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A model‐circulation increment‐based dynamic statistical technique (MIDST) is proposed in this paper to improve the prediction of summer rainfall over southern China (SC) where quite low prediction skills have been found in the Beijing Climate Center Climate System Model version 1.1 with a moderate resolution (BCC_CSM1.1m). The results show that BCC_CSM1.1m can hardly represent the variability of the summer rainfall anomaly and its year‐to‐year increment over SC, and the skillful predictions are mostly confined over the middle reaches of the Yangtze River. Using the dynamic model output and statistical method, the MIDST is established to capture the coupled modes between the year‐to‐year increments of the summer rainfall anomaly and the associated simultaneous three‐dimensional coupled air‐sea circulation predictors. The cross‐validation indicates that the prediction skills of the MIDST are evidently improved for both the summer rainfall increment prediction and summer rainfall anomaly prediction compared with the direct BCC_CSM1.1m prediction. The skillful prediction can persist for long forecast leads over most regions except southwestern China. As the major predictability source of seasonal prediction, the intense response to changes in the circulation related to the El Niño‐Southern Oscillation (ENSO) is well captured, and thus, the performance improvement of the MIDST is primarily due to its more realistic representation of the incremental circulation related to the ENSO. [ABSTRACT FROM AUTHOR]

An analysis is presented of the precipitation bias and change signal in an ensemble of regional climate model (RCM) (RegCM4) projections driven by multiple general circulation models (GCMs) over China. RegCM4 is driven by five different GCMs for the 120‐year period 1979–2099 at 25 km grid spacing, under the representative concentration pathway RCP8.5. We find that the GCMs and RegCM4 reproduce the general spatial pattern of precipitation over China in all four seasons, with RegCM4 providing greater spatial detail, especially over areas with complex terrain. The spatial patterns of precipitation bias show common features between the GCMs and RegCM4, characterized by an underestimation in the wetter regions, and an overestimation in the drier ones. Systematic increases of precipitation are projected in northern China, most pronounced in the Northwest basins, by both the GCMs and RegCM4 in all seasons except summer, when more mixed results are found. In addition, weak correlations of the projected change patterns are found in summer between the GCMs and nested RegCM4, indicating the greater role played by the representation of local convection processes during this monsoon season. The projections across the RegCM4 experiments show higher consistency and lower spread compared to the GCM ensemble, again indicating that the nested model physics significantly modulates the change signal deriving from the GCM boundary forcing. Plain Language Summary: China is a vulnerable country to climate change due to its dense population, unbalanced social and economic development, shortage of water resources, and fragile ecosystems. How future precipitation will change over the region is of great concern for the general public and decision makers. This paper presents a first analysis of precipitation simulations from a set of five RCM (RegCM4) 21st century climate change projections, driven by coarse resolution general circulation models (GCMs) over China. We find that the spatial patterns of precipitation bias show common features between the GCMs and RegCM4, characterized by a precipitation underestimation in the wetter regions, and an overestimation in the drier ones. Systematic increases of precipitation are projected in north China by both the GCMs and RegCM4 in all seasons except summer, when, weak correlations of the projected change patterns are found between the GCMs and nested RegCM4, indicating the greater role of the representation of local convection processes during this monsoon season. The projections across the RegCM4 experiments show higher consistency and lower spread compared to the GCM ensemble, again indicating that the nested model physics significantly modulates the change signal deriving from the GCM boundary forcing. Key Points: The spatial patterns of bias show common features between the GCMs and RegCM4RegCM4 provides greater spatial detail of present day precipitation simulation compared to the GCMs and finer structures of future changesThe change patterns across the RegCM4 projections show a high correlation, but not always between each pair of driving GCM and RegCM4 [ABSTRACT FROM AUTHOR]

