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OtherAdams JR, Mason PJ, Roberts SJ, et al., 2024,
Application of very high-resolution satellite imagery to identify silica-rich rock for future cosmogenic exposure dating in remote unvisited areas of Antarctica.
<jats:p>Rock outcrops protruding above the ice surface in Antarctica (nunataks) can provide direct geologic evidence for past ice sheet fluctuations through the measurement of concentrations of cosmogenic nuclides that accumulate in their surfaces once the rock is exposed. Felsic lithologies, which are typically pale in colour and dominated by quartz, feldspars, and micas, are suitable for exposure age dating since quartz is the often-preferred target mineral for extraction of the rare cosmogenic isotopes which make deglacial reconstructions possible. The geology of rock outcrops in Antarctica are, however, often sparsely mapped and many exposures are challenging to access due to both their remoteness and the extreme conditions typically encountered on the continent. Satellite based spectral mapping offers an effective way to characterise the geology of large areas of exposed rock rapidly and safely in regions where it is logistically very challenging and expensive to conduct fieldwork. Remote sensing therefore offers a valuable method for preliminary characterisation of an area&#8217;s suitability for eventual targeted retrieval of cosmogenic nuclide samples.&#160;Previous studies found that the Thermal Infra-Red (TIR) sensor onboard the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is very effective at discriminating rock types by their silica content, but spectral mapping of smaller felsic rock outcrops in Antarctica has been constrained by its low spatial resolution (90 m). Here we assess the potential of multispectral remote sensing using both ASTER and very high-resolution Worldview-3 (WV-3) imagery to distinguish felsic from mafic rock outcrops at visible-near infrared (VNIR) and shortwave infrared (SWIR) wavelengths. At Mount Murphy, a remote site in West Antarctica more than 1,600 kilometres from both the US Antarctic Program&#8217;s McMurdo Station and the British Antarctic Survey&#8217;s Rothe
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OtherWaters C, Eastwood J, Fargette N, et al., 2024,
A machine learning approach to structure and energy in magnetic reconnection
<jats:p>Magnetic reconnection is a fundamentally important process in space plasmas due to the release and repartition of the magnetic energy stored within the reconnecting field. As this energy transfer significantly impacts magnetospheric dynamics, understanding the partition of this energy and how this varies across the reconnection site can provide further insight into other magnetospheric processes. Although in situ spacecraft data provide direct measurements of relevant plasma properties, it can be difficult to establish the location of spacecraft relative to the reconnection site. This frustrates efforts to evaluate the way in which energy fluxes change with distance from the central reconnection X-line. Under certain circumstances, reconstruction techniques can be used to estimate the spacecraft trajectory through individual events, but these may rely on simplifying assumptions limiting their use.This motivates new approaches to determining where a spacecraft is relative to the reconnection structure. By utilising forefront machine learning techniques, we can more accurately study individual regions associated with the reconnection process and thus understand how they individually contribute to repartitioning the overall energy budget. In this context, we present these new applications of machine learning techniques to identify the regions in both simulation and spacecraft data.Firstly, we present the results of a robust method which utilises k-means clustering to identify different regions encountered within the overall reconnection X-line structure. This uses plasma fluid and field variables output by a 2.5-D PIC simulation with a geometry comparable to that of reconnection in Earth&#8217;s magnetotail. We then translate this model for use in spacecraft data by implementing an approach based on a recurrent neural network to account for the temporal context of the observations. We demonstrate the use of this model on MMS observations of reconn
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OtherWilson Kemsley S, Nowack P, Ceppi P, 2024,
A systematic evaluation of high-cloud controlling factors
<jats:p>Clouds strongly modulate the top-of-the-atmosphere (TOA) energy budget. While most evidence indicates that changes in cloud-induced radiative anomalies at the TOA likely amplifies warming, the magnitude of this global cloud feedback remains highly uncertain. &#8220;Cloud Controlling Factor&#8221; (CCF) analysis is an approach that can be used to tackle this uncertainty, deriving relationships between large-scale meteorological drivers and cloud-radiative anomalies which can subsequently be used to constrain cloud feedback. However, the choice of meteorological controlling factors is crucial for a meaningful constraint, and while there is rich literature investigating ideal CCF setups for low-level clouds, there is a distinct lack of analogous research that explicitly targets high clouds.Here, we use ridge regression to systematically evaluate CCFs that specifically target high cloud