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Ice Cover and Sea and Lake Ice Concentration with GOES-R ABI

Presented by Yinghui LiuPresented by Yinghui Liu1

Team Members: Yinghui LiuTeam Members: Yinghui Liu1, Jeffrey R Key, Jeffrey R Key2,, and Xuanji Wangand Xuanji Wang1

1UW-Madison CIMSSUW-Madison CIMSS2NOAA/NESDIS/STARNOAA/NESDIS/STAR

GOES-R AWG Cryosphere GOES-R AWG Cryosphere TeamTeam

2011 GOES-R AWG Annual Meeting, June 13-16, Fort Collins, CO

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OutlineOutline

Executive Summary Algorithm Description ADEB and IV&V Response Summary Requirements Specification Evolution Validation Strategy Validation Results Summary

3

Executive Summary Executive Summary

The GOES-R Ice Cover and Sea and Lake Ice Concentration The GOES-R Ice Cover and Sea and Lake Ice Concentration are Option 2 products. are Option 2 products.

Software Version 5 was delivered in May 2011. ATBD Software Version 5 was delivered in May 2011. ATBD (100%) is on track for a August delivery.(100%) is on track for a August delivery.

The algorithm has been developed and tested using MODIS, The algorithm has been developed and tested using MODIS, and SEVIRI data as proxy, and validated with the Advanced and SEVIRI data as proxy, and validated with the Advanced Microwave Scanning Radiometer - Earth Observing System Microwave Scanning Radiometer - Earth Observing System (AMSR-E) products.(AMSR-E) products.

Validation studies indicate spec compliance Validation studies indicate spec compliance

4MODIS true color image over Great

Lakes on February 24 2008.

Ice Cover:

A binary yes/no detection of ice cover over ocean, inland lakes, and rivers.

Ice Concentration:

The fraction (in tenths) of the sea or lake surface covered by ice.

Algorithm DescriptionAlgorithm Description

55Reflectances of ice, clouds, and water (Riggs et al. 1999).

8%

NDSI=(Rvis-Rswir)

/(Rvis+Rswir)

NDSI value:

Water: ~ 0.5

New ice: ~ 1.0

Snow ice: ~ 1.0

Cloud: ~ 0.0

Ice cover Detection: Ice or snow covered ice show high NSDI value and high reflectance at visible and near-infrared bands.

Algorithm DescriptionAlgorithm Description Ice Cover Ice Cover

666

Ice/snow surface temperature is retrieved by the following equation (Key et al. 1997).

Ts = a + b T11 + cT12 + d [(T11-T12)(sec-1)]  

Ts = the estimated surface temperature (K)

T11 = the brightness temperatures (K) at 11 um

T12 = the brightness temperatures (K) at 12 um

= sensor scan angle

a, b, c, d = coefficients, derived for the following temperature ranges: T11 < 240K, 240K < T11 < 260K, T11 > 260K. The

Algorithm DescriptionAlgorithm Description Ice Cover Ice Cover

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• In daytime, pixels with both NDSI and reflectance larger than set thresholds, with surface temperature lower than set thresholds are ice.

• NDSI in this algorithm is defined as

NDSI=(R1-R2)/(R1+R2)• R1 = reflectance at GOES-R ABI ch 3, 0.865 m

• R2 = reflectance at GOES-R ABI ch 5, 1.61 m

• Threshold : 0.6

• Reflectance at near infrared channelReflectance at near infrared channel, , 0.865 m

• Threshold 0.08

• At nighttime, pixels with surface temperature lower than set thresholds are ice.

Algorithm DescriptionAlgorithm Description Ice Cover Ice Cover

8Temperature

Reflectance

Pure water

Pure ice

Ice Concentration: Ice reflectance (temperature) change linearly with ice concentration

Algorithm DescriptionAlgorithm Description Ice Concentration Ice Concentration

99

Fractional ice concentration for each pixel (Fp) in a

search window is then calculated as

Fp = (Bp - Bwater) / (Bice – Bwater)

Bwater = the reflectance/temperature (K) of a pure water pixel

Bice = the reflectance/temperature (K) of a pure ice pixel

Bp = the observed reflectance/temperature (K) of the pixel.

