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 Diurnal fluctuations of glacier surface velocity observed with terrestrial radar interferometry at Laohugou No. 12 Glacier, western Qilian mountains, China

2019 ◽  
Vol 65 (250) ◽  
pp. 239-248 ◽  
Author(s):  
LIN LIU ◽  
LIMING JIANG ◽  
YONGLING SUN ◽  
HANSHENG WANG ◽  
YAFEI SUN ◽  
...  
Keyword(s):  
Air Temperature ◽  
Short Interval ◽  
Radar Interferometry ◽  
Surface Velocity ◽  
The Tibetan Plateau ◽  
Differential Gps ◽  
Night Time ◽  
Glacier Surface ◽  
Flow Speeds ◽  
Diurnal Fluctuations

ABSTRACTMeasurements of short-interval variations in glacier surface velocity, which contribute to our understanding of ice motion mechanisms, remain scarce on the Tibetan Plateau. Here we present sub-hourly measurements of glacier surface motion variations at the terminus region of Laohugou No. 12 Glacier. Field observations were collected over 4 d in July 2015 from terrestrial radar interferometry. The observed glacier displacement time series are generally in agreement with the results measured by differential GPS and highlight that glacier surface velocity is characterized by clear diurnal fluctuations in the study period. During day-time hours, glacier flow speeds were higher than 3.0 mm h−1, whereas they were below 1.0 mm h−1 during night-time hours. The large diurnal fluctuations of glacier surface velocity indicate that variations in basal slip are the dominant motion mechanism. Moreover, a positive correlation (R = 0.82, P < 0.001) between air temperature and glacier surface velocity suggests that glacier motion variations are probably affected by changes in air temperature during the ablation season.

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.

Air temperature estimation with MODIS data over the Northern Tibetan Plateau

2017 ◽  
Vol 34 (5) ◽  
pp. 650-662 ◽  
Author(s):  
Fangfang Huang ◽  
Weiqiang Ma ◽  
Binbin Wang ◽  
Zeyong Hu ◽  
Yaoming Ma ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Air Temperature ◽  
Temperature Estimation ◽  
Modis Data ◽  
Northern Tibetan Plateau ◽  
Air Temperature Estimation

How Accurately Can the Air Temperature Lapse Rate Over the Tibetan Plateau Be Estimated From MODIS LSTs?

2018 ◽  
Vol 123 (8) ◽  
pp. 3943-3960 ◽  
Author(s):  
Hongbo Zhang ◽  
Fan Zhang ◽  
Guoqing Zhang ◽  
Tao Che ◽  
Wei Yan
Keyword(s):  
Tibetan Plateau ◽  
Air Temperature ◽  
Lapse Rate ◽  
The Tibetan Plateau ◽  
Temperature Lapse Rate

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 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.

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