ALBERT

Description: Connecting the plateau with cratons in east China, the eastern margin of the Tibetan Plateau is an area with the youngest uplift, strongest deformation, and frequent occurrence of large earthquakes. This region where the topographic characteristics change significantly from south to north becomes an ideal experimental site for investigating the continental geodynamics and seismogenic environment. Most seismological researchers use seismic velocity to constrain the rheological strength and crustal flow distribution in the lithosphere, upon which the deformation can be explored for the crust and upper mantle. However, seismic velocity is related to both rock strength and composition. Therefore, the multiplicity of geodynamic interpretation is unavoidable. However, seismic attenuation is a direct observation of deep temperature and rheological strength. Therefore, we construct a broadband high-resolution layered attenuation model for the lithosphere in the eastern margin of the Tibetan Plateau by using the Pg, Lg, Pn, and Sn waves propagating in the crust and uppermost mantle. The attenuation model provides a fine structure with 3D rheological strength and thermal distribution in the lithosphere. We investigate the dynamic origins of the distribution of soft ductile materials and upon which we exploit the tectonic evolution and seismogenic environment under the lithospheric compression and collision in the eastern margin of the Tibetan Plateau. This research was supported by the National Natural Science Foundation of China (U2139206, 41974061, and 41974054).

Description: For urban flood simulation, Digital Elevation Model (DEM) provides essential topographic information for understanding and predicting the flow process. Although advanced techniques such as Light Detection and Ranging (LiDAR) can acquire surface elevation information at a rather high resolution, there is still a gap between detailed measurement data and accurate topographic representation for refined flood simulation on a heterogeneous surface with complex artificial infrastructures, which requires incorporating appropriate consideration of critical features during discretizing the simulation domain. In addition to surface elements, nodal elevation information of the underground pipeline system is often unavailable for the simulation, which inevitably necessitates time-consuming manual specification and directly constrains the precision of drainage process modeling. In this work, we develop an automated modeling toolset – AUTO-SHEDS (Automated UnsTructured urban flood Simulator using High-rEsolution DEM) to tackle the above challenges. For surface topography representation, AUTO-SHEDS introduces image processing-based algorithms to improve the efficiency of elevation data curation and boundary condition identification around typical riparian areas. For underground elevation specification, AUTO-SHEDS establishes mathematical programming-based solutions to allow the reconstruction of nodal elevation of pipelines constrained by realistic monotonic conditions and partially observed data. Furthermore, AUTO-SHEDS adopts a unified numerical scheme for flow simulation on both continuous and discontinuous topography, which enhances model capacities in simulating the interaction between fluvial flooding and pluvial inundation during extreme events. The performance of developed methods is demonstrated and validated in a highly urbanized area in Beijing, which reveals the promising potential of AUTO-SHEDS in urban flood forecasting.

Description: Long short-term memory (LSTM) networks have been proved to work favorably in precipitation-runoff modeling due to their outstanding performance in processing long-length temporal dynamics. However, the other hydrological processes and the spatial information are rarely incorporated in current LSTM hydrological models, which hinders the models from making full use of hydrological data. This study proposes a spatiotemporal deep-learning (DL)-based hydrological model, by coupling the 2-Dimension convolutional neural network (CNN) and LSTM and introducing actual evaporation (E) as an additional training target. We use three large mountainous basins on the Tibetan Plateau to test the proposed CNN-LSTM model and compare the results to the LSTM-only model. Further analyses are conducted to explore meteorological and hydrological information hidden in the CNN and LSTM based on the linear regression model. Results indicate that both LSTM and CNN-LSTM hydrological models perform well on runoff (Q) and E simulation, with Nash-Sutcliffe efficiency coefficients (NSE) higher than 0.82 and 0.95, respectively. Involving CNN in the LSTM-only Q model to capture spatial information enhances the overall and peak Q modeling performance. Multi-task simulation with LSTM-only models show better accuracy in the estimation of Q volume and performance. On the other hand, we conclude that CNN models can capture the basin spatially-averaged values from 2-D spatial meteorological data. The internal cells of LSTM models for Q (E) contain the E (Q) process. This study provides an essential tool for accurate flood forecasting and management in large mountainous basins.

Description: A record-breaking precipitation event caused 398 deaths and 20.06 billion RMB economic losses in Henan Province of China in July 2021. A maximum 24-h (1-h) precipitation of 624 mm (201.9mm) was observed at the Zhengzhou weather station. However, all global operational forecast models failed to predict the intensity and location of maximum precipitation for the event. This high social impact event has drawn much attention from the research community. This study provides a high-level review of the event and its research from the perspectives of observations, analysis, dynamics, predictability, and the connection with climate warming and urbanization.Global reanalysis revealed obvious abnormality in large-scale circulation patterns that resulted in abundant moisture supplies in the region of interest. Recent studies of this event also revealed, via high-resolution model simulation and data assimilation, that three mesoscale systems (a mesoscale low pressure system, a barrier jet and downslope gravity current) contributed to the local intensification of the rainstorm. Further, observational analysis suggested that an abrupt increase of graupel through microphysical processes contributed to the record-breaking precipitation. Although these findings aided in our understanding of the extreme rainfall event, preliminary analysis indicated that the practical predictability of the extreme rainfall for this event was rather low. The contrary influences of climate warming and urbanization on precipitation extremes as revealed by two studies could add further challenges to the predictability. We concluded by emphasizing that data sharing and collaboration between meteorological and hydrological researchers would be crucial in the future research on high-impact weather events.

