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TC Intensity Estimation From Satellite Microwave Sounders Derrick Herndon and Chris Velden International Workshop on Satellite Analysis of Tropical Cyclones.

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Presentation on theme: "TC Intensity Estimation From Satellite Microwave Sounders Derrick Herndon and Chris Velden International Workshop on Satellite Analysis of Tropical Cyclones."— Presentation transcript:

1 TC Intensity Estimation From Satellite Microwave Sounders Derrick Herndon and Chris Velden International Workshop on Satellite Analysis of Tropical Cyclones Honolulu, HI April 2011 University of Wisconsin - Madison Cooperative Institute for Meteorological Satellite Studies Jeff Hawkins Naval Research Laboratory Monterey, CA Research sponsors: the Oceanographer of the Navy through the program office at the PEO C4I&Space/PMW-120, under program element PE N and the Office of Naval Research under program element PE N

2 Flown aboard NOAA 15-19, METOP and Aqua 2 Instruments: AMSU-A (temperature), AMSU-B (moisture) Primary channels of interest are 5-8 on AMSU-A which measure upper-level warm core temperature anomalies that can be directly related to TC intensity The Advanced Microwave Sounding Unit -- AMSU Pressure Longitude AMSU-A Atmos Contribution Functions Result: AMSU-A Tb Anomaly Cross-Section AMSU-A Tb Ch 8 Ch 7 Ch 6 Ch 5 Height (km) ~150 hPa ~250 hPa ~400 hPa ~600 hPa

3 Relationship Between AMSU T b Anomaly and TC MSLP Channel 8 Tb anomalies ( mb) versus collocated and coincident recon MSLP measurements Sources of Relationship Spread Hydrometeor scattering (cooling) near TC core FoV resolution issues related to TC core size Juxtaposition of TC core relative to nearest FoV positions Pressure (mb) Tb Anomaly (K)

4 Field of View (FoV) resolution varies across the scan swath due to the instruments cross-track scanning strategy Best spatial resolution at nadir is ~50km Spatial resolution variability needs to be taken into account relative to the TC core position in the swath. A TC core-sized warm anomaly viewed at 50km will be better resolved then at 80km. AMSU Sensor Characteristics FOV 1FOV km80km Nadir Limb

5 AMSU Sensor Characteristics Precipitation Effects Hydrometeor scattering Corrected Radiative scattering due to eyewall hydrometeors can act to cool the Tb signal and mask the true warm core signal, especially for channels 6 and 7. The result is an underestimate of intensity. This contamination can be mitigated by comparing AMSU-A ch. 2 and 15 and then applying a statistical correction to ch. 4-8 TC core

6 (mb) (K) Precip Correction – Example: Channel 6

7 AMSU Sensor Characteristics: Sub-Sampling Issues Near Limb Footprint Nadir Footprint Compare to AMSU Footprint Eye Size (~2 x RMW) Adjust AMSU estimated pressure, if needed Eye size is used as a proxy for warm core size

8 AMSU FOV AMSU: Sub-Sampling Issues ADT (IR) AMSU FOV ARCHER (MW) Primary source of eye size: microwave estimate from ARCHER, if available If ARCHER not available then use IR estimate from ADT If neither is available use latest OFC estimate (ATCF)

9 Developing the Relationship Between AMSU T b and MSLP For channels 6/7/8, separate well-resolved cases out from the sub-sampled cases to develop the final regression relationships Pressure (mb) Tb Anomaly (K) Well-resolved cases Sub-sampled cases

10 Developing the Relationship Between AMSU Tb and MSLP Summary Apply scattering correction to Tbs Remove sub-sampled cases Regress Tb to MSLP anomaly for each channel and use relationships for initial estimates of MSLP anomaly CH 6 CH 7 CH 8

11 Storm center may fall between nearest AMSU FOV centers (Bracketing Effect) Results in sub-sampling of the warm core Use convolved AMSU-B moisture channels to assess Adjust MSLP (only applied if initial MSLP est < 995 mb) TC center between nearest FOVs AMSU-B 89 Ghz Tb shows adjustment to AMSU TC estimate is necessary TC center is well-centered on FOV AMSU-B 89 Ghz indicates no adjustment needed AMSU: Another Sub-Sampling Issue Ch 16 – 89Ghz

