Application of short range ensemble forecasts to convective aviation forecasting
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Application of Short Range Ensemble Forecasts to Convective Aviation Forecasting. David Bright NOAA/NWS/Storm Prediction Center Norman, OK Southwest Aviation Weather Safety Workshop October 23-24, 2008. Where Americas Climate and Weather Services Begin. Outline. Introduction

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Application of Short Range Ensemble Forecasts to Convective Aviation Forecasting

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Application of Short Range Ensemble Forecasts to Convective Aviation Forecasting

David Bright

NOAA/NWS/Storm Prediction Center

Norman, OK

Southwest Aviation Weather Safety Workshop

October 23-24, 2008

Where Americas Climate and Weather Services Begin


Outline

  • Introduction

  • Short Range Ensemble Forecasts (SREF)

  • Future Aviation Ensemble Applications


Outline

  • Introduction

    • The SPC, predictability, and ensembles

  • Short Range Ensemble Forecasts (SREF)

  • Future Aviation Ensemble Applications


STORM PREDICTION CENTER

LOCALIZED HIGH IMPACT

WEATHER

  • Hail, Wind, Tornadoes

  • Fire Weather

  • Winter Weather

  • Excessive Rainfall


The Butterfly Effect

  • Ensemble forecasting can be formally traced to the discovery of the "Butterfly Effect" (Lorenz 1963, 1965)…

    • The atmosphere is a non-linear, non-periodic, dynamical system such that tiny errors grow ... resulting in forecast uncertainty that increases with time resulting in limited predictability

    • “Does the flap of a butterfly’s wings in Brazil set off a tornado in Texas?” (Lorenz 1972)

    • Or, does the formation of an isolated storm over the Mogollon Rim set off a flash flood near Phoenix?

    • Predictability is a function of temporal and spatial scales: e.g., thunderstorms are inherently less predictable than synoptic scale cyclones


What are the Sources of These Tiny Errors?

Observations, Assimilation, and Models

  • Observations

    • Data gaps

    • Error

    • Representative

    • QC

  • Analysis

  • Models

  • LBCs, etc.

Satellite

Aircraft and Land


Reality

One

model

forecast


  • Numerical weather models...

    • All forecasts contain errors that increase with time

    • Doubling time of small initial errors

      ~1 to 2 days

    • Maximum large-scale (synoptic to planetary) predictability ~10 to 14 days

  • Ensembles…

    • A collection of models that provide information on the range of plausible forecasts, statistical measures of confidence, and extend predictability

    • Scales to the problem of interest

    • Increasing in popularity

    • Requires “tools” to view the large number of models using a slightly different approach (statistical)

Weather forecasting: It’s impossible to

be perfectly correct all of the time!


Outline

  • Introduction

  • Short Range Ensemble Forecasts (SREF)

    • Currently available through the SPC website

  • Future Aviation Ensemble Applications


Ensemble Guidance at the SPC

  • Develop specialized guidance for the specific application (convection, severe storms, fire weather, winter weather)

  • Design guidance that…

    • Help blend deterministic and ensemble approaches

    • Provide guidance for uncertainty/probabilistic forecasts

    • Provide guidance that aids confidence (i.e., better deterministic forecasts)

    • Illustrates plausible scenarios

    • Allows for diagnostic analysis –

      not just a statistical black-box


Ensembles Available at the SPC: SREF

NWS/NCEP Short Range Ensemble Forecast (SREF)

  • EMC SREF system (21 members)

    • 87 hr forecasts four times daily (03, 09, 15, 21 UTC)

    • North American domain

    • Model grid lengths 32-45 km

    • Multi-model: Eta, RSM, WRF-NMM, WRF-ARW

    • Multi-analysis: NAM, GFS initial and boundary conds.

    • IC perturbations and physics diversity

    • Recently added bias-correction to some fields (not covered and not available on the SPC webpage)


All example products available on the SPC webpage

http://www.spc.noaa.gov/exper/sref/

http://w1.spc.woc.noaa.gov/exper/sref/frames.php?run=case_2007060803


Basic Overview

[MN]: = Mean

[SP]: = Spaghetti

[MNSD]: = Mean/SD

[MAX]: Max value at each grid point


SREF 500 mb Mean Height, Wind, Temp


Instability

[MN]: = Mean

[PR]: Probability

[MDXN]: Median/union & intersect

[SP]: = Spaghetti

[MNSD]: = Mean/SD


SREF Pr[MUCAPE > 1000 J/kg] & Mean MUCAPE=1000 (dash)


Winds and Vertical Shear

[MN]: = Mean

[SP]: = Spaghetti

[MNSD]: = Mean/SD

[MDXN]: Median/union & intersect

[MAX]: Max value at each grid point


SREF Pr[ESHR > 30 kts] & Mean ESHR=30 kts (dash)

“Effective Shear” (ESHR; Thompson et al. 2007, WAF) is the bulk shear in the lower half of the convective cloud


Precipitation

[MN]: = Mean

[SP]: = Spaghetti

[MNSD]: = Mean/SD

[MDXN]: Median/union & intersect

[MAX]: Max value at each grid point


SREF Pr[C03I > .01”] and Mean C03I = .01” (dash)

C03I = 3hr Convective Precipitation


Severe Weather

[MN]: = Mean

[SP]: = Spaghetti

[MNSD]: = Mean/SD

[MDXN]: Median/union & intersect

[MAX]: Max value at each grid point


SREF Combined or Joint Probability

Probability of convection in moderate CAPE, moderate shear environment

Pr [MUCAPE > 1000 J/kg] X

Pr [ESHR > 30 kts] X

Pr [C03I > 0.01”]


Post-Processed Guidance

[PR]: = Probability (Calibrated)


