1 / 20

Storm-scale data assimilation and ensemble forecasting for Warn-on-Forecast

Storm-scale data assimilation and ensemble forecasting for Warn-on-Forecast. 5 th Warn-on-Forecast Workshop Dusty Wheatley 1 , Kent Knopfmeier 2 , and David Dowell 3

tclair
Download Presentation

Storm-scale data assimilation and ensemble forecasting for Warn-on-Forecast

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. Storm-scale data assimilation and ensemble forecasting for Warn-on-Forecast 5th Warn-on-Forecast Workshop Dusty Wheatley1, Kent Knopfmeier2, and David Dowell3 1,2Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, and NOAA/National Severe Storms Laboratory, Norman Oklahoma 3NOAA/Earth Systems Research Laboratory, Boulder, Colorado 2 April 2014

  2. Work highlights • Move to a GEFS-based NSSL Mesoscale Ensemble (NME) • Provides for a regional convection-allowing (grid spacing ~3 km) ensemble on which to perform radar DA • Baseline EnKF experiment for 24 May 2011 using NME background • New initialization techniques + radar DA • Convective initiation/suppression using an updraft nudging technique

  3. NSSL Mesoscale Ensemble (NME) • Currently: Regional convection-allowing grid (spacing 3 km) is event dependent • Ongoing work to consider the use of a single grid with horizontal spacing of 3 km

  4. Retrospective work: • 27 April 2011 • Spring tornado outbreak • Southeastern United States • 24 May 2011 • Warm season tornadic event • Central Oklahoma • 17 November 2013 • Cool season tornadic event • Midwestern United States

  5. 24 May 2011 Tornadic Event • First tornado reports in Oklahoma between 2015 – 2043 UTC

  6. Ensemble description • WRF-ARW v3.4.1 • 36-member ensemble, with physics diversity (same for storm-scale ensemble) • Microphysics: Thompson • Cumulus: Kain-Fritsch, Grell, Tiedtke • Radiation (LW/SW): RRTM/Dudhia, RRTMG/RRTMG • PBL: YSU, MYJ, MYNN • IC/BCs for *both* parent/nested grids downscaled from 21-member Global Ensemble Forecast System (GEFS) at 0000 UTC 24 May 2011 • No IC/BC perturbations • Parent/nested grids run simultaneously—from 0000 UTC—in a 1-way nest setup • Only information exchange occurs at nest’s lateral boundary

  7. Mesoscale data assimilation • EnKF approach encoded in the Data Assimilation Research Testbed (DART) • ‘Conventional’ observations (METAR, marine, radiosonde, ACARS, satellite-derived winds) assimilated every 1 h until 0300 UTC 25 May 2011 • Mesonet data assimilation on nested grid only • No radar data assimilation in producing backgrounds

  8. Ensemble-mean specific humidity at 1800 UTC Dryline • System coupled with either NOAH or RAP land surface models

  9. Model soundings at 1800 UTC • Near convective initiation • At KOUN in Norman, OK

  10. Storm-scale experiments • Start on nested grid at 1900 UTC • Assimilate radial velocity and reflectivity (and mesonet) data every 5 min through the period 1900 – 2030 UTC • Frederick (KFDR), Vance Air Force Base (KVNX), and Twin Lakes (KTLX) WSR-88D’s • Cleaned radar data objectively analyzed to 6-km grid using Observation Processing and Wind Synthesis (OPAWS) • Additive noise (T, Td, u, v) where refl. obs. indicate precip. • Launch 1-h storm-scale ensemble forecasts (with no assimilation) at 2000 and 2030 UTC 24 May

  11. All plots displayed at 1.5 km AGL

  12. Probability of REFL > 40 dBZ at 1.5 km AGLTop row: 1-h FCST init. @ 2000 UTC Bottom row: 1-h FCST init. @ 2030 UTC

  13. Vorticity swaths • Probability of low-level (below ~2 km) vorticity exceeding some threshold; calculated every 5 min during 1-h forecast period • Maximum probability value retrieved at each model gridpoint Canton Lake EF-3, 2015-2043 Lookeba EF-3, 2031-2046 El Reno EF-5, 2050-2235

  14. Forecast cold pools • Ensemble mean 2-m temp. field calculated every 5 min during forecast period • Minimum 2-m temp. value retrieved at each model gridpoint

  15. Updraft nudging technique • In the manner of Naylor and Gilmore (2012) • Modification to w tendency fields in the model • Use radar reflectivity observations from the NSSL National Mosaic to automatically select where to: • initiate observed storms that are absent in the model forecasts • suppress unobserved regions of simulated storms • REFL obs. swapped out every 10 min • Ultimately, a complement (not a substitute) to radar DA, similar to additive noise

  16. No wforce No wforce With wforce

  17. Vorticity swaths (1915-2015 UTC)

  18. Probability of REFL > 40 dBZ at 1.5 km AGL25-min fcst valid 1940 UTC

  19. Vorticity swaths (1930-2030 UTC)

  20. Ongoing Work • Collective evaluation of backgrounds generated for earlier listed cases, and severe events during the period 15 – 31 May 2013 • Impact of choice of land surface model • Impact of horizontal resolution, microphysics, etc. on storm-scale results • Further investigate the use of updraft nudging technique within ensemble-based framework • Use the Gridpoint Statistical Interpolation (GSI) software for preprocessing observations and computing prior ensemble estimates

More Related