The assimilation of dual-polarization(dual-pol)radar data plays a crucial role in enhancing the simulation of hydrometeors and improving the short-term precipitation forecasts of numerical weather prediction(NWP)model...The assimilation of dual-polarization(dual-pol)radar data plays a crucial role in enhancing the simulation of hydrometeors and improving the short-term precipitation forecasts of numerical weather prediction(NWP)models.However,existing dual-pol radar data assimilation(DA)methods exhibit limitations in terms of computational efficiency and data utilization.In this study,a new dual-pol radar DA approach is developed that utilizes a UNet-based model to retrieve mixing ratio information for four hydrometeor species from dual-pol radar data.The validation results for the UNet-based model indicate that the distributions of the retrieved hydrometeor mixing ratios provided by the model align well with the labeled data,yielding a reasonable range of root mean square errors(RMSEs).On this basis,the hydrometeor analysis increments retrieved by the UNet-based model are incorporated into the model integration process through the incremental analysis update(IAU)scheme,establishing a complete dual-pol radar DA framework for the CMA-MESO model.To evaluate the efficacy of this DA scheme,comparative simulation experiments were conducted for Typhoon Lekima(2019).Verification results indicate that using the hydrometeor DA scheme generally improves the threat scores(TSs)for 3-hour accumulated precipitation during medium-and heavy-rainfall events.Additionally,the 24-hour accumulated rainfall TSs for the medium-,heavy-,and extreme-precipitation categories in the DA experiment are all superior to those in the control experiment.The DA method also yields superior predictions of the spatial distribution of extremerainfall events.These results demonstrate that the proposed dual-pol radar DA approach effectively enhances the precipitation forecasting capabilities of numerical weather models.展开更多
Quantitative characterization of environmental characteristics of cropland(ECC)plays an important role in maintaining sustainable development of agricultural systems and ensuring regional food security. In this study,...Quantitative characterization of environmental characteristics of cropland(ECC)plays an important role in maintaining sustainable development of agricultural systems and ensuring regional food security. In this study, the changes in ECC over the Songnen Plain, a major grain crops production region in Northeast China, were investigated for the period 1990–2015. The results revealed significant changes in climate conditions, soil physical properties and cropland use patterns with socioeconomic activities. Trends in climate parameters showed increasing temperature(+0.49°C/decade, p < 0.05) and decreasing wind speed(–0.3 m/s/decade, p < 0.01) for the growing season, while sunshine hours and precipitation exhibited non-significant trends. Four topsoil parameters including soil organic carbon(SOC), clay, bulk density and pH, indicated deteriorating soil conditions across most of the croplands, although some do exhibited slight improvement. The changing amplitude for each of the four above parameters ranged within –0.052 to 0.029 kg C/kg, –0.38 to 0.30,–0.60 to 0.39 g/cm^3, –3.29 to 2.34, respectively. Crop production significantly increased(44.0 million tons) with increasing sown area of croplands(～2.5 million ha) and fertilizer application(～2.5 million tons). The study reveals the dynamics of ECC in the Songnen Plain with intensive cultivation from 1990 to 2015. Population growth, economic development, and policy reform are shown to strongly influence the spatiotemporal changes in cropland characteristics.The study potentially provides valuable scientific information to support sustainable agroecosystem management in the context of global climate change and national socioeconomic development.展开更多
Fifty-five evergreen tree's leaves growing less than one year were collected from Shougang industrial area in western suburb of Beijing, including steel plants and its ambient residential areas, recreational parks...Fifty-five evergreen tree's leaves growing less than one year were collected from Shougang industrial area in western suburb of Beijing, including steel plants and its ambient residential areas, recreational parks and farmlands. Rock magnetic properties and heavy metal contents were studied. The results show that the magnetic properties of leaf samples are predominated by low-coercivity magnetite, and both the concentration and grain size of magnetite particles gradually decreased with the distance from the main pollution source increases. Moreover, there is a significant linear relationship between magnetic parameters (the low-field magnetic susceptibility, saturation isothermal remanent magnetization and anhysteretic remanent magnetization) and heavy metals contents (Fe, Pb, V, Cr and Zn) (0.73≤R≤ 0.88). Hence, the magnetic parameters of leaves can serve as a proxy for quick detecting of the recent atmospheric metallic pollution.展开更多
