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At first glance, assessing future landslide‐exposed population appears to be a straightforward task if landslide hazard estimates, climate change, and population projections are available. However, the intersection of landslide hazard with socioeconomic elements may result in significant variation of estimated landslide exposure due to considerable variations in population projections. This study aims to investigate the effects of different sources of population data on the evaluation of landslide‐exposed population in China under four Shared Socioeconomic Pathways (SSPs) scenarios. We utilize multiple global climate models (GCMs) from Coupled Model Intercomparison Project Phase 6 and six high‐resolution spatially explicit static and dynamic population data sets to drive available landslide models. The results indicate an overall rise in landslide hazard projections, with an increase in the potential impact area of 0.4%–2.7% and an increase in the landslide frequency of 4.7%–20.1%, depending on the SSPs scenarios and future periods. However, the likely changes in future landslide exposed population, as modeled by incorporating population data from different sources with landslide hazard, yield divergent outcomes depending on the population data source. Thus, some of the projections depict an increase in future landslide exposure, while others show a clear decrease. The nationwide divergence ranged from −64% to +48%. These divergent findings were mainly attributed to differences in population data and a lesser extent to variations in GCMs. The present findings highlight the need to pay closer attention to the dynamic evolution of the elements at risk and the associated data uncertainties. Plain Language Summary: As climate change continues, extreme rainfall is expected to become more frequent and intense. This can lead to changes in landslide risks and how population is exposed to them. While previous studies have mainly focused on how the landslide likelihood may change in time, few have paid attention to how dynamic socioeconomic factors play a role in determining landslide risk. In this study, we used multiple global climate models and different population data sets to investigate how different sources of population information can affect estimates of future landslide risks in China. Overall, we found that landslide hazard is likely to increase in the future. However, when we incorporated different population data into our models, we found divergent results in terms of the number of people exposed to these phenomena. Depending on the population data used, the estimates ranged from a decrease of about 64% to an increase of 48%. These different outcomes were mainly due to variations in population data we used, although climate models also had an impact. These conflicting estimates highlight the need to consider changes in elements at risk when assessing disaster risks and developing targeted measures to adapt to and mitigate the effects of climate change. Key Points: Future landslide exposure is assessed by combining landslide model with spatially explicit population and global climate model dataPotential impact areas and frequency of landslides in China under climate change are projected to increase by 0.4%–2.7% and 4.7%–20.1%, respectivelyVarying sourced population projections may induce divergent signals (−64% to +48%) of landslide‐exposed population under climate change [ABSTRACT FROM AUTHOR]

Climate change has substantial impacts on regional hydrology in the major river basins. To figure out such latent hydrological impacts of changing climate, more reliable hydrological simulations are imperative. In this study, we evaluated the impacts of climate change on hydrological regime in the Upper Yangtze River Basin based on four downscaled and bias-corrected Global Climate Model outputs from Coupled Model Intercomparison Project Phase 5 under four Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, and RCP8.5) driving three hydrological models. Two model evaluation approaches were applied: simple and comprehensive. The comprehensive approach was used to evaluate models in the historical period, optimizing objective function at four gauges, and hydrological models were weighted for impact assessment based on their performance. In such a way, projected streamflow time series are obtained under different emission scenarios. Results show that the annual average discharge is projected to increase by 4.1–10.5% under the RCP scenarios at the end of twenty-first century relative to the reference period (1970–1999). Moreover, the high flow is projected to increase and the low flow to decrease indicating a higher probability of flood and drought occurrence in the basin. The severity of floods and droughts may increase. In comparison with the simple one-site model evaluation approach, the comprehensive method reveals that the anticipated extreme flow events would be less severe, and annual mean discharge slightly lower. The projected results imply that application of the comprehensive model evaluation approach could narrow the simulated spreads of projections significantly, and might provide more credible results. [ABSTRACT FROM AUTHOR]

