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  • 1
    Publication Date: 2022-05-25
    Description: Author Posting. © American Meteorological Society, 2014. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 27 (2014): 8422–8443, doi:10.1175/JCLI-D-14-00141.1.
    Description: This study quantifies, from a systematic set of regional ocean–atmosphere coupled model simulations employing various coupling intervals, the effect of subdaily sea surface temperature (SST) variability on the onset and intensity of Madden–Julian oscillation (MJO) convection in the Indian Ocean. The primary effect of diurnal SST variation (dSST) is to raise time-mean SST and latent heat flux (LH) prior to deep convection. Diurnal SST variation also strengthens the diurnal moistening of the troposphere by collocating the diurnal peak in LH with those of SST. Both effects enhance the convection such that the total precipitation amount scales quasi-linearly with preconvection dSST and time-mean SST. A column-integrated moist static energy (MSE) budget analysis confirms the critical role of diurnal SST variability in the buildup of column MSE and the strength of MJO convection via stronger time-mean LH and diurnal moistening. Two complementary atmosphere-only simulations further elucidate the role of SST conditions in the predictive skill of MJO. The atmospheric model forced with the persistent initial SST, lacking enhanced preconvection warming and moistening, produces a weaker and delayed convection than the diurnally coupled run. The atmospheric model with prescribed daily-mean SST from the coupled run, while eliminating the delayed peak, continues to exhibit weaker convection due to the lack of strong moistening on a diurnal basis. The fact that time-evolving SST with a diurnal cycle strongly influences the onset and intensity of MJO convection is consistent with previous studies that identified an improved representation of diurnal SST as a potential source of MJO predictability.
    Description: The authors gratefully acknowledge support from the Office of Naval Research (N00014-13-1-0133 and N00014-13-1-0139) and National Science Foundation EaSM-3 (OCE-1419235). HS especially thanks the Penzance Endowed Fund for their support of Assistant Scientists at WHOI.
    Description: 2015-05-15
    Keywords: Deep convection ; Diurnal effects ; Madden-Julian oscillation ; Air-sea interaction ; Numerical weather prediction/forecasting ; Regional models
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  • 2
    Publication Date: 2022-05-25
    Description: © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Jacox, M. G., Alexander, M. A., Siedlecki, S., Chen, K., Kwon, Y., Brodie, S., Ortiz, I., Tommasi, D., Widlansky, M. J., Barrie, D., Capotondi, A., Cheng, W., Di Lorenzo, E., Edwards, C., Fiechter, J., Fratantoni, P., Hazen, E. L., Hermann, A. J., Kumar, A., Miller, A. J., Pirhalla, D., Buil, M. P., Ray, S., Sheridan, S. C., Subramanian, A., Thompson, P., Thorne, L., Annamalai, H., Aydin, K., Bograd, S. J., Griffis, R. B., Kearney, K., Kim, H., Mariotti, A., Merrifield, M., & Rykaczewski, R. Seasonal-to-interannual prediction of North American coastal marine ecosystems: forecast methods, mechanisms of predictability, and priority developments. Progress in Oceanography, 183, (2020): 102307, doi:10.1016/j.pocean.2020.102307.
    Description: 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.
    Description: This study was supported by the NOAA Climate Program Office’s Modeling, Analysis, Predictions, and Projections (MAPP) program through grants NA17OAR4310108, NA17OAR4310112, NA17OAR4310111, NA17OAR4310110, NA17OAR4310109, NA17OAR4310104, NA17OAR4310106, and NA17OAR4310113. This paper is a product of the NOAA/MAPP Marine Prediction Task Force.
    Keywords: Prediction ; Predictability ; Forecast ; Ecological forecast ; Mechanism ; Seasonal ; Interannual ; Large marine ecosystem
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  • 3
    Publication Date: 2022-05-27
    Description: Author Posting. © American Meteorological Society, 2021. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 102(1), (2021): E99-E122, https://doi.org/10.1175/BAMS-D-19-0005.1.
