Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “ocean observation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Low frequency oscillations in total ozone measurements

Low frequency oscillations with periods of approximately one to two months are found in eight years of global grids of total ozone data from the Total Ozone Mapping Spectrometer (TOMS) satellite instrument. The low frequency oscillations corroborate earlier analyses based on four years of data. In addition, both annual and seasonal one-point correlation maps based on the 8-year TOMS data are presented. The results clearly show a standing dipole in ozone perturbations, oscillating with 35 to 50 day periods over the equatorial Indian Ocean-west Pacific region. This contrasts with the eastward moving dipole reported in other data sets. The standing ozone dipole appears to be a dynamical feature associated with vertical atmospheric motions. Consistent with prior analyses based on lower stratospheric temperature fields, large-scale standing patterns are also found in the extratropics of both hemispheres, correlated with ozone fluctuations over the equatorial west Pacific. In the Northern Hemisphere, a standing pattern is observed extending from the tropical Indian Ocean to the north Pacific, across North America, and down to the equatorial Atlantic Ocean region. This feature is most pronounced in the NH summer.

Gao, X. H.↗
NASA NTRS1990

Low-frequency oscillations in total ozone measurements

Low frequency oscillations with periods of approximately one to two months are found in eight years of global grids of total ozone data from the Total Ozone Mapping Spectrometer (TOMS) satellite instrument. The low frequency oscillations corroborate earlier analyses based on four years of data. In addition, both annual and seasonal one-point correlation maps based on the 8-year TOMS data are presented. The results clearly show a standing dipole in ozone perturbations, oscillating with 35 to 50 day periods over the equatorial Indian Ocean-west Pacific region. This contrasts with the eastward moving dipole reported in other data sets. The standing ozone dipole appears to be a dynamical feature associated with vertical atmospheric motions. Consistent with prior analyses based on lower stratospheric temperature fields, large-scale standing patterns are also found in the extratropics of both hemispheres, correlated with ozone fluctuations over the equatorial west Pacific. In the Northern Hemisphere, a standing pattern is observed extending from the tropical Indian Ocean to the north Pacific, across North America, and down to the equatorial Atlantic Ocean region. This feature is most pronounced in the NH summer.

Gao, X. H.↗
NASA NTRS2000

Global Warming Estimation from MSU: Correction for Drift and Calibration Errors

Microwave Sounding Unit (MSU) radiometer observations in Ch 2 (53.74 GHz), made in the nadir direction from sequential, sun-synchronous, polar-orbiting NOAA morning satellites (NOAA 6, 10 and 12 that have approximately 7am/7pm orbital geometry) and. afternoon satellites (NOAA 7, 9, 11 and 14 that have approximately 2am/2pm orbital geometry) are analyzed in this study to derive global temperature trend from 1980 to 1998. In order to remove the discontinuities between the data of the successive satellites and to get a continuous time series, first we have used shortest possible time record of each satellite. In this way we get a preliminary estimate of the global temperature trend of 0.21 K/decade. However, this estimate is affected by systematic time-dependent errors. One such error is the instrument calibration error eo. This error can be inferred whenever there are overlapping measurements made by two satellites over an extended period of time. From the available successive satellite data we have taken the longest possible time record of each satellite to form the time series during the period 1980 to 1998 to this error eo. We find eo can decrease the global temperature trend by approximately 0.07 K/decade. In addition there are systematic time dependent errors ed and ec present in the data that are introduced by the drift in the satellite orbital geometry. ed arises from the diurnal cycle in temperature and ec is the drift related change in the calibration of the MSU. In order to analyze the nature of these drift related errors the multi-satellite Ch 2 data set is partitioned into am and pm subsets to create two independent time series. The error ed can be assessed in the am and pm data of Ch 2 on land and can be eliminated. Observation made in the MSU Ch 1 (50.3 GHz) support this approach. The error ec is obvious only in the difference between the pm and am observations of Ch 2 over the ocean. We have followed two different paths to assess the impact of the error ec on the global temperature trend. In one path the entire error ec is placed in the am data while in the other it is placed in the pm data. Global temperature trend is increased or decreased by approximately 0.03 K/decade depending upon this placement. Taking into account all random errors and systematic errors our analysis of MSU observations leads us to conclude that a conservative estimate of the global warming is 0. 11 (+/-) 0.04 K/decade during 1980 to 1998.

