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Empirical models have been previously developed using the large dataset of satellite observations to obtain the global distributions of total electron density and whistler-mode wave power, which are important in modeling radiation belt dynamics. In this paper, we apply the empirical models to construct the total electron density and the wave amplitudes of chorus and hiss, and compare them with the observations along Van Allen Probes orbits to evaluate the model performance. The empirical models are constructed using the Hp30 and SME (or SML) indices. The total electron density model provides an overall high correlation coefficient with observations, while large deviations are found in the dynamic regions near the plasmapause or in the plumes. The chorus wave model generally agrees with observations when the plasma trough region is correctly modeled and for modest wave amplitudes of 10–100 pT. The model overestimates the wave amplitude when the chorus is not observed or weak, and underestimates the wave amplitude when a large-amplitude chorus is observed. Similarly, the hiss wave model has good performance inside the plasmasphere when modest wave amplitudes are observed. However, when the modeled plasmapause location does not agree with the observation, the model misidentifies the chorus and hiss waves compared to observations, and large modeling errors occur. In addition, strong (>200 pT) hiss waves are observed in the plumes, which are difficult to capture using the empirical model due to their transient nature and relatively poor sampling statistics. We also evaluate four metrics for different empirical models parameterized by different indices. Among the tested models, the empirical model considering a plasmapause and controlled by Hp* (the maximum Hp30 during the previous 24 h) and SME* (the maximum SME during the previous 3 h) or Hp* and SML has the best performance with low errors and high correlation coefficients. Our study indicates that the empirical models are applicable for predicting density and whistler-mode waves with modest power, but large errors could occur, especially near the highly-dynamic plasmapause or in the plumes.

 

Hiss waves play an important role in removing energetic electrons from Earth’s radiation belts by precipitating them into the upper atmosphere. Compared to plasmaspheric hiss that has been studied extensively, the evolution and effects of plume hiss are less understood due to the challenge of obtaining their global observations at high cadence. In this study, we use a neural network approach to model the global evolution of both the total electron density and the hiss wave amplitudes in the plasmasphere and plume. After describing the model development, we apply the model to a storm event that occurred on 14 May 2019 and find that the hiss wave amplitude first increased at dawn and then shifted towards dusk, where it was further excited within a narrow region of high density, namely, a plasmaspheric plume. During the recovery phase of the storm, the plume rotated and wrapped around Earth, while the hiss wave amplitude decayed quickly over the nightside. Moreover, we simulated the overall energetic electron evolution during this storm event, and the simulated flux decay rate agrees well with the observations. By separating the modeled plasmaspheric and plume hiss waves, we quantified the effect of plume hiss on energetic electron dynamics. Our simulation demonstrates that, under relatively quiet geomagnetic conditions, the region with plume hiss can vary from L = 4 to 6 and can account for up to an 80% decrease in electron fluxes at hundreds of keV at L > 4 over 3 days. This study highlights the importance of including the dynamic hiss distribution in future simulations of radiation belt electron dynamics.

 

Using 5‐year of measurements from Van Allen Probes, we present a survey of the statistical dependence of the Earth's outer radiation belt electron flux dropouts during geomagnetic storms on electron energy and various driving parameters including interplanetary magnetic field B_z, P_SW, SYM‐H, and AE. By systematically investigating the dropouts over energies of 1 keV–10 MeV at L‐shells spanning 4.0–6.5, we find that the dropouts are naturally divided into three regions. The dropouts show much higher occurrence rates at energies below ∼100 keV and above ∼1 MeV compared to much smaller occurrence rate at intermediate energies around hundreds of keV. The flux decays more dramatically at energies above ∼1 MeV compared to the energies below ∼100 keV. The flux dropouts of electrons below ∼100 keV strongly depend on magnetic local time (MLT), which demonstrate high occurrence rates on the nightside (18–06 MLT), with the highest occurrence rate associated with northward B_z, strong P_SWand SYM‐H, and weak AE conditions. The strongest flux decay of these dropouts is found on the nightside, which strongly depends on P_SWand SYM‐H. However, there is no clear MLT dependence of the occurrence rate of relativistic electron flux dropouts above ∼1 MeV, but the flux decay of these dropouts is more significant on the dayside, with stronger decay associated with southward IMF B_z, strong P_SW, SYM‐H, and AE conditions. Our statistical results are crucial for understanding of the fundamental physical mechanisms that control the outer belt electron dynamics and developing future potential radiation belt forecasting capability.

