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  • 1
    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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  • 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 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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  • 3
    Publication Date: 2022-10-26
    Description: © The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Rathore, S., Goyal, R., Jangir, B., Ummenhofer, C., Feng, M., & Mishra, M. Interactions between a marine heatwave and tropical cyclone Amphan in the Bay of Bengal in 2020. Frontiers in Climate, 4, (2022): 861477, https://doi.org/10.3389/fclim.2022.861477.
    Description: Interactions are diagnosed between a marine heatwave (MHW) event and tropical super cyclone Amphan in the Bay of Bengal. In May 2020, an MHW developed in the Bay of Bengal driven by coupled ocean-atmosphere processes which included shoaling of the mixed layer depth due to reduced wind speed, increased net surface shortwave radiation flux into the ocean, increased upper ocean stratification, and increased sub-surface warming. Ocean temperature, rather than salinity, dominated the stratification that contributed to the MHW development and the subsurface ocean warming that also increased tropical cyclone heat potential. The presence of this strong MHW with sea surface temperature anomalies 〉2.5°C in the western Bay of Bengal coincided with the cyclone track and facilitated the rapid intensification of tropical cyclone Amphan to a super cyclone in just 24 h. This rapid intensification of a short-lived tropical cyclone, with a lifespan of 5 days over the ocean, is unprecedented in the Bay of Bengal during the pre-monsoon period (March-May). As the cyclone approached landfall in northern India, the wind-induced mixing deepened the mixed layer, cooled the ocean's surface, and reduced sub-surface warming in the bay, resulting in the demise of the MHW. This study provides new perspectives on the interactions between MHWs and tropical cyclones that could aid in improving the current understanding of compound extreme events that have severe socio-economic consequences in affected countries.
    Description: CU acknowledges support from the James E. and Barbara V. Moltz Fellowship for Climate-Related Research and the Independent Research & Development Program at WHOI. MF 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.
    Keywords: Compound extreme events ; Marine heatwave ; Tropical cyclone ; Amphan ; Fani ; Super cyclone ; Rapid intensification ; Extremely severe cyclone
    Repository Name: Woods Hole Open Access Server
    Type: Article
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