Extending Geostationary Satellite Retrievals from Observations into Forecasts Using GOES Sounder Products to Improve Regional Hazardous Weather Forecasts.

Slides:



Advertisements
Similar presentations
Chapter 13 – Weather Analysis and Forecasting
Advertisements

February 19, 2004 Texas Dryline/Dust Storm Event.
New Product to Help Forecast Convective Initiation in the 1-6 Hour Time Frame Meeting September 12, 2007.
Stratus. Outline  Formation –Moisture trapped under inversion –Contact layer heating of fog –Fog induced stratus –Lake effect stratus/strato cu  Dissipation.
SPC Input – EMC GFS Satellite Data Denial Experiment April 2011 Tornado Outbreak Examination of Day 7 and Day 4 Guidance for SPC Severe Weather Outlooks.
Louisville, KY August 4, 2009 Flash Flood Frank Pereira NOAA/NWS/NCEP/Hydrometeorological Prediction Center.
 The main focus is investigating the dynamics resulting in synoptically forced training convective rainfall  Synoptic conditions necessary for the generation.
Aspects of 6 June 2007: A Null “Moderate Risk” of Severe Weather Jonathan Kurtz Department of Geosciences University of Nebraska at Lincoln NOAA/NWS Omaha/Valley,
A n Objective Nowcasting Tool that Optimizes the Impact of Frequent Observations in Short-Range Forecasts a.k.a. “Stopping Short-Range Gap-osis” Ralph.
Danielle M. Kozlowski NASA USRP Intern. Background Motivation Forecasting convective weather is a challenge for operational forecasters Current numerical.
An Overview of Environmental Conditions and Forecast Implications of the 3 May 1999 Tornado Outbreak Richard L. Thompson and Roger Edwards Presentation.
A tale of two severe weather surprises – The isolated event of 16 July 2010 and the severe weather outbreak of 17 July 2010 Neil A. Stuart NOAA/NWS Albany,
Rapid Update Cycle Model William Sachman and Steven Earle ESC452 - Spring 2006.
THE DISTINCTION BETWEEN LARGE- SCALE AND MESOSCALE CONTRIBUTION TO SEVERE CONVECTION: A CASE STUDY EXAMPLE Paper by Charles A. Doswell III Powerpoint by.
Characteristics of an Anomalous, Long-Lived Convective Snowstorm Rebecca L. Ebert Department of Soil, Environmental, and Atmospheric Sciences University.
An Examination of the Tropical System – Induced Flooding in Central New York and Northeast Pennsylvania in 2004.
SNOWIN’ TO BEAT THE BAND Using Satellite and Local Analysis and Prediction System Output to Diagnose the Rapid Development of a Mesoscale Snow Band Eleanor.
Characteristics of Isolated Convective Storms Meteorology 515/815 Spring 2006 Christopher Meherin.
Chapter 13 – Weather Analysis and Forecasting. The National Weather Service The National Weather Service (NWS) is responsible for forecasts several times.
Roll or Arcus Cloud Supercell Thunderstorms.
Corfidi, et al – convection where air parcels originate from a moist absolutely unstable layer above the PBL. Can produce severe hail, damaging.
Use of TAMDAR Data in a Convective Weather Event Saturday, May 21, 2005.
Climatology and Predictability of Cool-Season High Wind Events in the New York City Metropolitan and Surrounding Area Michael Layer School of Marine and.
NCEP’s Seamless Suite of Products  Covers events from Climate to Weather to Oceans  Spans ranges of time from Seasons to Weeks to Days to Hours in the.
Model Simulations of Extreme Orographic Precipitation in the Sierra Nevada Phillip Marzette ATMS 790 March 12, 2007.
Long lived Thundersnow March 23, 1966 By Kathy Lovett and Leah Smeltzer Authors: Patrick S. Market, Rebecca L. Ebert-Cripe Michael Bodner.
MDSS Lab Prototype: Program Update and Highlights Bill Mahoney National Center For Atmospheric Research (NCAR) MDSS Stakeholder Meeting Boulder, CO 20.
1 CIMSS Participation in the Development of a GOES-R Proving Ground Timothy J. Schmit NOAA/NESDIS/Satellite Applications and Research Advanced Satellite.
Objective Nowcasting Development What is our goal? Forecasters now use GOES imagery and Derived Product Imagery (DPI) to monitor weather – and make subjective.
Henry Fuelberg Pete Saunders Pendleton, Oregon Research Region Map Types and Lightning Frequencies.
Weather Forecasting Chapter 9 Dr. Craig Clements SJSU Met 10.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Nearcasting Severe Convection.
The Benefit of Improved GOES Products in the NWS Forecast Offices Greg Mandt National Weather Service Director of the Office of Climate, Water, and Weather.
The Need for an Advanced Sounder on GOES The Numerical Weather Prediction Perspective Robert M. Aune Center for Satellite Applications and Research, NESDIS.
