National Weather Service San Diego WRF - Leveraging Operational WRF Runs

1. National Weather Service San Diego WRF -Leveraging Operational WRF Runs Brandt Maxwell Meteorologist National Weather Service Forecast Office Web: weather.gov/sandiego San Diego, California USA Email: Brandt.maxwell@noaa.gov

2. Today’s Presentation • History of the WRF at NWS San Diego • Info about our WRF • How our WRF is Used • Positives/Negatives of our WRF • “Show and Tell” • The Best Part!

3. Short History of Numerical Modeling at NWS San Diego • First ran Workstation-ETA in 2001 • Predecessor to the WRF-EMS • As name suggests, ability to run a model with ETA physics on a Linux PC or workstation • Developed by COMET (UCAR) • Original intent: view terrain effects on wind, precipitation and temperature for operational forecasting • Original grid-spacing: approx. 8 km • Non-hydrostatic • Original computer had only 2 processors • No concurrent post-processing

4. Upgrade to WRF-EMS • First ran WRF-EMS in 2006 • Originally used the WRF-NMM for the dynamic core • WRF-EMS had 2 options (NMM vs. ARW) • Grid spacing was 4-km (but in diagonal/Arakawa-E grid) • Had better computer, with 4 cores • Separate post-processing computer let us generate the Grib files for AWIPS while the WRF was running • No waiting until the end of the run

5. Further Improvements • Big improvement in 2009 • New 8 core system (2.83 GHz each) with 12 GB memory (DDR) • Switched from WRF-NMM to WRF-ARW • 3.7-km grid spacing (non-diagonal) • 45 vertical (sigma) levels • Heavier distribution towards surface (marine layer) • Around this time, self-implemented e-mail notification of when the disk was full (due to a few WRF crashes due to disk-full errors)

6. Current WRF for NWS San Diego • We still use the WRF-EMS • We actually have 2 runs every 6 hours • One run is on our local machine (from 2010) • Alternate run is on the Triton system at the San Diego Supercomputer Center (since 2012) on space rented by SDG&E • Both runs use NAM for boundary conditions...but... • Different initial conditions (one uses NAM, one uses RAP) • NAM-init run gives 84-hours of output (takes approx. 3 ½ hours to run) • RAP-init run gives 48-hours of output (takes approx. 2 ½ hours to run)

7. More on Current WRF • Both runs now use 47 vertical levels • A couple of levels were added in the mid-levels to attempt to better view elevated convection • 13 levels below 900 mb (at sea level grid points) • Grid is 134 x 110 points in the following domain:

8. Normal Time Step • For WRF-ARW, time step (in seconds) should normally be about 6 times the grid spacing (in kilometers) • Allows one to usually satisfy the Courant, Friedrichs and Lewy (CFL) condition: • The time step must be less than the time it takes the fastest moving wave in the model to travel one grid space • Violation of this creates noise and/or a crash • In our case: 3.7-km grid spacing x 6 = 22 seconds • Normal operating mode until 2012

9. Adaptive Time Step • A way to speed up the model • If no fast-moving waves are threatening to violate the CFL condition: • The adaptive time step will increase and “speed up” the WRF • WRF allows as high as a 45-sec. time step for 3.7-km grid spacing • We began using this in April 2012 • Worked very reliably in late spring and summer with runs 30% faster than before • We started having crashes in autumn though

10. Adaptive Time Step Issue • What messed up the WRF? • CFL was violated • Happened when WRF was running at longer time steps (40-45 seconds) and a wave suddenly appeared • It has been suggested that due to our small domain, the adaptive time step does not work as well as with a large domain • Time step adjusts (by getting smaller) better with a larger domain when there are waves propagating really fast

11. Solution • Only run WRF with adaptive time step in late spring/summer/early fall • We run the main (84-hour NAM-init) WRF on our local machine with adaptive time step then • When we can’t run the WRF with adaptive time step, we run it (NAM-init WRF) on faster Triton and swap the WRF RAP-init to our local machine (since it’s only through 48 hours) • Computer power is limited, so can’t have a larger domain without sacrificing resolution • Other note: RAP-init WRF runs without adaptive time step to prevent both WRFs from crashing

12. Why can’t we just always run 84-hour NAM-init WRF on Triton? • A couple disadvantages of Triton: • Difficult to set up concurrent post-processing due to WRF being allocated to different processors each model run on Triton • When we can run WRF on our own computer, we can view the 24-hour prognosis when the later hours of the WRF are still running • Internet bandwidth is tight at NWS San Diego, and large post-processed Grib files can take 15-30 minutes to download

13. Other “specs” • For both NAM-init and RAP-init runs: • No convective parameterization • We’ve tried Kain-Fritsch and Grell 3D in the past • Microphysics: Thompson • PBL: Yonsei • Land-Surface: Noah • Long/Shortwave Radiation: Dudhia • Part of deciding the “specs” is computational times

14. Why do we use the WRF-EMS versus the NCAR version of WRF ARW? • Easy (and relatively fast) to install and configure • No compilers required • Access to COMET’s personal tiles for boundary and initial conditions • Only downloads data (Grib) for your domain • Can also access other Grib data sources, such as NOMADS (which now have geographic constraints on the data) • COMET has archived data (including offline NAM/GFS data) • Good network of support • WRF-EMS listserv • NWS offices are #1 on the COMET support priority list • Most other NWS offices use WRF-EMS

