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Understanding land-surface biophysical feedbacks to the atmosphere is needed if we are to simulate regional climate accurately. In the Arctic, previous studies have shown that enhanced vegetation growth decreases albedo and amplifies warming. In contrast, on the Tibetan Plateau, a statistical model based on in situ observations and decomposition of the surface energy budget suggests that increased vegetation activity may attenuate daytime warming by enhancing evapotranspiration (ET), a cooling process. A regional climate model also simulates daytime cooling when prescribed with increased vegetation activity, but with a magnitude smaller than observed, likely because this model simulates weaker ET enhancement in response to increased vegetation growth. In the Arctic, climate warming enhances vegetation activity by extending the length of the growing season and intensifying maximum rates of productivity. In turn, increased vegetation productivity reduces albedo, which causes a positive feedback on temperature. Over the Tibetan Plateau (TP), regional vegetation greening has also been observed in response to recent warming. Here, we show that in contrast to arctic regions, increased growing season vegetation activity over the TP may have attenuated surface warming. This negative feedback on growing season vegetation temperature is attributed to enhanced evapotranspiration (ET). The extra energy available at the surface, which results from lower albedo, is efficiently dissipated by evaporative cooling. The net effect is a decrease in daily maximum temperature and the diurnal temperature range, which is supported by statistical analyses of in situ observations and by decomposition of the surface energy budget. A daytime cooling effect from increased vegetation activity is also modeled from a set of regional weather research and forecasting (WRF) mesoscale model simulations, but with a magnitude smaller than observed, likely because the WRF model simulates a weaker ET enhancement. Our results suggest that actions to restore native grasslands in degraded areas, roughly one-third of the plateau, will both facilitate a sustainable ecological development in this region and have local climate cobenefits. More accurate simulations of the biophysical coupling between the land surface and the atmosphere are needed to help understand regional climate change over the TP, and possible larger scale feedbacks between climate in the TP and the Asian monsoon system.

Despite knowledge of the presence of the Tibetan Plateau (TP) in reorganizing large-scale atmospheric circulation, it remains unclear how surface albedo darkening over TP will impact local glaciers and remote Asian monsoon systems. Here, we use a coupled land-atmosphere global climate model and a glacier model to address these questions. Under a high-emission scenario, TP surface albedo darkening will increase local temperature by 0.24 K by the end of this century. This warming will strengthen the elevated heat pump of TP, increasing South Asian monsoon precipitation while exacerbating the current “South Flood-North Drought” pattern over East Asia. The albedo darkening-induced climate change also leads to an accompanying TP glacier volume loss of 6.9%, which further increases to 25.2% at the equilibrium, with a notable loss in western TP. Our findings emphasize the importance of land-surface change responses in projecting future water resource availability, with important implications for water management policies. Impacts of Tibetan Plateau darkening remain unclear. Here authors show that darkening under the RCP8.5 scenario will increase South Asian monsoon precipitation and the “South Flood-North Drought” pattern over East Asia, while lead to local glacier loss.

The seasonal greening of Northern Hemisphere (NH) ecosystems, due to extended growing periods and enhanced photosynthetic activity, could modify near-surface warming by perturbing land-atmosphere energy exchanges, yet this biophysical control on warming seasonality is underexplored. By performing experiments with a coupled land-atmosphere model, here we show that summer greening effectively dampens NH warming by −0.15 ± 0.03 °C for 1982–2014 due to enhanced evapotranspiration. However, greening generates weak temperature changes in spring (+0.02 ± 0.06 °C) and autumn (−0.05 ± 0.05 °C), because the evaporative cooling is counterbalanced by radiative warming from albedo and water vapor feedbacks. The dwindling evaporative cooling towards cool seasons is also supported by state-of-the-art Earth system models. Moreover, greening-triggered energy imbalance is propagated forward by atmospheric circulation to subsequent seasons and causes sizable time-lagged climate effects. Overall, greening makes winter warmer and summer cooler, attenuating the seasonal amplitude of NH temperature. These findings demonstrate complex tradeoffs and linkages of vegetation-climate feedbacks among seasons. The seasonal greening of Northern Hemisphere ecosystems due to extended growing periods and enhanced photosynthetic activity is, via experiments, shown to modify near-surface warming by perturbing land-atmosphere energy exchanges.

