Tropical convection is expected to decrease with warming, in a variety of ways. Specific incarnations of this idea include the ‘stability-iris’ hypothesis, as well as the decrease of both tropospheric and cloud-base mass fluxes with warming. This paper seeks to encapsulate these phenomena into three ‘rules’, and to explore their interrelationships and robustness, using both analytical reasoning as well as cloud-resolving and global climate simulations. We find that each of these rules can be derived analytically from the usual expression for clear-sky subsidence, so they all embody the same essential physics. But, these rules do not all provide the same degree of constraint: the stability-iris effect is not entirely robust due to relatively unconstrained microphysical degrees of freedom, and similarly the decrease in cloud-base mass flux is not entirely robust due to unconstrained effects of entrainment and detrainment. Tropospheric mass fluxes, on the other hand, are shown to be well-constrained theoretically, and when evaluated in temperature coordinates they exhibit a monotonic decrease with warming, at all levels and across a hierarchy of models.

The extreme variability of the cold point tropopause temperature (TCPT) and height (HCPT) are examined over a tropical station, Gadanki (13.45N, 79.2E) using high-resolution radiosonde data during the period 2006-2014. The extreme variabilities such as the coldest (warmest) tropopause is defined if TCPT is lesser (greater) than the lower (upper) limit of its two-sigma level whereas the highest (lowest) tropopause is defined as the HCPTis greater (lesser) than the lower (upper) limit of its two-sigma level. In total 161 extreme cases such as the coldest (52) and warmest (30) TCPT and the highest (57) and lowest (22) HCPT are observed. The coldest (187.2±1.60 K, 17.3±0.52 km), warmest (194.2±1.78 K, 16.9±0.89 km), lowest (191.7±1.78 K, 18.2±0.55 km) and highest (191.8±2.11 K, 16.2±0.38 km) occurs without preference of season. These extreme tropopause cases occur independently. Thermal structure of the coldest tropopause cases reveals that they are often sharper whereas the warmest, highest and lowest tropopause is broader. Water vapor and ozone concentrations are found to be high for the warmest tropopause and low for the coldest tropopause. Under the shallow convection, extreme temperature profiles, in general, show prominent warming between 8-14 km while anomalous cooling (warming) just below (above) the CPT. The occurrence of the tropical cyclones, cirrus clouds and equatorial wave propagation are the possible candidates for the occurrence of the extreme tropopauses.

We develop a generalized interpolation material point method (GIMPM) for the shallow shelf approximation (SSA) of ice flow. The GIMPM, which can be viewed as a particle version of the finite element method, is used here to solve the shallow shelf approximations of the momentum balance and ice thickness evolution equations. We introduce novel numerical schemes for particle splitting and integration at domain boundaries to accurately simulate the spreading of an ice shelf. The advantages of the proposed GIMPM-SSA framework include efficient advection of history or internal state variables without diffusion errors, automated tracking of the ice front and grounding line at sub-element scales, and a weak formulation based on well-established conventions of the finite element method with minimal additional computational cost. We demonstrate the numerical accuracy and stability of the GIMPM using 1-D and 2-D benchmark examples. We also compare the accuracy of the GIMPM with the standard material point method (sMPM) and a reweighted form of the sMPM. We find that the grid-crossing error is very severe for SSA simulations with the sMPM, whereas the GIMPM successfully mitigates this error. While the grid-crossing error can be reasonably reduced in the sMPM by implementing a simple material point reweighting scheme, this approach it not as accurate as the GIMPM. Thus, we illustrate that the GIMPM-SSA model is viable for the simulation of ice sheet-shelf evolution and enables boundary tracking and error-free advection of history or state variables, such as ice thickness or damage.

Local Seismic Response (LSR) studies are considerably conditioned by the seismic input features due to the non-linear soil behavior under dynamic loading and the sub-surface site conditions (e.g., mechanical properties of soils and rocks and geological setting) [1][2]. The selection of the most suitable seismic input is a key point in LSR. Unfortunately, a few natural recordings are available at seismic stations in near field areas [3][4]. Then, synthetic accelerograms can be helpful in LSR analysis in urbanized near field territories. Synthetic accelerograms are generated by simulation procedures that consider adequately supported hypotheses about the source mechanism at the seismotectonic region and the wave propagation path towards the surface. Hereafter, mainshocks recorded accelerograms at near field seismic stations during the 2016-17 Central Italy seismic sequence have been compared with synthetic accelerograms calculated by EXSIM code [5] [6]. The outcomes show that synthetic signals can reproduce the high-frequency content of seismic waves at near field areas. Then, in urbanized near field areas, synthetic accelerograms can be fruitfully used in Microzonation studies. References [1] Vessia G. et al. (2013), Bull. Earthq. Eng., 11(5), 1633-1660. [2] Vessia G. et al. (2021), Eng. Geol. 284, 106031. [3] Mancini F. et al. (2018), ESC2018, S29-639: 428429. [4] Luzi L. et al. (2016), Istituto Nazionale di Geofisica e Vulcanologia, Observatories & Research Facilities for European Seismology. [5] Boore D. M. (2003), Pure Appl. Geophys. 160 635–675. [6] Motazedian D. and Atkinson G. M. (2005), Bull. Seismol. Soc. Am. 95 995–1010.

