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Antonietta
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Antonietta
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ArticleObservational needs supporting marine ecosystems modeling and forecasting: from the global ocean to regional and coastal systems(Frontiers Media, 2019-10-15) Capotondi, Antonietta ; Jacox, Michael ; Bowler, Chris ; Kavanaugh, Maria T. ; Lehodey, Patrick ; Barrie, Daniel ; Brodie, Stephanie ; Chaffron, Samuel ; Cheng, Wei ; Dias, Daniela F. ; Eveillard, Damien ; Guidi, Lionel ; Iudicone, Daniele ; Lovenduski, Nicole S. ; Nye, Janet A. ; Ortiz, Ivonne ; Pirhalla, Douglas ; Pozo Buil, Mercedes ; Saba, Vincent S. ; Sheridan, Scott ; Siedlecki, Samantha A. ; Subramanian, Aneesh C. ; de Vargas, Colomban ; Di Lorenzo, Emanuele ; Doney, Scott C. ; Hermann, Albert J. ; Joyce, Terrence M. ; Merrifield, Mark ; Miller, Arthur J. ; Not, Fabrice ; Pesant, StephaneMany coastal areas host rich marine ecosystems and are also centers of economic activities, including fishing, shipping and recreation. Due to the socioeconomic and ecological importance of these areas, predicting relevant indicators of the ecosystem state on sub-seasonal to interannual timescales is gaining increasing attention. Depending on the application, forecasts may be sought for variables and indicators spanning physics (e.g., sea level, temperature, currents), chemistry (e.g., nutrients, oxygen, pH), and biology (from viruses to top predators). Many components of the marine ecosystem are known to be influenced by leading modes of climate variability, which provide a physical basis for predictability. However, prediction capabilities remain limited by the lack of a clear understanding of the physical and biological processes involved, as well as by insufficient observations for forecast initialization and verification. The situation is further complicated by the influence of climate change on ocean conditions along coastal areas, including sea level rise, increased stratification, and shoaling of oxygen minimum zones. Observations are thus vital to all aspects of marine forecasting: statistical and/or dynamical model development, forecast initialization, and forecast validation, each of which has different observational requirements, which may be also specific to the study region. Here, we use examples from United States (U.S.) coastal applications to identify and describe the key requirements for an observational network that is needed to facilitate improved process understanding, as well as for sustaining operational ecosystem forecasting. We also describe new holistic observational approaches, e.g., approaches based on acoustics, inspired by Tara Oceans or by landscape ecology, which have the potential to support and expand ecosystem modeling and forecasting activities by bridging global and local observations.
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ArticleUnderstanding ENSO diversity(American Meteorological Society, 2015-06) Capotondi, Antonietta ; Wittenberg, Andrew T. ; Newman, Matthew ; Di Lorenzo, Emanuele ; Yu, Jin-Yi ; Braconnot, Pascale ; Cole, Julia ; Dewitte, Boris ; Giese, Benjamin ; Guilyardi, Eric ; Jin, Fei-Fei ; Karnauskas, Kristopher B. ; Kirtman, Benjamin ; Lee, Tong ; Schneider, Niklas ; Xue, Yan ; Yeh, Sang-WookEl Niño–Southern Oscillation (ENSO) is a naturally occurring mode of tropical Pacific variability, with global impacts on society and natural ecosystems. While it has long been known that El Niño events display a diverse range of amplitudes, triggers, spatial patterns, and life cycles, the realization that ENSO’s impacts can be highly sensitive to this event-to-event diversity is driving a renewed interest in the subject. This paper surveys our current state of knowledge of ENSO diversity, identifies key gaps in understanding, and outlines some promising future research directions.
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ArticleENSO and Pacific decadal variability in the Community Climate System Model Version 4(American Meteorological Society, 2012-04-15) Deser, Clara ; Phillips, Adam S. ; Tomas, Robert A. ; Okumura, Yuko M. ; Alexander, Michael A. ; Capotondi, Antonietta ; Scott, James D. ; Kwon, Young-Oh ; Ohba, MasamichiThis study presents an overview of the El Niño–Southern Oscillation (ENSO) phenomenon and Pacific decadal variability (PDV) simulated in a multicentury preindustrial control integration of the NCAR Community Climate System Model version 4 (CCSM4) at nominal 1° latitude–longitude resolution. Several aspects of ENSO are improved in CCSM4 compared to its predecessor CCSM3, including the lengthened period (3–6 yr), the larger range of amplitude and frequency of events, and the longer duration of La Niña compared to El Niño. However, the overall magnitude of ENSO in CCSM4 is overestimated by ~30%. The simulated ENSO exhibits characteristics consistent with the delayed/recharge oscillator paradigm, including correspondence between the lengthened period and increased latitudinal width of the anomalous equatorial zonal wind stress. Global seasonal atmospheric teleconnections with accompanying impacts on precipitation and temperature are generally well simulated, although the wintertime deepening of the Aleutian low erroneously persists into spring. The vertical structure of the upper-ocean temperature response to ENSO in the north and south Pacific displays a realistic seasonal evolution, with notable asymmetries between warm and cold events. The model shows evidence of atmospheric circulation precursors over the North Pacific associated with the “seasonal footprinting mechanism,” similar to observations. Simulated PDV exhibits a significant spectral peak around 15 yr, with generally realistic spatial pattern and magnitude. However, PDV linkages between the tropics and extratropics are weaker than observed.
