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. Suzanne Wetzel Seemann Jonathan E. Martin Scott Bachmeier October 4, 2001 5 th Annual High Plains Conference North Platte, NE
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An Operational Ingredients-Based Methodology for Forecasting Midlatitude
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 - PowerPoint PPT Presentation
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An Operational Ingredients-Based Methodology for Forecasting Midlatitude Winter Season Precipitation
http://speedy.meteor.wisc.edu/~swetzel/winterreference: Wetzel and Martin, 2001. Weather and Forecasting,16 (1), 156-167.
Suzanne Wetzel SeemannJonathan E. MartinScott Bachmeier
October 4, 2001 5th Annual High Plains Conference
North Platte, NE
Introduction to the Ingredients-Based Methodology
Choice of Ingredients and Selected Diagnostics
Application of the Methodology and Ingredients Maps
Advantages and Limitations
Outline
October 4, 2001 5th Annual High Plains Conference
Ingredients-Based Forecast Methodology
October 4, 2001 5th Annual High Plains Conference
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.
An ingredient is a fundamental physical element or process that directly contributes to the development and intensity of a precipitation event.
Ingredient vs. Diagnostic
October 4, 2001 5th Annual High Plains Conference
An ingredient is a fundamental physical element or process that directly contributes to the development and intensity of a precipitation event.
A diagnostic is the observable or derived quantity that can be used to assess the presence and strength of an ingredient.
Ingredient vs. Diagnostic
October 4, 2001 5th Annual High Plains Conference
An ingredient is a fundamental physical element or process that directly contributes to the development and intensity of a precipitation event.
A diagnostic is the observable or derived quantity that can be used to assess the presence and strength of an ingredient.
Ingredient vs. Diagnostic
October 4, 2001 5th Annual High Plains Conference
Parameters will be introduced to diagnose each ingredient; however, the IM is not dependent on these specific diagnostics.
1. Forcing for ascent: Where and how strong is the forcing?
3. Moisture: Where and how much moisture is available?
Choice of Ingredients
October 4, 2001 5th Annual High Plains Conference
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?
Choice of Ingredients
October 4, 2001 5th Annual High Plains Conference
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?
Choice of Ingredients
October 4, 2001 5th Annual High Plains Conference
Ingredient 1: Forcing for Ascent
October 4, 2001 5th Annual High Plains Conference
Quasi-Geostrophic (QG) Forcing Diagnostic
Use of the Q-vector as the sole means of diagnosing vertical motion forcing is limiting
Q-Vector convergence Forcing for upward vertical motion
Ingredient 1: Forcing for Ascent (cont’d)
October 4, 2001 5th Annual High Plains Conference
Top right white contours:QG forcing diagnostic
(for an 80km grid)
Ingredient 1: Forcing for Ascent (cont’d)
October 4, 2001 5th Annual High Plains Conference
Diagnostic of Non-QG Forcing: Full Wind Frontogenesis
• Includes ageostrophic “thermally direct/indirect” circulations.
Ingredient 1: Forcing for Ascent (cont’d)
October 4, 2001 5th Annual High Plains Conference
Diagnostic of Non-QG Forcing: Full Wind Frontogenesis
Examples of other forcing mechanisms: Orographic forcing Thermodynamic forcing (diabatic & lake-effect)
• Includes ageostrophic “thermally direct/indirect” circulations.
Ingredient 1: Forcing for Ascent (cont’d)
October 4, 2001 5th Annual High Plains Conference
Bottom left white contours:Non-QG forcing diagnostic
Full-wind frontogenesis
Ingredient 2: Atmospheric Stability
October 4, 2001 5th Annual High Plains Conference
Instability Diagnostic
Conditional instability (CI or CSI) is diagnosed where PVes is negative
Saturated equivalent potential vorticity
PVes “combines vertical [CI] and slantwise [CSI] instabilities and so becomes an all-purpose convection potential tool.” (McCann, 1995)
Ingredient 2: Atmospheric Stability (cont’d)
October 4, 2001 5th Annual High Plains Conference
Colored contours:Instability diagnostic
Ingredients 1 & 2 Combined: PVQ
October 4, 2001 5th Annual High Plains Conference
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
red contours: mixing ratio (g/kg)filled contours: relative humidity (%)
Ingredient 4: Precipitation Efficiency
October 4, 2001 5th Annual High Plains Conference
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
Ingredient 4: Precipitation Efficiency (cont’d)
October 4, 2001 5th Annual High Plains Conference
Ice crystal growth after initiationDepositional Growth, maximized around -15 oCGrowth by Aggregation, maximized around 0 oC
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
Ingredient 5: Temperature
October 4, 2001 5th Annual High Plains Conference
1. Wet-bulb temperature < 0 at all levels above the surface: Snow likely
Ingredient 5: Temperature
October 4, 2001 5th Annual High Plains Conference
1. Wet-bulb temperature < 0 at all levels above the surface: Snow likely
colored contours
850 hPa Temperature (oC), shaded where negative
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
3. Elevated Warm Layer Precipitation type depends on whether the ice melts completely to a liquid while falling through the warm layer
Ingredient 5: Temperature (cont’d)
October 4, 2001 5th Annual High Plains Conference
3. Elevated Warm Layer Precipitation type depends on whether the ice melts completely to a liquid while falling through the warm layer
Ingredient 5: Temperature (cont’d)
October 4, 2001 5th Annual High Plains Conference
* 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).
