Approximately Double Increase in Flood Risk Under a 1.5°C/2.0°C Warmer Climate Over the Huai River Basin, China

Global warming has substantial effects on humans and ecosystems through changes in extreme events. China is a densely populated region with complex geographical characteristics, making it crucial to assess the changes in extreme events in China under various global warming scenarios. This study utilises 20 CMIP6 models to investigate how extreme heat and precipitation events in China are impacted by weak and strong global warming. The extreme heat indices in China are consistently on the rise in terms of their intensity, frequency, and duration. High latitude regions demonstrate a greater increase in intensity, whereas the Tibetan Plateau exhibits the most significant rise in frequency and duration. The rise of extreme precipitation indices is more distinct in the coastal area and less in the interior, consistent with the “dry gets drier, wet gets wetter”. Furthermore, there is a noteworthy increase in extreme precipitation in the Tibetan Plateau, which may be associated with glacial meltwater or the influence of the Indian monsoon.

Increased population exposures to extreme precipitation in Central Asia under 1.5 ℃ and 2 ℃ global warming scenarios

This study evaluates flood susceptibility and risk on Bulk Supply Points in the Greater Accra region (GAR) using a Frequency Ratio model based on 15 flood conditioning factors. The model explores the influence of natural, meteorological and anthropogenic factors on flooding occurrences under the Shared Socioeconomic Pathway (SSP) scenarios and assesses flood risks at Bulk Supply Points (BSPs). Flood susceptibility mapping was conducted for both current and future periods under various SSP scenarios. Results reveal that elevation, slope, soil type, distance from urban areas, and SPI are the most influential factors contributing to flooding susceptibility in the region. The current flood map, about 37% of the total area of GAR categorized under the moderate flood-susceptible zone category followed by about 30% categorized under the low flood-vulnerable zone. However, about 16% was categorized under the very high flood-vulnerable zone. The study projects increasing flood susceptibility under the SSP scenarios with intensification under SSP2 and SSP3 scenarios. For instance, the areas categorized as high and very high flood susceptibility zones are projected to expand to approximately 32% and 26% each by 2055 under SSP3. The study also assesses flood risks at Bulk Supply Points (BSPs), highlighting the escalating susceptibility of power assets to flooding under different scenarios. For instance, in the very high scenario, flooding is estimated to reach 640 h in 2045 and exceed 800 h in 2055—more than double the 2020 baseline. The analysis shows the bulk supply points face increasing flood susceptibility, with risks escalating most sharply under the severe climate change SSP3 and SSP5 scenarios. Over 75% of BSPs are expected to fall in the low- to medium-risk categories across SSPs while more than 50% of BSPs are within medium- to high-risk categories in all scenarios except SSP1, reflecting the impact of climate change. SSP3 and SSP5 stand out with over 60% of BSPs facing high or very high flooding risks by 2055. It indicates moderate resilience with proper adaptation but highlights potential disruptions in critical infrastructure, such as BSPs, during persistent flooding. The findings of the study are expected to inform Ghana’s contributions towards addressing Sustainable Development Goals (SDGs) 7, 11 and 13 in Ghana.

Quantifying future precipitation changes in central Asia (CA), one of the largest semiarid‐to‐arid regions in the world, is increasingly attracting attention. Extreme precipitation changes in CA have been studied based on global climate models (GCMs) in the Coupled Model Intercomparison Project (CMIP). However, quantitative information regarding projected changes in extreme precipitation in CA under the 1.5–4°C global warming scenario is lacking; the potential advantages of the latest‐generation GCMs (i.e., CMIP6) in characterizing precipitation in CA have not been investigated. Thus, in this study, we evaluated the models' overall performance in reproducing the spatiotemporal pattern of four extreme precipitation indices and further performed an observationally constrained projection of changes in extreme precipitation indices for 1.5–4°C global warming based on a weighted multimodel ensemble. Regarding homologous models, CMIP6 models exhibited limited improvement relative to their earlier versions in CMIP5. We project that extreme precipitation indices in CA will increase approximately linearly as global warming increases, except for the consecutive dry days (CDD) index. The changes in precipitation intensity and accumulation exhibit robust consistency between models, whereas the signal of CDD changes is masked by the noise produced by intermodel uncertainties. The changes in the average annual accumulated and maximum 1‐day precipitation relative to the reference period (1981–2010) in CA are 12.0 and 14.2% at 3°C global warming (similar to late‐century warming projected based on current mitigation policies), respectively. Moreover, we demonstrate the advantage of the weighted scheme over the traditional unweighted scheme for multimodel ensemble projection.

