Weather Analysis II - Final Exam
Winter Weather Forecasting
Snow
Snow Intensity
Light = visibility is >1km (⅝ SM)
Moderate = visibility between 1km (⅝ SM) and ½ km (5/16 SM)
Heavy - visibility is <½ km (5/16 SM)
Temperature profile
Entirely below freezing (32oF/0oC)
Sleet
Partially melted snow that re-freezes into milky-white/clear pellets before hitting the ground
Temperature profile
Deep surface Freezing Layer
Shallow elevated Melting Layer (EML)
Freezing Rain
Falling rain that freezes upon impact with the ground
Typically supercooled rain
Self-limiting process
Temperature profile
Shallow surface freezing layer
The rest of the profile above ground is below freezing
Graupel
Snow pellets, ”soft hail”
Formed through convective processes
Concepts
Rain drops do not freeze easily without the presence of a nuclei
Snowflakes do not form when temps reach freezing
Winter Weather Forecasting - Sounding Characteristics
Cloud Microphysics
Pure water freezes at -40C
Supercooled water freezes before -20C usually
Numerous particles exist for becoming cloud condensation nuclei
Amount of ice crystals activating increases with relative humidity
Ice Crystal Growth
Deposition
Gas to solid
Ice crystals growth at the expense of supercooled water
Water has a higher saturation vapor pressure than ice
Water flows to ice to equalize
Accretion
Growth through collision-coalescence with supercooled water
-10C to 0C (more riming occurs closest to 0C)
Aggregation
Ice crystals stick with each other
-5C to 0C
Bergeron Process - Deposition
Precipitation production is ideal when ice crystals/supercooled water droplets exist
Freezing nuclei are sparse
Deposition - Since the air is supersaturated, with respect to the limited ice crystals, water molecules begin to collect on the ice crystals
Relative humidity decreases → surrounding water droplets begin to evaporate to replenish lost water vapor
Bergeron Process - Ice Crystal Growth
Growth of ice crystals is dependent on evaporation and shrinkage of liquid droplets
Ice crystals become large and begin to fall due to gravity
Some ice crystals break apart as they fall through the air
Fragments create new freezing nuclei that draw water vapor from other droplets
The chain reaction creates many ice crystals that grow into snowflakes
Heterogeneous Nucleation
Silver Iodide activation temperature: -4C
Sounding Analysis
Is there a dendritic growth zone (DGZ)
Does it have >70% RH
Is there a melting layer
Elevated or surface
Maximum temperature
Thickness
Sounding Analysis - EML Temperature
If max temp is <1C, minimal melting will occur
Snow → Snow
If max temp is >3C or 4C, complete melting will occur
Snow → rain, freezing rain, sleet (rare)
If max temp is >1C but <3C or 4C, partial melting will occur
Retains ice nuclei that can refreeze
Depends on melting layer depth, temp and depth of surface freezing layer
Snow → rain, freezing rain, or sleet
Sounding Analysis - EML Thickness
If thickness is between 1500ft and 4000ft, partial melting will occur
Retains ice nuclei that can refreeze
Depends on melting layer depth, temp and depth of surface freezing layer
If thickness is >4000ft, total melting will likely occur regardless of max temp
Snow no longer has nuclei
Snow → rain, freezing, or sleet (rare)
Sounding Analysis - Surface Melting Layer
If the top of the surface melting layer is <900ft, limited melting will occur
Snow will maintain its appearance
Snow → Snow
If the top of the surface melting layer is >1200ft, total melting will occur
Snow will melt
Snow → Rain
Sounding Analysis - Surface Freezing Layer
Partially melted snowflakes refreeze much faster than fully melted snowflakes
An ice nuclei still exists
Sleet
Unmixed precip occurs when the min temp of the surface freezing layer is <-5C
Mixed precip occurs when the min temp of the surface freezing layer is between -2.5C and -5C
Freezing Rain
Unmixed precipitation (freezing rain) occurs when the min temp of the surface freezing layer is >-2.5C
If complete melting of the flake has occurred, sleet can still occur if the min temp of the surface freezing layer is <8C and the thickness of the sub-freezing layer is >3000ft
Snow-to-Liquid Ratios
Relative Humidity and DGZ
RH >70% in the DGZ to produce snowfall that survives to the surface
If dry air exists (RH <70%) below then the snow will sublimate
