Precipitation Flux Research Articles

Implementation of an Asymmetric Internal Field in the Comprehensive Inner Magnetosphere‐Ionosphere (CIMI) Model

AbstractA Comprehensive Inner Magnetosphere‐Ionosphere (CIMI) model has been developed to study the dynamics of the cold plasmasphere and the energetic plasmas in the inner magnetosphere, as well as their couplings with each other and with the ionosphere. The CIMI model is able to predict the cold plasma density and energetic electron and ion fluxes in geospace. Furthermore, CIMI is capable of predicting the Region 2 currents, penetration electric field, electron and ion precipitation and magnetospheric heat flux into the ionosphere. The CIMI model includes a realistic magnetic field configuration with a combination of an internal field and an external field imposed by the interaction of the solar wind with the magnetosphere. The internal field has previously been assumed to be a dipole. Recently, the International Geomagnetic Reference Field (IGRF) has been implemented. This new capability enables studies of north‐south and longitudinal dependences in particle precipitation and heat flux, as well as the corresponding asymmetries in ionospheric and thermospheric responses. In this paper, we will briefly review the CIMI equations and model output. Then we will describe the new implementation of the IGRF model into CIMI and how to estimate the north‐south asymmetry in precipitating fluxes from the differences in field strength between magnetic conjugate points. The inclusion of a realistic internal field leads CIMI into a better position to couple with sophisticated ionosphere‐thermosphere models, most of which are using the IGRF model.

Changes of Wet Precipitation Flux and Pollutants Associated with at Chongqing Urban Station from 2008 to 2020 and Influencing Factors

Changes of Wet Precipitation Flux and Pollutants Associated with at Chongqing Urban Station from 2008 to 2020 and Influencing Factors

Statistical downscaling model for future projection of daily IDF relationship by Markov chain and kernel density estimator

ABSTRACT Changes in climate might have a significant impact on rainfall characteristics, including extreme rainfall. This study aims to project the future daily rainfall, preserving most of the rainfall characteristics, including extreme rainfall incorporating climate changes. This paper presents two hybrid semi-parametric statistical downscaling models for future projection of IDF curves. The precipitation flux from seven scenarios of ten GCMs and observed daily rainfall data are considered as predictors and predictand variables, respectively. At site, daily rainfall occurrence is modeled using a two-state first-order Markov chain. Rainfall amounts on each wet day are modelled using a univariate nonparametric kernel density estimator. Two types of amount generation models are presented in this study. The bounded model (KDE-SP) is developed, considering the support for the kernel distribution as positive. In the unbounded model (KDE-Ext), the wet days are reclassified as extreme and non-extreme rainy days. A significant increasing trend can be observed in the future projected intensity–duration–frequency relationships. The maximum increment using empirical distribution is observed as 93.21 and 80.93% on a 5-year return period in the far future for the SSP5-8.5 scenario, using KDE-Ext and KDE-SP models, respectively. Although both methods show similar results, the KDE-Ext model performs better in simulating extreme rainfall.

Two Types of Transitions to Relatively Fast Spinup in Tropical Cyclone Simulations with Weak-to-Moderate Environmental Vertical Wind Shear

Abstract Tropical cyclone intensification is simulated with a cloud-resolving model under idealized conditions of constant SST and unidirectional environmental vertical wind shear maximized in the middle troposphere. The intensification process commonly involves a sharp transition to relatively fast spinup before the surface vortex achieves hurricane-force winds in the azimuthal mean. The vast majority of transitions fall into one of two categories labeled S and A. Type S transitions initiate quasi-symmetric modes of fast spinup. They occur in tropical cyclones after a major reduction of tilt and substantial azimuthal spreading of inner-core convection. The lead-up also entails gradual contractions of the radii of maximum wind speed rm and maximum precipitation. Type A transitions begin before an asymmetric tropical cyclone becomes vertically aligned. Instead of enabling the transition, alignment is an essential part of the initially asymmetric mode of fast spinup that follows. On average, type S transitions occur well after and type A transitions occur once the cyclonically rotating tilt vector becomes perpendicular to the shear vector. Prominent temporal peaks of lower-tropospheric CAPE and low-to-midlevel relative humidity averaged over the entire inner core of the low-level vortex characteristically coincide with type S but not with type A transitions. Prominent temporal peaks of precipitation and midlevel vertical mass flux in the meso-β-scale vicinity of the convergence center characteristically coincide with type A but not with type S transitions. Despite such differences, in both cases, the transitions tend not to begin before the distance between the low-level convergence and vortex centers divided by rm reduces to unity.

