Air temperature variability in high-elevation glacierized regions: observations from six catchments on the Tibetan Plateau

2021 ◽  
Keyword(s):  
Tibetan Plateau ◽  
Air Temperature ◽  
High Elevation ◽  
Temperature Variability ◽  
The Tibetan Plateau ◽  
Katabatic Winds ◽  
Near Surface ◽  
Southeastern Tibetan Plateau ◽  
Air Temperatures ◽  
Cooling Effects

Abstract Near-surface air temperature variability and the reliability of temperature extrapolation within glacierized regions are important issues for hydrological and glaciological studies that remain elusive because of the scarcity of high-elevation observations. Based on air temperature data in 2019 collected from 12 automatic weather stations, 43 temperature loggers and 6 national meteorological stations in six different catchments, this study presents air temperature variability in different glacierized/nonglacierized regions and assesses the robustness of different temperature extrapolations to reduce errors in melt estimation. The results show high spatial variability in temperature lapse rates (LRs) in different climatic contexts, with the steepest LRs located on the cold-dry northwestern Tibetan Plateau and the lowest LRs located on the warm-humid monsoonal-influenced southeastern Tibetan Plateau. Near-surface air temperatures in high-elevation glacierized regions of the western and central Tibetan Plateau are less influenced by katabatic winds and thus can be linearly extrapolated from off-glacier records. In contrast, the local katabatic winds prevailing on the temperate glaciers of the southeastern Tibetan Plateau exert pronounced cooling effects on the ambient air temperature, and thus, on-glacier air temperatures are significantly lower than that in elevation-equivalent nonglacierized regions. Consequently, linear temperature extrapolation from low-elevation nonglacierized stations may lead to as much as 40% overestimation of positive degree days, particularly with respect to large glaciers with a long flowline distances and significant cooling effects. These findings provide noteworthy evidence that the different LRs and relevant cooling effects on high-elevation glaciers under distinct climatic regimes should be carefully accounted for when estimating glacier melting on the Tibetan Plateau.

scholarly journals Linking deeply-sourced volatile emissions to plateau growth dynamics in southeastern Tibetan Plateau

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Maoliang Zhang ◽  
Zhengfu Guo ◽  
Sheng Xu ◽  
Peter H. Barry ◽  
Yuji Sano ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Growth Dynamics ◽  
High Elevation ◽  
Fault System ◽  
The Tibetan Plateau ◽  
Southeastern Tibetan Plateau ◽  
Surface Uplift ◽  
Multi Stage ◽  
Geodynamic Processes ◽  
Underlying Mechanisms

AbstractThe episodic growth of high-elevation orogenic plateaux is controlled by a series of geodynamic processes. However, determining the underlying mechanisms that drive plateau growth dynamics over geological history and constraining the depths at which growth originates, remains challenging. Here we present He-CO2-N2 systematics of hydrothermal fluids that reveal the existence of a lithospheric-scale fault system in the southeastern Tibetan Plateau, whereby multi-stage plateau growth occurred in the geological past and continues to the present. He isotopes provide unambiguous evidence for the involvement of mantle-scale dynamics in lateral expansion and localized surface uplift of the Tibetan Plateau. The excellent correlation between 3He/4He values and strain rates, along the strike of Indian indentation into Asia, suggests non-uniform distribution of stresses between the plateau boundary and interior, which modulate southeastward growth of the Tibetan Plateau within the context of India-Asia convergence. Our results demonstrate that deeply-sourced volatile geochemistry can be used to constrain deep dynamic processes involved in orogenic plateau growth.

Recent Trends in Land Surface Temperature on the Tibetan Plateau

2006 ◽  
Vol 19 (12) ◽  
pp. 2995-3003 ◽  
Author(s):  
Yuichiro Oku ◽  
Hirohiko Ishikawa ◽  
Shigenori Haginoya ◽  
Yaoming Ma
Keyword(s):  
Tibetan Plateau ◽  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Precipitation Amount ◽  
Surface Air Temperature ◽  
The Tibetan Plateau ◽  
Near Surface ◽  
Diurnal Range

Abstract The diurnal, seasonal, and interannual variations in land surface temperature (LST) on the Tibetan Plateau from 1996 to 2002 are analyzed using the hourly LST dataset obtained by Japanese Geostationary Meteorological Satellite 5 (GMS-5) observations. Comparing LST retrieved from GMS-5 with independent precipitation amount data demonstrates the consistent and complementary relationship between them. The results indicate an increase in the LST over this period. The daily minimum has risen faster than the daily maximum, resulting in a narrowing of the diurnal range of LST. This is in agreement with the observed trends in both global and plateau near-surface air temperature. Since the near-surface air temperature is mainly controlled by LST, this result ensures a warming trend in near-surface air temperature.