Omega (UVVs) and DGZ
Dependent on model resolution
Moderate lift for NAM: <-17ub/s
Moderate lift for GFS: <-5ub/s
Moderate lift for HRRR: <-90ub/s
Snow-to-Liquid Ratio - Factors
Amount of supercooled water that a snowflake will fall through from the DGZ to the surface
Is the flake growing through deposition or riming
Deposition - ice crystals grow directly from water vapor in a saturated sub-freezing cloud
Dendritic Growth Zone (-12C to -18C)
Riming - ice crystals fall from the DGZ and interact with supercooled water in a saturated sub-freezing layer
Temps between -10C and 0C
Most efficient closest to 0C
Height of the bottom of the DGZ
~15,000ft (high)
~10,000ft (medium)
~5,000ft (low)
Surface and ground temps
Wind speed (compact or broken apart)
Snow-to-Liquid Ratios - Determination
Average is around 10:1 (Kuchera Ratio)
Wet: <10:1
6:1, 8:1, 10:1
In-between: 12-18:1
12:1, 15:1, 18:1
Dry: >20:1
20:1, 25:1, 30:1
Lake-Effect Snow
Ingredients
Convective event from unstable conditions
>13C lake deltaT (difference of lake temp and 850mb temp)
Abundant low-level moisture (supplied by lake)
Heat and moisture from lake will cause destabilization of the lower atmosphere
Steep low-level lapse rates
Deep layer of arctic air → enhanced instability
Depth of the Inversion
Lake-effect snow is often associated with inversions above the convective mixed layer
Mixed layers thickness
<1km thick - significant lake-effect snow is unlikely
convective processes limited
>3km thick - significant single-band lake-effect snow likely
Between 1-3km thick - associated with roll convection and multiple snow bands
Orographic Lift
Forced ascent from terrain
Frictional Convergence
Water has less friction than land
Low-level convergence is favored on right-hand shore and leeward shore
Low-level divergence favored on the left-hand shore and windward shore
Thermal Convergence
Thermal low is created over warmer lake
Mesolow
Thermal high created over cooler land
Depth of the lake and surrounding terrain influences shape and orientation of convection
Leads to squalls and banding
Fetch
Distance air flows over water
For lake-effect snow:
>80km (50mi) - flurries
160km (100mi) - significant lake-effect snow
Analyze 850mb wind direction for fetch
If convective mixed layer is below 850mb then use the 925mb winds
For high elevations use 700mb winds
Lake-effect snow is most efficient when fetch and lake orientation align
Fetch - Multiple Bands
Shorter fetch - multiple band and convection rolls
Fetch parallel to lake short axis
Form with shallow convective mixed layer
1-3km
Typically weaker and produce less snowfall
Few km to 20km (12mi) wide
20-50km (31mi) long
Fetch - Single Bands
Longer fetch - single band
Fetch parallel to lake long axis
Form with deep convective mixed layer
>3km
Typically stronger and produce heavy snowfall
20-50km wide
50-200km (124mi) long
Drastically different snow-rates based on location (outside or inside the band)
Snow-rates up to 4”/hr
Water Temperature/Ice Coverage
Warmer water leads to increased moisture and heat transferred to lower atmosphere
Destabilizes lower atmosphere
Ice limits amount of heat and moisture transferred to lower atmosphere
Stabilizes lower atmosphere
Wind Speed
Determines residence time of a parcel over the lake and how far inland snow will go
Winds should be calculated from SFC-850mb (700mb for high elevations)
>25 kts - too strong, strong snow bands unlikely to form, snow distributed inland
15-20 kts - optimal
<10 kts - too weak, land breeze circulations dominate, and intense bands struggle to form
Wind Direction
Winds in convective mixed layer need to be uniform with height for lake-effect snow bands and convective rolls
Wind shear should be calculated from the surface to the top of the convective mixed layer
0-30o - optimal
30-60o - weaker bands with less organization
60o - band formation is disrupted
***end of exam 1 coverage***
Numerical Weather Prediction
NWP - Assimilation, Analysis, and Initialization
Assimilation
Process of blending observations with short range numerical weather models to represent the current state of the atmosphere
Analysis
Product of comparing the previous model run to new observational data and updating the starting values of the model
Initialization
Start of the updated model run (00Z, 06Z, etc.)
