The Open Global Glacier Model (http://oggm.org) is an open source modelling framework, helping various research groups to simulate and understand mountain glacier change at the regional or global scale. OGGM is modular, which means that we encourage users to develop their own physical parameterizations while staying compatible with the OGGM workflow. To achieve this goal, we need OGGM to be easy to understand, install, apply, and extend. In this presentation, I will talk about how we make use of the wealth of open-source tools available in the python and Jupyter ecosystems to provide an online documentation platform for OGGM. Our documentation combines text with interactive examples that run in your web browser, avoiding the typical installation and data download burden for newcomers. With selected examples from the collaborative educational content platform OGGM-Edu (http://edu.oggm.org), I will show how anyone can apply these ideas and tools to their own documentation or outreach project. Finally, I will talk about some of the challenges faced by the OGGM project in its pursuit of becoming a community model. With the increasing pressure on geoscientists who have to learn new complex technologies while navigating the “publish or perish” career model, the growing demand for better open science practices can be a blessing as well as a curse for many early career scientists.

Positive and negative electric streamers are column-shaped discharges which are an important stage in lightning development. The mechanism, by which the streamer acquires a certain velocity and radius of its head, had been a long-standing puzzle. In [1], we proposed a parametric streamer model (PSM), which may explain this mechanism, as well as the mechanism of the streamer threshold electric field. The PSM results for a positive isolated streamer in constant uniform external electric field are verified by comparing with hydrodynamic calculations of a ‘steady-state’ streamer, namely a streamer whose length is kept constant by synchronizing the position of the electrode to which it is attached with the moving streamer head. For this particular streamer configuration, we found that both velocity and radius of a streamer increase with its length, a results which was also observed in previously performed hydrodynamic calculations and experiments. Beside the velocity and radius of the streamer, PSM allows to quickly estimate all other streamer parameters, such as the maximum field at the streamer tip and the field inside the streamer channel. The relatively low, compared to, e.g., hydrodynamic or particle-in-cell (PIC) models, computational costs of PSM suggest that generalizion of PSM principles to more complicated streamer structures may be very valuable. In the present work, we generalize PSM to evaluate how different background conditions affect streamer propagation. In particular, we find that, unlike the uniform-field case described above, (1) for the non-uniform electric field such as that of a spherical electrode, the streamer velocity decreases with length; (2) for a streamer propagating parallel to other similar streamers (as in a streamer “bunch’‘), both velocity and radius stabilize to an approximately constant value. [1] N. G. Lehtinen, “Physics and mathematics of electric streamers,” Radiophysics and Quantum Electronics, 2021, in print [Russian version: DOI: 10.52452/00213462_2021_64_01_12].

Many of the unusual properties of the dwarf planet Pluto's orbit are widely accepted as evidence for the orbital migration of the giant planets in early solar system history. However, some properties remain an enigma. Pluto's long term orbital stability is supported by two special properties of its orbit that limit the location of its perihelion in azimuth and in latitude. We revisit Pluto's orbital dynamics with a view to elucidating the individual and collective gravitational effects of the giant planets on its perihelion location. In this presentation we demonstrate with numerical experiments that, while the resonant perturbations from Neptune account for the azimuthal constraint on Pluto's perihelion location, the long term and steady persistence of the latitudinal constraint is possible only in a narrow range of additional secular forcing which arises fortuitously from the particular orbital architecture of the other giant planets. Our numerical investigations also find that Jupiter has a largely stabilizing influence whereas Uranus has a largely destabilizing influence on Pluto's orbit.

The search for evidence of existing or extant Life (biosignatures) is a growing research topic and one of the main pillars of Astrobiology. There is significant interest in the search and exploration of new biosignatures, and increasing relevance of Potential Biosignatures. These are specific features that although consistent with biological processes can also be attributed to inanimate processes. Biogenic Metallic nanoparticles (MNPs), have been intensively studied and explored, yet their synthesis is not yet fully understood. Despite the lack of a systematic survey on this topic, it is well known that many microbes produce molecules with the capability of reducing metal ions. Given the wide diversity of such molecules, we can assume that all microbial life is capable of synthesizing them and, consequently, producing MNPs. Researchers agree that any existing or extant life on Mars or on other parts of the solar system, is (or was) likely microbial. Therefore, the detection of MNPs formation, when analyzing extraterrestrial samples (e.g., sediments, rocks), could be used to infer the presence of biological molecules and thus be employed as a new potential biosignature. Therefore, in short: yes, biogenic metallic nanoparticles have a great potential of being used as biosignatures.

