Sea surface temperature in global analyses: gains from the copernicus imaging microwave radiometer

Sea surface temperatures (SSTs) derived from passive microwave (PMW) observations benefit global ocean and SST analyses because of their near-all-weather availability. Present PMW SSTs have a real aperture-limited spatial resolution in excess of 50 km, limiting the spatial fidelity with which SST features, reflecting ocean dynamics, can be captured. This contrasts with the target resolution of global analyses of 5 to 10 km. The Copernicus Imaging Microwave Radiometer (CIMR) is a mission concept under consideration as a high-priority candidate mission for the expansion of the Copernicus space programme. This instrument would be capable of real aperture resolution < 15 km with low total uncertainties in the range 0.4–0.8 K for channels between 1.4 and 36.5 GHz, and a dual-view arrangement that further reduces noise. This paper provides a comparative study of SST uncertainty and feature resolution with and without the availability of CIMR in the future SST-observing satellite constellation based on a detailed simulation of CIMR plus infrared observations and the processing of global SST analyses with 0.05◦ final grid resolution. Simulations of CIMR data including structured errors were added to an observing system consisting of the Sea and Land Surface Temperature Radiometer (SLSTR) on Sentinel-3A and the Advanced Very High Resolution Radiometer (AVHRR) on MetOp-A. This resulted in a large improvement in the global root-mean-square error (RMSE) for SST from 0.37 K to 0.21 K for January and 0.40 K to 0.25 K for July. There was a particularly noticeable improvement in the performance of the analysis, as measured by the reduction in RMSE, for dynamical and persistently cloudy areas. Of these, the Aghulas Current showed an improvement of 43% in January and 48% in July, the Gulf Stream showed 70% and 44% improvements, the Southern Ocean showed 57% and 74% improvements, and the Maritime Continent showed 50% and 40% improvements, respectively

High performance software framework for the calculation of satellite-to-satellite data matchups (MMS version 1.2)

We present a Multisensor Matchup System (MMS) that allows systematic detection of satellite based sensor-to- sensor matchups and the extraction of local subsets of satellite data around matchup locations. The software system implements a generic matchup-detection approach and is currently being used for validation and sensor harmonisation purposes. An overview of the flexible and highly configurable software architecture and the target processing environments is given. We discuss improvements implemented with respect to heritage systems, and present some performance comparisons. A detailed description of the intersection algorithm is given which allows a fast matchup detection in geometry and time

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

Physical Aspects of Healthy Aging: Assessments of Three Measures of Balance for Studies in Middle-Aged and Older Adults

Objectives. To investigate the reliability and correlations with age of the balance components of the EPESE, NHANES, and the Good Balance Platform System (GBPS) in a normal population of adults. Design. Cross-sectional. Setting. Urban Medical Center in the Pacific. Participants. A random sample of 203 healthy offspring of Honolulu Heart Program participants, ages 38–71. Measurements. Subjects were examined twice at visits one week apart using the balance components of the EPESE, NHANES, and the good balance system tests. Results. The EPESE and NHANES batteries of tests were not sufficiently challenging to allow successful discrimination among subjects in good health, even older subjects. The GBPS allowed objective quantitative measurements, but the test-retest correlations generally were not high. The GBPS variables correlated with age only when subjects stood on a foam pad; they also were correlated with anthropometric variables. Conclusion. Both EPESE and NHANES balance tests were too easy for healthy subjects. The GBPS had generally low reliability coefficients except for the most difficult testing condition (foam pad, eyes closed). Both height and body fat were associated with GBPS scores, necessitating adjusting for these variables if using balance as a predictor of future health

Satellites will address critical science priorities for quantifying ocean carbon

The ability to routinely quantify global carbon dioxide (CO2) absorption by the oceans has become crucial: it provides a powerful constraint for establishing global and regional carbon (C) budgets, and enables identification of the ecological impacts and risks of this uptake on the marine environment. Advances in understanding, technology, and international coordination have made it possible to measure CO2 absorption by the oceans to a greater degree of accuracy than is possible in terrestrial landscapes. These advances, combined with new satellite‐based Earth observation capabilities, increasing public availability of data, and cloud computing, provide important opportunities for addressing critical knowledge gaps. Furthermore, Earth observation in synergy with in‐situ monitoring can provide the large‐scale ocean monitoring that is necessary to support policies to protect ocean ecosystems at risk, and motivate societal shifts toward meeting C emissions targets; however, sustained effort will be needed

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

Satellite-based time-series of sea-surface temperature since 1980 for climate applications

A 42-year climate data record of global sea surface temperature (SST) covering 1980 to 2021 has been produced from satellite observations, with a high degree of independence from in situ measurements. Observations from twenty infrared and two microwave radiometers are used, and are adjusted for their differing times of day of measurement to avoid aliasing and ensure observational stability. A total of 1.5 × 1013 locations are processed, yielding 1.4 × 1012 SST observations deemed to be suitable for climate applications. The corresponding observation density varies from less than 1 km−2 yr−1 in 1980 to over 100 km−2 yr−1 after 2007. Data are provided at their native resolution, averaged on a global 0.05° latitude-longitude grid (single-sensor with gaps), and as a daily, merged, gap-free, SST analysis at 0.05°. The data include the satellite-based SSTs, the corresponding time-and-depth standardised estimates, their standard uncertainty and quality flags. Accuracy, spatial coverage and length of record are all improved relative to a previous version, and the timeseries is routinely extended in time using consistent methods