Transcript Forecasting Extreme Rainfall - Wes Junker, Heavy

Forecasting extreme rainfall
Wes Junker
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
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
mm
25
50
75
100
THE AREA OBSERVED DECAYS
LOGARITHMICALLY AS THRESHOLDS
INCREASE
mm
25
50
75
THE ACCURACY OF FORECASTS ALSO
DECAYS LOGARITHMICALLY EXCEPT
FOR THE VERY HIGHEST THRESHOLDS
From Charles E. Konrad II (2001)
The Most Extreme Precipitation Events over
the Eastern United States from 1950 to
1996: Considerations of Scale
500,000 km2
DJF
100,000 km2
MAM
JJA
2,500 km2
SON
Precipitation with mesoscale
convective systems is very difficult
to predict
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
Extreme rainfall is a moving target
• May occur in association with a synoptic
scale event
– In winter, 1” to 2 inches of rain over a basin
may cause flooding
• In summer, flash flooding may occur due
to a mesoscale system or even occur from
a single storm that remains
quasistationary and has intense rainfall
rates
Forecasting extreme rainfall events
• You need to understand which
combination of ingredients that can lead to
– High rainfall rates
– For an extended period
• Most extreme rainfall events are
associated with convection.
– You need moisture, instability and lift.
• or by strong lifting due to orography
A various time ranges
• The methods of trying to predict extreme
rainfall differ
– At shorter time ranges
• Mesoscale analysis, satellite and radar imagery
are often the best tools for pinpointing where an
event is most likely and are used to monitor
ongoing convective trends
– At longer time ranges, numerical models and
ensemble forecast systems provide
information about potential extreme events.
START BY LOOKING AT SYNOPTIC
SCALE (THE BIG PICTURE)
• THERE IS A CLEAR ASSOCIATION BETWEEN
SHORT-WAVE TROUGHS AND CONVECTION
• THE VERTICAL MOTION ASSOCIATED WITH
SYNOPTIC SCALE LIFT DOES NOT TYPICALLY
ALLOW PARCELS TO REACH THE LEVEL OF
FREE CONVECTION (LFC)
• HOWEVER, LARGE SCALE LIFT
–
–
–
–
STEEPENS LAPSE RATE
PROMOTES MOISTURE TRANSPORT
WEAKENS CAP
AFFECTS VERTICAL SHEAR (more important for severe
weather forecasting)
SHORT RANGE (0-3 HR) FORECASTS
• RELY PRIMARILY ON CURRENT OBSERVATIONS AND
TRENDS
– NEXRAD AND SATELLITE IMAGERY ARE GREAT
TOOLS PROVIDING INFORMATION ON THE , SIZE AND
INTENSITY AND MOVEMENT OF PRECIPITATION
SYSTEMS
– HAVE TO KNOW LIMITATIONS OF OBSERVING
SYSTEMS
– STILL HAVE TO ANTICIPATE NON-LINEAR CHANGES
• NEW CELLS FORMING UPSTREAM
THE AMOUNT OF RAINFALL THAT
FALLS OVER AN AREA DEPENDS ON
• SIZE and SHAPE OF THE RAINFALL
AREA
• THE INTENSITY OF THE RAINFALL
WITHIN IT
• HOW FAST THESE AREAS MOVE
• HOW FAST NEW RAIN BEARING
CLOUDS ARE FORMING UPSTREAM
(PROPAGATION)
Sound Easy?
A FEW IDEAS TO HELP DETERMINE HOW BIG AN
AREA OF RAINFALL TO FORECAST
• THE SIZE IS DEPENDENT ON HOW MUCH MOISTURE IS
PRESENT AND ON THE STRENGTH OF THE MOISTURE
TRANSPORT
– IS DEPENDENT ON BOTH THE ABSOLUTE (PWS, MIXING RATIOS),
RELATIVE MOISTURE (RH) AND WIND SPEED AND DIRECTION
• SIZE IS DEPENDENT ON THE SCALE OF THE FORCING
– PATTERN RECOGNITION OFTEN PROVIDES CLUES BUT YOU
NEED TO UNDERSTAND WHY THE PATTERN IS FAVORABLE FOR
HEAVY RAINFALL.
• MODEL GUIDANCE PROVIDES A DECENT FIRST GUESS,
ESPECIALLY OF COOL SEASON STRATOFORM EVENTS
– NOT SO GOOD WITH RAINFALL FROM CONVECTION
• An argument for using pattern recognition
• And ensemble guidance to get a better feel about a systems potential.
RAINFALL RATE
RAINFALL RATE
RAINFALL RATE
TIME
RAINFALL RATE
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.
TIME
TIME
TIME
From
et al.,
1996
(Weather & Forecasting, 11, 560-581)
You Doswell
live at the
blue
dot
Adopted from Doswell et al. 1996
Where new cells form in relation to the
initial convection is important, to
• Determining the mode of development
– Whether the system will look like this
Or this
Or this
– Determining the speed and direction the system will
move
The mode of development and
propagation is influenced by a
number of factors.
• OUTFLOW
– EVAPORATIONAL COOLING RELATED TO THE
ENVIRONMENTAL HUMIDITY
– GUST FRONT SPEED RELATED TO TEMPERATURE DEFICIT
BETWEEN OUTFLOW AND AIR AROUND IT.
• WHERE THE STRONGEST LOW-LEVEL
CONVERGENCE, MOISTURE AND INSTABILITY IS
LOCATED
• SYSTEM RELATIVE WINDS
– DETERMINES WHERE LOW LEVEL CONVERGENCE WILL
BE LOCATED.
