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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 235 records · Page 13
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NASA NTRS2009

Momentum Flux Estimates for South Georgia Island Mountain Waves in the Stratosphere Observed via Satellite

We show high-resolution satellite observations of mountain wave events in the stratosphere above South Georgia Island in the remote southern Atlantic Ocean and compute the wave momentum fluxes for these events. The fluxes are large, and they imply important drag forces on the circulation. Small island orography is generally neglected in mountain wave parameterizations used in global climate models because limited model resolution treats the grid cell containing the island as ocean rather than land. Our results show that satellite observations can be used to quantitatively constrain mountain wave momentum fluxes, and they suggest that mountain waves from island topography may be an important missing source of drag on the atmospheric circulation.

SOUTH GEORGIA ISLANDS↗
NASA NTRSDate not supplied

TPSAS-NF1676L-10735-DND

The Clouds and the Earth's Radiant Energy System (CERES) project has now surpassed the 10-year mark, has combined rigorous calibration, improved scene identification, and multi-satellite data fusion to produce a climate-accuracy data set of global 1° gridded radiative surface and TOA fluxes, and cloud properties. CERES provides the climate community with four observed TOA flux products. The ERBE-like product uses the same algorithms as ERBE in order to be compared with the ERBE time period. The SSF product uses the improved scene identification and radiance to flux conversion. The SYN product uses GEO derived clouds and fluxes to provide diurnally complete TOA fluxes. The EBAF product provides net balanced fluxes tied to the ocean heat storage term. This product is suited for climate modelers estimating the global mean energy budget. Each successive CERES flux product applies the improvements over the previous product. This presentation will focus on the diurnal averaging improvements by the inclusion of imager radiances from 5 geostationary (GEO) satellites at 3-hourly intervals to estimate the flux in between CERES observations. The regional monthly mean flux differences based on SYN (CERES/GEO) and SSF (CERES-only) can exceed 20 Wm^-2. CERES shortwave and longwave fluxes have been rigorously validated and are key elements in evaluating the ability of climate models to predict both past and future climate states. The CERES normalization of GEO derived fluxes in order to maintain the CERES instrument calibration and are consistent globally within 0.1 Wm^-2, even if the GEO calibration is artificially altered by ±5%, twice the anticipated calibration error. The predicted GEO TOA fluxes normalized to Terra have been compared at Aqua times to Aqua flux observations, as well as with GERB hourly fluxes over the METEOSAT domain. Similarly ground based radiometers have been used to validate the CERES radiative transfer computed surface fluxes and have confirmed that the CERES/GEO fluxes have improved the computed surface flux product. Although the GEO based fluxes are of inferior quality then the CERES observed fluxes, they capture the diurnal signal more effectively than using constant meteorology between CERES measurements. The validation of the GEO derived fluxes and clouds will be shown.

D. R. Doelling↗
NASA NTRS2020

Black Carbon and Precipitation: an Energetics Perspective

Black carbon aerosols (BC) influence precipitation through a range of processes. The climate response to the presence of BC is however highly dependent on its vertical distribution. Here, we analyze the changes in the energy budget and precipitation impacts of adding a layer of BC at a range of altitudes in two independent global climate models. The models are run with atmosphere‐only and slab ocean model setup to analyze both fast and slow responses, respectively. Globally, precipitation changes are tightly coupled to the energy budget. We decompose the precipitation change into contributions from absorption of solar radiation, atmospheric longwave radiative cooling, and sensible heat flux at the surface. We find that for atmosphere‐only simulations, BC rapidly suppress precipitation, independent of altitude, mainly because of strong atmospheric absorption. This reduction is offset by increased atmospheric radiative longwave cooling and reduced sensible heat flux at the surface, but not of sufficient magnitude to prevent reduced precipitation. On longer timescales, when the surface temperature is allowed to respond, we find that the precipitation increase associated with surface warming can compensate for the initial reduction, particularly for BC in the lower atmosphere. Even though the underlying processes are strikingly similar in the two models, the resulting change in precipitation and temperature by BC differ quite substantially.

