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AbstractThe identification of projected changes in temperature caused by global warming at a fine-scale spatial resolution is of great importance for the high-altitude glacier and snow covered Upper Indus Basin. This study used a multimodel ensemble mean bias-correction technique which uses the ensemble empirical mode decomposition method to correct the bias of ensemble mean of seven CMIP6 GCMs outputs with reference to the European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5). The bias-corrected data have a nonlinear trend of seven GCMs but interannual variance and mean climate of ERA5 dataset. The dataset spans from 1985 to 2100 for historical and future climate scenarios (SSP126, SSP245, SSP370, and SSP585) at daily time intervals with a 1 km grid resolution. The result of different scenarios indicates that the increase in maximum (Tmax) and minimum temperature (Tmin) ranging from 1.5 to 5.4 °C and 1.8 to 6.8 °C from 2015 to 2100, respectively. Similarly, elevation-dependent warming is identified in Tmin from 1.7 to 7.0 °C at elevations <2,000 to 6,000 m asl, while the contrary relationship in Tmax is projected under different scenarios from 2015 to 2100. This study provides an insight into how to improve the GCMs projections and can be helpful for further climate change impact studies.

The Nanwenghe Wetlands Reserve in the Yile'huli Mountains is a representative region of the Xing'an permafrost. The response of permafrost to climate change remains unclear due to limited field investigations. Thus, longer-term responses of the ground thermal state to climate change since 2011 have been monitored at four sites with varied surface characteristics: Carex tato wetland (P1) and shrub-C. tato wetland (P2) with a multi-year average temperatures at the depth of zero annual amplitude (TZAA) of −0.52 and −1.19 °C, respectively; Betula platyphylla-Larix gmelinii (Rupr.) Kuzen mixed forest (P3) with TZAA of 0.17 °C, and; the forest of L. gmelinii (Rupr.) Kuzen (P4) with TZAA of 1.65 °C. Continuous observations demonstrate that the ecosystem-protected Xing'an permafrost experienced a cooling under a warming climate. The temperature at the top of permafrost (TTOP) rose (1.8 °C per decade) but the TZAA declined (−0.14 °C per decade), while the active layer thickness (ALT) thinned from 0.9 m in 2012 to 0.8 m in 2014 at P1. Both the TTOP and TZAA increased (0.89 and 0.06 °C per decade, respectively), but the ALT thinned from 1.4 m in 2012 to 0.7 m in 2016 at P2. Vertically detached permafrost at P3 disappeared in summer 2012, with warming rates of +0.42 and + 0.17 °C per decade for TTOP and TZAA, respectively. However, up to date, the ground thermal state has remained stable at P4. We conclude that the thermal offset is crucial for the preservation and persistence of the Xing'an permafrost at the southern fringe.

Study Region Mekong River Basin and surrounding areas. Study Focus: This study investigated the impacts of climate change on future meteorological and hydrological droughts in the Mekong River Basin and its surrounding areas. Our work is based on the output of five global climate models (GCMs) and simulations using the geomorphology-based hydrological model (GBHM) for the historical (1975–2004), near future (2010–2039), middle future (2040–2069), and far future (2070–2099) periods. The meteorological droughts in the study area were measured using SPI and SPEI, while the hydrological droughts were measured using SSI. New Hydrological Insights for the Region: The results suggest that droughts will generally reduce in the future over most of the study area, but will be more unevenly distributed with an eastward migration as compared to the historical period. Both meteorological and hydrological droughts will intensify in the near future, but will then reduce in intensity. Meteorological droughts will increase in the northeastern areas in the near future, followed by migration towards the south. Hydrological droughts showed similar aggravation followed by reduction, with upstream areas showing greater variability. In the general context of drought alleviation, southwestern China and the Mekong River estuary may suffer from a continuously increasing drought intensity in the future. This finding is based on 100-year extreme drought events.

There are many models presented that assess water quality. However, the applications of the models are limited due to the difficulty of preparing input data and interpreting model output. In this paper, we developed a Web-based platform to assist researchers in analyzing water quality. The data from sensors can be automatically imported to the platform according to the configured information of data structures. The platform also provides conventional methods and big data methods for the users to analyze water quality. Moreover, the users can choose the water quality parameters according to the water usage. The presented platform can show the model output in a text format and a graphic format, which allows for the analysis to be better understood by the user. The platform integrates the input, analysis, and output together well and brings great convenience to the research on water quality.

Abstract China is highly susceptible to landslides and debris flow disasters as it is a mountainous country with unique topography and monsoon climate. In this study, an efficient statistical model is used to predict the landslide risk in China under the Representative Concentration Pathway 8.5 by 2050, with the precipitation data from global climate models (GCMs) as the driving field. Additionally, for the first time, the impact of future changes in land use types on landslide risk is explored. By distinguishing between landslide susceptibility and landslide risk, the results indicate that the landslide susceptibility in China will change in the near future. The occurrence of high-frequency landslide risks is concentrated in southwestern and southeastern China, with an overall increase in landslide frequency. Although different GCMs differ in projecting the future spatio-temporal distribution of precipitation, there is a consensus that the increased landslide risk in China’s future is largely attributed to the increase in extremely heavy precipitation. Moreover, alterations in land use have an impact on landslide risk. In the Huang-Huai-Hai Plain, Qinghai Tibet Plateau, and Loess Plateau, changes in land types can mitigate landslide risks. Conversely, in other areas, such changes may increase the risk of landslides. This study aims to facilitate informed decision-making and preparedness measures to protect lives and assets in response to the changing climate conditions.

AbstractDetecting the response of the Atlantic meridional overturning circulation (AMOC) to anthropogenic warming can only be made with fingerprints indirectly because of the lack of sufficiently long direct measurements. However, whether the relationship between the AMOC and its fingerprints is stationary is rarely examined. This study uses coupled and ocean‐alone model simulations to investigate the sensitivity of two typical AMOC fingerprints under future anthropogenic warming. We found a lower sensitivity of the North Atlantic warming hole fingerprint in future warming scenarios associated with the differing vulnerability of deep‐water origins to external forcing and climate feedback. In contrast, the remote South Atlantic salinity pile‐up fingerprint is relatively insensitive to variations in AMOC sources, and its sensitivity to the AMOC is slightly enhanced by an intensified hydrological cycle. Our study implies that fingerprints outside the northern deep convection region may become more suitable in representing the response of AMOC to future warming.

AbstractGeoengineering has been proposed to stabilize global temperature, but its impacts on crop production and stability are not fully understood. A few case studies suggest that certain crops are likely to benefit from solar dimming geoengineering, yet we show that geoengineering is projected to have detrimental effects for groundnut. Using an ensemble of crop‐climate model simulations, we illustrate that groundnut yields in India undergo a statistically significant decrease of up to 20% as a result of solar dimming geoengineering relative to RCP4.5. It is somewhat reassuring, however, to find that after a sustained period of 50 years of geoengineering crop yields return to the nongeoengineered values within a few years once the intervention is ceased.