{"total":18,"items":[{"citing_arxiv_id":"2605.23875","ref_index":3,"ref_count":1,"confidence":0.5,"is_internal_anchor":false,"paper_title":"Atmosphere as a steam engine","primary_cat":"physics.ao-ph","submitted_at":"2026-05-22T17:34:17+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"Atmosphere functions as steam engine with global power 4.4±0.9 W/m² from water cycle, matching total atmospheric power 4.3±0.6 W/m² and explaining condensation-driven dynamics via precipitation.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2605.15367","ref_index":15,"ref_count":1,"confidence":0.5,"is_internal_anchor":false,"paper_title":"Juno Microwave Radiometer Observations Reveal A Warmer Polar Atmosphere on Jupiter","primary_cat":"astro-ph.EP","submitted_at":"2026-05-14T19:45:50+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"Juno MWR observations from PJ51-PJ61 show Jupiter's north pole 6-7 K warmer than the equator at 1 bar with ammonia at 3x solar and water at 2.1x solar, similar to lower latitudes.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2605.06944","ref_index":12,"ref_count":2,"confidence":0.5,"is_internal_anchor":false,"paper_title":"AIMIP Phase 1: systematic evaluations of AI weather and climate models","primary_cat":"physics.ao-ph","submitted_at":"2026-05-07T21:04:05+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"AIMIP Phase 1 sets up a common experiment and five evaluation criteria for AI atmosphere models forced by historical sea surface temperatures, finding they match conventional models on most metrics but underestimate some warming trends and diverge on out-of-sample tests.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2605.04164","ref_index":75,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Enabling Real-Time Training of a Wildfire-to-Smoke Map with Multilinear Operators","primary_cat":"cs.LG","submitted_at":"2026-05-05T18:02:14+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":7.0,"formal_verification":"none","one_line_summary":"A multilinear operator learned on PCA coefficients maps time-since-ignition inputs to smoke outputs, matching Monte Carlo accuracy with half the model calls and outperforming prior classifiers on holdout data.","context_count":1,"top_context_role":"background","top_context_polarity":"background","context_text":"1186/s42408-023-00190-7. [73] E. Qian, B. Kramer, B. Peherstorfer, and K. Willcox. \"Lift & Learn: Physics-Informed Machine Learn- ing for Large-Scale Nonlinear Dynamical Systems.\"Phys. D Nonlin. Phenom.406 (2020), p. 132401. doi:10.1016/j.physd.2020.132401. [74] C. E. Rasmussen and C. K. I. Williams.Gaussian Processes for Machine Learning. MIT Press, 2006. [75] J. Reisner, S. Wynne, L. Margolin, and R. Linn. \"Coupled Atmospheric-Fire Modeling Employing the Method of Averages.\"Mon. Weather Rev.128.10 (2000), pp. 3683 -3691.doi:10.1175/1520- 0493(2001)129<3683:CAFMET>2.0.CO;2. [76] C. C. Remy, D. J. Krofcheck, A. R. Keyser, and M. D. Hurteau. \"Restoring Frequent Fire to Dry ConiferForestsDelaystheDeclineofSubalpineForestsintheSouthwestUnitedStatesunderProjected"},{"citing_arxiv_id":"2605.03271","ref_index":33,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Inertial-Range Energy Transfer Free from Isotropic Assumption in Turbulent Space Plasma","primary_cat":"physics.plasm-ph","submitted_at":"2026-05-05T01:59:49+00:00","verdict":null,"verdict_confidence":null,"novelty_score":null,"formal_verification":null,"one_line_summary":null,"context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2605.00035","ref_index":4,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Novel Chemical Pathways for the Formation of Nucleobase Precursors via Benzene {\\pi}-Bond Addition to HCN","primary_cat":"physics.chem-ph","submitted_at":"2026-04-28T06:08:37+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"Benzene reacts with HCN via 1,4-cycloaddition and C2H2 loss to yield pyrimidine, which then forms purine with NH3 and HCN, as shown by quantum calculations and modeled for cold dry Mars conditions.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2604.10564","ref_index":29,"ref_count":1,"confidence":0.5,"is_internal_anchor":false,"paper_title":"Direct Lagrangian tracking simulation of droplet growth in vertically-developing turbulent cloud","primary_cat":"physics.ao-ph","submitted_at":"2026-04-12T10:13:13+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":7.0,"formal_verification":"none","one_line_summary":"Turbulence accelerates droplet collisions in developing clouds, causing earlier onset of precipitation at the ground and larger first raindrops than in non-turbulent cases.