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The projections of mean temperature, precipitation (P), and potential evapotranspiration (PET) reflect the probabilities of long-term changes of hydrologic processes and induced extreme events. In this paper, we investigated the future changes in some pivotal climatic variables (mean temperature, precipitation, and potential evapotranspiration) under 1.5 °C, 2.0 °C, and 3.0 °C specific warming levels (SWLs) across the Indus River Basin of South Asia. The seven global climate models output under seven different emission 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 latest Sixth phase of Coupled Model Intercomparison Project (CMIP6) are used for this purpose. The Penman-Monteith approach is applied to estimate PET, and the water balance equation is for reflecting water surplus/deficit. Results indicate that except for precipitation, the greater increases in temperature and PET are inclined to happen with continued global warming. The highest increase in temperature is accounted for 14.6% (2.4 °C), and the enhanced PET is estimated at 5.2% higher than the reference period (1995-2014) under 3.0 °C SWL. While the precipitation is projected to increase by the highest 4.8% for 2.0 °C warming level. The differences in regional climate for an additional 0.5 °C (2.0-1.5 °C) and 1.0 °C (3.0-2.0 °C) of warming, the temperature is projected to increase by 0.4 °C and 0.9 °C in the entire IRB respectively. The highest increase in mean temperature (5.1%) and PET (2.4%) in the IRB are predicted to intensify for an additional 1.0 °C than that of 0.5 °C of warming, but precipitation is intended to decrease by 0.4%. Spatially, the increase in temperature, precipitation, and PET are dominated towards high elevation in the upper basin (north) under all the SWLs. The increased variability in climatological parameters across IRB depicts an evident occurrence of both wet events (upper basin) as well as dry events (lower basin) with the increase in global average temperature rise. However, these findings provide an insightful basis for water resource management as well as initiating mitigation and adaptation measures in the IRB related to water surplus (floods) and water deficit (droughts)., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

In the context of global climate change and urban expansion, urban residents are encountering greater rainstorm waterlogging risk. Quantifying population exposure to rainstorms is an important component of rainstorm waterlogging risk assessments. This study utilized a two-dimensional hydrodynamic model to simulate the inundation water depth and inundation area resulting from rainstorms, with return periods of 5, 10, 50, and 100 years, in the Xiong'an New Area, and overlaid the gridded population data in 2017 and in 2035 under SSP2 to assess the change in population exposure. The results show that the average inundation depth and area increase were from 0.11 m and 207.9 km2 to 0.18 m and 667.2 km2 as the rainstorm return period increased from once in 5 years to once in 100 years. The greatest water depths in the main urban areas were mainly located in the low-lying areas along the Daqing River. The total population exposed to rainstorm waterlogging for the 5-, 10-, 50-, and 100-year return periods was 0.31, 0.37, 0.50, and 0.53 million, respectively, in 2017. However, this is projected to rise significantly by 2035 under SSP2, increasing 2–4-fold compared with that in 2017 for the four return periods. Specifically, the projected population exposure is expected to be 0.7, 1.0, 1.8, and 2.0 million, respectively. The longer the return period, the greater the increase in population exposure. The proportion of the population exposed at the 0.05–0.2 m water depth to the total population exposure decreases as the return periods increases, whereas the proportion changes in the opposite direction at the 0.2–0.6 m and >0.6 m depth intervals. Spatially, high-exposure areas are concentrated in densely populated main urban regions in the Xiong'an New Area. In the future, more attention should be paid to densely populated low-lying areas and extreme recurrence rainstorm events for urban flood-risk management to ensure population safety and sustainable urban development. [ABSTRACT FROM AUTHOR]

In the last decade, three persistent warm blob events (2013/14, 2015, and 2019/20) in the northeast Pacific (NEP) have been hotly debated given their substantial effects on climate, ecosystems, and the socioeconomy. This study investigates the changes of such long-lived NEP warm blobs in terms of their intensity, duration, structure, and occurrence frequency under Shared Socioeconomic Pathway (SSP) 119 and 126 low-warming scenarios of phase 6 of the Coupled Model Intercomparison Project. Results show that the peak timing of the warm blobs shifts from the cold season to boreal summer. For the summer-peak warm blobs, their maximum intensity increases by 6.7% (10.0%) under the SSP119 (SSP126) scenario, but their duration reduces by 31.0% (20.4%) under the SSP119 (SSP126) scenario. In terms of their vertical structure, the most pronounced temperature signal is located at the surface, and their vertical penetration is mostly confined to the mixed layer, which becomes shallower in warming climates. Based on a mixed layer heat budget analysis, we reveal that a shoaling mixed layer depth plays a dominant role in driving the stronger intensity of the warm blobs under low-warming scenarios, while the stronger magnitude of ocean heat loss after their peaks explains the faster decay and thus shorter duration. Regarding occurrence frequency, the total number of the warm blobs does not change robustly in the low-warming climates. Following the summer peak of the warm blobs, extreme El Niño events may occur more frequently under the low-warming scenarios, possibly through stronger air–sea coupling induced by tropical Pacific southwesterly anomalies. [ABSTRACT FROM AUTHOR]

Gridded distribution of future economy plays an important role in climate change impact assessment. The trend of the output values of different industries is crucial for a variety of planning and design processes. Under the Shared Socioeconomic Pathways (SSPs) global framework, the multidimensional model and Cobb-Douglas production model with localized population and economic parameters are used to develop the annual provincial population and value-added of primary, secondary and tertiary industries in China from 2020 to 2100. The most recently implemented fertility-promoting and industrial planning policies in China are considered in our projections. We build multiple models to evaluate the impact of different types of land use on the value-added of primary, secondary and tertiary industries and then gridded the projected value-added to a 5′ × 5′ resolution, based on recorded county-level economic statistics and gridded land use. The reliability of estimations is verified against 2011–2019 statistical data and multiple published datasets. The high-resolution economic dataset is expected to contribute greatly to national and regional climate change impact, adaptation, and vulnerability studies. Measurement(s) Population • Value-added of industries • Gridded data Technology Type(s) multidimensional projection model • Cobb-Douglas production model • computational modeling technique Sample Characteristic - Location China [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]

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]