AGU Advances最新文献

{"title":"Magnetic Reconnection as a Potential Trigger for Magnetotail Flapping at Mars: Insights From MAVEN and Tianwen-1 Observations","authors":"Yuanzheng Wen,&nbsp;Jasper S. Halekas,&nbsp;Han-Wen Shen,&nbsp;Chi Zhang,&nbsp;Robert J. Lillis,&nbsp;Jiawei Gao,&nbsp;Norberto Romanelli,&nbsp;Long Cheng,&nbsp;Chuanfei Dong,&nbsp;Yingjuan Ma,&nbsp;Yaxue Dong,&nbsp;Shaosui Xu,&nbsp;David A. Brain,&nbsp;Junfeng Qin,&nbsp;Jared R. Espley,&nbsp;David L. Mitchell,&nbsp;Christian Mazelle,&nbsp;James P. McFadden,&nbsp;Shannon M. Curry","doi":"10.1029/2026AV002343","DOIUrl":"10.1029/2026AV002343","url":null,"abstract":"<p>Magnetotail current sheet (CS) flapping is a universal plasma phenomenon observed at multiple planets, yet its triggering mechanisms remain poorly understood outside of Earth. At Mars, single-spacecraft observations have also reported tail flapping, but the processes responsible for its onset have never been identified. In this study, we investigate the potential correlation between magnetic reconnection and magnetotail flapping using multipoint measurements from Mars Atmosphere and Volatile EvolutioN (MAVEN) and Tianwen-1 (TW-1) missions. We analyze an example event in which MAVEN observed a reconnection-associated CS crossing in the near tail while TW-1 simultaneously detected CS flapping further downtail. A statistical survey of joint observations from November 2021 to February 2024 identifies that about two-thirds of TW-1 flapping events coincide with reconnection signatures observed by MAVEN. Multiple magnetic flux ropes were also detected before or during flapping intervals, similar to previous observations at Earth, suggesting that reconnection-generated magnetic flux ropes may propagate tailward and drive plasma instabilities that trigger the tail flapping at Mars. These results provide the first multipoint evidence of a potential statistical correlation between magnetic reconnection and magnetotail flapping at Mars, enabling us to explore the potential triggering mechanism of magnetotail flapping. Our findings also offer new insights into Martian magnetotail dynamics and broaden the comparative understanding of this fundamental plasma process across planetary environments.</p>","PeriodicalId":100067,"journal":{"name":"AGU Advances","volume":"7 2","pages":""},"PeriodicalIF":8.3,"publicationDate":"2026-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2026AV002343","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Magnetic Reconnection as a Potential Trigger for Magnetotail Flapping at Mars: Insights From MAVEN and Tianwen-1 Observations","authors":"Yuanzheng Wen,&nbsp;Jasper S. Halekas,&nbsp;Han-Wen Shen,&nbsp;Chi Zhang,&nbsp;Robert J. Lillis,&nbsp;Jiawei Gao,&nbsp;Norberto Romanelli,&nbsp;Long Cheng,&nbsp;Chuanfei Dong,&nbsp;Yingjuan Ma,&nbsp;Yaxue Dong,&nbsp;Shaosui Xu,&nbsp;David A. Brain,&nbsp;Junfeng Qin,&nbsp;Jared R. Espley,&nbsp;David L. Mitchell,&nbsp;Christian Mazelle,&nbsp;James P. McFadden,&nbsp;Shannon M. Curry","doi":"10.1029/2026AV002343","DOIUrl":"https://doi.org/10.1029/2026AV002343","url":null,"abstract":"<p>Magnetotail current sheet (CS) flapping is a universal plasma phenomenon observed at multiple planets, yet its triggering mechanisms remain poorly understood outside of Earth. At Mars, single-spacecraft observations have also reported tail flapping, but the processes responsible for its onset have never been identified. In this study, we investigate the potential correlation between magnetic reconnection and magnetotail flapping using multipoint measurements from Mars Atmosphere and Volatile EvolutioN (MAVEN) and Tianwen-1 (TW-1) missions. We analyze an example event in which MAVEN observed a reconnection-associated CS crossing in the near tail while TW-1 simultaneously detected CS flapping further downtail. A statistical survey of joint observations from November 2021 to February 2024 identifies that about two-thirds of TW-1 flapping events coincide with reconnection signatures observed by MAVEN. Multiple magnetic