black carbon aerosols↗
NASA NTRSDate not supplied

A Reference Ocean Surface Emission and Backscatter Model from Microwaves to Infrared

Satellite observations are vital for the initialization of Numerical Weather Prediction models, and very important for climate monitoring and prediction, as well as other applications such as hydrology and flood awareness prediction. Knowledge of radiative contributions from the Earth's surface is needed to sound the lower troposphere from space. The lack of a reference quality ocean emission and backscatter model is a major gap in our ability to provide absolute calibration of the satellite based observing system. Uncertainty in emissivity models is not well characterized and different models are used for different spectral bands, for active and passive instruments. An International Space Science Institute (ISSI) team was put together [4] to address these issues. The objectives of the team are to provide a reference model as a community software (i.e., documented and freely available code), that is maintained and supported, has traceable uncertainty estimations, and that enables new science from microwaves to infrared with bidirectional reflectance distribution function (BRDF) capability. We will present the model and its various components, discussing the choices between various parameterizations, building on the LOCEAN model of [2]. The model predictions will be evaluated at various frequencies, including comparisons to radiometric observations by SMAP, AMSR2 and GMI (e.g., [5]). We will discuss early model evaluation in the infrared and for active microwave sensors. Areas of ongoing research include improving the foam parametrization (coverage and emissivity) to provide consistent performances across frequencies, building on [1], and the azimuthal dependence of the active and passive signals. The model will be used to generate training data for fast models e.g., Fastem, [3], that are used in operational data assimilation and climate re-analysis.

Emmanuel Dinnat↗
NASA NTRS2019

Recent Antarctic Sea Ice Extent Variability and Its Relation to Atmospheric Circulation in Reanalyses and Seasonal Forecasts

Sea ice is considered an important indicator of climate change. Interest has focused on the trend towards reduced sea ice cover in the Arctic Ocean, particularly during summer months. In the Southern Hemisphere, sea ice has also received attention due to a trend towards increasing cover, in opposition to the Northern Hemisphere and to climate model projections. This all changed in the austral spring 2016, when the Southern Ocean sea ice cover dropped dramatically, and has remained consistently at below average values up to the present. Here I review some of the issues and perceived causes of the 2016 sea ice reduction. Several studies have suggested a change in surface winds, which would allow warmer waters to move upwards in the water column and towards the surface. Results from the GMAO (Global Modeling and Assimilation Office) ocean data assimilation system are consistent with this hypothesis, and indicate a significant warming of subsurface waters occurred in the winter of 2016, and has remained in place.

Polar↗
NASA NTRS2014

Use of Machine Learning Techniques for Iidentification of Robust Teleconnections to East African Rainfall Variability in Observations and Models

Providing advance warning of East African rainfall variations is a particular focus of several groups including those participating in the Famine Early Warming Systems Network. Both seasonal and long-term model projections of climate variability are being used to examine the societal impacts of hydrometeorological variability on seasonal to interannual and longer time scales. The NASA / USAID SERVIR project, which leverages satellite and modeling-based resources for environmental decision making in developing nations, is focusing on the evaluation of both seasonal and climate model projections to develop downscaled scenarios for using in impact modeling. The utility of these projections is reliant on the ability of current models to capture the embedded relationships between East African rainfall and evolving forcing within the coupled ocean-atmosphere-land climate system. Previous studies have posited relationships between variations in El Niño, the Walker circulation, Pacific decadal variability (PDV), and anthropogenic forcing. This study applies machine learning methods (e.g. clustering, probabilistic graphical model, nonlinear PCA) to observational datasets in an attempt to expose the importance of local and remote forcing mechanisms of East African rainfall variability. The ability of the NASA Goddard Earth Observing System (GEOS5) coupled model to capture the associated relationships will be evaluated using Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations.

