Validation of S-NPP VIIRS Sea Surface Temperature Retrieved from NAVO

Tu, Qianguang; Pan, Delu; Hao, Zengzhou

doi:10.3390/rs71215881

Cited by 14 publications

(7 citation statements)

References 27 publications

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“…The magnitude and characteristics This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/ of uncertainties in Suomi National Polar-orbiting Partnership, the Visible Infrared Imaging Radiometer Suite (S-NPP VIIRS) SST produced by the Naval Oceanographic Office (NAVO) are also investigated [7]. Recently, the pixel-to-pixel uncertainty in the VIIRS and AVHRR SST fields over the Sargasso Sea are evaluated [8].…”

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confidence: 99%

Validation of Sea Surface Temperature Derived From Himawari-8 by JAXA

Hao

2020

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Hourly sea surface temperature (SST) retrieved from Himawari-8 by the Japan Aerospace Exploration Agency (H8-SST/JAXA, latest version 1.2) is becoming an important data source for data merging as well as for resolving diurnal variation (DV). However, the spatial and temporal variation of the errors for the full disk is still unclear. In this article, two years of H8-SSTs/JAXA are validated against in situ measurements from iQuam2. In general, H8-SSTs/JAXA shows small biases between −0.11 and −0.03 K with root mean square error (RMSE) between 0.58 and 0.73 K. The spatial distributions of the errors reveal the following patterns: 1) a small median bias close to 0.1 K and RMSE of 0.4-0.6 K comparing to drifters are found at satellite zenith angle (SZA) 0°-35°; 2) negative biases (∼−0.3 K) are detected at SZA s 35°-58°; and 3) larger positive biases exceeding 0.3 K are also found along the viewing boundaries. The temporal variations of the errors show that 1) there is no prominent seasonal variation; 2) the amplitude of the DV of the errors is only ∼0.1 K for the statistical of all matchups, and 3) the maximum errors appears in the morning rather than in the noon. The statistics will be used in future work for DV analysis and merging purposes.

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confidence: 99%

Validation of Sea Surface Temperature Derived From Himawari-8 by JAXA

Hao

2020

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…This method is performed by analyzing the standard deviation of error of three kind of dataset derived from satellite and in-situ measurement (O'Carroll et al 2008). Xu and Ignatov (2010), used a three way error analysis method to calibrate and validate satellite data using insitu data, while Tu et al (2015), Using a 3 way method to validate The NAVO S-NPP VIIRS SST using in situ data from the National Oceanic and Atmospheric Administration insitu Quality Monitor (iQuam). In this study we use SST from Himawari-8, Multi-scale Ultra-high Resolution (MUR) SST, and buoy data.…”

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confidence: 99%

Three-Way Error Analysis of Sea Surface Temperature (Sst) Between Himawari-8, Buoy, and Mur SST in Savu Sea

Sukresno

Hanintyo²,

Kusuma³

et al. 2018

IJReSES

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Variance errors of Himawari-8, buoy, and Multi-scale Ultra-high Resolution (MUR) SST in Savu Sea have been investigated. This research used level 3 Himawari-8 hourly SST, in situ measurement of buoy, and daily MUR SST in the period of December 2016 to July 2017. The data were separated into day time data and night time. Skin temperature of Himawari-8 and subskin tempertaure of MUR SST were corrected with the value of 15âˆ†Tdept"> before compared with buoy data. Hourly SST of Himawari-8 and buoy data were converted to daily format by averaging process before collocated with MUR SST data. The number of 2,264 matchup data are obtained. Differences average between Himawari-8, buoy and MUR SST were calculated to get the value of variance (Vij). Using three-way error analysis, variance errors of each observation type can be known. From the analysis results can be seen that the variance error of Himawari-8, buoy and MUR SST are 2.5 oC, 0.28oC and 1.21oC respectively. The accuracy of buoy data was better than the other. With a small variance errors, thus buoy data can be used as a reference data for validation of SST from different observation type.

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“…where V ij gives the variance of the difference between two observation types i and j. This relationship has been recently applied to SST validation analyses [46][47][48], and it is used to inter-compare daily and 10-day mean SST (SST fnd and δSST) of the present study, with in situ measurements, and geostationary high-resolution datasets.…”

Section: Sst Validationmentioning

confidence: 99%

Variability of Diurnal Sea Surface Temperature during Short Term and High SST Event in the Western Equatorial Pacific as Revealed by Satellite Data

Wirasatriya

Hosoda²,

Setiawan

et al. 2020

Remote Sensing

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Near-surface diurnal warming is an important process in the climate system, driving exchanges of water vapor and heat between the ocean and the atmosphere. The occurrence of the hot event (HE) is associated with the high diurnal sea surface temperature amplitude (δSST), which is defined as the difference between daily maximum and minimum sea surface temperature (SST). However, previous studies still show some inconsistency for the area of HE occurrence and high δSST. The present study produces global δSST data based on the SST, sea surface wind data derived from microwave radiometers, and solar radiation data obtained from visible/infrared radiometers. The value of δSSTs are estimated and validated over tropical oceans and then used for investigating HE in the western equatorial Pacific. A three-way error analysis was conducted using in situ mooring buoy arrays and geostationary SST measurements by the Himawari-8 and Geostationary Operational Environmental Satellite (GOES). The standard deviation error of daily and 10-day validation is around 0.3 °C and 0.14–0.19 °C, respectively. Our case study in the western Pacific (from 110°E to 150°W) shows that the area of HE occurrence coincided well with the area of high δSST. Climatological analysis shows that the collocated area between high occurrence rate of HE and high δSST, which coincides with the western Pacific warm pool region in all seasons. Thus, this study provides more persuasive evidence of the relation between HE occurrence and high δSST.

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Validation of S-NPP VIIRS Sea Surface Temperature Retrieved from NAVO

Cited by 14 publications

References 27 publications

Validation of Sea Surface Temperature Derived From Himawari-8 by JAXA

Validation of Sea Surface Temperature Derived From Himawari-8 by JAXA

Three-Way Error Analysis of Sea Surface Temperature (Sst) Between Himawari-8, Buoy, and Mur SST in Savu Sea

Variability of Diurnal Sea Surface Temperature during Short Term and High SST Event in the Western Equatorial Pacific as Revealed by Satellite Data

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