Transcript A daily PNA index - University of Washington

Regional Impacts of day-to-day changes in
the large scale Pacific North America
(PNA) pattern: observations and prospects
for skillful 7-14 day lead-time weather risk
forecasts
Craig Brown, M.S. Thesis
UW Atmospheric Sciences
Advisers: David Battisti, Nate
Mantua and Ed Sarachik
Research Goals
• For selected stations, quantify the extent of
“extreme weather” sensitivity to changes in the
large scale PNA circulation pattern (freeze events,
heavy rain and snow, wind gusts, extreme
temperatures)
– Use Thompson and Wallace (1999) approach with AO
• examine the potential for extending deterministic
weather forecasts into skillful risk probability
forecasts at lead times up to 14 days
Tracking the PNA pattern
Wallace and Gutzler (1981): with standardized 500mb
height anomalies …
PNA(t) = 1/4*(Hawaii - Aleutians + Alberta - Florida)
PNA pattern
Seasonal mean PNA index
Created by Todd Mitchell, UW JISAO
Daily PNA index
St devs.
St devs.
PNA index values
Frequency distributions
Properties of the daily PNA index
• Gaussian
• Impressive
persistence, with an efolding time scale ~7
days
• Well-correlated with
heights at each of the 4
“centers of action”
Distribution of the daily PNA index
1948-1999
Impacts of the day-to-day PNA
variability
• Composite reanalysis fields to gain insights
into what PNA variations at day-to-day time
scales might be doing to surface weather
PNA 500 mb ht pattern: a dominant mode of cool
season intraseasonal-to-interannual variability
PNA +
PNA -
PNA +
Composite surface
wind fields for +/PNA
PNA -
PNA +
Composite surface
wind and surface
temperature
anomaly fields for
+/- PNA
PNA -
Craig’s Extreme Event Analysis
• At 50 stations, daily data for 5 weather
parameters, 1948-1999
– Tmin, Tmax, Snowfall, Precipitation, and peak wind
gusts
• Using Histograms:
– Identify extreme events: >1.5 and 2.0 std devs
– Compare event counts for PNA +/- days
– Map the ratios of event counts for PNA-/PNA+ days
All days
Avg=34.7 F
Histograms of daily
Oct-Mar Tmax at
Stampede Pass, WA
PNA < -1
Avg=29.2 F
PNA > +1
Avg=39.7 F
All days
Avg=26 F
Histograms of daily
Oct-Mar Tmin at
Juneau, AK
PNA < -1
Avg=18 F
PNA > +1
Avg=33 F
Daily PNA and
Peak wind gusts
Daily PNA and
extreme high
precipitation events
Daily PNA
and extreme
high
temperatures
Daily PNA and
extreme low
temperatures
Daily PNA
and number
of freeze
events
(Tmin < 0)
Daily
PNA and
extreme
snowfall
events
Seattle snowfall and the daily PNA
PNA and PNW weather extremes summary
Days with PNA < -1
• Increased frequency of
extreme cold
temperatures, freeze
events, heavy
precipitation, low
elevation snowfall,
and high wind gusts
Days with PNA > +1
• Increased frequency of
extremely warm
winter temperatures
• Reduced frequency of
extreme cold, freezes,
low elevation
snowfall, heavy
precip., and high wind
gusts
Ensemble PNA forecasts and
probabilistic risk assessments
• Lorenz told us the “butterflies” will trash the skill
of deterministic weather forecasts at lead times
>14 days, no exceptions!
• Due to the robust nature of PNA variability, and its
strong tendency for persistence, it is the most
predictable atmospheric pattern at lead times of 610 days (Renwick and Wallace (1995)).
• Ensemble PNA forecasts, based on the output of
global weather prediction models, show promising
skill at lead times of 7-to-14 days
NCEP 11 member
ensemble forecasts
for the daily PNA
index
derived from
Medium Range
Forecast (MRF)
model output
PNA prediction skill
Forecast lead time in days
Step 1:
Ensemble PNA forecast
-2 -1 0 1 2
Predicted probability
Predicted probability
PNA-based risk forecast
Step 2:
Probability risk forecast
0 1 2 3 4 5 6 7 8
Seattle Snowfall (inches)
Filling the holes in the existing prediction
system
ENSO, QBO, PDO
Interannual
GFS
PNA, AO/NAO,
AAO Ensembles
MM5
Forecast Lead-Time
Intraseasonal …
Madden-Julian
Oscillation --> PNA ?
fair weather Fall
2002 and the PNA