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  • 1
    Publication Date: 2021-12-14
    Description: Extreme events have long been underestimated in the extent to which they shape the surface of our planet, our environment, its ecological integrity, and the sustainability of human society. Extreme events are by definition rarely observed, of significant impact and, as a result of their spatiotemporal range, not always easily predicted. Extremes may be short-term catastrophic events such as tsunamis, or long-term evolving events such as those linked to climate change; both modify the environment, producing irreversible changes or regime shifts. Whatever the driver that triggers the extreme event, the damages are often due to a combination of several processes and their impacts can affect large areas with secondary events (domino effect), whose effects in turn may persist well beyond the duration of the trigger event itself. Early studies of extreme events were limited to opportunistic approaches: observations were made within the context of naturally occurring events with high societal impact. Given that climate change is now moving us out of a relatively static climate regime during the development of human civilization, extreme events are now a function of underlying climate shifts overlain by catastrophic processes. Their impacts are often due to synergistic factors, all relevant in understanding process dynamics; therefore, an integrated methodology has become essential to enhance the reliability of new assessments and to develop strategies to mitigate societal impacts. Here we summarize the current state of extreme event monitoring in the marine system, highlighting the advantages of a multidisciplinary approach using Research Infrastructures for providing the temporal and spatial resolution required to monitor Earth processes and enhance assessment of associated impacts.
    Description: Published
    Description: 626668
    Description: 3A. Geofisica marina e osservazioni multiparametriche a fondo mare
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 2
    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
    Repository Name: Woods Hole Open Access Server
    Type: Article
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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 Journal of Climate 34(7), (2021): 2473-2490, https://doi.org/10.1175/JCLI-D-20-0625.1.
    Description: This study uses sea surface salinity (SSS) as an additional precursor for improving the prediction of summer [December–February (DJF)] rainfall over northeastern Australia. From a singular value decomposition between SSS of prior seasons and DJF rainfall, we note that SSS of the Indo-Pacific warm pool region [SSSP (150°E–165°W and 10°S–10°N) and SSSI (50°–95°E and 10°S–10°N)] covaries with Australian rainfall, particularly in the northeast region. Composite analysis that is based on high or low SSS events in the SSSP and SSSI regions is performed to understand the physical links between the SSS and the atmospheric moisture originating from the regions of anomalously high or low, respectively, SSS and precipitation over Australia. The composites show the signature of co-occurring La Niña and negative Indian Ocean dipole with anomalously wet conditions over Australia and conversely show the signature of co-occurring El Niño and positive Indian Ocean dipole with anomalously dry conditions there. During the high SSS events of the SSSP and SSSI regions, the convergence of incoming moisture flux results in anomalously wet conditions over Australia with a positive soil moisture anomaly. Conversely, during the low SSS events of the SSSP and SSSI regions, the divergence of incoming moisture flux results in anomalously dry conditions over Australia with a negative soil moisture anomaly. We show from the random-forest regression analysis that the local soil moisture, El Niño–Southern Oscillation (ENSO), and SSSP are the most important precursors for the northeast Australian rainfall whereas for the Brisbane region ENSO, SSSP, and the Indian Ocean dipole are the most important. The prediction of Australian rainfall using random-forest regression shows an improvement by including SSS from the prior season. This evidence suggests that sustained observations of SSS can improve the monitoring of the Australian regional hydrological cycle.
    Description: This research is funded through the Earth System and Climate Change Hub of the Australian government’s National Environmental Science Programme. The assistance of computing resources from the National Computational Infrastructure supported by the Australian Government is acknowledged. Author Ummenhofer acknowledges support from the U.S. National Science Foundation under Grant OCE-1663704. Author Feng was supported by the Centre for Southern Hemisphere Oceans Research (CSHOR), which is a joint initiative between the Qingdao National Laboratory for Marine Science and Technology (QNLM), CSIRO, University of New South Wales, and the University of Tasmania. The authors also acknowledge Dr. Manali Pal for technical discussion on machine learning.
    Description: 2021-09-01
    Keywords: ENSO ; Flood events ; Hydrologic cycle ; Machine learning ; Rainfall ; Salinity ; Seasonal forecasting ; Soil moisture
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 4
    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 Journal of Climate 33(15), (2020): 6707-6730, https://doi.org/10.1175/JCLI-D-19-0579.1.