Floods and droughts are more closely related to the extreme precipitation over longer periods of time. The spatial and temporal changes and frequency analysis of 5-day and 10-day extreme precipitations (PX5D and PX10D) in the Huai River basin (HRB) are investigated by means of correlation analysis, trend and abrupt change analysis, EOF analysis, and hydrological frequency analysis based on the daily precipitation data from 1960 to 2014. The results indicate (1) PX5D and PX10D indices have a weak upward trend in HRB, and the weak upward trend may be due to the significant downward trend in the 21st century, (2) the multiday (5-day and 10-day) extreme precipitation is closely associated with flood/drought disasters in the HRB, and (3) for stations of nonstationary changes with significant upward trend after the abrupt change, if the whole extreme precipitation series are used for frequency analysis, the risk of future floods will be underestimated, and this effect is more pronounced for longer return periods.

Environmental changes have led to non-stationary flood risks in coastal cities. How to quantitatively characterize the future change trend and effectively adapt is a critical problem that needs urgent attention. To this end, this study uses the 2010 Shanghai land use data as the base and utilizes the future land use simulation (FLUS) model to simulate future land use change scenarios (2030, 2050, and 2100). Based on the results of storm and flood numerical simulations, probabilistic risk, and other multidisciplinary methods, extreme storm and flood risks of various land uses (residential, commercial and public service, industrial, transportation, agricultural, and other land) in Shanghai are analyzed. Our findings demonstrate that the future land use simulated results show that the simulation accuracy is very high, meeting the needs of our research. We evaluated future land use exposure assets and losses and found that their spatial distribution patterns are consistent, ranging from a sporadic distribution for 1/10-year to a banded distribution for 1/1000-year under the two emission scenarios. In terms of economic loss, the losses of total land use in Shanghai for 1/1000-year in 2100 are 1.8–2.7 times that of 2010 under the RCP8.5 scenario. The expected annual damage (EAD) of Shanghai’s land use in 2030, 2050, and 2100 is 189.9 million CNY, 409.8 million CNY, and 743.5 million CNY under the RCP8.5 scenario, respectively, which is 1.7–3.0 times the EAD under the RCP2.6 scenario. Among them, residential, commercial and public service land as well as industrial land has the highest EAD. Risks are mainly distributed in the city center, the lower reaches of the Huangpu River, the northern shore of Hangzhou Bay, the Qingpu (QP)–Songjiang (SJ) depression in the southwest, and Chongming (CM) Island (southwest and northeast). Our work can provide meaningful information for risk-sensitive urban planning and resilience building in Shanghai. These multidisciplinary methods can also be applied to assess flood risk in other coastal cities.

This study presents an analysis of the changes in extreme temperatures over major river basins in China under different shared socioeconomic pathway (SSP) scenarios based on a set of dynamical downscaling over CORDEX East Asia, performed with the regional climate model RegCM4 at a resolution of 25 km, driven by the global climate model FGOALS‐g3. The results indicated that the dynamical downscaling tended to reduce the warm (cold) biases of the present‐day daily maximum (TXx) and minimum temperatures (TNn) simulated by FGOALS‐g3. Under the SSP scenarios, substantial increases in TXx and TNn and the number of warm days and warm nights throughout China were projected by both models. The average increase in TXx in most of the river basins ranged from 1 to 2°C under the SSP1‐2.6 scenario, from 2 to 3°C under the SSP2‐4.5 scenario, and from 3 to 5°C under the SSP5‐8.5 scenario. Reductions in the number of cold days and cold nights were projected across China, but these reductions were smaller than the increases in the number of warm days and warm nights. The interregional variability in the increases in TXx and TNn was more pronounced in the SSP5‐8.5 scenario and the RegCM4 model than in the other SSP scenarios and the FGOALS‐g3 model, respectively. Larger percentages of the land area and population of China would be affected by greater increases in extreme high temperatures and TNn. Under the SSP2‐4.5 (SSP1‐2.6) scenario, 20–65% (50–95%) of the impacts of extreme temperatures under the SSP5‐8.5 scenario could be avoided across most regions in China. The avoided impacts of warm days and warm nights were greater than those of the other extreme temperature indices. More of the impacts of extreme temperatures could be avoided in the Huai River basin, Yellow River basin, Hai River basin, and Northwest Interior River basin than in the other river basins in China.

