Improving Satellite Retrieved Infrared Sea Surface Temperatures in Aerosol Contaminated Regions

Infrared satellite observations of sea surface temperature (SST) have become essential for many applications in meteorology, climatology, and oceanography. Infrared satellite instruments passively measure the infrared energy reflected and emitted by the Earth\u27s surface, which is then modified by the intervening atmosphere. Tropospheric aerosol concentrations increase infrared signal attenuation and affect the accuracy of infrared satellite SST retrievals. Satellite-derived skin SST with measurements from the Marine-Atmospheric Emitted Radiance Interferometer (M-AERI) deployed on ships during the Aerosols and Ocean Science Expeditions (AEROSE) and quality-controlled, collocated subsurface drifter temperatures. Satellite skin SSTs with any possible cloud contamination were removed from the dataset then the remaining measurements were temporally and spatially collocated with the in-situ SST (skin and bulk) measurements. With in-situ SSTskin and filtering of cloud contaminated data, results indicate that, in this region, SSTskin retrieved from MODIS (Moderate Resolution Imaging Spectroradiometer) aboard the Aqua satellites have cool biases compared to shipboard radiometric measurements. There is also a pronounced negative bias in the Saharan outflow area that can introduce SSTskin errors \u3e1 K at aerosol optical depths \u3e 0.5. In this study, a new method to derive night-time Dust-introduced SST Difference Index (DSDI) algorithms based on simulated brightness temperatures at infrared wavelengths of 3.9, 8.7, 10.8 and 12.0 μm, is derived using Radiative Transfer for TOVS (RTTOV). Algorithm for MODIS measurements were derived by regression of the difference between the MODIS SSTskin and the in-situ measurements against the DSDI. The biases and STD are reduced by 0.25K and 0.19K after the DSDI correction. The goal of this study is to understand better the characteristics of aerosol effects on satellite retrieved infrared SST, and to derive empirical formulae for improved accuracies in aerosol-contaminated regions

Comparison of SLSTR Thermal Emissive Bands Clear-Sky Measurements with Those of Geostationary Imagers

The Sentinel-3 series satellites belong to the European Earth Observation satellite missions for supporting oceanography, land, and atmospheric studies. The Sea and Land Surface Temperature Radiometer (SLSTR) onboard the Sentinel-3 satellites was designed to provide a significant improvement in remote sensing of skin sea surface temperature (SSTskin). The successful application of SLSTR-derived SSTskin fields depends on their accuracies. Based on sensor-dependent radiative transfer model simulations, geostationary Geostationary Operational Environmental Satellite (GOES-16) Advanced Baseline Imagers (ABI) and Meteosat Second Generation (MSG-4) Spinning Enhanced Visible and Infrared Imager (SEVIRI) brightness temperatures (BT) have been transformed to SLSTR equivalents to permit comparisons at the pixel level in three ocean regions. The results show the averaged BT differences are on the order of 0.1 K and the existence of small biases between them are likely due to the uncertainties in cloud masking, satellite view angle, solar azimuth angle, and reflected solar light. This study demonstrates the feasibility of combining SSTskin retrievals from SLSTR with those of ABI and SEVIRI

Saharan Dust Effects on Sea Surface Radiative Fluxes and Satellite Derived SSTs Determined from Field Data Analysis and Model Simulations

The large-scale Saharan dust outbreaks usually occur over the tropical and subtropical Atlantic Ocean and have been observed from the visible and infrared sensors on satellites for many years. The dust aerosol scattering and absorption effects the surface radiative fluxes (SRF); and the dust aerosols also increase the infrared signal attenuation and degrade the accuracy of Skin Sea-Surface Temperature (SSTskin) retrieved from infrared radiometers on satellites. Accurate quantification of the dust perturbation to the surface energy budget is fundamental to understanding critical climate feedbacks and to determine the Earth's surface energy budget. By exploiting large sets of measurements from many ship campaigns in conjunction with reanalysis products, this study characterizes the sensitivity of the SRF and SSTskin to the Saharan dust aerosols with radiative transfer model simulations. Strong SRF and SSTskin anomalies are often a consequence of Saharan dust outbreaks. The SSTskin derived from satellite radiometers is one of the critical factors for determining ocean-atmosphere interactions in climate prediction and ocean research. Different dust aerosol vertical distributions have varying effects on the satellite-derived SSTskin. To further investigate the physical mechanisms of aerosol effects on satellite derived SSTskin, the aerosol radiative effects were studied with an analysis of field measurement, satellite data, and radiative transfer simulations. Based on the analysis of field data and simulations, we have empirically determined that the sensitivity of the MODIS retrieved SSTskin accuracies is related to 1) dust concentration in the atmosphere, 2) the dust layer altitude, and 3) the dust layer temperature. As the dust aerosol layer altitude increases, the effect on the SSTskin retrievals becomes more negative with increasing temperature contrast with the sea surface. Satellite-derived SSTskin minus surface measured SSTskin differences vary between -3 K and 1 K.</p