NWP - Modeling
Generates analysis forecast (hour 0)
Repeated until end of forecast period
NWP uses a variety of equations:
Governing equations
Laws of conservation of momentum, mass, and energy
Ideal gas law
NWP - Post-Processing
Model output data converted from model coordinates to display coordinates
Filtered for known biases and deficiencies
Data interpolated vertically and horizontally
Gridpoint Models
Simplest type
Data converted into array of gridpoints
Model equations are applied to grid points to produce forecast map
Spectral Models
Data mapped on mathematical waves
Model equations are applied to mathematical waves and converted to geographic coordinate systems to produce forecast map
Dynamical Models
Simulate the atmosphere physically
Modelling changes in flow, heat, and humidity
Rely on primitive equations for atmospheric motion and physical parameterization (thunderstorms, surface heating, etc.)
Uses global or limited domain
Global Domain
Takes into account global weather
No boundary errors
Takes into account weather within a given region only
Boundary errors exist
Forecasts beyond 48 hours are increasingly challenging
Model Limitations
Lack of observational data vertically and horizontally
High resolution doesn’t equal increased accuracy
Boundary errors
Loss of mesoscale features
Sub-synopic features aren’t well represented
Topography included
Parameterization of physical processes
Parameterization of convection
Most models struggle
Convective Allowing Models (CAMs) are effective
Parameterization
Models can’t directly predict certain physical processes
Approximates those effects
Global Forecasting System (GFS)
Global domain
127 vertical layers
13km horizontal domain
Runs four times daily, every 6 hours (00Z, 06Z, 12Z, 18Z)
Forecasts up to 384-hours (3-hour increments
Has known southeast cold bias
North American Mesoscale Forecast System (NAM)
60 sigma-pressure hybrid levels
12km domain
Runs four times daily, every 6 hours (00Z, 06Z, 12Z, 18Z)
Forecasts up to 84-hours (3-hour increments)
NAM-3km
Four fixed nested 3km domains (CONUS, Alaska, Hawaii, and Puerto Rico
One moveable high-resolution nested 1.5km domain
Runs four times daily, every 6 hours (00Z, 06Z, 12Z, 18Z)
Forecasts up to 6-hours (1-hour increments)
Rapid Refresh (RAP)
Initialized by GFS
50 sigma layers
13km horizontal domain
Runs hourly
Assimilated hourly
Forecasts up to 21-hours (1-hour increments)
High-Resolution Rapid Refresh (HRRR)
Subset of RAP
Wind, temp, and moisture errors on RAP can negatively impact radar forecasts
3km horizontal domain
Forecasts up to 48-hours (1-hour increments)
For 00Z, 06Z, 12Z, 18Z runs
Forecasts up to 18-hours for all other hourly runs (01Z, 02Z, 03Z, etc.)
