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NASA NTRS2011

Seafloor Control on Sea Ice

The seafloor has a profound role in Arctic sea ice formation and seasonal evolution. Ocean bathymetry controls the distribution and mixing of warm and cold waters, which may originate from different sources, thereby dictating the pattern of sea ice on the ocean surface. Sea ice dynamics, forced by surface winds, are also guided by seafloor features in preferential directions. Here, satellite mapping of sea ice together with buoy measurements are used to reveal the bathymetric control on sea ice growth and dynamics. Bathymetric effects on sea ice formation are clearly observed in the conformation between sea ice patterns and bathymetric characteristics in the peripheral seas. Beyond local features, bathymetric control appears over extensive ice-prone regions across the Arctic Ocean. The large-scale conformation between bathymetry and patterns of different synoptic sea ice classes, including seasonal and perennial sea ice, is identified. An implication of the bathymetric influence is that the maximum extent of the total sea ice cover is relatively stable, as observed by scatterometer data in the decade of the 2000s, while the minimum ice extent has decreased drastically. Because of the geologic control, the sea ice cover can expand only as far as it reaches the seashore, the continental shelf break, or other pronounced bathymetric features in the peripheral seas. Since the seafloor does not change significantly for decades or centuries, sea ice patterns can be recurrent around certain bathymetric features, which, once identified, may help improve short-term forecast and seasonal outlook of the sea ice cover. Moreover, the seafloor can indirectly influence cloud cover by its control on sea ice distribution, which differentially modulates the latent heat flux through ice covered and open water areas.

Nghiem, S. V.↗
NASA NTRS2016

Estimation of the Ocean Skin Temperature using the NASA GEOS Atmospheric Data Assimilation System

This report documents the status of the development of a sea surface temperature (SST) analysis for the Goddard Earth Observing System (GEOS) Version-5 atmospheric data assimilation system (ADAS). Its implementation is part of the steps being taken toward the development of an integrated earth system analysis. Currently, GEOS-ADAS SST is a bulk ocean temperature (from ocean boundary conditions), and is almost identical to the skin sea surface temperature. Here we describe changes to the atmosphere-ocean interface layer of the GEOS-atmospheric general circulation model (AGCM) to include near surface diurnal warming and cool-skin effects. We also added SST relevant Advanced Very High Resolution Radiometer (AVHRR) observations to the GEOS-ADAS observing system. We provide a detailed description of our analysis of these observations, along with the modifications to the interface between the GEOS atmospheric general circulation model, gridpoint statistical interpolation-based atmospheric analysis and the community radiative transfer model. Our experiments (with and without these changes) show improved assimilation of satellite radiance observations. We obtained a closer fit to withheld, in-situ buoys measuring near-surface SST. Evaluation of forecast skill scores corroborate improvements seen in the observation fits. Along with a discussion of our results, we also include directions for future work.

AGCM↗
NASA NTRS2021

On Assessing ERA5 and MERRA2 Representations of Cold-Air Outbreaks Across the Gulf Stream

The warm Gulf Stream sea surface temperatures (SSTs) strongly impact the evolution of winter clouds behind atmospheric cold fronts. Such cloud evolution remains challenging to model. The Gulf Stream is too wide within the ERA5 and MERRA2 reanalyses, affecting the turbulent surface fluxes. Known problems within the ERA5 boundary layer (too-dry and too-cool with too strong westerlies), ascertained primarily from ACTIVATE 2020 campaign aircraft dropsondes and secondarily from older buoy measurements, reinforce surface flux biases. In contrast, MERRA2 winter surface winds and air-sea temperature/humidity differences are slightly too weak, producing surface fluxes that are too low. Reanalyses boundary layer heights in the strongly-forced winter cold-air-outbreak regime are realistic, whereas late-summer quiescent stable boundary layers are too shallow. Nevertheless, the reanalysis biases are small, and reanalyses adequately support their use for initializing higher-resolution cloud process modeling studies of cold-air outbreaks.

