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A Combined IR and Lightning Rainfall Algorithm for Application to GOES-R

A Combined IR and Lightning Rainfall Algorithm for Application to GOES-R Robert Adler, Weixin Xu and Nai-Yu Wang University of Maryland. Goal: Develop and test a combined geo-IR and lightning rain algorithm for use with GOES-R [and also applicable with other types of lightning information].

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A Combined IR and Lightning Rainfall Algorithm for Application to GOES-R

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  1. A Combined IR and Lightning Rainfall Algorithm for Application to GOES-R Robert Adler, Weixin Xu and Nai-Yu Wang University of Maryland Goal: Develop and test a combined geo-IR and lightning rain algorithm for use with GOES-R [and also applicable with other types of lightning information] Xu, Weixin, R. Adler, Nai-Yu Wang, 2014: Combining Satellite Infrared and Lightning Information to Estimate Warm‐Season Convective and Stratiform Rainfall. J. Appl. Meteor. Climatol., 53, 180–199. Xu, Weixin, R. Adler, Nai-Yu Wang, 2013: Improving Geostationary Satellite Rainfall Estimates Using Lightning Observations: Underlying Lightning–Rainfall–Cloud Relationships. J. Appl. Meteor. Climatol., 52, 213–229.

  2. Approach • Utilize Tropical Rainfall Measuring Mission (TRMM) data (IR, Lightning, Passive Microwave and Radar) to develop and test an instantaneous rain estimation technique for use in deep convective situations. • Apply IR-based Convective-Stratiform Technique (CST; Adler and Negri, 1988). CST defines convective cores by Tb minima and adds stratiform rain through Tb threshold. • Use Lightning flash rate as additional information to CST to detect new convective cores, eliminate incorrect IR-defined cores, and estimate convective core rainfall rates. • Compare CST and CSTL against TRMM PMW and Radar rainrates to understand impact of Lightning information.

  3. How Is Lightning Observed by TRMM LIS? While GOES-R GLM continuously monitors lightning, TRMM LIS monitors a region (600 km) every 80-90s. Lightning events are in color

  4. IR-lightning Combined Algorithm Base Algorithm (Adler and Negri, 1988) IR-based Conv./ Strat. Technique (CST) Convective Area Stratiform Area Lightning Information Convective Rain Rates Stratiform Rain Rates

  5. Development and Evaluation Datasets (TRMM) Dependentset: 2002-2004 (1427 cases); Independentset: 2005-2008 (2009 cases); Warm season (May-Aug), Southern CONUS; Case criteria: > 5 flashes, every 800 by 800 km2. Lightning events are in color

  6. Convective/Stratiform Technique (CST) 2. 1. black outlines = convective areas from TRMM radar IRTb & local Minima (+) Convective Area Stratiform Area CST: 1. Find local Tb minima; Do slope (gradient) test; 2. Assign conv. area as a function of min Tb; 3. Assign rain rates for C/S. 3. Rain Rate

  7. Functions for Convective Core and Area Conv. cores and area defined by TRMM radar observations Red: Conv. Blue: Non-Conv. Conv. Area as a function of Tmin Slope Tb Area Slope test for Tb minima Convective cores or not? Tb

  8. Use of Lightning (CST+Lightning) 1. Remove convective cores not associated with lightning. 2. Define additional convective areas by lightning area. PMW (Passive MicroWave) (Conv/Strat 10 mm/hr) IR Tb Convective Area Stratiform Area CST (Conv/Strat) CST + Lightning (Conv/Strat)

  9. Statistics (2002-2008) on Convective Rain Area POD FAR CSI Lightning info. consistently improves the convective detection (POD) by 8%, lowers the false alarm (FAR) by 30%.

  10. Functions for Rainrate Assignment Convective RR Stratiform RR RR = 2.5 mm hr-1 RR as a function of Lightning Density • Based on: • Xu, Adler, and Wang, JAMC(2013)

  11. Instantaneous Rain Estimates (10 km res.) PR RR PMW RR CST RR CST+L RR

  12. Instantaneous Rain Estimates IR PMW RR CST RR CST+L RR

  13. Instantaneous Rain Estimates IR PMW RR CST RR CST+L RR

  14. Instantaneous Rain Estimates IR PMW RR NOAA Operational GOES IR Product CST RR CST+L RR

  15. Instantaneous Rainrate (20km res.) May 2007—Similar in other months CST vs. PMW CSTL vs. PMW

  16. Rainfall Statistics (20km res.) 2002-2008 May-August Corr. Coeff. vs. PMW BIAS and RMSE vs. PMW Lightning information clearly improves rainfall statistics

  17. Estimation of Rainfall Total (over 800x800 km2) Rain Volume over TRMM Scene CST vs. PMW CSTL vs. PMW

  18. Summary and Suggested Next Steps • Results indicate that satellite lightning information from GLM will be very valuable in improving GOES-based rain estimation. This comes from the use of lightning information to establish location of convective cores “unseen” by IR and eliminate incorrect cores defined by IR, and by flash rate-rain rate relations. • A GOES-R IR/Lightning algorithm should be fully developed and tested, building on the convective-stratiform separation concept, which takes advantage of strength of the GLM lightning data. • Geostationary-based rain estimates should be a part of an overall integrated precipitation analysis system using ground-based (radar, raingauge) and low-orbit merged microwave estimates to provide users with an integrated space-time best estimate. Xu, W., R. F. Adler, and N.-Y. Wang, 2014: Combining Satellite Infrared and Lightning Information to Estimate Warm Season Convective and Stratiform Rainfall. J. Appl. Meteor. Climatol.

  19. Example 1: Early Stage of Convective Systems IR PMW RR CST RR CST+L RR

  20. Estimates of Convective Precipitation Convective-Stratiform Separation IR Tb PR C/S Convective-Stratiform Separation Convective-Stratiform Separation CST C/S CST+L C/S

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