Two-dimensional hybrid particle-in-cell (PIC) simulations are carried out on a constant L-shell (or drift shell) surface of the dipole magnetic field to investigate the generation process of near-equatorial fast magnetosonic waves (a.k.a equatorial noise; MSWs hereafter) in the inner magnetosphere. The simulation domain on a constant L-shell surface adopted here allows wave propagation and growth in the azimuthal direction (as well as along the field line) and is motivated by the observations that MSWs propagate preferentially in the azimuthal direction in the source region. Furthermore, the equatorial ring-like proton distribution used to drive MSWs in the present study is (realistically) weakly anisotropic. Consequently, the ring-like velocity distribution projected along the field line by Liouville’s theorem extends to rather high latitude, and linear instability analysis using the local plasma conditions predicts substantial MSW growth up to +- 27deg latitude. In the simulations, however, the MSW intensity maximizes near the equator and decreases quasi-exponentially with latitude. Further analysis reveals that the stronger equatorward refraction at higher latitude due to the larger gradient of the dipole magnetic field strength prevents off-equatorial MSWs from growing continuously, whereas MSWs of equatorial origin experience little refraction and can fully grow. Furthermore, the simulated MSWs exhibit a rather complex wave field structure varying with latitude, and the scattering of energetic ring-like protons in response to MSW excitation occurs faster than the bounce period of those protons so that they do not necessarily follow Liouville’s theorem during MSW excitation.

Soluble and total trace metals were measured in 4 size fractionated aerosol samples collected over the tropical eastern Atlantic Ocean. In samples that were dominated by Saharan dust, the size distributions of total iron, aluminium, titanium, manganese, cobalt and thorium were very similar to one another and to the size distributions of soluble manganese, cobalt and thorium. Finer particle sizes (< ~3 µm) showed enhanced soluble concentrations of iron, aluminium and titanium, possibly as a result of interactions with acidic sulfate aerosol during atmospheric transport. The difference in fine particle solubility between these two groups of elements might be related to the hyperbolic increase in the fractional solubility of iron, and a number of other elements, during the atmospheric transport of Saharan dust, which is not observed for manganese and its associated elements. In comparison to elements whose solubility varies during atmospheric transport, the stability of thorium fractional solubility should reduce uncertainties in the use of dissolved concentrations of this element in seawater as a proxy for dust deposition, although this topic requires further work.

Anthropogenic climate change is driving shifts in vegetation communities. These shifts are projected to increase in frequency and extent as climate change intensifies into the future. Trees are long-lived and, in the absence of disturbance, can tolerate years to decades of climate conditions for which they are maladapted. A disturbance, however, can trigger a sudden shift in vegetation type where “legacy” forests are maladapted. Identifying the level of forest maladaptation to climate and likelihood of disturbance could help land managers anticipate sudden vegetation shifts as they plan for the future. As part of the NASA CMS Project, we implemented an Environmental Evaluation Modeling System (EEMS) model to evaluate the risk for sudden forest shift in the western conterminous United States. To determine where forests will be maladapted under future conditions, we simulated vegetation without fire using the MC2 dynamic global vegetation model (DGVM) with 20 different climate scenarios. Vegetation type departure between historical and future periods is used as a proxy for the risk of vegetation shift due to maladaptation. The greater the departure, the greater the risk. To limit our analysis to actual forested areas, we used LandFire forest landcover from the U.S. Departments of Agriculture and Interior. To quantify disturbance risk, the EEMS model uses a disturbance dataset produced as part of the NASA CMS project. In addition to quantifying the risk of sudden vegetation shift, the EEMS model also provides a standalone data layer of forest maladaptation useful for decision support as well as the spatial data layers for each node in the EEMS model. To conclude, we discuss how the model can be combined with other models – e.g. species distribution models and economic models – to further inform land management decisions.

