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  • The dataset measures the long-term seasonal variations of the chlorophyll a concentrations of ocean surface waters. They are derived from MODIS (aqua) images using NASA's SeaDAS image processing software. The monthly chlorophyll a images between July 2002 and December 2017 are used to calculate the standard deviations of the four austral seasons: winter (June, July, and August), spring (September, October and November), summer (December, January and February) and autumn (March, April and May). The extent of the dataset covers the entire Australian EEZ and surrounding waters (including the southern ocean). The unit of the dataset is mg/m3. This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.

  • The dataset measures the long-term seasonal means of the sea surface temperature (SST) of ocean surface waters. They are derived from MODIS (aqua) images using NASA's SeaDAS image processing software. The monthly SST images between July 2002 and December 2017 are used to calculate the means of the four austral seasons: winter (June, July, and August), spring (September, October and November), summer (December, January and February) and autumn (March, April and May). The extent of the dataset covers the entire Australian EEZ and surrounding waters (including the southern ocean). The unit of the dataset is Celsius degree. This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.

  • This dataset measures the mean decadal warming rates of the sea surface temperature (SST) in 58 Australian Marine Parks (with the exception of the Heard Island and McDonald Islands Marine Park) over the past 25 years (1992 to 2016). They are derived from the Sea Surface Temperature Atlas of the Australian Regional Seas (SSTAARS). The field of “trend_d” represents the linear SST trend for March 1992 to December 2016. The unit of the warming rates is Celsius degree/per decade. This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.

  • The dataset measures the long-term seasonal means of the chlorophyll a concentrations of ocean surface waters. They are derived from MODIS (aqua) images using NASA's SeaDAS image processing software. The monthly chlorophyll a images between July 2002 and December 2017 are used to calculate the means of the four austral seasons: winter (June, July, and August), spring (September, October and November), summer (December, January and February) and autumn (March, April and May). The extent of the dataset covers the entire Australian EEZ and surrounding waters (including the southern ocean). The unit of the dataset is mg/m3. This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.

  • The dataset indicates the seasonal primary productivity hotspots of ocean surface waters. They are derived from MODIS (aqua) images using NASA's SeaDAS image processing software. The monthly chlorophyll a images between July 2002 and August 2014 are used to identify the primary productivity hotspots of the four austral seasons: winter (June, July, and August), spring (September, October and November), summer (December, January and February) and autumn (March, April and May). The extent of the dataset covers the entire Australian EEZ and surrounding waters (including the southern ocean). The value (between 0 and 1.0) of the dataset represents the likelihood of the location being a primary productivity hotspot. This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.

  • This dataset measures the overall warming rates of the sea surface temperature (SST) in 58 Australian Marine Parks (except the Heard Island and McDonald Islands Marine Park) over the past 15 years (2003 to 2017). They are derived from the monthly MODIS (aqua) SST images. The fields of "slope_y" and "slope_m" represent the annual and monthly SST warming rates, respectively. The units of the warming rates are Celsius degree/per annual and Celsius degree/per month. This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.

  • The dataset indicates the long-term overall primary productivity hotspots of ocean surface waters. They are derived from MODIS (aqua) images using NASA's SeaDAS image processing software. The monthly chlorophyll a images between July 2002 and August 2014 are used to identify the overall primary productivity hotspots. The extent of the dataset covers the entire Australian EEZ and surrounding waters (including the southern ocean). The value (between 0 and 1.0) of the dataset represents the likelihood of the location being a primary productivity hotspot. This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.

  • The dataset measures the long-term seasonal variations of the sea surface temperature (SST) of ocean surface waters. They are derived from MODIS (aqua) images using NASA's SeaDAS image processing software. The monthly SST images between July 2002 and December 2017 are used to calculate the standard deviations of the four austral seasons: winter (June, July, and August), spring (September, October and November), summer (December, January and February) and autumn (March, April and May). The extent of the dataset covers the entire Australian EEZ and surrounding waters (including the southern ocean). The unit of the dataset is Celsius degree. This research is supported by the National Environmental Science Program (NESP) Marine Biodiversity Hub through Project D1.

