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The interdecadal variability of tropical cyclone precipitation (TCP) over the western North Pacific (WNP) has not been thoroughly explored in previous studies. Here, we show that the TCP variations are modulated by both the Atlantic Multidecadal Oscillation (AMO) and Interdecadal Pacific Oscillation (IPO) as evidenced by reanalysis data and model experiments. A clustering analysis of tropical cyclone tracks shows that the AMO dominates a dipole pattern of TCP anomalies in the South China Sea and along the coastal eastern China. Meanwhile, the IPO dominates TCP over the southeastern WNP. Further analyses show that the AMO, particularly its extratropical component, affects TCP over the WNP by triggering an eastward‐propagating Rossby‐wave train, resulting in a pair of anomalous gyres over the WNP. Contrastly, the IPO modulates TCP by stimulating tropical circulation anomalies via the tropical pathway. These findings shed light on improving near‐term TCP forecast and its regional influence on East Asia. Plain Language Summary: Tropical cyclone precipitation (TCP) is a topic of great concern owing to its destructive nature. Here, we find that TCP over the western North Pacific (WNP) exhibits significantly interdecadal variability and regional characteristics, a departure from the previous studies focusing on the entire WNP. The Atlantic Multidecadal Oscillation (AMO) mainly causes a dipole response of decadal changes in TCP over the South China Sea and coastal eastern China. Moreover, the AMO primarily affects TCP over the sub‐regional WNP through the extra‐tropical pathway by exciting a Rossby wave train. On the other hand, the Interdecadal Pacific Oscillation (IPO) predominantly affects TCP over the southeastern part of the WNP through the tropical pathway, inducing significant circulation anomalies over the tropical WNP. These findings offer valuable insights for future research and forecasting of TCP. Key Points: The Atlantic Multidecadal Oscillation (AMO) contributes to the dipole pattern of interdecadal tropical cyclone precipitation (TCP) anomalies over the South China Sea and coastal eastern ChinaThe AMO affects TCP by triggering a westerly jet‐guided Rossby‐wave train via the extra‐tropical pathwayThe Interdecadal Pacific Oscillation dominates the TCP anomalies over the southeastern part of western North Pacific by modulating tropical circulation anomalies [ABSTRACT FROM AUTHOR]

With climate change, frequent forest fires and prolonged fire period occur all over the world. Moreover, carbon emission from forest fire affects the carbon cycle of the forest ecosystem. However, this effect varies by region with no uniform conclusions, and fewer comparative studies exist on such differences between regions. In this paper, net primary productivity (NPP) data MOD17A3 were used as an important parameter of forest carbon absorption, along with MODIS fire spot data MCD14DL and burned area data MCD64A1. Forest carbon lost under forest fire interference in the northeast and southwest natural forest areas of China was studied to explore the role of forest fire in the carbon cycle process and its differences in the unlike regions of China. Here, by means of kernel density analysis and M-K trend test, the characteristics of forest fires in China's southwest and northeast forests were calculated. Forest carbon emission under forest fire disturbance was quantified by reference to the forest fire emission factor list. We show that (1) the total number of forest fire spots in the southwest region from 2001 to 2020 was 1.06 × 105, 1.28 times that of Northeast China. However, the total burned area in the southwest was only 67.84% of that in the northeast. (2) The total carbon emissions from forest fires in the southwest from 2001 to 2020 was 37,559.94 Gg, 10.77% larger than the northeast forest, CH4 and CO2 were 13.52% and 11.29% larger respectively. Moreover, the carbon emissions of forest fire in the northeast showed a downward trend, R2 = 0.16 (p < 0.1), while it remained basically unchanged in the southwest. The contribution of carbon emissions from forest fires changed with forest types, it was shown as: evergreen needleleaf forest (14.98%) > evergreen broadleaf forest (10.81%) > deciduous needleleaf forest (6.52%) > deciduous broadleaf forest (5.22%). (3) From 2001 to 2020, under the premise that the NPP both manifested upward trends, the NPP of the burned areas showed a significant downward trend in the southwest forest, with R2 = 0.42 (p < 0.05), while it increased in the northeast forest, with R2 = 0.37 (p < 0.05). It showed negative correlation between NPP of burned areas and forest fire carbon emissions, and forest fire disturbance had no significant effect on forest NPP in Northeast China, while net carbon loss occurred in Southwest China. In general, under different forest fire characteristics, NPP, which represents forest carbon uptake, and carbon emissions from forest fires show differences. The impact of forest fire disturbance on forest carbon process varies with regions. The study can provide some ideas on the effects of forest fire disturbance on climate change. [ABSTRACT FROM AUTHOR]

