1. Forecast Pressure

2. Pressure Observations ASOS is the best…the gold standard Ships generally the worst

5. ASOS Pressure Sensor

6. High-Resolution Can Greatly Improve Pressure Forecasts Near Terrain

10. Pressure Reduction Issues for Model SLP is shown frequently and there are problems with the reductions as with observations

11. Major Problem is Pressure Reduction: For BOTH Analyses and Forecasts Model pressure fields at sea level and geopotential heights at lower levels (e.g., 925 hPa) are based on assuming a 6.5 K per km lapse rate through the ground (also called the Shuell method) Can give deceiving or WACKY results

12. During Warm Season: phony troughs under terrain during night

14. Why? During night the atmosphere can become more stable than U.S. Standard Atmosphere at low levels. Thus, starting with the same temperature at crest level, the low level air is colder over the lowlands, where no reduction is occurring, producing lower pressure over the mountains.

15. During a warm day, the opposite can happen, with low pressure over the lowlands

16. Why? During day, the atmosphere over a valley (e.g., Central Valley of CA) is near dry adiabatic (9.8 C per km), while over the mountains we assume U.S. Standard atmosphere valley (6.5C per km). Becomes cooler at low levels inside the mountains…thus higher pressure.

17. During the day, phony trough inland Fig. 5. Composites of sea level pressure (solid lines, hPa) and 1000-hPa temperature (color shading, °C) using the (left) Shuell and (right) Mesinger methods for JJA at 0000 UTC.

18. Although model improvements have occurred, major pressure errors sometimes occur

19. An example of a short-term forecast error Eta 24-h 03 March 00UT 1999 Eta 48-h 03 March 00UT 1999

20. 48-hr Forecasts Valid 00 UTC 8 February 2002 AVN UKMO ETA NOGAPS

21. 24-Hr Forecasts Valid 00 UTC 8 February 2002 AVN UKMO ETA NOGAPS

22. Station Locations Tatoosh Is. Cape Arago

23. 24 h Coastal Errors Large Errors Inter-annual variability TTI, WA Cape Arago, OR

24. 48-h Errors 48h errors much larger and frequent than 24-h errors

25. GFS vs. NAM 24-h errors NCEP GFS better than NAM on average

26. GFS generally has more accurate SLP than NAM

27. 48-h errors GFS over forecasts Eta under forecasts

28. The NCEP GFS has more skillful cyclone intensity and position forecasts than the NAM over the continental United States and adjacent oceans, especially over the eastern Pacific, where the NAM has a large positive (underdeepening) bias in cyclone central pressure. For the short-term (0–60 h) forecasts, the GFS and NAM cyclone center pressure errors over the eastern Pacific are larger than the other regions to the east.

29. SLP analysis (a)MAEand (b)MEfor the stations from west to east in Fig. 1 for the GFS (solid black), NAM (dashed), and NARR (gray). The numbers of cyclones verified between 2002 and 2007 are shown in the parentheses. The dashed horizontal lines represent the average error during the period and the 90% confidence intervals are shown using the vertical bar on the right.

30. 2015 Update EC best Then UKMET Then GFS

35. 2015 Update Some smartphones are measuring pressure information and one company is starting to collect it. Experimentation with more effective use of pressure information for model data assimilation.

37. Smartphone Pressure

38. Forecasting Pressure Dependent on models Need to evaluate various models to determine which is best for your region and phenomenon. Important to evaluate recent performance and effects of terrain.

39. Summary Large variations in quality of pressure observations (ASOS the best) Large semi-diurnal signal Difficult parameter for human intervention…need to pick best model. Resolution helps considerable in terrain. Major pressure errors still exist. Pressure reduction is a major problem, BOTH for analyses AND forecasts.