Prabhakara, C.↗
NASA NTRS1993

AVIRIS calibration and application in coastal oceanic environments

The Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) is a test-bed for future spacecraft sensors such as the High-Resolution Imaging Spectrometer and the Moderate-Resolution Imaging Spectrometers planned for the Earth Observing System. To use this sensor for ocean applications, S/N was increased by spatial averaging of images. Post-flight recalibration was accomplished by measuring in situ the water-leaving radiance at flight time, modeling its transmission to the aircraft, and adding modeled atmospheric radiance to that value. The preflight calibration curve was then adjusted until aircraft and modeled total radiance values matched. Water-leaving radiance values from the recalibrated AVIRIS imagery were consistent with in situ data supporting the validity of the approach. Imagery of the absorption coefficient at 415 nm and backscattering coefficient at 671 nm were used to depict the dissolved and particulate constituents of the Tampa Bay plume during late, ebb-tidal conditions.

Carder, Kendall L.↗
NASA NTRS1992

AVIRIS calibration and application in coastal oceanic environments

The Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) is a test-bed for future spacecraft sensors such as the High-Resolution Imaging Spectrometer and the Moderate-Resolution Imaging Spectrometers planned for the Earth Observing System. To use this sensor for ocean applications, S/N was increased by spatial averaging of images. Post-flight recalibration was accomplished using in situ the water-leaving radiance measured at flight time, modeling radiance transmission to the aircraft, and adding modeled atmospheric radiance to that value. The preflight calibration curve was then adjusted until aircraft and modeled total radiance values matched. Water-leaving radiance values from the recalibrated AVIRIS imagery were consistent with in situ data supporting the validity of the approach. Imagery of the absorption coefficient at 415 nm and backscattering coefficient at 671 nm were used to depict the dissolved and particulate constituents of an ebb-tidal esturance plume on the East coast of Florida.

Carder, Kendall L.↗
NASA NTRS2007

Lessons Learned from the Aquarius Radiometer Engineering Model

The Aquarius instrument is a combination microwave radiometer and scatterometer operating in the L-band for the measurement of sea surface salinity (SSS) over the open-ocean. "The Aquarius science goals are to observe and model the processes that relate salinity variations to climatic changes in the global cycling of water and to understand how these variations influence the general ocean circulation. By measuring salinity globally and synoptically every month for 3 years, Aquarius will provide an unprecedented new view of the ocean's role in climate." (http://aquarius.asfc.nasa.gov on Jan. 4, 2007). To launch in 2009, Aquarius will provide 8-day global coverage and monthly-averaged salinity maps at approx.120-km spatial resolution. Because the microwave emissivity of the ocean surface is weakly dependent upon salinity, the Aquarius radiometer remain sufficiently stable to provide accurate salinity measurements. An engineering model (EM) of one radiometer receiver was developed and tested for functionality and performance at NASA's Goddard Space Flight Center. It was tested for long-term stability starting July 27,2006. Two discrepancies where found at the start of testing and a four-month correction process ensued. This paper covers the testing and debugging of the EM radiometer through resolution of the problems. The radiometer is required to have calibration stability of less than or equal to 0.15 K over 7 days. The radiometer is in a three-beam push-broom configuration with each beam being an independent three-state Dicke radiometer (antenna, reference load, and additive noise). Internal noise diodes and reference loads provide periodic and rapid calibration of the receiver. Front-end loss contributions must be corrected as the lossy components are outside the calibration loop. A key design feature for obtaining stability is active thermal control of the front-end lossy components and the RF receiver. The thermal stability is predicted to be about 0.1 C over an orbit and no more than 1 C over a year. The radiometric stability requirement is 0.13 K rms 1 7 days without using temperature corrections. Temperature corrections and post-launch calibration are expected to extend the stability period through the life of the mission.