Human pressures on the coastal zones and oceans have increased considerably in the last decades. Human activities constitute the greatest threat to the coastal and marine environment, generating considerable quantities of plastic waste. Currently, it is widely recognized that the increase of marine-related activities has adversely affected the coastal environment as well as the associated ecosystems. Our study focuses on marine litter and specifically on the floating part of it which is frequently composed of plastic materials. Floating litter tends to accumulate on beach-dune ecosystems, already characterized by multiple anthropogenic pressures and environmental factors. In addition, litter items may be trapped by coastal dune vegetation or saltmarsh. Successively, the degradation of marine litter will cause the entering of secondary microplastics. Most of the previous studies are based on monitoring activities and aim to identify the origin and destination of litter in order to manage the fate and transport issues. Therefore, it is important to develop modeling and monitoring tools to detect and prevent marine debris dispersal in coastal environments. We applied field sampling and UAVs (Unmanned Aerial Vehicles) survey over a complex geomorphic set up in the Po River Delta (Italy). Our field data are implemented into a high-resolution hydro-morphodynamic numerical model for validation. Then, we are able to project into different scenarios of plastic debris accumulation in the coastal zone. Our preliminary results show an accumulation of floating debris in coastal dunes vegetation mainly driven by alongshore currents and wave set up in the nearshore area. Then, wind-dominated directions and magnitude disperse plastic debris in embryo dunes and back-barrier marshes. Specific cleaning operations are therefore needed. Considering that coastal management scenarios and decisions rely on numerical models that can predict best practices for coastal sustainability, our results might help local agencies and stakeholders to manage coastal environments.

DELTA (Deep Earth Learning, Tools, and Analysis) is an open-source framework developed at NASA to simplify running and training machine learning (ML) models on satellite imagery. Users new to machine learning can run existing ML models on satellite imagery with minimal setup and configuration. For experienced ML users, DELTA helps simplify data engineering, preprocessing steps, and reduces the need for boilerplate code that needs written to make satellite imagery datasets palatable for machine learning. This lets data scientists focus on model development while DELTA handles the imagery manipulation. This presentation will demonstrate DELTA’s functionality and share some examples from an active project using it for flood mapping using imagery from multiple satellite sources.

During the 21st century, human–environment interactions will increasingly expose both systems to risks, but also yield opportunities for improvement as we gain insight into these complex coupled-systems. Human–environment interactions operate over multiple spatial and temporal scales, requiring large data volumes of multi-resolution information for analysis. Climate change, land-use change, urbanization, and wildfires, for example, can affect regions differently depending on ecological and socioeconomic structures. The relative scarcity of data on both humans and natural systems at the relevant extent can be prohibitive when pursuing inquiries into these complex relationships. We explore the value of multitemporal, high-density, and high-resolution LiDAR, imaging spectroscopy, and digital camera data from the National Ecological Observatory Network’s Airborne Observation Platform (NEON AOP) for Socio-Environmental Systems (SES) research. We outline specific applications for addressing SES questions, highlight current challenges, and provide recommendations for the SES research community to improve and expand its use of this platform for SES research. The coordinated, nationwide AOP remote sensing data, collected annually over the next 30 years, offer exciting opportunities for cross-site analyses and comparison, upscaling metrics derived from LiDAR and hyperspectral datasets across larger spatial extents, and addressing questions across diverse scales. Integrating AOP data with other SES datasets will allow researchers to investigate complex systems and provide urgently needed policy recommendations for socio-environmental challenges. We urge the research community to further explore interdisciplinary questions and theories that might leverage NEON AOP data, and present a new Research Coordination Network aimed at supporting these efforts.

Twenty years ago, Andy Majda and Rupert Klein developed a multiscale asymptotic theory of tropical dynamics which they named IPESD. IPESD is a linear, forced, dynamical theory on the tropical synoptic scales coupled to a linear, slower, weak temperature gradient theory on the tropical planetary scales. The two scales interact with one another through upscale fluxes of momentum and temperature (the Reynolds stresses) and downscale advection from the planetary scale (developed by B. and Majda as the IMMD theory in 2010). Majda and myself used these theories in the following years to develop a multiscale kinematic model of the Madden Julian oscillation. Criticisms of this theory have missed the essential fact that the mathematics of the asymptotic analysis are inexorable, and verified by observation - the forcing is stronger on small scales and weaker on large scales; that’s all that is really needed to derive IMMD. In our MJO models, we showed that, in order to capture the westerly wind burst structure of the MJO, it was sufficient to force the planetary scales with momentum fluxes (Reynolds stresses) from westward tilted convective structures on the synoptic scales. Left unanswered was the cause of the westward tilted convection, though westward tilts had been observed repeatedly in MJO observing campaigns. The non-traditional terms in the Coriolis force (NCT) seem to provide an excellent candidate for westward tilts, but it is well known that these terms are too weak on scales greater than the mesoscale to affect the dynamics. However, the multiscale theories provide a distinct route for the NCT to affect the planetary scales - through upscale fluxes of momentum. We will show analytically that the net-NCT affects tropical convection by generating zero force in the vertical direction, a westward velocity field in regions of upward flow, and a recirculation in regions of downward flow, around a convective structure. The upscale fluxes from these circulations drive the vertical/westward tilt that was necessary to generate the westerly wind burst in the Majda/Biello models of the MJO. We will also show how these results, westward tilt and the westerly wind burst, can be created in simple laboratory experiments. We sincerely hope that Andy would have been gratified by these results, and excited by our experiment.