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

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

Skin Sea Surface Temperatures From the GOES-16 ABI Validated With Those of the Shipborne M-AERI

Derived from satellite measurements, the skin sea surface temperature (SSTHammerDriveskin) is a critical variable in research into the climate and other aspects of the ocean-atmosphere system As the new generation of visible and infrared imaging radiometers, the Advanced Baseline Imager (ABI) onboard the current U.S. geostationary satellites series provides marked improvements to remote sensing of the ocean surface from geostationary orbit, including a wider range of spectral bands and more rapid sampling. This research compares SSTHammerDriveskin derived from the ABI onboard the Geostationary Operational Environmental Satellite (GOES)-16 satellite from January 2018 to October 2019 with the independent data acquired from Marine-Atmospheric Emitted Radiance Interferometers (M-AERIs) deployed on ships. The result shows an averaged SSTHammerDriveskin mean bias of 0.086 K and a robust standard deviation of 0.220 K. The properties of the bias are determined based on various aspects such as geographical distribution, day/night, aerosol effect, and satellite zenith angle. This study also shows that the ABI sensor-specific error statistics (SSES) are effective to reduce the errors by slant-path water vapor and satellite zenith angle. The main result of this research is that the SSTHammerDriveskin products derived from the ABI compare well with independent, International System of Units (SI)-traceable radiometric skin temperatures taken from ships, and this should give confidence in the use of these remotely-sensed SSTHammerDriveskin fields for many scientific endeavors. Some remaining challenges have been identified for algorithm developers to address, and we hope these will be pursued in due course

Comparison of SLSTR Thermal Emissive Bands Clear-Sky Measurements with Those of Geostationary Imagers

The Sentinel-3 series satellites belong to the European Earth Observation satellite missions for supporting oceanography, land, and atmospheric studies. The Sea and Land Surface Temperature Radiometer (SLSTR) onboard the Sentinel-3 satellites was designed to provide a significant improvement in remote sensing of skin sea surface temperature (SSTskin). The successful application of SLSTR-derived SSTskin fields depends on their accuracies. Based on sensor-dependent radiative transfer model simulations, geostationary Geostationary Operational Environmental Satellite (GOES-16) Advanced Baseline Imagers (ABI) and Meteosat Second Generation (MSG-4) Spinning Enhanced Visible and Infrared Imager (SEVIRI) brightness temperatures (BT) have been transformed to SLSTR equivalents to permit comparisons at the pixel level in three ocean regions. The results show the averaged BT differences are on the order of 0.1 K and the existence of small biases between them are likely due to the uncertainties in cloud masking, satellite view angle, solar azimuth angle, and reflected solar light. This study demonstrates the feasibility of combining SSTskin retrievals from SLSTR with those of ABI and SEVIRI

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

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&ndash;sea temperature differences. This study provides suggestions for the applicability of ERA5 SSTskin fields in a selection of research applications

Ship-based high resolution sea surface skin temperature from the Marine-Atmospheric Emitted Radiance Interferometer (M-AERI) deployed between 2013 and 2020

