The formation of strong sporadic E-layers (Es) is frequently observed during the recovery phase of the magnetic storms over Boa Vista (BV, 2.8°N, 60.7°W), a low latitude region over the Brazilian sector. To provide some explanation for this behavior, we investigated in details the ionospheric response to the disturbed electric fields in these atypical Es layers appearance during the magnetic storm of 21-22 January 2016. The analysis was based on F region and Es layers ionospheric parameters obtained from digisonde, as well as on the Total Electron Content (TEC) obtained from Global Navigation SatelliteSystem (GNSS). Furthermore, a theoretical model for the E region named MIRE is used to simulate the Es layers development. Such simulation takes into account the E region winds and electric fields. The results show that the storm time electric field is enough to drive the strong Es layers development. Moreover, it is seen that the intensification of the Es layers is related to the inhibition of the F-region pre-reversal enhancement of the vertical drift due to a westward electric field during the disturbance dynamo effect. Finally, the combined results from the model and observational data seemed to contribute significantly to advance our understanding of the role of the electric fields in the Es layer formation.

At the Earth’s magnetopause, the Kelvin-Helmholtz (KH) instability, driven by the persistent velocity shear between the magnetosheath and the magnetosphere, has been frequently observed during northward interplanetary magnetic field (IMF) periods and considered as one of the most important candidates for transporting and mixing plasmas across the magnetopause. However, how this process interacts with magnetic field fluctuations, which persistently exist near the magnetopause, has been less discussed. Here we perform a series of 2-D fully kinetic simulations of the KH instability at the magnetopause considering a power-law spectrum of initial fluctuations in the magnetic field. The simulations demonstrate that when the amplitude level of the initial fluctuations is sufficiently large, the KH instability evolves faster, leading to a more efficient plasma mixing within the vortex layer. In addition, when the spectral index of the initial fluctuations is sufficiently small, the modes whose wavelength is longer than the theoretical fastest growing mode grow dominantly. The fluctuating magnetic field also results in the formation of the well-matured turbulent spectrum with a -5/3 index within the vortex layer even in the early non-linear growth phase of the KH instability. The obtained spectral features in the simulations are in reasonable agreement with the features in KH waves events at the magnetopause observed by the Magntospheric Multiscale (MMS) mission and conjunctively by the Geotail and Cluster spacecraft. These results indicate that the magnetic field fluctuations may really contribute to enhancing the wave activities especially for longer wavelength modes and the associated mixing at the magnetopause.

Throughout the last years, there is an increasing interest of the geoscientific community in using terrestrial gravimetry as an integrative and non-invasive method for observing mass change and mass redistribution in the environment due geophysical processes. The nature of the observed processes and the need for nearby data collection often require the gravimeters to be installed at remote field sites. In contrast to classical deployment at permanent observatory sites, this often is a challenge because there are three main requirements to be fulfilled for continuous high-quality operation of the gravimeter: electrical power, stable site conditions, and data connection. Whereas the latter can usually be accomplished by wireless solutions, the second requirement is more demanding as it requires an adequate design of a gravimeter enclosure and a stable pillar, while the first requirement so far has been practically insolvable in the absence of a power line. Here, we present the prototype of a mobile field container for gravity monitoring that fulfils all above requirements: the gPhone-solar-cube. The container consists of a cubic steel container as used by ships and trucks with edge length of about 2 meters. We optimized all components to host a continuously operating gPhoneX. Components include temperature shielding, ventilation, solar panels, power management and monitoring, storage batteries and an integrated backup generator to guarantee self-sufficient power supply, data loggers and wireless data transfer components. Furthermore we developed a new type of gravimeter pillar which is simple to install and to remove, without connection to the container floor to avoid vibration transfer. The pillar is large enough to accommodate two CG-6 field gravimeters, next to the gPhoneX. Other instruments integrated are a complete weather station and a cosmic ray neutron probe. The gPhone-solar-cube has been installed in the Ore mountains, Germany, as a continuously operating gravity reference station for time-lapse field surveys with CG-6 gravimeters to assess water storage changes in the course of heavy precipitation events. After 6 months of field operation, all requirements concerning data transmission, remote access, energy consumption, pillar stability and reliable gravity data were continuously met.