In this algorithm, reflectance at GOES-R ABI channel 2 (0.64 m) is used

during the day, and surface temperature is used at night.

The spatial resolution is 0.5 km at 0.64 m channel, and 2.0 km for surface

temperature at sub-satellite FOV

Bice is determined using tie-point algorithm; Bwater is parameterized.

Algorithm DescriptionAlgorithm Description Ice Concentration Ice Concentration

101010

step1

step2

step3

High Level Flowchart of the ice concentration and extent algorithm

Ice cover and concentration algorithm begin

Ice cover and concentration algorithm end

Group-criteria detection

Ice

Tie point algorithm

Ice concentration

Ice cover

ABI channel radiance, satellite viewing angles, cloud mask,

land/water mask

Algorithm DescriptionAlgorithm Description

1111

Algorithm Changes from Algorithm Changes from 80% to 100%80% to 100%

A new test, using the ice surface temperature in the daytime for ice detection is added in the version 5 code.

Pure water surface reflectance is parameterized as a function of water salinity and solar zenith angle. In the 80% version, it is a constant value.

Metadata output added Quality flag added

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All comments on ATBD clarification have been addressed.

Suggestions on algorithm improvement have been considered and implemented.

Suggestions on validation work are taken and more extensive validation work is undergoing.

Feedback:Feedback: I would recommend to explain this clearly in the I would recommend to explain this clearly in the beginning and possibly modify the title of ATBD to reflect beginning and possibly modify the title of ATBD to reflect ““the ice the ice over waterover water”” application, i.e. no land ice applications are included. application, i.e. no land ice applications are included. Response:Response: In the beginning of the ATBD, we point out that the In the beginning of the ATBD, we point out that the ice concentration is only retrieved in ABI pixels over water surfaces ice concentration is only retrieved in ABI pixels over water surfaces covered with ice. covered with ice.

ADEB and IV&V Response SummaryADEB and IV&V Response Summary

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Feedback:Feedback: While ATBD contains interesting comparisons between While ATBD contains interesting comparisons between retrievals from MODIS, SEVIRI and AMSR-E, it requires more systematic retrievals from MODIS, SEVIRI and AMSR-E, it requires more systematic analysis and quantitative evaluation of its performance. For 80% ATBD analysis and quantitative evaluation of its performance. For 80% ATBD level, the material is likely adequate.level, the material is likely adequate.Response:Response: More systematic analysis and quantitative validation of the More systematic analysis and quantitative validation of the products are undergoing using AMSR-E, ice charts, and Landsat data.products are undergoing using AMSR-E, ice charts, and Landsat data.

Feedback:Feedback: Explain why temperature thresholds are not used during Explain why temperature thresholds are not used during daytime ice detection. This would make algorithm more consistent between daytime ice detection. This would make algorithm more consistent between daytime and night time scenes.daytime and night time scenes.Response:Response: We added a new test, using the temperature in the daytime We added a new test, using the temperature in the daytime ice detection, in the version 5 code and updated this in the ATBD.ice detection, in the version 5 code and updated this in the ATBD.

ADEB and IV&V Response SummaryADEB and IV&V Response Summary

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Nam

e

User &

Priority

Geograp

hic

Coverage

(G, H

, C, M

)

Vertical

Resolu

tion

Horizon

tal

Resolu

tion

Map

pin

g

Accu

racy

Measu

remen

t

Ran

ge

Measu

remen

t

Accu

racy

Prod

uct R

efresh

Rate/C

overage Tim

e

Ven

dor A

llocated G

roun

d

Laten

cy

Prod

uct M

easurem

ent P

recision

Ice Cover GOES-R

FD N/A 2 km 1 km Binary yes/no detection

85% correct detection

180 min

77,756 sec

N/AFD – Full Disk

Requirements Specification Evolution

February 2009•Ice Cover / Landlocked: Change the accuracy from Binary yes/no detection to 85% correct detection. •Change the name to 'Ice Cover'. •Sea & Lake Ice: Extent: Delete product.

