scholarly journals Complex Principal Component Analysis of Mass Balance Change on Qinghai-Tibet Plateau

2016 ◽  
Author(s):  
Jingang Zhan ◽  
Hongling Shi ◽  
Yong Wang ◽  
Yixin Yao
Keyword(s):  
Climate Change ◽  
Mass Balance ◽  
El Niño ◽  
Indian Monsoon ◽  
El Nino ◽  
Principal Component ◽  
Mass Gain ◽  
Tibet Plateau ◽  
Major Influence ◽  
Qinghai Tibet Plateau

Abstract. Abstract. This paper analyzes the spatial characteristics of mass balance change on the Qinghai-Tibet Plateau and surrounding areas, using 153 monthly solutions of temporal gravity data from the Gravity Recovery and Climate Experiment(in this case GRACE) satellite. Spatial mode characteristics and phase information of mass balance change are analyzed using complex principal component analysis (in this case CPCA). Information on time-frequency change of major components is analyzed using the wavelet amplitude-period spectrum. The results show that the mass balance change on the plateau is influenced by various atmospheric circulations and there are obvious systemic differences, namely, glacial fluctuation of the Himalayas area was mainly influenced by the weakening Indian monsoon, El Niño and East Asian monsoon. There were drastic changes of glacier mass gain and loss balance. Apart from the Indian monsoon and El Niño affected on mass balance in inland areas of the plateau, the northern parts of the plateau was also affected by the westerlies and there was a positive mass balance, with mass gain exceeding loss. The Pamirs and the Karakoram Range areas are influenced not only by the Indian monsoon and westerlies but also by the climate change of El Niño and La Niña, and mass change shows a weak mass balanced. The major influence on the change of mass balance on the Qinghai-Tibet Plateau was the weakening Indian monsoon, which was responsible for 54.0 % of that change. Because El Niño is strengthening, it has recently become the second major factor affecting the change of mass balance, responsible for 16.3 % of that change. The third major influence was the westerlies and of La Niña-related climate change, accounting for 5.6 % of the mass balance change.

scholarly journals Complex principal component analysis of mass balance changes on the Qinghai–Tibetan Plateau

2017 ◽  
Vol 11 (3) ◽  
pp. 1487-1499 ◽  
Author(s):  
Jingang Zhan ◽  
Hongling Shi ◽  
Yong Wang ◽  
Yixin Yao
Keyword(s):  
Tibetan Plateau ◽  
Mass Balance ◽  
Correlation Coefficient ◽  
El Niño ◽  
El Nino ◽  
Principal Component ◽  
Mass Change ◽  
Eastern Himalayas ◽  
The Third ◽  
Northwestern India

Abstract. Climatic time series for Qinghai–Tibetan Plateau locations are rare. Although glacier shrinkage is well described, the relationship between mass balance and climatic variation is less clear. We studied the effect of climate changes on mass balance by analyzing the complex principal components of mass changes during 2003–2015 using Gravity Recovery and Climate Experiment satellite data. Mass change in the eastern Himalayas, Karakoram, Pamirs, and northwestern India was most sensitive to variation in the first principal component, which explained 54 % of the change. Correlation analysis showed that the first principal component is related to the Indian monsoon and the correlation coefficient is 0.83. Mass change on the eastern Qinghai plateau, eastern Himalayas–Qiangtang Plateau–Pamirs area and northwestern India was most sensitive to variation of the second major factor, which explained 16 % of the variation. The second major component is associated with El Niño; the correlation coefficient was 0.30 and this exceeded the 95 % confidence interval of 0.17. Mass change on the western and northwestern Qinghai–Tibetan Plateau was most sensitive to the variation of its third major component, responsible for 6 % of mass balance change. The third component may be associated with climate change from the westerlies and La Niña. The third component and El Niño have similar signals of 6.5 year periods and opposite phases. We conclude that El Niño now has the second largest effect on mass balance change of this region, which differs from the traditional view that the westerlies are the second largest factor.

VARIABILIDAD CLIMÁTICA, CAMBIO CLIMÁTICO Y PESQUERÍAS EN EL ECUADOR.

