1 / 34

PP KENDA-O : Km-Scale Ensemble-Based Data Assimilation

Status Report for KENDA-O. PP KENDA-O : Km-Scale Ensemble-Based Data Assimilation for the use of High-Resolution Observations (Sept. 2015 – Aug. 2020) Task 1: further development of LETKF scheme (conventional obs , operationalisation )

fowlerwilliam
Download Presentation

PP KENDA-O : Km-Scale Ensemble-Based Data Assimilation

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. Status Report for KENDA-O • PP KENDA-O : Km-Scale Ensemble-Based Data Assimilation • for the use of High-Resolution Observations • (Sept. 2015 – Aug. 2020) • Task 1: further development of LETKF scheme (conventional obs, operationalisation) •  understanding discrepancies betw. DWD and MeteoSwissKENDA results • Task 2: extended use of observations •  Mode-S operational at DWD • Task 3: lower boundary: soil moisture analysis using satellite soil moisture data •  new fellow Paride Ferrante familiarizing, SM-DA runs in parallel suite • Task 4: adaptation to ICON-LAM  schedule , • hybrid methods (also particle filters)  paper submitted

  2. Overview Task 1: Further development of KENDA DWD • (lots of) technical work (diagnostic datool; BACY-1; ‘Swiss experiment’) • bias correction for AMDAR temperature (mixed impact) • can AMDAR be omitted if Mode-S are used?  experiment: moderate negative impact, particularly on precipitation MeteoSwiss • parallel KENDA COSMO-E suite (up to +24h) with additive inflation since 1 Jan. 2018 (DACE V1.53; but still not with 24-bit coding of T_SO) • 2-year position on additive covariance inflation / regional B matrix: Claire Merker • NMC method, based on COSMO-E re-forecasts for 1 year • visit at DWD 30 – 31 Jan. (coord., learn about B matrix generation in DACE, …)

  3. Overview Task 1: Further development of KENDA ARPAE-SIMC • continued tests of KENDA initial conditions for the 2.2 km ensemble COMET • KENDA slightly worse than COMET-LETKF, continued investigation • implementation + test of KENDA at higher resolution (2.2 km) Stochastic Pattern Generator (Roshydromet) • work on a new Bayesian model Error Modeling Scheme (BEMS) • combines SPPT and an additive perturbation scheme • produces non-Gaussian perturbations consistent with model statistics, for meaningful humidity / cloud fields • the spatio-temporal aspect is simulated using the SPG

  4. Overview Task 2: Extended use of observations 3-D radar (radial velocity Vr , reflectivity Z) • Vr: Elisabeth Bauernschubert: • 5-week convective summer exp. (revised obs errors, elevations 0.5°, 1.5°, 3.5°): small positive impact on precipitation, reduced when Mode-S is also used; tiny benefit on (rs/sfc) wind; positive in radar verif up to +4h • neutral impact on low stratus; further winter test to be evaluated • Z: Axel Seifert, Alberto de Lozar: • positive impact from TKE cycling • issue: occasionally large spurious circles of reflectivity in 0-h forecasts, why? • plans (outside KENDA-O): investigate role of model errors in DA (rel. to LES), tune (micro)physics to better match obs (radar, satellite) • Uli Blahak: fixed position for radar, but fully busy with coordinating SINFONY  Christian Welzbacher ~ 50% ? • Z: Virginia Poli, Thomas Gastaldo (ARPAE-SIMC): DA with  1 Italian radars: • continued sensitivity exp. (using different obs errors for Z) • technical work

  5. Overview Task 2: Extended use of observations GNSS slant total delay (STD, Michael Bender) • experiments: positive impact on precip so far, mixed otherwise (negative at low levels) • obs positioned further aloft: negative impact • unexpected result finally identified to be due to a code bug in DACE/LETKF (related to vertical localisation set in namelistfor a specific obs type)  progress slowed down

  6. Overview Task 2: Extended use of observations SEVIRI radiances • direct use of all-sky (cloudy) SEVIRI WV + IR window radiances: Axel Hutt continued work on clear-skyWV radiances: • revised Jacobian / vertical localisation (no impact so far) • bias correction  small positive impact from clear-sky WV data for the first time • use of NWC-SAF cloud top height (CTH) product: currently no resources • (outside KENDA-O:) direct use of all-sky (cloudy) SEVIRI VIS/NIR radiances • first cycled DA test, working on vertical localisation, Albedo, etc.

