MODEL MODEL PARAMETERIZATIONS:PARAMETERIZATIONS:

IMPACTS ON QPFIMPACTS ON QPFWilliam A. Gallus, Jr.

Dept. of Geological & Atmospheric Science

Iowa State University

•Increased computer resources have allowed better parameterization schemes and model resolution

•2-day precipitation forecast today is now as accurate as 1-day forecast in 1974

•Each resolution improvement in NCEP Eta model improves skill scores

GOOD NEWS: QPF is GOOD NEWS: QPF is improving!!improving!!

BAD NEWS: Problems aboundBAD NEWS: Problems abound

•Most improvement in QPF scores occurs during cold season - little improvement in warm season

•Flash flooding kills more people than any other convective-related event

•QPF problems have several potential sources

•Skill scores used to evaluate forecasts themselves may be misleading or of little “real” value

Slow improvement in skill for human forecasters, but less skill for heavier amounts (Olson et al. 1995, WAF)

What are sources of What are sources of QPF error?QPF error?

• Resolution

• Initialization

• Parameterization

How do these interact?

What is the impact of What is the impact of resolution?resolution?

• For convection: not straightforward -- depends on parameterizations

• For stable precipitation: depends on parameterizations also

Gallus 1999 found QPF-horizontal resolution dependence is case-dependent and varies with convective parameterization

6/16/96 6/14/98 7/28/97

7/17/96 5/27/97

BMJ -shaded

KF - clear

Mx obs: 225 Mx obs: 330 Mx obs: 250

Mx obs: 300 Mx obs: 102

Extreme example of unexpected results and Conv. Param. Impacts: 7/17/96 00UTC

surface conditions

00 UTC 17 JUL 1996 - OMAHA

Betts-Miller- Janjic Reference T, Td profiles shown

Large MCS drops up to 300 mm of rain, causing record river crests and severe flash flooding in far eastern NE and western IA.

7/17/96 BMJ simulations with 78,39,22 and 12 km horizontal resolution

NOTE: actual reduction in peak QPF amounts as resolution improves

MX: 46 MX: 45

MX: 32 MX: 32

7/17/96 KF simulations:

NOTE: very strong QPF sensitivity to horizontal resolution. Precipitation area shifted much farther north than in BMJ runs, or observations

MX: 11 MX: 70

MX: 135MX: 186

Daytime precipitation (12-00 UTC 7/16-17/96)

BMJ produces much larger area and amounts

BMJ KF

Convective scheme influences cold pool strength, which in turn, affects evolution of events outside initial rain region

Impacts of convective schemes may be felt outside region of precipitation.

Here, stronger downdrafts in KF scheme result in greater northward transport of instability into Minnesota - leading to more intense subsequent development.

BMJ KF

Another case: Iowa flood of Another case: Iowa flood of June 1996June 1996

Large-scale region looked favorable for excessive rains

Heaviest rains (225 mm) fell in small area in warm sector

Impacts of horizontal resolution changes strongly depend on convective scheme used

Tropical-like soundings with very deep moisture

Td at 850 mb = 18 C

Td at 700 mb = 8 C

BMJ simulations:

Almost no horizontal resolution-QPF dependence

No hint of C IA maximum

21 UTC 6/16

Observed Surface Moisture Convergence

Flood-producing storms would form on C IA enhancement

Simulated Moisture Convergence -21 UTC - BMJ run with 12 km resolution

Despite poor initial wind field, model does show enhancement in W IA

BMJ simulation:

No general clearing into Iowa by 1 pm -

Less destabilization than actually occurred

KF simulations:

Strong horizontal resolution-QPF dependence

Some evidence of C IA enhancement with 22 and 12 km resolution

KF 6 hr forecast:

Some clearing into SW Iowa

more agreement with obs.

June case shows:June case shows:

• Moist low-mid troposphere allows BMJ scheme to be aggressive

• Even high resolution may not improve simulation of small QPF maxima if other simulated parameters are incorrect

• Generation of QPF upstream due to resolution changes may affect QPF downstream

For non-convective precipitation, For non-convective precipitation, sensitivities to grid spacing and sensitivities to grid spacing and microphysical parameterization microphysical parameterization

can be significantcan be significant

• Colle and Mass examine resolution-orographic precipitation (1999) dependence

• Microphysical schemes influence results

OBS PRECIP IN PACIFIC NORTHWEST FLOOD EVENT (1996)

from Colle and Mass (1999; MWR)

Pronounced orographic effects

4 km MM5 run does well at crest but underestimates lee precipitation

Horizontal resolution affects precipitation patterns near mountain due to resolution of mountain wave effects. Model QPF performance in lee of mountain fluctuates - low bias is best in coarsest run, but heaviest precipitation just to lee of crest occurs with highest resolution

1.33

4

12

36

Microphysical schemes may have significant influences at high resolution.