2012 ◽  
Vol 1 (1) ◽  
Author(s):  
Johnny Chavarría Viteri ◽  
Dennis Tomalá Solano
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Pacific Decadal Oscillation ◽  
El Niño ◽  
El Nino ◽  
Southern Oscillation ◽  
El Niño Southern Oscillation ◽  
El Nino Southern Oscillation ◽  
Current Action ◽  
Palabras Clave

La variabilidad climática es la norma que ha modulado la vida en el planeta. Este trabajo demuestra que las pesquerías y acuicultura costera ecuatorianas no son la excepción, puesto que tales actividades están fuertemente influenciadas por la variabilidad ENSO (El Niño-Oscilación del Sur) y PDO (Oscilación Decadal del Pacífico), planteándose que la señal del cambio climático debe contribuir a esta influencia. Se destaca también que, en el análisis de los efectos de la variabilidad climática sobre los recursos pesqueros, el esfuerzo extractivo también debe ser considerado. Por su parte, la acción actual de la PDO está afectando la señal del cambio climático, encontrándose actualmente en fases opuestas. Se espera que estas señales entren en fase a finales de esta década, y principalmente durante la década de los 20 y consecuentemente se evidencien con mayor fuerza los efectos del Cambio Climático. Palabras Clave: Variabilidad Climática, Cambio Climático, ENSO, PDO, Pesquerías, Ecuador. ABSTRACT Climate variability is the standard that has modulated life in the planet. This work shows that the Ecuadorian  fisheries and aquaculture are not the exception, since such activities are strongly influenced by ENSO variability (El Niño - Southern Oscillation) and PDO (Pacific Decadal Oscillation), considering that the signal of climate change should contribute to this influence. It also emphasizes that in the analysis of the effects of climate variability on the fishing resources, the extractive effort must also be considered. For its part, the current action of the PDO is affecting the signal of climate change, now found on opposite phases. It is hoped that these signals come into phase at the end of this decade, and especially during the decade of the 20’s and more strongly evidencing the effects of climate change. Keywords: Climate variability, climate change, ENSO (El Niño - Southern Oscillation) and PDO  (Pacific Decadal Oscillation); fisheries, Ecuador. Recibido: mayo, 2012Aprobado: agosto, 2012

scholarly journals Quantifying the Variability of Forest Ecosystem Vulnerability in the Largest Water Tower Region Globally

2021 ◽  
Vol 18 (14) ◽  
pp. 7529
Author(s):  
Siqi Sun ◽  
Yihe Lü ◽  
Da Lü ◽  
Cong Wang
Keyword(s):  
Forest Ecosystems ◽  
Human Impacts ◽  
Regional Scale ◽  
Principal Component ◽  
Tibet Plateau ◽  
Slope Aspect ◽  
Environmental Disturbances ◽  
Restoration Planning ◽  
Development Goals ◽  
Qinghai Tibet Plateau

Forests are critical ecosystems for environmental regulation and ecological security maintenance, especially at high altitudes that exhibit sensitivity to climate change and human activities. The Qinghai-Tibet Plateau—the world’s largest water tower region—has been breeding many large rivers in Asia where forests play important roles in water regulation and water quality improvement. However, the vulnerability of these forest ecosystems at the regional scale is still largely unknown. Therefore, the aim of this research is to quantitatively assess the temporal–spatial variability of forest vulnerability on the Qinghai-Tibet Plateau to illustrate the capacity of forests to withstand disturbances. Geographic information system (GIS) and the spatial principal component analysis (SPCA) were used to develop a forest vulnerable index (FVI) to assess the vulnerability of forest ecosystems. This research incorporates 15 factors covering the natural context, environmental disturbances, and socioeconomic impact. Results indicate that the measure of vulnerability was unevenly distributed spatially across the study area, and the whole trend has intensified since 2000. The three factors that contribute the most to the vulnerability of natural contexts, environmental disturbances, and human impacts are slope aspect, landslides, and the distance to the farmland, respectively. The vulnerability is higher in forest areas with lower altitudes, steeper slopes, and southerly directions. These evaluation results can be helpful for forest management in high altitude water tower regions in the forms of forest conservation or restoration planning and implementation towards sustainable development goals.

scholarly journals Spatial and Temporal Differences in Alpine Meadow, Alpine Steppe and All Vegetation of the Qinghai-Tibetan Plateau and Their Responses to Climate Change

