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Climate and Environmental Changes Monitored by Satellite Remote Sensing (Third Edition)

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

Deadline for manuscript submissions: closed (31 July 2024) | Viewed by 11732

Special Issue Editors


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Guest Editor
Center for Monsoon System Research, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
Interests: climate and environmental changes; climate dynamics; atmospheric physics; atmospheric teleconnection
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
National Satellite Meteorological Centre, Chinese Meteorological Administration, Beijing 100081, China
Interests: atmospheric remote sensing; quantitative remote sensing of aerosols and dust storms; application of satellite remote sensing products
Special Issues, Collections and Topics in MDPI journals
1. Department of Physics, Institute of Environmental Physics, University Bremen, 28359 Bremen, Germany
2. Institute for Remote Sensing Methods, German Aerospace Center (DLR), Oberpfaffenhofen, Wessling, Germany
Interests: clouds; aerosols; atmospheric composition; radiative transfer; time series analysis; trend detection; climate data records; climate networks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent decades, the global climate has experienced unprecedented changes. Extreme climate and environmental events are becoming more frequent and intense. Extreme climate and environmental events cause massive casualties and losses, high economic costs, and have far-reaching impacts on both human society and the natural environment. Therefore, knowledge of the regime of climate and environmental extremes is critical to assess the magnitude and rate of climate and environmental changes in the world. Satellite remote sensing data are very useful for monitoring the states and processes of climates and the environment at various spatiotemporal scales. Therefore, satellite remote sensing is crucial for advancing our understanding of the global climate and environmental extremes and their impacts.

This Special Issue is the third edition of “Climate and Environmental Changes Monitored by Satellite Remote Sensing” and “Climate and Environmental Changes Monitored by Satellite Remote Sensing II”, and is further devoted to advancing our understanding of climate and environmental extremes using satellite remote sensing observations and their derived products. Articles on all aspects of the analysis of climate and environmental extremes using satellite remote sensing observations are welcome, including but not limited to:

  • Extreme events (floods, droughts, tropical cyclones, heat waves, cold waves, dust storms, and severe haze);
  • Monitoring and detection;
  • Space–time distribution at various scales;
  • External forcing/drivers and internal factors/variability.

Dr. Hainan Gong
Prof. Dr. Peng Zhang
Dr. Luca Lelli
Guest Editors

Manuscript Submission Information

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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 and environmental extremes
  • remote sensing
  • floods
  • droughts
  • tropical cyclones
  • heat waves
  • cold waves
  • dust storms
  • severe haze

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Related Special Issue

Published Papers (10 papers)

