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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.

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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

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

mm

25

50

75

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

500,000 km2

100,000 km2

2,500 km2

SON

DJF

MAM

JJA


Precipitation with mesoscale convective systems is very difficult to predict
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
Extreme rainfall is a moving target difficult to predict

  • 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
Forecasting extreme rainfall events difficult to predict

  • 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
A various time ranges difficult to predict

  • 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) difficult to predict

  • 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 difficult to predict

  • 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
THE AMOUNT OF RAINFALL THAT FALLS OVER AN AREA DEPENDS difficult to predict 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
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.


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.

RAINFALL RATE

RAINFALL RATE

RAINFALL RATE

RAINFALL RATE

TIME

TIME

TIME

TIME

From Doswell et al., 1996 (Weather & Forecasting, 11, 560-581)

You live at the blue dot

Adopted from Doswell et al. 1996


Where new cells form in relation to the initial convection is important to
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

    • Determining the speed and direction the system will move

Or this

Or this


The mode of development and propagation is influenced by a number of factors
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
Rainfall rates number of factors.

  • 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
What is precipitation efficiency number of factors.

  • 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 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


Movement of the system
MOVEMENT OF THE SYSTEM number of factors.

  • SLOW MOVING SYSTEMS ARE USUALLY THE HEAVIEST RAINFALL PRODUCERS

  • AT SHORTER TIME RANGES-EXTRAPOLATION 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 number of factors.

  • 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 heightdominate 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
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



Sref has synoptic pattern right
SREF has synoptic pattern right rainfall.

Bottom panels 850 winds and normalized anomalies

250wind & v-anom

L

L

Correctly predicts strong southern wind anomalies, PW anomalies of greater than 2


12-36 hr gfs rainfall.

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 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 forecasting QPF

Strong agreement about the synoptic pattern.

Forecast

Observed



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

Forecast

Actual Event

Reporting station

30 miles

A perfectly predicted 125 mm area having a position error

may be a terrible forecast. Or is it?


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
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
Forecasting extreme rainfall requires what does it mean

  • 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


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