flux ropes were also detected before or during flapping intervals, similar to previous observations at Earth, suggesting that reconnection-generated magnetic flux ropes may propagate tailward and drive plasma instabilities that trigger the tail flapping at Mars. These results provide the first multipoint evidence of a potential statistical correlation between magnetic reconnection and magnetotail flapping at Mars, enabling us to explore the potential triggering mechanism of magnetotail flapping. Our findings also offer new insights into Martian magnetotail dynamics and broaden the comparative understanding of this fundamental plasma process across planetary environments.</p>","PeriodicalId":100067,"journal":{"name":"AGU Advances","volume":"7 2","pages":""},"PeriodicalIF":8.3,"publicationDate":"2026-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2026AV002343","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Explaining Glacial-Interglacial CO2 Changes Requires Multiple Ocean Processes","authors":"Juan Muglia","doi":"10.1029/2026AV002306","DOIUrl":"https://doi.org/10.1029/2026AV002306","url":null,"abstract":"&lt;p&gt;Changes in deep ocean carbon played a significant role in atmospheric CO&lt;sub&gt;2&lt;/sub&gt; variations during glacial-interglacial climate cycles. However, ocean carbon is a complex system that can reflect differing influences of physical and biological processes. To address this complexity, the ocean's dissolved inorganic carbon (DIC) pool is divided into different components that depend on their origin and formation processes (Figure 1). Understanding the behavior of each component to perturbations can help us improve the quantification of changes in DIC during glacial inceptions and terminations, and explain associated atmospheric CO&lt;sub&gt;2&lt;/sub&gt; changes (Khatiwala et al., &lt;span&gt;2019&lt;/span&gt;).&lt;/p&gt;&lt;p&gt;Past models have proposed that the disequilibrium component of DIC (C&lt;sub&gt;dis&lt;/sub&gt;), which is the deviation of DIC from saturation concentrations in equilibrium with the atmosphere, drives the change in deep ocean carbon in glacial-interglacial transitions. The differences in C&lt;sub&gt;dis&lt;/sub&gt; can be explained by changes in primary productivity, water temperature, and/or water mass distribution (Khatiwala et al., &lt;span&gt;2019&lt;/span&gt;; Schmittner &amp; Boling, &lt;span&gt;2025&lt;/span&gt;). These processes affect the accumulation of carbon in the deep ocean, and could explain part of the early rise in atmospheric CO&lt;sub&gt;2&lt;/sub&gt; after the Last Glacial Maximum (LGM, 19–15 ka before present). Distinguishing the relative roles of these processes in the light of multiple water masses in the Global Ocean and sea ice influencing the Southern Ocean is a consistent challenge for models.&lt;/p&gt;&lt;p&gt;In a new contribution, Gray et al. (&lt;span&gt;2026&lt;/span&gt;) use an ensemble of global ocean simulations to show that the disequilibrium components of deep O&lt;sub&gt;2&lt;/sub&gt; and DIC are negatively correlated. In other words, a decrease in O&lt;sub&gt;2&lt;/sub&gt;, as reconstructed for the LGM's deep ocean (Jaccard &amp; Galbraith, &lt;span&gt;2012&lt;/span&gt;), will induce an increase in the ocean carbon content by changes in the C&lt;sub&gt;dis&lt;/sub&gt; pool. The relationship between disequilibrium O&lt;sub&gt;2&lt;/sub&gt; and DIC remains constant through the different simulations, confirming the strength of the result. Gray et al. (&lt;span&gt;2026&lt;/span&gt;) suggest an expansion of the volume of glacial Antarctic Bottom Waters (AABW), which have greater disequilibrium with the atmosphere compared with North Atlantic Deep Waters (NADW). Other authors have suggested other mechanisms for higher C&lt;sub&gt;dis&lt;/sub&gt; in the glacial ocean, such as lower ocean temperatures and higher export production in the Southern Ocean (Khatiwala et al., &lt;span&gt;2019&lt;/span&gt;).