Leah Kos Sara Lavas Lauryn Gonzalez Mentor: Dr. Michael Douglas, NSSL.

Slides:



Advertisements
Similar presentations
Chapter 13 – Weather Analysis and Forecasting
Advertisements

AIRCRAFT METEOROLOGICAL DATA RELAY
NWS Meteorologists Guide to TAMDAR Weather Data The Great Lakes Fleet Experiment Fall 2004-Spring 2005.
Munehiko Yamaguchi Typhoon Research Department, Meteorological Research Institute of the Japan Meteorological Agency 9:00 – 12: (Thr) Topic.
Part 5. Human Activities Chapter 13 Weather Forecasting and Analysis.
Operational Forecasting and Sensitivity-Based Data Assimilation Tools Dr. Brian Ancell Texas Tech Atmospheric Sciences.
Transitioning unique NASA data and research technologies to the NWS 1 AIRS Products for the National Weather Service Brad Zavodsky SPoRT Science Advisory.
Acknowledgments Jennifer Fowler, University of Montana, Flight Director UM-BOREALIS Roger DesJardins, Canadian East Fire Region, Incident Meteorologist.
2012: Hurricane Sandy 125 dead, 60+ billion dollars damage.
Forecasting Weather After completing this section, students will analyze weather maps and the resulting regional weather (Standard PI – 061)
Using Scatterometers and Radiometers to Estimate Ocean Wind Speeds and Latent Heat Flux Presented by: Brad Matichak April 30, 2008 Based on an article.
Atmospheric Sciences 370 Observing Systems January 2007.
Weather Instruments.
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.
Dr Mark Cresswell Model Assimilation 69EG6517 – Impacts & Models of Climate Change.
Unit 4 Lesson 5 Weather Maps and Weather Prediction
20.5 Forecasting Weather Objectives
AMDAR Global Status, Benefits and Development Plans* WMO CBS ET Aircraft Based Observations Bryce Ford * Adapted from Presentation at WMO Congress XVII,
Using Ground-based Observations at NSSL Dr. David Turner (NSSL) February 25–27, 2015 National Weather Center Norman, Oklahoma non-radar ⌃ profiling ⌃
© TAFE MECAT 2008 Chapter 6(b) Where & how we take measurements.
Boundary Layer Targeted Observations using the Glidersonde Meteorological Package Part I: Description and Results Daniel B. Weber Frank W. Gallagher III.
Observations From the Global AMDAR Program Presentation to WMO TECO May 2005 by Jeff Stickland Technical Coordinator, WMO AMDAR Panel.
1 Short Course on Meteorological Applications of Aircraft Weather Data Introduction and Brief History January 14, 2007 David Helms
Global Observing System Simulation Experiments (Global OSSEs) How It Works Nature Run 13-month uninterrupted forecast produces alternative atmosphere.
Why We Care or Why We Go to Sea.
Evaluation of the WVSS-II Sensor Using Co-located In-situ and Remotely Sensed Observations Sarah Bedka, Ralph Petersen, Wayne Feltz, and Erik Olson CIMSS.
Meteorology What is it? How does it work? Meteorology in action!!
1 Results from Winter Storm Reconnaissance Program 2008 Yucheng SongIMSG/EMC/NCEP Zoltan TothEMC/NCEP/NWS Sharan MajumdarUniv. of Miami Mark ShirleyNCO/NCEP/NWS.
P1.7 The Real-Time Mesoscale Analysis (RTMA) An operational objective surface analysis for the continental United States at 5-km resolution developed by.
2006(-07)TAMDAR aircraft impact experiments for RUC humidity, temperature and wind forecasts Stan Benjamin, Bill Moninger, Tracy Lorraine Smith, Brian.
