Use of mesoscale observing network data in forecasting severe convection

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Use of mesoscale observing network data in
forecasting severe convection

• A-J Punkka
• Weather Warning Service, FMI

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Outline

• Use of HTB data at FMI Weather Warning Service
• Challenges and problems in severe thunderstorm
  forecasting
• Examples of testbed data exploitation
• Summary

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Use of HTB data at FMI Weather Warning Service
?

• Only traditional observations available in the
  meteorological workstation (will be fixed soon ?)
• Forecasters forced to use testbed.fmi.fi in order
  to see testbed data gtgt easy to forget if youre
  busy gtgt use of testbed data occasional
• However, denser observation network has clearly
  given extra value for nowcasting in some
  convection cases (e.g. 9.8.2005, 26.8.2005)

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Challenges and problems in severe thunderstorm
forecasting

• State of boundary layer
• Low-level humidity. Depth of moist layer and
  spatial distribution.
• Low-level winds. Low-level jets, convergence
  lines, outflow boundaries ( backed surface
  winds).
• Low-level temperature.
• Moisture and temperature advection.
• State of free atmosphere
• Elevated inversions.
• Location and strength of upper troughs.
• Intensity of temperature advection.
• Deep moist convection in NWP models
• Unable to produce small-scale variations in
  low-level moisture, temperature and wind.
• Convective mode incorrect in hi-res models.
  Convective systems usually inadequately
  predicted.
• Errors in timing and location of deep moist
  convection typical. For forecaster not as crucial
  as the previous one.

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Examples variations in sfc T, Td and winds
Wdir260
Wdir180
Primary tool Surface mesonet Benefits
Improved assessment of instability (CAPE),
thunderstorm initiation and convective mode
(storm-relative helicity)
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Examples mesolows and mesohighs
Primary tool Surface mesonet Benefits Improved
assessment of cold pool intensity and MCS motion
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Examples outflow boundaries
Source iastate.edu
Primary tools Surface mesonet, radar Benefits
Improved assessment of wind gust strength,
initiation of new convective cells
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Examples low-level humidity profile
Knee-deep moist layer MLCAPE 700 J/kg
Primary tools soundings, AMDARs (aircraft
soundings) Benefits Improved assessment of
instability (CAPE) and thunderstorm initiation
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Examples low-level wind profile
Gatzen (2004)
Primary tools soundings, wind
profilers Benefits Improved assessment of
convective mode and tornado and downburst risks
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Examples mesovortices
Atkins et al. (2004)
Primary tool doppler radar Benefits Improved
assessment of severe straight-line wind and
non-supercell tornado risks
Järvi et al. (2007)
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Summary challenges in severe convection
forecasting

• Improvements in forecasting
• Instability
• Convective mode
• Ts initiation
• Tornado and db risks

• Problems
• Moisture
• Low-level moisture
• Depth of moist layer
• Winds
• Low-level jets
• Backed surface winds
• Convergence lines
• Outflow boundaries
• Mesovortices
• Moisture and temperature advection.

• Observations
• Mesonet of sfc observations
• Wind profilers
• Denser radar network
• Soundings and AMDARs

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Summary challenges in severe convection
forecasting

• Improvements in forecasting
• Instability
• Convective mode
• Ts initiation
• Tornado and db risks

• Problems
• Moisture
• Low-level moisture
• Depth of moist layer
• Winds
• Low-level jets
• Backed surface winds
• Convergence lines
• Outflow boundaries
• Mesovortices
• Moisture and temperature advection.

• Observations
• Mesonet of sfc observations
• Wind profilers
• Denser radar network
• Soundings and AMDARs

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Summary challenges in severe convection
forecasting

• Improvements in forecasting
• Instability
• Convective mode
• Ts initiation
• Tornado and db risks

• Problems
• Moisture
• Low-level moisture
• Depth of moist layer
• Winds
• Low-level jets
• Backed surface winds
• Convergence lines
• Outflow boundaries
• Mesovortices
• Moisture and temperature advection.

• Observations
• Mesonet of sfc observations
• Wind profilers
• Denser radar network
• Soundings and AMDARs

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Summary challenges in severe convection
forecasting

• Improvements in forecasting
• Instability
• Convective mode
• Ts initiation
• Tornado and db risks

• Problems
• Moisture
• Low-level moisture
• Depth of moist layer
• Winds
• Low-level jets
• Backed surface winds
• Convergence lines
• Outflow boundaries
• Mesovortices
• Moisture and temperature advection.

• Observations
• Mesonet of sfc observations
• Wind profilers
• Denser radar network
• Soundings and AMDARs

Forecasters message to Testbed II
developers More instruments for the detection of
low-level profiles