Satellite-derived multivariate world-wide lake physical variable timeseries for climate studies (original) (raw)
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Scientific Data, 2015
Global environmental change has influenced lake surface temperatures, a key driver of ecosystem structure and function. Recent studies have suggested significant warming of water temperatures in individual lakes across many different regions around the world. However, the spatial and temporal coherence associated with the magnitude of these trends remains unclear. Thus, a global data set of water temperature is required to understand and synthesize global, long-term trends in surface water temperatures of inland bodies of water. We assembled a database of summer lake surface temperatures for 291 lakes collected in situ and/or by satellites for the period 1985-2009. In addition, corresponding climatic drivers (air temperatures, solar radiation, and cloud cover) and geomorphometric characteristics (latitude, longitude, elevation, lake surface area, maximum depth, mean depth, and volume) that influence lake surface temperatures were compiled for each lake. This unique dataset offers an invaluable baseline perspective on global-scale lake thermal conditions as environmental change continues. Design Type(s) time series design • Observational study Measurement Type(s) temperature Technology Type(s) Thermistor Device Component
2022
Lake surface temperature (LST) is an important attribute that highlights regional weather and climate variability and trends. The spatial resolution and thermal sensors on Landsat platforms provide the capability of monitoring the temporal and spatial distribution of lake surface temperature on small to medium size lakes. In this study, a retrieval algorithm was applied to the thermal bands of Landsat archives to generate a LST dataset (North Slave LST dataset) for 535 lakes in the North Slave Region (NSR) of the Northwest Territories (NWT), Canada for the period of 1984 to 2021. North Slave LST was retrieved from Landsat-5 TM, Landsat-7 ETM+ and Landsat-8 OLI/TIRS, however majority of the dataset were created from the thermal bands of Landsat-5 (43%) due to its longevity (1984-2013). Cloud masks were applied to Landsat images to eliminate cloud cover. In addition, a 100-meter inward buffer was applied to lakes to prevent pixel mixing with shorelines. To evaluate the algorithm applied, retrieved LST was compared with in-situ data and Moderate Resolution Imaging Spectroradiometer (MODIS) LST observations. A good agreement was observed between in-situ observations and North Slave LST derived in this study with a mean bias of 0.12 °C and an RMSD of 1.7 °C. The North Slave LST dataset contains more available data from warmer months (May to September), covering 57.3 % in comparison to colder months (October to April). Average number of images per year for each lake across the NSR ranged from 20 to 45. The North Slave LST dataset will provide communities, scientists and stakeholders with spatial and temporal changing trends of temperature on lakes for the past 38 years.
Recent Advances in Remote Sensing, 2024
The Lake Surface Water Temperature (LSWT) evolution is analysed in ten of the largest lakes innthe world: Caspian Sea, Superior, Victoria, Huron, Michigan, Tanganyika, Baikal, Great Slave Lake, Erie and Ontario. The time span selected is 2003-2020 and the satellite product, MODIS Level 3 SST Thermal IR 8 Day 4km V2019.0. Results show warming trends ranging from 0.012◦C/yr. in the Victoria Lake to 0.083 ◦C/yr in the Baikal Lake. Results have been validated with the product MOD11L2 LSWT estimations for the years 2003-2014 in the Laurentian Great Lakes, obtaining correlations between 0.962 and a 0.998. The validation has been enlarged by considering Sentinel 3 observations from the Issyk-Kul lake, with a 0.99 correlation. The validation shows that the MODIS SST product is capable of estimating the LSWT parameter with a high precision.
Remote Sensing of Environment, 2012
Lakes are major repositories of biodiversity, provide multiple ecosystem services and are widely recognised as key indicators of environmental change. However, studies of lake response to drivers of change at a pan-European scale are exceptionally rare. The need for such studies has been given renewed impetus by concerns over environmental change and because of international policies, such as the EU Water Framework Directive (WFD), which impose legal obligations to monitor the condition of European lakes towards sustainable systems with good ecological status. This has highlighted the need for methods that can be widely applied across large spatial and temporal scales and produce comparable results. Remote sensing promises much in terms of information provision, but the spatial transferability and temporal repeatability of methods and relationships observed at individual or regional case studies remains unproven at the continental scale. This study demonstrates that NOAA Advanced Very High Resolution Radiometer (AVHRR) thermal data are capable of producing highly accurate (R 2 > 0.9) lake surface temperature (LST) estimates in lakes with variable hydromorphological characteristics and contrasting thermal regimes. Validation of the approach using archived AVHRR thermal data for Lake Geneva produced observations that were consistent with field data for equivalent time periods. This approach provides the basis for generalizing temporal and spatial trends in European lake surface temperature over several decades and confirms the potential of the full 30 year NOAA AVHRR archive to can provide AVHRR-derived LST estimates to help inform European policies on lake water quality. 0 10 20 30 J M M J A O D J M M J A O D
USING SATELLITE DATA TO SUPPORT THE MONITORING AND ADMINISTRATION OF LAKES
The Danish national monitoring program seeks for new solutions for cost-effective monitoring of the more than 600 lakes (> 5 ha) in Denmark. Current monitoring builds solely upon in situ sampling, but only ca. 15% of the lakes can be annually covered with this approach. In this study we show the potential of Landsat 8-derived chlorophyll a (chl-a) estimates to expand conventional monitoring -spatially and temporally. A statistical model was applied on a time series of Landsat 8 data covering April-October 2013. Satellite-based chl-a concentrations were then compared to in situ sampled data. To make this information accessible to the Danish environmental administration it will be integrated into an administration tool together with traditional survey data for decision-making and cost-efficient monitoring of Danish freshwaters under the EU Water Framework Directive.
