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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 325 records · Page 18
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NASA NTRS2000

Predictability of Seasonal Means in the NSIPP-1 AGCM

The predictability of seasonal means during 1980-99 is examined from 720 seasonal integrations with version 1 of NASA's Seasonal to Interanual Prediction Project (NSIPP-1) atmospheric general circulation model (AGCM). The AGCM is the atmospheric (and land) component of the NSIPP fully-coupled atmosphere-land-ocean model. For these runs, the initial atmospheric conditions are taken from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalyses, and sea surface temperatures and sea ice are specified from observations. Results from the northern winter integrations show that the model has a very realistic El Nino/Southern Oscillation (ENSO) response in both the tropics and extratropics. Early results from the northern summer runs show a robust extratropical ENSO response in the Southern Hemisphere Pacific, as well as, a pronounced zonally-symmetric component to the ENSO response in both hemispheres. Results will be presented at the meeting highlighting the seasonal evolution in predictability and skill of the NSIPP model on both global and regional scales. A further analysis of the zonally-symmetric response will be discussed in terms of its potential impact on the predictability of middle-latitude climate variability on seasonal to interannual time scales.

Schubert, Siegfried↗
NASA NTRS2003

Seasonal Atmospheric and Oceanic Predictions

Several projects associated with dynamical, statistical, single column, and ocean models are presented. The projects include: 1) Regional Climate Modeling; 2) Statistical Downscaling; 3) Evaluation of SCM and NSIPP AGCM Results at the ARM Program Sites; and 4) Ocean Forecasts.

Roads, John↗
NASA NTRS2013

Software Engineering Tools for Scientific Models

Software tools were constructed to address issues the NASA Fortran development community faces, and they were tested on real models currently in use at NASA. These proof-of-concept tools address the High-End Computing Program and the Modeling, Analysis, and Prediction Program. Two examples are the NASA Goddard Earth Observing System Model, Version 5 (GEOS-5) atmospheric model in Cell Fortran on the Cell Broadband Engine, and the Goddard Institute for Space Studies (GISS) coupled atmosphere- ocean model called ModelE, written in fixed format Fortran.

Abrams, Marc↗
NASA NTRSDate not supplied

Influence of Heat Flow from the Planetary Interior on Surface Habitability

an primordial and/or radiogenic heat flow from a rocky planet’s interior help maintain a surface environment amenable to life?On rocky Earth-like planets with shallow oceans (≤5 km depth) that are on the outer edge of the habitable zone, the additional energy provided might make the difference between a world supporting regional habitat space and a world uninhabitable by any known life-form. To test this hypothesis, we introduce heat flux from the planetary interior as a forcing to the NASA/GISSROCKE-3D exoplanet GCM, and explore whether it can enhance the habitability of marginal terrestrial rocky planets (e.g.,paleo Earth in a “snowball” climate state).GCM simulations of modern Earth have not included geothermal heat flux as a climate forcing, as it is more than an order of magnitude less than the 2.9 W/m heating caused by anthropogenic greenhouse gases [Flanner, GRL 2009]. Modern Earth measurements in the oceans [Downes et al., GRL 2019] and results from ocean GCMs [Barnes et al., Ocean Model. 2017]suggest that localized higher heat flux can have measurable thermodynamic and dynamic impacts, such as weakening deep ocean stratification and increased poleward ocean heat transports. A similar result with ROCKE-3D would be important, since our snowball Earth simulations without heat flux produce features like ocean stratification that should have hampered the survival of life. We have created a set of spatially variable geothermal heat fluxes at varying horizontal resolutions based on modern Earth heat flow patterns [Davies, Geochem. Geophys. Geosys. 2013] to test the sensitivity of the ROCKE-3D GCM initially in a modern Earth context. Preliminary results show that even modest heat fluxes have a measurable impact on deep ocean temperatures (upto +0.9°C locally) and that this heat can be transported at depth along ocean circulation paths. Estimates of heat flux impacts on vertical ocean mixing and surface ocean conditions require long simulations at the higher spatial resolutions needed to express heat flow at the scale of most ocean ridges. Ongoing simulations are focused on testing the impacts of horizontal resolution and flux scaling on surface environments, especially for “snowball” climate scenarios.

