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  • Salinity  (7)
  • American Meteorological Society  (7)
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  • 2020-2023  (6)
  • 2005-2009  (1)
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  • 1
    Publication Date: 2017-04-04
    Description: In this paper results from the application of an ocean data assimilation (ODA) system, combining a multivariate reduced-order optimal interpolator (OI) scheme with a global ocean general circulation model (OGCM), are described. The present ODA system, designed to assimilate in situ temperature and salinity observations, has been used to produce ocean reanalyses for the 1962–2001 period. The impact of assimilating observed hydrographic data on the ocean mean state and temporal variability is evaluated. A special focus of this work is on the ODA system skill in reproducing a realistic ocean salinity state. Results from a hierarchy of different salinity reanalyses, using varying combinations of assimilated data and background error covariance structures, are described. The impact of the space and time resolution of the background error covariance parameterization on salinity is addressed.
    Description: This work has been funded by the ENACT Project (Contract EVK2-CT2001-00117) for A. Bellucci and P. Di Pietro, and partially by the ENSEMBLES Project (Contract GOCE-CT-2003-505539) for A. Bellucci.
    Description: Published
    Description: 3785-3807
    Description: 3.7. Dinamica del clima e dell'oceano
    Description: JCR Journal
    Description: reserved
    Keywords: ocean modelling ; data assimilation ; reanalysis ; upper ocean variability ; temperature ; Salinity ; 03. Hydrosphere::03.01. General::03.01.04. Ocean data assimilation and reanalysis
    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 Journal of the Atmospheric and Oceanic Technology 37(5), (2020): 789-806, doi:10.1175/JTECH-D-18-0244.1.
    Description: Realistic ocean state prediction and its validation rely on the availability of high quality in situ observations. To detect data errors, adequate quality check procedures must be designed. This paper presents procedures that take advantage of the ever-growing observation databases that provide climatological knowledge of the ocean variability in the neighborhood of an observation location. Local validity intervals are used to estimate binarily whether the observed values are considered as good or erroneous. Whereas a classical approach estimates validity bounds from first- and second-order moments of the climatological parameter distribution, that is, mean and variance, this work proposes to infer them directly from minimum and maximum observed values. Such an approach avoids any assumption of the parameter distribution such as unimodality, symmetry around the mean, peakedness, or homogeneous distribution tail height relative to distribution peak. To reach adequate statistical robustness, an extensive manual quality control of the reference dataset is critical. Once the data have been quality checked, the local minima and maxima reference fields are derived and the method is compared with the classical mean/variance-based approach. Performance is assessed in terms of statistics of good and bad detections. It is shown that the present size of the reference datasets allows the parameter estimates to reach a satisfactory robustness level to always make the method more efficient than the classical one. As expected, insufficient robustness persists in areas with an especially low number of samples and high variability.
    Description: This study has been conducted using EU Copernicus Marine Service Information and was supported by the European Union within the EU Copernicus Marine Service In Situ phase-I and phase-II contracts led by Ifremer. The publication was also supported by SOERE CTDO2 in France. The Argo data were collected and made freely available by the International Argo Program and the national programs that contribute to it (see http://www.argo.ucsd.edu, http://argo.jcommops.org). The Argo Program is part of the Global Ocean Observing System (http://doi.org/10.17882/42182). The marine mammal data were collected and made freely available by the International MEOP Consortium and the national programs that contribute to it (see http://www.meop.net; https://doi.org/10.17882/45461). Aleix Gelabert and Dídac Costa were the skippers of the OPOO, sponsored by the Intergovernmental Oceanographic Commission (UNESCO) and Pharmaton. The BWR is a periodic oceanic race organized by the Fundació Navegació Oceànica de Barcelona (FNOB). Reviewer D. Briand provided some useful comments on the final version of the draft paper before submission.
    Description: 2020-11-04
    Keywords: Ocean ; Climatology ; Salinity ; Temperature ; Data quality control ; Oceanic variability
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 3
    Publication Date: 2022-06-16
    Description: Author Posting. © American Meteorological Society, 2022. 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 35(11), (2022): 3445-3457, https://doi.org/10.1175/jcli-d-21-0656.1.
    Description: Unlike greenhouse gases (GHGs), anthropogenic aerosol (AA) concentrations have increased and then decreased over the past century or so, with the timing of the peak concentration varying in different regions. To date, it has been challenging to separate the climate impact of AAs from that due to GHGs and background internal variability. We use a pattern recognition method, taking advantage of spatiotemporal covariance information, to isolate the forced patterns for the surface ocean and associated atmospheric variables from the all-but-one forcing Community Earth System Model ensembles. We find that the aerosol-forced responses are dominated by two leading modes, with one associated with the historical increase and future decrease of global mean aerosol concentrations (dominated by the Northern Hemisphere sources) and the other due to the transition of the primary sources of AA from the west to the east and also from Northern Hemisphere extratropical regions to tropical regions. In particular, the aerosol transition effect, to some extent compensating the global mean effect, exhibits a zonal asymmetry in the surface temperature and salinity responses. We also show that this transition effect dominates the total AA effect during recent decades, e.g., 1967–2007.