  7. Overview Task 2: Extended use of observations Screen-level obs • RH2M (+ T2M) : preliminary tests at DWD • 10-m wind : test w. new criteria (dep on. roughness length + d2zs/(dx2dy2)) for station selection: ~ neutral impact Mode-S aircraft • winter tests, operational at DWD (see later) Ground-based remote sensing (T + qv prof.: Raman lidar, MW radiometer) • MCH: proof-of-concept assimilation trial with COSMO-7 by nudging: 0.5-hourly profiles are assimilated successfully AMSU, ATMS, IASI • nothing done

  8. Task 4.1 KENDA adaptation for ICON-LAM: (ambitious!) schedule (1) development of experimental KENDA-LETKF for ICON-LAM • 02/18: MEC-based LETKF for ICON-LAM (working) in BACY-1 basic cycle (technically,no snow/SST ana.)  short exp.1 – 4 days to find bugs, gain experience • 03/18: MEC-based LETKF for ICON-LAM in BACY-1 full DA cycle (with snow/SST analysis), technically with LHN (to do: use of obs only in inner part of (irregular) domain)  technical equivalence with MEC-based COSMO-KENDA cycle, diagnose • 04/18: ICON-LAM online-obs4-D LETKF in BACY-1 (implement obs operators in ICON)  technical equiv. with operational COSMO-KENDA, start running tests • 04 – 12/18: consolidate ICON-LAM-KENDA to get similar performance as with operational COSMO-KENDA (possibly with remaining ‘known issues’)

  9. Task 4.1 KENDA adaptation for ICON-LAM: (ambitious!) schedule (2) variational extension for deterministic analysis: • 02/18 – 12/18: ICON-LAM regional B matrix (in collab. w. MeteoSwiss) • 03/18 – 11/18: 3DVar for ICON-LAM, technical development (requires re-write of ‘COSMO’ obs operators, develop TL + adjoint, otherwise use global operator) • 07/18 – 03/19: EnVar for ICON-LAM, technical development (4-D EnVar would require substantial (> 3 months AR) implementation :  Grib input / output of several time slot and handling them in BACY)  extension of horiz. interpolation operators (2D  2D + time)) towards operational use • 07/18 – 12/18: ICON-LAM in NUMEX, thereafter extended experiments • 07/19: ICON-LAM parallel suite

  10. Mode-S aircraft: Introduction Mode-S aircraft • derived from radar data from air-traffic control, processed + provided by KNMI (de Haan, Geophys. Res., 2011; de Haan and Stoffelen, Wea. Forecast.., 2012) • wind vector + temperature, T derived from Mach number • every 4 sec • compared to AMDAR: • 4 x more data (after 40% thinning) • no humidity, larger T error from: Lange and Janjic, MWR 2016

  11. Mode-S aircraft: parallel trial with adjusted obs error 1 – 24 Sept. 2017 (trial in parallel suite) RH RH2M rad global T total cloud T2M wind speed ps mid-level cloud wind dir. 10-m wind dir. • slightly positive change in RMSE [%]

  12. Mode-S aircraft: winter test, upper-air / surface / radar verif. Dec 2016 (1 Dec. 2016 – 1 Jan. 2017) FSS (precip 0.1 mm/h , 30 km) RH RH2M 0 UTC runs REF Mode-S T T2M 12 UTC runs wind speed ps wind dir. 10-m wind dir. • Dec. 2016: positive impact in upper-air + synopverif. change in RMSE [%]

  13. Mode-S aircraft: winter test, low-level cloud (low stratus) REF Mode-S worse better hits / missed events / false alarms / undefined (observed mid-level, high, or fractional cloud)

