scholarly journals A New Map of the Permafrost Distribution on the Tibetan Plateau

2016 ◽  
Author(s):  
Defu Zou ◽  
Lin Zhao ◽  
Yu Sheng ◽  
Ji Chen ◽  
Guojie Hu ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
Water Resource Management ◽  
Climate Modelling ◽  
The Tibetan Plateau ◽  
Freezing And Thawing ◽  
Frozen Ground ◽  
Data Set ◽  
Distribution Maps ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. The Tibetan Plateau (TP) possesses the largest areas of permafrost terrain in the mid- and low-latitude regions of the world. A detailed database of the distribution and characteristics of permafrost is crucial for engineering planning, water resource management, ecosystem protection, climate modelling, and carbon cycle research. Although some permafrost distribution maps have been compiled in previous studies and have been proven to be very useful, due to the limited data source, ambiguous criteria, little validation, and the deficiency of high-quality spatial datasets, there is high uncertainty in the mapping of the permafrost distribution on the TP. In this paper, a new permafrost map was generated mostly based on freezing and thawing indices from modified Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperatures (LSTs) and validated by various ground-based datasets. The soil thermal properties of five soil types across the TP were estimated according to an empirical equation and in situ observed soil properties (moisture content and bulk density). The Temperature at the Top of Permafrost (TTOP) model was applied to simulate the permafrost distribution. The results show that permafrost, seasonally frozen ground, and unfrozen ground covered areas of 1.06×106 km2 (40 %), 1.46×106 km2 (56 %), and 0.03×106 km2 (1 %), respectively, excluding glaciers and lakes. The ground-based observations of the permafrost distribution across the five investigated regions (IRs, located in the transition zones of the permafrost and seasonally frozen ground) and three highway transects (across the entire permafrost regions from north to south) have been used to validate the model. The result of the validation shows that the kappa coefficient varies from 0.38 to 0.78 with an average of 0.57 at the five IRs and 0.62 to 0.74 with an average of 0.68 within the three transects. Compared with two maps compiled in 1996 and 2006 (kappa coefficients in average 0.06 and 0.35 in five IRs, 0.34 and 0.50 within three transects, respectively), the result of the TTOP modelling shows greater accuracy, especially in identifying thawing regions. Overall, the results provide much more detailed maps of the permafrost distribution and could be a promising basic data set for further research on permafrost on the Tibetan Plateau.

scholarly journals A new map of permafrost distribution on the Tibetan Plateau

2017 ◽  
Vol 11 (6) ◽  
pp. 2527-2542 ◽  
Author(s):  
Defu Zou ◽  
Lin Zhao ◽  
Yu Sheng ◽  
Ji Chen ◽  
Guojie Hu ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Spatial Data ◽  
Land Surface ◽  
Future Research ◽  
Data Sets ◽  
The Tibetan Plateau ◽  
Freezing And Thawing ◽  
Frozen Ground ◽  
Distribution Maps ◽  
Spatial Data Sets

Abstract. The Tibetan Plateau (TP) has the largest areas of permafrost terrain in the mid- and low-latitude regions of the world. Some permafrost distribution maps have been compiled but, due to limited data sources, ambiguous criteria, inadequate validation, and deficiency of high-quality spatial data sets, there is high uncertainty in the mapping of the permafrost distribution on the TP. We generated a new permafrost map based on freezing and thawing indices from modified Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperatures (LSTs) and validated this map using various ground-based data sets. The soil thermal properties of five soil types across the TP were estimated according to an empirical equation and soil properties (moisture content and bulk density). The temperature at the top of permafrost (TTOP) model was applied to simulate the permafrost distribution. Permafrost, seasonally frozen ground, and unfrozen ground covered areas of 1.06  ×  106 km2 (0.97–1.15  ×  106 km2, 90 % confidence interval) (40 %), 1.46  ×  106 (56 %), and 0.03  ×  106 km2 (1 %), respectively, excluding glaciers and lakes. Ground-based observations of the permafrost distribution across the five investigated regions (IRs, located in the transition zones of the permafrost and seasonally frozen ground) and three highway transects (across the entire permafrost regions from north to south) were used to validate the model. Validation results showed that the kappa coefficient varied from 0.38 to 0.78 with a mean of 0.57 for the five IRs and 0.62 to 0.74 with a mean of 0.68 within the three transects. Compared with earlier studies, the TTOP modelling results show greater accuracy. The results provide more detailed information on the permafrost distribution and basic data for use in future research on the Tibetan Plateau permafrost.

scholarly journals Variations in Winter Surface Temperature of the Purog Kangri Ice Field, Qinghai–Tibetan Plateau, 2001–2018, Using MODIS Data

2020 ◽  
Vol 12 (7) ◽  
pp. 1133
Author(s):  
Yufan Qie ◽  
Ninglian Wang ◽  
Yuwei Wu ◽  
An’an Chen
Keyword(s):  
Tibetan Plateau ◽  
Surface Temperature ◽  
Land Surface ◽  
Remote Sensing Data ◽  
Warming Trend ◽  
Data Set ◽  
Moderate Resolution ◽  
Ice Field ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Meteorological Observations

