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SEMI-INTELLIGENT USE OF THE ETA MODEL - Part 1. MICHAEL ECKERT. HYDROMETEOROLOGICAL PREDICTION CENTER. CAMP SPRINGS, MD. E-MAIL ADDRESS: [email protected] COMAP SYMPOSIUM 00-1 14 December 1999. Why models have forecast problems.

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Semi intelligent use of the eta model part 1
SEMI-INTELLIGENT USE OF THE ETA MODEL - Part 1

MICHAEL ECKERT

HYDROMETEOROLOGICAL PREDICTION CENTER

CAMP SPRINGS, MD

E-MAIL ADDRESS: [email protected]

COMAP SYMPOSIUM 00-1

14 December 1999


Why models have forecast problems
Why models have forecast problems

  • Initialization and quality control smooth data fields, but some of the lost detail may be important.

  • May have poor first guess

  • Lack of data over the oceans and Mexico.

  • Atmospheric processes are non-linear; small changes in initial conditions can lead to large forecast variations (this is the basis for ensemble forecasting).

  • Model physics are approximations

    • for lower resolution models, convection is parameterized

    • for higher resolution models the micro-physical processes are parameterized


Intelligent use of the model requires that the forecaster
INTELLIGENT USE OF THE MODEL REQUIRES THAT THE FORECASTER

  • COMPARE THE INITIAL 00HR FORECAST WITH DATA

  • BE FAMILIAR WITH CHARACTERTIC MODEL ERRORS AND BIASES.

  • HAVE A ROUGH UNDERSTANDING OF HOW APPROXIMATIONS OF THE PHYSICS MAY NEGATIVELY IMPACT A FORECAST.


The performance characteristics of the eta have changed dramatically during the past year
The performance characteristics of the eta have changed dramatically during the past year.

  • QPF forecasts during the past winter deteriorated when compared to the AVN or NGM.

  • ETA surface and 500 mb forecasts have also been worse compared to the other models.

    • April 1999 ETA 500 h and 250 mb forecasts usually verified worse than the AVN.


32 km terrain
32-km terrain dramatically during the past year.

Know the difference between model and real terrain!


DESPITE ITS RECENT PROBLEMS, THE ETA IS STILL USUALLY BETTER THAN THE AVN OR NGM FORECASTING PRECIPITATION OVER COMPLEX TERRAIN DURING WINTER IN A ZONAL PATTERN.

12-36 H ETA V.T. 12Z 3 JAN 97

ANALYSIS V.T. 12Z 3 JAN 97

12-36 H NGM V.T. 12Z 3 JAN 97

Note that the Eta max in California is a little too far west. It also often under predicts precipitation over the Siskiyou Mountains of northern California.


Eta model physics
Eta Model Physics BETTER THAN THE AVN OR NGM FORECASTING PRECIPITATION OVER COMPLEX TERRAIN DURING WINTER IN A ZONAL PATTERN.

  • Eta model calculates grid-scale precipitation using a simplified explicit cloud water scheme

    • includes super-cooled water, simplified snow processes and the advection of cloud water and cloud ice

    • but does not include horizontal advection of snow and rain.

      • In fast flow snow can advect 50 to 100 km downwind of its source region (Rauber, 1992)


Explicit cloud prediction scheme large scale
EXPLICIT CLOUD PREDICTION SCHEME (large scale) BETTER THAN THE AVN OR NGM FORECASTING PRECIPITATION OVER COMPLEX TERRAIN DURING WINTER IN A ZONAL PATTERN.

  • Cloud condensation is allowed to occur when the RH reaches a critical value

  • Cloud evaporation is allowed to take place only when the RH falls below the critical value

    • 70% over land, 80% over water

    • the difference in the critical value between land and water can produce discontinuities along the coast

    • this may be one of the reasons the Eta over predicts cold season precipitation along the Gulf and Atlantic Coasts.


The bmj convective scheme
The BMJ Convective Scheme BETTER THAN THE AVN OR NGM FORECASTING PRECIPITATION OVER COMPLEX TERRAIN DURING WINTER IN A ZONAL PATTERN.

  • 1st looks for deep convection

    • step 1 is to look for most unstable layer within the lowest 130 mb

    • Next calculates LCL to get cloud base

    • then lifts parcel to Equilibrium Level to get cloud top

    • then looks to see if the cloud layer is at least 290 mb in depth

      • If the cloud is not 290 mb then it searches for shallow convection


More about the bmj scheme
More about the BMJ scheme BETTER THAN THE AVN OR NGM FORECASTING PRECIPITATION OVER COMPLEX TERRAIN DURING WINTER IN A ZONAL PATTERN.

