scholarly journals Triassic-Jurassic Granitoids and Pegmatites from Western Kunlun-Pamir Syntax: Implications for the Paleo-Tethys Evolution at the Northern Margin of the Tibetan Plateau

Lithosphere ◽  
2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Xiao-Qiang Liu ◽  
Chuan-Lin Zhang ◽  
Haibo Zou ◽  
Qian Wang ◽  
Xiao-Shu Hao ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
The Tibetan Plateau ◽  
Northern Margin ◽  
Magmatic Rocks ◽  
Western Kunlun ◽  
Type Granite ◽  
Tethys Ocean ◽  
Terrane Accretion

Abstract The Western Kunlun-Pamir-Karakorum (WKPK) at the northwestern Tibetan Plateau underwent long-term terrane accretion from the Paleozoic to the Cenozoic. Within this time span, four phases of magmatism occurred in WKPK during the Early Paleozoic, Triassic-Jurassic, Early Cretaceous, and Cenozoic. These voluminous magmatic rocks contain critical information on the evolution of the Tethys Oceans. In this contribution, we provide field observations, petrography, ages, whole-rock elemental and Sr-Nd isotopic compositions, and zircon in situ Lu-Hf isotopes of the Triassic-Jurassic granitoids and pegmatites from the Dahongliutan in Western Kunlun and Turuke area at the Pamir Plateau, in an attempt to constrain their petrogenesis and to decipher a more detailed Paleo-Tethys evolution process. The Dahongliutan pluton is composed of diorites (ca. 210 Ma) and monzogranite (ca. 200 Ma). The diorites have moderate SiO2 (56.77–62.22 wt. %), variable Mg# (46–49), and low Cr (34.4–50.6 ppm) and Ni contents (7.0–14.5 ppm). They show LREE-enriched patterns (LaN/YbN=4.3–17), with variable negative Eu anomalies (0.63–0.91) and variable ratios of Nb/La (0.27–0.97). Isotopically, the diorites display enriched whole-rock εNdt (-5.43 to -7.67) and negative to positive zircon εHft values (-6.6 to 0.4). They were most likely generated by melting of a subduction-modified mantle source with subsequent assimilation and fractional crystallization. The Turuke monzogranites (ca. 202–197 Ma) have S-type granite characteristics and are characterized by high SiO2 (70.36–76.12 wt. %) and A/CNK values (1.19–1.36), variable LREE-enriched patterns (LaN/YbN=8.87–14.40), negative Eu anomaly (0.07–0.56), relatively uniform whole-rock εNdt (-10.49 to -11.22), and variable negative zircon εHft values (-10.7 to -1.3). They were probably generated by muscovite-dehydration melting of dominantly metapelitic sources. The widespread pegmatites (ca. 195 Ma) at the Dahongliutan area record an extensional setting after the collision of Karakorum with the South Kunlun-Tianshuihai terrane. Combining our new data with the previous studies, we propose a divergent double-sided subduction of the Paleo-Tethys Ocean (243–208 Ma) and a gradual closure of the Paleo-Tethys Ocean from east (ca. 200 Ma) to west (ca. 180 Ma) to explain the Triassic-Jurassic tectono-magmatism in the WKPK.

scholarly journals Measurement report: Changing characteristics of atmospheric CH<sub>4</sub> in the Tibetan Plateau: records from 1994 to 2019 at the Mount Waliguan station

2021 ◽  
Vol 21 (1) ◽  
pp. 393-413
Author(s):  
Shuo Liu ◽  
Shuangxi Fang ◽  
Peng Liu ◽  
Miao Liang ◽  
Minrui Guo ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
The Tibetan Plateau ◽  
Atmospheric Methane ◽  
Continuous Increase ◽  
Northern India ◽  
Source Regions ◽  
City Regions

