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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Optical and Microphysical Retrievals of Marine Stratocumulus Clouds off the Coast of Namibia from Satellite and Aircraft

Though the emphasis of the Southern Africa Regional Science Initiative 2000 (SAFARI-2000) dry season campaign was largely on emission sources and transport, the assemblage of aircraft (including the high altitude NASA ER-2 remote sensing platform and the University of Washington CV-580, UK MRF C-130, and South African Weather Bureau JRA in situ aircrafts) provided a unique opportunity for cloud studies. Therefore, as part of the SAFARI initiative, investigations were undertaken to assess regional aerosol-cloud interactions and cloud remote sensing algorithms. In particular, the latter part of the experiment concentrated on marine boundary layer stratocumulus clouds off the southwest coast of Africa. Associated with cold water upwelling along the Benguela current, the Namibian stratocumulus regime has received limited attention but appears to be unique for several reasons. During the dry season, outflow of continental fires and industrial pollution over this area can be extreme. From below, upwelling provides a rich nutrient source for phytoplankton (a source of atmospheric sulfur through DMS production as well as from decay processes). The impact of these natural and anthropogenic sources on the microphysical and optical properties of the stratocumulus is unknown. Continental and Indian Ocean cloud systems of opportunity were also studied during the campaign. SAFARI 2000 aircraft flights off the coast of Namibia were coordinated with NASA Terra Satellite overpasses for synergy with the Moderate Resolution Imaging Spectroradiometer (MODIS) and other Terra instruments. MODIS was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 (and Aqua spacecraft on May 4, 2002). Among the remote sensing algorithms developed and applied to this sensor are cloud optical and microphysical properties that include cloud thermodynamic phase, optical thickness, and effective particle radius of both liquid water and ice clouds. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, and fundamental atmospheric research. The archived MODIS Collection 5 cloud products processing stream will be used to analyze low water cloud scenes off the Namibian and Angolan coasts during SAFARI 2000 time period, as well as other years. Pixel-level Terra and Aqua MODIS retrievals (l. km spatial resolution at nadir) and gridded (1' uniform grid) statistics of cloud optical thickness and effective particle radius will be presented, including joint probability distributions between the two quantities. In addition, perspectives from the MODIS Airborne Simulator, which flew on the ER-2 during SAFARI 2000 providing high spatial resolution retrievals (50 m at nadir), will be presented as appropriate. The H-SAF Program requires an experimental operational European-centric Satellite Precipitation Algorithm System (E-SPAS) that produces medium spatial resolution and high temporal resolution surface rainfall and snowfall estimates over the Greater European Region including the Greater Mediterranean Basin. Currently, there are various types of experimental operational algorithm methods of differing spatiotemporal resolutions that generate global precipitation estimates. This address will first assess the current status of these methods and then recommend a methodology for the H-SAF Program that deviates somewhat from the current approach under development but one that takes advantage of existing techniques and existing software developed for the TRMM Project and available through the public domain.

Platnick, Steven E.↗
NASA NTRS2005

Spatial and Temporal Distribution of Tropospheric Clouds Observed by MODIS Onboard the Terra and Aqua Satellites

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and Aqua spacecraft on May 4, 2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various cloud properties being analyzed on a global basis from both Terra and Aqua. These include the latitudinal distribution of cloud optical and radiative properties of both liquid water and ice clouds, as well as joint histograms of cloud optical thickness and effective radius for selected geographical locations around the world.

King, Michael D.↗
NASA NTRS2020

GISS‐E2.1: Configurations and Climatology

This paper describes the GISS‐E2.1 contribution to the Coupled Model Intercomparison Project, Phase 6 (CMIP6). This model version differs from the predecessor model (GISS‐E2) chiefly due to parameterization improvements to the atmospheric and ocean model components, while keeping atmospheric resolution the same. Model skill when compared to modern era climatologies is significantly higher than in previous versions. Additionally, updates in forcings have a material impact on the results. In particular, there have been specific improvements in representations of modes of variability (such as the Madden‐Julian Oscillation and other modes in the Pacific) and significant improvements in the simulation of the climate of the Southern Oceans, including sea ice. The effective climate sensitivity to 2xCO2 is slightly higher than previously at 2.7‐‐3.1°C (depending on version), and is a result of lower CO2 radiative forcing and stronger positive feedbacks.

