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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Long-Period Tidal Variations in the Length of Day

A new model of long-period tidal variations in length of day is developed. The model comprises 80 spectral lines with periods between 18.6 years and 4.7 days, and it consistently includes effects of mantle anelasticity and dynamic ocean tides for all lines. The anelastic properties followWahr and Bergen; experimental confirmation for their results now exists at the fortnightly period, but there remains uncertainty when extrapolating to the longest periods. The ocean modeling builds on recent work with the fortnightly constituent, which suggests that oceanic tidal angular momentum can be reliably predicted at these periods without data assimilation. This is a critical property when modeling most long-period tides, for which little observational data exist. Dynamic ocean effects are quite pronounced at shortest periods as out-of-phase rotation components become nearly as large as in-phase components. The model is tested against a 20 year time series of space geodetic measurements of length of day. The current international standard model is shown to leave significant residual tidal energy, and the new model is found to mostly eliminate that energy, with especially large variance reduction for constituents Sa, Ssa, Mf, and Mt.

LOD tidal oscillations↗
NASA NTRS2014

Background Error Covariance Estimation using Information from a Single Model Trajectory with Application to Ocean Data Assimilation into the GEOS-5 Coupled Model

An attractive property of ensemble data assimilation methods is that they provide flow dependent background error covariance estimates which can be used to update fields of observed variables as well as fields of unobserved model variables. Two methods to estimate background error covariances are introduced which share the above property with ensemble data assimilation methods but do not involve the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The Space Adaptive Forecast error Estimation (SAFE) algorithm estimates error covariances from the spatial distribution of model variables within a single state vector. The Flow Adaptive error Statistics from a Time series (FAST) method constructs an ensemble sampled from a moving window along a model trajectory. SAFE and FAST are applied to the assimilation of Argo temperature profiles into version 4.1 of the Modular Ocean Model (MOM4.1) coupled to the GEOS-5 atmospheric model and to the CICE sea ice model. The results are validated against unassimilated Argo salinity data. They show that SAFE and FAST are competitive with the ensemble optimal interpolation (EnOI) used by the Global Modeling and Assimilation Office (GMAO) to produce its ocean analysis. Because of their reduced cost, SAFE and FAST hold promise for high-resolution data assimilation applications.

Data Assimilation↗
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 NTRS1983

TOPEX watershed coming in oceanography

The NASA Ocean Topography Experiment (TOPEX) will use precision radar altimetry to determine topographic features of the global oceans from which currents may be deduced. TOPEX will coincide with the World Ocean Circulation Experiment (WOCE), which will be conducted at the end of this decade and shall involve ships, fixed and drifting buoys, aircraft observations, and satellite remote sensing, to resolve fundamental questions about the flow of water in the global ocean. TOPEX will contribute to WOCE the measurement of satellite height above the sea surface, and the precise radial position above a reference ellipsoid for the earth. The combination of these two measurements with the marine geoid yields the topographic data sought. Three years of topographic data, together with conventional oceanographic data and theoretical ocean models, will be needed to derive the mean and variable components of ocean circulation.

Cleven, G. C.↗
NASA NTRS1999

Determining the Ocean's Role on the Variable Gravity Field on Earth Rotation

A number of ocean models of different complexity have been used to study changes in the oceanic mass field and angular momentum and their relation to the variable Earth rotation and gravity field. Time scales examined range from seasonal to a few days. Results point to the importance of oceanic signals in driving polar motion, in particular the Chandler and annual wobbles. Results also show that oceanic signals have a measurable impact on length-of-day variations. Various circulation features and associated mass signals, including the North Pacific subtropical gyre, the equatorial currents, and the Antarctic Circumpolar Current play a significant role in oceanic angular momentum variability.

