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At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Stability Analysis of Interface Conditions for Ocean-Atmosphere Coupling

In this paper, we analyze the stability of different coupling strategies for multidomain PDEs that arise in general circulation models used in climate simulations. We focus on fully coupled ocean–atmosphere models that are needed to represent and understand the complicated interactions of these two systems, becoming increasingly important in climate change assessment in recent years. Numerical stability issues typically arise because of different time-stepping strategies applied to the coupled PDE system. In particular, the contributing factors include using large time steps, lack of accurate interface flux, and single-iteration coupling. We investigate the stability of the coupled ocean–atmosphere models for various interface conditions such as the Dirichlet–Neumann condition and the bulk interface condition, which is unique to climate modeling. By analyzing a simplified model, we demonstrate here how the parameterization of the bulk condition and other numerical and physical parameters affect the coupling stability and establish stability conditions for different coupling strategies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Local radiative feedbacks over the Arctic based on observed short-term climate variations

We compare various radiative feedbacks in response to short-term climate variations estimated from reanalysis, satellite, and global climate model datasets using the combined Kernel-Gregory approach over the Arctic (60-90°N). Except for the shortwave cloud feedback, all feedbacks are positive over the Arctic. Lapse rate feedback is comparable with surface albedo feedback. Relative to the tropics (30°S-30°N), the temperature feedback (lapse rate feedback plus Planck feedback deviation from its global mean) is the largest contributor to Arctic amplification among all feedbacks, followed by surface albedo feedback. The choice of meteorological fields has a small impact on the cloud feedback estimate, but different top-of-the-atmosphere clear-sky fluxes datasets can result in a wide spread of estimated cloud feedbacks. The net cloud feedback over the Arctic is positive due to a larger positive in longwave than the negative shortwave feedback, but has the largest uncertainty. Relative to the tropics, the longwave cloud feedback largely contributes to the Arctic amplification.

Zhang, Rudong↗
NASA NTRSDate not supplied

3D Radiative MHD Modeling of the Solar Atmospheric Dynamics and Structure

Dramatic dynamical phenomena accompanied by strong thermodynamic and magnetic structuring are the primary drivers of great interest in studying the solar atmosphere with high spatial and temporal resolutions. Using current computational capabilities, it has become possible to model the magnetized solar plasma in different regimes with a high degree of realism. To study the fine structuring of the solar atmosphere and dynamics, we use 3D MHD radiative models covering all layers from the upper convection zone to the corona. Realistic 3D radiative MHD modeling of the solar magnetoconvection and atmosphere allows us to generate synthetic observables that directly link the physical properties of the solar plasma to spectroscopic observables. In the presentation, we discuss qualitative and quantitative changes of the atmospheric structure and dynamics at different layers of the solar atmosphere, properties of acoustic and surface gravity waves, sources of local heating in the chromosphere-corona transition region, formation of shocks, and high-frequency oscillations in the corona, as well as manifestation of these phenomena in the modeled observables.

SMD↗
NASA NTRS2023

AgMIP-Wheat Multi-Model Simulations on Climate Change Impact and Adaptation for Global Wheat

The climate change impact and adaptation simulations from the Agricultural Model Intercomparison and Improvement Project (AgMIP) for wheat provide a unique dataset of multi-model ensemble simulations for 60 representative global locations covering all global wheat mega environments. The multi-model ensemble reported here has been thoroughly benchmarked against a large number of experimental data, including different locations, growing season temperatures, atmospheric CO2 concentration, heat stress scenarios, and their interactions. In this paper, we describe the main characteristics of this global simulation dataset. Detailed cultivar, crop management, and soil datasets were compiled for all locations to drive 32 wheat growth models. The dataset consists of 30-year simulated data including 25 output variables for nine climate scenarios, including Baseline (1980-2010) with 360 or 550 ppm CO2, Baseline +2oC or +4oC with 360 or 550 ppm CO2, a mid-century climate change scenario (RCP8.5, 571 ppm CO2), and 1.5°C (423 ppm CO2) and 2.0oC (487 ppm CO2) warming above the pre-industrial period (HAPPI). This global simulation dataset can be used as a benchmark from a well-tested multi-model ensemble in future analyses of global wheat. Also, resource use efficiency (e.g., for radiation, water, and nitrogen use) and uncertainty analyses under different climate scenarios can be explored at different scales. The DOI for the dataset is 10.5281/zenodo.4027033 (AgMIP-Wheat, 2020), and all the data are available on the data repository of Zenodo (http://doi.org/10.5281/zenodo.4027033). Two scientific publications have been published based on some of these data here.

