MODIS__Arctic__MeltPondFraction__UHAM-CliSAP-ICDC__v02__12.5km__8day

doi:10.1594/WDCC/MODIS__Arctic__MPF_V02

Rösel, Anja; Kaleschke, Lars; Kern, Stefan

ExperimentDOI
arcticEOS-TERRAocean
Summary
Reflectances measured in the visible frequency range at three channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Earth Observation Satellite (EOS) TERRA were used to derive the melt pond fraction on Arctic sea ice using an artificial neural network. This analysis was done on reflectances gridded onto a polar-stereographic grid tangent to the Earths' surface at 70 deg N with 500 m grid resolution. The reflectances used originate from the 8-day composite reflectances provided via https://wist.echo.nasa.gov/api/ as product: "MODIS surface Reflectance 8-Day L3 Global 500m SIN Grid V005". After gridding and flagging for clouds and other disturbances the artificial neural network was applied, providing fractions of three surface classes: 1) melt ponds, 2) sea ice and snow, and 3) open water at 500 m grid resolution. This data has been interpolated onto a similar polar-stereographic grid but with 12.5 km grid resolution.
The data set offered here comprises several data layers: the melt pond fraction, its standard deviation, the open water fraction, and the number of individual valid grid cells with 500 m grid resolution included in each 12.5 km grid cell. In addition, in three separate data layers melt pond fraction, its standard deviation, and the open water fraction are given with those grid cells (with 12.5 km grid resolution) flagged as invalid where less than 90 % of the native 500 m grid resolution data indicate clear sky conditions. Valid for all these layers is, that grid cells with an open water fraction larger than 85 % have been flagged as invalid as well.
The data set offered here is version 02 of the melt pond data set. The main difference to version 01 is a bias correction carried out to remove a positive bias in the melt pond fraction and in the open water fraction.
Project
CliSAP (Integrated Climate System Analysis and Prediction)
Contact
Dr. Stefan Kern (
 stefan.kern@nulluni-hamburg.de
)
Location(s)
Arctic Ocean
Spatial Coverage
Longitude 0 to 360 Latitude 60 to 90 Altitude: 0 m
Temporal Coverage
2000-05-08 to 2011-09-13 (calendrical)
Use constraints
For scientific use only
Data Catalog
World Data Center for Climate
Size
2.32 GiB (2486486680 Byte)
Format
NetCDF
Status
completely archived
Creation Date
Future Review Date
2025-09-12
Previous Version(s)
doi:10.1594/WDCC/MODIS__Arctic__MPF
Find data Export dataset acronyms
Cite as
Rösel, Anja; Kaleschke, Lars; Kern, Stefan (2015). Gridded Melt Pond Cover Fraction on Arctic Sea Ice derived from TERRA-MODIS 8-day composite Reflectance Data bias corrected Version 02. World Data Center for Climate (WDCC) at DKRZ. https://doi.org/10.1594/WDCC/MODIS__Arctic__MPF_V02

BibTeX RIS
Description
observational: Level3b - Gridded Geophysical Variable - Basic Quality Control
Accuracy and reliability of the offered data have been tested against a number of independent data comprising ship-based observations, air-borne observations, and satellite observations; results of these activities are published as Roesel, A., L. Kaleschke, and G. Birnbaum, 2012. Melt ponds on Arctic sea ice determined from MODIS satellite data using an artifical neural network. The Cryosphere, 6, 431-446, doi: 10.5194/tc-6-431-2012.
It was found in the meantime, however, that a positive bias existed in the melt pond fraction as well as in the open water fraction. Information about this bias is given in Maekynen, M., S. Kern, A. Roesel, and L. T. Pedersen, 2014, On the Estimation of Melt Pond Fraction on the Arctic sea ice with Envisat WSM images. IEEE Transactions on Geoscience and Remote Sensing, 52, 11, 7366-7349, doi: 10.1109/TGRS.2014.2311476 and in Kern, S., M. Zygmuntowska, K. Khvorostovsky, G. Spreen, N. Ivanova, and A. Beitsch, 2015, D4.1 Product Validation and Intercomparison Report (PVIR), ESA CCI sea ice ECV project report: SICCI-PVIR, v1.1, 25. Feb 2015: attached as Additional Information. Now the data set is in better agreement about published knowledge of snow melt and melt pond evolution onset.
Description
Temporal completeness:
The data set covers the entire EOS-TERRA MODIS time series from 2000-2011. The data is however limited to the melting period which is defined, for our data set as beginning at May 9 (May 8 in leap years) and ending at September 13 (September 12 in leap years). Data are missing for 8-day composites starting at June 18 and June 26 2001.
An update of the data set covering years 2012-2015 could not yet be carried out because a) of lack of funding and b) this would require to re-process the entire time series rather than just updating the data set which is based on MODIS Collection 5 radiances; in the meantime MODIS Collection 6 radiances with an improved cloud mask are available and should be used.

