice as sensitive to air temperatures than antecedent snowfall. Second, in 74% of the ablation zone by area, winter snowfall rates are not significantly correlated with winter air temperatures. This relationship implies that ice sheet melt due to climate warming is unlikely to be compensated by higher snowfall rates in the ablation zone. Third, we find no significant change in snowfall rates in the ablation zone during our 1981–2021 study period. Our findings demonstrate that snowfall is unlikely to reduce future ice sheet melt and that ice sheet meltwater runoff should be accurately predicted by air temperatures. Although given the importance of melt-albedo feedbacks, ice sheet models that parameterize albedo or are coupled with regional climate models are likely to provide the most accurate projections of mass loss.

J. C. Ryan↗
DOE OSTI2020

Simulation and Emulation of X-Ray Diffraction from Dynamic Compression Experiments

Many important aspects of the dynamic thermo-mechanical response of materials occur at the mesoscale, i.e. a physical scale of interactions smaller than what can be adequately described by homogenous behaviors, yet larger than the scale of the atomic lattice. Concurrent advancements in computational power, continuum theory, and experimental diagnostics are enabling unprecedented understanding of such interactions. However, we cannot develop a sufficient level of confidence in such mesoscale capability until the constitutive description of the underlying constituents is reliably representative of their actual physical behavior. Therefore, there is a strong need to combine experimental, modeling, and data-science techniques to validate models of the thermomechanical response of individual single crystals. One experimental diagnostic with high potential impact to shock physics and materials science is in-situ x-ray diffraction. This paper is primarily focused on simulation of x-ray diffraction in shock physics, but with an aim toward quantifying parametric uncertainty of simulation models. Here, we develop and demonstrate a data-science and model-driven approach to constrain the parameterization of continuum models of crystal lattice deformation associated with the shock response of crystalline materials. The framework is built around the connection between continuum hydrodynamic simulations of lattice deformation and a new Bragg diffraction simulation code, BarberShop. The dynamic deformation of a crystal lattice is modeled using the DiscoFlux model within an arbitrary Lagrangian-Eulerian hydrodynamic code, FLAG. These detailed continuum simulations of lattice deformation can be computationally slow, thus a statistical model is used to emulate the evolution of lattice deformation fields in time and across the considered model parameter space. Emulated lattice deformation fields can then be generated rapidly for any combination of physics model parameters. In turn, these fields can be fed into BarberShop to realize a rapid prediction of Bragg diffraction patterns associated with particular values of physics model parameters. The framework enables parameterization of the single crystal model to obtain Bragg diffraction patterns that most closely resemble a corresponding measurement. Furthermore, the framework naturally provides sensitivities of the lattice deformation to the physics parameters. We highlight the utility of this framework through the application to a synthetic closed-loop inverse problem leading to the parameterization of a single crystal material model. As a model problem, we consider the dynamic response of the energetic molecular crystal, cyclotrimethylenetrinitramine (or RDX), under dynamic compression induced by simulated flyer plate impact experiments.

36 MATERIALS SCIENCE↗
NASA NTRS1997

Comparison of Ice Cloud Particle Sizes Retrieved From Satellite Data Derived From In Situ Measurements

Cloud microphysical parameterizations have attracted a great deal of attention in recent years due to their effect on cloud radiative properties and cloud-related hydrological processes in large-scale models. The parameterization of cirrus particle size has been demonstrated as an indispensable component in the climate feedback analysis. Therefore, global-scale, long-term observations of cirrus particle sizes are required both as a basis of and as a validation of parameterizations for climate models. While there is a global scale, long-term survey of water cloud droplet sizes (Han et al. 1994), there is no comparable study for cirrus ice crystals. In this paper a near-global survey of cirrus ice crystal sizes is conducted using ISCCP satellite data analysis. The retrieval scheme uses phase functions based upon hexagonal crystals calculated by a ray tracing technique. The results show that global mean values of D(e) are about 60 micro-m. This study also investigates the possible reasons for the significant difference between satellite retrieved effective radii (approx. 60 micro-m) and aircraft measured particle sizes (approx. 200 micro-m) during the FIRE I IFO experiment. They are (1) vertical inhomogeneity of cirrus particle sizes; (2) lower limit of the instrument used in aircraft measurements; (3) different definitions of effective particle sizes; and (4) possible inappropriate phase functions used in satellite retrieval.