2021 ◽  
Vol 13 (4) ◽  
pp. 669
Author(s):  
Hanchen Duan ◽  
Xian Xue ◽  
Tao Wang ◽  
Wenping Kang ◽  
Jie Liao ◽  
...  
Keyword(s):  
Climate Change ◽  
Alpine Meadow ◽  
Global Climate ◽  
Growing Season ◽  
Tibet Plateau ◽  
Vegetation Types ◽  
Analysis Method ◽  
Alpine Steppe ◽  
Qinghai Tibet Plateau ◽  
Variation Trends

Alpine meadow and alpine steppe are the two most widely distributed nonzonal vegetation types in the Qinghai-Tibet Plateau. In the context of global climate change, the differences in spatial-temporal variation trends and their responses to climate change are discussed. It is of great significance to reveal the response of the Qinghai-Tibet Plateau to global climate change and the construction of ecological security barriers. This study takes alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau as the research objects. The normalized difference vegetation index (NDVI) data and meteorological data were used as the data sources between 2000 and 2018. By using the mean value method, threshold method, trend analysis method and correlation analysis method, the spatial and temporal variation trends in the alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau were compared and analyzed, and their differences in the responses to climate change were discussed. The results showed the following: (1) The growing season length of alpine meadow was 145~289 d, while that of alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau was 161~273 d, and their growing season lengths were significantly shorter than that of alpine meadow. (2) The annual variation trends of the growing season NDVI for the alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau increased obviously, but their fluctuation range and change rate were significantly different. (3) The overall vegetation improvement in the Qinghai-Tibet Plateau was primarily dominated by alpine steppe and alpine meadow, while the degradation was primarily dominated by alpine meadow. (4) The responses between the growing season NDVI and climatic factors in the alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau had great spatial heterogeneity in the Qinghai-Tibet Plateau. These findings provide evidence towards understanding the characteristics of the different vegetation types in the Qinghai-Tibet Plateau and their spatial differences in response to climate change.

scholarly journals Climate Change Implications Found in Winter Extreme Sea Level Height Records around Korea

2021 ◽  
Vol 9 (4) ◽  
pp. 377
Author(s):  
Dong Eun Lee ◽  
Jaehee Kim ◽  
Yujin Heo ◽  
Hyunjin Kang ◽  
Eun Young Lee
Keyword(s):  
Climate Change ◽  
Thermal Expansion ◽  
Sea Level ◽  
El Niño ◽  
El Nino ◽  
Winter Season ◽  
Storm Tracks ◽  
Daily Maximum ◽  
The Impact ◽  
Level Height

The impact of climatic variability in atmospheric conditions on coastal environments accompanies adjustments in both the frequency and intensity of coastal storm surge events. The top winter season daily maximum sea level height events at 20 tidal stations around South Korea were examined to assess such impact of winter extratropical cyclone variability. As the investigation focusses on the most extreme sea level events, the impact of climate change is found to be invisible. It is revealed that the measures of extreme sea level events—frequency and intensity—do not correlate with the local sea surface temperature anomalies. Meanwhile, the frequency of winter extreme events exhibits a clear association with the concurrent climatic indices. It was determined that the annual frequency of the all-time top 5% winter daily maximum sea level events significantly and positively correlates with the NINO3.4 and Pacific Decadal Oscillation (PDO) indices at the majority of the 20 tidal stations. Hence, this indicates an increase in extreme event frequency and intensity, despite localized temperature cooling. This contradicts the expectation of increases in local extreme sea level events due to thermal expansion and global climate change. During El Nino, it is suggested that northward shifts of winter storm tracks associated with El Nino occur, disturbing the sea level around Korea more often. The current dominance of interannual storm track shifts, due to climate variability, over the impact of slow rise on the winter extreme sea level events, implies that coastal extreme sea level events will change through changes in the mechanical drivers rather than thermal expansion. The major storm tracks are predicted to continue shifting northward. The winter extreme sea level events in the midlatitude coastal region might not go through a monotonic change. They are expected to occur more often and more intensively in the near future, but might not continue doing so when northward shifting storm tracks move away from the marginal seas around Korea, as is predicted by the end of the century.

