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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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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Analysis of Near-Cloud Changes in Atmospheric Aerosols Using Satellite Observations and Global Model Simulations

This paper examines cloud-related variations of atmospheric aerosols that occur in partly cloudy regions containing low-altitude clouds. The goal is to better understand aerosol behaviors and to help better represent the radiative effects of aerosols on climate. For this, the paper presents a statistical analysis of a multi-month global dataset that combines data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite instruments with data from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) global reanalysis. Among other findings, the results reveal that near-cloud enhancements in lidar backscatter (closely related to aerosol optical depth) are larger (1) over land than ocean by 35%, (2) near optically thicker clouds by substantial amounts, (3) for sea salt than for other aerosol types, with the difference from dust reaching 50%. Finally, the study found that mean lidar backscatter is higher near clouds not because of large-scale variations in meteorological conditions, but because of local processes associated with individual clouds. The results help improve our understanding of aerosol-cloud-radiation interactions and our ability to represent them in climate models and other atmospheric models

aerosol↗
NASA NTRS2001

Improving Global Modeling and Data Analysis Using Remotely-Sensed Rainfall Data: Lessons From TRMM and Plans for GPM

I will discuss the need for accurate rainfall observations to improve our ability to model the earth's climate and improve short-range weather forecasts. I will give an overview of the recent progress in using of rainfall data provided by TRMM and other microwave instruments in data assimilation to improve global analyses and diagnose state-dependent systematic errors in physical parameterizations. I will outline the current and future research strategies in preparation for the Global Precipitation Mission.

Hou, Arthur Y.↗
NASA NTRS1984

Development of a global model for atmospheric backscatter at CO2 wavelengths

The effect of aerosol microphysical processes on the backscatter from an aerosol plume undergoing long-range atmospheric transport was studied. A numerical model which examines the effects of coagulation and sedimentation on an aerosol size distribution is under development and the initial results for a single homogeneous layer were obtained. Use was made of the SAGE/SAM II data set to study the global variation of aerosol concentration and, hence, to predict the variation of Beta sub CO2. Computer programs were written to determine the mean, median, and the probability distribution of the measured aerosol extinction as a function of altitude, latitude and geographical conditions. The first data sets analyzed in this way are under study. Data was used to study aerosol behavior over the U.S.A. and the Pacific Ocean.

Kent, G. S.↗
NASA NTRS2010

Finding the Missing Stratospheric Br(sub y): A Global Modeling Study of CHBr3 and CH2Br2

Recent in situ and satellite measurements suggest a contribution of ~5 pptv to stratospheric inorganic bromine from short-lived bromocarbons. We conduct a modeling study of the two most important short-lived bromocarbons, bromoform (CHBr3) and dibromomethane (CH2Br2), with the Goddard Earth Observing System Chemistry Climate Model (GEOS CCM) to account for this missing stratospheric bromine. We derive a "top-down" emission estimate of CHBr3 and CH2Br2 using airborne measurements in the Pacific and North American troposphere and lower stratosphere obtained during previous NASA aircraft campaigns. Our emission estimate suggests that to reproduce the observed concentrations in the free troposphere, a global oceanic emission of 425 Gg Br yr(exp -1) for CHBr3 and 57 Gg Br yr(exp -l) for CH2Br2 is needed, with 60% of emissions from open ocean and 40% from coastal regions. Although our simple emission scheme assumes no seasonal variations, the model reproduces the observed seasonal variations of the short-lived bromocarbons with high concentrations in winter and low concentrations in summer. This indicates that the seasonality of short-lived bromocarbons is largely due to seasonality in their chemical loss and transport. The inclusion of CHBr3 and CH2Br2 contributes ~5 pptv bromine throughout the stratosphere. Both the source gases and inorganic bromine produced from source gas degradation (Br~SLS) in the troposphere are transported into the stratosphere, and are equally important. Inorganic bromine accounts for half (2.5 pptv) of the bromine from the inclusion of CHBr3 and CHzBr2 near the tropical tropopause and its contribution rapidly increases to ~ 100% as altitude increases. More than 85% of the wet scavenging of Br(sub y)(sup VSLS) occurs in large-scale precipitation below 500 hPa. Our sensitivity study with wet scavenging in convective updrafts switched off suggests that Br(sub y)(sup SLS) in the stratosphere is not sensitive to convection. Convective scavenging only accounts for ~0.2 pptv (4%) difference in inorganic bromine delivered to the stratosphere.

