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Remote Sensing
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Global Climate and Ocean Warming—Recent Progress Using Remote Sensing
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Global Climate and Ocean Warming—Recent Progress Using Remote Sensing

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Ocean Remote Sensing".

Deadline for manuscript submissions: 31 May 2024 | Viewed by 7733

Special Issue Editors

Prof. Dr. Hua Su

E-Mail Website
Guest Editor
The Academy of Digital China, Fuzhou University, Fuzhou 350108, China
Interests: ocean remote sensing; coastal remote sensing; deep ocean remote sensing; global climate change; AI oceanography
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. James A. Carton

E-Mail Website
Guest Editor
Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD 20742, USA
Interests: remote sensing; tropical climate; ocean color; ocean wind
Dr. Lijing Cheng

E-Mail Website
Guest Editor
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
Interests: climate change; climate variability; climate dynamics; physics of global warming; ocean climatology
Dr. Wei Zhuang

E-Mail Website
Guest Editor
State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen 361005, China
Interests: physical oceanography; ocean circulation; climate change and variability
Special Issues, Collections and Topics in MDPI journals
Dr. Qutu Jiang

E-Mail Website
Guest Editor
Department of Geography, The University of Hong Kong, Hong Kong 999077, China
Interests: sustainable ocean/coastal development; marine ecology; spatiotemporal modeling; environmental pollution; risk assessment
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent decades, anthropogenic greenhouse gas emissions have significantly increased, causing global warming via heat trapped in the Earth’s climate system; this has led to a positive Earth energy imbalance (EEI) and global ocean warming. The ocean, as a vital regulator of the global climate system, has absorbed more than 90% of the EEI, resulting in an unprecedented increase in ocean heat content (OHC) and, consequently, the intensification of changes in the marine environment and climate. Global climate change and ocean warming have increased the number of extreme weather events such as typhoons and hurricanes and raised global sea levels; moreover, they pose a long-term threat to the marine ecological environment and sustainable development. Studies on global climate and ocean warming mainly emphasize the application of in situ gridded and reanalysis data, as well as remote sensing observations. For several decades, satellite remote sensing has collected multiple ocean observations at various spatiotemporal scales, greatly improving our understanding of ocean processes and climate change through space observation. However, the lack of consistent long-term and large-scale ocean observations (especially of the ocean interior) and advanced techniques hinders the inference and recognition of 3D ocean processes. Advanced remote sensing techniques must be used to further investigate the processes, mechanisms, and impacts of ocean warming and environmental changes under global warming, such as subsurface and deeper ocean warming, climate variability and extreme events, heat-transport and -redistribution processes, physical processes and internal dynamics, marine ecosystem health, and sustainable development, which have been greatly impacted by recent global climate change and ocean warming.

This Special Issue invites authors to contribute to advances in the study of global climate and ocean warming based on satellite remote sensing. We aim to present global climate change and variability studies reporting new techniques that combine satellite sensors and remote sensing big data with other observations (based on deep-ocean remote sensing; data fusion and gap-filling; artificial intelligence; deep learning; and dynamic model- and data-assimilation approaches) to detect the factors affected by global climate and ocean warming (such as ocean heat content, temperature, salinity, stratification, circulation, and other biogeochemistry factors). Articles may address, but are not limited to:

  • Sea surface temperature and subsurface thermohaline structure;
  • Ocean heat content and marine heatwaves;
  • Multi-sensor satellite remote sensing;
  • Deep-ocean remote sensing;
  • Marine ecosystem health assessment;
  • Ocean warming and sea level rise;
  • Ocean climate and blue carbon;
  • Sustainable development goals.

Prof. Dr. Hua Su
Prof. Dr. James A. Carton
Dr. Lijing Cheng
Dr. Wei Zhuang
Dr. Qutu Jiang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • climate change remote sensing
  • deep-ocean remote sensing
  • global climate and ocean warming
  • ocean climate and extreme events
  • artificial intelligence and data assimilation
  • multiscale physical processes
  • ocean heat content and blue carbon
  • marine environments and ecosystems
  • sustainable development goals

Published Papers (5 papers)

