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Precipitation in the Mediterranean region observed with TRMM microwave data

Precipitation in the Mediterranean region observed with TRMM microwave data. Martina Kästner & Jörg Steinwagner German Aerospace Center Applied Remote Sensing Cluster Oberpfaffenhofen, Germany. TRMM (Dec. 1997 – present) – NASA, NASDA. TRMM - Tropical Rainfall Measuring Mission. PR

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Precipitation in the Mediterranean region observed with TRMM microwave data

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  1. Precipitation in the Mediterranean region observed with TRMM microwave data Martina Kästner & Jörg Steinwagner German Aerospace Center Applied Remote Sensing Cluster Oberpfaffenhofen, Germany

  2. TRMM (Dec. 1997 – present) – NASA, NASDA TRMM - Tropical Rainfall Measuring Mission PR Precipitation Radar TMI TRMM microwave Imager VIRS Visible infrared Scanner CERES Clouds and Earth‘s Radiant system LIS Lightning imaging sensor

  3. TRMM TRMM = Tropical Rainfall Measuring Mission orbit in 400 km altitude inclination 35° • PR = precipitation radarTMI = TRMM Microwave Imager • Frequency 13.8 GHz 10.7, 19.4, 21.3, 37.0, 85.5 GHz • Swath 250 km 880 km • Horiz. resolution 5 km 5 to 70 km • Vert. resolution 250 m • Sensitivity 0.7 mm/h

  4. TRMM TMI brightness temperatures Spain 19 h North Africa 19 v 85 v

  5. Synoptic situation on 10 Nov 2001 trough > cut-off low > cyclogenesis

  6. common area: 15W ... 20E, 30N ... 60Ncommon grid, common period, common format 60° 50° 40° 40° 30°

  7. Correct negatives Retrieval 1 yes no yes hits misses no false correct alarms negatives Misses Hits Observed False alarms Retrieval 2 Retrieval 1 categorical statistics contingency table Retrieval 2 accuracy, bias sc., false alarm rate, probability of detection, threat sc., equivalent threat sc., Hansen-Kuipers- , Heidke skill score

  8. Intercomparisons • rain gauge • PMW • IR • combined MW/IR • mesoscale model • neural network • radar common grid (~28 km): ¼ deg lat x ¼ deg lon • PMW vs. PMW • PMW vs. combined MW/IR • PMW vs. BOLAM

  9. Intercomparison:PMW vs. PMW- different retrievals Spain PATER (P. Bauer, 2001) PR Adjusted TMI Estimation of Rainfall North Africa FDA_bham (TMI) (Ch. Kidd, 1998)frequency differencealgorithm visual inspection - subjective - all shown gridded precips are from 10 Nov. 2001, 03 UTCshown statistics are from all data (08 to 12 Nov. 2001)

  10. PMW vs. PMW statistics (8-12 Nov 2001) the best example N = 3.353 PATER PATER rain no rain FDA rain 84 297 FDA no rain 299 2673 accuracy = 0.82 bias score = 1.00 FDA FDA PATER similar quality, PATER-RR tend to higher values statistics driven by correct negatives PATER

  11. Combined (MW+IR) vs. PMW MW + IR combined (J. Turk) MW : PATER (P. Bauer) MW : FDA_bham (Ch. Kidd)

  12. model BOLAM vs. PMW BOLAM (A. Buzzi) MW MW : PATER (P. Bauer) MW : FDA_bham (Ch. Kidd)

  13. Correct negatives Misses False alarms Hits retrieval 2 retrieval 1 categorical statistics summary of all intercomparisons 0.25° grid N = 67 834 hits = 9 % misses = 15 % false alarms = 14 % corr. negatives = 62 % accuracy = 0.71 bias sc. = 0.96 far = 0.61 pod = 0.38 ts = 0.24 ets = 0.11 hk = 0.19 hss = 0.71

  14. Application: monthly mean precipitation Nov 2002 Jan 2003 Mar 2003 May 2003 PATER algorithm (PMW) 0.25° resolution ~ 28 km 0 20 40 60 80 100 mm/month

  15. Conclusion • Over the Mediterranean heavy rainfallevents occur several times a year • Need of improved weather forecasting of heavy rainfall • Need of rainfall data from over the sea -> satellites • Intercomparison of different satellite rainfall algorithms incl. model data,common grid = 0.25° (~28 km) • PMW techniques are directly related to 3-D structure of hydrometeors, but low revisit time; performance better over oceans than over land • IR techniques are widely used, but the physical relation of cloud top temperature and rain rate is weak; advantage: high revisit time • Combined techniques PMW and IR – TRMM 3B42, Turk, PERSIANN, etc. • Application of PATER PMW satellite rain retrieval:winter rain over the southern Mediterranean Seaand adjacent North Atlantic in high spatial resolution;seasonal changes in monthly mean precipitation • Step towards highly resolved precipclimatology over sea

  16. r = 0.71 n = 146 RR comparison - 1DD – 9-13 November 2001 Results Bauer approach PATER PR + TMI (AMW + PMW) Validation with 1DD GPCC data: r = 0.71 (n=146) Assessment: PIP-3 (Adler, 2002) best: r = 0.75 FAR – min detectable RR for PATER: 17 mm/d = 0.7 mm/h = 0.05 g/m³ lwc Outlook Combination IR +MW better cloud models

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