Influence of Climatic Factors on Rust Severity in Sorghum in Dharwad, Karnataka, India

Sorghum rust, caused by Puccinia purpurea, significantly reduces crop yield, affecting plant growth and grain quality. Understanding the impact of weather parameters on disease incidence is crucial for timely disease management, to enhance crop resilience and yield stability. This study aims to identify and quantify the relationship between weather parameters and the incidence of sorghum rust, to inform decision-making on disease management strategies. A comprehensive analysis was conducted utilizing 17 years of secondary data (2006-2022) sourced from the All India Coordinated Research Project (AICRP) on Sorghum and the Department of Agrometeorology at the Climate Model Intercomparison Project (CMIP), University of Agricultural Sciences (UAS), Dharwad. The study employed statistical methods, including Multiple Linear Regression (MLR) and Step-wise Regression, to model the dependence of rust disease incidence on independent variables such as precipitation, temperature, relative humidity, wind speed, radiation, and heat flux. The results revealed the MLR model explains 65.45% of the variation and the Step-wise Regression model identifies four critical parameters- relative humidity, heat flux, wind speed, and radiation that together accounted for 65.09% of the variation without exhibiting multicollinearity (Variance Inflation Factor values below 10). These findings enhance the understanding of environmental impacts on sorghum rust and can inform future agricultural management strategies for disease prediction and control.

Oceanic response to tropical cyclone in the northern South China Sea observed by underwater gliders during 2018 and 2020

In this study, we mainly used in-situ observations from underwater gliders to analyze the ocean response in the northern South China Sea affected by Son-tinh (2018), Mandal et al. (2018) Mangkhut (2018)and Noul (2020). The results showed that these TCs caused 0.6 °C, 1.1 °C and 1.7 °C maximum sea surface temperature cooling respectively, which were weaker than general conditions because of long distance, weak intensity and fast movement speed. Net solar radiation, precipitation, 10-m wind and sea surface heat flux also made contribution in changes of SST. The mixed layer depth (MLD) became shallower after Son-Tinh and Noul passed through, while during Mangkhut it did not change significantly. After TCs passed through, the stratification around MLD became more obvious, with a banded distribution and stronger high-value areas of buoyancy frequency. Within 1 week after the shortest distance, the temperature and salinity responses in the upper ocean were stronger than those at the sea surface, and the gradients of temperature and salinity and their anomalies were more evident in the subsurface layer. The results of this study show that underwater glider observations are important for understanding oceanic responses to tropical cyclones and are useful for studying tropical cyclone activities.

Operational and experimental snow observation systems in the upper Rofental: data from 2017 to 2023

Abstract. This publication presents a comprehensive hydrometeorological data set for three research sites in the upper Rofental (1891–3772 m a.s.l., Ötztal Alps, Austria) and is a companion publication to a data collection published in 2018. The time series presented here comprise data from 2017 to 2023 and originate from three meteorological and snow hydrological stations at 2737, 2805, and 2919 m a.s.l. The fully equipped automatic weather stations include a specific set of sensors to continuously record snow cover properties. These are automatic measurements of snow depth, snow water equivalent, volumetric solid and liquid water contents, snow density, layered snow temperature profiles, and snow surface temperature. One station is extended by a particular arrangement of two snow depth and water equivalent recording devices to observe and quantify wind-driven snow transport. These devices are installed at nearby wind-exposed and sheltered locations and are complemented by an acoustic-based snow drift sensor. We present data for temperature, precipitation, humidity, wind speed, and radiation fluxes and explore the continuous snow measurements by combined analyses of meteorological and snow data to show typical seasonal snow cover characteristics. The potential of the snow drift observations is demonstrated with examples of measured wind speeds, snow drift rates, and redistributed snow amounts during several blowing snow events. The data complement the scientific monitoring infrastructure in the research catchment and represent a unique time series of high-altitude mountain weather and snow observations. They enable comprehensive insights into the dynamics of high-altitude meteorological and snow processes and are collected to support the scientific community, local stakeholders, and the interested public, as well as operational warning and forecasting services. The data are publicly available from the GFZ Data Services repository: https://doi.org/10.5880/fidgeo.2023.037 (Department of Geography, University of Innsbruck, 2024).

