Atmospheric correction of infrared measurements of sea surface temperature using channels at 3.7, 11 and 12 ?m

Deschamps, Pierre-Yves; Phulpin, T.

doi:10.1007/bf00121320

Cited by 217 publications

(81 citation statements)

References 9 publications

(7 reference statements)

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“…Satellite-based retrieval of SST, a measure of the skin (top ~1 mm) temperature, is a benchmark parameter for monitoring long-term climate change owing to the tight coupling between the ocean and atmosphere. Satellite-based retrievals using multispectral observations in the infrared have been conducted routinely since the early 1980s (e.g., [98,99]). To reduce biases related to skin temperature warming in regions of lower wind speed (and less mixing, leading to warming of up to 3 °C in these areas; e.g., [100,101]) the SST CDR is based on nighttime retrievals.…”

Section: Climate Researchmentioning

confidence: 99%

Illuminating the Capabilities of the Suomi National Polar-Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band

Miller

Straka

Mills³

et al. 2013

Remote Sensing

296

207

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Daytime measurements of reflected sunlight in the visible spectrum have been a staple of Earth-viewing radiometers since the advent of the environmental satellite platform. At night, these same optical-spectrum sensors have traditionally been limited to thermal infrared emission, which contains relatively poor information content for many OPEN ACCESSRemote Sens. 2013, 5 6718 important weather and climate parameters. These deficiencies have limited our ability to characterize the full diurnal behavior and processes of parameters relevant to improved monitoring, understanding and modeling of weather and climate processes. Visible-spectrum light information does exist during the nighttime hours, originating from a wide variety of sources, but its detection requires specialized technology. Such measurements have existed, in a limited way, on USA Department of Defense satellites, but the Suomi National Polar-orbiting Partnership (NPP) satellite, which carries a new Day/Night Band (DNB) radiometer, offers the first quantitative measurements of nocturnal visible and near-infrared light. Here, we demonstrate the expanded potential for nocturnal low-light visible applications enabled by the DNB. Via a combination of terrestrial and extraterrestrial light sources, such observations are always available-expanding many current existing applications while enabling entirely new capabilities. These novel low-light measurements open doors to a wealth of new interdisciplinary research topics while lighting a pathway toward the optimized design of follow-on satellite based low light visible sensors.

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Section: Climate Researchmentioning

confidence: 99%

Illuminating the Capabilities of the Suomi National Polar-Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band

Miller

Straka

Mills³

et al. 2013

Remote Sensing

296

207

View full text Add to dashboard Cite

show abstract

“…The retrieval of sea surface temperature (SST) from space-based multichannel observations of infrared radiances (Deschamps and Phulpin 1980) has been performed routinely since 1981 and is now an important element of the global observing system for weather prediction and climate monitoring. Early retrieval schemes for the Advanced Very High Resolution Radiometer (AVHRR) were empirically determined by regression of observations matched to in situ SSTs (McClain et al 1985).…”

Section: Introductionmentioning

confidence: 99%

Retrieval of Sea Surface Temperature from Space, Based on Modeling of Infrared Radiative Transfer: Capabilities and Limitations

Merchant

Borgne

2004

Journal of Atmospheric and Oceanic Technology

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The retrieval (estimation) of sea surface temperatures (SSTs) from space-based infrared observations is increasingly performed using retrieval coefficients derived from radiative transfer simulations of top-of-atmosphere brightness temperatures (BTs). Typically, an estimate of SST is formed from a weighted combination of BTs at a few wavelengths, plus an offset. This paper addresses two questions about the radiative transfer modeling approach to deriving these weighting and offset coefficients. How precisely specified do the coefficients need to be in order to obtain the required SST accuracy (e.g., scatter <0.3 K in week-average SST, bias <0.1 K)? And how precisely is it actually possible to specify them using current forward models? The conclusions are that weighting coefficients can be obtained with adequate precision, while the offset coefficient will often require an empirical adjustment of the order of a few tenths of a kelvin against validation data. Thus, a rational approach to defining retrieval coefficients is one of radiative transfer modeling followed by offset adjustment. The need for this approach is illustrated from experience in defining SST retrieval schemes for operational meteorological satellites. A strategy is described for obtaining the required offset adjustment, and the paper highlights some of the subtler aspects involved with reference to the example of SST retrievals from the imager on the geostationary satellite GOES-8.

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“…So far, there exist several standard algorithms to derive sea surface temperature from NOAA/AVHRR data. They are based on the split-window technique that corrects for atmospheric effects using different channels in the thermal infrared wavelength range (Anding and Kauth, 1970;Deschamps and Phulpin, 1980;McMillin and Crosby, 1984;McClain et al, 1985;Yokoyama and Tanba, 1991;Barton, 1995;Schlüssel 1995Schlüssel , 1996. These algorithms have been developed on a global scale.…”

Section: Introductionmentioning

confidence: 99%

Determination of the bulk temperature from NOAA/AVHRR satellite data in a midlatitude lake

Thiemann

Schiller²

2003

International Journal of Applied Earth Observation and Geoinfor

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The spatial and temporal variability of the bulk temperature gives important insights into biological and hydrodynamic processes. However, standard algorithms for satellite data only provide information of the surface temperature. The comparison of current and new split-window coefficients applied on NOAA-14/AVHRR brightness temperatures of Lake Constance showed that a regional adaption was most promising. To derive the bulk temperature information, a priori progression from a weather station was included into the AVHRR analysis. Among the weather is data, the mean temperature of the three preceding days and the day of the year were the most relevant additional information. By a multiple regression approach the bulk temperature in the upper 4 m of Lake Constance could be determined with an accuracy of ±1.20 • C. The training of a neural network improved the determination of the bulk temperature to ±1.04 • C.An extended field campaign demonstrated that the algorithm is also applicable to other sensors with the same spectral band settings (in this case NOAA-16/AVHRR) with an acceptable error and that it is equally accurate over the entire lake.

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Atmospheric correction of infrared measurements of sea surface temperature using channels at 3.7, 11 and 12 ?m

Cited by 217 publications

References 9 publications

Illuminating the Capabilities of the Suomi National Polar-Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band

Illuminating the Capabilities of the Suomi National Polar-Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band

Retrieval of Sea Surface Temperature from Space, Based on Modeling of Infrared Radiative Transfer: Capabilities and Limitations

Determination of the bulk temperature from NOAA/AVHRR satellite data in a midlatitude lake

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