Liang, Q.↗
NASA NTRS2017

How the Emitted Size Distribution and Mixing State of Feldspar Affect Ice Nucleating Particles in a Global Model

The effect of aerosol particles on ice nucleation and, in turn, the formation of ice and mixed phase clouds is recognized as one of the largest sources of uncertainty in climate prediction. We apply an improved dust mineral specific aerosol module in the NASA GISS Earth System ModelE, which takes into account soil aggregates and their fragmentation at emission as well as the emission of large particles. We calculate ice nucleating particle concentrations from K-feldspar abundance for an active site parameterization for a range of activation temperatures and external and internal mixing assumption. We find that the globally averaged INP concentration is reduced by a factor of two to three, compared to a simple assumption on the size distribution of emitted dust minerals. The decrease can amount to a factor of five in some geographical regions. The results vary little between external and internal mixing and different activation temperatures, except for the coldest temperatures. In the sectional size distribution, the size range 24 micrometer contributes the largest INP number.

Perlwitz, Jan P.↗
DOE OSTI2021

Using machine learning to improve land use/cover characterization and projection for scenario-based global modeling

The characterization of the land surface in models is critical for robust estimation of the water cycle and associated extremes. Land use determines water demand, and land cover affects water availability. The interaction between water demand and availability is the key determinant of whether systems are resilient to variability in the overall water cycle. Furthermore, activities such as irrigation and deforestation or afforestation may influence regional to global precipitation patterns, depending on the extent of the activity. Thus this proposed work aims to address the following question: How does integrated land use/cover data and improved land use/cover projection, as informed by machine learning approaches, better resolve human-earth system resilience to water cycle variability and extremes?

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

Technical Report Series on Global Modeling and Data Assimilation: Soil Moisture Active Passive (SMAP) Project Assessment Report for the Beta-Release L4_SM Data Product - Volume 40

During the post-launch SMAP calibration and validation (Cal/Val) phase there are two objectives for each science data product team: 1) calibrate, verify, and improve the performance of the science algorithm, and 2) validate the accuracy of the science data product as specified in the science requirements and according to the Cal/Val schedule. This report provides an assessment of the SMAP Level 4 Surface and Root Zone Soil Moisture Passive (L4_SM) product specifically for the product's public beta release scheduled for 30 October 2015. The primary objective of the beta release is to allow users to familiarize themselves with the data product before the validated product becomes available. The beta release also allows users to conduct their own assessment of the data and to provide feedback to the L4_SM science data product team. The assessment of the L4_SM data product includes comparisons of SMAP L4_SM soil moisture estimates with in situ soil moisture observations from core validation sites and sparse networks. The assessment further includes a global evaluation of the internal diagnostics from the ensemble-based data assimilation system that is used to generate the L4_SM product. This evaluation focuses on the statistics of the observation-minus-forecast (O-F) residuals and the analysis increments. Together, the core validation site comparisons and the statistics of the assimilation diagnostics are considered primary validation methodologies for the L4_SM product. Comparisons against in situ measurements from regional-scale sparse networks are considered a secondary validation methodology because such in situ measurements are subject to upscaling errors from the point-scale to the grid cell scale of the data product. Based on the limited set of core validation sites, the assessment presented here meets the criteria established by the Committee on Earth Observing Satellites for Stage 1 validation and supports the beta release of the data. The validation against sparse network measurements and the evaluation of the assimilation diagnostics address Stage 2 validation criteria by expanding the assessment to regional and global scales.

ubRMSE↗
DOE OSTI2023

Arctic ice-ocean interactions in an 8-to-2 kilometer resolution global model

In the last decades, the Arctic climate has changed dramatically, with the loss of multiyear sea ice one of the clearest consequences. These changes have occurred on relatively rapid timescales, and both accurate short-term Arctic prediction (e.g., 10 days to three months) and climate projection of future Arctic scenarios present ongoing challenges. Here we describe a representation of the Arctic ocean and sea ice in a ultrahigh resolution simulation in which the horizontal grid mesh reduces from 8 km at the equator to 2 km at the poles (UH8to2) for the years 2017-2020. We find the simulation reproduces observed distributions of seasonal sea-ice thickness and concentration realistically, although concentration is biased low in the spring and summer and low biases in thickness are found in the central and eastern basins in the fall. Volume, fresh water, and heat transports through key passages are realistic, lying within observationally determined ranges. Climatological comparisons reveal that the UH8to2 Atlantic Water is shallower, warmer, and saltier than the World Ocean Atlas 2018 climatology for 2005-2017 in the eastern basin. Our analysis suggests that these biases, combined with a lack of stratification in the upper 100 m of the simulated ocean, contribute to the winter biases in modeled sea ice thickness. This relationship between biases in the sea ice and ocean points to a potential positive feedback within the model, illuminating challenges for long term model predictive power in a changing Arctic climate.

