Articles | Volume 13, issue 5
https://doi.org/10.5194/essd-13-2111-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-13-2111-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
18 May 2021
Data description paper |
| 18 May 2021
| 18 May 2021
A new global gridded sea surface temperature data product based on multisource data
Mengmeng Cao
Hulunbeir Grassland Ecosystem Research station, Institute of
Agricultural Resources and Regional Planning, Chinese Academy of
Agricultural Sciences, Beijing, 100081, China
Hulunbeir Grassland Ecosystem Research station, Institute of
Agricultural Resources and Regional Planning, Chinese Academy of
Agricultural Sciences, Beijing, 100081, China
School of Physics and Electronic-Engineering, Ningxia University,
Yinchuan, 750021, China
Yibo Yan
Hulunbeir Grassland Ecosystem Research station, Institute of
Agricultural Resources and Regional Planning, Chinese Academy of
Agricultural Sciences, Beijing, 100081, China
Jiancheng Shi
National Space Science Center, Chinese Academy of Sciences,
Beijing, 100190, China
Han Wang
Hulunbeir Grassland Ecosystem Research station, Institute of
Agricultural Resources and Regional Planning, Chinese Academy of
Agricultural Sciences, Beijing, 100081, China
Tongren Xu
State Key Laboratory of Remote Sensing Science, Jointly Sponsored
by the Aerospace Information Research Institute of Chinese Academy of
Sciences and Beijing Normal University, Beijing, 100101, China
School of Earth Sciences and Resources, China University of
Geosciences, Beijing, 100083, China
Zijin Yuan
Hulunbeir Grassland Ecosystem Research station, Institute of
Agricultural Resources and Regional Planning, Chinese Academy of
Agricultural Sciences, Beijing, 100081, China
Related authors
Shu Fang, Kebiao Mao, Xueqi Xia, Ping Wang, Jiancheng Shi, Sayed M. Bateni, Tongren Xu, Mengmeng Cao, Essam Heggy, and Zhihao Qin
Earth Syst. Sci. Data, 14, 1413–1432, https://doi.org/10.5194/essd-14-1413-2022, https://doi.org/10.5194/essd-14-1413-2022, 2022
Short summary
Short summary
Air temperature is an important parameter reflecting climate change, and the current method of obtaining daily temperature is affected by many factors. In this study, we constructed a temperature model based on weather conditions and established a correction equation. The dataset of daily air temperature (Tmax, Tmin, and Tavg) in China from 1979 to 2018 was obtained with a spatial resolution of 0.1°. Accuracy verification shows that the dataset has reliable accuracy and high spatial resolution.
Shaomin Liu, Ziwei Xu, Tao Che, Xin Li, Tongren Xu, Zhiguo Ren, Yang Zhang, Junlei Tan, Lisheng Song, Ji Zhou, Zhongli Zhu, Xiaofan Yang, Rui Liu, and Yanfei Ma
Earth Syst. Sci. Data, 15, 4959–4981, https://doi.org/10.5194/essd-15-4959-2023, https://doi.org/10.5194/essd-15-4959-2023, 2023
Short summary
Short summary
We present a suite of observational datasets from artificial and natural oases–desert systems that consist of long-term turbulent flux and auxiliary data, including hydrometeorological, vegetation, and soil parameters, from 2012 to 2021. We confirm that the 10-year, long-term dataset presented in this study is of high quality with few missing data, and we believe that the data will support ecological security and sustainable development in oasis–desert areas.
Xinlei He, Yanping Li, Shaomin Liu, Tongren Xu, Fei Chen, Zhenhua Li, Zhe Zhang, Rui Liu, Lisheng Song, Ziwei Xu, Zhixing Peng, and Chen Zheng
Hydrol. Earth Syst. Sci., 27, 1583–1606, https://doi.org/10.5194/hess-27-1583-2023, https://doi.org/10.5194/hess-27-1583-2023, 2023
Short summary
Short summary
This study highlights the role of integrating vegetation and multi-source soil moisture observations in regional climate models via a hybrid data assimilation and machine learning method. In particular, we show that this approach can improve land surface fluxes, near-surface atmospheric conditions, and land–atmosphere interactions by implementing detailed land characterization information in basins with complex underlying surfaces.
Ping Wang, Kebiao Mao, Fei Meng, Zhihao Qin, Shu Fang, and Sayed M. Bateni
Geosci. Model Dev., 15, 6059–6083, https://doi.org/10.5194/gmd-15-6059-2022, https://doi.org/10.5194/gmd-15-6059-2022, 2022
Short summary
Short summary
In order to obtain the key parameters of high-temperature spatial–temporal variation analysis, this study proposed a daily highest air temperature (Tmax) estimation frame to build a Tmax dataset in China from 1979 to 2018. We found that the annual and seasonal mean Tmax in most areas of China showed an increasing trend. The abnormal temperature changes mainly occurred in El Nin~o years or La Nin~a years. IOBW had a stronger influence on China's warming events than other factors.
Peilin Song, Yongqiang Zhang, Jianping Guo, Jiancheng Shi, Tianjie Zhao, and Bing Tong
Earth Syst. Sci. Data, 14, 2613–2637, https://doi.org/10.5194/essd-14-2613-2022, https://doi.org/10.5194/essd-14-2613-2022, 2022
Short summary
Short summary
Soil moisture information is crucial for understanding the earth surface, but currently available satellite-based soil moisture datasets are imperfect either in their spatiotemporal resolutions or in ensuring image completeness from cloudy weather. In this study, therefore, we developed one soil moisture data product over China that has tackled most of the above problems. This data product has the potential to promote the investigation of earth hydrology and be extended to the global scale.
Ming Li, Husi Letu, Yiran Peng, Hiroshi Ishimoto, Yanluan Lin, Takashi Y. Nakajima, Anthony J. Baran, Zengyuan Guo, Yonghui Lei, and Jiancheng Shi
Atmos. Chem. Phys., 22, 4809–4825, https://doi.org/10.5194/acp-22-4809-2022, https://doi.org/10.5194/acp-22-4809-2022, 2022
Short summary
Short summary
To build on the previous investigations of the Voronoi model in the remote sensing retrievals of ice cloud products, this paper developed an ice cloud parameterization scheme based on the single-scattering properties of the Voronoi model and evaluate it through simulations with the Community Integrated Earth System Model (CIESM). Compared with four representative ice cloud schemes, results show that the Voronoi model has good capabilities of ice cloud modeling in the climate model.
Shu Fang, Kebiao Mao, Xueqi Xia, Ping Wang, Jiancheng Shi, Sayed M. Bateni, Tongren Xu, Mengmeng Cao, Essam Heggy, and Zhihao Qin
Earth Syst. Sci. Data, 14, 1413–1432, https://doi.org/10.5194/essd-14-1413-2022, https://doi.org/10.5194/essd-14-1413-2022, 2022
Short summary
Short summary
Air temperature is an important parameter reflecting climate change, and the current method of obtaining daily temperature is affected by many factors. In this study, we constructed a temperature model based on weather conditions and established a correction equation. The dataset of daily air temperature (Tmax, Tmin, and Tavg) in China from 1979 to 2018 was obtained with a spatial resolution of 0.1°. Accuracy verification shows that the dataset has reliable accuracy and high spatial resolution.
Xiangjin Meng, Kebiao Mao, Fei Meng, Jiancheng Shi, Jiangyuan Zeng, Xinyi Shen, Yaokui Cui, Lingmei Jiang, and Zhonghua Guo
Earth Syst. Sci. Data, 13, 3239–3261, https://doi.org/10.5194/essd-13-3239-2021, https://doi.org/10.5194/essd-13-3239-2021, 2021
Short summary
Short summary
In order to improve the accuracy of China's regional agricultural drought monitoring and climate change research, we produced a long-term series of soil moisture products by constructing a time and depth correction model for three soil moisture products with the help of ground observation data. The spatial resolution is improved by building a spatial weight decomposition model, and validation indicates that the new product can meet application needs.
Bing Zhao, Kebiao Mao, Yulin Cai, Jiancheng Shi, Zhaoliang Li, Zhihao Qin, Xiangjin Meng, Xinyi Shen, and Zhonghua Guo
Earth Syst. Sci. Data, 12, 2555–2577, https://doi.org/10.5194/essd-12-2555-2020, https://doi.org/10.5194/essd-12-2555-2020, 2020
Short summary
Short summary
Land surface temperature is a key variable for climate and ecological environment research. We reconstructed a land surface temperature dataset (2003–2017) to take advantage of the ground observation site through building a reconstruction model which overcomes the effects of cloud. The reconstructed dataset exhibited significant improvements and can be used for the spatiotemporal evaluation of land surface temperature and for high-temperature and drought-monitoring studies.
S. Talebi, J. Shi, and T. Zhao
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1623–1627, https://doi.org/10.5194/isprs-archives-XLII-3-1623-2018, https://doi.org/10.5194/isprs-archives-XLII-3-1623-2018, 2018
S. Talebi, J. Shi, T. Zhao, Y. Li, X. Chuan, and L. Chai
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4-W4, 259–263, https://doi.org/10.5194/isprs-archives-XLII-4-W4-259-2017, https://doi.org/10.5194/isprs-archives-XLII-4-W4-259-2017, 2017
Matthew F. McCabe, Matthew Rodell, Douglas E. Alsdorf, Diego G. Miralles, Remko Uijlenhoet, Wolfgang Wagner, Arko Lucieer, Rasmus Houborg, Niko E. C. Verhoest, Trenton E. Franz, Jiancheng Shi, Huilin Gao, and Eric F. Wood
Hydrol. Earth Syst. Sci., 21, 3879–3914, https://doi.org/10.5194/hess-21-3879-2017, https://doi.org/10.5194/hess-21-3879-2017, 2017
Short summary
Short summary
We examine the opportunities and challenges that technological advances in Earth observation will present to the hydrological community. From advanced space-based sensors to unmanned aerial vehicles and ground-based distributed networks, these emergent systems are set to revolutionize our understanding and interpretation of hydrological and related processes.