Stable water isotopes are natural tracers in the hydrological cycle and have been applied in hydrology, atmospheric science, ecology, and paleoclimatology. However, the factors controlling the isotopic distribution, both at spatial and temporal scales, are debated in low and middle latitude regions, due to the significant influence of large-scale atmospheric circulation and complex sources of water vapor. For the first time, we made in situ observations of near-surface vapor isotopes over a large region (over 10 000 km) across China in both pre-monsoon and monsoon seasons, using a newly designed vehicle-based vapor isotope monitoring system. Combined with daily and multiyear monthly mean outputs from the isotope-incorporated global spectral model (Iso-GSM) and infrared atmospheric sounding interferometer (IASI) satellite to calculate the relative contribution, we found that the observed spatial variations in both periods represent mainly seasonal mean spatial variations, but are influenced by more significant synoptic-scale variations during the monsoon period. The spatial variations of vapor δ18O are mainly controlled by Rayleigh distillation along air mass trajectories during the pre-monsoon period, but are significantly influenced by different moisture sources, continental recycling processes, and convection during moisture transport in the monsoon period. Thus, the North–South gradient observed during the pre-monsoon period is counteracted during the monsoon period. The seasonal variation of vapor δ18O reflects the influence of the summer monsoon convective precipitation in southern China and a dependence on temperature in the North. The spatial and seasonal variations in d-excess reflect the different moisture sources and the influence of continental recycling. Iso-GSM successfully captures the spatial distribution of vapor δ18O during the pre-monsoon period, but the performance is weaker during the monsoon period, maybe due to the underestimation of local or short-term high-frequency synoptic variations. These results provide an overview of the spatial distribution and seasonal variability of water isotopic composition in East Asia and their controlling factors, and they emphasize the need to interpret proxy records in the context of the regional system.

Bioenergy crop with carbon capture and storage (BECCS) is a key negative emission technology to meet carbon neutrality. However, the biophysical effects of widespread bioenergy crop cultivation on temperature remain unclear. Here, using a coupled atmosphere-land model with an explicit representation of lignocellulosic bioenergy crops, we find that after 50 years of large-scale bioenergy crop cultivation following plausible scenarios, global air temperature decreases by 0.03~0.08 °C, with strong regional contrasts and interannual variability. Over the cultivated regions, woody crops induce stronger cooling effects than herbaceous crops due to larger evapotranspiration rates and smaller aerodynamic resistance. At the continental scale, air temperature changes are not linearly proportional to the cultivation area. Sensitivity tests show that the temperature change is robust for eucalypt but more uncertain for switchgrass among different cultivation maps. Our study calls for new metrics to take the biophysical effects into account when assessing the climate mitigation capacity of BECCS. Bioenergy crops has been proposed as a climate mitigation measure, but how the biophysical effects of large-scale cultivation would influence the climate is not well known. Here, the authors use models to show that large-scale cultivation could cool the global land by 0.03 to 0.08 °C.

Prediction of the landslide development process is always a hot issue in landslide research. So far, many methods for landslide displacement series prediction have been proposed. The support vector machine (SVM) has been proved to be a novel algorithm with good performance. However, the performance strongly depends on the right selection of the parameters (C and γ) of the SVM model. In this study, we present an application of genetic algorithm and support vector machine (GA–SVM) method with parameter optimization in landslide displacement rate prediction. We selected a typical large-scale landslide in a hydro-electrical engineering area of southwest China as a case. On the basis of analyzing the basic characteristics and monitoring data of the landslide, a single-factor GA–SVM model and a multi-factor GA–SVM model of the landslide were built. Moreover, the models were compared with single-factor and multi-factor SVM models of the landslide. The results show that the four models have high prediction accuracies, but the accuracies of GA–SVM models are slightly higher than those of SVM models, and the accuracies of multi-factor models are slightly higher than those of single-factor models for the landslide prediction. The accuracy of the multi-factor GA–SVM models is the highest, with the smallest root mean square error (RMSE) of 0.0009 and the highest relation index (RI) of 0.9992.

