Joel Jean-Marie Hirschi

On average flood events impact over 100 million people globally every year, and because of demographic changes and economic development in flood-prone areas, as well as climate change, the population exposed to flood risk is expected to double by 2050. Under anthropogenic climate change it is expected that flood events previously considered extreme will be occurring with more frequency, due to changing patterns of precipitation in a warming climate. It is, therefore, critically important to better understand how extreme weather events generate high river flows in exposed regions. Here we look specifically at the influence of precipitation from tropical cyclone (TC) activity on high river flows within one such exposed region: a 1.2 million km² area of South-east Asia encompassing the entirety of the Mekong and Red River catchments, plus 13 smaller catchments along the coastal fringe of Vietnam (collectively referred to here as the Greater Mekong region, or GMR). We use a hydrological model (GM-HYPE) with ERA5 precipitation data to simulate streamflows over the last 50 years (1970–2019) with, and without, TC-linked precipitation. Our results demonstrate that TC-linked precipitation around the GMR generate notable increases in high (95^th percentile) streamflows, and this is most notable in the steep sub-catchments draining to Vietnam’s northern coastline. These locations are more exposed to TC activity, and we determine that the elevated soil moisture levels there from monsoonal precipitation, prior to the typhoon season, are an exacerbating factor. Furthermore, trend analysis also shows that shifts in the spatial locations of TC-induced high river flows have been occurring since the 1970s: while statistically significant increases in TC-induced high river discharges are evident in localised regions of the GMR including the highlands of Laos and the Mekong’s delta region, declines in TC-induced high river discharges are much more widespread, with notable declines in the headwater and middle reaches of the Red and Mekong Rivers. Our findings on the changing pattern of high river flows in recent decades, in a region highly exposed to TCs, will be of great interest to strategic planners and flood managers. We conclude with a discussion on the impact of global climate model precipitation projections for this region, contrasting past/present (1980–2014), and future (2016–2050), GM-HYPE model results.

The Atlantic Meridional Overturning Circulation (AMOC) is a key component of the climate system, exhibiting strong variability across daily to millennial timescales and significantly influencing global climate. Sensitive to external conditions such as freshwater input, greenhouse gas concentrations, and aerosol forcing, important variations of the AMOC can be triggered by anthropogenic emissions. This study presents a comprehensive analysis of sources of AMOC variance in state-of-the-art climate ensemble models. By decomposing the effects of scenario, model, ensemble, and time variability, along with their interactions, through an Analysis of Variance (ANOVA) and by introducing a novel combination of the variance contributions based on physical considerations, we identify three distinct regimes of AMOC variability from 1850 to 2100. The first regime, spanning most of the historical period, is characterized by a relatively stable AMOC dominated by internal variability (i.e., ensemble spread). The second regime, initiated by AMOC decline at the end of the 20th century and lasting until mid-21st century, is governed by a transient increase of time variability. Notably, the direct effect of forcing scenario differences remains muted all along this regime, despite the start of emission-scenarios in 2015. The third regime, beginning around 2050, is marked by the emergence and rapid dominance of inter-scenario variability. Throughout the simulations, inter-model variability remains the primary source of uncertainty, influenced by aerosol forcing response, AMOC decline magnitude, and the physical variability. A key finding of this work is the evidence that internal variability decreases simultaneously with AMOC intensity and seems inversely proportional to emission-scenario intensity.

The ocean has absorbed over 90% of the excess heat trapped in the Earth system due to rising greenhouse gas emissions, with upper layers playing a crucial role. This study finds that 35% of the total ocean heat content (OHC) in the western Indian Ocean is stored within the upper 300 m. From 2000 to 2023, this layer shows a significant warming trend of over 24 years, making it the only tropical ocean basin with such a persistent rise. In contrast, the net surface heat flux into the ocean shows a declining trend of over 24 years, suggesting that direct atmospheric forcing is not the primary driver. Instead, seasonal ocean dynamics explains the observed increase in OHC and surface heat loss. During the winter monsoon, enhanced westward heat transport from the eastern equatorial Indian Ocean, driven by strengthened northeast monsoon currents, leads to heat accumulation in the western Indian Ocean. In the summer monsoon, the Great Whirl, a large anticyclonic eddy, plays a central role. Although northward heat transport associated with the Great Whirl has weakened, the southward transport has declined more sharply, resulting in net heat gain. Additionally, a northward shift in monsoon winds displaces the Great Whirl closer to the Socotra Islands, altering upwelling patterns and further redistributing heat. These findings underscore the dominant role of ocean circulation in driving long‐term upper‐ocean warming in the western Indian Ocean, contrasting with the expected influence of surface heat fluxes.

