Temperature variation and abrupt change analysis in the Three-River Headwaters Region during 1961–2010

Yi, Xiangsheng; Li, Guosheng; Yin, Yanyu

doi:10.1007/s11442-012-0939-9

Cited by 37 publications

(21 citation statements)

References 19 publications

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“…The highest mountain range is the "Third Pole" or Tibetan Plateau in western China, from where several major rivers of Asia originate, such as Mekong, Brahmaputra, Yangtze and Yellow rivers [47,48]. Species richness in China contributes about one-eighth of all species on Earth [49].…”

Section: Ecological Settingmentioning

confidence: 99%

Spatial-Temporal Dynamics of China’s Terrestrial Biodiversity: A Dynamic Habitat Index Diagnostic

et al. 2016

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Biodiversity in China is analyzed based on the components of the Dynamic Habitat Index (DHI). First, observed field survey based spatial patterns of species richness including threatened species are presented to test their linear relationship with remote sensing based DHI (2001( -2010. Areas with a high cumulative DHI component are associated with relatively high species richness, and threatened species richness increases in regions with frequently varying levels of the cumulative DHI component. The analysis of geographical and statistical distributions yields the following results on interdependence, polarization and change detection: (1) The decadal mean Cumulative Annual Productivity (DHI-cum < 4) in Northwest China and (DHI-cum > 4) in Southeast China are in a stable (positive) relation to the Minimum Annual Apparent Cover (DHI-min) and is positively (negatively) related to the Seasonal Variation of Greenness (DHI-sea); (2) The decadal tendencies show bimodal frequency distributions aligned near DHI-min~0.05 and DHI-sea~0.5 which separated by zero slopes; that is, regions with both small DHI-min and DHI-sea are becoming smaller and vice versa; (3) The decadal tendencies identify regions of land-cover change (as revealed in previous research). That is, the relation of strong and significant tendencies of the three DHI components with climatic or anthropogenic induced changes provides useful information for conservation planning. These results suggest that the spatial-temporal dynamics of China's terrestrial species and threatened species richness needs to be monitored by first and second moments of remote sensing based information of the DHI.

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Section: Ecological Settingmentioning

confidence: 99%

Spatial-Temporal Dynamics of China’s Terrestrial Biodiversity: A Dynamic Habitat Index Diagnostic

et al. 2016

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“…This region has been given the name 'Chinese water tower', and is a mosaic transition zone of seasonal frozen ground and areas of discontinuous and continuous permafrost. In recent years, the trends in many climate parameters, including temperature, rainfall, evaporation, relative humidity and wind speed have been studied in the TRSR because this region is particularly sensitive to the impacts of climate change (You et al 2008, 2014, Yi et al 2011, Guo & Wang 2012, Xu et al 2012. Meteorological data has demonstrated that air temperatures in the TRSR have been rising at an average rate of 0.32°C decade −1 for the past half century (Yi et al 2011.…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, the trends in many climate parameters, including temperature, rainfall, evaporation, relative humidity and wind speed have been studied in the TRSR because this region is particularly sensitive to the impacts of climate change (You et al 2008, 2014, Yi et al 2011, Guo & Wang 2012, Xu et al 2012. Meteorological data has demonstrated that air temperatures in the TRSR have been rising at an average rate of 0.32°C decade −1 for the past half century (Yi et al 2011. The annual number of warm days and nights increased from 1961−2005 (You et al 2008), and these warming trends have caused an increase in the number of permafrost thawing days and a thickening of the permafrost active layer (Xue et al 2009).…”

Section: Introductionmentioning

confidence: 99%

Frozen ground temperature trends associated with climate change in the Tibetan Plateau Three River Source Region from 1980 to 2014

Luo¹,

Fang²,

Lyu³

et al. 2016

Clim. Res.

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Long-term (1981Long-term ( −2014 trends in soil temperatures at depths ranging from 0−320 cm were used to examine relationships between regional climate change and soil temperatures in the Three River Source Region (TRSR) of the Tibetan Plateau (TP). Air temperature, precipitation, maximum depth of frozen ground and maximum snow depth were also analysed for trends and for correlations with soil temperatures. A significant warming trend was evident in the TRSR during the 35 yr analysed. Significant soil warming was detected, at rates of 0.706°C decade −1 for surface soils (0 cm), 0.477°C decade −1 for shallow layer soils (5−20 cm) and 0.417°C decade −1 for deep layer soils (40−320 cm). There was a clear effect of air temperature on soil temperature, as seen from the concurrent significant increases in air and soil temperature trends and the strong correlation between them. The relationship between precipitation and soil temperatures was complicated. Higher levels of precipitation on the ground also resulted in higher soil temperatures during the summer in the frozen soil, while the process of freezing and thawing had an inhibitory effect on the soil temperature increase. The warming trends in soil temperature are expected to continue with the degradation of frozen soil in the TRSR.

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“…The elevation in the TRHR ranges from 2610 to 6950 m, and the average elevation is 4500 m [51]. The climate in the study area is the typical plateau continental monsoon type, with an annual mean temperature range from −5.38 to 4.14 ∘ C and an annual precipitation between 262.2 and 772.8 mm [50,52].…”

Section: Study Area Descriptionmentioning

confidence: 99%

ANN Model-Based Simulation of the Runoff Variation in Response to Climate Change on the Qinghai-Tibet Plateau, China

Chang

Wang

Mao

et al. 2017

Advances in Meteorology

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Precisely quantitative assessments of stream flow response to climatic change and permafrost thawing are highly challenging and urgent in cold regions. However, due to the notably harsh environmental conditions, there is little field monitoring data of runoff in permafrost regions, which has limited the development of physically based models in these regions. To identify the impacts of climate change in the runoff process in the Three-River Headwater Region (TRHR) on the Qinghai-Tibet Plateau, two artificial neural network (ANN) models, one with three input variables (previous runoff, air temperature, and precipitation) and another with two input variables (air temperature and precipitation only), were developed to simulate and predict the runoff variation in the TRHR. The results show that the three-input variable ANN model has a superior real-time prediction capability and performs well in the simulation and forecasting of the runoff variation in the TRHR. Under the different scenarios conditions, the forecasting results of ANN model indicated that climate change has a great effect on the runoff processes in the TRHR. The results of this study are of practical significance for water resources management and the evaluation of the impacts of climatic change on the hydrological regime in long-term considerations.

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Temperature variation and abrupt change analysis in the Three-River Headwaters Region during 1961–2010

Cited by 37 publications

References 19 publications

Spatial-Temporal Dynamics of China’s Terrestrial Biodiversity: A Dynamic Habitat Index Diagnostic

Spatial-Temporal Dynamics of China’s Terrestrial Biodiversity: A Dynamic Habitat Index Diagnostic

Frozen ground temperature trends associated with climate change in the Tibetan Plateau Three River Source Region from 1980 to 2014

ANN Model-Based Simulation of the Runoff Variation in Response to Climate Change on the Qinghai-Tibet Plateau, China

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