Easier access to the project's datasets
Brought to you by NSF NOAA BIOS SUNY URI/GSO UHawaii WHOI
|
The Oleander Project ERDDAP
Easier access to the project's datasets |
Brought to you by NSF NOAA BIOS SUNY URI/GSO UHawaii WHOI |
| Dataset Title: | Oleander TSG data
|
| Institution: | Bermuda Institute of Ocean Sciences (Dataset ID: oleanderTsg) |
| Information: | Summary
| License
| FGDC
| ISO 19115
| Metadata
| Background
| Data Access Form
| Make a graph
|
(Refine the map and/or download the image)
To view the map, check View : Map of All Related Data above.
WARNING: This may involve lots of data.
For some datasets, this may be slow.
Consider using this only when you need it and
have selected a small subset of the data.
To view the counts of distinct combinations of the variables listed above,
check View : Distinct Data Counts above and select a value for one of the variables above.
Distinct Data
(Metadata)
(Refine the data subset and/or download the data)
| start_date | start_year | start_month | cruise_num |
|---|---|---|---|
| 201400925 | 2014 | 9 | 1774 |
| 201401009 | 2014 | 10 | 1776 |
| 201401016 | 2014 | 10 | 1777 |
| 201401023 | 2014 | 10 | 1778 |
| 201401031 | 2014 | 10 | 1780 |
| 201401107 | 2014 | 11 | 1781 |
| 201401114 | 2014 | 11 | 1782 |
| 201401121 | 2014 | 11 | 1783 |
| 201401128 | 2014 | 11 | 1784 |
| 201401205 | 2014 | 12 | 1785 |
| 201401212 | 2014 | 12 | 1786 |
| 201600922 | 2016 | 9 | 1876 |
| 201601015 | 2016 | 10 | 1880 |
| 201601021 | 2016 | 10 | 1881 |
| 201601105 | 2016 | 11 | 1883 |
| 201601112 | 2016 | 11 | 1884 |
| 201601209 | 2016 | 12 | 1888 |
| 201601223 | 2016 | 12 | 1890 |
| 201700120 | 2017 | 1 | 1893 |
| 201700127 | 2017 | 1 | 1894 |
| 201700203 | 2017 | 2 | 1895 |
| 201700211 | 2017 | 2 | 1896 |
| 201700224 | 2017 | 2 | 1898 |
| 201700303 | 2017 | 3 | 1899 |
| 201700310 | 2017 | 3 | 1900 |
| 201700325 | 2017 | 3 | 1902 |
| 201700408 | 2017 | 4 | 1904 |
| 201700418 | 2017 | 4 | 1905 |
| 201700428 | 2017 | 4 | 1907 |
| 201700512 | 2017 | 5 | 1908 |
| 201700519 | 2017 | 5 | 1910 |
| 201700527 | 2017 | 5 | 1911 |
| 201700602 | 2017 | 6 | 1912 |
| 201700609 | 2017 | 6 | 1913 |
| 201700616 | 2017 | 6 | 1914 |
| 201700623 | 2017 | 6 | 1915 |
| 201700630 | 2017 | 6 | 1916 |
| 201700714 | 2017 | 7 | 1918 |
| 201700721 | 2017 | 7 | 1919 |
| 201700728 | 2017 | 7 | 1920 |
| 201701006 | 2017 | 10 | 1930 |
| 201701014 | 2017 | 10 | 1931 |
| 201701212 | 2017 | 12 | 1939 |
| 201701216 | 2017 | 12 | 1940 |
| 201800106 | 2018 | 1 | 1942 |
| 201800113 | 2018 | 1 | 1943 |
| 201800120 | 2018 | 1 | 1944 |
| 201800127 | 2018 | 1 | 1945 |
| 201800203 | 2018 | 2 | 1946 |
| 201800210 | 2018 | 2 | 1947 |
| 201800217 | 2018 | 2 | 1948 |
| 201800224 | 2018 | 2 | 1949 |
| 201800303 | 2018 | 3 | 1950 |
| 201800311 | 2018 | 3 | 1951 |
| 201800319 | 2018 | 3 | 1952 |
| 201800325 | 2018 | 3 | 1953 |
| 201800418 | 2018 | 4 | 1956 |
| 201800421 | 2018 | 4 | 1957 |
| 201800512 | 2018 | 5 | 1960 |
| 201800519 | 2018 | 5 | 1961 |
| 201800525 | 2018 | 5 | 1962 |
| 201800602 | 2018 | 6 | 1963 |
| 201800804 | 2018 | 8 | 1972 |
| 201800811 | 2018 | 8 | 1973 |
| 201800817 | 2018 | 8 | 1974 |
| 201800824 | 2018 | 8 | 1975 |