Agricultural Model Intercomparison and Improvement↗
NASA NTRS1985

An evaluation and comparison of vertical profile data from the VISSR Atmospheric Sounder (VAS)

A statistical evaluation is used to compared vertical profiles of temperature and moisture derived from VISSR Atmospheric Sounder (VAS) with three different algorithms to that of corresponding rawinsonde measurements for a clear cold environment. To account for time and space discrepancies between the data sets, rawinsonde data were adjusted to be representative of the satellite sounding times. Both rawinsonde and satellite sounding data were objectively analyzed onto a mesoscale grid. These grid point values were compared at 50 mb pressure increments from the surface up to 100 mb. The data were analyed for horizontal and vertical structure, representatives of derived parameters, and significant departure (improvement) from the apriori (first guess) information. Results indicate some rather strong temperature and moisture biases exist in the satellite soundings. Temperature biases of 1 to 4 C and dewpoint biases of 2 to 6 C generally occur in layers where strong inversions are present and vary with time as these atmospheric features evolve. The biases also changes as a function retrieval scheme suggesting limitations and restrictions on the applications of the various techniques. Standard temperature deviations range from 1 to 2 C for each retrieval scheme with maximum values around 800 and 400 mb. Derived parameters (precipitable water and thickness) suffer from similar biases, though to a somewhat lesser extent. Gradients of basic and derived parameters are generally weaker but have good horizontal structure where magnitudes of the parameters are relatively strong. Integrated thermal (temperature) and moisture (precipitable water) parameters show mixed results.

Jedlovec, G. J.↗
NASA NTRS1985

An evaluation and comparison of vertical profile data from the VISSR Atmospheric Sounder (VAS)

A statistical evaluation is used to compared vertical profiles of temperature and moisture derived from VISSR Atmospheric Sounder (VAS) with three different algorithms to that of corresponding rawinsonde measurements for a clear cold environment. To account for time and space discrepancies between the data sets, rawinsonde data were adjusted to be representative of the satellite sounding times. Both rawinsonde and satellite sounding data were objectively analyzed onto a mesoscale grid. These grid point values were compared at 50 mb pressure increments from the surface up to 100 mb. The data were analyzed for horizontal and vertical structure, representatives of derived parameters, and significant departure (improvement) from the apriori (first guess) information. Results indicate some rather strong temperature and moisture biases exist in the satellite soundings. Temperature biases of 1 to 4 C and dewpoint biases of 2 to 6 C generally occur in layers where strong inversions are present and vary with time as these atmospheric features evolve. The biases also changes as a function retrieval scheme suggesting limitations and restrictions on the applications of the various techniques. Standard temperature deviations range from 1 to 2 C for each retrieval scheme with maximum values around 800 and 400 mb. Derived parameters (precipitable water and thickness) suffer from similar biases, though to a somewhat lesser extent. Gradients of basic and derived parameters are generally weaker but have good horizontal structure where magnitudes of the parameters are relatively strong. Integrated thermal (temperature) and moisture (precipitable water) parameters show mixed results.

Jedlovec, G. J.↗
NASA NTRS2012

Assess Calibration Consistency of MODIS and AVHRR Thermal Infrared Bands Using SNO Observations Corrected for Atmospheric Effects

Monitoring environmental changes from space requires extremely well-calibrated observations to achieve the necessary high accuracy and stability. The calibration differences between the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Very High Resolution Radiometer (AVHRR) thermal bands provide a valuable quality assessment of the instrument performance. This letter compares the calibration differences between the Aqua MODIS and NOAA-18 AVHRR bands at 11.0 and 12.0 /Lm using simultaneous nadir overpass observations obtained in nearly parallel orbits. Impacts due to the relative spectral-response differences between the two sensors are estimated by MODTRAN simulations with real-time atmospheric profiles of temperature, water vapor, atmospheric pressure and ozone, and surface skin temperatures. Results show that the temperature difference after the removal of atmospheric impacts is within 0.30 K (or 0.40% in radiance) across the effective calibration range (or the 1l.0 l'm band/channel. For the 12.0 pm band, the differences are OAO K (or 0.50%) at the typical radiance and up to 0.70 K (or 0.90%) close to the maximum radiance, indicating an excellent calibration consistency between MODIS and AVHRR for both bands.

