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First Workshop on EOS Snow and Ice Products 16-17 November 2004 MODIS Sea Ice Products and Validation George Riggs SSAI / GSFC / Code 971

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First Workshop on EOS Snow and Ice Products 16-17 November 2004 MODIS Sea Ice Products and Validation George Riggs SSAI / GSFC / Code 971. Outline Sequence of products, swath to 8-day composite images and brief description Ice surface temperature validation status Collection 5 revisions

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Presentation Transcript
slide1

First Workshop on EOS Snow

and Ice Products

16-17 November 2004

MODIS Sea Ice Products and Validation

George Riggs

SSAI / GSFC / Code 971

slide2

Outline

  • Sequence of products, swath to 8-day composite
    • images and brief description
  • Ice surface temperature validation status
  • Collection 5 revisions
  • Factors affecting usage of products
slide3

Sequence of MODIS Sea Ice Products

MOD29--swath, level-2 product in sensor sampling space

MOD29P1--daily, level-3 spatially resampled (mapped) to EASE-Grid polar projection, tiled product. Intermediate L2G product generated but not archived. Day and night products.

MOD29E1--daily, level-3 global EASE-Grid polar projection, Northern and Southern hemisphere maps included.

MOD29E2--eight-day, level-3 global EASE-Grid polar projection, Northern and Southern hemisphere maps included. Experimental at this time.

slide4

Sea Ice

MOD29 2004 309 1100 UTC

Ronne Ice Shelf

Sea ice by reflectance features and NDSI

MODIS bands, 2,4,6

1km resolution, swath ~ 2030x2340 km

Cloud masking from MOD35_L2

MOD021KM bands 1,4,6

Sea_Ice_by_Reflectance

slide5

Ronne Ice Shelf

MOD29 2004 309 1100 UTC

Ice surface temperature by split-window technique

MODIS bands 31 and 32

1km resolution, swath ~ 2030x2340 km

Cloud masking from MOD35_L2

MOD021KM bands 1,4,6

Ice_Surface_Temperature

slide6

Quality Assessment Data

  • QA bit encoded
  • set by checks on input data within or out of nominal rage
  • set for cloud
  • type of checks done vary for reflectance and thermal data
  • QA varies with product level
  • has rarely been used

Sea_Ice_by_Reflectance

Sea_Ice_by_Reflectance_Pixel_QA

Ice_Surface_Temperature

Ice_Surface_Temperature_Pixel_QA

slide7

Sea_Ice_by_Reflectance

Ice_Surface_Temperature

Ronne Ice Shelf

Input data is L2G product in which all swaths (15 in this case) for the day have been mapped onto the projection.

A scoring algorithm based on solar zenith, distance from nadir and observation coverage in a cell selects the most favorable observation for the day.

MOD29P1D

1km resolution

tiles are ~ 10° x 10°

slide8

Sea Ice

MOD29E1 2004 November 4

4km resolution

Sampling technique

The global 4km MOD29E1 grid is mapped over the MOD29P1 1km grid and the grid cell nearest the 4km cell center is chosen.

Northern Hemisphere mapping 40° to 90°

Southern Hemisphere mapping -50° to -90°

slide9

MOD29E2 : 8-day composite IST EASE-Grid

North Polar View South Polar View

Daily global 4-km resolution ice surface temperature products - composites from May 15-19, 2000.

slide10

MODIS Sea Ice Maps

  • Sea Ice Surface Temperature Product
  • Status: sea ice surface temperature product validated stage 2
  • Daytime
  • Nighttime
  • North and South Polar Maps (0.05° resolution – EASE-Grid)

1 km resolution

slide11

Sea ice surface temperature product (MOD29)

Hall, et al., 2004 IEEE Trans. Geosci. Remote Sensing 42:1076-1087.

AMSR-E

AMSR image from Don Cavalieri & Al Ivanov

slide12

MODIS IST Validation Study Conclusion

Excellent measurement of actual temperature of sea ice during the Arctic cold period

RMS error or accuracy, with bias removed, was 1.2 K for South Pole and 1.3 K for Arctic Ocean

Limited to clear-sky conditions

slide13

IST Potential Uses

Ice conditions: details of ice floes, new and young ice, leads and recently refrozen leads, low ice concentration and ice edges can be observed in the IST imagery

May be useful in energy-balance modeling

Suggested possible relationship between MODIS IST and AMSR-E derived ice temperature

slide14

Collection 5 Revisions

MOD29

Deleted ‘Sea Ice by IST’ and ‘Combined Sea Ice’ data arrays.

Spatial QA given as data values--change from bit encoding of V004. Set based on input data quality.

New land water/water mask with accurate mapping of Antarctica coastlines

slide15

Mosaic of MOD29P1N tiles on 20 July 2003

West Antarctica and Antarctic Peninsula shown

Tiles

h07v28, h08v28

h07v29, h08v29, h09v29

h07v30, h08v30, h09v30

Coastline of Antarctica is the feature of interest. The EOS land/water mask maps ice sheets as land with the coastline being the ice shelf edge. BU land/water mask maps grounding line of ice shelves as the coastline. And has a more accurate coastline elsewhere

BU land/water mask

EOS land/water mask

slide16

Antarctic coastline map in the BU land/water mask is vastly superior to the EOS land/water mask.

With the BU land/water mask;

Ice shelves are correctly mapped as being on the ocean! (Mapped at grounding line not the ice edge)

The BU integrated coastline map of Antarctica from the Antarctic Digital Database (www.nerc-bas.ac.uk/public/magic/add_home.html) is very accurate. (There is a newer version of that database available that adds details from -85 to -90 degrees.)

The accurate Antarctic coastline map enhances comparative studies and validation work because it agrees with other data sources and maps of Antarctica and ice shelves.

Snow products are improved because the ice shelves are removed from land. (Example of snow not shown because Antarctica in darkness during the July dates of the MODAPS test run.)

slide17

Collection 5 Revisions

MOD29P1

Deleted ‘Sea Ice by IST’ and ‘Combined Sea Ice’ data arrays.

Spatial QA passed through from the MOD29 data as data values.

HDF internal compression--transparent to the user.

slide18

Collection 5 Revisions

MOD29E1

Spatial QA given as data values--change from bit encoding of V004

HDF internal compression--transparent to the user

MOD29E2

MOD29E2

New eight-day product is anticipated.

slide19

Factors affecting usage of products

Cloud detection (Cloud mask product related issue.) Effects differ for observation of sea ice and calculation of IST.

Sea ice/cloud discrimination.

Frequency of cloud cover.

QA data--what is useful? Development of QA indices in the future?

Data format, HDF-EOS has been troublesome for some users.

Problematic detection of clouds and sea ice/cloud discrimination in the nighttime

slide20

http://modis-snow-ice.gsfc.nasa.gov

images

news

user guides

literature

links to other sites

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