Complete Melting*
Partial Melting*
No ice nucleation (T > - 10 oC) & No ice introduced from above
Elevated Warm Layer Cooler Layer Beneath
Possible ice nucleation(T < - 10 oC)
Rain or Freezing Rain
Snow or Ice Pellets
Application: Ingredients Maps
October 4, 2001 5th Annual High Plains Conference
Ingredients maps facilitate the use of the IM by displaying all diagnostics together in a convenient manner
Non-QG Forcing, Temperature & Efficiency
Moisture & PVQ
QG Forcing & Instability
Midwestern Winter Storm: January 26-27, 1996
October 4, 2001 5th Annual High Plains Conference
600:650 mb
Midwestern Winter Storm: January 26-27, 1996
October 4, 2001 5th Annual High Plains Conference
700:750 mb
Midwestern Winter Storm: January 26-27, 1996
October 4, 2001 5th Annual High Plains Conference
800:850 mb
00 UTC January 27, 1996
Cross-Section Ingredients Maps
October 4, 2001 5th Annual High Plains Conference
• 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)
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6-hour ETA model forecast valid at 06Z March 13, 1997600:650 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
Mg: red
colored:
white dashed
October 4, 2001 5th Annual High Plains Conference
6-hour ETA model forecast valid at 06Z March 13, 1997:non-standard pressure layer 550:600 hPa
Negative PVes in WI
Application of the Ingredients-Based Methodology
October 4, 2001 5th Annual High Plains Conference
• Precipitation onset and duration: If an area of forcing coincides with relative humidity > 80%, some precipitation is likely.
Application of the Ingredients-Based Methodology
October 4, 2001 5th Annual High Plains Conference
• 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
Application of the Ingredients-Based Methodology
October 4, 2001 5th Annual High Plains Conference
• 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
Steps In Preparing an Ingredients-Based Forecast
October 4, 2001 5th Annual High Plains Conference
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.
Case Example: January 26-27, 1996
October 4, 2001 5th Annual High Plains Conference
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.
800:850 hPaOnset of Precipitation: 12 UTC 26 January 1996
700:750 hPaOnset of Precipitation: 12 UTC 26 January 1996
600:650 hPaOnset of Precipitation: 12 UTC 26 January 1996
Cross-sectionOnset of Precipitation: 12 UTC 26 January 1996
Onset of Precipitation: 12 UTC 26 January 1996
800:850 hPa
600:650 hPa700:750 hPa
Period of Peak Intensity00 UTC 27 January 1996
Peak Intensity: 00 UTC 27 January 1996 Cross-section
Near Ending 12 UTC 27 January 1996 800:850 hPa
Near Ending 12 UTC 27 January 1996 700:750 hPa
Near Ending 12 UTC 27 January 1996 600:650 hPa
Near Ending 12 UTC 27 January 1996
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.
Advantages
October 4, 2001 5th Annual High Plains Conference
Limitations
October 4, 2001 5th Annual High Plains Conference
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.
Some Future Work
October 4, 2001 5th Annual High Plains Conference
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
Ingredients-Based Forecast Methodology: Final Comments
October 4, 2001 5th Annual High Plains Conference
“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)
Ingredients-Based Forecast Methodology: Final Comments
October 4, 2001 5th Annual High Plains Conference
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).
“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)
Ingredients-Based Forecast Methodology: Final Comments
October 4, 2001 5th Annual High Plains Conference
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
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).
“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)
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
October 4, 2001 5th Annual High Plains Conference
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.
22 UTC January 26, 1996
Near Ending: 12 UTC 27 January Cross-section
Summary of Some Useful Diagnostics
October 4, 2001 5th Annual High Plains Conference
Many other diagnostics can be incorporated into the IM to meet the specific needs of a forecast area or to include additional theory.