Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Nearcasting Severe Convection.

Slides:



Advertisements
Similar presentations
Chapter 13 – Weather Analysis and Forecasting
Advertisements

The Utility of GOES-R and LEO Soundings for Hurricane Data Assimilation and Forecasting Jun Timothy J. Schmit #, Hui Liu &, Jinlong and Jing.
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.
1 GOES Users’ Conference October 1, 2002 GOES Users’ Conference October 1, 2002 John (Jack) J. Kelly, Jr. National Weather Service Infusion of Satellite.
UW-CIMSS/UAH MSG SEVIRI Convection Diagnostic and Nowcasting Products Wayne F. Feltz 1, Kristopher M. Bedka 1, and John R. Mecikalski 2 1 Cooperative Institute.
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,
1 High impact weather nowcasting and short- range forecasting with advanced IR soundings Jun Tim Schmit &, Hui Liu #, Jinlong Jing
Improving Severe Weather Forecasting: Hyperspectral IR Data and Low-level Inversions Justin M. Sieglaff Cooperative Institute for Meteorological Satellite.
GOES-R Proving Ground NOAA’s Hazardous Weather Testbed Chris Siewert GOES-R Proving Ground Liaison OU-CIMMS / Storm Prediction Center.
Chapter 13 – Weather Analysis and Forecasting. The National Weather Service The National Weather Service (NWS) is responsible for forecasts several times.
Recent Progress on High Impact Weather Forecast with GOES ‐ R and Advanced IR Soundings Jun Li 1, Jinlong Li 1, Jing Zheng 1, Tim Schmit 2, and Hui Liu.
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.
GOES-R Synthetic Imagery over Alaska Dan Lindsey NOAA/NESDIS, SaTellite Applications and Research (STAR) Regional And Mesoscale Meteorology Branch (RAMMB)
Introduction and Methodology Daniel T. Lindsey*, NOAA/NESDIS/STAR/RAMMB Louie Grasso, Cooperative Institute for Research in the Atmosphere
1 Tropical cyclone (TC) trajectory and storm precipitation forecast improvement using SFOV AIRS soundings Jun Tim Schmit &, Hui Liu #, Jinlong Li.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Long-Term Upper Air Temperature.
1 CIMSS Participation in the Development of a GOES-R Proving Ground Timothy J. Schmit NOAA/NESDIS/Satellite Applications and Research Advanced Satellite.
GOES-R ABI PROXY DATA SET GENERATION AT CIMSS Mathew M. Gunshor, Justin Sieglaff, Erik Olson, Thomas Greenwald, Jason Otkin, and Allen Huang Cooperative.
Thanks also to… Tom Wrublewski, NOAA Liaison Office Steve Kirkner, GOES Program Office Scott Bachmeier, CIMSS Ed Miller, NOAA Liaison Office Eric Chipman,
IMPROVING VERY-SHORT-TERM STORM PREDICTIONS BY ASSIMILATING RADAR AND SATELLITE DATA INTO A MESOSCALE NWP MODEL Allen Zhao 1, John Cook 1, Qin Xu 2, and.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Precipitation and Flash Flood.
Objective Nowcasting Development What is our goal? Forecasters now use GOES imagery and Derived Product Imagery (DPI) to monitor weather – and make subjective.
Chapter 9: Weather Forecasting Acquisition of weather information Acquisition of weather information Weather forecasting tools Weather forecasting tools.
PLANS FOR THE GOES-R SERIES AND COMPARING THE ADVANCED BASELINE IMAGER (ABI) TO METEOSAT-8 UW-Madison James J Gurka, Gerald J Dittberner NOAA/NESDIS/OSD.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Image: MODIS Land Group,
Advanced Baseline Imager (ABI) will be flown on the next generation of NOAA Geostationary Operational Environmental Satellite (GOES)-R platform. The sensor.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 POES Microwave Products Presented.
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 Improving Hurricane Intensity.
The Need for an Advanced Sounder on GOES The Numerical Weather Prediction Perspective Robert M. Aune Center for Satellite Applications and Research, NESDIS.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Infrared Temperature and.
1 Hyperspectral Infrared Water Vapor Radiance Assimilation James Jung Cooperative Institute for Meteorological Satellite Studies Lars Peter Riishojgaard.
1 Using water vapor measurements from hyperspectral advanced IR sounder (AIRS) for tropical cyclone forecast Jun Hui Liu #, Jinlong and Tim.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Satellite Wind Products Presented.
Hyperspectral Infrared Alone Cloudy Sounding Algorithm Development Objective and Summary To prepare for the synergistic use of data from the high-temporal.
Linear Optimization as a Solution to Improve the Sky Cover Guess, Forecast Jordan Gerth Cooperative Institute for Meteorological Satellite Studies University.
Transitioning unique NASA data and research technologies to the NWS AIRS Profile Assimilation - Case Study results Shih-Hung Chou, Brad Zavodsky Gary Jedlovec,
High impact weather studies with advanced IR sounder data Jun Li Cooperative Institute for Meteorological Satellite Studies (CIMSS),
Studies of Advanced Baseline Sounder (ABS) for Future GOES Jun Li + Timothy J. Allen Huang+ W. +CIMSS, UW-Madison.
Extending Geostationary Satellite Retrievals from Observations into Forecasts Using GOES Sounder Products to Improve Regional Hazardous Weather Forecasts.
Transitioning unique NASA data and research technologies to the NWS 1 In-House Utilization of AIRS Data and Products for Numerical Weather Prediction Will.
The Hyperspectral Environmental Suite (HES) and Advanced Baseline Imager (ABI) will be flown on the next generation of NOAA Geostationary Operational Environmental.
Layered Water Vapor Quick Guide by NASA / SPoRT and CIRA Why is the Layered Water Vapor Product important? Water vapor is essential for creating clouds,
SPoRT’s Current and Planned Data Assimilation Activities Inaugural SPoRT/NWS Collaborative Partners Workshop 3-4 March 2010 Bradley Zavodsky Shih-Hung.
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.
Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Image: MODIS Land Group,
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.
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.
GOES-R ABI AS A WARNING AID Louie Grasso, Renate Brummer, and Robert DeMaria CIRA, Fort Collins, CO Dan Lindsey, Don Hillger, NOAA/NESDIS/RAMMB, Fort Collins,
Assimilating Cloudy Infrared Brightness Temperatures in High-Resolution Numerical Models Using Ensemble Data Assimilation Jason A. Otkin and Rebecca Cintineo.
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.
A. FY12-13 GIMPAP Project Proposal Title Page version 26 October 2011 Title: WRF Cloud and Moisture Verification with GOES Status: New GOES Utilization.
Atmospheric Motion Vectors - CIMSS winds and products (
Extending Geostationary Satellite Retrievals from
GOES visible (or “sun-lit”) image
NWS Forecast Office Assessment of GOES Sounder Atmospheric Instability
Tony Wimmers, Wayne Feltz
Geostationary Sounders
Hyperspectral Wind Retrievals Dave Santek Chris Velden CIMSS Madison, Wisconsin 5th Workshop on Hyperspectral Science 8 June 2005.
Generation of Simulated GIFTS Datasets
CRAS Forecast Satellite Imagery Input to AWIPS
Presentation transcript:

