scholarly journals Long-term variations in actual evapotranspiration over the Tibetan Plateau

2021 ◽  
Vol 13 (7) ◽  
pp. 3513-3524
Author(s):  
Cunbo Han ◽  
Yaoming Ma ◽  
Binbin Wang ◽  
Lei Zhong ◽  
Weiqiang Ma ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Tibetan Plateau ◽  
Water Cycle ◽  
Meteorological Data ◽  
Correlation Coefficients ◽  
Data Bank ◽  
The Tibetan Plateau ◽  
Science Data ◽  
Autumn And Winter ◽  
Mean Square Errors

Abstract. Actual terrestrial evapotranspiration (ETa) is a key parameter controlling land–atmosphere interaction processes and water cycle. However, spatial distribution and temporal changes in ETa over the Tibetan Plateau (TP) remain very uncertain. Here we estimate the multiyear (2001–2018) monthly ETa and its spatial distribution on the TP by a combination of meteorological data and satellite products. Validation against data from six eddy-covariance monitoring sites yielded root-mean-square errors ranging from 9.3 to 14.5 mm per month and correlation coefficients exceeding 0.9. The domain mean of annual ETa on the TP decreased slightly (−1.45 mm yr−1, p<0.05) from 2001 to 2018. The annual ETa increased significantly at a rate of 2.62 mm yr−1 (p<0.05) in the eastern sector of the TP (long >90∘ E) but decreased significantly at a rate of −5.52 mm yr−1 (p<0.05) in the western sector of the TP (long <90∘ E). In addition, the decreases in annual ETa were pronounced in the spring and summer seasons, while almost no trends were detected in the autumn and winter seasons. The mean annual ETa during 2001–2018 and over the whole TP was 496±23 mm. Thus, the total evapotranspiration from the terrestrial surface of the TP was 1238.3±57.6 km3 yr−1. The estimated ETa product presented in this study is useful for an improved understanding of changes in energy and water cycle on the TP. The dataset is freely available at the Science Data Bank (https://doi.org/10.11922/sciencedb.t00000.00010; Han et al., 2020b) and at the National Tibetan Plateau Data Center (https://doi.org/10.11888/Hydro.tpdc.270995, Han et al., 2020a).

scholarly journals Long term variations of actual evapotranspiration over the Tibetan Plateau

2021 ◽  
Author(s):  
Cunbo Han ◽  
Yaoming Ma ◽  
Binbin Wang ◽  
Lei Zhong ◽  
Weiqiang Ma ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Tibetan Plateau ◽  
Water Cycle ◽  
Meteorological Data ◽  
Correlation Coefficients ◽  
Actual Evapotranspiration ◽  
The Tibetan Plateau ◽  
Atmosphere Interaction ◽  
Mean Square Errors

Abstract. Terrestrial actual evapotranspiration (ETa) is a key parameter controlling the land-atmosphere interaction processes and the water cycle. However, the spatial distribution and temporal changes of ETa over the Tibetan Plateau (TP) remain very uncertain. Here we estimate the multiyear (2001–2018) monthly ETa and its spatial distribution on the TP by a combination of meteorological data and satellite products. Validation against data from six eddy-covariance monitoring sites yielded a root mean square errors ranging from 9.3 to 14.5 mm mo−1, and correlation coefficients exceeding 0.9. The domain mean of annual ETa on the TP decreased slightly (−1.45 mm yr−1, p 

scholarly journals The Precipitation Variations in the Qinghai-Xizang (Tibetan) Plateau during 1961-2015

2017 ◽  
Author(s):  
Guoning Wan ◽  
Meixue Yang ◽  
Zhaochen Liu ◽  
Xuejia Wang ◽  
Xiaowen Liang
Keyword(s):  
Spatial Distribution ◽  
Tibetan Plateau ◽  
Precipitation Variability ◽  
Annual Precipitation ◽  
The Tibetan Plateau ◽  
Four Seasons ◽  
Winter Half ◽  
Summer Half ◽  
Surrounding Areas ◽  
Autumn And Winter

