Storm Prediction Center Russell S. Schneider Steven J.
Storm Prediction Center Russell S. Schneider Steven J. Weiss DOC/NOAA/NWS/NCEP Storm Prediction Center Warn-on-Forecast Kickoff Workshop February 18, 2010 Where Americas Weather and Climate Services Begin NOAA NWS Storm Prediction Center Forecast tornadoes, thunderstorms, and wildfires nationwide Forecast information from 8 days to a few minutes in advance World class team engaged with the research community Partner with over 120 local National Weather Service offices Toward a Continuous Stream of Decision Information D a Thunderstorm, Fire Weather, SEVERE WEATHER
y s OUTLOOKS Detailed MESOSCALE H DISCUSSIONS o SPC u r s SVR/TOR WATCHES M i n u WARN
t e s Products Local NWS Products (WFO) NOAA Hazardous Weather Testbed Experimental Forecast Program Prediction of hazardous weather events from a few hours to a week in advance EFP EWP
GOES-R PG Experimental Warning Program Detection and prediction of hazardous weather events up to several hours in advance Primary HWT Collaborative Forecast Projects 1997 2000 2001 2002
WINWEX 97 2003 2004 2005 SE2002 SE2000 Evaluation of Model soundings, RUC-based SFCOA, hail IHOP forecasting support SE2001
Subjective Verif., Conv. Param. 2007-09 2006 SE2006 SE2004 First detailed look at Hi-Res WRF Pre-implementation evaluation of NCEP NAM-WRF SE2003 Short-Range Ensembles
(SREF) SE2005 SE2007-09 Hi-Res WRF configuration testing Hi-Res WRF & Ensembles Testbed R20 Process SPC-NSSL HWT pathway for operational assessment and feedback Engage the community with a focus on forecast improvement Ensembles: Explore & Define Uncertainty
ARPS C0 C0 18 hr Forecast - 1 km Radar Observed Radar Reflectivity HWT 2009 Spring Experiment SPC Contributions to WoF HWT is cornerstone for collaborative activities Key partnerships with NSSL, EMC, GSD, OU/CAPS, and NCAR Testing and evaluation of high-resolution model guidance for severe weather forecasting Convection-allowing WRF models and CAPS Storm Scale Ensemble Forecast (SSEF) system Extraction of storm mode and intensity information Supercells, linear mode, etc.
Probabilistic guidance information used in formulation of experimental severe weather forecasts Systematic feedback to model developers A community focused on forecast service improvement SPC Contributions to WoF SPC short-term Mesoscale Discussion and Watch focus coincide with near-term aviation impacts time frame (0-8 hrs) HRRR, HRRRE, and CoSPA overlap with WoF SPC will play active role in fine-tuning product suite to blend with WoF Ramping up process for consistent operational probabilistic Outlook-Watch-Warning suite Service delivery of risk/uncertainty information must include social science expertise to effectively convey threats to decision-makers SPC Contributions to WoF Additional Areas
Task 2 Data Assimilation Development Satellite data assimilation (HWT/GOES-R Proving Ground) Task 3 Case Studies for Evaluation SPC CONUS prediction/monitoring provides unique perspective to provide input for candidate cases Task 8 Model Parameterization Improvement Model simulated satellite imagery offers complementary ways to examine model performance (HWT/GOES-R PG) Task 9 Environmental Sensitivity Evaluation Ongoing study analyzing relationship between storm report storm mode - environment provides initial baseline Includes all tornadoes and extreme hail, extreme wind reports since 2003 High CAPE - Strong Shear Low CAPE - Strong Shear
Severe Reports Environment Hours ~50hr/yr ~100hr/yr 24 % of F2+ tornadoes 39 % of F2+ tornadoes local axis ~ 40 hr / year widespread ~ 80 hr / year All Reports or Modes (2005-2008) All Supercells (2005-2008) No Clear Organization (2005-2008)
QLCS & Bow - no Supercells (2005-2008) 74 % of all tornadoes 13 % of tornadoes 90 % of F2+ tornadoes 9 % of F2+ tornadoes www.spc.noaa.gov [email protected]
Matthew Dean [email protected] The Module The Project Not group work Where to source projects Pre requisites Teaching Learning and Assessment 1st year Teaching - 40% Learning - 40% Assessment - 20% This module Teaching - 10% Assessment - 40% Learning...
x. y. y. time. Frame# Text Fundamentals. One of the most popular modalities. May be viewed as a linear stream of data. Typically represented as an ASCII string for each document. Content indexing still requires certain level of understanding.
"Life is getting better!" Maths vs. Numeracy The doing Memorized patterns Cooking by recipe ----- vs. ----- Figuring stuff out Solving unusual problems The bigger picture of literacies and understanding Cooking for real Weaving webs of meaning Numbers: What are...
TAKS Objective 3. The student will demonstrate an understanding of the interdependence of organisms and the environment. 4C. ... According to this phylogenetic tree, which organism is most closely related to R? Which of the following explains this phenomenon? F...
Perception of consonant accuracy was most closely related to VOT for plosives, and moment 1 (mean) and moment 3 (skewness) for fricatives, affricates and plosives. Correct plosive consonant productions contained a normal range of VOT measures, however incorrect productions were...
* This table has six periods and 9 groups (families). You will most likely have your table with six families (same body type) and 9 periods. Notice that the number of fingers increases as you move from left to right....
MOBILE SOURCES 101 Presented by: Rob Klausmeier de la Torre Klausmeier Consulting, Inc Harold Garabedian Vermont Agency of Natural Resources Estimation of In-Use Emissions What will be covered: EPA's MOBILE model What are emission factor models Description of MOBILE6 How...
Ready to download the document? Go ahead and hit continue!