bluuebunny/crossref_metadata_2025 huggingface dataset:
The Decadal Variability of Extreme European Heat
Authors: Suarez-Gutierrez Laura , Müller Wolfgang A. , Marotzke Jochem
Published: March 2022

We evaluate the contribution of the decadal to multidecadal variability in the North Atlantic climate system to impact-relevant extreme heat metrics over Europe, and how this contribution evolves in a warming world. To do this, we use the largest existing ensemble of a comprehensive, fully-coupled climate model: the 100-member Max Planck Institute Grand Ensemble (MPI-GE). MPI-GE has been shown to have one of the most adequate representations of the variability and forced response in observed temperatures in the historical record. Furthermore, the large ensemble size of MPI-GE provides the robust sampling of internal variability that is required to evaluate the contribution of variability on decadal to multidecadal timescales to low-probability, high-impact extreme events.

In our evaluation, we go beyond common metrics defining heatwave intensity or duration, and employ heat excess metrics that account for the cumulative intensity and persistence of heat per Summer beyond given thresholds. We use these cumulative heat metrics to assess excess dry heat as well as other impact-relevant aspects of heatwaves, such as hot and humid conditions and lack of night time cooling. Our preliminary results indicate that the contribution of the decadal variability in the North Atlantic, represented by the Atlantic Multidecadal Variability (AMV), contributes to differences in these metrics between positive versus negative AMV phases that are comparable to the forced changes due to anthropogenic global warming in parts of Europe. This potential for the exacerbation of such extreme conditions under positive AMV phases highlights the necessity for considering these decadal variations both in the attribution of past events as well as in our projections of future extreme heat.
Assessing land use impacts on catchment hydrology with participatory monitoring: lessons for experimental design, network building, and policy support
Authors: Buytaert Wouter , Acosta Luis , Drenkhan Fabian , Perez Katya , Antiporta Javier , Ochoa Tocachi Boris
Published: March 2022

Many regions in the world face declining water availability and increasing water-related risks, as a result of pressures such as environmental degradation, global warming, and population growth. Sustainable and integrated land management is an important tools to improve and safeguard catchment water resources, and to minimize flood and drought risk. However, land management to optimise water security is still severely hindered by a lack of hydrological information about the impact of different management practices on the catchment hydrological response. Statutory hydrological monitoring networks tend to be sparse in most of the world, and focused on operational purposes such as water supply and flood risk. Here we present the case of iMHEA, a participatory hydrological monitoring network in the tropical Andes that aims at characterising the hydrological impact of different land management practices in the upper Andes, especially conservation, livestock grazing, and forestry. The network monitors currently 59 catchments in 22 Andean sites from Venezuela to Chile. It operates as a community of practice, exchanging experimental designs, technical expertise on monitoring equipment, protocols, and experience. It largely follows a pairwise catchment comparison approach, which has been able to show statistically significant trends in land-use impacts on flow characteristics such as runoff ratio, baseflow index, and slope of the flow duration curve. Thanks to rigorous technical support, the generated data are generally of high scientific quality and reliability. The involvement of stakeholders with a policy background, such as NGOs and government agencies, is key to dissemination and operational uptake of the scientific results. As such, iMHEA can be considered a success story, which has created a step change in scientific evidence for land use planning in the Andes. However, several challenges remain. One is the experimental design, which is not yet able to accommodate all the specific interests and challenges that iMHEA members are faced with. Longevity and long-term financial sustainability also remains a major challenge. Lastly, improvements are needed to process and dissimenate the results to specific stakeholders, and especially local communities and governments.
Quantifying the effect of prediction uncertainty from soil spectroscopy on soil management 
Authors: Milne Alice , Breuer Timo , Haefele Stephan , Hannam Jack , Webster Richard , Corstanje Ron
Published: March 2022

Few studies to date have investigated the effect of uncertainty in soil property estimates from spectroscopy on soil management. In this study we considered the implications for variable rate application of phosphorus (P) and potassium (K) fertiliser. First, the uncertainty in soil available P and K estimates from spectroscopy was quantified as a function of the calibration set size at the field-scale.

Based on the observed variation in P and K in four experimental fields, we simulated 100 realisations per field for an in silico experiment. To simulate the process of sampling soil and predicting fertiliser requirement, we performed sampling on our simulated fields using a spatial coverage design. We added a calibration error to each sample value to simulate the error associated with spectroscopic prediction. Kriging was used to estimate the variation in the soil property of interest. We then computed the fertiliser requirement needed to minimise the expected loss associated with predictions. Here, the expected loss is defined as the difference in profit between applying fertiliser based on the estimated soil nutrient concentration accounting for uncertainty relative to the profit that would be gained from fertiliser application given the true soil nutrient concentration in known. We also accounted for data acquisition costs in computing the expected profit.