Description: Hailstones have large damage potential; however, their explicit prediction remains quite challenging. The uncertainty in model's initial condition and microphysics are two of the significant contributors to the challenge. This study therefore aims to investigate the impacts of improved initial condition and microphysics on surface hail size and location prediction for a moderate hailstorm occurred in Beijing on 10 June 2016 using the WRF Model’s 3DVar system and the latest revised MP38 bulk scheme. The role of initial condition on hail prediction is first explored by assimilating high-resolution radar and surface observations. Results indicate that DA significantly improves the FSS score of hail size and location prediction. However, even with more accurate initial condition provided by DA, hail prediction still can be affected by microphysical parameterization processes. Then, the role of microphysics is discussed by comparing MP38 with two earlier schemes. MP38 is a newly revised two-moment hail-aware scheme that predicts graupel number concentration (N〈sub〉g〈/sub〉) and density, such modifications produced a smaller and more realistic forecast of hail size because of improved simulation of mass-weighted mean graupel diameter. However, it will significantly underpredict the hail size with only the revision of N〈sub〉g〈/sub〉. The smaller hail size in MP38 further led to a stronger graupel melting process and cold pool, which inhibited the development of spurious convection at the north and improved hail location prediction.The results of this work shed light on the importance of accurate representation of initial condition and microphysical processes in NWP models for explicit hail prediction.

Description: The vertical turbulent fluxes of nitrate to the base of the euphotic zone and effect of changing environmental conditions on bacterial metabolism were examined inside a cyclonic eddy (CE) and an anticyclonic eddy (AE) in an oligotrophic ocean, in order to better understand dynamics of nutrients and plankton in eddies. The turbulent nitrate flux at the base of the euphotic zone inside the CE was higher than inside the AE, while this flux contributed to 19.7‒76.3% of new production in the AE and only 〈 4.94% in the CE where new production was primarily driven by upwelling. Turbulent nitrate flux in the AE edge was higher than in the AE center, which was the most likely attributed to submesoscale processes. In contrast, the reverse pattern occurred in the CE, primarily due to difference in turbulent diffusivity. In addition, changes in environmental conditions in eddies mediate bacterial metabolism. The upwelling improved nutrient availability and bacterial production in CE. The enhanced temperature induced by downwelling in AE increased the cell-specific bacterial respiration. Our findings improved our understanding of biogeochemical processes in eddies in oceans.

Description: Saline water is a common fluid on the Earth‘s surface and in ice planets. Potassium chloride (KCl) is a common salt and is expected to be a ubiquitous solute in salt water in the Universe; however, few studies investigated the behavior of KCl-H2O system at high pressures and temperatures. In this study, powder and single-crystal X-ray diffraction (SC-XRD), Raman and Brillouin scattering combined with diamond anvil cells were used to investigate the phase relation in the KCl-H2O system for different KCl concentrations at 0–4 GPa and 298–405 K. The results of powder X-ray diffraction and Raman scattering demonstrate that a novel KCl hydrate is formed when KCl aqueous solutions transform to solid ice-VI and ice-VII at high pressure. Simultaneously, the single-crystal of KCl hydrate is synthesized from a supersaturated KCl solution at 298 K and 1.8 GPa. The structure is solved by SC-XRD, indicating a KCl monohydrate with the P21/n space group is formed. We have verified the phase stability of KCl monohydrate by using Raman spectroscopy and density functional theory. Our results indicate that KCl monohydrate is a stable phase under pressure and temperature conditions between 1.6 and 2.4 GPa and 298–359 K. By considering the thermal profile and composition of icy moons, we hypothesize that the formation and decomposition of KCl monohydrate might induce mantle convection in these moons.

Description: Interactions between soil quality and climate change may influence the capacity of croplands to produce sufficient food. Here, we address this issue by using a new dataset of soil, climate and associated yield observations for 12,115 site-years representing 90% of total cereal production in China. Across crops and environmental conditions, we show that high-quality soils reduced the sensitivity of crop yield to climate variability leading to both higher mean crop yield (10.3 ± 6.7%) and higher yield stability (decreasing variability by 15.6 ± 14.4%). High-quality soils improve the outcome for yields under climate change by 1.7% (0.5–4.0%), compared to low-quality soils. Climate-driven yield change could result in reductions of national cereal production of 11.4 Mt annually under representative concentration pathway RCP 8.5 by 2080–2099. While this production reduction was exacerbated by 14% due to soil degradation, it can be reduced by 21% through soil improvement. This study emphasizes the vital role of soil quality in agriculture under climate change.

Description: We summarise the discussions at a virtual Community Workshop on Cold Atoms in Space concerning the status of cold atom technologies, the prospective scientific and societal opportunities offered by their deployment in space, and the developments needed before cold atoms could be operated in space. The cold atom technologies discussed include atomic clocks, quantum gravimeters and accelerometers, and atom interferometers. Prospective applications include metrology, geodesy and measurement of terrestrial mass change due to, e.g., climate change, and fundamental science experiments such as tests of the equivalence principle, searches for dark matter, measurements of gravitational waves and tests of quantum mechanics. We review the current status of cold atom technologies and outline the requirements for their space qualification, including the development paths and the corresponding technical milestones, and identifying possible pathfinder missions to pave the way for missions to exploit the full potential of cold atoms in space. Finally, we present a first draft of a possible road-map for achieving these goals, that we propose for discussion by the interested cold atom, Earth Observation, fundamental physics and other prospective scientific user communities, together with the European Space Agency (ESA) and national space and research funding agencies.