This dataset is a part of that taken with sea-going instruments described by “Minnett, P.J., Knuteson, R.O., Best, F.A., Osborne, B.J., Hanafin, J.A., & Brown, O.B. (2001). The Marine-Atmospheric Emitted Radiance Interferometer (M-AERI), a high-accuracy, sea-going infrared spectroradiometer. Journal of Atmospheric and Oceanic Technology, 18, 994-1013". Specifically, this dataset comprises measurements of M-AERIs, ship-based Fourier Transform Infrared (FTIR) interferometric spectroradiometers mounted on ships a few meters (research ships) or a few tens of meters (cruise ships) above the sea surface. M-AERI spectra can be used to derive several geophysical variables, including accurate Skin Sea Surface Temperature (SSTskin) and near-surface air temperature (Minnett et al., 2005). M-AERI includes two infrared detectors and two internal blackbody cavities with SI-traceable calibration to perform real-time instrument calibration and achieve high-resolution spectra of the sea surface and atmospheric emitted infrared radiation. The scan mirror directs the field of view to include two internal blackbody calibration cavities to the sea surface and atmosphere. Before and after each deployment, the M-AERI calibration is tested using an external validation procedure in the University of Miami RSMAS laboratory using SI-traceable blackbody calibrator thus providing a calibration chain to standards at the National Institute of Standards and Technology (NIST) in the USA (Rice et al., 2004) and the National Physical Laboratory (NPL) in the UK (Theocharous et al., 2019). The absolute accuracy of the infrared spectra produced by the M-AERI is determined by the effectiveness of the black-body cavities as calibration targets. The absolute accuracy of the spectral measurements of the M-AERI is better than 0.03K, which is sufficiently small to give confidence in the use of such data in the validation of satellite SSTskin retrievals. The detailed technical description is given by Minnett et al. (2001), who describe the first generation of M-AERIs which have been replaced by newer models, but for which the measurement process and calibration remain the same.</p

Significant Diurnal Warming Events Observed by Saildrone at High Latitudes

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. Plain Language Summary At high latitudes, satellite remote sensing retrieval of sea surface temperature (SST) is challenging and the number of drifting buoys measuring in situ temperatures for atmospheric correction algorithm refinement and validation is sparser than elsewhere. Two Saildrone cruises in summer 2019, carrying a suite of scientific instruments onboard, can offer both accurate skin SST and subsurface SST measurements in the Pacific sector of Arctic. This study concentrates on those data along with associated atmospheric parameters to demonstrate the characteristics of diurnal variability of temperatures in the upper 2 m of the ocean. That the Arctic is warming much faster than elsewhere as a result of temperature‐dependent feedbacks, emphasizes the need for a better understanding of the thermal structure of the upper Arctic Ocean. Furthermore, comparisons with model simulations reveal that the diurnal warming schemes for high latitudes still need to be improved. Key Points Using skin and subsurface ocean temperatures from two Saildrones to study the 2 m upper ocean thermal stratifications at high latitudes Several diurnal warming events with significantly large amplitudes, some even with long persistence, are documented and discussed Model schemes for diurnal warming applied at high latitudes necessarily need to be improve

Infrared satellite-derived sea surface skin temperature sensitivity to aerosol vertical distribution ̶ Field data analysis and model simulations

Sea surface temperature is an Essential Climate Variable. The radiative impact of mineral dust is one of the major contributors to inaccuracies in the satellite-retrieved sea surface skin temperature (SSTskin). Different aerosol dust vertical distributions have varying effects on the satellite-derived SSTskin. To further investigate the physical mechanisms of aerosol effects on Terra MODerate-resolution Imaging Spectroradiometers (MODIS) derived SSTskin, the aerosol radiative effects were studied with a field-data match-up analysis and radiative transfer simulations. The field data are measurements of the SSTskin derived from highly accurate ship-based infrared spectrometers vertical atmospheric temperature and water vapor radiosonde profiles. The aerosol dust concentrations in three-dimensions from the NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 have been used as input to radiative transfer simulations. Based on the analysis of field data and simulations, we have empirically determined that the sensitivity of the Terra MODIS retrieved SSTskin accuracies is related to 1) dust concentration in the atmosphere, 2) the dust layer altitude, and 3) the dust layer temperature. As the aerosol altitude increases, the effect on the SSTskin retrievals becomes more negative in proportion to the temperature contrast with the sea surface. SSTskin differences, satellite-derived - surface measurements, for a given aerosol layer optical depth vary between −3 K and 1 K according to our match-up comparisons and radiative transfer simulations.•Validation of TERRA MODIS derived Sea-Surface Skin Temperatures (SSTskin)•SSTskin error's sensitivity to aerosol vertical distribution•Using independent in situ data analysis and model simulation