A heavy nocturnal warm sector rainfall occurred over the western coastal region of South China in June 2020, of which the precipitation magnitude was seriously underestimated by the operational TRAMS (Tropical Regional Atmosphere Model System) model. In this study, by improving the configuration of initial conditions (ICs) and lateral boundary conditions (LBCs) in offline nesting, the simulation of the convection initiation (CI) process can be well improved. The CI simulation is found to be sensitive to the vertical resolution in ICs in this case. When the low‐level vertical resolution of ICs is increased, the nocturnal near‐surface cold layer caused by inland mountains can be resolved better, which is necessary to form the convergence line along the coastline. Another important impact of increasing the vertical resolution of ICs is the successful simulation of horizontal convective rolls (HCRs) over the northern South China Sea. The HCRs apparently increase the depth of the warm‐moist marine boundary layer jet (MBLJ), and finally lead to the CI along the coastline. The increased vertical resolutions of LBCs can reduce the discontinuity of simulated moist tongue across the southern lateral boundary of the TRAMS model, which provides more moisture for the warm sector rainfall through MBLJ. LBCs with Higher temporal frequency help to alleviate the western position bias of rain belt by reducing the temporal interpolation error. Our study highlights the importance of finer ICs and LBCs in offline nesting for regional operational NWP systems in the South China region. Plain Language Summary: Warm‐sector heavy rainfall in South China usually develops under weakly forced weather condition, numerical forecasting of its initiation and intensification process is a difficult problem. To investigate its sensitivity to the configuration of initial conditions (ICs) and lateral boundary conditions (LBCs), a simulation study is carried out for a nocturnal warm sector rainfall event happened in western Guangdong. When the low‐level vertical resolution of ICs is increased, the nocturnal near surface cold layer from inland mountains can be resolved better. Another important impact of increasing vertical resolution of ICs is the successful simulation of horizontal convective rolls (HCRs) over the northern South China Sea. The HCRs apparently increase the depth of warm‐moist marine boundary layer jet (MBLJ), and finally lead to the CI along coast line. Additionally, the vertical resolution and the updating frequency of the lateral boundary conditions also have important effects on the simulation of the rainstorm intensification process. This paper emphasizes the importance of accurate ICs and LBCs to improve the predictability of warm‐sector rainfall in South China, which can provide practical reference for the design of operational systems. Key Points: Increasing low‐level vertical resolution of initial conditions is critical to the convection initiation (CI) simulation of warm‐sector rainfall caseThe increased vertical resolutions of lateral boundary conditions (LBCs) can provide more moisture for the CI and upscale convective growth process through marine boundary layer jetHigher temporal frequency LBCs is help to alleviate the western position bias of rain belt by reducing the temporal interpolation error [ABSTRACT FROM AUTHOR]

The hydrological projections provided by the outputs of Global Climate Models (GCMs) combining hydrological models include multi‐source uncertainties, which may challenge the formulation of relevant adaption and mitigation policies. In this paper, the overall uncertainty and the relative contribution of each uncertainty component were investigated for hydrological projections over 408 watersheds in China by using 3 shared socioeconomic pathway emission scenarios (SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5), 21 GCMs, 8 bias correction methods, 4 hydrological models, and 2 sets of optimized hydrological model parameters. The results show that the total uncertainty (T) is mainly contributed by uncertainty related to global climate models (G), with the mean percentage ranging from 60.4 to 64.1%, followed by the interaction uncertainties among all components, with the mean percentage ranging from 22.0 to 26.4%. The uncertainty contribution of hydrological models (H) (6.1–9.4%) ranks third, followed by emission scenarios (S) (2.9–5.9%) and bias correction methods (B) (0.2–1.1%). The uncertainty contribution of the optimized hydrological model parameters (P) (0.2–0.3%) is almost negligible. In terms of spatial variability, the relative contribution of uncertainty related to global climate models (G) is the highest in the near future for northern China (67.5–70.6%) and in the far future for southern China (66.1–66.7%). However, it was found to be lower for the Tibetan Plateau and northwestern China (45.3–57.9%) in the near and far future. The relative contribution of hydrological model uncertainty is higher for southwestern and northwestern China and the Tibetan Plateau (7.2–19.5%) and lower for northern, eastern, and southern China (2.5–6.6%). This study highlights the importance of including multiple GCMs and hydrological models in hydrological impact studies to consider their overall uncertainty. The development of global climate models and hydrological models is still the best way to reduce the uncertainty of climate change impact studies. [ABSTRACT FROM AUTHOR]