Results showed that calibration sample size outweighed the effect of total sample size on the uncertainty associated with predictions. Equally, for the same calibration set size, there were large differences in the kriging variance between total sample sizes. When data acquisition costs were disregarded, the expected loss for available P was particularly affected by the total sample size. For available K, the calibration sample size had a predominant effect on the expected loss. The expected loss showed diminishing returns on investment suggesting that there is an optimum sample size. However, the expected profit was dominated by the costs of sampling and spectroscopy, indicating that currently using spectral methods to inform fertiliser management is not cost effective. That is, no combination of the total- and calibration sample sizes considered would result in a financial gain and could thus be considered optimal. Should costs substantially reduce then spectral methods offer a promising method for informing variable rate management. We conclude that the loss function approach is an appropriate method to assess whether soil spectroscopy is a cost-effective means to inform soil management. We further suggest its application in different case-studies to gain more robust insight in the value of applied soil spectroscopy.
Semantic segmentation of historical images in Antarctica with neural networks
Authors: Dahle Felix , Lindenbergh Roderik , Tanke Julian , Wouters Bert
Published: March 2022

The USGS digitized many historical photos of Antarctica which could provide useful insights into this region from before the satellite era. However, these images are merely scanned and do not contain semantic information, which makes it difficult to use or search this archive (for example to filter for cloudless images). Even though there are countless semantic segmentation methods, they are not working properly with these images. The images are only grayscale, have often a poor image quality (low contrast or newton’s rings) and do not have very distinct classes, for example snow/clouds (both white pixels) or rocks/water (both black pixels). Furthermore, especially for this archive, these images are not only top-down but can also be oblique.

We are training a machine-learning based network to apply semantic segmentation on these images even under these challenging conditions. The pixels of each image will be labelled into one of the six different classes: ice, snow, water, rocks, sky and clouds. No training data was available for these images, so that we needed to create it ourselves. The amount of training data is therefore limited due to the extensive amount of time required for labelling. With this training data, a U-Net was trained, which is a fully convolutional network that can work especially with fewer training images and still give precise results.

In its current state, this model is trained with 67 images, split in 80% training and 20% validation images. After around 6000 epochs (approx. 30h of training) the model converges and training is stopped. The model is evaluated on 8 randomly selected images that were not used during training or validation. These images contain all different classes and are challenging to segment due to quality flaws and similar looking classes. The model is able to segment the images with an accuracy of around 75%. Whereas some classes, like snow, sky, rocks and water can be recognized consistently, the classes ice and clouds are often confused with snow. However, the general semantic structure of the images can be recognized.

In order to improve the semantic segmentation, more training imagery is required to increase the variability of each class and prepare the model for more challenging scenes. This new training data will include both labelled images from the TMA archive and from other historical archives in order to increase the variability of classes even more. It should be checked if the quality of the model can be further improved by including metadata of the images as additional data sources.
Meeting the challenging performance requirements of Global Seismic Observatory Networks with the new Trillium 360 GSN
Authors: Bainbridge Geoffrey , Townsend Bruce , Upadhyaya Sarvesh , Hamilton Valarie
Published: March 2022

Nanometrics new Trillium 360 GSN seismometer embodies the culmination of many years of research and technology innovation as well as extensive collaboration with and input from the scientific community interested in very broadband seismometry.  Several generations of seismometers with 240 or 360 second corner frequency have demonstrated successive improvements in self-noise at both very low and high frequencies.  The most recent development has produced the lowest self-noise of any vault seismometer, and is the only seismometer currently being manufactured that meets the performance requirements of a primary seismometer for the Global Seismographic Network and Geoscope. 

Posthole, Borehole and Vault form factors are available and being manufactured and delivered to the GSN.  Performance testing of several units of each model type has been carried out at the facilities of GSN participating member institutions.  The results of the performance testing are reviewed and interpreted, and compared with other co-located instrument types including the venerable STS-1.  Field deployment is now proceeding, to upgrade networks with the Trillium 360 GSN seismometer.  We will show results from new deployments as available at the time of the 2022 SSA conference.  

We will also present the Trillium 360 roadmap, with a smaller low-power version for ocean bottom and portable land deployments in development for 2022, and early test results as available.  The goal of this next phase is to bring very broadband performance to any location and environment at reduced logistical cost.
A hypothesis test on the nature of Holocene climate variability - A case study on replicated marine sediment records
Authors: Dyck Hanna , Dolman Andrew , Kunz Torben , Groeneveld Jeroen , Mohtadi Mahyar , Steinke Stephan , Laepple Thomas
Published: March 2022

 

To describe earth’s former and predict its expected future climate in a general way, we need to understand at least two basic characteristics of the distribution of earth’s temperature, its mean state and its temporal and spatial variance. While there is some confidence in projections of the mean state, earth system models (ESMs) models are suspected to underestimate natural climate variability on longer time scales, as they are developed and evaluated mainly on observational data that only cover a short time period. At low frequencies they show up to two orders of magnitude less temperature variability than data from proxy archives.