&lt;/p&gt;&lt;p&gt;In a novel result, Gray et al. (&lt;span&gt;2026&lt;/span&gt;) also find a relationship between the ideal age tracer Δ&lt;sup&gt;14&lt;/sup&gt;C&lt;sub&gt;age&lt;/sub&gt;, whose age restores to zero in the surface ocean, and the soft tissue component of DIC (C&lt;sub&gt;soft&lt;/sub&gt;). C&lt;sub&gt;soft&lt;/sub&gt; is the carbon regenerated from organic matter oxidation in the deep ocean, so it increases with decreased ventilation of deep waters, reflec","PeriodicalId":100067,"journal":{"name":"AGU Advances","volume":"7 2","pages":""},"PeriodicalIF":8.3,"publicationDate":"2026-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2026AV002306","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Explaining Glacial-Interglacial CO2 Changes Requires Multiple Ocean Processes","authors":"Juan Muglia","doi":"10.1029/2026AV002306","DOIUrl":"10.1029/2026AV002306","url":null,"abstract":"&lt;p&gt;Changes in deep ocean carbon played a significant role in atmospheric CO&lt;sub&gt;2&lt;/sub&gt; variations during glacial-interglacial climate cycles. However, ocean carbon is a complex system that can reflect differing influences of physical and biological processes. To address this complexity, the ocean's dissolved inorganic carbon (DIC) pool is divided into different components that depend on their origin and formation processes (Figure 1). Understanding the behavior of each component to perturbations can help us improve the quantification of changes in DIC during glacial inceptions and terminations, and explain associated atmospheric CO&lt;sub&gt;2&lt;/sub&gt; changes (Khatiwala et al., &lt;span&gt;2019&lt;/span&gt;).&lt;/p&gt;&lt;p&gt;Past models have proposed that the disequilibrium component of DIC (C&lt;sub&gt;dis&lt;/sub&gt;), which is the deviation of DIC from saturation concentrations in equilibrium with the atmosphere, drives the change in deep ocean carbon in glacial-interglacial transitions. The differences in C&lt;sub&gt;dis&lt;/sub&gt; can be explained by changes in primary productivity, water temperature, and/or water mass distribution (Khatiwala et al., &lt;span&gt;2019&lt;/span&gt;; Schmittner &amp; Boling, &lt;span&gt;2025&lt;/span&gt;). These processes affect the accumulation of carbon in the deep ocean, and could explain part of the early rise in atmospheric CO&lt;sub&gt;2&lt;/sub&gt; after the Last Glacial Maximum (LGM, 19–15 ka before present). Distinguishing the relative roles of these processes in the light of multiple water masses in the Global Ocean and sea ice influencing the Southern Ocean is a consistent challenge for models.&lt;/p&gt;&lt;p&gt;In a new contribution, Gray et al. (&lt;span&gt;2026&lt;/span&gt;) use an ensemble of global ocean simulations to show that the disequilibrium components of deep O&lt;sub&gt;2&lt;/sub&gt; and DIC are negatively correlated. In other words, a decrease in O&lt;sub&gt;2&lt;/sub&gt;, as reconstructed for the LGM's deep ocean (Jaccard &amp; Galbraith, &lt;span&gt;2012&lt;/span&gt;), will induce an increase in the ocean carbon content by changes in the C&lt;sub&gt;dis&lt;/sub&gt; pool. The relationship between disequilibrium O&lt;sub&gt;2&lt;/sub&gt; and DIC remains constant through the different simulations, confirming the strength of the result. Gray et al. (&lt;span&gt;2026&lt;/span&gt;) suggest an expansion of the volume of glacial Antarctic Bottom Waters (AABW), which have greater disequilibrium with the atmosphere compared with North Atlantic Deep Waters (NADW). Other authors have suggested other mechanisms for higher C&lt;sub&gt;dis&lt;/sub&gt; in the glacial ocean, such as lower ocean temperatures and higher export production in the Southern Ocean (Khatiwala et al., &lt;span&gt;2019&lt;/span&gt;).