Accelerometer-derived neutral mass density (NMD) is an important measurement of the variability in upper atmosphere and one of the widely used measurements to calibrate and validate models used for satellite orbit determination and prediction. Providing precise estimates of the true uncertainty of these NMD products is a challenging task but essential for the space weather and geodetic communities. Using multiple data assimilation (DA) experiments and robust statistical techniques, we investigate the uncertainty distribution of three different accelerometer-derived NMD products from the CHAMP satellite mission. Here, in three different DA experiments, we use an ensemble Kalman filter to drive a physics-based model with CHAMP in-situ electron density and temperature data as well as neutral wind estimates from an empirical model. Using a multi-model ensemble comprised of both physical and empirical models, we characterize the error variances among the different NMD products. Our results indicate considerable differences among the CHAMP data sets and also show a pronounced latitudinal dependency for the estimated error distributions. On average, the error estimates for NMD vary in the range 6.5–15.6% of the signal. Our experiments demonstrate that DA considerably enhances the capability of the physical model. We note that the generic strategies applied here may be useful and applicable to other space missions spanning over longer time periods.

In this presentation, we introduce a Bayesian updating method for inter-event times of different magnitude thresholds in marked point process, apply it to time-series of the ETAS model [1], and discuss the effectiveness in probabilistic forecasting of forthcoming large event considering the information on smaller events. To investigate magnitude threshold dependence of the inter-event time distribution of earthquakes, the conditional probability between inter-event times of different magnitude thresholds is proposed [2]. This gives the one-to-one statistical relationship between inter-event times of different magnitude thresholds. Firstly, we show the Bayes’ theorem on this conditional probability and derive the representation of the inverse probability density function. Secondly, we extend it to the Bayesian updating that gives the relationship between multiple intervals for lower threshold and an interval for upper threshold. We show the derivation of the inverse probability density function and its approximation function for uncorrelated marked point process (background seismicity in the ETAS model). The condition for the inverse probability density function to have a peak is also shown. The approximation function consists of two parts, a kernel-part that determines its outline and a correction term. The former has an easy form to handle numerically and is applicable to the time-series with correlations among events. Thirdly, based on the results for uncorrelated time-series, we apply the Bayesian updating method to time-series of the ETAS model. The mode of the approximation function is numerically shown to be nearly the same as that of the kernel-part. Therefore, the mode of the kernel part is used as the estimate of the occurrence time of forthcoming large event. By using the relative error between the estimate and the actual occurrence time of large event, effectiveness of the estimation with the approximation function is statistically evaluated. As a result, it is shown that if the time-series is dominated by stationary part, immediately or long after the large event, the forecasting is effectively conducted. [1] Y. Ogata, Ann. Inst. Statist. Math. 50(2), 379 (1998). [2] H. Tanaka and Y. Aizawa, J. Phys. Soc. Jpn. 86, 024004 (2017).

There has been increasing realization that the non-traditional Coriolis force terms may have a significant effect on convective circulation and organization in the tropics. In this talk, we introduce the concept of the net Coriolis force of a fluid dynamical flow. In order to compute the net Coriolis force, we assume incompressible flow - and therefore incompressible net Corolis force. Through the Leray projection we are able to construct, both, the pressure needed to maintain an incompressible force, and the net Coriolis force, itself. We explore the effects of the net Coriolis force on basic flows by decomposing the velocity field using the Helmholtz decomposition, and we describe poloidal and horizontal flows separately. We then compute the net Coriolis force associated with the Traditional Corolis terms (proportional to the sine of latitude) and, separately, the net Non-Traditional Coriolis terms (proportional to the cosine of latitude). We show that all poloidal circulations - which are flows which lack a vertical component of vorticity - are in vertical gesotrophic balance. Therefore, the pressure induced by such flows is simply computed without the need to invert a Laplacian. Using the Dynamics of Non-rotating Updraft Tori (DoNUT), which is a polodial circulation framework introduced by Igel & Biello (2020) to describe the full kinematic circulation of atmospheric convection, we show that the net non-traditional Coriolis force has zero component in the vertical direction, is westward in the regions of upward flow, and recirculates eastward poleward of the upward flow. The resulting circulations lead to vertical/westward oriented momentum flux from the resulting Reynold’s stress terms. We will conclude by discussing implications of these circulations for tropical convective organization.

