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The complex composition of hydrological systems, climates and landscapes makes it challenging to explain and predict hydrological streamflow response. Many previous large-sample studies, mostly focused on the United States, identified climate as the primary control, with landscape exerting only a minor role in shaping hydrological behaviour. Yet, a few other studies report contradictory results with landscape being a more dominant driver. In this study, we use an unprecedented sample of more than 7000 catchments in Europe from the EStreams dataset to identify and map functionally similar catchments, together with their spatially variable climate and landscape controls. The wide spatial and temporal gradient of the study catchments was used to identify hydrological response types (HRTs) based on 40 hydrological streamflow signatures related to long-term averages and inter-annual variability of magnitude, timing, duration, frequency, and seasonality. Overall, 10 HRTs could be identified. Several HRTs are well defined and well distinguishable, largely due to catchments with strongly seasonal or more extreme behaviour. Other HRTs remain difficult to distinguish, as these catchments represent more transitional conditions with increasingly overlapping characteristics between HRTs. The underlying drivers of the HRTs were identified by using 84 climate- and landscape attributes to predict catchment membership to their respective HRT with a Random Forest classification model. Climate emerges as the dominant driver of hydrological behaviour at the continental scale. However, landscape was found, in 4 out of 10 HRTs, to be at least as strong or even stronger a control on the hydrological streamflow response. These results highlight that the complex, integrated nature of hydrological response remains challenging to disentangle, even with extensive datasets and advanced modelling approaches, and therefore, climate and landscape need to be understood as joint drivers in a co-evolutionary perspective.
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The complex composition of hydrological systems, climates and landscapes makes it challenging to explain and predict hydrological streamflow response. Many previous large-sample studies, mostly focused on the United States, identified climate as the primary control, with landscape exerting only a minor role in shaping hydrological behaviour. Yet, a few other studies report contradictory results with landscape being a more dominant driver. In this study, we use an unprecedented sample of more than 7000 catchments in Europe from the EStreams dataset to identify and map functionally similar catchments, together with their spatially variable climate and landscape controls. The wide spatial and temporal gradient of the study catchments was used to identify hydrological response types (HRTs) based on 40 hydrological streamflow signatures related to long-term averages and inter-annual variability of magnitude, timing, duration, frequency, and seasonality. Overall, 10 HRTs could be identified. Several HRTs are well defined and well distinguishable, largely due to catchments with strongly seasonal or more extreme behaviour. Other HRTs remain difficult to distinguish, as these catchments represent more transitional conditions with increasingly overlapping characteristics between HRTs. The underlying drivers of the HRTs were identified by using 84 climate- and landscape attributes to predict catchment membership to their respective HRT with a Random Forest classification model. Climate emerges as the dominant driver of hydrological behaviour at the continental scale. However, landscape was found, in 4 out of 10 HRTs, to be at least as strong or even stronger a control on the hydrological streamflow response. These results highlight that the complex, integrated nature of hydrological response remains challenging to disentangle, even with extensive datasets and advanced modelling approaches, and therefore, climate and landscape need to be understood as joint drivers in a co-evolutionary perspective.
The Greenland ice sheet (GrIS) is an important component of the climate system and is a key contributor to future sea level rise, as it is storing frozen water that would raise sea levels by 7.4 m should it all melt (Bamber et al., 2018). Of particular concern is the amount of global warming we are facing now and in the future, as it is becoming more likely that even if our emissions are significantly reduced, global warming will reach at least 2∘𝐶 (Arias et al., 2021). Much research concerns the future contribution of the GrIS to sea level rise for high emissions scenarios and low emission scenarios, but there are few studies giving the main focus to what is becoming a more likely future, the moderate emissions scenarios. This research aims to quantify the mass loss of the Greenland ice sheet and subsequent contribution to future sea level rise under a moderate CO2 concentration scenario over a multimillennia timescale. An idealised simulation of 3000 years, where CO2 concentrations are increased by 1% annually until reaching two times pre-industrial values and then kept constant, is run with the high-resolution Community Earth System Model version 2.1 (CESM2.1) and Community Ice Sheet Model version 2.1 (CISM2.1). The climate, run with CESM2.1, is simulated for 1000 years. After 500 years, it is assumed that the climate is close to equilibrium, and thus one climate year is used for five years of forcing the ice sheet in CISM2.1, resulting in 3000 years of ice sheet simulation. At the end of the simulation, the global mean annual temperature has increased by 5∘𝐶 and the temperature over Greenland is 9∘𝐶 warmer than pre-industrial. The rate of sea level contribution in the first centuries is lower than the observed contemporary mass loss of 0.7 mm/yr (Shepherd et al., 2020) but increases after year 710 to a rate of 1 mm/yr. Another increase in mass loss is happening from the year 1380 until the end of the simulation where the rate is 2 mm/yr and the total contribution to sea level rise is 4.1 m. The limited mass loss in the period between years 71-400 and its increase thereafter is found to relate to temporal strong weakening and posterior recovery of the NAMOC. This study projects that the GrIS is a major contributor to future sea level rise, even in a moderate warming scenario, and that the changing NAMOC has a noteworthy effect on the GrIS mass budget.
...
The Greenland ice sheet (GrIS) is an important component of the climate system and is a key contributor to future sea level rise, as it is storing frozen water that would raise sea levels by 7.4 m should it all melt (Bamber et al., 2018). Of particular concern is the amount of global warming we are facing now and in the future, as it is becoming more likely that even if our emissions are significantly reduced, global warming will reach at least 2∘𝐶 (Arias et al., 2021). Much research concerns the future contribution of the GrIS to sea level rise for high emissions scenarios and low emission scenarios, but there are few studies giving the main focus to what is becoming a more likely future, the moderate emissions scenarios. This research aims to quantify the mass loss of the Greenland ice sheet and subsequent contribution to future sea level rise under a moderate CO2 concentration scenario over a multimillennia timescale. An idealised simulation of 3000 years, where CO2 concentrations are increased by 1% annually until reaching two times pre-industrial values and then kept constant, is run with the high-resolution Community Earth System Model version 2.1 (CESM2.1) and Community Ice Sheet Model version 2.1 (CISM2.1). The climate, run with CESM2.1, is simulated for 1000 years. After 500 years, it is assumed that the climate is close to equilibrium, and thus one climate year is used for five years of forcing the ice sheet in CISM2.1, resulting in 3000 years of ice sheet simulation. At the end of the simulation, the global mean annual temperature has increased by 5∘𝐶 and the temperature over Greenland is 9∘𝐶 warmer than pre-industrial. The rate of sea level contribution in the first centuries is lower than the observed contemporary mass loss of 0.7 mm/yr (Shepherd et al., 2020) but increases after year 710 to a rate of 1 mm/yr. Another increase in mass loss is happening from the year 1380 until the end of the simulation where the rate is 2 mm/yr and the total contribution to sea level rise is 4.1 m. The limited mass loss in the period between years 71-400 and its increase thereafter is found to relate to temporal strong weakening and posterior recovery of the NAMOC. This study projects that the GrIS is a major contributor to future sea level rise, even in a moderate warming scenario, and that the changing NAMOC has a noteworthy effect on the GrIS mass budget.
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