• INTERACTION OF UPDRAFT WITH ENVIRONMENTAL
WIND
Rainfall rates
• Vertical moisture transport into the system which is dependent
– on the amount of moisture that is available. Precipitable water,
dewpoints, winds, moisture flux
– The magnitude of the vertical motions
• What produces the strongest vertical motion and rainfall rates?
– Convection
– High CAPE
• The proportion of the condensate that is fed into the cloud that
reaches the ground (the precipitation efficiency)
– Which is dependent on the shear
– Relative humidity
– An even shape of the sounding
What is precipitation efficiency
• The ratio of moisture that falls beneath the cloud
to how much moisture is being fed into it.
• High precipitation efficiency is more likely when
– Mean relative humidity is high
• Cloud bases are low
– Don’t want a lot of shear
– More likely with warm rain processes
– And airmass with maritime origins
• Because of having a more larger hygroscopic nucleii (more
large salt particles.
• On radar look for high reflectivities below the zero wetbulb.
Madison County flash flood event at 1800 UTC
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
MOVEMENT OF THE SYSTEM
• SLOW MOVING SYSTEMS ARE USUALLY
THE HEAVIEST RAINFALL PRODUCERS
• AT SHORTER TIME RANGESEXTRAPOLATION BASED ON RADAR AND
SATELLITE PROVIDES PRIMARY GUIDANCE
• AT LONGER RANGES, MODELS CAN
PROVIDE A FIRST GUESS, BUT
– YOU STILL NEED TO TAKE INTO ACCOUNT MODEL
CHARACTERISTICS AND BIASES.
• AT ALL TIME RANGES, YOU MUST
ANTICIPATE WHEN NEW ACTIVITY MAY
FORM UPSTREAM (Propagation effects)
A slow moving or backbuilding MCS is more
likely when
• When weak 850-300 mean winds are present.
• When the low level jet is upstream and of the MCS
location and the low level jet is strong compared to
the 850-300 mb mean wind.
• When you expect the MCS to be near the upper level
ridge.
• When veering winds with height dominate speed
shear
• When the strongest moisture transport and low-level
convergence is located upstream from the MCS.
• When the airmass is unstable upstream but stable
downstream
• When the mean RH is high.
Models often have problems handling the
development and motion of MCSs
– Because of lack of data
• This is especially true when dealing with
– The vertical and horizontal distribution of temperature and
moisture
» Unfortunately, the vertical distribution of moisture and
temperature governs where the airmass is unstable or not.
– Because certain physical processes occur below the
scale that the NCEP operational models can resolve
• The following physical processes are therefore
parameterized (and are handled in rather crude ways)
– Convection (in mesoscale models), within cloud
microphysical processes, radiation, boundary layer
processes
USE MODELS TO IDENTIFY SYNOPTIC AND
MESOSCALE PATTERNS THAT ARE
FAVORABLE TO HEAVY RAINS
• CAN USE THE SURFACE, 850- AND 500-MB
PATTERNS TO IDENTIFY MADDOX ET AL. OR
OTHER TYPES OF HEAVY RAINFALL EVENTS
– ALSO NEED TO LOOK CLOSELY AT MOISTURE,
MOISTURE TRANSPORT AND INSTABILITY
• MODELS OFTEN PROVIDE DECENT FORECASTS
OF LOW-LEVEL WIND AND MOISTURE FIELDS
– 850 MOISTURE TRANSPORT (MOISTURE FLUX)
– PWS
• OUTPUT CAN BE USED TO ASSESS FORCING
AND TO FORECAST THE LOCATION OF
BOUNDARIES.
• Ensembles can provide information about the
probability of the pattern actually occurring.
Use models to identify patterns associated with extreme rainfall.
Composite for East coast synoptic type
Lets look at a classic synoptic
heavy rainfall event in the east
Borrowed from Rich Grumm
Synoptic composite for extreme rainfall events
SREF has synoptic pattern right
250wind & v-anom
Bottom panels 850 winds and normalized
anomalies
L
L
Correctly predicts strong southern wind anomalies, PW anomalies of greater
than 2
12-36 hr
gfs
12-36 hr
NAM
observed
Heavier and
farther southeast
All valid at 1200 UTC 26 June
SREF again does better at recognizing
pattern than forecasting QPF
SREF probability of
2.00 inches
Probability of 2.00 inches
was 20% and in the wrong
place
Observed
Another case
Strong agreement about
the synoptic pattern.
Forecast
Observed
GEFS was forecasting a nice MCS with heavy rainfall.
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
Forecast
Actual Event
more of rain (magenta). It verifies as the light blue area
30 miles
Reporting station
A perfectly predicted 125 mm area having a position error
may be a terrible forecast. Or is it?
ns f
Or is it? How Good Are these hypothetical
ensemble forecasts?
How do you statistically forecast the probability of such a
small scale event?
Ensemble members
observed
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
Even with 100% of the ensemble
members forecasting an event,
what does it mean
• Do the model members have an individual
bias for each member
• If you use probabilities based on
ensembles, are they well calibrated.
• is there a resolution problem that may bias
the members?
– For the GEFS and SREF when dealing with
weak summertime forcing, probably yes
Forecasting extreme rainfall
requires
• Looking at the synoptic, mesoscale and
storm scale environments
• For any one location they are rare and
often of small scale making it difficult to
deterministically predict the exact location
of the rainfall maximum
• We need to develop better ways to convey
the potential for extreme rainfall