Future land use simulation modeling for sustainable urban development under the shared socioeconomic pathways in West African megacities: Insights from Greater Accra Region.

It is indisputable that global warming has triggered more frequent extreme weather and in turn led to severe flood disasters. To understand the trend of extreme rainfall under 1.5 °C and 2 °C warming, we investigated the historical variation and future trends in extreme rainfall for the Huai River basin, which has frequently been hit by floods, using recorded meteorological data and a projection of five General Circulation Models in the Coupled Model Intercomparison Project 6. We used the years 1995–2014 as the baseline period to study the temporal and spatial changes in extreme rainfall under 1.5 °C and 2.0 °C warming scenarios. The results indicated that (1) temperatures in the Huai River basin have risen significantly from 1995 to 2014, but there are insignificant variation trends in annual precipitation (AP), intensive precipitation (R95P), maximum daily precipitation (Rx1d) and heavy rain days (Rr50) during the same time span. (2) From 2015 to 2100, both temperature and extreme rainfall indices show increase trends, with a higher rate of increase under a higher emission scenario. (3) Under the warming scenario of 1.5 °C, AP, R95P, Rx1d and Rr50 in the basin will likely increase by 4.6%, 5.7%, 6.2% and 13.4%, respectively, compared with that in the baseline period. Under the warming scenario of 2.0 °C, AP, R95P, Rx1d and Rr50 will probably increase by 7.3%, 7.4%, 10.9% and 19.0%, respectively. (4) Spatially, the changes in extreme rainfall indices under the warming scenarios of 1.5 °C and 2.0 °C generally tend to increase from north to south. Higher intensity extreme rainfall will likely extend to the whole of the Huai River basin. It is therefore essential to study adaptive measures to cope with flooding in the Huai River basin induced by the increase in future rainfall extremes.

In this study we simulated the watershed response according to future climate and land use change scenarios through a hydrological model and predicting future hydroclimate changes by applying the Budyko framework. Future climate change scenarios were derived from the UK Earth system model (UKESM1), and future land use changes were predicted using the future land use simulation (FLUS) model. To understand the overall trend of hydroclimatic conditions, the movements in Budyko space were represented as wind rose plots. Moreover, the impacts of climate and land use changes were separated, and the watersheds’ hydroclimatic conditions were classified into five groups. In future scenarios, both increase and decrease of aridity index were observed depending on the watershed, and land use change generally led to a decrease in the evaporation index. The results indicate that as hydroclimatic movement groups are more diversely distributed by region in future periods, regional adaptation strategies could be required to reduce hydroclimatic changes in each region. The results derived from this study can be used as basic data to establish an appropriate water resource management plan and the governments’ land use plan. As an extension of this study, we can consider more diverse land use characteristics and other global climate model (GCMs) in future papers.

Variations in the intensity of the global hydrological cycle can have far-reaching effects on living conditions on our planet. While climate change discussions often revolve around possible consequences of future temperature changes, the adaptation to changes in the hydrological cycle may pose a bigger challenge to societies and ecosystems. Floods and droughts are already today amongst the most damaging natural hazards, with floods being globally the most significant disaster type in terms of loss of human life (Jonkman 2005). From an economic perspective, changes in the hydrological cycle can impose great pressures and damages on a variety of industrial sectors, such as water management, urban planning, agricultural production and tourism. Despite their obvious environmental and societal importance, our understanding of the causes and magnitude of the variations of the hydrological cycle is still unsatisfactory (e.g., Ramanathan et al 2001, Ohmura and Wild 2002, Allen and Ingram 2002, Allan 2007, Wild et al 2008, Liepert and Previdi 2009).