However, while climate proxies, such as oxygen isotopes from foraminifera retrieved from marine sediments, provide long records, they are sparse in time and space and contain additional non-climate components such as measurement error. A fundamental criticism of proxy data is that correlation between even nearby records is low and therefore they cannot represent the shared climate signal between the two locations.

So how to decide whether climate models simulate enough variability at long timescales? We here suggest a new evaluation method for existing climate models. The idea is to combine proxy data, proxy understanding and climate models in such a way that we can derive a plausibility check on the ability of the climate models to reproduce natural climate variability.  Considering the high noise levels that we find, what if the proxy records don’t replicate well but still replicate too well enough to have come from a relatively low-variability climate like the climate models?

This is the question we answer in this combined data analysis and simulation study. We do this by developing a hypothesis test where transient ESM simulation TraCE21k forms the null hypothesis on the nature of climate variability. Our proxy data base are multiple and high-resolution Holocene oxygen isotopes and Mg/Ca records from marine sediment cores from the Eastern tropical Indian Ocean - a region with a strong variability mismatch between proxy data and climate model simulations.

The result of the hypothesis test is that, based on the correlation we find in our records, we have to reject the null hypothesis. That means the possibility that the climate signal that was imprinted in our records was generated by a climate system with TraCE21k-like variability characteristics is very unlikely. We therefore reject the hypothesis that TraCE21k reproduces the climate variability characteristics.

We will expand the analysis on different simulations of last generation of ESMs to see if they perform better.

 
The use of the Unidata Science Gateway as a cyberinfrastructure resource to facilitate education and research during COVID-19
Authors: Ramamurthy Mohan , Chastang Julien
Published: March 2022

Unidata has developed and deployed data infrastructure and data-proximate scientific workflows and software tools using cloud computing technologies for accessing, analyzing, and visualizing geoscience data. These resources are provided to educators and researchers through the Unidata Science Gateway (https://science-gateway.unidata.ucar.edu) and deployed on the U. S. National Science Foundation funded Jetstream (https://jetstream-cloud.org) cloud facility. During the SARS-CoV-2/COVID-19 pandemic, the Unidata Science Gateway has been used by many universities to teach data-centric atmospheric science courses and conduct several software training workshops to advance skills in data science.

The COVID-19 pandemic led to the closure of university campuses with little advance notice. Educators at institutions of higher learning had to urgently transition from in-person teaching to online classrooms. While such a sudden change was disruptive for education, it also presented an opportunity to experiment with instructional technologies that have been emerging for the last few years. Web-based computational notebooks, with their mixture of explanatory text, equations, diagrams and interactive code are an effective tool for online learning. Their use is prevalent in many disciplines including the geosciences. Multi-user computational notebook servers (e.g., Jupyter Notebooks) enable specialists to deploy pre-configured scientific computing environments for the benefit of students. The use such tools and environments removes barriers for students who otherwise have to download and install complex software tools that can be time consuming to configure, simplifying workflows and reducing time to analysis and interpretation. It also provides a consistent computing environment for all students and democratizes access to resources. These servers can be provisioned with computational resources not found in a desktop computing setting and leverage cloud computing environments and high speed networks. They can be accessed from any web browser-enabled device like laptops and tablets.

Since spring 2020 when the Covid pandemic led to the closure of universities across the U. S., Unidata has assisted several earth science departments with computational notebook environments for their classes. We worked with educators to tailor these resources for their teaching objectives. We ensured the technology was correctly provisioned with appropriate computational resources and collaborated to have teaching material immediately available for students. There were many successful examples of online learning experiences.

In this paper, we describe the details of the Unidata Science Gateway resources and discuss how those resources enabled Unidata to support universities during the COVID-19 lockdown.
Coastal and offshore controls on the variability of the Undercurrent in the Amundsen Sea
Authors: Dragomir Oana , Silvano Alessandro , Hogg Anna , Meredith Michael , Nurser George , Naveira Garabato Alberto
Published: March 2022

The marine-terminating glaciers of the Amundsen Sea are experiencing increased basal melting associated with an inflow of warm and salty water from the deep ocean onto the shelf via submarine glacial troughs. Modelling work suggests that variability in the transport of this source of heat across the shelf-break and onto the Dotson Trough in the western Amundsen Sea is regulated by wind-driven changes in an eastward undercurrent that flows along the continental slope.

What controls the strength and variability of the undercurrent, however, is not well documented due to a lack of observations in the region. Here, we use a 5-year mooring record of undercurrent velocity in the Dotson Trough in conjunction with a novel 16-year altimetric sea level product that includes measurements in regions of near-perennial ice cover to describe the connection between undercurrent variability and climate modes on seasonal to interannual time scales.