  • then develops sounding based on a reference profile.

    • The important thing to remember about the profile is it will not allow the sounding to become completely saturated.

    • The saturation pressure deficit is found for three levels (cloud base, freezing level and cloud top) and the final reference profile based on the type of cloud efficiency

    • Saturation pressure deficits are then found for other points along the profile

      • when the saturation pressure deficits are exceeded, the moisture produces rain.

      • however, the amount of rainfall must be in balance with the latent heating.


The bmj scheme
The BMJ scheme BETTER THAN THE AVN OR NGM FORECASTING PRECIPITATION OVER COMPLEX TERRAIN DURING WINTER IN A ZONAL PATTERN.

  • Was developed for tropical systems

    • does not handle elevated convection well

      • the convection may not extend through a deep enough layer

  • does not develop realistic downdrafts/outflow boundaries

    • therefore, during summer it sometimes predicts the convective development too far north

  • the saturation pressure deficits in the scheme are different over land and water


THE ETA OFTEN FORECASTS BETTER THAN THE AVN OR NGM FORECASTING PRECIPITATION OVER COMPLEX TERRAIN DURING WINTER IN A ZONAL PATTERN. TOO MUCH RAINFALL NEAR THE GULF AND SOUTHEAST COASTS BECAUSE OF THE PROBLEMS WITH THE WAY THE ETA HANDLES THE LAND-SEA INTERFACE

12-36 HR PRECIPITATION FORECAST V. T. 12Z 1 APR

24 HR PRECIPITATION ANALYSIS V. T. 12Z 1 APR


For any model always beware of the 1st guess
FOR ANY MODEL, ALWAYS BEWARE OF THE 1ST GUESS BETTER THAN THE AVN OR NGM FORECASTING PRECIPITATION OVER COMPLEX TERRAIN DURING WINTER IN A ZONAL PATTERN.

00 HR ETA SURFACE AND 1000-500 MB THICKNESS V.T. 00Z 3 SEP 1998

00 HR ETA 500 MB HEIGHT AND VORTICITY V.T. 00Z 3 SEP 1998

SURFACE ANALYSIS V.T. 00Z 3 SEP 1998

TROPICAL STORM EARL WAS LOCATED JUST SOUTHWEST OF THE FLORIDA PENINSULA. THE 1ST GUESS WILL SOMETIMES OVERRIDE DATA WHEN INTENSE SMALL SCALE FEATURES ARE PRESENT.


What happened
WHAT HAPPENED? BETTER THAN THE AVN OR NGM FORECASTING PRECIPITATION OVER COMPLEX TERRAIN DURING WINTER IN A ZONAL PATTERN.

THE MRF 1ST GUESS FIELD TRIED TO DRAW TO THE DATA BUT THE FIRST GUESS FIELD OVERWHELMED IT. IF NCEP HAS A COMPUTER FAILURE, THE ETA DATA ASSIMILATION MAY BE CANCELLED AND THE ETA MAY RUN ON AN EARLIER GLOBAL MODEL 1ST GUESS


A poor initial analysis can produce huge forecast errors
A POOR INITIAL ANALYSIS CAN PRODUCE HUGE FORECAST ERRORS BETTER THAN THE AVN OR NGM FORECASTING PRECIPITATION OVER COMPLEX TERRAIN DURING WINTER IN A ZONAL PATTERN.

ETA 48 HR V.T. 00Z SEP 5

ETA 48 HR V.T. 00Z SEP 5

EARL

EARL

EARL

EARL

ETA 00 HR V.T. 00Z SEP 5

ETA 00 HR V.T. 00Z SEP 5


IN THE PAST, ETA MODEL HAS HAD PROBLEMS PREDICTING THE STABILITY. PROBLEM IS OFTEN TIED TO THE 1ST GUESS

HIGH SOIL MOISTURE CASE

WHEN SOIL MOISTURE IS HIGH, THE ETA DEWPOINTS ARE TOO HIGH AND LOW-LEVEL TEMPERATURES ARE TOO LOW.

