We argue that the core technological concept remains largely unchanged from earlier proposals and therefore inherits many of the same challenges – notably high costs and engineering complexity. We examine the potential role of radioisotope production as an additional revenue stream beyond electricity generation and waste incineration in more detail. We find that the projected contribution of radioisotope production to the overall economics of ADS facilities is highly sensitive to assumptions about market size, price stability, and deployment scale.
]]>This article was initiated to mark Nakaya’s 125th anniversary year and aims to introduce his life and achievements to a broad international audience. We review Nakaya’s biography and highlights of his scientific career, and include some brief discussion of the Japanese cultural context for his scientific work. We recount some particularly dramatic aspects of Nakaya’s life which was shadowed by the great historical developments of his era, notably the Second World War. We also review his contributions to Japanese literature of his time. We sample a handful of Nakaya’s articles written for the general public in order to convey the scope and flavour of his literary oeuvre. We describe in detail two of Nakaya’s most ambitious magazine essays: “World of the Black Moon” and “World of the White Moon”, which are of particular interest as vivid first person accounts of middle 20th century research field trips (to Hawaii and Greenland, respectively). “World of the White Moon” is also notable for including a very early description for the general public of the issue of anthropogenic climate change.]]>
Sensitivity of dynamical variables and hazards to model configuration depends strongly on cyclone type, with medicanes exhibiting substantially greater and more robust dependence than more extratropical systems. The 2.2 km CoMorph configuration consistently over-intensifies medicanes, producing much lower minimum mean-sea-level pressures, and stronger winds and gusts than other simulations, especially for medicanes Ianos and Apollo. In contrast, the 12-km GAL9 configuration generally produces the weakest medicanes and tracks that is displaced eastward or southward; these biases are reduced using the 12-km CoMorph configuration. An in-depth analysis of medicane Ianos, which deepens by at least 20 hPa more in the 2.2-km CoMorph simulation than in the other simulations is presented. This CoMorph simulation yields a Ianos with a stronger potential vorticity tower, ascent and latent heat fluxes, and an eyewall structure resembling a tropical cyclone. These results demonstrate that the forecast skill of hazardous Mediterranean cyclones depends critically on the interaction between model resolution and physical parameterisations, implying that improvements in kilometre-scale forecasting require advances in model physics as well as increased resolution.]]>
We performed α-pinene photooxidation experiments systematically exploring these parameters and present the impacts on HOM and SOA formation within a generic framework explaining the changes in HOM production. Steady-state experiments were performed in the SAPHIR-STAR atmospheric simulation chamber. The reaction regime was shifted by increasing HO₂· and NO, separately and simultaneously, while keeping the α-pinene primary oxidation conditions constant. (NH₄)₂SO₄ particles were added to observe gas-phase HOM condensation and investigate product volatilities.
We find decreasing SOA formation potential when moving away from RO₂·-dominated regimes. One reason is the suppression of HOM accretion product formation from HOM-RO₂·+RO₂·. Alkoxy radicals (RO·) from RO₂·+RO₂· or RO₂·+NO play another important role. RO· are crucial intermediates in certain HOM formation pathways but also produce lower-mass, more fragmented HOM with higher volatility, decreasing SOA formation potential. Additionally, RO₂·+NO forms organic nitrates, which we show have higher volatility than other termination products. Our mechanistic considerations illustrate which factors impact the HOM product distribution and explain the reduced SOA formation through changes in HOM composition and volatility.]]>
This study investigates how residence time inside ARLs affects radiosonde humidity sensor performance and the adequacy of SHC tests for automated GRUAN operations. A coordinated experiment was conducted at six sites using three radiosonde models (Vaisala RS41, Meisei IMS-100, and MeteoModem M10) and three ARL systems (Vaisala AS15, Meisei ARS, and MeteoModem Robotsonde). Radiosondes were tested in an SHC prior to storage and again after residence times of 7 and 14 days. Relative humidity biases at saturation (RH = 100 %) were analyzed using aggregated statistics, including a paired RH bias difference—i.e., the change in bias between pre-storage and post-storage measurements, to quantify temporal drift. A non-parametric bootstrap resampling analysis was first applied to assess the robustness and confidence intervals of the paired RH bias difference estimates. Statistical significance of the paired RH bias difference distributions was subsequently evaluated using the Wilcoxon signed-rank test. A normalized storage-effect metric, combining the systematic drift and variability of the paired RH bias differences, was compared with the GRUAN humidity uncertainty contribution associated with ground preparation.
Results indicate that radiosonde humidity performance remains stable for residence times up to 14 days under the tested storage conditions, particularly for the RS41–AS15 configuration, where only small negative drifts were observed (approximately ~ −0.1 % RH week-1). In contrast, the IMS-100–ARS configuration exhibited a pronounced increase in drift with storage time (approximately ~ −0.8 % RH week-1), which was amplified under high-humidity and temperature seasonal conditions, while the M10–Robotsonde configuration showed a reversed drift with partial bias reduction during storage (~ +0.12 % RH week-1). These findings demonstrate that radiosonde behavior during storage strongly depends on the combined radiosonde–ARL system.
Based on the experimental and statistical evidence, an operational upper limit of 14 days for radiosonde storage inside ARLs is recommended for GRUAN-compliant operations, with residence times up to 7 days providing optimal reliability. The study confirms the feasibility of implementing SHC tests for ARL operations while highlighting the need for manufacturer- and site-specific procedures to ensure long-term traceability and consistency of reference humidity measurements. The results demonstrate that residence time inside ARLs constitutes a system-dependent source of uncertainty, warranting explicit inclusion as an additional component in the GRUAN Data Product (GDP) humidity uncertainty budget.]]>
Here, we assess the feasibility of this approach in the context of the Sentinel-5 mission, systematically comparing two different emulation strategies: an end-to-end approach, which directly approximates the full forward model with neural networks, and a hybrid approach, which combines fast non-scattering simulations with a neural network-based correction for atmospheric scattering effects. We comprehensively validate each emulator in the full retrieval chain, evaluating their impact on the accuracy of retrieved XCO2 and XCH4.