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Nam

e

User &

Priority

Geographic

Coverage

(G, H

, C, M

)

Vertical

Resolution

Horizontal

Resolution

Mapping

Accuracy

Measurem

ent

Range

Measurem

ent

Accuracy

Product R

efresh

Rate/C

overage Tim

e

Vendor A

llocated Ground

Latency

Product M

easurement P

recision

Sea & Lake Ice: Concentration

Sea & Lake Ice: Concentration

GOES-R

GOES-R

C: Regional & Great Lakes and US costal waters containing sea ice hazards to navigation

FD: Sea ice covered waters in N & S Hemispheres

Ice Surface

Ice Surface

3 km

10 km

< = 1.5 km

< = 5 km

Ice concentration – 1/10 to 10/10

Ice concentration – 1/10 to 10/10

Ice concentration – 10%

Ice concentration – 10%

180 min

6 hr

3236 sec

9716 sec

30%

30%

Requirements Specification Evolution

No changes in specification in ice concentration

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Ice Cover and Sea and Lake Ice Concentration retrieved from Ice Cover and Sea and Lake Ice Concentration retrieved from MODIS data as proxy were validated with ice cover and MODIS data as proxy were validated with ice cover and concentration from the AMSR-E product as truth.concentration from the AMSR-E product as truth.

AMSR-E Level 3 product provides ice concentration over the Great Lakes and the Arctic Ocean. Ice cover is assigned when ice concentration is larger than 15%.

Ice cover and sea and lake ice concentration retrievals uses the GOES-R ABI algorithm, and MODIS data as proxy.

Two datasets are matched daily by averaging the retrieved product in the footprint of AMSR-E product.

Validation statistics are computed based on 1,576,298 matched pairs Validation statistics are computed based on 1,576,298 matched pairs covering different seasons.covering different seasons.

Validation Strategy

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• Validate of ice cover and concentration retrievals using MODIS data as proxy with ice cover and concentration results from Landsat , which has much higher spatial resolution, and ice charts, which have better spatial resolution than AMSR-E, are undergoing. Meanwhile, validation with AMSR-E are continuing.

Validation Strategy

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Lake ice concentration (%) with MODIS Aqua data (left), MODIS true color image (middle), and from AMSR-E (right) over Great Lakes on February 24 2008.

Ice concentration over Great Lakes

Validation Strategy

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Case numberCase number

Total pairs: 1576298Total pairs: 1576298Sea/Lake ice cover determined Sea/Lake ice cover determined from AMSR-Efrom AMSR-E Water determined from AMSR-EWater determined from AMSR-E

Sea/Lake ice coverSea/Lake ice cover 10751241075124

WaterWater 305872305872

Correct detection ratio = (1075124+305872)/1576298 = 87.6%Correct detection ratio = (1075124+305872)/1576298 = 87.6%

The product measurement accuracy is higher than required 85% correct detection.

Performance of Ice Cover product

Validation ResultsValidation ResultsIce coverIce cover

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Ice concentration difference of AMSRE Ice concentration difference of AMSRE product and MODISproduct and MODIS

Mean biasMean bias

(%)(%)

Standard deviationStandard deviation

(%)(%)

Over Arctic OceanOver Arctic Ocean 4.04.0 15.715.7

Over Great LakesOver Great Lakes -4.0-4.0 25.625.6

Required measurement accuracyRequired measurement accuracy 1010

Required measurement precisionRequired measurement precision 3030

Performance of Ice Concentration product

The product measurement accuracy and precision meet the requirement.

Validation ResultsValidation ResultsIce concentrationIce concentration

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Performance of ice concentration product

Frequency distribution of ice concentration differences between the AMSR-E product and retrievals using the ABI algorithm based on selected 41 clear day MODIS data in four seasons in 2007 over the Arctic Ocean.

Validation ResultsValidation ResultsIce concentrationIce concentration

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• ABI allows us to monitor ice conditions at high temporal and spatial resolution.

• The ice cover product is generated using group threshold tests. Comparison of ice cover products using MODIS as proxy with AMSR-E shows that products exceed the required detection accuracy of 85%.

• The ice concentration product is produced using a tie-point algorithm. Validation of this product with the AMSR-E product shows that products meet the required measurement accuracy and precision.

• Further tuning of the algorithm, including test thresholds in the group threshold test, and parameters in tie-point algorithm are needed. More quantitative validation of the products with AMSRE and other available products, including ice chart, and data from LANDSAT are undergoing.

SummarySummary