Atmospheric bores are disturbances whose passage is accompanied by a pressure rise and a semi-permanent upward displacement of the isentropic surfaces. A series of waves often trails behind the bore’s leading edge, and in contrast to density currents, the near-surface temperature remains relatively unchanged, or even warms, after the bore passes. One of the most spectacular and well-studied examples of an atmospheric bore is the “Morning Glory”, which occurs in the Gulf of Carpentaria region of northeastern Australia. Atmospheric bores also occur frequently in the nocturnal environment over the Great Plains of the United States, where they are often initiated by gust fronts and density currents in thunderstorm outflows. In favorable conditions, these nocturnal bores can propagate hundreds of kilometers and trigger new convection through low-level lifting that can grow upscale into large organized convective systems. The dynamics of a prototypical atmospheric bore are investigated through a series of two-dimensional numerical simulations and linear theory. These simulations demonstrate that the bore dynamics are inherently finite amplitude. Although the environment supports linear trapped waves, the supported waves propagate in roughly the opposite direction to that of the bore. Qualitative analysis of the Scorer parameter can therefore give misleading indications of the potential for wave trapping, and linear internal gravity wave dynamics do not govern the behavior of the bore. The presence of a layer of enhanced static stability below a deep layer of lower stability, as would be created by a nocturnal inversion, was not necessary for the development of a bore. The key environmental factor allowing bore propagation was the presence of a low-level jet directed opposite to the movement of the bore. Significant turbulence developed in the layer between the jet maximum and the surface, which reduced the low-level static stability behind the bore. Given the essential role of jets and thereby strong environmental wind shear, and given that idealized bores may persist in environments in which the static stability is constant with height, shallow-water dynamics do not appear to be quantitatively applicable to atmospheric bores propagating against low-level jets, although there are qualitative analogies.

The compound extremes of hydrometeorological variables might not only affect as an extreme from a single variable, but might also result due to their interaction in time and space. This occurrence is called compound unusual events. A statistical approach based on the data depth function is being used to identify these occurrences in the multivariate dataset. To illustrate the methodology, the daily historical series of precipitation and mean temperature series from several selected observation stations in Germany will be used. The zero values of precipitation and the anomalies of mean temperature are used in this study. This study will help in answering the occurrence of unusual events for both variables on temporal and spatial scales.

Year-round demand for luxury food crops, such as berries, has rapidly increased for high income populations in the last twenty years. For example, the United States per capita import of berries has increased tenfold in twenty years, with at least 98% of its imported strawberries, raspberries, and blackberries being sourced from Mexico. In the Mexican state of Michoacan, agricultural areas have transformed to satisfy the global demand, altering local water and land resource patterns. While previous studies have examined the water resource sustainability of export agriculture, more research is needed to understand how export-oriented agriculture competes with or complements common pool resource systems previously established in production regions. In this study, we combine a national dataset on communal-tenured land (ejidal land) with geospatial agricultural data to quantify the water and land use resource changes of Michoacan – the booming heart of Mexican berries. This study captures the berry boom that occurred in the state between 2010 and 2020 using machine learning algorithms on satellite images, land cover change mapping, and biophysical modelling. It asks to what extent the communal land, with its associated natural resources, has been incorporated into the agro-export crop industry. This study adds to the existing commons literature by assessing local land use and resource use change within an increasingly globalized world.

The variability of the middle atmosphere is driven by a variety of atmospheric waves covering various spatial and temporal scales. In particular, the northern winter mesosphere/ lower thermosphere at mid- and polar-latitudes shows a huge variability related to planetary waves, which can disturb the polar vortex leading to large scale coupling effects like sudden stratospheric warmings (SSWs) altering the vertical propagation conditions of tides and gravity waves. Here we are going to investigate and diagnose the short time variability of tides (several days) at the MLT using ground-based observations at mid and polar latitudes and data from NAVGEM-HA for selected periods. NAVGEM-HA provides information about the global structure of the zonal mean zonal and meridional wind and the zonal mean temperature as well as the tides. At mid- and high-latitudes the semi-diurnal tide (SW1 and SW2) is the dominating tidal wave during the winter season, which is also seen in meteor radar and lidar climatologies. Further, we analyze local meteor radar and lidar observations at Andenes (polar-latitude) and Juliusruh (mid-latitude) to diagnose the local amplitude and phase variability due to changes in the background mean winds caused by planetary waves and SSWs. We will show that the tidal phase (in UT) can drift significantly within several days and weeks. These local measurements are also compared to NAVGEM-HA applying the same diagnostic as to the observations. In addition to the winter time observations, we will also show results for the phase propagation of tides from summer periods.