We find a robust signature of the undercurrent variability that is linked to both a circumpolar coastal sea level signal as well as to the sea level in an offshore region in the Amundsen Sea. We discuss the implications of this undercurrent-sea level covariability in the context of atmospheric climate modes and we further explore what this link conveys about the undercurrent variability on interannual timescales by using of our full altimetry record.
Validation of the North American Ice Service iceberg drift model using a novel database of in-situ iceberg drift observations
Authors: Garbo Adam , Copland Luke , Mueller Derek , Tivy Adrienne , Lamontagne Philippe
Published: March 2022

Icebergs calved from high-latitude glaciers and ice shelves pose a threat to vessels and offshore infrastructure at a time when Arctic shipping and offshore resource exploration are increasing. Knowledge of the location of potential ice hazards is therefore critical to ensure safe and efficient operations in this remote region. The Canadian Ice Service provides information to stakeholders on the observed and predicted distribution of icebergs in Canadian waters by combining iceberg observations with forecasts from the North American Ice Service (NAIS) iceberg drift model. The NAIS model estimates the forces acting on an iceberg to predict its future position and velocity and is widely used for the East Coast of Canada. However, the model is unproven for areas >60°N and suffers from insufficient validation due to a lack of reliable in-situ observations of iceberg drift. In this study, we use a newly compiled iceberg tracking beacon database to assess the skill of the NAIS iceberg model's predictions of iceberg drift and investigate sensitivity to morphology and environmental forcing (e.g., ocean currents, winds).

Hindcast simulations of the observed tracks of 44 icebergs over the period 2008-2019 were run using ocean currents from three ocean models (CECOM, GLORYS and RIOPS) and wind and wave inputs from the ERA5 reanalysis. Comparisons of several distance error metrics between observed and modelled drift tracks indicate that the NAIS model produces realistic simulations of iceberg drift in Baffin Bay. The root mean square error after the initial 24-hour hindcast period ranged from 18-22 km and increased at a daily rate of 11-13 km, which is comparable to operational forecasts elsewhere. Improved model performance was observed for longer (>250 m) and deeper-keeled (>100 m) icebergs, which appears to counteract the model’s tendency to overestimate drift by reducing the influence of stronger surface ocean currents acting on the iceberg. Ocean current direction, wind direction, and iceberg keel geometry were identified by a sensitivity analysis as the model parameters and environmental driving forces that have the greatest influence on modelled iceberg drift. These results emphasize the need for accurate environmental information and underscore the importance of properly representing the physical characteristics of icebergs in drift models.
The TSI Instruments – What’s Old, What’s New, and What’s Next
Authors: Kopp Greg
Published: March 2022

What is the Earth’s incoming energy, that is, the value of the total solar irradiance (TSI) powering the entire Earth’s climate system on an absolute scale? How accurate are the instruments providing these data? How stable are they on climate-relevant timescales? How well can the 43-year spaceborne TSI measurement record from over a dozen instruments be put into a single time-series composite for the climate- and solar-research communities? How can that composite be extrapolated to historical times using other solar-activity proxies via reconstructions? How do these historical-reconstruction models differ from each other, and how well do they agree with the current measurements? And what is the future of those measurements?
The effects of meridional temperature contrast on local temperature fluctuations in the mid-latitude atmosphere: a laboratory experiment
Authors: Vincze Miklos , Hancock Cathrine , Speer Kevin
Published: March 2022

In a water-filled rotating annulus setup, a widely studied laboratory toy model of the mid-latitude atmospheric circulation, we investigated the statistical properties of pointwise temperature "station data" from a series of long experiment runs. Our aim was to explore how the thermal boundary conditions affect temperature fluctuations in a quasi-geostrophic flow system dominated by irregular Rossby waves. While the rotation rates and the geometrical dimensions of the experimental configuration were kept identical in all runs (yielding Taylor number Ta ≈ 3.3×1011), the values of the prescribed "meridional" temperature contrast ΔT – measured between the two coaxial lateral sidewalls of the annular tank – were different, thus Rossby numbers ranged from Ro = 0.009 to 0.026. We found that for larger values of ΔT the temperature distribution became wider, and the thermal fluctuations appeared more symmetric under time-reversal. Discrete AR(1) autoregressive processes were fitted to the time series of temperature fluctuations, and the resulting correlation timescales and average forecast errors of the AR(1) models also increased with ΔT. The persistence of the "weather" in the tank was also evaluated in terms of Hurst exponent spectra. Our results imply that in a realistic polar amplification scenario, where the meridional temperature contrast decreases over time, mid-latitude extreme temperatures (due to Rossby wave dynamics) are not expected to occur more frequently. However, the temporal autocorrelation and predictability of daily temperature signals may decrease, and sudden cooling events may become more likely to occur than sharp increases in temperature.
Atmospheric Gravity Wave Observations from a Special Aeolus Campaign over the Southern Andes during Winter 2021
Authors: Banyard Timothy , Wright Corwin , Hindley Neil , Halloran Gemma
Published: March 2022

As the first Doppler wind lidar in space, ESA’s flagship Aeolus satellite provides us with a unique opportunity to study the propagation of gravity waves (GWs) from near the surface to the tropopause and UTLS. Existing space-based measurements of GWs in this altitude range are spatially limited and, where available, use temperature as a proxy for wind perturbations. Recent research confirms Aeolus’ ability to measure GWs, and so this and future spaceborne wind lidars have the potential to transform our understanding of these critically-important dynamical processes.