Piepmeier, Jeffrey↗
NASA NTRS2022

Global Hydrogen Abundances on the Lunar Surface

A global map of bulk hydrogen abundances on the Moon is presented. This map was generated using data from the Lunar Prospector Neutron Spectrometer. This map required corrections for variations due to rare-earth elements, and was calibrated to Apollo sample hydrogen abundances. Since neutron-derived measurements sample hydrogen content to a depth of tens of cm, these results provide complementary insights to those provided by studies using spectral reflectance data, which sample depths of order μm. Comparison of these abundances to Apollo sample values suggest that the samples reflect actual hydrogen content on the lunar surface, not dominantly from non-lunar contamination. The average lunar hydrogen abundance is 47 ppm with a systematic uncertainty of ∼10 ppm. This is consistent with bulk hydrogen from solar wind emplacement. A bulk hydrogen enhancement (50–68 ppm) has been identified at the Moon's largest pyroclastic deposit (Aristarchus Plateau), which corroborates prior observations that hydrogen and/or water plays a role in lunar magmatic events. Global data show a correlation between hydrogen and evolved materials rich in incompatible trace elements (i.e., KREEP type rocks), with a hydrogen excess of 14–36 ppm in these materials. Based on this hydrogen enhancement, we estimate a lower-limit water abundance within urKREEP materials (i.e., the final ∼2% of the lunar magma ocean) of 320–820 ppm H2O. This observation implies that water played a role in the original magma-ocean formation and solidification with a lower-limit water content in the original lunar magma ocean of 7–16 ppm or higher.

David J. Lawrence↗
NASA NTRS2018

Impact of Satellite Sea Surface Salinity Observations on ENSO Predictions from the GMAO S2S Forecast System

El Nino/Southern Oscillation (ENSO) has far reaching global climatic impacts and so extending useful ENSO forecasts would be of great benefit for society. However, one key variable that has yet to be fully exploited within coupled forecast systems is accurate estimation of near-surface ocean density. Satellite Sea Surface Salinity (SSS), combined with temperature, help to identify ocean density changes and associated mixing near the ocean surface. We assess the impact of satellite SSS observations for improving near-surface dynamics within ocean analyses and how these impact dynamical ENSO forecasts using the NASA GMAO (Global Modeling and Assimilation Office) Sub-seasonal to Seasonal (S2S_v2.1) coupled forecast system (Molod et al. 2018 - i.e. NASA's contribution to the NMME (National Multi-Model Ensemble) project). For all initialization experiments, all available along-track absolute dynamic topography and in situ observations are assimilated using the LETKF ( Local Ensemble Transform Kalman Filter) scheme similar to Penny et al., 2013. A separate reanalysis additionally assimilates Aquarius V5 (September 2011 to June 2015) and SMAP (Soil Moisture Active Passive) V4 (March 2015 to present) along-track data.We highlight the impact of satellite SSS on ocean reanalyses by comparing validation statistics of experiments that assimilate SSS versus our current prediction system that withholds SSS. We find that near-surface validation versus observed statistics for salinity are slightly degraded when assimilating SSS. This is an expected result due to known biases between SSS (measured by the satellite at approximately 1 centimeter) and in situ measurements (typically measured by Argo floats at 3 meters). On the other hand, a very encouraging result is that both temperature, absolute dynamic topography, and mixed layer statistics are improved with SSS assimilation. Previous work has shown that correcting near-surface density structure via gridded SSS assimilation can improve coupled forecasts. Here we present results of coupled forecasts that are initialized from the GMAO S2S reanalyses that assimilates/withholds along-track (L2) SSS. In particular, we contrast forecasts of the overestimated 2014 El Nino, the big 2015 El Nino, and the minor 2016 La Nina. For each of these ENSO scenarios, assimilation of satellite SSS improves the forecast validation. Improved SSS and density upgrades the mixed layer depth leading to more accurate coupled air/sea interaction.