THE ETA FORECAST CAPE=1177, LI=-4

OBSERVED CAPE=5, LI=2

THIS SOMETIMES CAUSES THE MODEL TO BE TOO UNSTABLE

FORECAST

OBSERVED


When high soil moisture is present or when the model first guess thinks the soil moisture is high

OBSERVED STABILITY. PROBLEM IS OFTEN TIED TO THE 1ST GUESS

ETA FORECAST

WHEN HIGH SOIL MOISTURE IS PRESENT, OR WHEN THE MODEL FIRST GUESS THINKS THE SOIL MOISTURE IS HIGH,

THEN, THE MODEL FORECASTS SURFACE DEWPOINTS TOO HIGH AND SURFACE TEMPS TOO LOW.

32

SURFACE TEMPERATURE

28

24

20

24

DEWPOINT TEMPERATURE

20

16

12

1024

1020

SURFACE PRESSURE

1016

1012

THE MODEL UNDERPREDICTS THE BOUNDARY LAYER WINDS. HOWEVER, MODEL FORECASTS OF 850 MB WINDS ARE OFTEN TOO STRONG

18/00

18/06

18/12

18/18

19/00

19/06

19/12

19/18

20/00


WHEN LOW SOIL MOISURE IS PRESENT DURING SUMMER OVER THE HIGH PLAINS, ESPECIALLY WEST TX, THE FORECAST CAPE IS TOO LOW


OBSERVED PLAINS, ESPECIALLY WEST TX, THE FORECAST CAPE IS TOO LOW

ETA FORECAST

WHEN SOIL MOISTURE IS LOW IN SUMMER IN THE PLAINS, THE SURFACE DEWPOINT IS TOO LOW AND THE TEMPERATURE IS TOO HIGH

THE DEWPOINTS IN THE PLAINS AND SOUTHWEST WERE TOO LOW THIS SUMMER

OKLAHOMA CITY

36

SURFACE TEMPERATURE

32

28

24

20

20

DEWPOINT

16

TEMPERATURE

12

1016

SURFACE PRESSURE

1008

ETA SURFACE WINDS WERE TOO WESTERLY, WAS THERE TOO MUCH DOWN-SLOPE?

19/00

19/06

19/12

19/18

20/00

20/06

20/12

20/180

21/00

MAY 1998


Forecast vs observed best cape spring 96

Line x=y PLAINS, ESPECIALLY WEST TX, THE FORECAST CAPE IS TOO LOW

Line x=y

Forecast precipitation

1 - less than .25”

2 - more than .25”

Forecast -Vs- Observed Best CapeSpring 96

Note the large spread. The model stability forecasts are worst when precipitation is forecast


More on eta performance
MORE ON ETA PERFORMANCE PLAINS, ESPECIALLY WEST TX, THE FORECAST CAPE IS TOO LOW

  • TOO WET IN FLORIDA

  • SOMETIMES OVERDEVELOPS LOW-LEVEL JET

  • HAS BEEN TOO FAST BRINGING SHORTWAVES THROUGH THE ROCKIES INTO THE PLAINS.

  • HAS BEEN TOO FAR SOUTH WITH CLOSED LOWS COMING EASTWARD INTO THE PLAINS

  • OVERFORECASTS THE STRENGTH OF ANTICYCLONES

  • HAS PROBLEMS INITIALIZING TROPICAL SYSTEMS


Eta and storm tracks
ETA AND STORM TRACKS PLAINS, ESPECIALLY WEST TX, THE FORECAST CAPE IS TOO LOW

DURING 1999 TENDED TO BE TOO FAR SOUTH WITH LOWS AS THEY REFORMED EAST OF ROCKIES. THIS ERROR USUALLY CONTINUED UNTIL THE LOW MOVED EAST OF THE MISSISSIPPI RIVER.

BY CONTRAST, THE AVN IS SOMETIMES TOO FAR NORTH

TENDS TO SOMETIMES TRACK LOWS TOO FAR NORTH AND WEST WITH LOWSALONG THE EAST COAST.

ESPECIALLY DURING MAJOR CYCLOGENESIS WHEN A COASTAL TROUGH IS PRESENT


Common eta error along east coast
COMMON ETA ERROR ALONG EAST COAST PLAINS, ESPECIALLY WEST TX, THE FORECAST CAPE IS TOO LOW

WHEN A CLOSED UPPER LOW APPROACHES THE COAST THE ETA SOMETIMES HAS PROBLEMS FORECASTING THE LOCATION OF THE SURFACE LOW. NOTE WHERE THE UPPER LOW IS CENTERED AND WHERE THE STRONGEST UPPER-LEVEL DIVERGENCE IS IMPLIED.

