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description Publicationkeyboard_double_arrow_right Article , Journal , Other literature type 2020Publisher:MDPI AG Pengfei Zhan; Chunqiao Song; Jida Wang; Wenkai Li; Linghong Ke; Kai Liu; Tan Chen;doi: 10.3390/rs12182986
Inland lakes in the Tibetan Plateau (TP) with closed catchments and minimal human disturbance are an important indicator of climate change. However, the examination of changes in the spatiotemporal patterns of Tibetan lakes, especially water level variations, is limited due to inadequate access to measurements. This obstacle has been improved by the development of satellite altimetry observations. The more recent studies revealed that the trend of central TP to grow decreased or reversed between 2010 and 2016. However, thus far, this trend has not been investigated to determine whether this pattern would last for the following years. This study aims to combine the traditional (launched before 2010, e.g., TOPEX/POSEIDON, ERS-1, ERS-2, Jason-1/-2, and Envisat) and recently advanced (launched after 2010, e.g., SARAL and Sentinel-3) altimetry observations to understand the Tibetan lake changes further in recent years. Therefore, we acquired information on the continuous lake level changes in Tibetan lakes using the lake level sequence integration method based on multisource altimetry satellites. The results revealed that water level changes in 22 examined lakes showed abrupt rises in 2016–2018, but the onsets and magnitudes of the rises varied among the lakes. During the study period, the water levels of the lakes (except Nam Co) revealed a drastic rising tendency with a mean rate of 0.74 m/a, which was remarkably higher than the average rate of water level rise over the period 2010–2015 (approximately 0.28 m/a). Specifically, the water level of the nine lakes in the Northern TP (NTP) displayed a significant rising trend, with an average rate of 0.82 m/a. In the Central TP (CTP), the lake level changes were generally divided into two categories. The water levels for the lakes in the Western CTP rose rapidly, while, in the Eastern CTP, the lake water levels rose slowly, with an average rising rate less than 0.40 m/a. The water levels for the lakes in the Northeastern TP (NETP) and Northwestern TP (NWTP) kept a stable rising tendency. According to the results of the climate analysis, the spatial differences of the lake level rise rates were primarily caused by the spatial and temporal changes of precipitation over the TP.
Remote Sensing arrow_drop_down Remote SensingOther literature type . 2020License: CC BYFull-Text: http://www.mdpi.com/2072-4292/12/18/2986/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.more_vert Remote Sensing arrow_drop_down Remote SensingOther literature type . 2020License: CC BYFull-Text: http://www.mdpi.com/2072-4292/12/18/2986/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.description Publicationkeyboard_double_arrow_right Article , Other literature type 2024Publisher:Springer Science and Business Media LLC Kebin Cheng; Haitao Yang; Shengli Tao; Yanjun Su; Haijing Guan; Yu Ren; Tianyu Hu; Wenkai Li; Guang-Hui Xu; Mengxi Chen; Xin-Shi Lu; Zekun Yang; Yanhong Tang; Keping Ma; Jingyun Fang; Qinghua Guo;pmid: 38750031
pmc: PMC11096308
AbstractChina’s extensive planted forests play a crucial role in carbon storage, vital for climate change mitigation. However, the complex spatiotemporal dynamics of China’s planted forest area and its carbon storage remain uncaptured. Here we reveal such changes in China’s planted forests from 1990 to 2020 using satellite and field data. Results show a doubling of planted forest area, a trend that intensified post-2000. These changes lead to China’s planted forest carbon storage increasing from 675.6 ± 12.5 Tg C in 1990 to 1,873.1 ± 16.2 Tg C in 2020, with an average rate of ~ 40 Tg C yr−1. The area expansion of planted forests contributed ~ 53% (637.2 ± 5.4 Tg C) of the total above increased carbon storage in planted forests compared with planted forest growth. This proactive policy-driven expansion of planted forests has catalyzed a swift increase in carbon storage, aligning with China’s Carbon Neutrality Target for 2060.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.description Publicationkeyboard_double_arrow_right Article , Journal , Other literature type 2017 Hong Kong, China (People's Republic of), China (People's Republic of)Publisher:MDPI AG Authors: Linghong Ke; Xiaoli Ding; Wenkai Li; Bo Qiu;doi: 10.3390/rs9020114
handle: 10397/67341