Hackert, E.↗
NASA NTRS2009

An Empirical Approach to Ocean Color Data: Reducing Bias and the Need for Post-Launch Radiometric Re-Calibration

A new empirical approach is developed for ocean color remote sensing. Called the Empirical Satellite Radiance-In situ Data (ESRID) algorithm, the approach uses relationships between satellite water-leaving radiances and in situ data after full processing, i.e., at Level-3, to improve estimates of surface variables while relaxing requirements on post-launch radiometric re-calibration. The approach is evaluated using SeaWiFS chlorophyll, which is the longest time series of the most widely used ocean color geophysical product. The results suggest that ESRID 1) drastically reduces the bias of ocean chlorophyll, most impressively in coastal regions, 2) modestly improves the uncertainty, and 3) reduces the sensitivity of global annual median chlorophyll to changes in radiometric re-calibration. Simulated calibration errors of 1% or less produce small changes in global median chlorophyll (less than 2.7%). In contrast, the standard NASA algorithm set is highly sensitive to radiometric calibration: similar 1% calibration errors produce changes in global median chlorophyll up to nearly 25%. We show that 0.1% radiometric calibration error (about 1% in water-leaving radiance) is needed to prevent radiometric calibration errors from changing global annual median chlorophyll more than the maximum interannual variability observed in the SeaWiFS 9-year record (+/- 3%), using the standard method. This is much more stringent than the goal for SeaWiFS of 5% uncertainty for water leaving radiance. The results suggest ocean color programs might consider less emphasis of expensive efforts to improve post-launch radiometric re-calibration in favor of increased efforts to characterize in situ observations of ocean surface geophysical products. Although the results here are focused on chlorophyll, in principle the approach described by ESRID can be applied to any surface variable potentially observable by visible remote sensing.

Gregg, Watson W.↗
NASA NTRS2019

Impact of Satellite Sea Surface Salinity Observations on ENSO Predictions from the GMAO Seasonal Forecast System

El Nino/Southern Oscillation (ENSO) has far reaching global climatic impacts and so extending useful ENSO forecasts would be of great benefit for society. However, one key variable that has yet to be fully exploited within coupled forecast systems is accurate estimation of near-surface ocean density. Satellite sea surface salinity (SSS), combined with temperature, help to identify ocean density changes and associated mixing near the ocean surface. We assess the impact of satellite SSS observations for improving near-surface dynamics within ocean analyses and how these impact dynamical ENSO forecasts using the NASA GMAO (Global Modeling and Assimilation Office) Sub-seasonal to Seasonal (S2S_v2.1) coupled forecast system (Molod et al. 2018 - i.e. NASA's contribution to the NMME (North American Multi-Model Ensemble) project). For all initialization experiments, all available along-track absolute dynamic topography and in situ observations are assimilated using the LETKF (Local Ensemble Transform Kalman Filter) scheme similar to Penny et al., 2013. A separate reanalysis additionally assimilates Aquarius V5 (September 2011 to June 2015) and SMAP (Soil Moisture Active Passive satellite) V4.1 (March 2015 to present) along-track data.We highlight the impact of satellite SSS on ocean reanalyses by comparing validation statistics of experiments that assimilate SSS versus our current prediction system that withholds SSS. We find that near-surface validation versus observed statistics for salinity are slightly degraded when assimilating SSS. This is an expected result due to known biases between SSS (measured by satellite at approximately 1-centimeter depth) and in situ measurements (typically measured by Argo floats at 3-meters depth). On the other hand, a very encouraging result is that both temperature, absolute dynamic topography, and mixed layer statistics are improved with SSS assimilation. Previous work has shown that correcting near-surface density structure via gridded SSS assimilation can improve coupled forecasts. Here we present results of coupled forecasts that are initialized from GMAO S2S spring reanalyses that assimilate/withhold along-track (L2) SSS. In particular, we contrast forecasts of the big 2015 El Nino, the 2017 La Nina and the 2018 weak El Nino. For each of these ENSO scenarios, assimilation of satellite SSS improves the forecast validation. Improved SSS and density upgrade the mixed layer depth leading to more accurate coupled air/sea interaction. From March to June 2015, the availability of two overlapping satellite SSS instruments, Aquarius and SMAP, allows a unique opportunity to compare and contrast forecasts initialized with the benefit of these two satellite SSS observation types. We assess the impact of gridded satellite sea surface salinity observations on dynamical ENSO forecasts for the big 2015 El Nino.