12 Relationship used to Adjust MSLP Estimate if Bracketing Effect Noted

13 AMSU-A in center - no correction AMSU-A partially in eyewall - apply correction Eye smaller than AMSU-A FOV, - apply correction Iris 2001: Core is very small and nearest AMSU-A FOV is in moat. Signal suggests (incorrectly) that no correction is required. Examples

14 Start with regressions based on well-resolved cases and estimate pressure anomaly for each channel Use a weighted average of each channels pressure anomaly contribution to get the final pressure anomaly Make corrections for position within the scan swath (distance from nadir) Apply AMSU-B 98 Ghz Tb correction to account for bracketing Use estimated eye size to correct for sub-sampling due to resolution Developing the Relationship Between AMSU Tb and MSLP

15 Start by removing storm motion component from the dependent sample validation (Best Track) MSW sample (1-min sust. wind) Regress storm-relative MSW against AMSU-measured MSLP anomaly Make situational corrections for T b gradient of inner core, latitude, momentum transfer Once all corrections are applied, add storm motion (from BT or ATCF in real time) to AMSU MSW estimate AMSU MSW represents a 1-min sust. max sfc wind AMSU: Max Sfc Winds (MSW) Estimation

16 Inner core gradient contribution to MSW estimate Tight warm core Warm core expanding AMSU Ch7 for Hurricane Isabel 2003 AMSU: MSW Estimation

17 Account for momentum transfer Locate strongest 89 Ghz gradient within 150 km of center AMSU 89Ghz for Hurricane Wilma 2005 Decreased MSW from convective component AMSU: MSW Estimation

18 AMSU: Performance N = 727 AMSU MSLP Dvorak MSLP AMSU MSW Dvorak MSW BIAS AVG ERROR RMSE Dependent Sample MSLP in hPa, MSW in Kts Validation is recon-measured central pressure within 3 hours of AMSU pass for MSLP and recon-aided Best Track for MSW

19 AMSU: Performance N = 426 AMSU MSLP Dvorak MSLP AMSU MSW Dvorak MSW BIAS AVG ERROR RMSE Independent Sample MSLP in hPa, MSW in Kts Validation is recon-measured central pressure within 3 hours of AMSU pass for MSLP and recon-aided Best Track for MSW

20 AMSU: Performance N = 116 AMSU MSLP Dvorak MSLP AMSU MSW Dvorak MSW BIAS AVG ERROR RMSE Independent Sample Cases < 45 knots MSLP in hPa, MSW in Kts Validation is recon-measured central pressure within 3 hours of AMSU pass for MSLP and recon-aided Best Track for MSW

21 Ongoing/Future Work Re-examine MSW estimates using improved motion component Address strong bias for weak storms caused by over-correcting T b s in the presence of center convection and associated hydrometeor scattering Add more Depression-stage cases to the sample Use improved fix accuracy from ARCHER position estimates to better correct errors from FOV bracketing effect Explore SSMIS Sounder as a viable complement to AMSU for TC intensity estimates

22 SSMIS Flown aboard active DMSP F16-18 satellites Atmospheric sounding channels are similar to AMSU Slightly different atmos contribution functions and peaks Much improved resolution at 37 km which is consistent across the the scan swath due to the conical scanning strategy Improved resolution of co-located imager channels allows for superior determination of TC structure info (eye size, RMW) at the time of the sounder TC intensity estimate

23 SSMIS

24 SSMIS F17 compared to AMSU NOAA-15 for Choi-Wan 2009 (15W) SDR Lower Air Sounder Tbs adjusted to match AMSU Tb scale. Large eye allows both sensors to resolve warm core SSMIS 91 GhzAMSU 89 Ghz SSMIS

25 SSMIS CH Ghz (~300mb) AMSU CH Ghz (~400mb) SSMIS

26 SSMIS CH Ghz (~150mb) AMSU CH Ghz (~180mb) SSMIS


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