Wu, Aisheng↗
NASA NTRS1992

Multi-resolution processing for fractal analysis of airborne remotely sensed data

Fractal geometry is increasingly becoming a useful tool for modeling natural phenomenon. As an alternative to Euclidean concepts, fractals allow for a more accurate representation of the nature of complexity in natural boundaries and surfaces. Since they are characterized by self-similarity, an ideal fractal surface is scale-independent; i.e. at different scales a fractal surface looks the same. This is not exactly true for natural surfaces. When viewed at different spatial resolutions parts of natural surfaces look alike in a statistical manner and only for a limited range of scales. Images acquired by NASA's Thermal Infrared Multispectral Scanner are used to compute the fractal dimension as a function of spatial resolution. Three methods are used to determine the fractal dimension - Schelberg's line-divider method, the variogram method, and the triangular prism method. A description of these methods and the results of applying these methods to a remotely-sensed image is also presented. Five flights were flown in succession at altitudes of 2 km (low), 6 km (mid), 12 km (high), and then back again at 6 km and 2 km. The area selected was the Ross Barnett reservoir near Jackson, Mississippi. The mission was flown during the predawn hours of 1 Feb. 1992. Radiosonde data was collected for that duration to profile the characteristics of the atmosphere. This corresponds to 3 different pixel sizes - 5m, 15m, and 30m. After, simulating different spatial sampling intervals within the same image for each of the 3 image sets, the results are cross-correlated to compare the extent of detail and complexity that is obtained when data is taken at lower spatial intervals.

Jaggi, S.↗
NASA NTRS2020

An Algorithm to Derive Temperature and Humidity Profile Changes Using Spatially and Temporally Averaged Spectral Radiance Differences

A linear inversion algorithm to derive changes of surface skin temperature and atmospheric temperature and specific humidity vertical profiles using spatially and temporally averaged spectral radiance differences is developed. The algorithm uses spectral radiative kernels, which is the top-of-atmosphere spectral radiance change caused by perturbations of skin temperature and air temperature and specific humidity in the atmosphere, and is an improved version of the algorithm used in earlier studies. Two improvements are the inclusion of the residual and cloud spectral kernels in the form of eigenvectors of principal components. Three and six eigenvectors are used for, respectively, the residual and cloud spectral kernels. An underlying assumption is that the spectral shape of the principal components is constant and their magnitude varies temporally and spatially. The algorithm is tested using synthetic spectral radiances with the spectral range of the Atmospheric Infrared Sounder averaged over 16 days and over a 10° × 10° grid box. Changes of skin temperature, air temperature, and specific humidity vertical profiles are derived from the difference of nadir-view all-sky spectral radiances. The root-mean-square difference of retrieved and true skin temperature differences is 0.59 K. The median of absolute errors in the air temperature change is less than 0.5 K above 925 hPa. The median of absolute errors in the relative specific humidity changes is less than 10% above 825 hPa.

Fang Pan↗
DOE OSTI2023

Effects of a nuclear-disturbed environment on electromagnetic wave propagation through the atmosphere

This paper investigates the effects of a nuclear-disturbed environment on the transmission of electromagnetic (EM) waves through the atmosphere. An atmospheric nuclear detonation can produce heightened free electron densities in the surrounding atmosphere that can disrupt EM waves that propagate through the disturbed region. Radiation transport models simulated the ionization and free electron densities created in the atmosphere from a 1 MT detonation at heights of burst of 5 km, 25 km, and 75 km. Recombination rates for the free electrons in the atmosphere were applied, from previous work in the literature, to determine the nuclear-induced electron densities as a function of time and space after the detonation. A ray-tracing algorithm was applied to determine the refraction and reflection of waves propagating in the different nuclear-disturbed environments. The simulation results show that the free electron plasma created from an atmospheric nuclear detonation depend on the height of burst of the weapon, the weapon yield, and the time after detonation. Detonations at higher altitudes produce higher free electron densities for greater durations and over larger ranges. The larger the free electron densities, the greater the impact on EM wavelengths in regards to refraction, reflection, and absorption in the atmosphere. An analysis of modern infrastructure and the effects of nuclear-disturbed atmospheres on different signal wavelengths and systems is discussed.