Delivering the Lake Essential Climate VariableAn update from ESA CCI Lakes
2019
Poster at CLIMRISK19, Trento TheLakesCCIprojectispartoftheClimateChangeInitiative(CCI)EuropeanSpaceAgency(ESA)andrunforthreeyears.<br> Mainobjectiveistoexploitsatellitedatatocreatethelargestandlongestpossibleconsistent,globalrecordofthefivelakevariables:lakewaterlevel(LWL),extent(LWE),temperature(LSWT),surface-leavingreflectance(LWLR),andicecover(LIC).
Rapid and highly variable warming of lake surface waters around the globe
Geophysical Research Letters, 2015
In this first worldwide synthesis of in situ and satellite-derived lake data, we find that lake summer surface water temperatures rose rapidly (global mean = 0.34°C decade−1) between 1985 and 2009. Our analyses show that surface water warming rates are dependent on combinations of climate and local characteristics, rather than just lake location, leading to the counterintuitive result that regional consistency in lake warming is the exception, rather than the rule. The most rapidly warming lakes are widely geographically distributed, and their warming is associated with interactions among different climatic factors—from seasonally ice-covered lakes in areas where temperature and solar radiation are increasing while cloud cover is diminishing (0.72°C decade−1) to ice-free lakes experiencing increases in air temperature and solar radiation (0.53°C decade−1). The pervasive and rapid warming observed here signals the urgent need to incorporate climate impacts into vulnerability assessments and adaptation efforts for lakes.
Remote Sensing, 2021
Evaluation of the impact of climate change on water bodies has been one of the most discussed open issues of recent years. The exploitation of satellite data for the monitoring of water surface temperatures, combined with ground measurements where available, has already been shown in several previous studies, but these studies mainly focused on large lakes around the world. In this work the water surface temperature characterization during the last few decades of two small–medium Italian lakes, Lake Bracciano and Lake Martignano, using satellite data is addressed. The study also takes advantage of the last space-borne platforms, such as Sentinel-3. Long time series of clear sky conditions and atmospherically calibrated (using a simplified Planck’s Law-based algorithm) images were processed in order to derive the lakes surface temperature trends from 1984 to 2019. The results show an overall increase in water surface temperatures which is more evident on the smallest and shallowest o...
Hydrological Processes, 2020
In this study, data from MODIS land surface temperature product level 3 (MOD11A2) were used to investigate the spatiotemporal variation of Eurasian lakes water surface temperature (LWST) from 2001 to 2015, and to examine the most influencing factors of that variation. The temperature of most lakes in the dry climate zone and in the equatorial climatic zone varied from 17 to 31°C and from 23 to 27°C, respectively. LWSTs in the warm temperate and cold climatic zones were in the range of 20 to 27°C and-0.6 and 17°C, respectively. The average daytime LWST in the polar climate zone was-0.71°C in the summer. Lakes in high latitude and in the Tibetan Plateau displayed low LWST, ranging from-11°C to 26°C during the nighttime. Large spatial variations of diurnal temperature difference (DTD) was observed in lakes across Eurasia. However, variations in DTDs were small in lakes located in high latitude and in tropical rainforest regions. The shallow lakes showed a rapid response of LWST to solar and atmospheric forcing, while in the large and deep lakes, that response was sluggish. Results of this study demonstrated the applicability of remote sensing and MODIS LST products to capture the spatial-temporal variability of LWST across continental scales, in particular for the vast wilderness areas and protected environment in high latitude regions of the world. The approach can be used in future studies examining processes and factors controlling large scale variability of LWST.