Han, Qingyuan↗
NASA NTRS1997

Comparison of Ice Cloud Particle Sizes Retrieved from Satellite Data Derived from In Situ Measurements

Cloud microphysical parameterizations have attracted a great deal of attention in recent years due to their effect on cloud radiative properties and cloud-related hydrological processes in large-scale models. The parameterization of cirrus particle size has been demonstrated as an indispensable component in the climate feedback analysis. Therefore, global-scale, long-term observations of cirrus particle sizes are required both as a basis of and as a validation of parameterizations for climate models. While there is a global scale, long-term survey of water cloud droplet sizes (Han et al.), there is no comparable study for cirrus ice crystals. This study is an effort to supply such a data set.

Han, Qingyuan↗
DOE OSTI2023

Carbon Organisms Rhizosphere and Protection in Soil Environment model script and input data for soil moisture-respiration responses in tropical forests

Objectives: Climatic drying is predicted for many tropical forests, yet models remain poorly parameterized for tropical forests, hampering predictions of forest-climate feedbacks. We applied an integrated model–experiment approach, parameterizing an ecosystem model Carbon Organisms Rhizosphere and Protection in the Soil Environment (CORPSE) with tropical forest observational data, and comparing model predictions with a field drying manipulation. We hypothesized that drying would suppress soil CO2 fluxes (i.e., respiration) in already-drier tropical forests, but increases CO2 fluxes in wetter tropical forests by alleviating anaerobiosis. We measured soil CO2 fluxes, soil moisture, soil temperature, and forest floor biomass during wet-dry cycles (2015 – 2022) in four Panamanian forests that vary in rainfall and soil fertility. We used the field data to parameterize and run tests in the model.Results: Measured CO2 fluxes declined in the dry season and peaked in the early wet season ahead of peak soil moisture, resulting in a lower soil moisture optimum for respiration than previously modeled. We used this data to parameterize the model, which then predicted increased soil CO2 fluxes in wetter and fertile forests with drying, and decreased fluxes in drier, infertile forests. In contrast to model predictions, a chronic throughfall exclusion experiment in the forests initially suppressed soil CO2 fluxes across forests, with sustained suppression after four years in the wettest forest only (-28 ± 4% during the dry season), but elevated soil CO2 fluxes in a fertile forest after four years (+75 ± 28% during the late wet season), as predicted by the model. The unexpected negative drying effect in the wettest, most infertile forest could have resulted from reduced vertical flushing of nutrients into soils. Including hydro-nutrient interactions in ecosystem models could improve predictions of tropical forest-climate feedbacks (results presented in Cusack et al. 2023). Datasets included: Code files:CORPSE_array.py: Defines the equations of the CORPSE modelCORPSE_solvers: Functions for running the CORPSE model using either iterative or ordinary differential equation (ODE) solversrun_Panama_sims.py: Read in datasets and run the model simulations for this studyInput data:PanamaGradientEcosystemChem_BT_CPools_20152016CO2_DC_20190615.xlsx: Plot characteristics used in running model simulationsLiCor compiled surface flux only to 2020_03 DC_20200825.xlsx: Surface gas exchange fluxes used in model-data comparisonsPARCHED litterfall data for Ben Sulman LD 20200902.xlsx: Litterfall data used to drive model simulationsInitialization data:state_500y_20190823.csv: Initial state of model pools based on previous spinup runsOutput data:Outputs/prev_moisture_response.csv: Simulations of multiple sites using original model moisture response function.Outputs/updated_moisture_response.csv: Simulations of multiple sites using updated model moisture response function.Outputs/dry15_prev_moisture_response.csv: Simulations with soil moisture reduced by 15%, using original moisture response function.Outputs/dry15_updated_moisture_response.csv: Simulations with soil moisture reduced by 15%, using updated moisture response function.Outputs/dry30_prev_moisture_response.csv: Simulations with soil moisture reduced by 30%, using original moisture response function.Outputs/dry30_updated_moisture_response.csv: Simulations with soil moisture reduced by 30%, using updated moisture response function.Outputs/latestart_prev_moisture_response.csv: Simulations with extended dry season, using original moisture response function.Outputs/latestart_updated_moisture_response.csv: Simulations with extended dry season, using updated moisture response function.Outputs/[site name]_oneyear.csv: One-year simulation for each site in expanded site list using original moisture response function.Outputs/[site name]_oneyear_dried.csv: One-year simulation for each site in expanded site list using original moisture response function, with soil moisture reduced by 25%.Outputs/[site name]_oneyear_updated_moisture_response.csv: One-year simulation for each site in expanded site list using updated moisture response function.Outputs/[site name]_oneyear_updated_moisture_response_dried.csv: One-year simulation for each site in expanded site list using updated moisture response function, with soil moisture reduced by 25%.Field plot location data:There is also a .kml file that includes coordinates for all 32 plots included in the study of four forests (n = 4 throughfall reduction and n = 4 control plots per site).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Quantum Drude oscillators coupled with Coulomb potential as an efficient model for bonded and non-covalent interactions in atomic dimers

