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Assimilating Moisture Information from GPS Dropwindsondes into the NOAA Global Forecast System

Assimilating Moisture Information from GPS Dropwindsondes into the NOAA Global Forecast System A NOAA/Joint Hurricane Testbed Project. Jason P. Dunion 1 and Sim D. Aberson 2 1 University of Miami/RMSAS/CIMAS-NOAA/AOML/HRD 2 NOAA/AOML/HRD. Motivation

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Assimilating Moisture Information from GPS Dropwindsondes into the NOAA Global Forecast System

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  1. Assimilating Moisture Information from GPS Dropwindsondes into the NOAA Global Forecast System A NOAA/Joint Hurricane Testbed Project Jason P. Dunion1 and Sim D. Aberson2 1 University of Miami/RMSAS/CIMAS-NOAA/AOML/HRD 2 NOAA/AOML/HRD

  2. Motivation Assessing atmospheric moisture and predicting its affect on TC intensity…no easy task. The NOAA GFS model does not currently assimilate humidity information from GPS dropsondes

  3. Project Objectives Year 1: • Perform parallel runs of the GFS model that assimilate dropsonde moisture information from NOAA G-IV missions • Begin assessing the impact of this data on GFS forecasts of TC track and intensity Year 2: • Perform detailed assessments of the impact of GPS dropsonde humidity data on GFS TC forecasts of track & intensity • Assess how effectively the GFS is able to represent dry layers such as the Saharan Air Layer • Assess the feasibility of performing targeted observations of humidity to improve GFS forecasts

  4. 2005 Atlantic Hurricane Season G-IV Missions: 10 TCs, 50 missions** **Note to self…pick an El Nino year next time**

  5. Project Methodology • In order to be assimilated into the GFS, GPS dropsondes must be transmitted in real - time from the aircraft • Run GFS parallel runs at lower resolution (T254) for Year 1 assessments • Compare T254 parallel runs with T254 operational runs for “apples to apples” comparisons

  6. Project Challenges • “Old dog new trick” syndrome: teaching a satellite guy how to run a global model • Setting up the code at NCEP to run the parallel GPS dropsonde humidity runs (never been done) • GFS parallel run forecast failures • -recently corrected bug in the radiation code: dry profiles…>…can generate bad profile temperatures…>…model bombs • -some runs still failing (e.g. Cindy and Dennis)

  7. Current Storm Catalogue Arlene; Emily, Irene; Katrina (12 NOAA G-IV missions) 26 25 24 21 19 16 14 11 8 4 # of cases

  8. Irene (08-09 September 2005)

  9. Katrina (25-27 August 2005)

  10. Drop #10 Drop #21 Drop #21 Drop #10 Hurricane Rita 22 Sept 2005 00 UTC G-IV Mission 050921n

  11. Impact of GPS Sonde Moisture on the GFS TS Irene 08 Aug 2005 0000 UTC

  12. Saharan Air Layer Experiment (SALEX) G-IV Mission 050807n Polar 1 10 15 SAL 3 SAL 2 5 1 SAL 1 Irene Drop #19 Drop #19 20 AEW 1 25 Drop #2

  13. Summary of Findings • Humidity information from G-IV GPS dropsondes can significantly affect the T254 GFS (EMC was smart no to just throw the switch) • Early results: the GPS dropsonde humidity data doesn’t have a strong negative OR positive impact on GFS forecasts of track/intensity • For some individual cases (e.g. Irene and Katrina), the GPS dropsonde humidity information had a significant impact on the GFS track forecast • The GFS analysis of humidity appears to be significantly affected by the GPS dropsonde humidity. This difference appears to grow with successive forecast times.

  14. Future Work • Continue running the remaining 2005 cases • Test the impact of the GFS operational vs GPS dropsonde humidity fields on SHIPS (GFDL?) intensity forecasts • Assess whether targeted observing strategies can optimize GPS dropsonde humidity impacts on the GFS

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