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TIGGE data via OPeNDAP. Jennifer M. Adams and Brian Doty IGES/COLA. What is GrADS?. GrADS is an interactive tool that integrates data access, analysis, and visualization Handles many data formats: Binary, NetCDF, HDF, GRIB, BUFR Two data models for gridded and in situ data
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TIGGE data via OPeNDAP Jennifer M. Adams and Brian DotyIGES/COLA
What is GrADS? • GrADS is an interactive tool that integrates data access, analysis, and visualization • Handles many data formats: Binary, NetCDF, HDF, GRIB, BUFR • Two data models for gridded and in situ data • Expression handling is flexible, compact, recursive • Programmable interface for scripting • Written in C; code is open source (GPL) • Active users forum with 1800+ subscribers
GOES VIS Image with Radar, 500mb Heights, and SLP 18z 4 June 2009
Analysis of Surface METAR Observations with Radar 18z 29 May 2009
QuikSCAT Winds (HDF), Surface Obs (BUFR), and ETA Model SLP (GRIB) Another Example of GrADS Graphics Output 00z 6 Dec 2003
What is the GrADS Data Server? • GDS is a stable, secure, OPeNDAP data server that provides subsetting and server-side analysis services over the internet • GDS can serve any GrADS-readable dataset, and unifies all data formats into a NetCDF framework • Open a data set with http://server/filenameinstead of /disk/filename
News from GrADS/GDS Team • GrADS has a 5th grid dimension for ensemblesset X, Y, Z, T, or Eset lon, lat, lev, time, or ens • GrADS has an interface for HDF5 and GRIB2 • GDS can serve any GrADS data set • GrADS is a client for anyOPeNDAP data set • GrADS supports GIS-compatible formatsGeoTIFF, KML, and ESRI Shapefiles
Ensemble Forecast Time Series(Longitude, Latitude, and Level are fixed) Forecast Time --->
Ensemble Forecast Grid(Longitude, Latitude, and Level are fixed) Ensemble Member Forecast Time --->
Ten Ensemble Forecasts(Longitude, Latitude, and Level are fixed) Ensemble Member Forecast Time --->
Ensemble Forecast Time Series(Longitude, Latitude, and Level are fixed) Forecast Time --->
Ensemble Mean = tloop(ave(Z,e=1,e=21))Ensemble Min/Max = tloop(min(Z,ens=c00,ens=p20))+/- StdDev of Ensemble Mean = tloop(sqrt(ave(pow(Z-Zave,2),e=1,e=21))) Forecast Time --->
Ensemble Data Sets Behind GDS • File aggregation • Format translation • Subset over all dimensions • Server-side analysis • Data become more usable and accessible
TIGGE Data Behind GDS at NCAR • Perfect testbed for ensemble handling and GRIB2 interface • Boost to usage of TIGGE data • Forecasts organized by date and by provider • Time series of analyses • Nearly unbearable load on old hardware • 48-hour data embargo • Int’l agreement requires password protection
TIGGE Multi-Member Multi-Model Ensemble500mb Geopotential Height valid August 30, 2008 7-day Lead 5-day Lead 3-day Lead 1-day Lead
2008 Indian Monsoon Comparison of surface observations, TRMM satellite estimates, and TIGGE forecasts Station Observations TRMM Estimate ECMWF 1.5-day Forecast NCEP 1.5-day Forecast All-India Precipitation (mm/day)
TIGGE Forecasts of Hurricane Ikein the Gulf of Mexico, September 2008 00z 8 Sep 12z 8 Sep 00z 9 Sep 12z 9 Sep
Init:00z 8 Sep TIGGE Forecasts of Hurricane Ike valid: 12z 9 Sep - 00z 13 Sep 2008 Init:12z 8 Sep Init:00z 9 Sep Init:12z 9 Sep
TIGGE GDS http://cdp.ucar.edu:9090 Jennifer Miletta Adamsjma@iges.org