Abstract. A 26-year, long-term record of atmospheric methane (CH4) measured in situ at the Mount Waliguan (WLG) station, the only World Meteorological Organization (WMO) and Global Atmosphere Watch (GAW) global station in inland Eurasia, is presented. Overall, a nearly continuous increase in atmospheric CH4 was observed at WLG, with a yearly growth rate of 5.1±0.1 parts per billion (ppb) per year during 1994–2019, except for some particular periods with near-zero or negative values, e.g., 1999–2000 and 2004–2006. The average CH4 mole fraction was only 1799.0±0.4 ppb in 1994 but increased to about 133 ppb and reached a historic level of 1932.0±0.1 ppb in 2019. The case study in the Tibetan Plateau showed that the atmospheric CH4 increased rapidly. During some special periods, it is even larger than that of city regions (e.g., 6.7±0.2 ppb yr−1 in 2003–2007). Generally, the characteristics of CH4 varied in different observing periods as follows: (i) the diurnal cycle has become apparent and the amplitudes of the diurnal or seasonal cycles increased over time; (ii) the wind sectors with elevated CH4 mole fractions switched from ENE-E-ESE-SE-SSE sectors (wind directions) in early periods to NNE-NE-ENE-E sectors in later years; (iii) the area of source regions increased as the years progressed, and strong sources shifted from northeast (city regions) to southwest (northern India); and (iv) the annual growth rates in recent years (e.g., 2008–2019) were significantly larger than those in the early periods (e.g., 1994–2007).

scholarly journals Quantifying Long-Term Land Surface and Root Zone Soil Moisture over Tibetan Plateau

2020 ◽  
Vol 12 (3) ◽  
pp. 509 ◽  
Author(s):  
Ruodan Zhuang ◽  
Yijian Zeng ◽  
Salvatore Manfreda ◽  
Zhongbo Su
Keyword(s):  
Soil Moisture ◽  
Tibetan Plateau ◽  
Land Surface ◽  
Root Zone ◽  
Cumulative Distribution ◽  
Analytical Relationship ◽  
The Tibetan Plateau ◽  
Climate Systems

It is crucial to monitor the dynamics of soil moisture over the Tibetan Plateau, while considering its important role in understanding the land-atmosphere interactions and their influences on climate systems (e.g., Eastern Asian Summer Monsoon). However, it is very challenging to have both the surface and root zone soil moisture (SSM and RZSM) over this area, especially the study of feedbacks between soil moisture and climate systems requires long-term (e.g., decadal) datasets. In this study, the SSM data from different sources (satellites, land data assimilation, and in-situ measurements) were blended while using triple collocation and least squares method with the constraint of in-situ data climatology. A depth scaling was performed based on the blended SSM product, using Cumulative Distribution Function (CDF) matching approach and simulation with Soil Moisture Analytical Relationship (SMAR) model, to estimate the RZSM. The final product is a set of long-term (~10 yr) consistent SSM and RZSM product. The inter-comparison with other existing SSM and RZSM products demonstrates the credibility of the data blending procedure used in this study and the reliability of the CDF matching method and SMAR model in deriving the RZSM.

The evaluation of land surface parameters for model to derive land surface fluxes in the Tibetan Plateau

2021 ◽  
Author(s):  
Weiqiang Ma ◽  
Yaoming Ma ◽  
Yizhe Han ◽  
Wei Hu ◽  
Lei Zhong ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
Atmospheric Model ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
The Tibetan Plateau ◽  
Default Model ◽  
Model Configuration

&lt;p&gt;Firstly, based on the difference of model and in-situ observations, a serious of sensitive experiments were done by using WRF. In order to use remote sensing products, a land-atmosphere model was initialized by ingesting land surface parameters, such as AMSR-E RS products, and the results were compared with the default model configuration and with in-situ long-term CAMP/Tibet observations.&lt;/p&gt;&lt;p&gt;Secondly, a land-atmosphere model was initialized by ingesting AMSR-E products, and the results were compared with the default model configuration and with in-situ long-term CAMP/Tibet observations. The differences between the AMSR-E initialized model runs with the default model configuration and in situ data showed an apparent inconsistency in the model-simulated land surface heat fluxes. The results showed that the soil moisture was sensitive to the specific model configuration. To evaluate and verify the model stability, a long-term modeling study with AMSR-E soil moisture data ingestion was performed. Based on test simulations, AMSR-E data were assimilated into an atmospheric model for July and August 2007. The results showed that the land surface fluxes agreed well with both the in-situ data and the results of the default model configuration. Therefore, the simulation can be used to retrieve land surface heat fluxes from an atmospheric model over the Tibetan Plateau.&lt;/p&gt;&lt;p&gt;All of the different methods will clarify the land surface heating field in complex plateau, it also can affect atmospheric cycle over the Tibetan Plateau even all of the global atmospheric cycle pattern.&lt;/p&gt;

Quantitative Estimates of Holocene Glacier Mass Fluctuations on the Western Tibetan Plateau

2020 ◽  
Author(s):  
Juzhi Hou
Keyword(s):  
Tibetan Plateau ◽  
Mass Gain ◽  
The Tibetan Plateau ◽  
Alpine Glacier ◽  
Kunlun Mountain ◽  
Western Kunlun ◽  
Long Time ◽  
Western Tibetan Plateau ◽  
The Difference

