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Urbanization is one of the pivotal aspects of socioeconomic advancement which is critically vulnerable to climatic extremes. Extreme precipitation and urbanization are largely interlinked. Estimating the extreme precipitation-induced urban area exposure is the fundamental aspect of urban risk assessment for precipitation-related floods. In this study, future urban area exposure to extreme precipitation and associated influential factors are investigated over South Asia under 1.5 °C, 2.0 °C, 3.0 °C, and 4.0 °C global warming thresholds. In this regard, we used newly released 20 up-to-date climate models outputs, and five Integrated Assessment Models (IAMs) based urban land-use products under four combined scenarios of the Shared Socioeconomic Pathways and Representative Concentration Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) from the sixth phase of Coupled Model Intercomparison Project (CMIP6). Extreme precipitation is characterized by adopting 20-, 50-, and 100-year return periods of annual maximum daily precipitation. Results reveal a massive urban area expansion over South Asia which is the utmost by 186.4% under SSP3-7.0 than the reference period (1995-2014). The variations in projected urban areas mainly occur in Indo-Gangetic Plain (IGP) region among scenarios. In relative terms, extreme precipitation frequency and associated urban area exposure are prospective to increase with continued global warming. The exposed urban area varies 4.5- to 7.4-fold higher under different warming thresholds than the reference period. The leading increase is estimated (7.4-fold) under 4.0 °C. Notably, for global warming targets set out by the Paris Agreement (1.5 °C, and 2.0 °C), exposed urban area is intended to be 10.2% higher under 2.0 °C than 1.5 °C. Spatially, the exposed urban area will be dominant in the southeast region relative to the reference period. Importantly, the interaction effect (simultaneous change in climate-urban land) is the principal contributor to the changes in urban area exposure to extreme precipitation over South Asia. However, this study's findings strongly support the accomplishment of the Paris Agreement target and provide a scientific basis for formulating urban land-use policy interventions., 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 © 2022. Published by Elsevier B.V.)

To quantify climate change impact and difference on basin-scale river runoff under the limiting global warming thresholds of 1.5 and 2.0 ∘ C, this study examined four river basins covering a wide hydroclimatic setting. We analyzed projected climate change in four basins, quantified climate change impact on annual and seasonal runoff based on the Soil Water Assessment Tool, and estimated the uncertainty constrained by the global circulation model (GCM) structure and the representative concentration pathways (RCPs). All statistics for the two river basins (the Shiyang River, SYR, and the Chaobai River, CBR) located in northern China indicated generally warmer and wetter conditions, whereas the two river basins (the Huaihe River, HHR, and the Fujiang River, FJR) located in southern China projected less warming and were inconsistent regarding annual precipitation change. The simulated changes in annual runoff were complex; however, there was no shift in seasonal runoff pattern. The 0.5 ∘ C global warming difference resulted in 0.7 and 0.6 ∘ C warming in basins in northern and southern China, respectively. This led to a projected precipitation increase by about 2 % for the four basins and to a decrease in simulated annual runoff of 8 % and 1 % in the SYR and the HHR, respectively, but to an increase of 4 % in the CBR and the FJR. The uncertainty in projected annual temperature was dominated by the GCMs or the RCPs; however, that of precipitation was constrained mainly by the GCMs. The 0.5 ∘ C difference decreased the uncertainty in the annual precipitation projection and the annual and monthly runoff simulation. [ABSTRACT FROM AUTHOR]

Under climate change, land use has an essential effect on the carbon cycle in the climate change sensitive area of Qinghai-Tibet Plateau (QTP). This study about ambitions to check out the spatial and temporal patterns of carbon storage (CS) on the QTP under future land-use changes and their influencing factors. Based on historical and projected climate and land-use information and the compiled carbon-intensity dataset derived from 839 sampling points, we projected future changes in CS in the region. We projected changes of CS in the QTP in the near-term (2021–2040), mid-term (2041–2060), and long-term (2081–2100) periods, using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. We found that the total carbon storage (TCS) from 1980 to 2020 was approximately equal to 247–259 × 108 t, where C soil had the greatest contribution (about 88% of the TCS), while C above , C below and C dead accounted for approximately 5%, 5% and 2% of the TCS, respectively. Furthermore, the TCS decreased from southeast to northwest, corresponding to decreasing forest coverage and increasing unused land area in the QTP. Compared to the baseline period (1995–2014, 259 × 108 t), the CS in the QTP under the Shared Socioeconomic Pathways (SSPs) is expected to increase by 7.3–13.5%, 6.2–14.7% and 5.4–14.3% in the three future periods, respectively. Spatially, the carbon increase will be concentrated in the southeastern and northern parts of the QTP, where the land-use types are mainly forest land and grassland. Increases in precipitation and temperature are predicted to take place for the duration of the QTP in the future, driving land-use changes that are projected to result in increased area of forest land, which would increase CS. The CS in QTP is high, being influenced by land use and climatic factors, and future climate change may enhance the carbon sink capacity of the QTP. [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]

The realistic simulation and projection of the Amundsen Sea Low (ASL) are essential for understanding the Antarctic climate and global climate change. Using 14 models that participated in phase 6 of the Coupled Model Intercomparison Project (CMIP6), this study evaluates the climatological characteristics of ASL with comparison to the ERA5 reanalysis and their CMIP5 versions and assesses the future change of ASL under 1.5 °C–4 °C global warming. The climatological spatial distribution of ASL is captured reasonably but with underestimated intensity by CMIP6 multi-model ensemble (MME). Among the CMIP6 models, EC-Earth3 has most accurate representation of ASL according to the pattern correlation and biases. The seasonal variation of the ASL depth and location are found to be reasonably reproduced by the CMIP6 models. CMIP6 MME has higher skills in simulating the seasonal cycle of absolute depth and zonal migration of the ASL center. The relative central pressure of ASL is underestimated in all seasons and there is a 4-degree northward shift bias of the ASL center in austral winter, which were also evident in the CMIP5. The semiannual cycle of ASL absolute depth with two deepest pressure in April and October is also captured by CMIP6 MME. However, the observed peak of pressure between the two months occurs in June, while it delays one month and appears until July in CMIP6 MME. Compared with CMIP5, CMIP6 MME exhibit evident reduced uncertainties and overall improvement in simulating absolute depth and location of the ASL center, which might be attributed to models' capability of representing the location of Southern Hemisphere westerlies, while the biases in relative depth become even large in CMIP6 MME. In response to future warming from 1.5 °C to 4 °C above pre-industrial levels, the absolute depth of ASL will very likely deepen with larger amplitude in all seasons, while the relative depth might enhance only under high-level warmer world in austral autumn to winter. The CMIP6 MME also projects that the ASL will shift poleward constantly in austral summer and migrate southwestward during austral autumn with the rising global mean temperature. Among all the seasons, the most prominent future changes in intensity and location of ASL are found in autumn. The enhancement and poleward movement of ASL could also be identified during the Ross Sea ice advance season under 1.5 °C–4 °C global warming. The results reveal the potential of CMIP6 models in the ASL study and the impact of ASL on Antarctic climate under different global warming levels. • Latest CMIP6 models exhibit generally better representation and reduced uncertainties in reproducing Amundsen Sea Low (ASL) than CMIP5. • The improvement in ASL of CMIP6 models might be associated with more robust simulation of Southern Hemisphere westerlies. • ASL will very likely deepen and migrate poleward constantly under 1.5 °C to 4 °C global warming above pre-industrial levels. [ABSTRACT FROM AUTHOR]