Title: Radiometric measurements of ocean surface thermal variability Running title:Ocean surface diurnal warming (original) (raw)
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Radiometric measurements of ocean surface thermal variability
Journal of Geophysical Research, 2008
1] Measurements of diurnal temperature variability at the ocean surface have been available primarily from satellite Sea Surface Temperature (SST) retrievals and a small number of ship-based radiometers. Since most areas are sampled from polar orbiting satellites at most twice a day, surface diurnal variability studies relied on theoretical modeling or extrapolation of results from in situ measurements at depth. The ocean surface responds very rapidly to changes in fluxes of heat and momentum, therefore diurnal variability at the ocean surface may be quite different than heating at depth. Measurements from the Marine Atmospheric Emitted Radiance Interferometer (M-AERI) provide one of the few skin SST data sets augmented by ancillary measurements necessary for investigations into surface diurnal heating and cooling. This unique data set spans all major ocean basins and contains many days with diurnal warming. The timing of the peak in diurnal warming is directly related to the minimum wind speed and varies from 8:00 to 18:00 local-mean-time. Fluctuations in wind speed can result in multiple peaks in diurnal heating during a single afternoon. As wind speed increases, diurnal warming decreases (negatively correlated) and as insolation increases, diurnal warming increases (positively correlated). Changes in wind speed affect diurnal warming amplitudes very rapidly, while changes in insolation have a more gradual effect. The maximum correlation of wind speed (insolation) with changes in diurnal warming is at a time lag of 0 (50) min.
Continental Shelf Research (82):85-98., 2014
A good understanding of diurnal warming in the upper ocean is important for the validation of satellitederived sea surface temperature (SST) against in-situ buoy data and for merging satellite SSTs taken at different times of the same day. For shallow coastal regions, better understanding of diurnal heating could also help improve monitoring and prediction of ecosystem health, such as coral reef bleaching.
Sea surface temperature signals from satellites-An update
Geophysical Research Letters, 2000
Polar satellite-derived observations of sea surface temperatures (SSTs) have been used routinely since 1982 to provide a complete monitoring of our planet, covering all comers of the oceans (unless covered by clouds) twice each day. In 1992, an initial glimpse was published (Strong, 1992) of some tendencies that had been observed during the 1980s. Now that seven additional years of NOAA satellite SST data have become available, the earlier time-series (Strong, 1992) has been up-dated. In this analysis of the global nighttime SSTs, care was taken to avoid the anomalous conditions found during the 1982-83 E1 Chich6n aerosols, 1991-92 Mt. Pmambo aerosols, and the strong E1 Nifio of 1997-98. Evidence of warming is found to be present throughout much of the Tropics and in the mid-latitude Northern Hemisphere. Estimates fxom the Southern Hemisphere, while strongly indicative of compensatory cooling m the region, are found to be not as reliable.
Diurnally Varying Wind Forcing and Upper Ocean Temperature: Implications for the Ocean Mixed Layer
Solar radiation varies on a diurnal cycle, and therefore so do all the climate variables that it forces, including sea surface temperature (SST), wind, and in turn mixed-layer depth and upper- oceanheatstorage. SatellitescatterometerdatafromtheQuikSCAT and ADEOS-2 tandem mission have been used to estimate the am- plitude and phasing of diurnal wind variations on a global basis. Statistically significant diurnal wind variations occur along coast- lines all over the world, where they are commonly thought of as the land/sea breeze. Open ocean winds also undergo substantial diurnal variability at latitudes equatorward of 30 latitude. The phasing of diurnal winds varies with distance from the shore. Up- per ocean temperatures measured from profiling Argo floats are compared with microwave SSTs from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) to estimate the amplitude and phasing of the diurnal cycle in up- per ocean temperature. Differences between ...
Sea surface temperature variability: patterns and mechanisms
Annual review of marine science, 2010
Patterns of sea surface temperature (SST) variability on interannual and longer timescales result from a combination of atmospheric and oceanic processes. These SST anomaly patterns may be due to intrinsic modes of atmospheric circulation variability that imprint themselves upon the SST field mainly via surface energy fluxes. Examples include SST fluctuations in the Southern Ocean associated with the Southern Annular Mode, a tripolar pattern of SST anomalies in the North Atlantic associated with the North Atlantic Oscillation, and a pan-Pacific mode known as the Pacific Decadal Oscillation (with additional contributions from oceanic processes). They may also result from coupled ocean-atmosphere interactions, such as the El Niño-Southern Oscillation phenomenon in the tropical Indo-Pacific, the tropical Atlantic Niño, and the cross-equatorial meridional modes in the tropical Pacific and Atlantic. Finally, patterns of SST variability may arise from intrinsic oceanic modes, notably the ...
