1

An Algorithm for Measuring

Rain over Oceans using the

QuikSCAT Radiometer

Mladen Susanj

July 14, 2000

Thesis Defense for the Degree of M.S.E.E.

2

Overview

1. SeaWinds on QuikSCAT

2. Effect of Precipitation on Ocean Tb

3. Rain Algorithm Definition

4. Rain Algorithm Validation and Results

5. Conclusion

3

• Mission - to provide continuous

measurements of the Ocean surface winds.

• Problem - Wind vector products occasionally

degraded by the presence of rain.

• Idea - to develop the technique for

identification of contaminated wv cells.

Chapter - 1

SeaWinds on QuikSCAT

4

Geometry of the Sea Winds scatterometer on QuikSCAT

5

QuikSCAT swath projection

6

QuikSCAT Radiometer’s (QRad) simplified block diagram

7

Be

Bn

Frequency

Pow

er

Received Spectrum

Radar Echo

Echo Channel

Noise Channel

GBBTEEN nensysenxk )(

QuikSCAT Radiometer receiver spectrum

8

Chapter - 2

Effect of Precipitation on Ocean Tb

9

Theoretical QRad Brightness Temp. vs. Rain Rate

),,,,( RainsalanitywvwsSSTfTb • General case

• Theoretical QRad Tb salinitywvwsSSTRainfTb ,,,)(

10

Typical Rain Signature in QRad Tb

QRad 3-Day Avg.

H-pol Brightness

SSM/I Monthly Avg.

Rain Rate

11

Chapter - 3

Rain Algorithm Definition

12

Surface Truth - TMI and SSMI Rain Rates

Advantage:

• utilization of multiple frequencies and

multiple polarization enable superior

accuracy of measurements.

Restrictions:

• variable spatial and time collocation with

QuikSCAT wind vector cells,

• measurements just in Tropics (TMI).

13

QuikSCAT and TRMM Swath

21 rain events covered by both instruments within one

hour time difference used to develop the algorithm

14

Rain Event #1493

QRad Tb

TMI

Rain Rate

15

Collocation of QuikSCAT and SSMI Measurements

16

Collocation of QuikSCAT and SSMI Measurements

17

pbpbbp oceanTQRadTT )()(

Ocean Background Brightness and “Excess Brightness”

18

Excess Brightness

Calculation

Rain Index

Calculation &

Quantization

Qrad Tb’sOcean

Tbackgroun

d

Flow Chart - 1st Part

19

Rain Index

• At QSCAT wind vector cells, calculate rain indices for

both H & V-pol

0

,

,,

,,

n ji

p

ppjib

pji

TTRI

n i,j … # of measurements

p … standard deviation of Tb

i , j … bin indices

p … polarization

20

Brightness Temp. Offset T0

Excess Brightness vs. TMI Rain Rate

’h=12K

Exce

ss T

b, K

TMI Rain Rate, mm/hr

21

Initial Rain Mask

For SQRI 4

Excess Brightness

Calculation

Rain Index

Calculation &

Quantization

SQRI = QRIh+QRIv

Qrad Tb’sOcean

Tbackgroun

d

Flow Chart - 1st Part

To Spatial Filter

22

Threshold Determination - I

Rain Index Probability Density Functions

Clear Sky and Ocean Moderate Rain

Mean QRI = - 1 Mean QRI = + 1

23

T

c dRIRIpPFA )(

T

r dRIRIpPMc )(

FAMcE PPP

Threshold Determination - II

Threshold “T” is defined where PE has minimum !!

Clear Ocean and Sky pdf

Moderate Rain pdf

Threshold

24

Rain Event #1493

QRad Tb

Rain Event Area

No-Rain Area

25

Initial Rain Mask - Input to Spatial Filter

Random Rain False Alarms

26

Flow Chart - 2nd part Spatial Filter

Center bin ‘No-

Rain’ Flag 0

Input Rain Mask

Center bin

‘Rain’

3

Neighbors

Flag 1

< 3

Neighbors

Comparison

with higher

threshold (6)

for SQRI

Flag

0/1

Revised Rain Mask

0/1

27

Spatial Filter Performance

Output

Input

5 iterations

Spatial Filter

28

Flow Chart - Part-3

Assign

Probabilities

Joint Probability

Calculation

Rain Rate

Calculation

Output of the Spatial Filter

Rain Flag

Calculation

29

Rain Index Probability and Neighbor Probability

QRIh

Rain

In

dex

Pro

bab

ilit

y

H-pol Rain Index Pr Neighbor Pr

# Rain-Flagged Neighbors

30

QRad Joint Probability

)(Pr)(Pr)Pr( QRIQRINbsJP vh

TMI Rain Rate QRad Joint Pr

31

QRad Rain Rate

JPBJPARR 2

Regression TMI Rain Rates

with Joint Probabilities

gives the expression;

32

QRad Rain Flag

33

Chapter - 4

Rain Algorithm Validation and Results

34

Rain Rate Comparison with TMI - Rain Event #1176

TMI QRad

Accumulative

Rain Rate, mmTMI QRad QRad/TMI

2,462 1,750 0.71

35

Rain Rate Comparison with TMI - Rain Event #1493

TMI QRad

Accumulative

Rain Rate, mm

TMI QRad QRad/TMI

5,745 4,701 0.82

36

Rain Rate Comparison with SSMI - QuikSCAT Rev #1439

QRad SSMI

Accumulative

Rain Rate, mmQRad SSMI QRad/SSMI

4473 4539 0.99

37

Correct No-Rain

Correct Rain

Misclassification

False Alarm

Rain Flag Classification - Rain Event #1176

QRadTMI

Classification

(89.27%)

(70.00%)

(30.00%)

(10.73%)

38

Rain Flag Classification - Rain Event #1493

Correct No-Rain

Correct Rain

Misclassification

False Alarms

QRadTMI

Classification

(88.86%)

(85.67%)

(14.33%)

(11.14%)

39

Conclusion

•A statistical rain rate retrieval algorithm has been developed

using QRad Tb’s and rain rates derived from TRMM TMI.

•Also a binary rain flag has been produced using 1.4 mm/hr

as the threshold.

•Comparisons between QRad, TMI & SSMI rain rates show

excellent spatial correlation when properly collocated in

time.

•Some solutions and procedures proposed in this thesis have

been accepted by the sponsor of the project, JPL, and

implemented into operational SeaWinds rain algorithm.