Roberts, J. Brent↗
NASA NTRS1988

Abrupt climate change and extinction events

There is a growing body of theoretical and empirical support for the concept of instabilities in the climate system, and indications that abrupt climate change may in some cases contribute to abrupt extinctions. Theoretical indications of instabilities can be found in a broad spectrum of climate models (energy balance models, a thermohaline model of deep-water circulation, atmospheric general circulation models, and coupled ocean-atmosphere models). Abrupt transitions can be of several types and affect the environment in different ways. There is increasing evidence for abrupt climate change in the geologic record and involves both interglacial-glacial scale transitions and the longer-term evolution of climate over the last 100 million years. Records from the Cenozoic clearly show that the long-term trend is characterized by numerous abrupt steps where the system appears to be rapidly moving to a new equilibrium state. The long-term trend probably is due to changes associated with plate tectonic processes, but the abrupt steps most likely reflect instabilities in the climate system as the slowly changing boundary conditions caused the climate to reach some threshold critical point. A more detailed analysis of abrupt steps comes from high-resolution studies of glacial-interglacial fluctuations in the Pleistocene. Comparison of climate transitions with the extinction record indicates that many climate and biotic transitions coincide. The Cretaceous-Tertiary extinction is not a candidate for an extinction event due to instabilities in the climate system. It is quite possible that more detailed comparisons and analysis will indicate some flaws in the climate instability-extinction hypothesis, but at present it appears to be a viable candidate as an alternate mechanism for causing abrupt environmental changes and extinctions.

Crowley, Thomas J.↗
NASA NTRS1998

Improved Upper Ocean/Sea Ice Modeling in the GISS GCM for Investigating Climate Change

This project built on our previous results in which we highlighted the importance of sea ice in overall climate sensitivity by determining that for both warming and cooling climates, when sea ice was not allowed to change, climate sensitivity was reduced by 35-40%. We also modified the GISS 8 deg x lO deg atmospheric GCM to include an upper-ocean/sea-ice model involving the Semtner three-layer ice/snow thermodynamic model, the Price et al. (1986) ocean mixed layer model and a general upper ocean vertical advection/diffusion scheme for maintaining and fluxing properties across the pycnocline. This effort, in addition to improving the sea ice representation in the AGCM, revealed a number of sensitive components of the sea ice/ocean system. For example, the ability to flux heat through the ice/snow properly is critical in order to resolve the surface temperature properly, since small errors in this lead to unrestrained climate drift. The present project, summarized in this report, had as its objectives: (1) introducing a series of sea ice and ocean improvements aimed at overcoming remaining weaknesses in the GCM sea ice/ocean representation, and (2) performing a series of sensitivity experiments designed to evaluate the climate sensitivity of the revised model to both Antarctic and Arctic sea ice, determine the sensitivity of the climate response to initial ice distribution, and investigate the transient response to doubling CO2.

Source record↗
NASA NTRS2017

Remote Linkages to Anomalous Winter Atmospheric Ridging over the Northeastern Pacific

Severe drought in California between 2013 and 2016 has been linked to the multiyear persistence of anomalously high atmospheric pressure over the northeastern Pacific Ocean, which deflected the Pacific storm track northward and suppressed regional precipitation during California's winter 'rainy season.' Multiple hypotheses have emerged regarding why this high pressure ridge near the west coast of North America was so resilient-including unusual sea surface temperature patterns in the Pacific Ocean, reductions in Arctic sea ice, random atmospheric variability, or some combination thereof. Here we explore relationships between previously documented atmospheric conditions over the North Pacific and several potential remote oceanic and cryospheric influences using both observational data and a large ensemble of climate model simulations. Our results suggest that persistent wintertime atmospheric ridging similar to that implicated in California's 2013-2016 drought can at least partially be linked to unusual Pacific sea surface temperatures, and that Pacific Ocean conditions may offer some degree of cool-season foresight in this region despite the presence of substantial internal variability.