48 H ETA 500H V.T. 12Z 23 APR 98

48 H NGM 500H V.T. 12Z 23 APR 98

Based on the 500 h and vorticity pattern, where would you predict the surface low?


NOTE THAT THE ETA SURFACE LOW IS A LITTLE WEST OF ITS 500 MB CENTER. THE NGM HAS A MUCH BETTER FIT TO THE 500 MB PATTERN.

THE STRONG EASTERLY COMPONENT TO THE WINDS NORTH OF THE ETA MODEL LOW ALLOWS IT TO WRAP MOISTURE AND PRECIPITATION TOO FAR WEST

48 H ETA SURFACE V.T. 12Z 23 APR 98

48 H NGM SURFACE V.T. 12Z 23 APR 98


THE LOW VERIFIES A LITTLE NORTH AND EAST OF THE NGM. REMEMBER, THE NGM IS TYPICALLY TOO SLOW WITH LOWS ALONG THE COAST.

VERIFYING SURFACE V.T. 12Z 23 APR 98

VERIFYING 500H V.T. 12Z 23 APR 98

L

ETA SURFACE LOW


When the NGM and AVN sheared 500 troughs approaching the east coast in 1999, the eta often amplified the trough and overdeepened the surface low. An example:

48 HR ETA 500

48 HR ETA SFC

48 HR NGM 500

48 HR NGM SFC


The eta predicted a major east coast snowstorm the ngm and avn predicted light snow at best
The Eta predicted a major east coast snowstorm. The NGM and AVN predicted light snow at best

36-48 hr ETA precipitation

36-48 hr NGM precipitation


How the model verified no major snowstorm developed
HOW THE MODEL VERIFIED. NO MAJOR SNOWSTORM DEVELOPED AVN predicted light snow at best.

48 HR ETA 500

VERIFYING 500 MB

48 HR NGM 500

VERIFYING SFC


Lows to the lee of the rockies
LOWS TO THE LEE OF THE ROCKIES AVN predicted light snow at best

  • THE AVN AND NGM USUALLY PREDICT THEM TO FORM TOO FAR NORTH

  • THE ETA IS SOMETIMES A LITTLE TOO FAR SOUTH

  • USE THE 300 MB UPPER LEVEL JET. THE SURFACE LOW IS USUALLY FOUND IN THE LEFT EXIT REGION OF THE JET, USUALLY JUST TO THE NORTH


28 ETA model runs were evaluated during the period from 00Z March 30-12 Z April 13. During the entire period the mean 500h pattern was similar to the one shown below.

A RIDGE AND POSITIVE ANOMALY NEAR 160W, BELOW NORMAL HEIGHTS OVER ALASKA AND A TROUGH NEAR OF JUST INLAND FROM THE WEST COAST WITH BELOW NORMAL HEIGHTS EXTENDING EASTWARD INTO THE SOUTHWESTERN U.S.

THE ETA SHOWED A CONSISENT CHARACTERISTIC ERROR DURING THE PERIOD. THE NEXT FEW SLIDES WILL DESCRIBE THE ERROR


As the upper trough digs into the west the ETA did not dig the shortwaves strongly enough once the trough reached the ca coast. Note how much lower the heights are across NV and CA.

48 hr ETA valid 00Z 1 April

00 hr eta valid 00Z 1 April


The eta underplays the second shortwave diving into the mean trough and overplays the first one
The eta underplays the second shortwave diving into the mean trough and overplays the first one.

48 hr ETA 500 h and vorticity v.t. 12Z 4 April

00 hr ETA 500 h and vorticity v.t. 12Z 4 April

THE ETA PREDICTED THE UPPER LOW ASSOCIATED WITH THE FIRST SHORTWAVE TOO FAR SOUTH AND EAST IN THE PLAINS. INSTEAD THE INITIAL SHORTWAVE LIFTED MORE TO THE NORTH BEFORE BEING FORCED EASTWARD. THIS HAPPENED SEVERAL TIMES DURING THE STUDY.


The eta was generally too fast trough and overplays the first one.and far southeast with the 500h low over the Plains with 120 meter errors over MO and IA. This can have a very serious impact on frontal speed and on the position of the low level convergence and resulting convection.

