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Suzanne Wetzel Seemann Jonathan E. Martin Scott Bachmeier October 4, 2001 5 th Annual High Plains Conference North Platte, NE. An Operational Ingredients-Based Methodology for Forecasting Midlatitude Winter Season Precipitation. http://speedy.meteor.wisc.edu/~swetzel/winter

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Suzanne Wetzel SeemannJonathan E. MartinScott Bachmeier October 4, 2001 5th Annual High Plains ConferenceNorth Platte, NE

An Operational Ingredients-Based Methodology

for Forecasting Midlatitude

Winter Season Precipitation

http://speedy.meteor.wisc.edu/~swetzel/winter

reference: Wetzel and Martin, 2001. Weather and Forecasting,16 (1), 156-167.


Outline

Introduction to the Ingredients-Based Methodology

Choice of Ingredients and Selected Diagnostics

Application of the Methodology and Ingredients Maps

Advantages and Limitations

October 4, 2001 5th Annual High Plains Conference


Ingredients-Based Forecast Methodology

The Ingredients-Based Forecast Methodology (IM)

provides a framework for a systematic assessment of the fundamental physical ingredients that influence the duration, intensity, and type of winter precipitation.

  • Based on physical principles

  • Flexibility to accommodate a variety of synoptic and thermodynamic conditions.

October 4, 2001 5th Annual High Plains Conference


Ingredient vs. Diagnostic

An ingredient is a fundamental physical element or process that directly contributes to the development and intensity of a precipitation event.

October 4, 2001 5th Annual High Plains Conference


Ingredient vs. Diagnostic

An ingredient is a fundamental physical element or process that directly contributes to the development and intensity of a precipitation event.

A diagnosticis the observable or derived quantity that can be used to assess the presence and strength of an ingredient.

October 4, 2001 5th Annual High Plains Conference


Ingredient vs. Diagnostic

An ingredient is a fundamental physical element or process that directly contributes to the development and intensity of a precipitation event.

A diagnosticis the observable or derived quantity that can be used to assess the presence and strength of an ingredient.

Parameters will be introduced to diagnose each ingredient; however, the IM is not dependent on these specific diagnostics.

October 4, 2001 5th Annual High Plains Conference


Choice of Ingredients

1. Forcing for ascent: Where and how strong is the forcing?

3. Moisture: Where and how much moisture is available?

October 4, 2001 5th Annual High Plains Conference


Choice of Ingredients

1. Forcing for ascent: Where and how strong is the forcing?

2. Atmospheric Stability: Will there be an enhanced response to the forcing?

3. Moisture: Where and how much moisture is available?

4. Precipitation Efficiency: How will cloud microphysical characteristics affect the precipitation rate?

October 4, 2001 5th Annual High Plains Conference


Choice of Ingredients

1. Forcing for ascent: Where and how strong is the forcing?

2. Atmospheric Stability: Will there be an enhanced response to the forcing?

3. Moisture: Where and how much moisture is available?

4. Precipitation Efficiency: How will cloud microphysical characteristics affect the precipitation rate?

5. Temperature: What form will the precipitation take, and what snow-to-water ratio is expected?

October 4, 2001 5th Annual High Plains Conference


Ingredient 1: Forcing for Ascent

Quasi-Geostrophic (QG)

Forcing Diagnostic

Q-Vector convergence Forcing for upward vertical motion

Use of the Q-vector as the sole means of

diagnosing vertical motion forcing is limiting

October 4, 2001 5th Annual High Plains Conference


Ingredient 1: Forcing for Ascent (cont’d)

Top right white contours:

QG forcing diagnostic

(for an 80km grid)

October 4, 2001 5th Annual High Plains Conference


Ingredient 1: Forcing for Ascent (cont’d)

Diagnostic of Non-QG Forcing: Full Wind Frontogenesis

  • Includes ageostrophic “thermally direct/indirect”

  • circulations.