Spatial completeness:
Several factors, as are detailed below, limit the spatial coverage:
i) Limited day light and gaps in acquisition of the original MODIS data causes a data gap centered at the pole which has a varying latitudinal extent.
ii) Varying cloud cover and sea ice extent causes data gaps to occur allover the region.
iii) In order to focus on the Arctic Ocean regions south of 60°N are excluded.
Description
Summary:
Findable: 6 of 7 level
Accessible: 2 of 3 level
Interoperable: 4 of 4 level
Reusable: 4 of 10 level
Assessment Results: https://doi.org/10.35095/WDCC/F-UJI_results_WDCC
Method
F-UJI online v1.1.1 automated
Method Description
Checks performed by WDCC. Metrics documentation: https://doi.org/10.5281/zenodo.4081213 Metric Version: metrics_v0.4
Method Url
https://www.f-uji.net
Result Date
2021-05-05
Description
Assessment Results: https://doi.org/10.35095/WDCC/Results_from_FAIRness_eval https://fairshake.cloud/project/132/
Method
FAIRshake hybrid
Method Description
Checks performed by WDCC. Metrics documentation: doi:10.1016/j.cels.2019.09.011
Method Url
https://fairshake.cloud/
Result Date
2021-08-12
Description
Assessment Results: https://fairsharing.github.io/FAIR-Evaluator-FrontEnd/#!/evaluations search 'WDCC' https://doi.org/10.35095/WDCC/Results_from_FAIRness_eval
Method
FMES automated
Method Description
FAIR Maturity Evaluation Service (FMES) Checks performed by WDCC. Metrics documentation: doi:10.1038/s41597-019-0184-5
Method Url
https://fairsharing.github.io/FAIR-Evaluator-FrontEnd/#!/collections/new/evaluate
Result Date
2021-08-12
Description
Assessment Results: https://doi.org/10.35095/WDCC/Results_from_FAIRness_eval
Method
CFU manual
Method Description
Checklist for Evaluation of Dataset Fitness for Use. Checks performed by WDCC. Metrics documentation: https://doi.org/10.15497/rda00034
Result Date
2021-08-12
Description
Assessment Results: https://doi.org/10.35095/WDCC/Results_from_FAIRness_eval
Method
Self Assessment manual
Method Description
Checks performed by WDCC. Metrics documentation: https://doi.org/10.5334/dsj-2020-041
results are provided on AIC level (experiment, dataset_group and dataset (meta)data are combined for evaluation)
Result Date
2021-08-12
Description
There is no specific report about the horizontal accuracy of this data set available.
The data set is offered at a certain spatial resolution which should be regarded as a compromise between a reasonable spatial coverage with valid data and an as high as possible degree of resolving small-scale variations. The temporal resolution to 8-day composites poses limits to the spatial resolution and thus horizontal accuracy anyways.
Users should be aware of the fact that usage of an 8-day composite of clear-sky radiances could mean that the information retrieved for adjacent grid cells may originate, in extreme cases, from data of two different days which are 7 days apart.
Users interested in products at native spatial resolution (500 m) or finer temporal resolution (daily) should contact the author and/or the investigator (see above).
Result Date
2015-10-21
Description
1. Number of data sets is correct and > 0: passed;
2. Size of every data set is > 0: passed;
3. The data sets and corresponding metadata are accessible: passed;
4. The data sizes are controlled and correct: passed;
5. The temporal coverage description (metadata) is consistent to the data: passed;
6. The format is correct: passed;
7. Variable description and data are consistent: passed
Method
WDCC-TQA checklist
Method Description
Checks performed by WDCC. The list of TQA metrics are documented in the 'WDCC User Guide for Data Publication' Chapter 8.1.1
Method Url
https://www.wdc-climate.de/docs/WDCC_User_Guide_Data_v1.pdf
Result Date
2015-11-10
Contact typePersonORCIDOrganization
Contact
Dr. Stefan Kern
-
Center for Earth System Research and Sustainability, University of Hamburg
Author
Dr. Anja Rösel
-
University of Hamburg (IfM)
Author
Prof. Dr. Lars Kaleschke
0000-0001-7086-3299
Center for Earth System Research and Sustainability, University of Hamburg
Author
Dr. Stefan Kern
-
Center for Earth System Research and Sustainability, University of Hamburg
Investigator
Prof. Dr. Lars Kaleschke
0000-0001-7086-3299
University of Hamburg (IfM)
Originator
Dr. Anja Rösel
-
Center for Earth System Research and Sustainability, University of Hamburg
Hostinginstitution
-
-
University of Hamburg / ICDC
Contributor
-
-
University of Hamburg (IfM)
Contributor
-
-
University of Hamburg / ICDC
Contributor
-
-
University of Hamburg / CliSAP
Metadata
Dr. Stefan Kern
-
University of Hamburg (IfM)

Is new version of

[1] DOI MODIS__Arctic__MeltPondFraction__UHAM-CliSAP-ICDC__v01__12.5km__8day. (2015). doi:10.1594/WDCC/MODIS__Arctic__MPF

Is documented by

[1] DOI Rösel, A.; Kaleschke, L.; Birnbaum, G. (2012). Melt ponds on Arctic sea ice determined from MODIS satellite data using an artificial neural network. doi:10.5194/tc-6-431-2012
[2] DOI Makynen, Marko; Kern, Stefan; Rosel, Anja; Pedersen, Leif Toudal. (2014). On the Estimation of Melt Pond Fraction on the Arctic Sea Ice With ENVISAT WSM Images. doi:10.1109/TGRS.2014.2311476

Documents

[1] DOI Rösel, Anja. (2013). Detection of Melt Ponds on Arctic Sea Ice with Optical Satellite Data. doi:10.1007/978-3-642-37033-5
[2] Kern, S.; Zygmuntowska, M.; Khvorostovsky, K.; Spreen, G.; Ivanova, N.; Beitsch, A. (2015). D4.1 Product Validation and Intercomparison Report (PVIR), ESA CCI sea ice ECV project report: SICCI-PVIR, v1.1. http://esa-cci.nersc.no/webfm_send/262

Attached Datasets ( 1 )

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Additional Info

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Parent project(s)

Integrated Climate System Analysis and Prediction

[Entry acronym: MODIS__Arctic__MPF_V02] [Entry id: 3501558]