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    At the inception of our project, no study had examined particle fluxes in the Subantarctic Zone (SAZ) of the Southern Ocean, despite the fact that the SAZ represents a large portion of the total area of the Southern Ocean, serve as a strong sink for atmospheric (~1G t C yr-1 [Metzl et al., 1999]), and is central to hypotheses linking particle fluxes and climate change [Francois et al., 1997; Kumar et al., 1995; Sigman et al., 1999]. The SAZ serves as an interface between the cold nutrient-rich waters to its south and the nutrient-depleted subtropical gyres to its north. SAZ upper layers are marked by a thick layer of relatively homogenous Subantarctic Mode Water (SAMW), which overlies Antarctic Intermediate Water (AAIW). Both water masses are subducted northward beneath the subtropical gyres. Thus particles leaving the surface in these regions contribute to carbon redistribution via both the fraction that reaches the deep sea by settling and the fraction that is remineralized within SAMW or AAIW and subsequently subducted. The SAZ exhibits surface water carbon dioxide partial pressures well below atmospheric equilibrium, but PFZ waters are closer to atmospheric equilibrium in this sector [Metal et al., 1999; Poppet al., 1999]. The relative physical and biological contributions to these carbon dioxide partial pressure variations are unclear, but it is important to determine them because physical and biological carbon dioxide transfers are expected to show different responses to climate change [ Matear et al., 1999; Sarmiento and LeQuere, 1996]. For these reasons we focused on the SAZ and, for comparative purposes, on the PFZ to its south. We measured particle fluxes using moored sinking particle traps at three sites in the SAZ, in the PFZ, and beneath the Subantarctic Front (SAF), which separates them. This record describes particle flux data collected between 2000 and 2001. The NetCDF data contains the following variables. Please note not all variables are supplied in all files, specifically there are not uncertainty estimates and no quality control flags for this data. -----DATA DICTIONARY----- Name, description, units, standard name TIME, time, YYYY-MM-DD, time of sample midpoint TIME_START, time sample open, YYYY-MM-DD, time sample open NOMINAL_DEPTH, depth, m, nominal depth LATITUDE, latitude, degrees_north, latitude of anchor LONGITUDE, longitude, degrees_east, longitude of anchor pressure_actual, actual, dbar, actual pressure sample, sample number, 1, sample number sample_quality_control, quality flag for sample number, unitless, quality flag for sample number mass_flux, <1mm, mg m-2 d-1, particulate total mass flux mass_flux_uncertainty, uncertainty for particulate total mass flux, mg m-2 d-1,), uncertainty for particulate total mass flux mass_flux_quality_control, quality flag for particulate total mass flux, unitless, quality flag for particulate total mass flux SAL_BRINE, supernatant, 1, sample supernatant practical salinity SAL_BRINE_uncertainty, uncertainty for sample supernatant practical salinity, 1, uncertainty for sample supernatant practical salinity SAL_BRINE_quality_control, quality flag for sample supernatant practical salinity, unitless, quality flag for sample supernatant practical salinity pH_BRINE, supernatant, 1, sample supernatant pH NBS scale pH_BRINE_uncertainty, uncertainty for sample supernatant pH NBS scale, 1, uncertainty for sample supernatant pH NBS scale pH_BRINE_quality_control, quality flag for sample supernatant pH NBS scale, unitless, quality flag for sample supernatant pH NBS scale PC_mass_flux, <1mm, mg m-2 d-1, particulate total carbon mass flux PC_mass_flux_uncertainty, uncertainty for particulate total carbon mass flux, mg m-2 d-1, uncertainty for particulate total carbon mass flux PC_mass_flux_quality_control, quality flag for particulate total carbon mass flux, unitless, quality flag for particulate total carbon mass flux PN_mass_flux, <1mm, mg m-2 d-1, particulate total nitrogen mass flux PN_mass_flux_uncertainty, uncertainty for particulate total nitrogen mass flux, mg m-2 d-1, uncertainty for particulate total nitrogen mass flux PN_mass_flux_quality_control, quality flag for particulate total nitrogen mass flux, unitless, quality flag for particulate total nitrogen mass flux POC_mass_flux, <1mm, mg m-2 d-1, particulate organic carbon mass flux POC_mass_flux_uncertainty, uncertainty for particulate organic carbon mass flux, mg m-2 d-1, uncertainty for particulate organic carbon mass flux POC_mass_flux_quality_control, quality flag for particulate organic carbon mass flux, unitless, quality flag for particulate organic carbon mass flux PIC_mass_flux, <1mm, mg m-2 d-1, particulate inorganic carbon mass flux PIC_mass_flux_uncertainty, uncertainty for particulate inorganic carbon mass flux, mg m-2 d-1, uncertainty for particulate inorganic carbon mass flux PIC_mass_flux_quality_control, quality flag for particulate inorganic carbon mass flux, unitless, quality flag for particulate inorganic carbon mass flux BSi_mass_flux, <1mm, mg m-2 d-1, particulate biogenic silicon mass flux BSi_mass_flux_uncertainty, uncertainty for particulate biogenic silicon mass flux, mg m-2 d-1, uncertainty for particulate biogenic silicon mass flux BSi_mass_flux_quality_control, quality flag for particulate biogenic silicon mass flux, unitless, quality flag for particulate biogenic silicon mass flux TIME_END, time sample closed, YYYY-MM-DD, time sample closed Reference, citable reference DOI, DOI