  14. Mode-S aircraft: winter test, low-level cloud (low stratus) REF Mode-S better hits / missed events / false alarms / undefined (observed mid-level, high, or fractional cloud)

  15. Mode-S aircraft: winter test, low-level cloud (low stratus) REF Mode-S better hits / missed events / false alarms / undefined (observed mid-level, high, or fractional cloud)

  16. Mode-S aircraft: winter test, low-level cloud (low stratus) REF Mode-S better worse hits / missed events / false alarms / undefined (observed mid-level, high, or fractional cloud)

  17. Mode-S aircraft: winter test, low-level cloud (low stratus) REF Mode-S better worse hits / missed events / false alarms / undefined (observed mid-level, high, or fractional cloud)

  18. Mode-S aircraft: summary • impact tested in summer + winter, in BACY experiments (data cut-off time not taken into account) + in parallel suite • impact varies between neutral and clearly positive • no single parameter in any test period worse • impact depends on weather situation: clearly positive for • precipitation in convective situations with weak advection / large-scale forcing • (radiative) low stratus  Mode-S introduced operationally at DWD on 4 Oct. 2018

  19. Investigation of discrepancies between MeteoSwiss & DWD KENDA MeteoSwiss analysis verification DWD verification + 0 h COSMO-1  nudging COSMO-E  KENDA COSMO-7  nudging Winter 2016 Spring 2017 (without additive inflation)

  20. Investigation of discrepancies between MeteoSwiss & DWD KENDA  run experiments: comparison KENDA vs. Nudging for Dec. 2016 (winter, extended low stratus periods) MeteoSwiss • MCH COSMO-E setup (EC-LBC, domain, …) + MCH obs (BUFR radiosondes), but DWD settings of KENDA (additive inflation, 24-bit coding of T_SO, etc.) • still being set up DWD : ‘Swiss experiment’ • DWD setup (KENDA, ICON-LBC, obs(no Mode-S)), but on COSMO-E domain • standard verification: similar results as with COSMO-DE

  21. Investigation of discrepancies between MeteoSwiss & DWD KENDA temperature # obs RMSE MEC based on Swiss cdfin files  no LETKF first guess check 1 – 26 Dec 2016 RMSE # obs MEC based on DWD ekf files  with LETKF first guess check 1 – 27 Dec 2016 • LETKF f.g. check • rejects too many obs • (for verif & analysis)

  22. Investigation of discrepancies between MeteoSwiss & DWD KENDA temperature f.g.: < 100 1 – 25 Dec 2016 act + pass: ~ 48000 MEC based on Swiss cdfin files  no LETKF first guess check MEC based on DWD ekf files  with LETKF first guess check f.g.: ~ 1500 act + pass: ~ 32000 near LBC / above 300 hPa • LETKF f.g. check • rejects too many obs • (for verif & analysis)

  23. Investigation of discrepancies between MeteoSwiss & DWD KENDA relative humidity # obs RMSE MEC based on Swiss cdfin files  no LETKF first guess check 1 – 26 Dec 2016 RMSE # obs MEC based on DWD ekf files  with LETKF first guess check 1 – 27 Dec 2016 • LETKF f.g. check • rejects too many obs • (for verif & analysis)

  24. Investigation of discrepancies between MeteoSwiss & DWD KENDA wind speed # obs RMSE MEC based on Swiss cdfin files  no LETKF first guess check 1 – 26 Dec 2016 RMSE # obs MEC based on DWD ekf files  with LETKF first guess check 1 – 27 Dec 2016 • LETKF f.g. check • rejects too many obs • (for verif & analysis)

  25. Investigation of discrepancies between MeteoSwiss & DWD KENDA RH T wind speed wind dir. 1 – 27 Dec 2016 MEC based on Swiss cdfin files  no LETKF first guess check MEC based on DWD ekf files  with LETKF first guess check • MEC mode: no effect on wind scores • but affects T at low levels and RH