General Circulation Model↗
NASA NTRS2022

The Transformation and Export of Organic Carbon Across an Arctic River-Delta-Ocean Continuum

The Arctic Ocean is surrounded by land that feeds highly seasonal rivers with water enriched in high concentrations of dissolved and particulate organic carbon (DOC and POC). Explicit estimates of the flux of organic carbon across the land-ocean interface are difficult to quantify and many interdependent processes makes source attribution difficult. A high-resolution 3-D biogeochemical model was built for the lower Yukon River and coastal ocean to estimate biogeochemical cycling across the land-ocean continuum. The model solves for complex reactions related to organic carbon transformation, including mechanistic photodegradation and multi-reactivity microbial processing, DOC to POC flocculation, and phytoplankton dynamics. The baseline DOC and POC flux out of the delta from April to September 2019, was 977 and 536 Gg C (~80% of the annual total), but only 50% of the DOC and 25% of the POC exited the plume across the 10 m isobath. Microbial breakdown of DOC accounted for a net loss of 168 Gg C (17% of delta export) within the plume and photodegradation accounted for a net loss of 46.6 Gg C DOC (5% of delta export) in 2019. Flocculation decreased the total organic carbon flux by only 6.4 Gg C (~1%), while POC sinking accounted for 63.3 Gg C (10%) settling in the plume. The loss of chromophoric dissolved organic matter (CDOM) due to photodegradation increased the light available for phytoplankton growth throughout the coastal ocean, demonstrating the secondary effects that organic carbon reactions can have on biological processes and the net coastal carbon flux.

Land-Ocean Continuum↗
DOE OSTI2012

Integrated Assessment Modeling

This paper discusses the role of Integrated Assessment models (IAMs) in climate change research. IAMs are an interdisciplinary research platform, which constitutes a consistent scientific framework in which the large-scale interactions between human and natural Earth systems can be examined. In so doing, IAMs provide insights that would otherwise be unavailable from traditional single-discipline research. By providing a broader view of the issue, IAMs constitute an important tool for decision support. IAMs are also a home of human Earth system research and provide natural Earth system scientists information about the nature of human intervention in global biogeophysical and geochemical processes.

global climate change↗
DOE OSTI2014

Atmospheric Rivers Coming to a Cloud Near You

Learn about the ARM Cloud Aerosol Precipitation Experiment (ACAPEX) field campaign in this short video. Ruby Leung, PNNL's lead scientist on this campaign's observational strategy to monitor precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Aboard the R/V Oceanus: Carbon Flux Explorers

Jim Bishop, senior scientist at Berkeley Lab and professor at UC Berkeley, is leading a project to deploy robotic floats that provide data on how microorganisms sequester carbon in the ocean. He recently led a research team on a 10-day voyage, funded by the National Science Foundation, to put the Carbon Flux Explorers to the test. Read more at http://oceanbots.lbl.gov (Video edited by Roxanne Makasdjian and Stephen McNally/UC Berkeley. Video shot by Jessica Kendall-Bar. Drone footage provided by Mark Booher.)

47 OTHER INSTRUMENTATION↗
NASA NTRS2016

Crop Model Improvement Reduces the Uncertainty of the Response to Temperature of Multi-Model Ensembles

To improve climate change impact estimates and to quantify their uncertainty, multi-model ensembles (MMEs) have been suggested. Model improvements can improve the accuracy of simulations and reduce the uncertainty of climate change impact assessments. Furthermore, they can reduce the number of models needed in a MME. Herein, 15 wheat growth models of a larger MME were improved through re-parameterization and/or incorporating or modifying heat stress effects on phenology, leaf growth and senescence, biomass growth, and grain number and size using detailed field experimental data from the USDA Hot Serial Cereal experiment (calibration data set). Simulation results from before and after model improvement were then evaluated with independent field experiments from a CIMMYT worldwide field trial network (evaluation data set). Model improvements decreased the variation (10th to 90th model ensemble percentile range) of grain yields simulated by the MME on average by 39% in the calibration data set and by 26% in the independent evaluation data set for crops grown in mean seasonal temperatures greater than 24 C. MME mean squared error in simulating grain yield decreased by 37%. A reduction in MME uncertainty range by 27% increased MME prediction skills by 47%. Results suggest that the mean level of variation observed in field experiments and used as a benchmark can be reached with half the number of models in the MME. Improving crop models is therefore important to increase the certainty of model-based impact assessments and allow more practical, i.e. smaller MMEs to be used effectively.

