Abstract
This review examines complexity science in the context of Heliophysics, describing it not as a discipline, but as a paradigm. In the context of Heliophysics, complexity science is the study of a star, interplanetary environment, magnetosphere, upper and terrestrial atmospheres, and planetary surface as interacting subsystems. Complexity science studies entities in a system (e.g., electrons in an atom, planets in a solar system, individuals in a society) and their interactions, and is the nature of what emerges from these interactions. It is a paradigm that employs systems approaches and is inherently multi- and cross-scale. Heliophysics processes span at least 15 orders of magnitude in space and another 15 in time, and its reaches go well beyond our own solar system and Earth’s space environment to touch planetary, exoplanetary, and astrophysical domains. It is an uncommon domain within which to explore complexity science. After first outlining the dimensions of complexity science, the review proceeds in three epochal parts: 1) A pivotal year in the Complexity Heliophysics paradigm: 1996; 2) The transitional years that established foundations of the paradigm (1996-2010); and 3) The emergent literature largely beyond 2010. This review article excavates the lived and living history of complexity science in Heliophysics. It identifies five dimensions of complexity science, some enjoying much scholarship in Heliophysics, others that represent relative gaps in the existing research. The history reveals a grand challenge that confronts Heliophysics, as with most physical sciences, to understand the research intersection between fundamental science (e.g., complexity science) and applied science (e.g., artificial intelligence and machine learning (AI/ML)). A risk science framework is suggested as a way of formulating the grand scientific and societal challenges in a way that AI/ML and complexity science converge. The intention is to provide inspiration, help researchers think more coherently about ideas of complexity science in Heliophysics, and guide future research. It will be instructive to Heliophysics researchers, but also to any reader interested in or hoping to advance the frontier of systems and complexity science.
The traditional approach for estimating the b-value of the Gutenberg–Richter law, which is posited to inversely correlate with differential stress, has historically relied on the maximum likelihood technique, ...
А.В. Леонидов
В 2024 году отмечается 90-летие Физического института Академии наук СССР/Российской академии наук (ФИАН). Важнейшей составляющей научной жизни ФИАН являлись исследования по теоретической физике, проводимые в Отделе/Отделении теоретической физики ФИАН по различным направлениям. В настоящем обзоре обсуждаются идеи в физике сильного взаимодействия частиц, разработанные в Секторе/Лаборатории физики высоких энергий теоротдела ФИАН.
Abstract
Understanding how aerosols affect cloud cover is critical for reducing the large uncertainty of the aerosol-cloud interaction (ACI). The 2014 Holuhraun effusive eruption in Iceland resulted in a significant increase in cloud drop number concentration (N
d
) relative to the climatological N
d
observed during periods of relatively infrequent volcanic activity. Previous studies show a significant “Twomey” effect during this eruption; however, aerosol-induced changes in cloud fraction (Cf) appeared negligible. This leads to the question of why changes in aerosols do not cause Cf changes. To address this question, prediction models were derived to predict Cf based on N
d
and meteorological parameters. These validated models allow us to investigate aerosol perturbations on Cf in various N
d
scenarios by controlled meteorological conditions. Here our analysis unveiled that the increase in N
d
was primarily observed under polluted conditions where N
d
surpassing the threshold of 60 cm−3. After this point, cloud cover stops increasing even as N
d
increases. On the contrary, the cloud cover did increase by 9.0% under conditions of clean backgrounds (N
d
< 60 cm−3). Accordingly, the aerosol-driven cloud adjustment is hidden behind the seemingly insignificant cloud cover effect in areas with large background N
d
. These findings provide insights into the importance of considering background N
d
and the saturation status of cloud covers in ACI studies.