scholarly journals Daily air temperature estimation on glacier surfaces in the Tibetan Plateau using MODIS LST data

2018 ◽  
Vol 64 (243) ◽  
pp. 132-147 ◽  
Author(s):  
HONGBO ZHANG ◽  
FAN ZHANG ◽  
GUOQING ZHANG ◽  
YAOMING MA ◽  
KUN YANG ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Air Temperature ◽  
Lapse Rate ◽  
The Tibetan Plateau ◽  
Mean Square ◽  
Night Time ◽  
Glacier Surface ◽  
Temperature Estimation ◽  
Air Temperatures ◽  
Air Temperature Estimation

ABSTRACTThe MODerate resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) data have been widely used for air temperature estimation in mountainous regions where station observations are sparse. However, the performance of MODIS LST in high-elevation glacierized areas remains unclear. This study investigates air temperature estimation in glacierized areas based on ground observations at four glaciers across the Tibetan Plateau. Before being used to estimate the air temperature, MODIS LST data are evaluated at two of the glaciers, which indicates that MODIS night-time LST is more reliable than MODIS daytime LST data. Then, linear models based on each of the individual MODIS LST products from two platforms (Terra and Aqua) and two overpasses (night-time and daytime) are built to estimate daily mean, minimum and maximum air temperatures in glacierized areas. Regional glacier surface (RGS) models (mean /-mean-square differences: 3.3, 3.0 and 4.8°C for daily mean, minimum and maximum air temperatures, respectively) show higher accuracy than local non-glacier surface models (mean root-mean-square differences: 4.2, 4.7 and 5.7°C). In addition, the RGS models based on MODIS night-time LST perform better to estimate daily mean, minimum and maximum air temperatures than using temperature lapse rate derived from local stations.

scholarly journals Evaluation of cloud effects on air temperature estimation using MODIS LST based on ground measurements over the Tibetan Plateau

2016 ◽  
Author(s):  
Hongbo Zhang ◽  
Fan Zhang ◽  
Guoqing Zhang ◽  
Xiaobo He ◽  
Lide Tian
Keyword(s):  
Tibetan Plateau ◽  
Air Temperature ◽  
Land Surface ◽  
Estimation Accuracy ◽  
Daily Maximum ◽  
The Tibetan Plateau ◽  
Cloud Detection ◽  
Air Temperatures ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) data have played a significant role in estimating the air temperature (Tair) due to the sparseness of ground measurements, especially for remote mountainous areas. Generally, two types of air temperatures are studied including daily maximum (Tmax) and minimum (Tmin) air temperatures. MODIS daytime and nighttime LST are often used as proxies for estimating Tmax and Tmin, respectively. The Tibetan Plateau (TP) has a high daily cloud cover fraction (> 45 %). The presence of clouds can affect the relationship between Tair and LST and can further affect the estimation accuracies. This study comprehensively analyzes the effects of clouds on Tair estimation based on MODIS LST using detailed half-hourly ground measurements and daily meteorological station observations collected from over the TP. Comparisons made between in-situ cloudiness observations and MODIS claimed clear-sky records show that erroneous rates of MODIS nighttime cloud detection are obviously higher than those achieved in daytime. Our validation of the MODIS LST values under different cloudiness constraining conditions shows that the accuracy of MODIS nighttime LST is severely affected by undetected clouds. Large errors introduced by undetected clouds are found to significantly affect the Tmin estimations based on nighttime LST through cloud effect tests. However, clouds are mainly found to affect Tmax estimation by affecting the essential relationship between Tmax and daytime LST. The obviously larger errors of Tmax estimation than those of Tmin could be attributed to larger MODIS daytime LST errors resulting from higher degrees of daytime LST heterogeneity within MODIS pixel than those of nighttime LST. Constraining all four MODIS observations per day to non-cloudy observations can efficiently screen samples to build a strong fit of Tmin estimation using MODIS nighttime LST. The present study reveals the effects of clouds on Tair estimation through MODIS LST and will thus help improve the estimation accuracy levels while alleviating the problems associated with severe data sparseness over the TP.

scholarly journals Analysis On The Regional Features of Future Warming Using High-Resolution Downscaled Multi-Model Climate Scenarios In China

2021 ◽  
Author(s):  
Lei Zhang ◽  
Yinlong Xu ◽  
Chunchun Meng ◽  
Yuncheng Zhao ◽  
Changgui Wang
Keyword(s):  
Heat Stress ◽  
High Resolution ◽  
Tibetan Plateau ◽  
Air Temperature ◽  
South China ◽  
Surface Air Temperature ◽  
Northern China ◽  
The Tibetan Plateau ◽  
Near Surface ◽  
Future Warming