Heat flow↗
NASA NTRS1998

Decadal Air-Sea Interaction in the North Atlantic Based on Observations and Modeling Results

The decadal, 12-14 year, cycle observed in the North Atlantic SST and tide gauge data was examined using the NCEP/NCAR reanalyses, COADS data and an ocean model simulation. Besides this decadal mode, a shorter, subdecadal period of about 8 years exists in tide gauge data north of 40N, in the subpolar SST and in the winter North Atlantic Oscillation (NAO) index and in subpolar winter heat flux values. The decadal cycle is a well separated mode in a singular spectrum analysis (SSA) for a time series of SST EOF mode 1 with a center over the Gulf Stream extension. Tide gauge and SST data are consistent in that both show a significant subdecadal periodicity exclusively in the subpolar gyre, but in subtropics the 12-14 year period is the prominent, but nonstationary, decadal signal. The main finding of this study is that this 12-14 year cycle can be constructed based on the leading mode of the surface heat flux. This connection to the surface heat flux implicates the participation of the thermohaline circulation in the decadal cycle. During the cycle starting from the positive index phase of NAO, SST and oceanic heat content anomalies are created in subtropics due to local heat flux and intensification of the thermohaline circulation. The anomalies advect to the subpolar gyre where they are amplified by local heat flux and are part of the negative feedback of thermohaline circulation on itself. Consequently the oceanic thermohaline circulation slows down and the opposite cycle starts. The oscillatory nature would not be possible without the active atmospheric participation in the cycle, because it provides the unstable interaction through heat flux, without it, the oceanic mode would be damped. This analysis suggests that the two principal modes of heat flux variability, corresponding to patterns similar to North Atlantic Oscillation (NAO) and Western Atlantic (WA), are part of the same decadal cycle and an indirect measure of the north-south movement of the storm tracks.

Hakkinen, Sirpa↗
NASA NTRS1988

Analytic solution of the box diffusion model for a global ocean

The paper presents an analytic solution for the temperature of the mixed layer for a box diffusion model of a global ocean. It is shown that the exact solution approaches the appropriate limits of a mixed layer ocean model and of a diffusive ocean without a mixed layer on top. It is also shown that, over a large range of parameters of the box diffusion model, the difference between the temperature calculated using a box diffusion model and the temperature calculated using a purely diffusive ocean is buried in the noise.

Lebedeff, Sergej A.↗
NASA NTRS1999

Comparison of Model and Observed Regional Temperature Changes During the Past 40 Years

Results are presented for six simulations of the Goddard Institute for Space Studies (GISS) global atmosphere-ocean model for the years 1950 to 2099. There are two control simulations with constant 1950 atmospheric composition from different initial states, two GHG experiments with observed greenhouse gases up to 1990 and compounded .5% CO2 annual increases thereafter, and two GHG+SO4 experiments with the same varying greenhouse gases plus varying tropospheric sulfate aerosols. Surface air temperature trends in the two GHG experiments are compared between themselves and with the observed temperature record from 1960 and 1998. All comparisons show high positive spatial correlation in the northern hemisphere except in summer when the greenhouse signal is weakest. The GHG+SO4 experiments show weaker correlations. In the southern hemisphere, correlations are either weak or negative which in part are due to the model's unrealistic interannual variability of southern sea ice cover. The model results imply that temperature changes due to forcing by increased greenhouse gases have risen above the level of regional interannual temperature variability in the northern hemisphere over the past 40 years. This period is thus an important test of reliability of coupled climate models.

Russell, Gary L.↗
NASA NTRS1992

The three stages of magma ocean cooling

Models of magma ocean (MO) cooling and crystallization can provide important constraints on MO plausibility for a given planet, on the origin of long term, stable crusts, and even on the origin of the solar system. Assuming the MO is initially extensive enough to have a mostly molten surface, its first stage of cooling is an era of radiative heat loss from the surface, with extremely rapid convection below, and no conductive layer in between. The development of the chill crust starts the second stage of MO cooling. Heat loss is now limited by conduction through the crust. The third stage of cooling starts when the near surface MO evolves compositionally to the point of saturation with feldspar. At this point, the cooling rate again precipitously diminishes, the rate of crustal thickness growth as a function of temperature suddenly increases. More work on incorporating chemical constraints into the evolving physical models of MO solidification would be worthwhile.