    Description: All three authors are supported by U.S. National Science Foundation (OCE-2048336). The Community Earth System Model project is supported primarily by the National Science Foundation (https://www.cesm.ucar.edu/projects/community-projects/LENS/data-sets.html and https://www.cesm.ucar.edu/working_groups/CVC/simulations/cesm1-single_forcing_le.html).
    Keywords: Aerosol radiative effect ; Climate Change ; Climate variability ; Sea surface temperature ; Salinity
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 4
    Publication Date: 2022-05-27
    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 Nezlin, N. P., Dever, M., Halverson, M., Leconte, J., Maze, G., Richards, C., Shkvorets, I., Zhang, R., & Johnson, G. Accuracy and long-term stability assessment of inductive conductivity cell measurements on Argo Floats. Journal of Atmospheric and Oceanic Technology, 37(12), (2020): 2209-2223, https://doi.org/10.1175/JTECH-D-20-0058.1.
    Description: This study demonstrates the long-term stability of salinity measurements from Argo floats equipped with inductive conductivity cells, which have extended float lifetimes as compared to electrode-type cells. New Argo float sensor payloads must meet the demands of the Argo governance committees before they are implemented globally. Currently, the use of CTDs with inductive cells designed and manufactured by RBR, Ltd., has been approved as a Global Argo Pilot. One requirement for new sensors is to demonstrate stable measurements over the lifetime of a float. To demonstrate this, data from four Argo floats in the western Pacific Ocean equipped with the RBRargo CTD sensor package are analyzed using the same Owens–Wong–Cabanes (OWC) method and reference datasets as the Argo delayed-mode quality control (DMQC) operators. When run with default settings against the standard DMQC Argo and CTD databases, the OWC analysis reveals no drift in any of the four RBRargo datasets and, in one case, an offset exceeding the Argo target salinity limits. Being a statistical tool, the OWC method cannot strictly determine whether deviations in salinity measurements with respect to a reference hydrographic product (e.g., climatologies) are caused by oceanographic variability or sensor problems. So, this study furthermore investigates anomalous salinity measurements observed when compared with a reference product and demonstrates that anomalous values tend to occur in regions with a high degree of variability and can be better explained by imperfect reference data rather than sensor drift. This study concludes that the RBR inductive cell is a viable option for salinity measurements as part of the Argo program.
    Description: Author Dr. G. Maze was supported by the EARISE project, a European Union’s Horizon 2020 research and innovation program under Grant Agreement 824131, Call INFRADEV-03-2018-2019: Individual support to ESFRI and other world-class research infrastructures. We acknowledge Susan Wijffels, who provided advice on reference climatologies, coordinated access to the data from Argo Australia float 5904925, and provided ship CTD data to evaluate the initial accuracy of the float. Toshio Suga and Shigeki Hosoda provided ship CTD data for assessing the initial accuracy of Japan Argo floats 2903005 and 2903327. We thank Zenghong Liu for coordinating access to ship CTD data and continued discussion regarding RBRargo CTD accuracy and stability. We thank IFREMER for providing us access to ADMT-CTD and ADMT-Argo reference datasets.
    Keywords: Pacific Ocean ; Salinity ; Instrumentation/sensors ; Profilers, oceanic ; Quality assurance/control
    Repository Name: Woods Hole Open Access Server
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  • 5
    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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  • 6
    Publication Date: 2022-05-27
    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 Physical Oceanography 50(11),(2020): 3219–3234, https://doi.org/10.1175/JPO-D-19-0277.1.
    Description: Preexisting, oceanic barrier layers have been shown to limit turbulent mixing and suppress mixed layer cooling during the forced stage of a tropical cyclone (TC). Furthermore, an understanding of barrier layer evolution during TC passage is mostly unexplored. High precipitation rates within TCs provide a large freshwater flux to the surface that alters upper-ocean stratification and can act as a potential mechanism to strengthen the barrier layer. Ocean glider observations from the Bermuda Institute of Ocean Sciences (BIOS) indicate that a strong barrier layer developed during the approach and passage of Hurricane Gonzalo (2014), primarily as a result of freshening within the upper 30 m of the ocean. Therefore, an ocean model case study of Hurricane Gonzalo has been designed to investigate how precipitation affects upper-ocean stratification and sea surface temperature (SST) cooling during TC passage. Ocean model hindcasts of Hurricane Gonzalo characterize the upper-ocean response to TC precipitation forcing. Three different vertical mixing parameterizations are tested to determine their sensitivity to precipitation forcing. For all turbulent mixing schemes, TC precipitation produces near-surface freshening of about 0.3 psu, which is consistent with previous studies and in situ ocean observations. The influence of precipitation-induced changes to the SST response is more complicated, but generally modifies SSTs by ±0.3°C. Precipitation forcing creates a dynamical coupling between upper-ocean stratification and current shear that is largely responsible for the heterogeneous response in modeled SSTs.
    Description: This work was supported by the National Aeronautics and Space Administration (NASA; Grant NNX15AD45G) and the National Oceanic and Atmospheric Administration (NOAA; Grant NA11OAR4320199).
    Keywords: Air-sea interaction ; Hurricanes/typhoons ; Salinity ; Ocean models
    Repository Name: Woods Hole Open Access Server
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  • 7
    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
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