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Observation Feedback from Reanalysis

Observation Feedback from Reanalysis. Paul Poli, Cristian Codorean , Hans Hersbach , Dick Dee. Observation Feedback from Reanalysis. What is this? Applications Facility: Observation Feedback Archive Your wish-list?. What is “Observation Feedback from Reanalysis” ? (1/2).

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Observation Feedback from Reanalysis

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  1. Observation Feedback from Reanalysis Paul Poli, CristianCodorean, Hans Hersbach, Dick Dee 4th ACRE workshop, 21-23 Sep 2011, De Bilt

  2. Observation Feedback from Reanalysis • What is this? • Applications • Facility: Observation Feedback Archive • Your wish-list? 4th ACRE workshop, 21-23 Sep 2011, De Bilt

  3. What is“Observation Feedback from Reanalysis” ? (1/2) Observations, with error estimates Background forecast (propagates forward previous information, constrained by dynamical and physical relationships), with error estimates p • Reanalysis “reconstructs” the weather by using all available observations, to optimally determine an “optimal trajectory” of the weather over a few hours (say 12 hours here: the trajectory is issued by a forecast model) • We do this with a forward integration: data assimilation: 4DVAR Analysis Analysis Analysis Analysis Time 00UTC 12UTC 00UTC An ancient date + 1 day An ancient date 4th ACRE workshop, 21-23 Sep 2011, De Bilt

  4. What is “Observation Feedback from Reanalysis” ? (2/2) • In this integration, each observation is compared with the reanalysis product • Before the observation is assimilated: • Comparison with the background • Difference is background departure, also called observation innovation • After the observation is assimilated: • We compare with the analysis • Difference is analysis departure, also called observation residual • Also, the assimilation procedure may involve bias correction, which means differences between observation and reanalysis should be considered • Before bias correction: uncorrected background departure • After bias correction: (corrected) background departure Observationwith error estimate Analysis trajectory Background forecast with error estimate 4th ACRE workshop, 21-23 Sep 2011, De Bilt

  5. ISPD v2.2 All data in 20CR for year 1900 Break-down by report type: LAND / SHIP /Cyclone tracks 4th ACRE workshop, 21-23 Sep 2011, De Bilt

  6. ISPD v2.2 Data used by 20CR for year 1900 Break-down by reporting practice: SEA LEVEL / STATION LEVEL 4th ACRE workshop, 21-23 Sep 2011, De Bilt

  7. ISPD v2.2 Bias corrections applied by 20CR, year 1900 4th ACRE workshop, 21-23 Sep 2011, De Bilt

  8. ISPD v2.2 Background departures (after bias correction) from 20CR, year 1900 4th ACRE workshop, 21-23 Sep 2011, De Bilt

  9. ISPD v2.2 Background and analysis departures from 20CR, year 1900 4th ACRE workshop, 21-23 Sep 2011, De Bilt

  10. Also, learn from long time-series • Data homogenization • U. Vienna • For ERA-20C • ERA-CLIM (WP3) surface-pressure-only reanalysis of the 20th century, using boundary and forcing data from (WP2) • We hope to be able to learn from the 20CR feedbackby running break detection algorithms developed by ERA-CLIM partners (WP4) 4th ACRE workshop, 21-23 Sep 2011, De Bilt

  11. Generalization • One wants to be able to look at • Data counts • But also • Mean, • Stdev, • RMS • Min, max ... • (aggregate functions) • Of • Background departures • Uncorrected • Corrected • Analysis departures • And to break-down the results by: • Dates and times • Regional domains • Altitude bands • Low areas • Mountains • … • Observation report types • Surface stations • Ships • Buoys • … • Usage types (used or not) • Stations • Any other dimension of interest 4th ACRE workshop, 21-23 Sep 2011, De Bilt

