Forecasting Convective Downburst Potential Using GOES ... · • A continuum between wet and dry...
Transcript of Forecasting Convective Downburst Potential Using GOES ... · • A continuum between wet and dry...
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Forecasting Convective Downburst Potential Using GOES Sounder
Derived Products
Ken PryorCenter for Satellite Applications and
Research (NOAA/NESDIS)
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Topics of Discussion
• Description of the GOES Microburst Products
• Case Studies• Use of the GOES Microburst Products with
Other Satellite and Radar Data
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Introduction
• GOES sounder-derived parameters have been shown to be useful in assessing the potential for convective downbursts. Products include:
• Wet Microburst Severity Index (WMSI)• Dry Microburst Index (DMI)• Wind Index (WINDEX)
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GOES Microburst Products
• Generated hourly at the NOAA Science Center in Camp Springs, MD.
• Available on the GOES Microburst Products web page at the following URL:http://www.orbit.nesdis.noaa.gov/smcd/opdb/aviation/mb.html
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GOES Microburst Products
• Microburst program ingests the vertical temperature and moisture profiles derived from GOES sounder radiances, using a subset of single field of view.
• Microburst products are available approximately 50 minutes after sounder scan.
• Based on the thermodynamic structure of the ambient atmosphere.
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Wet Microburst
From Atkins and Wakimoto (1991)UCAR
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Wet Microburst Severity Index (WMSI)
WMSI = (CAPE)(TeD)/1000 • CAPE (positive buoyancy):
– updraft strength and precipitation formation • Theta-e Difference (TeD):
– Presence of a dry (low theta-e) layer in the middle troposphere
– favorable for the production of large negative buoyancy due to evaporative cooling.
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Theta-e Difference (TeD)
• Maximum vertical difference in equivalent potential temperature (θe) from the surface to the middle troposphere (Atkins and Wakimoto 1991).
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Wet Microburst Severity Index (WMSI)
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Wet Microburst Severity Index (WMSI)
WMSI Predicted Wind Gust Magnitude
< 10 Downbursts unlikely
10 to 50 < 35 knots
50 to 80 35 to 50 knots
> 80 > 50 knots
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Dry Microburst
UCAR
From Wakimoto (1985)
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Dry Microburst Index (DMI)
DMI = Γ + (T - Td)700 - (T - Td)500
• Γ = temperature lapse rate (°C km-1) from 700 to 500 mb
• T = temperature (°C) • Td = dew point temperature (°C)• Dry microbursts may occur when the DMI
> 6 (Ellrod et al 2000)
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Dry Microburst Index (DMI)
An example of the DMI product with stable soundings (CAPE<50 J kg-1) filtered and removed from the image.
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Summary of Microburst Generation Processes
• DMI: subcloud evaporative and sublimationalcooling
• WMSI: strong updrafts, precipitation loading, and evaporative cooling from the entrainment of dry ambient air into the precipitation core
• A continuum between wet and dry microbursts(“hybrid”) based on the depth of the moist layer and sub-cloud dry air layer
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Hybrid Microburst
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Cold Season Downbursts
• Strong and diffluent winds aloft with significant vertical wind shear
• Strong correlation found between mid-tropospheric and surface winds:– suggests downward transport of momentum
from the midlevels of a convective storm environment to the surface is a major factor in downburst magnitude.
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Cold Season Downbursts
• Sasaki and Baxter (1986): Downward transfer of entrained momentum from the strong flow aloft was responsible for the generation of strong surface winds in convective systems. – Descending evaporatively cooled air tends to
carry the horizontal momentum that it had at its original level.
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Cold Season Downbursts
• Weisman and Klemp (1982):• Bulk Richardson Number: R=B/.5ū2
• ū2 represents inflow kinetic energy made available to the storm by vertical wind shear.
• Large ū2 can be associated with strong forced convection: – supplemental convective energy source
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WMSI Validation
2003-04 Convective Seasons:• Strong positive linear relationship
(correlation) between GOES WMSI and surface wind gusts for both daytime and nighttime events.
• Complete discussion in online paper:http://www.orbit.nesdis.noaa.gov/smcd/opdb/kpryor/mburst/wmsipaper/wmsi.html
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14 July 2004 Downburst
• Convective cluster merged to form a squall line- broken areal evolution (Bluestein and Jain 1985). – Weakly-forced environment
• Evolved into a bow echo pattern. (Przybylinski 1995)
• 74 knot wind gust at Patuxent River Naval Air Station, MD (2105 UTC)
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14 July 2004 Downburst
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14 July 2004 Downburst
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24 Nov 2004 Squall Line
• Strong frontal convergence and negatively-tilted short wave trough served as an initiating mechanism for deep convection.– enhanced vertical circulation and static
instability• Downward momentum transport, by the
strong convective downdrafts, from the mid-troposphere to surface – Strong vertical wind shear
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24 Nov 2004 Squall Line
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24 Nov 2004 Squall Line
BRN Shear = 25
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30 March 2005 Squall Line• Several downburst wind gusts between 35 and 55
knots over eastern Iowa, southern Wisconsin and northern Illinois.
• Elevated WMSI values in excess of 50 extended from east-central Iowa to the Chicago metro area.
• Strong vertical wind shear :– served as a source of inflow kinetic energy to enhance
convective updrafts – downward momentum transfer was a factor in the
magnitude of downburst wind gusts.
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30 March 2005 Squall Line
1800 UTC 2000 UTC
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30 March 2005 Squall Line
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Cold Season Forecast Technique
• WMSI:– Identify regions of static instability and
elevated downburst potential• GOES sounding profiles:
– Wind shear: presence of inflow kinetic energy to enhance convective updrafts
– Dry layer wind speed: estimate magnitude of downbursts observed at surface
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Use with Other Data Types
• Radar imagery to identify and monitor: – Convergence boundaries (i.e. outflow
boundaries) that could initiate deep convection– Cell mergers
• Visible satellite imagery can also be used to identify and track outflow boundaries during daylight hours.
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Future Research Directions
• Use of the microburst products during the cold season:– Environment, physical processes
• Coordinated use of WMSI and DMI to forecast “hybrid” microburst potential:– Focus on Western High Plains region
• Establish severity thresholds for DMI.
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ReferencesAtkins, N.T., and R.M. Wakimoto, 1991: Wet microburst
activity over the southeastern United States: Implications for forecasting. Wea. Forecasting, 6, 470-482.
Bluestein, H.B., and M.H. Jain, 1985: Formation of mesoscale lines of precipitation: severe squall lines in Oklahoma during the spring. J. Atmos. Sci., 42, 1711-1732.
Ellrod, G.P., J.P. Nelson, M.R. Witiw, L. Bottos, and W.P. Roeder, 2000: Experimental GOES sounder products for the assessment of downburst potential. Wea. Forecasting, 15, 527-542.
Pryor, K.L., and G.P. Ellrod, 2004: Recent improvements to the GOES microburst products. Wea. Forecasting, 19,582-594.
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ReferencesPrzybylinski, R.W., 1995: The bow echo. Observations,
numerical simulations, and severe weather detection methods. Wea. Forecasting, 10, 203-218.
Sasaki, Y.K., and T.L. Baxter, 1986: The gust front. Thunderstorm Morphology and Dynamics, University of Oklahoma, 187-196.
Wakimoto, R.M., 1985: Forecasting dry microburst activity over the high plains. Mon. Wea. Rev., 113, 1131-1143.
Weisman, M.L., and J.B. Klemp, 1982: The dependence of numerically simulated convective storms on vertical wind shear and buoyancy. Mon. Wea. Rev.,, 110, 504-520.
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Questions?
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Thank You!