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15 pages, 11072 KiB  
Article
Unraveling Regional Patterns of Sea Level Acceleration over the China Seas
by Ying Qu, Svetlana Jevrejeva and Shijin Wang
Remote Sens. 2023, 15(18), 4448; https://doi.org/10.3390/rs15184448 - 09 Sep 2023
Viewed by 820
Abstract
Accelerated sea level rise is placing coastal communities in a vulnerable position; however, the processes underlying sea level acceleration in China remain uncertain. In this study, we examine the sea level acceleration and its contributors over the China Seas. We calculate acceleration along [...] Read more.
Accelerated sea level rise is placing coastal communities in a vulnerable position; however, the processes underlying sea level acceleration in China remain uncertain. In this study, we examine the sea level acceleration and its contributors over the China Seas. We calculate acceleration along the Chinese coast using satellite altimetry and tide gauge records. During the satellite altimetry era, sea level acceleration from tide gauge records varies across all stations, reaching up to 0.30 ± 0.20 mm/yr2, while satellite altimetry could underestimate/overestimate the sea level acceleration in most locations. Acceleration near the coast, except in the Bohai Sea, is mainly driven by changes in the mass component. In contrast, for the open ocean, changes in steric sea level are the main contributor to sea level acceleration. The evolution of spatial acceleration patterns over the China Seas reveals that the ENSO and PDO variabilities dominate the changing patterns of sea level acceleration in the open ocean, including the Philippine Sea through steric sea level, and changes in most coastal locations are due to the non-steric component. Full article
(This article belongs to the Special Issue Global Climate and Ocean Warming—Recent Progress Using Remote Sensing)
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17 pages, 7286 KiB  
Article
Spaceborne Relative Radiometer: Instrument Design and Pre-Flight Test
by Duo Wu, Wei Fang, Kai Wang, Xin Ye, Ruidong Jia, Dongjun Yang, Baoqi Song, Zhitao Luo, Yuwei Wang, Zhiwei Xia, Ping Zhu and Michel van Ruymbeke
Remote Sens. 2023, 15(12), 3085; https://doi.org/10.3390/rs15123085 - 13 Jun 2023
Cited by 1 | Viewed by 978
Abstract
In order to simultaneously determine the values of total solar irradiance (TSI) and the Earth’s radiation at the top of the atmosphere (TOA) on board the Fengyun-3F satellite, a spaceborne relative radiometer (SRR) was developed. It adopts a dual-channel structure, including a solar [...] Read more.
In order to simultaneously determine the values of total solar irradiance (TSI) and the Earth’s radiation at the top of the atmosphere (TOA) on board the Fengyun-3F satellite, a spaceborne relative radiometer (SRR) was developed. It adopts a dual-channel structure, including a solar radiometer channel (SR) with an unobstructed field of view (FOV) of 1.5° and an Earth radiometer channel (ER) with a wide field of view (WFOV) of 95.3° and a diameter of about 1900 km on the ground. Before the launch, both the SR and ER were calibrated. The SR, installed on the inner frame of the solar tracker of the SIM-II (solar irradiance monitor-II), is used to observe rapid changes in solar radiance with the SIAR (solar irradiance absolute radiometer), an electrical-substitution radiometer, on orbit. The ER is mounted on the U-shaped frame of the solar tracker, directly pointing in the nadir direction. Additionally, a dark space observation mode is used to determine the on-orbit background noise and lunar observation mode for on-orbit calibration. In this article, the instrument design and working principle of the SRR is first introduced, and an analysis of the measurement model of the ER, the WFOV channel of the SRR, is focused on. Finally, ground test results of the SRR are introduced. Full article
(This article belongs to the Special Issue Global Climate and Ocean Warming—Recent Progress Using Remote Sensing)
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23 pages, 5794 KiB  
Article
On Evaluating the Predictability of Sea Surface Temperature Using Entropy
by Chang Jin, Han Peng, Hanchen Yang, Wengen Li and Jihong Guan
Remote Sens. 2023, 15(8), 1956; https://doi.org/10.3390/rs15081956 - 07 Apr 2023
Viewed by 1194
Abstract
Sea surface temperature (SST) has important impacts on the global ecology, and having a good understanding of the predictability, i.e., the possibility of achieving accurate prediction, of SST can help us monitor the marine environment and climate change, and guide the selection and [...] Read more.
Sea surface temperature (SST) has important impacts on the global ecology, and having a good understanding of the predictability, i.e., the possibility of achieving accurate prediction, of SST can help us monitor the marine environment and climate change, and guide the selection and design of SST prediction methods. However, existing studies for analyzing SST mostly measure the rising or falling trends of SST. To address this issue, we introduce a temporal-correlated entropy to quantify the predictability of SST series from both global coarse-grained and local fine-grained aspects, and make SST prediction with multiple deep learning models to prove the effectiveness of such predictability evaluation method. In addition, we explore the dynamics of SST predictability by dividing the time range of interest into consecutive time periods, evaluating the corresponding predictability of SST for each time period, and analyzing the stability of the predictability of SST over time. According to the experiments, the SST predictability values near the poles and equator are really high. The average SST predictability values of the East China Sea, Bohai Sea, and Antarctic Ocean are 0.719, 0.706, and 0.886, respectively, and the size relationship of the SST predictability in the three local sea areas is consistent with our prediction results using multiple representative SST prediction methods, which corroborates the reliability of the predictability evaluation method. In addition, we found that the SST predictability in the Antarctic Ocean changes more dramatically over time than in the East China Sea and the Bohai Sea. The results of SST predictability and its dynamic analysis indicate that global warming, ocean currents, and human activities all have significant impacts on the predictability of SST. Full article