In the context of global warming, the land surface temperature (LST) from remote sensing data is one of the most useful indicators to directly quantify the degree of climate warming in high-altitude mountainous areas where meteorological observations are sparse. Using the daily Moderate Resolution Imaging Spectroradiometer (MODIS) LST product (MOD11A1 V6) after eliminating pixels that might be contaminated by clouds, this paper analyzes temporal and spatial variations in the mean LST on the Purog Kangri ice field, Qinghai–Tibetan Plateau, in winter from 2001 to 2018. There was a large increasing trend in LST (0.116 ± 0.05 °C·a−1) on the Purog Kangri ice field during December, while there was no evident LST rising trend in January and February. In December, both the significantly decreased albedo (−0.002 a−1, based on the MOD10A1 V6 albedo product) on the ice field surface and the significantly increased number of clear days (0.322 d·a−1) may be the main reason for the significant warming trend in the ice field. In addition, although the two highest LST of December were observed in 2017 and 2018, a longer data set is needed to determine whether this is an anomaly or a hint of a warmer phase of the Purog Kangri ice field in December.

scholarly journals Investigating basin-scale water budget dynamics in 18 rivers across Tibetan Plateau through multiple datasets

2017 ◽  
Author(s):  
Wenbin Liu ◽  
Fubao Sun ◽  
Yanzhong Li ◽  
Guoqing Zhang ◽  
Yan-Fang Sang ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
Water Budget ◽  
Water Resource Management ◽  
Management Practices ◽  
Yellow River ◽  
Aridity Index ◽  
Surface Model ◽  
The Tibetan Plateau ◽  
Basin Scale

Abstract. The dynamics of basin-scale water budgets are not well understood nowadays over the Tibetan Plateau (TP) due to the lack of hydro-climatic observations. In this study, we investigate seasonal cycles and trends of water budget components (e.g., precipitation-P, evapotranspiration-ET and runoff-Q) in eighteen TP river basins during the period 1982–2011 through the use of multi-source datasets (e.g., in situ observations, satellite retrievals, reanalysis outputs and land surface model simulations). A water balance-based two-step procedure, which considers the changes in basin-scale water storage at the annual scale, is also adopted to calculate actual ET. The results indicated that precipitation (mainly snowfall from mid-autumn to next spring), which mainly concentrated during June–October (varied among different monsoons-impacted basins), was the major contributor to the runoff in TP basins. Increased P, ET and Q were found in most TP basins during the past 30 years except for the upper Yellow River basin and some sub-basins of Yalong River, which were mainly affected by the weakening East Asian Monsoon. Moreover, the aridity index (PET/P) and runoff coefficient (Q/P) decreased in most basins, which were in agreement with the warming and moistening climate in the Tibetan Plateau. The results obtained demonstrated the usefulness of integrating multi-source datasets to hydrological applications in the data-sparse regions. More generally, such approach might offer helpful insights towards understanding the water and energy budgets and sustainability of water resource management practices of data-sparse regions in a changing environment.

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 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 Performance of GLASS and MODIS Satellite Albedo Products in Diagnosing Albedo Variations during Different Time Scales and Special Weather Conditions in the Tibetan Plateau

2020 ◽  
Vol 12 (15) ◽  
pp. 2456
Author(s):  
Yingying An ◽  
Xianhong Meng ◽  
Lin Zhao ◽  
Zhaoguo Li ◽  
Shaoying Wang ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
Surface Albedo ◽  
Weather Conditions ◽  
Glass Product ◽  
The Tibetan Plateau ◽  
Actual Surface ◽  
Multiple Observations ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Surface albedo is a crucial parameter in accurately and quantitatively estimating energy and water budget on the Tibetan Plateau (TP) and is also one of the largest radiative uncertainties in land surface modelling attempts. Based on an 8-year ground-based observation of the surface albedo over typical alpine meadows at Maqu and Maduo sites in the eastern TP, the performance of surface albedo products of Global LAnd Surface Satellite (GLASS) and Moderate Resolution Imaging Spectroradiometer (MODIS) in describing albedo variations at daily, 8-day, seasonal timescales, and during different special weather conditions were analyzed. Compared with the ground-based observation in Maqu, the 8-day albedo products from GLASS and MCD43B3 present maximum negative biases of −0.030 and −0.027 at Maqu, respectively. The black-sky albedo (BSA) of GLASS product coincides well with the ground-based observation in Maduo, with root mean square error (RMSE) of 0.092 and correlation coefficient (R) of 0.833, whereas that of MCD43B3 had an RMSE of 0.072 and R of 0.752. However, they are underestimated when the albedo is greater than 0.4. At the seasonal timescale, the BSA of GLASS and MCD43B3 underestimated the ground-based observation of Maqu by 0.015 in summer, while their white-sky albedo (WSA) are slightly overestimated and closer to the ground-based observation. In daily timescale, the response of surface albedo to soil moisture is different in semihumid and semiarid areas in summer. For both sites, the blue-sky-albedo of MCD43A3 has better agreement with the ground-based observation than GLASS and MCD43B3, as it improves the temporal resolution and calculates the albedo by weighting multiple observations within 16 days to be closer to the actual surface. However, even MCD43A3 could not capture the slowdown processes of albedo changes resulted by small snowfall processes or the snow aging due to cloud cover and inversion algorithms.

