• Energy Research
• 2021-2025close
• environmental engineering close
• Chinese Academy of Sciences close

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.

Water quality safety has attracted global attention and is closely related to the development of the social economy and human health. It is widely recognized that climate change and human activities significantly affect water quality changes. Therefore, quantifying the contributions of factors that drive long-term water quality changes is crucial for effective water quality management. Here, we built a climate-water quality assessment framework (CWQAF) based on climate-water quality response coefficients and trend analysis methods, to achieve this goal. Our results showed that the water quality improved significantly by 4.45%-20.54% from 2011 to 2020 in the Minjiang River basin (MRB). Human activities (including the construction of ecological projects, stricter discharge measures, etc.) were the main driving factors contributing 65%-77% of the improvement effect. Notably, there were differences in the contributions of human activities to water quality parameter changes, such as DO (increase (I): 0.12 mg/L, human contribution (HC): 66.8%), CODMn (decrease (D): 0.71 mg/L, HC: 67.2%), BOD5 (D: 1.10 mg/L, HC: 77.7%), CODCr (D: 4.20 mg/L, HC: 81.2%), TP (D: 0.13 mg/L,HC: 72.8%) and NH3-N (D: 0.40 mg/L, HC: 63.0%). Climate change explained 23%-35% of the variation in water quality. The water quality response to climate change was relatively significant with precipitation. For example, the downstream region was more susceptible to climate change than was the upstream region, as the downstream movement of precipitation centers strengthened the process of climatic factors affecting water quality changes in the MRB. Generally, although human activities were the main driving factor of water quality changes at the basin scale, the contribution of climate change could not be ignored. This study provided a manageable framework for the quantitative analysis of the influence of human activities and climate change on water quality to enable more precise and effective water quality management.

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.

There has been much debate on the temporal change trend and existence of a turning point in spring green-up date (GUD) of plants on the Qinghai-Tibetan Plateau (QTP). Most previous studies on the QTP used remote sensing data, which have large uncertainties. In this study, using a large amount of long-term ground observation data at 27 phenological stations across the QTP (1694 GUD records), we showed that on the whole, QTP herbaceous plant GUD insignificantly advanced during 1982-2017. Although the direction of the GUD trend did not change from 1982 to 2017, the magnitude of the advancing trend greatly weakened after 1999. According to our estimated results from 28 paired GUD time series, the overall GUD trend shifted from -2.70 days/decade during 1982-1999 to -0.56 days/decade during 2000-2017. This finding contrasts with the conclusions of previous satellite-based studies, which either reported a continuous significant advancement of GUD or a turning point in the mid-to-late 1990s. Through partial correlation analysis and partial least squares regression, we found that winter and spring air temperatures were the primary climatic factors that influenced the temporal change in GUD, and both had negative effects on GUD. The decreased GUD trend was mainly attributable to the warming slowdown in spring. On average, the spring warming rate decreased by 52.43% after 1999, whereas the winter warming rate displayed no obvious change. This study also found that the GUD of forbs showed stronger sensitivity to air temperature change than that of sedges and grasses. This indicates that forbs are more competitive in adaptation to climate warming, which might shift plant community structure and affect ecosystem service function. Moreover, the declined advancement in GUD implies that the spring phenologically driven increase in carbon uptake may have also slowed in the past two decades.