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2604.10371","ref_index":29,"ref_count":1,"confidence":0.5,"is_internal_anchor":false,"paper_title":"Structural Gating and Effect-aligned Lag-resolved Temporal Causal Discovery Framework with Application to Heat-Pollution Extremes","primary_cat":"cs.LG","submitted_at":"2026-04-11T22:50:26+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":5.0,"formal_verification":"none","one_line_summary":"SGED-TCD is a lag-resolved causal discovery framework that uses structural gating and perturbation-effect alignment to infer interpretable weighted causal networks from complex time series, shown on heat-pollution extremes in China.","context_count":1,"top_context_role":"background","top_context_polarity":"background","context_text":"nal of climate 13 (5) (2000) 1000-1016. doi:10.1175/1520- 0442(2000)013<1000:AMITEC>2.0.CO;2. [28] Z. Zhang, X. Zhang, D. Gong, S.-J. Kim, R. Mao, X. Zhao, Possi- ble influence of atmospheric circulations on winter haze pollution in the beijing-tianjin-hebei region, northern china, Atmospheric Chem- istry and Physics 16 (2) (2016) 561-571. doi:10.5194/acp-16-561-2016. [29] M. Li, Y. Yao, I. Simmonds, D. Luo, L. Zhong, L. Pei, Linkages between the atmospheric transmission originating from the north atlantic oscilla- tion and persistent winter haze over beijing, Atmospheric Chemistry and Physics 21 (24) (2021) 18573-18588. doi:10.5194/acp-21-18573-2021. [30] W. Zhong, Z. Yin, H. Wang, The relationship between anticyclonic"},{"citing_arxiv_id":"2604.09385","ref_index":25,"ref_count":1,"confidence":0.5,"is_internal_anchor":false,"paper_title":"NCCR PlanetS: Observational and computational characterization of exoplanet atmospheres","primary_cat":"astro-ph.EP","submitted_at":"2026-04-10T14:55:12+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":1.0,"formal_verification":"none","one_line_summary":"The paper reviews physical processes, modeling techniques, retrieval methods, and observational strategies for characterizing exoplanet atmospheres, emphasizing Swiss research progress.","context_count":1,"top_context_role":"background","top_context_polarity":"background","context_text":"version operations as part of their methodology. Where computational efficiency is paramount, such as in retrieval and 3D GCM simulations, a trade-off between accuracy and speed must be made to remain viable in a suitable timeframe. To tackle this, in [24] examined the approximate longwave radiative-transfer methods; Absorption Approximation (AA) ([25]) and Variational Iteration Method (VIM) ([26]) which were first developed for Earth atmospheric science, but now altered for a sub-stellar atmosphere context. [24] found that the AA and VIM methods were highly suitable and accurate for sub-stellar atmosphere calculations, producing similar heating/cooling rates in the atmosphere and outgoing fluxes to traditional"},{"citing_arxiv_id":"2604.06433","ref_index":18,"ref_count":1,"confidence":0.5,"is_internal_anchor":false,"paper_title":"Operator Learning for Surrogate Modeling of Wave-Induced Forces from Sea Surface Waves","primary_cat":"physics.comp-ph","submitted_at":"2026-04-07T20:16:04+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":4.0,"formal_verification":"none","one_line_summary":"DeepONet surrogate model accurately predicts wave-induced radiation stress and wave heights in steady-state simulations as a replacement for the SWAN numerical model.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2604.06000","ref_index":34,"ref_count":1,"confidence":0.5,"is_internal_anchor":false,"paper_title":"Regimes of Scale in AI Meteorology","primary_cat":"cs.HC","submitted_at":"2026-04-07T15:28:25+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":5.0,"formal_verification":"none","one_line_summary":"AI/ML weather tools face integration challenges from mismatched 'regimes of scale' in how data and models are organized compared to traditional meteorology practices.","context_count":1,"top_context_role":"background","top_context_polarity":"background","context_text":"P12 notes that one major difference between meteorology and domains like NLP is that \"we have this strong physical structure, physical information, to the problem that we have. \" Meteorology established itself as a \"physics-based\" science in the 1950s and 60s in explicit contrast to existing statistical and time-series methods of weather/climate prediction [34], making then \"audacious\" claims [5] that a \"dynamical core\" of physical equations could extend model prediction across a global scale. This means that AI/ML methods, which depend heavily on \"black-boxed\" statistical methods, have had to reckon with the secondary position pure statistics has had in meteorological history. In contrast to popular depictions of AI/ML"},{"citing_arxiv_id":"2604.05536","ref_index":7,"ref_count":1,"confidence":0.5,"is_internal_anchor":false,"paper_title":"Turbulence-like 5/3 spectral scaling in contextual representations of language as a complex system","primary_cat":"cs.CL","submitted_at":"2026-04-07T07:36:12+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":7.0,"formal_verification":"none","one_line_summary":"Contextual language embeddings exhibit a robust 5/3 power-law spectrum in token-sequence fluctuations, analogous to Kolmogorov turbulence.