&lt;p&gt;&lt;strong&gt;&lt;span&gt;Knowledge of the alpine glacier mass fluctuations is a fundamental prerequisite for understanding glacier dynamics, projecting future glacier change, and assessing the availability of freshwater resources. The glaciers on the Tibetan Plateau (TP) are sources of water for most of the major Asian rivers and their fate remains unclear due to accurate estimates of glacier mass fluctuations are lacking over long time scales. Here, we used d&lt;/span&gt;&lt;sup&gt;&lt;span&gt;18&lt;/span&gt;&lt;/sup&gt;&lt;span&gt;O record at a proglacial open lake as proxy to estimate the Holocene glacier mass fluctuations in the Western Kunlun Mountain (WKM) quantitatively and continuously. Relative to past decades, maximum WKM glacier mass loss (-28.62&amp;#177;25.76 Gt) occurred at 9.5-8.5 ka BP, and maximum glacier mass gain (24.53&amp;#177;25.02 Gt) occurred at 1.3~0.5 ka BP, the difference in WKM glacier mass between the two periods account for ~20% of the total glaciers. Long-term changes in glacier mass suggests the TP glaciers likely face severe threats at the current rates of global warming. &lt;/span&gt;&lt;/strong&gt;&lt;/p&gt;

scholarly journals Status of the Tibetan Plateau observatory (Tibet-Obs) and a 10-year (2009–2019) surface soil moisture dataset

2020 ◽  
Author(s):  
Pei Zhang ◽  
Donghai Zheng ◽  
Rogier van der Velde ◽  
Jun Wen ◽  
Yijian Zeng ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Tibetan Plateau ◽  
Current Model ◽  
Regional Scale ◽  
In Situ Measurements ◽  
The Tibetan Plateau ◽  
Model Based ◽  
Network Area

Abstract. The Tibetan Plateau observatory of plateau scale soil moisture and soil temperature (Tibet-Obs) was established ten years ago, which has been widely used to calibrate/validate satellite- and model-based soil moisture (SM) products for their applications to the Tibetan Plateau (TP). This paper reports on the status of the Tibet-Obs and presents a 10-year (2009–2019) surface SM dataset produced based on in situ measurements taken at a depth of 5 cm collected from the Tibet-Obs that consists of three regional-scale SM monitoring networks, i.e. the Maqu, Naqu, and Ngari (including Ali and Shiquanhe) networks. This surface SM dataset includes the original 15-min in situ measurements collected by multiple SM monitoring sites of the three networks, and the spatially upscaled SM records produced for the Maqu and Shiquanhe networks. Comparisons between four spatial upscaling methods, i.e. arithmetic averaging, Voronoi diagram, time stability and apparent thermal inertia, show that the arithmetic average of the monitoring sites with long-term (i.e. ≥ six years) continuous measurements are found to be most suitable to produce the upscaled SM records. Trend analysis of the 10-year upscaled SM records using the Mann-Kendall method shows that the Maqu network area in the eastern part of the TP is drying while the Shiquanhe network area in the west is getting wet that generally follow the change of precipitation. To further demonstrate the uniqueness of the upscaled SM records in validating existing SM products for long term period (~ 10 years), comparisons are conducted to evaluate the reliability of three reanalysis datasets for the Maqu and Shiquanhe network areas. It is found that current model-based SM products still show deficiencies in representing the trend and variation of measured SM dynamics in the Tibetan grassland (i.e. Maqu) and desert ecosystems (i.e. Shiquanhe) that dominate the landscape of the TP. The dataset would be also valuable for calibrating/validating long-term satellite-based SM products, evaluation of SM upscaling methods, development of data fusion methods, and quantifying the coupling strength between precipitation and SM at 10-year scale. The dataset is available in the 4TU.ResearchData repository at https://doi.org/10.4121/uuid:21220b23-ff36-4ca9-a08f-ccd53782e834 (Zhang et al., 2020).

scholarly journals Status of the Tibetan Plateau observatory (Tibet-Obs) and a 10-year (2009–2019) surface soil moisture dataset

2021 ◽  
Vol 13 (6) ◽  
pp. 3075-3102
Author(s):  
Pei Zhang ◽  
Donghai Zheng ◽  
Rogier van der Velde ◽  
Jun Wen ◽  
Yijian Zeng ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Tibetan Plateau ◽  
Current Model ◽  
Regional Scale ◽  
In Situ Measurements ◽  
The Tibetan Plateau ◽  
Monitoring Networks ◽  
Model Based