&lt;/p&gt;&lt;p&gt;In a novel result, Gray et al. (&lt;span&gt;2026&lt;/span&gt;) also find a relationship between the ideal age tracer Δ&lt;sup&gt;14&lt;/sup&gt;C&lt;sub&gt;age&lt;/sub&gt;, whose age restores to zero in the surface ocean, and the soft tissue component of DIC (C&lt;sub&gt;soft&lt;/sub&gt;). C&lt;sub&gt;soft&lt;/sub&gt; is the carbon regenerated from organic matter oxidation in the deep ocean, so it increases with decreased ventilation of deep waters, reflec","PeriodicalId":100067,"journal":{"name":"AGU Advances","volume":"7 2","pages":""},"PeriodicalIF":8.3,"publicationDate":"2026-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2026AV002306","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thank You to Our 2025 Peer Reviewers","authors":"Alberto Montanari,&nbsp;Ana Barros,&nbsp;Thorsten Becker,&nbsp;Marc Bierkens,&nbsp;Sharon Billings,&nbsp;M. Bayani Cardenas,&nbsp;Eric Davidson,&nbsp;Eileen Hofmann,&nbsp;Matthew Huber,&nbsp;Tissa Illangasekare,&nbsp;Marcos Moreno,&nbsp;Vaishali Naik,&nbsp;Francis Nimmo,&nbsp;Francois Primeau,&nbsp;Vincent Salters,&nbsp;David Schimel,&nbsp;Thomas Stocker,&nbsp;Jessica Tierney,&nbsp;Susan Trumbore,&nbsp;Donald Wuebbles,&nbsp;Andrew Yau,&nbsp;Peter Zeitler,&nbsp;Binzheng Zhang,&nbsp;Xi Zhang","doi":"10.1029/2026AV002449","DOIUrl":"https://doi.org/10.1029/2026AV002449","url":null,"abstract":"&lt;p&gt;The editorial team of &lt;i&gt;AGU Advances&lt;/i&gt; is grateful for the excellent contributions of our peer reviewers. We rely on their expertise to ensure that the manuscripts submitted to the journal undergo a rigorous, fair, and timely review. Remarkably, during 2025, the journal benefitted from the dedication from 389 reviewers, contributing a total of 507 reviews. These reviewers represented 31 countries. These reviewers provided insights of tremendous and generous value, and they assisted our authors in strengthening the rigor, quality, and presentation of their scholarship. Peer reviewing provides a natural way to engage in continuous learning and professional development. The majority of our reviewers are geoscientists, although we also have interdisciplinary contributions as the scope of Advances covers the extended domain of geosciences, intersecting with economics, communication and computational science, and the social sciences at large. Authors benefit greatly from reviewers' comments and suggestions: already more than 10 years ago, a study reported that most authors (90%) believe that peer review improved the last paper they published (Mulligan et al., 2013; https://doi.org/10.1002/asi.22798). Although the research and publishing arena is rapidly changing, peer review is considered the optimal standard for evaluating and selecting quality scientific manuscripts for publication, and therefore is highly deserving of our appreciation. We thank all of our peer reviewers for their selfless service and dedication to the scientific community. Your continuing support to the authors and editorial team of AGU Advances is deeply appreciated.&lt;/p&gt;&lt;p&gt;Individuals in italics provided three or more reviews for &lt;i&gt;AGU Advances&lt;/i&gt; during the year.&lt;/p&gt;&lt;p&gt;Aaron Breneman&lt;/p&gt;&lt;p&gt;Aaron Ridley&lt;/p&gt;&lt;p&gt;Adam Scaife&lt;/p&gt;&lt;p&gt;Adriaan Teuling&lt;/p&gt;&lt;p&gt;Adrian Burd&lt;/p&gt;&lt;p&gt;Ajay Limaye&lt;/p&gt;&lt;p&gt;Alan Robock&lt;/p&gt;&lt;p&gt;Alberto Bellin&lt;/p&gt;&lt;p&gt;Alberto Montanari&lt;/p&gt;&lt;p&gt;Aleah Sommers&lt;/p&gt;&lt;p&gt;Alessandro Lelpi&lt;/p&gt;&lt;p&gt;Alexander Cobb&lt;/p&gt;&lt;p&gt;Alexandra Iezzi&lt;/p&gt;&lt;p&gt;Alexandra Konings&lt;/p&gt;&lt;p&gt;Alfredo Martinez-Garcia&lt;/p&gt;&lt;p&gt;Alice-Agnes Gabriel&lt;/p&gt;&lt;p&gt;Andre Izidoro&lt;/p&gt;&lt;p&gt;André Niemeijer&lt;/p&gt;&lt;p&gt;Andrea Emmanuelli&lt;/p&gt;&lt;p&gt;Andreas Fichtner&lt;/p&gt;&lt;p&gt;Andrés Tassara&lt;/p&gt;&lt;p&gt;Andrew Heymsfield&lt;/p&gt;&lt;p&gt;Andrew Schauer&lt;/p&gt;&lt;p&gt;Anna Wilson&lt;/p&gt;&lt;p&gt;Anne Smith&lt;/p&gt;&lt;p&gt;Antoine Ringard&lt;/p&gt;&lt;p&gt;&lt;i&gt;Anton Artemyev&lt;/i&gt;&lt;/p&gt;&lt;p&gt;Antonietta Capotondi&lt;/p&gt;&lt;p&gt;Antonio Costa&lt;/p&gt;&lt;p&gt;Arif Hussain&lt;/p&gt;&lt;p&gt;Armin Sorooshian&lt;/p&gt;&lt;p&gt;Ashraf Rateb&lt;/p&gt;&lt;p&gt;Ashutosh Tripathy&lt;/p&gt;&lt;p&gt;Austin Chadwick&lt;/p&gt;&lt;p&gt;Baibhav Srivastava&lt;/p&gt;&lt;p&gt;Bea Gallardo-Lacourt&lt;/p&gt;&lt;p&gt;Ben