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Towards Improved Quality Control of In Situ Sea Surface Temperatures from Drifting and Moored Buoys in the NOAA iQuam System
The NOAA in situ Sea Surface Temperature (SST) Quality Monitor (iQuam) online system collects in situ SSTs from various sources, performs quality control (QC), and provides QC’ed data to users. Like many other in situ QCs, the iQuam QC employs comparisons with Level 4 SST analysis. However, the curr...
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Published in: | Applied sciences 2023-09, Vol.13 (18), p.10205 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | The NOAA in situ Sea Surface Temperature (SST) Quality Monitor (iQuam) online system collects in situ SSTs from various sources, performs quality control (QC), and provides QC’ed data to users. Like many other in situ QCs, the iQuam QC employs comparisons with Level 4 SST analysis. However, the current daily L4 analyses do not capture the diurnal cycle, nor do they resolve the fine structure of SST in dynamic areas. As a result, high-quality in situ SSTs significantly deviating from the L4 SST may be rejected. This paper discusses the new Diurnal Reference Check (DRC), which addresses overscreening for buoys whose sampling frequency is sufficient for resolving the diurnal cycle. The DRC separates records from individual buoys into 24-h segments and characterizes each segment with the median nighttime (MNT) SST and the amplitude of the diurnal signal (ADS). The segment is rejected if the ADS is unrealistically large or if the difference between the MNT and L4 SST exceeds a geographically dependent threshold. The outliers are further screened out by comparison of individual in situ SSTs with the MNT. All thresholds are determined from the analysis of matchups with reprocessed NOAA SSTs from multiple low-orbiting satellites. The satellite matchups are also used to validate the QC results. The DRC minimizes the overscreening, increases the number of high-quality in situ data by ~5%, and reduces the QC reliance on the L4 analysis. In addition, a new retrospective satellite-based quality check is introduced to identify matchups, which are most useful for training SST algorithms and validation of reprocessed satellite data. |
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ISSN: | 2076-3417 2076-3417 |
DOI: | 10.3390/app131810205 |