An Update on Regional Profile Assimilation and Near-Real-Time - - PowerPoint PPT Presentation

an update on regional profile assimilation and near real
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An Update on Regional Profile Assimilation and Near-Real-Time - - PowerPoint PPT Presentation

Science Mission Directorate UAH UAH UAH National Aeronautics and Space Administration An Update on Regional Profile Assimilation and Near-Real-Time Modeling Plans Brad Zavodsky University of Alabama in Huntsville Huntsville, Alabama


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SLIDE 1

Science Mission Directorate

National Aeronautics and Space Administration

transitioning unique NASA data and research technologies to the NWS

UAH UAH UAH

An Update on Regional Profile Assimilation and Near-Real-Time Modeling Plans

Brad Zavodsky

University of Alabama in Huntsville Huntsville, Alabama

Shih-hung Chou, Gary Jedlovec, & Bill Lapenta

NASA / Marshall Space Flight Center Huntsville, Alabama

AIRS Science Team Meeting – September 2006

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SLIDE 2

Science Mission Directorate

National Aeronautics and Space Administration

transitioning unique NASA data and research technologies to the NWS

UAH UAH UAH

Outline

  • Motivation
  • Overview of Previous AIRS Science Team

Meeting Presentations

  • New Results from Assimilation/Forecasting Work
  • Near-Real-Time (NRT) AIRS Assimilation
  • Brief Discussion
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SLIDE 3

Science Mission Directorate

National Aeronautics and Space Administration

transitioning unique NASA data and research technologies to the NWS

UAH UAH UAH

Motivation

  • AIRS data complements traditional upper-air
  • bservations in data sparse regions (e.g. ocean).
  • Hyperspectral nature of AIRS sounder allows

for highest vertical resolution of any current remote sensing system

  • In-house computing resources at SPoRT are

currently not able to handle radiance assimilation

  • Level-II profiles provide a straightforward

method for obtaining information in data-void regions without running complex RTA

  • Profiles are easier to handle than radiances in a

NRT environment

Sample swath of AIRS data with prototype V5.0 quality indicators

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SLIDE 4

Science Mission Directorate

National Aeronautics and Space Administration

transitioning unique NASA data and research technologies to the NWS

UAH UAH UAH

Summary of Recent Results

  • ADAS configured to optimally assimilate AIRS thermodynamic profiles

intelligently using quality indicators (QIs) to determine largest volume of highest quality data

  • Short WRF forecast used as background for ADAS analysis (previously initialized

with GFS, but discussing moving to the NAM), WRF produced 65-h forecasts

  • Two case studies: west coast (V4.0, Jan. 2004) and east coast (prototype V5.0,
  • Nov. 2005)
  • Impact in temperature and moisture analyses in region of AIRS data
  • Overall positive impact on temperature and moisture forecasts with the inclusion
  • f AIRS profiles
  • Prototype V5.0 data reduced bias and RMSE of temperature and moisture in

forecasts when compared to RAOBs—improvements in RTA and QC

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SLIDE 5

Science Mission Directorate

National Aeronautics and Space Administration

transitioning unique NASA data and research technologies to the NWS

UAH UAH UAH

Case Study: November 20-22, 2005

  • WRF domain covers most of

CONUS—similar domain to be used for testing NRT

  • Rapidly intensifying storm in region

relevant to SPoRT interests

  • Under forecasted by operational models

at storm’s strongest point—potential impact

  • Ample verification data available over the

Eastern US (minimal terrain issues)

Surface analysis 11/22/05 12 UTC Surface analysis 11/22/05 12 UTC Surface analysis 11/20/05 12 UTC Surface analysis 11/20/05 12 UTC Surface analysis 11/21/05 12 UTC Surface analysis 11/21/05 12 UTC

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WRF Domain for November 2005 Case Study

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SLIDE 6

Science Mission Directorate

National Aeronautics and Space Administration

transitioning unique NASA data and research technologies to the NWS

UAH UAH UAH

53h Forecast Impact—Mean Sea Level Pressure

Valid at 1200 UTC 22 November 2005

  • Low pressure area deepens by more than 4 hPa with inclusion of AIRS data
  • Storm center shifts slightly to the south and west
  • Both alterations are improvements over the control when compared to surface analysis

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SLIDE 7

Science Mission Directorate

National Aeronautics and Space Administration

transitioning unique NASA data and research technologies to the NWS

UAH UAH UAH

41h Forecast Impact—6h Cumulative Precipitation

Valid at 0000 UTC 22 November 2005 Valid at 0000 UTC 22 November 2005

  • Subtle precipitation coverage

difference between control & AIRS

  • AIRS seems to better forecast

intensity (MD/DE/VA)