Key Points: • Ecological and evapotranspiration characteristics of ten typical vegetation communities in semi-arid steppe were refined and decomposed. • Sensitive parameters of dynamic evapotranspiration improve the regional simulation effect. • Deep learning was used to downscale regional evapotranspiration at the 3-hour scale. Abstract Reports on ecohydrological models for semi-arid steppe basins with scarce historical data are rare. To fully understand the ecohydrological processes in such areas and accurately describe the coupling and mutual feedback between ecological and hydrological processes, a distributed ecohydrological model was constructed , which integrates multi-source information into the MY Ecohydrology (MYEH) model. This paper mainly describes the evapotranspiration module (Eva module) based on sensitive parameters and deep learning. Based on multi-source meteorological, soil, vegetation, and remote sensing data, the historical dynamic characteristics of ten typical vegetation communities in the semi-arid steppe are refined in this study and seven evaporation (ET) components in the Xilin River Basin (XRB) from 1980 to 2018 are simulated. The results show that the Naive Bayesian model constructed based on the temperature and three types of surface reflectance can clearly distinguish between snow-covered or-free conditions. Based on the refinement of typical vegetation communities, the ET process characteristics of different vegetation communities in response to climate change can be determined. Dynamic sensitive parameters significantly improve the regional ET simulation. Based on the validation with the Global Land Evaporation Amsterdam Model product and multiple models in multiple time scales (year, quarter, day, 3 h), a relatively consistent and reliable ET process 1 was obtained for the XRB at the 3-hour scale. The uncertainties of adding and dynamizing more ET process parameters and adjusting the algorithm structure must be further studied.

Although the non-uniqueness of the solution is commonly mentioned in the context of studies that perform spectral decompositions to separate source and propagation effects, its impact on the interpretation of the results is often overlooked. The purpose of this study is to raise awareness on this important subject for modelers and users of the models and to evaluate the impact of strategies commonly applied to constrain the solution. In the first part, we study the connection between the source-station geometry of an actual data set and the properties of the design matrix that defines the spectral decomposition. We exemplify the analyses by considering a geometry extracted from the data set prepared for the benchmark Community Stress Drop Validation Study (Baltay et al., 2021). In the second part, we analyze two different strategies followed to constrain the solutions. The first strategy assumes a reference site condition where the average site amplification for a set of stations is constrained to values fixed a-priori. The second strategy consists in correcting the decomposed source spectra for unresolved global propagation effects. Using numerical analysis, we evaluate the impact on source scaling relationships of constraining the corner frequency of magnitude 2 events to 30 Hz when the true scaling deviates from this assumption. We show that the assumption can not only shift the overall seismic moment versus corner frequency scaling but can also affect the source parameters of larger events and modify their spectral shape.

A strong stratospheric sudden warming (SSW) event occurred in the southern hemisphere (SH) in September 2019 and significantly weakened the stratospheric polar vortex. Due to the positive zonal wind anomalies in the troposphere, the barotropic/baroclinic instability, primarily controlled by the horizontal/vertical wind shear, weakened in the mid-latitude upper troposphere from September 17 to October 15. As a result, planetary waves (PWs) deflect equatorward near the tropopause rather than vertically into the stratosphere, resulting in less perturbing of the polar vortex. After October 15, the westward zonal wind anomalies propagate downward and reach the troposphere, increasing the tropospheric barotropic/baroclinic instability. This benefits the propagation of PWs into the stratosphere, leading to the early breaking of the stratospheric polar vortex. The anomalous cooling due to enhanced upwelling in the SH mesosphere is caused by stronger stratospheric wind filtering of gravity waves (GWs), governing the early onset of polar mesospheric clouds (PMCs).

Optimization of spatially consistent parameter fields is believed to increase the robustness of parameter estimation and its transferability to ungauged basins. The current paper extends previous multi-objective and transferability studies by exploring the value of both multi-basin and spatial pattern calibration of distributed hydrologic models as compared to single-basin and single-objective model calibrations, with respect to tradeoffs, performance and transferability. The mesoscale Hydrological Model (mHM) is used across six large central European basins. Model simulations are evaluated against daily streamflow observations at the basin outlets and remotely sensed evapotranspiration patterns obtained with a two-source energy balance approach. Several model validation experiments are performed through combinations of single- (discharge) and multi-objective (discharge and spatial evapotranspiration patterns) calibrations with holdout experiments saving alternating basins for model evaluation. The study shows that there are very minimal tradeoffs between spatial and temporal performance objectives and that a joint calibration of multiple basins using multiple objective functions provides the most robust estimations of parameter fields that perform better when transferred to ungauged basins. The study indicates that particularly the multi-basin calibration approach is key for robust parametrizations, and that the addition of an objective function tailored for matching spatial patterns of ET fields alters the spatial parameter fields while significantly improving the spatial pattern performance without any tradeoffs with discharge performance. In light of model equifinality, the minimal tradeoff between spatial and temporal performance shows that adding spatial pattern evaluation to the traditional temporal evaluation of hydrological models can assist in identifying optimal parameter sets.