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ArticleAtmospheric convection and air-sea interactions over the tropical oceans: scientific progress, challenges, and opportunities(American Meteorological Society, 2020-03-10) Hagos, Samson ; Foltz, Gregory R. ; Zhang, Chidong ; Thompson, Elizabeth ; Seo, Hyodae ; Chen, Sue ; Capotondi, Antonietta ; Reed, Kevin A. ; DeMott, Charlotte ; Protat, AlainOver the past 30 years, the scientific community has made considerable progress in understanding and predicting tropical convection and air–sea interactions, thanks to sustained investments in extensive in situ and remote sensing observations, targeted field experiments, advances in numerical modeling, and vastly improved computational resources and observing technologies. Those investments would not have been fruitful as isolated advancements without the collaborative effort of the atmospheric convection and air–sea interaction research communities. In this spirit, a U.S.- and International CLIVAR–sponsored workshop on “Atmospheric convection and air–sea interactions over the tropical oceans” was held in the spring of 2019 in Boulder, Colorado. The 90 participants were observational and modeling experts from the atmospheric convection and air–sea interactions communities with varying degrees of experience, from early-career researchers and students to senior scientists. The presentations and discussions covered processes over the broad range of spatiotemporal scales (Fig. 1).
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ArticleSeasonal-to-interannual prediction of North American coastal marine ecosystems: forecast methods, mechanisms of predictability, and priority developments(Elsevier, 2020-02-20) Jacox, Michael ; Alexander, Michael A. ; Siedlecki, Samantha A. ; Chen, Ke ; Kwon, Young-Oh ; Brodie, Stephanie ; Ortiz, Ivonne ; Tommasi, Desiree ; Widlansky, Matthew J. ; Barrie, Daniel ; Capotondi, Antonietta ; Cheng, Wei ; Di Lorenzo, Emanuele ; Edwards, Christopher ; Fiechter, Jerome ; Fratantoni, Paula S. ; Hazen, Elliott L. ; Hermann, Albert J. ; Kumar, Arun ; Miller, Arthur J. ; Pirhalla, Douglas ; Pozo Buil, Mercedes ; Ray, Sulagna ; Sheridan, Scott ; Subramanian, Aneesh C. ; Thompson, Philip ; Thorne, Lesley ; Annamalai, Hariharasubramanian ; Aydin, Kerim ; Bograd, Steven ; Griffis, Roger B. ; Kearney, Kelly ; Kim, Hyemi ; Mariotti, Annarita ; Merrifield, Mark ; Rykaczewski, Ryan R.Marine ecosystem forecasting is an area of active research and rapid development. Promise has been shown for skillful prediction of physical, biogeochemical, and ecological variables on a range of timescales, suggesting potential for forecasts to aid in the management of living marine resources and coastal communities. However, the mechanisms underlying forecast skill in marine ecosystems are often poorly understood, and many forecasts, especially for biological variables, rely on empirical statistical relationships developed from historical observations. Here, we review statistical and dynamical marine ecosystem forecasting methods and highlight examples of their application along U.S. coastlines for seasonal-to-interannual (1–24 month) prediction of properties ranging from coastal sea level to marine top predator distributions. We then describe known mechanisms governing marine ecosystem predictability and how they have been used in forecasts to date. These mechanisms include physical atmospheric and oceanic processes, biogeochemical and ecological responses to physical forcing, and intrinsic characteristics of species themselves. In reviewing the state of the knowledge on forecasting techniques and mechanisms underlying marine ecosystem predictability, we aim to facilitate forecast development and uptake by (i) identifying methods and processes that can be exploited for development of skillful regional forecasts, (ii) informing priorities for forecast development and verification, and (iii) improving understanding of conditional forecast skill (i.e., a priori knowledge of whether a forecast is likely to be skillful). While we focus primarily on coastal marine ecosystems surrounding North America (and the U.S. in particular), we detail forecast methods, physical and biological mechanisms, and priority developments that are globally relevant.
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Working PaperDaily to decadal ecological forecasting along North American coastlines(Woods Hole Oceangraphic Institution, 2024-12-16) Capotondi, Antonietta ; Coles, Victoria J. ; Clayton, Sophie A. ; Friedrichs, Marjorie A. M. ; Gierach, Michelle ; Miller, Arthur J. ; Stock, Charles A.Coastal areas share unique intersections of large-scale climate variability and local hydrology, wetland, benthic and pelagic ecosystems, and anthropogenic pressures. Forecasting of harmful environmental conditions for planning, adaptation, and mitigation purposes is both complex and urgently needed. Ecological forecasting is the qualitative or quantitative projection of biogeochemical, organismal or ecosystem state variables and their drivers on timescales that can range from “now” to decades from now. Estimating hypoxia in Chesapeake Bay today, predicting acidity conditions in the Northeast Pacific in a few months, or projecting the depth of the Bering Sea nutricline in 2075 are all ecological forecasts relevant to planning, adaptation, and mitigation efforts. In 2022, the US CLIVAR and Ocean Carbon & Biogeochemistry (OCB) Programs convened a joint workshop to advance the development of US ecological forecasting. The workshop goals were to 1) identify sources of predictability of physical quantities relevant for marine ecosystems along US coastlines; 2) assess the observational needs of forecast systems and limitations due to gaps in understanding; and 3) promote the development of dynamical and statistical models suitable to meet the forecasting requirements. About 80 participants from over 40 US and international institutions joined this hybrid workshop for plenary talks and breakout discussions. Participants represented a diversity of career stages across academic institutions, government agencies, and non-government organizations. By working together, they collectively identified a path forward for a coordinated US ecological forecasting effort as detailed in this report.