 

Energetic electron precipitation (EEP) associated with pulsating aurora can transfer greater than 30 keV electrons from the outer radiation belt region into the upper atmosphere and can deplete atmospheric ozone via collisions that produce NOx and HOx molecules. Our knowledge of exactly how EEP occurs is incomplete. Previous studies have shown that pitch angle scattering between electrons and lower‐band chorus waves can cause pulsating aurora associated with EEP and that substorms play an important role. In this work, we quantify the timescale of chorus wave decay following substorms and compare that to previously determined timescales. We find that the chorus decay e‐folding time varies based on magnetic local time (MLT), magnetic latitude, and wave frequency. The shortest timescales occur for lower‐band chorus in the 21 to 9 MLT region and compares, within uncertainty, to the energetic pulsating aurora timescale of Troyer et al. (2022,https://doi.org/10.3389/fspas.2022.1032552) for energetic pulsating aurora. We are able to further support this connection by modeling our findings in a quasi‐linear diffusion simulation. These results provide observations of how chorus waves behave after substorms and add additional statistical evidence linking energetic pulsating aurora to substorm driven lower‐band chorus waves.

 

Electromagnetic ion cyclotron (EMIC) waves lead to rapid scattering of relativistic electrons in Earth's radiation belts, due to their large amplitudes relative to other waves that interact with electrons of this energy range. A central feature of electron precipitation driven by EMIC waves is deeply elusive. That is, moderate precipitating fluxes at energies below the minimum resonance energy of EMIC waves occur concurrently with strong precipitating fluxes at resonance energies in low‐altitude spacecraft observations. This paper expands on a previously reported solution to this problem: nonresonant scattering due to wave packets. The quasi‐linear diffusion model is generalized to incorporate nonresonant scattering by a generic wave shape. The diffusion rate decays exponentially away from the resonance, where shorter packets lower decay rates and thus widen the energy range of significant scattering. Using realistic EMIC wave packets fromδfparticle‐in‐cell simulations, test particle simulations are performed to demonstrate that intense, short packets extend the energy of significant scattering well below the minimum resonance energy, consistent with our theoretical prediction. Finally, the calculated precipitating‐to‐trapped flux ratio of relativistic electrons is compared to ELFIN observations, and the wave power spectra is inferred based on the measured flux ratio. We demonstrate that even with a narrow wave spectrum, short EMIC wave packets can provide moderately intense precipitating fluxes well below the minimum resonance energy.

 

Abstract Remote sensing is a powerful tool for understanding and scaling measurements of plant carbon uptake via photosynthesis, gross primary productivity (GPP), across space and time. The success of remote sensing measurements can be attributed to their ability to capture valuable information on plant structure (physical) and function (physiological), both of which impact GPP. However, no single remote sensing measure provides a universal constraint on GPP and the relationships between remote sensing measurements and GPP are often site specific, thereby limiting broader usefulness and neglecting important nuances in these signals. Improvements must be made in how we connect remotely sensed measurements to GPP, particularly in boreal ecosystems which have been traditionally challenging to study with remote sensing. In this paper we improve GPP prediction by using random forest models as a quantitative framework that incorporates physical and physiological information provided by solar-induced fluorescence (SIF) and vegetation indices (VIs). We analyze 2.5 years of tower-based remote sensing data (SIF and VIs) across two field locations at the northern and southern ends of the North American boreal forest. We find (a) remotely sensed products contain information relevant for understanding GPP dynamics, (b) random forest models capture quantitative SIF, GPP, and light availability relationships, and (c) combining SIF and VIs in a random forest model outperforms traditional parameterizations of GPP based on SIF alone. Our new method for predicting GPP based on SIF and VIs improves our ability to quantify terrestrial carbon exchange in boreal ecosystems and has the potential for applications in other biomes.