River riparian basins play a crucial role in mitigating greenhouse gas (GHG) emissions through carbon sequestration and nitrogen sinks. However, increased ecological stresses led to the release of CO2, CH4 and N2O. This study aimed to investigate how extreme temperatures, water levels, moisture content, land use changes and soil composition influence GHG emissions in the riparian corridor and to recommend mitigation techniques. It was carried out at the Yangtze River Riparian zone, China, using soil column testing. It used soil column testing. The results showed that extreme temperatures caused the highest emissions of CO2 (29-45%), CH4 (24-43%) and N2O (27-33%). This was due to increased soil temperatures and accelerated organic carbon/nitrogen decomposition. Conversely, control and wet-dry cycles absorbed CO2 (1-3%), CH4 (3-10%) and N2O (1-21%) by improving soil aeration, increased oxygen availability, soil structure, stable water table and low temperature change. Grasses in riparian areas also improved carbon sinks. Highest water levels had lowest gas concentrations and emissions due to low oxygen level. Adaptive wet-dry cycles, grass cover and better water table management can restore riparian areas, maintain soil moisture, balance soil carbon/nitrogen levels and mitigate climate change by improving soil quality. Dissolved organic matter fluorescence (DOMFluor) components are essential for soil carbon dynamics, aquatic biome safety, nutrient cycling and ecological balance in riparian zones. The study recommends implementing restoration practices, managing soil moisture, afforestation, regulating temperature and monitoring water tables to mitigate GHG emissions and address climate change. Future policies should focus on promoting resilient land use and ecosystems.

Irrigation has distinct impacts on extreme temperatures. Due to the carryover effect of soil moisture into other seasons, temperature impacts of irrigation are not limited to irrigated seasons. Focusing on the North China Plain, where irrigation occurs in both spring (March-April-May) and summer (June-July-August), with a higher proportion of irrigation water applied during spring, we investigate the impact of spring irrigation on summer extreme heat events. Based on partial correlation analysis of data products, we find positive correlations between spring and summer soil moisture, suggesting that spring irrigation-induced water surplus persists into the following summer and affects regional climate by impacting surface energy partitioning. Regional climate simulations confirm cross-seasonal climatic effects and show that spring irrigation reduces the frequency and intensity of summer extreme heat events by approximately -2.5 days and -0.29 degrees C, respectively. Our results highlight the importance of the cross-seasonal climatic effect of irrigation in mitigating climate extremes. Irrigation exerts a stronger impact on extreme temperatures than on mean temperatures. The North China Plain (NCP) is a typical winter wheat-summer maize rotation planting area, where irrigation is necessary in both spring and summer, but with a higher proportion of irrigation water applied during spring. The climatic effects of spring and summer irrigation in the NCP are intertwined due to the carryover effects of soil moisture. Recently, the climatic effect of irrigation in the NCP has been extensively explored, whereas the cross-seasonal effects of irrigation on summer extreme heat events have never been quantified. In this study, we employ the Weather Research and Forecasting model coupled with a demand-driven irrigation algorithm to discern the effects of spring and/or summer irrigation on summer extreme heat events by means of idealized climate simulations. The results show that spring and summer irrigation significantly reduces the frequency and intensity of summer extreme heat events by approximately -6.5 days and -1.0 degrees C, of which spring irrigation contributes about 38% and 30%, respectively. Our findings underline the importance of irrigation-induced climate impacts in mitigating extreme heat events and emphasize that climate change adaptation planning in terms of irrigation must account for cross-seasonal climatic effects. Effect of multi-seasonal irrigation on summer extreme heat events is investigated Spring irrigation is beneficial for reducing summer extreme heat events Irrigation modulates the relationship between spring and summer soil moisture

Despite the importance of the Yellow River to China, climate change for the middle reaches of the Yellow River Basin (YRB) has been investigated far less than for other regions. This work focuses on future changes in mean and extreme climate of the YRB for the near-term (2021-2040), mid-term (2041-2060), and far-term (2081-2100) future, and assesses these with respect to the reference period (1986-2005) using the latest REgional MOdel (REMO) simulations, driven by three global climate models (GCMs) and assuming historical and future [Representative Concentration Pathway (RCP) 2.6 and 8.5] forcing scenarios, over the CORDEX East Asia domain at 0.22 degrees horizontal resolution. The results show that REMO reproduces the historical mean climate state and selected extreme climate indices reasonably well, although some cold and wet biases exist. Increases in mean temperature are strongest for the far-term in winter, with an average increase of 5.6 degrees C under RCP 8.5. As expected, the future temperatures of the warmest day (TXx) and coldest night (TNn) increase and the number of frost days (FD) declines considerably. Changes to mean temperature and FD depend on elevation, which could be explained by the snow-albedo feedback. A substantial increase in precipitation (34%) occurs in winter under RCP 8.5 for the far-term. Interannual variability in precipitation is projected to increase, indicating a future climate with more extreme events compared to that of today. Future daily precipitation intensity and maximum 5-day precipitation would increase and the number of consecutive dry days would decline under RCP 8.5. The results highlight that pronounced warming at high altitudes and more intense rainfall could cause increased future flood risk in the YRB, if a high GHG emission pathway is realized.