Abstract The frequency and magnitude of global warming events varies greatly across different regions and countries. The climatic diversity for China and future warming features are projected across twelve climatic zones based on the ensemble of the five well-performing high resolution downscaled climate models for each zone. There are warming patterns for the mean near surface air temperature (Tm), maximum near surface air temperature (Tmax), minimum near surface air temperature (Tmin) as well as heat stress and frost events. Under RCP4.5 and RCP8.5 scenarios, the three indices (i.e., Tm, Tmax and Tmin) countrywide are likely to increase at respective rates of 0.30-0.31 and 0.64-0.67 oC per decade. The extent of freezing-event extent (FE) are projected to decrease at a rate of -1912 and -4442 day·km2 per decade while the extent of heat-stress event (HE) increase at 1116 and 3557 day·km2 per decade. A higher increment in temperatures as well as a decreasing trend in the diurnal temperature range (DTR) and frost days and FE are present on the Tibetan Plateau and northern China including Xinjiang, Northeast China, the eastern part of northwest China, Inner Mongolia and North China. These trends are opposite to those projected for southern China including Huanghuai, Jianghuai, Jianghan, the south Yangzi River, South China and Southwestern China. The warming occur faster in the current colder zones (northern China and the Tibetan Plateau) while heat stress is more intense and severe in Jianghuai, Jianghan, the south Yangzi River, South China and Xinjiang. These potential changes indicate that adaption and mitigation strategies are necessary in response to future warming.

scholarly journals Evaluation of cloud effects on air temperature estimation using MODIS LST based on ground measurements over the Tibetan Plateau

2016 ◽  
Vol 16 (21) ◽  
pp. 13681-13696 ◽  
Author(s):  
Hongbo Zhang ◽  
Fan Zhang ◽  
Guoqing Zhang ◽  
Xiaobo He ◽  
Lide Tian
Keyword(s):  
Tibetan Plateau ◽  
Air Temperature ◽  
Land Surface ◽  
Estimation Accuracy ◽  
Daily Maximum ◽  
The Tibetan Plateau ◽  
Cloud Detection ◽  
Air Temperatures ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Moderate Resolution Imaging Spectroradiometer (MODIS) daytime and nighttime land surface temperature (LST) data are often used as proxies for estimating daily maximum (Tmax) and minimum (Tmin) air temperatures, especially for remote mountainous areas due to the sparseness of ground measurements. However, the Tibetan Plateau (TP) has a high daily cloud cover fraction (> 45 %), which may affect the air temperature (Tair) estimation accuracy. This study comprehensively analyzes the effects of clouds on Tair estimation based on MODIS LST using detailed half-hourly ground measurements and daily meteorological station observations collected from the TP. It is shown that erroneous rates of MODIS nighttime cloud detection are obviously higher than those achieved in daytime. Large errors in MODIS nighttime LST data were found to be introduced by undetected clouds and thus reduce the Tmin estimation accuracy. However, for Tmax estimation, clouds are mainly found to reduce the estimation accuracy by affecting the essential relationship between Tmax and daytime LST. The errors of Tmax estimation are obviously larger than those of Tmin and could be attributed to larger MODIS daytime LST errors that result from higher degrees of LST heterogeneity within MODIS pixel compared to those of nighttime LST. Constraining MODIS observations to non-cloudy observations can efficiently screen data samples for accurate Tmin estimation using MODIS nighttime LST. As a result, the present study reveals the effects of clouds on Tmax and Tmin estimation through MODIS daytime and nighttime LST, respectively, so as to help improve the Tair estimation accuracy and alleviate the severe air temperature data sparseness issues over the TP.

scholarly journals Creating New Near-Surface Air Temperature Datasets to Understand Elevation-Dependent Warming in the Tibetan Plateau

2020 ◽  
Vol 12 (11) ◽  
pp. 1722
Author(s):  
Mingxi Zhang ◽  
Bin Wang ◽  
James Cleverly ◽  
De Li Liu ◽  
Puyu Feng ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Air Temperature ◽  
Land Surface ◽  
Vegetation Indices ◽  
Surface Air Temperature ◽  
The Tibetan Plateau ◽  
Global Studies ◽  
Near Surface ◽  
Automated Mapping ◽  
Land Surface Temperatures

The Tibetan Plateau has been undergoing accelerated warming over recent decades, and is considered an indicator for broader global warming phenomena. However, our understanding of warming rates with elevation in complex mountain regions is incomplete. The most serious concern is the lack of high-quality near-surface air temperature (Tair) datasets in these areas. To address this knowledge gap, we developed an automated mapping framework for the estimation of seamless daily minimum and maximum Land Surface Temperatures (LSTs) for the Tibetan Plateau from the existing MODIS LST products for a long period of time (i.e., 2002–present). Specific machine learning methods were developed and linked with target-oriented validation and then applied to convert LST to Tair. Spatial variables in retrieving Tair, such as solar radiation and vegetation indices, were used in estimation of Tair, whereas MODIS LST products were mainly focused on temporal variation in surface air temperature. We validated our process using independent Tair products, revealing more reliable estimates on Tair; the R2 and RMSE at monthly scales generally fell in the range of 0.9–0.95 and 1–2 °C. Using these continuous and consistent Tair datasets, we found temperature increases in the elevation range between 2000–3000 m and 4000–5000 m, whereas the elevation interval at 6000–7000 m exhibits a cooling trend. The developed datasets, findings and methodology contribute to global studies on accelerated warming.

