Hurricane Wind Retrieval Algorithm Development for the Imaging Wind and Rain Airborne Profiler (IWRAP) MS Thesis Project Santhosh Vasudevan End of Semester Meeting December 10, 2005 Central Florida Remote Sensing Lab

Thesis Objective Develop a hurricane wind vector retrieval algorithm for the UMass dual frequency (C- SCAT and Ku-SCAT) Imaging Wind and Rain Airborne Profiler (IWRAP) Provide a real time simulation of hurricane wind vector retrieval

2 286 meters IWRAP Overview

Ocean Surface Sigma-0 Measurements Collected during 360 deg conical scan Data are averaged into 32 az sectors (11.25° bins) Grouped into wind vector cells (WVC) WVC’s are chosen to be 1 km x 1 km Swath comprises 4 WVC’s ( 2 on either side of sub-track)

3836 m 4000 m 2640 m Wind vector cells, 1Km by 1 Km Scan Geometry and Sigma-0 Collocation

Example–WVC 4c WVC 4C is populated by 6 az-bins at outer(40deg) and 8 az bins at inner(30deg) beam. Total of 14 az bins available for both beams WVC 4c

Effect of A/C Attitude Variations on Sigma-0 Grouping Typical aircraft attitude variations are ± 2 deg in roll & pitch Attitude changes cause the scan geometry to change which can effect the collocation (grouping) of sigma-0’s for wind retrieval Effects are presented next

-2 Deg Roll, -2 Deg Pitch Contour changed by attitude change Actual scan contour

Result of Attitude Variability Study Changes in scan geometry, with typical A/C attitude changes, is negligible for WVC sig- 0 collocation No attitude correction required for the wind vector retrieval algorithm

High Wind Speed Geophysical Model Function (GMF)

GMF - High Speed Adjustment C & Ku band high wind speed GMF’s are developed from experimental airborne scatterometer data obtained over 10 years of HRD flights through hurricanes (UMASS) GMF exhibits a slow roll-off in the power law wind exponent and causes the sig-0 to saturate with wind speed (Usat )

C-Band V-pol GMF 30° inc

C-Band H-pol GMF 30° inc

Wind Retrieval Method of Maximum Likelihood Estimator (MLE) was adopted to retrieve wind speed and direction from measured sigma-0’s

Wind Vector Retrieval - 1st Results Wind retrieval was tested using a compass simulation –Constant wind speed & direction –Gaussian noise corrupted sig-0’s –Monte Carlo simulation 100 trials For case of 65° constant wind- field,the following results were obtained

C-Band Wind vector cell#1, retrieved speed

C-Band Wind vector cell#1, retrieved direction

Ku-Band Wind vector cell#1 retrieved speed

Ku-Band Wind vector cell#1 retrieved direction

Hurricane Simulation A simulated hurricane wind field based on hurricane Floyd used Resolution set to 100m by interpolation Noise added to the wind field

Simulated Hurricane Wind field -Magnitude

Simulated Hurricane Wind field -Direction

IWRAP scan simulation Using IWRAP Radar geometry,flight altitude and speed- scan pattern generated The scan pattern flown over simulated wind field to generate hurricane sigma-0 measurements IWRAP Scan pattern

Simulated flight over the hurricane

Simulated IWRAP Wind retrieval Data generated in stream to simulate real scenario The streaming sig-0 measurements at 100m resolution from the simulated flight is co-located into 1 Km WVC Co-located sigma-0’s grouped and averaged: magnitude and direction retrieved for 1 Km WVC using the wind retrieval algorithm

Preliminary Results: Retrieved wind magnitude from several flights m/s

Preliminary Results: Retrieved wind magnitude from several flights deg

Future Work Perform multiple retrievals. Compare retrieved parameters with true values to validate measurements Add a rain flag to measurement