October 4, 2001 5th Annual High Plains Conference


Ingredient 1: Forcing for Ascent (cont’d)

Diagnostic of Non-QG Forcing: Full Wind Frontogenesis

  • Includes ageostrophic “thermally direct/indirect”

  • circulations.

Examples of other forcing mechanisms:

Orographic forcing

Thermodynamic forcing (diabatic & lake-effect)

October 4, 2001 5th Annual High Plains Conference


Ingredient 1: Forcing for Ascent (cont’d)

Bottom left white contours:

Non-QG forcing diagnostic

Full-wind frontogenesis

October 4, 2001 5th Annual High Plains Conference


Ingredient 2: Atmospheric Stability

Instability Diagnostic

Saturated equivalent potential vorticity

Conditional instability (CI or CSI) is diagnosed where PVes is negative

PVes“combines vertical [CI] and slantwise [CSI] instabilities and so becomes an all-purpose convection potential tool.” (McCann, 1995)

October 4, 2001 5th Annual High Plains Conference


Ingredient 2: Atmospheric Stability (cont’d)

Colored contours:

Instability diagnostic

October 4, 2001 5th Annual High Plains Conference


Ingredients 1 & 2 Combined: PVQ

for negative and negative

for positive or positive

PVQ is not intended as a numerical quantity, but as a graphical aid

to identify where instability and forcing are co-located

October 4, 2001 5th Annual High Plains Conference


Ingredients 1 & 2 Combined: PVQ (cont’d)

white contours

colored contours

green contours

October 4, 2001 5th Annual High Plains Conference


Ingredient 3: Moisture

Moisture Diagnostics

  • Absolute Moisture: Mixing Ratio

  • Degree of Saturation: Relative Humidity

red contours: mixing ratio (g/kg)

filled contours: relative humidity (%)

October 4, 2001 5th Annual High Plains Conference


Ingredient 4: Precipitation Efficiency

1. Ice Nucleation (Initiation): Is ice present in the cloud?

2. Ice Crystal Growth: After ice has been initiated, how do the crystals grow to larger snowflakes? Under what conditions do maximum growth rates occur?

D.A. Baumgardt, SOO NWS LaCrosse, WI: http://www.crh.noaa.gov/arx/micrope.html

October 4, 2001 5th Annual High Plains Conference


Ingredient 4: Precipitation Efficiency (cont’d)

How do clouds initiate ice from supercooled liquid droplets?

Without ice nuclei, T < - 40 oC

With ice nuclei present, T < -10 to -20 oC

Baumgardt: -12 oC to -14 oC recommended range for a high likelihood of ice

-10 oC operational cutoff point for no ice in a cloud

Ice crystal growth after initiation

Depositional Growth, maximized around -15 oC

Growth by Aggregation, maximized around 0 oC

October 4, 2001 5th Annual High Plains Conference


Ingredient 5: Temperature

1. Wet-bulb temperature < 0 at all levels above the surface: Snow likely

October 4, 2001 5th Annual High Plains Conference


Ingredient 5: Temperature

1. Wet-bulb temperature < 0 at all levels above the surface: Snow likely

2. Wet-bulb temperature > 0 at some level above the surface, decreasing

monotonically: 850 hPa 0 to -4 oC T roughly identifies the region of precipitation

type transition (“rain edge” of the rain-snow boundary), always apply with caution

colored contours

850 hPa Temperature (oC), shaded where negative

October 4, 2001 5th Annual High Plains Conference


Ingredient 5: Temperature (cont’d)

3. Elevated Warm Layer

Precipitation type depends on whether the ice melts

completely to a liquid while falling through the warm layer

October 4, 2001 5th Annual High Plains Conference


Ingredient 5: Temperature (cont’d)

3. Elevated Warm Layer

Precipitation type depends on whether the ice melts

completely to a liquid while falling through the warm layer

Cooler Layer Beneath

Elevated Warm Layer

Rain or

Freezing Rain

No ice nucleation (T > - 10 oC)

& No ice introduced from above

Complete Melting*

Possible ice nucleation

(T < - 10 oC)

Partial Melting*

Snow or Ice Pellets

* Degree of melting determined by relationships based on the warm layer temperature and the depth of the warm layer (Czys et al. 1996, Stewart and King 1988).

