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New Resources in the Research Data Archive Doug Schuster.

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Presentation on theme: "New Resources in the Research Data Archive Doug Schuster."— Presentation transcript:

1 New Resources in the Research Data Archive Doug Schuster

2 Topic Outline lNew Resources lSearch/Discovery and Data Delivery lTIGGE lJRA-25 lRoutine Updates

3 Data Search, Discovery and Delivery lPopular Datasets lGoogle Style Search lDrill Down Style Search lFile Level Metadata lExample: lSearch for model generated tropical cyclone track data using “Drill Down” method.

4 Data Search, Discovery, and Delivery

5 Data Search, Discovery, and Delivery (Drill Down)

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7 Data Search, Discovery, and Delivery (File Level Metadata)

8 Background on TIGGE WMO World Weather Research Programme THORPEX –THe Observing system Research and Predictability EXperiment –THORPEX Interactive Global Grand Ensemble (TIGGE) Archive supports research Grand Ensemble = multiple NWP centers ensembles are combined (an ensemble of ensembles) 10 international NWP Centers contributing to TIGGE

9 Background on TIGGE Three mirrored archive centers NCAR ECMWF CMA {Shared System Development!} Daily Data Flow Metrics –245 GB –1.6 Million gridded fields as separate data packets –3000+ Files/day

10 Data Receipt Archive Centre Current Data Provider NCAR NCEP CMC UKMO ECMWF MeteoFrance JMA KMA CMA BoM CPTEC IDD/LDM HTTP FTP Unidata IDD/LDM Internet Data Distribution / Local Data Manager Commodity internet application to send and receive data NCDC

11 Archive Summary Online Data –Period, most recent two weeks –~ 4 TB, public products –~ 2 TB, data preparation, subsetting, DB Offline Data –Full period of record –~ 200 TB, NCAR MSS system

12 Major Challenges Insure data receipt, build complete archive  Exchange manifest files as part of IDD/LDM data transmission between Archive centers  Verify send, receive  Automated resend requests for missing fields  Collate data fields into different files types  Harvest and hold metadata in MySQL DB’s  Identify location of every field in file set  Updated often  Critical for users interface and background data processing

13 Major Challenges  Access system must accurately display what common parameters are available as users make selections  Driven by multi-center research (Grand Ensemble)  Parameters vary between centers.

14 Variance between centers

15 Get Forecast Data NCAR online file archive Selection options (Portal or RDA) Center(s) Date File type (sl, pl, etc) Initialization time Forecast length Download Options Point and click using browser, one file at a time Script to run on local machine User and password encrypted ‘wget’ commands background process to access all files User customized files Selection options (Portal) Same as for files, plus Parameter Subsets Grid Interpolation Spatial subsets Formats, GRIB2, NetCDF Delayed ModeReal Time Two User Interfaces

16 User access selection demonstration Animation, what you will see –Multiple centers (ECMWF, UKMO, NCEP, CMA, CMC, KMA) –Fields/Parameters (Geopotential Height, 2m Temperature) –Levels (500 hPa, Single Level) –Spatial and temporal ranges (Global, 3-days, 12Z initializations, 48 hour forecasts) –Regridding to common spatial resolution (1.5°) –Output format (netCDF)

17 Sample Data Request for an Event

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21 Retrieve Completed Subset

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23 Subset Request Animation

24 Gustav/Hannah Animation

25 Features of JRA-25/JCDAS at NCAR All data available through web/RDA portal and NCAR MSS, 11 TB Available dates, 1979 though different data products – 4 x daily, GRIB1 format –Monthly mean, netCDF (NCAR derived from binary) format All data users are registered and must agree to JMA’s ‘Condition of Use’

26 Typhoon Sepat, 16 August 2007 Images courtesy Dave Stepaniak

27 Routine Updates NCEP FNL Global Tropospheric Analysis (Daily) BUFR/PREPBUFR obs. data (Weekly) NCEP FNL Global Tropospheric Analysis (Daily) BUFR/PREPBUFR obs. data (Weekly) Unidata IDD data (Daily) NetCDF format obs collected from GTS IDD model data (GRIB-2)  GFS  NAM  RUC Unidata IDD data (Daily) NetCDF format obs collected from GTS IDD model data (GRIB-2)  GFS  NAM  RUC

28 Routine Updates SST NCEP OI Global SST 1x1 Deg (weekly) NOAA OI Global 0.25 x 0.25 SST (monthly) Hadley Centre Global Sea Ice and SST (monthly) SST NCEP OI Global SST 1x1 Deg (weekly) NOAA OI Global 0.25 x 0.25 SST (monthly) Hadley Centre Global Sea Ice and SST (monthly) Reanalysis NNR Yearly updates NARR Yearly updates JRA-25 Reanalysis NNR Yearly updates NARR Yearly updates JRA-25

29 Questions?

30 Lessons Learned  Manifest files and automated resend are critical for a complete archive  The impact of different contributions from the NWP centers across archive cannot be under estimated  There are important design considerations to insure prompt browser interactions  Caching data from the DB

31 Lessons Learned  Computational resource requirements ramp up quickly with multi-dimensional problems  D’s, center, ensemble member, parameter, forecast length, etc.  Archive file structure choices greatly impact subsetting ability  TIGGE currently based on synoptic order  Time-series by parameter could be better?

32 Major Challenges  Limited online storage – 4 TB, ≅ 2 weeks temporal coverage  Full archive on NCAR Mass Storage System  User registration and metrics required  Accept data policy; for research and education only  48 hour delay from forecast initialization time


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