The Rapid Evolution of Convection Approaching the New York City Metropolitan Region Brian A. Colle and Michael Charles Institute for Terrestrial and Planetary.
Soundings and Adiabatic Diagrams for Severe Weather Prediction and Analysis.
Using Ensemble Probability Forecasts And High Resolution Models To Identify Severe Weather Threats Josh Korotky NOAA/NWS, Pittsburgh, PA and Richard H.
Steve Koch National Severe Storms Laboratory Steve Koch National Severe Storms Laboratory WELCOME to the WoF – HiW Workshop of 2014.
ATS/ESS 452: Synoptic Meteorology Friday 2/8/2013 Quiz & Assignment 2 Results Finish Thermal Wind MOS decoding (Assignment) New England weather.
Dynamic tropopause analysis; What is the dynamic tropopause?
High impact weather studies with advanced IR sounder data Jun Li Cooperative Institute for Meteorological Satellite Studies (CIMSS),
Title card A Look at Environments Associated with Nighttime Supercell Tornadoes in the Central Plains Meteorologist Jon Davies Private © Dick McGowan &
Satellite based instability indices for very short range forecasting of convection Estelle de Coning South African Weather Service Contributions from Marianne.
GII to RII to CII in South Africa Estelle de Coning South African Weather Service Senior Scientist.
Madden/Julian Oscillation: Recent Evolution, Current Status and Forecasts Update prepared by Climate Prediction Center / NCEP February 5, 2007.
Madden/Julian Oscillation: Recent Evolution, Current Status and Forecasts Update prepared by Climate Prediction Center / NCEP January 29, 2007.
A Satellite-Based Objective Analysis Scheme for Nowcasting Applications Robert M. Aune Advanced Satellite Products Team NOAA/NESDIS/ORA/ARADand Ralph Petersen.
GOES Sounder Hyper-spectral Environmental Suite (HES) Data from the HES will revolutionize short-term weather forecasting Impact on short-term weather.
NearCasting Severe Convection using Objective Techniques that Optimize the Impact of Sequences of GOES Moisture Products Ralph Petersen 1 and Robert M.
Madden/Julian Oscillation: Recent Evolution, Current Status and Forecasts Update prepared by Climate Prediction Center / NCEP April 3, 2006.
Conditions for Convection The Ingredients Method.
Examining the Role of Mesoscale Features in the Structure and Evolution of Precipitation Regions in Northeast Winter Storms Matthew D. Greenstein, Lance.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Nearcasting Severe Convection.
VISITview Teletraining Nearcasting Convection using GOES Sounder Data 1 ROBERT M. AUNE AND RALPH PETERSEN NOAA/ASPB/STAR JORDAN GERTH AND SCOTT LINDSTROM.
Satellite Data Assimilation Activities at CIMSS for FY2003 Robert M. Aune Advanced Satellite Products Team NOAA/NESDIS/ORA/ARAD Cooperative Institute for.
Madden/Julian Oscillation: Recent Evolution, Current Status and Forecasts Update prepared by Climate Prediction Center / NCEP November 6, 2006.
Matthew Lagor Remote Sensing Stability Indices and Derived Product Imagery from the GOES Sounder
High impact weather nowcasting and short-range forecasting using advanced IR soundings Jun Li Cooperative Institute for Meteorological.
PRELIMINARY VALIDATION OF IAPP MOISTURE RETRIEVALS USING DOE ARM MEASUREMENTS Wayne Feltz, Thomas Achtor, Jun Li and Harold Woolf Cooperative Institute.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Combining GOES Observations with Other Data to Improve Severe Weather Forecasts.
Dynamic NearCasting of Severe Convection using Sequences of GOES Moisture Products - Applicability to NASA Aviation Program? - Ralph Petersen 1 and Robert.
Developing GFS-based MOS Thunderstorm Guidance for Alaska Phillip E. Shafer* and Kathryn Gilbert Meteorological Development Laboratory, NWS, NOAA
ABC’s of weather forecasting NOAA/NATIONAL WEATHER SERVICE WFO BALTIMORE / WASHINGTON OPEN HOUSE – APRIL 30-MAY 1, 2016 RAY MARTIN –– Lead Forecaster.
Heavy Rain Climatology of Upper Michigan Jonathan Banitt National Weather Service Marquette MI.
Extending Geostationary Satellite Retrievals from
Characteristics of Isolated Convective Storms
Soundings and Adiabatic Diagrams for Severe Weather Prediction and Analysis Ooohhhh!!!!!!!!!!! Aaaahhhhhhhh!!!!!! Look at the pretty picture!
NWS Forecast Office Assessment of GOES Sounder Atmospheric Instability
Tony Wimmers, Wayne Feltz
Comparison of Observed Conditions with Stability Indices
Presentation transcript:

