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Climate Modeling SupportatGES DISC Forward Stream data set and subsets GMAO MERRA Data Set 1979 – Present
Forward stream support • ½ deg data set resolution • Restricted access data set • Parent granule data continuously archived and available by FTP • 15 Parameter subsets created and pushed/pulled to various instrument teams. Data provided as 60 day rolling archive. • Higher resolution data set HDF5 and ¼ deg data set shortly to be delivered by GMAO to DISC • Initially provided as restricted access dataset • Currently being considered by GMAO for public distribution
MERRA Data Set • Time period 1979 – Present (Feb. 2011) • Data holdings ~ 75.5 TBS, 284,020 files • Data Distribution • Cumulative stats (12/08 – 04/11) • 618 TBs • 37.8 Million files • Apr/2011 stats • 46.0 TBS • 4.3 Million files
GMAO MERRA Obsvs Model dataset • New dataset more specialized than MERRA • Provides a deeper understanding of MERRA • User may see a strange/ questionable model feature • Input observed data can be compared with model output to evaluate reasonableness/error of feature • Obs satellite/conventional data on same model grid to facilitate inter-comparison analyses
Gridded data characteristics-1 • Total data volume ~ 1 TB • Satellites (SSMI, NOAA, AIRS, AMSU,HIRS, MSU, etc) • Diurnal, monthly brightness temps • Conventional data buoy, ship, soundings, etc • Daily, sub-daily • Temporal period varies with satellite • Number of products ~150 • each prod. requires a DIFF for GCMD publication • Each product requires a GRADS control file
Gridded data characteristics-2 • Three grid types • Observed minus Analysis • Observed minus Forecast • Observed values • Variables • Mean difference • SD of difference • # observed values per grid box
Planned User Interface • Similar but separated from MERRA portal ordering page • Two tier product grouping • Satellite • Sub-product • Access services GRADS and FTP (no subsetting) • normal level of user support
Questions to UWG • Does UWG consider that this dataset fits in to DISC’s climate modeling support role? • Should we consider ingesting other datasets of this type to facilitate modeling research studies?
Some background notes • Close collaboration with GMAO (Mike, Arlindo & Gi-Kong) has resulted in production of a very high quality distribution service which has been well received and praised by our user community. • Excellent support and hard work by our contractors (Dana, Bhagi, Guang-dih) • Arlindo author of our grad’s subsetter (LATS4D) and new observed vs model datset.