Stream metabolism is a key biogeochemical process in river networks, synthesising the balance between gross primary production (GPP) and ecosystem respiration (ER). Globally, more rivers and streams are drying due to climate change and water abstraction for human uses and this can alter the organic carbon residence time, leading to decoupled ER and terrestrial organic matter supply. While the consequences of drying on CO2 emissions have been recently quantified, its effects on stream metabolism are still poorly studied. We addressed the short- and long-term effects of drying on stream metabolism by monitoring oxygen dynamics at 20 reaches across a drying river network, including perennial (PR) and non-perennial reaches (NPR) for one year. We also calculated several climatic, land use variables and characterized and local abiotic conditions, and biofilm and sediment communities at five sampling dates. ER was significantly higher in NPR than in PR reaches demonstrating in-situ the effects of drying on stream metabolism. When analyzing the long-term drivers of ER and GPP, we found a direct positive effect of drying on ER and a negative effect on GPP. Drying also altered microbial community composition, with algal communities from NPRs being different from those in PRs. In the short-term, the amount of C emitted during rewetting events was positively related to the duration of precedent non-flow period. Our results show that drying had an important effect on stream metabolism both in the short and long term, and supports the need of including NPRs in global estimates of stream metabolism.

Redlining, a historically discriminatory mortgage lending practice, has recently gained attention as a potential cause of public health disparities. However, no study has attempted to synthesize the growing body of research linking redlining to present-day inequalities in access to green space and corresponding environmental health risks. This scoping review aims to provide a comprehensive summary that identifies key characteristics (data, methods, outcomes) and knowledge gaps of current studies exploring the impact of redlining on disproportionate exposure to environmental goods and harms. Using PRISMA guidelines, 21 peer-reviewed articles published between 2020 and 2023 met inclusion criteria. Across included studies, we identified a variety of different study designs (e.g., cross-sectional, longitudinal), outcomes (green space disparity, environmental health inequalities), measures of greenspace (e.g., tree canopy, tree size, NDVI), and environmental health risks (air pollution, extreme heat). The results of this scoping review show that historically redlined neighborhoods have less green space and face greater environmental health risks compared to non-redlined neighborhoods. Although green space and large or mature trees remains scarce in redlined neighborhoods compared to non-redlined neighborhoods, studies show that redlined neighborhoods exhibit a more noticeable increase in tree canopy over time and a higher presence of smaller trees. Disproportionate exposure to air pollution and heat underscores the need for green space planning in redlined neighborhoods that addresses these environmental burdens. Future redlining studies should incorporate additional dimensions of environmental justice, including procedural and recognition justice, to understand the underlying factors perpetuating distributive injustices and identify potential solutions to these health challenges.

In this study, we develop an approach to correct biases in the atmospheric component of the Community Earth System Model (CESM) using convolutional neural networks (CNNs) to create a corrective model parameterization for online bias reduction. By learning to predict systematic nudging increments derived from a linear relaxation towards the ERA5 reanalysis, our method dynamically adjusts the model state, significantly outperforming traditional corrections based on climatological increments alone. Our results demonstrate substantial improvements in the root mean square error (RMSE) across all state variables, with precipitation biases over land reduced by 25-35\%, depending on the season. Beyond reducing climate biases, our approach enhances the representation of major modes of variability, including the North Atlantic Oscillation (NAO) and other key aspects of boreal winter variability. A particularly notable improvement is observed in the Madden-Julian Oscillation (MJO), where the CNN-corrected model successfully propagates the MJO across the maritime continent, a challenge for many current climate models. This advancement underscores the potential of using CNNs for real-time model correction, providing a robust framework for improving climate simulations. Our findings highlight the efficacy of integrating machine learning techniques with traditional dynamical models to enhance climate prediction accuracy and reliability. This hybrid approach offers a promising direction for future research and operational climate forecasting, bridging the gap between observed and simulated climate dynamics.

Flow through a granular, natural porous media can erode it chemically by dissolving and thus shrinking the solid particles, or mechanically, by removing them. The two-way interplay between the transport of fluids and dissolved solutes and alteration of the porous structure and hence the medium's transport properties is of interest to processes ranging from subsurface energy storage to contamination in groundwater. Here, we conduct a quantitative pore-scale analysis through a combination of numerical simulations and microfluidic experiments. We find that erosion enhances solute dispersion at low Pe (diffusion-dominated) and diminishes it at high Pe. Residence time distribution reveals that mechanical erosion tends to induce non-Fickian transport more than chemical erosion, which we attribute to the differences in their effects on pore size distribution.

A document by Natalie Nelson. Click on the document to view its contents.