  12. Letter to Santa Dear Santa, Besides data counts by station and so on, I would like to be able to compare stations in the same regions, compare data collections (looking for some possible systematic errors…), compare different versions of databanks (say ISPD v2.2 versus ISPD v3) compare different reanalyses, and slice all this in any dimension: map, time-series… I have left milk and cookies for you by the tree. Seriously, is that asking too much? 4th ACRE workshop, 21-23 Sep 2011, De Bilt

  13. Having (recently?) learnt that Santa *may* not exist (apologies if I disappoint anyone else…) • We have chosen to follow a two-step approach: • First, build an infrastructure where all the needed information can be stored and retrieved: • Observation Feedback Archive • Second, we have developed some ideas on how to build queries in a way that reduces the problem of computing a set of statistics into a unique SQL query • ERA-CLIM will deliver the first of these two points • I will only talk briefly about the second point 4th ACRE workshop, 21-23 Sep 2011, De Bilt

  14. Schematic contents of the Observation Feedback Archive ObservationFeedbackArchive • Observation record attributes: • Time and geolocation (lat, lon, alt.) • Observation report type (buoy…) • Geophysical variable (T,p,q…) • Source (=which databank), collection, station name • Unique identifier* • Reporting practice* • Observation value • Feedback added value: • Model land-sea mask • Model orography • Background & analysis dep. • Obs. bias correction estimate(~ accuracy) • Probable obs. error stdev. (~ 1-sigma precision) Reanalyses(20CR, ERA-40…) Databanks(ISPD 2.2…) Supports SQL queries Data collections (Byrd Antarctic expeditions…) Stations/ships(DeBilt, Lusitania…) Observation record81513 Pa at station level (1861m) AGUASCAL, Mexico, 17 Sep 1900 at 23UTC 4th ACRE workshop, 21-23 Sep 2011, De Bilt

  15. Observation Feedback Archive Interface Browser Auto-update of the availability, based on selection Reanalysis Decade / Year / Month Vertical sounding? Observation report type Geophysical variable Assimilated? Q:SHOULD OTHER DIMENSIONS BE INCLUDED FOR QUICK BROWSING? Note: we will eventually display proper names instead of numbers (these numbers are only intelligible by persons familiar with the specifics of our observation archive nomenclature) 4th ACRE workshop, 21-23 Sep 2011, De Bilt

  16. Anticipated functions of the interface • Locate datasets rapidly • In a few clicks on one page • Submit a query • Standard record attributes are returned to the user (text format) Possible additions: • User choice of the attributes to be retrieved • Basic plotting of the spatio-temporal data coverage • Map • Time-series of data counts • Other formats for returning data to users Q: ANYTHING ELSE? 4th ACRE workshop, 21-23 Sep 2011, De Bilt

  17. Second step… • Assuming all the data are in a SQL-type database, how can you get statistics computed for you? (without asking someone to write code to do this) • What is the domain of the search? • WHERE • What quantities are to be computed? • SELECT + aggregate functions, e.g. avg() • What are the independent coordinates against which you want to compute your statistics? • GROUP BY: can act on bins [], or discrete values • That’s all you need • A generic algorithm has been written to apply this logic to build a SQL query and decode results into a structured dataset (JSON) 4th ACRE workshop, 21-23 Sep 2011, De Bilt

  18. Conclusions: Observation Feedback from Reanalysis • Observations + feedback from reanalyses will be stored in a centralized repository, the Observation Feedback Archive • SQL functionality, back-up, etc… • Will provide user-friendly… • …browsing of the data (via a web interface) • … access to the data (serving text files) • Reanalysis feedback will provide powerful information on: • Consistency between various data sets • Systematic errors • Changes in behavior (breaks)… in short … data quality and problems that remain to be solved! • All outputs from our future reanalyses will be stored on this Observation Feedback Archive, a PUBLIC facility • CONSEQUENTLY, WE WILL NOT USE OBSERVATIONS THAT HAVE RESTRICTIONS 4th ACRE workshop, 21-23 Sep 2011, De Bilt

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