Compound climate extremes, such as events with concurrent temperature and precipitation extremes, have significant impacts on the health of humans and ecosystems. This paper aims to analyze temporal and spatial characteristics of compound extremes of monthly temperature and precipitation, evaluate the performance of the sixth phase of the Coupled Model Intercomparison Project (CMIP6) models in simulating compound extremes, and investigate their future changes under Shared Socioeconomic Pathways (SSPs). The results show a significant increase in the frequency of compound warm extremes (warm/dry and warm/wet) but a decrease in compound cold extremes (cold/dry and cold/wet) during 1985–2014 relative to 1955–1984. The observed upward trends of compound warm extremes over China are much higher than those worldwide during the period of interest. A multi‐model ensemble (MME) of CMIP6 models performs well in simulating temporal changes of warm/wet extremes, and temporal correlation coefficients between MME and observations are above 0.86. Under future scenarios, CMIP6 simulations show substantial rises in compound warm extremes and declines in compound cold extremes. Globally, the average frequency of warm/wet extremes over a 30‐yr period is projected to increase for 2070–2099 relative to 1985–2014 by 18.53, 34.15, 48.79, and 59.60 under SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5, respectively. Inter‐model uncertainties for the frequencies of compound warm extremes are considerably higher than those of compound cold extremes. The projected uncertainties in the global occurrences of warm/wet extremes are 3.82 times those of warm/dry extremes during 2070–2099 and especially high for the Amazon and the Tibetan Plateau. Plain Language Summary: Compound climate extremes, such as the events with concurrent temperature and precipitation extremes, have significant impacts on the health of humans and ecosystems. Can climate model simulate the historical compound extremes? If yes, how the global compound extremes will change in the future? In this study, we found that the global climate model performs well in simulating temporal changes of warm/wet and warm/dry extremes during the period 1955–2014. With greenhouse gas emissions continuing to increase in the future, compound warm/dry and warm/wet extremes show a continuous increase in frequency in the next few decades, while compound cold/dry and cold/wet extremes are projected to occur less frequently. Key Points: A multi‐model ensemble of CMIP6 models performs well in simulating temporal changes of warm/wet extremesThe inter‐model uncertainties for the frequencies of compound warm extremes are considerably higher than those of compound cold extremesThe projected uncertainties in the global occurrences of warm/wet extremes are 3.82 times those of warm/dry extremes during 2070–2099 [ABSTRACT FROM AUTHOR]

The projection of runoff in a large‐scale basin under climate change and human activities is crucial for the future management of water supplies. The impacts of climate change on runoff projections are associated with large uncertainties. In this study, using the optimization and selection of climate models, as well as an uncertainty analysis via the global Bayesian model averaging (BMA) approach, an ensemble projection framework was established to significantly improve the reliability of runoff projections in the future. The global BMA algorithm proposed in this study is an improvement on the BMA algorithm for large basins and is designed to reflect the differences among various models across the basin. In this algorithm, comprehensive BMA weights are obtained by considering the number (N) of stations in a basin. To verify the feasibility and improvement of this method, the runoff in 2050 and 2070 was projected with data from the Yellow River Basin, China. The runoff and its 90% confidence intervals at the six main stations in the Yellow River Basin were obtained. The increased evapotranspiration will exceed the increase in runoff generated by increase in precipitation in the future. The runoff in the upper and middle reaches of the Yellow River in 2050 and 2070 are projected to be 9% and 7% lower, respectively, than those in the reference period. The ensemble projection method proposed in this paper can be used as a widely applicable process in hydrometeorological ensemble projection and provides a basis for water resource management planning. Key Points: An ensemble projection framework was established to significantly improve the reliability of runoff in the futureThe global BMA algorithm is proposed to obtain comprehensive BMA weights by considering number of stations in a basinThe runoff of the Yellow River Basin in 2050 and 2070 will decrease by 9% and 7%, respectively [ABSTRACT FROM AUTHOR]

ABSTRACT This paper presents an evaluation study of the Regional Climate Model version 4.3 ( RegCM4.3) over the Loess Plateau in northern China, which is a semi-arid region characterized by complex topography. During recent years, a series of reforestation programmes have been implemented across the region that might influence the local climate in complex ways. To better understand the local climate, the RegCM4.3 was applied to simulate the present-day conditions over the Loess Plateau. The simulation was carried out from 1990 to 2009 at the 50-km horizontal resolution, with lateral boundary conditions taken from the ECMWF-Interim reanalysis. A series of climate variables and processes were evaluated during the winter and summer seasons, such as 2-m air temperature, precipitation, wind circulation, surface energy balance, full moisture budget, and cloud radiative forcing (CRF). The possible origins of the simulation bias and the physical linkages with other model processes were examined. In general, RegCM4.3 is able to reproduce both the spatial and temporal features of the regional climate over the Loess Plateau. However, there are still biases in some meteorological variables including precipitation and 2-m air temperature. In particular, the model tends to produce cold biases during winter and underestimate precipitation during summer. Further analyses indicates that the cold biases in winter may have resulted from the deficiency of the downward longwave radiation fluxes, excessive ground heat fluxes, and negative temperature advection by the seasonal mean circulation. These processes are primarily triggered by deficiencies in CRF and excessive northwesterlies over the plateau. The underestimated precipitation during summer is associated with a weak southerly monsoon in the model. A full moisture budget analysis reveals that the dry bias in this region can be mainly attributed to model deficiency in moisture advection and convergence, and to a lesser extent to that in surface evaporation. [ABSTRACT FROM AUTHOR]

