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ECMWF ReAnalysis (ERA) Data assimilation aspects

ECMWF Meteorological Training Course Numerical Weather Prediction Data Assimilation and Use of Satellite Data (NWP-DA). ECMWF ReAnalysis (ERA) Data assimilation aspects. Paul Poli paul.poli@ecmwf.int. Context of this module in the training course. Physics and Observations.

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ECMWF ReAnalysis (ERA) Data assimilation aspects

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  1. ECMWF Meteorological Training Course Numerical Weather Prediction Data Assimilation and Use of Satellite Data (NWP-DA) ECMWF ReAnalysis (ERA)Data assimilation aspects Paul Polipaul.poli@ecmwf.int ECMWF NWP-DA Reanalysis

  2. Context of this module in the training course Physics and Observations Analysis algorithms Applications Statistics Domains ECMWF NWP-DA Reanalysis

  3. Preamble: How to reconstruct the past? “Observations-only” climatology Gross exaggeration towards discontinuity Reanalysis “Model only” integration Gross exaggeration towards continuity ECMWF NWP-DA Reanalysis

  4. Reanalysis course outline ECMWF NWP-DA Reanalysis

  5. General concepts (common to all geosciences) ArgoFloat Polar-orbiting Satellite Geostationary Satellite Bathythermograph Aircraft Buoy Balloon, Radiosonde Ship • Errors in observations • Errors in models • Predictability • Variability Observer (Semi-) Automatic Station ECMWF NWP-DA Reanalysis

  6. Why reanalysis?Overall aim is a greater time-consistency of the products 1 May 2011 1 Feb 1985 Was there a sudden change inSouth Pole summer variability in 1997? 1 May 2011 1 Feb 1985 … probably not ECMWF NWP-DA Reanalysis

  7. More about time-consistencyRMS(Obs-Background), for radiosonde temperatures ECMWF Operations ERA-40 ERA-Interim ECMWF NWP-DA Reanalysis

  8. Time consistency: re-forecasts Northern Hemisphere SouthernHemisphere Forecast error anomaly correlation in percent, w.r.t. own analysis A. Simmons ECMWF NWP-DA Reanalysis

  9. Advantages against “observations-only” multi-decadal gridded datasets … for climate studies ECMWF NWP-DA Reanalysis

  10. Summary of the goals: reanalysis products should be consistent … …in Time …across Atmospheric Parameters …in the Horizontal …in the Vertical ECMWF NWP-DA Reanalysis

  11. Reanalysis course outline ECMWF NWP-DA Reanalysis

  12. background constraint observation constraint simulates the observations The ubiquitous data assimilation slide Observations, with error estimates Background forecast (propagates forward previous information, constrained by dynamical and physical relationships), with error estimates p 4DVAR Analysis Analysis Analysis Analysis Time 00UTC 12UTC 00UTC 25 January 1979 24 January 1979 12-hourly 4D-Var assimilation For eachanalysis, construct a costfunction and findits minimum: This produces the “most probable” atmospheric state ** In a maximum-likelihood sense, which is equivalent to the minimum variance, provided that background and observation errors are Gaussian, unbiased, uncorrelated with each other; all error covariancesare correctly specified; model errors are negligible within the 12-h analysis window ECMWF NWP-DA Reanalysis

  13. Under the hood of a reanalysis • Grab observations from archive • Basic pre-processing • Ingest observations into assimilation • Run 4D-Var (atmosphere) and wave/land-surface DA • Integrate forecast Generate monitoring and diagnostics plots Compute advanced diagnostics (energy budget…) Feed monitoring databases ECMWF NWP-DA Reanalysis

  14. Reanalysis componentsPart 1: Observations ECMWF NWP-DA Reanalysis

  15. Evolution of the observing system 1945 US Weather Bureau log(number of observations) D. Dee Satellites Manual stations, limited data exchange First radiosonde networks, systematic soundings International Geophysical Year: radiosonde network enhanced, especially in the Southern Hemisphere First operational satellite soundings (NOAA-2) Improved sounding from polar orbiters; Winds from geostationary orbit; More data from commercial aircraft; Drifting buoys More satellites, aircraft, buoys, ocean drifters. Radiosondes: fewer, but probe higher. Better knowledge of instrument errors. More obs. per hour per sensor. Upper-air soundings Surface observations Today 1938 1957 1979 1890 1973 ECMWF NWP-DA Reanalysis

  16. M M A A I I B B C C P P J J D D Q Q K K E E V V H H N N U U Evolution of radiosonde coverage 1958 1979 Ships maintaining fixed locations 2001 Average number of soundings per day: 1189 Average number of soundings per day: 1609 Average number of soundings per day: 1626 ECMWF NWP-DA Reanalysis