Interpretable Multiscale Machine Learning‐Based Parameterizations of Convection for ICON

AbstractMachine learning (ML)‐based parameterizations have been developed for Earth System Models (ESMs) with the goal to better represent subgrid‐scale processes or to accelerate computations. ML‐based parameterizations within hybrid ESMs have successfully learned subgrid‐scale processes from short high‐resolution simulations. However, most studies used a particular ML method to parameterize the subgrid tendencies or fluxes originating from the compound effect of various small‐scale processes (e.g., radiation, convection, gravity waves) in mostly idealized settings or from superparameterizations. Here, we use a filtering technique to explicitly separate convection from these processes in simulations with the Icosahedral Non‐hydrostatic modeling framework (ICON) in a realistic setting and benchmark various ML algorithms against each other offline. We discover that an unablated U‐Net, while showing the best offline performance, learns reverse causal relations between convective precipitation and subgrid fluxes. While we were able to connect the learned relations of the U‐Net to physical processes this was not possible for the non‐deep learning‐based Gradient Boosted Trees. The ML algorithms are then coupled online to the host ICON model. Our best online performing model, an ablated U‐Net excluding precipitating tracer species, indicates higher agreement for simulated precipitation extremes and mean with the high‐resolution simulation compared to the traditional scheme. However, a smoothing bias is introduced both in water vapor path and mean precipitation. Online, the ablated U‐Net significantly improves stability compared to the non‐ablated U‐Net and runs stable for the full simulation period of 180 days. Our results hint to the potential to significantly reduce systematic errors with hybrid ESMs.

Evolution of Physical and Chemical Characteristics of Atmospheric Precipitation and Its Significant Impacts on the Environment in Beijing

Atmospheric precipitation samples were collected in 2018, 2019, and 2021 in Beijing to study the concentrations and changes of the main metal elements and water-soluble ions； the wet deposition fluxes of heavy metals, water-soluble ions, dissolved inorganic nitrogen, and sulfur in the atmospheric precipitation and their impacts on the ecological environment； and the scavenging mechanisms of the typical precipitation to atmospheric pollutants during the study period. The results showed that the precipitation in Beijing during the study period was mostly neutral or alkaline, and the frequency of acid rain occurrence was very low, only accounting for 3.06%. The total concentrations of major metal elements in 2018, 2019, and 2021 were （4 787.46 ±4 704.31）, （7 663.07 ±8 395.05）, and （2 629.13 ±2 369.51） μg·L-1, respectively. The total equivalent concentrations of ions in 2018, 2019, and 2021 were （851.68 ±649.16）, （973.98 ±850.94）, and （644.31 ±531.16） μeq·L-1, respectively. The interannual changes in major metal elements and ions followed the order of 2019 > 2018 > 2021. The seasonal average total concentrations of major metal elements in spring, summer, autumn, and winter were （9 624.25 ±7 327.92）, （4 088.67 ±5 710.14）, （3 357.68 ±3 995.64）, and （6 203.19 ±3 857.43） μg·L-1, respectively, and the seasonal average total equivalent concentrations of ions in spring, summer, autumn, and winter were （1 014.71 ±512.21）, （729.83 ±589.90）, （724.35 ±681.40）, and （1 014.03 ±359.67） μeq·L-1, respectively, all presenting the order of spring > winter > summer > autumn. NO3- and SO42- were the main acid-causing ions in precipitation, whereas NH4+ and Ca2+ were the main acid-neutralizing ions. The wet deposition fluxes of the heavy metal Cd were very low [（0.05 ±0.01） mg·（m2·a）-1], only accounting for （0.13 ±0.04）% of the total wet deposition fluxes of main metal elements； however, its soil safety years were 291 years, significantly lower than those of other heavy metals, displaying that its ecological risk was relatively the highest. The total wet precipitation flux of water-soluble ions NH4+, Ca2+, NO3-, and SO42- accounted for （85.72 ±2.18）% of the wet precipitation flux of total ions, suggesting that their comprehensive impact on the ecological environment might have been higher. DIN wet deposition flux was mainly characterized by NH4+-N, which had a positive impact on the ecological environment in summer. SO42--S wet deposition flux was higher in summer, so its positive impact on the ecological environment was also greater. The scavenging effects of atmospheric precipitations to pollutants from the air were impacted by various factors, and the synergism effects of these factors could directly influence the scavenging mechanisms of precipitation to pollutants.