California drought;Atmospheric ridging;Ocean-atmos↗
NASA NTRSDate not supplied

Ice Sheet and Ice Shelf Freshwater Forcing of the NASA GISS ModelE GCM

Recent mass loss from ice sheets and ice shelves is now persistent and prolonged enough that it impacts downstream oceanographic conditions. To demonstrate this, we use an ensemble of coupled GISS-E2.1-G (a CMIP6 model) simulations forced with historical estimates of anomalous freshwater, in addition to other climate forcings, from 1990 through 2019. In this ensemble there are detectable differences in zonal-mean sea surface temperatures (SST) and sea ice in the Southern Ocean, and in regional sea level around Antarctica and in the western North Atlantic. These impacts mostly improve the model's representation of historical changes, including reversing the forced trends in Southern Ocean surface temperature and Antarctic sea ice. The changes in SST may have implications for estimates of the SST pattern effect on climate sensitivity and for cloud feedbacks. We conclude that the changes are sufficiently large that model groups should strive to include more accurate estimates of these drivers in all-forcing historical simulations in future coupled model intercomparisons.

Ice sheet↗
NASA NTRS2021

Mid-Pliocene Atlantic Meridional Overturning Circulation simulated in PlioMIP2

In the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2), coupled climate models have been used to simulate an interglacial climate during the mid-Piacenzian warm period (mPWP; 3.264 to 3.025 Ma). Here, we compare the Atlantic Meridional Overturning Circulation (AMOC), poleward ocean heat transport and sea surface warming in the Atlantic simulated with these models. In PlioMIP2, all models simulate an intensified mid-Pliocene AMOC. However, there is no consistent response in the simulated Atlantic ocean heat transport nor in the depth of the Atlantic overturning cell. The models show a large spread in the simulated AMOC maximum, the Atlantic ocean heat transport and the surface warming in the North Atlantic. Although a few models simulate a surface warming of ~8–12°C in the North Atlantic, similar to the reconstruction from Pliocene Research, Interpretation and Synoptic Mapping (PRISM) version 4, most models appear to underestimate this warming. The large model spread and model–data discrepancies in the PlioMIP2 ensemble do not support the hypothesis that an intensification of the AMOC, together with an increase in northward ocean heat transport, is the dominant mechanism for the mid-Pliocene warm climate over the North Atlantic.

Pliocene Model Intercomparison Project Phase 2 (Pl↗
NASA NTRS2012

Climate Variability and Phytoplankton in the Pacific Ocean

The effect of climate variability on phytoplankton communities was assessed for the tropical and sub-tropical Pacific Ocean between 1998 and 2005 using an established biogeochemical assimilation model. The phytoplankton communities exhibited wide range of responses to climate variability, from radical shifts in the Equatorial Pacific, to changes of only a couple of phytoplankton groups in the North Central Pacific, to no significant changes in the South Pacific. In the Equatorial Pacific, climate variability dominated the variability of phytoplankton. Here, nitrate, chlorophyll and all but one of the 4 phytoplankton types (diatoms, cyanobacteria and coccolithophores) were strongly correlated (p<0.01) with the Multivariate El Nino Southern Oscillation Index (MEI). In the North Central Pacific, MEI and chlorophyll were significantly (p<0.01) correlated along with two of the phytoplankton groups (chlorophytes and coccolithophores). Ocean biology in the South Pacific was not significantly correlated with MEI. During La Nina events, diatoms increased and expanded westward along the cold tongue (correlation with MEI, r=-0.81), while cyanobacteria concentrations decreased significantly (r=0.78). El Nino produced the reverse pattern, with cyanobacteria populations increasing while diatoms plummeted. The diverse response of phytoplankton in the different major basins of the Pacific suggests the different roles climate variability can play in ocean biology.

Rousseaux, Cecile↗
NASA NTRS2017

Temperature Changes in the United States

Temperature is among the most important climatic elements used in decision-making. For example, builders and insurers use temperature data for planning and risk management while energy companies and regulators use temperature data to predict demand and set utility rates. Temperature is also a key indicator of climate change: recent increases are apparent over the land, ocean, and troposphere, and substantial changes are expected for this century. This chapter summarizes the major observed and projected changes in near-surface air temperature over the United States, emphasizing new data sets and model projections since the Third National Climate Assessment (NCA3). Changes are depicted using a spectrum of observations, including surface weather stations, moored ocean buoys, polar-orbiting satellites, and temperature-sensitive proxies. Projections are based on global models and downscaled products from CMIP5 (Coupled Model Intercomparison Project Phase 5) using a suite of Representative Concentration Pathways (RCPs; see Ch. 4: Projections for more on RCPs and future scenarios).