Warren, Paul H.↗
NASA NTRS1999

Effects of Precipitation on Ocean Mixed-Layer Temperature and Salinity as Simulated in a 2-D Coupled Ocean-Cloud Resolving Atmosphere Model

A two-dimensional coupled ocean-cloud resolving atmosphere model is used to investigate possible roles of convective scale ocean disturbances induced by atmospheric precipitation on ocean mixed-layer heat and salt budgets. The model couples a cloud resolving model with an embedded mixed layer-ocean circulation model. Five experiment are performed under imposed large-scale atmospheric forcing in terms of vertical velocity derived from the TOGA COARE observations during a selected seven-day period. The dominant variability of mixed-layer temperature and salinity are simulated by the coupled model with imposed large-scale forcing. The mixed-layer temperatures in the coupled experiments with 1-D and 2-D ocean models show similar variations when salinity effects are not included. When salinity effects are included, however, differences in the domain-mean mixed-layer salinity and temperature between coupled experiments with 1-D and 2-D ocean models could be as large as 0.3 PSU and 0.4 C respectively. Without fresh water effects, the nocturnal heat loss over ocean surface causes deep mixed layers and weak cooling rates so that the nocturnal mixed-layer temperatures tend to be horizontally-uniform. The fresh water flux, however, causes shallow mixed layers over convective areas while the nocturnal heat loss causes deep mixed layer over convection-free areas so that the mixed-layer temperatures have large horizontal fluctuations. Furthermore, fresh water flux exhibits larger spatial fluctuations than surface heat flux because heavy rainfall occurs over convective areas embedded in broad non-convective or clear areas, whereas diurnal signals over whole model areas yield high spatial correlation of surface heat flux. As a result, mixed-layer salinities contribute more to the density differences than do mixed-layer temperatures.

Li, Xiaofan↗
NASA NTRS1997

Comparison of TOPEX/Poseidon Sea Level and Linear Model Results forced by Various Wind Products for the Tropical Pacific

The goal of this paper is to compare TOPEX/Posaidon (T/P) sea level with sea level results from linear ocean model experiments forced by several different wind products for the tropical Pacific. During the period of this study (October 1992 - October 1995), available wind products include satellite winds from the ERS-1 scatterometer product of [HALP 97] and the passive microwave analysis of SSMI winds produced using the variational analysis method (VAM) of [ATLA 91]. In addition, atmospheric GCM winds from the NCEP reanalysis [KALN 96], ECMWF analysis [ECMW94], and the Goddard EOS-1 (GEOS-1) reanalysis experiment [SCHU 93] are available for comparison. The observed ship wind analysis of FSU [STRI 92] is also included in this study. The linear model of [CANE 84] is used as a transfer function to test the quality of each of these wind products for the tropical Pacific. The various wind products are judged by comparing the wind-forced model sea level results against the T/P sea level anomalies. Correlation and RMS difference maps show how well each wind product does in reproducing the T/P sea level signal. These results are summarized in a table showing area average correlations and RMS differences. The large-scale low-frequency temporal signal is reproduced by all of the wind products, However, significant differences exist in both amplitude and phase on regional scales. In general, the model results forced by satellite winds do a better job reproducing the T/P signal (i.e. have a higher average correlation and lower RMS difference) than the results forced by atmospheric model winds.

Hackert, Eric C.↗
NASA NTRS1995

Mean Sea Level Derived from Altimetry and Wind-Driven Numerical Models in the Indian Ocean

Wind-driven model skill in simulating sea level variations in the Indian Ocean depends on our knowledge of the mean ocean dynamic topography. This is demonstrated by running the nonlinear or linear version of a shallow-water model driven by observed winds over Geosat and TOPEX periods. Geosat variations are assimilated in the nonlinear shallow-water model with the objective of obtaining topography data.