Hackert, E.↗
NASA NTRS1986

Hydrodynamics of internal solitons and a comparison of SIR-A and SIR-B data with ocean measurements

Large internal solitary waves have been observed by Shuttle SIR-A and SIR-B at locations in the Andaman Sea and the New York Bight. Satellite imagery and oceanographic measurements are used in conjunction with hydrodynamic interaction and electromagnetic scattering models to estimate the expected SAR image intensity modulations associated with the internal waves. There is reasonable agreement between the predicted and observed internal wave signatures.

Apel, J. R.↗
NASA NTRS2002

Visions of our Planet's Atmosphere, Land and Oceans

The NASA/NOAA Electronic Theater presents Earth science observations and visualizations in a historical perspective. Fly in from outer space to South Africa, Cape Town and Johannesburg using NASA Terra/MODIS data, Landsat data and 1 m IKONOS 'Spy Satellite' data. Zoom in to any place South Africa using Earth Viewer 3D from Keyhole Inc. and Landsat data at 30 m resolution Go back to the early weather satellite images from the 1960s and see them contrasted with the latest US and international global satellite weather movies including hurricanes & 'tornadoes'. See the latest visualizations of spectacular images from NASANOAA remote sensing missions like Terra, GOES, TRMM, SeaWiFS, Landsat 7 including 1 - min GOES rapid scan image sequences of Nov 9th 2001 Midwest tornadic thunderstorms and have them explained.

Hasler, A. F.↗
NASA NTRS2006

The Effect of the Saharan Air Layer on the Formation of Hurricane Isabel (2003) Simulated with AIRS Data

The crucial physics of how the atmosphere really accomplishes the tropical cyclogenesis process is still poorly understood. The presence of the Saharan Air Layer (SAL), an elevated mixed layer of warm and dry air that extends from Africa to the tropical Atlantic and contains a substantial amount of mineral dust, adds more complexity to the tropical cyclogenesis process in the Atlantic basin. The impact of the SAL on tropical cyclogenesis is still uncertain. Karyampudi and Carlson (1988) conclude that a strong SAL can potentially aid tropical cyclone development while Dunion and Velden (2004) argue that the SAL generally inhibits tropical cyclogenesis and intensification. Advancing our understanding of the physical mechanisms of tropical cyclogenesis and the associated roles of the SAL strongly depends on the improvement in the observations over the data-sparse ocean areas. After the Atmospheric Infrared Sounder (AIRS), the Advanced Microwave Sounding Unit (AMSU), and the microwave Humidity Sounder of Brazil (HSB) were launched with the NASA Aqua satellite in 2002, new data products retrieved from the AIRS suite became available for studying the effect of the warm, dry air mass associated with the SAL (referred to as the thermodynamic effect). The vertical profiles of the AIRS retrieved temperature and humidity provide an unprecedented opportunity to examine the thermodynamic effect of the SAL. The observational data can be analyzed and assimilated into numerical models, in which the model thermodynamic state is allowed to relax to the observed state from AIRS data. The objective of this study is to numerically demonstrate that the thermodynamic effect of the SAL on the formation of Hurricane Isabel (2003) can be largely simulated through nudging of the AIRS data.