    Description: The Red Sea, home to the second-longest coral reef system in the world, is a vital resource for the Kingdom of Saudi Arabia. The Red Sea provides 90% of the Kingdom’s potable water by desalinization, supporting tourism, shipping, aquaculture, and fishing industries, which together contribute about 10%–20% of the country’s GDP. All these activities, and those elsewhere in the Red Sea region, critically depend on oceanic and atmospheric conditions. At a time of mega-development projects along the Red Sea coast, and global warming, authorities are working on optimizing the harnessing of environmental resources, including renewable energy and rainwater harvesting. All these require high-resolution weather and climate information. Toward this end, we have undertaken a multipronged research and development activity in which we are developing an integrated data-driven regional coupled modeling system. The telescopically nested components include 5-km- to 600-m-resolution atmospheric models to address weather and climate challenges, 4-km- to 50-m-resolution ocean models with regional and coastal configurations to simulate and predict the general and mesoscale circulation, 4-km- to 100-m-resolution ecosystem models to simulate the biogeochemistry, and 1-km- to 50-m-resolution wave models. In addition, a complementary probabilistic transport modeling system predicts dispersion of contaminant plumes, oil spill, and marine ecosystem connectivity. Advanced ensemble data assimilation capabilities have also been implemented for accurate forecasting. Resulting achievements include significant advancement in our understanding of the regional circulation and its connection to the global climate, development, and validation of long-term Red Sea regional atmospheric–oceanic–wave reanalyses and forecasting capacities. These products are being extensively used by academia, government, and industry in various weather and marine studies and operations, environmental policies, renewable energy applications, impact assessment, flood forecasting, and more.
    Description: The development of the Red Sea modeling system is being supported by the Virtual Red Sea Initiative and the Competitive Research Grants (CRG) program from the Office of Sponsored Research at KAUST, Saudi Aramco Company through the Saudi ARAMCO Marine Environmental Center at KAUST, and by funds from KAEC, NEOM, and RSP through Beacon Development Company at KAUST.
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  • 4
    Publication Date: 2022-05-27
    Description: Author Posting. © American Meteorological Society, 2021. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 102(10), (2021): E1936–E1951, https://doi.org/10.1175/BAMS-D-20-0113.1.
    Description: In the Bay of Bengal, the warm, dry boreal spring concludes with the onset of the summer monsoon and accompanying southwesterly winds, heavy rains, and variable air–sea fluxes. Here, we summarize the 2018 monsoon onset using observations collected through the multinational Monsoon Intraseasonal Oscillations in the Bay of Bengal (MISO-BoB) program between the United States, India, and Sri Lanka. MISO-BoB aims to improve understanding of monsoon intraseasonal variability, and the 2018 field effort captured the coupled air–sea response during a transition from active-to-break conditions in the central BoB. The active phase of the ∼20-day research cruise was characterized by warm sea surface temperature (SST 〉 30°C), cold atmospheric outflows with intermittent heavy rainfall, and increasing winds (from 2 to 15 m s−1). Accumulated rainfall exceeded 200 mm with 90% of precipitation occurring during the first week. The following break period was both dry and clear, with persistent 10–12 m s−1 wind and evaporation of 0.2 mm h−1. The evolving environmental state included a deepening ocean mixed layer (from ∼20 to 50 m), cooling SST (by ∼1°C), and warming/drying of the lower to midtroposphere. Local atmospheric development was consistent with phasing of the large-scale intraseasonal oscillation. The upper ocean stores significant heat in the BoB, enough to maintain SST above 29°C despite cooling by surface fluxes and ocean mixing. Comparison with reanalysis indicates biases in air–sea fluxes, which may be related to overly cool prescribed SST. Resolution of such biases offers a path toward improved forecasting of transition periods in the monsoon.
    Description: This work was supported through the U.S. Office of Naval Research’s Departmental Research Initiative: Monsoon Intraseasonal Oscillations in the Bay of Bengal, the Indian Ministry of Earth Science’s Ocean Mixing and Monsoons Program, and the Sri Lankan National Aquatic Resources Research and Development Agency. We thank the Captain and crew of the R/V Thompson for their help in data collection. Surface atmospheric fields included fluxes were quality controlled and processed by the Boundary Layer Observations and Processes Team within the NOAA Physical Sciences Laboratory. Forecast analysis was completed by India Meteorological Department. Drone image was taken by Shreyas Kamat with annotations by Gualtiero Spiro Jaeger. We also recognize the numerous researchers who supported cruise- and land-based measurements. This work represents Lamont-Doherty Earth Observatory contribution number 8503, and PMEL contribution number 5193.