While previous studies have largely focused on anthropogenic warming characterized by surface air temperature, little is known about the behaviors of human‐perceived temperature (HPT), which describe the "feels‐like" equivalent temperature by considering the joint effects of temperature, humidity and/or wind speed. Here we adopted an optimal fingerprinting method to compare seasonal mean HPTs in China with those from simulations conducted with multiple climate models participating in the Coupled Model Intercomparison Project Phase 6. We found clear anthropogenic signals in the observational records of changes in both summer and winter HPTs over the period 1971–2020. Moreover, the anthropogenic greenhouse gas influence was robustly detected, with clear separation from natural and anthropogenic aerosol forcings. The anthropogenic greenhouse gas forcing plays the dominant role (>90%) of human‐perceived warming. Urbanization effects contribute slightly and moderately to the estimated trends in summer and winter HPTs, respectively, in addition to the effects of external forcing. Plain Language Summary: Human influences have been identified in the observed warming quantified by surface air temperature (SAT), but SAT alone is inadequate as a metric for human thermal comfort. Here we focus on human‐perceived temperature (HPT), which describes the "feels‐like" equivalent temperature by considering the joint effects of temperature, humidity, and/or wind speed. We isolate anthropogenic impacts on the observed increase in summer and winter HPTs in China during 1971–2020 by comparing observations with state‐of‐the‐art climate models. Results show that the influence of anthropogenic greenhouse gas is detected, with clear separation from other external forcings such as solar and volcanic activities and anthropogenic aerosols. The human‐induced greenhouse gas increases are also found to explain most (>90%) of the observed human‐perceived warming. Along with the effects of large‐scale anthropogenic forcing, urbanization effects also have a slight to moderate influence on the estimated trends in summer and winter HPTs. Our work is an early attempt to provide quantitative evidence for the physiological impacts of anthropogenic global warming and local urbanization on human beings. Key Points: The warming is quantified by human‐perceived temperature that considers the joint effects of temperature, humidity and/or wind speedHuman influence could be robustly detected in both summer and winter human‐perceived warmingThe observed increase in human‐perceived temperature is mostly attributed to anthropogenic greenhouse gas increases [ABSTRACT FROM AUTHOR]

Changes in winter cloudy days (CDs) exert substantial impacts on agricultural production, public transport, and the solar photovoltaic (PV) power industry. However, the physical mechanism behind the variability of winter CDs over China remains largely unclear, making it challenging to predict the future dynamics of winter CDs. In this study, we explored the spatiotemporal features of winter CDs over China from 1961 to 2013 and identified two independent formation mechanisms associated with its leading mode. Then, we projected the future changes (2021–2099) in winter CDs under global warming constrained by the identified formation mechanisms. Results revealed that: (a) The leading mode of winter CDs from 1961 to 2013 presents a homogeneous pattern. The positive winter CDs anomaly is connected to the anomalous southerlies related to the Eurasian Rossby wave train triggered by the Barents Sea thermal forcing, as well as the Asia‐Pacific zonal geopotential height gradient induced by the convection over the Maritime Continent; (b) Selected state‐of‐the‐art climate models project a notable decrease in winter CDs in the Tibetan Plateau and southern China regions, and almost unchanged winter CDs over northern China, under global warming; (c) In contrast to present‐day mechanisms, in the future, the shift of the Eurasian mean flow will terminate the role of the Barents Sea thermal forcing. Instead, the enhanced convection over the Maritime Continent emerges as the primary contributor to the decline in winter CDs. Our findings provide valuable insights for policymakers in the solar PV industry, particularly in relation to the challenges faced under global warming. Plain Language Summary: Winter cloudy days (CDs) over China exhibit significant spatiotemporal variability, greatly impacting agriculture, transportation, and the solar photovoltaic (PV) power industry. However, the physical mechanism and future changes of winter CDs in China under global warming have not been extensively explored. We revealed two independent routes influencing the formation of winter CDs in China. Furthermore, state‐of‐the‐art climate models project a clear diminish in winter CDs over the Tibetan Plateau and southern China in the mid‐term and long‐term under global warming, providing valuable guidance to policymakers involved in the solar PV power industry. Key Points: The uniform pattern observed in the dominant mode of winter cloudy days (CDs) over China can be attributed to the anomalous southerlies in East AsiaThe warming Arctic forcing and negative convection anomalies over the Maritime Continent both lead to the anomalous southerlies in East AsiaWinter CDs will diminish with enhanced greenhouse forcing, owing to a shift in Eurasian westerly jet affecting the Arctic forcing on East Asian anomalous southerlies [ABSTRACT FROM AUTHOR]