Colle and Mass (1999; MWR) found that lee-side precipitation was too small in high-res MM5 simulations, partly because snow fallspeeds were too large.

Best results may not occur with most sophisticated microphysical scheme

Microphysical scheme differences affect QPF in different areas

What impact does What impact does initialization have?initialization have?

• Although impacts can be significant in some cases, recent ensemble work suggests parameterization details have bigger impact on short-term mesoscale forecasts

10 km Eta simulations run for 10 km Eta simulations run for 20 cases of Midwest MCSs20 cases of Midwest MCSs

• Improvements in initialization to better depict mesoscale features generally result in limited improvement in skill scores

• Variations in forecast are much larger for change in convective parameterization than for any change in initial conditions

Equitable Threat Score

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0.02

0.04

0.06

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Series 1 Series 2 Series 3Series 4 Series 5 Series 6

ETS Scores averaged over 50 periods

BMJ

KFMOCP

.01 .05 .10 .15 .20 .25 .35 .50 1.0

What impact does What impact does initialization have?initialization have?

• Although impacts can be significant in some cases, recent ensemble work suggests parameterization details have bigger impact on short-term mesoscale forecasts

• One example in one case: Gallus and Segal (2000) found potentially strong sensitivity of QPF to soil moisture, but depended greatly on choice of convective scheme

Impact of varied soil moisture on QPF depends greatly on convective scheme.

With BMJ - wetter soil yields heavier peak QPF

With KF - heaviest QPF occurs with dry soil due to stronger low-level winds and previous outflow

Parameterizations are clearly a Parameterizations are clearly a primary influence on QPF:primary influence on QPF:

Which are key?Which are key?

• Convective Parameterizations

• Land-Surface/Boundary Layer Schemes

• Microphysical parameterizations (also influence radiative schemes)

Ways for Convective Schemes to Ways for Convective Schemes to activateactivate:

• Presence of instability at grid point

• Existence of low or mid-level mass or moisture convergence exceeding threshold

• Rate of destabilization at a grid point

How does convection affect How does convection affect the larger-scale?the larger-scale?

• Adjustment schemes nudge toward empirical curves, a function of difference between the moist adiabats of cloud and environment

• Mass flux schemes explicitly model convective feedback at each grid point

Let’s examine primary NCEP Let’s examine primary NCEP modelsmodels

• ETA: 22 km horizontal resolution/50 layers - uses BMJ (adjustment w/o downdraft) test version uses KF (mass flux w downdraft)

• RUC: 20 km horizontal resolution/40 layers - uses Grell (mass flux w downdraft)

• AVN: 70 km horizontal resolution/42 layers - uses Grell-Pan (mass flux) for deep with Tiedke (mass flux w downdraft) for shallow

Operational Eta:

•In BMJ scheme, both shallow and deep convection occur.

•Deep convection potential is first evaluated

•Shallow convection only occurs if no deep convection is present

Deep Convection

• Most unstable parcel in lowest 200* hPa

• Cloud depth must exceed 200 hPa (or less if terrain is elevated)

• Reference Temp profile in cloud layer has 90% of slope of moist adiabat at cloud base

• Reference Moisture profile based on deficit from saturation pressure at cloud base, freezing level and cloud top

Deep Convection (cont.)

• Modification made for precipitation efficiency (less mature system has larger P.E.)

• PE is a measure of how well the cloud transports enthalpy upward vs. how much precip is produced

• If negative precipitation is produced by convective adjustment toward moisture profile, shallow scheme is called

00 UTC 17 JUL 1996 - OMAHA

Betts-Miller- Janjic Reference T, Td profiles shown

Shallow BMJ scheme

• Clouds must be 10-200 hPa deep

• Lower cloud is warmed/dried while upper portion is cooled and moistened

• Moist mixing process can help the deep convection to later activate, but also result in unrealistic thermodynamic profiles

Effect of Eta BMJ shallow convection - from Baldwin

et al. 2000

Eta: KF Scheme

• Activated by more traditional trigger function - W

• Mass flux scheme with parameterized downdrafts

• Original scheme much less aggressive than BMJ - more grid-resolved precipitation, but changes have made it more like BMJ (though still with lower bias scores)

Any general rules about the Eta convective schemes?