A document by Cameron MacDonald. Click on the document to view its contents.

It is challenging to estimate how the regional climate will be shifted under future global warming. To reduce the potential risk of regional climate shift under future climates, examining the change in climate features over Asia is important, as approximately 60 percent of the world’s population resides there. In this study, climate shifts are assessed over the Asian monsoon region under global mean temperature warming targets from 1.5 °C to 5.0 °C above preindustrial (PI) levels based on different shared socioeconomic pathway (SSP) scenarios. Global warming impacts the individual climate variables, and consequently, it impacts the regional climate features across the Asia region. Temperature change patterns are more dominant contributors to the spatial extent and magnitude of climate shifts than precipitation change patterns. Changes in regional climates show different behaviors according to the degree of global warming rather than the type of SSP scenario. Climate shifts are intensified under a higher level of global warming that is above the PI levels. The largest climate shifts in this region are shown under global warming of 5.0 °C based on the SSP5-8.5 scenario, especially in current polar climate zones. Future change patterns in individual climate zone can differ. Regions with tropical climates and arid climates are likely to be expanded, whereas some regions with warm temperate climates, cold climates, and polar climates are likely to shrink under global warming conditions. Therefore, this study supports the necessity of mitigating greenhouse gas (GHG) emissions and establishing an adaptation plan for future global warming conditions.

We investigate the relationship between the seismogenic behavior of global megathrusts and various subduction parameters. We performed a parametric approach by implementing three decision tree-based Machine Learning (ML) algorithms to predict the b-value of the frequency-magnitude relationship of seismicity as a non-linear combination of subduction variables (subducting plate age and roughness, slab dip, convergence speed and azimuth, distance to closest ridge and plate boundary). Using the Shapley Additive exPlanations (SHAP) to interpret the ML results, we observe that plate age and subduction dip are the most influential variables. The results suggest that older, shallow-dipping plates contribute to low b-values, indicating higher megathrust stress. This pattern is attributed to the higher rigidity of older plates, increasing flexural strength, and generating a shallow penetration angle, increasing the frictional interplate area and intensifying the megathrust stress. These findings offer new insights into the non-linear complexity of seismic behaviour at global scale.

The biological carbon pump transfers large amounts of carbon from the atmosphere into the ocean’s interior, contributing to oceanic carbon sequestration. Efforts to identify the geographical variability in the transfer efficiency of sinking organic material to depth have yielded inconsistent results. This may in part be due to methodological differences across studies in collecting or analysing particulate organic carbon (POC) flux data. To address this, we compiled data of POC flux and key BCP metrics from selected data-rich locations across biogeographically distinct ocean regions. We integrated multiple BCP observational techniques, encompassing diverse sampling methods, sampling efforts and working protocols, to capture diverse facets of POC flux at varying spatiotemporal resolutions. To make the data comparable across studies, we harmonised reported errors and used Monte Carlo error propagation to calculate uncertainties consistently. Our analysis of BCP metrics from observation-based studies reveals large local uncertainties, blurring expected geographical patterns.

We present observations on 24 April 2023 by the Magnetospheric Multiscale spacecraft at the dayside, mid-latitude magnetopause, when an interplanetary magnetic cloud (MC) with sub-Alfvénic flows and northward and dawnward interplanetary magnetic field components impacted Earth’s magnetosphere. The aim is to reveal the processes of solar wind-magnetosphere interaction under sub-Alfvénic solar wind with northward magnetic field. Our analysis of electron and ion data suggests that magnetopause reconnection occurred near both polar cusps, forming boundary layers on closed magnetic field lines on both the MC and magnetospheric sides of the magnetopause. Grad-Shafranov, electron-magnetohydrodynamics, and polynomial reconstructions of magnetopause current layers show that local (equator-of-the-cusp) reconnection occurred in a sub-ion-scale magnetopause current sheet with a low magnetic shear angle (30°). Interestingly, the local reconnection was observed between the two (MC-side and magnetosphere-side) layers of closed field lines. It indicates that reconnected field lines from double cusp reconnection were interacting to induce another reconnection at the mid-latitude magnetopause. Our results suggest that magnetopause reconnection was more efficient or frequent under sub-Alfvénic solar wind with much lower beta plasma conditions than typical conditions. We will discuss the role of such efficient reconnection in the formation of low-latitude boundary layers.