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2509.16962","ref_index":9,"ref_count":1,"confidence":0.5,"is_internal_anchor":false,"paper_title":"Temporal Drift in Privacy Recall: Users Misremember From Verbatim Loss to Gist-Based Overexposure","primary_cat":"cs.HC","submitted_at":"2025-09-21T07:50:19+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":5.0,"formal_verification":"none","one_line_summary":"Users' memory of privacy settings drifts over time from exact recall to gist-based impressions that bias toward sharing with larger audiences than originally intended.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2507.18937","ref_index":30,"ref_count":1,"confidence":0.5,"is_internal_anchor":false,"paper_title":"CNN-based Surface Temperature Forecasts with Ensemble Numerical Weather Prediction","primary_cat":"physics.ao-ph","submitted_at":"2025-07-25T04:19:05+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":4.0,"formal_verification":"none","one_line_summary":"CNN post-processing applied member-wise to a 51-member 40-km NWP ensemble creates a 5-km high-resolution ensemble forecast system with improved deterministic accuracy and probabilistic reliability for surface temperatures.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2504.09375","ref_index":58,"ref_count":1,"confidence":0.5,"is_internal_anchor":false,"paper_title":"Efficient Gradient-Enhanced Bayesian Optimizer with Comparisons to Conjugate-Gradient and Quasi-Newton Optimizers for Unconstrained Local Optimization","primary_cat":"math.OC","submitted_at":"2025-04-12T23:49:17+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":5.0,"formal_verification":"none","one_line_summary":"A gradient-enhanced local Bayesian optimization framework that converges optimality as deeply as standard optimizers but with significantly fewer function evaluations on 2-40 dimensional unimodal problems, outperforming them under noisy gradients.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2103.09781","ref_index":122,"ref_count":1,"confidence":0.5,"is_internal_anchor":false,"paper_title":"Reviewing methods and assumptions for high-resolution large-scale onshore wind energy potential assessments","primary_cat":"econ.GN","submitted_at":"2021-03-17T17:07:38+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":2.0,"formal_verification":"none","one_line_summary":"A critical review of methods for estimating onshore wind energy potentials at multiple levels, with an attempt to derive best practice recommendations.","context_count":1,"top_context_role":"background","top_context_polarity":"background","context_text":"Historical and future, X-Y years Ca. 10km - 300km Hourly to monthly Regional reanalyses. While ERA5 provides hourly data with ~30 km horizon tal grid spacing, higher resolutions may be required to resolve wind patterns in complex terrain [120,121]. In fact, using global reanalyses can lead to a severe underestimation of wind energy technical p otential [122]. Regional reanalyses provide higher resolution. COSMO-REA2, for example, has a horizontal resolutio n of 2 km, and can effectively resolve meteorologic al phenomena from a scale of ~14 km [114]. This is suf ficient to resolve some mountainous weather pattern s [122], while disagreement with observations remains large in particularly complex terrain [103,122]."},{"citing_arxiv_id":"1907.10007","ref_index":14,"ref_count":1,"confidence":0.5,"is_internal_anchor":false,"paper_title":"Ground/space, passive/active remote sensing observations coupled with particle dispersion modelling to understand the inter-continental transport of wildfire smoke plumes","primary_cat":"physics.ao-ph","submitted_at":"2019-07-23T17:02:03+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":3.0,"formal_verification":"none","one_line_summary":"Multi-platform remote sensing and modeling document the arrival and altitude-dependent properties of intercontinental smoke from 2017 Pacific Northwest wildfires over Spain.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"1907.00999","ref_index":14,"ref_count":1,"confidence":0.5,"is_internal_anchor":false,"paper_title":"Evidence against a general positive eddy feedback in atmospheric blocking","primary_cat":"physics.ao-ph","submitted_at":"2019-07-01T18:11:10+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"Large-ensemble experiments in a minimal QG model show that generic eddy straining does not maintain atmospheric blocks.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null}],"limit":50,"offset":0}