Ponte, Rui M.↗
NASA NTRS2003

Observed and Modeled Trends in Southern Ocean Sea Ice

Conceptual models and global climate model (GCM) simulations have both indicated the likelihood of an enhanced sensitivity to climate change in the polar regions, derived from the positive feedbacks brought about by the polar abundance of snow and ice surfaces. Some models further indicate that the changes in the polar regions can have a significant impact globally. For instance, 37% of the temperature sensitivity to a doubling of atmospheric CO2 in simulations with the GCM of the Goddard Institute for Space Studies (GISS) is attributable exclusively to inclusion of sea ice variations in the model calculations. Both sea ice thickness and sea ice extent decrease markedly in the doubled CO, case, thereby allowing the ice feedbacks to occur. Stand-alone sea ice models have shown Southern Ocean hemispherically averaged winter ice-edge retreats of 1.4 deg latitude for each 1 K increase in atmospheric temperatures. Observations, however, show a much more varied Southern Ocean ice cover, both spatially and temporally, than many of the modeled expectations. In fact, the satellite passive-microwave record of Southern Ocean sea ice since late 1978 has revealed overall increases rather than decreases in ice extents, with ice extent trends on the order of 11,000 sq km/year. When broken down spatially, the positive trends are strongest in the Ross Sea, while the trends are negative in the Bellingshausen/Amundsen Seas. Greater spatial detail can be obtained by examining trends in the length of the sea ice season, and those trends show a coherent picture of shortening sea ice seasons throughout almost the entire Bellingshausen and Amundsen Seas to the west of the Antarctic Peninsula and in the far western Weddell Sea immediately to the east of the Peninsula, with lengthening sea ice seasons around much of the rest of the continent. This pattern corresponds well with the spatial pattern of temperature trends, as the Peninsula region is the one region in the Antarctic with a strong record of temperature increases. Still, although the patterns of the temperature and ice changes match fairly well, there is a substantial ways to go before these patterns are understood (and can be modeled) in the full context of global change.

Parkinson, Claire L.↗
NASA NTRS2022

Along-Orbit Analysis of GRACE Follow-On Inter-Satellite Laser Ranging Measurements for Sub-Monthly Surface Mass Variations

We examined the sensitivity of GRACE Follow-On (GRACE-FO) laser ranging interferometer (LRI) measurements to sub-monthly time-variable gravity (TVG) signals caused by transient, high-frequency mass changes in the Earth system. GRACE-FO LRI provides complementary inter-satellite ranging measurements with higher precision over a wider range of frequencies than the baseline K-band microwave ranging system. The common approach for studying mass variation relies on the inverted TVG or mascon solutions over a period of, for example, one month or 10 days which are adversely affected by temporal aliasing and/or smoothing. In this article, we present the alternative along-orbit analysis methodology in terms of line-of-sight gravity difference (LGD) to fully exploit the higher precision LRI measurements for examination of sub-monthly mass changes. The discrepancy between “instantaneous” LGD LRI observations and monthly mean LGD (from Level-2 data) at satellite altitude indicates the sub-monthly gravitational variability not captured by monthly-mean solutions. In conjunction with the satellite ocean altimetry observations, high frequency non-tidal atmosphere and ocean models, and hydrology models, we show that the LGD LRI observations detect the high-frequency oceanic mass variability in the Argentine Basin and the Gulf of Carpentaria, and sub-monthly variations in surface (river) water in the Amazon Basin. We demonstrate the benefits gained from repeat ground track analysis of GRACE-FO LRI data in the case of the Amazon surface water flow. The along-orbit analysis methodology based on LGD LRI time series presented here is especially suitable for quantifying temporal and spatial evolution of extreme, rapidly changing mass variations.

Khosro Ghobadi-Far↗
NASA NTRS2001

Simulation of Climatic Changes in the Arctic and North Atlantic During Recent Decades

The interactions of the atmosphere and ice-ocean system in the Arctic will be studied using a coupled ice-ocean model which will also use ice drift derived from microwave observations as forcing. We especially search for linkages between the recent large climatic shifts in the Arctic Ocean and atmosphere for which period we also have microwave sea ice data. The coupled model area covers the whole N. Atlantic thus interactions between the lower latitudes are also investigated because we anticipate that the same large scale atmospheric patterns which dominate the midlatitudes extend their influence on the Arctic. The model hindcast for 1951-1993 shows clear decadal variability in the leading modes of ocean circulation. No specific low-freq modes are expected for the ice drift because its spectrum is white. However, the ice drift exhibits two see-saw patterns in response to the leading atmospheric circulation mode ('Arctic Oscillation'), one of them is the well-known out of phase relationship between Baffin Bay and Barents-Kara Seas, the other one is between Siberian shelf and Alaskan Coast (Hakkinen and Geiger, 2000).