基金Major Key Project of PCL(PCL2025A10)Open Research Project of the China Meteorological Administration Hydro-Meteorology Key Laboratory(23SWQXM036)+2 种基金National Natural Science Foundation of China(42375160)Project of the Key Laboratory of Atmospheric Sounding of China Meteorological Administration(2022KLAS06M)Science and Technology Research Project of the Guangdong Provincial Meteorological Bureau(GRMC2024M04)。
文摘The assimilation of dual-polarization(dual-pol)radar data plays a crucial role in enhancing the simulation of hydrometeors and improving the short-term precipitation forecasts of numerical weather prediction(NWP)models.However,existing dual-pol radar data assimilation(DA)methods exhibit limitations in terms of computational efficiency and data utilization.In this study,a new dual-pol radar DA approach is developed that utilizes a UNet-based model to retrieve mixing ratio information for four hydrometeor species from dual-pol radar data.The validation results for the UNet-based model indicate that the distributions of the retrieved hydrometeor mixing ratios provided by the model align well with the labeled data,yielding a reasonable range of root mean square errors(RMSEs).On this basis,the hydrometeor analysis increments retrieved by the UNet-based model are incorporated into the model integration process through the incremental analysis update(IAU)scheme,establishing a complete dual-pol radar DA framework for the CMA-MESO model.To evaluate the efficacy of this DA scheme,comparative simulation experiments were conducted for Typhoon Lekima(2019).Verification results indicate that using the hydrometeor DA scheme generally improves the threat scores(TSs)for 3-hour accumulated precipitation during medium-and heavy-rainfall events.Additionally,the 24-hour accumulated rainfall TSs for the medium-,heavy-,and extreme-precipitation categories in the DA experiment are all superior to those in the control experiment.The DA method also yields superior predictions of the spatial distribution of extremerainfall events.These results demonstrate that the proposed dual-pol radar DA approach effectively enhances the precipitation forecasting capabilities of numerical weather models.
基金National Natural Science Foundation of China,No.41571410,No.41571199,No.41401589
文摘Quantitative characterization of environmental characteristics of cropland(ECC)plays an important role in maintaining sustainable development of agricultural systems and ensuring regional food security. In this study, the changes in ECC over the Songnen Plain, a major grain crops production region in Northeast China, were investigated for the period 1990–2015. The results revealed significant changes in climate conditions, soil physical properties and cropland use patterns with socioeconomic activities. Trends in climate parameters showed increasing temperature(+0.49°C/decade, p < 0.05) and decreasing wind speed(–0.3 m/s/decade, p < 0.01) for the growing season, while sunshine hours and precipitation exhibited non-significant trends. Four topsoil parameters including soil organic carbon(SOC), clay, bulk density and pH, indicated deteriorating soil conditions across most of the croplands, although some do exhibited slight improvement. The changing amplitude for each of the four above parameters ranged within –0.052 to 0.029 kg C/kg, –0.38 to 0.30,–0.60 to 0.39 g/cm^3, –3.29 to 2.34, respectively. Crop production significantly increased(44.0 million tons) with increasing sown area of croplands(～2.5 million ha) and fertilizer application(～2.5 million tons). The study reveals the dynamics of ECC in the Songnen Plain with intensive cultivation from 1990 to 2015. Population growth, economic development, and policy reform are shown to strongly influence the spatiotemporal changes in cropland characteristics.The study potentially provides valuable scientific information to support sustainable agroecosystem management in the context of global climate change and national socioeconomic development.
基金the National Natural Science Foundation of China (Grant Nos. 40374021, 40674033, 40172102)DFG project (AP 34/21)
文摘Fifty-five evergreen tree's leaves growing less than one year were collected from Shougang industrial area in western suburb of Beijing, including steel plants and its ambient residential areas, recreational parks and farmlands. Rock magnetic properties and heavy metal contents were studied. The results show that the magnetic properties of leaf samples are predominated by low-coercivity magnetite, and both the concentration and grain size of magnetite particles gradually decreased with the distance from the main pollution source increases. Moreover, there is a significant linear relationship between magnetic parameters (the low-field magnetic susceptibility, saturation isothermal remanent magnetization and anhysteretic remanent magnetization) and heavy metals contents (Fe, Pb, V, Cr and Zn) (0.73≤R≤ 0.88). Hence, the magnetic parameters of leaves can serve as a proxy for quick detecting of the recent atmospheric metallic pollution.
