Dataset
GloboLakes: Lake Surface Water Temperature (LSWT) v4.0 (1995-2016)
Abstract
Global Observatory of Lake Responses to Environmental Change (GloboLakes) was a project funded by the Natural Environment Research Council (NERC) with the following grant references: NE/J023345/2, NE/J02211X/1, NE/J023396/1, NE/J021717/1 and NE/J022810/1.
This dataset contains the GloboLakes LSWT v4.0 of daily observations of Lake Surface Water Temperature (LSWT), its uncertainty and quality levels. The LSWTs are obtained by combining the orbit data from the AVHRR (Advanced Very High Resolution Radiometer) on MetOpA, AATSR (Advanced Along Track Scanning Radiometer) on Envisat and ATSR-2 (Along Track Scanning Radiometer) on ERS-2 (European Remote Sensing Satellite). The temperatures from the different instruments have been derived with the same algorithm and harmonised to insure consistency for the period 1995-2016. The GloboLakes LSWT v4.0 was produced by the University of Reading in 2018 for long term observations of surface water temperature for about 1000 lakes globally.
The dataset consist of two sets of files: 1) a single file per day on a 0.05° regular latitude- longitude grid covering the period from June 1995 to December 2016 (folder = daily), 2) a file per lake which contains the time series (daily) of the lake on a 0.05° regular grid (folder = per-lake). The list of the GloboLakes lakes is included as a CSV file and it contains name, GLWD identifier, coordinate of the lake centre and a set of coordinates that can be used to locate the lake in the daily-file dataset. The LSWTs consists of the daily observations of the temperature of the water (skin temperature). Uncertainty estimates and quality levels are provided for each value.
Details
Previous Info: |
No news update for this record
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Previously used record identifiers: |
No related previous identifiers.
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Access rules: |
Access to these data is available to any registered CEDA user. Please Login or Register for a CEDA account to gain access.
Use of these data is covered by the following licence(s): http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/ When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record. |
Data lineage: |
Data were processed by the University of Reading within the GloboLakes project and deposited at the Centre for Environmental Data Analysis (CEDA) for archiving. |
Data Quality: |
Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).
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File Format: |
Data are NetCDF formatted and a metadata file describing the lake ID's and locations that is BADC-CSV formatted.
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Related Documents
Citations: 9
The following citations have been automatically harvested from external sources associated with this resource where DOI tracking is possible. As such some citations may be missing from this list whilst others may not be accurate. Please contact the helpdesk to raise any issues to help refine these citation trackings.
Bernus, A. & Ottlé, C. (2022) Modeling subgrid lake energy balance in ORCHIDEE terrestrial scheme using the FLake lake model. Geoscientific Model Development 15, 4275–4295. https://doi.org/10.5194/gmd-15-4275-2022 https://doi.org/10.5194/gmd-15-4275-2022 |
Jia, T., Yang, K., Peng, Z., Tang, L., Duan, H. & Luo, Y. (2022) Review on the Change Trend, Attribution Analysis, Retrieval, Simulation, and Prediction of Lake Surface Water Temperature. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 15, 6324–6355. https://doi.org/10.1109/jstars.2022.3188788 https://doi.org/10.1109/jstars.2022.3188788 |
Lee, H., Ganbat, G., Jin, H., Seo, J.M., Moon, S., Bok, H. & Baik, J. (2023) Effects of Lake Baikal on Summertime Precipitation Climatology Over the Lake Surface. Geophysical Research Letters 50. https://doi.org/10.1029/2023gl103426 https://doi.org/10.1029/2023gl103426 |
Shi, Y., Huang, A., Ma, W., Wen, L., Zhu, L., Yang, X., Wu, Y. & Gu, C. (2022) Drivers of Warming in Lake Nam Co on Tibetan Plateau Over the Past 40 Years. Journal of Geophysical Research: Atmospheres 127. https://doi.org/10.1029/2021jd036320 https://doi.org/10.1029/2021jd036320 |
Wang, S., He, Y., Hu, S., Ji, F., Wang, B., Guan, X. & Piccolroaz, S. (2021) Enhanced Warming in Global Dryland Lakes and Its Drivers. Remote Sensing 14, 86. https://doi.org/10.3390/rs14010086 https://doi.org/10.3390/rs14010086 |
Wang, X., Shi, K., Qin, B., Zhang, Y. & Woolway, R.I. (2024) Disproportionate impact of atmospheric heat events on lake surface water temperature increases. Nature Climate Change. https://doi.org/10.1038/s41558-024-02122-y https://doi.org/10.1038/s41558-024-02122-y |
Woolway, R.I., Jennings, E. & Carrea, L. (2020) Impact of the 2018 European heatwave on lake surface water temperature. Inland Waters 10, 322–332. https://doi.org/10.1080/20442041.2020.1712180 https://doi.org/10.1080/20442041.2020.1712180 |
Woolway, R.I., Kraemer, B.M., Lenters, J.D., Merchant, C.J., O’Reilly, C.M. & Sharma, S. (2020) Global lake responses to climate change. Nature Reviews Earth & Environment 1, 388–403. https://doi.org/10.1038/s43017-020-0067-5 https://doi.org/10.1038/s43017-020-0067-5 |
Woolway, R.I., Kraemer, B.M., Zscheischler, J. & Albergel, C. (2021) Compound hot temperature and high chlorophyll extreme events in global lakes. Environmental Research Letters 16, 124066. https://doi.org/10.1088/1748-9326/ac3d5a https://doi.org/10.1088/1748-9326/ac3d5a |
Process overview
Instrument/Platform pairings
ATSR2 | Deployed on: European Remote Sensing satellite 2 - ERS-2 |
AATSR | Deployed on: Envisat |
AVHRR series | Deployed on: Metop-A |
Mobile platform operations
Mobile Platform Operation 1 | Mobile Platform Operation for: Envisat |
Mobile Platform Operation 2 | Mobile Platform Operation for: ERS-2 |
Mobile Platform Operation 3 | Mobile Platform Operation for: Metop-A |
Output Description | None |
- long_name: Global Lakes and Wetlands Database (GLWD) identifiers
- units: 1
- long_name: Lake ID
- standard_name: lake_identifier
- var_id: lakeid
- units: Kelvin
- long_name: Total uncertainty
- standard_name: lake_surface_water_temperature_uncertainty
- var_id: lswt_uncertainty
- long_name: bias correction flag
- standard_name: instrument_bias_correction_flag
- var_id: flag_bias_correction
- long_name: country
- long_name: lake name
- units: Kelvin
- long_name: lake surface skin temperature
- standard_name: lake_surface_water_temperature
- var_id: lake_surface_water_temperature
- long_name: latitude of the lake centre
- long_name: longitude of the lake centre
- long_name: maximum distance to the closest land of the centre
- long_name: maximum latitude of a box to locate the lake
- long_name: maximum longitude of a box to locate the lake
- long_name: minimum latitude of a box to locate the lake
- long_name: minimum longitude of a box to locate the lake
- long_name: observation instruments
- standard_name: instrument_for_observation
- var_id: obs_instr
- var_id: quality_level
- long_name: quality levels
- standard_name: lake_surface_water_temperature_quality_level
Co-ordinate Variables
- units: degrees_north
- standard_name: latitude
- long_name: latitude
- var_id: lat
- units: degrees_east
- standard_name: longitude
- long_name: longitude
- var_id: lon
- standard_name: time
- var_id: time
- long_name: reference time of the lswt file
Temporal Range
1995-05-31T23:00:00
2016-12-31T23:59:59
Geographic Extent
90.0000° |
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-180.0000° |
180.0000° |
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-90.0000° |