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Giovanni and LOCUS: Innovative Ways for Teachers and Students to Conduct Online Learning and Research with Oceanographic Remote Sensing Data James G. Acker.

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Presentation on theme: "Giovanni and LOCUS: Innovative Ways for Teachers and Students to Conduct Online Learning and Research with Oceanographic Remote Sensing Data James G. Acker."— Presentation transcript:

1 Giovanni and LOCUS: Innovative Ways for Teachers and Students to Conduct Online Learning and Research with Oceanographic Remote Sensing Data James G. Acker NASA Goddard Space Flight Center Earth Sciences Data and Information Services Center (GES DISC) Code 610.2 Greenbelt, MD 20771 jim.acker@gsfc.nasa.gov National Marine Educators Association Annual Meeting 2006 New York City July 17, 2006

2 Goals for this demonstration: To provide several examples of how the GES DISC Interactive Online Visualization AN aNalysis Infrastructure (Giovanni) can be used to investigate oceanographic phenomena To introduce the Laboratory for Ocean Color Users (LOCUS)

3 What is Giovanni ?? Giovanni is a Web-based data exploration system that enables rapid data access, analysis, and visualization online – users do not have to download data files to their own system before initiating analysis and research Ocean Color Giovanni contains data from the SeaWiFS and MODIS-Aqua missions; other “instances” of Giovanni have data from other satellite missions, and supplemental data sets

4  SeaWiFS – the Sea-viewing Wide Field-of-view Sensor, and MODIS-Aqua, the Moderate Resolution Imaging Spectroradiometer on the Aqua satellite, provide ocean color data to Giovanni. The primary data of interest is chlorophyll a concentration (chl a), though additional data products are available.  MODIS-Aqua also provides sea surface temperature (SST) data.  This demonstration will utilize chl a and SST data.

5 The main components of the Giovanni interface are:  interactive map for region-of-interest selection;  menu of available data products;  calendar menu for time-period selection;  menu of visualization options;  visualization-specific options (color palette, axis values);  menu of output options

6 URL for Ocean Color Giovanni: http://reason.gsfc.nasa.gov/Giovanni/ (This instance of Giovanni was funded partly by a NASA REASoN CAN project, the Ocean Color Time-Series Project) Entry Page: MODIS-Aqua Monthly products SeaWiFS Monthly products SeaWiFS 8-day products (new!) SeaWiFS and MODIS-Aqua Multi-parameter Inter- Comparison (Monthly)

7 Demonstration Project 1: Peru Upwelling Zone Goal: Visualize chlorophyll concentrations in a selected region-of-interest Select region- of-interest with click-and-drag Select parameter: Chlorophyll a concentration is the default selection Lat-lon values may be entered instead of click-and- drag Data Types: Parameter Animation Climatology

8 Visualization and Plotting Options Plot types: Lat-Lon map; Animation; Time-Series; Hovmöller plots Time period selection Color palette options Steps: 1. Keep all default options 2. Select any time period in mission range (Example: January 2001 to December 2001) 3. Click “Generate plot” Y-axis plotting options Output options: Numeric (ASCII) data can be chosen Data files with increased spatial resolution can be ordered

9 Peru Upwelling Zone, January-December 2001 Output: Image is the average of all chlorophyll concentration values for the entire 2001 year. The image provides lat/lon information and a color bar scale. It can be downloaded immediately.

10 Demonstration Project 2: Arabian Sea Monsoon Goals:  Create an animation of the Arabian Sea monsoon with SeaWiFS 8-day data;  Create a time-series of chl a in the Arabian Sea Steps: 1. “Back” to entry page 2.Choose SeaWiFS 8-day data 3. Select the region 4.Select Animation 5.Select a year 6.Click “Generate Plot” Region Animation Year

11 Animation output: selected frame Images can be stepped through (+1, -1) or whole animation can be viewed

12 Arabian Sea Monsoon: Time-Series 1.Choose a smaller area within the Arabian Sea (try the “Zoom In” button) 2.Select “Time Series” under Plot Type 3.Click “Generate Plot” (I chose an area off the coast of Somalia to generate the demonstration plot)

13 Arabian Sea Monsoon: Time-Series Output Note that values in this time period may be suspect due to cloud cover The Y-axis can be “customized” to emphasize features in the data, or to make several plots with the same axis range, to enable comparisons. The default option, a “dynamic” Y-axis, is based on the range of values in the data.

14 Demonstration Project 3: Central America (Wind-driven productivity and El Niño anomalies) 1.Choose the Region 2.Select February 2000 3.Generate the Lat/Lon map 4.Change “Data Type” to Anomaly 5.Change the month to February 1998 6.Generate the Lat/Lon map 7.Choose a region inside a jet 8.Change “Data Type” to “Time-Lon Hovmöller, Lat-Averaged” 9. Choose Oct 97-Dec 2000 10. Generate the plot Goal: Create chl a anomaly plots and Hovmöller plots First: “Back” to entry page; select SeaWiFS Monthly data. Then:

15 Demonstration Project 3: Central America (Wind-driven productivity and El Niño anomalies) Output Productivity driven by gap winds dominates this region during normal winter months During the 1997-1998 El Niño, productivity was markedly suppressed due to increased thermocline depth (negative anomalies are blue and purple) The Hovmöller plot demonstrates the seasonality of the phenomenon and the effect of the 1997-1998 El Niño Jets

16 Demonstration Project 4: North Atlantic Bloom (Multi-parameter intercomparison Part 1) The next two demonstrations utilize the Multi- Parameter Intercomparison System Goal: Create a two-parameter time plot

17 Demonstration Project 4: North Atlantic Bloom (Multi-parameter intercomparison Part 1) Region For the time period, select a full year of data. MODIS-Aqua data begin in 2002; try Jan-Dec 2003. Select “Time plot of area-averaged parameters” Select SeaWiFS chl a and MODIS-Aqua SST

18 Demonstration Project 4: North Atlantic Bloom (Multi-parameter intercomparison Part 1) Output Students may think that the North Atlantic Bloom is related to warmer ocean temperatures; a plot like this may force modification of that idea

19 Demonstration Project 5: Benguela Upwelling Zone (Chl a vs. SST scatter plots) Goal: Create a Chl a vs. SST scatter plot Region Plot type: select “Scatter plot of parameters in selected area and time period” (Area plot is also interesting) Select SeaWiFS chl a and Aqua SST

20 Demonstration Project 5: Benguela Upwelling Zone (Chl a vs. SST scatter plots) Output The chl a vs. SST scatter plot shows that lower SST is associated with higher chl a in the upwelling zone The area plot of chl a (color) and SST (contour lines) shows the colder temperatures are near the coast, as are the higher chl a values

21 The Laboratory for Ocean Color Users (LOCUS) The URL for the Laboratory for Ocean Color Users: http://disc.gsfc.nasa.gov/oceancolor/locus/index.shtml LOCUS currently features  recent articles;  Educational Modules illustrating basic concepts; and  Tutorials combining research and data aspects. LOCUS needs:  more research projects! LOCUS is ready to become collaborative at several levels of expertise – experts can be consulted to assist with research projects. We need “researchers” – especially educators and students – to ask questions and provide research project examples.

22 Thanks for coming to the presentation and demonstration! Any questions?


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