Precipitation fluctuations are continuously threatening the environment and may cause huge economic losses. In present study, the precipitation over China has been evaluated under five principal shared socioeconomic pathways (SSPs) scenarios during 2015–2099 based on eight CMIP6 models bias-corrected by the method of Equidistant Cumulative Distribution Functions. The results showed that (1) the simulated precipitation in China was in good agreement with observed precipitation for the eight CMIP6 models during 1961–2014, especially for the UKESM1-0-LL and MIROC6. However, the simulated annual mean precipitation has been significantly overvalued in the Southwest River basin (> 50%), while it was undervalued in the higher elevations of the Northwest River basin (< − 60%); (2) the annual mean precipitation will show a fluctuating upward trend during 2015–2099 over China under all the SSPs scenarios for the eight CMIP6 models. The rate of precipitation increase over north China will be higher than that in south China, especially in the Northwest River basin (reach 57.44% in the 2090s under the SSP5-8.5 for the ensemble mean). This increase of the precipitation in north China might alleviate the shortage of water there, but will not change the pattern of more rain in the south and less in the north; (3) in the southeastern basins, the precipitation of the multi-model ensemble (MME) and MIROC6 during 2011–2020 will be lower than that of 1961–2010 (− 6.53 to − 0.06%) under all SSPs scenarios. While the precipitation will increase obviously under all the SSPs scenarios, especially for the SSP5-8.5 scenario after the year of 2060; (4) the bias of the MME was much lower than that of individual CMIP6 models, and the bias of lower SSPs scenarios will be relatively lower. Generally, uncertainty ranges of precipitation fluctuations in north China (15.31–79.26%) will be higher than those in south China (16.06–7.55%). These findings revealed the projections and uncertainties of CMIP6 precipitation over China, which will be helpful for a better understanding of the future evolution of precipitation in China at large scale and in other regions of the world. [ABSTRACT FROM AUTHOR]

China is the largest CO 2 emitting country on Earth. During the COVID-19 pandemic, China implemented strict government control measures on both outdoor activity and industrial production. These control measures, therefore, were expected to significantly reduce anthropogenic CO 2 emissions. However, large discrepancies still exist in the estimated anthropogenic CO 2 emission reduction rate caused by COVID-19 restrictions, with values ranging from 10% to 40% among different approaches. Here, we selected Nanchang city, located in eastern China, to examine the impact of COVID-19 on CO 2 emissions. Continuous atmospheric CO 2 and ground-level CO observations from January 1st to April 30th, 2019 to 2021 were used with the WRF-STILT atmospheric transport model and a priori emissions. And a multiplicative scaling factor and Bayesian inversion method were applied to constrain anthropogenic CO 2 emissions before, during, and after the COVID-19 pandemic. We found a 37.1–40.2% emission reduction when compared to the COVID-19 pandemic in 2020 with the same period in 2019. Carbon dioxide emissions from the power industry and manufacturing industry decreased by 54.5% and 18.9% during the pandemic period. The power industry accounted for 73.9% of total CO 2 reductions during COVID-19. Further, emissions in 2021 were 14.3–14.9% larger than in 2019, indicating that economic activity quickly recovered to pre-pandemic conditions. [Display omitted] • A 40% decrease of anthropogenic CO 2 emissions was observed during the 2020 COVID-19 pandemic. • Power industry accounted for 73.9% of total CO 2 reductions during COVID-19. • Anthropogenic CO 2 emissions in 2021 were 14% larger than in 2019. • The recovery of CO 2 emissions between year 2021 and 2019 indicates a fast economic rebound. • Point source location mismatches should be evaluated in city scale emission inversion. [ABSTRACT FROM AUTHOR]