Here, we present results from a special campaign onboard Aeolus, involving a change to the satellite’s range-bin settings designed to allow better observations of orographic GWs over the Southern Andes during winter 2021. In line with recent research, we expect to see GW wind structures extending down to near the wave sources, enabling detailed measurements of vertical and horizontal wavelength, pseudo-momentum flux and wave intermittency. Such parameters will feed into the next generation of NWP and global circulation models, which will resolve waves at higher resolutions and employ more advanced parametrization schemes.
Characterization of spatial heterogeneity in sedimentary aquifer systems at regional scale by using hydrogeological modeling: A case study of the Middle Magdalena Valley basin - Colombia.
Authors: Lora Boris , Silva Luis , Castro Eduardo , Donado Leonardo
Published: March 2022

The characterization of the inherent heterogeneity of aquifer systems on a regional scale represents one of the main challenges in the study of groundwater, especially when there are uncertainties associated with the scarcity of hydrogeological information (Maliva, 2016).

Based on the implementation of a numerical hydrogeological model in a regional scale, the objective of this study was to characterize the most recent geological formations which have the greatest hydrogeological potential in the Middle Magdalena Valley (VMM) in Colombia. The VMM is bounded by the Eastern Cordillera of the Colombian Andes and the Bucaramanga-Santa Marta fault to the east and the San Lucas Mountain range and the Central Cordillera to the west. This is considered one of the main hydrogeological basins in the country, in which a high potential of hydrocarbon production from the exploitation of unconventional deposits has also been identified (Sarmiento et al., 2015; Londoño, 2019).  For these reasons, the groundwater management, based on the characterization of this hydro system, has a national interest.

In this study the characterization of the heterogeneity was approached from the estimation of hydraulic parameters by solving the inverse problem by means of a hydrogeological model on a regional scale (Carrera et al., 2005; Zhou et al., 2014). For this, 153 pumping tests were carried out and interpreted, allowing to parameterize the model in seven iso-conductivity zones. Also 12,383 discrete static level data were measured and collected in 19 years -time window and they were used in the calibration process. Furthermore, three field campaigns for measuring in-situ parameters (electrical conductivity, pH, dissolved oxygen, and temperature) were performed they served to enhance the conceptual model.

Based on this, variations in hydraulic conductivities were identified on a regional scale for each iso-conductivity zone, fluctuating by four (4) orders of magnitude. The main flow direction was in the south-north, parallel to the Andes cordillera and therefore to the Magdalena River, and with some minor local flows perpendicular to them, producing important outflows from the system in permanent lentic water bodies in the north. The results of the research are encouraging, but at a regional scale they still do not allow to have a high resolution of the heterogeneity of the hydro system models for decision making, so it is suggested to implement stochastic models at a regional scale and to construct multi-purpose groundwater monitoring networks in this basin.

Acknowledgments
The researcher thanks the MEGIA Research Project, Contingent Recovery Contract FP44842-157-2018 funded by Minciencias and the National Hydrocarbons Agency.
Rumble on the River: Analyzing Model Performance in a Year-Long, Live Streamflow Forecasting Competition
Authors: Sampson Alden Keefe , Lambl David , Gulland Lauren , Elkurdy Mostafa , Butcher Phillip , Read Laura
Published: March 2022

Accurate streamflow forecasts equip water managers to adapt to changing flow regimes and constraints, increase water supply reliability, reduce flood risk, and maximize revenue. Over the 2021 water year, the Upstream Tech team took part in a live, 1-10 day ahead streamflow forecasting competition using our flow forecast system, HydroForecast. The competition was a chance to objectively compare operational forecasts using a range of modeling approaches from national agencies, hydropower utilities’ in-house teams, private forecasters and individual modelers at 19 sites in North America. HydroForecast outperformed both statistical and conceptual models and won the competition. We evaluate HydroForecast’s performance relative to other models to identify its strengths and areas for further research by region, season, and forecast horizon. We also share what our theory-guided machine learning approach to hydrologic modeling means in practice for HydroForecast, focusing on the key facets of our approach which contribute most to our accuracy. Finally, we describe the largest opportunities for further forecast accuracy gains we identified in this competition and some of the research efforts we are working on to meet those opportunities.
Multi-Spacecraft Observations of Interplanetary Shocks
Authors: Kruparova Oksana , Krupar Vratislav , Szabo Adam
Published: March 2022

Interplanetary (IP) shocks provide us with a unique opportunity to extensively investigate properties of collisionless shocks using in situ measurements under a wide range of upstream conditions. Here we report a case study of several IP shock crossings observed by the Wind, Solar and Heliospheric Observatory (SOHO), Advanced Composition Explorer (ACE), and Deep Space Climate Observatory (DSCOVR) spacecraft. By applying a simple timing method to multipoint measurements, we are able to investigate their characteristic spatiotemporal features. We assume that an IP shock can be represented by a moving plane with a constant velocity, when observed at closely separated points in space and time. We compared IP shock parameters obtained with the timing method with those obtained using the magnetic coplanarity, the mixed mode methods, and Rankine-Hugoniot jump relations.