The western tropical Pacific (WTP) exhibits large interannual sea level anomalies (SLAs), and the sea level falling in El Niño is evidently stronger than the rising in La Niña. The asymmetry is most prominent near 160°E with the response to El Niño larger by three times and becomes less obvious near the western boundary. Sensitivity experiments of a simplified ocean model suggest that the asymmetry in surface wind forcing structure between El Niño and La Niña is critical. The El Niño’s westerly wind anomaly patch locates more east than the La Niña’s easterly wind patch during the mature stage, and its upwelling effects are accumulated over a wider longitude range and cause stronger negative SLAs in the WTP. Near the western boundary, however, upwelling effects are attenuated by easterly wind anomalies during El Niño conditions. The asymmetric ocean responses to ENSO winds may participate in the asymmetry of ENSO cycle.

The traditional ocean color remote sensing usually focuses on using optical inversion models to estimate the properties of in-water components from the above-surface spectra, so we call it the spectrum-concentration (SC) scheme. Unlike the SC scheme, this study proposed a new research scheme, distribution-distribution (DD) scheme, which uses statistical inference models to estimate the possibility distribution of these in-water components, based on the possibility distribution of the observed spectra. The DD scheme has the advantages that (1) it can rapidly give the key and overview information of the interest water, instead of using the SC scheme to compute each image pixel, (2) it can assist the SC scheme to improve their models and parameters, and (3) it can provide more valuable information for better understanding and indicating the features and dynamics of aquatic environment. In this study, based on Landsat-8 images, we analyzed the spectral possibility distributions (SPD) of 688 global water and found many of them were normal, lognormal, and exponential distributions, but with diverse patterns in distribution parameters such as the mean, standard deviation, skewness and kurtosis. Furthermore, we used Monte-Carlo and Hydrolight simulations to study the theoretical and statistical connections between the possibility distributions of in-water components and SPDs. The simulation results were basically consistent with the observations on the real water. Then by using the simulation and field measured data, we proposed a bootstrap-based DD scheme and developed some simple statistical inference models to estimate the distribution parameters of yellow substance in lakes. Since DD scheme is still on its early stage, we also suggested some potential and useful topics for the future work.

This study uses cloud and radiative properties collected from in-situ and remote sensing instruments during two coordinated campaigns over the Southern Ocean between Tasmania and Antarctica in January-February 2018 to evaluate the simulations of clouds and precipitation in nudged-meteorology simulations with the CAM6 and AM4 global climate models sampled at the times and locations of the observations. Fifteen SOCRATES research flights sampled cloud water content, cloud droplet number concentration, and particle size distributions in mixed-phase boundary-layer clouds at temperatures down to -25 C. The six-week CAPRICORN2 research cruise encountered all cloud regimes across the region. Data from vertically-pointing 94 GHz radars deployed was compared with radar-simulator output from both models. Satellite data was compared with simulated top-of-atmosphere (TOA) radiative fluxes. Both models simulate observed cloud properties fairly well within the variability of observations. Cloud base and top in both models are generally biased low. CAM6 overestimates cloud occurrence and optical thickness while cloud droplet number concentrations are biased low, leading to excessive TOA reflected shortwave radiation. In general, low clouds in CAM6 precipitate at the same frequency but are more homogeneous compared to observations. Deep clouds are better simulated but produce snow too frequently. AM4 underestimates cloud occurrence but overestimates cloud optical thickness even more than CAM6, causing excessive outgoing longwave radiation fluxes but comparable reflected shortwave radiation. AM4 cloud droplet number concentrations match observations better than CAM6. Precipitating low and deep clouds in AM4 have too little snow. Further investigation of these microphysical biases is needed for both models.

