Forecast Pressure

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

ASOS Pressure Sensor

High-Resolution Can Greatly Improve Pressure Forecasts Near Terrain

He S 12-km

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) and 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

Mesinger Method is alternative that uses free our temp Mesinger Method is alternative that uses free our temp. structures on the side

Even for WRF! H over Mts, L over lowlands

Can also get lows over mountains, particularly under stable conditions

Although model improvements have occurred, major pressure errors sometimes occur

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

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

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

Extended Verification of Surface Pressure

Station Locations Tatoosh Is. Cape Arago

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

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

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

48-h errors Eta under forecasts GFS over forecasts

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 errors over the eastern Pacific are larger than the other regions to the east.

SLP analysis (a)MAEand (b)MEfor the stations from west to east in Fig 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.

Coastal Mean Absolute Error for all models, forecast hours and both coasts NAM upgrade to WRF-NMM ECMWF has smaller errors than other models for most months. NAM has larger errors than other models for most months and forecast hrs.

Coastal Mean Absolute Error for all models, forecast hours and both coasts East Coast errors smaller than West Coast errors for all months and forecast hours

Histograms of f48 Errors

Frequency of Large Errors >3hPa >5hPa >7hPa Same conclusions apply: ECMWF smallest frequency and NAM the largest frequency of large errors, East Coast smaller frequency of large errors than West Coast for all models and forecast hours.

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.

2013 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.