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Research

17 pages, 12797 KiB  
Article
Study on the Momentum Flux Spectrum of Gravity Waves in the Tropical Western Pacific Based on Integrated Satellite Remote Sensing and In Situ Observations
by Zhimeng Zhang, Yang He, Yuyang Song and Zheng Sheng
Remote Sens. 2024, 16(14), 2550; https://doi.org/10.3390/rs16142550 - 11 Jul 2024
Viewed by 645
Abstract
Gravity wave (GW) momentum flux spectra help to uncover the mechanisms through which GWs influence momentum transfer in the atmosphere and provide crucial insights into accurately characterizing atmospheric wave processes. This study examines the momentum flux spectra of GWs in the troposphere (2–14 [...] Read more.
Gravity wave (GW) momentum flux spectra help to uncover the mechanisms through which GWs influence momentum transfer in the atmosphere and provide crucial insights into accurately characterizing atmospheric wave processes. This study examines the momentum flux spectra of GWs in the troposphere (2–14 km) and stratosphere (18–28 km) over Koror Island (7.2°N, 134.3°W) using radiosonde data from 2013–2018. Utilizing hodograph analysis and spectral methods, the characteristics of momentum flux spectra are discussed. Given that the zonal momentum flux spectra of low-level atmospheric GWs generally follow a Gaussian distribution, Gaussian fitting was applied to the spectral structures. This fitting further explores the seasonal variations of the zonal momentum flux spectra and the average spectral parameters for each month. Additionally, the GW energy is analyzed using SABER (Sounding of the Atmosphere using Broadband Emission Radiometry) satellite data and compared with the results of the momentum flux spectra from radiosonde data, revealing the close negative correlation between wave energy and wave momentum for stratospheric GW changing with time. The findings indicate that the Gaussian peak shifts more eastward in both the troposphere and stratosphere, primarily due to the absorption of eastward-propagating GWs by the winter tropospheric westerly jet and critical layer filtering. The full width at half maximum (FWHM) in the stratosphere is larger than in the troposphere, especially in June and July, as the spectrum broadens due to propagation effects, filtering, and interactions among waves. The central phase speed in the stratosphere exceeds that in the troposphere, reflecting the influences of Doppler effects and background wind absorption. The momentum flux in the stratosphere is lower than in the troposphere, which is attributed to jet absorption, partial reflection, or the dissipation of GWs. Full article
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19 pages, 8155 KiB  
Article
Comparison of the Water Vapor Budget Evolution of Developing and Non-Developing Disturbances over the Western North Pacific
by Zhihong Sun, Si Gao and Maoqiu Jian
Remote Sens. 2024, 16(13), 2396; https://doi.org/10.3390/rs16132396 - 29 Jun 2024
Viewed by 729
Abstract
Tropical cyclone (TC) genesis prediction remains a major operational challenge. Using multiple satellite datasets and a state-of-the-art reanalysis dataset, this study identifies developing and non-developing tropical disturbances over the western North Pacific from June to November of 2000–2019 and conducts composite analyses of [...] Read more.
Tropical cyclone (TC) genesis prediction remains a major operational challenge. Using multiple satellite datasets and a state-of-the-art reanalysis dataset, this study identifies developing and non-developing tropical disturbances over the western North Pacific from June to November of 2000–2019 and conducts composite analyses of their water vapor budget components and relevant dynamic–thermodynamic parameters in the Lagrangian framework following three-day disturbance tracks. Both groups of disturbances have a similar initial 850 hPa synoptic-scale relative vorticity, while the water vapor budget of developing disturbances exhibits distinct stage-wise evolution characteristics from non-developing cases. Three days prior to TC genesis, developing cases are already associated with significantly higher total precipitable water (TPW), vertically integrated moisture flux convergence (VIMFC), and precipitation, of which TPW is the most important parameter to differentiate two groups of disturbances. One day later, all the water vapor budget components (i.e., TPW, VIMFC, precipitation, and evaporation) strengthened, linked with the enhancement of the mid-to lower-tropospheric vortices. A negative radial gradient of evaporation occurs, suggesting the beginning of the wind−evaporation feedback. On the day prior to TC genesis, the water vapor budget components, as well as the mid-to lower-tropospheric vortices, continue to intensify, eventually leading to TC genesis. By contrast, non-developing disturbances are associated with a drier environment and weaker VIMFC, precipitation, and evaporation during the three-day evolution. All these factors are not favorable for the intensification of the mid-to lower-tropospheric vortices; thus, the disturbances fail to upgrade to TCs. The results may shed light on TC genesis prediction. Full article
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18 pages, 3997 KiB  
Article
Augmentation Method for Weighted Mean Temperature and Precipitable Water Vapor Based on the Refined Air Temperature at 2 m above the Surface of Land from ERA5
by Caiya Yue, Hu Wang and Changhui Xu
Remote Sens. 2024, 16(12), 2055; https://doi.org/10.3390/rs16122055 - 7 Jun 2024
Viewed by 740
Abstract