The Mount Nyiragongo volcano is known for its active lava lake and for major socio-economic issues raising from future possible eruptive events having global impacts on the whole community living in the Virunga region. The 2020 field expedition inside the summit crater has allowed the collection of unprecedented field observations to state on the current eruptive activity. Since the intra-crater event of February 2016, the lava lake level has been rising much faster than during the 2010-2016 period. The current activity reminds the 1970-1972 and 1994-1995 periods preceding the lava lake draining in 1977 and 2002, respectively. Numerical simulations, successfully validated over the past 30 years of data, show that the rising of the lava lake could slow down in the next months/years and reach a critical equilibrium. However, we calculate that the probability of a failure of the system in the interval March 2024 - November 2027 is not negligible.

Geological faults may produce earthquakes under the increased stresses associated with hydrocarbon recovery, geothermal extraction, CO2 storage. The associated risks depend on the frequency and magnitude of these earthquakes. Within seismic risk analysis, the exceedance probability of seismic moments, Μ, is treated as a pure power-law distribution, Μ^{-β}, where the power-law exponent, β, may vary in time or space or with stress. Insights from statistical mechanics theories of brittle failure, statistical seismology, and acoustic emissions experiments all indicate this pure power-law may contain an exponential taper, Μ^{-β}e^{-ζ Μ}, where the taper strength, ζ, decreases with increasing stress. The role of this taper is to significantly reduce the probability of earthquakes larger than ζ^{-1} relative to the pure power-law. We review the existing theoretical and observational evidence for a stress-dependent exponential taper to motivate a range of magnitude models suitable for induced seismicity risk analysis. These include stress-invariant models with and without a taper, stress-dependent β models without a taper, and stress-dependent ζ models. For each of these models, we evaluated their forecast performance within the Groningen gas field in the Netherlands using a combination of Bayesian inference, and simulations. Our results show that the stress-dependent ζ-model with constant β likely offer (75–85%) higher performance forecasts than the stress-dependent β-models with ζ = 0. This model also lowers the magnitudes with a 10% and 1% chance of exceedance over the next 5 years of gas production from 4.3 to 3.7 and from 5.5 to 4.3 respectively.

TanSat is the 1st Chinese carbon dioxide (CO) measurement satellite, launched in 2016. In this study, the University of Leicester Full Physics (UoL-FP) algorithm is implemented for TanSat nadir mode XCO retrievals. We develop a spectrum correction method to reduce the retrieval errors by the online fitting of an 8 order Fourier series. The model and a priori is developed by analyzing the solar calibration measurement. This correction provides a significant improvement to the O A band retrieval. Accordingly, we extend the previous TanSat single CO weak band retrieval to a combined O A and CO weak band retrieval. A Genetic Algorithm (GA) has been applied to determine the threshold values of post-screening filters. In total, 18.3% of the retrieved data is identified as high quality compared to the original measurements. The same quality control parameters have been used in a footprint independent multiple linear regression bias correction due to the stronger correlation with the XCO retrieval error. Twenty sites of the Total Column Carbon Observing Network (TCCON) have been selected to validate our new approach for the TanSat XCO retrieval. We show that our new approach produces a significant improvement on the XCO retrieval accuracy and precision when compared to TCCON with an average bias and RMSE of -0.08 ppm and 1.47 ppm, respectively. The methods used in this study can help to improve the XCO retrieval from TanSat and subsequently the Level-2 data production, and hence will be applied in the TanSat operational XCO processing.

