Estimating Sea Surface Temperature from Infrared Satellite and In Situ Temperature Data

Emery, William J.; Castro, Sandra L.; Wick, Gary A.; Schluessel, Peter; Donlon, Craig

doi:10.1175/1520-0477(2001)082<2773:esstfi>2.3.co;2

Cited by 86 publications

(49 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…• research cruises from the air-sea interaction group at the National Oceanic and Atmospheric Administration (NOAA) Environmental Technology Laboratory (ETL) (Fairall et al 1997;Edson et al 1998), • mooring observations (Weller and Anderson 1996), • skin sea surface temperature measurements (Emery et al 2001), • mid-and high-latitude observations from German research vessels (Bruemmer 1993), • meteorological and flux data from World Ocean Circulation Experiment (WOCE) cruises ; available online at www.coaps.fsu.…”

Section: A General Discussion Of Flux Measurement Issues Is Given In mentioning

confidence: 99%

Seaflux

Curry¹,

Bentamy²,

Bourassa³

et al. 2004

Bull. Amer. Meteor. Soc.

Self Cite

143

130

View full text Add to dashboard Cite

Satellite-based datasets of surface turbulent fluxes over the global oceans are being evaluated and improved.O cean surface fluxes of heat, moisture, and momentum observed during field experiments show strong variability on temporal scales that range from the diurnal cycle to the life cycle of storms, and on spatial scales as small as that of an individual convective cloud. High-frequency variability (e.g., diurnal, storm scale) in tropical air-sea fluxes has been hypothesized to influence intraseasonal and interannual variability of the monsoon (e.g., Webster et al. 1998) and the Pacific Ocean warm pool and El Nino (e.g., Sui and Lau 1997;Fasullo and Webster 2000). At high latitudes, large variations in surface fluxes and sea surface temperature are seen in response to storms, which impact the temperature, density, and mixing in the upper ocean, further influencing the atmospheric dynamics and thermodynamics. Storm-scale events have been hypothesized (e.g., Marshall et al. 1998;Nardelli and Salusti 2000) to be associated with ocean convection in the high-latitude water mass formation regions, contributing to deep water formation and the global ocean thermohaline circulation. Ocean mixing induced by tropical cyclones might play an important role in driving the global ocean thermohaline circulation and, thereby,

show abstract

Section: A General Discussion Of Flux Measurement Issues Is Given In mentioning

confidence: 99%

Seaflux

Curry¹,

Bentamy²,

Bourassa³

et al. 2004

Bull. Amer. Meteor. Soc.

Self Cite

143

130

View full text Add to dashboard Cite

show abstract

“…The sea surface temperature observed from infrared channels of satellites indicates the values at the skin of sea water, in contrast with the sea surface temperature measured from buoys, of which values represent the temperature of bulk water near the sea surfaces. The infrared sea SST was measured at depths of approximately 10 µm within the oceanic skin layer (∼ 500 µm) at the water side of the airsea interface where the conductive and diffusive heat transfer processes dominated (Emery et al, 2001;Donlon et al, 2002;Liou, 2002).…”

Section: Methodsmentioning

confidence: 99%

Uncertainties of satellite-derived surface skin temperatures in the polar oceans: MODIS, AIRS/AMSU, and AIRS only

