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At least 649 records · Page 36

Evidence that Horizontal Moisture Advection Regulates the Ubiquitous Amplification of Rainfall Variability over Tropical Oceans

The column moist static energy (MSE) budget equation approximates the processes associated with column moistening and drying in the tropics, and is therefore predictive of precipitation amplification and decay. We use ERA-Interim (ERA-I) and TRMM 3B42 data to investigate day-to-day convective variability and distinguish the roles of horizontal MSE (or moisture) advection versus vertical advection, sources, and sinks. Over tropical convergence zones, results suggest that horizontal moisture advection is a primary driver of day-to-day precipitation fluctuations; when drying via horizontal moisture advection is smaller (greater) than Chikira’s “column process,” precipitation tends to amplify (decay). In the absence of horizontal moisture advection, precipitation tends to increase spontaneously almost universally through a positive column process feedback. This bulk positive feedback is characterized by negative effective gross moist stability (GMS), which is maintained throughout the tropical convergence zones. How this positive feedback is achieved varies geographically, depending on the shape of vertical velocity (omega) profiles. In regions where omega profiles are top-heavy, the effective GMS is negative primarily owing to strong feedbacks between convection and diabatic MSE sources (radiative and surface fluxes). In these regions, vertical MSE advection stabilizes the atmosphere (positive vertical GMS). Where omega profiles are bottom-heavy, by contrast, a positive feedback is primarily driven by import of MSE through a shallow circulation (negative vertical GMS). The diabatic feedback and vertical GMS are in a seesaw balance, offsetting one another. Our results suggest that ubiquitous convective variability is amplified by the same mechanism as moisture-mode instability.

horizontal moisture advection↗

Dam Construction in Lancang-Mekong River Basin Could Mitigate Future Flood Risk From Warming-Induced Intensified Rainfall

Water resources management, in particular flood control, in the Mekong River Basin (MRB) faces two key challenges in the 21st century: climate change and dam construction. Herein, a large scale distributed Geomorphology-Based Hydrological Model coupled with a simple reservoir regulation model (GBHM-MK-SOP) is used to investigate the relative effects of climate change and dam construction on the flood characteristics in the MRB. Results suggest an increase in both flood magnitude and frequency under climate change, which is more severe in the upstream basin and increases over time. However, dam construction and stream regulation reduce flood risk consistently throughout this century, with more obvious effects in the upstream basin where larger reservoirs will be located. The flood mitigation effect of dam regulation dominates over the flood intensification effect of climate change before 2060, but the latter emerges more prominently after 2060 and dominates the flood risk especially in the lower basin.

54 ENVIRONMENTAL SCIENCES↗

Near-Real-Time Statistical Analysis and Visualization of Streamflow from a Deep-Learning Rainfall-Runoff Model

Near-real-time (NRT) streamflow data are critical importance for timely water resources management. Here, we developed an open-source tool, FlowStats, for NRT streamflow analysis and visualization in Germany, based on NRT meteorological data from the German Weather Service and simulated streamflow from a long short-term memory neural network (LSTM). The LSTM model achieved very good overall performance, median NSE of 0.80 for the test period across 1,479 catchments. FlowStats provides options for deriving various streamflow statistics, from normal and abnormal streamflow detection to drought and flood analyses. An example analysis from FlowStats revealed widespread below-normal to extreme low-flow conditions across Germany from March to May 2025, which weakened from June to September 2025. Drought analysis for September 2025 highlighted severe to extreme drought conditions in northwestern Germany, while flood classifications indicated that high-flow events occurred in southwestern Germany. FlowStats can be used for various hydrological assessments to support water resources management.

Hydrological modeling↗