numerical models Indian ocean mean sea level remot↗
NASA NTRS2001

Variability of Antarctic Sea Ice 1979-1998

The principal characteristics of the variability of Antarctic sea ice cover as previously described from satellite passive-microwave observations are also evident in a systematically-calibrated and analyzed data set for 20.2 years (1979-1998). The total Antarctic sea ice extent (concentration > 15 %) increased by 13,440 +/- 4180 sq km/year (+1.18 +/- 0.37%/decade). The area of sea ice within the extent boundary increased by 16,960 +/- 3,840 sq km/year (+1.96 +/- 0.44%/decade). Regionally, the trends in extent are positive in the Weddell Sea (1.5 +/- 0.9%/decade), Pacific Ocean (2.4 +/- 1.4%/decade), and Ross (6.9 +/- 1.1 %/decade) sectors, slightly negative in the Indian Ocean (-1.5 +/- 1.8%/decade, and strongly negative in the Bellingshausen-Amundsen Seas sector (-9.5 +/- 1.5%/decade). For the entire ice pack, small ice increases occur in all seasons with the largest increase during autumn. On a regional basis, the trends differ season to season. During summer and fall, the trends are positive or near zero in all sectors except the Bellingshausen-Amundsen Seas sector. During winter and spring, the trends are negative or near zero in all sectors except the Ross Sea, which has positive trends in all seasons. Components of interannual variability with periods of about 3 to 5 years are regionally large, but tend to counterbalance each other in the total ice pack. The interannual variability of the annual mean sea-ice extent is only 1.6% overall, compared to 5% to 9% in each of five regional sectors. Analysis of the relation between regional sea ice extents and spatially-averaged surface temperatures over the ice pack gives an overall sensitivity between winter ice cover and temperature of -0.7% change in sea ice extent per K. For summer, some regional ice extents vary positively with temperature and others negatively. The observed increase in Antarctic sea ice cover is counter to the observed decreases in the Arctic. It is also qualitatively consistent with the counterintuitive prediction of a global atmospheric-ocean model of increasing sea ice around Antarctica with climate warming due to the stabilizing effects of increased snowfall on the Southern Ocean.

Zwally, H. Jay↗
NASA NTRS1977

Numerical simulation of the Gulf Stream and Mid-Ocean eddies

Oceanographic field measurements have revealed intense, transient mesoscale motions in many parts of the world ocean. The circulation of the western North Atlantic, considered in the present study as a rectangular basin, is simulated with a primitive equation model that has five levels and a horizontal grid size of 37 km. The model ocean is driven by a 2.5 gyre pattern of steady zonal wind stress and by a Newtonian-type surface heating. Two cases are considered: the first uses a Laplacian formulation for the subgrid-scale lateral diffusions of heat and momentum; the second uses a highly scale-selective biharmonic formulation for these diffusions. An analysis of the heat transport, in the biharmonic experiment, shows that the horizontal transport of heat by eddies is much larger than the subgrid-scale horizontal heat diffusion. In the Gulf Stream region, the eddy heat transport is comparable to the effect of a lateral diffusion coefficient of 10 to the 7th sq cm/s.

Semtner, A. J., Jr.↗
NASA NTRS2015

Ocean-Atmosphere Coupled Model Simulations of Precipitation in the Central Andes

The meridional extent and complex orography of the South American continent contributes to a wide diversity of climate regimes ranging from hyper-arid deserts to tropical rainforests to sub-polar highland regions. In addition, South American meteorology and climate are also made further complicated by ENSO, a powerful coupled ocean-atmosphere phenomenon. Modelling studies in this region have typically resorted to either atmospheric mesoscale or atmosphere-ocean coupled global climate models. The latter offers full physics and high spatial resolution, but it is computationally inefficient typically lack an interactive ocean, whereas the former offers high computational efficiency and ocean-atmosphere coupling, but it lacks adequate spatial and temporal resolution to adequate resolve the complex orography and explicitly simulate precipitation. Explicit simulation of precipitation is vital in the Central Andes where rainfall rates are light (0.5-5 mm hr-1), there is strong seasonality, and most precipitation is associated with weak mesoscale-organized convection. Recent increases in both computational power and model development have led to the advent of coupled ocean-atmosphere mesoscale models for both weather and climate study applications. These modelling systems, while computationally expensive, include two-way ocean-atmosphere coupling, high resolution, and explicit simulation of precipitation. In this study, we use the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST), a fully-coupled mesoscale atmosphere-ocean modeling system. Previous work has shown COAWST to reasonably simulate the entire 2003-2004 wet season (Dec-Feb) as validated against both satellite and model analysis data when ECMWF interim analysis data were used for boundary conditions on a 27-9-km grid configuration (Outer grid extent: 60.4S to 17.7N and 118.6W to 17.4W).