Radar data assimilate every 15 min over a 1 hour period
European Centre for Medium-Range Weather Forecasts (ECMWF)
Most reliable model
Global domain
Spectral model
137 sigma-pressure hybrid levels
16km horizontal resolution
Runs four times daily (00Z, 06Z, 12Z, 18Z)
Forecasts out to 144 hours (3-hour increments)
00Z and 12Z continue on 6-hour increments until 360 hours
Temperature Forecasting
Barotropic Environment
Lack of advection and fronts
Baroclinic Environment
Advection and fronts
More challenging to forecast
Planetary Boundary Layer (PBL)
Lowest layer of the troposphere where frictional effects are heightened
Friction decreases with height in the PBL
Temperatures are impacted by daytime incoming (shortwave) solar radiation and nighttime outgoing longwave radiation
Expands during the day
Contracts at night
Characterized by the following: inversion, air mass change, hydrolapse, and change in wind speed and direction
Mixing in the PBL
Mixing occurs throughout the PBL due to convection and turbulence
Thermals and wind shear
Leads to more uniform air characteristics
Mixing leads to stronger winds at the surface
Mixing can lead to a decrease in surface moisture
Pollutant dispersion is controlled by the depth of the PBL
PBL Changes
Lowest 1-2km, but changes diurnally
Strongest mechanical turbulence in the afternoon
No thermal/mechanical turbulence at night
Max Temperature
Identify thermal advection (850mb/700mb charts)
Where are the winds coming from? Look at soundings upstream
Top of the PBL tends to have the strongest thermal advection due to less friction
Top of the PBL is located around ~850mb (~5,000ft) for sea-level locations and ~700mb (~10,000ft) for high elevation locations
Temps from the PBL can be mixed down to the surface due to atmospheric mixing
Analyzing the temperature of the PBL can help you determine the highest possible temp for the day
If mixing is present in the PBL, air in it will sink and warm by the DALR (10C/km or 5.5F/1000ft)
Find 850mb temp and warm dry adiabatically to the surface
Cloud Cover
Clouds limit the amount of diurnal heating and nocturnal cooling
Filtered sun
Cloud height, type of clouds, and thickness of clouds impact
Impact of Frontal Systems
Fronts can cause highs to occur during the night and lows to occur during the day
Inaccurately forecasting the timing of a front can lead to a busted forecast
Type and strength of the front can dramatically impact the weather
Impact of Terrain
Mountain ranges are heavily impacted by winds
Highly variable PBL
Varying wind directions can lead to a wide variety of weather
Windward side vs. leeward side
Impacts of Precipitation
Unexpected precipitation can lead to cooler temperatures due to evaporative cooling
Impacts are dependent upon the amount, the duration, and the timing of the precipitation
Precipitation Forecasting
Probability of Precipitation (PoP)
PoP Forecast Definition
Forecast of >0.01 in of liquid precip at a given point over a given time
PoP Forecast Challenges
Area
Size of forecast area
Point location vs county warning area
Forcing
Dynamically-forced precipitation or convectively-forced precipitation
Stratiform vs. convective
Confidence
Variation from person-to-person, model-to-model, and experience
Quantitative Precipitation Forecast (QPF)
Prediction of the amount of precip that will fall at a location over a given time interval
Look for pressure level precip signatures
300mb/200mb - Jet Stream/Jet Streak
500mb - Vorticity advection
700mb - UVVs (Omega)
850mb - Thermal advection
Surface - High and low pressure center locations, air masses, fronts/boundaries
Cloud Cover
Relative humidity is a great measure of synoptic-scale lift and moisture
Relative humidity values of 70% or dewpoint depressions of <5C tend to produce overcast conditions
Upward Vertical Velocities
Based on the omega equation
Combination of thermal advection and vorticity advection
WAA in the low-levels and PVA in the mid-levels