The widely distributed glaciers over the Qinghai-Tibet Plateau (QTP) represent important freshwater reserves and the meltwater feeds many major rivers of Asia. Glacier change over the QTP has shown high temporal and spatial variability in recent decades, and the driving forces of the variability are not yet clear. This study examines the area and thickness change of glaciers in the Dongkemadi (DKMD) region over central QTP by exploring all available Landsat images from 1976 to 2013 and satellite altimetry data over 2003–2008, and then analyzes the relationships between glacier variation and local and macroscale climate factors based on various remote sensing and re-analysis data. Results show that the variation of glacier area over 1976–2013 is characterized by significant shrinkage at a linear rate of −0.31 ± 0.04 km2·year−1. Glacier retreat slightly accelerated in the 2000s, and the mean glacier surface elevation lowered at a rate of −0.56 m·year−1 over 2003–2008. During the past 38 years, glacier change in the DKMD area was dominated by the variation of mean annual temperature, and was influenced by the state of the North Atlantic Oscillation (NAO). The mechanism linking climate variability over the central QTP and the state of NAO is most likely via changes in the strength of westerlies and Siberian High. We found no evidence supporting the role of summer monsoons (Indian summer monsoon and East Asian monsoon) in driving local climate and glacier changes. In addition, El Niño Southern Oscillation (ENSO) may be associated with the extreme weather (snow storm) in October 1986 and 2000 which might have led to significant glacier expansion in the following years. Further research is needed to better understand the physical mechanisms linking NAO, ENSO and climate variability over the mid-latitude central QTP.
Remote Sensing arrow_drop_down Remote SensingOther literature type . 2017License: CC BYFull-Text: http://www.mdpi.com/2072-4292/9/2/114/pdfData sources: Multidisciplinary Digital Publishing InstituteHong Kong Polytechnic University: PolyU Institutional Repository (PolyU IR)Article . 2017License: CC BYFull-Text: http://hdl.handle.net/10397/67341Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.more_vert Remote Sensing arrow_drop_down Remote SensingOther literature type . 2017License: CC BYFull-Text: http://www.mdpi.com/2072-4292/9/2/114/pdfData sources: Multidisciplinary Digital Publishing InstituteHong Kong Polytechnic University: PolyU Institutional Repository (PolyU IR)Article . 2017License: CC BYFull-Text: http://hdl.handle.net/10397/67341Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.
description Publicationkeyboard_double_arrow_right Article , Journal , Other literature type 2020Publisher:MDPI AG Pengfei Zhan; Chunqiao Song; Jida Wang; Wenkai Li; Linghong Ke; Kai Liu; Tan Chen;doi: 10.3390/rs12182986
Inland lakes in the Tibetan Plateau (TP) with closed catchments and minimal human disturbance are an important indicator of climate change. However, the examination of changes in the spatiotemporal patterns of Tibetan lakes, especially water level variations, is limited due to inadequate access to measurements. This obstacle has been improved by the development of satellite altimetry observations. The more recent studies revealed that the trend of central TP to grow decreased or reversed between 2010 and 2016. However, thus far, this trend has not been investigated to determine whether this pattern would last for the following years. This study aims to combine the traditional (launched before 2010, e.g., TOPEX/POSEIDON, ERS-1, ERS-2, Jason-1/-2, and Envisat) and recently advanced (launched after 2010, e.g., SARAL and Sentinel-3) altimetry observations to understand the Tibetan lake changes further in recent years. Therefore, we acquired information on the continuous lake level changes in Tibetan lakes using the lake level sequence integration method based on multisource altimetry satellites. The results revealed that water level changes in 22 examined lakes showed abrupt rises in 2016–2018, but the onsets and magnitudes of the rises varied among the lakes. During the study period, the water levels of the lakes (except Nam Co) revealed a drastic rising tendency with a mean rate of 0.74 m/a, which was remarkably higher than the average rate of water level rise over the period 2010–2015 (approximately 0.28 m/a). Specifically, the water level of the nine lakes in the Northern TP (NTP) displayed a significant rising trend, with an average rate of 0.82 m/a. In the Central TP (CTP), the lake level changes were generally divided into two categories. The water levels for the lakes in the Western CTP rose rapidly, while, in the Eastern CTP, the lake water levels rose slowly, with an average rising rate less than 0.40 m/a. The water levels for the lakes in the Northeastern TP (NETP) and Northwestern TP (NWTP) kept a stable rising tendency. According to the results of the climate analysis, the spatial differences of the lake level rise rates were primarily caused by the spatial and temporal changes of precipitation over the TP.