  17. Timeline of non-radiance observations in ERA-Interim ECMWF NWP-DA Reanalysis

  18. Timeline of radiance observations in ERA-Interim ECMWF NWP-DA Reanalysis

  19. Example of improved data coverage, through reprocessing of Meteosat data into Atmospheric Motion Vectors Early 1980s Expanded Low-resolution Winds ECMWF NWP-DA Reanalysis

  20. Reanalysis componentsPart 2: forecast model ECMWF NWP-DA Reanalysis

  21. 25 km resolution Illustration of resolution improvements Alps 40 km resolution Orography of the Western Alps(500m contours) Alps 80 km resol. Alps 125 km resol. 125 km resol. Alps ECMWF NWP-DA Reanalysis

  22. Reanalysis componentsPart 3: Data assimilation ECMWF NWP-DA Reanalysis

  23. Reconstructing the past: 7 November 1901, 12UTC Geopotential at … 1000 hPa … 500 hPa … 300 hPa Analysis made by Bjerknes Reanalysis from 20CR (56-member T62 EnKF, assimilating surface pressures only) Reanalysis from ERA-20C prototype (T159 deterministic 24-hour 4DVAR, assimilating surface pressures only) ECMWF NWP-DA Reanalysis

  24. Reconstructing the past: 7 November 1901, 12UTC Reanalysis from ERA-20C prototype: Z 1000 hPa(T159 deterministic 24-hour 4DVAR, assimilating surface pressures only) Observed winds (not assimilated in this experiment) Ps observation: Used Rejected VarQC-reject’d Advances in data assimilation can help extract more information from historic data that could ever be thought possible at the time the observations were collected ECMWF NWP-DA Reanalysis

  25. Time inconsistency exposed:tropical atmosphere (20S-20N) 1979 1990 2000 2011 ~1 hPa (K) Mean analysis increments Model levels (K) Sfc. JRA-25 ERA-40 (K) Mean analyses at 1hPa ERA-Interim ECMWF NWP-DA Reanalysis

  26. Estimation of observation error standard deviation, for surface pressure observations assimilated by Gil Compo et al. 20CR (hPa) Ship (rarely in altitude) reporting at sea-level 3 Buoy, reporting at sea-level 2 1 Station (sometimes in altitude) reporting at sea-level Stations (sometimes in altitude)reporting at station-level 1900 1950 2000 Applying the method of Desroziers et al., QJRMS, 2005 (DOI: 10.1256/qj.05.108) ECMWF NWP-DA Reanalysis

  27. 39-year time-series (1973-2012) of reanalysis departures, infra-red channel near 746 cm-1 Stdev(O-B), without bias correction (K) VTPR ERA-40 VTPR1, ch.7, 747.65 cm-1 VTPR2, ch.7, 747.55 cm-1 HIRS, ch.6, 748.27 cm-1 AIRS, ch.333 746.01 cm-1 HIRS ERA-40 HIRS ERA-Interim AIRS ERA-Interim ECMWF NWP-DA Reanalysis

  28. Bias correction schemes in ERA-Interim ECMWF NWP-DA Reanalysis

  29. Satellite AMSU-A channel number VarBC correcting for scan-angle bias in AMSUA Latitudes 20S-20N, ocean only 1998 2010 After METOP-A recalib. Before METOP-A recalibration Note: asymmetric shapes, drift over time, differences between satellites ECMWF NWP-DA Reanalysis

  30. AMSU-A biases, after variational bias correction Note: channel 14 is used as a reference to make sure the top stratosphere does not drift ECMWF NWP-DA Reanalysis

  31. Example of recalibration too large leading to systematic rejection of NOAA 9 HIRS channel 7 Global histograms of observed values 28 Dec 1984, 00UTC TIME 1 Feb 1985, 00UTC • Only current solution, if problem had been detected on time: would have been to force a VARBC restart • Future solutions: 1) detect such problems as they happen 2) relax back-ground VARBC tie to let observations in again Instrument probably got recalibrated • From this date on-wards, all data got bg-rejected 1 Feb 1985, 12UTC 2 Feb 1985, 00UTC 1 Mar 1985, 00UTC -20K -15K -10K -5K 0K 5K ECMWF NWP-DA Reanalysis

  32. We need to use time-varying background error covariances ERA-40 fit to assimilated radiosonde temperatures at 500hPa Assimilation of TOVS Stdev(O-B) SH 2K Stdev(O-B) NH 1K Stdev(O-A) SH Stdev(O-A) NH Jul 1977 Jan 1978 Jan 1979 Jan 1980 Jan 1981 Jan 1982 ECMWF NWP-DA Reanalysis