Adverse impacts and increasing economic losses from tropical cyclones (TCs) are a major focus in respect to the potential global warming of 1.5 °C or even 2.0 °C. Based on observed meteorological data and county‐scale loss records, loss‐inducing rainfall and wind speed thresholds are identified using the regional climate model CCLM to project future TC events in China. An established damage function is combined with future gross domestic product predictions under five shared socio‐economic pathways. At the 1.5 °C warming level, normalized TC losses will be four times higher than in the reference period (1986–2005). At the 2.0 °C warming level, a sevenfold increase is projected. Relative to the 1.5 °C warming level, TCs will become more frequent under the 2.0 °C scenario, especially along the southeast coast of China. Nearly 0.2–0.5% of the increase in gross domestic product might be offset by TC losses between the 1.5 °C and 2.0 °C warming levels, and the single highest TC loss at 2.0 °C may double that at 1.5 °C, with a larger affected area and more severe rainstorms and wind speeds. Rainfall is attributed more often to TC losses than wind speed. Limiting global warming at 1.5 °C would avoid an estimated increase in TC losses of more than 120 billion CNY annually. Based on a simple linear regression approach, normalized event‐based (a) and annual aggregated (b) TC losses in China will be four times higher at the 1.5 °C warming level than in the reference period (1986–2005). Relative to the 1.5 °C warming level, TCs will become more frequent under the 2.0 °C scenario, especially along the southeast coast of China. Limiting global warming at 1.5 °C would avoid an estimated increase in TC losses of more than 120 billion CNY annually. [ABSTRACT FROM AUTHOR]

In this paper, the intensity, area and duration of future droughts in China are analyzed using the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). The SPI and SPEI are used to evaluate the simulation ability of drought characteristics with the regional climate model COSMO-CLM (CCLM). The projected intensity and duration of future drought events are analyzed for the period 2016-2050 under three different respective concentration pathways (RCPs). The simulated and projected drought events are analyzed by applying the intensity-area-duration method. The results show that CCLM has a robust capability to simulate the average drought characteristics, while some regional disparities are not well captured, mainly the simulation of more drought events of shorter duration in Northwest China. For the future period 2016-2050, more intense dryness conditions are projected for China. An increase in evapotranspiration is found all over China, while a reduction in precipitation is apparent in the southern river basins. The increase in evapotranspiration plays an important role in the changes of future droughts over the northern river basins and southern river basins. Under RCP2.6, drought events of longer duration and with higher frequency are projected for the southwest and southeast of China. Under RCP4.5 and RCP8.5, a continuing tendency to more dry conditions is projected along a dryness band stretching from the southwest to the northeast of China. More frequent drought events of longer duration are projected in the southwestern river basins. For all future droughts, larger extents are projected, especially for events with long-term duration. The projected long-term drought events will occur more often and more severe than during the baseline period, and their central locations will likely shift towards Southeast China. The results of this study can be used to initiate and strengthen drought adaptation measures at regional and local scale, especially in the south of China. [ABSTRACT FROM AUTHOR]

In the discussion of climate impacts, 1.5 and 2 °C have become iconic values. This study examines the impacts of 1.5 and 2 °C global warming on water availability, runoff seasonality, and extreme monthly and daily runoff in two catchments, using the semi-distributed hydrological model Hydrologiska Byråns Vattenbalansavdelning-D, based on a combination of five global climate models (GCMs) and four representative concentration pathways (RCPs). Subsequently, quantitative assessments were made for projection uncertainties from GCMs and RCPs. The two catchments are the Yiluo River catchment (YLC) in northern China and the Beijiang River catchment (BJC) in southern China. The results indicate wetter flood seasons for YLC and warmer mean annual temperatures, drier springs, and more severe floods over long return periods (25 and 50 years) for both catchments. The change magnitude of most indicators is expected to be larger in YLC than in BJC. Mean annual temperatures in both catchments are expected to have smaller changes under the 1.5 °C scenario than under the 2.0 °C scenario. However, the change magnitude of the other hydrological variables is projected to be approximately equivalent for both catchments under both scenarios. Uncertainties of projected impacts from GCMs are generally larger than those from RCP scenarios, for both catchments and warming scenarios, with the exception of mean annual temperature of BJC. These findings indicate that effective measures are required to address increasing annual temperatures, more severe flood events (25- and 50-year return periods), and drier spring seasons in both catchments and wetter flood seasons in YLC. [ABSTRACT FROM AUTHOR]

