For most of the last century, traditional limnological research has heavily relied on fieldwork, with a relatively small fraction of lakes subjected to extensive, in-depth investigations. High temporal resolution and long-term in-situ observations, often combined with well-calibrated and validated models, have so far provided detailed knowledge of the physics and ecology governing the overall behavior of a few lakes worldwide.
The latest advancements in limnological research have demonstrated the potential for upscaling from single-lake studies to global-scale applications. Such advancements have been made possible through the synoptic-scale coverage and availability of remote sensing products integrated with numerical modeling, as well as the development of global-scale datasets of in-situ observations. While remote sensing data primarily informs on surface features, coupling with models has enabled its extensive use in inspecting internal dynamics and shifts in mixing regimes.
In the current context of limnological research, a global approach is emerging as a means to assess the impacts of anthropogenic activities on both the quantity and quality of lake waters. However, upscaling inevitably introduces uncertainties and inaccuracies, raising concerns about the reliability of global conclusions at the single-lake scale.
This session welcomes contributions that apply an upscaled approach to limnological research. We invite studies that employ global datasets of satellite-derived or in-situ lake variables, physically based models, as well as hybrid models or AI-based algorithms, to draw conclusions on the past and/or future behavior of lakes at regional to global scales, analyzing long-term changes or studying the effects of extreme events. Emphasis will be placed on contributions that stimulate discussion about the limits, current challenges, and overall opportunities and potentialities of limnological investigations at global scales.
The latest advancements in limnological research have demonstrated the potential for upscaling from single-lake studies to global-scale applications. Such advancements have been made possible through the synoptic-scale coverage and availability of remote sensing products integrated with numerical modeling, as well as the development of global-scale datasets of in-situ observations. While remote sensing data primarily informs on surface features, coupling with models has enabled its extensive use in inspecting internal dynamics and shifts in mixing regimes.
In the current context of limnological research, a global approach is emerging as a means to assess the impacts of anthropogenic activities on both the quantity and quality of lake waters. However, upscaling inevitably introduces uncertainties and inaccuracies, raising concerns about the reliability of global conclusions at the single-lake scale.
This session welcomes contributions that apply an upscaled approach to limnological research. We invite studies that employ global datasets of satellite-derived or in-situ lake variables, physically based models, as well as hybrid models or AI-based algorithms, to draw conclusions on the past and/or future behavior of lakes at regional to global scales, analyzing long-term changes or studying the effects of extreme events. Emphasis will be placed on contributions that stimulate discussion about the limits, current challenges, and overall opportunities and potentialities of limnological investigations at global scales.