We introduce the inductive effects of polar cap motions towards and way from the Sun into magnetospheric electrodynamics and show how this explains observed Universal Time variations in hemispheric geomagnetic indices. The large (and growing) hemispheric asymmetry in the offsets of the geomagnetic (dip or eccentric dipole) poles from Earth’s rotational axis means that the effect is not cancelled out in global indices. By adding this effect to that of the Russell-McPherron effect on solar wind-magnetosphere coupling, that of ionospheric conductivities, and that of the solar wind dynamic pressure and dipole tilt on the near-Earth tail lobe field and cross-tail current sheet, we are able to model the persistent “equinoctial” time-of-day/time-of-year pattern (with additional net Universal time variations) observed in the an, as and am geomagnetic indices since 1959. We discuss the implications for the longitudinal dependence of the effects of extreme space weather events

A document by Aurélien Podglajen. Click on the document to view its contents.

We examine tropical rainfall from Geophysical Fluid Dynamics Laboratory’s Atmosphere Model version 4 (GFDL AM4) at three horizontal resolutions of 100 km, 50 km, and 25 km. The model produces more intense rainfall at finer resolutions, but a large discrepancy still exists between the simulated and the observed frequency distribution. We use a theoretical precipitation scaling diagnostic to examine the frequency distribution of the simulated rainfall. The scaling accurately produces the frequency distribution at moderate-to-high intensity (≥10 mm day-1). Intense tropical rainfall at finer resolutions is produced primarily from the increased contribution of resolved precipitation and enhanced updrafts. The model becomes more sensitive to the grid-scale updrafts than local thermodynamics at high rain rates as the contribution from the resolved precipitation increases. On the contrary, the observed tropical precipitation extremes do not show a strong sensitivity to the grid-scale updrafts.

A method is presented to address model state uncertainty in hydrologic model simulation. This is achieved by introducing tuneable parameters that allow adjustments to the model states. Excessive dimensionality is avoided by introducing only a limited number of parameters that control the index (timing) and size of the state adjustments. The method is designed to compensate for issues with hydrologic model structures, particularly those relevant to the soil moisture state in a rainfall-runoff model. In the context of water resource planning and management, errors in the model states have often been overlooked as an important source of uncertainty and have the potential to significantly degrade model simulations. A synthetic study shows that a classical parameter estimation approach will produce biased distributions when state errors exist, and that the proposed state and parameter uncertainty estimation (SPUE) can remove the bias in parameter estimates for improved model simulations. In a real case study, SPUE and the classical approach are implemented in 46 sites around Australia. The results show that hydrologic parameter distributions for a selected conceptual model can be significantly different when accounting for state uncertainty. This has large implications for scenario modelling since it puts into dispute how to determine appropriate parameters for such studies. SPUE parameters outperform the classical approach in a range of metrics including the Akaike Information Criterion. Additionally, SPUE parameters performed better during validation periods. Future work involves testing SPUE with different hydrologic model and likelihood formulations, and enhancing rigor by explicitly accounting for observational data uncertainty.

The largest volcanic eruption of this century, which was submarine, led to a dramatic phytoplankton bloom north of the island of Tongatapu, in the Kingdom of Tonga. In the absence of shipboard observations, we reconstructed the dynamics of this event by using a suite of satellite observations. Two independent bio-optical approaches confirmed that the phytoplankton bloom was a robust observation and not an optical artifact due to volcanogenic material. Furthermore, the timing, size, and position of the phytoplankton bloom suggest that plankton growth was primarily stimulated by nutrients released from volcanic ash rather than by nutrients upwelled through submarine volcanic activity. The appearance of a large region with high chlorophyll a concentrations less than 48 hours after the largest eruptive phase indicates a fast ecosystem response to nutrient fertilization. However, net phytoplankton growth probably initiated before the main eruption, when weaker volcanism had already fertilized the ocean.

