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A climate data record of global sea surface temperature (SST) spanning 1981-2016 has been developed from 4 × 10 satellite measurements of thermal infra-red radiance. The spatial area represented by pixel SST estimates is between 1 km and 45 km. The mean density of good-quality observations is 13 km yr. 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 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.
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http://dx.doi.org/10.1038/s41597-019-0236-x | DOI Listing |
Camb Prism Coast Futur
December 2024
Geoscience Australia, Canberra, Australian Capital Territory, Australia.
Tropical cyclones can significantly impact mangrove forests, with some recovering rapidly, whilst others may change permanently. Inconsistent approaches to quantifying these impacts limit the capacity to identify patterns of damage and recovery across landscapes and cyclone categories. Understanding these patterns is critical as the changing frequency and intensity of cyclones and compounding effects of climate change, particularly sea-level rise, threaten mangroves and their ecosystem services.
View Article and Find Full Text PDFJ Imaging
July 2025
Department of Biological, Geological and Environmental Sciences, Alma Mater Studiorum-Università di Bologna, Via Irnerio 42, Emilia-Romagna, 40126 Bologna, Italy.
Image analysis is a valuable approach in a wide array of environmental applications. Mapping land cover categories depicted from satellite images enables the monitoring of landscape dynamics. Such a technique plays a key role for land management and predictive ecosystem modelling.
View Article and Find Full Text PDFJ Hazard Mater
September 2025
State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China.
Satellite-detected water color anomalies around coastal wastewater treatment plant (WWTP) outfalls can serve as indicators of potential environmental contamination, enabling faster and broader-scale assessments compared to traditional field measurements. This study investigated intermittent reddish-brown water color anomalies observed by Sentinel-2 satellite imagery since 2021 near the Shangyu WWTP outfall in Hangzhou Bay (HZB), a highly turbid estuary in eastern China. Although pre-discharge water samples appeared pale yellow and complied with discharge standards, the anomalies suggest more complex optical processes.
View Article and Find Full Text PDFPlant Biol (Stuttg)
May 2025
Department of Earth Observation Science, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, The Netherlands.
Global warming and anthropogenic climate change have intensified drought occurrences, raising concerns about their escalating frequency, intensity, and persistence. With the projection that droughts will increase at the end of the century, it is important to find efficient and cost-effective methods to assess and monitor drought impacts. We leverage freely available satellite-based remote sensing images to study drought stress in forest.
View Article and Find Full Text PDFSci Total Environ
May 2025
Geodesy Group, Department of Sustainability and Planning, Aalborg University, Rendsburggade 14, Aalborg 9000, Denmark.
The integration of satellite-based observations into hydrological models contributes to achieving more precise simulations, thus supporting hazard mitigation and policy-making especially in poorly gauged basins. Sub-monthly Terrestrial Water Storage (TWS) observations derived from the Gravity Recovery and Climate Experiment (GRACE) mission have been shown to contain useful information for the prediction and monitoring of sub-monthly water storage anomalies such as floods. This study assesses, for the first time, the benefits and challenges of integrating sub-monthly TWS into a large-scale hydrological model during flood events.
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