Probabilistic Forecasts Based on

1
Probabilistic Forecasts Based on Reforecasts

• Tom Hamill and Jeff Whitaker
• tom.hamill_at_noaa.gov and
• jeffrey.s.whitaker _at_noaa.gov

2
(No Transcript)
3
Improving probabilistic forecasts

• Better ensembles
• More members
• Improved initial conditions
• Higher resolution
• Improved forecast models
• Statistical corrections of the NWP forecasts (our
  main point this can improve forecasts so much
  that it deserves more attention)

4
A tool for exploring calibration the CDC
reforecast data set

• Definition of reforecast a data set of
  retrospective numerical forecasts using the same
  model to generate real-time forecasts.
• Model T62L28 NCEP MRF (now GFS), circa 1998
  (http//www.cdc.noaa.gov/people/jeffrey.s.whitaker
  /refcst for details).
• Initial states NCEP-NCAR reanalysis plus 7 /-
  bred modes (Toth and Kalnay 1993).
• Duration 15-day runs every day at 00Z from
  19781101 to now. (http//www.cdc.noaa.gov/people/j
  effrey.s.whitaker/refcst/week2).
• Data Selected fields (winds, geo ht, temp on 5
  press levels, and precip, t2m, u10m, v10m, pwat,
  prmsl, rh700, conv. heating). NCEP/NCAR
  reanalysis verifying fields included (Web form to
  download at http//www.cdc.noaa.gov/reforecast).
• Experimental PQPF http//www.cdc.noaa.gov/refore
  cast/narr/

5
Application tercile probability forecasts
Climatological distribution split into 3 equally
likely bins. These categories are often called
Below/Near/Above Normal terciles.
NCEP Climate Prediction Center (CPC) operational
product
6
What can we do with a long data setof observed
and forecast anomalies?
With our reforecasts, we have 25 years of data.
Lets use old data in a 31-day window around
the date of interest to make statistical
corrections.
Dashed lines tercile boundaries Red points
samples above upper tercile Blue points samples
below upper tercile Solid bars probabilities by
bin count Dotted line a fitted model, TBD
7
Example floods causing La Chonchita, CA
landslide, 12 Jan 2005
week-2 forecast
6-10 day forecast
8
Comparison against NCEP / CPC forecasts at 155
stations, 100 days in winter 2001-2002
MOS-based Week 2 forecasts using low-res T62
model more skillful than operational NCEP/CPC 6-1
0 day!
9
2004-2005 results
10
Other examples of calibrationusing reforecasts
Example Decile forecasts of 850 hPa temps over US
11
Analog high-resolution precipitation forecast
technique
(actually run with 10 to 75 analogs)
12
www.cdc.noaa.gov/reforecast/narr
forecasts now downscaled to 5-km using
Mountain Mapper technique.
13
Analog example Day 4-6 heavy precipitation in
California, 0000 UTC 29 December 1996 - 0000
UTC 1 January 1997
14
Skill as function of location

• Notes
• Less skill where
• its dry (climatological
• forecasts better here,
• tougher to beat).
• (2) Regions where
• precipitation analyses
• are poor are less
• skillful (snowy regions,
• poor coverage by
• gages Doppler)

15
Skill as f(time of year)
16
Comparison against NCEP medium-range T126
ensemble
the improvement is a little bit of increased
reliability, a lot of increased resolution.
17
Regional Reforecasts based on NARR and 32-km Eta?

• Leverage Mesinger et al.s Eta regional
  reanalysis.
• Run small (5 mbr) ensemble to 3 days? 8 days?
  for 25 years.
• Continue to run Eta in real time.
• Develop range of statistical products based on
  Eta reforecasts.
• Preliminary estimate computationally very
  expensive. 100 K for disk storage at CDC.
• Need advocacy of users to make this happen.

18
Conclusions

• Possible to achieve near-perfect reliability,
  good skill by calibrating forecasts with many
  years of old forecasts
• Great results with low-res model even better
  results with higher-res. model?
• Want your feedback on important products
• Continued development depends on your advocacy.

19
Hacienda Heights, CA mudslides, 22 Feb 2005 (also
rain on snow event for intermountain west)
6-10 day fcst
20
6-10 Day
Week 2