42 ENGINEERING↗
DOE OSTI2022

Better calibration of cloud parameterizations and subgrid effects increases the fidelity of the E3SM Atmosphere Model version 1

Abstract. Realistic simulation of the Earth's mean-state climate remains a major challenge, and yet it is crucial for predicting the climate system in transition. Deficiencies in models' process representations, propagation of errors from one process to another, and associated compensating errors can often confound the interpretation and improvement of model simulations. These errors and biases can also lead to unrealistic climate projections and incorrect attribution of the physical mechanisms governing past and future climate change. Here we show that a significantly improved global atmospheric simulation can be achieved by focusing on the realism of process assumptions in cloud calibration and subgrid effects using the Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1 (EAMv1). The calibration of clouds and subgrid effects informed by our understanding of physical mechanisms leads to significant improvements in clouds and precipitation climatology, reducing common and long-standing biases across cloud regimes in the model. The improved cloud fidelity in turn reduces biases in other aspects of the system. Furthermore, even though the recalibration does not change the global mean aerosol and total anthropogenic effective radiative forcings (ERFs), the sensitivity of clouds, precipitation, and surface temperature to aerosol perturbations is significantly reduced. This suggests that it is possible to achieve improvements to the historical evolution of surface temperature over EAMv1 and that precise knowledge of global mean ERFs is not enough to constrain historical or future climate change. Cloud feedbacks are also significantly reduced in the recalibrated model, suggesting that there would be a lower climate sensitivity when it is run as part of the fully coupled E3SM. This study also compares results from incremental changes to cloud microphysics, turbulent mixing, deep convection, and subgrid effects to understand how assumptions in the representation of these processes affect different aspects of the simulated atmosphere as well as its response to forcings. We conclude that the spectral composition and geographical distribution of the ERFs and cloud feedback, as well as the fidelity of the simulated base climate state, are important for constraining the climate in the past and future.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2003

Cloud-Resolving Model and GPM

Over the past twenty years, rainfall retrieval algorithms have been developed to retrieve rainfall and vertical hydrometeor structures from passive microwave observations by making use of the fact that weighting functions for various frequencies peak at different levels within a rainy atmosphere. GPROF is one of two TMI rainfall algorithms. It is physically based retrieval that finds the vertical hydrometeor profile that best fits the brightness temperatures in the available passive radiometer channels. Matching is achieved using a library of hydrometeor profiles generated by cloud-resolving models (CRMs). The hydrometeor profiles have a corresponding surface precipitation rate. The algorithm retrieves the hydrometeor profiles and associated surface rainfall using a Bayesian approach that gives the estimated expected values. The ability of CRMs to produce cloud structures that are reliable and representative of observed storms is crucial for the success of GPROF. The cloud mycrophysics are one of the keys to achieving this. In addition, CRMs have been a very useful tool for GPM-algorithm developers through Cloud-Radiation Simulations (CRS), one of the nine GPM disciplinary research themes. This paper will discuss how to generate consistent and comprehensive 4D cloud datasets from an improved (i.e., in regard to bulk and multi-moment microphysics) CRM for TRMM and GPM rainfall retrieval algorithm developers. These cloud datasets include CRM-simulated clouds and cloud systems from different geographic locations in the tropics and midlatitudes. By linking the CRM with a passive microwave radiative-transfer model and using satellite and airborne data, the performance of the "cloud physics" can be assessed and in turn modified and improved. This paper will also address how to assess and improve the performance of various latent and diabatic heating algorithms and develop an algorithm to retrieve the vertical structure of apparent moistening (Q2). Considering that the GPM will produce high (temporal and spatial) resolution heating and rainfall data, these algorithms will be used to obtain the temporal and spatial distributions of surface rainfall and the associated vertical heating and moistening profiles throughout the subtropical and midlatitudes.

Tao, Wei-Kuo↗
NASA NTRS1992

Atmospheric effects on cratering efficiency

The dramatic effects of an atmosphere on impact excavation of particulate targets are investigated, with emphasis on common trends and systematic differences for contrasting target types. The observed differences are reconciled through identification of additional atmospheric effects and consideration of scaling relations. When both static (ambient) and dynamic (drag) atmospheric pressure controls crater growth, the combined factors exhibit a functional dependence consistent with the coupling-parameter exponents suggested by Holsapple and Schmidt (1987). The disturbed air mass accompanying the projectile at laboratory scales is observed to further modify cratering efficiency. The effect of projectile-atmosphere interactions depends on the degree of coupling between the air disturbance and the impactor. At very high velocities (M greater than 10), the air disturbance changes the effective impactor dimension. If the dimensionless scaling parameters can be applied to broader planetary scales, these results have implications for interpreting the size of craters on surfaces with contrasting atmospheric envelopes.

