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LACE DA working days 14-16, June 2011 Budapest

LACE DA working days 14-16, June 2011 Budapest. X. Yan. outline. GPS data assimilation results DA experiment results comparison using old and new Bmatrix. EGVAP GPS network used for 2009 experiment. 2010: GPS stations used / Austria 40. ALST. MIST. ZIDF. ANDF. LINZ. LEOP. TRAI.

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LACE DA working days 14-16, June 2011 Budapest

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  1. LACE DA working days 14-16, June 2011 Budapest X. Yan

  2. outline (Präsentation) • GPS data assimilation results • DA experiment results comparison using old and new Bmatrix

  3. EGVAP GPS network used for 2009 experiment (Präsentation)

  4. 2010: GPS stations used / Austria 40 ALST MIST ZIDF ANDF LINZ LEOP TRAI AMST ATPU BADE NEUS WEYE SALZ MATT LIEZ MURZ OBER KIBG SHLA JENB SAAL SEEF LEOB ROET LAND MATR SHEI GRAZ SONN GUES OCHS TREI WOBG SILL LEIB GUMM KOET KLAF

  5. Scores for 2009 and 2010 (Präsentation) 14.09.2014 Folie 5 Scores on the upper air parameters for 2010 are generally better than 2009. Improvements on temperature of 700, 850 and 925hPa temperature were found. Humidity improved on 700hPa. Neutral impact on geopotential and wind. Precipitation score SAL showed a slightly improvement for the whole period. Slight better location score is found in general.

  6. Conclusion on case study (Präsentation) 14.09.2014 Folie 6 GPS brings very local but in most cases positive impact (Main feature still decided by first guess) In general, we observed that model tends to underestimate the amount of precipitation especially for the heavy precipitating events. The GPS assimilation experiments proved to have a positive impact on the intensity of precipitation in most of the case studies emphasizing the potential hidden in GPS data especially for extreme events forecast.

  7. Scores 2010 - Humidity GPS vs. Control (Präsentation) 14.09.2014 Folie 7 500hPa 700hPa 850hPa 925hPa

  8. upper air temperature bias20100520-20100629 GPS vs. Control 925hPa 850hPa 700hPa 500hPa

  9. (Präsentation) Case study 2009 : 062200-24h 14.09.2014 Folie 9 EGVAP REF OBS EGVAP + TU

  10. Case study 2009 : 070600-24h EGVAP REF OBS EGVAP + TU

  11. Bmatrix 35t1 vs. 32t1 (Präsentation) Ensemble method Bmatrix 35t1: Autumn Bmatrix 32t1: Winter-Spring

  12. Bmatrix 35t1 vs. 32t1 35t1 32t1

  13. Bmatrix 35t1 vs. 32t1 35t1 32t1

  14. Bmatrix 35t1 vs. 32t1 32t1 35t1

  15. Bmatrix 35t1 (red) vs. 32t1(blue) :surface score for 2010. 10 / 0-500m 2m temperature 2m relative humidity

  16. Bmatrix 35t1 (red) vs. 32t1(blue) :surface score for 2010. 10 / 500-1000m 2m temperature 2m relative humidity

  17. Bmatrix 35t1 (red) vs. 32t1(blue)surface score for 2010. 10 / 1000-1500m 2m temperature 2m relative humidity

  18. Bmatrix 35t1 (red) vs. 32t1(blue) surface score for 2010. 10 / mountain stations 2m temperature 2m relative humidity

  19. Bmatrix 35t1 (red) vs. 32t1(blue) :geopotential score for 2010. 10 925hPa 850hPa 700hPa 500hPa

  20. Bmatrix 35t1 (red) vs. 32t1(blue) :relative humidity score for 2010. 10 925hPa 850hPa 500hPa 700hPa

  21. Bmatrix 35t1 (red) vs. 32t1(blue)temperature score for 2010. 10 925hPa 850hPa 500hPa 700hPa

  22. Bmatrix 35t1 (red) vs. 32t1(blue) :wind score for 2010. 10 925hPa 850hPa 500hPa 700hPa

  23. conclusion (Präsentation) • The adding of GPS data and using of a new B matrix is not degrading the results, instead a slightly positive impact

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