Hakkinen, Sirpa↗
NASA NTRS2000

Atlas of Seasonal Means Simulated by the NSIPP 1 Atmospheric GCM

This atlas documents the climate characteristics of version 1 of the NASA Seasonal-to-Interannual Prediction Project (NSIPP) Atmospheric General Circulation Model (AGCM). The AGCM includes an interactive land model (the Mosaic scheme), and is part of the NSIPP coupled atmosphere-land-ocean model. The results presented here are based on a 20-year (December 1979-November 1999) "ANIIP-style" integration of the AGCM in which the monthly-mean sea-surface temperature and sea ice are specified from observations. The climate characteristics of the AGCM are compared with the National Centers for Environmental Prediction (NCEP) and the European Center for Medium-Range Weather Forecasting (ECMWF) reanalyses. Other verification data include Special Sensor Microwave/Imager (SSNM) total precipitable water, the Xie-Arkin estimates of precipitation, and Earth Radiation Budget Experiment (ERBE) measurements of short and long wave radiation. The atlas is organized by season. The basic quantities include seasonal mean global maps and zonal and vertical averages of circulation, variance/covariance statistics, and selected physics quantities.

Suarez, Max J.↗
NASA NTRS1996

Responses of the Tropical Pacific to Wind Forcing as Observed by Spaceborne Sensors and Simulated by an Ocean General Circulation Model

In this study, satellite observations, in situ measurements, and model simulations are combined to assess the oceanic response to surface wind forcing in the equatorial Pacific. The surface wind fields derived from observations by the spaceborne special sensor microwave imager (SSM/I) and from the operational products of the European Centre for Medium-Range Weather Forecasts (ECMWF) are compared. When SSM/I winds are used to force a primitive-equation ocean general circulation model (OGCM), they produce 3 C more surface cooling than ECMWF winds for the eastern equatorial Pacific during the cool phase of an El Nino-Southern Oscillation event. The stronger cooling by SSM/I winds is in good agreement with measurements at the moored buoys and observations by the advanced very high resolution radiometer, indicating that SSM/I winds are superior to ECMWF winds in forcing the tropical ocean. In comparison with measurements from buoys, tide gauges, and the Geosat altimeter, the OGCM simulates the temporal variations of temperature, steric, and sea level changes with reasonable realism when forced with the satellite winds. There are discrepancies between model simulations and observations that are common to both wind forcing fields, one of which is the simulation of zonal currents; they could be attributed to model deficiencies. By examining model simulations under two winds, vertical heat advection and uplifting of the thermocline are found to be the dominant factors in the anomalous cooling of the ocean mixed layer.

Liu, W. Timothy↗
NASA NTRS2004

Crustal Magnetization Model of Maud Rise in the Southwest Indian Ocean

We modeled the crustal magnetization for the Maud Rise in the south-west Indian Ocean off the coast of East Antarctica using magnetic observations from the Oersted satellite and near-surface surveys complied by the Antarctic Digital Magnetic Anomaly Project (ADMAP). A new inversion modeling scheme of the multi-altitude anomaly fields suggests that the magnetic effects due to crustal thickness variations and remanence involving the normal polarity Cretaceous Quiet Zone (KQZ) become increasingly dominant with altitude. The magnetic crustal thickness effects were modeled in the Oersted data using crustal thickness variations derived from satellite altitude gravity data. Remanent magnetization modeling of the residual Oersted and near-surface magnetic anomalies supports extending the KQZ eastwards to the Astrid Ridge. The remaining near-surface anomalies involve crustal features with relatively high frequency effects that are strongly attenuated at satellite altitudes. The crustal modeling can be extended by the satellite magnetic anomalies across the Indian Ocean Ridge for insight on the crustal properties of the conjugate Agulhas Plateau. The modeling supports the Jurassic reconstruction of Gondwana when the African Limpopo-Zambezi and East Antarctic Princess Astrid coasts were connected as part of a relatively demagnetized crustal block.