Randall&lt;/p&gt;&lt;p&gt;Benjamin Cook&lt;/p&gt;&lt;p&gt;Benjamin Getraer&lt;/p&gt;&lt;p&gt;Bettina Gier&lt;/p&gt;&lt;p&gt;Bin Zhou&lt;/p&gt;&lt;p&gt;&lt;i&gt;Binayak Mohantzy&lt;/i&gt;&lt;/p&gt;&lt;p&gt;Binbin Ni&lt;/p&gt;&lt;p&gt;Bjorn Stevens&lt;/p&gt;&lt;p&gt;Blaž Gasparini&lt;/p&gt;&lt;p&gt;Bo Qin&lt;/p&gt;&lt;p&gt;Brandon Schmandt&lt;/p&gt;&lt;p&gt;Brenhin Keller&lt;/p&gt;&lt;p&gt;C. R. Brown&lt;/p&gt;&lt;p&gt;Callum Shakespeare&lt;/p&gt;&lt;p&gt;Cameron Homeyer&lt;/p&gt;&lt;p&gt;Carlotta Dentico&lt;/p&gt;&lt;p&gt;Carol Arnosti&lt;/p&gt;&lt;p&gt;Cathy Hohenegger&lt;/p&gt;&lt;p&gt;Celso H. L. Silva-Junior&lt;/p&gt;&lt;p&gt;Charles Ichoku&lt;/p&gt;&lt;p&gt;Charles Luce&lt;/","PeriodicalId":100067,"journal":{"name":"AGU Advances","volume":"7 2","pages":""},"PeriodicalIF":8.3,"publicationDate":"2026-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2026AV002449","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147667941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thank You to Our 2025 Peer Reviewers","authors":"Alberto Montanari,&nbsp;Ana Barros,&nbsp;Thorsten Becker,&nbsp;Marc Bierkens,&nbsp;Sharon Billings,&nbsp;M. Bayani Cardenas,&nbsp;Eric Davidson,&nbsp;Eileen Hofmann,&nbsp;Matthew Huber,&nbsp;Tissa Illangasekare,&nbsp;Marcos Moreno,&nbsp;Vaishali Naik,&nbsp;Francis Nimmo,&nbsp;Francois Primeau,&nbsp;Vincent Salters,&nbsp;David Schimel,&nbsp;Thomas Stocker,&nbsp;Jessica Tierney,&nbsp;Susan Trumbore,&nbsp;Donald Wuebbles,&nbsp;Andrew Yau,&nbsp;Peter Zeitler,&nbsp;Binzheng Zhang,&nbsp;Xi Zhang","doi":"10.1029/2026AV002449","DOIUrl":"10.1029/2026AV002449","url":null,"abstract":"&lt;p&gt;The editorial team of &lt;i&gt;AGU Advances&lt;/i&gt; is grateful for the excellent contributions of our peer reviewers. We rely on their expertise to ensure that the manuscripts submitted to the journal undergo a rigorous, fair, and timely review. Remarkably, during 2025, the journal benefitted from the dedication from 389 reviewers, contributing a total of 507 reviews. These reviewers represented 31 countries. These reviewers provided insights of tremendous and generous value, and they assisted our authors in strengthening the rigor, quality, and presentation of their scholarship. Peer reviewing provides a natural way to engage in continuous learning and professional development. The majority of our reviewers are geoscientists, although we also have interdisciplinary contributions as the scope of Advances covers the extended domain of geosciences, intersecting with economics, communication and computational science, and the social sciences at large. Authors benefit greatly from reviewers' comments and suggestions: already more than 10 years ago, a study reported that most authors (90%) believe that peer review improved the last paper they published (Mulligan et al., 2013; https://doi.org/10.1002/asi.22798). Although the research and publishing arena is rapidly changing, peer review is considered the optimal standard for evaluating and selecting quality scientific manuscripts for publication, and therefore is highly deserving of our appreciation. We thank all of our peer reviewers for their selfless service and dedication to the scientific community. Your continuing support to the authors and editorial team of AGU Advances is deeply appreciated.&lt;/p&gt;&lt;p&gt;Individuals in italics provided three or more reviews for &lt;i&gt;AGU Advances&lt;/i&gt; during the year.&lt;/p&gt;&lt;p&gt;Aaron Breneman&lt;/p&gt;&lt;p&gt;Aaron Ridley&lt;/p&gt;&lt;p&gt;Adam Scaife&lt;/p&gt;&lt;p&gt;Adriaan Teuling&lt;/p&gt;&lt;p&gt;Adrian Burd&lt;/p&gt;&lt;p&gt;Ajay Limaye&lt;/p&gt;&lt;p&gt;Alan Robock&lt;/p&gt;&lt;p&gt;Alberto Bellin&lt;/p&gt;&lt;p&gt;Alberto Montanari&lt;/p&gt;&lt;p&gt;Aleah Sommers&lt;/p&gt;&lt;p&gt;Alessandro Lelpi&lt;/p&gt;&lt;p&gt;Alexander Cobb&lt;/p&gt;&lt;p&gt;Alexandra Iezzi&lt;/p&gt;&lt;p&gt;Alexandra Konings&lt;/p&gt;&lt;p&gt;Alfredo Martinez-Garcia&lt;/p&gt;&lt;p&gt;Alice-Agnes Gabriel&lt;/p&gt;&lt;p&gt;Andre Izidoro&lt;/p&gt;&lt;p&gt;André Niemeijer&lt;/p&gt;&lt;p&gt;Andrea