formation and cessation using historical data. We evaluate the addition of five candidate CCFs to previously established core CCFs within large spatial domains to predict longwave high-cloud radiative anomalies: upper-tropospheric static stability (SUT), sub-cloud moist static energy, convective available potential energy, convective inhibition, and upper-tropospheric wind shear. We identify an optimal configuration including SUT, and show that the spatial distribution of the&#160; SUT &#160;ridge regression coefficients are congruent with the physical drivers of known high-cloud feedbacks. We further deduce that inclusion of SUT into observational constraint frameworks may reduce uncertainty associated with changes in anvil cloud amount as a function of climate change. These results highlight upper-tropospheric static stability as an important CCF for high clouds and longwave cloud feedback, which we begin to explore using modelled data under an abrupt quadrupling of CO2&#160;(abrupt-4xCO2).</jats:p>
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OtherKuhlbrodt T, Swaminathan R, Ceppi P, et al., 2024,
A glimpse into the future: The 2023 temperature extremes in the North Atlantic in the context of longer-term climate change
<jats:p>In the year 2023, we have seen extraordinary extrema in high sea-surface temperature (SST) in the North Atlantic which are outside the 4-sigma envelope of the 1982-2011 daily timeseries. Here we take a first look at the large-scale, longer-term drivers of these extrema. Earth&#8217;s net global energy imbalance (in the 12 months up to September 2023) amounts to +1.9 W/m2 as part of a remarkably large upward trend, ensuring continuous heating of the ocean. However, the regional radiation budget over the North Atlantic does not show signs of a significant step increase from less negative aerosol forcing since 2020 as was suggested elsewhere. While the temperature in the top 100 m of the global ocean has been rising in all basins since about 1980, specifically the Atlantic basin has continued to further heat up since 2016. Similarly, salinity in the top 100 m of the ocean has increased in recent years specifically in the Atlantic basin. Outside the North Atlantic, around 2015 a substantial negative trend for sea-ice extent in the Southern Ocean has begun, leading to record low sea-ice extent in 2023. We suggest analysing the 2023 temperature extremes in the North Atlantic in the context of these recent global-scale ocean changes. Analysing climate and Earth System model simulations of the future, we find that the extreme SST in the North Atlantic and the extreme in Southern Ocean sea-ice extent in 2023 lie at the fringe of the expected mean climate change for a global surface-air temperature warming level (GWL) of 1.5&#176;C, and closer to the average at a 3.0&#176;C GWL. Understanding the regional and global drivers of these extremes is indispensable for assessing frequency and impacts of similar events in the coming years.</jats:p>
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OtherWagener T, Coxon G, Bloomfield JP, et al., 2024,
The value of hydrologic observatories for large sample hydrology and vice versa
<jats:p>Hydrologic observatories have been a cornerstone of hydrologic science for many decades, advancing hydrologic process understanding with focused field observations and targeted experiments. Observatories present our key opportunity for achieving great depth of hydrologic investigation, most often at the headwater catchment scale. We address two main aspects concerning hydrologic observatories in this contribution: (1) While reviews of individual hydrologic observatories and observatory networks exist, no study has investigated the diversity of observatories to understand whether common aspects increase the likelihood of scientific success. We synthesise information from 80 hydrologic observatories and conduct 25 interviews with observatory leads to fill this gap. We find that scientific outcomes are most enhanced by involving scientific and stakeholder communities throughout observatory inception, design, and operation; by enabling infrastructure to be adjustable to changing ideas and conditions; and by facilitating widespread data use for analysis. (2) While observatories are key for advancing local hypotheses, the transferability of knowledge gained locally to other places or scales has often been difficult or even remained elusive. Headwater catchments in particular show a wide range of process controls often only understood if viewed in a wider regional context of climatic, topographic, or other gradients. We therefore must place observatories into the wider tapestry of hydrologic variability, for example through comparison with large samples of catchments, even though significantly less information is available to characterise these diverse systems. We provide some thoughts on how this connection could be improved through digital infrastructure, mobile observational infrastructure and a renewed focus on gradients and contrasts of controlling processes. We believe that there is a significant opportunity to enhance transferrable knowledge creation i
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OtherVanacker V, Molina A, Rosas M, et al., 2024,
Nature-based solutions for erosion mitigation : insights from a systematic review for the Andean region