The study and simulation of the Urban Heat Island (UHI) and Heat Index (HI) effects in the Houston-Galveston metropolitan area demand special attention, particularly in considering moist processes aloft. During the warm season, the afternoon sea breeze phenomenon in this coastal city acts as a natural air conditioner for city residents, facilitating the dispersion of moisture, heat, and pollutants. To delve into the intricate relationships among urbanization, clouds, and land-sea interactions, we conducted cloud- and urban-resolving simulations at a 900 m grid resolution. Results show that urbanization correlates with the presence of shallow cumulus clouds, higher cloud bases, and increased cloud duration over the Galveston-Houston region compared to rural areas. These urban clouds benefit from the enhanced sensible heat and dynamic drag imparted by the urban landscape, thereby intensifying vertical mixing and moisture flux convergence. This dynamic interplay uplifts heat and moisture convergence, contributing to the enhancement of moist static energy that sustains the additional urban convection. Interestingly, our findings suggest that urbanization augments the mean HI while mitigating its afternoon high. An urban circulation dome emerges, overpowering the influence of land-sea circulations. Contrary to expectations, urbanization doesn’t seem to promote a stronger sea breeze that would favor moist and cooler air mass advection to the city. Instead, the influence of urbanization on cloud enhancement emerges as a crucial pathway responsible for reducing the afternoon HI values. Moreover, uncertainties in SSTs are closely linked to the sensitivities of land-sea circulations, which in turn modulate UHI and extreme heat indicators.