Impact of the transport of magnetospheric electrons on the composition of the Triton atmosphere

Due to its inclined orbit and the complex geometry of the magnetic field of Neptune, Triton experiences a highly variable magnetic environment. As precipitation of magnetospheric electrons is thought to have a large impact on the Triton atmosphere, a better understanding of the interaction between its atmosphere and the magnetosphere of Neptune is important. We aim to couple a model of the Triton atmosphere with an electron transport model to compute the impact of a varying electron precipitation on the atmospheric composition. We coupled a recent photochemical model of the Triton atmosphere with the electron transport model TRANSPlanets. The inputs of this code were determined from Voyager 2 observations and previous studies. The main inputs were the electron precipitation flux, the orbital scaling factor, and the magnetic field strength. The electron-impact ionization and electron-impact dissociation rates computed by TRANSPlanets were then used in the photochemical model. We also analyzed the model uncertainties. The coupling of the two models enabled us to find an electron density profile, as well as N$_2$ and N number densities, that are consistent with the Voyager 2 observations. We found that photoionization and electron-impact ionization are of the same order, in contrast to the results of previous photochemical models. However, we emphasize that this result depends on the hypotheses we used to determine the input variables of TRANSPlanets. Our model would greatly benefit from new measurements of the magnetic environment of Triton, as well as of the electron fluxes in the Neptune magnetosphere.

Modeling the Global Distribution of Chorus Wave Induced Relativistic Microburst Spatial Characteristics

AbstractThe full spatiotemporal distribution of chorus wave‐induced relativistic electron microburst is modeled for chorus waves originated from different L shells and MLTs, based on the newly developed numerical precipitation model (Kang et al., 2022, https://doi.org/10.1029/2022gl100841). The wave‐particle interaction process that induces each microburst is analyzed in detail, and its relation to the chorus wave propagation effects is explained. The global distribution of maximum precipitation fluxes and scale sizes of relativistic microbursts is then obtained by modeling chorus waves at different L‐shells and local times. The characteristics of dawn and midnight sector microbursts have little difference, but the noon sector has much larger maximum flux and much smaller full width at half maximum, which may be due to dayside's low electron flux in the Landau resonance range. This suggests the controlling effect of keV electrons on the MeV electron precipitation intensity and properties and the overall relativistic electron loss in the outer radiation belt.

Aggradation and reworking of an alluvial fan in response to climate changes on the south bank of Lake Qinghai, NE Tibetan Plateau

Alluvial fans in the piedmont zones of mountains respond most rapidly to tectonic activity, base-level conditions, and climate changes. These allogenic signals are effectively recorded by the external morphology and internal sedimentary characteristics of the fan. Based on field survey interpretation and integrated optically stimulated luminescence (OSL) chronology, we selected a case study of the modern Xiangpi Fan on the south bank of Lake Qinghai, NE Tibetan Plateau, and built a three-stage alluvial fan pattern since Marine isotope stages 3 (MIS3), namely, the debris flow lobe building stage (DFLBS), aeolian building stage (ABS), and streamflow reworking stage (SRS). The climatic indicators, such as the total organic carbon (TOC) flux, precipitation, and sediment particle size flux, are highly correlated with the above stages, indicating that the sedimentary process and changes in fan morphology effectively record orbital climate changes in the Lake Qinghai basin. During the DFLBS, the cold-dry climate accelerated the sediment yield sufficiently, leading to many coarse-grained sediments and low TOC flux being imported into the basin through debris flow processes. During the ABS, the extreme dry-cold climate caused the stagnation of fan development, and aeolian processes dominated the transport of fine sediment. In the SRS, warm-humid conditions led to limited sediment yield and perennial stream power, which promoted the transport of fine-grained material and TOC to the basin by braided–meandering channels. This study provides an excellent case showing how an alluvial fan responds to climate oscillations through changes in sedimentology and geomorphology.