Antibiotic resistance and associated genes are ubiquitous and ancient, with most genes that encode resistance in human pathogens having originated in bacteria from the natural environment (eg, β-lactamases and fluoroquinolones resistance genes, such as qnr). The rapid evolution and spread of \"new\" antibiotic resistance genes has been enhanced by modern human activity and its influence on the environmental resistome. This highlights the importance of including the role of the environmental vectors, such as bacterial genetic diversity within soil and water, in resistance risk management. We need to take more steps to decrease the spread of resistance genes in environmental bacteria into human pathogens, to decrease the spread of resistant bacteria to people and animals via foodstuffs, wastes and water, and to minimize the levels of antibiotics and antibiotic-resistant bacteria introduced into the environment. Reducing this risk must include improved management of waste containing antibiotic residues and antibiotic-resistant microorganisms.

The Last Glacial Maximum (LGM; 21 ka BP) was the most recent glacial period when the global ice sheet volume was at a maximum. Therefore, the LGM can be used to investigate atmospheric dynamics under a climate that differed significantly from the present. This study quantitatively compares pollen records of boreal summer (June–July–August) precipitation with the PMIP3 LGM simulations. The data-model comparison shows an overall agreement on a drier than pre-industrial East Asian summer monsoon (EASM) climate. Nevertheless, 17 out of 55 records show a regional precipitation increase that is also simulated over the additional land mass area due to sea level drop. The thermodynamic and dynamic responses are analyzed to explain a drier LGM EASM as a combination of these two antagonistic mechanisms. Relatively low atmospheric moisture content was the main thermodynamic control on the lower LGM (relative to pre-industrial levels) EASM precipitation amounts in both the reconstructions and the models. In contrast, two dynamic processes in relation to stationary eddy activity act to increase EASM precipitation regionally in records and simulations, respectively. Precipitation increase in records is explained by dynamic enhancement of the horizontal moisture transport, while dynamic enhancement of the vertical moisture transport leads to simulated precipitation increase over the specific region where landmass was exposed during LGM along continental coastlines of China due to significant drop in sea level (relative to pre-industrial levels). Overall, the opposing effects of thermodynamic and dynamic processes on precipitation during the LGM provide a means to reconcile the spatial heterogeneity of recorded precipitation changes in sign, although data-model comparison suggests that the simulated dynamic wetting mechanism is too weak relative to the thermodynamic drying mechanism over data-model disagreement regions.

Bioenergy with carbon capture and storage (BECCS) is considered to be a key technology for removing carbon dioxide from the atmosphere. However, large-scale bioenergy crop cultivation results in land cover changes and activates biophysical effects on climate, with earth’s water recycling altered and energy budget re-adjusted. Here, we use a coupled atmosphere-land model with explicit representations of high-transpiration woody (i.e., eucalypt) and low-transpiration herbaceous (i.e., switchgrass) bioenergy crops to investigate the range of impact of large-scale rainfed bioenergy crop cultivation on the global water cycle and atmospheric water recycling. We find that global land precipitation increases under BECCS scenarios, due to enhanced evapotranspiration and inland moisture advection. Despite enhanced evapotranspiration, soil moisture decreases only slightly, due to increased precipitation and reduced runoff. Our results indicate that, at the global scale, the water consumption by bioenergy crop growth would be partially compensated by atmospheric feedbacks. Thus, to support more effective climate mitigation policies, a more comprehensive assessment, including the biophysical effects of bioenergy cultivation, is highly recommended. Increased global land precipitation, due to the atmospheric feedbacks of large-scale bioenergy cultivation, may partially compensate the water consumption by such rainfed bioenergy crops at the global scale.

Rapidly quenched ternary Ni-Mn-T (T = In, Sn) alloys exhibit features associated with magnetic skyrmions, so that XRD, TEM, EDS, SAED and HREM investigations were carried out for structural characterization on the two alloy systems. In this paper, we report a new type of Mn-rich Heusler compound with a cubic unit cell, a  = 0.9150 nm in Ni-Mn-In and a  = 0.9051 nm in Ni-Mn-Sn, which coexist with a Ni-rich full-Heusler compound with defects, a  = 0.6094 nm in Ni-Mn-In and a  = 0.6034 nm in Ni-Mn-Sn. A further analysis of the experimental results reveals a close structural relationship between these two compounds.