546

558

00 hr Eta v.t. 12Z 10 Apr

48 hr Eta v.t. 12Z 10 Apr


The Eta surface low and associated fronts can also be affected. The slower eastward movement of the ridge axis may allowed for the flow along the east to be more northwesterly which allowed the surface boundary to sink farther to the south

48 hr Eta v.t. 12Z 10 Apr

00 hr Eta v.t. 12Z 10 Apr


Why models have problems with arctic airmasses
Why models have problems with arctic airmasses affected. The slower eastward movement of the ridge axis may allowed for the flow along the east to be more northwesterly which allowed the surface boundary to sink farther to the south

  • Terrain is averaged

  • Initialization process sometimes robs shallow airmass of its coldness

  • Models have problems handling the strength of the inversion

  • The sigma coordinate system, the Eta coordinate system does better

  • The leading edge of the ETA LI gradient is often the best indicator of the frontal position


The ngm and avn mrf have serious problems with arctic airmasses

36 HR AVN V.T. 00Z APR 09, 1995 affected. The slower eastward movement of the ridge axis may allowed for the flow along the east to be more northwesterly which allowed the surface boundary to sink farther to the south

THE NGM AND AVN/MRF HAVE SERIOUS PROBLEMS WITH ARCTIC AIRMASSES.

L

36 HR NGM V.T. 00Z APR 09, 1995

AVN ANALYSIS V.T. 00Z APR 09, 1995

TEMPERATURES ACROSS KANSAS WERE IN THE LOW TO MID 50s WITH STRONG NORTH WINDS. SOUTH OF THE FRONT TEMPERATURES WERE IN THE UPPER 70s TO LOW 90s.

PRIOR TO THE 1998-99 WINTER SEASON ,ETA USUALLY HANDLED ARCTIC AIR MASSES BETTER.


When using models pattern recognition remains important
WHEN USING MODELS, PATTERN RECOGNITION REMAINS IMPORTANT! affected. The slower eastward movement of the ridge axis may allowed for the flow along the east to be more northwesterly which allowed the surface boundary to sink farther to the south

VALID AT BEGINNING OF PERIOD

MSL, THICKNESS AND 850 WINDS

PRECIPITABLE WATER (INCHES) AND 850 MB WINDS

SEVERAL THINGS TO NOTE: 1) A LONG FETCH OF DEEP MOISTURE, 2) A BARRIER JET AND STRONG SOUTHERLY FLOW UP THE SACREMENTO VALLEY. THIS JET HELPS PRODUCE HEAVY RAINS NEAR SHASTA, 3) STRONG WARM ADVECTION.


Do the forecasts look consistent with what you see in the pacific check ssmi data
DO THE FORECASTS LOOK CONSISTENT WITH WHAT YOU SEE IN THE PACIFIC? CHECK SSMI DATA

VALID AT THE END OF THE PERIOD

PRECIPITABLE WATER (INCHES) AND 850 MB WINDS

MSL, THICKNESS AND 850 WINDS


OVERLAYING MODEL OUTPUT WITH SSMI IMAGERY CAN GIVE YOU A GOOD IDEA OF THE MOISTURE THAT WILL BE FEEDING INTO THE WEST COAST. THE MODEL OUTPUT LOOKS REASONABLE

NOTE THE TROPICAL CONNECTION AND PLUME OF PWS ABOVE 1.00”


THE MODEL’S TERRAIN IS AVERAGED OVER THE GRID BOX SO THE SLOPE OF THE TERRAIN IS USUALLY NOT STEEP ENOUGH

THIS CAUSES THE VERTICAL MOTION FIELD TO BE SHIFTED AWAY FROM THE MOUNTAINS


Things to remember about model qpfs in complex terrain during winter
THINGS TO REMEMBER ABOUT MODEL QPFS IN COMPLEX TERRAIN DURING WINTER

BECAUSE OF THE SIMPLIFIED MICROPYSICS AND INADEQUATE RESOLUTION OF MOUNTAINS.

MODELS USUALLY:

1) PREDICT PRECIPITATION TOO FAR WEST AWAY FROM MOUNTAIN PEAKS

2) DO NOT ALLOW ENOUGH PRECIPITATION ON THE IMMEDIATE DOWNWIND SIDE OF MOUNTAIN RANGES



32 KM ETA TERRAIN DURING WINTER

24 HOUR PRECIPITATION VALID JAN. 9, 1995

WITH STRONG VERY MOIST SOUTHWESTERLY FLOW AT 850 AND 700 MB NOTE HOW CLOSELY THE PRECIPITATION CONFORMS TO THE TERRAIN

WHEN SOUTHWESTERLY FLOW IS PRESENT A BARRIER JET FORMS AND FUNNELS THE FLOW UP THE SACREMENTO VALLEY.