The increasing anthropogenic aerosols (AAs) over East Asia have caused significant regional climate responses, but the role of urban land-use changes which occur simultaneously, in altering these AA-induced changes, is not well understood. Here, the modulation of the AAs' effect on the East Asian winter (November–January) climate by the urban cover in eastern China was investigated using the Community Atmosphere Model version 5.1 coupled with the Community Land Model version 4. Results show that the winter sulfate aerosol burden is higher from central eastern China to southern Japan in the case with the presence of urban cover than in the case without it, resulting from urban-induced circulation changes. Such aerosol changes markedly increase the cloud fraction and precipitation over northern China and the adjacent ocean to the east, especially convection activities around southern Japan. This leads to a cooling effect near the surface over northern China and in the mid-upper troposphere to the east due to aerosol direct and indirect effects. The resulting circulation responses act to shift the mid-tropospheric East Asian trough southward and the upper-level East Asian westerly jet-stream as well, further supporting the surface changes. These winter climate responses to the urban-modulated aerosols can largely offset or even reverse those to the AAs forcing without the urban cover in the model, especially in northern East Asia. This study highlights the need to consider the modulating role of urban land-use changes in assessing the AAs' climatic effect over East Asia and other regions. [ABSTRACT FROM AUTHOR]

Methane is the second largest anthropogenic greenhouse gas, and changes in atmospheric methane concentrations can reflect the dynamic balance between its emissions and sinks. Therefore, the monitoring of CH 4 concentration changes and the assessment of underlying driving factors can provide scientific basis for the government's policy making and evaluation. China is the world's largest emitter of anthropogenic methane. However, due to the lack of ground-based observation sites, little work has been done on the spatial-temporal variations for the past decades and influencing factors in China, especially for areas with high anthropogenic emissions as Central and Eastern China. Here to quantify atmospheric CH 4 enhancements trends and its driving factors in Central and Eastern China, we combined the most up-to-date TROPOMI satellite-based column CH 4 (xCH 4) concentration from 2018 to 2022, anthropogenic and natural emissions, and a random forest-based machine learning approach, to simulate atmospheric xCH 4 enhancements from 2001 to 2018. The results showed that (1) the random forest model was able to accurately establish the relationship between emission sources and xCH 4 enhancement with a correlation coefficient (R²) of 0.89 and a root mean-square error (RMSE) of 11.98 ppb; (2)The xCH 4 enhancement only increased from 48.21±2.02 ppb to 49.79±1.87 ppb from the year of 2001 to 2018, with a relative change of 3.27%±0.13%; (3) The simulation results showed that the energy activities and waste treatment were the main contributors to the increase in xCH 4 enhancement, contributing 68.00% and 31.21%, respectively, and the decrease of animal ruminants contributed -6.70% of its enhancement trend. [Display omitted] [ABSTRACT FROM AUTHOR]

China is the largest CO 2 emitting country on Earth. During the COVID-19 pandemic, China implemented strict government control measures on both outdoor activity and industrial production. These control measures, therefore, were expected to significantly reduce anthropogenic CO 2 emissions. However, large discrepancies still exist in the estimated anthropogenic CO 2 emission reduction rate caused by COVID-19 restrictions, with values ranging from 10% to 40% among different approaches. Here, we selected Nanchang city, located in eastern China, to examine the impact of COVID-19 on CO 2 emissions. Continuous atmospheric CO 2 and ground-level CO observations from January 1st to April 30th, 2019 to 2021 were used with the WRF-STILT atmospheric transport model and a priori emissions. And a multiplicative scaling factor and Bayesian inversion method were applied to constrain anthropogenic CO 2 emissions before, during, and after the COVID-19 pandemic. We found a 37.1-40.2% emission reduction when compared to the COVID-19 pandemic in 2020 with the same period in 2019. Carbon dioxide emissions from the power industry and manufacturing industry decreased by 54.5% and 18.9% during the pandemic period. The power industry accounted for 73.9% of total CO 2 reductions during COVID-19. Further, emissions in 2021 were 14.3-14.9% larger than in 2019, indicating that economic activity quickly recovered to pre-pandemic conditions., (Copyright © 2022 Elsevier Ltd. All rights reserved.)