StorAge Selection (SAS) functions describe how catchments selectively remove water of different ages in storage via discharge, thus controlling the transit time distribution (TTD) and solute composition of discharge. SAS-based models have been emerging as promising tools for quantifying catchment-scale solute export, providing a coherent framework for describing both velocity and celerity driven transport. However, due to their application in headwaters only, the spatial heterogeneity of catchment physiographic characteristics, land-use management practices, and large-scale validation have not been adequately addressed with SAS-based models. In this study, we integrated SAS functions into the grid-based mHM-Nitrate model (mesoscale Hydrological Model) at both grid scale (distributed model) and catchment scale (lumped model). The proposed model provides a spatially distributed representation of nitrogen dynamics within the soil zone and a unified approach for representing both velocity and celerity driven subsurface transport below the soil zone. The model was tested in a heterogeneous mesoscale catchment. Simulated results show a strong spatial heterogeneity in nitrogen dynamics within the soil zone, highlighting the necessity of a spatially explicit approach for describing near-surface nitrogen processing. The lumped model could well capture instream nitrate concentration dynamics and the concentration-discharge relationship at the catchment outlet. In addition, the model could satisfactorily represent the relations between subsurface storage, mixing scheme, solute export, and the TTDs of discharge. The distributed model shows comparable results with the lumped model. Overall, the results reveal the potential for large-scale applications of SAS-based transport models, contributing to the understanding of water quality-related issues in agricultural landscapes.

The arrival of the Juno satellite at Jupiter has led to an increased interest in the dynamics of the Jovian magnetosphere. Jupiter’s auroral emissions often exhibit quasi-periodic oscillations with periods of tens of minutes. Magnetic observations indicate that ultra-low-frequency (ULF) waves with similar periods are often seen in data from Galileo and other satellites traversing the Jovian magnetosphere. Such waves can be associated with field line resonances, which are standing shear Alfvén waves on the field lines. Using model magnetic fields and plasma distributions, the frequencies of field line resonances and their harmonics on field lines connecting to the main auroral oval have been determined. Time domain simulations of Alfvén wave propagation have illustrated the evolution of such resonances. These studies indicate that harmonics of the field line resonances are common in the 10-40 minute band.

Accurate precipitation monitoring is crucial for understanding climate change and rainfall-driven hazards at a local scale. However, the current suite of monitoring approaches have different insufficiencies, including low spatial and temporal resolutions, and the inability to monitor potentially destructive precipitation events such as hailstorms. In this study, we develop an array-based solution to monitor rainfall with seismic nodal stations, offering both high spatial and high temporal resolutions. We analyze seismic records from densely spaced, high-frequency seismometers in Oklahoma, and identify signals from all 9 precipitation events that occurred during the one-month station deployment in 2016. After removing anthropogenic noise and Earth structure response, the obtained precipitation spatial pattern mimics the one from an operational weather radar, while offering higher spatial and temporal resolutions. We further show the potential of this approach to monitor hail with joint analysis of seismic intensity and independent precipitation rate measurements, and advocate for coordinated seismological-meteorological field campaign design.

For over a decade, the Super Dual Auroral Radar Network (SuperDARN) and the Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE) have been measuring ionospheric convection and field-aligned currents in the high-latitude regions, respectively. Using both, whole hemisphere maps of the magnetosphere-ionosphere energy transfer rate (the Poynting flux) have been generated with a time resolution of two minutes between 2010 and 2017. These uniquely data driven Poynting flux patterns are used in this study to perform a superposed epoch analysis of the northern hemisphere ionospheric response to transitions of the IMF B_z component. We discuss the difference in the distribution of Poynting flux between the magnetosphere-ionosphere Dungey cycle “switching on” and “switching off” to solar wind driving, revealing that they are not symmetric temporally or spatially.

This study explores the impact of deep ( >5 m) critical zone (CZ) architecture on vegetation distribution in a semi-arid snow-dominated climate. Utilizing seismic refraction surveys, we identified a significant correlation between saprolite thickness and LiDAR-derived canopy heights (R²=0.47). We argue that CZ structure, specifically shallow fractured bedrock under valley bottoms, redirects groundwater to locations where trees are established—suggesting they are located in specific locations with access to nutrients and water. This work provides a unique spatially exhaustive perspective and adds to growing evidence that in addition to other factors such as slope, aspect, and climate, deep CZ structure plays a vital role in ecosystem development and resilience.