The frequency and the intensity of extreme temperature events have both increased globally because of the effects of climate warming. Such extreme events should be distinct in high-elevation areas owing to the phenomenon of elevation-dependent warming; however, corroborating evidence remains limited because of scarce observations. This study used the percentile method to identify annual extreme temperature events recorded in the delta O-18 of the Laohugou ice core (1960-2006) retrieved from the high-elevation area of the northeastern Tibetan Plateau (NETP). Comparison of these events with synchronous observations obtained at surrounding meteorological stations indicated that extreme temperature events identified from the ice core corresponded well with most temperature observations from the meteorological stations, suggesting that the delta O-18 record could be considered a reasonable proxy for regional temperature. However, occasional discord between the ice core and station records might reflect specific climatic shifts. Using circulation synthesis, the influencing circulation mechanism of each event was determined on the basis of differences in atmospheric parameters between each event and the average climatic state during 1970-2000. A double blocking high with warming over the Ural Mountains and east of Kuril-Kamchatka resulted in Eurasian warming, which transported warm air to the NETP and triggered the extreme high-temperature events. Conversely, a polar vortex in the Arctic led to a cold low over Eurasia, which transported cold air to the NETP causing extreme low-temperature events. The finding that variation of the Arctic air mass triggers extreme temperature events at high elevations in the NETP provides crucial insight for improved comprehension and forecasting of regional extreme temperature events.

Global warming increases the frequency and intensity of climate extremes, but the changes in climate extremes over the Antarctic Ice Sheet (AIS) during different periods are unknown. Changes in surface temperature extreme indices (TN10p, TX10p, TN90p, TX90p, CSDI, WSDI, TNn, TNx, TXn, TXx and DTR) are assessed during 2021-2050 and 2071-2100 under SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5, based on the multi-model ensemble mean (MMEM) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). The extreme indices, excluding TXn and DTR, illustrate the opposite trend in the two periods in SSP1-2.6 over the AIS. Generally, the changes in extreme indices reflect the continued warming over AIS in the future, and the warming is projected to intensify in SSP3-7.0 and SSP5-8.5. The variations in the extreme indices exhibit regional differences. The Antarctic Peninsula displays rapid changes in TNn, TXn and DTR. In SSP5-8.5, the magnitudes of all climate index tendencies are greater during 2071-2100 than 2021-2050. The variations in TX10p, TX90p, TN10p, TN90p, WSDI and CSDI are faster in the Antarctic inland than in the other regions over the AIS. However, the decrease in the DTR is concentrated along the AIS coast and extends to the interior region, whereas the increasing trend occurs in the Antarctic inland. In West AIS, TX90p and TN90p rapidly increase during 2021-2050, whereas the rapid changing signals disappear in this region in 2071-2100. The dramatic changes in TNn, TXn and DTR occur at the Ross Ice Shelf during 2071-2100, indicating an increased risk of collapse. For TNx and TXx, the degree of warming in the later part of the 21st century is divided by the transantarctic mountains, and greater changes appear on the eastern side. Generally, Antarctic amplification of TNn, TXn and DTR is observed except under SSP1-2.6. In addition, TNx and TXx amplifications occur in SSP3-7.0 and SSP5-8.5.

Heat waves in India during the pre-monsoon months have significant impacts on human health, productivity and mortality. While greenhouse gas-induced global warming is believed to accentuate high temperature extremes, anthropogenic aerosols predominantly constituted by radiation-scattering sulfate are believed to cause an overall cooling in most world regions. However, the Indian region is marked by an abundance of absorbing aerosols, such as black carbon (BC) and dust. The goal of this work was to understand the association between aerosols, particularly those that are absorbing in nature, and high-temperature extremes in north-central India during the pre-monsoon season. We use 30-year simulations from a chemistry-coupled atmosphere-only general circulation model (GCM), ECHAM6-HAM2, forced with evolving aerosol emissions in an interactive aerosol module, along with observed evolving SSTs. A composite of high-temperature extremes in the model simulations, compared to climatology, shows large-scale conditions conducive to heat waves. Importantly, it reveals concurrent positive anomalies of BC and dust aerosol optical depths. Changes in near-surface properties include a reduction in single scattering albedo (implying greater absorption) and enhancement in short-wave heating rate, compared to climatological conditions. Alterations in surface energy balance include reduced latent heat flux, but increased sensible heat flux, consistent with enhanced temperatures. Thus, chemistry-coupled GCM simulations capture an association of absorbing aerosols with high-temperature extremes in north India, arising from radiative heating in the surface layer.