Notwithstanding the large number of studies on bedforms such as dunes and antidunes, performing quantitative predictions of bedform type and geometry remains an open problem. Here we present the results of laboratory experiments specifically designed to study how sediment supply and caliber may impact equilibrium bedform type and geometry in the upper regime. Experiments were performed in a sediment feed flume with flow rates varying between 5 l/s and 30 l/s, sand supply rates varying between 0.6 kg/min and 20 kg/min, uniform and non-uniform sediment grain sizes with geometric mean diameter varying between 0.22 mm and 0.87 mm. The experimental data and the comparison with datasets available in the literature revealed that the ratio of the volume transport of sediment to the volume transport of water Qs/Qw plays a prime control on the equilibrium bed configuration. The equilibrium bed configuration transitions from washed out dunes (lower regime), to downstream migrating antidunes (upper regime) for Qs/Qw between 0.0003 and 0.0007. For values of Qs/Qw greater than those typical of downstream migrating antidunes, the bedform wavelength increases with Qs/Qw. At these high values of Qs/Qw equilibrium bed configurations with fine sand are characterized by upstream migrating antidunes or cyclic steps, and significant suspended load. In experiments with coarse sand, equilibrium is characterized by plane bed with bedload transport in sheet flow mode. Standing waves form at the transition between downstream migrating antidunes and bed configurations with upstream migrating bedforms.

A document by James Conder. Click on the document to view its contents.

In Greek mythology, Cassandra was cursed with a prophetic knowledge of the future that no one would believe. The premise of this mythological prophet is also an apt description of the challenge facing scientists in communicating climate change. Central to addressing this challenge is the ability to examine, interpret and understand the individual scaffolding that underlies people's perception of climate change. Human-centered design incorporates a deep assessment of human needs in the design of systems and services, providing an alternative lens to engage in action towards climate change. Over the course of three separate design classes, attracting a diverse array of students from undergraduate to PhD to professional degrees, from engineers to humanists, we have explored the intersection of design education and climate change communication. In Design for a Habitable Planet, students conducted broad unstructured interviews to populate a matrix of beliefs and experiences around climate change, allowing them to bridge a perceived empathy gap. Their subjects included local fisherman, who are experiencing climate change but are ideologically opposed to the concept, and Alaska Native students who are experiencing climate change as part of a larger portfolio of challenges facing their communities. Leveraging theories from behavioral psychology, students then developed and prototyped an array of climate action campaigns, using an array of mediums from Snapchat filters to crowd-sourced climate haiku on beer labels. A unique outcome of the design process was a set of strategies intended to engage voices from all corners of the climate change debate and in turn inspire action. In Design of Data, students were challenged to design a data journalism piece highlighting positive action to address climate change. Students struggled with their pre-conceived negative bias around climate change, but after an examination of their own communities, what emerged were eight compelling stories daylighting positive and collective action to address global change. Ultimately, through our classroom experiments integrating design, behavioral psychology and climate change communication, students have not only learned to engage across differences, but we have developed a first glimpse of the power of design to inspire novel strategies to incite positive action to address climate change.

Thematic map creation is a process that implies several steps to be accomplished regardless of the type of the map to be produced, starting from data collection, through data exploitation and ending with maps publication as print, image, and GIS format. An example are geological, lithological, and geomorphological maps, in which most of the highest time-consuming tasks are those related to the discretization of single objects by identifying a set of unique characteristics that describe uniquely those objects. Commonly these tasks introduce interpretative biases due to the different experience of the mappers who's performing it. In this setting, Deep Learning Computer Vision techniques could play a key-role but lack the availability of a complete set of tools specific for planetary mapping. The aim of this work is to develop a comprehensive set of ready-to-use tools for landforms mapping, in which users have full access to the workflow and over all the processes involved, granting complete control and customization capabilities. In this work are presented both the developed tools and the approach that has been used and that is based on consolidated Deep Learning methodologies and open-source libraries commonly applied in other fields of Computer Vision. The toolset and the approach presented have been tested in the science case of mapping sinkhole-like landforms on Mars and results are presented.

It has long been recognized that the energy source for major solar flares and coronal mass ejections (CMEs) is the solar magnetic field within active regions. Specifically, it is believed to be the release of the free magnetic energy (energy above the potential field state) stored in the field prior to eruption. For estimates of the free energy to provide a prognostic for future eruptions, we must know how much energy an active region can store – Is there a bound to this energy? The Aly-Sturrock theorem shows that the energy of a fully force-free field cannot exceed the energy of the so-called open field. If the theorem holds, this places an upper limit on the amount of free energy that can be stored. In recent simulations, we have found that the energy of a closely related field, the partially open field (POF), can place a useful bound on the energy of an eruption from real active regions, a much tighter constraint than the energy of the fully open field. A database of flare ribbons (Kazachenko et al., ApJ 845, 2017) offers us an opportunity to test this idea observationally. A flare ribbon mask is defined as the area swept out by the ribbons during the flare. It can serve as a proxy for the region of the field that opened during the eruption. In this preliminary study, we use the ribbon masks to define the POF for several large events originating in solar cycle 24 active regions, and compute the energy of the POF. We compare these energies with the X-ray fluxes and CME energies for these events. Work supported by NSF, NASA, and AFOSR.