  33. Reanalysis course outline ECMWF NWP-DA Reanalysis

  34. A short history of atmospheric reanalysis • 1979: Observation datasets collected for the First GARP Global Atmospheric Research Program Experiment (FGGE): used a posteriorifor several years, to initialize models, compare performance and track progress in NWP. • 1983: Reanalysis concept proposed by Daley for monitoring the impact of forecasting system changes on the accuracy of forecasts • 1988: Concept proposed again, but for climate-change studies, in two separate papers: by Bengtsson and Shukla, and by Trenberth and Olson • 1990s: First-generation comprehensive global reanalysis products (~OI-based) • NASA/DAO (1980 - 1993) from USA • NCEP/NCAR (1948 - present) from USA • ERA-15 (1979 - 1993) from ECMWF – with significant funding from USA • Mid 2000s: Second-generation products (~3DVAR) • JRA-25 (1979 - 2004) from Japan • NCEP/DOE (1979 - present) from USA • ERA-40 (1958 - 2001) from ECMWF – with significant funding from EU FP5 • Today: Third generation of comprehensive global reanalyses (~better than 3DVAR) • NASA/GMAO-MERRA (1979 – present) from USA (IAU) • NCEP-CFSRR (1979 – 2008) from USA (land/ocean/ice coupling) • JRA-55 (1958 – 2012) from Japan (4DVAR) • 20-CR from USA (Ensemble Kalman Filter, surface pressure observations only) • ERA-Interim (1979 – present) from ECMWF (4DVAR) ECMWF NWP-DA Reanalysis

  35. Regional reanalysis and down-scaling from global reanalysis Long-term reanalysis using only surface-pressure observations: 20th Century Reanalysis (20CR) Short-term reanalysis for chemistry& aerosols Atmospheric reanalysis: becoming more diverse North American Regional Reanalysis Maximum gusts 26 December 1999 2m temperature 6UTC, 1 January 1999 ECMWF NWP-DA Reanalysis

  36. Thousands of users • 12000 registered users of ERA public data server • ≳5M fields retrieved daily by ECMWF and Member-State users • National mirror sites for ERA in several countries • And many citations • Paper on NCEP/NCAR reanalysis is most cited paper in geosciences • Paper on ERA-40 is most cited recently in the geosciences • Many references in IPCC Fourth Assessment report (AR4) ECMWF NWP-DA Reanalysis

  37. How (outside) users exploit reanalysis data • Monitor the observing system • Feedback on observational quality, bias corrections • Basis for homogenization studies of long data records • Develop climate models • Use reanalysis products for verification, diagnosis, calibrating output,, … • Drive users’ models/applications • Use reanalysis as large-scale initial or boundary conditions for smaller-scale models (global→regional; regional→local), in various fields: wind energy, ocean circulation, chemical transport and dispersion, crop yield, health indicators, … • Use climatologies derived from reanalysis for direct applications • Ocean waves, wind and solar power generation, insurance, … • Study short-term atmospheric processes and influences • Process of drying of air entering stratosphere, bird migration, … • Study of longer-term climate variability/trends • Requires caution due to changes in observations input • Lead to major findings in recent years in understanding variability How ECMWF users exploit reanalysis data • Baseline to track NWP scoreimprovements • Calibration for seasonal forecasting system • Reference to diagnose changes brought by model improvements ECMWF NWP-DA Reanalysis

  38. Growing recognition of reanalysis for climate application: BAMS “State of the Climate in 2009” Plate 2.1. Global annual anomaly maps for those variables for which it is possible to create a meaningful 2009 anomaly estimate. Climatologies differ among variables, but spatial patterns should largely dominate over choices of climatology period. Dataset sources/names are as follows: lower stratospheric temperature (RSS MSU); lower tropospheric temperature (ERA-interim); surface temperature (NOAA NCDC); cloudiness (PATMOS-x); total column water vapor (SSM/I over ocean, ground based GPS over land); precipitation (RSS over ocean, GHCN (gridded) over land); river discharge (authors); mean sea level pressure (HadSLP2r); wind speed (AMSR-E); ozone (GOME2); FAPAR (SeaWIFS); Biomass Burning (GEMS/MACC). See relevant section text and figures for more details. ECMWF NWP-DA Reanalysis

  39. ERA web visualization facilities • Selection of key meteorological parameters • Circulation indices Very strong NAO- during winter 2010 ECMWF NWP-DA Reanalysis

