1. TropicalCyclone Tropical Cyclone Studies by Microwave Sensors Chandra Mohan Kishtawal ASDMOG ASD/MOG Space Applications Centre ISRO/MOP/SM-2.1

2. Channel Number 1/2 3/4 5 6/ 78/ 9 Center Freq [GHz] 10.65 19.3521.3 37.0 85.5 Beam EFOV [kmxkm]63x3730x1823x18 16x9 7x5 Objectives : TC Geolocation, Intensity Estimation and prediction Using Microwave observations Data : TMI observations for TC Over global oceans during past 5 years ( more than 400 TMI scenes analyzed). TC Track and Intensity data was collected from NHC/TPC archives for algorithm development and validation

3. Geolocation Cyclone Geolocation ave Observations Using Microwave Observations

4. Warned region is 3 times larger than the region where actual damage takes place. This proves Very Expensive. Also this shows the importance of Even A marginal improve ment in track prediction accuracy. Warned region Damaged Region

5. Impact of Initial Position Error on Track Forecast

6. A Comparison of Microwave and Infrared Observations of Tropical Cyclones

7. 10 GHz 19-37 GHz 85 GHz TRMM - 33151 Rain Rate BT 100 K 310 K 0 50 mm/h Sensitivity of different TMI frequencies to TC-Rain 2 km 4 km 8 km

8. 85 GHz “Cold” Precipitation Against Warmer Ocean Background 37 GHz “Warm” Precipitation Against Colder Ocean Background Two Main Microwave Sensing Channels for TC’s Cold Warm Cold

9. PARALAX PROBLEM IN CONICAL SCAN Paralax Error Paralax Errors 85 GHz 15-20 km 37 Ghz ~ 5 km

10. 08-Aug-2000, 1057 UTC TC-JALAWAT 37 GHz 85 GHz Example of Paralax

11. Differences between TMI derived TC centers from Best- track Positions (IMD) ( After Paralax Compensation)

12. CycloneIntensity Cyclone Intensity Estimation Estimation

13. Operational Centers worldwide still depend on Dvorak’s technique for TC intensity estimates that uses manual pattern-analysis of VIS/IR images. In operational set-up it proves slow. We developed an automatic technique for TC intensity assessment, that is quick, and reliable.

14. 15582 33108 CONVCTIVE ORGANIZATION WITHIN STORMS 100 K 310 K

15. 10 GHz 19-37 GHz 85 GHz TRMM - 33151 Rain Rate BT 100 K 310 K 0 50 mm/h Sensitivity of different TMI frequencies to TC-Rain 2 km 4 km 8 km

16. 1.0 O 2.5 O 100 K 310 K

17. ISO IN = 0.621 ISO OUT = 0.234 ISO IN = 0.832 ISO OUT = 0.523 ISO =  i Øi /((n-1)* Ā), n=12 (5) Øi = (Loge(Ni+1) – Ā) if Loge(Ni+1)  Ā, otherwise Øi =0 N I = No of TMI pixels with PCT < 240 K Quantifying Isotropy of Convection

18. ALGORITHM DEVELOPMENT BY GENETIC ALGORITHMS Randomized search and optimization technique guided by the principle of natural genetic systems.

19. PARENT-1 PARENT-2 CHROMOSOMES GENETIC EVOLUTION OF PATTERNS

20. PARENT-1 PARENT-2 CHILDREN

21. 1 2 1 2 Random Initialization of Equation Population Select the best individuals as per “cost” Best ones get chance to reproduce Offspring again reproduces as per merit Mutation of a fraction of low-order population Fittest individual emerges after N generations A Simplified Concept of Genetic Algorithm

22. PARAMETER LIST FOR INTENSITY ESTIMATION MEAN BT 10(H) 10-MAX(BT 10H ) 10-MIN(BT 10H ) 10-GHZ BT WITHIN 2 DEG RADIUS

23. Distance from Center Maximum Sensitivity Region

24. CONVECTIVE ISOTROPY (SYMETRY OF THE REGION DEFINED BY PCT < 240 K) 100 K 310 K ISO =  i Øi /((n-1)* Ā), n=12 (5) Øi = (Loge(Ni+1) – Ā) if Loge(Ni+1)  Ā, otherwise Øi =0 N I = No of TMI pixels with PCT < 240 K