Kim, Hyung Rae↗
NASA NTRS2001

Dynamical Interpolation of Mesoscale Flows in the TOPEX/Poseidon Diamond Surrounding the U.S. Joint Global Ocean Flux Study Bermuda Atlantic Time-Series Study Site

An open boundary ocean model is configured in a domain bounded by the four TOPEX/Poseidon (T/P) ground tracks surrounding the US Joint Global Ocean Flux Study Bermuda Atlantic Time-Series Study (BATS) site. This implementation facilitates prescription of model boundary conditions directly from altimetric measurements (both TIP and ERS-2). The expected error characteristics for a domain of this size with periodically updated boundary conditions are established with idealized numerical experiments using simulated data. A hindcast simulation is then constructed using actual altimetric observations during the period October 1992 through September 1998. Quantitative evaluation of the simulation suggests significant skill. The correlation coefficient between predicted sea level anomaly and ERS observations in the model interior is 0.89; that for predicted versus observed dynamic height anomaly based on hydrography at the BATS site is 0.73. Comparison with the idealized experiments suggests that the main source of error in the hindcast is temporal undersampling of the boundary conditions. The hindcast simulation described herein provides a basis for retrospective analysis of BATS observations in the context of the mesoscale eddy field.

McGillicuddy, Dennis J., Jr.↗
NASA NTRS2001

Dynamical Interpolation of Mesoscale Flows in the TOPEX/ Poseidon Diamond Surrounding the U.S. Joint Global Ocean Flux Study Bermuda Atlantic Time-Series Study Site

An open boundary ocean model is configured in a domain bounded by the four TOPEX/Poseidon (TIP) ground tracks surrounding the U.S. Joint Global Ocean Flux Study Bermuda Atlantic Time-series Study (BATS) site. This implementation facilitates prescription of model boundary conditions directly from altimetric measurements (both TIP and ERS-2). The expected error characteristics for a domain of this size with periodically updated boundary conditions are established with idealized numerical experiments using simulated data. A hindcast simulation is then constructed using actual altimetric observations during the period October 1992 through September 1998. Quantitative evaluation of the simulation suggests significant skill. The correlation coefficient between predicted sea level anomaly and ERS observations in the model interior is 0.89; that for predicted versus observed dynamic height anomaly based on hydrography at the BATS site is 0.73. Comparison with the idealized experiments suggests that the main source of error in the hindcast is temporal undersampling of the boundary conditions. The hindcast simulation described herein provides a basis for retrospective analysis of BATS observations in the context of the mesoscale eddy field.

McGillicuddy, D. J.↗
NASA NTRS2018

GEOS-5 Seasonal Forecast System: ENSO Prediction Skill and Bias

The GEOS-5 AOGCM known as S2S-1.0 has been in service from June 2012 through January 2018 (Borovikov et al. 2017). The atmospheric component of S2S-1.0 is Fortuna-2.5, the same that was used for the Modern-Era Retrospective Analysis for Research and Applications (MERRA), but with adjusted parameterization of moist processes and turbulence. The ocean component is the Modular Ocean Model version 4 (MOM4). The sea ice component is the Community Ice CodE, version 4 (CICE). The land surface model is a catchment-based hydrological model coupled to the multi-layer snow model. The AGCM uses a Cartesian grid with a 1 deg × 1.25 deg horizontal resolution and 72 hybrid vertical levels with the upper most level at 0.01 hPa. OGCM nominal resolution of the tripolar grid is 1/2 deg, with a meridional equatorial refinement to 1/4 deg. In the coupled model initialization, selected atmospheric variables are constrained with MERRA. The Goddard Earth Observing System integrated Ocean Data Assimilation System (GEOS-iODAS) is used for both ocean state and sea ice initialization. SST, T and S profiles and sea ice concentration were assimilated.