The National Oceanic and Atmospheric Administration (NOAA) is working to use Unmanned Aircraft Systems (UAS) to improve its ability to monitor the global.
Project goals Evaluate the accuracy and precision of the CO2 DIAL system, in particular its ability to measure: –Typical atmospheric boundary layer - free.
Predicting the Weather Section Forecasting Weather Collecting Data Direct Observations Use of instruments.
MADIS Airlines for America Briefing Meteorological Assimilated Data Ingest System (MADIS) FPAW Briefing Steve Pritchett NWS Aircraft Based Observations.
Autonomous Polar Atmospheric Observations John J. Cassano University of Colorado.
The Cost-Effectiveness of an Adaptive Radiosonde Observing Strategy for the United States Lauryn Gonzalez, Leah Kos and Sara Lavas Mentor: Dr. Michael.
Aviation Applications of Automated Aircraft Weather Data Examples from meteorologists in forecast offices Richard Mamrosh National Weather Service Green.
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,
WMO AMDAR Programme Overview Bryce Ford - presenting on behalf of WMO and NOAA FPAW Nov 1, 2012.
Comparison of Radiosonde and Profiler Data with ACARS Data for Describing the Great Plains Low-Level Jet Ross W. Bradshaw Meteorology Program, Dept. of.
CO-OPS Expands Meteorological Sensor Network and Quality Control Kathleen Egan, Tom Landon NOAA/NOS/Center for Operational Oceanographic Products and Services.
1 Short Course on Meteorological Applications of Aircraft Weather Data Future Plans – Opportunities for the Private Sector January 14, 2007 Kevin Johnston.
Atmospheric Sciences 370 Observing Systems January 2012.
The Over Forecast Advisory Event on St. Patricks Day Weekend 2013 NOAA’s National Weather Service Ron W. Przybylinski Science and Operations Officer Fred.
Gathering Weather Data Section Data From Earth ’ s Surface Meteorologists measure temperature, air pressure, wind speed, and relative humidity __________–
Weather Science and Airport Applications Jonathan Dutton 23 rd June 2015.
TAMDAR Status FPAW Forum November 11, The patented TAMDAR sensor Measures and derives: Ice presence Median and peak turbulence Winds aloft Indicated.
Atmospheric Sciences 370 Observing Systems Winter 2016.
Unit 4 Lesson 5 Weather Maps and Weather Prediction Copyright © Houghton Mifflin Harcourt Publishing Company.
Unit 4 Lesson 5 Weather Maps and Weather Prediction
The Course of Synoptic Meteorology
Upper Air Data The Atmosphere is 3D and can not be understood or forecast by using surface data alone.
New Unit! Climate Change.
Presentation on Weather Balloon
Aircraft weather observations: Impacts for regional NWP models
Weather Forecasting Lesson Objectives
Essential Questions Why is accurate weather data important?
Progress in Weather Observations
Hui Liu, Jeff Anderson, and Bill Kuo
Upper air Meteorological charts
The Course of Meteorological Instrumentation and Observations
Upper Air Data The Atmosphere is 3D and can not be understood or forecast by using surface data alone.
Weather Instruments.
Upper Air Observations The atmosphere is 3D and can not be understood or forecast by using surface data alone ATM 101W2019.
Airborne Weather Sensors
Marine Environment Radio-Sonde Verification of High Resolution Mesoscale MM5 Model Runs   OC 3570 Project By LCDR Jimmy Horne.
Weather Forecasting.
Predicting the Weather
The Course of Synoptic Meteorology
Presentation transcript:

