Marine Data Literacy 2.0

Providing instruction for managing, converting, analyzing and displaying oceanographic station data, marine meteorological data, GIS-compatible marine and coastal data or model simulations, and mapped remote sensing imagery

 

 

 

 

Home > 2. Marine GIS > 2.36 OceanColor T/Chl/S

2.36 Obtaining Operational & Climatological Satellite T, Chlorophyll and S Ocean Data: OceanColor Web

  • Exercise Title:  Obtaining Operational & Climatological Satellite Temperature, Chlorophyll and Salinity Ocean Data: OceanColor Web

  • Abstract:  This exercise shows you how to obtain global climatological grids of temperature, chlorophyll and salinity and similar operational grids of temperature and chlorophyll from an enormous online collection of hundreds of closely related parameters from current satellite sensors.  The eventual usagr of these data is covered in 2.21 Importing NetCDF Satellite Surface Chlorophyll and Salinity Climatologies into Marine GIS: OceanColor Web "Chlorophyll" is used here as a placeholder for many optical parameters.

  • Preliminary Reading (in OceanTeacher, unless otherwise indicated):

  • Required Software:

  • Other Resources: 

    • US NASA OceanColor Web (OCW) - Huge archive of SST, salinity and optics parameters (especially chlorophyll)  from a long series of satellites, now mainly provided as NetCDF.  Nearly everything here is compatible with Saga, ncBrowse, Panoply; only SST and chlorophyll are compatible with IDV.

  • Author:  Murray Brown

  • Version:  12-14-2015

1.  This exercise is provided for you to obtain satellite data to visualize in these separate exercises: 
2.  Open the OCW website, and take some time to read over the explanatory materials.

Then, click on Data Access (top left)

3.  You'll see these 7 access routes.  Please explore them later on your own time.

 

4.  Click on LEVEL 3 BROWSER to see this visual menu.  There are hundreds of data products and many thousands of data rasters here, so take your time and inspect everything carefully as you go.

5.  Now, from the menu of choices (just above these images), make these selections:
  • Product Line:  STANDARD
  • Dataset:  AQUA Modis Sea Surface Temperature (11 u daytime); you need to read up on SST data to see how time of day (night versus day) and wavelength (11 microns/4 microns) are important
  • Product Type:  Monthly climatology; useful for atlases
  • Resolution: 4 km; the finest resolution available for these data
  • Thumbnails:  12; the default number

 

6.  The display of available products will change accordingly, as you make these choices.  They each refer to the maximum available data from 2002 or 2003 to the present (2014 or 2015, depending on the current month).

7.  Hover your cursor over the thumbnail image for the current month (in this case December), and you'll see 2 small icons appear:
  • SMI = Standard Mapped Image (the basic NetCDF raster data product)
  • BIN = Much larger file containing all system data and metadata

Click on SMI.

8.  Save the offered file to LIBERIA > DATA > OCEAN > COLORWEB > SST with the offered filename A20023352014365.L3m_MC_SST_sst_4km.nc
9.  Explanation of ColorWeb filenames (using the example just above):
  • A - A NASA mystery
    • 2002 - From the year 2002
      • 335 - From year-day 335 in 2002
        • 2014 - To the year 2014
          • 365 - To the year-day 365 in 2014
            • L3 - Processed to Level 3
              • MC_SST - Multichannel SST instrument
                • sst - Sea surface temperature measurement
                  • 4km - Resolution in km

10.  In the same way, obtain these files, to give you a complete year:

11.  Use the year-day ranges in the filename dates to determine which month goes with each file.  Add the month abbreviation to each filename to simplify access.

HINT:  The 13th, 14th and 15th digits are the last day of the particular year-month.  For example "031" is for January.