Abstract
Researchers have recently focused on the interplay of the urban heat island (UHI) effect and heat waves (HWs). However, the synergies of these two phenomena remains inconclusive at present. To address this gap, this study investigated UHIs and HWs synergies during the last 30 years in the Tokyo metropolitan area, through a unique and novel approach named Land-Surface-Physics-Based Downscaling (LSP-DS). LSP-DS integrates the widely used Noah-Multiparameterization (Noah-MP) land-surface model coupled with urban canopy-process physics, aiming to conduct high-resolution, long-term urban-specific simulations with much less computational resources. Our comprehensive analysis combining observation data and numerous LSP-DS simulations confirms exacerbated UHIs during HWs. Specifically, HWs amplify the temperature differences between urban and rural environments, which is quantified by UHI intensity (UHII). During HWs, UHII increased more at night in inland areas and more during daytime in coastal areas. HWs present especially a heightened threat to coastal regions where daytime UHII increased by approximately 1°C during HWs. The Bowen ratio can explain the increase in the daytime UHII, and the daytime accumulated storage heat increase during HWs can explain the increase in nighttime UHII. Based on future projections of the increasing frequency of high temperatures, our findings highlight the impending heat-related health challenges faced by urban residents.
Earth system models (ESMs) help us understand climate and environmental changes. With advances in computing power, ESMs can now be run at kilometer-scale (k-scale) resolutions, capturing very fine details to better predict extreme weather and understand water, carbon, and energy cycles.
A new study questions the coherence of the circulation in the North Atlantic Ocean, as researchers show that the Gulf Stream exists, but variations off the coast of Florida do not necessarily reach Norway.
Toward on-demand measurements of greenhouse gas emissions using an uncrewed aircraft AirCore system
Zihan Zhu, Javier González-Rocha, Yifan Ding, Isis Frausto-Vicencio, Sajjan Heerah, Akula Venkatram, Manvendra Dubey, Don Collins, and Francesca M. Hopkins
Atmos. Meas. Tech., 17, 3883–3895, https://doi.org/10.5194/amt-17-3883-2024, 2024
Increases in agriculture, oil and gas, and waste management activities have contributed to the increase in atmospheric methane levels and resultant climate warming. In this paper, we explore the use of small uncrewed aircraft systems (sUASs) and AirCore technology to detect and quantify methane emissions. Results from field experiments demonstrate that sUASs and AirCore technology can be effective for detecting and quantifying methane emissions in near real time.
Fast retrieval of XCO2 over east Asia based on Orbiting Carbon Observatory-2 (OCO-2) spectral measurements
Fengxin Xie, Tao Ren, Changying Zhao, Yuan Wen, Yilei Gu, Minqiang Zhou, Pucai Wang, Kei Shiomi, and Isamu Morino
Atmos. Meas. Tech., 17, 3949–3967, https://doi.org/10.5194/amt-17-3949-2024, 2024
This study demonstrates a new machine learning approach to efficiently and accurately estimate atmospheric carbon dioxide levels from satellite data. Rather than using traditional complex physics-based retrieval methods, neural network models are trained on simulated data to rapidly predict CO2 concentrations directly from satellite spectral measurements.
Transferability of machine-learning-based global calibration models for NO2 and NO low-cost sensors
Ayah Abu-Hani, Jia Chen, Vigneshkumar Balamurugan, Adrian Wenzel, and Alessandro Bigi
Atmos. Meas. Tech., 17, 3917–3931, https://doi.org/10.5194/amt-17-3917-2024, 2024
This study examined the transferability of machine learning calibration models among low-cost sensor units targeting NO2 and NO. The global models were evaluated under similar and different emission conditions. To counter cross-sensitivity, the study proposed integrating O3 measurements from nearby reference stations, in Switzerland. The models show substantial improvement when O3 measurements are incorporated, which is more pronounced when in regions with elevated O3 concentrations.
Sensitivity of thermodynamic profiles retrieved from ground-based microwave and infrared observations to additional input data from active remote sensing instruments and numerical weather prediction models
Laura Bianco, Bianca Adler, Ludovic Bariteau, Irina V. Djalalova, Timothy Myers, Sergio Pezoa, David D. Turner, and James M. Wilczak
Atmos. Meas. Tech., 17, 3933–3948, https://doi.org/10.5194/amt-17-3933-2024, 2024
The Tropospheric Remotely Observed Profiling via Optimal Estimation physical retrieval is used to retrieve temperature and humidity profiles from various combinations of passive and active remote sensing instruments, surface platforms, and numerical weather prediction models. The retrieved profiles are assessed against collocated radiosonde in non-cloudy conditions to assess the sensitivity of the retrievals to different input combinations. Case studies with cloudy conditions are also inspected.