  40. Temperature: Global anomalies July 2010 ECMWF NWP-DA Reanalysis

  41. (mm/day) Rainfall: Regional anomalies for 1x1 degree boxes Anomalies are computed with respect to (1989-2009) means for each month from ERA and GPCC respectively. Time series of 12-month running means are shown here. ECMWF NWP-DA Reanalysis

  42. Wind speed: spectral analysis of surface station data 1989-2010 Roches Point station Observations ERA-Interim first-guess Nombre Vitesse du vent (m/s) Reanalysisproperlyreproducingdaily, seasonal, and interannualtimescales, but missingdiurnalvariability LombperiodogramGiven observations irregularlyspaced, and a frequency w, fit a function f(t)=A sin(wt) + B cos(wt) Time period (y=year, m=month, d=day) ECMWF NWP-DA Reanalysis

  43. Clouds: simple comparison ERA-Interim total cloud cover19 May 1979, 12 UTC TIROS-N AVHRR VIS19 May 1979, 15 UTC --Any takers for assimilating these data in our next reanalysis? ECMWF NWP-DA Reanalysis

  44. Reanalysis course outline ECMWF NWP-DA Reanalysis

  45. Summary of important concepts • Reanalysis does not produce “gridded observations” • But it enables to extract information from observations in one, unique, theoretically consistent framework • Reanalysis sits at the end of the (long) meteorological research and development chain that encompasses • observation and measurement collection, • observation processing and data exchange, • numerical weather prediction modelling and data assimilation • Unlike NWP, a very important concern in reanalysis is the consistency in time, over several years • Reanalysis is bridging slowly, but surely, the gap between the “weather datasets” and the “climate datasets” • Resolution gets finer • Reanalyses cover longer time periods, without gap • Helps different communities work together • Reanalysis has developed into a powerful tool for many users and applications ECMWF NWP-DA Reanalysis

  46. Current status of global reanalysis& Future outlook • It is worth repeating as all ingredients continue to evolve: • Models are getting better • Data assimilation methods are getting better • Observation processing is improving • Old observations (paper records) are being rescued • The technical infrastructure for running & monitoring improves constantly • With each new reanalysis we improve our understanding of systematic errors in the various components of the observing system • Major challenges for a future comprehensive reanalysis project: • Bringing in additional observations (not dealt with in ERA-Interim) • Dealing with changing background quality over time • Dealing with model bias, tied to problems with trends interpretation • Coupling with ocean and land surface • Making observations used in reanalysis more accessible to users • Providing meaningful uncertainty estimates for the reanalysis products ERA-CLIM ECMWF NWP-DA Reanalysis

  47. ERA-CLIM: data recovery efforts ECMWF NWP-DA Reanalysis

  48. Further reading and on-line material • Kalnay et al. (1996), “The NCEP/NCAR 40-Year Reanalysis Project”, Bull. Am. Meteorol. Soc.77 (3), 437-471 • Uppala et al. (2005), “The ERA-40 reanalysis”, Q. J. R. Meteorol. Soc.131 (612), 2961-3012, doi:10.1256/qj.04.176 • Bengtsson et al. (2007), “The need for a dynamical climate reanalysis”, Bull. Am. Meteor. Soc.88 (4), 495-501 • SciDAC Review (2008), “Bridging the gap between weather and climate”, on the web at http://www.scidacreview.org/0801/pdf/climate.pdf with contributions from G. P. Compo and J. S. Whitaker • European reanalysis (ERA): http://www.ecmwf.int/research/era • NCEP/NCAR reanalysis: http://www.cdc.noaa.gov/data/reanalysis/reanalysis.shtml • NCEP CFSR: http://cfs.ncep.noaa.gov/cfsr/ • Japanese 25-year reanalysis (JRA-25): http://jra.kishou.go.jp • NASA GMAO Modern Era Retrospective-analysis for Research and Applications (MERRA) http://gmao.gsfc.nasa.gov/research/merra/ • Dee et al. (2011), “The ERA-Interim reanalysis: configuration and performance of the data assimilation system ”, Q. J. R. Meteorol. Soc., 137 (656), 553-597 • http://www.oldweather.org • http://www.data-rescue-at-home.org ECMWF NWP-DA Reanalysis

  49. ERA-Interim data availability and access • Currently Jan 1979 until present, with monthly updates (2-3 month delay) • Resolution: T255L60, 6-hourly upper-air fields, 3-hourly surface fields • Analysis + forecast products; monthly averages • Access to products: • Member state users: MARS: full access • All users: ECMWF Public Data Server: http://data-portal.ecmwf.int/data/d/interim_full_daily/ ECMWF NWP-DA Reanalysis

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