NOTE:  The 7th file in the list will be used in xxxxxxxxxxxxx

12.  That gives us monthly averages, a typical climatological parameter.  Now we'll obtain an operational parameter, the sea temperature on a particular day.  We'll try to get the absolute latest today, either yesterday or possibly even today.
13.  Now, along the menu of choices (above the images), make these selection to obtain an operational SST product, i.e. no older than about a day:
  • Product Line:  STANDARD
  • Dataset:  AQUA Modis Sea Surface Temperature (11 u daytime)
  • Product Type:  Daily; in the case of data downloaded on Dec 10, 2015, the latest product is from Dec 9th, etc.
  • Resolution: 4 km; the finest resolution available for these data
  • Thumbnails:  12; the default number

14.  Click on SMI, and then save the offered file to LIBERIA > DATA > OCEAN > COLORWEB > SST with the offered filename A2015343.L3m_DAY_SST4_sst4_4km.nc.  You should probably rename the file to A2015343.L3m_DAY_SST4_sst4_4km_2015dec09.nc or similar to insure correct identification later.
15.  Now, we have our OCS temperature data.  Let's go for a parallel set of chlorophyll data.  Along the menu of choices (above the images), make these selections:
  • Product Line:  STANDARD
  • Dataset:  AQUA Modis Sea Chlorophyll concentration (either of the 2 algorithms offered, OCl or OCx)
  • Product Type:  Monthly climatology; useful for climatologies/atlases
  • Resolution: 4 km; the finest resolution available for these data
  • Thumbnails:  12; the default number

The display of available products will change automaticallly change accordingly, as you make these choices.

16.  Notice that the legend shows a log scale (0.01 to 10+) in mg/m3.  This sort of scale is typical for parameters like nutrients and chlorophyll that tend to be mainly small values.

17.  As you did above:
  • Download the monthly climatologies to LIBERIA > DATA > OCEAN > COLORWEB > CHLOROPHYLL
  • Add 3-letter month abbreviations to the filenames, as you did above.  Be careful to get them right.
  • You should now see, as a minimum, these files

 

18.  Now we need an operational salinity product.
19.  Along the menu of choices (above the images), make these selections to obtain an operational chlorophyll product, i.e. no older than about a day:
  • Product Line:  STANDARD
  • Dataset:  AQUA Modis Sea Chlorophyll concentration (either of the 2 algorithms offered, OCl or OCx)
  • Product Type:  Daily; in the case of data downloaded on Dec 11, 2015, the latest product, for the author, is from Dec 10, 2015
  • Resolution: 4km; the finest resolution available for these data
  • Thumbnails:  12; the default number

Click on SMI of the latest available data product, as indicated by the presence of a thumbnail image.

20.  Save the offered file to LIBERIA > DATA > OCEAN > COLORWEB > CHLOROPHYLL with the offered filename A2015344.L3m_DAY_CHL_chlor_a_4km.nc.  You should probably rename the file to A2015344.L3m_DAY_CHL_chlor_a_4km_2015dec10.nc or similar to insure correct identification later.
21.  You should have something like this file now.  It is probably much smaller than the climatologies because on any given day you won't have much clearly viewed ocean surface.
22.  Now, we have our OCS chlorophyll data.  Let's go for a parallel set of salinity data.  Along the menu of choices (above the images), make these selections:
  • Product Line:  STANDARD
  • Dataset:  Select either one of the ALL BEAMS products for Aquarius sea surface salinity with SST-based adjustment
  • Product Type:  Monthly climatology; useful for climatologies/atlases
  • Resolution: 1 degree
  • Thumbnails:  12; the default number

The display of available products might change accordingly, as you make these choices.  YOU are the scientist, so come back later and study the products to make sure you're getting what you really need, and you understand why.

 

23.  Notice that the legend shows a peculiar scale, that expands in the middle-region (33-37, but is much tighter below (30-33 and above (37-40.  [The "units" are PSU.]  This is obviously tailor-made to global salinities, which cluster around the mid range (except, of course, in marginal seas). 

24.  As you did above, download the monthly climatologies to LIBERIA > DATA > OCEAN > COLORWEB > SALINITY

You should see this in the folder.