Abstract. The Tibetan Plateau observatory (Tibet-Obs) of plateau scale soil moisture and soil temperature was established 10 years ago and has been widely used to calibrate/validate satellite- and model-based soil moisture (SM) products for their applications to the Tibetan Plateau (TP). This paper reports on the status of the Tibet-Obs and presents a 10-year (2009–2019) surface SM dataset produced based on in situ measurements taken at a depth of 5 cm collected from the Tibet-Obs that consists of three regional-scale SM monitoring networks, i.e. the Maqu, Naqu, and Ngari (including Ali and Shiquanhe) networks. This surface SM dataset includes the original 15 min in situ measurements collected by multiple SM monitoring sites of the three networks and the spatially upscaled SM records produced for the Maqu and Shiquanhe networks. Comparisons between four spatial upscaling methods – i.e. arithmetic averaging, Voronoi diagrams, time stability, and apparent thermal inertia – show that the arithmetic average of the monitoring sites with long-term (i.e. ≥ 6-year) continuous measurements is found to be most suitable to produce the upscaled SM records. Trend analysis of the 10-year upscaled SM records indicates that the Shiquanhe network in the western part of the TP is getting wet, while there is no significant trend found for the Maqu network in the east. To further demonstrate the uniqueness of the upscaled SM records in validating existing SM products for a long-term period (∼10 years), the reliability of three reanalysis datasets is evaluated for the Maqu and Shiquanhe networks. It is found that current model-based SM products still show deficiencies in representing the measured SM dynamics in the Tibetan grassland (i.e. Maqu) and desert ecosystems (i.e. Shiquanhe). The dataset would also be valuable for calibrating/validating long-term satellite-based SM products, evaluation of SM upscaling methods, development of data fusion methods, and quantifying the coupling of SM and precipitation at a 10-year scale. The dataset is available in the 4TU.ResearchData repository at https://doi.org/10.4121/12763700.v7 (Zhang et al., 2020).

scholarly journals Combining and Comparing an Unmanned Aerial Vehicle and Multiple Remote Sensing Satellites to Calculate Long-Term River Discharge in an Ungauged Water Source Region on the Tibetan Plateau

2020 ◽  
Vol 12 (13) ◽  
pp. 2155 ◽  
Author(s):  
Hezhen Lou ◽  
Pengfei Wang ◽  
Shengtian Yang ◽  
Fanghua Hao ◽  
Xiaoyu Ren ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Tibetan Plateau ◽  
Unmanned Aerial Vehicle ◽  
River Discharge ◽  
The Tibetan Plateau ◽  
Aerial Vehicle ◽  
Spot 5 ◽  
Sentinel 2

Research into global water resources is challenged by the lack of ground-based hydrometric stations and limited data sharing. It is difficult to collect good quality, long-term information about river discharges in ungauged regions. Herein, an approach was developed to determine the river discharges of 24 rivers in ungauged regions on the Tibetan Plateau on a long-term scale. This method involved coupling the Manning–Strickler formula, and data from an unmanned aerial vehicle (UAV) and the Gaofen-2, SPOT-5, and Sentinel-2 satellites. We also compared the discharges calculated by using the three satellites’ data. Fundamental information about the rivers was extracted from the UAV data. Comparison of the discharges calculated from the in-situ measurements and the UAV data gave an R2 value of 0.84, an average NSE of 0.79, and an RMSE of 0.11 m3/s. The river discharges calculated with the GF-2 remote sensing data and the in-situ experiments for the same months were compared and the R2, RMSE, and the NSE were 0.80, 1.8 m3/s, and 0.78, respectively. Comparing the discharges calculated over the long term from the measured in-situ data and the SPOT-5 and Sentinel-2 data gave R2 values of 0.93 and 0.92, and RMSE values of 2.56 m3/s and 3.16 m3/s, respectively. The results showed that the GF-2 and UAV were useful for calculating the discharges for low-flow rivers, while the SPOT-5 or the Sentinel-2 satellite gave good results for high-flow river discharges in the long-term. Our results demonstrate that the discharges in ungauged tributaries can be reliably estimated in the long-term with this method. This method extended the previous research, which described river discharge only in one period and provided more support to the monitoring and management of the tributaries in ungauged regions.

scholarly journals The evaluation of AMSR-E soil moisture data in atmospheric modeling using a suitable time series iteration to derive land surface fluxes over the Tibetan Plateau

