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The accuracy and applications of synthetic aperture radar interferometry (InSAR) are severely suppressed by tropospheric error. Numerical Weather Models (NWMs) and GPS-derived tropospheric delays have been widely used to correct the tropospheric error considering their complete spatial coverage or high accuracy. However, few studies focus on the fusion of both NWMs and GPS for the tropospheric error correction. In this study, we used the Weather Research and Forecasting (WRF) to obtain NWMs with a higher spatial-temporal resolution of 3 km and 20 s from both ERAI (79 km and 6 h) and ERA5 (0.25° and 1 h). After that, we utilized the WRF Data Assimilation (WRFDA) system to assimilate the GPS ZTD into these enhanced NWMs and generate merged NWMs products. The tropospheric correction effectiveness from different NWMs products was evaluated in a case in the Pearl River Delta region of China. The results showed that all the NWMs products could correct the stratified component in the interferogram but could not mitigate the turbulence well, even after improving the spatial-temporal resolution. As for the trend component, the merged NWMs products showed obvious superiority over other products. From the statistics perspective, the stdev of the interferogram decreased further over 20% by the merged NWMs products than other products when using both ERAI and ERA5, indicating the significant effectiveness of GPS ZTD assimilation. [ABSTRACT FROM AUTHOR]

The ground-based GPS provides a promising way to assess and calibrate precipitable water vapor (PWV) products from the Moderate-Resolution Imaging Spectrometer (MODIS) which has high spatial resolution and near global coverage. This study utilized PWV at about 260 ground-based GPS stations from the Crustal Movement Observation Network of China (CMONOC) from 2015 to 2018 to comprehensively assess the MODIS Near Infrared (NIR) PWV products as well as the latest ECMWF reanalysis, ERA5. Results reveal a general underestimate of MODIS PWV compared to GPS over China, with mean bias of 1.32 mm (GPS-MODIS), compared to −0.28 mm for ERA5 (GPS-ERA5). Taking GPS PWV as references, the average MODIS PWV error root mean square (RMS) is about 5.35 mm, with correlation coefficient (R) of ~90% between GPS and MODIS PWV, compared to the RMS of 1.73 mm and R of ~98% for ERA5. PWV differences between MODIS and GPS also show clear seasonal and climate type dependency over China. A refined linear MODIS PWV calibration model taking into account of climate region difference was then developed and examined. The calibrated MODIS PWV at more than 800 independent GPS stations from China Meteorological Administration (CMA) in the year of 2016 show obvious improvements, with RMS reduced by about 14.7, 17.7, 20.9, 2.5 and 11.3% in tropical monsoon (TM), subtropical monsoon (SM), midlatitude monsoon (MM), humid continental (HC) and plateau (PL) climate region, respectively. Compared to the unified calibration model which does not distinguish the climate regions, the RMS values after calibration using the refined model are reduced by 10.5, 8.3, 9.1, and 11.9% in TM, SM, MM and Plateau climate (PL) region, respectively. In addition, bias values are reduced from 2.01, 3.42, 1.50 and 0.84 mm to 1.64, 0.33, 0.68 and −0.06 mm in TM, SM, MM, PL region, respectively. • Assessment of MODIS PWV and ERA5 PWV by using PWV at ~260 GPS stations over China from 2015 to 2018. • The temporal and spatial characteristics of MODIS PWV errors depend on season and climate type. • The climate related MODIS PWV calibration model is developed, and the calibration effect of the model is remarkable. [ABSTRACT FROM AUTHOR]

The molecular structure of soil organic matter (SOM) is closely related to the structure and functions of the rhizosphere community. In this study, a microcosm experiment was conducted to investigate the effect of straw-derived biochar on the structural differentiation of SOM and rhizosphere bacterial communities. 13 C NMR spectra showed that the relative abundance of carboxyl, alkyl, N-alkyl, O-alkyl and methoxyl groups decreased by 22%, 31%, 27%, 27% and 27%, respectively, and the relatively stable structure of aryl and O-aryl groups increased by 213% and 41%, respectively. In addition, network-based analysis showed that biochar amendment not only improved the network connectivity of the rhizosphere bacteria, but also enhanced the linkage between bacteria and the molecular structure of SOM. The topological properties of the network, including the number of edges, network density, and average clustering coefficient, were increased by 79%, 15% and 22%, respectively. Moreover, modularization analysis and structural equation model indicated that rhizosphere bacterial network was the important bio-factor affecting the content of labile carbon., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Radon is naturally released from the soil into the surface layer of the atmosphere, and by monitoring the natural radioactivity data of radon and its shot-live decay products we can get valuable information about the dilution properties of the lower boundary layer. This paper explores the dispersion characteristics of the lower layer of the atmosphere in Lanzhou, China, and the close relationship with the patterns of primary pollutants' concentrations. Measurements were conducted from July 2007 to May 2008 at one station and a fifty-day campaign was carried out at two stations in Lanzhou. The interpretation of radon radioactivity measurement showed that the measured atmospheric stability index (ASI) data at two stations in Lanzhou had statistically significant correlation, and well described the lower atmospheric layer mixing property in the area. The temporal trend of PM10 data was consistent with the temporal trend of ASI, with almost twice as high values in December than it in August. The results show that the ASI allows to highlight the dilution factor playing an important role in determining primary pollution events, and the mixing properties of the lower boundary layer is the key factor determining PM10 concentration in urban areas.