This paper discusses the performance of the National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) forecast model in predicting rainfall over the Korean Peninsula caused by tropical cyclones (TCs). TCs forecasted in GFS were characterized by overestimated intensity and well-organized inner core structure during landfall, and the associated TC-induced rainfall forecast errors were examined from two perspectives: TC tracks and TC-environmental interactions. The results provide implications in three ways. First, the predicted TC track is biased to the west, bringing it closer to the Korean Peninsula landmass and contributing to an overall increase in overland precipitation. Second, the strongly simulated TC during landfall predicted rainfall only in a narrow radius around the TC center. Third, the TCs were characterized by weak upper-level TC outflow due to the well-developed TC structure, which could increase the inertial stability of the TC center during jet interaction, leading to an underestimated precipitation in outer core region of the storm. These results suggest specific sources of error in the forecast of TC precipitation over the Korean Peninsula, which can contribute to improving numerical models and providing forecasters with information about model characteristics.This paper discusses the performance of the National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) forecast model in predicting rainfall over the Korean Peninsula caused by tropical cyclones (TCs). TCs forecasted in GFS were characterized by overestimated intensity and well-organized inner core structure during landfall, and the associated TC-induced rainfall forecast errors were examined from two perspectives: TC tracks and TC-environmental interactions. The results provide implications in three ways. First, the predicted TC track is biased to the west, bringing it closer to the Korean Peninsula landmass and contributing to an overall increase in overland precipitation. Second, the strongly simulated TC during landfall predicted rainfall only in a narrow radius around the TC center. Third, the TCs were characterized by weak upper-level TC outflow due to the well-developed TC structure, which could increase the inertial stability of the TC center during jet interaction, leading to an underestimated precipitation in outer core region of the storm. These results suggest specific sources of error in the forecast of TC precipitation over the Korean Peninsula, which can contribute to improving numerical models and providing forecasters with information about model characteristics.This paper discusses the performance of the National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) forecast model in predicting rainfall over the Korean Peninsula caused by tropical cyclones (TCs). TCs forecasted in GFS were characterized by overestimated intensity and well-organized inner core structure during landfall, and the associated TC-induced rainfall forecast errors were examined from two perspectives: TC tracks and TC-environmental interactions. The results provide implications in three ways. First, the predicted TC track is biased to the west, bringing it closer to the Korean Peninsula landmass and contributing to an overall increase in overland precipitation. Second, the strongly simulated TC during landfall predicted rainfall only in a narrow radius around the TC center. Third, the TCs were characterized by weak upper-level TC outflow due to the well-developed TC structure, which could increase the inertial stability of the TC center during jet interaction, leading to an underestimated precipitation in outer core region of the storm. These results suggest specific sources of error in the forecast of TC precipitation over the Korean Peninsula, which can contribute to improving numerical models and providing forecasters with information about model characteristics.This paper discusses the performance of the National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) forecast model in predicting rainfall over the Korean Peninsula caused by tropical cyclones (TCs). TCs forecasted in GFS were characterized by overestimated intensity and well-organized inner core structure during landfall, and the associated TC-induced rainfall forecast errors were examined from two perspectives: TC tracks and TC-environmental interactions. The results provide implications in three ways. First, the predicted TC track is biased to the west, bringing it closer to the Korean Peninsula landmass and contributing to an overall increase in overland precipitation. Second, the strongly simulated TC during landfall predicted rainfall only in a narrow radius around the TC center. Third, the TCs were characterized by weak upper-level TC outflow due to the well-developed TC structure, which could increase the inertial stability of the TC center during jet interaction, leading to an underestimated precipitation in outer core region of the storm. These results suggest specific sources of error in the forecast of TC precipitation over the Korean Peninsula, which can contribute to improving numerical models and providing forecasters with information about model characteristics.This paper discusses the performance of the National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) forecast model in predicting rainfall over the Korean Peninsula caused by tropical cyclones (TCs). TCs forecasted in GFS were characterized by overestimated intensity and well-organized inner core structure during landfall, and the associated TC-induced rainfall forecast errors were examined from two perspectives: TC tracks and TC-environmental interactions. The results provide implications in three ways. First, the predicted TC track is biased to the west, bringing it closer to the Korean Peninsula landmass and contributing to an overall increase in overland precipitation. Second, the strongly simulated TC during landfall predicted rainfall only in a narrow radius around the TC center. Third, the TCs were characterized by weak upper-level TC outflow due to the well-developed TC structure, which could increase the inertial stability of the TC center during jet interaction, leading to an underestimated precipitation in outer core region of the storm. These results suggest specific sources of error in the forecast of TC precipitation over the Korean Peninsula, which can contribute to improving numerical models and providing forecasters with information about model characteristics.This paper discusses the performance of the National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) forecast model in predicting rainfall over the Korean Peninsula caused by tropical cyclones (TCs). TCs forecasted in GFS were characterized by overestimated intensity and well-organized inner core structure during landfall, and the associated TC-induced rainfall forecast errors were examined from two perspectives: TC tracks and TC-environmental interactions. The results provide implications in three ways. First, the predicted TC track is biased to the west, bringing it closer to the Korean Peninsula landmass and contributing to an overall increase in overland precipitation. Second, the strongly simulated TC during landfall predicted rainfall only in a narrow radius around the TC center. Third, the TCs were characterized by weak upper-level TC outflow due to the well-developed TC structure, which could increase the inertial stability of the TC center during jet interaction, leading to an underestimated precipitation in outer core region of the storm. These results suggest specific sources of error in the forecast of TC precipitation over the Korean Peninsula, which can contribute to improving numerical models and providing forecasters with information about model characteristics.This paper discusses the performance of the National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) forecast model in predicting rainfall over the Korean Peninsula caused by tropical cyclones (TCs). TCs forecasted in GFS were characterized by overestimated intensity and well-organized inner core structure during landfall, and the associated TC-induced rainfall forecast errors were examined from two perspectives: TC tracks and TC-environmental interactions. The results provide implications in three ways. First, the predicted TC track is biased to the west, bringing it closer to the Korean Peninsula landmass and contributing to an overall increase in overland precipitation. Second, the strongly simulated TC during landfall predicted rainfall only in a narrow radius around the TC center. Third, the TCs were characterized by weak upper-level TC outflow due to the well-developed TC structure, which could increase the inertial stability of the TC center during jet interaction, leading to an underestimated precipitation in outer core region of the storm. These results suggest specific sources of error in the forecast of TC precipitation over the Korean Peninsula, which can contribute to improving numerical models and providing forecasters with information about model characteristics.This paper discusses the performance of the National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) forecast model in predicting rainfall over the Korean Peninsula caused by tropical cyclones (TCs). TCs forecasted in GFS were characterized by overestimated intensity and well-organized inner core structure during landfall, and the associated TC-induced rainfall forecast errors were examined from two perspectives: TC tracks and TC-environmental interactions. The results provide implications in three ways. First, the predicted TC track is biased to the west, bringing it closer to the Korean Peninsula landmass and contributing to an overall increase in overland precipitation. Second, the strongly simulated TC during landfall predicted rainfall only in a narrow radius around the TC center. Third, the TCs were characterized by weak upper-level TC outflow due to the well-developed TC structure, which could increase the inertial stability of the TC center during jet interaction, leading to an underestimated precipitation in outer core region of the storm. These results suggest specific sources of error in the forecast of TC precipitation over the Korean Peninsula, which can contribute to improving numerical models and providing forecasters with information about model characteristics.This paper discusses the performance of the National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) forecast model in predicting rainfall over the Korean Peninsula caused by tropical cyclones (TCs). TCs forecasted in GFS were characterized by overestimated intensity and well-organized inner core structure during landfall, and the associated TC-induced rainfall forecast errors were examined from two perspectives: TC tracks and TC-environmental interactions. The results provide implications in three ways. First, the predicted TC track is biased to the west, bringing it closer to the Korean Peninsula landmass and contributing to an overall increase in overland precipitation. Second, the strongly simulated TC during landfall predicted rainfall only in a narrow radius around the TC center. Third, the TCs were characterized by weak upper-level TC outflow due to the well-developed TC structure, which could increase the inertial stability of the TC center during jet interaction, leading to an underestimated precipitation in outer core region of the storm. These results suggest specific sources of error in the forecast of TC precipitation over the Korean Peninsula, which can contribute to improving numerical models and providing forecasters with information about model characteristics.This paper discusses the performance of the National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) forecast model in predicting rainfall over the Korean Peninsula caused by tropical cyclones (TCs). TCs forecasted in GFS were characterized by overestimated intensity and well-organized inner core structure during landfall, and the associated TC-induced rainfall forecast errors were examined from two perspectives: TC tracks and TC-environmental interactions. The results provide implications in three ways. First, the predicted TC track is biased to the west, bringing it closer to the Korean Peninsula landmass and contributing to an overall increase in overland precipitation. Second, the strongly simulated TC during landfall predicted rainfall only in a narrow radius around the TC center. Third, the TCs were characterized by weak upper-level TC outflow due to the well-developed TC structure, which could increase the inertial stability of the TC center during jet interaction, leading to an underestimated precipitation in outer core region of the storm. These results suggest specific sources of error in the forecast of TC precipitation over the Korean Peninsula, which can contribute to improving numerical models and providing forecasters with information about model characteristics.This paper discusses the performance of the National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) forecast model in predicting rainfall over the Korean Peninsula caused by tropical cyclones (TCs). TCs forecasted in GFS were characterized by overestimated intensity and well-organized inner core structure during landfall, and the associated TC-induced rainfall forecast errors were examined from two perspectives: TC tracks and TC-environmental interactions. The results provide implications in three ways. First, the predicted TC track is biased to the west, bringing it closer to the Korean Peninsula landmass and contributing to an overall increase in overland precipitation. Second, the strongly simulated TC during landfall predicted rainfall only in a narrow radius around the TC center. Third, the TCs were characterized by weak upper-level TC outflow due to the well-developed TC structure, which could increase the inertial stability of the TC center during jet interaction, leading to an underestimated precipitation in outer core region of the storm. These results suggest specific sources of error in the forecast of TC precipitation over the Korean Peninsula, which can contribute to improving numerical models and providing forecasters with information about model characteristics.This paper discusses the performance of the National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) forecast model in predicting rainfall over the Korean Peninsula caused by tropical cyclones (TCs). TCs forecasted in GFS were characterized by overestimated intensity and well-organized inner core structure during landfall, and the associated TC-induced rainfall forecast errors were examined