 
Detecting the edges of Earth's ion foreshock using Magnetic Gauss's Law
Authors: Dorfman Seth , Zhang Kun , Turc Lucile , Ganse Urs
Published: March 2022

Various types of plasma waves play key roles in magnetospheric physics in contexts ranging from the magnetosphere and its boundary layers to planetary bow shocks and foreshocks.  Due to limited available spacecraft measurements, the waves are often assumed to be plane waves that extend to infinity in all directions. A good example is the Earth's ion foreshock where intrinsically right-hand circularly polarized magnetosonic modes are generated by a fast ion beam. Many prior studies of these waves assume no variation of important physical quantities in the direction perpendicular to wave propagation. We show that Magnetic Gauss's Law implies that this assumption must be violated near the edge of the wave domain. The resulting false signature in the standard Magnetic Gauss's Law calculation of the wave vector orientation may be used to detect the domain edge. We demonstrate this new edge detection method in a simple wave model, a 2-D hybrid Vlasov simulation conducted using the Vlasiator code, and ARTEMIS spacecraft observations. In both the simulation and the spacecraft observations, this new signature is shown to correlate well with a determination of the foreshock edge based on the properties of the fast ion beam.  As the plane wave assumption is widely used in space physics data analysis techniques such as minimum variance analysis, these results may stimulate a reexamination of this assumption in other magnetospheric physics contexts.

This study is supported by NASA Grant 80NSSC20K0801.  Vlasiator is developed by the European Research Council Starting grant 200141-QuESpace, and Consolidator grant GA682068-PRESTISSIMO received by the Vlasiator PI. Vlasiator has also received funding from the Academy of Finland. See www.helsinki.fi/vlasiator
Understanding climate, precipitation and δ18O linkages over Eastern Asia
Authors: Sinha Nitesh , Timmermann Axel , Wessenburg Jasper A. , Lee Sun-Seon
Published: March 2022

The interpretation of East Asian monsoon speleothem δ18O records is heavily debated in the paleoclimate community. Besides developing new speleothem proxies, the use of isotope-enabled climate simulations is one of the key tools to enhance our understanding of speleothem δ18O records. Here we present results from novel climate simulations performed with the fully coupled isotope-enabled Community Earth System Model (iCESM1.2), which simulates global variations in water isotopes in the atmosphere, land, ocean, and sea ice. The model closely captures the major observed features of the isotopic compositions in precipitation over East Asia for the present-day conditions. To better understand the physical mechanisms causing interannual to orbital timescale variations in δ18O in East Asian speleothems, we ran a series of experiments with iCESM. We perturbed solar, orbital, bathymetry, ice-sheet, and greenhouse gas radiative forcings. The simulations supporting of observations/reconstructed records (GNIP/SISAL) from East Asia, help understand the controls on the isotope composition of East Asian monsoon rainfall and how speleothem δ18O records may be interpreted in terms of climate. The study provides new insights into the mechanisms of East Asian monsoon changes on different timescales.
Investigating the seasonal triggering of earthquakes in the Azores
Authors: Neves Maria C. , Dias Ana Laura , Custódio Susana
Published: March 2022

The relationship between seismicity rates and water load variations has been recognized across the world at various spatial and temporal scales. In the oceans, one of the most notable such observations is that earthquakes at mid-ocean ridges tend to occur preferentially during low tide. In the region of the Azores triple junction, the analysis of a seismic catalogue from 2008 to 2018 revealed that earthquakes in the ocean present a genuine and statistically significant semi-annual seasonality, with more earthquakes occurring in the summer than in the winter. We have looked for mechanisms that could justify this observation. First, we assembled several geophysical time-series of regionally averaged variables that could constitute likely earth loading mechanisms, such as ocean bottom pressure anomalies, and performed a singular spectral analysis to identify and characterize their main modes of variability. Then, we computed the correlation between the possible loading mechanisms and the principal components of the seismicity rate. We found that the variable that best correlates with the seismicity rate (correlation coefficient of 0.9) is the sea level anomaly, which at the Azores latitude presents a marked seasonality related to the barotropic response to changes in wind stress. We therefore suggest that the seismicity peaks during low tide at mid-ocean ridges and the enhanced seismicity in the summer months in the Azores region share an analogous stress triggering mechanism. This work presents the results of Coulomb stress models that help to verify this hypothesis and better understand the relationship between the Earth's deformation and the annual ocean water load variations. The authors would like to acknowledge the financial support of FCT through project UIDB/50019/2020–IDL. This is a contribution to the RESTLESS project PTDC/CTA-GEF/6674/2020.
The effect of climate change on internal wave activity in the Andaman Sea 
Authors: Yadidya Badarvada , Devendra Rao Ambarukhana
Published: March 2022