<jats:p>The Andes Mountains stretch over about 8900 km and cross tropical, subtropical, temperate and arid latitudes. More than 85 million people lived in the Andean region by 2020, with the northern Andes being one of the most densely populated mountain regions in the world. The demographic growth and a stagnating agricultural productivity per hectare led to an expansion of the total agricultural land area, either upward to steep hillsides at high elevations covered by native grassland-wetlands ecosystems, or downward to lands east and west of the Andes covered by tropical and subtropical forests. Land use and management have significantly altered the magnitude and frequency of erosion events.&#160;This study systematically reviews the state of evidence on the effectiveness of interventions to mitigate soil erosion by water and is based on Andean case studies published in gray and peer-reviewed literature. After screening 1798 records, 118 empirical studies were eligible and included in the quantitative analysis on soil quality and soil erosion. Six indicators were pertinent to study the effectiveness of natural infrastructure: soil organic carbon and bulk density of the topsoil, soil loss rate and run-off coefficient at the plot scale, and specific sediment yield and catchment-wide run-off coefficient at the catchment scale. The protection and conservation of natural vegetation has the strongest effect on soil quality, with 3.01 &#177; 0.893 times higher soil organic carbon content in the topsoil compared to control sites. Soil quality improvements are significant but lower for forestation and soil and water conserva- tion measures. Soil and water conservation measures reduce soil erosion to 62.1 % &#177; 9.2 %, even though erosion mitigation is highest when natural vegetation is maintained.Further research is needed to evaluate whether the reported effectiveness holds during extreme events related to, for example, El Nin&#771
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OtherSalvi P, Gregory J, Ceppi P, 2024,
Assessing the Impact of Surface Energy Inputs on Radiative Feedbacks in Tropical and Extra-tropical Regions: Strength, Evolution, and Timescales
<jats:p>In recent years, radiative feedbacks in the earth system have been strongly tied to the spatial pattern of sea surface temperatures (SSTs). This &#8220;pattern effect&#8221; has been strongly tied to the strength of cloud radiative feedbacks driven by atmospheric stability changes. SST patch Green&#8217;s functions experiments have revealed that the ratio of warming in deep convective tropical regions, versus outside, drives significant changes in atmospheric stability. These Green&#8217;s functions can be used to reconstruct feedbacks from given warming patterns. However, it remains unclear how different warming patterns arise. Different Green&#8217;s functions, prescribing surface heat fluxes in atmosphere-ocean coupled models instead of temperature changes in fixed SST experiments, may answer this question by showing how energy inputs translate into temperature changes.Using a simplistic set of patches of applied surface heat fluxes in CESM2-CAM6 and HadCM3, we find that heat input into the tropics results in strongly negative radiative feedbacks from enhanced warm pool warming. This results in a small climate sensitivity to this tropical forcing. Conversely, heat fluxes input into the extratropics cause significantly less negative feedbacks that result in greater climate sensitivity to extratropical forcing.Furthermore, the response to tropical forcing occurs rapidly, with equilibrium roughly achieved within a few years both in slab ocean and fully coupled models. The response to extratropical forcing, by contrast, induces near-zero feedbacks in the first few years, followed by significantly weaker negative feedbacks than seen under tropical forcing, which leave this simulation far from equilibrium after 150 years in the fully coupled model.These outcomes of forcing, from within the tropics and outside, can be combined to explain the early changes in feedbacks in response to global uniform forcing, or near-un
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Journal articleRizos G, Lawson J, Mitchell S, et al., 2024,
Propagating variational model uncertainty for bioacoustic call label smoothing
, Patterns, Vol: 5, ISSN: 2666-3899Along with propagating the input toward making a prediction, Bayesian neural networks also propagate uncertainty. This has the potential to guide the training process by rejecting predictions of low confidence, and recent variational Bayesian methods can do so without Monte Carlo sampling of weights. Here, we apply sample-free methods for wildlife call detection on recordings made via passive acoustic monitoring equipment in the animals' natural habitats. We further propose uncertainty-aware label smoothing, where the smoothing probability is dependent on sample-free predictive uncertainty, in order to downweigh data samples that should contribute less to the loss value. We introduce a bioacoustic dataset recorded in Malaysian Borneo, containing overlapping calls from 30 species. On that dataset, our proposed method achieves an absolute percentage improvement of around 1.5 points on area under the receiver operating characteristic (AU-ROC), 13 points in F1, and 19.5 points in expected calibration error (ECE) compared to the point-estimate network baseline averaged across all target classes.