58 GEOSCIENCES↗
DOE OSTI2025

Global models predict clouds at the wrong time of day: Does it matter for radiation and climate?

Accurate prediction of future climate change hinges upon the ability of Earth system models (ESMs) to simulate clouds and their radiative effects. Even if an ESM can simulate the correct clouds, a systematic error in the amount of sunlight reflected by clouds (and, thus, cloud radiative effect) can exist if the clouds are simulated at the incorrect time of day. In this work, we develop an analytical model connecting diurnal cloud biases to emergent mean state radiative biases. With the use of satellite observations, we demonstrate that there are errors in the time of day that clouds are occurring in ESMs that would cause bias in shortwave cloud radiative effect (SWCRE) that is greater than 45% of the total SWCRE bias, but such errors in the cloud diurnal cycle are masked by other compensating errors, indicating that these ESMs are getting the right answer for the wrong reasons.

Geosciences↗
DOE OSTI2022

Evaluation of a quasi-steady-state approximation of the cloud droplet growth equation (QDGE) scheme for aerosol activation in global models using multiple aircraft data over both continental and marine environments

This research introduces a numerically efficient aerosol activation scheme and evaluates it by using stratus and stratocumulus cloud data sampled during multiple aircraft campaigns in Canada, Chile, Brazil, and China. The scheme employs a quasi-steady-state approximation of the cloud droplet growth equation (QDGE) to efficiently simulate aerosol activation, the vertical profile of supersaturation, and the activated cloud droplet number concentration (CDNC) near the cloud base. The calculated maximum supersaturation values using the QDGE scheme were compared with multiple parcel model simulations under various aerosol and environmental conditions. The differences are all below 0.18 %, indicating good performance and accuracy of the QDGE scheme. We evaluated the QDGE scheme by specifying observed environmental thermodynamic variables and aerosol information from 31 cloud cases as input and comparing the simulated CDNC with cloud observations. The average of mean relative error ($\overline{MRE}$) of the simulated CDNC for cloud cases in each campaign ranges from 17.30 % in Brazil to 25.90 % in China, indicating that the QDGE scheme successfully reproduces observed variations in CDNC over a wide range of different meteorological conditions and aerosol regimes. Additionally, we carried out an error analysis by calculating the maximum information coefficient (MIC) between the MRE and input variables for the individual campaigns and all cloud cases. MIC values were then sorted by aerosol properties, pollution level, environmental humidity, and dynamic condition according to their relative importance to MRE. Based on the error analysis, we found that the magnitude of MRE is more relevant to the specification of input aerosol pollution level in marine regions and aerosol hygroscopicity in continental regions than to other variables in the simulation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1974

A global model of the earth's ionosphere for use in space applications

A general expression is derived for the F layer electron density profile as a function of latitude and longitude for that part of the earth which is in direct sunlight including dawn and dusk. Furthermore, the derived model is extended to encompass the night-time ionosphere. The expressions allow determination by standard means of the range correction for arbitrary ray path directions. It is also shown that the naive application of the Chapman ionospheric model entails range correction errors which for low elevation angles (less than 20 deg) and large solar zenith angles (40 deg) cannot be tolerated. Numerical calculations are displayed showing the dependence of the range correction on the pertinent parameters.

Von Roos, O. H.↗
NASA NTRS1979

Global model of longitude/UT variations in thermospheric composition and temperature based on mass spectrometer data

Measurements of N2, O, He, and Ar densities from neutral gas mass spectrometers on four satellites and inferred O2 and H densities from an ion mass spectrometer have been combined to produce a model of longitude/UT variations in thermospheric neutral composition and temperature. The longitude/UT model is an extension of the mass spectrometer-incoherent scatter thermospheric model (Hedin et al., 1977) and uses spherical harmonic terms dependent on geographic latitude, longitude, and UT. The combined longitude and UT variations reflect the influence of the geomagnetic field but indicate that the variations may not simply be represented in magnetic coordinates.

Hedin, A. E.↗