Emmanuelli&lt;/p&gt;&lt;p&gt;Andreas Fichtner&lt;/p&gt;&lt;p&gt;Andrés Tassara&lt;/p&gt;&lt;p&gt;Andrew Heymsfield&lt;/p&gt;&lt;p&gt;Andrew Schauer&lt;/p&gt;&lt;p&gt;Anna Wilson&lt;/p&gt;&lt;p&gt;Anne Smith&lt;/p&gt;&lt;p&gt;Antoine Ringard&lt;/p&gt;&lt;p&gt;&lt;i&gt;Anton Artemyev&lt;/i&gt;&lt;/p&gt;&lt;p&gt;Antonietta Capotondi&lt;/p&gt;&lt;p&gt;Antonio Costa&lt;/p&gt;&lt;p&gt;Arif Hussain&lt;/p&gt;&lt;p&gt;Armin Sorooshian&lt;/p&gt;&lt;p&gt;Ashraf Rateb&lt;/p&gt;&lt;p&gt;Ashutosh Tripathy&lt;/p&gt;&lt;p&gt;Austin Chadwick&lt;/p&gt;&lt;p&gt;Baibhav Srivastava&lt;/p&gt;&lt;p&gt;Bea Gallardo-Lacourt&lt;/p&gt;&lt;p&gt;Ben Randall&lt;/p&gt;&lt;p&gt;Benjamin Cook&lt;/p&gt;&lt;p&gt;Benjamin Getraer&lt;/p&gt;&lt;p&gt;Bettina Gier&lt;/p&gt;&lt;p&gt;Bin Zhou&lt;/p&gt;&lt;p&gt;&lt;i&gt;Binayak Mohantzy&lt;/i&gt;&lt;/p&gt;&lt;p&gt;Binbin Ni&lt;/p&gt;&lt;p&gt;Bjorn Stevens&lt;/p&gt;&lt;p&gt;Blaž Gasparini&lt;/p&gt;&lt;p&gt;Bo Qin&lt;/p&gt;&lt;p&gt;Brandon Schmandt&lt;/p&gt;&lt;p&gt;Brenhin Keller&lt;/p&gt;&lt;p&gt;C. R. Brown&lt;/p&gt;&lt;p&gt;Callum Shakespeare&lt;/p&gt;&lt;p&gt;Cameron Homeyer&lt;/p&gt;&lt;p&gt;Carlotta Dentico&lt;/p&gt;&lt;p&gt;Carol Arnosti&lt;/p&gt;&lt;p&gt;Cathy Hohenegger&lt;/p&gt;&lt;p&gt;Celso H. L. Silva-Junior&lt;/p&gt;&lt;p&gt;Charles Ichoku&lt;/p&gt;&lt;p&gt;Charles Luce&lt;/","PeriodicalId":100067,"journal":{"name":"AGU Advances","volume":"7 2","pages":""},"PeriodicalIF":8.3,"publicationDate":"2026-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2026AV002449","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147667940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Amazon River-Breeze Circulation Limits Detection of Aerosol-Cloud Interactions in Warm Clouds","authors":"Matthew W. Christensen,&nbsp;Adam C. Varble,&nbsp;Sheng-Lun Tai,&nbsp;Gala Wind,&nbsp;Kerry Meyer,&nbsp;Robert Holz,&nbsp;Steven Platnick,&nbsp;Jerome Fast","doi":"10.1029/2025AV002188","DOIUrl":"https://doi.org/10.1029/2025AV002188","url":null,"abstract":"<p>Increased aerosol concentrations can brighten low-level clouds and extend their lifetimes, but aerosol–cloud interactions (ACI) remain highly uncertain and difficult to quantify. We show that part of this uncertainty is caused by topographical influences on clouds, that is, those arising from land–water contrasts. This is demonstrated using satellite retrievals in regions with extensive river networks, such as the Amazon Basin. 15 years of MODerate resolution Imaging Spectroradiometer (MODIS) satellite data show cloud formation over the Amazon River basin is suppressed by 26% with warm low clouds above the river exhibiting a 22% smaller droplet effective radius and 18% higher droplet concentration (<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mi>N</mi>\u0000 <mi>d</mi>\u0000 </msub>\u0000 </mrow>\u0000 <annotation> ${N}_{d}$</annotation>\u0000 </semantics></math>) compared to adjacent land clouds. Thus, clouds above the river may <i>appear</i> polluted but are actually influenced by river-breeze circulations driven by the thermal contrast between the river and the surrounding land. These responses are robust in both wet and dry seasons, and tests using an improved MODIS retrieval product show cloud differences are unlikely due to retrieval artifacts. In situ measurements from the Green Ocean Amazon Experiment (GoAmazon) confirm that <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mi>N</mi>\u0000 <mi>d</mi>\u0000 </msub>\u0000 </mrow>\u0000 <annotation> ${N}_{d}$</annotation>\u0000 </semantics></math> is elevated above rivers and are also higher when carbon monoxide concentrations are elevated near the large city of Manaus. Lagrangian airmass tracking over Manaus shows that regional-scale river-breeze circulations impact <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mi>N</mi>\u0000 <mi>d</mi>\u0000 </msub>\u0000 </mrow>\u0000 <annotation> ${N}_{d}$</annotation>\u0000 </semantics></math> as much as the urban aerosol plume, complicating ACI attribution and highlighting the need to isolate land-surface effects to assess ACI in continental regions.