-omega or -UVVs → rising air
CAA in the low-levels and NVA in the mid-levels
+omega or +UVVs → sinking air
Thermal Advection
Occurs when isotherms and height lines intersect
Warm Air Advection (WAA) → upward motion and atmospheric expansion
Cold Air Advection (CAA) → sinking motion and atmospheric compression
***end of exam 2 coverage***
Long Range Forecasting
Ensembles
Collection of two or more model solutions (members)
Valid for the same time and location
Running the model with a slightly different model package
Changes in the model’s physics, dynamics, and parameterization
Perturbation for model physics
Running the model with slightly different analysis data
Perturbation for the initial conditions
Allows the forecaster to determine similarities and differences between different runs of the model
Ensemble Types
Ensemble Mean
Average of all model members for a given point in time
Smoothed data
Spaghetti diagram
Two or more model members on one map
Increased spread between members leads to low confidence
Standard deviation
Measure of the difference between all model members
High standard deviation leads to low confidence
El Nino-Southern Oscillation (ENSO)
Fluctuation in sea-surface temperatures and atmospheric pressure
Pressure differences between Darwin, Australia and Tahiti are used to generate the Southern Oscillation Index (SOI)
Typically, lasts 6 to 18 months
El Nino (-SOI)
Warm phase of ENSO (-SOI)
Warmer than normal sea-surface temperatures in the eastern Pacific
Weaker east-to-west flow (trade winds) across the Pacific
Lack of upwelling on the coast of South America
Typically, occurs around the N.H. winter (Christmas)
La Nina (+SOI)
Cool phase of ENSO (+SOI)
Cooler than normal sea-surface temperatures in the eastern Pacific
Stronger east-to-west flow (trade winds) across the Pacific
Upwelling on the coast of South America
Negative vs. Positive SOI
Sustained negative SOI values
Higher than normal pressure at Darwin
Lower than normal pressure at Tahiti
Pacific trade winds weaken
El Nino (warm phase)
Sustained positive SOI values
Lower than normal pressure at Darwin
Higher than normal pressure at Tahiti
Pacific trade winds strengthen
La Nina (cool phase)
ENSO - Nino 3.4
El Nino
5 consecutive 3-month mean of SSTs >0.5C above normal
La Nina
5 consecutive 3-month mean of SSTs <-0.5C below normal
El Nino Impacts
Convection decreases over western Pacific
Convection increases over eastern Pacific
Increased north-south temperature gradient over eastern Pacific
Strong zonal jet stream across the southern US
Cooler and increased storms across the southern US
Warmer and decreased storms across the northern US
La Nina Impacts
Convection increases over western Pacific
Convection decreases over eastern Pacific
Decreased north-south temperature gradient over eastern Pacific
Amplified jet stream across the US
Blocking high near the Gulf of Alaska
Variable jet stream for the western US
Cold outbreaks in the northern US
Colder and increased storms across the northern US
Warmer and drier weather across the southern US
North Atlantic Oscillation (NAO)
Differences in surface SLP between the Azores High and the Icelandic polar low
Calculated through weighted ratios of SLP between Lisbon, Portugal and Stykkisholmur, Iceland
Typically, phases can last for several years
NAO +
Positive phase
Increased PGF
Stronger than normal Azores high
Stronger than normal Icelandic low
Increase in frequency and strength of storms crossing the Atlantic Ocean on a more northerly track
Milder and wetter winter in eastern US
NAO -
Negative Phase
Decreased PGF
Weaker than normal Azores high
Weaker than normal Icelandic low
Decrease in frequency and strength of storms crossing the Atlantic on a more easterly track
Arctic outbreaks in eastern US
Arctic Oscillation
Closely related to NAO
Pressure in the polar regions and the mid-latitudes change in opposition
Typically, phases can last for weeks to decades
AO -
Negative Phase
Blocking high in the arctic region
