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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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857 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Exploring the Climatic Impact of Bi-Modal Dust Particle Size Distributions During the MY34/2018 Global Dust Storm with the NASA Ames Mars Global Climate Model.

We have implemented a bi-modal dust lifting scheme in the NASA Ames Mars Global Climate Model (GCM) and investigated the climatic impact on the MY34/2018 Global Dust Storm (GDS). We found that the climate is measurably responsive to the inclusion of a second, smaller dust mode. Dust tends to be lifted through a deeper column in the atmosphere, which is reflected in the climate as changes to atmospheric temperature, tide amplitudes, and surface temperatures. Adding a modest fraction of a smaller dust mode improves simulations during the GDS compared to Curiosity semi-diurnal tide observations as well as Mars Climate Sounder (MCS) T15 brightness temperatures

R A Urata↗
NASA NTRSDate not supplied

Toward NASA/GMAO Coupled Data Assimilation Using JEDI

NASA’s Global Modeling and Assimilation Office (GMAO) is establishing coupled Earth system capabilities using the Joint Effort for Data Assimilation Integration (JEDI) framework, developed in collaboration with the Joint Center for Satellite Data Assimilation(JCSDA). Marine and atmospheric components will utilize a weakly-coupled data assimilation approach. The implementation of the sea-ice, ocean, and coupled analysis (SOCA) component of JEDI is highlighted here, while parallel work on atmospheric data assimilation is also in progress. Improvements to the ocean data assimilation system (ODAS) include: 1) adopting the JEDI framework, 2) a new coupled GCM, and 3) incorporation of new observation sources.

Dorukhan Ardağ↗
NASA NTRS2011

Global Precipitation Measurement: Methods, Datasets and Applications

This paper reviews the many aspects of precipitation measurement that are relevant to providing an accurate global assessment of this important environmental parameter. Methods discussed include ground data, satellite estimates and numerical models. First, the methods for measuring, estimating, and modeling precipitation are discussed. Then, the most relevant datasets gathering precipitation information from those three sources are presented. The third part of the paper illustrates a number of the many applications of those measurements and databases. The aim of the paper is to organize the many links and feedbacks between precipitation measurement, estimation and modeling, indicating the uncertainties and limitations of each technique in order to identify areas requiring further attention, and to show the limits within which datasets can be used.

Global Climate Models (GCM)↗
NASA NTRS2013

How Well Do Global Climate Models Simulate the Variability of Atlantic Tropical Cyclones Associated with ENSO?

The variability of Atlantic tropical cyclones (TCs) associated with El Nino-Southern Oscillation (ENSO) in model simulations is assessed and compared with observations. The model experiments are 28-yr simulations forced with the observed sea surface temperature from 1982 to 2009. The simulations were coordinated by the U.S. CLIVAR Hurricane Working Group and conducted with five global climate models (GCMs) with a total of 16 ensemble members. The model performance is evaluated based on both individual model ensemble means and multi-model ensemble mean. The latter has the highest anomaly correlation (0.86) for the interannual variability of TCs. Previous observational studies show a strong association between ENSO and Atlantic TC activity, as well as distinctions in the TC activities during eastern Pacific (EP) and central Pacific (CP) El Nino events. The analysis of track density and TC origin indicates that each model has different mean biases. Overall, the GCMs simulate the variability of Atlantic TCs well with weaker activity during EP El Nino and stronger activity during La Nina. For CP El Nino, there is a slight increase in the number of TCs as compared with EP El Nino. However, the spatial distribution of track density and TC origin is less consistent among the models. Particularly, there is no indication of increasing TC activity over the U.S. southeast coastal region as in observations. The difference between the models and observations is likely due to the bias of vertical wind shear in response to the shift of tropical heating associated with CP El Nino, as well as the model bias in the mean circulation.

Tropical Cyclones↗
NASA NTRS2014

Characteristics of Tropical Cyclones in High-Resolution Models of the Present Climate

The global characteristics of tropical cyclones (TCs) simulated by several climate models are analyzed and compared with observations. The global climate models were forced by the same sea surface temperature (SST) in two types of experiments, using a climatological SST and interannually varying SST. TC tracks and intensities are derived from each model's output fields by the group who ran that model, using their own preferred tracking scheme; the study considers the combination of model and tracking scheme as a single modeling system, and compares the properties derived from the different systems. Overall, the observed geographic distribution of global TC frequency was reasonably well reproduced. As expected, with the exception of one model, intensities of the simulated TC were lower than in observations, to a degree that varies considerably across models.

Typical Cyclone↗
NASA NTRS2019

Venus Topography and Boundary Conditions in 3D General Circulation Modeling

We describe how one ingests 3D topographic data from NASA's Venus Magellan Spacecraft radar observations into the ROCKE-3D Planetary General Circulation Model. We also explain how boundary condition choices such as ocean/lake coverage/depth, rotation rate, atmospheric constituents, and other factors influence surface conditions in ROCKE-3D paleo-Venus simulations. Studies such as these should also be considered when examining liquid water habitability in similar exoplanet experiments.

topography↗
NASA NTRS2022

Assessment of Two Stochastic Cloud Subcolumn Generators Using Observed Fields of Vertically Resolved Cloud Extinction

We evaluate two stochastic subcolumn generators used in GCMs to emulate subgrid cloud variability enabling comparisons with satellite observations and simulations of certain physical processes. Our evaluation necessitated the creation of a reference observational dataset that resolves horizontal and vertical cloud variability. The dataset combines two CloudSat cloud products that resolve two-dimensional cloud optical depth variability of liquid, ice, and mixed phase clouds when blended at ~200 m vertical and ~ 2 km horizontal scales. Upon segmenting the dataset to individual “scenes”, mean profiles of the cloud fields are passed as input to generators that produce scene-level cloud subgrid variability. The assessment of generator performance at the scale of individual scenes and in a mean sense is largely based on inferred joint histograms that partition cloud fraction within predetermined combinations of cloud top pressure –cloud optical thickness ranges. Our main finding is that both generators tend to underestimate optically thin clouds, while one of them also tends to overestimate some cloud types of moderate and high optical thickness. Associated radiative flux errors are also calculated by applying a simple transformation to the cloud fraction histogram errors, and are found to approach values almost as high as 3 Wm-2 for the cloud radiative effect in the shortwave part of the spectrum.

cloud variability↗