  26. Investigation of discrepancies between MeteoSwiss & DWD KENDA • performance differences between KENDA and nudging similar in ‘Swiss experiment’ as with COSMO-DE (e.g. low stratus, surface verif, standard radiosonde verif) • MeteoSwiss radiosonde (cdfin) obs input: about 50% more data (T, RH, wind) • COSMO (cdfin-based MEC) first guess check rejects almost no data • LETKF first guess check rejects about 5% for T, RH and about 2.5% for wind, particularly near inversions (and in stratosphere)  too many good obs are rejected • discrepancies in upper-air analysis scores at MCH and DWD are (apparently) mainly due to different quality control in verification, not due to difference in analysis and forecast performance of KENDA as a result of different model domains, ensemble LBC’s, data input, etc. • solution: refine first guess check in LETKF analysis (work started)

  27. Status Report for KENDA-O Christoph SchraffDeutscher Wetterdienst, Offenbach, Germany Contributions / input by: Hendrik Reich, Andreas Rhodin, Roland Potthast, Klaus Stephan, Ulrich Blahak, Michael Bender, Elisabeth Bauernschubert, Axel Hutt, … (DWD) Daniel Leuenberger, Alexander Haefele (MeteoSwiss); Sylvain Robert (ETH) Chiara Marsigli, Virginia Poli, Tiziana Paccagnella, Thomas Gastaldo (ARPA-SIM) Lucio Torrisi, Francesca Marcucci, Valerio Cardinali (COMET) Mikhail Tsyrulnikov, Dmitri Gayfulin (HMC)

  28. Mode-S aircraft: Introduction • bug fixes in COSMO V5.04d • experiment 26 May – 10 June 2016 (‘E19’) • best results with thinning (40 % active) • Mode-S dominate above 800 hPa number of active obs • a-posteriori Desroziers statistics from DA experiment for estimation of obs errors: unexpected large Mode-S wind errors • data processing corrected by KNMI since 15 May 2017, re-processed historical data on request • new exp. ‘E22’ with re-processed data: Mode-S wind obs errors similar to AMDAR (but specified obs error variance still large)

  29. Mode-S aircraft: BACY test for convective period with weak advection Mode-S aircraft : forecast verification (26 May – 10 June 2016) wind dir. RH wind dir. wind speed ps RH2M wind speed T T2M TD2M change in RMSE [%] • positive impact from Mode-S throughout

  30. Mode-S aircraft: BACY test for convective period with weak advection 0-UTC runs 26 May – 10 June 2016 12-UTC runs Ref Mode-S (E19) Mode-S (E22) 0.1 mm/h 1-hrly precip FSS ( 30 km) 1 mm/h • Mode-S: clear long-lasting positive impact

  31. Mode-S aircraft: parallel trial trial in parallel suite 1 – 28 Aug. 2017 1 – 20 Aug. 2017 , 0-UTC runs 0.1 mm/h RH ps RH2M T 1 mm/h T2M wind speed change in RMSE [%] • Aug. 2017: much smaller positive impact than in 2016 convective period ! Why? • weather? data quality, data cut-off time ? (the last 15 min of Mode-S obs not available in time)

  32. Mode-S aircraft: data availability / timeliness / cut-off time data availability at cut-off time = 15 min (!) of COSMO-DE AMDAR obs valid -29 to -15 min AMDAR obs valid -14 to -0 min Mode-S obs valid -29 to -15 min 97 % available 70 % available 95 % available • operational setup: only the last 15 min of Mode-S data are missing  cut-off time unlikely reason of minor impact in parallel suite Mode-S obs valid -14 to -0 min 0 % available

  33. Mode-S aircraft: new obs errors (specified / estimated) 1 – 24 Sept. 2017 (trial in parallel suite) • in comparison to AMDAR: Mode-S data quality at least as good as for re-processed data  data quality very unlikely reason of minor impact in parallel suite  forecast impact of Mode-S apparently dependent on weather regime

  34. Mode-S aircraft: winter test, cloud Percent Correct (-1, 1) Mode-S – REF low-level cloud total cloud

More Related