adaptive observations at nws

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Adaptive observations at NWS. Lacey Holland, SAIC at EMC/NCEP/NWS Zoltan Toth, EMC/NCEP/NWS. Acknowledgements: Dave Emmitt, Steve Lord, Sharan Majumdar, Jon Moskaitis, Craig Bishop. http://wwwt.emc.ncep.noaa.gov/gmb/targobs/. Outline. Introduction Targeting for WSR WSR Results - PowerPoint PPT Presentation

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Adaptive observations at NWS

Lacey Holland, SAIC at EMC/NCEP/NWS

Zoltan Toth, EMC/NCEP/NWS

http://wwwt.emc.ncep.noaa.gov/gmb/targobs/

Acknowledgements: Dave Emmitt, Steve Lord, Sharan Majumdar, Jon Moskaitis, Craig Bishop

Outline

• Introduction

• Targeting for WSR

• WSR Results

• Future Work

Winter Storm Reconnaissance (WSR)

• Based on collaborative research between university and gov’t agencies. EMC/NCEP/NWS established the program in 1999.

• Dropwinsonde observations taken over the Pacific by aircraft operated by NOAA’s Aircraft Operations Center (G-IV) and the US Air Force Reserve (C-130s).

• Observations are adaptive – collected only prior to significant winter weather events in areas that influence the forecast the most.

• Results show 60-80% improvement over forecast area

• Operational since January 2001

How WSR targeting

happens…

1. Targets selected in areas where critical winter weather events with high forecast uncertainty may have a potentially large societal impact.

2. Sensitivity calculations performed using ETKF, and a decision is made (flight/no flight).

3. Observations are taken and used in operational analysis and forecast products by major NWP centers.

4. Verification is performed by comparing operational analyses/forecasts including the targeted data with analyses/forecasts excluding the targeted data.

54 Predetermined Flight Tracks

Data Impact and Forecast Verification

Forecast improvement (red) and degradation (blue)

Data impact

48-hr verification

Flight track with initial

impact

Verification region with impact at

48-hrs

Estimated forecast error variance reduction with possible flight tracks

Results from previous years of WSR

Surface Pressure RMS Error

Vector Wind RMS Error

From Toth et al. (1999)

Data Impact – WSR 2000

Summary of WSR results

• Overall, biggest improvement in surface pressure over verification region for 2002-2003

• Winds and temperature from dropsondes have the most impact, followed by winds only and temperature only

• Dropsonde winds have greater positive impact than dropsonde temperatures in initial studies

Future Work

• Verify precipitation forecasts for all years of WSR; introduce new metric (storm track error)

• Continue collaboration with LIDAR group (Emmitt et al.) in support of Atlantic and Pacific TOST or other campaigns

• Test adaptive observations technique in OSSE environment, on global scales with simulated LIDAR measurements

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