On average flood events impact over 100 million people globally every year, and because of demographic changes and economic development in flood-prone areas, as well as climate change, the population exposed to flood risk is expected to double by 2050. Under anthropogenic climate change it is expected that flood events previously considered extreme will be occurring with more frequency, due to changing patterns of precipitation in a warming climate. It is, therefore, critically important to better understand how extreme weather events generate high river flows in exposed regions. Here we look specifically at the influence of precipitation from tropical cyclone (TC) activity on high river flows within one such exposed region: a 1.2 million km² area of South-east Asia encompassing the entirety of the Mekong and Red River catchments, plus 13 smaller catchments along the coastal fringe of Vietnam (collectively referred to here as the Greater Mekong region, or GMR). We use a hydrological model (GM-HYPE) with ERA5 precipitation data to simulate streamflows over the last 50 years (1970–2019) with, and without, TC-linked precipitation. Our results demonstrate that TC-linked precipitation around the GMR generate notable increases in high (95^th percentile) streamflows, and this is most notable in the steep sub-catchments draining to Vietnam’s northern coastline. These locations are more exposed to TC activity, and we determine that the elevated soil moisture levels there from monsoonal precipitation, prior to the typhoon season, are an exacerbating factor. Furthermore, trend analysis also shows that shifts in the spatial locations of TC-induced high river flows have been occurring since the 1970s: while statistically significant increases in TC-induced high river discharges are evident in localised regions of the GMR including the highlands of Laos and the Mekong’s delta region, declines in TC-induced high river discharges are much more widespread, with notable declines in the headwater and middle reaches of the Red and Mekong Rivers. Our findings on the changing pattern of high river flows in recent decades, in a region highly exposed to TCs, will be of great interest to strategic planners and flood managers. We conclude with a discussion on the impact of global climate model precipitation projections for this region, contrasting past/present (1980–2014), and future (2016–2050), GM-HYPE model results.

On average flood events impact over 100 million people globally every year, and because of demographic changes and economic development in flood-prone areas, as well as climate change, the population exposed to flood risk is expected to double by 2050. Under anthropogenic climate change it is expected that flood events previously considered extreme will be occurring with more frequency, due to changing patterns of precipitation in a warming climate. It is, therefore, critically important to better understand how extreme weather events generate high river flows in exposed regions. Here we look specifically at the influence of precipitation from tropical cyclone (TC) activity on high river flows within one such exposed region: a 1.2 million km² area of South-east Asia encompassing the entirety of the Mekong and Red River catchments, plus 13 smaller catchments along the coastal fringe of Vietnam (collectively referred to here as the Greater Mekong region, or GMR). We use a hydrological model (GM-HYPE) with ERA5 precipitation data to simulate streamflows over the last 50 years (1970–2019) with, and without, TC-linked precipitation. Our results demonstrate that TC-linked precipitation around the GMR generate notable increases in high (95^th percentile) streamflows, and this is most notable in the steep sub-catchments draining to Vietnam’s northern coastline. These locations are more exposed to TC activity, and we determine that the elevated soil moisture levels there from monsoonal precipitation, prior to the typhoon season, are an exacerbating factor. Furthermore, trend analysis also shows that shifts in the spatial locations of TC-induced high river flows have been occurring since the 1970s: while statistically significant increases in TC-induced high river discharges are evident in localised regions of the GMR including the highlands of Laos and the Mekong’s delta region, declines in TC-induced high river discharges are much more widespread, with notable declines in the headwater and middle reaches of the Red and Mekong Rivers. Our findings on the changing pattern of high river flows in recent decades, in a region highly exposed to TCs, will be of great interest to strategic planners and flood managers. We conclude with a discussion on the impact of global climate model precipitation projections for this region, contrasting past/present (1980–2014), and future (2016–2050), GM-HYPE model results.