et al. 2015

View full text Add to dashboard Cite

Abstract. Uncertainties in the satellite-derived surface skin temperature (SST) data in the polar oceans during two periods (16-24 April and 15-23 September) 2003-2014 were investigated and the three data sets were intercompared as follows: MODerate Resolution Imaging Spectroradiometer Ice Surface Temperature (MODIS IST), the SST of the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit-A (AIRS/AMSU), and AIRS only. The AIRS only algorithm was developed in preparation for the degradation of the AMSU-A. MODIS IST was systematically warmer up to 1.65 K at the sea ice boundary and colder down to −2.04 K in the polar sea ice regions of both the Arctic and Antarctic than that of the AIRS/AMSU. This difference in the results could have been caused by the surface classification method. The spatial correlation coefficient of the AIRS only to the AIRS/AMSU (0.992-0.999) method was greater than that of the MODIS IST to the AIRS/AMSU (0.968-0.994). The SST of the AIRS only compared to that of the AIRS/AMSU had a bias of 0.168 K with a RMSE of 0.590 K over the Northern Hemisphere high latitudes and a bias of −0.109 K with a RMSE of 0.852 K over the Southern Hemisphere high latitudes. There was a systematic disagreement between the AIRS retrievals at the boundary of the sea ice, because the AIRS only algorithm utilized a less accurate GCM forecast over the seasonally varying frozen oceans than the microwave data. The three data sets (MODIS, AIRS/AMSU and AIRS only) showed significant warming rates (2.3 ± 1.7 ∼ 2.8 ± 1.9 K decade −1 ) in the northern high regions (70-80 • N) as expected from the icealbedo feedback. The systematic temperature disagreement associated with surface type classification had an impact on the resulting temperature trends.

show abstract

“…28, No. 3, 517-524, June 2017 magnitude of these mean bias errors can vary between about -0.2 to +0.2°C (Emery et al 2001;Li et al 2001;Donlon et al 2002;Barton 2007;Alvera-Azcárate et al 2011). It is widely recognized that operational calibration algorithms are needed to bring SST sat and SST bulk back to agreement (Schluessel et al 1990;Walton et al 1998;Kilpatrick et al 2001;Donlon et al 2002).…”

Section: Introductionmentioning

confidence: 99%

“…In shallow waters, it is highly likely that SST sat and SST bulk may be different from each other because the bottom reflectance in these waters may be large and this may result in small scale temperature structure in the water column. However, since the available operational calibration algorithms have been developed almost exclusively in the deep waters (Emery et al 2001), whether they may be directly applicable to the shallow waters is questionable since the mechanism that gives rise to the temperature structures in the surface waters may be different.…”

Section: Introductionmentioning

confidence: 99%

Validation of the remotely sensed nighttime sea surface temperature in the shallow waters at the Dongsha Atoll

Pan¹,

Wong²,

DeCarlo³

et al. 2017

Terr. Atmos. Ocean. Sci.

View full text Add to dashboard Cite

Fine scale temperature structures, which are commonly found in the top few meters of shallow water columns, may result in deviations of the remotely sensed night-time sea surface temperatures (SST) by the MODIS-Aqua sensor (SST sat ) from the bulk sea surface temperatures (SST bulk ) that they purport to represent. The discrepancies between SST sat and SST bulk recorded by temperature loggers at eight stations with bottom depths of 2 -20 m around the Dongsha Atoll (DSA) between June 2013 and May 2015 were examined. The SST sat had an average cool bias error of -0.43 ± 0.59°C. The bias error was larger in the warmer (> 26°C) waters which were presumably more strongly stratified. The root mean square error (RMSE) between SST sat and SST bulk , ±0.73°C, was 25% larger than that reported in the open northern South China Sea. An operational calibration algorithm was developed to increase the accuracy in the estimation of SST bulk from SST sat . In addition to removing the cool bias error, this algorithm also reduced the RMSE to virtually the same level as that found in the open northern South China Sea. With the application of the algorithm, in June 2015, the average SST in the lagoon of the DSA was raised by about 0.5°C to 31.1 ± 0.4°C, and the area of lagoon with SST bulk above 31°C, the median value of the physiological temperature threshold of reef organisms, was increased by 69% to about three quarters of the lagoon.

show abstract

Estimating Sea Surface Temperature from Infrared Satellite and In Situ Temperature Data

Cited by 86 publications

References 34 publications

Seaflux

Seaflux

Uncertainties of satellite-derived surface skin temperatures in the polar oceans: MODIS, AIRS/AMSU, and AIRS only

Validation of the remotely sensed nighttime sea surface temperature in the shallow waters at the Dongsha Atoll

Contact Info

Product

Resources

About