October 4, 2001 5th Annual High Plains Conference


Application: Ingredients Maps

Ingredients maps facilitate the use of the IM by displaying all diagnostics together in a convenient manner

QG Forcing & Instability

Non-QG Forcing, Temperature & Efficiency

Moisture & PVQ

October 4, 2001 5th Annual High Plains Conference


Midwestern Winter Storm: January 26-27, 1996

600:650 mb

October 4, 2001 5th Annual High Plains Conference


Midwestern Winter Storm: January 26-27, 1996

700:750 mb

October 4, 2001 5th Annual High Plains Conference


Midwestern Winter Storm: January 26-27, 1996

800:850 mb

October 4, 2001 5th Annual High Plains Conference



Cross-Section Ingredients Maps

  • Assist in determining precipitation type and efficiency

  • Identify layers of instability at levels not captured by the isobaric

  • ingredients maps (800-850, 700-750, 600-650 hPa)

  • Assess the depth of forecasted dry or moist layers

  • Distinguish between CI and CSI (provided the flow is 2D and the cross-section is oriented perpendicular to the shear of the geostrophic wind)

October 4, 2001 5th Annual High Plains Conference


6-hour ETA model forecast valid at 06Z March 13, 1997

600:650 hPa

700:750 hPa

No negative PVes in WI

October 4, 2001 5th Annual High Plains Conference


6-hour ETA model forecast valid at 06Z March 13, 1997 Cross Section Ingredients Map

colored:

Mg: red

white dashed

October 4, 2001 5th Annual High Plains Conference


6-hour ETA model forecast valid at 06Z March 13, 1997:

non-standard pressure layer550:600 hPa

Negative PVes in WI

October 4, 2001 5th Annual High Plains Conference


Application of the Ingredients-Based Methodology

  • Precipitation onset and duration:

  • If an area of forcing coincides with relative humidity > 80%, some

  • precipitation is likely.

October 4, 2001 5th Annual High Plains Conference


Application of the Ingredients-Based Methodology

  • Precipitation onset and duration:

  • If an area of precipitation coincides with relative humidity > 80%,

  • some precipitation is likely.

  • Intensity of precipitation:

  • - Related to the strength of forcing

  • - May be limited by moisture availability and depth of moist layer

  • - Enhanced response if forcing coincides with instability

  • - May be modulated by efficiency mechanisms

October 4, 2001 5th Annual High Plains Conference


Application of the Ingredients-Based Methodology

  • Precipitation onset and duration:

  • If an area of precipitation coincides with relative humidity > 80%,

  • some precipitation is likely.

  • Intensity of precipitation:

  • - Related to the strength of forcing

  • - May be limited by moisture availability and depth of moist layer

  • - Enhanced response if forcing coincides with instability

  • - May be modulated by efficiency mechanisms

  • Precipitation type:

  • Rough characterization based on 850 0 to -4 oC transition region

  • Inspection of forecast and observed soundings is essential

October 4, 2001 5th Annual High Plains Conference


Steps In Preparing an Ingredients-Based Forecast

1. Choose a forecast area and evaluate all ingredient parameters at

the 850mb, 700mb, and 600mb levels for each forecast hour.

2. Inspect cross-sections and forecast soundings.

3. Compile information into a time series of forecasted storm intensity

and precipitation type.

4. Re-evaluate ingredient diagnostics with new model data.

5. Monitor conditions as the storm develops to decide how well the

model-predicted ingredient diagnostics are verifying.

October 4, 2001 5th Annual High Plains Conference


Case Example: January 26-27, 1996

NWS Storm Report:

Major snowstorm across most of Wisconsin. Total snowfall 8-18" except NW and SE corners where only a few inches fell. Maximum snow amounts were just east of LaCrosse (SW Wisconsin). At the height of the storm, thunder and lightning were observed with blizzard conditions.