T. R. Xu, S. M. Liu, Z. W. Xu, S. Liang, and L. Xu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-3927-2013, https://doi.org/10.5194/hessd-10-3927-2013, 2013
Preprint withdrawn
Related subject area
Physical oceanography
A Mediterranean drifter dataset
The DTU21 global mean sea surface and first evaluation
A dataset for investigating socio-ecological changes in Arctic fjords
Oceanographic dataset collected during the 2021 scientific expedition of the Canadian Coast Guard Ship Amundsen
Dataset of depth and temperature profiles obtained from 2012 to 2020 using commercial fishing vessels of the AdriFOOS fleet in the Adriatic Sea
Measurements and modeling of water levels, currents, density, and wave climate on a semi-enclosed tidal bay, Cádiz (southwest Spain)
Wind wave and water level dataset for Hornsund, Svalbard (2013–2021)
Hyperspectral reflectance of pristine, ocean weathered and biofouled plastics from dry to wet and submerged state
Lagoon hydrodynamics of pearl farming atolls: the case of Raroia, Takapoto, Apataki and Takaroa (French Polynesia)
Deep-water hydrodynamic observations around a cold-water coral habitat in a submarine canyon in the eastern Ligurian Sea (Mediterranean Sea)
Ocean cross-validated observations from R/Vs L'Atalante, Maria S. Merian, and Meteor and related platforms as part of the EUREC4A-OA/ATOMIC campaign
A global Lagrangian eddy dataset based on satellite altimetry
The sea level time series of Trieste, Molo Sartorio, Italy (1869–2021)
Measurements of Nearshore Waves through Coherent Arrays of Free-Drifting Wave Buoys
Southern Europe and western Asian marine heatwaves (SEWA-MHWs): a dataset based on macroevents
An evaluation of long-term physical and hydrochemical measurements at the Sylt Roads Marine Observatory (1973–2019), Wadden Sea, North Sea
Annual hydrographic variability in Antarctic coastal waters infused with glacial inflow
Argo salinity: bias and uncertainty evaluation
Improved global sea surface height and current maps from remote sensing and in situ observations
Extension of high temporal resolution sea level time series at Socoa (Saint Jean-de-Luz, France) back to 1875
Sea surface height anomaly and geostrophic current velocity from altimetry measurements over the Arctic Ocean (2011–2020)
SDUST2020 MSS: a global 1′ × 1′ mean sea surface model determined from multi-satellite altimetry data
Synoptic observations of sediment transport and exchange mechanisms in the turbid Ems Estuary: the EDoM campaign
A compilation of global bio-optical in situ data for ocean colour satellite applications – version three
Deep-water hydrodynamic observations of two moorings sites on the continental slope of the southern Adriatic Sea (Mediterranean Sea)
Hydrodynamic and hydrological processes within a variety of coral reef lagoons: field observations during six cyclonic seasons in New Caledonia
Reconstructing ocean subsurface salinity at high resolution using a machine learning approach
The HYPERMAQ dataset: bio-optical properties of moderately to extremely turbid waters
Mesoscale observations of temperature and salinity in the Arctic Transpolar Drift: a high-resolution dataset from the MOSAiC Distributed Network
SDUST2021GRA: global marine gravity anomaly model recovered from Ka-band and Ku-band satellite altimeter data
Reanalyses of Maskelyne's tidal data at St. Helena in 1761
Twenty-one years of hydrological data acquisition in the Mediterranean Sea: quality, availability, and research
A new operational Mediterranean diurnal optimally interpolated sea surface temperature product within the Copernicus Marine Service
Wind waves in the North Atlantic from ship navigational radar: SeaVision development and its validation with the Spotter wave buoy and WaveWatch III
Wave attenuation potential, sediment properties and mangrove growth dynamics data over Guyana's intertidal mudflats: assessing the potential of mangrove restoration works
High-resolution bathymetry models for the Lena Delta and Kolyma Gulf coastal zones
Towards improved analysis of short mesoscale sea level signals from satellite altimetry
META3.1exp: a new global mesoscale eddy trajectory atlas derived from altimetry
Global sea-level budget and ocean-mass budget, with a focus on advanced data products and uncertainty characterisation
Improved BEC SMOS Arctic Sea Surface Salinity product v3.1
Monitoring the ocean heat content change and the Earth energy imbalance from space altimetry and space gravimetry
Water masses distribution offshore the Sabrina Coast (East Antarctica)
Next generation of Bluelink ocean reanalysis with multiscale data assimilation: BRAN2020
Arctic sea surface height maps from multi-altimeter combination
Laboratory data on wave propagation through vegetation with following and opposing currents
Minute Sea-Level Analysis (MISELA): a high-frequency sea-level analysis global dataset
EOT20: a global ocean tide model from multi-mission satellite altimetry
North SEAL: a new dataset of sea level changes in the North Sea from satellite altimetry
An integrated marine data collection for the German Bight – Part 2: Tides, salinity, and waves (1996–2015)
A climate index for the Newfoundland and Labrador shelf
Alberto Ribotti, Antonio Bussani, Milena Menna, Andrea Satta, Roberto Sorgente, Andrea Cucco, and Riccardo Gerin
Earth Syst. Sci. Data, 15, 4651–4659, https://doi.org/10.5194/essd-15-4651-2023, https://doi.org/10.5194/essd-15-4651-2023, 2023
Short summary
Short summary
Over 100 experiments were realized between 1998 and 2022 in the Mediterranean Sea using surface coastal and offshore Lagrangian drifters. Raw data were initially unified and pre-processed. Then, the integrity of the received data packages was checked and incomplete ones were discarded. Deployment information was retrieved and integrated into the PostgreSQL database. Data were interpolated at defined time intervals, providing a dataset of 158 trajectories, available in different formats.
Ole Baltazar Andersen, Stine Kildegaard Rose, Adili Abulaitijiang, Shengjun Zhang, and Sara Fleury
Earth Syst. Sci. Data, 15, 4065–4075, https://doi.org/10.5194/essd-15-4065-2023, https://doi.org/10.5194/essd-15-4065-2023, 2023
Short summary
Short summary
The mean sea surface (MSS) is an important reference for mapping sea-level changes across the global oceans. It is widely used by space agencies in the definition of sea-level anomalies as mapped by satellite altimetry from space. Here a new fully global high-resolution mean sea surface called DTU21MSS is presented, and a suite of evaluations are performed to demonstrate its performance.
Robert W. Schlegel and Jean-Pierre Gattuso
Earth Syst. Sci. Data, 15, 3733–3746, https://doi.org/10.5194/essd-15-3733-2023, https://doi.org/10.5194/essd-15-3733-2023, 2023
Short summary
Short summary
A single dataset was created for investigations of changes in the socio-ecological systems within seven Arctic fjords by amalgamating roughly 1400 datasets from a number of sources. The many variables in these data were organised into five distinct categories and classified into 14 key drivers. Data for seawater temperature and salinity are available from the late 19th century, with some other drivers having data available from the 1950s and 1960s and the others starting from the 1990s onward.
Tahiana Ratsimbazafy, Thibaud Dezutter, Amélie Desmarais, Daniel Amirault, Pascal Guillot, and Simon Morisset
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-204, https://doi.org/10.5194/essd-2023-204, 2023
Revised manuscript accepted for ESSD
Short summary
Short summary
The Canadian Coast Guard Ship collects oceanographic data across the Canadian Arctic annually since the year 2003. Such activity aims to support Canadian and international researchers. The ship has several instruments with cutting-edge technology available for research each year during the summer. The data presented here includes measurements of physical, chemical, and biological variables during the year 2021. All datasets outputted from each expedition are free for access for the public.
Pierluigi Penna, Filippo Domenichetti, Andrea Belardinelli, and Michela Martinelli
Earth Syst. Sci. Data, 15, 3513–3527, https://doi.org/10.5194/essd-15-3513-2023, https://doi.org/10.5194/essd-15-3513-2023, 2023
Short summary
Short summary
This work presents the pressure (depth) and temperature profile dataset provided by the AdriFOOS infrastructure in the Adriatic Sea (Mediterranean basin) from 2012 to 2020. Data were subject to quality assurance (QA) and quality control (QC). This infrastructure, based on the ships of opportunity principle and involving the use of commercial fishing vessels, is able to produce huge amounts of useful data both for operational oceanography and fishery biology purposes.
Carmen Zarzuelo, Alejandro López-Ruiz, María Bermúdez, and Miguel Ortega-Sánchez
Earth Syst. Sci. Data, 15, 3095–3110, https://doi.org/10.5194/essd-15-3095-2023, https://doi.org/10.5194/essd-15-3095-2023, 2023
Short summary
Short summary
This paper presents a hydrodynamic dataset for the Bay of Cádiz in southern Spain, a paradigmatic example of a tidal bay of complex geometry under high anthropogenic pressure. The dataset brings together measured and modeled data on water levels, currents, density, and waves for the period 2012–2015. It allows the characterization of the bay dynamics from intratidal to seasonal scales. Potential applications include the study of ocean–bay interactions, wave propagation, or energy assessments.
Zuzanna M. Swirad, Mateusz Moskalik, and Agnieszka Herman
Earth Syst. Sci. Data, 15, 2623–2633, https://doi.org/10.5194/essd-15-2623-2023, https://doi.org/10.5194/essd-15-2623-2023, 2023
Short summary
Short summary
Monitoring ocean waves is important for understanding wave climate and seasonal to longer-term (years to decades) changes. In the Arctic, there is limited freely available observational wave information. We placed sensors at the sea bottom of six bays in Hornsund fjord, Svalbard, and calculated wave energy, wave height and wave period for full hours between July 2013 and February 2021. In this paper, we present the procedure of deriving wave properties from raw pressure measurements.
Robin V. F. de Vries, Shungudzemwoyo P. Garaba, and Sarah-Jeanne Royer
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-209, https://doi.org/10.5194/essd-2023-209, 2023
Revised manuscript accepted for ESSD
Short summary
Short summary
This paper presents a unique dataset of hyperspectral measurements of various plastics, including aged plastics harvested from the open ocean (North Pacific Ocean) and COVID-19 related plastic items. These datasets are vital as input for the development of remote sensing technology to better map and locate plastic litter pollution in the natural environment. In this study, there is specific emphasis on the spectral characteristics of submerged plastics.