ABSTRACT In this article, the analysis of simulated and projected climatic changes in the Indus River Basin ( IRB) is presented. The performance of the regional climate model COSMO-CLM ( CCLM) driven by the global circulation model MPI-ESM-LR is evaluated on the ability of reproducing temperature, precipitation, and wind pattern for the period 1961-2005. There exist quantitative biases, especially in precipitation pattern, which are associated to the diverse reproduction of the atmospheric circulation by the global circulation model. The overall results show that CCLM is able to satisfyingly capture the dominant spatial characteristics in annual temperature and precipitation time series, including the warming trend, and the seasonal variations. The changes in precipitation and temperature over the IRB are projected for the mid- (2046-2065) and late-21st century (2081-2100). Relative to the baseline period (1986-2005), the average annual temperature will increase during the mid- and late-21st century over the whole basin. Extreme temperature events, i.e. heat waves, are more likely to occur. An increase in summer temperature is also projected especially in the upper IRB, where the persistent increase is likely to cause further melting of glaciers. The annual precipitation will decrease in both the mid- and late-21st century with significant spatial changes. A decrease in the monsoon precipitation is also projected, particularly in the central and southern plains of lower altitudes, which might be highly related to the reduction of wet air from the Indian Ocean and the increment in outflow to the east of the IRB. For winter and spring precipitation, except for the late-21st century under the representative climate pathway (RCP) 2.6, a decreasing trend is projected, which might be caused by the reduction of water vapour from the west. This will further weaken the availability of water resources in these seasons, especially in the upper IRB of higher altitudes. [ABSTRACT FROM AUTHOR]

Using data from the Integrated Global Radiosonde Archive Version 2 (IGRA2) and the Multi Model Ensemble (MME) of four global climate models (GCMs), named CanESM5, IPSL-CM6A-LR, MIROC6, and MRI-ESM2-0, within the framework of phase 6 of the Coupled Model Intercomparison Project (CMIP6), we analyzed the changes in atmospheric total column water vapor (TCWV) over Central Asia in the future (2021–2100) under SSP-RCPs scenarios: SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5, relative to baseline period (1986–2005). Results showed that the annual mean TCWV from IGRA2 was consistent with the model output from 1979 to 2014 in Central Asia. Besides, the spatial distribution of TCWV in Central Asia during the baseline period was consistent between the models. The regional average value of Central Asia was between 10.8 mm and 12.4 mm, and decreased with elevation. TCWV will increase under different SSP-RCPs from 2021 to 2040, but showed different trends after 2040. It will increase under SSP1-1.9 and SSP1-2.6 scenarios from 2021 to 2050, and decrease after that. It will grow from 2021 to 2055 under SSP4-3.4 scenario, and then stay essentially constant. Under SSP2-4.5 and SSP4-6.0 scenarios, TCWV will rise rapidly during 2021–2065, but the growth will decline from 2065 to 2100. TCWV will continue to increase under SSP3-7.0 and SSP5-8.5 scenarios, and the largest increase is projected under SSP5-8.5 scenario. Change in near-surface temperature (Ts) matched the change in TCWV, but changes in precipitation and evapotranspiration are not significant during 2021–2100. In spite of the large variations in TCWV under different SSP-RCPs, the dominant characteristic in all scenarios shows that a large TCWV increase is demonstrated over areas with small TCWV amounts during the baseline period. On the contrary, increases will be small where the TCWV amounts had been large during the baseline period. The change in TCWV is highly correlated to the increase in Ts in Central Asia. Under SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5 scenarios, the higher the temperature due to higher radiative forcing, the steeper the regression slope between TCWV and Ts change. It is closest to the theoretical value of the Clausius-Clapeyron equation under SSP3-7.0 and SSP5-8.5 scenarios, but not presented under other scenarios. Spatially, steeper regression slopes during 2021–2100 have been found around the Caspian Sea in the southwest and in the high-elevation areas in the southeast of Central Asia, which is likely related to the abundant local water supply for evaporation. [ABSTRACT FROM AUTHOR]