Extending Geostationary Satellite Retrievals from Observations into Forecasts Using GOES Sounder Products to Improve Regional Hazardous Weather Forecasts Ralph A. Petersen : University of Wisconsin – Madison Robert M Aune : NOAA/NESDIS/STAR - Advanced Satellite Products Branch - Madison, WI

Focus on the next 1-6 hours – Fill the Gap between Nowcasts and NWP Update/enhance NWP guidance: - Be Fast and updated very frequently Use ALL available data - quickly: - “Draw closely” to good data - Avoid analysis smoothing / superobing (Issues of longer-range NWP) Anticipate rapidly developing weather events: - “Perishable” guidance products need rapid delivery - Detect the “pre-storm environment” - Increase lead time Probability of Detection (POD) - Reduce False Alarm Rate (FAR) Run locally if needed: - Few resources needed - Improve Forecaster’s Situational Awareness What is an Objective NearCasting System hours Fill the Gap Between Nowcasting & NWP A NearCasting model should:

13 April 2006 – 2100 UTC hPa GOES PW 0 Hour Ob Locations Updated Hourly - Full-resolution 10 km data - 10 minute time steps Objectives: ♦Preserve Data Maxima/Minima/Large Gradients ♦ Use Geostationary satellite data at Full Resolution ♦ Be Fast Methodology: The Lagrangian approach first interpolates wind data to locations of full resolution GOES multi- layer moisture & temperature observations How the Lagrangian NearCasts work:

13 April 2006 – 2100 UTC hPa GOES PW 0 Hour Ob Locations 13 April 2006 – 2100 UTC hPa GOES PW 3 Hour NearCast Image Updated Hourly - Full-resolution 10 km data - 10 minute time steps Objectives: ♦Preserve Data Maxima/Minima/Large Gradients ♦ Use Geostationary satellite data at Full Resolution ♦ Be Fast Methodology: The Lagrangian approach first interpolates wind data to locations of full resolution GOES multi- layer moisture & temperature observations Next, these high-definition data are moved to future locations, using dynamically changing winds with ‘long’ (10 min.) time steps.. How the Lagrangian NearCasts work:

13 April 2006 – 2100 UTC hPa GOES PW 0 Hour Ob Locations 13 April 2006 – 2100 UTC hPa GOES PW 3 Hour NearCast Image Updated Hourly - Full-resolution 10 km data - 10 minute time steps Vertical Moisture Gradient (indicating Convective Instability) ( hPa GOES PW hPa GOES PW) 3 Hour NearCast : Valid 0000UTC Objectives: ♦Preserve Data Maxima/Minima/Large Gradients ♦ Use Geostationary satellite data at Full Resolution ♦ Be Fast Methodology: The Lagrangian approach first interpolates wind data to locations of full resolution GOES multi- layer moisture & temperature observations Next, these high-definition data are moved to future locations, using dynamically changing winds with ‘long’ (10 min.) time steps.. Finally, the moved ‘obs’ values from each layer are then both: 1) Transferred back to an ‘image’ for display of ‘predicted DPIs’, 2) Several parameters are combined to produce derived parameters and 3) Results between layers are compared to obtain various “Stability Indices” that are combined with ‘conventional tools’ to identify mesoscale areas where severe convective will develop - even after convective clouds appear. Verification How the Lagrangian NearCasts work:

Recent Progress Example many new cases where NearCasts of GOES vertical moisture gradients (a necessary condition for Convective Instability) helped isolate areas of Hazardous Weather Potential –Useful in many seasons/regions of US Severe Convection Emphasis on rapid development of isolated storm – Heavy Precipitation –Output in GRIB-II and NWS Graphics formats –... Expanded analyses of Convective Environment Diagnose case using SEVIRI data

Mid-layer Moisture ( hPa GOES PW ) 7 Analyses plus 6-Hour NearCast from 1100UTC 10 February, 2009 Formation of Strong Pre- Frontal Convection Moving GOES data from Observations to Forecasts Event: Winter Tornado Begin Date: 10 Feb 2009, 14:52:00 PM CST Begin Location: Edmond, Oklahoma Path: 6.5 miles End Date: 10 Feb 2009, 15:05:00 PM CST End Location: Not Known Magnitude: EF2

Vertical Moisture Gradient ( hPa GOES PW hPa GOES PW) 7 Analyses Plus 6-Hour NearCast from 1100UTC 10 February 2009 Moving GOES data from Observations to Forecasts Formation of Strong Pre- Frontal Convection Verification: Radar/ReportsPsuedo-Convective Stability

Using true Equivalent Potential Temperature ( Theta-E or Θ e ) instead of TPW, to diagnose Total Thermal Energy and Convective Instability Fundament Question: Do GOES temperature profiles add information regarding the potential for the timing and location of convection development to that already present in the DPI moisture products already being used? A case when Severe Thunderstorm Warnings were issued for all of western Iowa Rapid Development of Convection over NE IA between 2000 and 2100 UTC 9 July 2009

Using Equivalent Potential Temperature ( Theta-E or Θe ) instead of TPW to diagnose Total Thermal Energy and true Convective Instability A case when Severe Thunderstorm Warnings were issued for all of western Iowa Theta-E measures TOTAL moist energy, not only latent heat potential  Lower-Layer Θe NearCasts shows warm / moist air band moving into far NW Iowa, where deep convection formed rapidly by 2100 UTC.  Vertical Θe Differences shows full Convective Instability - at the correct time and place - GOES temperature data in Θe do enhance the vertical moisture gradient fields used previously. Negative ∂ Θ e / ∂Z (blue to red areas) indicates Convective Instability Rapid Development of Convection over NE IA between 2000 and 2100 UTC 9 July hr NearCast for 2100 UTC Low to Mid Layer Theta-E Differences 6 hr NearCast for 2100 UTC Low Layer Theta-E

How well can the NearCasting approach be applied to SEVIRI data? Tests were conducted with 2 time periods of retrievals obtained 8 and 6 hours prior to development of the F2/T4 tornado that occurred in Częstochowa, Poland near 16UTC - 20 July –Full description in Pajek, Iwanski, König and Struzik from last meeting –Results using 09UTC retrievals (provided by König) shown here NearCast results valid from 09UTC to 15UTC Initial Wind and Geopotential data from NCEP 0.5 o resolution Results displayed on 0.25 o output grid NearCasts were made or a wider variety of variable than in previous US tests –Multi-Layer and Total Precipitable Water –Lower- and Mid-tropospheric parameters: Temperature Mixing Ratio Temperature at LCL Equivalent Potential Temperature Several Stability Indices were derived from NearCasts of these primary variables

Tests were conducted with 2 time periods of retrievals obtained 8 and 6 hours prior to development of the F2/T4 tornado that occurred in Częstochowa, Poland near 16UTC - 20 July –Full description in Pajek, Iwanski, König and Struzik from last meeting –Results using only 09UTC retrievals (provided by Konig) shown here NearCast results valid from 09UTC to 15UTC Initial Wind and Geopotential data from NCEP 0.5 o resolution Results displayed on 0.25 o output grid NearCasts were made for more variable than in previous US tests –Multi-Layer and Total Precipitable Water –Lower- and Mid-tropospheric parameters: Temperature Mixing Ratio Temperature at LCL Equivalent Potential Temperature Several Stability Indices were derived from NearCasts of these primary variables Note: Apologies for “quality” of graphics - but they get the point across –Currently integrating NearCasts into McIdas-V How well can the NearCasting approach be applied to SEVIRI data?

