U.S Drought Highlights Since U.S Drought Highlights Since October 2006 October 2006 Douglas Le Comte Douglas Le Comte NOAA/CPC NOAA/CPC 32nd Annual Climate Diagnostics and Prediction 32nd Annual Climate Diagnostics and Prediction Workshop Workshop October 22-26, 2007 October 22-26, 2007 Morristown, Morristown, TN, Sep. 12, TN, Sep. 12, 2007 2007
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U.S Drought Highlights Since October 2006 Douglas Le Comte NOAA/CPC 32nd Annual Climate Diagnostics and Prediction Workshop October 22-26, 2007 Morristown,
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U.S Drought Highlights Since U.S Drought Highlights Since October 2006October 2006
Douglas Le ComteDouglas Le Comte
NOAA/CPCNOAA/CPC
32nd Annual Climate Diagnostics and Prediction Workshop32nd Annual Climate Diagnostics and Prediction Workshop
Improvement over PersistenceImprovement over PersistencePercent of Grid Points Correct vs a Forecast Based on Persisting DroughtsPercent of Grid Points Correct vs a Forecast Based on Persisting Droughts
Drought Outlook -- Forecast minus Persistence
-20
-10
0
10
20
30
40
50
60
Jul '03 Nov'03
Mar'04
Jul '04 Nov'04
Mar'05
Jul '05 Nov'05
Mar'06
Jul '06 Nov'06
Date of Forecast
Fo
reca
st L
ess
Per
sist
ence
Skill MEAN Linear (Skill)
Long-term mean = 13%Long-term mean = 13%
Two Path Approach to Improving Two Path Approach to Improving Drought Forecasts at CPCDrought Forecasts at CPC
• Continue to produce and refine seasonal drought outlooks for the Continue to produce and refine seasonal drought outlooks for the general publicgeneral public
a. Consider adding monthly forecastsa. Consider adding monthly forecasts
b. Consider adding probability information to mapb. Consider adding probability information to map
• Develop Develop objective seasonal probabilityobjective seasonal probability forecasts for drought forecasts for drought (guidance useful for an array of users)(guidance useful for an array of users)
a. Drought probabilities (soil moisture, runoff, drought a. Drought probabilities (soil moisture, runoff, drought indices) at some point in the futureindices) at some point in the future
b. Probabilities for changeb. Probabilities for change
c. Consider NIDIS goalsc. Consider NIDIS goals
d. Climate Test Bed products to contribute d. Climate Test Bed products to contribute
One Prototype Suggestion of a One Prototype Suggestion of a Probabilistic ForecastProbabilistic Forecast
University of Washington ForecastsUniversity of Washington Forecasts
““Prediction is very difficult, especially Prediction is very difficult, especially about the futureabout the future” ” Niels Bohr, Danish Niels Bohr, Danish