SREF 3h Calibrated Probability of a Thunderstorm

Thunderstorm =

> 1 CG Lightning Strike in 40 km grid box

(Bright et al., 2005) http://ams.confex.com/ams/pdfpapers/84173.pdf


Calibrated SREF Thunder Reliability

Frequency

[0%, 5%, …]

Perfect Forecast

No Skill

Climatology

Calibrated Thunder Probability


SREF 3h Calibrated Probability of a Severe Thunderstorm

Severe Thunderstorm =

> 1 CG Lightning Strike in 40 km grid box

and

Wind > 50 kts or Hail > 0.75” or Tornado

(Bright and Wandishin, 2006) http://ams.confex.com/ams/pdfpapers/98458.pdf


Severe

Verification

Hail > .75”

Wind > 50 kts

Tornado

21 UTC F039 24h forecasts from 15 April to 15 October 2005

ROC Area= .86

Ave Hit = 15%

Ave Miss= 3%

(24h Fcst: F39, 21Z only)

21 UTC SREF only


Aviation Guidance

[MN]: = Mean

[MD]: Median/union & intersect

[MAX]: Max value at each grid point

[CPR]: Conditional probability

[PR]: Probability


SREF Probability Convective Cloud Top > 37 KFt


Test Version: 03Z SREF Day 1 ENH Guidance (Summer 2008)

Probability Echo Tops >= 35KFT


Severe Weather on June 9, 2007

  • 107 total severe reports in CONUS

    • 3 tornadoes over nrn New Mexico (~22 UTC)


Outline

  • Introduction

  • Short Range Ensemble Forecasts (SREF)

  • Future Aviation Ensemble Applications

    • Applications and calibration under development

      • One hourly SREF thunderstorm guidance (through F036) *

      • Calibration of potential impacts of convection in SREF ^

      • Rapid Refresh Ensemble Forecast (RREF) – 1hr updates, RUC based *

      • Storm scale (e.g., supercells, squall lines) applications being evaluated

*Not discussed today

^Collaborating with John Huhn, Mitre Corp.


Gridded Flight Composite (20 km)December 2007 to August 2008 – Above 250 KFT

Probability (%) aircraft is inside grid box

20 km Grid (AWIPS 215)

Data from John Huhn, Mitre


Gridded Flight Composite (40 km)December 2007 to August 2008

21 UTC Composite < 10 KFT

21 UTC Composite > 25 KFT

Probability (%) aircraft is inside grid box at exactly 21 UTC


Example of Potential ImpactsProbability Thunderstorm X Gridded Composites

SREF F036: 3h Calibrated

Probability of a T-storm

Valid: 21 UTC 8 June 2007

SREF F036: Impact

Potential Below 10 KFT

Valid: 21 UTC 8 June 2007

SREF F036: Impact

Potential Above 25 KFT

Valid: 21 UTC 8 June 2007


Future Applications: Storm Scale Ensemble (SSEF)

  • NOAA Hazardous Weather Testbed (HWT)

  • HWT Spring Experiment

    • Focused on experimental high-res WRF forecasts since 2004 (dx ~2-4 km)

  • Convection allowing ensemble forecasts (2007-2009) to address uncertainty

    • 10 WRF members

    • 4 km grid length over 3/4 CONUS

    • Major contributions from: SPC, NSSL, OU/CAPS, EMC, NCAR

    • Resolving convection explicitly in the model

  • Evaluate the ability of convection allowing ensembles to predict:

    • Convective mode (i.e., type of severe wx)

    • Magnitude of severe type (e.g., peak wind)

    • Aviation impacts (e.g., convective lines/tops)

    • QPF/Excessive precipitation

    • Year 1 Objective (2007): Assess the role

      of physics vs. initial condition uncertainty at

      high resolution

2003 Spring Experiment


Probability Updraft Helicity > 50 m2/s2

Probability of Supercell Thunderstorms

F026: Valid 02 UTC 22 Apr 2008

UH > 50 + 25 mi


Observed Radar

Radar BREF 0142 UTC 22 Apr 2008


Probability Updraft Helicity > 50 m2/s2

Jack Hales

View of the left split looking south from Norman, OK (0145 UTC 22 Apr 2008)

(Numerous large hail reports up to 2.25”)


Convective Mode: Linear Detection

  • Determine contiguous areas exceeding 35 dbZ

  • Estimate mean length-to-width ratio of the contiguous area; search for ratios > 5:1

  • Flag grid point if the length exceeds:

    • 200 miles


Probability Linear Mode Exceeding 200 miles

Squall Line Detection

F024: Valid 00 UTC 18 Apr 2008

Linear mode + 25 miles


Probability Linear Mode Exceeding 200 miles

Squall Line Detection

F026: Valid 02 UTC 18 Apr 2008

Linear mode + 25 miles


Probability Linear Mode Exceeding 200 miles

Squall Line Detection

F028: Valid 04 UTC 18 Apr 2008

Linear mode + 25 miles


Linear Convective Mode: Impacts

Aviation impacts ~ 01 UTC

18 April 2008

Image provided by Jon Racy


Summary: Ensemble Applications in Convective/Aviation Forecasting

  • Ensemble approach to forecasting has many similarities to the deterministic approach

    • Ingredients based inputs

    • Diagnostic and parameter evaluation

  • Ensembles contribute appropriate levels of confidence to the forecast process

    • Ability to view diagnostics and impacts in probability space

  • Calibration of ensemble output can remove systematic biases and improve the spread

  • Ensemble techniques scale to the problem of interest (weeks, days, or hours)

  • Ensemble systems are here to stay…and will evolve downscale toward high-impact forecasting


SPC SREF Products on WEB

http://www.spc.noaa.gov/exper/sref/

Questions/Comments…

[email protected]


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