1 / 25

IHOP-2002 Data Archive and Development of Composite Data Sets

IHOP-2002 Data Archive and Development of Composite Data Sets. Steven F. Williams, Scot M. Loehrer, Linda E. Cully, Darren R. Gallant, Janine Goldstein, and Don Stott UCAR/Joint Office for Science Support IHOP-2002 Spring Science Workshop Boulder, CO March 2003.

judithh
Download Presentation

IHOP-2002 Data Archive and Development of Composite Data Sets

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. IHOP-2002 Data Archive and Development of Composite Data Sets Steven F. Williams, Scot M. Loehrer, Linda E. Cully, Darren R. Gallant, Janine Goldstein, and Don Stott UCAR/Joint Office for Science Support IHOP-2002 Spring Science Workshop Boulder, CO March 2003

  2. http://www.joss.ucar.edu/ihop/dm/

  3. IHOP-2002 Data Policy and Protocol

  4. http://www.joss.ucar.edu/ihop/dm/photo.html

  5. IHOP-2002 DATA BASE STATUS(as of 24 March 2003) • 196 of 254 Data sets (77%) have been submitted or linked. 183 are available on-line (13 in progress) • Field Catalog (w/reports and preliminary products) is on-line • Data submission instructions and guidelines are available on-line • For details see: http://www.joss.ucar.edu/ihop/dm/

  6. Composites: What and Why A composite dataset is a collection (over some time period and region) of similar data (e.g. surface met) from a variety of sources, put into a common format, and passed through a uniform quality control. Why does UCAR/JOSS develop composites? - Provides data in a uniform format with QC. - Allows determination of network/site problems. - Useful for model applications. - Prevents duplication of effort.

  7. Composite Data Sets To Be Developed by UCAR/JOSS for IHOP-2002 • Surface Meteorological - 1 min, 5 min, and Hourly • Precipitation - 15 min, Hourly, and Daily • Soundings - High Resolution and 5 hPa

  8. 1-min Surface Meteorological Data Composite (65 stations) ASOS (41) ARM SMOS (14) ABLE AWS (5) NCAR Supp. (5)

  9. 5-min Surface Meteorological Data Composite (224 stations) Oklahoma Mesonet (115) NCAR ISS/ISFF (10) West Texas Mesonet (34) 1-min sites (65)

  10. Hourly Surface Meteorological Data Composite (743 stations) CoAgMet (*) (23) AWOS (*) (110) RAWS (+) (10) SCAN (o) (6) GWMD (*) (18) Ameriflux (+) (3) HPCN (o) (72) Texas ET (o) (19) KVII-TV (+) (4) MADIS (o) (246) NMSU (*) (7) 5-min sites (o) (225)

  11. 15-minute Precipitation Composite NCDC Coop (429) 5-min surface (224)

  12. Hourly Precipitation Composite NCDC Coop (509) NCEP hourly (1155) Hourly Met (743)

  13. Daily Precipitation Composite NCDC Coop (1581) Hourly Met (743) NCEP Daily (1611)

  14. Incomplete? Incomplete? Incomplete? Time ACTION GENERAL DATASET PROCESSING LIFE CYCLE • Phone, email, paperwork, $, meetings, • procurement arrangements. • (Days to months) • (Minutes to months) • Auto retrieval, FTP, online requests, • etc. (minutes to days) • Verify AOI, TOI, Format; spot check • values, visual inspection or limited • processing (Minutes to days) • Format change, new parameters • manual “cleanup”, etc. • (Days to months) • Purchase hardware, configuration • management, etc. • (Minutes to days) • Put into common format, run data checkers • “check gross limits” (Days to months) • HQC for SFC, Gross limits for precip, • Composite level and value checkers, limited • statistics (% G, B, D by network, stn, • parameter for SFC). (days to months) 1 Contact SRC Agency to Acquire Data and Metadata 2 Wait for SRC Agency Data/Metadata Preparation days/months 3 Acquire Data and Metadata OR Create “Best” Metadata 4 Examine Data & Metadata for Consistency and Completeness 5 Develop New Software or Modify Existing Software 6 Acquire Computer System Space and Time weeks/months 7 Process Data and Metadata then Check 8 Form Composite with Like Datasets Add stn info to final list 9 Perform QC and Final Data Checks. Generate Statistics Processing Problems? months/year Prepare ASCii format data & docs for CD-Roms Create EBUFR format data & DOCS for CODIAC Prepare, manufacture, & distribute CD-Roms Load Data and Metadata onto CODIAC z:\cully\Esop96\esop3.ppt

  15. QC of Surface Meteorological Data • Parameters: Calculated Sea Level Pressure, Sea Level Pressure, Temperature, Dew Point, Wind Speed, Wind Direction • Expected value derived from objective analysis method adapted from Cressman (1959) and Barnes (1964) using 300km Radius of Influence. θe = Expected Value θi= Observation at site i wi = Weight factor for site i where wi = 1/di di= Distance between site i and QC site Σθiwi Σwi θe = i i

  16. QC of Surface Meteorological Data • Deviation between actual and expected values subjected to dynamically determined limits. Values compared at like solar times. Limits are sensitive to diurnal and intra-seasonal variations and dependent upon spatial and temporal continuity. • Additional consistency checks, visual quality assurance, and gross limit checks are typically also applied. • Precipitation gross limit checked based on frequency. • Data are never changed, only flagged. • α= Normalization Factor (predetermined) • σ = Standard Deviation (computed over previous 30 days for each time; 15 obs minimum) θa - θeασ

  17. What Can Lead to Surface Data Being Flagged? • Instrument failure, bias, drift, random errors • Incorrect latitude, longitude, or elevation • Differences in siting or height of instruments • Misidentified units, dates, or stations • Terrain impacts • Data problems at surrounding stations • Unique meteorological phenomena

  18. Obvious Problems Detected

  19. Subtle Problems Detected

  20. Embedded Accumulative Precipitation

  21. High Resolution and 5 hPa Radiosonde Composites Fixed Sites: Mobile Sites: NWS (14) ARM (5) ISS (1) Falcon Drops (86) Learjet (330)NCAR GLASS (146) NSSL CLASS (80)

  22. UCAR/JOSS Atmospheric Sounding Processing Procedures Observing System Output e.g. NWS Micro-ART Convert to JOSS Quality-control Calculate Derived Format (ASCII) Parameters e.g., u, v, dz/dt Gross Limit Checks Automated Checks QC Flags Error Files Vertical Consistency Checks Visual Examination QC Flags High-resolution and/or Interpolated Vertical Composite e.g., 5 hPa Inventory, Archive, and Develop Metadata Data and Metadata Available Online

  23. Wind Oscillations • Wind oscillations at low elevation angles (approaching limiting angles) due in part to questionable angles. Adjusted Algorithm Original Algorithm

  24. Summary • The High Resolution and 5 hPa Radiosonde Composites have been completed and are available: http://www.joss.ucar.edu/ihop/dm • Surface Meteorological (1-min, 5-min, and hourly) and Precipitation (15-min, hourly, and daily) Composites currently being developed. Planned completion Fall 2003.

More Related