Due to the difference in the quality of the global assimilation data and the ability to reproduce the real conditions of the atmosphere, the hourly atmospheric temperature at 2 m above the land surface from ERA5 cannot be used with complete confidence for [...] Read more.
Due to the difference in the quality of the global assimilation data and the ability to reproduce the real conditions of the atmosphere, the hourly atmospheric temperature at 2 m above the land surface from ERA5 cannot be used with complete confidence for the atmospheric weighted mean temperature (Tm) calculations and global navigation satellite system (GNSS) precipitable water vapor (PWV) inversion. A systematic and complete refinement method is proposed, including the compensation of elevation matching bias of gridded temperature, correction of fixed-time cusp data fitting and refinement based on the remove-and-restore model. The usability and accuracy improvement of the refined ERA5 2 m atmospheric temperature in the Tm and PWV calculation were validated based on three GNSS stations. The result shows that the average accuracy of the Tm and PWV for the entire region could be increased by 74.4% and 75.1%, respectively. The RMS of the highest station was reduced from 4.28 K to 0.62 K for the Tm and 0.662 mm to 0.203 mm for the PWV, and the RMS of other stations was reduced from 1.25 to 0.44 K for the Tm and 0.211 mm to 0.101 mm for the PWV. This overall refinement method has important implications for atmospheric remote sensing. Full article
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17 pages, 6294 KiB  
Article
Study on the Impact of Urban Morphologies on Urban Canopy Heat Islands Based on Relocated Meteorological Stations
by Tao Shi, Yuanjian Yang and Ping Qi
Remote Sens. 2024, 16(9), 1500; https://doi.org/10.3390/rs16091500 - 24 Apr 2024
Viewed by 881
Abstract
This study addresses a crucial gap in understanding the impact of urban morphologies on the canopy urban heat islands (CUHI) effect. The selection of reference stations lacks a unified standard, and their surface air temperature (SAT) sequences are also inevitably influenced by urbanization. [...] Read more.
This study addresses a crucial gap in understanding the impact of urban morphologies on the canopy urban heat islands (CUHI) effect. The selection of reference stations lacks a unified standard, and their surface air temperature (SAT) sequences are also inevitably influenced by urbanization. However, synchronous observational data from relocated meteorological stations could provide high-quality sample data for studying CUHI. Utilizing remote sensing techniques, the findings of this paper revealed that the observation environment of stations after relocation exhibited remarkable representativeness, with their observation sequences accurately reflecting the local climatic background. The differences in synchronized observation sequences could characterize the CUHI intensity (CUHII). Among the various factors, land use parameters and landscape parameters played particularly significant roles. Furthermore, the fitting performance of the random forest (RF) model for both training and testing data was significantly superior to that of the linear model and support vector regression (SVR) model. Additionally, the influence of local circulation on CUHI could not be overlooked. The mechanisms by which urban morphologies affect CUHII under different circulation backgrounds deserve further investigation. Full article
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20 pages, 6847 KiB  
Article
If Some Critical Regions Achieve Carbon Neutrality, How Will the Global Atmospheric CO2 Concentration Change?
by Jiaying Li, Xiaoye Zhang, Lifeng Guo, Junting Zhong, Deying Wang, Chongyuan Wu and Lifeng Jiang
Remote Sens. 2024, 16(9), 1486; https://doi.org/10.3390/rs16091486 - 23 Apr 2024
Cited by 1 | Viewed by 1122
Abstract
Due to anthropogenic emissions, the global CO2 concentration increases at a rate of approximately 2 ppm per year. With over 130 countries and regions committing to carbon neutrality goals and continuously reducing anthropogenic CO2 emissions, understanding how atmospheric CO2 concentrations [...] Read more.
Due to anthropogenic emissions, the global CO2 concentration increases at a rate of approximately 2 ppm per year. With over 130 countries and regions committing to carbon neutrality goals and continuously reducing anthropogenic CO2 emissions, understanding how atmospheric CO2 concentrations will change globally and in other regions has become an intriguing question. Examining different regions’ efforts to reduce anthropogenic CO2 emissions through atmospheric CO2 observations is also meaningful. We used prior and posterior fluxes to drive the TM5 model. The posterior fluxes were based on the China Carbon Monitoring, Verification and Support System for Global (CCMVS-G), which assimilated the atmospheric CO2 concentration data from ground-based observation and satellite observation. We found that the CO2 concentration obtained using the posterior fluxes was more in line with the actual situation. Then, we presented some experiments to estimate how global and regional CO2 concentrations would change if certain key regions and the whole world achieved net zero emissions of anthropogenic CO2. After removing carbon fluxes from China, North America, and Europe, global CO2 concentrations decreased by around 0.58 ppm, 0.22 ppm, and 0.10 ppm, respectively. The most significant decrease occurred in the regions where fluxes were removed, followed by other areas at the same latitude affected by westerly winds. This indicates that fossil fuel flux is the main factor affecting CO2 concentrations, and that meteorological-driven transportation also significantly impacts CO2 concentrations. Most importantly, using this method, it is possible to quantitatively estimate the impact of achieving carbon neutrality in one region on CO2 concentrations in local regions as well as globally. Full article