The Andaman Sea, located in the Indian Ocean's northeastern region, is well known for its large-amplitude internal waves. The Indian Ocean Dipole, according to recent research, has a significant impact on the interannual variability of density stratification and internal wave activity in this region. The global climate model IPSL-CM6A-LR has demonstrated a reasonable ability to capture the variability of the Indian Ocean Dipole in its historical simulations. As a result, the long-term variability of internal waves is investigated using the IPSL-CM6A-LR density stratification. The stratification showed an increasing trend in the upper 100 m since 1900 due to radiative forcing. Internal wave activity is expected to increase in the twenty-first century, altering the effects of climate change on coastal ecosystems. Additionally, model simulations utilizing the three-dimensional Massachusetts Institute of Technology general circulation model are conducted to investigate the impact of increasing stratification on internal tides. Variations in the generation, propagation, and dissipation of internal tides along with their basic characteristics are quantified.  
Diurnal and seasonal variation in ET at canopy scales using a novel UAV-based approach
Authors: Morgan Bryn , Caylor Kelly
Published: March 2022

Unmanned aerial vehicles (UAVs) constitute a new frontier in remote sensing of ET that bridges the gap between in situmeasurements and remotely sensed observations of plant water use. While a single satellite pixel often comprises a mixture of plant types and bare soil, UAV imagery can resolve fine- (m- to cm-) scale differences in surface temperature without thermal unmixing. Furthermore, they can be used to observe diurnal patterns of plant water use and photosynthesis, providing critical insights into the timing and severity of plant water stress. We highlight a novel approach for estimating ET at leaf- to canopy-scales using thermal infrared (TIR) imagery, structural data, and a suite of environmental sensors mounted on a UAV platform. ET is calculated solely from these UAV-acquired data using a combined atmospheric profile and surface energy balance algorithm. Centimeter-scale leaf position and orientation information derived from Structure-from-Motion (SfM) are integrated with the functional data to constrain available energy, allowing for multi-scale estimation of plant water use within and across canopies.

We present UAV-derived ET across diurnal and seasonal time scales for two landscapes, a native California grassland and a riparian oak woodland. Grassland flights were conducted at 90-minute intervals spanning early morning to late afternoon during the 2021 and 2022 growing seasons. Results show good agreement (<20%) with measured ET fluxes from a collocated eddy covariance tower throughout the growing season. Riparian oak canopies were observed monthly and diurnally over the summer of 2021. Ground measurements of surface temperature, stomatal conductance, and soil moisture were collected during each flight. Water-stressed tress at the driest site showed peak ET at midday, decreasing into afternoon, reflecting down-regulation of photosynthesis to preserve hydraulic function. Relative canopy water use and stress across a range of tree sizes will also be discussed using measurements of stem and canopy area and ET for individual tree crowns extracted from the UAV imagery. By collecting comprehensive meteorological data from sensors on the UAV itself, our approach eliminates the need for extensive field data collection and enables characterization of highly spatially and temporally resolved fluxes within and across complex landscapes. This work opens up new avenues to investigate how ecologically important species—and even individual trees—respond to drought and the impacts of these responses on water use, water stress, and the ecological health of critical habitats like riparian forests.
Accounting for carbon allocation shifts after drought improves NBE predictions
Authors: Worden Matthew , Famiglietti Caroline , Konings Alexandra , Levine Paul , Bloom Anthony
Published: March 2022

