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Ensemble Handlingin GrADS
Jennifer M. Adams 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, GRIB1&2, 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)
A GrADS Graphics Example
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://servername/filename instead of /disk/filename
News from GrADS/GDS Team
GrADS has a 5th grid dimension for ensembles GrADS has a GRIB2 interface GDS can serve any GrADS data set GrADS is a client for all OPeNDAP data sets• GrADS will support GIS-compatible outputs
The New Ensemble Dimension in GrADS
• A 5th grid dimension for ensemble members‘set X, Y, Z, T, or E’ or ‘set lon, lat, lev, time, or ens’
• A virtual dimension for forecast time offset‘display temp(ft=2)’‘display temp(ftime=24hr)’
GrADS Metadata Requirements for Ensemble Members
• Unique name / number• Initial time• Length• If GRIB2, some additional octet values• One time axis spans all members• All members must have common X, Y, Z axes
GrADS GRIB2 Descriptor File
Wesley’s g2ctl works very well, but doesn’t handle EDEF (yet). DSET /gens/prod/gefs.%iy4%im2%id2/%ih2/pgrb2a/ge%e.t%ih2z.pgrb2af%f2TDEF 17 linear 00z09oct2008 6hrEDEF 23avg 17 00z09oct2008 0spr 17 00z09oct2008 2c00 17 00z09oct2008 1,0p01 17 00z09oct2008 3,1p02 17 00z09oct2008 3,2p03 17 00z09oct2008 3,3p04 17 00z09oct2008 3,4. . .p19 17 00z09oct2008 3,19p20 17 00z09oct2008 3,20ENDEDEF@ ens String avg Unweighted mean of all members@ ens String spr Standard deviation with respect to ensemble mean@ ens String c00 Control forecast@ ens String p01 Positively perturbed forecast
The GRIB2 codes are octets 35 and 36 from Section 4 (PDT # 1, 2, 11, and 12)
Examples of Ensemble Data Sets
• NCEP GFS Ensembles (GENS)• NCEP Climate Forecast System (CFS)• NCEP Short Range Ensemble Forecasts (SREF)• ESRL MRF Reforecasting Experiment • WCRP CMIP3 Multi-Model Data (IPCC AR4)• TIGGE
• Data become more usable and accessible
• Subsets over all dimensions
• Server-side analysis
• File aggregation
• Format translation
• Ensemble metadata standards:
Ensemble Data Sets Behind GDS
Ensemble Forecast Time Series (Longitude, Latitude, and Level are fixed)
Forecast Time --->
Ensemble Forecast Grid (Longitude, Latitude, and Level are fixed)
Forecast Time --->
Ens
embl
e M
embe
r
Ten Ensemble Forecasts (Longitude, Latitude, and Level are fixed)
Forecast Time --->
Ens
embl
e M
embe
r
Time Axis ---->
Ens
embl
e M
embe
r
CFS Daily Hindcast (Longitude, Latitude, and Level are fixed)
Ensemble Forecast Time Series (Longitude, Latitude, and Level are fixed)
Forecast Time --->
Ensemble Mean = tloop(ave(Z,e=2,e=23))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 --->
+ Perfect testbed for ensemble handling and GRIB2 interface+ Boost to usage of TIGGE data+ Forecasts sorted 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 Data Behind GDS at NCAR
TIGGE Multi-Member Multi-Model Ensemble 500mb Geopotential Height valid August 30, 2008
7-day Lead
3-day Lead
5-day Lead
1-day Lead
TIGGE MME Forecast Error and Ensemble Spread 500mb Geopotential Height valid August 30, 2008
7-day Lead
3-day Lead
5-day Lead
1-day Lead
TIGGE Forecasts of Hurricane Ike valid: 12z 9 Sep - 00z 13 Sep in
it:
00z
8 S
epin
it: 1
2z 8
Sep
init
: 00z
9 S
epin
it: 1
2z 9
Sep