from two perspectives: TC tracks and TC-environmental interactions. The results provide implications in three ways. First, the predicted TC track is biased to the west, bringing it closer to the Korean Peninsula landmass and contributing to an overall increase in overland precipitation. Second, the strongly simulated TC during landfall predicted rainfall only in a narrow radius around the TC center. Third, the TCs were characterized by weak upper-level TC outflow due to the well-developed TC structure, which could increase the inertial stability of the TC center during jet interaction, leading to an underestimated precipitation in outer core region of the storm. These results suggest specific sources of error in the forecast of TC precipitation over the Korean Peninsula, which can contribute to improving numerical models and providing forecasters with information about model characteristics.This paper discusses the performance of the National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) forecast model in predicting rainfall over the Korean Peninsula caused by tropical cyclones (TCs). TCs forecasted in GFS were characterized by overestimated intensity and well-organized inner core structure during landfall, and the associated TC-induced rainfall forecast errors were examined from two perspectives: TC tracks and TC-environmental interactions. The results provide implications in three ways. First, the predicted TC track is biased to the west, bringing it closer to the Korean Peninsula landmass and contributing to an overall increase in overland precipitation. Second, the strongly simulated TC during landfall predicted rainfall only in a narrow radius around the TC center. Third, the TCs were characterized by weak upper-level TC outflow due to the well-developed TC structure, which could increase the inertial stability of the TC center during jet interaction, leading to an underestimated precipitation in outer core region of the storm. These results suggest specific sources of error in the forecast of TC precipitation over the Korean Peninsula, which can contribute to improving numerical models and providing forecasters with information about model characteristics.This paper discusses the performance of the National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) forecast model in predicting rainfall over the Korean Peninsula caused by tropical cyclones (TCs). TCs forecasted in GFS were characterized by overestimated intensity and well-organized inner core structure during landfall, and the associated TC-induced rainfall forecast errors were examined from two perspectives: TC tracks and TC-environmental interactions. The results provide implications in three ways. First, the predicted TC track is biased to the west, bringing it closer to the Korean Peninsula landmass and contributing to an overall increase in overland precipitation. Second, the strongly simulated TC during landfall predicted rainfall only in a narrow radius around the TC center. Third, the TCs were characterized by weak upper-level TC outflow due to the well-developed TC structure, which could increase the inertial stability of the TC center during jet interaction, leading to an underestimated precipitation in outer core region of the storm. These results suggest specific sources of error in the forecast of TC precipitation over the Korean Peninsula, which can contribute to improving numerical models and providing forecasters with information about model characteristics.This paper discusses the performance of the National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) forecast model in predicting rainfall over the Korean Peninsula caused by tropical cyclones (TCs). TCs forecasted in GFS were characterized by overestimated intensity and well-organized inner core structure during landfall, and the associated TC-induced rainfall forecast errors were examined from two perspectives: TC tracks and TC-environmental interactions. The results provide implications in three ways. First, the predicted TC track is biased to the west, bringing it closer to the Korean Peninsula landmass and contributing to an overall increase in overland precipitation. Second, the strongly simulated TC during landfall predicted rainfall only in a narrow radius around the TC center. Third, the TCs were characterized by weak upper-level TC outflow due to the well-developed TC structure, which could increase the inertial stability of the TC center during jet interaction, leading to an underestimated precipitation in outer core region of the storm. These results suggest specific sources of error in the forecast of TC precipitation over the Korean Peninsula, which can contribute to improving numerical models acharacteristics.This paper discusses the performance of the National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) forecast model in predicting rainfall over the Korean Peninsula caused by tropical cyclones (TCs). TCs forecasted in GFS were characterized by overestimated intensity and well-organized inner core structure during landfall, and the associated TC-induced rainfall forecast errors were examined from two perspectives: TC tracks and TC-environmental interactions. The results provide implications in three ways. First, the predicted TC track is biased to the west, bringing it closer to the Korean Peninsula landmass and contributing to an overall increase in overland precipitation. Second, the strongly simulated TC during landfall predicted rainfall only in a narrow radius around the TC center. Third, the TCs were characterized by weak upper-level TC outflow due to the well-developed TC structure, which could increase the inertial stability of the TC center during jet interaction, leading to an underestimated precipitation in outer core region of the storm. These results suggest specific sources of error in the forecast of TC precipitation over the Korean Peninsula, which can contribute to improving numerical models acharacteristics.This paper discusses the performance of the National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) forecast model in predicting rainfall over the Korean Peninsula caused by tropical cyclones (TCs). TCs forecasted in GFS were characterized by overestimated intensity and well-organized inner core structure during landfall, and the associated TC-induced rainfall forecast errors were examined from two perspectives: TC tracks and TC-environmental interactions. The results provide implications in three ways. First, the predicted TC track is biased to the west, bringing it closer to the Korean Peninsula landmass and contributing to an overall increase in overland precipitation. Second, the strongly simulated TC during landfall predicted rainfall only in a narrow radius around the TC center. Third, the TCs were characterized by weak upper-level TC outflow due to the well-developed TC structure, which could increase the inertial stability of the TC center during jet interaction, leading to an underestimated precipitation in outer core region of the storm. These results suggest specific sources of error in the forecast of TC precipitation over the Korean Peninsula, which can contribute to improving numerical models acharacteristics.This paper discusses the performance of the National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) forecast model in predicting rainfall over the Korean Peninsula caused by tropical cyclones (TCs). TCs forecasted in GFS were characterized by overestimated intensity and well-organized inner core structure during landfall, and the associated TC-induced rainfall forecast errors were examined from two perspectives: TC tracks and TC-environmental interactions. The results provide implications in three ways. First, the predicted TC track is biased to the west, bringing it closer to the Korean Peninsula landmass and contributing to an overall increase in overland precipitation. Second, the strongly simulated TC during landfall predicted rainfall only in a narrow radius around the TC center. Third, the TCs were characterized by weak upper-level TC outflow due to the well-developed TC structure, which could increase the inertial stability of the TC center during jet interaction, leading to an underestimated precipitation in outer core region of the storm. These results suggest specific sources of error in the forecast of TC precipitation over the Korean Peninsula, which can contribute to improving numerical models acharacteristics.This paper discusses the performance of the National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) forecast model in predicting rainfall over the Korean Peninsula caused by tropical cyclones (TCs). TCs forecasted in GFS were characterized by overestimated intensity and well-organized inner core structure during landfall, and the associated TC-induced rainfall forecast errors were examined from two perspectives: TC tracks and TC-environmental interactions. The results provide implications in three ways. First, the predicted TC track is biased to the west, bringing it closer to the Korean Peninsula landmass and contributing to an overall increase in overland precipitation. Second, the strongly simulated TC during landfall predicted rainfall only in a narrow radius around the TC center. Third, the TCs were characterized by weak upper-level TC outflow due to the well-developed TC structure, which could increase the inertial stability of the TC center during jet interaction, leading to an underestimated precipitation in outer core region of the storm. These results suggest specific sources of error in the forecast of TC precipitation over the Korean Peninsula, which can contribute to improving numerical models acharacteristics.This paper discusses the performance of the National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) forecast model in predicting rainfall over the Korean Peninsula caused by tropical cyclones (TCs). TCs forecasted in GFS were characterized by overestimated intensity and well-organized inner core structure during landfall, and the associated TC-induced rainfall forecast errors were examined from two perspectives: TC tracks and TC-environmental interactions. The results provide implications in three ways. First, the predicted TC track is biased to the west, bringing it closer to the Korean Peninsula landmass and contributing to an overall increase in overland precipitation. Second, the strongly simulated TC during landfall predicted rainfall only in a narrow radius around the TC center. Third, the TCs were characterized by weak upper-level TC outflow due to the well-developed TC structure, which could increase the inertial stability of the TC center during jet interaction, leading to an underestimated precipitation in outer core region of the storm. These results suggest specific sources of error in the forecast of TC precipitation over the Korean Peninsula, which can contribute to improving numerical models acharacteristics.This paper discusses the performance of the National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) forecast model in predicting rainfall over the Korean Peninsula caused by tropical cyclones (TCs). TCs forecasted in GFS were characterized by overestimated intensity and well-organized inner core structure during landfall, and the associated TC-induced rainfall forecast errors were examined from two perspectives: TC tracks and TC-environmental interactions. The results provide implications in three ways. First, the predicted TC track is biased to the west, bringing it closer to the Korean Peninsula landmass and contributing to an overall increase in overland precipitation. Second, the strongly simulated TC during landfall predicted rainfall only in a narrow radius around the TC center. Third, the TCs were characterized by weak upper-level TC outflow due to the well-developed TC structure, which could increase the inertial stability of the TC center during jet interaction, leading to an underestimated precipitation in outer core region of the storm. These results suggest specific sources of error in the forecast of TC precipitation over the Korean Peninsula, which can contribute to improving numerical models acharacteristics.This paper discusses the performance of the National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) forecast model in predicting rainfall over the Korean Peninsula caused by tropical cyclones (TCs). TCs forecasted in GFS were characterized by overestimated intensity and well-organized inner core structure during landfall, and the associated TC-induced rainfall forecast errors were examined from two perspectives: TC tracks and TC-environmental interactions. The results provide implications in three ways. First, the predicted TC track is biased to the west, bringing it closer to the Korean Peninsula landmass and contributing to an overall increase in overland precipitation. Second, the strongly simulated TC during landfall predicted rainfall only in a narrow radius around the TC center. Third, the TCs were characterized by weak upper-level TC outflow due to the well-developed TC structure, which could increase the inertial stability of the TC center during jet interaction, leading to an underestimated precipitation in outer core region of the storm. These results suggest specific sources of error in the forecast of TC precipitation over the Korean Peninsula, which can contribute to improving numerical models acharacteristics.This paper discusses the performance of the National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) forecast model in predicting rainfall over the Korean Peninsula caused by tropical cyclones (TCs). TCs forecasted in GFS were characterized by overestimated intensity and well-organized inner core structure during landfall, and the associated TC-induced rainfall forecast errors were examined from two perspectives: TC tracks and TC-environmental interactions. The results provide implications in three ways. First, the predicted TC track is biased to the west, bringing it closer to the Korean Peninsula landmass and contributing to an overall increase in overland precipitation. Second, the strongly simulated TC during landfall predicted rainfall only in a narrow radius around the TC center. Third, the TCs were characterized by weak upper-level TC outflow due to the well-developed TC structure, which could increase the inertial stability of the TC center during jet interaction, leading to an underestimated precipitation in outer core region of the storm. These results suggest specific sources of error in the forecast of TC precipitation over the Korean Peninsula, which can contribute to improving numerical models a