| 201800831 | 2018 | 8 | 1976 |
| 201800911 | 2018 | 9 | 1977 |
| 201800915 | 2018 | 9 | 1978 |
| 201800926 | 2018 | 9 | 1979 |
| 201800929 | 2018 | 9 | 1980 |
| 201801005 | 2018 | 10 | 1981 |
| 201801016 | 2018 | 10 | 1982 |
| 201801020 | 2018 | 10 | 1983 |
| 201801027 | 2018 | 10 | 1984 |
| 201801102 | 2018 | 11 | 1985 |
| 201801110 | 2018 | 11 | 1986 |
| 201801117 | 2018 | 11 | 1987 |
| 201801201 | 2018 | 12 | 1989 |
| 201801208 | 2018 | 12 | 1990 |
| 201801215 | 2018 | 12 | 1991 |
| 201801222 | 2018 | 12 | 1992 |
| 201900105 | 2019 | 1 | 1993 |
| 201900112 | 2019 | 1 | 1994 |
| 201900119 | 2019 | 1 | 1995 |
| 201900126 | 2019 | 1 | 1996 |
| 201900202 | 2019 | 2 | 1997 |
| 201900209 | 2019 | 2 | 1998 |
| 201900216 | 2019 | 2 | 1999 |
| 201900223 | 2019 | 2 | 2000 |
| 201900809 | 2019 | 8 | 2024 |
| 201900816 | 2019 | 8 | 2025 |
| 201900823 | 2019 | 8 | 2026 |
| 201900830 | 2019 | 8 | 2027 |
| 201900906 | 2019 | 9 | 2028 |
| 201900913 | 2019 | 9 | 2029 |
| 201900926 | 2019 | 9 | 2030 |
| 201901004 | 2019 | 10 | 2032 |
| 201901011 | 2019 | 10 | 2033 |
| 201901019 | 2019 | 10 | 2034 |
| 201901026 | 2019 | 10 | 2035 |
| 201901102 | 2019 | 11 | 2036 |
| 201901109 | 2019 | 11 | 2037 |
| 201901116 | 2019 | 11 | 2038 |
| 201901123 | 2019 | 11 | 2039 |
| 201901130 | 2019 | 11 | 2040 |
| 201901207 | 2019 | 12 | 2041 |
| 201901213 | 2019 | 12 | 2042 |
| 201901221 | 2019 | 12 | 2043 |
| 202000104 | 2020 | 1 | 2044 |
| 202000111 | 2020 | 1 | 2045 |
| 202000118 | 2020 | 1 | 2046 |
| 202000125 | 2020 | 1 | 2047 |
| 202000131 | 2020 | 1 | 2048 |
| 202000208 | 2020 | 2 | 2049 |
| 202000229 | 2020 | 2 | 2052 |
| 202000306 | 2020 | 3 | 2053 |
| 202000314 | 2020 | 3 | 2054 |
| 202000320 | 2020 | 3 | 2055 |
| 202000327 | 2020 | 3 | 2056 |
| 202000403 | 2020 | 4 | 2057 |
| 202000410 | 2020 | 4 | 2058 |
| 202000417 | 2020 | 4 | 2059 |
| 202000424 | 2020 | 4 | 2060 |
| 202000501 | 2020 | 5 | 2061 |
| 202000508 | 2020 | 5 | 2062 |
| 202000515 | 2020 | 5 | 2063 |
| 202000522 | 2020 | 5 | 2064 |
| 202000529 | 2020 | 5 | 2065 |
| 202000606 | 2020 | 6 | 2066 |
| 202000612 | 2020 | 6 | 2067 |
| 202000619 | 2020 | 6 | 2068 |
| 202000626 | 2020 | 6 | 2069 |
| 202000703 | 2020 | 7 | 2070 |
| 202000711 | 2020 | 7 | 2071 |
| 202000718 | 2020 | 7 | 2072 |
| 202000724 | 2020 | 7 | 2073 |
| 202000731 | 2020 | 7 | 2074 |
| 202000807 | 2020 | 8 | 2075 |
| 202000814 | 2020 | 8 | 2076 |
In total, there are 140 rows of distinct combinations of the variables listed above.
All of the rows are shown above.
To change the maximum number of rows displayed, change View : Distinct Data above.
To view the related data counts,
check View : Related Data Counts above and select a value for one of the variables above.
WARNING: This may involve lots of data.
For some datasets, this may be slow.
Consider using this only when you need it and
have selected a small subset of the data.
Related Data
(Metadata)
(Refine the data subset and/or download the data)
To view the related data, change View : Related Data above.
WARNING: This may involve lots of data. For some datasets, this may be slow. Consider using this only when you need it and have selected a small subset of the data.