Oriane Bruyère, Romain Le Gendre, Mathilde Chauveau, Bertrand Bourgeois, David Varillon, John Butscher, Thomas Trophime, Yann Follin, Jerome Aucan, Vetea Liao, and Serge Andréfouët
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-198, https://doi.org/10.5194/essd-2023-198, 2023
Revised manuscript accepted for ESSD
Short summary
Short summary
In 2018–2022, 4 pearl farming Tuamotu atolls (French Polynesia) were studied with oceanographic instruments to measure lagoon hydrodynamics and ocean-lagoon water exchanges. The goal was to gain knowledge on the processes influencing the spat collection of the pearl oyster Pinctada margaritifera, the species used to produce black pearls. A worldwide unique oceanographic atoll data set is provided to address local pearl farming questions and other fundamental and applied investigations as well.
Tiziana Ciuffardi, Zoi Kokkini, Maristella Berta, Marina Locritani, Andrea Bordone, Ivana Delbono, Mireno Borghini, Maurizio Demarte, Roberta Ivaldi, Federica Pannacciulli, Anna Vetrano, Davide Marini, and Giovanni Caprino
Earth Syst. Sci. Data, 15, 1933–1946, https://doi.org/10.5194/essd-15-1933-2023, https://doi.org/10.5194/essd-15-1933-2023, 2023
Short summary
Short summary
This paper presents the results of the first 2 years of the Levante Canyon Mooring, a mooring line placed since 2020 in the eastern Ligurian Sea, to study a canyon area at about 600 m depth characterized by the presence of cold-water living corals. It provides hydrodynamic and thermohaline measurements along the water column, describing a water-mass distribution coherent with previous evidence in the Ligurian Sea. The data also show a Northern Current episodic and local reversal during summer.
Pierre L'Hégaret, Florian Schütte, Sabrina Speich, Gilles Reverdin, Dariusz B. Baranowski, Rena Czeschel, Tim Fischer, Gregory R. Foltz, Karen J. Heywood, Gerd Krahmann, Rémi Laxenaire, Caroline Le Bihan, Philippe Le Bot, Stéphane Leizour, Callum Rollo, Michael Schlundt, Elizabeth Siddle, Corentin Subirade, Dongxiao Zhang, and Johannes Karstensen
Earth Syst. Sci. Data, 15, 1801–1830, https://doi.org/10.5194/essd-15-1801-2023, https://doi.org/10.5194/essd-15-1801-2023, 2023
Short summary
Short summary
In early 2020, the EUREC4A-OA/ATOMIC experiment took place in the northwestern Tropical Atlantic Ocean, a dynamical region where different water masses interact. Four oceanographic vessels and a fleet of autonomous devices were deployed to study the processes at play and sample the upper ocean, each with its own observing capability. The article first describes the data calibration and validation and second their cross-validation, using a hierarchy of instruments and estimating the uncertainty.
Tongya Liu and Ryan Abernathey
Earth Syst. Sci. Data, 15, 1765–1778, https://doi.org/10.5194/essd-15-1765-2023, https://doi.org/10.5194/essd-15-1765-2023, 2023
Short summary
Short summary
Nearly all existing datasets of mesoscale eddies are based on the Eulerian method because of its operational simplicity. Using satellite observations and a Lagrangian method, we present a global Lagrangian eddy dataset (GLED v1.0). We conduct the statistical comparison between two types of eddies and the dataset validation. Our dataset offers relief from dilemma that the Eulerian eddy dataset is nearly the only option for studying mesoscale eddies.
Fabio Raicich
Earth Syst. Sci. Data, 15, 1749–1763, https://doi.org/10.5194/essd-15-1749-2023, https://doi.org/10.5194/essd-15-1749-2023, 2023
Short summary
Short summary
In the changing climate, long sea level time series are essential for studying the variability of the mean sea level and the occurrence of extreme events on different timescales. This work summarizes the rescue and quality control of the ultra-centennial sea level data set of Trieste, Italy. The whole time series is characterized by a linear trend of about 1.4 mm yr−1, the period corresponding to the altimetry coverage by a trend of about 3.0 mm yr−1, similarly to the global ocean.
Edwin John Rainville, Jim Thomson, Melissa Moulton, and Morteza Derakhti
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-64, https://doi.org/10.5194/essd-2023-64, 2023
Revised manuscript accepted for ESSD
Short summary
Short summary
Measuring ocean waves nearshore is essential for understanding how the waves impact our coastlines. We designed and deployed many small wave buoys into the nearshore ocean over 27 days in Duck, North Carolina, USA, in 2021. The wave buoys measure their motion as they drift. In this paper, we describe how we use the measurements from the buoys to measure nearshore wave properties. We find that the buoy measurements are accurate and reliable compared to other nearby instruments.
Giulia Bonino, Simona Masina, Giuliano Galimberti, and Matteo Moretti
Earth Syst. Sci. Data, 15, 1269–1285, https://doi.org/10.5194/essd-15-1269-2023, https://doi.org/10.5194/essd-15-1269-2023, 2023
Short summary
Short summary
We present a unique observational dataset of marine heat wave (MHW) macroevents and their characteristics over southern Europe and western Asian (SEWA) basins in the SEWA-MHW dataset. This dataset is the first effort in the literature to archive extremely hot sea surface temperature macroevents. The advantages of the availability of SEWA-MHWs are avoiding the waste of computational resources to detect MHWs and building a consistent framework which would increase comparability among MHW studies.
Johannes J. Rick, Mirco Scharfe, Tatyana Romanova, Justus E. E. van Beusekom, Ragnhild Asmus, Harald Asmus, Finn Mielck, Anja Kamp, Rainer Sieger, and Karen H. Wiltshire
Earth Syst. Sci. Data, 15, 1037–1057, https://doi.org/10.5194/essd-15-1037-2023, https://doi.org/10.5194/essd-15-1037-2023, 2023
Short summary
Short summary
The Sylt Roads (Wadden Sea) time series is illustrated. Since 1984, the water temperature has risen by 1.1 °C, while pH and salinity decreased by 0.2 and 0.3 units. Nutrients (P, N) displayed a period of high eutrophication until 1998 and have decreased since 1999, while Si showed a parallel increase. Chlorophyll did not mirror these changes, probably due to a switch in nutrient limitation. Until 1998, algae were primarily limited by Si, and since 1999, P limitation has become more important.
Maria Osińska, Kornelia A. Wójcik-Długoborska, and Robert J. Bialik
Earth Syst. Sci. Data, 15, 607–616, https://doi.org/10.5194/essd-15-607-2023, https://doi.org/10.5194/essd-15-607-2023, 2023
Short summary
Short summary
Water properties, including temperature, conductivity, turbidity and pH as well as the dissolved oxygen, dissolved organic matter, chlorophyll-a and phycoerythrin contents, were investigated in 31 different locations at up to 100 m depth over a period of 38 months in a glacial bay in Antarctica. These investigations were carried out 142 times in all seasons of the year, resulting in a unique dataset of information about seasonal and long-term changes in polar water properties.
Annie P. S. Wong, John Gilson, and Cécile Cabanes
Earth Syst. Sci. Data, 15, 383–393, https://doi.org/10.5194/essd-15-383-2023, https://doi.org/10.5194/essd-15-383-2023, 2023
Short summary
Short summary
This article describes the instrument bias in the raw Argo salinity data from 2000 to 2021. The main cause of this bias is sensor drift. Using Argo data without filtering out this instrument bias has been shown to lead to spurious results in various scientific applications. We describe the Argo delayed-mode process that evaluates and adjusts such instrument bias, and we estimate the uncertainty of the Argo delayed-mode salinity dataset. The best ways to use Argo data are illustrated.
Maxime Ballarotta, Clément Ubelmann, Pierre Veillard, Pierre Prandi, Hélène Etienne, Sandrine Mulet, Yannice Faugère, Gérald Dibarboure, Rosemary Morrow, and Nicolas Picot
Earth Syst. Sci. Data, 15, 295–315, https://doi.org/10.5194/essd-15-295-2023, https://doi.org/10.5194/essd-15-295-2023, 2023
Short summary
Short summary
We present a new gridded sea surface height and current dataset produced by combining observations from nadir altimeters and drifting buoys. This product is based on a multiscale and multivariate mapping approach that offers the possibility to improve the physical content of gridded products by combining the data from various platforms and resolving a broader spectrum of ocean surface dynamic than in the current operational mapping system. A quality assessment of this new product is presented.
Md Jamal Uddin Khan, Inge Van Den Beld, Guy Wöppelmann, Laurent Testut, Alexa Latapy, and Nicolas Pouvreau
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-443, https://doi.org/10.5194/essd-2022-443, 2023
Revised manuscript accepted for ESSD
Short summary
Short summary
Established in 1875, Socoa tide gauge is one of the long-running permanent tide-gauge of the South-Western France region. However, a large part of its record was in paper format in various archives facing risk of damage. Through data archaeology, these data and associated metadata documents are rescued, digitized, and constructed into a uniform hourly sea level time series from 1875 to date. This new dataset will be useful for climate research on sea level rise, tide, and storm surges.
Francesca Doglioni, Robert Ricker, Benjamin Rabe, Alexander Barth, Charles Troupin, and Torsten Kanzow
Earth Syst. Sci. Data, 15, 225–263, https://doi.org/10.5194/essd-15-225-2023, https://doi.org/10.5194/essd-15-225-2023, 2023
Short summary
Short summary
This paper presents a new satellite-derived gridded dataset, including 10 years of sea surface height and geostrophic velocity at monthly resolution, over the Arctic ice-covered and ice-free regions, up to 88° N. We assess the dataset by comparison to independent satellite and mooring data. Results correlate well with independent satellite data at monthly timescales, and the geostrophic velocity fields can resolve seasonal to interannual variability of boundary currents wider than about 50 km.
