OC 3570 Final Project

1
OC 3570Final Project

• AVHRR and Ship IR sensor
• versus
• in situ SAIL, BOOM and CTD instruments
• LCDR Marcus Simoes

2
OC 3570AVHRR/Ship IR versus CTD,SAIL and BOOM
in situ data

• Guidelines
• Introduction
• Data acquisition
• Data processing
• Statistics Computations and Results
• Conclusions

3
Introduction

• Main Goal to compare /BOOM/ Sail /CTD in situ
  data with AVHRR and IR sensor data
• SST Data from AVHRR only in 5 and 8 of Feb( leg
  1) due to cloud conditions.
• Differences in data due to acquisition depths

4
Data Acquisition

• Remote.
• NOAA-14 AVHRR/2 ( channels 1 to 5) images of 5
  and 8 Feb.
• Infrared ship sensor onboard.
• In situ.
• Boom probe.
• SAIL Serial ASCII Interface Loop.
• CTD Conductivity-Temperature-Depth Sea bird
  SBE-9 on stations 1,2,3 (5th Feb) and 8and 9
  (8th Feb).
• All data placed on the WEB in suitable ASCII.

5
Data Processing

• BOOM , SAIL, CTD and IR sensor temperatures ready
  to use.
• AVHRR temperatures should be retrieved by a
  preset SST algorithm stored in TERASCAN manually
  (as you did in RS labs)
• IR sensor does not work well these days and it
  was disregard ( many possible reasons as moisture
  contamination, malfunction,etc.)
• Only 5 CTD stations in two days so they were used
  as cross check information for BOOM and SAIL
  temperatures.Disregarded on the comparative
  statistical analysis and plots.

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Data ProcessingAVHRR

• Summary AVHRR SST retrieval Methodology used.
• Exclusion of Data at Large Zenith Angles
• Cloud Clearing (Measurements over cloud area are
  not used).
• IR uniformity test.
• Maximum Value in the Channel 2 Albedo .
• Difference in Channel 3,4 and 5.
• Test for daytime/nighttime
• Minimum Channel 4 Temperature
• Use of Day and Night time algorithms

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Data ProcessingAVHRR

• SST Algorithms
• NOAA-14 Daytime Algorithm
• MCSST Day Split Window Algorithm
• sst (1.017342 T4 ) 2.139588 (T4 - T5 )
  0.779706
• (T4 - T5 ) (sec(ZA) - 1) -278.43 273.16
• where
• sst - computed SST value in degrees C.
• T4 - channel 4 scene temperature
• T5 - channel 5 scene temperature
• ZA - solar zenith angle

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Data ProcessingAVHRR

• NOAA-14 Night time Algorithms
• MCSST Night Dual Channel Algorithmsst1
  (1.008751 T4 ) 1.409936 (T3 - T4 )
  1.975581 (sec(ZA) - 1) - 273.914
  273.16MCSST Night Split Window Algorithmsst2
  (1.029088 T4 ) 2.275385 (T4 - T5 )
  0.752567 (T4 - T5 ) (sec(ZA) - 1) - 282.24
  273.16MCSST Night Triple Channel Algorithmsst3
  (1.010037 T4 ) 0.920822 (T3 - T5 )
  0.067026 (sec(ZA) - 1) - 275.364 273.16
• where
• sst n - computed SST value in degrees C.
• T3 - channel 3 scene temperature
• T4 - channel 4 scene temperature
• T5 - channel 5 scene temperature
• ZA - solar zenith angle
• Computed SST rejected if differs from climatology
  by more than 10

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AVHRR data processing day 5 results
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AVHRR Data processing day 8 results
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BOOM Data Processing Day 5 Results
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BOOM Data Processing Day 8 Results
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SAIL Data Processing Day 5 Results
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SAIL Data Processing Day 8 Results
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Statistical Computations and Results

• Calculate parameters for each instrument
• Mean temperature.
• Standard deviation and Variance.
• Calculated parameters among instruments
• Correlation
• Linear Regression

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Statistical Computations and Results
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Statistical Computations and Results
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Statistical Computations and Results
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Conclusions

• BOOM x SAIL with good agreement in the cruise
• AVHRR useful to detected large features.
• Be sure when you are retrieving temperatures from
  AVHRR that you have a good image, the methodology
  and the right algorithm.
• Use good in situ measurements as control points
  to AVHRR images.

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OC 3570AVHRR/Ship IR versus CTD,SAIL and BOOM
in situ data

• Questions ?