Quantification of the magnitude and long-term changes of ozone concentrations transported into the US is important for effective air quality policy development. We synthesize multiple published trend analyses of western US baseline ozone, and show that all results are consistent with an overall, non-linear change – rapid increase during the 1980s that slowed in the 1990s, maximized in the mid-2000s, and was followed by a slow decrease thereafter. This non-linear change accounts for ~2/3 of the variance in the published linear trend analyses; we attribute the other 1/3 to unquantified autocorrelation in the analyzed data sets. Recent systematic changes in baseline ozone at the US West Coast have been relatively small - the standard deviation of the 2-year means over the 1990-2017 period is 1.5 ppb. International efforts to reduce anthropogenic precursor emissions from all northern mid-latitude sources could possibly reduce baseline ozone concentrations, thereby improving US ozone air quality.

In order to test the hypothesis that EMIC waves are responsible for the acceleration of auroral protons, we have used spectrograph measurements of proton aurora over Svalbard alongside co-located magnetometer measurements of Pc1 pulsations. No evidence of a link between proton aurora and Pc1 waves was found by three different methods. Firstly, accelerated protons and Pc1 pulsations have no coincident occurrence. Secondly, the proton energy spectrum does not change between Pc1 activity and quiet times. Finally, no imprint of the EMIC wave is found in periodicity of the intensity and blue-shift of the proton H-α line, unlike in flickering electron aurora where intensity fluctuations are caused by EMIC waves. We find no evidence that EMIC waves are the mechanism responsible for accelerating auroral protons in the high-latitude dayside, at least based on the considered ground-based data of proton aurora and magnetic Pc1 pulsations.