The Tibetan Plateau(TP) is known as &lsquo;the water tower of Asian&rsquo;, its precipitation variation play an important role in the eco-hydrological processes and water resources regimes. based on the monthly mean precipitation data of 65 meteorological stations over the Tibetan Plateau and the surrounding areas from 1961-2015,variations, trends and temporal-spatial distribution were analyzed, furthermore, the possible reasons were also discussed preliminarily. The main results are summarized as follows: the annual mean precipitation in the TP is 465.54mm during 1961-2015, among four seasons, the precipitation in summer accounts for 60.1% of the annual precipitation, the precipitation in summer half year (May.- Oct.) accounts for 91.0% while that in winter half year (Nov.- Apr.) only accounts for 9.0%; During 1961-2015, the annual precipitation variability is 0.45mm/a and the seasonal precipitation variability is 0.31mm/a, 0.13mm/a, -0.04mm/a and 0.04mm/a in spring, summer, autumn and winter respectively on the TP; The spatial distribution of precipitation can be summarized as decreasing from southeast to northwest in the TP, the trend of precipitation is decreasing with the increase of altitude, but the correlation is not significant. The rising of air temperature and land cover changes may cause the precipitation by changing the hydrologic cycle and energy budget, furthermore, different pattern of atmospheric circulation can also influence on precipitation variability in different regions.

scholarly journals Evaluation of high-resolution satellite precipitation products using rain gauge observations over the Tibetan Plateau

2012 ◽  
Vol 9 (8) ◽  
pp. 9503-9532 ◽  
Author(s):  
Y. C. Gao ◽  
M. F. Liu
Keyword(s):  
High Resolution ◽  
Tibetan Plateau ◽  
Correlation Coefficients ◽  
Tropical Rainfall Measuring Mission ◽  
Global Precipitation Climatology Project ◽  
Rain Gauge ◽  
The Tibetan Plateau ◽  
Satellite Precipitation ◽  
Precipitation Estimation ◽  
Mean Square Errors

Abstract. High-resolution satellite precipitation products are very attractive for studying the hydrologic processes in mountainous areas where rain gauges are generally sparse. Three high-resolution satellite precipitation products are evaluated using gauge measurements over different climate zones of the Tibetan Plateau (TP) within a 6 yr period from 2004 to 2009. The three satellite-based precipitation datasets are: Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA), Climate Prediction Center Morphing Technique (CMOPRH) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network (PERSIANN). TMPA and CMORPH, with higher correlation coefficients and lower root mean square errors (RMSEs), show overall better performance than PERSIANN. TMPA has the lowest biases among the three precipitation datasets, which is likely due to the correction process against monthly gauge observations from global precipitation climatology project (GPCP). The three products show better agreement with gauge measurements over humid regions than that over arid regions where correlation coefficients are less than 0.5. Moreover, the three precipitation products generally tend to overestimate light rainfall (0–10 mm) and underestimate moderate and heavy rainfall (>10 mm). PERSIANN produces obvious underestimation at low elevations and overestimation at high elevations. CMORPH and TMPA do not present strong bias-elevation relationships in most regions of TP.

scholarly journals Evaluation of high-resolution satellite precipitation products using rain gauge observations over the Tibetan Plateau

2013 ◽  
Vol 17 (2) ◽  
pp. 837-849 ◽  
Author(s):  
Y. C. Gao ◽  
M. F. Liu
Keyword(s):  
High Resolution ◽  
Tibetan Plateau ◽  
Correlation Coefficients ◽  
Global Precipitation Climatology Project ◽  
Rain Gauge ◽  
Data Sets ◽  
The Tibetan Plateau ◽  
Precipitation Data ◽  
Satellite Precipitation ◽  
Mean Square Errors

Abstract. High-resolution satellite precipitation products are very attractive for studying the hydrologic processes in mountainous areas where rain gauges are generally sparse. Four high-resolution satellite precipitation products are evaluated using gauge measurements over different climate zones of the Tibetan Plateau (TP) within a 6 yr period from 2004 to 2009. The four satellite-based precipitation data sets are: Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis 3B42 version 6 (TMPA) and its Real Time version (TMPART), Climate Prediction Center Morphing Technique (CMOPRH) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network (PERSIANN). TMPA and CMORPH, with higher correlation coefficients and lower root mean square errors (RMSEs), show overall better performance than PERSIANN and TMPART. TMPA has the lowest biases among the four precipitation data sets, which is likely due to the correction process against the monthly gauge observations from global precipitation climatology project (GPCP). TMPA also shows large improvement over TMPART, indicating the importance of gauge-based correction on accuracy of rainfall. The four products show better agreement with gauge measurements over humid regions than that over arid regions where correlation coefficients are less than 0.5. Moreover, the four precipitation products generally tend to overestimate light rainfall (0–10 mm) and underestimate moderate and heavy rainfall (>10 mm). Moreover, this study extracts 24 topographic variables from a DEM (digital elevation model) and uses a linear regression model to explore the bias–topography relationship. Results show that biases of TMPA and CMORPH present weak dependence on topography. However, biases of TMPART and PERSIANN present dependence on topography and variability of elevation and surface roughness plays important roles in explaining their biases.

