1 / 32

GV for Taiwan ’ s precipitation retrieval research

GV for Taiwan ’ s precipitation retrieval research. Wann-Jin Chen Chung Cheng Institute Technology of National Defense University, Taiwan. Outline. Introduction Estimates of Rainfall using TMI data over the Ocean during Mei-Yu and Typhoon season

udell
Télécharger la présentation

GV for Taiwan ’ s precipitation retrieval research

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. GV for Taiwan’s precipitation retrieval research Wann-Jin Chen Chung Cheng Institute Technology of National Defense University, Taiwan

  2. Outline • Introduction • Estimates of Rainfall using TMI data over the Ocean during Mei-Yu and Typhoon season • Estimates of Rainfall using TMI data over the Land during Mei-Yu and Typhoon season • Ground Validation • Future work

  3. Two Heavy rainfall Season • Mei-Yu (Meso-scale convective systems), occurred during May and June. • Typhoon occurred during August through October. • Many natural disasters in Taiwan areas caused by the two weather systems, so the following studies were focused on them.

  4. Estimates of Rainfall using TMI data over the Oceanduring Mei-Yu season

  5. Methodology Match-up with TMI_Tb and Rain Gauge

  6. The regression of Multichannel during Mei-Yu season

  7. Typhoon SINLAKU GMS-2002-09-05_1400 TMI-2002-09-05_1407

  8. Quantification Validation during Mei-Yu season 1998~2001 18 points R2= 0.812

  9. Estimates of Rainfall using TMI data over the Oceanduring Typhoon season

  10. The regression over ocean

  11. Rainfall Rate (mm/hr) by Regression. #37769 (this study) Typhoon MINDULLE Rainfall Rate (mm/hr) by 2A12. Delta Rainfall Rate (mm/hr).

  12. Validation R=0.74, RMS=3.75 mm/hr, Bias: 0.68 (1.24%) , Points=66 (CO:25, ST:41) CO :● Convective ST : + Stratiform Average Rain Rate of Rain Gauge : 4.9 mm/hr. Average Rain Rate of Estimated : 5.6 mm/hr.

  13. Validation (2A12) R=0.45, RMS=5.76 mm/hr, Bias=2.52 (-0.29%), Points: 66

  14. Estimates of Rainfall using TMI data over the Landduring Typhoon season

  15. Data Collection The scan patterns and resolutions of TRMM sensors, including TMI, PR, and VIRS. The illustration is a scatter of ground rain gauge in Taiwan

  16. Scattering Index over Land( SIL ) Equation • Developing Scattering Index over Land( SIL ) equation for Taiwan land area. • Using TRMM/TMI 19.35V, 21.3V and 85.5V GHz channel. • Under non-scattering atmosphere conditions, that identified weather as cloud-free on Taiwan region with GOES-9 IR images.

  17. TMI data set used in the study.

  18. The Rainfall Retrievals over Land • The scatter diagrams of the SIL and Gauge Rain rate Gauge Rain rate (mm/hr) Sample:74 SIL(K) RR(rain rate) = 0.126 SIL 1.239

  19. *LRCT（Land Rainfall Retrieval by Chen and Tsai）

  20. Validating the Accuracy of Estimated Rainfall over land _TyphoonAERE(sample:23)

  21. Validating the Accuracy of Estimated Rainfall over land _TyphoonMINDULLE (sample:74)

  22. Error analysis : time difference • Satellite rainfall retrievals have a good result when comparing with rain gauge with 10 min. later after satellite overpass for the Mei-Yu cases.

  23. Over the land _ Mei-Yu Validating the Accuracy of Estimated Rainfall with QPESUMS Data ( -/+: before/after satellite overpass)

  24. RMS June May ( -/+: before/after satellite overpass ; ‘0’: same time )

  25. Correlation Coefficient June May ( -/+: before/after satellite overpass ; ‘0’: same time )

  26. Gauge Rain rate(mm/hr) Gauge Rain rate(mm/hr) Estimated Rainfall (mm/hr) Estimated Rainfall (mm/hr) The scatter diagrams of the estimated rainfall and the Gauge Rain rate Correlation Coefficient ：0.82 Correlation Coefficient ：0.81 Rainfall Retrievals derived from LRCT(2005) (left)， Ferraro (1994) (right) （ Black solid line is the regression line between Est.-RR and rain gauge RR, and the red solid line is for the equivalent values between them. ）

  27. Error analysis : terrain effect • Satellite rainfall retrieval underestimated on upsloping side of the mountain and overestimated on the downsloping side of the mountain.

  28. lee side facing wind side

  29. facing wind side lee side

  30. Future works • Improve rain gauge QC. • Develope more algorithms for other weather systems in Taiwan area. • Use more passive microwave radiometer sensors, like AMSR, AMSU in our algorithm. • Compare satellite rainfall retrievals with those derived from ground-based radar.

  31. The End !Thanks for your attention!

More Related