Forecasting extreme rainfall. Wes Junker. Wes. Can be difficult!!. Iand getting people to listen to watches or warnings. Because……. From. Climatology of Heavy Rain Events in the United States from Hourly Precipitation Observations HAROLD E. BROOKS AND DAVID J. STENSRUD.
Can be difficult!!
Iand getting people to listen to watches or warnings
Climatology of Heavy Rain Events in the United States from
Hourly Precipitation Observations
HAROLD E. BROOKS AND DAVID J. STENSRUD
5 inch an hour rainfall rates lasting an hour are very, very rare but……do happen
Frequency changes with seasons
Inch an hour rainfall frequency.
Because higher amounts or thresholds are relatively rare, it is difficult getting a big enough sample to calibrate forecasts using traditional statistical techniques. Verification of 24 hour QPF for various thresholds
THE AREA OBSERVED DECAYS LOGARITHMICALLY AS THRESHOLDS INCREASE
THE ACCURACY OF FORECASTS ALSO DECAYS LOGARITHMICALLY EXCEPT FOR THE VERY HIGHEST THRESHOLDS
From Charles E. Konrad II (2001) is difficult getting a big enough sample to calibrate forecasts using traditional statistical techniques. Verification of 24 hour QPF for various thresholds
The Most Extreme Precipitation Events over the Eastern United States from 1950 to
1996: Considerations of Scale
Inside the red line, the probability of 1 mm is 100% but the probability of 3 inches is only a little above 10% in the blue area
START BY LOOKING AT SYNOPTIC SCALE (THE BIG PICTURE) difficult to predict
SHORT RANGE (0-3 HR) FORECASTS difficult to predict
Schematic representing the affect the shape and movement of a system has on the rainfall at a particular point. The shaded colors on the system represent the radar echoes.
From Doswell et al., 1996 (Weather & Forecasting, 11, 560-581)
You live at the blue dot
Adopted from Doswell et al. 1996
Madison County flash flood event at 1800 UTC number of factors.
A high precipitation efficiency event
1800 UTC IAD sounding
CAPE is low but positive
Relative humidity is high
PW is <2.00 inches
Not much shear, weak mean winds compared to low level winds
Low centroid of max echo returns <55 DBZ
Low centroid mean it’s not hail but rain…..very heavy rainfall
A slow moving or backbuilding MCS is more likely when number of factors.
USE MODELS TO IDENTIFY SYNOPTIC AND MESOSCALE PATTERNS THAT ARE FAVORABLE TO HEAVY RAINS
Composite for East coast synoptic type
Lets look at a classic synoptic heavy rainfall event in the east
Borrowed from Rich Grumm
Bottom panels 850 winds and normalized anomalies
250wind & v-anom
Correctly predicts strong southern wind anomalies, PW anomalies of greater than 2
12-36 hr gfs rainfall.
12-36 hr NAM
Heavier and farther southeast
All valid at 1200 UTC 26 June
SREF probability of 2.00 inches
Probability of 2.00 inches was 20% and in the wrong place
Another case forecasting QPF
Strong agreement about the synoptic pattern.
GEFS was forecasting a nice MCS with heavy rainfall. forecasting QPF
Stronger than normal low level jet….over 3 SD v-wind component at 850, Some uncertainty about placement of moisture plume (PW across threat area)
SREF trending towards high MF anomalies…greater than 5 SD. NAM (right) forecasting greater than 5 SD.
For extreme events is there a better way than trying to deterministically forecast a extreme event or forecast the probability of an event at a single point
Imagine a non-hydrostatic model forecasting 125 mm (5 inches) or more of rain (magenta). It verifies as the light blue area
A perfectly predicted 125 mm area having a position error
may be a terrible forecast. Or is it?
How do you statistically forecast the probability of such a small scale event?
In this case, the probability of 125 mm (5 inches) would be zero based on the raw ensemble members but, all ten forecast a major event. Within the circle, 100% of the members forecast 5 inches
Your point probability forecasts of such an event will always be small