AIRWAVE-SLSTR—An Algorithm to Estimate the Total Column of Water Vapour from SLSTR Measurements over Liquid Surfaces
In the past, the possibility to retrieve the total column of water vapour (TCWV) from the thermal infrared (TIR) day and night measurements above water surfaces of the dual-view Along Track Scanning Radiometers (ATSR) has been demonstrated, and an algorithm, named Advanced InfrarRed Water Vapour Est...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/17/7/1205 |
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| Summary: | In the past, the possibility to retrieve the total column of water vapour (TCWV) from the thermal infrared (TIR) day and night measurements above water surfaces of the dual-view Along Track Scanning Radiometers (ATSR) has been demonstrated, and an algorithm, named Advanced InfrarRed Water Vapour Estimator (AIRWAVE), was developed and successfully applied to the measurements of the (A)ATSR instrument series. A similar instrument, the Sea and Land Surface Temperature Radiometer (SLSTR), is currently operating on board the Sentinel 3 satellite series. In this paper, we demonstrate that the AIRWAVE algorithm can be successfully applied to the SLSTR instrument to obtain reliable TCWV measurements. The steps performed for upgrading the algorithm are thoroughly described. The new AIRWAVE algorithm makes use of parameters computed offline with a state-of-the-art radiative transfer model using the most recent spectroscopic data and continuum model. For the parameters calculation, a new climatology capable of representing the average atmospheric and sea surface status during SLSTR measurements has been developed. The new algorithm, named AIRWAVE-SLSTR, has been implemented in both IDL and Python languages. In the frame of an EUMETSAT contract, AIRWAVE-SLSTR has been applied to a full year of SLSTR measurements (2021) and the retrieved TCWV have been validated with the help of both satellite- and ground-based measurements. The correlation of the retrieved TCWV with satellite MW measurements is 0.94 and the average bias is of the order of 0.66 kg/m<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mo></mo><mn>2</mn></msup></semantics></math></inline-formula>. When compared to ground-based measurements, the average correlation is 0.93 and the bias −0.48 kg/m<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mo></mo><mn>2</mn></msup></semantics></math></inline-formula>. The obtained accuracy is well within the requirements set for both numerical weather predictions (1–5 kg/m<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mo></mo><mn>2</mn></msup></semantics></math></inline-formula>) and for coastal altimetry applications (1.8–3 kg/m<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mo></mo><mn>2</mn></msup></semantics></math></inline-formula>). Therefore, the AIRWAVE-SLSTR algorithm can be safely applied to obtain a long time series of reliable TCWV above water surfaces. |
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| ISSN: | 2072-4292 |