The complex spatial and temporal structure of cumulus clouds complicates their representation in weather and climate models. Classic meteorological instrumentation struggles to fully capture these features. Networks of multiple high-resolution hemispheric cameras are increasingly used to fill this data gap, and provide information on this missing multi-dimensional spatial information. In this study, a path-tracing algorithm is used to generate virtual camera images of resolved clouds in Large-Eddy Simulations (LES). These images are then used as a camera network simulator, allowing reconstructions of three-dimensional cloud edges from the model output. Because the actual LES cloud field is fully-known, the combined path-tracing and reconstruction method can be statistically analyzed. The method is applied to LES realizations of summertime shallow cumulus at the Jülich Observatory for Cloud Evolution (JOYCE), Germany, which also routinely operates a camera network. We find that the Blender path-tracing method allows accurate reconstruction of up to 70% of the visible cloud edges, depending on camera distance and accuracy thresholds. Additionally, we conducted sensitivity tests and find that our method remains consistent and independent of changes in its hyperparameters. The sensitivity of the stereo reconstruction algorithm to cloud optical thickness is investigated, finding a cloud boundary placement error of approximately 182 m. This error can be considered typical for cloud boundary reconstruction using stereo camera imagery in general. The results provide proof of principle for future use of the method for evaluating LES clouds against real camera imagery, and for further optimizing the configuration of such camera networks.

This study presents ultra-low frequency (ULF) Pc5 discrete spectrum simultaneously observed in the magnetosphere and high- to low-latitude ionospheres near noon hours (~10-14 MLT) during the recovery phase of geomagnetic storm on November 4, 2021. During the recovery phase, magnetospheric toroidal mode oscillations (GOES-16 Bn) appeared according to solar wind dynamic pressure enhancements after GOES Bp and Be (poloidal mode) oscillations precede during high solar wind speeds. When Bn oscillates, the ionospheric line-of-sight (LOS) velocity and echo power oscillate at the same discrete frequencies of 1.7 and 2.2 mHz (9.7 and 7.5 min), observed by Super Dual Auroral Radar Network (SuperDARN) at Saskatoon (eastward LOS). The period of negative LOS velocity (away from the radar) for 7.5 min or 9.7 min corresponds to echo power increase. This signifies that both the ionospheric density and poleward convection velocity increase are driven by the periodic forcing of the convection electric field and energetic electron precipitation. The same frequency pulsations have also been observed in the geomagnetic field (H-component) and Global Positioning System (GPS) total electron content (TEC) from high- to low-latitude ionosphere. The oscillation frequency of the H-component is consistently preserved at 1.7 mHz (9.7 min) down to low latitudes. The Pc5 oscillations at high to low latitudes can be attributed to toroidal mode Alfven waves and the compressional mode propagating across magnetic field lines as well as the fast magnetosonic waveguide mode at work by the solar wind dynamic pressure enhancements at high solar wind speeds.enhancements at high solar wind speeds.enhancements at high solar wind speeds.enhancements at high solar wind speeds.enhancements at high solar wind speeds.

Flood impacts to residential properties threaten the resilience of communities and the institutions that support them. These events can cause negative impacts to property-level balance sheets through uninsured damage and property value decreases, which in turn can increase the likelihood of mortgage default and property abandonment. To date, there have been limited attempts to quantify the magnitude and distribution of additional financial consequences that could arise from these processes following flood events. In this work, property-scale financial data, including property sales, mortgage originations, and insurance claims, are used within an analytical framework to quantify flood-related uninsured damages and property value decrease in order to estimate the financial risk that property owners, mortgage lenders, and local governments are exposed to via recovery decisions (i.e., default and/or abandonment). This framework is applied to residential properties in eastern North Carolina following Hurricane Florence (2018). Within the study area, Hurricane Florence generated $366M in observed insured losses and we estimate an additional $1.77B in balance sheet losses (i.e., uninsured damage and property value decrease). In addition, property owners, mortgage lenders, and local governments were exposed to an estimated $562M of risk from the increased likelihood of mortgage default and property abandonment. Areas with lower pre-event property values and lower rates of insurance purchase experienced significantly higher risk of mortgage default and abandonment. The method described provides more highly resolved estimates of how floods can drive systemic financial risk, information that can be useful in developing improved flood resilience strategies.