Cold air funnels in mid-latitudes
Colder than normal temps, on average, across the US
AO +
Positive Phase
Jet stream is positioned further to the north
Warmer than normal temperatures, on average, across the US
Pacific North American (PNA)
Atmospheric flow along the west coast of US is out of phase with the eastern Pacific Ocean and southeastern US (i.e. trough-ridge-trough)
PNA +
Positive phase (amplified)
Deeper than normal troughs over Aleutians and eastern US
Stronger than normal ridges over the western US
Colder than normal in the southeastern US
Warmer than normal in the western US
PNA -
Negative phase (zonal)
Zonal flow across the US
Cooler and wetter in the northwestern US
Warmer than normal in the southeastern US
Pacific Decadal Oscillation
Similar pacific climate variability to ENSO
Greatest impacts in the northern Pacific and North America
Typically, lasts 20-30 years
PDO +
Cool SSTs in the central North Pacific Ocean
Warm SSTs along the west coast of North America
Correlated to El Nino-like climate patterns
PDO -
Warm SSTs in the central North Pacific Ocean
Cool SSTs along the west coast of North America
Correlated to La Nina-like climate patterns
Area Forecast Discussions (AFDs)
Overview
Issued at least 2x daily (usually 4x)
Frequent updates are provided
Covers a 7-day period
Semi-technical product
Scientific reasoning behind a forecast
Summarizes any watches, warning, or advisories in effect
Discussion Content - Old Version
Chronological order
Three primary sections
Synopsis
Description of forecast info and reasoning behind forecast
Near term (up to 12-24 hours)
Short term (up to 48 hours)
Long term
Summary of public, marine and fire outlooks, watches, warnings, and advisories
Discussion Content - New Version
Impact first messaging
Streamlined messaging, enhanced clarity, and reduced redundancy
Three primary sections
Highlights
Key Message 1 - Brief
Key Message 2 - Brief
Key Message 3 - Brief
Description of forecast information and reasoning behind the forecast
Key Message 1 - Discussion
Key Message 2 - Discussion
Key Message 3 - Discussion
Summary of public, marine and fire outlooks, watches, warnings, and advisories
Severe Weather - Indices and SHARPpy
CAPE and CIN
CAPE
CIN
0-3km Mixed-Layer CAPE
CAPE confined in the lowest 3km of the atmosphere
Believed that a “quick” acceleration of parcels increases the ability of those parcels to tilt and stretch horizontal vorticity
In order to generate “high” values of 0-3km CAPE, LCL and LFC height must be “low”
Downdraft CAPE (DCAPE)
Estimate of the potential strength of the rain-cooled downdraft within thunderstorm convection
Large downdraft CAPE is conducive to strong downdrafts
Lifted Index
Comparison of a parcel raised adiabatically to 500mb to the environmental temp at 500mb
Parcel temperature subtracted from the environmental temp
Larger negative values implies more instability
Mid-Level (700-500mb) Lapse Rates
Rate of environmental temperature change with height
10,000-18,000ft above sea level
Steeper lapse rates (greater temperature change) leads to a more unstable atmosphere
Low-Level (850-500mb) Lapse Rates
Rate of environmental temperature change with height
4,500-18,000ft above sea level
Steeper lapse rates (greater temperature change) leads to a more unstable atmosphere
Lifting Condensation Level (LCL) Height
Tornadoes are most likely with LCLs <1000m
Level of Free Convection (LFC) Height
0-1km Shear Vector
Difference between the surface wind and the wind at 1km
>10-15kts shear vectors favor tornadic supercells
0-3km Shear Vector
Difference between the surface wind and the wind at 3km
>30kts shear vectors favor QLCS tornadoes
0-6km Shear Vector
Difference between the surface wind and the wind at 6km
>35-40kts and greater shear vectors favor supercells
Effective Bulk Shear Vector
Difference between the wind at the effective inflow base and the wind halfway to the equilibrium level for the most unstable parcel in the lowest 300mb
