EXPLORING LINKAGES BETWEEN PLANT-AVAILABLE SOIL MOISTURE, VEGETATION PHENOLOGY AND CONVECTIVE INITIATION

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EXPLORING LINKAGES BETWEEN PLANT-AVAILABLE SOIL
MOISTURE, VEGETATION PHENOLOGY AND CONVECTIVE
INITIATION By Julian Brimelow and John
Hanesiak
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The sensitivity of the synoptically forced
convection to soil and vegetative processes
including transpiration indicates that detailed
representation of land surface processes should
be included in weather forecasting models,
particularly for severe storm forecasting where
local-scale information is important.
Holt et al. (2006)
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SCIENCE QUESTIONS UNSTABLE 2008 Theme II

• 2.1) Is there a noticeable difference in storm
  initiation between wet and dry areas over the
  cropped region?
• 2.2) Is there a noticeable gradient of surface
  and boundary layer water vapour across the major
  wet/dry areas, and how do these evolve?
• 2.3) Are mesoscale circulations detectable in
  the vicinity of boundaries between wet and dry
  areas? If so, how do they influence storm
  initiation?

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HYPOTHESIS

• Modification of the local thermodynamics,
  causing changes in the LCL, and CAPE,can have
  important consequences regarding the location and
  timing of convection initiation
• Georgescu et
  al. (2003)

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Sensitivity of convection to near surface T and q

• MSE gz CpT Lq
• Must increase T by 2.5 C to increase MSE by
  same amount as 1C increase in q
• CAPE is very sensitive to ?q
• CIN, however, sensitive to surface ?T

Crook (1996)?
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PRIMARY CAUSES OF LAND-ATMOSPHERE FEEDBACKS

• Soil moisture
• Vegetation
• Orography
• Land use

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SOIL MOISTURE
The role of soil moisture in ABL development
involves a complex interaction of surface and
atmospheric processes. Ek and Holtslag
(2003)
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Findell and Eltahir (2003) The propensity of
the atmosphere to support convection is not only
dependent on the surface and energy budgets, but
also on the structure of the low-level
temperature and moisture profiles in the early
morning.
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Energy Balance Crop vs. Bare Ground
Energy Balance Crop vs. Forest
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VEGETATION
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UNSTABLE PROJECT AREA

• Calgary

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TOOLS
Mobile Atmospheric Research System (MARS)?
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DATA BASES
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METHODOLOGY

• STEP 1
• Document the spatial and temporal evolution of
  the plant-available moisture in the root zone
  (PAW) using crop model and in-situ obs
• Document the spatial and temporal evolution of
  the NDVI
• Create an inventory of wet vs. dry areas, and
  tight PAW/NDVI gradients

• STEP 2
• For each day, classify synoptic-scale forcing as
  weak, moderate or strong
• For each day, characterize structure of the
  boundary layer in morning

• STEP 3
• Use mesonet, mobile mesonet, MARS, Doppler radar
  and aircraft data to create an inventory of
  mesoscale boundaries
• Use high resolution VIS satellite images to
  create archive of those boundaries associated
  with deep, moist convection
• Determine whether boundaries are associated with
  gradients in PAW

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• STEP 4
• Quantify CG flash density over wet vs. dry
  areas, and near PAW gradients
• Use radar data to document storm intensity over
  wet and dry areas
• Use radar data to document any changes in storm
  structure and intensity when transitioning from
  wet to dry PAW and vice versa

• STEP 5
• Document cloud base height (from celiometer)
  over wet and dry areas
• Compare with cloud-base height derived using
  sfc. and mixed-layer parcels

• STEP 6
• Search for correlations between PAW and NDVI and
  observed lightning flash density
• Search for correlations between PAW and NDVI and
  storm strength as determined from radar data
• Search for possible connections between storm
  initiation zones and gradients between wet and
  dry PAW

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THE END
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Breakout Session (Theme 2)

• Participants
• Daniel ? (AB Ag)
• Craig Smith (CRB)
• Gary Burke (HAL)
• Ron Stewart (McGill)
• Julian Brimelow (UofM)
• John Hanesiak (UofM)

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Summary of Breakout Session

• Refinement of UNSTABLE questions
• Concerns about Question d.
• Can we realistically achieve this? Need to
  contact experts in the field. If not willing to
  do that then should let go.
• Do some preliminary follow up to see whether
  obtaining EC towers and people to process and
  analyze data is realistic?

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Identify of who plans to be directly involved in
UNSTABLE field campaign and how

• Alberta Agriculture Not directly involved with
  field operations, but willing to offer data from
  network of stations, as well as QC of data from
  stations
• Ag stations that use GOES platform available in
  real time
• Craig Smith, CRD Provide FOPEX data, two
  upper-air systems and 50 sondes, student/s,
  Mobile GPS sensor
• HAL Funding, students from Saskatoon Winnipeg
  (two perhaps), HAL staff willing to participate
  with field program.
• Could also perhaps arrange four students from
  Edmonton office

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Data requirements, instrumentation and deployment
strategies

• Conduct observations as stated in Theme 2 for
  each sub-question
• Need to arrange for crop model to be run in real
  time from 1 April using as many stations as
  possible
• In-situ soil moisture measurements from AB Ag
  stations
• Satellite-- NDVI, SM and other surface anomalies
• Integrate wide variety of data sets, data QC and
  management critical
• Make stronger link between DRI and UNSTABLE,
  natural fit, ET working group water cycle

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Champions for Data Analysis

• Page 11
• (a), (b) maybe (c) - Brimelow
• (d) (e) - Hanesiak et al
• (f) - Strong?

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Funding strategies and opportunities for in-kind
support

• NSERC-- Collaborative research and development
  fund (CRDF) to pay for students and post docs
• NSERC 50 industry 50 (50 in-kind 50 cash)
• Alberta Financial Services
• Insurance Bureau of Canada
• WMI can provide significant in-kind contributions
• May want some kind of evolution component (of
  thunderstorms) of the science plan. Have to be
  careful how we present UNSTABLE to them (heavy
  precip slant?) - Ralph Wright
• Timeline would need attention now