Vose, R. S.↗
NASA NTRS2012

The Effect of ENSO on Phytoplankton Composition in the Pacific Ocean

The effect of climate variability on phytoplankton communities was assessed for the tropical and sub-tropical Pacific Ocean between 1998 and 2005 using an established biogeochemical assimilation model. The phytoplankton communities exhibited wide range of responses to climate variability, from radical shifts in the Equatorial Pacific, to changes of only a couple of phytoplankton groups in the North Central Pacific, to no significant changes in the South Pacific. In the Equatorial Pacific, climate variability dominated the variability of phytoplankton. Here, nitrate, chlorophyll and all but one of the 4 phytoplankton types (diatoms, cyanobacteria and coccolithophores) were strongly correlated (p less than 0.01) with the Multivariate El Nino Southern Oscillation Index (MEI). In the North Central Pacific, MEI and chlorophyll were significantly (p<0.01) correlated along with two of the phytoplankton groups (chlorophytes and coccolithophores). Ocean biology in the South Pacific was not significantly correlated with MEI. During La Ni a events, diatoms increased and expanded westward along the cold tongue (correlation with MEI, r=-0.81), while cyanobacteria concentrations decreased significantly (r=0.78). El Nino produced the reverse pattern, with cyanobacteria populations increasing while diatoms plummeted. The diverse response of phytoplankton in the different major basins of the Pacific suggests the different roles climate variability can play in ocean biology.

Rousseaux, Cecile↗
NASA NTRS1985

Volatiles on satellites of the outer solar system

Molecules of cosmochemically abundant elements can act as volatiles and hence play a dominant role in the climatic and surficial evolution of solid bodies. Examples on terrestrial planets are H2O on Earth and H2O and CO2 on Mars. Analogous processes in the outer solar system focussing on CH4, its associated hydrocarbons, and N2 on Titan and Triton, the large moons of Saturn and Neptune were explored. A kilometer-deep C2H6-CH4 ocean was proposed for the surface of Titan to reconcile data on the lower atmosphere with understanding of the photochemical conversion of methane to heavier hydrocarbons. If such ocean exists, then it has dissolved in it an amount of N2 equal to the present atmospheric abundance. Since N2 contributes with CH4 a substantial greenhouse effect, the atmospheric physical and chemical characteristics are strongly coupled to those of the ocean, which change with time as methane is photolyzed in the stratosphere. Some relationship exists to the runaway greenhouse model for primordial Venus and the possible climatic implications of the buffering of Earth's atmospheric CO2 by the oceans. Two important diagnostics, measurable in Titan's atmosphere, of the conditions under which icy satellites formed are the abundances of noble gases and the CHd/CH4 radio. Both of these indicators have been altered during the evolution of Titan's surface-atmosphere system, the former by interaction with the ocean and the latter by progressive photolysis of methane into heavier hydrocarbons. The physical state and composition of volatiles on the surface of Triton is controversial, but plausibly could include CH4 N2 and perhaps CO. If condensed CH4 and N2 are widespread, their transformation to and from the vapor phase dominates the surface energy balance with sunlight. The extreme seasonal modulation of subsolar latitude on Triton is thus primarily expressed by volatile transport rather than large teperature changes, with possibly drastic observational consequences. The presence of two volatile species differing greatly in their vapor pressures make Triton a crude analog of Mars. Triton might be more appropriately regarded as a deep-freeze version of Titan.