If the model is so dry during the summer in the plains how do i use it
IF THE MODEL IS SO DRY DURING THE SUMMER IN THE PLAINS, HOW DO I USE IT?

WARM FRONT?

USING PATTERN RECOGNITION AND KNOWLEDGE OF TYPICAL MODEL ERRORS.

DOES THIS LOOK LIKE A MADDOX FRONTAL TYPE EVENT?


Boundary layer wind and temperature forecast v t 00z 18 july
BOUNDARY LAYER WIND AND TEMPERATURE FORECAST V.T. 00Z 18 JULY

THE BLUE LINE INDICATES A THERMAL BOUNDARY THAT SHOWS UP IN THE FORECAST


A strong low level jet is present with lots of moisture this is a typical maddox type set up
A STRONG LOW LEVEL JET IS PRESENT WITH LOTS OF MOISTURE. THIS IS A TYPICAL MADDOX TYPE SET UP.

IS IT TIME TO CALL EMERGENCY MANAGERS? FOR WHICH STATE? MINNESOTA? WISCONSIN? IOWA? ILLINOIS?


Ooz 18 july forecasts of
OOZ 18 JULY FORECASTS OF THIS IS A TYPICAL MADDOX TYPE SET UP.

250 JET AND DIVERGENCE

BEST LI AND BOUNDARY LAYER WINDS

A SHORTWAVE AND JET STREAK IS APPROACHING THE RIDGE. UNSTABLE LIS ALONG SURFACE BOUNDARY


Is this a good qpf do you think the rainfall is oriented correctly
IS THIS A GOOD QPF? DO YOU THINK THE RAINFALL IS ORIENTED CORRECTLY

WHICH WSFOS NEED TO CONTACT EMERGENCY MANAGERS?


How did you do

DURING SUMMER THE ETA IS OFTEN UNDERPLAYS THE PRECIPITATION ASSOCIATED WITH MCCS. IT ALSO OFTEN PREDICTS ITS RAINFALL MAXIMUM TOO FAR NORTH BECAUSE IT CANNOT HANDLE OUTFLOW BOUNDARIES, OR IN THIS CASE THE LAKE BREEZE.

HOW DID YOU DO?

MODEL FORECAST

OBSERVED

6” OR MORE

3” OR MORE

1” OR MORE


Verifying precipitation
VERIFYING PRECIPITATION ASSOCIATED WITH MCCS. IT ALSO OFTEN PREDICTS ITS RAINFALL MAXIMUM TOO FAR NORTH BECAUSE IT CANNOT HANDLE OUTFLOW BOUNDARIES, OR IN THIS CASE THE LAKE BREEZE.

  • BIAS=FORECAST/OBSERVED

  • EQUITABLE THREAT=(H-E)/(F+O-H-E)

  • THREAT SCORE=H/(F+O-H)

    • N=NUMBER OF HITS, F=NUMBER OF GRID POINTS FORECAST, O=GRID POINTS OBSERVED, E=(F*O)/N


Model bias and threat score
MODEL BIAS AND THREAT SCORE ASSOCIATED WITH MCCS. IT ALSO OFTEN PREDICTS ITS RAINFALL MAXIMUM TOO FAR NORTH BECAUSE IT CANNOT HANDLE OUTFLOW BOUNDARIES, OR IN THIS CASE THE LAKE BREEZE.

  • IS DEPENDENT ON RESOLUTION OF MODEL

  • HOW THE MODEL IS DISPLAYED. THE FAX VERSION OF ETA IS NOT DISPLAYED WITH FULL MODEL RESOLUTION!