Our results show that a hybrid approach is needed to meet the stringent accuracy requirements on XCH4 and XCO2. While the end-to-end emulator achieves large speed-ups exceeding a factor of 300, it introduces considerable errors of 7.22 ppb for XCH4 and 4.25 ppm for XCO2 compared to full-physics retrievals, and fails to generalize to high-emission scenarios beyond the training range. In contrast, the hybrid approach can effectively leverage the information provided by the non-scattering approximation, reducing emulator-induced retrieval errors to less than 1.5 ppb for XCH4 and 0.5 ppm for XCO2, while still being an order of magnitude faster than full-physics retrievals and maintaining robust performance for high-emission scenarios.
Together, these results pave the way for operational deployment of neural network-based forward models in GHG retrievals from Sentinel-5, and more broadly demonstrate the potential of hybrid machine learning emulators to facilitate timely and accurate processing of the rapidly growing data volumes from modern satellite missions.]]>
This methodology identified a significant correlation between the collapsed health system and crisis stagnation at a high-severity level. The Syrian emergency serves as the most accurate comparative proxy for managing this health system collapse. Addressing a health system collapsed prior to seismic events requires holistic strategies; isolated, disaster-focused interventions risk becoming temporary solutions that deepen the crisis.
Comparing pre- and post-disaster severity and need scores validates the utility of this model in recognizing acute disaster impacts within a protracted emergency. Medium- and long-term planning must adopt a Triple Nexus approach, integrating humanitarian aid, peacebuilding, and development. Ultimately, utilizing the Need Score to guide funding allocation presents a critical opportunity to reduce human suffering by overcoming inefficiencies inherent in delayed emergency decision-making.]]>
Satellite measurements, especially those from the Gravity Recovery And Climate Experiment (GRACE, 2002–2017) and GRACE Follow-On (GRACE-FO, 2018–present) missions, now allows to estimate the water budget closure level for large basins worldwide, including those poorly or not instrumented at all. One of the outgoing fluxes for exorheic basins, river discharge, is not available for many basins, particularly during the twenty‑first century due to the spatial and temporal heterogeneity of openly accessible in‑situ river discharge. To address this issue, several studies have attempted to close the basin‑scale water‑budget by estimating river discharge as the simple sum of runoff calculated from Land Surface Models. Despite well-documented significant errors in runoff estimation, uncertainties associated with these approaches are often neglected as river discharge is, in most cases, the flux with the smallest amplitude in the water budget. In this study, using an ensemble approach to assess the state‑of‑the‑art estimates of water cycle fluxes and stocks, we precisely evaluate the impact of river discharge errors on the conclusions drawn from the water budget analysis of 82 exorheic basins worldwide. When ensembles of products are used to estimate combination of precipitation, evapotranspiration and discharge that are the closest to the GRACE storage change variations, we demonstrate compensations between the components of the water budget can occur. Although river discharge is the flux with the smallest amplitude, its dispersion (36 %), when derived from aggregated runoff, is comparable to that of precipitation (44 %) and evapotranspiration (34 %) and a seemingly high level of water budget closure can be achieved with, for some basin, errors of more than 40 % in the annual volume assessment of precipitation and evaporation. Errors caused by these compensations are larger for continental, sub‑arctic and polar basins (around 15 %) than for tropical, arid and temperate basins (around 6 %). Moreover, applying a simple routing scheme to the runoff does not significantly reduce these errors. In this study, we mitigate and assess these compensations by using a combination of in situ and satellite-based discharge estimates. Future studies should explore methods that further limit the compensation effect when attempting to approach a water budget closure at basin scale.]]>
The purpose of this study is to use a catalog derived from seismic detection, giving a much greater temporal accuracy, to explore and better understand the meteorological conditions that contribute to rockfall at Mont Saint-Eynard, a limestone cliff in the French Alps. This study introduces a probabilistic approach that combines different temporal horizons and cumulative models capturing delayed effects to analyze the influence of rainfall and freezing conditions on rockfall triggering. By integrating multiple statistical metrics relative to a specific condition including empirical probabilities, lift measures, confidence intervals and Chi-squared tests, we identified not only the likelihood but also the strength and reliability of triggering patterns. We identified the significant role of short term triggers like recent intense rainfall on high magnitude rockfall, and delayed effect of freezing depth in rockfall activity. This knowledge could be used to implement a risk management strategy.]]>
Our analysis incorporates meteorological records from two primary sources: (1) 37 Weather Underground (WUnderground) personal weather stations (PWS) across Manhattan and Brooklyn with 5 and 15 min sampling, and (2) three Automated Surface Observing System (ASOS) stations. The study period saw total rainfall of approximately 900 mm and included diverse weather events, from intense rain to snowstorms in winter 2023–2024. These events were captured by the NYC Mesh wireless network, with intense rainfall causing attenuation up to 30 dB and frequent outages, especially on high-frequency V-band links. This highlights the trade-off of using high-frequency bands in wireless networks: while precipitation might cause severe channel disruptions, this greater sensitivity simultaneously makes them effective opportunistic weather sensors. The OpenMesh dataset is available at https://doi.org/10.5281/zenodo.15287692 (Jacoby et al., 2025b). By publishing the dataset and demonstrating its usability, we aim to encourage further research that leverages wireless networks for real-time urban weather sensing.
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