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Accurate estimate of the size of land carbon sink is essential for guiding climate mitigation actions to fulfill China's net-zero ambitions before 2060. The atmospheric inversion is an effective approach to provide spatially explicit estimate of surface CO 2 fluxes that are optimally consistent with atmospheric CO 2 measurements. But atmospheric inversion of China's land carbon sink has enormous uncertainties, with one major source arising from the poor coverage of CO 2 observation stations. Here we use a regional atmospheric inversion framework to design an observation network that could minimize uncertainties in inverted estimate of China's land carbon sink. Compared with the large spread of inverted sink (∼1 Pg C a−1) from state-of-the-art inversions using existing CO 2 observations, the uncertainty is constrained within 0.3 Pg C a−1 when a total of 30 stations were deployed, and is further reduced to approximately 0.2 Pg C a−1 when 60 stations were deployed. The proposed stations are mostly distributed over areas with high biosphere productivity during the growing season, such as Southeast China, Northeast China, North China, and the Tibetan Plateau. Moreover, the proposed stations can cover areas where existing satellites have limited coverage due to cloud shadowing in the monsoon season or over complex topography. Such ground-based observation network will be a critical component in the future integrated observing system for monitoring China's land carbon fluxes. [ABSTRACT FROM AUTHOR]

Extreme weather and climate events tend to increase and strengthen as global warming intensifies, which severely affect human life and sustainable economic development. Therefore, based on the Detection and Attribution Model Intercomparison Project (DAMIP) and the Land Use Model Intercomparison Project (LUMIP) provided by the Coupled Model Intercomparison Project phase 6 (CMIP6), the optimal fingerprinting method is applied to quantify the greenhouse gases (GHG), aerosols (AA), natural forcing (NAT), and land use/cover change (LUCC) contributions to the intensity, frequency, and duration of extreme temperatures in China during 1960—2020. The results show that GHG is the main driver of extreme temperature changes in China, except for ice days (ID0) and cold spells (CSDI). GHG causes an increase in warm spells (WSDI) by about 10 days and an extension of the growing season length (GSL) by 6 to 8 days. The Tibetan Plateau is the region with the strongest extreme temperature changes influenced by GHG. AA forcing has a cooling effect that partially offsets the warming effect of GHG, especially in southeastern China. It should be pointed out that AA forcing is also the main driver for the changes in diurnal temperature range (DTR) in southeastern China, which exceeds the GHG contribution. Additionally, LUCC has greater impact in nighttime extreme temperature indices changes than the regional AA, and becomes the second dominant factor beside GHG. LUCC leads to an attributable cooling contribution of 0.34 °C for the maximum of daily minimum temperatures (TNx). Spatially, the LUCC effects on extreme temperature changes are stronger in western China than in eastern China. The more robust estimation of the GHG, AA, NAT, and LUCC contributions over distinct regions provides an advanced understanding of anthropogenic impacts on regional extreme temperatures, which is expected to be an important reference for regional climate change adaptation and mitigation. [Display omitted] • Tibetan Plateau is the region with the strongest extreme temperature changes influenced by greenhouse gases (GHG). • GHG displays a nonuniformity effect on the changes in the extreme temperature frequency. • Land use/cover change (LUCC) has a stronger role in nighttime extreme temperature indices changes than the regional AA. • The LUCC effects on extreme temperature changes are stronger in western China than in eastern China • The LUCC effects on extreme temperature show asymmetrical characteristics. [ABSTRACT FROM AUTHOR]