    Description: 2022-04-01
    Keywords: Atmosphere-ocean interaction ; Monsoons ; In situ atmospheric observations ; In situ oceanic observations
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  • 5
    Publication Date: 2022-05-26
    Description: Author Posting. © American Meteorological Society, 2020. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 101(11), (2020): E1891-E1913, https://doi.org/10.1175/BAMS-D-19-0209.1
    Description: The Indian Ocean Observing System (IndOOS), established in 2006, is a multinational network of sustained oceanic measurements that underpin understanding and forecasting of weather and climate for the Indian Ocean region and beyond. Almost one-third of humanity lives around the Indian Ocean, many in countries dependent on fisheries and rain-fed agriculture that are vulnerable to climate variability and extremes. The Indian Ocean alone has absorbed a quarter of the global oceanic heat uptake over the last two decades and the fate of this heat and its impact on future change is unknown. Climate models project accelerating sea level rise, more frequent extremes in monsoon rainfall, and decreasing oceanic productivity. In view of these new scientific challenges, a 3-yr international review of the IndOOS by more than 60 scientific experts now highlights the need for an enhanced observing network that can better meet societal challenges, and provide more reliable forecasts. Here we present core findings from this review, including the need for 1) chemical, biological, and ecosystem measurements alongside physical parameters; 2) expansion into the western tropics to improve understanding of the monsoon circulation; 3) better-resolved upper ocean processes to improve understanding of air–sea coupling and yield better subseasonal to seasonal predictions; and 4) expansion into key coastal regions and the deep ocean to better constrain the basinwide energy budget. These goals will require new agreements and partnerships with and among Indian Ocean rim countries, creating opportunities for them to enhance their monitoring and forecasting capacity as part of IndOOS-2.
    Description: We thank the World Climate Research Programme (WCRP) and its core project on Climate and Ocean: Variability, Predictability and Change (CLIVAR), the Indian Ocean Global Ocean Observing System (IOGOOS), the Intergovernmental Oceanographic Commission of UNESCO (IOC-UNESCO), the Integrated Marine Biosphere Research (IMBeR) project, the U.S. National Oceanic and Atmospheric Administration (NOAA), and the International Union of Geodesy and Geophysics (IUGG) for providing the financial support to bring international scientists together to conduct this review. We thank the members of the independent review board that provided detailed feedbacks on the review report that is summarized in this article: P. E. Dexter, M. Krug, J. McCreary, R. Matear, C. Moloney, and S. Wijffels. PMEL Contribution 5041. C. Ummenhofer acknowledges support from The Andrew W. Mellon Foundation Award for Innovative Research.
    Description: 2021-05-01
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  • 6
    Publication Date: 2022-05-26
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Hermes, J. C., Masumoto, Y., Beal, L. M., Roxy, M. K., Vialard, J., Andres, M., Annamalai, H., Behera, S., D'Adamo, N., Doi, T., Peng, M., Han, W., Hardman-Mountford, N., Hendon, H., Hood, R., Kido, S., Lee, C., Lees, T., Lengaigne, M., Li, J., Lumpkin, R., Navaneeth, K. N., Milligan, B., McPhaden, M. J., Ravichandran, M., Shinoda, T., Singh, A., Sloyan, B., Strutton, P. G., Subramanian, A. C., Thurston, S., Tozuka, T., Ummenhofer, C. C., Unnikrishnan, A. S., Venkatesan, R., Wang, D., Wiggert, J., Yu, L., & Yu, W. (2019). A sustained ocean observing system in the Indian Ocean for climate related scientific knowledge and societal needs. Frontiers in Marine Science, 6, (2019): 355, doi: 10.3389/fmars.2019.00355.
