|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Evaluation of surface temperature and pressure derived from MERRA-2 and ERA5 reanalysis datasets and their applications in hourly GNSS precipitable water vapor retrieval over China显示文摘Temperature and pressure play key roles in Global Navigation Satellite System(GNSS) precipitable water vapor(PWV) retrieval. The National Aeronautics and Space Administration(NASA) and European Center for Medium-Range Weather Forecasts(ECMWF) have released their latest reanalysis product: the modern-era retrospective analysis for research and applications, version 2(MERRA-2) and the fifthgeneration ECMWF reanalysis(ERA5), respectively. Based on the reanalysis data, we evaluate and analyze the accuracy of the surface temperature and pressure products in China using the the measured temperature and pressure data from 609 ground meteorological stations in 2017 as reference values.Then the accuracy of the two datasets and their performances in estimating GNSS PWV are analyzed. The PWV derived from the pressure and temperature products of ERA5 and MERRA-2 has high accuracy. The annual average biases of pressure and temperature for ERA5 are-0.07 hPa and 0.45 K, with the root mean square error(RMSE) of 0.95 hPa and 2.04 K, respectively. The annual average biases of pressure and temperature for MERRA-2 are-0.01 hPa and 0.38 K, with the RMSE of 1.08 h Pa and 2.66 K, respectively.The accuracy of ERA5 is slightly higher than that of MERRA-2. The two reanalysis data show negative biases in most regions of China, with the highest to lowest accuracy in the following order: the south,north, northwest, and Tibet Plateau. Comparing the GNSS PWV calculated using MERRA-2(GNSS MERRA-2 PWV) and ERA5(GNSS ERA5 PWV) with the radiosonde-derived PWV from 48 co-located GNSS stations and the measured PWV of the co-location radiosonde stations, it is found that the accuracy of GNSS ERA5 PWV is better than that of GNSS MERRA-2 PWV. These results show the different applicability of surface temperature and pressure products from MERRA-2 and ERA5 data, indicating that both have important applications in meteorological research and GNSS water vapor monitoring in China. | Liangke Huang Xiaoyang Fang Tengxu Zhang Haoyu Wang Lei Cui Lilong Liu | 2023 | Geodesy and Geodynamics2023，14，2： | 1 |
| 2 | HLA-B-associated transcript 3 (Bat3) stabilizes and activates p53 in a HAUSP-dependent manner显示文摘The p53 pathway is a highly complex signaling network including several key regulators.HAUSP is a critical component of the p53 pathway acting as a deubiquitinase for both p53 and its key repressor Mdm2.Here,we identified a novel HAUSP-interacting protein,HLA-B-associated transcript 3(Bat3)and found it to be capable of inducing p53 stabilization and activation via a HAUSP-dependent mechanism,resulting in cell growth inhibition.Surprisingly,the deubiquitylating enzymatic activity of HAUSP was not required for this phenomenon.Co-immunoprecipitation showed that p53 coexisted in a complex with Bat3 and HAUSP in vivo,and HAUSP may serve as a binding mediator to enhance the interaction between p53 and Bat3.Further studies revealed that formation of this three-protein complex interfered with the binding of p53 to its proteasome receptor S5a and promoted the accumulation of p53 in nucleus.Notably,Mdm2 protein abundance is also regulated by Bat3 in the presence of HAUSP.Overexpression of Bat3 and HAUSP increases Mdm2 protein levels without influencing the p53–Mdm2 interaction and Mdm2-mediated p53 ubiquitination,indicating that Bat3–HAUSP-mediated protein stabilization is not specific to p53 and different mechanisms may be involved in Bat3-mediated regulation of p53–Mdm2 pathway.Together,our study unravels a novel mechanism by which p53 is stabilized and activated by HAUSP-mediated interaction with Bat3 and implies that Bat3 might function as a tumor suppressor through the stabilization of p53. | Rui Zhang Di Cui TengXue Yue Lang Yunfan Zhang Lianjie Li Haili Sun Yu Kuang Gebin Li Jun Tang | 2020 | Journal of Molecular Cell Biology2020，12，2： | 0 |
| 3 | Periodic signal extraction of GNSS height time series based on adaptive singular spectrum analysis显示文摘Singular spectrum analysis is widely used in geodetic time series analysis.However,when extracting time-varying periodic signals from a large number of Global Navigation Satellite System(GNSS)time series,the selection of appropriate embedding window size and principal components makes this method cumbersome and inefficient.To improve the efficiency and accuracy of singular spectrum analysis,this paper proposes an adaptive singular spectrum analysis method by combining spectrum analysis with a new trace matrix.The running time and correlation analysis indicate that the proposed method can adaptively set the embedding window size to extract the time-varying periodic signals from GNSS time series,and the extraction efficiency of a single time series is six times that of singular spectrum analysis.The method is also accurate and more suitable for time-varying periodic signal analysis of global GNSS sites. | Chenfeng Li Peibing Yang Tengxu Zhang Jiachun Guo | 2024 | Geodesy and Geodynamics2024，15，1： | 0 |
| 4 | A new method for coseismic offset detection from GPS coordinate time series显示文摘Currently,the extraction of coseismic offset signals primarily relies on earthquake catalog data to determine the occurrence time of earthquakes.This is followed by the process of differencing the average GPS coordinate time series data,with a time interval of 3 to 5 days before and after the earthquake.In the face of the huge amount of GPS coordinate time series data today,the conventional approach of relying on earthquake catalog data to assist in obtaining coseismic offset signals has become increasingly burdensome.To address this problem,we propose a new method for automatically detecting coseismic offset signals in GPS coordinate time series without an extra earthquake catalog for reference.Firstly,we pre-process the GPS coordinate time series data for filtering out stations with significant observations missing and detecting and removing outliers.Secondly,we eliminate other signals and errors in the GPS coordinate time series,such as trend and seasonal signals,leaving the coseismic offset signals as the primary signal.The resulting coordinate time series is then modeled using the first-order difference and data stacking method.The modeling method enables automatic detection of the coseismic offset signals in the GPS coordinate time series.The aforementioned method is applied to automatically detect coseismic offset signals using simulated data and the Searles Valley GPS data in California,USA.The results demonstrate the efficacy of our proposed method,successfully detecting coseismic offsets from vast amounts of GPS coordinate time series data. | Zhiwei Yang Guangyu Xu Tengxu Zhang Mingkai Chen FeiWu Zhiping Chen | 2023 | Geodesy and Geodynamics2023，14，6： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员