Harmonization of space-borne infra-red sensors measuring sea surface temperature

Sea surface temperature (SST) is observed by a constellation of sensors, and SST retrievals are commonly combined into gridded SST analyses and climate data records (CDRs). Differential biases between SSTs from different sensors cause errors in such products, including feature artefacts. We introduce a new method for reducing differential biases across the SST constellation, by reconciling the brightness temperature (BT) calibration and SST retrieval parameters between sensors. We use the Advanced Along-Track Scanning Radiometer (AATSR) and the Sea and Land Surface Temperature Radiometer (SLSTR) as reference sensors, and the Advanced Very High Resolution Radiometer (AVHRR) of the MetOp-A mission to bridge the gap between these references. Observations across a range of AVHRR zenith angles are matched with dual-view three-channel skin SST retrievals from the AATSR and SLSTR. These skin SSTs act as the harmonization reference for AVHRR retrievals by optimal estimation (OE). Parameters for the harmonized AVHRR OE are iteratively determined, including BT bias corrections and observation error covariance matrices as functions of water-vapor path. The OE SSTs obtained from AVHRR are shown to be closely consistent with the reference sensor SSTs. Independent validation against drifting buoy SSTs shows that the AVHRR OE retrieval is stable across the reference-sensor gap. We discuss that this method is suitable to improve consistency across the whole constellation of SST sensors. The approach will help stabilize and reduce errors in future SST CDRs, as well as having application to other domains of remote sensing

Stability assessment of the (A)ATSR sea surface temperature climate dataset from the European Space Agency Climate Change Initiative

Sea surface temperature is a key component of the climate record, with multiple independent records giving confidence in observed changes. As part of the European Space Agencies (ESA) Climate Change Initiative (CCI) the satellite archives have been reprocessed with the aim of creating a new dataset that is independent of the in situ observations, and stable with no artificial drift (<0.1 K decade−1 globally) or step changes. We present a method to assess the satellite sea surface temperature (SST) record for step changes using the Penalized Maximal t Test (PMT) applied to aggregate time series. We demonstrated the application of the method using data from version EXP1.8 of the ESA SST CCI dataset averaged on a 7 km grid and in situ observations from moored buoys, drifting buoys and Argo floats. The CCI dataset was shown to be stable after ~1994, with minimal divergence (~0.01 K decade−1) between the CCI data and in situ observations. Two steps were identified due to the failure of a gyroscope on the ERS-2 satellite, and subsequent correction mechanisms applied. These had minimal impact on the stability due to having equal magnitudes but opposite signs. The statistical power and false alarm rate of the method were assessed

Intercomparison of long-term sea surface temperature analyses using the GHRSST Multi-Product Ensemble (GMPE) system

Six global, gridded, gap-free, daily sea surface temperature (SST) analyses covering a period of at least 20 years have been intercompared: ESA SST CCI anal- ysis long-term product v1.0, MyOcean OSTIA reanalysis v1.0, CMC 0.2 degree, AVHRR ONLY Daily 1/4 degree OISST v2.0, HadISST2.1.0.0 and MGDSST. A seventh SST product of the ensemble median of all six has also been produced using the GMPE (Group for High Resolution SST Multi-Product Ensemble) sys- tem. Validation against independent near-surface Argo data, a long timeseries of moored buoy data from the tropics and anomalies to the GMPE median have been used to examine the temporal and spatial homogeneity of the analyses. A comparison of the feature resolution of the analyses has also been undertaken. A summary of relative strengths and weaknesses of the SST datasets is presented, intended to help users to make an informed choice of which analysis is most suitable for their proposed application

Satellite-based time-series of sea-surface temperature since 1981 for climate applications

