Evaluation of the ERA5 Sea Surface Skin Temperature with Remotely-Sensed Shipborne Marine-Atmospheric Emitted Radiance Interferometer Data

Bingkun Luo,Peter J Minnett

doi:10.3390/rs12111873

Abstract

Sea surface temperature is very important in weather and ocean forecasting, and studying the ocean, atmosphere and climate system. Measuring the sea surface skin temperature (SSTskin) with infrared radiometers onboard earth observation satellites and shipboard instruments is a mature subject spanning several decades. Reanalysis model output SSTskin, such as from the newly released ERA5, is very widely used and has been applied for monitoring climate change, weather prediction research, and other commercial applications. The ERA5 output SSTskin data must be rigorously evaluated to meet the stringent accuracy requirements for climate research. This study aims to estimate the accuracy of the ERA5 SSTskin fields and provide an associated error estimate by using measurements from accurate shipboard infrared radiometers: the Marine-Atmosphere Emitted Radiance Interferometers (M-AERIs). Overall, the ERA5 SSTskin has high correlation with ship-based radiometric measurements, with an average difference of~0.2 K with a Pearson correlation coefficient (R) of 0.993. Parts of the discrepancies are related to dust aerosols and variability in air-sea temperature differences. The downward radiative flux due to dust aerosols leads to significant SSTskin differences for ERA5. The SSTskin differences are greater with the large, positive air–sea temperature differences. This study provides suggestions for the applicability of ERA5 SSTskin fields in a selection of research applications.

Highlights

Sea-surface temperature (SST) has been declared to be an Essential Climate Variable (ECV; [1]) by the Global Climate Observing System (GCOS)
The comparison of ERA5 SSTskin with Marine-Atmosphere Emitted Radiance Interferometers (M-AERIs) SSTskin values can be made by populating a matchup data base (MUDB)
Each MUDB record includes the ERA5 SSTskin corresponding to a set of times and locations of a M-AERI measurement

Summary

Introduction

Sea-surface temperature (SST) has been declared to be an Essential Climate Variable (ECV; [1]) by the Global Climate Observing System (GCOS). SST data are essential in many areas of research, such as climate change and weather forecasting [2,3,4]. Climate change research usually needs consistent SST data, which may be acquired by long series of measurements. Weather and ocean forecasting typically require the best estimate data, collected by as many observations as possible within a specific period of time, and available within a short interval after the measurements are taken. Reanalysis datasets usually strike a balance between these two requirements, trying to generate long-term, consistent, high-quality data [7]. Over the past few decades, a number of reanalyses, such as the European Centre for Medium-Range Weather Forecasts (ECMWF) re-analyses, ERA-Interim [8] and ERA5 [9,10]; the National Centers for Environmental Predictions (NCEP)—National

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