Temperature and salinity dependence of sea surface emissivity in the thermal infrared

Newman, Stuart M.; Smith, J. A.; Glew, Martin D.; Rogers, Stuart; Taylor, Jonathan P.

doi:10.1256/qj.04.150

Cited by 93 publications

(90 citation statements)

References 20 publications

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“…Because these two cases were made with the BAE 146 aircraft flying as low as 30 m above the sea, the surface properties, like the sea surface temperature (SST) and emissivity, are observed with the Airborne Research Interferometer Evaluation System (ARIES) on board (e.g. Newman et al, 2005;Taylor et al, 2007). NAST-I and ARIES observations within the AIRS FOV are used for intercomparisons.…”

Section: -10 September Over Potenza Italymentioning

confidence: 99%

Retrieval validation during the European Aqua Thermodynamic Experiment

Zhou

Smith

Cuomo

et al. 2007

Q.J.R. Meteorol. Soc.

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Atmospheric and surface thermodynamic parameters retrieved with advanced hyperspectral remote sensors aboard Earth observing satellites are critical to weather prediction and scientific research. The retrieval algorithms and retrieved parameters from satellite sounders must be validated to demonstrate the capability and accuracy of both observation and data processing systems. The European Aqua Thermodynamic Experiment (EAQUATE) was conducted not only for validation of the Atmospheric InfraRed Sounder on the Aqua satellite, but also for assessment of validation systems of both ground-based and aircraft-based instruments that will be used for other satellite systems, such as the Infrared Atmospheric Sounding Interferometer on the European MetOp satellite, the Cross-track Infrared Sounder from the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project and the continuing series of NPOESS satellites. Detailed intercomparisons were conducted and presented using different retrieval methodologies: measurements from airborne ultraspectral Fourier transform spectrometers, aircraft in situ instruments, dedicated dropsondes and radiosondes, ground-based Raman lidar, as well as the European Centre for Medium-range Weather Forecasting modelled thermal structures. The results of this study not only illustrate the quality of the measurements and retrieval products, but also demonstrate the capability of the validation systems put in place to validate current and future hyperspectral sounding instruments and their scientific products.

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Section: -10 September Over Potenza Italymentioning

confidence: 99%

Retrieval validation during the European Aqua Thermodynamic Experiment

Zhou

Smith

Cuomo

et al. 2007

Q.J.R. Meteorol. Soc.

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“…Newman et al [34] mention that the temperature-dependent emissivity is often underestimated and its effect neglected as a result. Nevertheless, differentiated SWC for ranges of surface temperatures are only associated with moderate improvements, even though temperature dependent emissivity of the surface is not considered within the split-window equation (Equation (1)).…”

Section: Discussionmentioning

confidence: 99%

“…It determines the strength of the emitted signal at the earth's surface and also influences the emissivity itself [34]. Similar to the VZA limit, the parameter represents the number of bins that is applied to split the range; the result is then applied to separate coefficients.…”

Section: Sensitivity Analysismentioning

confidence: 99%

Performance Assessment of Tailored Split-Window Coefficients for the Retrieval of Lake Surface Water Temperature from AVHRR Satellite Data

2017

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Abstract:Although lake surface water temperature (LSWT) is defined as an essential climate variable (ECV) within the global climate observing system (GCOS), current satellite-based retrieval techniques do not fulfill the GCOS accuracy requirements. The split-window (SW) retrieval method is well-established, and the split-window coefficients (SWC) are the key elements of its accuracy. Performances of SW depends on the degree of SWC customization with respect to its application, where accuracy increases when SWC is tailored for specific situations. In the literature, different SWC customization approaches have been investigated, however, no direct comparisons have been conducted among them. This paper presents the results of a sensitivity analysis to address this gap. We show that the performance of SWC is most sensitive to customizations for specific time-windows (Sensitivity Index SI of 0.85) or spatial extents (SI 0.27). Surprisingly, the study highlights that the use of separated SWC for daytime and night-time situations has limited impact (SI 0.10). The final validation with AVHRR satellite data showed that the subtle differences among different SWC customizations were not traceable to the final uncertainty of the LSWT product. Nevertheless, this study provides a basis to critically evaluate current assumptions regarding SWC generation by directly comparing the performance of multiple customization approaches for the first time.

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“…A unique first guess of dust vertical distribution (the same profile for all pixels and all seasons) is considered in the inversion, which is obtained from an average of CALIOP extinction vertical profiles for dust over the Sahara (during large dust outbreaks in late June 2011), scaled to particle concentration units (in order to set an a priori AOD at 10 µm of 0.03). Forward simulations include surface emissivity from a global monthly IASI-derived climatology over land (Paul et al, 2012) and a surface-temperature-dependent model over ocean (Newman et al, 2005).…”

Section: Iasi Lisa Algorithm -Aeroiasimentioning

confidence: 99%

Comparison of dust-layer heights from active and passive satellite sensors

et al. 2018

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Abstract. Aerosol-layer height is essential for understanding the impact of aerosols on the climate system. As part of the European Space Agency Aerosol_cci project, aerosollayer height as derived from passive thermal and solar satellite sensors measurements have been compared with aerosollayer heights estimated from CALIOP measurements. The Aerosol_cci project targeted dust-type aerosol for this study. This ensures relatively unambiguous aerosol identification by the CALIOP processing chain. Dust-layer height was estimated from thermal IASI measurements using four different algorithms (from BIRA-IASB, DLR, LMD, LISA) and from solar GOME-2 (KNMI) and SCIAMACHY (IUP) measurements. Due to differences in overpass time of the various satellites, a trajectory model was used to move the CALIOPderived dust heights in space and time to the IASI, GOME-2 and SCIAMACHY dust height pixels. It is not possible to construct a unique dust-layer height from the CALIOP data. Thus two CALIOP-derived layer heights were used: the cumulative extinction height defined as the height where the CALIOP extinction column is half of the total extinction column, and the geometric mean height, which is defined as the geometrical mean of the top and bottom heights of the dust layer. In statistical average over all IASI data there is a general tendency to a positive bias of 0.5-0.8 km against CALIOP extinction-weighted height for three of the four algorithms assessed, while the fourth algorithm has almost no bias. When comparing geometric mean height there is a shift of −0.5 km for all algorithms (getting close to zero for the three algorithms and turning negative for the fourth). The standard deviation of all algorithms is quite similar and ranges between 1.0 and 1.3 km. When looking at different conditions (day, night, land, ocean), there is more detail in variabilities (e.g. all algorithms overestimate more at night than during the day). For the solar sensors it is found that on average SCIAMACHY data are lower by −1.097 km (−0.961 km) compared to the CALIOP geometric mean (cumulative extinction) height, and GOME-2 data are lower by −1.393 km (−0.818 km).

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Temperature and salinity dependence of sea surface emissivity in the thermal infrared

Cited by 93 publications

References 20 publications

Retrieval validation during the European Aqua Thermodynamic Experiment

Retrieval validation during the European Aqua Thermodynamic Experiment

Performance Assessment of Tailored Split-Window Coefficients for the Retrieval of Lake Surface Water Temperature from AVHRR Satellite Data

Comparison of dust-layer heights from active and passive satellite sensors

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