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18 pages, 7362 KiB  
Article
Characterizing Smoke Haze Events in Australia Using a Hybrid Approach of Satellite-Based Aerosol Optical Depth and Chemical Transport Modeling
by Miles Sowden, Ivan C. Hanigan, Daniel Jamie Victor Robbins, Martin Cope, Jeremy D. Silver and Julie Noonan
Remote Sens. 2024, 16(7), 1266; https://doi.org/10.3390/rs16071266 - 3 Apr 2024
Cited by 1 | Viewed by 1018
Abstract
Smoke haze events have increasingly affected Australia’s environmental quality, having demonstrable effects on air quality, climate, and public health. This study employs a hybrid methodology, merging satellite-based aerosol optical depth (AOD) data with Chemical Transport Model (CTM) simulations to comprehensively characterize these events. [...] Read more.
Smoke haze events have increasingly affected Australia’s environmental quality, having demonstrable effects on air quality, climate, and public health. This study employs a hybrid methodology, merging satellite-based aerosol optical depth (AOD) data with Chemical Transport Model (CTM) simulations to comprehensively characterize these events. The AOD data are sourced from the Japan Aerospace Exploration Agency (JAXA), Copernicus Atmosphere Monitoring Service (CAMS), and the Commonwealth Scientific and Industrial Research Organization (CSIRO), and they are statistically evaluated using mean, standard deviation, and root mean square error (RMSE) metrics. Our analysis indicates that the combined dataset provides a more robust representation of smoke haze events than individual datasets. Additionally, the study investigates aerosol distribution patterns and data correlation across the blended dataset and discusses possible improvements such as data imputation and aerosol plume scaling. The outcomes of this investigation contribute to enhancing our understanding of the impacts of smoke haze on various environmental factors and can assist in developing targeted mitigation and management strategies. Full article
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16 pages, 8818 KiB  
Article
Increased Warming Efficiencies of Lake Heatwaves Enhance Dryland Lake Warming over China
by Yuchen Wu, Fei Ji, Siyi Wang, Yongli He and Shujuan Hu
Remote Sens. 2024, 16(3), 588; https://doi.org/10.3390/rs16030588 - 4 Feb 2024
Cited by 1 | Viewed by 1138
Abstract
Lake surface water temperature (LSWT) has significantly increased over China and even globally in recent decades due to climate change. However, the responses of LSWTs to climate warming in various climatic regions remain unclear due to the limited lake observations. Satellite-observed LSWT data [...] Read more.
Lake surface water temperature (LSWT) has significantly increased over China and even globally in recent decades due to climate change. However, the responses of LSWTs to climate warming in various climatic regions remain unclear due to the limited lake observations. Satellite-observed LSWT data from the Moderate Resolution Imaging Spectroradiometer (MODIS) dataset were extended using the air2water model. This research aimed to investigate summer LSWT trends across various climatic zones in China, shedding light on the complex interplay between surface air temperatures and LSWT from 1950 to 2020. The results demonstrate robust model performance, with high Nash–Sutcliffe efficiency coefficients, affirming its capability to simulate LSWT variability. Regional disparities in LSWT patterns are identified, revealing notable warming trends in dryland lakes, particularly in central Inner Mongolia. Notably, the study unveils a substantial increase in the intensity and duration of lake heatwaves, especially in semi-arid regions. Dryland lake heatwaves emerge as dominant contributors to intensified LSWT warming, showcasing stronger and longer-lasting events than humid regions. The research highlights a positive feedback loop between lake warming and heatwaves, further amplifying dryland LSWT warming. These findings underscore the vulnerability of dryland lakes to climate change and signal the potential ramifications of increased greenhouse gas concentrations. Full article
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23 pages, 6688 KiB  
Article
Integrated Remote Sensing Observations of Radiative Properties and Sources of the Aerosols in Southeast Asia: The Case of Thailand
by Arika Bridhikitti, Pakorn Petchpayoon and Thayukorn Prabamroong
Remote Sens. 2023, 15(22), 5319; https://doi.org/10.3390/rs15225319 - 10 Nov 2023
Cited by 1 | Viewed by 1174
Abstract
Aerosols in Southeast Asia (SEA) are entangled with complex land–sea–atmosphere–human interactions, and it is difficult for scientists to understand their dynamic behaviors. This study aims to provide an insightful understanding of aerosols across SEA with respect to their radiative properties using several lines [...] Read more.