The grassland ecosystems in Tibetan Plateau (TP) and Inner Mongolia (IM) of China play important roles in climate change mitigation and food and livestock production. These two regions have increasingly experienced higher temperatures and changing precipitation regimes over the past three decades. However, it remains uncertain to what extent rising temperature and varying precipitation regulate the water and carbon fluxes across alpine (TP) and temperate (IM) grasslands. Here, we first optimize a process-based model of carbon and water fluxes using eddy-covariance data (three sites in TP and six sites in IM), and analyze the simulated carbon and water fluxes based upon the optimized model exposed to a range of annual temperature and precipitation anomalies. We found that the changes in net ecosystem-atmosphere carbon exchange (NEE) of TP grassland are relatively small because the ecosystem respiration (R e ) and the gross primary productivity (GPP) increase at comparable rate with warming across multiple sites (R e : 22.1 ± 21.4 g C m −2 year −1 °C −1 , GPP: 22.43 ± 36.41 g C m −2 year −1 °C −1 ), which is due to the possibility that grasslands cannot respire more than the available supply of photosynthesis. The NEE of IM grassland increases (more carbon loss from ecosystem) with warming, which is mainly because GPP decreases faster than R e under warm-induced reduction in moisture availability, and the sensitivity of R e to warming (1.17 ± 3.56 g C m −2 year −1 °C −1 ) is much smaller than that of GPP (15.53 ± 15.91 g C m −2 year −1 °C −1 ). These results indicate that water is the major limiting factor in IM grasslands, but not in TP grasslands. In contrast to warming, we found an asymmetric response of water and carbon fluxes to drying and wetting in TP grasslands (i.e. a large decrease under the drying condition and a small increase under the wetting condition) but almost a linear response in IM grasslands. We therefore highlight that the underlying processes regulating the responses of water and carbon cycles to warming are fundamentally different between TP and IM grasslands, with the moisture being the major limiting factor in IM while grasslands in TP are much more limited by thermal conditions. Our results also imply that warming would significantly stimulate the net ecosystem carbon loss to atmosphere but not significantly enhance ET in IM grasslands, which may provide a positive feedback to accelerate climate change. Inversely, warming could not significantly affect the ecosystem carbon exchange but significantly enhance ET in TP grasslands, which may provide a negative feedback to mitigate climate change in alpine grasslands. [ABSTRACT FROM AUTHOR]

In recent years, ozone pollution has attracted wide attention from the scientific community, policymakers and the public. Previous studies have already confirmed the effects of meteorological conditions on regional ozone pollution events in the last two decades. However, due to the lack of historical ozone observations, the relationship of climate variability and ozone pollution has been less discussed. In our study, we use the NCEP/NCAR Reanalysis data and modeled historical surface ozone from CMIP6 (Coupled Model Intercomparison Project Phase 6) to explore the impact of climate variability related to Tibetan Plateau on summertime (June, July and August) ozone in Central China during 1950–2019. The results show that in interdecadal timescale, the annual summertime ozone over Central China is significantly correlated (R = −0.52; P -value <0.05) with the springtime (March, April and May) thermal forcing, indicated by total atmospheric energy (TPE), over Tibetan Plateau. In high TPE years, the East Asian monsoon (southerly wind flow) and vertical ascending motion have been enhanced in summer. It is conducive to both the diffusion of ozone and its precursors and occurrence of cloudy and high humidity weather. These processes lead to lower ozone concentrations up to 6.97 ppb (compared with values averaged during 1950–2019) over Central China. On the contrary, in low TPE years, summertime surface ozone concentrations have been increased by 2.96 ppb (the mean value is 49.00 ppb and the standard deviation is 11.75 ppb for 1950–2019) on average of Central China, due to the weakened East Asian monsoon and weakened vertical ascent, thus the stable weather with low humidity and small near surface wind. After the year 2000, the TPE has increased with a rapid growth rate of 3 × 104 hPa J kg−1 yr−1. However, similar to the reported surface ozone increments based on the modeling results and observations, the CMIP6 summertime surface ozone has shown an increasing trend in the last two decades (0.45 ppb yr−1 and 0.25 ppb yr−1 over Central China and entire China during 1950–2019, respectively). While a decline trend (0.18 ppb yr−1) of ozone from 1980 to 2019 over Central China is calculated after the removal of emission-attributed trend. These results indicate that the ozone increasing trend dependent on the changes of precursor emissions has offset the ozone mitigation attributed to the climate. • Effect of springtime thermal forcing over TP on summertime ozone is revealed. • Thermal forcing over Tibetan Plateau has an interannual to decadal variation. • Historical weather over Asian monsoon region are affected by thermal forcing over TP. • Ozone increases due to emissions has offset the ozone mitigation due to the climate. [ABSTRACT FROM AUTHOR]