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4.1 Working with Gridded Data
Gridded data can be the output from a numerical model or an objective analysis of observational data. Each gridded data source is comprised of a set of 2- and/or 3-D fields. Each field may have of one or more times associated with it. The IDV supports a variety of ways of visualizing gridded data. In this section we will explore some of these.

4.1.0  Loading Gridded Data
Gridded data can be accessed in the IDV from a remote server or from local files. For the exercises in this section, we will use ETA model output from the COMET Case Study on Bow Echoes (39) from June 29, 1998.
4.1.1  Plan Views of Gridded Data

Plan views are horizontal displays of two dimensional data. These data can be true 2D fields (e.g., sea level pressure) or a slice of a 3D dataset at a constant pressure or height (e.g., 500 hPa heights). The IDV can display these plan views as contours, color filled contours, or color shaded displays.

4.1.2  Isosurfaces of Gridded Data
While plan views of 3D fields are useful, the three dimensionality of the atmosphere can be displayed in the IDV using isosurfaces. An isosurface represents a 3-D surface that connects points with the same value. On one side of the surface, values are greater than the surface value; on the other side, values are less than the surface value.
4.1.3  Cross Sections of Gridded Data
Cross sections of data can be useful to show the variation of a field along a transect. In the IDV, a cross section display consists of a selector line and display in the main window, and a 2D display of the cross section in the control window.
4.1.4  Probing Gridded Data

The IDV has a variety of data probes that can be used with gridded data. Probes include value readouts, vertical profiles, model soundings, time/height cross sections and time series displays.

4.1.5  Probing Gridded Data (continued)
4.1.6  Vector Displays

Vector components (e.g. winds, ocean currents, mantle plate velocities) can be displayed in the IDV in a variety of ways.

4.1.7  Working with Large Grids

Displaying high resolution grids in the IDV can be memory intensive. If you are reading from a remote server, you also have to deal with the latency of reading the grids across the internet. There are several strategies you can use to reduce the amount of memory used by the IDV.

4.1.8  Doing More with Grid Displays
Additional exercises you can do with gridded data.

 


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U09-NRM-127: The role of Distributed Data Access Technologies in NRM - for ITC-IDV version 2.7 > Accessing and Displaying Data