High-resolution observations made by the Hubble Space Telescope have developed the modern picture of the Jovian main oval emission as the signature of field-aligned corotation-enforcement currents which keep magnetospheric plasma rotating at the same rate as Jupiter's magnetic field. This model explains the slowly changing behavior and bright emissions of the main oval and allows the magnetosphere to be studied by remote observations, as the auroral oval directly reflects processes in the magnetosphere and properties of the plasma therein. Recent results from the Juno mission have called these results into question, as the strong, field-aligned currents required by the corotation-enforcement current system have not been measured. Where is the corotation-enforcement current-- which must exist to move magnetospheric plasma-- a dominant driver of the main oval emission? Where do other processes drive the main oval aurora instead? We present one of the widest surveys of Jupiter's main oval auroral features to date by combining over 180 hours of Hubble Space Telescope observations to address these questions. This comprehensive survey is the first to measure the corotation rate, an important tool for distinguishing auroral drivers, of all individual auroral features. This analysis is made possible due to the development of automated pipelines to reduce observations, produce keograms, identify discrete auroral emission features, and measure the corotation rates of these features, among other properties. We present the measured properties of emission features as a function of location along the main oval, in terms of longitude, local time, auroral local time, and magnetic local time. These results serve as the foundation for comparison to in-situ measurements from both the Galileo and Juno missions, which will ultimately help reveal which magnetospheric conditions are likely responsible for driving corotating emissions and which are responsible for sub-corotating emissions, such as the dawn storms.

Stratospheric aerosol injection (SAI) can provide global cooling by adding aerosols to the lower stratosphere, and thus is considered as a possible supplement to emission reduction. Previous studies have shown that injecting aerosols at different latitude(s) and season(s) can lead to differences in regional surface climate, and there are at least three independent degrees of freedom (DOF) that can be used to simultaneously manage three different climate goals. To understand the fundamental limits of how well SAI might compensate for anthropogenic climate change, we need to know the possible surface climate responses to SAI by evaluating the SAI design space. This research work quantifies the number of meaningfully-independent DOFs of the SAI design space. This number of meaningfully-independent DOF depends on both the climate metrics that we care about and the amount of cooling. From the available simulation data of different SAI strategies, we observe that between surface air temperature and precipitation, surface air temperature dominates the change of surface climate. The number of injection choices that produce detectably different surface temperature is more than the number of injection choices that produce detectably different precipitation. At low levels of cooling, only a small set of injection choices yield detectably different surface climate responses. As more cooling is needed, more injection choices produce detectably different surface climate. For a cooling level of 1-2C, we find that there are likely between 6 and 12 DOFs. This reveals new opportunities for exploring alternate SAI designs with different distributions of climate impacts and evaluating the underlying trade-offs between different climate goals.

Tides are critical to coastal and oceanic processes. While tidal data are available readily, they are often corrupted by various sources of error. An automated, fast MATLAB toolbox is developed to clean-up tidal timeseries data from estuarine and oceanic locations corrupted by errors. This toolbox will immensely speed up delivery of quality-controlled tidal data. It will also reduce errors in quality control, which typically involves several manual tasks. The toolbox corrects poorly interpolated and noisy data, erroneous outliers, and instrumentation bias such as spurious jumps, drifts, spikes, and modulations in the true signal. Signal clean-up involves multiple stages. First, thresholds are imposed on higher order temporal derivatives of the signal to remove gross interpolations and noise saturated signal chunks, followed by a moving median threshold to remove outliers. Then the surviving signal is filtered into tidal, subtidal and long-period components, and the long-period component is subject to a maximal overlap discrete wavelet transformation, in which the transform coefficients corresponding to multi-scale edge features are removed. Subsequently, local information in the subtidal and tidal components is compared relative to the whole signal to correct spurious amplitude modulations and sudden biases. Consequently, these components are added to recover the uncorrupted signal, and large data gaps are filled with short term harmonic reconstruction. For estuarine locations, the correlation in the spectrogram between two nearby stations is initially used to quantify and remove river influence in the signal. Applications to datasets at multiple global locations demonstrate the value of the toolbox.