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GrADS

Enabling the Transition of CPC Products to GIS Format: GrADS/GIS Viviane Silva Jennifer Adams & Brian Doty (COLA) Mike Halpert & Wesley Ebisuzaki (CPC) 34 th Climate Diagnostics and Prediction Workshop 28 October 2009. GrADS.

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GrADS

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  1. Enabling the Transition of CPC Products to GIS Format: GrADS/GISViviane SilvaJennifer Adams & Brian Doty (COLA) Mike Halpert & Wesley Ebisuzaki (CPC)34th Climate Diagnostics and Prediction Workshop 28 October 2009

  2. GrADS • GrADS is the core software used to generate the vast majority of CPC’s web products distributed to the public. • GRADS: The Grid Analysis and Display System • It is widely used around the world by the Climate community. • GrADS was developed and is maintained and supported at the Center for Ocean-Land-Atmosphere Studies (COLA)

  3. GrADS/GIS CPC / COLA GIS Proposal Funded by the NOAA/ Climate Test Bed (CTB) The goal of this proposal is to enhance GrADS by: • Adding GIS vector and raster formats as output options, and • Facilitating the analysis of multi-member and multi-model ensemble forecast data sets.

  4. GIS Format as Output Options

  5. GrADS Version:2.0a7 • Currently available formats: • GeoTIFF • KML • GrADS Commands: KML GeoTIFF 'set kml filename' 'set gxout kml' 'display variable' 'set geotiff filename' 'set gxout geotiff' 'display variable' KML still needs some work.

  6. CPC Global Data Sets Available in GeoTIFF: • CPC Daily Precipitation Analysis (0.5x0.5 deg.) • Daily CMORPH (0.25x0.25 deg.) • Hourly QMORPH (8km) • GFS Week-1 and Week-2 Precipitation Forecasts ftp://ftp.cpc.ncep.noaa.gov/GIS/GRADS_GIS/GeoTIFF/

  7. GrADS - GeoTIFF Example: CPC Global Precipitation Analysis

  8. Facilitating the Analysis of multi-member and multi-model Ensemble Forecast data sets • A Diagonal Slice • A Time-Varying Diagonal Slice

  9. Example:A Diagonal Slice • Suppose we use a lag ensemble data set that contains 10 members • Each member consists of forecasts out to 96 hours, with output every 6 hours, and initialized at 12-hour intervals The figure illustrates the coverage of all 10 members in the Time-Ensemble domain; the rainbow colored boxes represent individual time steps in each member. • Suppose we want to extract the 12-hour precipitation forecast from each ensemble member • --- this is the third time step from the initial time of each forecast, which would be a diagonal slice through the domain (solid black outline).

  10. The first step is to set the time dimension to a fixed value and set the ensemble dimension to include all the desired members:'set t 1''set e 1 10' • Next, determine the offset value that will give you the time index you desire. In this example, we want the third time step, which is an offset of two from the initial time, so our offset value is 2. • 'd p(offt=2)' GrADS will retrieve the third valid time step from each ensemble member. GrADS then aligns all the retrieved values into a single column and returns a result grid with a fixed T and a varying E dimension.

  11. Expand the data request to include more than one time step:A Time-Varying Diagonal Slice Suppose we want to extract the precipitation values over the first 24 hours of each ensemble member -- you need the second, third, fourth, and fifth time step from each forecast.

  12. 'd tloop(p(offt+0)) 'As tloop builds the time-varying result, it steps through the desired offset values, retrieving the second, third, fourth, and fifth timesteps of each ensemble member, and stacking them in an aligned grid: More Details can be found at: http://iges.org/grads/gadoc/offt.html

  13. Thanks !!! Viviane.Silva@noaa.gov

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