damage assessment↗
DOE OSTI2017

Cloud feedback mechanisms and their representation in global climate models

Cloud feedback—the change in top-of-atmosphere radiative flux resulting from the cloud response to warming—constitutes by far the largest source of uncertainty in the climate response to CO 2 forcing simulated by global climate models (GCMs). In this paper, we review the main mechanisms for cloud feedbacks, and discuss their representation in climate models and the sources of intermodel spread. Global-mean cloud feedback in GCMs results from three main effects: (1) rising free-tropospheric clouds (a positive longwave effect); (2) decreasing tropical low cloud amount (a positive shortwave [SW] effect); (3) increasing high-latitude low cloud optical depth (a negative SW effect). These cloud responses simulated by GCMs are qualitatively supported by theory, high-resolution modeling, and observations. Rising high clouds are consistent with the fixed anvil temperature (FAT) hypothesis, whereby enhanced upper-tropospheric radiative cooling causes anvil cloud tops to remain at a nearly fixed temperature as the atmosphere warms. Tropical low cloud amount decreases are driven by a delicate balance between the effects of vertical turbulent fluxes, radiative cooling, large-scale subsidence, and lower-tropospheric stability on the boundary-layer moisture budget. High-latitude low cloud optical depth increases are dominated by phase changes in mixed-phase clouds. Finally, the causes of intermodel spread in cloud feedback are discussed, focusing particularly on the role of unresolved parameterized processes such as cloud microphysics, turbulence, and convection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Examining global electricity supply vulnerability to climate change using a high-fidelity hydropower dam model

Here, an important and plausible impact of a changing global climate is altered power generation from hydroelectric dams. Here we project 21st century global hydropower production by forcing a coupled, global hydrological and dam model with three General Circulation Model (GCM) projections run under two emissions scenarios. Dams are simulated using a detailed model that accounts for plant specifications, storage dynamics, reservoir bathymetry and realistic, optimized operations. We show that the inclusion of these features can have a non-trivial effect on the simulated response of hydropower production to changes in climate. Simulation results highlight substantial uncertainty in the direction of change in globally aggregated hydropower production (~–5 to + 5% change in mean global production by the 2080s under a high emissions scenario, depending on GCM). Several clearly impacted hotspots are identified, the most prominent of which encompasses the Mediterranean countries in southern Europe, northern Africa and the Middle East. In this region, hydropower production is projected to be reduced by approximately 40% on average by the end of the century under a high emissions scenario. After accounting for each country's dependence on hydropower for meeting its current electricity demands, the Balkans countries emerge as the most vulnerable (~ 5–20% loss in total national electricity generation depending on country). On the flipside, a handful of countries in Scandinavia and central Asia are projected to reap a significant increase in total electrical production (~ 5–15%) without investing in new power generation facilities.

13 HYDRO ENERGY↗
DOE OSTI2021

Mapping Post-Climate Change Biogeographical Regions with Deep Latent Variable Models

Forecasting future changes to biodiversity due to shifts in climate is challenging due to nonlinear interactions between species as recorded in their presence/absence data. This work proposes using variational autoencoders with environmental covariates to identify low-dimensional structure in species’ joint co-occurrence patterns and leveraging this simplified representation to provide multivariate predictions of their habitat extent under future climate scenarios. We pursue a latent space clustering approach to map biogeographical regions of frequently co-occurring species and apply this methodology to a dataset from northern Belgium, generating predictive maps illustrating how these regions may expand or contract with changing temperature under a future climate scenario.

Krapu, Chris↗
NASA NTRS2013

Pre-industrial to End 21st Century Projections of Tropospheric Ozone from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP)

Present day tropospheric ozone and its changes between 1850 and 2100 are considered, analysing 15 global models that participated in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). The ensemble mean compares well against present day observations. The seasonal cycle correlates well, except for some locations in the tropical upper troposphere. Most (75 %) of the models are encompassed with a range of global mean tropospheric ozone column estimates from satellite data, but there is a suggestion of a high bias in the Northern Hemisphere and a low bias in the Southern Hemisphere, which could indicate deficiencies with the ozone precursor emissions. Compared to the present day ensemble mean tropospheric ozone burden of 337+/-23 Tg, the ensemble mean burden for 1850 time slice is approx. 30% lower. Future changes were modelled using emissions and climate projections from four Representative Concentration Pathways (RCPs). Compared to 2000, the relative changes in the ensemble mean tropospheric ozone burden in 2030 (2100) for the different RCPs are: −4% (−16 %) for RCP2.6, 2% (−7%) for RCP4.5, 1% (−9%) for RCP6.0, and 7% (18 %) for RCP8.5. Model agreement on the magnitude of the change is greatest for larger changes. Reductions in most precursor emissions are common across the RCPs and drive ozone decreases in all but RCP8.5, where doubled methane and a 40-150% greater stratospheric influx (estimated from a subset of models) increase ozone. While models with a high ozone burden for the present day also have high ozone burdens for the other time slices, no model consistently predicts large or small ozone changes; i.e. the magnitudes of the burdens and burden changes do not appear to be related simply, and the models are sensitive to emissions and climate changes in different ways. Spatial patterns of ozone changes are well correlated across most models, but are notably different for models without time evolving stratospheric ozone concentrations. A unified approach to ozone budget specifications and a rigorous investigation of the factors that drive tropospheric ozone is recommended to help future studies attribute ozone changes and inter-model differences more clearly.

Troposphere↗