Lunine, J. I.↗
NASA NTRS2010

The Effect of Satellite Observing System Changes on MERRA Water and Energy Fluxes

Because reanalysis data sets offer state variables and fluxes at regular space / time intervals, atmospheric reanalyses have become a mainstay of the climate community for diagnostic purposes and for driving offline ocean and land models. Although one weakness of these data sets is the susceptibility of the flux products to uncertainties because of shortcomings in parameterized model physics, another issue, perhaps less appreciated, is the fact that continual but discreet changes in the evolving observational system, particularly from satellite sensors, may also introduce artifacts in the time series of quantities. In this paper we examine the ability of the NASA MERRA (Modern Era Retrospective Analysis for Research and Applications) and other recent reanalyses to determine variability in the climate system over the satellite record (approximately the last 30 years). In particular we highlight the effect on the reanalysis of discontinuities at the junctures of the onset of passive microwave imaging (Special Sensor Microwave Imager) in late 1987 as well as improved sounding and imaging with the Advanced Microwave Sounding Unit, AMSU-A, in 1998. We first examine MERRA fluxes from the perspective of how physical modes of variability (e.g. ENSO events, Pacific Decadal Variability) are contaminated by artificial step-like trends induced by the onset of new moisture data these two satellite observing systems. Secondly, we show how Redundancy Analysis, a statistical regression methodology, is effective in relating these artifact signals in the moisture and temperature analysis increments to their presence in the physical flux terms (e.g. precipitation, radiation). This procedure is shown to be effective greatly reducing the artificial trends in the flux quantities.

Robertson, Franklin R.↗
NASA NTRS2011

The Effect of Satellite Observing System Changes on MERRA Water and Energy Fluxes

Because reanalysis data sets offer state variables and fluxes at regular space / time intervals, atmospheric reanalyses have become a mainstay of the climate community for diagnostic purposes and for driving offline ocean and land models. Although one weakness of these data sets is the susceptibility of the flux products to uncertainties because of shortcomings in parameterized model physics, another issue, perhaps less appreciated, is the fact that continual but discreet changes in the evolving observational system, particularly from satellite sensors, may also introduce artifacts in the time series of quantities. In this paper we examine the ability of the NASA MERRA (Modern Era Retrospective Analysis for Research and Applications) and other recent reanalyses to determine variability in the climate system over the satellite record (approx. the last 30 years). In particular we highlight the effect on the reanalysis of discontinuities at the junctures of the onset of passive microwave imaging (Special Sensor Microwave Imager) in late 1987 and, more prominently, with improved sounding and imaging with the Advanced Microwave Sounding Unit, AMSU-A, in 1998. We first examine MERRA fluxes from the perspective of how physical modes of variability (e.g. ENSO events, Pacific Decadal Variability) are contained by artificial step-like trends induced by the onset of new moisture data these two satellite observing systems. Secondly, we show how Redundancy Analysis, a statistical regression methodology, is effective in relating these artifact signals in the moisture and temperature analysis increments to their presence in the physical flux terms (e.g. precipitation, radiation). This procedure is shown to be effective greatly reducing the artificial trends in the flux quantities.

Robertson, Franklin R.↗
NASA NTRS2016

Exploring and Analyzing Climate Variations Online by Using NASA MERRA-2 Data at GES DISC

NASA Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) (http:giovanni.sci.gsfc.nasa.govgiovanni) is a web-based data visualization and analysis system developed by the Goddard Earth Sciences Data and Information Services Center (GES DISC). Current data analysis functions include Lat-Lon map, time series, scatter plot, correlation map, difference, cross-section, vertical profile, and animation etc. The system enables basic statistical analysis and comparisons of multiple variables. This web-based tool facilitates data discovery, exploration and analysis of large amount of global and regional remote sensing and model data sets from a number of NASA data centers. Long term global assimilated atmospheric, land, and ocean data have been integrated into the system that enables quick exploration and analysis of climate data without downloading, preprocessing, and learning data. Example data include climate reanalysis data from NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) which provides data beginning in 1980 to present; land data from NASA Global Land Data Assimilation System (GLDAS), which assimilates data from 1948 to 2012; as well as ocean biological data from NASA Ocean Biogeochemical Model (NOBM), which provides data from 1998 to 2012. This presentation, using surface air temperature, precipitation, ozone, and aerosol, etc. from MERRA-2, demonstrates climate variation analysis with Giovanni at selected regions.

knowledge base↗