Satellite and in situ measurements of the sea surface and the atmosphere often have inadequate sampling frequencies and often lack consistent global coverage. Because of such limitations, reanalysis model output is frequently used in atmospheric and oceanographic research endeavors to complement satellite and in situ data. The National Aeronautics and Space Administration’s (NASA’s) Goddard Earth Sciences Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) and the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) datasets provide accurate, complete fields through the assimilation of many atmospheric and surface observations. Still, the reanalysis output data must be rigorously and continuously evaluated to understand their strengths and weaknesses. To this end, this study evaluates sea surface skin temperature (SST_skin) and atmospheric temperature and humidity profiles in MERRA-2 and ERA-Interim data through comparisons with independent Marine-Atmospheric Emitted Radiance Interferometer (M-AERI) and radiosonde data from the Aerosols and Ocean Science Expeditions (AEROSE) cruises, focusing on the representation of spatial and temporal variability. SST_skinvalues are generally in good agreement with corresponding M-AERI measurements, with the average differences on the order of 0.1 K. Comparisons between MERRA-2 and ERA-Interim relative humidity and air temperature profiles with a total of 553 radiosondes that have been withheld from data assimilation schemes show good correspondence below 500 hPa: the average air temperature difference is <2 K and the average relative humidity discrepancy is within 10%. These results support the use of these MERRA-2 and ERA-Interim reanalysis fields in a variety of research applications.

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 (SST_skin) with infrared radiometers onboard earth observation satellites and shipboard instruments is a mature subject spanning several decades. Reanalysis model output SST_skin, 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 SST_skin data must be rigorously evaluated to meet the stringent accuracy requirements for climate research. This study aims to estimate the accuracy of the ERA5 SST_skin 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 SST_skin 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 SST_skin differences for ERA5. The SST_skin differences are greater with the large, positive air–sea temperature differences. This study provides suggestions for the applicability of ERA5 SST_skin fields in a selection of research applications.

The sea surface temperature (SST) is one of the essential parameters needed to understand the climate change in the Arctic. Saildrone, an advanced autonomous surface vehicle, has proven to be a useful tool for providing accurate SST data at high latitudes. Here, data from two Saildrones, deployed in the Arctic in the summer of 2019, are used to investigate the diurnal variability of upper ocean thermal structure. An empirical cool skin effect model with dependence on the wind speed with new coefficients was generated. Several local large diurnal warming events were observed, the amplitudes of warming in the skin layer >5 K, rarely reported in previous studies. Furthermore, the warming signals could persist beyond 1 day. For those cases, it was found surface warm air suppressed the surface turbulent heat loss to maintain the persistence of diurnal warming under low wind conditions. Salinity also plays an important role in the formation of upper ocean density stratification during diurnal warming at high latitudes. A less salty and hence less dense surface layer was likely created by precipitation or melting sea ice, providing favorable conditions for the formation of upper ocean stratification. Comparisons with two prognostic diurnal warming models showed the simulations match reasonably well with Saildrone measurements for moderate wind speeds but exhibit large differences at low winds. Both schemes show significant negative biases in the early morning and late afternoon. It is necessary to improve the model schemes when applied at high latitudes.