Remote Sensing arrow_drop_down Remote SensingOther literature type . 2020License: CC BYFull-Text: http://www.mdpi.com/2072-4292/12/18/2986/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.more_vert Remote Sensing arrow_drop_down Remote SensingOther literature type . 2020License: CC BYFull-Text: http://www.mdpi.com/2072-4292/12/18/2986/pdfData sources: Multidisciplinary Digital Publishing Instituteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.description Publicationkeyboard_double_arrow_right Article , Other literature type 2024Publisher:Springer Science and Business Media LLC Kebin Cheng; Haitao Yang; Shengli Tao; Yanjun Su; Haijing Guan; Yu Ren; Tianyu Hu; Wenkai Li; Guang-Hui Xu; Mengxi Chen; Xin-Shi Lu; Zekun Yang; Yanhong Tang; Keping Ma; Jingyun Fang; Qinghua Guo;pmid: 38750031
pmc: PMC11096308
AbstractChina’s extensive planted forests play a crucial role in carbon storage, vital for climate change mitigation. However, the complex spatiotemporal dynamics of China’s planted forest area and its carbon storage remain uncaptured. Here we reveal such changes in China’s planted forests from 1990 to 2020 using satellite and field data. Results show a doubling of planted forest area, a trend that intensified post-2000. These changes lead to China’s planted forest carbon storage increasing from 675.6 ± 12.5 Tg C in 1990 to 1,873.1 ± 16.2 Tg C in 2020, with an average rate of ~ 40 Tg C yr−1. The area expansion of planted forests contributed ~ 53% (637.2 ± 5.4 Tg C) of the total above increased carbon storage in planted forests compared with planted forest growth. This proactive policy-driven expansion of planted forests has catalyzed a swift increase in carbon storage, aligning with China’s Carbon Neutrality Target for 2060.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.description Publicationkeyboard_double_arrow_right Article , Journal , Other literature type 2017 Hong Kong, China (People's Republic of), China (People's Republic of)Publisher:MDPI AG Authors: Linghong Ke; Xiaoli Ding; Wenkai Li; Bo Qiu;doi: 10.3390/rs9020114
handle: 10397/67341
The widely distributed glaciers over the Qinghai-Tibet Plateau (QTP) represent important freshwater reserves and the meltwater feeds many major rivers of Asia. Glacier change over the QTP has shown high temporal and spatial variability in recent decades, and the driving forces of the variability are not yet clear. This study examines the area and thickness change of glaciers in the Dongkemadi (DKMD) region over central QTP by exploring all available Landsat images from 1976 to 2013 and satellite altimetry data over 2003–2008, and then analyzes the relationships between glacier variation and local and macroscale climate factors based on various remote sensing and re-analysis data. Results show that the variation of glacier area over 1976–2013 is characterized by significant shrinkage at a linear rate of −0.31 ± 0.04 km2·year−1. Glacier retreat slightly accelerated in the 2000s, and the mean glacier surface elevation lowered at a rate of −0.56 m·year−1 over 2003–2008. During the past 38 years, glacier change in the DKMD area was dominated by the variation of mean annual temperature, and was influenced by the state of the North Atlantic Oscillation (NAO). The mechanism linking climate variability over the central QTP and the state of NAO is most likely via changes in the strength of westerlies and Siberian High. We found no evidence supporting the role of summer monsoons (Indian summer monsoon and East Asian monsoon) in driving local climate and glacier changes. In addition, El Niño Southern Oscillation (ENSO) may be associated with the extreme weather (snow storm) in October 1986 and 2000 which might have led to significant glacier expansion in the following years. Further research is needed to better understand the physical mechanisms linking NAO, ENSO and climate variability over the mid-latitude central QTP.
Remote Sensing arrow_drop_down Remote SensingOther literature type . 2017License: CC BYFull-Text: http://www.mdpi.com/2072-4292/9/2/114/pdfData sources: Multidisciplinary Digital Publishing InstituteHong Kong Polytechnic University: PolyU Institutional Repository (PolyU IR)Article . 2017License: CC BYFull-Text: http://hdl.handle.net/10397/67341Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.more_vert Remote Sensing arrow_drop_down Remote SensingOther literature type . 2017License: CC BYFull-Text: http://www.mdpi.com/2072-4292/9/2/114/pdfData sources: Multidisciplinary Digital Publishing InstituteHong Kong Polytechnic University: PolyU Institutional Repository (PolyU IR)Article . 2017License: CC BYFull-Text: http://hdl.handle.net/10397/67341Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.