    Description: The Indian Ocean is warming faster than any of the global oceans and its climate is uniquely driven by the presence of a landmass at low latitudes, which causes monsoonal winds and reversing currents. The food, water, and energy security in the Indian Ocean rim countries and islands are intrinsically tied to its climate, with marine environmental goods and services, as well as trade within the basin, underpinning their economies. Hence, there are a range of societal needs for Indian Ocean observation arising from the influence of regional phenomena and climate change on, for instance, marine ecosystems, monsoon rains, and sea-level. The Indian Ocean Observing System (IndOOS), is a sustained observing system that monitors basin-scale ocean-atmosphere conditions, while providing flexibility in terms of emerging technologies and scientificand societal needs, and a framework for more regional and coastal monitoring. This paper reviews the societal and scientific motivations, current status, and future directions of IndOOS, while also discussing the need for enhanced coastal, shelf, and regional observations. The challenges of sustainability and implementation are also addressed, including capacity building, best practices, and integration of resources. The utility of IndOOS ultimately depends on the identification of, and engagement with, end-users and decision-makers and on the practical accessibility and transparency of data for a range of products and for decision-making processes. Therefore we highlight current progress, issues and challenges related to end user engagement with IndOOS, as well as the needs of the data assimilation and modeling communities. Knowledge of the status of the Indian Ocean climate and ecosystems and predictability of its future, depends on a wide range of socio-economic and environmental data, a significant part of which is provided by IndOOS.
    Description: This work was supported by the PMEL contribution no. 4934.
    Keywords: Indian Ocean ; sustained observing system ; IndOOS ; data ; end-user connections and applications ; regional observing system ; interdisciplinary ; integration
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  • 7
    Publication Date: 2022-05-27
    Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Sun, R., Subramanian, A. C., Cornuelle, B. D., Mazloff, M. R., Miller, A. J., Ralph, F. M., Seo, H., & Hoteit, I. The role of air-sea interactions in atmospheric rivers: Case studies using the SKRIPS regional coupled model. Journal of Geophysical Research: Atmospheres, 126(6), (2021): e2020JD032885, https://doi.org/10.1029/2020JD032885.
    Description: Atmospheric rivers (ARs) play a key role in California's water supply and are responsible for most of the extreme precipitation and major flooding along the west coast of North America. Given the high societal impact, it is critical to improve our understanding and prediction of ARs. This study uses a regional coupled ocean–atmosphere modeling system to make hindcasts of ARs up to 14 days. Two groups of coupled runs are highlighted in the comparison: (1) ARs occurring during times with strong sea surface temperature (SST) cooling and (2) ARs occurring during times with weak SST cooling. During the events with strong SST cooling, the coupled model simulates strong upward air–sea heat fluxes associated with ARs; on the other hand, when the SST cooling is weak, the coupled model simulates downward air–sea heat fluxes in the AR region. Validation data shows that the coupled model skillfully reproduces the evolving SST, as well as the surface turbulent heat transfers between the ocean and atmosphere. The roles of air–sea interactions in AR events are investigated by comparing coupled model hindcasts to hindcasts made using persistent SST. To evaluate the influence of the ocean on ARs we analyze two representative variables of AR intensity, the vertically integrated water vapor (IWV) and integrated vapor transport (IVT). During strong SST cooling AR events the simulated IWV is improved by about 12% in the coupled run at lead times greater than one week. For IVT, which is about twice more variable, the improvement in the coupled run is about 5%.
    Description: The authors gratefully acknowledge the research funding (grant number: OSR-2-16-RPP-3268.02) from KAUST (King Abdullah University of Science and Technology). The authors also appreciate the computational resources on supercomputer Shaheen II and the assistance provided by KAUST Supercomputer Laboratory. Additional funding from the NSF (OCE2022846, and OCE2022868) and the National Oceanic and Atmospheric Administration (MAPP NA17OAR4310106 and NA17OAR4310255) is also greatly appreciated. This study is also supported by the U.S. Army Corps of Engineers (USACE)-Cooperative Ecosystem Studies Unit (CESU) as part of Forecast Informed Reservoir Operations (FIRO) under grant W912HZ-15-2-0019. The authors thank Caroline Papadopoulos for important technical support when installing software and using the Shaheen II cluster.