Accounts for storm depth
Surface-based and “elevated” supercell environments
>25-40kts favor supercells
0-1km Storm Relative Helicity
Measure of the potential for cyclonic updraft rotation in right-moving supercells
No clear threshold value for SRH when forecasting supercells
Larger values of 0-1km SRH of >100 m2/s2 favor an increased threat of tornadoes
0-3km Storm Relative Helicity
Measure of the potential for cyclonic updraft rotation in right-moving supercells
No clear threshold value for SRH when forecasting supercells
Larger values of 0-3km SRH of >250 m2/s2 favor an increased threat of tornadoes
0-1km and 0-3km Energy Helicity Index (EHI)
Combination of instability and storm relative helicity
0-1km EHI = (CAPE x 0-1km SRH)/160,000
0-3km EHI = (CAPE x 0-3km SRH)/160,000
4-6km Storm Relative Winds
Mid-level storm relative winds
Some use in discriminating between tornadic and non-tornadic supercells
>15kts favor tornadic supercells
9-11km Storm Relative Winds
Upper-level storm relative winds
Meant to discriminate between supercell type
Supercell Composite Parameter (SCP)
Composite index that includes ESRH, MUCAPE, and EBWD
SCP=MUCAPE1000 J/kgESRH50 m2/s2EBWD20 m/s
Greater values indicate greater overlap of the three indices
Significant Tornado Parameter (STP)
Composite index that includes EBWD, ESRH, MLCAPE, MLCIN, and MLLCL
STP=MLCAPE1500 J/kg2000-MLLCL1000mESRH150m2/s2EBWD20m/s200+MLCIN150 J/kg
Greater values indicate greater overlap of the five indices
Convective Mode
Boundary type
Subtle vs. strong forcing
0-6km shear vector
Parallel vs. perpendicular to forcing
Storm motion
Moving away from boundary vs. staying close to boundary
Convective inhibition
Weak vs. strong
Inflow vs. outflow dominant
SHARPpy sub-section
Sounding - Box A
Red line - temp
Red-dashed line - virtual temp
Green line - dew point temp
Cyan line - wet-bulb temp
Purple dashed line - downdraft parcel virtual temp
White dashed line - parcel virtual temp
Virtual Temperature
Temperature that dry air would have if its pressure and density were equal to those of a given sample of moist air
Always greater than or equal to the actual temperature
Moist air less dense than dry air
Warm air less dense than cold air
Vertical Wind Profile - Box B
Colors represents height (same for box D and E)
Red = 0-3km
Green = 3-6km
Yellow = 6-9km
Cyan = 9-15km
Vertical Advection Profile - Box C
Geostrophic temperature advection
Veering vs. Backing winds
Red = WAA
Blue = CAA
Hodograph - Box D
Yellow box - storm motion
White circles - Bunkers left and right moving storm motion
Cyan lines - effective inflow layer
Same as box A
Storm Slinky - Box E
3D trajectory of a parcel in the updraft (looking down on the parcel)
From LFC to EL
Storm relative winds are used to determine trajectory
Degree value represents tilt of the updraft
White line = storm motion
Look for kidney bean shape
Theta-e vs. Pressure - Box F
Equivalent potential temperature
Temp of a parcel after all latent heat energy is released in a parcel then brought to 1000mb
Storm Relative Winds - Box G
Storm relative winds
Red bar = 0-2km
Blue bar = 4-6km
Purple bar = 9-11km
Classic Supercell 9-11km SRW = 40-60kts
HP Supercell = <40kts
LP Supercell = >60kts
Used to determine supercell type
Hazard Type - Box H
PDS TOR
TOR
MRGL TOR
SVR
MRGL SVR
FLASH FLOOD
BLIZZARD
EXCESSIVE HEAT
NONE
Effective Inflow Layer
Lifted parcels with CAPE >100 J/kg and CINH >-250 J/kg are considered to be part of the potential thunderstorm “inflow” layer
Thermodynamic Calculations and Parameters - Box I
Kinematic Calculations and Parameters - Box J
Sounding Analogue System - Box K
Probabilistic forecast of significant hail (>2in) and tornadoes
Matches sounding with past severe weather proximity soundings
Significant Tornado Parameter Box and Whisker Plot - Box L
How STP (effective layer) varies based on EF-scale of previous severe weather proximity soundings
Right-clicking on the box can change display