The quantum Drude oscillator (QDO) model has been widely used as an efficient surrogate to describe the electric response properties of matter as well as long-range interactions in molecules and materials. Most commonly, QDOs are coupled within the dipole approximation so that the Hamiltonian can be exactly diagonalized, which forms the basis for the many-body dispersion method [Phys. Rev. Lett. 108, 236402 (2012)]. The dipole coupling is efficient and allows us to study non-covalent many-body effects in systems with thousands of atoms. However, there are two limitations: (i) the need to regularize the interaction at short distances with empirical damping functions and (ii) the lack of multipolar effects in the coupling potential. In this work, we convincingly address both limitations of the dipole-coupled QDO model by presenting a numerically exact solution of the Coulomb-coupled QDO model by means of quantum Monte Carlo methods. We calculate the potential-energy surfaces of homogeneous QDO dimers, analyzing their properties as a function of the three tunable parameters: frequency, reduced mass, and charge. We study the coupled-QDO model behavior at short distances and show how to parameterize this model to enable an effective description of chemical bonds, such as the covalent bond in the H2 molecule.

Chemistry↗
NASA NTRS1981

Calculation of surface temperature and surface fluxes in the GLAS GOM

Because the GLAS model's surface fluxes of sensible and latent heat exhibit strong 2 delta t oscillations at the individual grid points as well as in the zonal hemispheric averages and because a basic weakness of the GLAS model lower evaporation over oceans and higher evaporation over land in a typical monthly simulation, the GLAS model PBL parameterization was changed to calculate the mixed layer temperature gradient by solution of a quadratic equation for a stable PBL and by a curve fit relation for an unstable PBL. The new fluxes without any 2 delta t oscillation. Also, the geographical distributions of the surface fluxes are improved. The parameterization presented is incorporated into the new GLAS climate model. Some results which compare the evaporation over land and ocean between old and new calculations are appended.

Sud, Y. C.↗
DOE OSTI2016

Global parameterization and validation of a two-leaf light use efficiency model for predicting gross primary production across FLUXNET sites: TL-LUE Parameterization and Validation

We present the first extended validation of satellitemicrowave (MW) liquidwater path (LWP) for low nonprecipitating clouds, from four operational sensors, against ship-borne observations from a three-channel MW radiometer collected along ship transects over the northeast Pacific during May–August 2013. Satellite MW retrievals have an overall correlation of 0.84 with ship observations and a bias of 9.3 g/m2. The bias for broken cloud scenes increases linearly with water vapor path and remains below 17.7 g/m2. In contrast, satelliteMWLWP is unbiased in overcast scenes with correlations up to 0.91, demonstrating that the retrievals are accurate and reliable under these conditions. Satellite MW retrievals produce a diurnal cycle amplitude consistent with ship-based observations (33 g/m2). Observations taken aboard extended ship cruises to evaluate not only satellite MW LWP but also LWP derived from visible/infrared sensors offer a new way to validate this important property over vast oceanic regions.

Zhou, Yanlian↗
NASA NTRS1994

Impact of stratospheric aircraft on calculations of nitric acid trihydrate cloud surface area densities using NMC temperatures and 2D model constituent distributions

A parameterization of NAT (nitric acid trihydrate) clouds is developed for use in 2D models of the stratosphere. The parameterization uses model distributions of HNO3 and H2O to determine critical temperatures for NAT formation as a function of latitude and pressure. National Meteorological Center temperature fields are then used to determine monthly temperature frequency distributions, also as a function of latitude and pressure. The fractions of these distributions which fall below the critical temperatures for NAT formation are then used to determine the NAT cloud surface area density for each location in the model grid. By specifying heterogeneous reaction rates as functions of the surface area density, it is then possible to assess the effects of the NAT clouds on model constituent distributions. We also consider the increase in the NAT cloud formation in the presence of a fleet of stratospheric aircraft. The stratospheric aircraft NO(x) and H2O perturbations result in increased HNO3 as well as H2O. This increases the probability of NAT formation substantially, especially if it is assumed that the aircraft perturbations are confined to a corridor region.

Considine, David B.↗