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Journal articleDo Prado AH, Mair D, Garefalakis P, et al., 2024,
Check dam impact on sediment loads: example of the Guerbe River in the Swiss Alps - a catchment scale experiment
, Hydrology and Earth System Sciences, Vol: 28, Pages: 1173-1190, ISSN: 1027-5606The construction of check dams is a common practice around the world where the aim is to reduce the damage by flooding events through mountain streams. However, quantifying the effectiveness of such engineering structures has remained very challenging and requires well-selected case studies, since the outcome of such an evaluation depends on site-specific geometric, geologic and climatic conditions. Conventionally, the check dams' effectiveness has been estimated using information about how the bedload sediment flux in the stream changes after the check dams are constructed. A permanent lowering of the bedload flux not only points to a success in reducing the probability of sediment transport occurrence but also implies that the sediment input through the system is likely to decrease. Here, we applied a method for data acquisition and two different equations (Meyer-Peter-Müller and Recking approach) to estimate and compare the sediment transport in a mountain stream in Switzerland under engineered and non-engineered conditions. Whereas the first equation is derived from a classical approach that is based on flume experiment data with a slope of less than 0.02mm-1, the second equation (Recking) has been derived based on a bedload field dataset comprising active mountain streams under steeper conditions. We selected the Guerbe (Gürbe) River situated in the Swiss Alps as a case study, which has been engineered since the end of the 19th century. This has resulted in more than 110 check dams along a ca. 5ĝ€¯km reach where sediment has continuously been supplied from adjacent hillslopes, primarily by landsliding. We measured the riverbed grain size, topographic gradients and river widths within selected segments along this reach. Additionally, a gauging station downstream of the reach engineered with check dams yielded information to calibrate the hydroclimatic situation for the study reach, thus offering ideal conditions for our catchment-scale experi
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Journal articleRasheed S, Warder SC, Plancherel Y, et al., 2024,
Nearshore tsunami amplitudes across the Maldives archipelago due to worst-case seismic scenarios in the Indian Ocean
, Natural Hazards and Earth System Sciences, Vol: 24, Pages: 737-755, ISSN: 1561-8633The Maldives face the threat of tsunamis from a multitude of sources. However, the limited availability of critical data, such as bathymetry (a recurrent problem for many island nations), has meant that the impact of these threats has not been studied at an island scale. Conducting studies of tsunami propagation at the island scale but across multiple atolls is also a challenging task due to the large domain and high resolution required for modelling. Here we use a high-resolution bathymetry dataset of the Maldives archipelago, as well as corresponding high numerical model resolution, to carry out a scenario-based tsunami hazard assessment for the entire Maldives archipelago to investigate the potential impact of plausible far-field tsunamis across the Indian Ocean at the nearshore island scales across the atolls. The results indicate that the bathymetry of the atolls, which are characterized by very steep boundaries offshore, is extremely efficient in absorbing and redirecting incoming tsunami waves. Results also highlight the importance that local effects have in modulating tsunami amplitude nearshore, including the location of the atoll in question, the location of a given island within the atoll, and the distance of that island to the reef, as well as a variety of other factors. We also find that the refraction and diffraction of tsunami waves within individual atolls contribute to the maximum tsunami amplitude patterns observed across the islands in the atolls. The findings from this study contribute to a better understanding of tsunamis across complex atoll systems and will help decision and policy makers in the Maldives assess the potential impact of tsunamis across individual islands. An online tool is provided which presents users with a simple interface, allowing the wider community to browse the simulation results presented here and assess the potential impact of tsunamis at the local scale.
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