 

25.  Perform these tasks:
  • Unzip the BZ2 files in place
  • Add the extension HD5 to each filename.  This indicates the files are HDF5 format, which is recognized and formally included within NetCDF4.  Saga, ncBrowse, HDFView and Panoply all recognize it and display it readily.  IDV does not, yet.
  • Add the month abbreviations as above.
  • Delete the BZ2 files to save space.
26.  Operational Aquarius salinity data are not available, because the sensor has failed.
27.  Checking data files utility/validity with ncBrowse.  In the following panels, this "sentinel" software program is used to view the indicated files.
28.  Temperature > January Average:
  • Grid opened in ncBrowse
  • Double-click on the SST object to view metadata (i.e. next panel)
29.  Temperature > January Average:
  • Look at the first metadata line which implies the full global grid is >32 megapixels (i.e. 4320 X 8640)
  • Global grids of this huge size often fail to "open" in ncBrowse
    • Try to open it with GRAPH VARIABLE, and probably nothing will happen.  This indicates data overload, i.e. the grid is too big
  • Look second at the geographic START and END values to confirm that true geographic units are used.
  • We need to reduce the geographic coverage
  • We also need to exchange the grid axes
30.  Temperature > January Average:
  • Set LAT axis to Y
  • Set LAT START - END for Liberia's top and bottom values
  • Set LON axis to X (usually automatic)
  • Set LON START - END for Liberia's left and right values
  • Then click GRAPH VARIABLE
31.  Temperature > January Average
  • The palette needs some work, but this is a good product.  Our 12 monthly grids are probably good to use.
32.  ncBrowse usually can graph variables for most global grids, but if you have trouble, then use the method above to decimate the data to the area of interest if you have problems.  Use common sense and maybe a small diagram to help you pick the values to use.
33.  Let's move on to the "operational" temperature raster for a particular day you obtained above.
34.  Temperature > December 10, 3015
  • All of the above adjustments and specifications are used here to see the image.
  • Obviously the palette needs some work to see the actual values, but everything else seems to be ok.
35.  Now let's view the chlorophyll images.
36.  Chlorophyll > January Average
  • Grid opened in ncBrowse
  • Double-click on the CHLOR_A object to view metadata (i.e. next panel)

 

37.  Chlorophyll > January Average
  • Because all the physical dimensions are the same as above, all of the same adjustments and settings are applied
  • Click GRAPH VARIABLE
38.  Chlorophyll > January Average
  • The palette here is unacceptable, but the placement is fine, so these operational data will be good to use
39.  Chlorophyll > December 10, 2015
  • The amount of data showing here is extremely small, just a few dots in the SE and the SW.
  • We need to check the image on the source OCS page to see if this is realistic.
40.  Chlorophyll > December 10, 2015
  • You can click on the thumbnail image (between the SMI and the BIN in Panl 13, above, to see a PNG image of the whole globe.
  • We've done that here for the chlorophyll data on December 10, 2015, and you can see that there's almost no data in our area of interest.  So this agrees with the above data.
41.  Now let's view the salinity data.
42.  Salinity > January Average
  • Grid opened in ncBrowse
  • Double-click on the L3M_DATA object to view metadata (i.e. next panel)

 

43.  Look carefully at the first line of metadata, and you'll see that this grid is much smaller than the above grids, so it will probably open directly in ncBrowse, without Start-End subsetting, as we did above.
44.  Looking below, you'll see there are no helpful hints to identify the axes.  The only hint is that latitude is usually reported by an axis that is half the longitude axis.  This lets us assign Y to the first axis and X to the second. 

You can't guess anything else yet, so just click GRAPH VARIABLE to see what you get.

45.  The map is obviously upside down.  We need to fix the latitude specification.
46.  So we have to check the REVERSE box for the latitude, as you see here.  Then click the GRAPH control again.
47.  And all seems to be well with the salinity grid.  You'll see this grid later in a GIS context, where we'll need to know what we just learned about it.

Notice the very obvious higher salinity regime in the Atlantic, compared to the other seas.

48.  Now you have a good way to get global climatological T, Chlorophyll and Salinity data, and operational data for T and Chlorophyll only.  The T and Chlorophyll grids are "geographic" and plot easily (as typical NetCDF).  The S grids operate as NetCDF in many programs (excluding IDV), but will require georegistration for further analyses.