ATSR Reprocessing for Climate: Lake Surface Water Temperature & Ice Cover (ARC-Lake)

 

ARC-Lake is a European Space Agency (ESA) funded project that aims:

  • to use the exceptional radiometric qualities and dual-view scanning capability of the (A)ATSRs to derive observations of Lake Surface Water Temperature (LSWT) and Lake Ice Cover (LIC), for major lakes, globally, for 1991 – 2010;
  • and to demonstrate the usefulness of these observations to climate science

Lakes are a distinct category of target for remote sensing, and attempts to deliver LSWT as a by-product of sea surface temperature (SST) retrieval or land surface temperature (LandST) retrieval have not delivered sufficiently convincing results. Nonetheless, the potential exists for (A)ATSR LSWT/LIC to be a major contribution to monitoring of lakes within the Global Climate Observing System, because the (A)ATSRs are in principle capable to be a highly accurate source of information on LSWTs on a systematic global basis. LSWT and LIC observations have potential environmental and meteorological applications for inland water management and numerical weather prediction (NWP). They also offer the basis of a long term record of the physical state of lakes.

A number of different types of data product are available, from gridded observations on a lake-by-lake basis to global climatology. Data products derived from spatially complete reconstructions are available alongside those derived directly from the ARC-Lake observations. A summary of the possible variants is given below. Note that not all possible combinations are availble.

Table 1. Summary of possible ARC-Lake data files
Possible variants
Coverage Per-lake / Global
Source Observations / Reconstructions
Time Day / Night
Spatial Resolution 0.05 degree grid / Lake-mean
Temporal Averaging None / Climatology / Timeseries
Temporal Averaging Period Seasonal / Monthly / Twice-monthly / Daily

Extensive details of the data products available and their contents are provided in the documentation. The methodology and some validation results are presented in MacCallum and Merchant (under review) amd further details of aspects of the methodology are presented in the algorithm theoretical basis document.

The dataset is split into three components: (1) per-lake (2) global, and (3) ancillary.

  1. Per-lake contains data products on a lake-by-lake basis. A range of products are available, covering different spatial and temporal averaging for both observations and reconstructions.
  2. Version 2.0

    Version 1.1

  3. Global contains data products with global coverage (i.e. all lakes, where available, are included in the same product). As for the per-lake data, global data products are available with a range of different spatial and temporal averaging, for both observations and reconstructions. Note that equivalent global data products are not available for every possible type of per-lake data product.
  4. Version 2.0

    Version 1.1

  5. Ancillary contains the land/water mask used to determine the lake locations.
  6. Versions 1.1 and 2.0

Within each component the data is stored in zip archives. A full listing of the contents of each of these zip archives for v1.1 data is provided in ARCLake_DPFL_v1_1_2.pdf.

Additional information about the ARC-Lake project and some basic data analysis tools can be found on the project website: www.geos.ed.ac.uk/arclake

ARC-Lake v2.0 data products cover the period from 1st August 1991 to 31st December 2011.

ARC-Lake v1.1 data products cover the period from 1st June 1995 to 31st December 2009.

ARC-Lake v2.0 and v1.1 data products may be downloaded and used freely, but we ask that the dataset is referenced if used in any publications. Please reference as:

Version Citation
2.0 MacCallum, S. N., and Merchant, C. J. (2013). ARC-Lake v1.1, 1991-2011 [Dataset]. University of Edinburgh, School of GeoSciences / European Space Agency, http://hdl.handle.net/10283/88
1.1 MacCallum, S. N., and Merchant, C. J. (2011). ARC-Lake v1.1, 1995-2009 [Dataset]. University of Edinburgh, School of GeoSciences / European Space Agency, http://hdl.handle.net/10283/88

The methodolgy used to create these data products is outlined in the following paper:

MacCallum, S. N. and C. J. Merchant (2012), Surface Water Temperature Observations of Large Lakes by Optimal Estimation, Can J Remote Sensing, 38(1), 25 - 45. doi:10.5589/m12-010.
Available from http://pubs.casi.ca/doi/pdf/10.5589/m12-010

Update - 25/10/13 - ARC-Lake v3.0 data, covering 1995-2012 for over 1000 water bodies, is now available for download via http://www.geos.ed.ac.uk/arclake.

Recent Submissions

  • MacCallum, Stuart N; Merchant, Christopher J (University of Edinburgh, School of GeoSciences / European Space Agency, 2013-10-25)
  • MacCallum, Stuart N; Merchant, Christopher J (University of Edinburgh, School of GeoSciences / European Space Agency, 2013-10-25)
  • MacCallum, Stuart N; Merchant, Christopher J (University of Edinburgh, School of GeoSciences / European Space Agency, 2011-12-08)
  • MacCallum, Stuart N; Merchant, Christopher J (University of Edinburgh, School of GeoSciences / European Space Agency, 2011-12-08)
  • MacCallum, Stuart N; Merchant, Christopher J (University of Edinburgh, School of GeoSciences / European Space Agency, 2011-12-08)

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