Spatial variability of topsoil δ13C across Qinghai-Tibet Plateau

2021 ◽  
Author(s):  
Yunsen Lai ◽  
Shaoda Li ◽  
Xiaolu Tang ◽  
Xinrui Luo ◽  
Liang Liu ◽  
...  
Keyword(s):  
Climate Change ◽  
Machine Learning ◽  
Spatial Variability ◽  
Soil Carbon ◽  
Tibet Plateau ◽  
Learning Approach ◽  
Carbon Turnover ◽  
Machine Learning Approach ◽  
Qinghai Tibet Plateau ◽  
Soil Carbon Turnover

<p>Soil carbon isotopes (δ<sup>13</sup>C) provide reliable insights at the long-term scale for the study of soil carbon turnover and topsoil δ<sup>13</sup>C could well reflect organic matter input from the current vegetation. Qinghai-Tibet Plateau (QTP) is called “the third pole of the earth” because of its high elevation, and it is one of the most sensitive and critical regions to global climate change worldwide. Previous studies focused on variability of soil δ<sup>13</sup>C at in-site scale. However, a knowledge gap still exists in the spatial pattern of topsoil δ<sup>13</sup>C in QTP. In this study, we first established a database of topsoil δ<sup>13</sup>C with 396 observations from published literature and applied a Random Forest (RF) algorithm (a machine learning approach) to predict the spatial pattern of topsoil δ<sup>13</sup>C using environmental variables. Results showed that topsoil δ<sup>13</sup>C significantly varied across different ecosystem types (p < 0.05).  Topsoil δ<sup>13</sup>C was -26.3 ± 1.60 ‰ for forest, 24.3 ± 2.00 ‰ for shrubland, -23.9 ± 1.84 ‰ for grassland, -18.9 ± 2.37 ‰ for desert, respectively. RF could well predict the spatial variability of topsoil δ<sup>13</sup>C with a model efficiency (pseudo R<sup>2</sup>) of 0.65 and root mean square error of 1.42. The gridded product of topsoil δ<sup>13</sup>C and topsoil β (indicating the decomposition rate of soil organic carbon, calculated by δ<sup>13</sup>C divided by logarithmically converted SOC) with a spatial resolution of 1000 m were developed. Strong spatial variability of topsoil δ<sup>13</sup>C was observed, which increased gradually from the southeast to the northwest in QTP. Furthermore, a large variation was found in β, ranging from -7.87 to -81.8, with a decreasing trend from southeast to northwest, indicating that carbon turnover rate was faster in northwest QTP compared to that of southeast. This study was the first attempt to develop a fine resolution product of topsoil δ<sup>13</sup>C for QTP using a machine learning approach, which could provide an independent benchmark for biogeochemical models to study soil carbon turnover and terrestrial carbon-climate feedbacks under ongoing climate change.</p>

scholarly journals Global warming in Amazonia: impacts and Mitigation

2009 ◽  
Vol 39 (4) ◽  
pp. 1003-1011 ◽  
Author(s):  
Philip Martin Fearnside
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Forest Fires ◽  
El Niño ◽  
El Nino ◽  
Cost Effective ◽  
Climatic Conditions ◽  
Carbon Accounting ◽  
Amazon Forest ◽  
Temperature Oscillations

Global warming has potentially catastrophic impacts in Amazonia, while at the same time maintenance of the Amazon forest offers one of the most valuable and cost-effective options for mitigating climate change. We know that the El Niño phenomenon, caused by temperature oscillations of surface water in the Pacific, has serious impacts in Amazonia, causing droughts and forest fires (as in 1997-1998). Temperature oscillations in the Atlantic also provoke severe droughts (as in 2005). We also know that Amazonian trees die both from fires and from water stress under hot, dry conditions. In addition, water recycled through the forest provides rainfall that maintains climatic conditions appropriate for tropical forest, especially in the dry season. What we need to know quickly, through intensified research, includes progress in representing El Niño and the Atlantic oscillations in climatic models, representation of biotic feedbacks in models used for decision-making about global warming, and narrowing the range of estimating climate sensitivity to reduce uncertainty about the probability of very severe impacts. Items that need to be negotiated include the definition of "dangerous" climate change, with the corresponding maximum levels of greenhouse gases in the atmosphere. Mitigation of global warming must include maintaining the Amazon forest, which has benefits for combating global warming from two separate roles: cutting the flow the emissions of carbon each year from the rapid pace of deforestation, and avoiding emission of the stock of carbon in the remaining forest that can be released by various ways, including climate change itself. Barriers to rewarding forest maintenance include the need for financial rewards for both of these roles. Other needs are for continued reduction of uncertainty regarding emissions and deforestation processes, as well as agreement on the basis of carbon accounting. As one of the countries most subject to impacts of climate change, Brazil must assume the leadership in fighting global warming.

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