Jiajia Yuan, Jinyun Guo, Chengcheng Zhu, Zhen Li, Xin Liu, and Jinyao Gao
Earth Syst. Sci. Data, 15, 155–169, https://doi.org/10.5194/essd-15-155-2023, https://doi.org/10.5194/essd-15-155-2023, 2023
Short summary
Short summary
The mean sea surface (MSS) is a relative steady-state sea level within a finite period with important applications in geodesy, oceanography, and other disciplines. In this study, the Shandong University of Science and Technology 2020 (SDUST2020), a new global MSS model, was established with a 19-year moving average method from multi-satellite altimetry data. Its global coverage is from 80 °S to 84 °N, the grid size is 1'×1', and the reference period is from January 1993 to December 2019.
Dirk S. van Maren, Christian Maushake, Jan-Willem Mol, Daan van Keulen, Jens Jürges, Julia Vroom, Henk Schuttelaars, Theo Gerkema, Kirstin Schulz, Thomas H. Badewien, Michaela Gerriets, Andreas Engels, Andreas Wurpts, Dennis Oberrecht, Andrew J. Manning, Taylor Bailey, Lauren Ross, Volker Mohrholz, Dante M. L. Horemans, Marius Becker, Dirk Post, Charlotte Schmidt, and Petra J. T. Dankers
Earth Syst. Sci. Data, 15, 53–73, https://doi.org/10.5194/essd-15-53-2023, https://doi.org/10.5194/essd-15-53-2023, 2023
Short summary
Short summary
This paper reports on the main findings of a large measurement campaign aiming to better understand how an exposed estuary (the Ems Estuary on the Dutch–German border) interacts with a tidal river (the lower Ems River). Eight simultaneously deployed ships measuring a tidal cycle and 10 moorings collecting data throughout a spring–neap tidal cycle have produced a dataset providing valuable insight into processes determining exchange of water and sediment between the two systems.
André Valente, Shubha Sathyendranath, Vanda Brotas, Steve Groom, Michael Grant, Thomas Jackson, Andrei Chuprin, Malcolm Taberner, Ruth Airs, David Antoine, Robert Arnone, William M. Balch, Kathryn Barker, Ray Barlow, Simon Bélanger, Jean-François Berthon, Şükrü Beşiktepe, Yngve Borsheim, Astrid Bracher, Vittorio Brando, Robert J. W. Brewin, Elisabetta Canuti, Francisco P. Chavez, Andrés Cianca, Hervé Claustre, Lesley Clementson, Richard Crout, Afonso Ferreira, Scott Freeman, Robert Frouin, Carlos García-Soto, Stuart W. Gibb, Ralf Goericke, Richard Gould, Nathalie Guillocheau, Stanford B. Hooker, Chuamin Hu, Mati Kahru, Milton Kampel, Holger Klein, Susanne Kratzer, Raphael Kudela, Jesus Ledesma, Steven Lohrenz, Hubert Loisel, Antonio Mannino, Victor Martinez-Vicente, Patricia Matrai, David McKee, Brian G. Mitchell, Tiffany Moisan, Enrique Montes, Frank Muller-Karger, Aimee Neeley, Michael Novak, Leonie O'Dowd, Michael Ondrusek, Trevor Platt, Alex J. Poulton, Michel Repecaud, Rüdiger Röttgers, Thomas Schroeder, Timothy Smyth, Denise Smythe-Wright, Heidi M. Sosik, Crystal Thomas, Rob Thomas, Gavin Tilstone, Andreia Tracana, Michael Twardowski, Vincenzo Vellucci, Kenneth Voss, Jeremy Werdell, Marcel Wernand, Bozena Wojtasiewicz, Simon Wright, and Giuseppe Zibordi
Earth Syst. Sci. Data, 14, 5737–5770, https://doi.org/10.5194/essd-14-5737-2022, https://doi.org/10.5194/essd-14-5737-2022, 2022
Short summary
Short summary
A compiled set of in situ data is vital to evaluate the quality of ocean-colour satellite data records. Here we describe the global compilation of bio-optical in situ data (spanning from 1997 to 2021) used for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The compilation merges and harmonizes several in situ data sources into a simple format that could be used directly for the evaluation of satellite-derived ocean-colour data.
Francesco Paladini de Mendoza, Katrin Schroeder, Leonardo Langone, Jacopo Chiggiato, Mireno Borghini, Patrizia Giordano, Giulio Verazzo, and Stefano Miserocchi
Earth Syst. Sci. Data, 14, 5617–5635, https://doi.org/10.5194/essd-14-5617-2022, https://doi.org/10.5194/essd-14-5617-2022, 2022
Short summary
Short summary
This work presents the dataset of continuous monitoring in the southern Adriatic Margin, providing a unique observatory of deep-water dynamics. The study area is influenced by episodic dense-water cascading, which is a fundamental process for water renewal and deep-water dynamics. Information about the frequency and intensity variations of these events is observed along a time series. The monitoring activities are still ongoing and the moorings are part of the EMSO-ERIC network.
Oriane Bruyère, Benoit Soulard, Hugues Lemonnier, Thierry Laugier, Morgane Hubert, Sébastien Petton, Térence Desclaux, Simon Van Wynsberge, Eric Le Tesson, Jérôme Lefèvre, Franck Dumas, Jean-François Kayara, Emmanuel Bourassin, Noémie Lalau, Florence Antypas, and Romain Le Gendre
Earth Syst. Sci. Data, 14, 5439–5462, https://doi.org/10.5194/essd-14-5439-2022, https://doi.org/10.5194/essd-14-5439-2022, 2022
Short summary
Short summary
From 2014 to 2021, extensive monitoring of hydrodynamics was deployed within five contrasted lagoons of New Caledonia during austral summers. These coastal physical observations encompassed unmonitored lagoons and captured eight major atmospheric events ranging from tropical depression to category 4 cyclone. The main objectives were to characterize the processes controlling hydrodynamics of these lagoons and record the signature of extreme events on land–lagoon–ocean continuum functioning.
Tian Tian, Lijing Cheng, Gongjie Wang, John Abraham, Wangxu Wei, Shihe Ren, Jiang Zhu, Junqiang Song, and Hongze Leng
Earth Syst. Sci. Data, 14, 5037–5060, https://doi.org/10.5194/essd-14-5037-2022, https://doi.org/10.5194/essd-14-5037-2022, 2022
Short summary
Short summary
A high-resolution gridded dataset is crucial for understanding ocean processes at various spatiotemporal scales. Here we used a machine learning approach and successfully reconstructed a high-resolution (0.25° × 0.25°) ocean subsurface (1–2000 m) salinity dataset for the period 1993–2018 (monthly) by merging in situ salinity profile observations with high-resolution satellite remote-sensing data. This new product could be useful in various applications in ocean and climate fields.
Héloïse Lavigne, Ana Dogliotti, David Doxaran, Fang Shen, Alexandre Castagna, Matthew Beck, Quinten Vanhellemont, Xuerong Sun, Juan Ignacio Gossn, Pannimpullath Remanan Renosh, Koen Sabbe, Dieter Vansteenwegen, and Kevin Ruddick
Earth Syst. Sci. Data, 14, 4935–4947, https://doi.org/10.5194/essd-14-4935-2022, https://doi.org/10.5194/essd-14-4935-2022, 2022
Short summary
Short summary
Because of the large diversity of case 2 waters and the complexity of light transfer, retrieving main biogeochemical parameters in these waters is still challenging. By providing optical and biogeochemical parameters for 180 sampling stations with turbidity and chlorophyll-a concentration ranging from low to extreme values, the HYPERMAQ dataset will contribute to a better description of marine optics in optically complex water bodies and can help the scientific community to develop algorithms.
Mario Hoppmann, Ivan Kuznetsov, Ying-Chih Fang, and Benjamin Rabe
Earth Syst. Sci. Data, 14, 4901–4921, https://doi.org/10.5194/essd-14-4901-2022, https://doi.org/10.5194/essd-14-4901-2022, 2022
Short summary
Short summary
The role of eddies and fronts in the oceans is a hot topic in climate research, but there are still many related knowledge gaps, particularly in the ice-covered Arctic Ocean. Here we present a unique dataset of ocean observations collected by a set of drifting buoys installed on ice floes as part of the 2019/2020 MOSAiC campaign. The buoys recorded temperature and salinity data for 10 months, providing extraordinary insights into the properties and processes of the ocean along their drift.
Chengcheng Zhu, Jinyun Guo, Jiajia Yuan, Zhen Li, Xin Liu, and Jinyao Gao
Earth Syst. Sci. Data, 14, 4589–4606, https://doi.org/10.5194/essd-14-4589-2022, https://doi.org/10.5194/essd-14-4589-2022, 2022
Short summary
Short summary
Accurate marine gravity anomalies play an important role in the fields of submarine topography, Earth structure, and submarine exploitation. With the launch of different altimetry satellites, the density of altimeter data can meet the requirements of inversion of high-resolution and high-precision gravity anomaly models. We construct the global marine gravity anomaly model (SDUST2021GRA) from altimeter data (including HY-2A). The accuracy of the model is high, especially in the offshore area.
Philip L. Woodworth and John M. Vassie
Earth Syst. Sci. Data, 14, 4387–4396, https://doi.org/10.5194/essd-14-4387-2022, https://doi.org/10.5194/essd-14-4387-2022, 2022
Short summary
Short summary
An electronic data set of tidal measurements at St. Helena in 1761 by Nevil Maskelyne is described. These data were first analysed by Cartwright in papers on changing tides, but his data files were never archived. The now newly digitised Maskelyne data have been reanalysed in order to obtain an updated impression of whether the tide has changed at that location in over two and a half centuries. Our main conclusion is that the major tidal constituent (M2) has changed little.