October 4, 2001 5th Annual High Plains Conference







800:850 hPa

Period of Peak Intensity

00 UTC 27 January 1996

700:750 hPa

600:650 hPa







Advantages

Systematic approach, provides focus and organization

Flexible, not restricted to synoptic or thermodynamic conditions, provided the diagnostics are chosen carefully

Aids in the interpretation of QPF: diagnoses mechanisms responsible for the event instead of ‘black box’ interpretation

Helps to identify the source of differences between model scenarios

Depicts forecasted instantaneous precipitation and intensity distribution.

Identifies boundaries of moisture, localized regions of stronger or weaker forcing.

October 4, 2001 5th Annual High Plains Conference


Limitations

Ingredients maps rely on the accuracy of a numerical forecast model.

The IM does not independently provide a quantitative precipitation forecast.

Choice of diagnostics can limit the analysis.

October 4, 2001 5th Annual High Plains Conference


Some Future Work

Assess QPV “false alarm” frequency

Incorporate more diagnostics for temperature and efficiency

Include an equivalent of QPV using frontogenesis instead of QG forcing

More case studies and operational testing

October 4, 2001 5th Annual High Plains Conference


Ingredients-Based Forecast Methodology: Final Comments

“We invite extensions and improvements to the diagnostics employed for each ingredient, recognizing that any choice comes with limitations and that any one set of diagnostics will not be suitable for all forecasters in all regions.” (Wetzel & Martin, 2002)

October 4, 2001 5th Annual High Plains Conference


Ingredients-Based Forecast Methodology: Final Comments

“We invite extensions and improvements to the diagnostics employed for each ingredient, recognizing that any choice comes with limitations and that any one set of diagnostics will not be suitable for all forecasters in all regions.” (Wetzel & Martin, 2002)

Copies are available of our reply to Schultz et al.’s “Comments on an operational ingredients-based methodology for forecasting midlatitude winter season precipitation” (submitted to Weather and Forecasting, 2001).

October 4, 2001 5th Annual High Plains Conference


Ingredients-Based Forecast Methodology: Final Comments

“We invite extensions and improvements to the diagnostics employed for each ingredient, recognizing that any choice comes with limitations and that any one set of diagnostics will not be suitable for all forecasters in all regions.” (Wetzel & Martin, 2002)

Copies are available of our reply to Schultz et al.’s “Comments on an operational ingredients-based methodology for forecasting midlatitude winter season precipitation” (submitted to Weather and Forecasting, 2001).

Current (0Z and 12Z ETA) Ingredients Maps, scripts to generate the ingredients maps, links to AWIPS ingredients maps, and other information is available at http://speedy.meteor.wisc.edu/~swetzel/winter

October 4, 2001 5th Annual High Plains Conference


THIS IS THE END OF THE SLIDES I USED IN NORTH PLATTE

There are some additional slides after this point that were not included


Application of the Ingredients-Based Methodology

  • Although analysis of the ingredient maps requires considerable subjective judgement, certain guidelines have been found to apply in most situations:

  • With sufficient moisture and no instability, weak, moderate, and strong forcing for ascent will generally correspond to light, moderate, and heavy precipitation.

  • The intensity of precipitation will be greater in the presence of instability and weaker when small amounts of moisture are available.

  • Instability at any level with ample moisture and at least weak forcing can result in heavy precipitation, possibly accompanied by thunder and lightning.

  • The depth of the moist layer may have a significant impact on the intensity of precipitation.

October 4, 2001 5th Annual High Plains Conference




Summary of Some Useful Diagnostics

Many other diagnostics can be incorporated into the IM to meet the specific needs of a forecast area or to include additional theory.

October 4, 2001 5th Annual High Plains Conference


Checklist?

…or Reality?

October 4, 2001 5th Annual High Plains Conference



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