2020 ◽  
Author(s):  
Weiqiang Ma ◽  
Yaoming Ma ◽  
Yizhe Han ◽  
Wei Hu ◽  
Lei Zhong
Keyword(s):  
Soil Moisture ◽  
Tibetan Plateau ◽  
Land Surface ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
The Tibetan Plateau ◽  
Default Model ◽  
Model Configuration

&lt;p&gt;Firstly, based on the difference of model and in-situ observations, a serious of sensitive experiments were done by using WRF. In order to use remote sensing products, a land-atmosphere model was initialized by ingesting AMSR-E RS products, and the results were compared with the default model configuration and with in-situ long-term CAMP/Tibet observations.&lt;/p&gt;&lt;p&gt;Secondly, a land-atmosphere model was initialized by ingesting AMSR-E products, and the results were compared with the default model configuration and with in-situ long-term CAMP/Tibet observations. The differences between the AMSR-E initialized model runs with the default model configuration and in situ data showed an apparent inconsistency in the model-simulated land surface heat fluxes. The results showed that the soil moisture was sensitive to the specific model configuration. To evaluate and verify the model stability, a long-term modeling study with AMSR-E soil moisture data ingestion was performed. Based on test simulations, AMSR-E data were assimilated into an atmospheric model for July and August 2007. The results showed that the land surface fluxes agreed well with both the in-situ data and the results of the default model configuration. Therefore, the simulation can be used to retrieve land surface heat fluxes from an atmospheric model over the Tibetan Plateau.&lt;/p&gt;&lt;p&gt;All of the different methods will clarify the land surface heating field in complex plateau, it also can affect atmospheric cycle over the Tibetan Plateau even all of the global atmospheric cycle pattern.&lt;/p&gt;

scholarly journals A long-term (2005–2016) dataset of hourly integrated land–atmosphere interaction observations on the Tibetan Plateau

2020 ◽  
Vol 12 (4) ◽  
pp. 2937-2957
Author(s):  
Yaoming Ma ◽  
Zeyong Hu ◽  
Zhipeng Xie ◽  
Weiqiang Ma ◽  
Binbin Wang ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Tibetan Plateau ◽  
Soil Temperature ◽  
Global Climate ◽  
High Elevation ◽  
Scientific Data ◽  
The Tibetan Plateau ◽  
Atmosphere Interaction

Abstract. The Tibetan Plateau (TP) plays a critical role in influencing regional and global climate, via both thermal and dynamical mechanisms. Meanwhile, as the largest high-elevation part of the cryosphere outside the polar regions, with vast areas of mountain glaciers, permafrost and seasonally frozen ground, the TP is characterized as an area sensitive to global climate change. However, meteorological stations are biased and sparsely distributed over the TP, owing to the harsh environmental conditions, high elevations, complex topography and heterogeneous surfaces. Moreover, due to the weak representation of the stations, atmospheric conditions and the local land–atmosphere coupled system over the TP as well as its effects on surrounding regions are poorly quantified. This paper presents a long-term (2005–2016) in situ observational dataset of hourly land–atmosphere interaction observations from an integrated high-elevation and cold-region observation network, composed of six field stations on the TP. These in situ observations contain both meteorological and micrometeorological measurements including gradient meteorology, surface radiation, eddy covariance (EC), soil temperature and soil water content profiles. Meteorological data were monitored by automatic weather stations (AWSs) or planetary boundary layer (PBL) observation systems. Multilayer soil temperature and moisture were recorded to capture vertical hydrothermal variations and the soil freeze–thaw process. In addition, an EC system consisting of an ultrasonic anemometer and an infrared gas analyzer was installed at each station to capture the high-frequency vertical exchanges of energy, momentum, water vapor and carbon dioxide within the atmospheric boundary layer. The release of these continuous and long-term datasets with hourly resolution represents a leap forward in scientific data sharing across the TP, and it has been partially used in the past to assist in understanding key land surface processes. This dataset is described here comprehensively for facilitating a broader multidisciplinary community by enabling the evaluation and development of existing or new remote sensing algorithms as well as geophysical models for climate research and forecasting. The whole datasets are freely available at the Science Data Bank (https://doi.org/10.11922/sciencedb.00103; Ma et al., 2020) and additionally at the National Tibetan Plateau Data Center (https://doi.org/10.11888/Meteoro.tpdc.270910, Ma 2020).

Sign in / Sign up

Export Citation Format

Share Document