Field kits for testing the level of a toxicant in the environment are inherently less accurate than a laboratory instrument. Using a specific example, we argue here that kit measurements still have a key role to play when the spatial distribution of a toxicant is very heterogeneous. The context is provided by the groundwater arsenic problem in Bangladesh. We combine here two data sets, a blanket survey of 6595 wells over a 25 km2 based on laboratory measurements and 900 paired kit and laboratory measurements from the same area. We explore different hypothetical mitigation scenarios based on actual data that rely on households with a high-arsenic well switching to a nearby low-arsenic well. We show that the decline in average exposure to arsenic from relying on kit rather than laboratory data is modest in relation to the logistical and financial challenge of delivering exclusively laboratory data. Our analysis indicates that the 50 ug/L threshold used in Bangladesh to distinguish safe and unsafe wells, rather than the WHO guideline of 10 ug/L, is close to optimal in terms of average exposure reduction. We also show, however, that providing kit data at the maximum possible resolution rather than merely classifying wells as unsafe or safe would be even better. These findings are relevant as the government of Bangladesh is about to launch a new blanket testing campaign of millions of wells using field kits.

The magnitude of aerosol radiative effects remains the single largest uncertainty in current estimates of anthropogenic radiative forcing. One of the key quantities needed for accurate estimates of anthropogenic radiative forcing is an accurate estimate of the radiative effects from natural aerosol. The dominant source of natural aerosols over Earth’s forested regions is biogenic volatile organic compounds (BVOC) which, following oxidation in the atmosphere, can participate in new particle formation or condense onto aerosols to form secondary organic aerosol (SOA). Consequently, BVOC emissions could introduce a regionally relevant cooling feedback in a warming climate. The main objective of this study is to provide a quantitative estimate of the regional aerosol direct radiative effect caused by the temperature-dependent biogenic emissions over the boreal forests in present day conditions and in a warmer future. The study is done using a combination of climate modeling and satellite data. The aerosol-chemistry climate model used is ECHAM-HAMMOZ, which describes the relevant atmospheric aerosol processes. The BVOC emissions are computed online using the MEGAN model, which enables the simulation of the effects of temperature changes on atmospheric aerosol load. Key remote sensing data used are the AATSR based aerosol optical depth (AOD) and land surface temperature (LST) products available from the Aerosol-CCI and GlobTemperature projects, together with ancillary data, such as column concentrations of CO and water vapour from AIRS, and NO2 column densities from OMI. Our analysis shows that there could be a small temperature dependence in AOD over the boreal forests but it cannot be reliably detected from the simulations or observations. The only subregion with a clear temperature dependence in AOD was found over western Russia. Anthropogenic emissions affect this subregion more than the other regions analyzed thus, it is likely that in addition to BVOC emissions hygroscopic sulfate aerosols affect the temperature dependence of AOD. In a warmer future the clear-sky radiative forcing caused by biogenic aerosols will increase, following the increase of BVOC emissions, but if anthropogenic emissions will decrease at the same time the total clear-sky forcing will also decrease.

Jupiter is surrounded by intense and energetic radiation belts, yet most of the available in-situ data, in volume and quality, were taken outside of Europa’s orbit, where radiation conditions are not that extreme. Here we study measurements of ions of tens of keV to tens of MeV at <10 Jupiter radii (RJ) distance to Jupiter, therefore inward of the orbit of Europa. Ion intensities drop around 6RJ, near Io’s orbit. Previous missions reported on radiation belts of tens and hundreds of MeV ions located between 2 and 4 RJ. Measurements of lower energies were not conclusive because high energy particles typically contaminate the measurement of lower energy particles. Here we show for the first time that ions in the hundreds of keV range are present and suggest that ions may extend even into the GeV range. The observation of charged particles yields information on the entire field line, not just the local field. We find that there is a region close to Jupiter where no magnetic trapping is possible. Jupiter’s innermost radiation belt is located at <2RJ, inward of the main ring. Previous work suggested that this belt is sourced by reionized energetic neutral atoms coming steadily inward from distant regions. Here we perform a phase space density analysis that shows consistency with such a local source. However, an alternative explanation is that the radiation belt is populated by occasional strong radial transport and then decays on the timescale of years.