We developed a new experimental system with which anelasticity of a rock analogue sample (polycrystalline borneol) can be measured in situ during dislocation creep. We attached a piezo-electric actuator to a triaxial deformation apparatus, to add a small cyclic load to a large constant load. We also attached a load cell and two laser displacement meters to measure the small cyclic load and displacement accurately. Using this new system, we deformed a polycrystalline borneol sample under diffusion creep (σ = 0.27 MPa) for about 1 day, intermediate creep (σ ≈ 1.1 MPa) for about 0.5 day and dislocation creep (σ ≈ 2.2 MPa) for about 1 day continuously, and performed an in-situ measurement of Young’s modulus and attenuation at frequencies of 2.5 and 1.0 Hz. During the first diffusion creep, Young’s modulus increased, probably due to the improved contact between the sample and the piston, and reached a constant value. Although the modulus did not change during the second intermediate creep, it gradually decreased during the third dislocation creep. The final modulus reduction was about 20%. The present result supports our previous result obtained from the anelasticity measurement of a pre-deformed sample (Sasaki et al., 2017, AGU fall meeting; Sasaki et al., 2019, submitted to JGR). In the previous study, we showed that detailed form of the dislocation creep curves can be explained well by considering a gradual increase in dislocation density during the dislocation creep. Also, reduction of Young’s modulus by about 10% was observed after the dislocation creep under the similar condition to this study. The gradual decrease in Young’s modulus observed in this present study provides a supporting evidence for these previous results. Frequency dependence of the dislocation-induced anelasticity obtained from our previous study is a peak at much higher frequency than the grain boundary-induced anelasticity (Sasaki et al., 2017, AGU fall meeting; Sasaki et al., 2019, submitted to JGR). In contrast, dislocation-induced anelasticity obtained from single crystal forsterite or polycrystalline olivine is a broad absorption band (Guéguen et al., 1989; Farla et al., 2012). It is important to clarify the reason for this discrepancy.

The NASA InSight lander successfully placed a seismometer on the surface of Mars. Alongside, a hammering device was deployed that penetrated into the ground to attempt the first measurements of the planetary heat flow of Mars. The hammering of the heat probe generated repeated seismic signals that were registered by the seismometer and can potentially be used to image the shallow subsurface just below the lander. However, the broad frequency content of the seismic signals generated by the hammering extends beyond the Nyquist frequency governed by the seismometer's sampling rate of 100 samples per second. Here, we propose an algorithm to reconstruct the seismic signals beyond the classical sampling limits. We exploit the structure in the data due to thousands of repeated, only gradually varying hammering signals as the heat probe slowly penetrates into the ground. In addition, we make use of the fact that repeated hammering signals are sub-sampled differently due to the unsynchronised timing between the hammer strikes and the seismometer recordings. This allows us to reconstruct signals beyond the classical Nyquist frequency limit by enforcing a sparsity constraint on the signal in a modified Radon transform domain. Using both synthetic data and actual data recorded on Mars, we show how the proposed algorithm can be used to reconstruct the high-frequency hammering signal at very high resolution. In this way, we were able to constrain the seismic velocity of the top first meter of the Martian regolith.

We present a method of characterizing the horizontal and vertical electron density roughness of the D-region ionosphere using Nationwide Differential GPS (NDGPS) transmitters as Low Frequency (LF; 30-300 kHz) and Medium Frequency (MF; 300-3000 kHz) signals of opportunity. The horizontal roughness is characterized using an amplitude cross-correlation method, which yields the correlation length scale metric. The vertical roughness is characterized using a differential phase height, which is needed to mitigate the effects of transmitter phase instability. The ranges and typical values of roughness metrics are investigated using data from several field campaign measurements. Finally, the roughness metrics for an NDGPS transmitter and VLF transmitter are compared. It is found that the roughness detected by the VLF transmitter is significantly smoother and demonstrates the utility of this method to complement traditional VLF measurements.