</p>","PeriodicalId":100067,"journal":{"name":"AGU Advances","volume":"7 2","pages":""},"PeriodicalIF":8.3,"publicationDate":"2026-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025AV002188","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147666271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Amazon River-Breeze Circulation Limits Detection of Aerosol-Cloud Interactions in Warm Clouds","authors":"Matthew W. Christensen,&nbsp;Adam C. Varble,&nbsp;Sheng-Lun Tai,&nbsp;Gala Wind,&nbsp;Kerry Meyer,&nbsp;Robert Holz,&nbsp;Steven Platnick,&nbsp;Jerome Fast","doi":"10.1029/2025AV002188","DOIUrl":"https://doi.org/10.1029/2025AV002188","url":null,"abstract":"<p>Increased aerosol concentrations can brighten low-level clouds and extend their lifetimes, but aerosol–cloud interactions (ACI) remain highly uncertain and difficult to quantify. We show that part of this uncertainty is caused by topographical influences on clouds, that is, those arising from land–water contrasts. This is demonstrated using satellite retrievals in regions with extensive river networks, such as the Amazon Basin. 15 years of MODerate resolution Imaging Spectroradiometer (MODIS) satellite data show cloud formation over the Amazon River basin is suppressed by 26% with warm low clouds above the river exhibiting a 22% smaller droplet effective radius and 18% higher droplet concentration (<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mi>N</mi>\u0000 <mi>d</mi>\u0000 </msub>\u0000 </mrow>\u0000 <annotation> ${N}_{d}$</annotation>\u0000 </semantics></math>) compared to adjacent land clouds. Thus, clouds above the river may <i>appear</i> polluted but are actually influenced by river-breeze circulations driven by the thermal contrast between the river and the surrounding land. These responses are robust in both wet and dry seasons, and tests using an improved MODIS retrieval product show cloud differences are unlikely due to retrieval artifacts. In situ measurements from the Green Ocean Amazon Experiment (GoAmazon) confirm that <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mi>N</mi>\u0000 <mi>d</mi>\u0000 </msub>\u0000 </mrow>\u0000 <annotation> ${N}_{d}$</annotation>\u0000 </semantics></math> is elevated above rivers and are also higher when carbon monoxide concentrations are elevated near the large city of Manaus. Lagrangian airmass tracking over Manaus shows that regional-scale river-breeze circulations impact <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mi>N</mi>\u0000 <mi>d</mi>\u0000 </msub>\u0000 </mrow>\u0000 <annotation> ${N}_{d}$</annotation>\u0000 </semantics></math> as much as the urban aerosol plume, complicating ACI attribution and highlighting the need to isolate land-surface effects to assess ACI in continental regions.</p>","PeriodicalId":100067,"journal":{"name":"AGU Advances","volume":"7 2","pages":""},"PeriodicalIF":8.3,"publicationDate":"2026-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025AV002188","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147666276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detecting Regimes of Critical Zone Processes, Drivers and Predictability With a Data-Driven Framework","authors":"Allison E. Goodwell,&nbsp;Brian Saccardi,&nbsp;Ashlee Dere,&nbsp;Jennifer Druhan,&nbsp;Jinyu Wang,&nbsp;Lisa R. Welp,&nbsp;Andrew J. Stumpf,&nbsp;Erin Bauer,&nbsp;Steve Sargent,&nbsp;Praveen Kumar","doi":"10.1029/2025AV002098","DOIUrl":"https://doi.org/10.1029/2025AV002098","url":null,"abstract":"<p>In highly productive agricultural landscapes, human impacts combine with naturally variable climate conditions and geologic legacies to fundamentally alter critical zone (CZ) processes. For example, artificial drainage and fertilizer applications impact riverine transport of water and nutrients, and abrupt transitions in vegetation states impact land-atmosphere fluxes of water and energy. Subsystem components may switch from being nearly independent to tightly synchronized, and drivers may elicit