0.1 0.2 0.3 0.4 0.5 0.6 0.254 0.635 1.588 3.175 4.763 6.350 9.525 12.70 Minimum Precipitation Threshold (mm) Equitable Threat Score 0.5 1 1.5 2 2.5 3 3.5 4 Bias Score NO AIRS-ETS ALL AIRS_ETS NO AIRS-bias ALL AIRS_bias

  • ETS for AIRS case similar to or

better than the control

  • AIRS case bias score

comparable to control

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SLIDE 8

Science Mission Directorate

National Aeronautics and Space Administration

transitioning unique NASA data and research technologies to the NWS

UAH UAH UAH

  • Single case studies are not necessarily representative (statistically significant) of
  • verall model performance
  • Twice daily model runs (AM and PM) for a contiguous period
  • Initial sensitivity study using over water soundings (latest prototype V5.0) will help

determine optimal data set for later NRT assimilation:

  • CNTL: control; use no AIRS data
  • NOQC: use all AIRS data without regard for QIs
  • BEST: use only full soundings
  • ALLW: use QIs to select the highest quality data

NRT Assimilation

  • Troubleshoot process, determine case studies,

and provide results for a journal article

L

  • Date, time, and location of AIRS data will control which data are used and will

run system from pre- through postprocessing

Looking for cases like this

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SLIDE 9

Science Mission Directorate

National Aeronautics and Space Administration

transitioning unique NASA data and research technologies to the NWS

UAH UAH UAH

  • NAM is run 4 times daily with a lag time of ≈ 2 hours; ≈ 3 hours for 0-48 hour forecasts
  • 1-hr WRF forecasts can be completed in 30 seconds; 48-hr forecast can be completed

in under 9 minutes using full capabilities of our cluster

  • Preprocessing of AIRS profiles into ADAS format takes ≈ 5 minutes
  • Assimilation of AIRS profiles in current configuration takes ≈ 10 minutes
  • Time lag of AIRS data processing—how long after observation time until data are

available? Ideally, we would like AIRS data to be available ≤ 2 hours after valid time*

0600 UTC

Desired initialization time

1200 UTC 0900 UTC

WRF forecast complete as next NAM forecast cycle begins NAM data available 1st AIRS valid 2nd AIRS valid

NRT Assimilation

0700 analysis complete WRF bkgd ready for 0700 ADAS 1st AIRS available* 2nd AIRS available* WRF bkgd ready for 0900 ADAS 0900 analysis complete

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SLIDE 10

Science Mission Directorate

National Aeronautics and Space Administration

transitioning unique NASA data and research technologies to the NWS

UAH UAH UAH

  • Verification at 6-hour intervals at each grid point using analyses (F00)

collocated in time to calculate bias and RMSE for:

  • temperature, specific humidity, height, MSLP, winds
  • Verification at 3-hour intervals in each grid box using extrapolated NCEP

Stage IV precipitation data to calculate equitable threat scores and bias scores for:

  • 6h and 24h cumulative precipitation totals
  • Time series of MSLP for the forecast period for each case against METAR

data along the east coast

  • If month-long set of cases yields extra-tropical cyclone events, storm tracks

between the various model runs and observations can be compared

  • Results will be posted daily on the SPoRT website after forecast run to track

the statistics

Verification of Forecast Impact

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SLIDE 11

Science Mission Directorate

National Aeronautics and Space Administration

transitioning unique NASA data and research technologies to the NWS

UAH UAH UAH

Conclusions/Wrap-Up

  • Improvements in temperature, moisture, MSLP, and

precipitation fields at various forecast times with addition of AIRS profiles for one case study

  • More thorough assessment through extended NRT study
  • AIRS Level-II thermodynamic profiles are desired in NRT

with less than 2 hours lag for continued research

  • We would like to test our system with at least a month of

NRT prototype V5 data prior to the official V5 release

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SLIDE 12

Science Mission Directorate

National Aeronautics and Space Administration

transitioning unique NASA data and research technologies to the NWS

UAH UAH UAH

Supplemental Slides

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SLIDE 13

Science Mission Directorate

National Aeronautics and Space Administration

transitioning unique NASA data and research technologies to the NWS

UAH UAH UAH

Date Algorithm to determine time/location of AIRS overpasses Obtain NAM Short WRF forecast Preprocess AIRS profiles ADAS Last AIRS swath?

No: initialize another short WRF forecast Yes: run 48h WRF forecast

WRF postprocessing