Mesoscale Convective Systems (MCSs) are crucial in shaping large-scale tropical circulation and the hydrological cycle, particularly in Northwestern South America (NwSA), a region marked by complex terrain and significant MCS activity. Understanding MCSs in NwSA is vital due to their impact on precipitation patterns and potential for severe weather events. To enhance this understanding, the ATRACKCS algorithm was developed for tracking convective systems, utilizing precipitation and brightness temperature datasets. This research focuses on documenting the spatiotemporal variability of MCS occurrence, life cycle, and movement. Notably, MCS hotspots were identified to the west of the major orographic features in the region, with maximum occurrences at night, contrasting with the region's typical afternoon peak in land convection. MCS movement is also heavily influenced by topography, with higher velocities on the eastern (windward) side of the Andes compared to velocities on the western (leeward) side. MCSs generally move westward, driven by easterly winds, but this pattern is not consistent throughout the year or region. Northward movement is predominant to the west of the Andes, while southward movement is observed to the east. These seasonal and regional movement variations are linked to factors such as the intertropical convergence zone position, moisture availability, topography, and low-level jets. This research underscores the complexity of MCSs in NwSA and emphasizes the need for detailed studies on the atmospheric environment shaping these systems. Additionally, it provides a robust 21-year MCS database for NwSA and an advanced tracking tool for research in various geographic contexts and impact areas.