non-linear or threshold responses. These shifts have implications for predictive understanding, but are challenging to identify and quantify. We present a flexible, data-driven framework that identifies temporal regimes in CZ behavior, associated with particular environmental drivers and modes of variability. We integrate unsupervised clustering, dimensionality reduction, and information-theoretic metrics to isolate temporal regimes and assess changes in drivers and predictability across several case studies. Specifically, we analyze high-frequency time-series data sets of root-soil gases, land-atmosphere fluxes, and river chemistry in intensively managed and more natural CZ study sites. Clusters and variability in these multivariate systems relate to rapid seasonal transitions in agricultural relative to prairie sites, and impacts of fertilizer timing on solute responses to events. Environmental drivers have variable explanatory power over system states that align with growing season, flows, or management. This study objectively detects dynamic transitions in CZ systems, and is more broadly applicable to any Earth system time-series data or model evaluation to detect behavioral regimes and shifts in predictability of complex systems.</p>","PeriodicalId":100067,"journal":{"name":"AGU Advances","volume":"7 2","pages":""},"PeriodicalIF":8.3,"publicationDate":"2026-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025AV002098","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147666317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detecting Regimes of Critical Zone Processes, Drivers and Predictability With a Data-Driven Framework","authors":"Allison E. Goodwell,&nbsp;Brian Saccardi,&nbsp;Ashlee Dere,&nbsp;Jennifer Druhan,&nbsp;Jinyu Wang,&nbsp;Lisa R. Welp,&nbsp;Andrew J. Stumpf,&nbsp;Erin Bauer,&nbsp;Steve Sargent,&nbsp;Praveen Kumar","doi":"10.1029/2025AV002098","DOIUrl":"https://doi.org/10.1029/2025AV002098","url":null,"abstract":"<p>In highly productive agricultural landscapes, human impacts combine with naturally variable climate conditions and geologic legacies to fundamentally alter critical zone (CZ) processes. For example, artificial drainage and fertilizer applications impact riverine transport of water and nutrients, and abrupt transitions in vegetation states impact land-atmosphere fluxes of water and energy. Subsystem components may switch from being nearly independent to tightly synchronized, and drivers may elicit non-linear or threshold responses. These shifts have implications for predictive understanding, but are challenging to identify and quantify. We present a flexible, data-driven framework that identifies temporal regimes in CZ behavior, associated with particular environmental drivers and modes of variability. We integrate unsupervised clustering, dimensionality reduction, and information-theoretic metrics to isolate temporal regimes and assess changes in drivers and predictability across several case studies. Specifically, we analyze high-frequency time-series data sets of root-soil gases, land-atmosphere fluxes, and river chemistry in intensively managed and more natural CZ study sites. Clusters and variability in these multivariate systems relate to rapid seasonal transitions in agricultural relative to prairie sites, and impacts of fertilizer timing on solute responses to events. Environmental drivers have variable explanatory power over system states that align with growing season, flows, or management. This study objectively detects dynamic transitions in CZ systems, and is more broadly applicable to any Earth system time-series data or model evaluation to detect behavioral regimes and shifts in predictability of complex systems.</p>","PeriodicalId":100067,"journal":{"name":"AGU Advances","volume":"7 2","pages":""},"PeriodicalIF":8.3,"publicationDate":"2026-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2025AV002098","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147666318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}