scholarly journals Sediment transport processes across the Tibetan Plateau inferred from robust grain-size end members in lake sediments

2014 ◽  
Vol 10 (1) ◽  
pp. 91-106 ◽  
Author(s):  
E. Dietze ◽  
F. Maussion ◽  
M. Ahlborn ◽  
B. Diekmann ◽  
K. Hartmann ◽  
...  
Keyword(s):  
Grain Size ◽  
Sediment Transport ◽  
Tibetan Plateau ◽  
Transport Processes ◽  
The Tibetan Plateau ◽  
Dust Deposition ◽  
Northerly Wind ◽  
Near Surface ◽  
Depositional Processes ◽  
End Members

Abstract. Grain-size distributions offer powerful proxies of past environmental conditions that are related to sediment sorting processes. However, they are often of multimodal character because sediments can get mixed during deposition. To facilitate the use of grain size as palaeoenvironmental proxy, this study aims to distinguish the main detrital processes that contribute to lacustrine sedimentation across the Tibetan Plateau using grain-size end-member modelling analysis. Between three and five robust grain-size end-member subpopulations were distinguished at different sites from similarly–likely end-member model runs. Their main modes were grouped and linked to common sediment transport and depositional processes that can be associated with contemporary Tibetan climate (precipitation patterns and lake ice phenology, gridded wind and shear stress data from the High Asia Reanalysis) and local catchment configurations. The coarse sands and clays with grain-size modes >250 μm and <2 μm were probably transported by fluvial processes. Aeolian sands (~200 μm) and coarse local dust (~60 μm), transported by saltation and in near-surface suspension clouds, are probably related to occasional westerly storms in winter and spring. Coarse regional dust with modes ~25 μm may derive from near-by sources that keep in longer term suspension. The continuous background dust is differentiated into two robust end members (modes: 5–10 and 2–5 μm) that may represent different sources, wind directions and/or sediment trapping dynamics from long-range, upper-level westerly and episodic northerly wind transport. According to this study grain-size end members of only fluvial origin contribute small amounts to mean Tibetan lake sedimentation (19± 5%), whereas local to regional aeolian transport and background dust deposition dominate the clastic sedimentation in Tibetan lakes (contributions: 42 ± 14% and 51 ± 11%). However, fluvial and alluvial reworking of aeolian material from nearby slopes during summer seems to limit end-member interpretation and should be crosschecked with other proxy information. If not considered as a stand-alone proxy, a high transferability to other regions and sediment archives allows helpful reconstructions of past sedimentation history.

scholarly journals Seasonal dynamics of methane emissions from a subarctic fen in the Hudson Bay Lowlands

2013 ◽  
Vol 10 (7) ◽  
pp. 4465-4479 ◽  
Author(s):  
K. L. Hanis ◽  
M. Tenuta ◽  
B. D. Amiro ◽  
T. N. Papakyriakou
Keyword(s):  
Soil Temperature ◽  
Air Temperature ◽  
Growing Season ◽  
Near Surface ◽  
Growing Seasons ◽  
Air Temperatures ◽  
Soil Temperatures ◽  
Surface Soil Temperature ◽  
Filling Method ◽  
Highly Correlated

Abstract. Ecosystem-scale methane (CH4) flux (FCH4) over a subarctic fen at Churchill, Manitoba, Canada was measured to understand the magnitude of emissions during spring and fall shoulder seasons, and the growing season in relation to physical and biological conditions. FCH4 was measured using eddy covariance with a closed-path analyser in four years (2008–2011). Cumulative measured annual FCH4 (shoulder plus growing seasons) ranged from 3.0 to 9.6 g CH4 m−2 yr−1 among the four study years, with a mean of 6.5 to 7.1 g CH4 m−2 yr−1 depending upon gap-filling method. Soil temperatures to depths of 50 cm and air temperature were highly correlated with FCH4, with near-surface soil temperature at 5 cm most correlated across spring, fall, and the shoulder and growing seasons. The response of FCH4 to soil temperature at the 5 cm depth and air temperature was more than double in spring to that of fall. Emission episodes were generally not observed during spring thaw. Growing season emissions also depended upon soil and air temperatures but the water table also exerted influence, with FCH4 highest when water was 2–13 cm below and lowest when it was at or above the mean peat surface.

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