The three Swarm satellites provide an optimum, low Earth orbit (LEO) and multi-spacecraft platform, to explore for the first time the local correlation between field-aligned currents (FACs), auroral electrojets, and magnetic perturbations at the Earth’s surface. By Swarm and ground magnetic field data together, one can investigate systematically the full correlation chain, whose final link controls the ground induced currents and related space weather effects. We introduce an integrated FAC product, the Sheet FAC (SFAC) index, as a convenient measure of the in-situ FAC data, and check the correlations SFAC-AE, SFAC-PEJ and SFAC-dH, with AE the standard auroral electrojet index, PEJ the local, Swarm based, polar electrojet index, and dH the horizontal magnetic field perturbation at the Earth’s surface. Given the good SFAC-dH correlation, we also suggest an extension of SFAC to higher LEO satellites, which cannot observe any more the electrojet currents, but are fully capable to monitor SFAC.

A document by Chao Song. Click on the document to view its contents.

Most of the world’s population faces freshwater scarcity threats, and reservoirs, built both for ensuring water supply during prolonged droughts and reducing downstream flood risks, are critical infrastructure for water sustainability. Historical inflow data and water demand were used to estimate reservoir storage allocation and operation policies when designing and building reservoirs, 50 to 100 years ago. This study assesses historical reservoir operations in 16 Southeastern reservoirs and evaluates the potential for utilizing existing flood control storage for alternative purposes without increasing downstream flood risk. Using a reservoir simulation model, we evaluate the resulting storage under four initial storage conditions for observed and synthetic seasonal maximum six-day flood pulses. For most reservoirs, we find conservation storage is depleting and did not exceed the flood storage capacity in their historical operation. The simulation model resulted in most of the reservoirs’ storage levels staying within the flood control pool for all scenarios (for observed and synthetic floods). Additional flood risk was lowest for initial storage condition 1 (flood control pool empty) and highest with condition 2 (50% of the flood control pool full). Flood risk increased the most for reservoirs with small ratios of flood control to conservation pool storage. Our study shows the potential for reallocation and utilization of flood control storage to meet the increasing demand. As limited opportunities for new reservoirs exist, utilizing current reservoir storage without introducing additional downstream risk may be an effective management strategy to mitigate flood and drought risk under climate change and population growth.