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Near-Real Time Lake Surface Water Temperature product monitoring
The NRT CGLOPS LSWT is generated from brightness temperatures observed by the SLSTR instruments onboard Sentinel3A and Sentinel3B.
The monitoring of the CGLOPS NRT LSWT product consists of a comparison with the climatology only for the lake centre and an inspection of the spatial plot for the current dekead presented in Latest Observations.
Anothor important aspect of the monitoring is the timeliness and the completeness of the SLSTR instrument L1b data at the time of processing. The plots for the monitoring are reported in Product Completeness.
Latest Observations
The interactive table below provides the latest LSWT information for each CGLOPS lake. You can search for any CGLOPS lakes by using the search criteria selections boxes below, by clicking on the map, or by scrolling through the table. The small circle on the spatial plots (far two right-hand columns) indicate the lake centre. Please note that the table may take a while to load.
Verification
Monitoring global LSWT is important to identify extreme temperature values that are associated with actual changes in LSWT or potential issues with the SLSTR satellites and LSWT retrieval methods. As such, to support the monitoring of the CGLOPS LSWT product, routine checks are now performed to identify lakes with anomalous LWST. The figure below gives the location of lakes where the dekadal mean LSWT value exceeds +/- 3 standard deviations from the 1995-2020 climatology (calculated on a pixel basis). Only those lakes where greater than 10% of the lake area exceeding this threshold have been flagged. For each lake that meets these criteria, the colour of the circle indicates the mean LSWT anomaly (left-hand column) and percentage of lake area exceeding the threshold (right-hand column).
Past dekadal LSWT verifcation plots can be found here.
Product Completeness
Each LSWT dekad (10-day) product is derived from multiple 3-minute satellite SLSTR granules (Sentinel3A and Sentinel3B). Due to the requirement to generate the dekadal product within 3 days after the end of each dekad, it is not always possible to process all available granules in time. There are two types of granules used in the LSWT product generation, based on their timeliness (further details avaiable here):
- The Near Real Time (NRT) timeliness implies a delivery in less than 3 hours after data acquisition.
- The Non-Time Critical (NTC) timeliness is typically defined for deliveries within 1 month after data acquisition (although in practice this is several days). This additional delay allows consolidation of some auxiliary or ancillary data (e.g. precise orbit data)
Temporal completeness
Spatial completeness
The points on the map below indicate the centre point of the granules used in the LSWT product. Only those granules which contain CGLOPS lakes are included. Further details on the SLSTR granule coverage can be found here.
Temporal completeness for previous months since the start of May 2020 (delayed assessment accounting for missed granules)
Missed granules are any granules (NRT or NTC) that have not been included in the LSWT dekadal product due to them not being available for processing during generation of the LSWT dekadal product. Typically, these will occur at the end of the dekad. The NRT LSWT files up until the end of April 2020 have been reprocessed using all available granules, so do not suffer from missing granules. Temporal completeness plots for thr NRT LSWT files prior May 2020 before they were reprocessed can be found here.
(SLSTR-A and SLSTR-B)
December 2023 (SLSTR-A and SLSTR-B) |
November 2023 (SLSTR-A and SLSTR-B) |
October 2023 (SLSTR-A and SLSTR-B) |
September 2023 (SLSTR-A and SLSTR-B) |
August 2023 (SLSTR-A and SLSTR-B) |
July 2023 (SLSTR-A and SLSTR-B) |
June 2023 (SLSTR-A and SLSTR-B) |
May 2023 (SLSTR-A and SLSTR-B) |
April 2023 (SLSTR-A and SLSTR-B) |
March 2023 (SLSTR-A and SLSTR-B) |
February 2023 (SLSTR-A and SLSTR-B) |
January 2023 (SLSTR-A and SLSTR-B) |
December 2022 (SLSTR-A and SLSTR-B) |
November 2022 (SLSTR-A and SLSTR-B) |
October 2022 (SLSTR-A and SLSTR-B) |
September 2022 (SLSTR-A and SLSTR-B) |
August 2022 (SLSTR-A and SLSTR-B) |
July 2022 (SLSTR-A and SLSTR-B) |
June 2022 (SLSTR-A and SLSTR-B) |
May 2022 (SLSTR-A and SLSTR-B) |
April 2022 (SLSTR-A and SLSTR-B) |
March 2022 (SLSTR-A and SLSTR-B) |
February 2022 (SLSTR-A and SLSTR-B) |
January 2022 (SLSTR-A and SLSTR-B) |
December 2021 (SLSTR-A and SLSTR-B) |
November 2021 (SLSTR-A and SLSTR-B) |
October 2021 (SLSTR-A and SLSTR-B) |
September 2021 (SLSTR-A and SLSTR-B) |
August 2021 (SLSTR-A and SLSTR-B) |
July 2021 (SLSTR-A and SLSTR-B) |
June 2021 (SLSTR-A and SLSTR-B) |
May 2021 (SLSTR-A and SLSTR-B) |
April 2021 (SLSTR-A and SLSTR-B) |
March 2021 (SLSTR-A and SLSTR-B) |
February 2021 (SLSTR-A and SLSTR-B) |
January 2021 (SLSTR-A and SLSTR-B) |
December 2020 (SLSTR-A and SLSTR-B) |
November 2020 (SLSTR-A and SLSTR-B) |
October 2020 (SLSTR-A and SLSTR-B) |
September 2020 (SLSTR-A and SLSTR-B) |
21st-31st August 2020 (SLSTR-A and SLSTR-B) |
1st-20th August 2020 (SLSTR-A only) |
July 2020 (SLSTR-A only) |
June 2020 (SLSTR-A only) |
May 2020 (SLSTR-A only) |