Gulf stream↗
NASA NTRSDate not supplied

Status of the Microwave Barometric Radar and Sounder (MBARS)

Atmospheric surface pressure and pressure profiles are essential variables in weather modeling and forecasting. Pressure gradients generate atmospheric motion and are essential to the air-sea heat exchange feedbacks within the planetary boundary layer (PBL) that lead to convective storms and heavy precipitation. Despite the importance of pressure and pressure gradients on meso-, synoptic-, and global-scale weather patterns, current technology relies almost entirely on buoy measurements over the majority of the ocean. These measurements are too sparse to capture pressure gradients of even many synoptic scale events, and leave models starved of information. NASA/Goddard Space Flight Center (GSFC), NASA/Langley Research Center (LaRC), and Tomorrow.io have begun development of the Microwave Barometric Radar and Sounder (MBARS), an airborne sensor to retrieve surface air pressure and vertical pressure profiles, especially over oceans. MBARS is a new combined active/passive microwave instrument in the O2 absorption V-band (64-70 GHz) funded by the NASA Earth Science Technology Office (ESTO) Instrument Incubator Program (IIP). This instrument consists of an innovative scanning multi-channel differential absorption radar (DAR) to provide an estimation of total atmospheric column oxygen content and thus the surface dry air pressure. MBARS also will provide hyperspectral radiometric temperature profiling to enables vertical pressure profiles using the hypsometric relationship between pressure and temperature. A co-located microwave radiometer will provide the integrated water vapor mass contribution to atmospheric pressure. This presentation will summarize the project, retrieval concept, and engineering status of the MBARS project.

Radar, Radiometer↗
NASA NTRSDate not supplied

Assessing the Variability of Radiation, Water and Energy in the Deep Tropics Over the Last 3 Decades

Global surface energy closure and its variability depends heavily upon the surface radiative energy budget in the deep tropics. A key process observed is the change in convection regimes from disorganized convection to organized deep convection. During these periods an imbalance is observed between energy and water fluxes in terms of energy closure in some atmospheric reanalysis systems, implying that processes are not simulated well. A recent paper by Hsaio et al (2023, pre-published version) found that the transition process has wind shear and longwave cloud radiative feedback signatures. In this presentation, we assess the surface radiative budget in the deep tropics by comparing multiple data products (GEWEX SRB Rel4IP, CERES Ed4.1, ISSCP FH, etc.) and describing the variability across the deep tropics for the period from 1988 to near present. We assess this variability of the radiative flux anomalies (including the net TOA, surface and the atmospheric divergence fluxes) against water vapor divergence, cloud properties (include ISCCP “Weather States, Tselioudis et al. 2021) and larger scale wind shear. We include further analysis contrasting 6 key tropical oceanic regions (Indian Ocean east and west, tropical western, central and eastern Pacific Ocean, and Tropical Atlantic Ocean) and the sensitivity of the fluxes as a function of fluctuations in cloud types in response to various larger scale atmospheric processes (e.g. El Niño, Indian Ocean Dipole). These are contrasted against the modeled radiative fluxes from ERA-5 and MERRA-2. Ocean buoy measurements of radiative fluxes are utilized to help assess data radiative flux uncertainty over the nearly 40 year period. In general, the variability for overlap periods of these various data products agrees well, but there are significant differences in the net fluxes that vary according to the rendering of surface, atmospheric, aerosol and cloud properties. We conclude with recommendations for continuing work.

Radiation budget↗
NASA NTRSDate not supplied

Exploring Radiation, Water and Energy Closure in Key Deep Tropical Regions Over the Last 3 Decades

The closure of global energy and water budgets at various time scales depends heavily upon the on the processes of water and energy exchange in the deep tropics. A key process observed is the change in convection regimes from disorganized convection to organized deep convection. During these periods an imbalance in key tropical regions is observed of water budget terms between observations and atmospheric reanalysis systems, implying that processes are not simulated well. For instance, periods of imbalance in the water budget may be at least partly attributed to precipitation estimates due to the transition between cloud and precipitation systems in which ice cloud affects microwave radar estimates (Lietmann-Niimi et al. 2024, submitted). A recent paper by Hsaio et al (2023, pre-published version) found that the transition process is characterized by wind shear and longwave cloud radiative feedback signatures as well. This is just one example how these processes also affect the radiative fluxes and thus the energy budget at the TOA. In this presentation, we assess the net radiative budget and components in the deep tropics by comparing multiple data products (GEWEX SRB Rel4IP, CERES EBAF/SYN1deg Ed4.2, ISSCP FH, etc.) and describing the temporal variability of energy balance terms across the deep tropics for the period from 1988 to near present in six key oceanic regions. These six key tropical oceanic regions are West Indian Ocean, the south Indian Ocean east, tropical western, central and eastern Pacific Ocean, and Tropical Atlantic Ocean. In these regions we assess the sensitivity of the fluxes as a function of fluctuations in cloud types in response to various larger scale atmospheric processes (e.g. El Niño, Indian Ocean Dipole). We assess this variability of the radiative flux anomalies (including the net TOA, surface and the atmospheric divergence fluxes) against water vapor divergence, cloud properties (include ISCCP “Weather States, Tselioudis et al. 2021) and larger scale wind shear to assess the uncertainties of energy closure in these regions. These are contrasted against the modeled radiative fluxes from ERA-5 and MERRA-2. Ocean buoy measurements of radiative fluxes are utilized to help assess data radiative flux uncertainty over the nearly 40 year period. In general, the variability for overlap periods of these various data products agrees well, but there are significant differences in the net fluxes that vary according to the rendering of surface, atmospheric, aerosol and cloud properties. These differences also affect closure terms and inferences on systematic uncertainties within the observational estimates. We conclude with recommendations for continuing work

Radiation budget↗
NASA NTRS2011

Analysis of Ultra High Resolution Sea Surface Temperature Level 4 Datasets

Sea surface temperature (SST) studies are often focused on improving accuracy, or understanding and quantifying uncertainties in the measurement, as SST is a leading indicator of climate change and represents the longest time series of any ocean variable observed from space. Over the past several decades SST has been studied with the use of satellite data. This allows a larger area to be studied with much more frequent measurements being taken than direct measurements collected aboard ship or buoys. The Group for High Resolution Sea Surface Temperature (GHRSST) is an international project that distributes satellite derived sea surface temperatures (SST) data from multiple platforms and sensors. The goal of the project is to distribute these SSTs for operational uses such as ocean model assimilation and decision support applications, as well as support fundamental SST research and climate studies. Examples of near real time applications include hurricane and fisheries studies and numerical weather forecasting. The JPL group has produced a new 1 km daily global Level 4 SST product, the Multiscale Ultrahigh Resolution (MUR), that blends SST data from 3 distinct NASA radiometers: the Moderate Resolution Imaging Spectroradiometer (MODIS), the Advanced Very High Resolution Radiometer (AVHRR), and the Advanced Microwave Scanning Radiometer ? Earth Observing System(AMSRE). This new product requires further validation and accuracy assessment, especially in coastal regions.We examined the accuracy of the new MUR SST product by comparing the high resolution version and a lower resolution version that has been smoothed to 19 km (but still gridded to 1 km). Both versions were compared to the same data set of in situ buoy temperature measurements with a focus on study regions of the oceans surrounding North and Central America as well as two smaller regions around the Gulf Stream and California coast. Ocean fronts exhibit high temperature gradients (Roden, 1976), and thus satellite data of SST can be used in the detection of these fronts. In this case, accuracy is less of a concern because the primary focus is on the spatial derivative of SST. We calculated the gradients for both versions of the MUR data set and did statistical comparisons focusing on the same regions.

sea surface temperature SST)↗
NASA NTRS1994

Wave-current interaction near the Gulf Stream during the surface wave dynamics experiment

This paper presents a case study on the wave-current interaction near the local curvature of a Gulf Stream meander. The wave data were obtained from in situ measurements by a pitch-roll discus buoy during the Surface Wave Dynamics Experiment (SWADE) conducted off Wallops Island, Virginia, from October 1990 to March 1991. Owing to the advection of the Gulf Stream by the semidiurnal tide, the discus buoy was alternately located outside and inside the Gulf Stream. The directional wave measurements from the buoy show the changes in wave direction, wave energy, and directional spreading when waves encountered the current in the Gulf Stream meanders. A wave refraction model, using the ray-tracing method with an estimated Gulf Stream velocity field and meandering condition, was used to simulate wave refraction patterns and to estimate wave parameters at relative locations corresponding to buoy measurements. The numerical simulation shows that a focusing zone of wave rays was formed near the boundary and behind the crest of a simulated Gulf Stream meander. The focusing of wave rays causes changes in wave direction, increases in wave energy, and decreases in wave directional spreading, which are in good agreement with the results from the buoy measurements.

Wang, David W.↗
NASA NTRS1994

Precise mean sea level measurements using the Global Positioning System

This paper describes the results of a sea level measurement test conducted off La Jolla, California, in November of 1991. The purpose of this test was to determine accurate sea level measurements using a Global Positioning System (GPS) equipped buoy. These measurements were intended to be used as the sea level component for calibration of the ERS 1 satellite altimeter. Measurements were collected on November 25 and 28 when the ERS 1 satellite overflew the calibration area. Two different types of buoys were used. A waverider design was used on November 25 and a spar design on November 28. This provided the opportunity to examine how dynamic effects of the measurement platform might affect the sea level accuracy. The two buoys were deployed at locations approximately 1.2 km apart and about 15 km west of a reference GPS receiver located on the rooftop of the Institute of Geophysics and Planetary Physics at the Scripps Institute of Oceanography. GPS solutions were computed for 45 minutes on each day and used to produce two sea level time series. An estimate of the mean sea level at both locations was computed by subtracting tide gage data collected at the Scripps Pier from the GPS-determined sea level measurements and then filtering out the high-frequency components due to waves and buoy dynamics. In both cases the GPS estimate differed from Rapp's mean altimetric surface by 0.06 m. Thus, the gradient in the GPS measurements matched the gradient in Rapp's surface. These results suggest that accurate sea level can be determined using GPS on widely differing platforms as long as care is taken to determine the height of the GPS antenna phase center above water level. Application areas include measurement of absolute sea level, of temporal variations in sea level, and of sea level gradients (dominantly the geoid). Specific applications would include ocean altimeter calibration, monitoring of sea level in remote regions, and regional experiments requiring spatial and temporal resolution higher than that available from altimeter data.

Kelecy, Thomas M.↗
NASA NTRS1981

Remote sensing of the ocean waveheight spectrum using synthetic-aperture-radar images

The paper discusses problems in the detection and measurement of ocean waves from their SAR images, in particular the measurement of the wavenumber spectrum of ocean-wave-height fluctuations. Comparisons on a limited set of pitch-roll buoy and SEASAT SAR measurements during the 1978 JASIN experiment reveal that degradation of SAR resolution caused by wave orbital motion is a crucial factor in the detection of waves by SAR images. Thus, waves with small slopes traveling perpendicular to the SAR flight path are more easily detected than waves with large slopes traveling along the flight path. Although the SAR estimates in this comparison were found to contain significant biases, they were in rough agreement with buoy measurements, provided the ocean wavelength was between about 120 and 400 m and the ocean wave direction was not approximately along the SAR flight path.

Vesecky, J. F.↗
NASA NTRS1987

Comparison of moored wind measurements from a spar and toroidal buoy in the eastern equatorial Pacific during February-March 1981

Wind measurements at 3.8 m from a surface-following toroid and at 4.0 m from a vertically stable spar were compared to estimate the influence of mooring motion. Buoys were separated by 9 km. Data were obtained at 15-min intervals for 41 days in the equatorial Pacific, where the maximum 15-min averaged wind speed was 9.0 m/s and wind speeds averaged 4.5 m/s. Toroid wind speeds were 3.5 percent greater than the spar data, and the correlation coefficient between 15-min toroid and spar data was 0.92. The frequency of the 50-percent noise level was 0.125 cph, and the correlation coefficient between 8-hour averaged toroid and spar data was 0.98. Toroid 8-hour averaged wind speeds referenced to 10-m height were 2 percent larger thancorresponding spar data.

Halpern, David↗
NASA NTRS1993

Validation of Special Sensor Microwave Imager monthly-mean wind speed from July 1987 to December 1989

Since July 1987, the Remote Sensing Systems (Santa Rosa, California) routinely computes from first principles the wind speed from Special Sensor Microwave Imager (SSM/I) measurements of the intensity of microwave radiation emitted at the ocean surface. The accuracy of monthly-mean SSM/I wind speeds is determined by comparisons with moored-buoy wind measurements, which were recorded by four different institutions at 44 sites in the Atlantic and Pacific Oceans during July 1987 to December 1989. All results for 1988 were virtually identical with 1989. The range of monthly mean moored-buoy wind speeds was 2-10 m/s. The rms difference of 697 monthly-mean matchups of the composite 1988 and 1989 data set was 1.2 m/s. The rms differences were smaller in the equatorial zone and higher in middle latitudes, in accord with the monthly standard deviation. At middle latitudes, the time series of rms differences displayed an annual cycle. In the equatorial zone, the agreement between SSM/I and in situ data was better in regions with a lesser amount of clouds, and vice versa. For SSM/I monthly standard deviations of 1-2, 2-3, and 3-4 m/s, the average absolute values of the monthly-mean difference between SSM/I and moored-buoy wind speeds were 0.6, 0.9, and 1.4 m/s, respectively.

Halpern, David↗
NASA NTRS1992

Validation of Special Sensor Microwave Imager Monthly-Mean Wind Speed From July 1987 to December 1989

Since July 1987 the Remote Sensing Systems, Santa Rosa, California, routinely computes from first principles the wind speed from Special Sensor Microwave Imager (SSM/I) measurements of the intensity of microwave radiation emitted at the ocean surface. The accuracy of monthly-mean SSM/I wind speeds is determined by comparisons with moored-buoy wind measurements, which were recorded by four different institutions at 44 sites in the Atlantic and Pacific Oceans during July 1987 to December 1989. All results for 1988 were virtually identical with 1989. The range of monthly mean moored-buoy wind speeds was 2-10 m s^(-1). During 1987, the equatorial matchups were not equivalent with 1998 and 1989, and the cause remains unknown. The root-mean-square (rms) difference of 697 monthly-mean matchups of the composite 1988 and 1989 data set was 1.2 m s^(-1). The rms differences were smaller in the equatorial zone and higher in middle latitudes, in accord with the monthly standard deviation. At middle latitudes the time series of rms differences displayed an annual cycle. In the equatorial zone the agreement between SSM/I and in situ data was better in regions with a lesser amount of clouds, and vice versa. For SSM/I monthly standard deviations of 1-2, 2-3, and 3-4 m s^(-1), the average absolute values of the monthly-mean difference between SSM/I and moored-buoy wind speeds were 0.6, 0.9, and 1.4 m s^(-1), respectively.

Halpern, D.↗
NASA NTRS2003

Simultaneous Ocean Wave Measurements by the JASON and TOPEX Satellites, With Buoy and Model Comparisons

The verification phase of the Jason-1 satellite altimeter mission presents a unique opportunity for comparing near-simultaneous, independent satellite measurements. We here examine simultaneous significant wave height measurements by the Jason-1 and Topex/Poseidon altimeters. These data are also compared with in-situ measurements from deep-ocean buoys and with predicted wave heights from the WaveWatch 111 operational model. The rms difference between Jason and Topex wave heights is 28 cm, and this can be lowered by half through improved outlier editing and filtering of high-frequency noise. Noise is slightly larger in the Jason dataset, exceeding Topex by about 7 cm rms at frequencies above 0.05 Hz, which is the frequency at which the coherence between Topex and Jason measurements drops to zero. Jason wave heights are more prone to outliers, especially during periods of moderate to high backscatter. Buoy comparisons confirm previous reports that Topex wave heights are roughly 5% smaller than buoy measurements for waves between 2 and 5m; Jason heights in general are 3% smaller than Topex. Spurious dips in the Topex density function for 3- and 6-meter waves, a problem that has existed since the beginning of the mission, can be solved by waveform retracking.

Ray, R. D.↗
NASA NTRS1983

Mechanisms for SAR imaging of ocean surface phenomena: Theory and experiment

Understanding the SAR response to surface wave is a central issue in the analysis of SAR ocean images. The imaging mechanism for gravity waves and the practical question of just which characteristics of the ocean wave field can be measured remotely using SAR were examined. Assessments of wave imaging theory are based primarily on comparisons of the directional wave height variance spectrum psi (K) measured by in situ buoys with estimates from SAR images. Other criteria are also recommended, e.g., the effects of focus adjustments. It is assumed that fluctuations in SAR image intensity are proportional to fluctuations in ocean surface height. If this were true, the Fourier power spectrum of a SAR image and corresponding surface measurements of psi would coincide. Differences between SAR estimates based on this hypothesis and buoy measurements of psi are then used to begin the assessment of rival wave imaging theories.

Vesecky, J. F.↗
NASA NTRS1993

Evaluation of two January - June 1992 ERS-1 AMI wind vector data sets

A Jan. - Jun. 1992 10 m height wind vector field was computed with the CMOD2 model function. Freilich and Dunbar used ESA measurements of AMI (Active Microwave Instrument) sigma-naught to derive a refined model function and to produce an alternate Jan. - Jun. 1992 10 m height wind vector field, named FD data. The ESA and FD model functions and algorithms were substantially different. The FD wind vectors were in better agreement with the climatological mean wind field and with moored buoy wind measurements. The average correlation coefficients between monthly mean and daily averaged FD and moored buoy matchups of the Cartesian wind components were 0.84 and 0.74, respectively. The average root mean square differences between the monthly mean and daily averaged FD and moored buoy matchups of the Cartesian wind components were 1.25 and 3.0 m/s, respectively.

Halpern, D.↗
NASA NTRS2003

Simultaneous Ocean Wave Measurements by the Jason and Topex Satellites, With Buoy and Model Comparisons

The verification phase of the Jason-1 satellite altimeter mission presents a unique opportunity for comparing near-simultaneous, independent satellite measurements. We here examine simultaneous significant wave height measurements by the Jason-1 and Topex/Poseidon altimeters. These data are also compared with in-situ measurements from deep-ocean buoys and with predicted wave heights from the Wave Watch 111 operational model. The rms difference between Jason and Topex wave heights is 21 cm, and this can be further lowered by application of median filters to reduce high-frequency noise. This noise is slightly larger in the Jason dataset, amounting to about 7 cm rms for frequencies above 0.05 Hz, which is the frequency at which the coherence between Topex and Jason measurements drops to zero. The probability density function for Jason shows a dearth of small waves relative to Topex. Buoy comparisons confirm that this problem lies with the Jason measurements. The buoy comparisons confirm previous reports that Topex wave heights are roughly 5% smaller than buoy measurements for waves between 2 and 5m; Jason heights in general are 2.7% smaller than Topex. Spurious dips in the Topex density function for 3- and 6-meter waves, a problem that has existed since the beginning of the mission, can be solved by waveform retracking..

Ray, Richard D.↗
NASA NTRS1981

Global satellite measurements of water vapour, wind speed and wave height

The results of global measurements of atmospheric water vapor by the Seasat Scanning Multichannel Microwave Radiometer and wave height and wind speed by the Seasat altimeter (ALT) are reported. The 13.5 GHz ALT has a 3.125 ns pulsewidth and 1022 Hz repetition rate, and measures surface height to a resolution exceeding 10 cm celative to a reference ellipsoid. Full ALT data comprise 135 km equatorial groundtracks, with about a 50 cm difference of sea wave height compared to buoy reference measurements, and windspeed accuracy to within 0.25-1.58 m/sec up to 20 m/sec. Highest water vapor concentrations were observed in the tropics and the lowest at high latitudes. Wind speeds were highest for the north-east and south-east tradewinds in both the Atlantic and Pacific oceans. Average wave height is small in the summer North Hemisphere and the largest waves are in the winter Southern ocean, and lowest in western Atlantic and Pacific ocean areas where winds are lightest.

Chelton, D. B.↗