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  • 8
    Publication Date: 2022-10-26
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Boas, A. B. V., Ardhuin, F., Ayet, A., Bourassa, M. A., Brandt, P., Chapron, B., Cornuelle, B. D., Farrar, J. T., Fewings, M. R., Fox-Kemper, B., Gille, S. T., Gommenginger, C., Heimbach, P., Hell, M. C., Li, Q., Mazloff, M. R., Merrifield, S. T., Mouche, A., Rio, M. H., Rodriguez, E., Shutler, J. D., Subramanian, A. C., Terrill, E. J., Tsamados, M., Ubelmann, C., & van Sebille, E. Integrated observations of global surface winds, currents, and waves: Requirements and challenges for the next decade. Frontiers in Marine Science, 6, (2019): 425, doi:10.3389/fmars.2019.00425.
    Description: Ocean surface winds, currents, and waves play a crucial role in exchanges of momentum, energy, heat, freshwater, gases, and other tracers between the ocean, atmosphere, and ice. Despite surface waves being strongly coupled to the upper ocean circulation and the overlying atmosphere, efforts to improve ocean, atmospheric, and wave observations and models have evolved somewhat independently. From an observational point of view, community efforts to bridge this gap have led to proposals for satellite Doppler oceanography mission concepts, which could provide unprecedented measurements of absolute surface velocity and directional wave spectrum at global scales. This paper reviews the present state of observations of surface winds, currents, and waves, and it outlines observational gaps that limit our current understanding of coupled processes that happen at the air-sea-ice interface. A significant challenge for the coming decade of wind, current, and wave observations will come in combining and interpreting measurements from (a) wave-buoys and high-frequency radars in coastal regions, (b) surface drifters and wave-enabled drifters in the open-ocean, marginal ice zones, and wave-current interaction “hot-spots,” and (c) simultaneous measurements of absolute surface currents, ocean surface wind vector, and directional wave spectrum from Doppler satellite sensors.
    Description: AV was funded by NASA Earth and Space Science Fellowship award number 80NSSC17K0326. MB was funded by NOAA (FundRef number 100007298) through the NGI (grant number 18-NGI3-42). SG was funded by NASA grants NNX16AH67G, NNX14A078G, NNX17AH53G, and 80NSSC19K0059. MT acknowledges support from the Natural Environment Research Council (grant number NE/R000654/1). MT, MR, JS, and EvS were partially funded by the SKIM Mission Science Study (SKIM-SciSoc) project ESA RFP 3-15456/18/NL/CT/gp. AA was supported by DGA grant No D0456JE075 and the French Brittany Regional Council. MF was supported by NASA Ocean Vector Winds Science Team Grant 80NSSC18K1611 and Jet Propulsion Laboratory/CalTech subcontract 1531731. FA, BC, and AM were supported by ESA under the Sea State CCI project, with additional support from CNES and ANR grants for ISblue (ANR-17-EURE-0015) and LabexMER (ANR-10-LABX-19). MZ was funded by NASA (grant number NNX16AH67G).
    Keywords: Air-sea interactions ; Doppler oceanography from space ; Surface waves ; Absolute surface velocity ; Ocean surface winds
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  • 9
    Publication Date: 2022-10-26
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Subramanian, A. C., Balmaseda, M. A., Centurioni, L., Chattopadhyay, R., Cornuelle, B. D., DeMott, C., Flatau, M., Fujii, Y., Giglio, D., Gille, S. T., Hamill, T. M., Hendon, H., Hoteit, I., Kumar, A., Lee, J., Lucas, A. J., Mahadevan, A., Matsueda, M., Nam, S., Paturi, S., Penny, S. G., Rydbeck, A., Sun, R., Takaya, Y., Tandon, A., Todd, R. E., Vitart, F., Yuan, D., & Zhang, C. Ocean observations to improve our understanding, modeling, and forecasting of subseasonal-to-seasonal variability. Frontiers in Marine Science, 6, (2019): 427, doi:10.3389/fmars.2019.00427.