This study considers 28 geomagnetic storms with Dst $\leq-50$ nT driven by high-speed streams (HSSs) and associated stream interaction regions (SIRs) during 2010-2017. Their impact on ionospheric horizontal and field-aligned currents (FACs) have been investigated using superposed epoch analysis of SuperMAG and AMPERE data, respectively. The zero epoch ($t_0$) was set to the onset of the storm main phase. Storms begin in the SIR with enhanced solar wind density and compressed southward oriented magnetic field. The integrated FAC and equivalent currents maximise 40 and 58 min after $t_0$, respectively, followed by a small peak in the middle of the main phase ($t_0$+4h), and a slightly larger peak just before the Dst minimum ($t_0$+5.3h). The currents are strongly driven by the solar wind, and the correlation between the Akasofu $\varepsilon$ and integrated FAC is $0.90$. The number of substorm onsets maximises near $t_0$. The storms were also separated into two groups based on the solar wind dynamic pressure p_dyn in the vicinity of the SIR. High p_dyn storms reach solar wind velocity maxima earlier and have shorter lead times from the HSS arrival to storm onset compared with low p_dyn events. The high p_dyn events also have sudden storm commencements, stronger solar wind driving and ionospheric response at $t_0$, and are primarily responsible for the first peak in the currents after $t_0$. After $t_0+2$ days, the currents and number of substorm onsets become higher for low compared with high p_dyn events, which may be related to higher solar wind speed.

Low-clouds and fog moderate the diurnal temperature range (DTR) through radiative effects. Consequently, frequent foggy events make montane cloud forests (MCFs) stable and unique. However, observations in the understory of the forest are rare. To investigate the DTR variation in elevations, we surveyed the Central Cross-Island Highway in central Taiwan transects with MCFs. The results from paired weather stations revealed that the DTR increases significantly with altitude in open fields but not in the forest’s understory. Furthermore, the continuous observations in altitude across non-cloud forest and MCFs indicate that DTR decreases in both the open field and understory of MCFs. The DTR discontinuity highlights the indispensability of MCF for the mountain ecosystem. Further simulating the integrative effect of the climate and land-use change on fog is crucial for the ecoclimate in mountainous regions.

Nonlinear internal waves (NLIWs) are prevalent on the northern continental shelf south of Hainan Island in the South China Sea. However, our understanding of these NLIWs is still in a preliminary state. In the study, through a synergistic analysis of satellite observations, in situ measurements and numerical simulations, we take a step toward fully elucidating the generation and propagation process of the NLIWs on the northern continental shelf south of Hainan Island. Both mooring and satellite observations suggest that the Xisha Islands remotely generate the NLIWs on the northern continental shelf south of Hainan Island; moreover, more than one source exists in the Xisha Islands. Based on the realistic topography, stratification and tidal forcing, two-dimensional numerical simulations using the MITgcm reveal that the NLIWs observed on the continental shelf can be generated from different sills in Xisha Islands through the internal tidal beam or mixed tidal lee wave regime. Furthermore, the internal tide energy flux estimation suggests that the locally generated internal tides emanating from the continental shelf break play an essential role in the baroclinic energy field of the deep sea while their influence on the baroclinic energy field of the mid-continental shelf can be almost negligible.

Over the last decade, the opportunistic use of broadband Ocean Bottom Seismometer (OBS) recordings has been extremely beneficial for baleen whales studies as they regularly record their stereotyped calls ([10-40] Hz). Often deployed in remote areas, OBSs offer additional and often unprecedented locations for acoustic data collection. The long-term, widespread networks are then ideal for passive acoustic monitoring. Therefore OBS-recorded data are crucial to conservation purposes from monitoring their post-exploitation recovery to improving our understanding of these endangered species and threats. As an example of the potential of OBSs for baleen whale studies, this work exploits data collected by the RHUM-RUM (Réunion Hotspot and Upper Mantle - Réunions Unterer Mantel) seismic network. It aimed initially at imaging the mantle structure beneath the Western Indian Ocean and the dynamics of La Réunion volcanic hotspot. To that extent, 57 OBSs were deployed on the ocean floor, covering an area of 2000x2000 km2 (Lat. 16-34°S, Long. 048-070°E), from October 2012 to November 2013. The RHUM-RUM data provides the second opportunity to record species-specific or regionally-distinct signals of Blue Whales (BWs; Antarctic and Madagascar Pygmy BW) within the Western Indian Ocean Sanctuary. BW calls can propagate from tens to hundreds of kilometers. Consequently, results show that recordings from a single OBS are sufficient to determine the acoustic presence of a species and estimate the range of a calling individual. However, the data analysis benefits from the use of automatic and reliable detection processes. Additional information arises from increasing the number of sensors: a small array of the RHUM-RUM network (20km inter-sensor distance) is used for localization and tracking, essential for animal counting. Besides, the broader configuration showed repartition and migration patterns of the studied species. These recordings from the bottom of the ocean shed new light on the study of BWs and, more generally, low-frequency sounds in this area.