A 2-year intercomparison of three methods for measuring black carbon concentration at a high-altitude research station in Europe
Sarah Tinorua, Cyrielle Denjean, Pierre Nabat, Véronique Pont, Mathilde Arnaud, Thierry Bourrianne, Maria Dias Alves, and Eric Gardrat
Atmos. Meas. Tech., 17, 3897–3915, https://doi.org/10.5194/amt-17-3897-2024, 2024
The three most widely used techniques for measuring black carbon (BC) have been deployed continuously for 2 years at a French high-altitude research station. Despite a similar temporal variation in the BC load, we found significant biases by up to a factor of 8 between the three instruments. This study raises questions about the relevance of using these instruments for specific background sites, as well as the processing of their data, which can vary according to the atmospheric conditions.
Roads and sidewalks in some areas get so hot that skin contact could result in second-degree burns.
Accurate and comprehensive building data is critical for urban management and planning. Existing datasets, such as those from Microsoft and OpenStreetMap, often lack completeness and accuracy in East Asia, limiting their utility for large-scale applications. The complex distribution of buildings and scarcity of auxiliary data in this region further complicate the extraction of reliable building footprints.
Climate is a major factor affecting economic and social outcomes. In China, the country's National Climate Center releases an annual climate report that comprehensively covers China's achievements and progress that year in climate monitoring and impact assessment. This series of reports has been published in Atmospheric and Oceanic Science Letters for six consecutive years since 2019, and the "State of China's climate in 2023" is now available.
Global warming as well as recent droughts and floods threaten large populations along the Nile Valley. Understanding how such a large river will respond to an invigorated hydrological cycle is therefore a pressing issue. Insights can be gained by studying past periods with wetter and warmer conditions, such as the North African Humid Period 11 to 6 thousand years ago.
Automatic adjoint-based inversion schemes for geodynamics: reconstructing the evolution of Earth's mantle in space and time
Sia Ghelichkhan, Angus Gibson, D. Rhodri Davies, Stephan C. Kramer, and David A. Ham
Geosci. Model Dev., 17, 5057–5086, https://doi.org/10.5194/gmd-17-5057-2024, 2024
We introduce the Geoscientific ADjoint Optimisation PlaTform (G-ADOPT), designed for inverse modelling of Earth system processes, with an initial focus on mantle dynamics. G-ADOPT is built upon Firedrake, Dolfin-Adjoint and the Rapid Optimisation Library, which work together to optimise models using an adjoint method, aligning them with seismic and geologic datasets. We demonstrate G-ADOPT's ability to reconstruct mantle evolution and thus be a powerful tool in geosciences.
Validating a microphysical prognostic stratospheric aerosol implementation in E3SMv2 using observations after the Mount Pinatubo eruption
Hunter York Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, and Lin Lin
Geosci. Model Dev., 17, 5087–5121, https://doi.org/10.5194/gmd-17-5087-2024, 2024
Explosive volcanic eruptions lead to long-lived, microscopic particles in the upper atmosphere which act to cool the Earth's surface by reflecting the Sun's light back to space. We include and test this process in a global climate model, E3SM. E3SM is tested against satellite and balloon observations of the 1991 eruption of Mt. Pinatubo, showing that with these particles in the model we reasonably recreate Pinatubo and its global effects. We also explore how particle size leads to these effects.
Understanding how gold forms is crucial for knowing where to find it and how to extract it sustainably. McGill researchers have answered a long-standing question in geology that could lead to new ore discoveries.
Risk reduction through managed retreat? Investigating enabling conditions and assessing resettlement effects on community resilience in Metro Manila
Hannes Lauer, Carmeli Marie C. Chaves, Evelyn Lorenzo, Sonia Islam, and Jörn Birkmann
Nat. Hazards Earth Syst. Sci., 24, 2243–2261, https://doi.org/10.5194/nhess-24-2243-2024, 2024
In many urban areas, people face high exposure to hazards. Resettling them to safer locations becomes a major strategy, not least because of climate change. This paper dives into the success factors of government-led resettlement in Manila and finds surprising results which challenge the usual narrative and fuel the conversation on resettlement as an adaptation strategy. Contrary to expectations, the location – whether urban or rural – of the new home is less important than safety from floods.