Center for Satellite Applications and Research (STAR) Review 09 – 11 March 2010 Image: MODIS Land Group, NASA GSFC March 2000 Nearcasting Severe Convection Using the GOES Sounder Robert M. Aune Scott S. Lindstrom Robert M. Aune Scott S. Lindstrom

VISITview Teletraining 2 Requirement, Science, and Benefit Requirement/Objective Mission Goal: Weather and water –Increase lead time and accuracy for weather and water warnings and forecasts –Improve predictability of the onset, duration, and impact of hazardous and severe weather and water events –Increase development, application, and transition of advanced science and technology to operations and services Science Can observations from a geostationary IR sounder be used to predict severe weather outbreaks 1 to 6 hours in advance, filling the gap between radar nowcasts and NWP models? Benefits Reduce loss of life, injury and damage to the economy Better, quicker, and more valuable weather and water information to support improved decisions Increased customer satisfaction with weather and water information and services

VISITview Teletraining Nearcasting uses GOES Sounder Data The GOES Sounder includes three separate water vapor channels The water vapor channels have weighting functions that peak in different parts of the troposphere (longer wavelengths see farther down into the atmosphere) Therefore have a three-dimensional look at atmospheric moisture 3

VISITview Teletraining 4

5

6

7

8

9

10

VISITview Teletraining 11

VISITview Teletraining 12

VISITview Teletraining 13 Premise: Sounder gives information on distinct layers in atmosphere at observation time Winds from a numerical model can move those slabs of moisture around Question: Where does Convective Instability develop because of the moving slabs? Very Moist Layer Somewhat Moist Layer Very Dry Layer

VISITview Teletraining How is nearcasting done? Data Data include winds and sounder observations of  e and  e that has moved to a point at time=0 and geopotential heights at t=0, 3 and 6h obs time increasing fcst time increasing Start at an initial time. Use a Lagrangian model. Step forward 6 hours. Output hourly forecasts

VISITview Teletraining 15 Nearcasting Severe Convection Using the GOES Sounder Research description –The GOES sounder can provide hourly snapshots of layer-averaged stability parameters. These observations can be assimilated at multiple levels using a simple approach to provide fast, short-term projections of atmospheric stability. Recent science accomplishments (~FY08 to present) –In collaboration with CIMSS, a Lagrangian approach was selected that moves the GOES observations along forward trajectories. Observation error growth remains small to 4 hours and beyond. –GOES sounder retrieved parameters such as equivalent potential temperature (Theta-E) at 750hPa and 500hPa are projected forward 6 hours. Destabilization is indicated when Theta-E 500 (5800m) minus Theta-E 750 (2500m) becomes negative. –The nearcasting model has been tested in real time at CIMSS using the GOES-12 sounder. Products are displayed on the internet ( –Hourly nearcasts are currently being transmitted to NWS Central Region AWIPS for evaluation. –Product will be evaluated at the NWS Storm Prediction Center’s Spring Experiment in May 2010.