A climate data record of global sea surface temperature (SST) spanning 1981–2016 has been developed from 4 × 10^12 satellite measurements of thermal infra-red radiance. The spatial area represented by pixel SST estimates is between 1 km^2 and 45 km^2. The mean density of good-quality observations is 13 km^−2 yr^−1. SST uncertainty is evaluated per datum, the median uncertainty for pixel SSTs being 0.18 K. Multi-annual observational stability relative to drifting buoy measurements is within 0.003 K yr^−1 of zero with high confidence, despite maximal independence from in situ SSTs over the latter two decades of the record. Data are provided at native resolution, gridded at 0.05° latitude-longitude resolution (individual sensors), and aggregated and gap-filled on a daily 0.05° grid. Skin SSTs, depth-adjusted SSTs de-aliased with respect to the diurnal cycle, and SST anomalies are provided. Target applications of the dataset include: climate and ocean model evaluation; quantification of marine change and variability (including marine heatwaves); climate and ocean-atmosphere processes; and specific applications in ocean ecology, oceanography and geophysics

A pathway to generating Climate Data Records of sea-surface temperature from satellite measurements

In addition to having known uncertainty characteristics, Climate Data Records (CDRs) of geophysical variables derived from satellite measurements must be of sufficient length to resolve signals that might reveal the signatures of climate change against a background of larger, unrelated variability. The length of the record requires using satellite measurements from many instruments over several decades, and the uncertainty requirement implies that a consistent approach be used to establish the errors in the satellite retrievals over the entire period. Retrieving sea-surface temperature (SST) from satellite is a relatively mature topic, and the uncertainties of satellite retrievals are determined by comparison with collocated independent measurements. To avoid the complicating effects of near-surface temperature gradients in the upper ocean, the best validating measurements are from ship-board radiometers that measure, at source, the surface emission that is measured in space, after modification by its propagation through the atmosphere. To attain sufficient accuracy, such ship-based radiometers must use internal blackbody calibration targets, but to determine the uncertainties in these radiometric measurements, i.e. to confirm that the internal calibration is effective, it is necessary to conduct verification of the field calibration using independent blackbodies with accurately known emissivity and at very accurately measured temperatures. This is a well-justifiable approach to providing the necessary underpinning of a Climate Data Record of SST

A concurrent multi-axis differential optical absorption spectroscopy system for the measurement of tropospheric nitrogen dioxide

The development of a new concurrent multi-axis sky viewing spectrometer for monitoring rapidly changing urban concentrations of nitrogen dioxide is detailed. The concurrent multi-axis differential optical absorption spectroscopy (CMAX-DOAS) technique involves simultaneous spectral imaging of the zenith and off-axis measurements of spatially resolved scattered sun-light. Trace gas amounts are retrieved from the measured spectra using the established DOAS technique. The potential of the CMAX DOAS technique to derive information on rapidly changing concentrations and the spatial distribution of nitrogen dioxide in an urban environment is demonstrated. Three example datasets are presented from measurements during 2004 of tropospheric NO2 over Leicester, UK (52.62 °N, 1.12 °W). The data demonstrates the current capabilities and future potential of the CMAX-DOAS method in terms of the ability to measure the real-time spatially disaggregated urban NO2

Spatially resolved measurements of nitrogen dioxide in an urban environment using concurrent multi-axis differential optical absorption spectroscopy

A novel system using the technique of concurrent multi-axis differential optical absorption spectroscopy system has been developed and applied to the measurement of nitrogen dioxide in an urban environment. Using five fixed telescopes, slant columns of nitrogen dioxide, ozone, water vapour, and the oxygen dimer, O4, are simultaneously retrieved in five vertically separated viewing directions. The application of this remote sensing technique in the urban environment is explored. Through the application of several simplifying assumptions a tropospheric concentration of NO2 is derived and compared with an urban background in-situ chemiluminescence detector. Trends derived from remote sensing and in-situ techniques show agreement to within 15 to 40% depending on conditions. Owing to the high time resolution of the measurements, the ability to image and quantify plumes within the urban environment is demonstrated. The CMAX-DOAS measurements provide a useful measure of overall NO2 concentrations on a city-wide scale