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Update on the Northwest Regional Modeling System 2013

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Presentation on theme: "Update on the Northwest Regional Modeling System 2013"— Presentation transcript:

1 Update on the Northwest Regional Modeling System 2013
Cliff Mass and David Ovens University of Washington

2

3 NW High Resolution Regional Prediction
Supported by NW Modeling Consortium-a collection of local, state, and Federal Agencies AND the private sector (King-5) Currently runs with 36, 12, 4, and 1.3 km grid spacing using the WRF (Weather Research and Forecasting) ARW model twice a day at 0000 and 1200 UTC (5 AM and 5 PM PDT) One of the highest resolution numerical weather prediction efforts in the U.S.

4 36 km

5 12 km

6 4 km

7 1.33 km

8 Who is looking?

9 New Mode of Distribution: TV!
King-5 is getting our model grids and creating on-air graphics.

10 Verification: Does Resolution Help? Yes!

11

12 Lots of Upgrades Over the Past Year

13 Upgrades Moved to the latest version of the WRF model (3.1.1 to 3.4.1) was about two years old. Pushed the upper boundary of the model way up! 100 hPa to 50 hPa (16 to 21 km) Installed a radiation condition that stopped unphysical reflections off the top.

14 Shading is vertical velocity.

15

16 New Cumulus Parameterization
We were getting wacky cloud and precipitation lines over the ocean when the air was less stable. To fix this we moved from the old Kain-Fritsch scheme to the same one used by the National Weather Service in the global GFS model (Simplified Arakawa Schubert-SAS).

17 Old Kain-Fritsch

18 SAS

19 Also partially solved a major summer problem we had: lack of convection over the Cascades and downstream over western Washington and Oregon

20 Old

21 New

22 New

23 Two Major Proposed Improvements for Next Few Months
Better radiation scheme-RRTMG Adding Land Surface Model (LSM)-RUC LSM

24 RRTMG much more sophisticated

25 Some 2-m Temperature Results at 4 PM in Winter (all stations) Red (original), Green (with RRTMG)
Mean Error or Bias

26 Summer

27 Land Surface Model (LSM)
Land Surface Models provide much more sophisticated descriptions of surface properties and how they evolve. Generally also provides much better dew point forecasts Snow distribution can change in time. We had been using the NOAH LSM but found unacceptable cold biases over the interior. But things (and the model) have changed.

28 Land Surface Model Schematic

29 Testing LSMs Old NOAH LSM (had cold bias)
New NOAH MP (had stability issue) RUC LSM (tested comprehensively)

30 RUC LSM with RRTMG Radiation
As expected dew point is much improved in summer.

31 Winter Temp: Improvement

32 Snow Can Change in Time During a Forecast with LSM

33

34 Finally, we are continuing development and operational availability of our local data assimilation and forecasting system

35 Regional Data Assimilation and Forecasting

36 The Long Term Future of the UW Modeling Effort
Based on a large (64 member) ensemble of forecasts at 36 and 4 km grid spacing. WRF model and DART Ensemble Kalman Filter (EnKF) System Every three hours assimilate a wide range of observations to create 64 different analyses. Then we forecast forward for 3 hours and then assimilate new observations. Thus, we have a continuous cycle of probabilistic analyses.

37 EnKF Ensemble Forecasting System
We can run ensemble of forecasts forward to give us probabilistic forecasts for any period we want. Now doing 24h ahead, four times a day. Planning to go to a 1-hr cycle and to use more observations (e.g., more surface pressure obs). More next year.

38 Improvement in short-term forecast using our local assimilation system

39 WRF 4 km at same time

40 NWS NAM

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43 Major New Enhancement The use of high density, bias-corrected surface pressure observations…more next year…. Including the use of pressures from smartphones!

44 The End


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