Alberto Ribotti, Roberto Sorgente, Federica Pessini, Andrea Cucco, Giovanni Quattrocchi, and Mireno Borghini
Earth Syst. Sci. Data, 14, 4187–4199, https://doi.org/10.5194/essd-14-4187-2022, https://doi.org/10.5194/essd-14-4187-2022, 2022
Short summary
Short summary
Over 1468 hydrological vertical profiles were acquired in 21 years in the Mediterranean Sea. This allowed us to follow the diffusion of the Western Mediterranean Transient along all western seas or make some important repetitions across straits, channels, or at defined locations. These data are now available in four open-access online datasets, including profiles of water temperature, conductivity, dissolved oxygen, chlorophyll α fluorescence, and, after 2004, turbidity and pH.
Andrea Pisano, Daniele Ciani, Salvatore Marullo, Rosalia Santoleri, and Bruno Buongiorno Nardelli
Earth Syst. Sci. Data, 14, 4111–4128, https://doi.org/10.5194/essd-14-4111-2022, https://doi.org/10.5194/essd-14-4111-2022, 2022
Short summary
Short summary
A new operational diurnal sea surface temperature (SST) product has been developed within the Copernicus Marine Service, providing gap-free hourly mean SST fields from January 2019 to the present. This product is able to accurately reproduce the diurnal cycle, the typical day–night SST oscillation mainly driven by solar heating, including extreme diurnal warming events. This product can thus represent a valuable dataset to improve the study of those processes that require a subdaily frequency.
Natalia Tilinina, Dmitry Ivonin, Alexander Gavrikov, Vitali Sharmar, Sergey Gulev, Alexander Suslov, Vladimir Fadeev, Boris Trofimov, Sergey Bargman, Leysan Salavatova, Vasilisa Koshkina, Polina Shishkova, Elizaveta Ezhova, Mikhail Krinitsky, Olga Razorenova, Klaus Peter Koltermann, Vladimir Tereschenkov, and Alexey Sokov
Earth Syst. Sci. Data, 14, 3615–3633, https://doi.org/10.5194/essd-14-3615-2022, https://doi.org/10.5194/essd-14-3615-2022, 2022
Short summary
Short summary
We present wind wave parameter data from research cruises in the North Atlantic in 2020 and 2021 and the SeaVision system for measuring wind wave characteristics with a standard marine navigation X-band radar. We promote the potential of ship navigation X-band radars (when assembled with SeaVision or similar systems) for the development of a new near-global observational network, providing a much larger number of wind wave observations.
Üwe S. N. Best, Mick van der Wegen, Jasper Dijkstra, Johan Reyns, Bram C. van Prooijen, and Dano Roelvink
Earth Syst. Sci. Data, 14, 2445–2462, https://doi.org/10.5194/essd-14-2445-2022, https://doi.org/10.5194/essd-14-2445-2022, 2022
Short summary
Short summary
The combination of seawalls and vegetation may be the key to Guyana's survival against rising water levels; however knowledge about the system behaviour and use of vegetation is inadequate. This paper comprises the first dataset since the 1970s along the Guyana coastline. Instruments were deployed to capture data on the water levels, waves and sediment locally. Data revealed the ways in which sediment is transported and deposited, as well as the wave damping of the mangrove–mudflat system.
Matthias Fuchs, Juri Palmtag, Bennet Juhls, Pier Paul Overduin, Guido Grosse, Ahmed Abdelwahab, Michael Bedington, Tina Sanders, Olga Ogneva, Irina V. Fedorova, Nikita S. Zimov, Paul J. Mann, and Jens Strauss
Earth Syst. Sci. Data, 14, 2279–2301, https://doi.org/10.5194/essd-14-2279-2022, https://doi.org/10.5194/essd-14-2279-2022, 2022
Short summary
Short summary
We created digital, high-resolution bathymetry data sets for the Lena Delta and Kolyma Gulf regions in northeastern Siberia. Based on nautical charts, we digitized depth points and isobath lines, which serve as an input for a 50 m bathymetry model. The benefit of this data set is the accurate mapping of near-shore areas as well as the offshore continuation of the main deep river channels. This will improve the estimation of river outflow and the nutrient flux output into the coastal zone.
Yves Quilfen, Jean-François Piolle, and Bertrand Chapron
Earth Syst. Sci. Data, 14, 1493–1512, https://doi.org/10.5194/essd-14-1493-2022, https://doi.org/10.5194/essd-14-1493-2022, 2022
Short summary
Short summary
Satellite sea surface heights (SSHs) are key observations used to monitor ocean dynamics. For each satellite altimeter mission, differing noise mixes with SSH signals preclude analysis of the smallest ocean scales. Using an adaptive filter, a new data set is produced for three altimeters, showing that SSH variability in the mesoscale 30–120 km wavelength band can now be more consistently resolved. For the first time, global small-scale ocean kinetic energy distributions are precisely monitored.
Cori Pegliasco, Antoine Delepoulle, Evan Mason, Rosemary Morrow, Yannice Faugère, and Gérald Dibarboure
Earth Syst. Sci. Data, 14, 1087–1107, https://doi.org/10.5194/essd-14-1087-2022, https://doi.org/10.5194/essd-14-1087-2022, 2022
Short summary
Short summary
The new global Mesoscale Eddy Trajectory Atlases (META3.1exp) provide eddy identification and trajectories from altimetry maps. These atlases comprise an improvement to and continuation of the historical META2.0 product. Changes in the detection parameters and tracking were tested by comparing the eddies from the different datasets. In particular, the eddy contours available in META3.1exp are an asset for multi-disciplinary studies.
Martin Horwath, Benjamin D. Gutknecht, Anny Cazenave, Hindumathi Kulaiappan Palanisamy, Florence Marti, Ben Marzeion, Frank Paul, Raymond Le Bris, Anna E. Hogg, Inès Otosaka, Andrew Shepherd, Petra Döll, Denise Cáceres, Hannes Müller Schmied, Johnny A. Johannessen, Jan Even Øie Nilsen, Roshin P. Raj, René Forsberg, Louise Sandberg Sørensen, Valentina R. Barletta, Sebastian B. Simonsen, Per Knudsen, Ole Baltazar Andersen, Heidi Ranndal, Stine K. Rose, Christopher J. Merchant, Claire R. Macintosh, Karina von Schuckmann, Kristin Novotny, Andreas Groh, Marco Restano, and Jérôme Benveniste
Earth Syst. Sci. Data, 14, 411–447, https://doi.org/10.5194/essd-14-411-2022, https://doi.org/10.5194/essd-14-411-2022, 2022
Short summary
Short summary
Global mean sea-level change observed from 1993 to 2016 (mean rate of 3.05 mm yr−1) matches the combined effect of changes in water density (thermal expansion) and ocean mass. Ocean-mass change has been assessed through the contributions from glaciers, ice sheets, and land water storage or directly from satellite data since 2003. Our budget assessments of linear trends and monthly anomalies utilise new datasets and uncertainty characterisations developed within ESA's Climate Change Initiative.
Justino Martínez, Carolina Gabarró, Antonio Turiel, Verónica González-Gambau, Marta Umbert, Nina Hoareau, Cristina González-Haro, Estrella Olmedo, Manuel Arias, Rafael Catany, Laurent Bertino, Roshin P. Raj, Jiping Xie, Roberto Sabia, and Diego Fernández
Earth Syst. Sci. Data, 14, 307–323, https://doi.org/10.5194/essd-14-307-2022, https://doi.org/10.5194/essd-14-307-2022, 2022
Short summary
Short summary
Measuring salinity from space is challenging since the sensitivity of the brightness temperature to sea surface salinity is low, but the retrieval of SSS in cold waters is even more challenging. In 2019, the ESA launched a specific initiative called Arctic+Salinity to produce an enhanced Arctic SSS product with better quality and resolution than the available products. This paper presents the methodologies used to produce the new enhanced Arctic SMOS SSS product.
Florence Marti, Alejandro Blazquez, Benoit Meyssignac, Michaël Ablain, Anne Barnoud, Robin Fraudeau, Rémi Jugier, Jonathan Chenal, Gilles Larnicol, Julia Pfeffer, Marco Restano, and Jérôme Benveniste
Earth Syst. Sci. Data, 14, 229–249, https://doi.org/10.5194/essd-14-229-2022, https://doi.org/10.5194/essd-14-229-2022, 2022
Short summary
Short summary
The Earth energy imbalance at the top of the atmosphere due to the increase in greenhouse gases and aerosol concentrations is responsible for the accumulation of energy in the climate system. With its high thermal inertia, the ocean accumulates most of this energy excess in the form of heat. The estimation of the global ocean heat content through space geodetic observations allows monitoring of the energy imbalance with realistic uncertainties to better understand the Earth’s warming climate.
Manuel Bensi, Vedrana Kovačević, Federica Donda, Philip Edward O'Brien, Linda Armbrecht, and Leanne Kay Armand
Earth Syst. Sci. Data, 14, 65–78, https://doi.org/10.5194/essd-14-65-2022, https://doi.org/10.5194/essd-14-65-2022, 2022
Short summary
Short summary
The Totten Glacier (Sabrina Coast, East Antarctica) has undergone significant retreat in recent years, underlining its sensitivity to climate change and its potential contribution to global sea-level rise. The melting process is strongly influenced by ocean dynamics and the spatial distribution of water masses appears to be linked to the complex morpho-bathymetry of the area, supporting the hypothesis that downwelling processes contribute to shaping the architecture of the continental margin.
Matthew A. Chamberlain, Peter R. Oke, Russell A. S. Fiedler, Helen M. Beggs, Gary B. Brassington, and Prasanth Divakaran
Earth Syst. Sci. Data, 13, 5663–5688, https://doi.org/10.5194/essd-13-5663-2021, https://doi.org/10.5194/essd-13-5663-2021, 2021
Short summary
Short summary
BRAN2020 is a dynamical reconstruction of the ocean, combining observations with a high-resolution global ocean model. BRAN2020 currently spans January 1993 to December 2019, assimilating in situ temperature and salinity, as well as satellite-based sea level and sea surface temperature. A new multiscale approach to data assimilation constrains the broad-scale ocean properties and turbulent mesoscale dynamics in two steps, showing closer agreement to observations than all previous versions.