hPa Precipitable Water – 09Z – F00:Valid 09Z Slide Orientation NearCast Length and Valid Time indicated by F00:Valid 09Z Display area: Centered on Poland 11 o to 27 o E and 47 o to 60 o N Location of F2/T4 Tornado indicated by Cross

hPa Precipitable Water – 09Z – F06:Valid 15Z Middle-Layer Precipitable Water Observations show: - No terrain effects Maximum of Middle-Layer PW - Only one observed maximum in area -Initially West of tornado location - Moves to region North-West of Tornado at time of development

Lower-Tropospheric Temperature Observations show: - Temperature front North of area of tornado formation - Highest Temperatures were well south of tornado Temperature – 840 hPa – 09Z – F00:Valid 09Z

Temperature – 840 hPa – 09Z – F06:Valid 15Z Lower-Tropospheric Temperature Observations show: - Temperature front North of area of tornado formation - Highest Temperatures were well south of tornado Front strengthens and temperatures increase near and west of tornadic area during NearCast - Low-level Lifting ?

Equivalent Potential Temperature (Өe) – 840 hPa – 09Z – F00:Valid 09Z Lower-Tropospheric Equivalent Potential Temperature ( Ө e) Observations show: - Significant front immediately North of area where tornado formed (a potential lifting mechanism) - Area of Warm/Moist air South-West of tornado development

Equivalent Potential Temperature (Өe) – 840 hPa – 09Z – F06:Valid 15Z Lower-Tropospheric Equivalent Potential Temperature ( Ө e) Observations show: - Significant front immediately North of area where tornado formed (a potential lifting mechanism) - Area of Warm/Moist air South-West of tornado development -Warm/Moist air moved to area where severe convection was forming rapidly by 15UTC

Convective Instability Observations show: - Weakest Stability South-West of tornado development NearCasts show combined effects of differential advection between Warm/Moist air at low levels and Dry/Cool air aloft - Area of greatest Convective Instability moves to tornado site at same time as rapid lapse rate change Vertical Equiv. Pot. Temp. Difference (∂ Ө e/∂p) – hPa – 09Z – F00:Valid 09Z Convective Instability

Vertical Equiv. Pot. Temp. Difference (∂Өe/∂p) – hPa – 09Z – F00:Valid 09Z Convective Instability Observations show: - Weakest Stability South-West of tornado development NearCasts show combined effects of differential advection between Warm/Moist air at low levels and Dry/Cool air aloft - Area of greatest Convective Instability moves to tornado site at same time as rapid lapse rate change

Vertical Equiv. Pot. Temp. Difference (∂Өe/∂p) – hPa – 09Z – F01:Valid 10Z Convective Instability Observations show: - Weakest Stability South-West of tornado development NearCasts show combined effects of differential advection between Warm/Moist air at low levels and Dry/Cool air aloft - Area of greatest Convective Instability moves to tornado site at same time as rapid lapse rate change

Vertical Equiv. Pot. Temp. Difference (∂Өe/∂p) – hPa – 09Z – F02:Valid 11Z Convective Instability Observations show: - Weakest Stability South-West of tornado development NearCasts show combined effects of differential advection between Warm/Moist air at low levels and Dry/Cool air aloft - Area of greatest Convective Instability moves to tornado site at same time as rapid lapse rate change

Vertical Equiv. Pot. Temp. Difference (∂Өe/∂p) – hPa – 09Z – F03:Valid 12Z Convective Instability Observations show: - Weakest Stability South-West of tornado development NearCasts show combined effects of differential advection between Warm/Moist air at low levels and Dry/Cool air aloft - Area of weakest strengthens as it move to tornado site at same time as rapid lapse rate change

Vertical Equiv. Pot. Temp. Difference (∂Өe/∂p) – hPa – 09Z – F04:Valid 13Z Convective Instability Observations show: - Weakest Stability South-West of tornado development NearCasts show combined effects of differential advection between Warm/Moist air at low levels and Dry/Cool air aloft - Area of greatest Convective Instability moves to tornado site at same time as rapid lapse rate change