    Description: Subseasonal-to-seasonal (S2S) forecasts have the potential to provide advance information about weather and climate events. The high heat capacity of water means that the subsurface ocean stores and re-releases heat (and other properties) and is an important source of information for S2S forecasts. However, the subsurface ocean is challenging to observe, because it cannot be measured by satellite. Subsurface ocean observing systems relevant for understanding, modeling, and forecasting on S2S timescales will continue to evolve with the improvement in technological capabilities. The community must focus on designing and implementing low-cost, high-value surface and subsurface ocean observations, and developing forecasting system capable of extracting their observation potential in forecast applications. S2S forecasts will benefit significantly from higher spatio-temporal resolution data in regions that are sources of predictability on these timescales (coastal, tropical, and polar regions). While ENSO has been a driving force for the design of the current observing system, the subseasonal time scales present new observational requirements. Advanced observation technologies such as autonomous surface and subsurface profiling devices as well as satellites that observe the ocean-atmosphere interface simultaneously can lead to breakthroughs in coupled data assimilation (CDA) and coupled initialization for S2S forecasts. These observational platforms should also be tested and evaluated in ocean observation sensitivity experiments with current and future generation CDA and S2S prediction systems. Investments in the new ocean observations as well as model and DA system developments can lead to substantial returns on cost savings from disaster mitigation as well as socio–economic decisions that use S2S forecast information.
    Description: AS was funded by NOAA Climate Variability and Prediction Program (NA14OAR4310276) and the NSF Earth System Modeling Program (OCE1419306). CD was funded by NA16OAR4310094. SG and DG were funded by NASA awards NNX14AO78G and 80NSSC19K0059. DY was supported by NSFC (91858204, 41720104008, and 41421005).
    Keywords: Subseasonal ; Seasonal ; Predictions ; Air-sea interaction ; Satellite ; Argo ; Gliders ; Drifters
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  • 10
    Publication Date: 2022-10-26
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Capotondi, A., Jacox, M., Bowler, C., Kavanaugh, M., Lehodey, P., Barrie, D., Brodie, S., Chaffron, S., Cheng, W., Dias, D. F., Eveillard, D., Guidi, L., Iudicone, D., Lovenduski, N. S., Nye, J. A., Ortiz, I., Pirhalla, D., Buil, M. P., Saba, V., Sheridan, S., Siedlecki, S., Subramanian, A., de Vargas, C., Di Lorenzo, E., Doney, S. C., Hermann, A. J., Joyce, T., Merrifield, M., Miller, A. J., Not, F., & Pesant, S. Observational needs supporting marine ecosystems modeling and forecasting: from the global ocean to regional and coastal systems. Frontiers in Marine Science, 6, (2019): 623, doi:10.3389/fmars.2019.00623.
    Description: Many 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.
    Description: This study was supported by the NOAA’s Climate Program Office’s Modeling, Analysis, Predictions, and Projections (MAPP) Program through grants NA17OAR4310106, NA17OAR4310104, NA17OAR4310108, NA17OAR4310109, NA17OAR4310110, NA17OAR4310111, NA17OAR4310112, and NA17OAR4310113. This manuscript is a product of the NOAA/MAPP Marine Prediction Task Force. The Tara Oceans consortium acknowledges support from the CNRS Research Federation FR2022 Global Ocean Systems Ecology and Evolution, and OCEANOMICS (grant agreement ‘Investissement d’Avenir’ ANR-11-BTBR-0008). This is article number 95 of the Tara Oceans consortium. MK and SD acknowledge support from NASA grant NNX14AP62A “National Marine Sanctuaries as Sentinel Sites for a Demonstration Marine Biodiversity Observation Network (MBON)” funded under the National Ocean Partnership Program (NOPP RFP NOAA-NOS-IOOS-2014-2003803 in partnership between NOAA, BOEM, and NASA), and the NOAA Integrated Ocean Observing System (IOOS) Program Office. WC, IO, and AH acknowledge partial support from the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) under NOAA Cooperative Agreement NA15OAR4320063, Contribution No. 2019-1029. This study received support from the European H2020 International Cooperation project MESOPP (Mesopelagic Southern Ocean Prey and Predators), grant agreement no. 692173.
    Keywords: Marine ecosystems ; Modeling and forecasting ; Seascapes ; Genetics ; Acoustics
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