Comprehensive modelling of dust events requires a full physical representation of small-scale emission mechanisms and description of long-range transport dynamic. In this paper we propose a simulation system that integrates three different models in order to represent the whole dust cycle. The RAMS atmospheric model configuration has two nested grids, at 50 km and 10 km horizontal resolution, and is used to force both the dust emission model DUSTEM, and the transport model CAMx. The performance of the three-model simulation system was evaluated using a major dust storm that occurred in March 2002 in the desert of the Alashan Prefecture (Inner Mongolia, China) and which had a significant impact over a large area in northern China. In order to identify potential active dust sources, a specific remote sensed analysis, calibrated through a field campaign in the Alashan Prefecture region, has been assimilated in the modelling system. Simulated dust storm features, from the higher resolution grid, are in good agreement with observed data: surface wind values discrepancies are less than 2 m/s in the Alashan area and less than 5 m/s along the dust storm track. In comparison to ground observations, the modelled dust surface concentration peaks in Beijing differ by only 2 mg/m³ although the timing of dust peaks is delayed in the model. As a consequence this integrated numerical model, along with the remote sensed land surface characterization, is suggested to be a practical and flexible tool for simulating and analysing the whole dust storm dynamics. [ABSTRACT FROM AUTHOR]

The frequency and magnitude of global warming events varies greatly across different regions and countries. The climatic diversity for China and future warming features are projected across 12 climatic zones based on the ensemble of the five well‐performing high‐resolution downscaled climate models for each zone. There are warming patterns for the mean near‐surface air temperature (Tm), maximum near‐surface air temperature (Tmax), minimum near‐surface air temperature (Tmin) as well as heatwave and frost events. Under RCP4.5 and RCP8.5 scenarios, the three indices (i.e., Tm, Tmax and Tmin) countrywide are likely to increase at respective rates of 0.30–0.31 and 0.64–0.67°C·decade−1. The extent of frost event (FE) are projected to decrease at a rate of −1912 and −4442 day·km−2·decade−1 while the extent of heatwave event (HE) increase at a rate of 1116 and 3557 day·km−2·decade−1 under RCP4.5 and RCP8.5 scenarios, respectively. A higher increment in temperatures, a decreasing trend in diurnal temperature range (DTR), frost days and FE are highlighted in the western and northern zones, while these trends are opposite in southern zones. The warming is likely to get faster in the current colder zones (western and northern zones) while heatwave is more intense and severe in Jianghuai, Jianghan, the south Yangzi River, South China and Xinjiang. These potential changes indicate that adaption and mitigation strategies are necessary in response to future warming. [ABSTRACT FROM AUTHOR]

Many studies have shown that the climate system has the long‐range correlation (LRC) characteristics, which provide a good test bed for evaluating the performance of climate models. In this study, the LRC characteristics of the observed surface daily temperature data in China is first analysed by detrended fluctuation analysis. It is found that the daily temperature records, including daily mean temperature (Tmean), daily maximum temperature (Tmax), and daily minimum temperature (Tmin), all exhibit LRC characteristics with scaling exponents more than 0.6 in most of China. Then, the performances of two different versions for the Beijing Climate Center Climate System Model (BCC‐CSM), namely, BCC‐CSM1.1m in CMIP5 and BCC‐CMS2‐MR in CMIP6, are quantitatively evaluated by comparing the differences of the LRC characteristics between the observations and the simulations. The results indicate that BCC‐CSM2‐MR performs better than BCC‐CSM1.1(m) in western Northwest China, most of south of the middle and lower reaches of Yangtze River, North China, central Inner Mongolia for the daily Tmean and Tmax. As far as the daily Tmin is concerned, BCC‐CSM1.1(m) performs better than BCC‐CSM2‐MR in western South China and southern Xinjiang, and the performance of BCC‐CSM2‐MR in CMIP6 has not been significant improved. Compared with BCC‐CSM1.1(m), BCC‐CSM2‐MR cannot significantly improve the simulations for the LRC characteristics of the three daily temperature variables in central and eastern Qinghai‐Tibet plateau, and the areas of between lower reaches of Yellow River and Yangtze River. [ABSTRACT FROM AUTHOR]

The simultaneous occurrence of droughts and floods in neighboring regions amplifies the threats posed by droughts and floods individually. