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This paper presents the first experimental evidence that the polarimetric brightness temperatures of sea surfaces are sensitive to ocean wind direction in the incidence angle range of 30 to 50 degrees.
The need for autonomous navigation and intelligent control of unmanned sea surface vehicles requires a mechanically robust sensing architecture that is watertight, durable, and insensitive to vibration and shock loading. The sensing system developed here comprises four black and white cameras and a single color camera. The cameras are rigidly mounted to a camera bar that can be reconfigured to mount multiple vehicles, and act as both navigational cameras and application cameras. The cameras are housed in watertight casings to protect them and their electronics from moisture and wave splashes. Two of the black and white cameras are positioned to provide lateral vision. They are angled away from the front of the vehicle at horizontal angles to provide ideal fields of view for mapping and autonomous navigation. The other two black and white cameras are positioned at an angle into the color camera's field of view to support vehicle applications. These two cameras provide an overlap, as well as a backup to the front camera. The color camera is positioned directly in the middle of the bar, aimed straight ahead. This system is applicable to any sea-going vehicle, both on Earth and in space.
With their complex narrow passages and vigorous mixing, the Indonesian seas provide the only low-latitude pathway between the Pacific and Indian Oceans and thus play an essential role in regulating Pacific-Indian Ocean exchange, regional air-sea interaction, and ultimately, global climate phenomena. While previous investigations using remote sensing and numerical simulations strongly suggest that this mixing is tidally driven, the impacts of monsoon and El Niño Southern Oscillation (ENSO) on tidal mixing in the Indonesian seas must play an important role. Here we use high-resolution sea surface temperature from June 2002 to June 2021 to reveal monsoon and ENSO modulations of mixing. The largest spring-neap (fortnightly) signals are found to be localized in the narrow passages/straits and sills, with more vigorous tidal mixing during the southeast (boreal summer) monsoon and El Niño than that during the northwest (boreal winter monsoon) and La Niña. Therefore, tidal mixing, which necessarily responds to seasonal and interannual changes in stratification, must also play a feedback role in regulating seasonal and interannual variability of water mass transformations and Indonesian throughflow. The findings have implications for longer-term variations and changes of Pacific–Indian ocean water mass transformation, circulation, and climate.
Climate models struggle to produce sea surface temperature (SST) gradient trends in the tropical Pacific comparable to those seen recently in nature. Here, we find that the magnitude of the cloud-SST feedback in the subtropical Southeast Pacific is correlated across models with the magnitude of Eastern Pacific multi-decadal SST variability. A heat-budget analysis reveals coupling between cloud-radiative effects, circulation, and SST gradients in driving multi-decadal variability in the Eastern Pacific. Using this relationship and observed feedback estimates, we find that internal Eastern Pacific SST variability is underestimated in most models. Adjusting for model bias increases the likelihood of generating a cooling trend at least as large as observations in preindustrial control simulations by ~56% on average. If models underestimate climate “noise,” as our results suggest, this bias should be accounted for when attributing the relative importance of forced versus unforced changes in the climate.
Ocean currents and sea surface temperature remote sensing by Nimbus 2 High Resolution IR Radiometer
Atmospheric effects on infrared multispectral sensing of sea-surface temperature from space
The sea-surface microwave emissivity is derived using SMMR brightness temperatures and SASS inferred friction velocities for three North Pacific Seasat passes. The results show the emissivity increasing linearly with friction velocity with no obvious break between the foam-free and foam regimes up to a friction velocity of about 70 cm/sec (15 m/sec wind speed). For horizontal polarization the sensitivity of emissivity to friction velocity greatly increases with frequency, while for vertical polarization the sensitivity is much less and is independent of frequency. This behavior is consistent with two-scale scattering theory. A limited amount of high friction velocity data above 70 cm/sec suggests an additional increase in emissivity due to whitecapping.
A procedure is developed for estimating sea surface temperatures from multispectral image data acquired from the VISSR atmospheric sounder on the geostationary GOES satellites. Theoretical regression equations for two and three infrared window channels are empirically tuned using clear field of view satellite radiances matched with reports of SST from NOAA fixed environmental buoys. The empirical regression equations are then used to produce daily regional analyses of SST. Monthly mean SST's for the western North Atlantic and the eastern equatorial Pacific during March and July 1982 were produced for use in the SST Intercomparison Workshop Series. Workshop results showed VAS SST's have a scatter of 0.8-1.0 C and a slight warm bias with respect to the other measurements of SST. The VAS SST's show no discernible bias in the region of El Chichon volcanic aerosol cloud.
A series of satellite sea surface temperature intercomparison workshops were conducted under NASA sponsorship at the Jet Propulsion Laboratory. Three different satellite data sets were compared with each other, with routinely collected ship data, and with climatology, for the months of November 1979, December 1981, March 1982, and July 1982. The satellite and ship data were differenced against an accepted climatology to produce anomalies, which in turn were spatially and temporally averaged into two-degree latitude-longitude, one-month bins. Monthly statistics on the satellite and ship bin average temperatures yielded rms differences ranging from 0.58 to 1.37 C, and mean differences ranging from -0.48 to 0.72 C, varying substantially from month to month, and sensor to sensor.
A series of satellite sea surface temperature intercomparison workshops were conducted under NASA sponsorship at the Jet Propulsion Laboratory. Three different satellite data sets were compared with each other, with routinely collected ship data, and with climatology, for the months of November 1979, December 1981, March 1982, and July 1982. The satellite and ship data were differenced against an accepted climatology to produce anomalies, which in turn were spatially and temporally averaged into two-degree latitude-longitude, one-month bins. Monthly statistics on the satellite and ship bin average temperatures yielded rms differences ranging from 0.58 to 1.37 C, and mean differences ranging from -0.48 to 0.72 C, varying substantially from month to month, and sensor to sensor.
The relationship between the sea surface temperature anomalies (SSTAs) and the anomalies of the monthly mean cloud cover (including the high-level, low-level, and total cloud cover), the outgoing longwave radiation, and the reflected solar radiation was analyzed using a least absolute deviations regression at each grid point over the open ocean for a 6-yr period. The results indicate that cloud change in association with a local 1-C increase in SSTAs cannot be used to predict clouds in a potential future world where all the oceans are 1-C warmer than at present, because much of the observed cloud changes are due to circulation changes, which in turn are related not only to changes in SSTAs but to changes in SSTA gradients. However, because SSTAs are associated with changes in the local ocean-atmosphere moisture and heat fluxes as well as significant changes in circulation (such as ENSO), SSTAs can serve as a surrogate for many aspects of global climate change.
A high-resolution, global satellite-derived sea surface temperature (SST) data set called Pathfinder, from the Advanced Very High Resolution Radiometer (AVHRR) aboard the NOAA Polar Orbiters, is available from the Jet Propulsion Laboratory Physical Oceanography Distributed Active Archive Center (JPL PO.DAAC). Suitable for research as well as education, the Pathfinder SST data set is a result of a collaboration between the National Oceanographic and Atmospheric Administration (NOAA), the National Aeronautics and Space Administration (NASA) and investigators at several universities. NOAA and NASA are the sponsors of the Pathfinder Program, which takes advantage of currently archived Earth science data from satellites. Where necessary, satellite sensors have been intercalibrated, algorithms improved and processing procedures revised, in order to produce long time-series, global measurements of ocean, land and atmospheric properties necessary for climate research. Many Pathfinder data sets are available to researchers now, nearly a decade before the first launch of NASA's Earth Observing System (EOS). The lessons learned from the Pathfinder programs will facilitate the processing and management of terabytes of data from EOS. The Oceans component of Pathfinder has undertaken to reprocess all Global Area Coverage (GAC) data acquired by the 5-channel AVHRRs since 1981. The resultant data products are consistent and stably calibrated [Rao, 1993a, Rao, 1993b, Brown et al., 1993], Earth-gridded SST fields at a variety of spatial and temporal resolutions.
The Hadley sea-surface temperature (HadSST) dataset is investigated for the interval 1871-2008. The purpose of this investigation is to determine the degree of success in identifying and characterizing El Nino (EN) southern (ENSO) extreme events, both EN and La Nina (LN) events. Comparisons are made against both the Southern Oscillation Index for the same time interval and with published values of the Oceanic Nino Index for the interval since 1950. Some 60 ENSO extreme events are identified in the HadSST dataset, consisting of 33 EN and 27 LN events. Also, preferential associations are found to exist between the duration of ENSO extreme events and their maximum anomalous excursion temperatures and between the recurrence rate for an EN event and the duration of the last known EN event. Because the present ongoing EN is a strong event, it should persist 11 months or longer, inferring that the next EN event should not be expected until June 2012 or later. Furthermore, the decadal sum of EN-related months is found to have increased somewhat steadily since the decade of 1920-1929, suggesting that the present decade (2010-2019) possibly will see about 3-4 EN events, totaling about 37 +/- 3 EN-related months (i.e., months that meet the definition for the occurrence of an EN event).
Abstract The amplitude of the annual cycle of sea surface temperatures (SSTs) within the tropics is the largest in the eastern Atlantic and Pacific Oceans. Upwelling activity in these regions is maximum during late boreal summer and autumn, resulting in cool SSTs, and minimum in spring, leading to warm SSTs. The fundamental question of how this large seasonal cycle affects the atmosphere has received relatively little scientific attention. In this study, we use perturbed-SST experiments in an atmosphere model to identify the effects of the seasonal cycle of upwelling zone SSTs on the atmospheric state. Although annual-mean upwelling zone SSTs are cool, preventing their convective coupling with the free troposphere for much of the year, their boreal spring warmth can activate precipitating convection. We find that in this season, upwelling zone SSTs affect the atmosphere by 1) altering the intensity and position of the local intertropical convergence zone and 2) inducing a thermally forced Matsuno–Gill response, altering subtropical winds. On the seasonal time scale, the Atlantic upwelling zone is more effective than the Pacific in inducing this response. We also find that, consistent with prior work, the Pacific upwelling zone excites extratropical modes of internal atmospheric variability. Upwelling zone SSTs have remained poorly simulated through generations of climate models; our experiments allow us to diagnose the atmospheric biases that arise in response to upwelling zone SST biases. Our experiments show that upwelling zone SST biases are most impactful in boreal spring, particularly over the Atlantic.
Computer processing of satellite infrared data for determining sea surface temperature
Infrared radiometer system for airborne measurements of sea surface temperature and heat flow
There exists observational and modeling evidence to the effect that sea surface temperature (SST) anomalies in the equatorial Pacific have a significant effect upon wintertime climate in the Pacific/North American sector of the hemisphere. In connection with the emergence of a more definitive observational basis for designing general circulation model (GCM) experiments to investigate the atmospheric response to equatorial SST anomalies, it was recommended to conduct a series of GCM experiments. The present study involves a series of extended (1-2 month) integrations.Attention is given to a review of previous GCM experiments, the plan for the present study, the general circulation model and its simulation of the winter and summer circulation described by Shukla et al. (1981), tropical precipitation, upper level flow, low-level circulation and temperature, and the tropical tropospheric temperature.
Given any set of three 2 degree binned anomaly sea surface temperature (SST) data sets by three different sensors, estimates of the mean square error of each sensor estimate is made. The above formalism performed on every possible triplet of sensors. A separate table of error estimates is then constructed for each sensor.