AbstractsAstronomy & Space Science

Recent studies, based on a combination of long-term in-situ and satellite derived temperature data indicate that lakes are rapidly warming at the global scale. Since Lake Surface Water Temperature (LSWT) is highly responsive to long-term modifications in the thermal structure of lakes, it is a good indicator of changes in lake characteristics. There have not been done many studies at a regional scale to understand the lakes’ response to climate change, mainly due to lack of high spatio-temporal data. Therefore, further studies are needed to understand variation in trends, impacts and consequences at a regional scale. It is essential to have highly frequent spatially explicit data to understand the spatio-temporal thermal variations of LSWT. Continuous in-situ water temperature data measured at high temporal resolution from permanently installed stations are becoming increasingly available through GLEON (Global Lake Ecological Observatory Network) or NetLake (Networking Lake Observatories in Europe). But these data are often heterogeneous with different sources and time line, point based, and not available for many lakes around the globe. To establish permanent weather stations for all the large lakes in the world is also not economically viable. As an alternative to direct measurements, remote sensing is considered as a promising approach to reconstruct complete time series of LSWT where direct measurements are missing. Temperature of land/water surfaces is one of the direct and accurate measurements using satellite data acquired in the thermal infra-red spectral region. Furthermore, the availability of daily satellite data since the 1980s at a moderate resolution of 1 km from multiple polar orbiting satellites is an opportunity not to be missed. But owing to the complexities related to earlier satellite missions, and the need of high level of processing, the potential of the historical satellite data in deriving a homogenised LSWT is still not explored well. There is a gap in the availability of long-term time series of LSWT from the satellite data which could be used in understanding the patterns and drivers of thermal variations in large lakes. This thesis aims to fill this gap by developing reproducible and extendable methods to derive homogenised daily LSWT for thirty years from 1986 to 2015. Hence, the main objectives of this thesis are i) to reconstruct thirty years (1986-2015) of daily satellite thermal data as a homogenised time series of LSWT for five large Italian lakes by combining thermal data from multiple satellites, ii) to assess the quality of the satellite derived LSWT using long-term in-situ data collected from the same lakes, iii) to report the seasonal and annual trends in LSWT using robust statistical tests. The first part of the thesis deals with the accurate processing of historical Advanced Along-Track Scanning Radiometer (AVHRR) sensor data to derive time series of LSWT. A new method to resolve the complex geometrical issues with the earlier AVHRR data obtained from National Oceanic…