Vertical Equiv. Pot. Temp. Difference (∂Өe/∂p) – hPa – 09Z – F05:Valid 14Z Convective Instability Observations show: - Weakest Stability South-West of tornado development NearCasts show combined effects of differential advection between Warm/Moist air at low levels and Dry/Cool air aloft - Area of greatest Convective Instability moves to tornado site at same time as rapid lapse rate change

Vertical Equiv. Pot. Temp. Difference (∂Өe/∂p) – hPa – 09Z – F06:Valid 15Z Convective Instability Observations show: - Weakest Stability South-West of tornado development NearCasts show combined effects of differential advection between Warm/Moist air at low levels and Dry/Cool air aloft - Area of greatest Convective Instability moves to tornado site at same time as rapid lapse rate change

Vertical Equiv. Pot. Temp. Difference (∂Өe/∂p) – hPa – 09Z – F06:Valid 15Z Convective Instability Observations show: - Weakest Stability South-West of tornado development NearCasts show combined effects of differential advection between Warm/Moist air at low levels and Dry/Cool air aloft - Area of greatest Convective Instability moves to tornado site at same time as rapid lapse rate change

Lifted Index Difference between T LCL 840 and T 480 Observations show: - Weakest Stability South-West of tornado development- …but… - NearCasts show: - Initial Instability weakens and moves East - Second area of Instability forms to west and moves to tornado site by 15Z Lifted Index – hPa – 09Z – F00:Valid 09Z

Lifted Index – hPa – 09Z – F01:Valid 10Z Lifted Index Difference between T LCL 840 and T 480 Observations show: - Weakest Stability South-West of tornado development- …but… - NearCasts show: - Initial Instability weakens and moves East - Second area of Instability forms to west and moves to tornado site by 15Z Lifted Index Difference between T LCL 840 and T 480 Observations show: - Weakest Stability South-West of tornado development- …but… - NearCasts show: - Initial Instability weakens and moves East - Second area of Instability forms to west and moves to tornado site by 15Z

Lifted Index – hPa – 09Z – F02:Valid 11Z Lifted Index Difference between T LCL 840 and T 480 Observations show: - Weakest Stability South-West of tornado development- …but… - NearCasts show: - Initial Instability weakens and moves East - Second area of Instability forms to west and moves to tornado site by 15Z

Lifted Index – hPa – 09Z – F03:Valid 12Z Lifted Index Difference between T LCL 840 and T 480 Observations show: - Weakest Stability South-West of tornado development- …but… - NearCasts show: - Initial Instability weakens and moves East - Second area of Instability forms to west and moves to tornado site by 15Z

Lifted Index – hPa – 09Z – F04:Valid 13Z Lifted Index Difference between T LCL 840 and T 480 Observations show: - Weakest Stability South-West of tornado development- …but… - NearCasts show: - Initial Instability weakens and moves East - Second area of Instability forms to west and moves to tornado site by 15Z

Lifted Index – hPa – 09Z – F05:Valid 14Z Lifted Index Difference between T LCL 840 and T 480 Observations show: - Weakest Stability South-West of tornado development- …but… - NearCasts show: - Initial Instability weakens and moves East - Second area of Instability forms to west and moves to tornado site by 15Z

Lifted Index – hPa – 09Z – F06:Valid 15Z Lifted Index Difference between T LCL 840 and T 480 Observations show: - Weakest Stability South-West of tornado development- …but… - NearCasts show: - Initial Instability weakens and moves East - Second area of Instability forms to west and moves to tornado site by 15Z

Lifted Index – hPa – 09Z – F06:Valid 15Z Lifted Index Difference between T LCL 840 and T 480 Observations show: - Weakest Stability South-West of tornado development- …but… - NearCasts show: - Initial Instability weakens and moves East - Second area of Instability forms to west and moves to tornado site by 15Z

Summary Additional tests show utility of GOES DPI NearCasts in detecting the pre-convective environment for hazardous weather in many US cases Effect for detecting isolated convection and reducing warning area sizes Important for predicting various type of Hazardous Convection Useful in adding detail to Heavy Precipitation Forecasts GOES Temperature Soundings provide additional information beyond TPW in defining Convective Potential when using Ө e Tests using SEVIRI retrieval positive Useful in diagnosing the pre-convective environment evolution Applicable to many forecasting Indices FUTURE Beta-test version available for distribution by mid-October Major US testing at SPC/NSSL in 2010 Plans for improved graphics using McIDAS-V Ensembles, Consistency,...