GEOS-↗
NASA NTRS1995

Simulated interannual variability of the Greenland Sea deep water formation and its connection to surface forcing

A fully prognostic Arctic ice-ocean model is used to study the interannual variability of deepwater formation in the Greenland Sea Gyre based on the simulations for the Arctic ice-ocean system for the period 1955 and 1960 - 1985. The model uses monthly climatology for thermodynamic forcing components (such as air temperature and cloudiness), together with constant annual net precipitation and river runoff. The daily wind forcing is derived from analyzed sea level air pressures from the National Center for Atmospheric Research (NCAR). In summary, the model shows that the occurence of deep convection in the Greenland Sea Gyre is controlled by the extensive Fram Strait ice export and/or local wind conditions in the Greenland Sea. In the latter case the weakening of the local wind curl allows the Polar Front to move eastward. The movement of the Polar Front causes adverse ice conditions, often together with much larger than normal ice export from the Arctic, such as in 1968, which can block convection in the gyre. The density difference between upper and lower layers is investigated as an indication of water mass formation through convection, occurring as strong diffusion in the model. The model-simulated density difference between the average top 100 m and deep levels reveals that the period 1960 - 1985 had only a few distinct years with weak stratification, and, especially, the model predicts no deep convection since the nid-1970s. The common factor for the years of the weakest decrease of the model-predicted heat content of the upper 2000 m which can, to a high degree, be explained by local heat loss.

Haekkinen, Sirpa↗
NASA NTRS2015

Is Ice-Rafted Sediment in a North Pole Marine Record Evidence for Perennial Sea-ice Cover?

Ice-rafted sediments of Eurasian and North American origin are found consistently in the upper part (13 Ma BP to present) of the Arctic Coring Expedition (ACEX) ocean core from the Lomonosov Ridge, near the North Pole (approximately 88 degrees N). Based on modern sea-ice drift trajectories and speeds, this has been taken as evidence of the presence of a perennial sea-ice cover in the Arctic Ocean from the middle Miocene onwards. However, other high latitude land and marine records indicate a long-term trend towards cooling broken by periods of extensive warming suggestive of a seasonally ice-free Arctic between the Miocene and the present. We use a coupled sea-ice slab-ocean model including sediment transport tracers to map the spatial distribution of ice-rafted deposits in the Arctic Ocean. We use 6 hourly wind forcing and surface heat fluxes for two different climates: one with a perennial sea-ice cover similar to that of the present day and one with seasonally ice-free conditions, similar to that simulated in future projections. Model results confirm that in the present-day climate, sea ice takes more than 1 year to transport sediment from all its peripheral seas to the North Pole. However, in a warmer climate, sea-ice speeds are significantly faster (for the same wind forcing) and can deposit sediments of Laptev, East Siberian and perhaps also Beaufort Sea origin at the North Pole. This is primarily because of the fact that sea-ice interactions are much weaker with a thinner ice cover and there is less resistance to drift. We conclude that the presence of ice-rafted sediment of Eurasian and North American origin at the North Pole does not imply a perennial sea-ice cover in the Arctic Ocean, reconciling the ACEX ocean core data with other land and marine records.

Palaeoclimate↗
NASA NTRS1991

On the remote forcing of the circulation in the Bay of Bengal

The paper presents a hypothesis that the remote forcing is one of the mechanisms that determine the semiannual reversal of the upper ocean circulation in the Bay of Bengal. A simple reduced-gravity oceanic model is used to explain the hypothesis. Three numerical experiments have been performed to compare the oceanic responses to a remote forcing, a local forcing, and a combined forcing. It is found that the long Rossby waves excited by the remotely forced Kelvin waves contribute substantially to the variability of the local circulation. This research indicates that equatorial Kelvin waves are one of the major factors determining the circulation in the eastern equatorial Indian Ocean.

Yu, Lisan↗
NASA NTRS1992

World Ocean Circulation Experiment

The oceans are an equal partner with the atmosphere in the global climate system. The World Ocean Circulation Experiment is presently being implemented to improve ocean models that are useful for climate prediction both by encouraging more model development but more importantly by providing quality data sets that can be used to force or to validate such models. WOCE is the first oceanographic experiment that plans to generate and to use multiparameter global ocean data sets. In order for WOCE to succeed, oceanographers must establish and learn to use more effective methods of assembling, quality controlling, manipulating and distributing oceanographic data.

Clarke, R. Allyn↗