Schultz, Peter H.↗
NASA NTRS1992

The slant path atmospheric refraction calibrator - An instrument to measure the microwave propagation delays induced by atmospheric water vapor

The water vapor-induced propagation delay experienced by a radio signal traversing the atmosphere is characterized by the Slant Path Atmospheric Refraction Calibrator (SPARC), which measures the difference in the travel times between an optical and a microwave signal propagating along the same atmospheric path with an accuracy of 15 picosec or better. Attention is given to the theoretical and experimental issues involved in measuring the delay induced by water vapor; SPARC measurements conducted along a 13.35-km ground-based path are presented, illustrating the instrument's stability, precision, and accuracy.

Walter, Steven J.↗
NASA NTRS2000

Comment on "Heterodyne Lidar Returns in the Turbulent Atmosphere: Performance Evaluation of Simulated Systems"

The explanation for the difference between simulation and the zero-order theory for heterodyne lidar returns in a turbulent atmosphere proposed by Belmonte and Rye is incorrect. The theoretical expansion is not developed under a square- law-structure function approximation (random wedge atmosphere). Agreement between the simulations and the zero-order term of the theoretical expansion is produced for the limit of statistically independent paths (bi-static operation with large transmitter-receiver separation) when the simulations correctly include the large-scale gradients of the turbulent atmosphere.

Frehlich, Rod↗
NASA NTRS2003

A Possible Bifurcation in Atmospheres of Strongly Irradiated Stars and Planets

We show that under certain circumstances the differences between the absorption mean and Planck mean opacities can lead to multiple solutions for an LTE atmospheric structure. Since the absorption and Planck mean opacities are not expected to differ significantly in the usual case of radiative equilibrium, nonirradiated atmospheres, the most interesting situations in which the effect may play a role are strongly irradiated stars and planets, and also possibly structures in which there is a significant deposition of mechanical energy, such as stellar chromospheres and accretion disks. We have presented an illustrative example of a strongly irradiated giant planet in which the bifurcation effect is predicted to occur for a certain range of distances from the star.

Hubeny, Ivan↗
NASA NTRS2004

Radicals and Reservoirs in the GMI Chemistry and Transport Model: Comparison to Measurements

The most important use of atmospheric chemistry and transport models is to predict the future composition of the atmosphere. The amounts of gases like chlorofluorcarbons, methyl bromide, nitrous oxide and methane are changing and the stratospheric ozone layer will change because these gases are changing. Methyl bromide, nitrous oxide and methane all have natural sources, and also change because of human activity. Chlorofluorcarbons are man-made gases; these are known to decrease stratospheric ozone and future production is banned. They are long-lived gases, and many decades will pass before they are insignificant in the atmosphere. The models are used to predict changes in ozone and other gases; this is a straightforward application. The models must be also tested using observations for the present day atmosphere. This is a challenging task, because the model contains more than 50 species and more than 150 chemical reactions. Data from satellites, ground stations, aircraft and balloons are used to evaluate the model. Different models that are used in international assessments produce different results; in the most recent assessment some predict that ozone will return to 1980 levels by 2025 and others predict that this will not happen until 2050. Since all the parts of the models are conceptually the same, there must be differences in implementation that produce these differences, This work takes a single model, two different sets of winds and temperatures, and repeats the same prediction for the future. Here we compare the results for these two simulations with many observations. The purpose is to identify differences in the model results for the present atmosphere that will lead to different predictions. This sort of controlled comparison will reduce uncertainty in the predictions for stratospheric ozone.

Douglas, Anne R.↗
NASA NTRS1981

Atmospheric media effects on ARIES baseline determination

Different types of media effects on ARIES baseline determination are compared. The effectiveness of simple ionospheric calibration models are studied. To perform the covariance analysis, an ARIES observation sequence needs to be assumed. For the current purposes, the observation sequence is selected to be that of experiment 80D over the JPL/Goldstone baseline (approximately 180 km). This experiment consisted of 96 observations over a period of approximately 25 hours on March 25 to 26, 1980. It is found through covariance analyses that the component most sensitive to media depends heavily upon the correlation, between the two stations, of the media effects. It is also found that relying on the cancellation of ionospheric delays between the two ray paths of VLBI observations at S band results in a large error in baseline length determination. High degree removal of ionospheric effects is possible with a crude model, providing correct diurnal peak and minimum ionospheric levels are input.

Wu, S. C.↗