Global-level warming largely influences drought dynamics. Therefore, a robust drought projection is critical to support sustainable development under a future warming climate, especially at the regional level (i.e., South Asia). Encouraged by the Paris Agreement, this study investigates the changes in the intensity, area, and duration of future droughts under 1.5 °C, 2.0 °C, 3.0 °C, and 4.0 °C global warming levels over South Asia. In this regard, seven global climate model outputs under seven newly designed climate change scenarios (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5) from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) are used. The standardized precipitation evapotranspiration index (SPEI), self-calibrating Palmer drought severity index (scPDSI), and intensity-area-duration (IAD) method are adopted to characterize drought. Drought events are identified considering an area coverage greater than 50,000 km2 for predefined drought durations of 3- (short-term), 6- (medium-term), and 12-month (long-term). A significant drying trend is seen and tested against the two-sample t -test. Notably, to represent the more concrete picture of changes in drought characteristics, the results based on two indices (SPEI and scPDSI) are combined (average) in this paper. The results reveal that droughts with higher-intensity, and long-term duration will increase with continued warming. As drought features, the number of long-term droughts will increase by 21.5% (highest), and the leading area coverage is also estimated (>7%) for long-term drought at higher warming (i.e.4.0 °C) than the reference period (1995–2014). Furthermore, drought events with large-area (>3 × 105 km2) coverage are projected to become more frequent. For drought severity, extreme drought events and associated area coverage are more likely to unfold over the region. However, overall drought conditions are inclined to worsen under higher warming, especially 4.0 °C warming. Importantly, for global warming targets set by the Paris Agreement (1.5 °C and 2.0 °C), drought conditions will be more acute at 2.0 °C than at 1.5 °C. Spatially, a significant drying trend is mainly observed in the western part of South Asia (Southwest-Northwest) according to both drought metrics (SPEI and scPDSI). Notably, NW will experience acute droughts under all warming levels. Droughts in this region will be mainly influenced by the combined effect of decreasing precipitation and escalated evapotranspiration. As global warming increases, a significant increase in PET and temperature is found over South Asia. In addition, the model evaluation shows that the CMIP6-Global climate models (GCMs) are capable of satisfactorily reproducing climate variables and drought events in South Asia. However, our study's findings strongly support the execution of the Paris Agreement target and provide a scientific basis for articulating drought adaptation measures at the regional scale, especially in South Asia. • Intensity-Area-Duration approach is used to analyze future drought over South Asia for 1.5oC - 4.0oC warming. • The modified Penman-Monteith method (considering CO 2) are adopted to estimate PET. • Overall drought conditions will worsen under 4.0oC warming. • The Northwest of South Asia is inclined to be affected by intense drought in the future. [ABSTRACT FROM AUTHOR]