  • Categories    

    At the inception of our project, no study had examined particle fluxes in the Subantarctic Zone (SAZ) of the Southern Ocean, despite the fact that the SAZ represents a large portion of the total area of the Southern Ocean, serve as a strong sink for atmospheric (~1G t C yr-1 [Metzl et al., 1999]), and is central to hypotheses linking particle fluxes and climate change [Francois et al., 1997; Kumar et al., 1995; Sigman et al., 1999]. The SAZ serves as an interface between the cold nutrient-rich waters to its south and the nutrient-depleted subtropical gyres to its north. SAZ upper layers are marked by a thick layer of relatively homogenous Subantarctic Mode Water (SAMW), which overlies Antarctic Intermediate Water (AAIW). Both water masses are subducted northward beneath the subtropical gyres. Thus particles leaving the surface in these regions contribute to carbon redistribution via both the fraction that reaches the deep sea by settling and the fraction that is remineralized within SAMW or AAIW and subsequently subducted. The SAZ exhibits surface water carbon dioxide partial pressures well below atmospheric equilibrium, but PFZ waters are closer to atmospheric equilibrium in this sector [Metal et al., 1999; Poppet al., 1999]. The relative physical and biological contributions to these carbon dioxide partial pressure variations are unclear, but it is important to determine them because physical and biological carbon dioxide transfers are expected to show different responses to climate change [ Matear et al., 1999; Sarmiento and LeQuere, 1996]. For these reasons we focused on the SAZ and, for comparative purposes, on the PFZ to its south. We measured particle fluxes using moored sinking particle traps at three sites in the SAZ, in the PFZ, and beneath the Subantarctic Front (SAF), which separates them. This record describes particle flux data collected between 2004 and 2005. The NetCDF data contains the following variables. Please note not all variables are supplied in all files, specifically there are not uncertainty estimates and no quality control flags for this data. -----DATA DICTIONARY----- Name, description, units, standard name TIME, time, YYYY-MM-DD, time of sample midpoint TIME_START, time sample open, YYYY-MM-DD, time sample open NOMINAL_DEPTH, depth, m, nominal depth LATITUDE, latitude, degrees_north, latitude of anchor LONGITUDE, longitude, degrees_east, longitude of anchor pressure_actual, actual, dbar, actual pressure sample, sample number, 1, sample number sample_quality_control, quality flag for sample number, unitless, quality flag for sample number mass_flux, <1mm, mg m-2 d-1, particulate total mass flux mass_flux_uncertainty, uncertainty for particulate total mass flux, mg m-2 d-1,), uncertainty for particulate total mass flux mass_flux_quality_control, quality flag for particulate total mass flux, unitless, quality flag for particulate total mass flux SAL_BRINE, supernatant, 1, sample supernatant practical salinity SAL_BRINE_uncertainty, uncertainty for sample supernatant practical salinity, 1, uncertainty for sample supernatant practical salinity SAL_BRINE_quality_control, quality flag for sample supernatant practical salinity, unitless, quality flag for sample supernatant practical salinity pH_BRINE, supernatant, 1, sample supernatant pH NBS scale pH_BRINE_uncertainty, uncertainty for sample supernatant pH NBS scale, 1, uncertainty for sample supernatant pH NBS scale pH_BRINE_quality_control, quality flag for sample supernatant pH NBS scale, unitless, quality flag for sample supernatant pH NBS scale PC_mass_flux, <1mm, mg m-2 d-1, particulate total carbon mass flux PC_mass_flux_uncertainty, uncertainty for particulate total carbon mass flux, mg m-2 d-1, uncertainty for particulate total carbon mass flux PC_mass_flux_quality_control, quality flag for particulate total carbon mass flux, unitless, quality flag for particulate total carbon mass flux PN_mass_flux, <1mm, mg m-2 d-1, particulate total nitrogen mass flux PN_mass_flux_uncertainty, uncertainty for particulate total nitrogen mass flux, mg m-2 d-1, uncertainty for particulate total nitrogen mass flux PN_mass_flux_quality_control, quality flag for particulate total nitrogen mass flux, unitless, quality flag for particulate total nitrogen mass flux POC_mass_flux, <1mm, mg m-2 d-1, particulate organic carbon mass flux POC_mass_flux_uncertainty, uncertainty for particulate organic carbon mass flux, mg m-2 d-1, uncertainty for particulate organic carbon mass flux POC_mass_flux_quality_control, quality flag for particulate organic carbon mass flux, unitless, quality flag for particulate organic carbon mass flux PIC_mass_flux, <1mm, mg m-2 d-1, particulate inorganic carbon mass flux PIC_mass_flux_uncertainty, uncertainty for particulate inorganic carbon mass flux, mg m-2 d-1, uncertainty for particulate inorganic carbon mass flux PIC_mass_flux_quality_control, quality flag for particulate inorganic carbon mass flux, unitless, quality flag for particulate inorganic carbon mass flux BSi_mass_flux, <1mm, mg m-2 d-1, particulate biogenic silicon mass flux BSi_mass_flux_uncertainty, uncertainty for particulate biogenic silicon mass flux, mg m-2 d-1, uncertainty for particulate biogenic silicon mass flux BSi_mass_flux_quality_control, quality flag for particulate biogenic silicon mass flux, unitless, quality flag for particulate biogenic silicon mass flux TIME_END, time sample closed, YYYY-MM-DD, time sample closed Reference, citable reference DOI, DOI