Pierre Prandi, Jean-Christophe Poisson, Yannice Faugère, Amandine Guillot, and Gérald Dibarboure
Earth Syst. Sci. Data, 13, 5469–5482, https://doi.org/10.5194/essd-13-5469-2021, https://doi.org/10.5194/essd-13-5469-2021, 2021
Short summary
Short summary
We investigate how mapping sea level in the Arctic Ocean can benefit from combining data from three satellite radar altimeters: CryoSat-2, Sentinel-3A and SARAL/AltiKa. A dedicated processing for SARAL/AltiKa provides a baseline for the cross-referencing of CryoSat-2 and Sentinel-3A before mapping. We show that by combining measurements coming from three missions, we are able to increase the resolution of gridded sea level fields in the ice-covered Arctic Ocean.
Zhan Hu, Simei Lian, Huaiyu Wei, Yulong Li, Marcel Stive, and Tomohiro Suzuki
Earth Syst. Sci. Data, 13, 4987–4999, https://doi.org/10.5194/essd-13-4987-2021, https://doi.org/10.5194/essd-13-4987-2021, 2021
Short summary
Short summary
The process of wave attenuation in vegetation is important as it is related to the coastal protection service of these coastal ecosystems. In intertidal environments, waves often propagate into vegetation fields with underlying tidal currents, but the effect of these currents on the wave attenuation is often overlooked, and the relevant dataset is rarely available. Here, we present a dataset of wave propagation through vegetation with following and opposing currents to assist further studies.
Petra Zemunik, Jadranka Šepić, Havu Pellikka, Leon Ćatipović, and Ivica Vilibić
Earth Syst. Sci. Data, 13, 4121–4132, https://doi.org/10.5194/essd-13-4121-2021, https://doi.org/10.5194/essd-13-4121-2021, 2021
Short summary
Short summary
A new global dataset – MISELA (Minute Sea-Level Analysis) – has been developed and contains quality-checked sea-level records from 331 tide gauges worldwide for a period from 2004 to 2019. The dataset is appropriate for research on atmospherically induced high-frequency sea-level oscillations. Research on these oscillations is important, as they can, like all sea-level extremes, seriously threaten coastal zone infrastructure and populations.
Michael G. Hart-Davis, Gaia Piccioni, Denise Dettmering, Christian Schwatke, Marcello Passaro, and Florian Seitz
Earth Syst. Sci. Data, 13, 3869–3884, https://doi.org/10.5194/essd-13-3869-2021, https://doi.org/10.5194/essd-13-3869-2021, 2021
Short summary
Short summary
Ocean tides are an extremely important process for a variety of oceanographic applications, particularly in understanding coastal sea-level rise. Tidal signals influence satellite altimetry estimations of the sea surface, which has resulted in the development of ocean tide models to account for such signals. The EOT20 ocean tide model has been developed at DGFI-TUM using residual analysis of satellite altimetry, with the focus on improving the estimation of ocean tides in the coastal region.
Denise Dettmering, Felix L. Müller, Julius Oelsmann, Marcello Passaro, Christian Schwatke, Marco Restano, Jérôme Benveniste, and Florian Seitz
Earth Syst. Sci. Data, 13, 3733–3753, https://doi.org/10.5194/essd-13-3733-2021, https://doi.org/10.5194/essd-13-3733-2021, 2021
Short summary
Short summary
In this study, a new gridded altimetry-based regional sea level dataset for the North Sea is presented, named North SEAL. It is based on long-term multi-mission cross-calibrated altimetry data consistently preprocessed with coastal dedicated algorithms. On a 6–8 km wide triangular mesh, North SEAL provides time series of monthly sea level anomalies as well as sea level trends and amplitudes of the mean annual sea level cycle for the period 1995–2019 for various applications.
Robert Hagen, Andreas Plüß, Romina Ihde, Janina Freund, Norman Dreier, Edgar Nehlsen, Nico Schrage, Peter Fröhle, and Frank Kösters
Earth Syst. Sci. Data, 13, 2573–2594, https://doi.org/10.5194/essd-13-2573-2021, https://doi.org/10.5194/essd-13-2573-2021, 2021
Short summary
Short summary
We established an open-access, integrated marine data collection for 1996 to 2015 in the German Bight as a database of scientific, economic, and governmental interest. This paper presents data for tidal elevation, depth-averaged current velocity, bottom shear stress, depth-averaged salinity, and wave parameters and spectra at a high temporal and spatial resolution. Data are additionally processed into meaningful parameters (i.e., tidal characteristic values, e.g., tidal range) for accessibility.
Frédéric Cyr and Peter S. Galbraith
Earth Syst. Sci. Data, 13, 1807–1828, https://doi.org/10.5194/essd-13-1807-2021, https://doi.org/10.5194/essd-13-1807-2021, 2021
Short summary
Short summary
Climate indices are often regarded as simple ways to relate mean environmental conditions to the state of an ecosystem. Such indices are often used to inform fisheries scientists and managers or used in fisheries resource assessments and ecosystem studies. The Newfoundland and Labrador (NL) climate index aims to describe the environmental conditions on the NL shelf and in the Northwest Atlantic as a whole. It consists of annual normalized anomalies of 10 subindices relevant for the NL shelf.
Cited articles
Ackerman, S. A., Holz, R. E., Frey, R., Eloranta, E. W., Maddux, B. C., and
McGill, M.: Cloud detection with MODIS. Part ii: validation, J. Atmos.
Ocean. Tech., 25, 1073–1086, https://doi.org/10.1175/2007JTECHA1053.1,
2008.
Alerskans, E., Høyer, J. L., Gentemann, C. L., Pedersen, L. T.,
Nielsen-Englyst, P., and Donlon, C.: Construction of a climate data record
of sea surface temperature from passive microwave measurements, Remote Sens.
Environ., 236, 11485, https://doi.org/10.1016/j.rse.2019.111485, 2020.
Banzon, V., Smith, T. M., Steele, M., Huang, B., and Zhang, H.-M.: Improved
estimation of proxy sea surface temperature in the Arctic, J. Atmos. Ocean.
Tech., 37, 341–349, https://doi.org/10.1175/jtech-d-19-0177.1, 2020.
Banzon, V. F. and Reynolds, R. W.: Use of windsat to extend a
microwave-based daily optimum interpolation sea surface temperature time
series, J. Climate, 26, 2557–2562, https://doi.org/10.1175/jcli-d-12-00628.1,
2013.
Barton, I. and Pearce, A.: Validation of GLI and other satellite-derived sea
surface temperatures using data from the Rottnest Island ferry, Western
Australia, J. Oceanogr., 62, 303–310,
https://doi.org/10.1007/s10872-006-0055-5, 2006.
Benali, A., Carvalho, A. C., Nunes, J. P., Carvalhais, N., and Santos, A.:
Estimating air surface temperature in Portugal using MODIS LST data, Remote
Sens. Environ., 124, 108–121, https://doi.org/10.1016/j.rse.2012.04.024,
2012.
Bretherton, F. P., Davis, R. E., and Fandry, C. B.: A technique for
objective analysis and design of oceanographic experiments applied to
MODE-73, Deep-Sea Res. Oceanogr. Abstr., 23, 559–582, https://doi.org/10.1016/0011-7471(76)90001-2, 1976.
Burnett, W., Harper, S., Preller, R., Jacobs, G., and LaCroix, K.: Overview
of operational ocean forecasting in the US navy past, present, and future,
Oceanography, 27, 24–31, https://doi.org/10.5670/oceanog.2014.65, 2014.
Cao, M., Mao, K., Yan, Y., Shi, J., Wang, H., Xu, T., Fang, S., and Yuan,
Z.: A new global gridded sea surface temperature data product based on
multisource data (Version 1.0) [Dataset], Zenodo,
https://doi.org/10.5281/zenodo.4419804, 2021a.
Cao, M., Mao, K., Yan, Y., Shi, J., Wang, H., Xu, T., Fang, S., and Yuan, Z.: A New Global Gridded Sea Surface Temperature Data Product Based on Multisource Data (Version 1.0) [Code], Zenodo, https://doi.org/10.5281/zenodo.4762067, 2021b.
Carton, J. A. and Giese, B. S.: A Reanalysis of Ocean Climate Using Simple
Ocean Data Assimilation (SODA), Mon. Weather Rev., 136, 2999–3017,
https://doi.org/10.1175/2007mwr1978.1, 2008.
Carton, J. A., Chepurin, G. A., and Chen, L.: SODA3: A new ocean climate
reanalysis, J. Climate, 31, 6967–6983,
https://doi.org/10.1175/JCLI-D-18-0149.1, 2018.
Castro, S. L., Emery, W. J., and Wick, G. A.: Skin and bulk sea surface
temperature estimates from passive microwave and thermal infrared satellite
imagery and their relationships to atmospheric forcing, Gayana
(Concepción), 68, 96–101,
https://doi.org/10.4067/S0717-65382004000200018, 2004.
Castro, S. L., Wick, G. A., and Steele, M.: Validation of satellite sea
surface temperature analyses in the Beaufort Sea using UpTempO buoys, Remote
Sens. Environ., 187, 458–475, https://doi.org/10.1016/j.rse.2016.10.035,
2016.
Chao, Y., Li, Z., Farrara, J. D., and Hung, P.: Blending sea surface
temperatures from multiple satellites and in situ observations for coastal
oceans, J. Atmos. Ocean. Tech., 26, 1415–1426,
https://doi.org/10.1175/2009jtecho592.1, 2009a.
Chao, Y., Li, Z., Farrara, J., McWilliams, J. C., Bellingham, J., Capet, X.,
Chavez, F., Choi, J.-K., Davis, R., Doyle, J., Fratantoni, D. M., Li, P.,
Marchesiello, P., Moline, M. A., Paduan, J., and Ramp, S.: Development,
implementation and evaluation of a data-assimilative ocean forecasting
system off the central California coast, Deep-Sea Res. Pt. II, 56, 100–126, https://doi.org/10.1016/j.dsr2.2008.08.011, 2009b.
Chassignet, E. P., Hurlburt, H. E., Metzger, E. J., Smedstad, O. M.,
Cummings, J. A., Halliwell, G. R., Bleck, R., Baraille, R., Wallcraft, A.