VISITview Teletraining 16 Filling the Guidance Gap and Atmospheric Stability Basics 3hr Model Forecast Valid 1700 UTC 7/2/08 Verification 7/2/ UTC Radar 2hr Model Forecast Valid 1700 UTC 7/2/08 The Guidance Gap Very-short-range NWP precipitation forecasts often either: 1) miss significant moisture features 2) have difficulty with exact position and timing of events / phenomena Fill the Gap Between Nowcasting & NWP hours Max Precipitation Axis To detect the development of areas becoming convectively unstable, we need to monitor not only the increase of low level moisture, but areas where low-level moistening and upper-level drying overlap The GOES sounder can detect water vapor at 2-3 layers in a clear atmosphere. Gradients of water vapor can be tracked using multiple GOES sounder scans. Upper level drying over lower level moistening conditions lead to autoconvection. When the layer is lifted the inversion bottom cools less than top and it becomes absolutely unstable If moisture is present in the stable layer and the entire layer is lifted, it can become unstable.

VISITview Teletraining 17 Lagrangian Nearcasting Approach GOES hPa precipitable water analysis valid 21 UTC 13 April 2006 How it works NWP models use randomly spaced moisture observations interpolated on to a fixed grid, and use gridded wind data to advect the moisture information forward in time at fixed grid points. This process smooths horizontal gradients. O Dry Moist Dry Moist GOES hPa precipitable water retrievals valid 00 UTC 14 April 2006 O The Lagrangian approach interpolates wind data to each observation location (~10km spacing) which is then projected forward to a new location forced by dynamically changing wind forecasts. A relatively long time step (10 min) can be used. The new data locations are then transferred back to a regular grid. Starting locationNew location 0-hour Nearcast 3-hour Nearcast

VISITview Teletraining 18 Nearcasts of Severe Weather Low-level Theta-E nearcasts shows warm moist air band moving into far NW Iowa by 2100 UTC. Vertical Theta-E Differences predict complete convective instability by 2100 UTC. 6-hour NearCast for 2100 UTC Mid - Low level Theta-E Differences 6-hour NearCast for 2100 UTC Low level Theta-E Radar indicates rapid development of convection over NW Iowa between 2000 and 2100 UTC, 9 July Correct shape is indicated. 4-hour nearcast of precipitable water lapse rate (mm differences) near Oklahoma City valid 22UTC Feb 10, De-stabilization potential is indicated. Oklahoma City tornado De-stabilization predicted by nearcast

VISITview Teletraining 19 Evaluation by NWS Forecast Office, Sullivan, Wisconsin CIMSS nearcast products are currently being inserted into the operational AWIPS data stream for NWS evaluation. CIMSS precipitable water lapse rate product valid 15UTC April 13, NWS Milwaukee is evaluating the CIMSS precipitable water nearcasting product. The example below shows a good relationship between amount of convective clouds (or lack of them) and strong vertical gradients of PW. 1-hour nearcast of vertical precipitable water differences (mm) valid 19 UTC, July 2, Visible image for 19 UTC, July 2, Red indicates where convection is likely. Black indicates areas where convection is not likely. Same CIMSS nearcast product displayed on an AWIPS workstation.

VISITview Teletraining 20 Challenges and Path Forward Continuing science challenges –Current GOES sounders cannot see low-level temperature inversions and dryness which leads to false alarms –Accurate mesoscale wind information is needed to initialize trajectories Next steps –Assimilate additional products from the GOES sounder to determine which is the best indicator of de-stabilization –Perform Observing System Simulation Experiments (OSSEs) to determine the impact of using a hyperspectral sounder Path into applications/operations –Evaluation at NWS forecast office has commenced (AWIPS, webpage) –Evaluation at Storm Prediction Center Severe Weather Test Bed to commence May, 2010 (supported by GOES-R Risk Reduction)

VISITview Teletraining 21 Nearcasting Severe Weather using a Hyperspectral Environmental Sounder (HES) A WRF model simulation of the June 12, 2002 IHOP case was used to generate simulated radiances from an Advanced Baseline Imager (ABI), a geostationary Hyper-spectral Environmental Sounder (HES), and simulated radar reflectivity. Temperature and moisture profiles were retrieved from the radiance datasets and assimilated by the CIMSS Nearcasting Model and compared. Detailed Theta-E gradients were resolved by HES. 5-hour NearCast for 2000 UTC Low level Theta-E 5-hour NearCast for 2000 UTC Low to Mid level Theta-E Differences Rapid Development of Convection over Texas and Nebraska between 2000 and 2100 UTC 12 June 2002 Strong low-level Theta-E gradients are indicated by HES which has the ability to detect low-level moisture. 5-hour NearCast for 2000 UTC Low to Mid level Theta-E Differences 5-hour NearCast for 2000 UTC Low level Theta-E Weak gradients of low-level Theta-E are indicated by ABI which has only two water vapor channels. Simulated composite reflectivity from nature run indication the formation of convection. Simulated ABI Simulated HES