Estimating Sea Surface Temperature from Infrared Satellite and In Situ Temperature Data
Bulletin of The American Meteorological Society, 2001
Sea surface temperature (SST) is a critical quantity in the study of both the ocean and the atmosphere as it is directly related to and often dictates the exchanges of heat, momentum and gases between the ocean and the atmosphere. As the most widely observed variable in oceanography, SST is used in many different studies of the ocean and its coupling with the atmosphere. We examine the history of this measurement and how this history led to today's practice of computing SST by regressing satellite infrared measurements against in situ SST observations made by drifting/moored buoys and ships. The fundamental differences between satellite and in situ SST are discussed and recommendations are made for how both data streams should be handled. A comprehensive in situ validation/calibration plan is proposed for the satellite SSTs and consequences of the suggested measurements are discussed with respect to the role of SST as an integral part of the fluxes between the ocean and the atmosphere.
Remotely sensed sea surface temperature variability off California during a “Santa Ana” clearing
Journal of Geophysical Research, 1984
During a prolonged clearing with particularly dry atmospheric conditions over the Southern California Bight, four NOAA 6 satellite overpasses at 12-hour intervals w r e recorded while a research vessel measured ocean temperatures within the,field of view of the satellite. This data set is used to evaluate two versions of an equation f i r estimating sea surface temperature from satellite data and for examining short-term changes in surface temperature caused by diurnal variation and surface layer movement. Surface temperatures calculated from data taken during a daytime overpass. using two slightly differing versions of a multiwindow atmospheric correction equation. match the ocean temperatures within the expected range of scatter: +0.6"C. One version has a mean daytime bias of +O.S"C, the other has-0.4"C. and thus the two versions dfler by 0.9"C. The satellite-deriwd sea surface temperatures show a diurnal variation in the range of 0.25" to 1.0"C. Hence the bias of calculated satellite temperatures for the nighttime overpasses differ from those for the daytime; the bias in one version is +l.Z"C and in the other is +0.4"C. It is suggested that these biases are caused by inherent problems in the selection and matching of satellite and ocean data sets used to determine the equation coeficients as well as poorly understood diurnal variation of the surface temperature as measured by satellite. Advection. evidenced by an image-to-image shfl of thermal gradients owr 12and 24-hour periods can produce local temperature changes that add to the problem. Noise in one of the satellite data channels, another part of the problem, is shown IO be amenable to.filtering techniques. Diurnal dflerences in satellite-obserwd surface temperatures are found to v a y regionally; larger variation is found in waters that are turbid and have a shallow thermocline. Near surface in situ temperature measurements suggest a diurnal layer variation of 0.2"C. much less than the variation observed by satellite. An estimation of diurnal sea surface temperature variation based on heat budget calculations supports the in situ observations.
Chapter 2 Review of Literature 2.1 Conceptualizing of Sea Surface Temperature (SST
The Sea Surface Temperature (SST) is a direct measure of the energy balance which drives the circulation and ultimately defines the climate. The energy transferred between the ocean and the atmosphere is to a large extent dependent on SST and functions of sea surface temperature such as the sensible heat flux, latent heat flux, and radiative flux at the sea surface. Sea surface temperature is an important physical property of the ocean to understand the features like current flows, precipitation, biological production, properties of surface air over the ocean, upwelling etc. SST is influenced by the parameters such as net incoming shortwave solar radiation, net long wave radiation, and the turbulent air-sea heat fluxes (the latent heat and sensible heat fluxes), wind stress curl, mixed layer depth,
Simulated and observed variability in ocean temperature and heat content
Proceedings of the National Academy of Sciences, 2007
Observations show both a pronounced increase in ocean heat content (OHC) over the second half of the 20th century and substantial OHC variability on interannual-to-decadal time scales. Although climate models are able to simulate overall changes in OHC, they are generally thought to underestimate the amplitude of OHC variability. Using simulations of 20th century climate performed with 13 numerical models, we demonstrate that the apparent discrepancy between modeled and observed variability is largely explained by accounting for changes in observational coverage and instrumentation and by including the effects of volcanic eruptions. Our work does not support the recent claim that the 0-to 700-m layer of the global ocean experienced a substantial OHC decrease over the 2003 to 2005 time period. We show that the 2003-2005 cooling is largely an artifact of a systematic change in the observing system, with the deployment of Argo floats reducing a warm bias in the original observing system. climate ͉ models ͉ observations ͉ ocean heat content O bservations suggest that the world's oceans were responsible for most of the heat content increase in the earth's climate system between 1955 and 1998 (1). This increase is embedded in substantial variability on interannual-to-decadal time scales. State-of-the-art climate models have been able to replicate both the overall increase in ocean heat content (OHC) during this period and its horizontal and vertical structure (2-7). Such detection and attribution studies have identified a large anthropogenic component in the observed changes and find that the ''noise'' of natural climate variability is an inadequate explanation for these changes.