Energy-conserving physics for nonhydrostatic dynamics in mass coordinate models

Abstract. Motivated by reducing errors in the energy budget related to enthalpy fluxes within the Energy Exascale Earth System Model (E3SM), we study several physics–dynamics coupling approaches. Using idealized physics, a moist rising bubble test case, and the E3SM's nonhydrostatic dynamical core, we consider unapproximated and approximated thermodynamics applied at constant pressure or constant volume. With the standard dynamics and physics time-split implementation, we describe how the constant-pressure and constant-volume approaches use different mechanisms to transform physics tendencies into dynamical motion and show that only the constant-volume approach is consistent with the underlying equations. Using time step convergence studies, we show that the two approaches both converge but to slightly different solutions. We reproduce the large inconsistencies between the energy flux internal to the model and the energy flux of precipitation when using approximate thermodynamics, which can only be removed by considering variable latent heats, both when computing the latent heating from phase change and when applying this heating to update the temperature. Finally, we show that in the nonhydrostatic case, for physics applied at constant pressure, the general relation that enthalpy is locally conserved no longer holds. In this case, the conserved quantity is enthalpy plus an additional term proportional to the difference between hydrostatic pressure and full pressure.

Astronomically forced paleoclimate and sea-level changes recorded in the continental margin of the South China Sea over the past ~23 m.y.

AbstractThe Earth has witnessed the emergence of continental-sized ice sheets, starting with Antarctica and gradually extending to both hemispheres over the past 40 million years. These ice accumulations have had a dramatic impact on both paleoclimate and sea level, substantially influencing sediment deposition in the continental margins. However, understanding sediment accumulation on an orbital scale in continental margins remains limited because of the scarcity of high-resolution, chronologically constrained sedimentary records. Here, we conducted a highly resolved cyclostratigraphic analysis based on natural gamma radiation (GR) series in depth domain at the continental margin of the South China Sea. We established a 22.8 m.y.-long high-resolution astronomical time scale spanning from the Miocene to the Quaternary by tuning the GR records to the global deep-sea benthic foraminifera carbon isotope curves and the 405 k.y. eccentricity cycles. The m.y.-scale sea-level changes since the Miocene were reconstructed through the sedimentary noise modeling of the 405-k.y.-tuned GR series. These reconstructions aligned with regional and global sea-level changes. The phase correlation between the filtered 1.2 m.y. cycles of sea-level change curves (dynamic noise after orbital tuning and ρ1 median models) from δ13Cbenthic and tuned GR series and the 1.2 m.y. obliquity amplitude modulation cycles revealed a shift from an anti-phase to an in-phase relationship across the middle Miocene climate transition (ca. 13.8 Ma), suggesting extensive expansion of the Antarctic ice sheet played a key role. In addition, a shift from an in-phase to an anti-phase relationship during the late Miocene (ca. 8 Ma and 5.3 Ma), indicating ephemeral expansion of the Arctic ice sheets or the changes in carbon cycle involving the terrestrial and deep ocean carbon reservoirs, might be the primary driver of eustatic changes. Furthermore, obliquity forcing and changes in meridional gradients in insolation that transported poleward flux of heat, moisture, and precipitation increased ice accumulation in both pole ice sheets and nonlinearly transferred high-latitude signals to low-latitude regions. This phenomenon is supported by the observation of strong obliquity signals in low latitude during global climate cooling interval. Our results suggest that m.y.-scale sea-level variations respond to astronomically induced climate change and ice sheet dynamics of both poles. This work contributes a highly resolved low-latitude geological archive to the future reconstruction of paleoclimate evolution on a global scale.

