Satellite Chlorophyll-a Imagery from Giovanni
exercise shows how to access, visualize and download monthly images of
climatological satellite chlorophyll-a concentration at the surface from the
Web-based application developed by the Goddard Earth Sciences Data and
Information Services Center from NASA. After downloading, the exercise
demonstrates how to import the rasters to SAGA, change color settings and visualize it in
comparison with current vectors obtained in previous exercise.
Lilian Krug and
Ocean Color Radiometry Online Visualization and Analysis - Global Monthly
which contain a list of settings to be defined in order to generate your
product. The first setting is the SPATIAL one. Provide coordinates of
Scrolling down, next setting is the Parameters. Check ‘Climatology’ in the Analysis Options and the Display
settings changes automatically to ‘Climatology info’.
Here we can see the list of sensors which data are available, their spatial
resolution and period of activity. Go to the MODIS-Aqua 4 km box, scroll down to the very last item and
check chlorophyll a concentration 4 km.
(Unfortunately, they don’t have Sea Surface Temperature
Moving on, next setting is time. For now, let’s get the climatology for
January only, so adjust Begin and End
Date to JAN.
Visualization has many options. Here you
can choose between Hovmollers, Scatterplots, Time
series averages, Animations and others. For this exercise, we will stick
with the default
Lat-Lon map, Time-averaged.
click on Generate Visualization
and wait while the product is being processed.
This is the
climatological January chlorophyll-a map for Liberia. You may notice that
even though this is a monthly average, it still contains a lot of missing
data due to cloud presence. A big constraint for ocean color science.
download the data, go to the Download
Data tab, on the upper left corner of the page.
Select and download the
NCD format of Input file category, it is a netcdf
format. If you wish, you may download the KMZ file, readable in Google
Save in DATA/OCEAN/Giovanni with
the suggested filename ChlaModisA_4Km_Jan_Giovanni_Liberia.nc
6. Go back to the Visualization Results tab, select Refine Constraints,
change the temporal setting Begin and End Dates to July and July and click
on Submit Refinements. Download the July climatology, renaming the file to ChlaModisA_4Km_Jul_Giovanni_Liberia.nc
7. Run SAGA and select MODULES > IMPORT/EXPORT > GDAL/OGR > GDAL:IMPORT
Locate the file and click OK. Make sure you
check Transformation. This will guarantee your data comes associated
with the metadata (namely, geographical coordinates). Interpolation choice
will slightly affect the Chl-a value (±0.003 mg.m-3
difference in between interpolation methods). We will use same as in
previous exercises with raster files and use the
Nearest Neighbor method.
8. Import both images (January and July) and change settings regarding color
scheme. Use histograms to define the value range and set the mode to Logarithic (up) – Logarithmic stretch factor =10.
9. Now we can compare the effect of wind on surface primary productivity by
loading the climatological wind vectors from lesson
6.2 Plotting Vector
Arrows from U and V Component Grids with Saga. Load Shape PRODUCTS >
SAGA > VECTORS saved as wind_vecs_jan_liberia_coads_nvods_saga.shp and wind_vecs_jul_liberia_coads_nvods_saga.shp