scholarly journals Estimating Water Vapor Using Signals from Microwave Links below 25 GHz

2021 ◽  
Vol 13 (8) ◽  
pp. 1409
Author(s):  
Kun Song ◽  
Xichuan Liu ◽  
Taichang Gao ◽  
Peng Zhang
Keyword(s):  
Water Vapor ◽  
Weather Forecasting ◽  
Water Cycle ◽  
Correlation Coefficients ◽  
Support Vector ◽  
Vapor Density ◽  
Measurement Resolution ◽  
Sensing Model ◽  
Numerical Weather Forecasting ◽  
Mean Square Errors

Water vapor is a key element in both the greenhouse effect and the water cycle. However, water vapor has not been well studied due to the limitations of conventional monitoring instruments. Recently, estimating rain rate by the rain-induced attenuation of commercial microwave links (MLs) has been proven to be a feasible method. Similar to rainfall, water vapor also attenuates the energy of MLs. Thus, MLs also have the potential of estimating water vapor. This study proposes a method to estimate water vapor density by using the received signal level (RSL) of MLs at 15, 18, and 23 GHz, which is the first attempt to estimate water vapor by MLs below 20 GHz. This method trains a sensing model with prior RSL data and water vapor density by the support vector machine, and the model can directly estimate the water vapor density from the RSLs without preprocessing. The results show that the measurement resolution of the proposed method is less than 1 g/m3. The correlation coefficients between automatic weather stations and MLs range from 0.72 to 0.81, and the root mean square errors range from 1.57 to 2.31 g/m3. With the large availability of signal measurements from communications operators, this method has the potential of providing refined data on water vapor density, which can contribute to research on the atmospheric boundary layer and numerical weather forecasting.

scholarly journals Plants and Microbes Mediate the Shift in Ecosystem Multifunctionality From Low to High Patterns Across Alpine Grasslands on the Tibetan Plateau

2021 ◽  
Vol 12 ◽  
Author(s):  
Yi Wang ◽  
Miao Liu ◽  
Youchao Chen ◽  
Tao Zeng ◽  
Xuyang Lu ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Correlation Coefficients ◽  
Terrestrial Ecosystems ◽  
Alpine Grassland ◽  
Future Climate Change ◽  
The Tibetan Plateau ◽  
Grassland Ecosystem ◽  
The Impact ◽  
Ecosystem Multifunctionality ◽  
Alpine Grassland Ecosystem

Both plant communities and soil microbes have been reported to be correlated with ecosystem multifunctionality (EMF) in terrestrial ecosystems. However, the process and mechanism of aboveground and belowground communities on different EMF patterns are not clear. In order to explore different response patterns and mechanisms of EMF, we divided EMF into low (&lt;0) and high patterns (&gt;0). We found that there were contrasting patterns of low and high EMF in the alpine grassland ecosystem on the Tibetan Plateau. Specifically, compared with low EMF, environmental factors showed higher sensitivity to high EMF. Soil properties are critical factors that mediate the impact of community functions on low EMF based on the change of partial correlation coefficients from 0 to 0.24. In addition, plant community functions and microbial biomass may mediate the shift of EMF from low to high patterns through the driving role of climate across the alpine grassland ecosystem. Our findings will be vital to clarify the mechanism for the stability properties of grassland communities and ecosystems under ongoing and future climate change.

scholarly journals Seasonal variations in aerosol optical properties over China

2008 ◽  
Vol 8 (3) ◽  
pp. 8431-8453 ◽  
Author(s):  
Y. Wang ◽  
J. Xin ◽  
Z. Li ◽  
S. Wang ◽  
P. Wang ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Seasonal Variations ◽  
Rural Areas ◽  
Meteorological Data ◽  
Agricultural Practices ◽  
Hainan Island ◽  
Northern China ◽  
The Tibetan Plateau ◽  
Northern Forest ◽  
Aerosol Emissions

