Energy exchange of an alpine grassland on the eastern Qinghai-Tibetan Plateau

Study on Spatial and Temporal Characteristics of Surface Albedo at the Northern Edge of the Badain Jaran Desert Based on C + STNLFFM Model

Obtaining surface albedo data with high spatial and temporal resolution is essential for measuring the factors, effects, and change mechanisms of regional land-atmosphere interactions in deserts. In order to obtain surface albedo data with higher accuracy and better applicability in deserts, we used MODIS and OLI as data sources, and calculated the daily surface albedo data, with a spatial resolution of 30 m, of Guaizi Lake at the northern edge of the Badain Jaran Desert in 2016, using the Spatial and Temporal Non-Local Filter-based Fusion Model (STNLFFM) and topographical correction model (C model). We then compared the results of STNLFFM and C + STNLFFM for fusion accuracy, and for spatial and temporal distribution differences in surface albedo over different underlying surfaces. The results indicated that, compared with STNLFFM surface albedo and MODIS surface albedo, the relative error of C + STNLFFM surface albedo decreased by 2.34% and 3.57%, respectively. C + STNLFFM can improve poor applicability of MODIS in winter, and better responds to the changes in the measured value over a short time range. After the correction of the C model, the spatial difference in surface albedo over different underlying surfaces was enhanced, and the spatial differences in surface albedo between shifting dunes and semi-shifting dunes, fixed dunes and saline-alkali land, and the Gobi and saline-alkali land were significant. C + STNLFFM maintained the spatial and temporal distribution characteristics of STNLFFM surface albedo, but the increase in regional aerosol concentration and thickness caused by frequent dust storms weakened the spatial difference in surface albedo over different underlying surfaces in March, which led to the overcorrection of the C model.

Remotely monitoring ecosystem respiration from various grasslands along a large-scale east-west transect across northern China

BACKGROUND

Grassland ecosystems play an important role in the terrestrial carbon cycles through carbon emission by ecosystem respiration (R_e) and carbon uptake by plant photosynthesis (GPP). Surprisingly, given R_e occupies a large component of annual carbon balance, rather less attention has been paid to developing the estimates of R_e compared to GPP.

RESULTS

Based on 11 flux sites over the diverse grassland ecosystems in northern China, this study examined the amounts of carbon released by R_e as well as the dominant environmental controls across temperate meadow steppe, typical steppe, desert steppe and alpine meadow, respectively. Multi-year mean R_e revealed relatively less CO₂ emitted by the desert steppe in comparison with other grassland ecosystems. Meanwhile, C emissions of all grasslands were mainly controlled by the growing period. Correlation analysis revealed that apart from air and soil temperature, soil water content exerted a strong effect on the variability in R_e, which implied the great potential to derive R_e using relevant remote sensing data. Then, these field-measured R_e data were up-scaled to large areas using time-series MODIS information and remote sensing-based piecewise regression models. These semi-empirical models appeared to work well with a small margin of error (R² and RMSE ranged from 0.45 to 0.88 and from 0.21 to 0.69 g C m^-2 d^-1, respectively).

CONCLUSIONS

Generally, the piecewise models from the growth period and dormant season performed better than model developed directly from the entire year. Moreover, the biases between annual mean R_e observations and the remotely-derived products were usually within 20%. Finally, the regional R_e emissions across northern China's grasslands was approximately 100.66 Tg C in 2010, about 1/3 of carbon fixed from the MODIS GPP product. Specially, the desert steppe exhibited the highest ratio, followed by the temperate meadow steppe, typical steppe and alpine meadow. Therefore, this work provides a novel framework to accurately predict the spatio-temporal patterns of R_e over large areas, which can greatly reduce the uncertainties in global carbon estimates and climate projections.

Evaluation of the rescaled complementary principle in the estimation of evaporation on the Tibetan Plateau

Accurate quantification of the terrestrial water balance can improve our knowledge of regional water cycle changes, and deepen our understanding of evaporation in hydrological cycle and under climate change. However, sparse observation networks on the Tibetan Plateau (TP) prevent the reliable estimates of actual evaporation. Based on the China regional surface Meteorological Feature Dataset (CMFD) and the Global Land Surface Satellite (GLASS) product, we adopted the latest rescaled nonlinear complementary relationship (CR) to calculate the monthly actual evaporation (E) from 1982 to 2015. We analyzed the spatio-temporal variability of the annual E on the entire TP, and explored the main meteorological factors controlling the annual E and the regulation of multiyear average annual E in different vegetation zones from southeast to northwest. Our results indicated that the net radiation (R_n) and E exhibited a favorable agreement with monthly changes of the observed values; and E estimated by the CR explained 79-96% variation of the eddy covariance flux measurements. The multiyear average E was 373.12 mm yr^-1 and displayed similar spatial patterns of decreasing from southeast to northwest with two remote sensing products (GLDAS_VIC, GLEAM_v3.3) and one hydrological model (Budyko). Additionally, based on the Mann-Kendall trend test, there were 21.56% of the TP with significant upward trend of annual E which mainly distributed in the area with dense glaciers. The Nyenchen Tanglha Mountains and Pamirs Plateau area had the most obvious upward trend, with up to over 6 mm yr^-1. In a relative sense, the key meteorological elements which affected annual E on the TP were relative humidity (RH) (r = 0.63) and R_n (r = 0.56).

Seasonal and Inter-Annual Variations in Carbon Dioxide Exchange over an Alpine Grassland in the Eastern Qinghai-Tibetan Plateau

This work analyzed carbon dioxide exchange and its controlling factors over an alpine grassland on the eastern Qinghai-Tibetan Plateau. The main results show that air temperature and photosynthetically active radiation are two dominant factors controlling daily gross primary production. Soil temperature and soil water content are the main factors controlling ecosystem respiration. Canopy photosynthetic activity is also responsible for the variation of daily ecosystem respiration other than environmental factors. No clear correlation between net ecosystem exchange and environmental factors was observed at daily scale. Temperature sensitive coefficient was observed to increase with larger soil water content. High values of temperature sensitive coefficient occurred during the periods when soil water content was high and grass was active. Annual integrated net ecosystem exchange, gross primary production and ecosystem respiration were -191, 1145 and 954 g C m^-2 for 2010, and -250, 975 and 725 g C m^-2 for 2011, respectively. Thus, this alpine grassland was a moderate carbon sink in both of the two years. Compared to alpine grasslands on the Qinghai-Tibetan Plateau, this alpine grassland demonstrated a much greater potential for carbon sequestration than others. Annual precipitation is a dominant factor controlling the variation of annual net ecosystem exchange over this grassland. The difference in gross primary production between the two years was not caused by the variation in annual precipitation. Instead, air temperature and the length of growing season had an important impact on annual gross primary production. Variation of annual ecosystem respiration was closely related to annual gross primary production and soil water content during the growing season.