    Description: The long-term trend of sea surface salinity (SSS) reveals an intensification of the global hydrological cycle due to human-induced climate change. This study demonstrates that SSS variability can also be used as a measure of terrestrial precipitation on interseasonal to interannual time scales, and to locate the source of moisture. Seasonal composites during El Niño–Southern Oscillation/Indian Ocean dipole (ENSO/IOD) events are used to understand the variations of moisture transport and precipitation over Australia, and their association with SSS variability. As ENSO/IOD events evolve, patterns of positive or negative SSS anomaly emerge in the Indo-Pacific warm pool region and are accompanied by atmospheric moisture transport anomalies toward Australia. During co-occurring La Niña and negative IOD events, salty anomalies around the Maritime Continent (north of Australia) indicate freshwater export and are associated with a significant moisture transport that converges over Australia to create anomalous wet conditions. In contrast, during co-occurring El Niño and positive IOD events, a moisture transport divergence anomaly over Australia results in anomalous dry conditions. The relationship between SSS and atmospheric moisture transport also holds for pure ENSO/IOD events but varies in magnitude and spatial pattern. The significant pattern correlation between the moisture flux divergence and SSS anomaly during the ENSO/IOD events highlights the associated ocean–atmosphere coupling. A case study of the extreme hydroclimatic events of Australia (e.g., the 2010/11 Brisbane flood) demonstrates that the changes in SSS occur before the peak of ENSO/IOD events. This raises the prospect that tracking of SSS variability could aid the prediction of Australian rainfall.
    Description: This research is funded through the Earth System and Climate Change Hub of the Australian government’s National Environmental Science Programme. The assistance of computing resources from the National Computational Infrastructure supported by the Australian Government is acknowledged. CCU acknowledges support from the U.S. National Science Foundation under Grant OCE-1663704. MF was supported by the by Centre for Southern Hemisphere Oceans Research (CSHOR), which is a joint initiative between the Qingdao National Laboratory for Marine Science and Technology (QNLM), CSIRO, University of New South Wales and University of Tasmania. The authors wish to acknowledge PyFerret (https://ferret.pmel.noaa.gov/Ferret/) and the Cimate Data Operators (https://code.mpimet.mpg.de/projects/cdo/) for the data analysis and graphical representations in this paper.
    Keywords: Atmosphere-ocean interaction ; El Nino ; Extreme events ; La Nina ; Precipitation ; Salinity
    Repository Name: Woods Hole Open Access Server
    Type: Article
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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(8), (2020): E1397-E1412, https://doi.org/10.1175/BAMS-D-19-0278.1.
    Description: Sea surface temperatures (SSTs) north of Australia in the Indonesian–Australian Basin are significantly influenced by Madden–Julian oscillation (MJO), an eastward-moving atmospheric disturbance that traverses the globe in the tropics. The region also has large-amplitude diurnal SST variations, which may influence the air–sea heat and moisture fluxes, that provide feedback to the MJO evolution. During the 2018/19 austral summer, a field campaign aiming to better understand the influences of air–sea coupling on the MJO was conducted north of Australia in the Indonesian–Australian Basin. Surface meteorology from buoy observations and upper-ocean data from autonomous fast-profiling float observations were collected. Two MJO convective phases propagated eastward across the region in mid-December 2018 and late January 2019 and the second MJO was in conjunction with a tropical cyclone development. Observations showed that SST in the region was rather sensitive to the MJO forcing. Air–sea heat fluxes warmed the SST throughout the 2018/19 austral summer, punctuated by the MJO activities, with a 2°–3°C drop in SST during the two MJO events. Substantial diurnal SST variations during the suppressed phases of the MJOs were observed, and the near-surface thermal stratifications provided positive feedback for the peak diurnal SST amplitude, which may be a mechanism to influence the MJO evolution. Compared to traditionally vessel-based observation programs, we have relied on fast-profiling floats as the main vehicle in measuring the upper-ocean variability from diurnal to the MJO time scales, which may pave the way for using cost-effective technology in similar process studies.
    Description: MF, SW, and JH are supported by the Centre for Southern Hemisphere Oceans Research (CSHOR), which is a joint initiative between the Qingdao National Laboratory for Marine Science and Technology (QNLM), CSIRO, University of New South Wales, and University of Tasmania. Y. Duan is supported by National Natural Science Foundation of China (41706032) and Basic Scientific Fund for National Public Research Institutes of China (2019Q03).
    Repository Name: Woods Hole Open Access Server
    Type: Article
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