Regional Climate Model↗
NASA NTRSDate not supplied

Improving Ocean Reanalyses and ENSO Forecasts By Assimilation of Rain-Corrected Satellite Sea Surface Salinity Using the GMOA S2s Forecast System

The ENSO phenomenon has a significant global socio-economic impact and has been the key focus for improving coupled ocean-atmosphere forecasts. Assimilation of satellite altimetry and subsurface temperature and salinity from (mostly) Argo help improve the initialization of the thermocline, while satellite SST aids in constraining surface heat-fluxes, leading to improved coupled system sub-seasonal to seasonal forecasts. However, few studies have focused on improving the near-surface density and mixing through satellite sea surface salinity (SSS) assimilation. The few ocean models that assimilate satellite SSS, bias correct to normalize towards the near-surface Argo data for expediency. This assumption is likely inadequate in rainy regions, where buoyant water forms a fresh surface lens. In previous work, we showed that adjusting SSS to bulk salinity (Sb) using the Rain Impact Model (RIM) of Santos-Garcia et al., 2014 improves the near-surface density and mixed layer depth, leading to deeper thermocline and improved NINO3.4 SST forecasts. We now utilize the Soil Moisture and Ocean Salinity rain-corrected (SMOS_RC) SSS, available in SMOS-CATDS products, to represent Sb more accurately at the first model layer (e.g., 5 m). Rather than a diffusivity model as RIM, SMOS_RC uses a statistical correction dependent on Integrated Multi-satellitE Retrievals for GPM (IMERG) rain rates, established on observed SMOS SSS decreases related to Sb in the presence of rain (Supply et al., 2020). For all experiments, all available along-track absolute dynamic topography and in situ observations are assimilated using the LETKF scheme (Penny et al., 2013). One reanalysis additionally assimilates SMOS SSS data as is, and a separate reanalysis assimilates SMOS_RC. We assess the impact on near-surface and subsurface dynamics by validating against observations and explore how SSS assimilation (SMOS vs SMOS_RC) impacts ENSO forecasts using the NASA GMAO Sub-seasonal to Seasonal coupled forecast system (S2S-v3, Molod et al. 2020). We show that improved estimates of density and near-surface mixing led to more accurate coupled air/sea interaction and better ENSO forecasts. The increased SSS, resulting from the removal of the instantaneous rain effect, modifies the ocean state by enhancing mixing and deepening the thermocline.

Veronica Ruiz Xomchuk↗
NASA NTRS1976

Calculation of wind-driven surface currents in the North Atlantic Ocean

Calculations to simulate the wind driven near surface currents of the North Atlantic Ocean are described. The primitive equations were integrated on a finite difference grid with a horizontal resolution of 2.5 deg in longitude and latitude. The model ocean was homogeneous with a uniform depth of 100 m and with five levels in the vertical direction. A form of the rigid-lid approximation was applied. Generally, the computed surface current patterns agreed with observed currents. The development of a subsurface equatorial countercurrent was observed.

Rees, T. H.↗
NASA NTRS1993

A comparison of GCM-simulated and observed mean January and July surface air temperature

Results are presented of a comparison of four present-day GCM simulations (GFDL, OSU, GISS, and UKMO) of high-resolution surface air temperature climatology, with both January and July scenarios being evaluated for each GCM. Results indicate that the surface air temperature simulations are significantly affected by model representations of the topography, sea level pressure, and precipitation, with the other factors being the inclusion of the diurnal cycle and the type of ocean model. The GISS and UKMO GCMs were found to simulate well the mean January and July surface air temperatures, whereas the OSU GCM overestimated and the GFDL GCM underestimated the temperatures.

Willmott, Cort J.↗
NASA NTRS2007

Improving an Atlantic Fisheries DSS using Sea Surface Salinity Data from NASA's Aquarius Mission

This report assesses the capacity of incorporating NASA#s Aquarius SSS (sea surface salinity) data into the SMAST (School of Marine Science and Technology) DSS for Fisheries Science. This data will enhance the SMAST DSS by providing SSS over a large area. Aquarius is a focused satellite mission designed to measure global SSS. SSS mapping is limited because conventional in situ SSS sampling is too sparse to give a large-scale view of the salinity variability. Aquarius will resolve missing physical processes that link the water cycle, the climate, and the ocean. The SMAST Fisheries program provides a DSS for fisheries science. It collects fisheries and environmental data, integrates them into a suite of data assimilation ocean models, and provides hindcasts, nowcasts, and forecasts for fisheries research, fisheries management, and the fishery industry. Currently, SMAST is using SSS data from the National Oceanic and Atmospheric Administration#s National Data Buoy Center. The SMAST DSS would be enhanced with SSS data from the Aquarius mission.

Guest, DeNeice↗