Two decades variations of nutrients in precipitation at the Qianliyan island, the western Yellow Sea

Precipitation is of great significance in the transport and removal of atmospheric nutrients. For the sake of the acquaintance of nutrient level, deposition flux and secular trend of marginal sea precipitation, two decades (1997–2019) atmospheric investigations were conducted at the Qianliyan island, the western Yellow Sea. Overall, the annual average wet deposition fluxes of nitrate (NO3−), ammonium (NH4+), phosphate (PO43−), silicate (SiO32−), dissolved organic nitrogen (DON) and organic phosphorus (DOP) ranged 9.17–42.80, 13.50–41.44, 0.06–1.88, 0.07–5.56, 14.20–42.14 and 0.09–0.62 mmol·m−2·a−1, respectively. The annual average concentrations of NO3− in precipitation showed a monotonic rising trend, while that of SiO32− showed a monotonic decreasing trend. From the long-term observation, it found an alleviation of acidic precipitation of the Yellow Sea under the policy controls of sulfur dioxide (SO2) and nitrogen oxide (NOx) emissions. Meanwhile, effective control of sand-dust largely reduced precipitation SiO32− concentration. Source also effected precipitation nutrients. Average concentrations of NO3−, NH4+ and SiO32− in precipitation from the ocean were lower than those from the northern arid area, while average concentrations of PO43−, DON and DOP in precipitation from the ocean were higher than those from the northern arid area. Qianliyan precipitation brought rich dissolved inorganic nitrogen (DIN) over PO43− to the ocean surface, which might alter the phytoplankton community succession ultimately.

Process‐Based Intercomparison of Water Isotope‐Enabled Models and Reanalysis Nudging Effects

AbstractThe products from the Stable Water Isotope Intercomparison Group, Phase 2, are currently used for numerous studies, allowing water isotope model‐data comparisons with various isotope‐enabled atmospheric general circulation model (AGCMs) outputs. However, the simulations under this framework were performed using different parameterizations and forcings. Therefore, a uniform experimental design with state‐of‐the‐art AGCMs is required to interpret isotope observations rigorously. Here, we evaluate the outputs from three isotope‐enabled numerical models nudged by three different reanalysis products and investigate the ability of the isotope‐enabled AGCMs to reproduce the spatial and temporal patterns of water isotopic composition observed at the surface and in the atmospheric airborne water. Through correlation analyses at various spatial and temporal scales, we found that the model's performance depends on the model or reanalysis we use, the observations we compare, and the vertical levels we select. Moreover, we employed the stable isotope mass balance method to conduct decomposition analyses on the ratio of isotopic changes in the atmosphere. Our goal was to elucidate the spread in simulated atmospheric column δ18O, which is influenced by factors such as evaporation, precipitation, and horizontal moisture flux. Satisfying the law of conservation of water isotopes, this budget method is expected to explain various fractionation phenomena in atmospheric meteorological and climatic events. It also aims to highlight the spreads in modeled isotope results among different experiments using multiple models and reanalyses, which are primarily dominated by uncertainties in moisture flux and precipitation, respectively.

Dynamics of major environmental disasters involving fire in the Brazilian Pantanal

The 2020 environmental catastrophe in Pantanal has highlighted the fragility of environmental policies and practices for managing and fighting fires in this biome. Therefore, it is essential to know the causes and circumstances that potentiate these fires. This study aimed to: (I) assess the relationship between fire foci and carbon absorption (GPP), precipitation, and carbon dioxide (CO2) flux; (ii) analyze vegetation recovery using the differenced normalized burn ratio (ΔNBR) in Brazilian Pantanal between 2001 and 2022; and (iii) identify priority areas, where the highest intensities of fire foci have occurred, in order to guide public policies in Brazil to maintain local conservation. To this purpose, fire foci were detected using data from the MODIS MOD14/MYD14 algorithm, annual precipitation with CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data), and CO2 flux using the MODIS/MODO9A1 product, and Gross Primary Production (GPP) with the MODIS/MOD17A2 product. The severity of the burned area was also assessed using the ΔNBR index and the risk areas were determined using the averages of these images. During the time series studied, a total of 300,127 fire foci were detected throughout the Pantanal, where 2020 had the highest number of foci and the lowest accumulated precipitation. The years with the highest precipitation were 2014 and 2018. The year 2018 was also the second year with the highest GPP value. The Pettit test showed a trend for 2008 and 2011 as the points of change in the CO2 flux and GPP variables. Principal component analysis clustered fire foci and precipitation on opposite sides, as well as GPP and CO2 flux, while ΔNBR clustered HS, MHS and MLS classes with the years 2020, 2019, 2002 and 2021. There was a high negative correlation between fire foci × rainfall and GPP × CO2 flux. The years with the largest areas of High severity (HS), Moderate-high severity (MHS) and Moderate-low severity (MLS) classes were 2020 and 2019, respectively. The most vulnerable areas for severe fires were the municipalities of Cáceres, Poconé, and Corumbá. The major fire catastrophe in 2020 is correlated with the low precipitation in 2019, the high precipitation in 2018, and the increased GPP, as well government policies unfavorable to the environment.