The global land monsoon region, with substantial monsoon rainfall and hence freshwater resources, is home to nearly two-thirds of the world’s population. However, it is overwhelmed by extreme precipitation, which is more intense than that on the rest of the land. Whether extreme precipitation has changed significantly, particularly in association with global warming, remains unclear for this region. This study investigates the presence of monotonic trends in extreme precipitation and its association with global warming over the past century over the global land monsoon regions, by employing the most comprehensive, long-running, and high-quality observational extreme precipitation records currently available. Based on a total of 5066 stations with at least 50 years of records, we found significant increases in the annual maximum daily precipitation and associations with global warming in regional monsoon domains, including the southern part of the South African monsoon region, the South Asian monsoon region (dominated by India), the North American monsoon region, and the eastern part of the South American monsoon region during the period of 1901–2010, with responses to global warming of ~10.4%–14.2% K−1, 7.9%–8.3% K−1, 6.4%–10.8% K−1, and 15.1%–24.8% K−1, respectively. For the global monsoon region as a whole, significant increases in extreme precipitation and associations with global warming are also identified, but with limited spatial coverage. The qualitative results on the significance of the changes on the regional scale are generally robust against different time periods, record lengths of stations, and datasets used. The uncertainty in the quantitative results arising from limited spatial and temporal coverages and use of different datasets deserves attention.

<p>Indian Summer Monsoon is vulnerable to climate change. Analysis of precipitation over India suggests more increase in extreme precipitation over south India as compared to north and central India during post-1970 (1971-2017) as compared to pre-1970 (1930-1970) (Suman and Maity, 2020). This contrast in the characteristics of extreme precipitation over south and north India is expected to continue as revealed by the analysis of precipitation from the Coordinated Regional Downscaling Experiment (CORDEX) simulations. Additionally, precipitation extreme are expected to shift southward over South Asia in the future (2006-2100 as compared to 1961-2005). For instance, the Arabian Sea, south India, Myanmar, Thailand, and Malaysia are expected to have the maximum increase (~18.5 mm/day for RCP8.5 scenario) in mean extreme precipitation (average precipitation for the days with more than 99<sup>th</sup> percentile of daily precipitation). However, north and central India and Tibetan Plateau show relatively less increase (~2.7 mm/day for RCP8.5 scenario). The increase in extreme precipitation over most part of South Asia can be attributed to stronger monsoon due to increase in air temperature over Tibetan Platue and Himalayas, stronger positive Indian Ocean Dipole events, and high precipitatible water over land areas in the future. However, while analysis of moisture flux and moisture convergence at 850mb, an intense eastward shift is noticed for moisture flux (over Indian Ocean region). This shift in moisture flux along with associated changes in moisture convergence over landmass are found to intensify during days with extreme precipitation. These changes are expected to intensify the observed contrast in extreme precipitation over south and north India and shift the extreme precipitation southward over south Asia, causing more extreme precipitation events in the countries like Myanmar, Thailand, Malaysia, etc.</p><p><strong>Keywords:</strong> Extreme Precipitation; Indian Summer Monsoon; Climate Change; Indian Ocean Dipole.</p><p> </p><p><strong>Reference:</strong></p><p>Suman, M., Maity, R. (2020), Southward shift of precipitation extremes over south Asia: Evidences from CORDEX data. <em>Sci Rep</em> <strong>10, </strong>6452 (2020). https://doi.org/10.1038/s41598-020-63571-x.</p>

Projected changes in extreme daily precipitation linked to changes in precipitable water and vertical velocity in CMIP6 models

Flood hazard is a global problem, but regions such as south Asia, where people’s livelihoods are highly dependent on water resources, can be affected disproportionally. The 2017 monsoon flooding in the Ganges–Brahmaputra–Meghna (GBM) basin, with record river levels observed, resulted in ∼1200 deaths, and dramatic loss of crops and infrastructure. The recent Paris Agreement called for research into impacts avoided by stabilizing climate at 1.5 °C over 2 °C global warming above pre-industrial conditions. Climate model scenarios representing these warming levels were combined with a high-resolution flood hazard model over the GBM region. The simulations of 1.5 °C and 2 °C warming indicate an increase in extreme precipitation and corresponding flood hazard over the GBM basin compared to the current climate. So, for example, even with global warming limited to 1.5 °C, for extreme precipitation events such as the south Asian crisis in 2017 there is a detectable increase in the likelihood in flooding. The additional ∼0.6 °C warming needed to take us from current climate to 1.5 °C highlights the changed flood risk even with low levels of warming.