Abstract

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.

Highlights

  • S EA surface temperature (SST) is a crucial component in many physical, biological, and chemical processes within the Earth system [1]

  • Larger positive biases exceeding 0.3 K are found along the viewing boundaries, where satellite zenith angle (SZA) near 60°

  • Statistical results show that the H8-SST/Japan Aerospace Exploration Agency (JAXA) has a biases and root mean square error (RMSE) of −0.03 and 0.73 K, −0.11 and 0.58 K, −0.11 and 0.64 K when comparing against ships, drifter, and Argo, respectively

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Summary

Introduction

S EA surface temperature (SST) is a crucial component in many physical, biological, and chemical processes within the Earth system [1]. SST directly affects the air–sea interactions, seawater composition, and primary productivity. It is a key variable in the fluxes calculation of ocean surface heat and gas. It is used to drive the numerical weather prediction and ocean forecasting models.

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