J., Lozano, C., Tolman, H. L., Srinivasan, A., Hankin, S., Cornillon, P.,
Weisberg, R., Barth, A., He, R., Werner, F., and Wilkin, J.: US GODAE Global
Ocean Prediction with the HYbrid Coordinate Ocean Model (HYCOM),
Oceanography, 22, 64–75, https://doi.org/10.5670/oceanog.2009.39, 2009.
Dash, P., Ignatov, A., Martin, M., Donlon, C., Brasnett, B., Reynolds, R.,
Banzon, V., Helen, B., Cayula, J.-F., Chao, Y., Grumbine, R., Maturi, E.,
Harris, A., Mittaz, J., Sapper, J., Chin, T., Vazquez, J., Armstrong, E.,
Gentemann, C., and Poulter, D.: Group for High Resolution SST (GHRSST)
Analysis Fields Inter Comparisons: Part2. Near real-time web-based Level 4
SST Quality Monitor (L4-SQUAM), Deep-Sea Res. Pt. II,
7, 31–43, 2011.
Donlon, C. J., Minnett, P. J., Gentemann, C., Nightingale, T. J., Barton, I.
J., Ward, B., and Murray, M. J.: Toward improved validation of satellite sea
surface skin temperature measurements for climate research, J. Climate, 15,
353–369, https://doi.org/10.1175/1520-0442(2002)015<0353:TIVOSS>2.0.CO;2, 2002.
Fairall, C. W., Bradley, E. F., Godfrey, J. S., Wick, G. A., Edson, J. B.,
and Young, G. S.: Cool-skin and warm-layer effects on sea surface
temperature, J. Geophys. Res.-Oceans, 101, 1295–1308,
https://doi.org/10.1029/95jc03190, 1996.
Gentemann, C. L.: Microwave sea surface temperatures for climate,
available at: http://www.wcrp-climate.org/conference2011/posters/C14/C14_Gentemann_T45B.pdf (last access: 2 March 2020), 2011.
Gentemann, C. L.: Three way validation of MODIS and AMSR-E sea surface
temperatures, J. Geophys. Res.-Oceans, 119, 2583–2598,
https://doi.org/10.1002/2013jc009716, 2014.
Gentemann, C. L., Meissner, T., and Wentz, F. J.: Accuracy of satellite sea
surface temperatures at 7 and 11 GHz, IEEE Trans. Geosci. Remote Sensing,
48, 1009–1018, https://doi.org/10.1109/tgrs.2009.2030322, 2010.
Guan, L. and Kawamura, H.: SST availabilities of satellite infrared and
microwave measurements, J. Oceanogr., 59, 201–209,
https://doi.org/10.1023/A:1025543305658, 2003.
Guan, L. and Kawamura, H.: Merging satellite infrared and microwave SSTs:
Methodology and evaluation of the new SST, J. Oceanogr., 60, 905–912,
https://doi.org/10.1007/s10872-004-5782-x, 2004.
Han, G., Li, W., Zhang, X., Li, D., He, Z., Wang, X., Wu, X., Yu, T., and
Ma, J.: A regional ocean reanalysis system for coastal waters of China and
adjacent seas, Adv. Atmos. Sci., 28, 682,
https://doi.org/10.1007/s00376-010-9184-2, 2011.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, j., Nicolas, J., Peubey, C., Radu, R., Schepers, D.,
Simmons, D., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P.,
Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D.,
Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer,
A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková,
M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay,
P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J. N.: The ERA5 global
reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049,
https://doi.org/10.1002/qj.3803,2020.
Hosoda, K. and Sakaida, F.: Global daily high-resolution satellite-based
foundation sea surface temperature dataset: development and validation
against two definitions of foundation SST, Remote Sens., 8, 962,
https://doi.org/10.3390/rs8110962, 2016.
Hosoda, K., Kawamura, H., and Sakaida, F.: Improvement of New Generation Sea
Surface Temperature for Open ocean (NGSST-O): a new sub-sampling method of
blending microwave observations, J. Oceanogr., 71, 205–220,
https://doi.org/10.1007/s10872-015-0272-x, 2015.
Høyer, J. L., Karagali, I., Dybkjær, G., and Tonboe, R.: Multi sensor
validation and error characteristics of Arctic satellite sea surface
temperature observations, Remote Sens. Environ., 121, 335–346,
https://doi.org/10.1016/j.rse.2012.01.013, 2012.
Huang, B., Wang, W., Liu, C., Banzon, V., Zhang, H., and Lawrimore, J.: Bias
adjustment of AVHRR SST and its impacts on two SST analyses, J. Atmos.
Ocean. Tech., 32, 372–387, https://doi.org/10.1175/jtech-d-14-00121.1,
2015.
Huang, S., Cheng, L., and Sheng, Z.: A method of making up the satellite
retrieval data of sea surface temperature, Scientia Meteorologica Snica, 28,
237–243, https://doi.org/10.3969/j.issn.1009-0827.2008.03.001, 2008 (in
Chinese).
Karagali, I., Høyer, J. L., and Donlon, C. J.: Using a 1-D model to
reproduce the diurnal variability of SST, J. Geophys. Res.-Oceans, 122,
2945–2959, https://doi.org/10.1002/2016JC012542, 2017.
Kawai, Y. and Wada, A.: Diurnal sea surface temperature variation and its
impact on the atmosphere and ocean: A review, J. Oceanogr., 63, 721–744,
https://doi.org/10.1007/s10872-007-0063-0, 2007.
Kilpatrick, K. A., Podesta, G. P., and Evans, R.: Overview of the NOAA/NASA
advanced very high resolution radiometer Pathfinder algorithm for sea
surface temperature and associated matchup database, J. Geophys.
Res.-Oceans, 106, 9179–9197, https://doi.org/10.1029/1999jc000065, 2001.
Kilpatrick, K. A., Podestá, G., Walsh, S., Williams, E., Halliwell, V.,
Szczodrak, M., Brown, O. B., Minnett, P. J., and Evans, R.: A decade of sea
surface temperature from MODIS, Remote Sens. Environ., 165, 27–41,
https://doi.org/10.1016/j.rse.2015.04.023, 2015.
Li, A., Bo, Y., Zhu, Y., Guo, P., Bi, J., and He, Y.: Blending
multi-resolution satellite sea surface temperature (SST) products using
Bayesian maximum entropy method, Remote Sens. Environ., 135, 52–63,
https://doi.org/10.1016/j.rse.2013.03.021, 2013.
Li, W., Xie, Y., He, Z., Han, G., Liu, K., Ma, J., and Li, D.: Application
of the multigrid data assimilation scheme to the China seas' temperature
forecast, J. Atmos. Ocean. Technol., 25, 2106–2116,
https://doi.org/10.1175/2008jtecho510.1, 2008.
Li, Y. and He, R.: Spatial and temporal variability of SST and ocean color
in the Gulf of Maine based on cloud-free SST and chlorophyll reconstructions
in 2003–2012, Remote Sens. Environ., 144, 98–108,
https://doi.org/10.1016/j.rse.2014.01.019, 2014.
Liu, M., Guan, L., Zhao, W., and Chen, G.: Evaluation of sea surface
temperature from the HY-2 scanning microwave radiometer, IEEE T. Geosci.
Remote, 55, 1372–1380, https://doi.org/10.1109/TGRS.2016.2623641,
2017.
Liu, Y., Chin, T. M., and Minnett, P. J.: Sampling errors in
satellite-derived infrared sea-surface temperatures. Part II: Sensitivity
and parameterization, Remote Sens. Environ., 198, 297–309,
https://doi.org/10.1016/j.rse.2017.06.011, 2017.
Luo, B., Minnett, P. J., Gentemann, C., and Szczodrak, G.: Improving
satellite retrieved night-time infrared sea surface temperatures in aerosol
contaminated regions, Remote Sens. Environ., 223, 8–20,
https://doi.org/10.1016/j.rse.2019.01.009, 2019.
Luo, B., Minnett, P. J., Szczodrak, M., Kilpatrick, K., and Izaguirre, M.:
Validation of Sentinel-3A SLSTR derived sea-surface skin temperatures with
those of the shipborne M-AERI, Remote Sens. Environ., 244, 111826,
https://doi.org/10.1016/j.rse.2020.111826, 2020.
Mao, K., Yuan, Z., Zuo, Z., Xu, T., Shen, X., and Gao, C.: Changes in global
cloud cover based on remote sensing data from 2003 to 2012, Chinese Geogr.
Sci., 29, 306–315, https://doi.org/10.1007/s11769-019-1030-6, 2019.
Martin, A. J., Hines, A., and Bell, M. J.: Data assimilation in the FOAM
operational short-range ocean forecasting system: A description of the
scheme and its impact, Q. J. Roy. Meteor. Soc., 133, 981–995,
https://doi.org/10.1002/qj.74, 2007.
McCoy, D. T., Eastman, R., Hartmann, D. L., and Wood, R.: The change in low
cloud cover in a warmed climate inferred from AIRS, MODIS, and ERA-Interim,
J. Climate, 30, 3609–3620, https://doi.org/10.1175/JCLI-D-15-0734.1, 2017.
Minnett, P. J.: Consequences of sea surface temperature variability on the
validation and applications of satellite measurements, J. Geophys.
Res.-Oceans, 96, 18475–18489, https://doi.org/10.1029/91JC01816, 1991.
Minnett, P. J.: Radiometric measurements of the sea-surface skin
temperature: the competing roles of the diurnal thermocline and the cool
skin, Int. J. Remote Sens., 24, 5033–5047,
https://doi.org/10.1080/0143116031000095880, 2003.
Minnett, P. J., Smith, M., and Ward, B.: Measurements of the oceanic thermal
skin effect, Deep-Sea Res. Pt. II, 58, 861–868,
https://doi.org/10.1016/j.dsr2.2010.10.024, 2011.