Drought affects carbon fluxes by influencing photosynthesis, respiration, and disturbance, as well as by impacting the size of the different vegetation and soil pools. Changes to how much photosynthetic carbon is allocated to foliage, woody components, roots, and more persist even after meteorological conditions have returned to normal. These shifts in carbon allocations in turn affect future photosynthesis through changes in leaf area and water uptake ability, for instance. However, the magnitude of post-drought recovery effects on terrestrial carbon fluxes are often overlooked and poorly modeled. This is especially the case in tropical ecosystems as there are large uncertainties in the tropical ecosystem sensitivity to climate forcing such as drought. We hypothesize that a key driver of carbon flux predictive error in land surface model simulations is their representation of changes in carbon allocation during and after water stress. Most models use static carbon allocation schemes which, given their assumption of uniformity through time, do not account for the impact of drought. Those that do have dynamic allocation are often poorly parameterized due to the difficulty of in situ carbon allocation measurements. We investigate first whether it is possible to constrain dynamic carbon allocation based on observations of fluxes and model data fusion. We then investigate whether the constrained dynamic carbon allocation model has improved predictions of modeled net biosphere exchange (NBE) during drought and drought recovery. To do so, we implement a dynamic carbon allocation scheme within the CArbon DAta MOdel fraMework (CARDAMOM) data assimilation system, which robustly optimizes the parameters and carbon cycle states of an intermediate-complexity ecosystem model based on a suite of observational data on carbon fluxes and pools. We test the dynamic allocation scheme at a wet tropical (French Guiana) and a dry tropical (Cumberlands Plain) flux tower site. We find at the Cumberland Plains flux tower that the dynamic allocation model outperforms the static allocation model in predicting NBE. Furthermore, we retrieve significant carbon allocation shifts during drought periods at this site with increasing allocation to autotrophic respiration, wood biomass, and labile biomass and decreasing allocation to foliage biomass and fine root biomass relative to non-drought conditions. Our results demonstrate the importance of accounting for stress-induced carbon allocation shifts in land surface models as well as the ability to infer carbon allocation shifts from flux measurements.
Limb darkening values of Jupiter’s atmosphere at 600 MHz measured by Juno Microwave Radiometer
Authors: Li Cheng , Bhattacharya Ananyo , Atreya Sushil , Levin Steven , Bolton Scott , Guillot Tristan , Gupta Pranika , Ingersoll Andrew , Lunine Jonathan , Orton Glenn , Steffes Paul , Waite Hunter , Wong Michael
Published: March 2022

Sensing potential microwave opacity sources well below the water cloud potentially allows us to probe whether rock-forming species are present in Jupiter—here, specifically, the alkali metals.  The measurement of limb darkening (relative change of the brightness temperature from nadir viewing to limb viewing at the 45-degree emission angle) by the Juno Microwave Radiometer (MWR) is very precise ( 0.1%) due to the stability of the instrument. We analyzed the MWR data from perijove 1 to perijove 12 and found that the 600 MHz channel of the MWR observed a consistent limb darkening value of around 14% from 40oS to 40oN for Jupiter’s atmosphere while thermodynamic models predict that the limb darkening should be about 18%. The 4% difference is well above the uncertainty of the measurement. We construct end-member models to investigate the possible cause. We have examined the effect of 1) ammonia depletion, 2) the existence of a deep radiative layer between 1000 ~ 2000 K, 3) concentration of alkali metals, 4) opacity models of water vapor continuum and 5) opacity models of ammonia and concluded that the most likely cause is the presence of alkali metals, which thermally dissociate at temperatures > 1000 K. Other factors may also contribute to the anomalous limb darkening. To fully resolve the degeneracy, laboratory measurements of the opacities of ammonia and water at high temperatures are recommended.
Clustering fine-scale river network topologies for use in Earth system models
Authors: Torres-Rojas Laura , Vergopolan Noemi , Guyumus Daniel , Chaney Nathaniel W.
Published: March 2022

Representing the physical heterogeneity of the land surface in Earth System Models (ESM) remains a persistent challenge due to its relevance to represent weather and climate dynamics and the hydrological cycle accurately. To address this challenge, the HydroBlocks Land Surface Model (LSM) [1] uses a hierarchical tiling scheme that defines its Hydrologic Response Units (HRUs) by clustering high-resolution global environmental data (e.g., 30-m land cover, topography, soil properties). The recently implemented reach-based routing scheme in HydroBlocks enables a two-way coupling between the high-resolution river network and the land HRUs. However, preliminary results show that the implementation is only computationally manageable for a limited number of river reaches (~5,000) per macroscale grid cell (1x1 arc degree). This hinders the scheme generalization and scalability over continental scales. As such, further simplification of the river network structure in routing schemes is required to ensure the feasibility of the approach in ESMs.

This presentation will explore simplification alternatives for river network topologies using clustering analysis. Initially, given that a significant fraction of the total river reaches on any domain are first-order, we propose an approach that clusters these streams based on average basins’ physical and environmental features (e.g., slope, upslope contributing area, aspect, average precipitation, and land cover), and channels’ geometry. The river network topology is simplified by depicting all the clusters’ members as single equivalent channels. The clustering is performed using K-means, and the number of clusters depends on a maximum target number of reaches required to provide computational tractability. Although useful, this approach will not be enough to sufficiently reduce the computational burden, for which solving the second- and even third-order reaches remain a substantial load. Therefore, the second approach relies on clustering the river channel structure over sets of interconnected reaches (i.e., topologies including first-, second-, and third-order streams). The performance of the proposed approach will be compared to the original HydroBlocks implementation for the temporal evolution of the streamflow, inundation height and the resulting computation times.

 

[1]      N. W. Chaney, L. Torres-Rojas, N. Vergopolan, and C. K. Fisher, “HydroBlocks v0.2: enabling a field-scale two-way coupling between the land surface and river networks in Earth system models,” Geosci. Model Dev., vol. 14, no. 11, pp. 6813–6832, Nov. 2021, doi: 10.5194/gmd-14-6813-2021.