(This article belongs to the Special Issue Global Climate and Ocean Warming—Recent Progress Using Remote Sensing)
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21 pages, 4492 KiB  
Article
Unabated Global Ocean Warming Revealed by Ocean Heat Content from Remote Sensing Reconstruction
by Hua Su, Yanan Wei, Wenfang Lu, Xiao-Hai Yan and Hongsheng Zhang
Remote Sens. 2023, 15(3), 566; https://doi.org/10.3390/rs15030566 - 17 Jan 2023
Cited by 6 | Viewed by 3123
Abstract
As the most relevant indicator of global warming, the ocean heat content (OHC) change is tightly linked to the Earth’s energy imbalance. Therefore, it is vital to study the OHC and heat absorption and redistribution. Here we analyzed the characteristics of [...] Read more.
As the most relevant indicator of global warming, the ocean heat content (OHC) change is tightly linked to the Earth’s energy imbalance. Therefore, it is vital to study the OHC and heat absorption and redistribution. Here we analyzed the characteristics of global OHC variations based on a previously reconstructed OHC dataset (named OPEN) with four other gridded OHC datasets from 1993 to 2021. Different from the other four datasets, the OPEN dataset directly obtains OHC through remote sensing, which is reliable and superior in OHC reconstruction, further verified by the Clouds and the Earth’s Radiant Energy System (CERES) radiation flux data. We quantitatively analyzed the changes in the upper 2000 m OHC of the oceans over the past three decades from a multisource and multilayer perspective. Meanwhile, we calculated the global ocean heat uptake to quantify and track the global ocean warming rate and combined it with the Oceanic Niño Index to analyze the global evolution of OHC associated with El Niño–Southern Oscillation variability. The results show that different datasets reveal a continuously increasing and non-decaying global ocean warming from multiple perspectives, with more heat being absorbed by the subsurface and deeper ocean over the past 29 years. The global OHC heating trend from 1993 to 2021 is 7.48 ± 0.17, 7.89 ± 0.1, 10.11 ± 0.16, 7.78 ± 0.17, and 12.8 ± 0.26 × 1022 J/decade according to OPEN, IAP, EN4, Ishii, and ORAS5, respectively, which shows that the trends of the OPEN, IAP, and Ishii datasets are generally consistent, while those of EN4 and ORAS5 datasets are much higher. In addition, the ocean warming characteristics revealed by different datasets are somewhat different. The OPEN OHC dataset from remote sensing reconstruction shows a unique remote sensing mapping advantage, presenting a distinctive warming pattern in the East Indian Ocean. Meanwhile, the OPEN dataset had the largest statistically significant area, with 85.6% of the ocean covered by significant positive trends. The significant and continuous increase in global ocean warming over the past three decades, revealed from remote sensing reconstruction, can provide an important reference for projecting ocean warming in the context of global climate change toward the United Nations Sustainable Development Goals. Full article
(This article belongs to the Special Issue Global Climate and Ocean Warming—Recent Progress Using Remote Sensing)
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15 pages, 6168 KiB  
Technical Note
Inclination Trend of the Agulhas Return Current Path in Three Decades
by Yan Lin, Liru Lin, Dongxiao Wang and Xiao-Yi Yang
Remote Sens. 2023, 15(24), 5652; https://doi.org/10.3390/rs15245652 - 07 Dec 2023
Viewed by 604
Abstract
The Agulhas Return Current (ARC), as a primary component of the Agulhas system, contributes to water exchange and mass transport between the southern portions of the Indian and Atlantic Ocean basins. In this study, satellite altimeter data and reanalysis datasets, and a new [...] Read more.
The Agulhas Return Current (ARC), as a primary component of the Agulhas system, contributes to water exchange and mass transport between the southern portions of the Indian and Atlantic Ocean basins. In this study, satellite altimeter data and reanalysis datasets, and a new set of criteria for the piecewise definition of the jet axis are used to explore the long-term change of the ARC’s axis position in recent three decades. It is found that the ARC axis exhibits a significant slanting trend with its western part (35–48°E) migrating northward and the eastern part (48–70°E) migrating southward. The meridional movement of the ARC path could be attributed to large-scale wind forcing. The anomalous surface wind stress curl, by Ekman pumping mechanism, leads to positive–negative–positive sea surface height anomalies in the western section and negative–positive–negative anomalies in the eastern section, thus the ARC axis tilts accordingly, in a northwest–southeast direction. Further analysis suggests that this ARC slanting trend is more dependent on the southward shift of the downstream axis and less on the topographic steering upstream. The downstream axis is more likely to interact with the ACC fronts and its migration could dominate the local EKE pattern by changing the background circulation and energy cascade direction. For the headstream west of 35°E, the ARC axis is more subject to topography, thus the EKE change is more dominated by eddy activity processes, including shedding, propagation and merging. This study provides some new insights into the long-term change of ARC and its interaction with the local EKE variability. Full article
(This article belongs to the Special Issue Global Climate and Ocean Warming—Recent Progress Using Remote Sensing)
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