Leah Kos Sara Lavas Lauryn Gonzalez Mentor: Dr. Michael Douglas, NSSL

 Determine cost and accuracy of current radiosonde network  Research adaptive strategies  Find cost and accuracy of adaptive strategies  Compile data to find best solution

 Adaptive Measurement Strategy: strategy that varies its spatial or temporal measurements to maximize its benefit-to-cost ratio

 NOAA keeps receiving a tight budget  NWS requested $988.0 M in FY 2012 ◦ Of this, + $5.0 M for GPS radiosondes  NWS requests $972.2 M for FY 2013 ◦ Will result in downsized programs

 Accuracy: ◦ Pressure Sensor: ± 0.5 mb ◦ Temperature Sensor: ± 0.2 ºC ◦ Humidity Sensor: ± 2.0 %  Cost: $325 per launch ◦ Price includes radiosonde, balloon and labor ◦ Totals to $21,827,000 a year  2 launches daily at 92 sites

 THORPEX (The Observing System Research and Predictability Experiment)  SUMO (Small Unmanned Meteorological Observer)  TAMDAR (Tropospheric Aircraft Meteorological Data Reports)

 What is it? ◦ International research program determining if targeted observations will improve forecasts of high- impact weather and short range forecasts  Accuracy? ◦ Target observations for tropical cyclones tracks are beneficial ◦ Value of data in continental areas are positive yet small ◦ Observations taken at target areas are more valuable than random areas  Good for? ◦ Test validity of observation sites over ocean and land ◦ Improve short range (1-3 day) forecasts

 What is it? ◦ Cost-efficient measurement system for understanding the 3-D structure of the atmospheric boundary layer ◦ Structure based off a commercial model airplane, has an autopilot system and sensors  Accuracy? ◦ Concerns include time lag induced errors ◦ Compared and verified with Vaisala RS92 Radiosonde

 Good For? ◦ Can be used in remote areas and under harsh environmental conditions ◦ Easy to handle, minimal infrastructures, “recoverable radiosonde”

 What is it? ◦ Consists of a sensor on aircraft, aircraft tracking, and computer processing ◦ Aircraft cruises at lower altitudes, below 500 hPa and flies into regional airports not serviced by AMDAR jets  Accuracy? ◦ Improves 3-hr RUC forecasts ◦ Reduces 3-hour forecast errors of: temperature by 0.4 K, wind by 0.25 m/s, and relative humidity by 3%

 Good For? ◦ Fills in the lack of data from AMDAR (water vapor and below 20,000 ft) ◦ Aids forecast accuracy by filling in the 12 hour gap between balloon launches

 Contacted meteorologists who: analyze data for legal and insurance claims, forecast for government and industry, specialize in air quality, forensic, and weather modification  Asked the following questions: 1.Does your company use radiosonde data? 2.Would more sounding data lead to a better forecast? How? 3.If less sounding data were given, how would that impact your profession?

 All use radiosonde data ◦ Use NWS data ◦ Focus on temperature and wind data  All would like more data ◦ Would help aid forecast and hindcast accuracy and improve resolution of upper level profile ◦ Adaptive network would help identify situations with large gradients of temperature or wind  Professions would all be negatively impacted

 What is your name?  What forecast office are you employed at?  What is your position at that forecasting office?  How many times per year does your office launch special radiosonde soundings?  What synoptic or mesoscale conditions are most often responsible for your launch of a special sounding?  Do you coordinate your special radiosonde observation soundings with other forecast offices?

 Would it be valuable to make occasional special soundings in locations different from the current NWS Radiosonde Observation Sites? Where might you like such soundings to be made that would likely add to your forecast area’s short-range forecast skill?  Any comments of the possible benefits (or problems with forecaster use) of special radiosonde observations on-demand at non-NWS sites? Any other thoughts related to possible adaptive observations would be welcomed

 Total: 86

 Most Common: ◦ Other (Pacific/Alaska): not enough data ◦ Eastern: tropical ◦ Western: severe weather ◦ Central: severe weather ◦ Southern: severe weather

 Related to non-NWS sites: ◦ Help to fill real time data gaps… more data the better for forecasting ◦ Good idea in theory but budget would not allow ◦ All schools with atmospheric science programs should be able to launch radiosondes ◦ Asynoptic/non-routine times ◦ Only helpful if forecasters aware of launch and can receive data easily into AWIPS/AWIPS II in a familiar format

 Related to adaptive network idea: ◦ Only launch when weather situation is in need of one to save money ◦ Budget issue again, but if could find an alternative to save money would be beneficial ◦ GPSMet sites from ESRL ◦ Collect data as radiosonde descends addition to the data as it ascends

 Compare cost-effectiveness of current and adaptive strategies  Further analyze the survey results  Determine best solution for fixed radiosonde budget