scholarly journals Impact of frozen soil processes on soil thermal characteristics at seasonal to decadal scales over the Tibetan Plateau and North China

2021 ◽  
Vol 25 (4) ◽  
pp. 2089-2107
Author(s):  
Qian Li ◽  
Yongkang Xue ◽  
Ye Liu
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
North China ◽  
Thermal Characteristics ◽  
Cold Season ◽  
Frozen Soil ◽  
The Tibetan Plateau ◽  
Soil Processes ◽  
Frozen Ground ◽  
Freeze Thaw

Abstract. Frozen soil processes are of great importance in controlling surface water and energy balances during the cold season and in cold regions. Over recent decades, considerable frozen soil degradation and surface soil warming have been reported over the Tibetan Plateau and North China, but most land surface models have difficulty in capturing the freeze–thaw cycle, and few validations focus on the effects of frozen soil processes on soil thermal characteristics in these regions. This paper addresses these issues by introducing a physically more realistic and computationally more stable and efficient frozen soil module (FSM) into a land surface model – the third-generation Simplified Simple Biosphere Model (SSiB3-FSM). To overcome the difficulties in achieving stable numerical solutions for frozen soil, a new semi-implicit scheme and a physics-based freezing–thawing scheme were applied to solve the governing equations. The performance of this model as well as the effects of frozen soil process on the soil temperature profile and soil thermal characteristics were investigated over the Tibetan Plateau and North China using observation sites from the China Meteorological Administration and models from 1981 to 2005. Results show that the SSiB3 model with the FSM produces a more realistic soil temperature profile and its seasonal variation than that without FSM during the freezing and thawing periods. The freezing process in soil delays the winter cooling, while the thawing process delays the summer warming. The time lag and amplitude damping of temperature become more pronounced with increasing depth. These processes are well simulated in SSiB3-FSM. The freeze–thaw processes could increase the simulated phase lag days and land memory at different soil depths as well as the soil memory change with the soil thickness. Furthermore, compared with observations, SSiB3-FSM produces a realistic change in maximum frozen soil depth at decadal scales. This study shows that the soil thermal characteristics at seasonal to decadal scales over frozen ground can be greatly improved in SSiB3-FSM, and SSiB3-FSM can be used as an effective model for TP and NC simulation during cold season. Overall, this study could help understand the vertical soil thermal characteristics over the frozen ground and provide an important scientific basis for land–atmosphere interactions.

Trends of land surface heat fluxes on the Tibetan Plateau from 2001 to 2012

2017 ◽  
Vol 37 (14) ◽  
pp. 4757-4767 ◽  
Author(s):  
Cunbo Han ◽  
Yaoming Ma ◽  
Xuelong Chen ◽  
Zhongbo Su
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
Surface Heat ◽  
Heat Fluxes ◽  
The Tibetan Plateau ◽  
Surface Heat Fluxes ◽  
Land Surface Heat Fluxes

scholarly journals Uncertainty and Variation of Remotely Sensed Lake Ice Phenology across the Tibetan Plateau

2018 ◽  
Vol 10 (10) ◽  
pp. 1534 ◽  
Author(s):  
Linan Guo ◽  
Yanhong Wu ◽  
Hongxing Zheng ◽  
Bing Zhang ◽  
Junsheng Li ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
Regional Climate ◽  
Local Environment ◽  
Remotely Sensed ◽  
The Tibetan Plateau ◽  
Remotely Sensed Data ◽  
Lake Ice ◽  
Reflectance Data ◽  
Ice Phenology

In the Tibetan Plateau (TP), the changes of lake ice phenology not only reflect regional climate change, but also impose substantial ecohydrological impacts on the local environment. Due to the limitation of ground observation, remote sensing has been used as an alternative tool to investigate recent changes of lake ice phenology. However, uncertainties exist in the remotely sensed lake ice phenology owing to both the data and methods used. In this paper, three different remotely sensed datasets are used to investigate the lake ice phenology variation in the past decade across the Tibetan Plateau, with the consideration of the underlying uncertainties. The remotely sensed data used include reflectance data, snow product, and land surface temperature (LST) data of moderate resolution imaging spectroradiometer (MODIS). The uncertainties of the three methods based on the corresponding data are assessed using the triple collocation approach. Comparatively, it is found that the method based on reflectance data outperforms the other two methods. The three methods are more consistent in determining the thawing dates rather than the freezing dates of lake ice. It is consistently shown by the three methods that the ice-covering duration in the northern part of the TP lasts longer than that in the south. Though there is no general trend of lake ice phenology across the TP for the period of 2000–2015, the warmer climate and stronger wind have led to the earlier break-up of lake ice.

Sign in / Sign up

Export Citation Format

Share Document