Development of an 11-year (2000-2010) land surface energy balance dataset for mainland China

Abstract HKT-ISTP 2013 B

Numerical correction of anti-symmetric aberrations in single HRTEM images of weakly scattering 2D-objects

Here, we present a numerical post-processing method for removing the effect of anti-symmetric residual aberrations in high-resolution transmission electron microscopy (HRTEM) images of weakly scattering 2D-objects. The method is based on applying the same aberrations with the opposite phase to the Fourier transform of the recorded image intensity and subsequently inverting the Fourier transform. We present the theoretical justification of the method and its verification based on simulated images in the case of low-order anti-symmetric aberrations. Ultimately the method is applied to experimental hardware aberration-corrected HRTEM images of single-layer graphene and MoSe2 resulting in images with strongly reduced residual low-order aberrations, and consequently improved interpretability. Alternatively, this method can be used to estimate by trial and error the residual anti-symmetric aberrations in HRTEM images of weakly scattering objects

Comparison of satellite-based evapotranspiration estimates over the Tibetan Plateau

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 northwest 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

Growing season net ecosystem CO2 exchange of two desert ecosystems with alkaline soils in Kazakhstan

Central Asia is covered by vast desert ecosystems, and the majority of these ecosystems have alkaline soils. Their contribution to global net ecosystem CO(2) exchange (NEE) is of significance simply because of their immense spatial extent. Some of the latest research reported considerable abiotic CO(2) absorption by alkaline soil, but the rate of CO(2) absorption has been questioned by peer communities. To investigate the issue of carbon cycle in Central Asian desert ecosystems with alkaline soils, we have measured the NEE using eddy covariance (EC) method at two alkaline sites during growing season in Kazakhstan. The diurnal course of mean monthly NEE followed a clear sinusoidal pattern during growing season at both sites. Both sites showed significant net carbon uptake during daytime on sunny days with high photosynthetically active radiation (PAR) but net carbon loss at nighttime and on cloudy and rainy days. NEE has strong dependency on PAR and the response of NEE to precipitation resulted in an initial and significant carbon release to the atmosphere, similar to other ecosystems. These findings indicate that biotic processes dominated the carbon processes, and the contribution of abiotic carbon process to net ecosystem CO(2) exchange may be trivial in alkaline soil desert ecosystems over Central Asia

Long-term variations in actual evapotranspiration over the Tibetan Plateau

Actual terrestrial evapotranspiration (ET$_{a}$) is a key parameter controlling land–atmosphere interaction processes and water cycle. However, spatial distribution and temporal changes in ET$_{a}$ over the Tibetan Plateau (TP) remain very uncertain. Here we estimate the multiyear (2001–2018) monthly ET$_{a}$ 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 ET$_{a}$ on the TP decreased slightly (−1.45 mm yr$^{-1}$, p90° 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 ET$_{a}$ were pronounced in the spring and summer seasons, while almost no trends were detected in the autumn and winter seasons. The mean annual ET$_{a}$ 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 ET$_{a}$ 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)

Dysnatremia is associated with increased risk of all-cause mortality within 365 days post-discharge in patients with atrial fibrillation without heart failure: A prospective cohort study

Aim: The aim of this study is to evaluate the association between serum sodium concentrations at hospital admission and all-cause mortality within 365 days post-discharge in patients with atrial fibrillation (AF) without heart failure (HF). Methods: The prospective cohort study enrolled 1,446 patients with AF without HF between November 2018 and October 2020. A follow-up was performed 30, 90, 180, and 365 days after enrollment through outpatient visits or telephone interviews. All-cause mortality was estimated in three groups according to serum sodium concentrations: hyponatremia ( \u3c 135 mmol/L), normonatremia (135 – 145 mmol/L), and hypernatremia ( \u3e 145 mmol/L). We estimated the risk of all-cause mortalities using univariable and multivariable Cox proportional hazards models with normonatremia as the reference. Results: The all-cause mortalities of hyponatremia, normonatremia, and hypernatremia were 20.6, 9.4, and 33.3 % within 365 days post-discharge, respectively. In the univariable analysis, hyponatremia (HR: 2.19, CI 1.5 – 3.2) and hypernatremia (HR: 4.03, CI 2.32 – 7.02) increased the risk of all-cause mortality. The HRs for hyponatremia and hypernatremia were 1.55 (CI 1.05 – 2.28) and 2.55 (CI 1.45 – 4.46) after adjustment for age, diabetes mellitus, loop diuretics, antisterone, antiplatelet drugs, and anticoagulants in the patients with AF without HF. The association between serum sodium concentrations and the HRs of all-cause mortality was U-shaped. Conclusion: Dysnatremia at hospital admission was an independent factor for all-cause mortality in patients with AF without HF within 365 days post-discharge

Parameter Optimization of a Discrete Scattering Model by Integration of Global Sensitivity Analysis Using SMAP Active and Passive Observations

Active and passive microwave signatures respond differently to the land surface and provide complementary information on the characteristics of the observed scenes. The objective of this paper is to explore the synergy of active radar and passive radiometer observations at the same spatial scale to constrain a discrete radiative transfer model, the Tor Vergata (TVG) model, to gain insights into the microwave scattering and emission mechanisms over grasslands. The TVG model can simultaneously simulate the backscattering coefficient and emissivity with a set of input parameters. To calibrate this model, in situ soil moisture and temperature data collected from the Maqu area in the northeastern region of the Tibetan Plateau, interpolated leaf area index (LAI) data from the Moderate Resolution Imaging Spectroradiometer LAI eight-day products, and concurrent and coincident Soil Moisture Active Passive (SMAP) radar and radiometer observations are used. Because this model needs numerous input parameters to be driven, the extended Fourier amplitude sensitivity test is first applied to conduct global sensitivity analysis (GSA) to select the sensitive and insensitive parameters. Only the most sensitive parameters are defined as free variables, to separately calibrate the active-only model (TVG-A), the passive-only model (TVG-P), and the active and passive combined model (TVG-AP). The accuracy of the calibrated models is evaluated by comparing the SMAP observations and the model simulations. The results show that TVG-AP can well reproduce the backscattering coefficient and brightness temperature, with correlation coefficients of 0.87, 0.89, 0.78, and 0.43 and root-mean-square errors of 0.49 dB, 0.52 dB, 7.20 K, and 10.47 K for &#x03C3; HH&#x2070; , &#x03C3; VV&#x2070; , TBH, and TBV, respectively. In contrast, TVG-A and TVG-P can only accurately model the backscattering coefficient and brightness temperature, respectively. Without any modifications of the calibrated parameters, the error metrics computed from the validation data are slightly worse than those of the calibration data. These results demonstrate the feasibility of the synergistic use of SMAP active radar and passive radiometer observations under the unified framework of a physical model. In addition, the results demonstrate the necessity and effectiveness of applying GSA in model optimization. It is expected that these findings can contribute to the development of model-based soil moisture retrieval methods using active and passive microwave remote sensing data