Minnett, P. J., Alvera-Azcárate, A., Chin, T. M., Corlett, G. K.,
Gentemann, C. L., Karagali, I., Li, X., Marsouin, A., Marullo, S., Maturi,
E., Santoleri, R., Saux Picart, S., Steele, M., and Vazquez-Cuervo, J.: Half
a century of satellite remote sensing of sea-surface temperature, Remote
Sens. Environ., 233, 111366, https://doi.org/10.1016/j.rse.2019.111366,
2019.
Ng, H. G., MatJafri, M. Z., Abdullah, K., and Othman, N.: Merging infrared
and microwave SST data at south China sea, Proceedings of the 6th
International Conference on Computer Graphics, Imaging and Visualization
(CGIV 2009), Tianjin, China, 11–14 August 2009, 530–535, 2009.
Oke, P. R., Brassington, G. B., Griffin, D. A., and Schiller, A.: The
Bluelink ocean data assimilation system (BODAS), Ocean Model., 21, 46–70,
https://doi.org/10.1016/j.ocemod.2007.11.002, 2008.
Peres, L. F., Franca, G. B., Paes, R. C. O. V., Sousa, R. C., and Oliveira,
A. N.: Analyses of the positive bias of remotely sensed SST retrievals in
the coastal waters of Rio de Janeiro, IEEE T. Geosci. Remote,
55, 6344–6353, https://doi.org/10.1109/tgrs.2017.2726344, 2017.
Pimentel, S., Tse, W.-H., Xu, H., Denaxa, D., Jansen, E., Korres, G.,
Mirouze, I., and Storto, A.: Modeling the near-surface diurnal cycle of sea
surface temperature in the Mediterranean Sea, J. Geophys. Res.-Oceans, 124,
171–183, https://doi.org/10.1029/2018JC014289, 2018.
Pisano, A., Buongiorno Nardelli, B., Tronconi, C., and Santoleri, R.: The
new Mediterranean optimally interpolated pathfinder AVHRR SST Dataset
(1982–2012), Remote Sens. Environ., 176, 107–116, https://doi.org/10.1016/j.rse.2016.01.019, 2016.
Purdy, W. E., Gaiser, P. W., Poe, G. A., Uliana, E. A., Eissner, T., and
Wentz, F. J.: Geolocation and pointing accuracy analysis for the WindSat
sensor, IEEE T. Geosci. Remote, 44, 496–505,
https://doi.org/10.1109/tgrs.2005.858415, 2006.
Reynolds, R. W. and Smith, T. M.: Improved global sea surface temperature
analyses using optimum interpolation, J. Climate, 7, 929–948,
https://doi.org/10.1175/1520-0442(1994)007<0929:IGSSTA>2.0.CO;2, 1994.
Reynolds, R. W. and Smith, T. M.: A high-resolution global sea surface
temperature climatology, J. Climate, 8, 1571–1583,
https://doi.org/10.1175/1520-0442(1995)008<1571:Ahrgss>2.0.Co;2, 1995.
Reynolds, R. W., Rayner, N. A., Smith, T. M., Stokes, D. C., and Wang, W.
Q.: An improved in situ and satellite SST analysis for climate, J. Climate,
15, 1609–1625, https://doi.org/10.1175/1520-0442(2002)015<1609:Aiisas>2.0.Co;2, 2002.
Reynolds, R. W., Smith, T. M., Liu, C., Chelton, D. B., Casey, K. S., and
Schlax, M. G.: Daily high-resolution-blended analyses for sea surface
temperature, J. Climate, 20, 5473–5496,
https://doi.org/10.1175/2007JCLI1824.1, 2007.
Sakalli, A. and Basusta, N.: Sea surface temperature change in the Black Sea
under climate change: A simulation of the sea surface temperature up to
2100, Int. J. Climatol., 38, 4687–4698, https://doi.org/10.1002/joc.5688,
2018.
Satyamurty, P. and Rosa, M. B.: Synoptic climatology of tropical and
subtropical South America and adjoining seas as inferred from Geostationary
Operational Environmental Satellite imagery, Int. J. Climatol., 40, 378–399,
https://doi.org/10.1002/joc.6217, 2020.
Saunders, P. M.: The temperature at the ocean-air interface, Asia-Pac, J.
Atmos. Sci., 24, 269–273,
https://doi.org/10.1175/1520-0469(1967)024<0269:TTATOA>2.0.CO;2, 1967.
Shi, Y., Zhou, X., Yang, X., Shi, L., and Ma, S.: Merging satellite ocean
color data with bayesian maximum entropy method, IEEE J. Sel. Top. Appl.
Earth Observ., 8, 3294–3304, https://doi.org/10.1109/JSTARS.2015.2425691,
2015.
Smith, T. M. and Reynolds, R. W.: Extended reconstruction of global sea
surface temperatures based on COADS data (1854–1997), J. Climate, 16,
1495–1510, https://doi.org/10.1175/1520-0442-16.10.1495, 2003.
Storkey, D., Blockley, E. W., Furner, R., Guiavarc'h, C., Lea, D., Martin,
M. J., Barciela, R. M., Hines, A., Hyder, P., and Siddorn, J. R.:
Forecasting the ocean state using NEMO:The new FOAM system, J. Oper.
Oceanogr., 3, 3–15, https://doi.org/10.1080/1755876X.2010.11020109, 2010.
Sun, W., Wang, J., Zhang, J., Ma, Y., Meng, J., Yang, L., and Miao, J.: A
new global gridded sea surface temperature product constructed from infrared
and microwave radiometer data using the optimum interpolation method, Acta
Oceanol. Sin., 37, 41–49, https://doi.org/10.1007/s13131-018-1206-4, 2018.
Taylor, K. E.: Summarizing multiple aspects of model performance in a single
diagram, J. Geophys. Res.-Atmos., 106, 7183–7192,
https://doi.org/10.1029/2000jd900719, 2001.
Thiebaux, J., Rogers, E., Wang, W. Q., and Katz, B.: A new high-resolution
blended real-time global sea surface temperature analysis, B. Am.
Meteorol. Soc., 84, 645–656, https://doi.org/10.1175/bams-84-5-645, 2003.
Varela, R., Costoya, X., Enriquez, C., Santos, F., and Gomez-Gesteira, M.:
Differences in coastal and oceanic SST trends north of Yucatan Peninsula, J.
Mar. Syst., 182, 46–55, https://doi.org/10.1016/j.jmarsys.2018.03.006, 2018.
Vincent, R. F., Marsden, R. F., Minnett, P. J., Creber, K. A. M., and
Buckley, J. R.: Arctic waters and marginal ice zones: A composite Arctic sea
surface temperature algorithm using satellite thermal data, J. Geophys.
Res.-Atmos., 113, C04021, https://doi.org/10.1029/2007jc004353, 2008.
Wang, Y., Guan, L., and Qu, L.: Merging sea surface temperature observed by
satellite infrared and microwave radiometers using kalma, Periodical of
Ocean University of China, 40, 126–130, https://doi.org/10.16441/j.cnki.hdxb.2010.12.019, 2010 (in Chinese).
Wentz, F. J., Gentemann, C., Smith, D., and Chelton, D.: Satellite
measurements of sea surface temperature through clouds, Science, 288,
847–850, https://doi.org/10.1126/science.288.5467.847, 2000.
Wick, G. A., Jackson, D. L., and Castro, S. L.: Production of an enhanced
blended infrared and microwave sea surface temperature product, IGARSS 2004.
2004 IEEE International Geoscience and Remote Sensing Symposium, 20–24 September 2004, Anchorage,
AK, USA, 2004.
Xie, J., Zhu, J., and Li, Y.: Assessment and inter-comparison of five
high-resolution sea surface temperature products in the shelf and coastal
seas around China, Cont. Shelf Res., 28, 1286–1293,
https://doi.org/10.1016/j.csr.2008.02.020, 2008.
Xu, F. and Ignatov, A.: In situ SST Quality Monitor (iQuam), J. Atmos.
Ocean. Tech., 31, 164–180, https://doi.org/10.1175/JTECH-D-13-00121.1,
2014.
Xu, S. and Cheng, J.: A new land surface temperature fusion strategy based
on cumulative distribution function matching and multiresolution Kalman
filtering, Remote Sens. Environ., 254, 112256,
https://doi.org/10.1016/j.rse.2020.112256, 2021.
Yan, Y., Mao, K., Shi, J., Piao, S., Shen, X., Dozier, J., Liu, Y., Ren, H.,
and Bao, Q.: Driving forces of land surface temperature anomalous changes in
North America in 2002–2018, Sci. Rep.-UK, 10, 6931,
https://doi.org/10.1038/s41598-020-63701-5, 2020.
Zabolotskikh, E. V., Mitnik, L. M., Reul, N., and Chapron, B.: New
possibilities for geophysical parameter retrievals opened by GCOM-W1 AMSR2,
IEEE J. Sel. Top. Appl. Earth Observ., 8, 4248–4261,
https://doi.org/10.1109/JSTARS.2015.2416514, 2015.
Zhao, B., Mao, K., Cai, Y., Shi, J., Li, Z., Qin, Z., Meng, X., Shen, X., and Guo, Z.: A combined Terra and Aqua MODIS land surface temperature and meteorological station data product for China from 2003 to 2017, Earth Syst. Sci. Data, 12, 2555–2577, https://doi.org/10.5194/essd-12-2555-2020, 2020.
Zhu, J., Zhou, G., Yan, C., Fu, W., and You, X.: A three-dimensional
variational ocean data assimilation system: Scheme and preliminary results,
Science in China Series D: Earth Sciences, 49, 1212–1222,
https://doi.org/10.1007/s11430-006-1212-9, 2006 (in Chinese).
Short summary
We constructed a temperature depth and observation time correction model to eliminate the sampling depth and temporal differences among different data. Then, we proposed a reconstructed spatial model that filters and removes missing pixels and low-quality pixels contaminated by clouds from raw SST images and retrieves real sea surface temperatures under cloud coverage based on multisource data to generate a high-quality unified global SST product with long-term spatiotemporal continuity.
We constructed a temperature depth and observation time correction model to eliminate the...
Altmetrics
Final-revised paper
Preprint