• BMJ generally likes moist environments - usually rain areas are too broad and not intense enough

• KF may be better in showing heavier amounts in small regions, and in activating along dry lines

• BMJ traditionally was too dry in elevated terrain of West USA (change in cloud depth may improve this dry bias)

• For elevated nocturnal convection, BMJ may do better since it doesn’t depend much on low-level forcing

• KF may have tendency to focus precipitation too far north (reasons unclear)

Land-Surface/PBL schemes

• Eta uses 4 soil layer OSU land-surface scheme

• Mellor-Yamada Level 2.5 model for vertical turbulent exchange

• Soil moisture and temperature explicitly forecasted for soil layers and skin temperature, with 3 components of evaporation

Eta Microphysics

• Rather simple Zhao (1991) scheme used with cloud water explicitly forecasted

• Microphysics influences radiative parameterization

RUC Convective Scheme

• Grell scheme modified for scale dependence and shallow convection, interaction with cloud microphysics

• Mass flux scheme activated by destabilization rate

• Contains parameterized convective downdraft, and allows detrainment of liquid, solid and vapor water from convection

RUC Convection (Cont.)

• Initiation based upon a lifting depth trigger (if the depth from source level [max moist static energy] to LFC is less than a threshold [often 100 hPa], scheme activates

• Scheme is generally drier than KF in dry, deep boundary layer regimes

• Grell scheme may work well over bigger range of horizontal resolutions than some other schemes

RUC Convection (cont.)• Boundary layer tendencies impact the

parameterization significantly - may get too much rain over warm oceans, and widespread rain in summer, but too little near SE coast in winter.

• Precipitation in RUC generally over smaller areas with sharper gradients than ETA-BMJ (more passive scheme than BMJ)

• False alarms lower than Eta, but less POD also

Other RUC parameterizations

• Refined Burk-Thompson turbulence scheme with explicit TKE prediction

• Reisner 2 (4) microphysical scheme (cloud water, rainwater, snow, ice, graupel and # concentration of ice crystals explicitly predicted)

• Land-sfc scheme uses 6 soil/vegetation layers (Smirnova 1997, 1999)

AVN Convective scheme

• Grell-Pan scheme for deep convection, Tiedke for shallow

• Convective initiation requires time rate of change of stability as primary trigger

• Cap strength influences activation

• Modifies column buoyancy toward equilibrium as a function of cloud base vertical motion

AVN Deep Convection

• Does not consider ice phase, water loading, or evaporation of falling rain below cloud base

• Moisture convergence between cloud base and top is partitioned into rain-producing part, and relative humidity increasing part, based on column relative humidity

Deep Convection (Cont.)

• Convection not permitted if low levels are cooler than 5 C, low-level inversions exist, or moisture convergence would not be enough to allow 2 mm/day rainfall

• Buoyant layer must be more than 30% of sfc pressure deep

AVN Shallow Convection

• Only permitted if no deep convection occurs

• Enhanced vertical diffusion of humidity and heat if conditional instability present near sfc

• No convergence required

• Restricted to roughly 5 lower model layers

• No precipitation produced

Other AVN parameterizations

• Grid-resolved precipitation falls out if supersaturation occurs

• Evaporation of this precipitation can occur as long as relative humidity doesn’t increase beyond 80 (or 90)%

• Land-sfc scheme uses 2 soil layers, but in most other ways is similar to Eta

Other details to consider:

• Few extensive studies of how different schemes in different models perform under different weather conditions

• QPF can be very sensitive to small changes made within convective schemes

Spencer & Stensrud Spencer & Stensrud variations in KF schemevariations in KF scheme

•Permit Precipitation Efficiency to remain at maximum (90%) instead of varying from 10-90%

•Neglect convective downdrafts

•Delay convective downdrafts

Max. Prec for 4 tests

Case OBS nomod mpe ndd DddAug86 170 53 61 107 66Jul87 254 48 53 188 79Sep89 150 76 94 170 97Jun90 127 48 36 142 52Nov92 236 51 61 132 80AVG 196 67 74 150 83

Maximum QPF in 4 KF MM4 runs

From Spencer and Stensrud 1998 - MWR

Concluding ThoughtsConcluding Thoughts

•QPF is probably the most difficult aspect of NWP - the hardest one to envision being solved in 25 years

Concluding ThoughtsConcluding Thoughts •QPF is probably the most difficult aspect of NWP - the hardest one to envision being solved in 25 years

•If convective parameterizations are used, behavior of these schemes exerts powerful impact (primary differences between different models are probably related to the Cu scheme)

Concluding ThoughtsConcluding Thoughts •QPF is probably the most difficult aspect of NWP - the hardest one to envision being solved in 25 years

•If convective parameterizations are used, behavior of these schemes exerts powerful impact (primary differences between different models are probably related to the Cu scheme)

•Forecasters can benefit by understanding the specifics of how the schemes behave (along with other parameterizations interacting with Cu scheme)