The ocean has absorbed over 90% of the excess heat trapped in the Earth system due to rising greenhouse gas emissions, with upper layers playing a crucial role. This study finds that 35% of the total ocean heat content in the western Indian Ocean is stored within the upper 300 meters. From 2000 to 2023, this layer shows a significant warming trend of 0.90 GJ/m^2 over 24 years, making it the only tropical ocean basin with such a persistent rise. In contrast, the net surface heat flux into the ocean shows a declining trend of -11.53 W/m^2 over 24 years, suggesting that direct atmospheric forcing is not the primary driver. Instead, seasonal ocean dynamics explain nearly 87% of the observed increase in ocean heat content and surface heat loss. During the winter monsoon, enhanced westward heat transport from the eastern equatorial Indian Ocean, driven by strengthened northeast monsoon currents, leads to heat accumulation in the western Indian Ocean. In the summer monsoon, the Great Whirl, a large anticyclonic eddy, plays a central role. Although northward heat transport associated with the Great Whirl has weakened, the southward transport has declined more sharply, resulting in net heat gain. Additionally, a northward shift in monsoon winds displaces the Great Whirl closer to the Socotra Islands, altering upwelling patterns and further redistributing heat. These findings underscore the dominant role of ocean circulation in driving long-term upper-ocean warming in the western Indian Ocean, contrasting with the expected influence of surface heat fluxes.

The Atlantic Meridional Overturning Circulation (AMOC) is a key component of the climate system, exhibiting strong variability across daily to millennial timescales and significantly influencing global climate. Sensitive to external conditions such as freshwater input, greenhouse gas concentrations, and aerosol forcing, important variations of the AMOC can be triggered by anthropogenic emissions. This study presents a comprehensive analysis of sources of AMOC variance in state-of-the-art climate ensemble models. By decomposing the effects of scenario, model, ensemble, and time variability, along with their interactions, through an Analysis of Variance (ANOVA), we identify three distinct regimes of AMOC variability from 1850 to 2100. The first regime, spanning most of the historical period, is characterized by a relatively stable AMOC dominated by internal variability. The second regime, initiated by AMOC decline at the end of the 20^th century and lasting until mid-21^st century, is governed by a transient increase of time variability. Notably, the direct effect of forcing differences remains muted all along this regime, despite the start of emission-scenarios in 2015. The third regime, beginning around 2050, is marked by the emergence and rapid dominance of inter-scenario variability. Throughout the simulations, model variability remains the primary source of uncertainty, influenced by aerosol forcing response, AMOC decline magnitude, and the physical variability. A key finding of this work is the evidence that internal variability decreases simultaneously with AMOC intensity and seems proportional to emission-scenario intensity.

We perform modelling experiments designed to decompose the historical buoyancy and momentum flux contributions to observed AMOC variability. Using NEMO, we have forced the model with interannually varying momentum fluxes, while keeping the buoyancy fluxes fixed with a repeat year forcing (momentum experiment), and then with interannual buoyancy forcing and repeat year momentum forcing (buoyancy experiment). These are compared to a full interannually forced control.Our analysis focuses on comparisons with the RAPID and OSNAP arrays to assess how well each of the momentum and buoyancy experiments matches AMOC variability at RAPID/OSNAP across different timescales. One key result is that decadal variability of AMOC is most dependent on buoyancy forcing, and that both momentum and buoyancy forcing are important for reproducing interannual variability.

The Atlantic Meridional Overturning Circulation (AMOC) is a key component of the climate system, exhibiting strong variability across daily to millennial timescales and significantly influencing global climate. Sensitive to external conditions such as freshwater input, greenhouse gas concentrations, and aerosol forcing, important variations of the AMOC can be triggered by anthropogenic emissions. This study presents a comprehensive analysis of sources of AMOC variance in state-of-the-art climate ensemble models. By decomposing the effects of scenario, model, ensemble, and time variability, along with their interactions, through an Analysis of Variance (ANOVA), we identify three distinct regimes of AMOC variability from 1850 to 2100. The first regime, spanning most of the historical period, is characterized by a relatively stable AMOC dominated by internal variability. The second regime, initiated by AMOC decline at the end of the 20th century and lasting until mid-21st century, is governed by a transient increase of time variability. Notably, the direct effect of forcing differences remains muted all along this regime, despite the start of emission-scenarios in 2015. The third regime, beginning around 2050, is marked by the emergence and rapid dominance of inter-scenario variability. Throughout the simulations, model variability remains the primary source of uncertainty, influenced by aerosol forcing response, AMOC decline magnitude, and the physical variability. A key finding of this work is the evidence that internal variability decreases simultaneously with AMOC intensity and seems proportional to emission-scenario intensity.