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Special Issue "Climate and Environmental Changes Monitored by Satellite Remote Sensing III"

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

Deadline for manuscript submissions: 15 December 2023 | Viewed by 1736

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Special Issue Editors

Dr. Hainan Gong

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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
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Peng Zhang

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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
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Dr. Luca Lelli

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Guest Editor

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

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

Related Special Issue

Climate and Environmental Changes Monitored by Satellite Remote Sensing II in Remote Sensing (10 articles)

Published Papers (3 papers)

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Research

23 pages, 6688 KiB

Open AccessArticle

Integrated Remote Sensing Observations of Radiative Properties and Sources of the Aerosols in Southeast Asia: The Case of Thailand

Arika Bridhikitti

Pakorn Petchpayoon

and

Thayukorn Prabamroong

Remote Sens. 2023, 15(22), 5319; https://doi.org/10.3390/rs15225319 - 10 Nov 2023

Viewed by 423

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 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

(This article belongs to the Special Issue Climate and Environmental Changes Monitored by Satellite Remote Sensing III)

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17 pages, 7223 KiB

Open AccessArticle

Analysis of Land Surface Temperature Sensitivity to Vegetation in China

and

Remote Sens. 2023, 15(18), 4544; https://doi.org/10.3390/rs15184544 - 15 Sep 2023

Viewed by 513

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 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 \cdot m^{2} \cdot m^{- 2}

, 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

(This article belongs to the Special Issue Climate and Environmental Changes Monitored by Satellite Remote Sensing III)

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16 pages, 5346 KiB

Open AccessArticle

An ENSO Prediction Model Based on Backtracking Multiple Initial Values: Ordinary Differential Equations–Memory Kernel Function

and

Remote Sens. 2023, 15(15), 3767; https://doi.org/10.3390/rs15153767 - 28 Jul 2023

Viewed by 565

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 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

(This article belongs to the Special Issue Climate and Environmental Changes Monitored by Satellite Remote Sensing III)

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Special Issue "Climate and Environmental Changes Monitored by Satellite Remote Sensing III"

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