Motivated by the Paris Agreement, this study aims to investigate the changes in precipitation extremes across South Asia and its five climatic zones for each 0.5 °C of warming above the pre-industrial level from 1.5 °C to 3.0 °C. In this regard, 20 global climate model outputs from the latest CMIP6 under four combinations of SSP-RCP scenarios (SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5) are used. Four widely used extreme precipitation indices such as number of consecutive wet days (CWD), number of heavy precipitation days (R10mm), maximum consecutive 5-day precipitation (RX5day), and the number of very wet days (R99pTOT) defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) are applied to detect the extreme events. To ensure reduced uncertainty, we used bias-corrected and multi-model ensemble outputs. Results indicate that as the degree of global warming increases, the changes in magnitudes of extreme events are projected to intensify (except for CWD) and the largest growth is found under 3.0 °C in the entire domain and its five climatic zones. The polar climatic zone is anticipated to experience the highest magnitude of changes for extreme events under all the warming scenarios. The largest percentage of area with significant increase is found under the highest warming level (3.0 °C), especially for R95pTOT (95.5% of the entire domain). For an additional 0.5 °C (2.0–1.5 °C) of warming, the anticipated precipitation-related extremes will increase by 3.5%, (RX5day), 3.6% (R10mm) and 6.6% (R99pTOT), as mitigation targets set out in the Paris Agreement. The projected intense sea surface temperature over the Arabian Sea, and large water vapor content over South Asian landmass are expected to influence precipitation-related extreme events. Notably, considering all aspects of our analysis, R99pTOT is expected to be the most predominant extreme precipitation index across the domain with continued warming. So, our findings strongly support the Paris Agreement target to limit global warming to 1.5 °C and provide a scientific basis. • Precipitation extremes over South Asia will intensify with continued warming. • The polar climatic zone will experienceprecipitation-related extremes largely. • Extra 0.5 °C (2.0–1.5 °C) will increase the extreme event by 3.5%, (RX5day), 3.6% (R10mm) and 6.6% (R99pTOT). • R99pTOT is expected to be the most predominant event for South Asia. [ABSTRACT FROM AUTHOR]

In this paper, future drought characteristics (frequency, duration and intensity) over China are analysed by using four climate models from CMIP6 under the seven SSP-RCP (shared socioeconomic pathway-representative concentration pathway) scenarios (SSP119, SSP126, SSP434, SSP245, SSP460, SSP370, and SSP585) for three defined periods of 2021–2040 (near-term), 2041–2060 (mid-term) and 2081–2100 (long-term). The corresponding four climate models output from CMIP5 are also used to conduct a comparison analysis between CMIP5 and CMIP6 to address the improvements added to CMIP6 in terms of drought identification. The drought characteristics are identified by applying the standardized precipitation-evapotranspiration index (SPEI) at a 12-month timescale and run theory. The results show that CMIP6 has a robust capability to capture historical (1986–2005) drought characteristics. For the future period of 2021–2040, the decrease in precipitation and increase in potential evapotranspiration will lead to continuous dry conditions in the upper and middle Yangtze River basin and eastern Pearl River basin. Relative to the reference period, drought events will be more frequent and severe with longer durations in the Northwest River basins and middle Yangtze River basin. Furthermore, higher emissions signify a greater increase in drought frequency and intensity in the long-term period. Except for the SSP585 scenario, the lower emission scenario corresponds to the higher drought duration soon and in the mid-21st century (2021–2060). This finding is regarded as a "strange phenomenon", which cannot be detected by the previous CMIP5-based emission scenarios (RCP2.6, RCP4.5 and the unlikely pathway RCP8.5). Therefore, additional "possible future"-based scenarios (SSP119, SSP126, SSP434, SSP245, SSP460, and SSP370) should be included in extreme climate studies, especially for the near future and mid-21st century. Notably, compared with CMIP5, the reduced biases in drought characteristics are more likely associated with improvements in the representation of physical processes in climate models from CMIP6. The results of this study could provide a basis for the development of drought adaptation measures over China. • Latest CMIP6 climate models and seven SSP-RCP scenarios are used to analyze the possible changes in droughts over China. • More robust projections will be presented by CMIP6 than CMIP5, due to the better representations in physical processes. • The higher emission signifies shorter drought duration, lower precipitation and PET in mid-21st century over China. [ABSTRACT FROM AUTHOR]