Aerosols in Southeast Asia (SEA) are entangled with complex land–sea–atmosphere–human interactions, and it is difficult for scientists to understand their dynamic behaviors. This study aims to provide an insightful understanding of aerosols across SEA with respect to their radiative properties using several lines of evidence obtained from remote sensing instruments, including those from onboard Earth observation satellites (MODIS/Terra and MODIS/Aqua, CALIOP/CALIPSO) and from ground-based observation (AERONET). The findings, obtained from cluster analysis of aerosol optical properties, showed seven aerosol types which were dominant across the country, exhibiting diverse radiative forcing potentials. The light-absorbing (prone to warm the atmosphere) aerosols were likely found in mainland SEA, both for background and high-aerosol events. The light-scattering aerosols were associated with aging processes and hygroscopic growth. The neutral potential, which comprised a mixture of oceanic and local anthropogenic aerosols, was predominant in background aerosols in insular SEA. Further studies should focus on carbonaceous aerosols (organic carbons, black carbon, and brown carbon), the aging processes, and the hygroscopic growth of these aerosols, since they play significant roles in the regional aerosol optical properties. Full article
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17 pages, 7223 KiB  
Article
Analysis of Land Surface Temperature Sensitivity to Vegetation in China
by Zhonghua Qian, Yingxiao Sun, Zheng Chen, Fei Ji, Guolin Feng and Qianrong Ma
Remote Sens. 2023, 15(18), 4544; https://doi.org/10.3390/rs15184544 - 15 Sep 2023
Cited by 2 | Viewed by 1798
Abstract
China has emerged as one of the global leaders in greening, achieved through human land use management practices, particularly afforestation projects. However, accurately calculating the energy balance processes of vegetated areas remains challenging because of the complexity of physical mechanisms, parameterization schemes, and [...] Read more.
China has emerged as one of the global leaders in greening, achieved through human land use management practices, particularly afforestation projects. However, accurately calculating the energy balance processes of vegetated areas remains challenging because of the complexity of physical mechanisms, parameterization schemes, and driving dataset used in current research. In this study, we address these challenges by employing moving window methods in space inspired by “space-for-time”. This approach allows us to eliminate the influence of climate signals on vegetation development over long periods and determine the sensitivity of seasonal contributions of Land Surface Temperature (LST) to Leaf Area Index (LAI) in China from 2001 to 2018. Our findings reveal that the sensitivity of LST to LAI in the climatology period is approximately −0.085 K·m2·m2, indicating a cooling effect. Moreover, the climatological trend remains negative, suggesting that Chinese vegetation greening is playing an increasingly important role in cooling the land surface. Considering the energy balance equation, we further investigate the underlying mechanisms. It is observed that the radiative feedback consistently contributes positively, while the non-radiative feedback always exerts a negative influence on the sensitivity. These results provide valuable insights into the complex interactions between vegetation greening and land surface temperature in China, providing informed land management and climate adaptation strategies. Understanding these trends and mechanisms is essential for sustainable and effective environmental planning and decision making. Full article
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16 pages, 5346 KiB  
Article
An ENSO Prediction Model Based on Backtracking Multiple Initial Values: Ordinary Differential Equations–Memory Kernel Function
by Qianrong Ma, Yingxiao Sun, Shiquan Wan, Yu Gu, Yang Bai and Jiayi Mu
Remote Sens. 2023, 15(15), 3767; https://doi.org/10.3390/rs15153767 - 28 Jul 2023
Viewed by 1378
Abstract
This article presents a new prediction model, the ordinary differential equations–memory kernel function (ODE–MKF), constructed from multiple backtracking initial values (MBIV). The model is similar to a simplified numerical model after spatial dimension reduction and has both nonlinear characteristics and the low-cost advantage [...] Read more.
This article presents a new prediction model, the ordinary differential equations–memory kernel function (ODE–MKF), constructed from multiple backtracking initial values (MBIV). The model is similar to a simplified numerical model after spatial dimension reduction and has both nonlinear characteristics and the low-cost advantage of a time series model. The ODE–MKF focuses on utilizing more temporal information and includes machine learning to solve complex mathematical inverse problems to establish a predictive model. This study first validates the feasibility of the ODE–MKF via experiments using the Lorenz system. The results demonstrate that the ODE–MKF prediction model could describe the nonlinear characteristics of complex systems and exhibited ideal predictive robustness. The prediction of the El Niño-Southern Oscillation (ENSO) index further demonstrates its effectiveness, as it achieved 24-month lead predictions and effectively improved nonlinear problems. Furthermore, the reliability of the model was also tested, and approximately 18 months of prediction were achieved, which was verified with the Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) radiation fluxes. The short-term memory index Southern Oscillation (SO) was further used to examine the applicability of ODE–MKF. A six-month lead prediction of the SO trend was achieved, indicating that the predictability of complex systems is related to their inherent memory scales. Full article
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