The directional unit hydrograph model: Connecting streamflow response to storm dynamics

Storm velocity (i.e., direction and speed) and structure (i.e., shape and intensity) play a critical role in streamflow response. These characteristics determine the timing and magnitude of precipitation fluxes across the watershed that drive runoff generation and conveyance along the river network. While previous efforts have used spatially explicit hydrologic models to assess the role of storm properties in streamflow magnitude, their computational demand significantly limits the range of scenarios that can be explored, hindering our ability to systematically identify critical conditions leading to extreme events. To address this technical gap, we introduce the Directional Unit Hydrograph (Directional-UH) model, a parsimonious approach based on the classic theory of the Unit Hydrograph. The Directional-UH extends the original theory by relaxing the assumption of spatial uniform rainfall and incorporating storm direction and speed into the unit hydrograph function. The model conceptualizes storms as rectangular structures with constant intensity moving along a linear trajectory with constant speed. We verify and validate our conceptualization by comparing with simulations, based on observations of extreme rainfall events, of the distributed hydrological model Hillslope-Link-Model (HLM) in the Turkey River basin in Iowa, USA. Then, the Turkey River basin is used as a testbed to illustrate three practical applications of the Directional-UH model. First, we identify the storm trajectory that produces the highest peak flow response. Second, we determine the storm characteristics that maximize the peak flow response by synchronizing storm motion and flood wave; we refer to this as the resonance condition. Third, we systematically explore the compounding effects of consecutive storm events with different trajectories to identify critical combinations that exacerbate the peak flow magnitude. The results on our testbed demonstrate that storm velocity has the potential to increase by a factor of two the peak flow magnitude when compared to stationary storm events. Overall, the parsimonious nature of the Directional-UH model offers a unique and valuable tool for modeling, predicting, and interpreting rainfall-runoff dynamics through the lens of storm direction, speed, and structure.

Energetic Electrons Near Europa From Juno JEDI Data

AbstractOptical remote sensing observations have suggested that the top layer of Europa's icy surface is heavily affected by external weathering agents. To model and understand these effects, it is necessary to characterize the environment as fully as possible. In this paper, we focus on one agent in the environment (energetic electrons). We show Juno electron data from its 2022 Europa flyby and other time periods. While the Juno sensor used here (Jupiter Energetic Particle Detector Instrument) was not designed to obtain high quality electron data in an intense radiation environment, it is possible to extract information such as how Europa blocks energetic particles from accessing some of the surrounding space. The decrease in charged particle flux in Europa's wake provides an upper limit on the precipitation fluxes of the same particles. We also report that electron pitch angle distributions near Europa for the single energy channel considered here are time variable and not isotropic.

Global Distribution of Relativistic Electron Precipitation and the Dependences on Substorm Injection and Solar Wind Ram Pressure: Long‐Term POES Observations

AbstractRelativistic electron precipitation (REP) into the Earth's atmosphere is one of the fundamental mechanisms causing radiation belt electron flux dropout. It is important to know the preferred regions of REP events and the interplanetary and magnetospheric conditions under which the events take place. In this study of the POES relativistic electron data during 1998–2017, we have examined all REP events from L = 3–10 using an automatic algorithm. The REP events preferentially occur in MLT = 17–03 at L = 4–6.5, where the precipitation fluxes also peak. The monthly average REP event number is correlated with both monthly average AE (auroral electrojet index) and Pd (solar wind ram pressure) indices, so we separately investigate the spatial dependences of the events on one index by restricting the other one to a low level. The occurrence rate of REP events increases with both the AE* and the indices (where AE* and are time‐modified from the AE and Pd indices). During large AE* but low , the events occur mainly in the dusk sector (MLT = 17–22) near the plasmapause. For large but low AE* intervals, most of the events occur outside the plasmapause in the midnight sector (MLT = 23–03). Possible REP loss mechanisms are discussed based on our findings. Our study provides new insights into the distribution and dependences of REP in the Earth's magnetosphere.