Wu, iguang↗
NASA NTRS2019

Atmospheric Correction for Coastal Waters Based on Multi-Angle Polarimetric Observations

Atmospheric correction is an essential procedure of ocean color remote sensing, which obtains water-leaving signals from satellite or airborne sensors. Due to the small percentage of the water leaving signals in the total measurement, atmospheric correction requires precise evaluation of the radiometric contributions from the aerosol and ocean surface. It is often challenging over coastal waters when absorbing aerosols are present and when water leaving signals in the near infrared spectral region are non-negligible. In this work, we report on a joint retrieval algorithm that determines aerosol and ocean optical properties using the polarimetric measurements based on a coupled atmosphere and ocean radiative transfer model. Two bio-optical models are designed for ocean water properties. One model parameterizes the open ocean optical properties in terms of the concentration of chlorophyll a. The other is a generalized bio-optical model for coastal waters that describes the absorption and scattering by phytoplankton, colored dissolved organic matter and non-algal particles using multiple parameters. We applied the algorithm to the airborne Research Scanning Polarimeter (RSP) measurements acquired over both open and coastal ocean waters. Through the comparisons with in situ ocean color measurements, the flexibility and accuracy of the retrieval algorithm in retrieving aerosol and water leaving radiance properties are demonstrated under various aerosol and ocean water conditions.

Gao, Meng↗
NASA NTRS2022

Gulf of Maine Water Resources: Assessing the Use of Nasa Earth Observations for Identifying Harmful Algal Blooms of Pseudo-Nitzschia in the Gulf of Maine

The Gulf of Maine has a history of harmful algal blooms (HABs) that have been increasing in frequency and intensity in recent years, raising concerns in the community. Specifically, the Pseudo-nitzschia genus possesses harmful toxins that can induce food-borne illnesses and infect humans through ambient water. We observed in-situ data from known 2016 and 2020 Pseudo-nitzschia blooms as case studies to test the feasibility of using satellite data to track bloom events. In order to map the frequency and distribution of Pseudo-nitzschia bloom events, we used satellite data from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Sentinel-3 Ocean and Land Colour Instrument (OLCI). We utilized Earth observation data to calculate normalized fluorescence line height (nFLH) and absorption by phytoplankton (aph443), which are satellite products that more accurately depict phytoplankton reflectance. We compared these products with in-situ observations in order to analyze ocean color differences and distinguish diatomic algal particles from other organic and inorganic particles.

harmful algal blooms↗
DOE OSTI2023

Vertical Structure and Ice Production Processes of Shallow Convective Postfrontal Clouds over the Southern Ocean in MARCUS. Part II: Modeling Study

Abstract Part I of this series presented a detailed overview of postfrontal mixed-phase clouds observed during the Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) field campaign. In Part II, we focus on a multiday (23–26 February 2018) case with the aim of understanding ice production as well as model sensitivity to ice process parameterizations using the Weather Research and Forecasting (WRF) Model. The control simulation with the Predicted Particle Properties (P3) microphysics scheme underestimates the ice content and overestimates the supercooled liquid water content, contrary to the bias common in global climate models. The simulations targeted at ice production processes show negligible sensitivity to cloud droplet number concentrations. Further, neither increasing ice nuclei particle (INP) concentrations to an unrealistic level nor adjusting it to MARCUS field estimations alone guarantees more ice production in the model. However, the simulated clouds are found to be highly sensitive to the implementation of immersion freezing, the thresholding of condensation/deposition freezing initiation, and the rime splintering process. By increasing immersion freezing of cloud droplets, relaxing thresholds for condensation/deposition freezing, or removing rime splintering thresholds, the model significantly improves its performance in producing ice. The relaxation of the immersion freezing temperature threshold to the observed cloud-top temperature suggests an in-cloud seeder–feeder mechanism. The results of this work call for an increase in observations of INP, especially over the remote Southern Ocean and at relatively high temperatures, and measurements of ice particle size distributions to better constrain ice nucleating processes in models.

Meteorology & Atmospheric Sciences↗