Because of their limited spatial resolution, numerical weather prediction and climate models have to rely on parameterizations to represent atmospheric turbulence and convection. Historically, largely independent approaches have been used to represent boundary layer turbulence and convection, neglecting important interactions at the subgrid scale. Here we build on an eddy-diffusivity mass-flux (EDMF) scheme that represents all subgrid-scale mixing in a unified manner, partitioning subgrid-scale fluctuations into contributions from local diffusive mixing and coherent advective structures and allowing them to interact within a single framework. The EDMF scheme requires closures for the interaction between the turbulent environment and the plumes and for local mixing. A second-order equation for turbulence kinetic energy (TKE) provides one ingredient for the diffusive local mixing closure, leaving a mixing length to be parameterized. A new mixing length formulation is proposed, based on constraints derived from the TKE balance. It expresses local mixing in terms of the same physical processes in all regimes of boundary layer flow. The formulation is tested at a range of resolutions and across a wide range of boundary layer regimes, including a stably stratified boundary layer, a stratocumulus-topped marine boundary layer, and dry convection. Comparison with large eddy simulations (LES) shows that the EDMF scheme with this diffusive mixing parameterization accurately captures the structure of the boundary layer and clouds in all cases considered.

We demonstrate that an extended eddy-diffusivity mass-flux (EDMF) scheme can be used as a unified parameterization of subgrid-scale turbulence and convection across a range of dynamical regimes, from dry convective boundary layers, over shallow convection, to deep convection. Central to achieving this unified representation of subgrid-scale motions are entrainment and detrainment closures. We model entrainment and detrainment rates as a combination of turbulent and dynamical processes. Turbulent entrainment/detrainment is represented as downgradient diffusion between plumes and their environment. Dynamical entrainment/detrainment are proportional to a ratio of buoyancy difference and vertical velocity scale, partitioned based on buoyancy sorting approaches and modulated by a function of relative humidity difference in cloud layer to represent buoyancy loss owing to evaporation in mixing. We first evaluate the closures offline against entrainment and detrainment rates diagnosed from large-eddy simulations (LES) in which tracers are used to identify plumes, their turbulent environment, and mass and tracer exchanges between them. The LES are of canonical test cases of a dry convective boundary layer, shallow convection, and deep convection, thus spanning a broad range of regimes. We then compare the LES with the full EDMF scheme, including the new closures, in a single column model (SCM). The results show good agreement between the SCM and LES in quantities that are key for climate models, including thermodynamic profiles, cloud liquid water profiles, and profiles of higher moments of turbulent statistics. The SCM also captures well the diurnal cycle of convection and the onset of precipitation.

Wetlands are the most important natural source of methane (CH4) to the atmosphere. When present, plant efflux is often the dominant pathway for methane emissions from the anoxic wetland sediments, however, they are rarely considered in chamber measurement campaigns of CH4 flux in wetlands. While studies have focused on the mechanisms that govern transport through plant structures, none have addressed how CH4 emissions relate with carbon uptake or how this relationship may vary among plants. Understanding this relationship has important implications for linking carbon flux at the ecosystem level to wetland CH4 emission predictions, and ultimately, to help improve current carbon budget and greenhouse gas models of wetlands. This study presents simultaneous measurements of CH4 and CO2 fluxes in three macrophyte species of different cosmopolitan genera: Typha (emergent), Nelumbo, and Nymphaea (floating attached). These measurements were conducted using the Picarro GasScouter G4301 fitted with custom-designed leaf chambers. Chamber measurements were performed three times during a day (morning, noon and afternoon), in three separate months. Results indicate significant negative correlations between CH4 flux and carbon uptake in Nelumbo and Nymphaea species and a non-significant positive correlation in Typha sp. We term the rate of CH4 flux per unit CO2 uptake – CH4 flux efficiency. We found that in Nymphaea CH4 flux efficiency is almost double that of Nelumbo. These results suggest the dependence of CH4 efflux in stomatal conductance in the floating attached macrophytes, while in the Typha CH4 flux is primarily through other pores, probably aerenchyma, not regulated by stomata. Our results emphasize the importance of species-specific knowledge and considering the growth type of different wetland macrophytes (e.g. emergent vs floating attached) in scaling of bottom-up observations and ecosystem models.