15. How Does NWS San Diego Use the WRF • First of all, WRF is *the* #1 model of choice at NWS San Diego • General Weather Forecasting • We mostly view WRF in AWIPS • Heavily used for IFPS grids • Need high-res model here especially for terrain and coastal effects • 84-hour WRF run means we can use it to populate 3 days worth of grids • Most often used for winds, temperatures, dew points • Bias-corrected grids are an option which takes into account WRF biases from past 30 days

16. Example of Wind Grids using WRF as Primary Component

17. WRF: Aviation Forecasting • Used frequently for aviation forecasting (TAFs) • We view them in AWIPS and BUFKIT • AWIPS has interpolated vertical levels (due to Grib files) every 3 hours, BUFKIT has *all* vertical model levels every hour • Specific uses: • Used for depth of marine layer (cloud heights; can impact visibility) • Used for locations of low clouds (low-level RH fields) • Used for winds at TAF sites • Used for wind shear (especially in BUFKIT soundings which show every WRF model level at every hour) • Used for pilot briefings (including winds aloft)

18. Example of Wind Shear in WRF BUFKIT Sounding

19. Fire Weather Forecasting • WRF inclusion in IFPS grids helps with • Fire weather forecasts • Spot forecasts • WRF is a major tool for deciding whether or not to issue a red flag warning • Excellent for verbal briefings

20. Marine Forecasting • Useful for winds over coastal waters • Especially when waves from the islands (or from offshore flow) impact surface winds • Useful for short-period, locally generated swell • Especially for WNW swells with a wind fetch south of Point Conception/through the Channel Islands • WRF low-level shear/instability can assist with waterspout forecasting

21. WRF Online • We have our WRF model online: • Some of our partners/users do look at the WRF (including fire weather) • Online WRF uses GrADS scripts created by Dan Leins, NWS Phoenix (with modifications by Stefanie Sullivan, NWS San Diego) • NAM-init is used during summer, RAP-init is used during winter http://weather.gov/sandiego/wrf

22. Research • WRF is used for case studies • All NWS San Diego WRF runs are archived back to 2010 • For older dates (or if other boundary/initial conditions are desired), other sources of data can be used as input to the WRF • If high-res nested domain is desired, output Grib files from the WRF can be used as input to the high-res run • Mixed results here, probably because domain can be too small

23. What the WRF does well • Winds: Does well in most cases • Gap winds perform well in places like San Gorgonio Pass, Cajon Pass • Mountain wave winds do moderately well • But...WRF has a tendency to go too high here • In “weak Santa Anas”, WRF sometimes erroneously predicts strong winds at 850 mb near Cajon Pass to reach the valley floor • Rotors (such as near Palm Springs) appear with some accuracy • Sea breeze winds are well modeled

24. What the WRF does well, cont. • Relative humidity: • Boundary layer RH is an accurate indicator of marine layer stratus (especially at night) • Good for showing marine layer depth (time-height cross sections) • Moderately good for fire weather • Temperature: • Performs well with bias correction for IFPS

25. Weaknesses of the WRF • Precipitation, especially convective • Stratiform precip is OK, though usually with values too high • Convective precip is difficult to predict in So-Cal • One problem is that a lot of our thunderstorms are very small core in summer • Convective parameterization has not helped enough to justify the extra model time needed • However, WRF is at least moderately good with predicting indicators for convection (instability, convergence, etc.) • Visibility values (aviation) are not good

26. “Self-Inflicted” Negative Impact on our WRF • Our domain is too small • Despite buffer of more than 5 grid points beyond our County Warning & Forecast Area (CWFA), a COMET study showed that the ideal domain should be much larger—perhaps double your forecast area! • Seems to impact precipitation (especially convective) the most • Likely impacts our adaptive time step • However...larger domain needs larger more expensive computer

27. “Show and Tell” – Operational WRF Run from 20 March 2011 • Low-pressure system with strong height/MSLP gradients moved through California • Strong mountain wave in San Bernardino County: Stationary jump and lee waves • Measured wind gust of 115 MPH at Lucerne Valley (Mojave Desert) • Damage: Lots of roof damage (one house had total roof destructions). Power lines and trees down.

28. WRF Surface Winds • All images are from 0600 UTC run (20 Mar 2011) • 2100 UTC prognosis • Time is near/just after the “peak” • Strongest winds are just north of the San Gabriel/San Bernardino Mtns.

29. WRF 700-mb Omega and Wind

30. WRF Cross-Section • Inland Empire – San Bernardino Mtns – Mojave Desert (including Lucerne Valley)

31. WRF Cross-Section • 2100 UTC • Potential temperature, omega and wind • Clear stationary jump with weaker lee waves • 15 deg C temperature jump in the wave at 700-mb! • 80-knot wind just above 850-mb

32. Summary • WRF is a big part of the forecast operations for NWS San Diego (#1 model) • IFPS would be difficult without it given our terrain/coastline • WRF does well with wind, temperature and dew point in So-Cal, not as well with precipitation (especially convective) • Great model for case studies • 20 March 2011 • Our WRF is online: http://weather.gov/sandiego/wrf

33. Questions?