  • HOW THE MODEL IS VERIFIED

    • WHETHER VERIFIED AT A POINT, OR AVERAGED OVER A GRID BOX



Regional eta verification using model grid 80 km
Regional ETA verification using model grid (80 km) SUBJECTIVE AND AVN GUIDANCE

WARM SEASON 1.00” OR MORE VERIFICATION

VERIFIED TO AN 80 KM GRID

.64 .15

.97 .18

.98 .15

.93 .17

.65 .14

.59 .19

.35 .09

.47 .08

.83 .12


Regional eta verification using model grid 80 km1
Regional ETA verification using model grid (80 km) SUBJECTIVE AND AVN GUIDANCE

COLD SEASON 1.00” OR MORE VERIFICATION

VERIFIED TO AN 80 KM GRID

.69 .17

.94 .18

1.07 .23

1.36 .22

.74 .09

.71 .27

.58 .10

.71 .15

1.04 .19

BIAS

ETS

AGAIN NOTE HIGH BIAS ALONG EAST COAST AND LOW BIAS OVER WEST


Regional eta verification using model grid 80 km2
Regional ETA verification using model grid (80 km) SUBJECTIVE AND AVN GUIDANCE

.01” OR GREATER AMOUNTS DURING COLD SEASON

VERIFIED TO AN 80 KM GRID

1.43 .25

1.05 .35

1.07 .35

.81 .37

1.23 .23

.79 .32

.95 .26

1.11 .34

1.07 .35

HIGHEST THREATS ALONG WEST COAST. HIGH BIAS OVER UPSLOPE AREAS EAST OF ROCKIES AND OVER PLAINS


Regional eta verification using model grid 80 km3
Regional ETA verification using model grid (80 km) SUBJECTIVE AND AVN GUIDANCE

.01” OR GREATER AMOUNTS DURING WARM SEASON

VERIFIED TO AN 80 KM GRID

1.11 .28

.96 .39

.92 .37

.81 .34

1.21 .19

1.00 .37

.82 .23

1.01 .32

.99 .38

BIG DIFFERENCES WITH POINT VERIFICATION. USING A POINT VERIFICATION, YOU SEE THE HUGE BIASES OVER THE SOUTH


Eta 50 or more performance during warm season
ETA .50” OR MORE PERFORMANCE DURING WARM SEASON SUBJECTIVE AND AVN GUIDANCE

VERIFIED TO AN 80 KM GRID

.77 .21

1.10 .23

1.09 .25

1.07 .24

.88 .12

.82 .17

.82 .28

.62 .14

.86 .20

BIAS

ETS

DURING SUMMER ETA UNDERPREDICTS .50” OR GREATER AMOUNTS IN PLAINS. MESO-ETA HAS SAME BIAS


Eta performance for 50 or greater amounts apr 96 nov 97

. SUBJECTIVE AND AVN GUIDANCE89 .23

1.32 .31

1.00 .15

1.10 .23

1.13 .31

.83 .35

.97 .13

1.10 .26

.90 .23

BIAS THREAT

ETA PERFORMANCE FOR .50 OR GREATER AMOUNTS APR 96-NOV 97

VERIFIED TO AN 80 KM GRID

ETA OVERPREDICTS .50 OR GREATER ACROSS SOUTH AND ALONG EAST COAST. MESO-ETA HAS SAME BIAS


Prior to the changes last summer the eta model was best
PRIOR TO THE CHANGES LAST SUMMER, THE ETA MODEL WAS BEST SUBJECTIVE AND AVN GUIDANCE

  • AT HANDLING ARCTIC AIRMASSES PLUNGING SOUTHWARD ALONG THE FRONT RANGE OF THE ROCKIES

  • FORECASTING PRECIPITATION ALONG THE WEST COAST INCLUDING THE CASCADE AND SIERRA RANGES

  • USUALLY BEST IN FORECASTING COLD-AIR DAMMING ALONG THE EAST COAST (ITS LI FORECAST IS OFTEN THE BEST INDICATOR)


In conclusion
IN CONCLUSION SUBJECTIVE AND AVN GUIDANCE

  • THE ETA MODEL HAS HAD SERIOUS PROBLEMS SINCE 3DVAR WAS IMPLIMENTED.

  • PRIOR TO 3D-VAR ETA QUANTITATIVE PRECIPITATION FORECASTS WERE BETTER THAN THOSE OF THE AVN.

    • AVN PRECIPITATION FORECASTS HAVE BEEN SUPERIOR DURING THE PAST 7 MONTHS

  • BETTER VERIFICATION IS NEEDED OF OPERATIONAL MODELS. THE VERIFICATION NEEDS TO BE SHARED WITH FORECASTERS. EMC IS NOW MAINTAINING A VERIFICATION SECTION ON ITS HOMEPAGE.

  • EACH TIME A MODEL IS CHANGED, IT MAY AND PROBABLY WILL CHANGE THE PERFORMANCE CHARACTERISTICS.


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