Abstract. The seasonal variations in background aerosol optical depth (AOD) and aerosol type are investigated over various ecosystems in China based upon three years' worth of meteorological data and data collected by the Chinese Sun Hazemeter Network. In most parts of China, AODs are at a maximum in spring or summer and at a minimum in autumn or winter. Minimum values (0.10~0.20) of annual mean AOD at 500 nm are found in the Qinghai-Tibetan Plateau, which is located in the remote northeast corner of China, the northern forest ecosystems and Hainan Island. Annual mean AOD ranges from 0.25 to 0.30 over desert and oasis areas as well as the desertification grasslands in northern China; the annual mean AOD over the Loess Plateau is moderately high at 0.36. Regions where the highest density of agricultural and industrial activities are located and where anthropogenic sulphate aerosol and soil aerosol emissions are consistently high throughout the whole year (e.g. the central-eastern, southern and eastern coastal regions of China) experience annual mean AODs ranging from 0.50~0.80. Remarkable seasonal changes in the main types of aerosol over northern China (characterized by the Angstrom exponent, α) are seen. Due to biomass and fossil fuel burning from extensive agricultural practices in northern rural areas, concentrations of smoke and soot aerosols rise dramatically during autumn and winter (high α), while the main types of aerosol during spring and summer are dust and soil aerosols (low α). Over southeast Asia, biomass burning during the spring leads to increases in smoke and soot emissions. Over the Tibetan Plateau and Hainan Island where the atmosphere is pristine, the main types of aerosol are dust and sea salt, respectively.

Recent climate changes over the Tibetan Plateau and their impacts on energy and water cycle: A review

2014 ◽  
Vol 112 ◽  
pp. 79-91 ◽  
Author(s):  
Kun Yang ◽  
Hui Wu ◽  
Jun Qin ◽  
Changgui Lin ◽  
Wenjun Tang ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Climate Changes ◽  
Water Cycle ◽  
The Tibetan Plateau ◽  
Recent Climate

scholarly journals Comparison of satellite-based evapotranspiration estimates over the Tibetan Plateau

2016 ◽  
Vol 20 (8) ◽  
pp. 3167-3182 ◽  
Author(s):  
Jian Peng ◽  
Alexander Loew ◽  
Xuelong Chen ◽  
Yaoming Ma ◽  
Zhongbo Su
Keyword(s):  
Tibetan Plateau ◽  
Vegetation Index ◽  
Water Cycle ◽  
Global Climate ◽  
Spatial Scales ◽  
Accurate Estimation ◽  
The Tibetan Plateau ◽  
North West ◽  
Comparison Results ◽  
Normalised Difference Vegetation Index

Abstract. The Tibetan Plateau (TP) plays a major role in regional and global climate. The understanding of latent heat (LE) flux can help to better describe the complex mechanisms and interactions between land and atmosphere. Despite its importance, accurate estimation of evapotranspiration (ET) over the TP remains challenging. Satellite observations allow for ET estimation at high temporal and spatial scales. The purpose of this paper is to provide a detailed cross-comparison of existing ET products over the TP. Six available ET products based on different approaches are included for comparison. Results show that all products capture the seasonal variability well with minimum ET in the winter and maximum ET in the summer. Regarding the spatial pattern, the High resOlution Land Atmosphere surface Parameters from Space (HOLAPS) ET demonstrator dataset is very similar to the LandFlux-EVAL dataset (a benchmark ET product from the Global Energy and Water Cycle Experiment), with decreasing ET from the south-east to north-west over the TP. Further comparison against the LandFlux-EVAL over different sub-regions that are decided by different intervals of normalised difference vegetation index (NDVI), precipitation, and elevation reveals that HOLAPS agrees best with LandFlux-EVAL having the highest correlation coefficient (R) and the lowest root mean square difference (RMSD). These results indicate the potential for the application of the HOLAPS demonstrator dataset in understanding the land–atmosphere–biosphere interactions over the TP. In order to provide more accurate ET over the TP, model calibration, high accuracy forcing dataset, appropriate in situ measurements as well as other hydrological data such as runoff measurements are still needed.

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