One third of all coastlines worldwide consist of permafrost. Many of these permafrost coasts are presently exposed to greater environmental forcing as a consequence of climate change, such as a lengthening of the open water season, intensified storms, and higher water and air temperatures. As a result, increasing erosion rates are currently reported from various sites across the Arctic. It is crucial to synthetize these data on Arctic shoreline dynamics in order to improve our understanding on present coastal dynamics on the pan-Arctic scale. A first synthesis product was released in form of the Arctic Coastal Dynamics databse in 2012, which included data published until 2009 (Lantuit et al., 2012). Since then, numerous publications and data products were published on short and long term changes of Arctic coasts across a wide range of study sites. We made an extensive literature review of publications released within the last 10 years and updated the shoreline change data section in the Arctic Coastal Dynamics database. While in 2009 for one percent of the Arctic shoreline data on coastal dynamics was available, the addition of new data leads to a broader data coverage, which is mainly the effect of the greater availability of remotely sensed products for analyses conducted in these remote regions. Further, the additional data allow us to update the current mean rate of Arctic shoreline change.

The intraseasonal variation of the Tibetan Plateau summer monsoon (TPSM) during 1979–2011 is investigated. The TPSM shows a dominant quasi-biweekly oscillation (QBWO) in most summer seasons, and its active/break phases are closely related to more/less precipitation over the Tibetan Plateau. We suggest that the TPSM QBWO is associated with a southeastward propagating nonstationary wave train in the middle and upper troposphere. It shows equivalent barotropic vertical structures over the midlatitudes and a baroclinic structure over the eastern Tibetan Plateau. Wave activity flux analysis indicates that it originates from northern Europe, which is an active center of the summertime Arctic Oscillation (AO). The AO also shows significant QBWO signals and leads TPSM QBWO by about 13 days. Phase composite and wave activity flux analyses of AO QBWO confirmed that the wave train influences TPSM QBWO, suggesting that AO plays an important role in the TPSM on a 10- to 20-day timescale.

Extreme floods which overwhelm the capacity of a system of flood control dams may result in overtopping one or more of those structures. Traditional US Army Corps of Engineers analysis of hydrologic hazards isolates the study area to a single dam. However, in watersheds where flood hazard is managed by several dams, the estimate for the annual probability of overtopping a dam may be influenced by the operation of one or more other dams in that system. Evaluation and prioritization of modifications for dam safety in a portfolio of structures requires a sound estimate of overtopping probability for every structure. In an effort to properly characterize the hydrologic hazard for five dams in the Trinity River Basin above Dallas, Texas, synthetic weather generation coupled with hydrologic and reservoir models is applied to extend the stage-frequency curve for each dam beyond the observed record. The synthetic weather model is comprised of processes which typify floods most likely to result in overtopping the study dams: 1) continuous, local-scale precipitation and temperature sampling to characterize antecedent hydrologic conditions, 2) intermittent (inhomogenous Poisson), synoptic-scale precipitation sampling based on regional precipitation-frequency analysis to generate hazardous floods, 3) k-nearest-neighbor resampling of precipitation and temperature spatiotemporal patterns and 4) temporal disaggregation of daily precipitation to hourly using correlated Brownian processes. Interrelations between local-scale precipitation, synoptic-scale precipitation and temperature are preserved using a Gaussian copula. Natural variability in annual maximum reservoir stage is described using a stratified sampling scheme used to disproportionately represent extreme floods in a fixed sample of 1,000 events, resulting in fewer model events required to span the probability space from 0.5 to 10-8 annual exceedance probability. Knowledge uncertainty in model components is estimated using a parametric bootstrap, resulting in multiple realizations of synthetic weather. Each weather realization of 1,000 events generated using varying parameters is routed using hydrologic and reservoir models for the system which produce a posterior distribution of annual overtopping probability for each structure.