1. Robert Conrick, Qi Zhong, and Cliff Mass
An evaluation of precipitation forecasts during November 12-15, 2015 and November 16-19, 2015
Robert Conrick, Qi Zhong, and Cliff Mass
University of Washington
Pacific NW Weather Workshop 2017

2. Cases: November 12-15, 2015 November 16-19, 2015
Atmospheric river events, producing over 400 mm of precipitation in some areas.
Divided into two periods: - Prefrontal: Warm period prior to frontal passage - Postfrontal: Cooler period following frontal passage
Modeled at km resolutions using the WRF-ARW v Microphysics: WSM5 & 6, Thompson, Goddard, SBU-YLin

3. Why evaluate model microphysics?
Accurate microphysics representation is important for:
Hydrologic impacts
Water resource management
Forecasting of high-impact events

4. Why evaluate model microphysics?
WRF has more than 20 microphysics (MP) options.
What problems exist in schemes?

5. Which microphysics deficiencies are known?
Variability in location and amount microphysical species and precipitation
Ice and snow representations - Many schemes still use spherical snow.
Riming and graupel
- Most schemes have ice as discrete catagories
Photo credit: NOAA NSSL

6. 36 km 1.3 km Does resolution improve forecast accuracy?
Increasing resolution improves precipitation forecasts in PNW.
- We’ll revisit this in a few slides.
Nov. 01, 2015 – Feb. 01, 2016
36 km
1.3 km

7. Does elevation influence forecast accuracy?
Nov :
Lower elevations tend to be better forecast with less spread.
Higher elevations are underforecast by 20-30%.
Percent of Observed
ASOS & Mesowest stations

8. Does elevation influence forecast accuracy?
Nov :
Lower elevations: Still less spread.
All elevations have large underprediction.
Percent of Observed
ASOS & Mesowest stations

9. Olympic Mountains: Windward vs. Leeward
Underforecasting precipitation is common on both windward and leeward slopes. Nov has worse windward than leeward forecasts; Nov is opposite.
Percent of Observed
Percent of Observed
credit: Qi Zhong
Nov 12-15
Nov 16-19

10. Olympic Mountains: Windward vs. Leeward
Microphysics (MP) shows less resolution dependence than PBL.
Nov 12-15
Percent of Observed
Percent of Observed
credit: Qi Zhong
Microphysics
PBL
(Thompson MP)

11. Quinault Area Forecasts
SW-NE transect up the Quinault
Goals:
Do microphysics and precipitation forecasts differ as the flow is modified by terrain?
Is pre- and post-frontal forecast accuracy different?

12. Quinault Area Forecasts
Nov
Nov
Percent of Observed
Percent of Observed

13. Are synoptic differences responsible?
Melting levels do not substantially differ by MP scheme.
Beach
Nov
Height (m; agl)
Bishop

14. Are synoptic differences responsible?
850 mb wind speed & direction (not shown) do not substantially differ by MP scheme.
Beach
Nov
Speed (m/s)
Bishop

15. Are differing microphysical species responsible?
Hypothesis: Different schemes produce different amounts of species and hydrometeors, which influences precipitation forecasts.
Cloud ice
Snow
Nov Case:
Pre-frontal Average

16. Conclusions
Increasing resolution improves model accuracy substantially.
Low elevations tend to have less spread in forecasts, but elevation does not determine how accurate a forecast is.
Underforecasting precipitation is a problem, especially on windward slopes where observed precipitation is high. - No resolution dependence when varying MP schemes. - Varying PBL schemes shows strong resolution dependence.
In the Quinault region, sensitivity to partitioning of MP species yields very poor forecasts.