25. MSW(kt) = a-d/(i-7.09)+(e+f-d)/ ((-52.15+c/b-f/(h-75.75))* (-21.96))+b-168.17 TermExpression aMean of 10-H for r < 1 o bConvective Isotropy for r < 1 o cConvective Isotropy for 1 o < r < 2.5 o dMean of cold 10-V pixels ( r < 1 o ) eSum of 11 warmest 10-H ( r < 1 o ) fgfg Sum of 11 coldest 10-H ( r < 1 o ) Mean (37-V – 37-H) ( r < 1 o )

26. NoParameterLow Intensity Storms (MSW < 64 Kt) High Intensity storms (MSW > 64kt) 1212 Mean BT 10-h in R < 1 deg Mean of coldest 10 pix 1.33 0.54 1.33 0.69 3Isotropy (inner) 0.020.73 4Isotropy (outer) 0.040.24 SENSITIVITY OF DIFFERENT TERMS

27. Automatic Intensity Estimation : Skill for Global TCs Paper to appear in GRL:April-2005. TC-CASES NIO NATL NEP (Mean ~ 11 kt)

28. Depression Severe Cyclone JTWC : 25 Kt Estimated : 27 Kt JTWC : 60 Kt Estimated : 52 Kt Automatic Intensity Estimation : Case Studies 18-Oct-200022-May-2001

29. Very Severe Cyclone-1Very Severe Cyclone-2 JTWC : 94 Kt Estimated : 88 Kt JTWC : 110 Kt Estimated : 120 Kt Automatic Intensity Estimation : Case Studies 18-May-1999 16-Oct-1999

30. Automatic Intensity Estimation : Skill Levels TMI estimated v/s JTWC Intensity Correlations and RMS Error Training Set ( 60 TMI Scenes) : 91% Verification Set ( 20 TMI Scenes) : 90% Mean RMS error : 12.53 Kt Compare with Bankert & Tag-2002 RMSE : 19.7 Kt NEP+ ATL + IO

31. CycloneIntensity Cyclone Intensity Prediction Prediction

32. Area of cyclonic influence (R o =u/(f*r) ~ 1, core boundary) Environmental forcing begins To take over. Eye wall Principal Band The outward edge of bands respond earliest to environmental flow Convective bands transport large cloud mass upward, much larger than eye-wall OBSERVATION-1 : Intensification Process Of Weak Cyclones ( Msw 64 kt)

33. BT ( 37-H) Predictors Intensity Change For Normal Intensity Cyclones Mean of 5 low frequency channels over the un-masked region Convective Mass in high CLW region ( BT-37 H > 240 K) Convective Mass =  CM CM=(240-PCT) 1.1 if PCT < 240 K, Else CM=0 Minimum PCT in high CLW region High CLW region

34. With the use of Cloud Mask, the correlations of low frequency channels with 24-hour intensity change improve, implying that much of the signals arrive from ‘outside’ the storm ( due to wind ? SST ? ) However these are unusable if storm intensity increases beyond ~ 60 kt. PCT min is computed from masked area in both the graphs. It is shown only for comparison

35. Convective Mass in Inner Core ( r < 1.3 o ) Convective Mass =  CM CM=(230-PCT) 1.1 if PCT < 230 K, Else CM=0 Convective Isotropy in Inner Core ( r < 1.3 o ) Convective Isotropy in outer Core ( 1.3 o < r < 2.5 o ) Low Isotropy Case High Isotropy Case PCT (K) Predictors Intensity Change For High Intensity Cyclones

36. PredictorsHigh Intensity PredictorsHigh Intensity Minimum PCT in inner core Average PCT in inner core Average 10 V BT inner core Average 10 V BT in outer core Convective SHEAR ( angular shift b/w high density region of high BT(37 H ) and that of low PCT in 85 GHz image. BT (37-H) PCT

37. Picking the SST Signatures Mean of 10 GHz (V) BT in 45 o angular section surrounding the direction of cyclone motion during past 12 hours. A Pixel is Considered only if BT(37-H) < 185 K. This parameter may pick SST signatures ahead of a TC Direction of TC Motion in last 12 hours Predictors Intensity Change For High Intensity Cyclones

38. Mean Histograms Of Decaying And Intensifying Storms 100 K 310 K

40. BT (100-325) 85 GHZ 10 GHZ +1 -1 BAR-CODING FOR SIGNAL ENHANCEMENT

41. Performance of Prediction Algorithm (Accuracy ~ 8 kt)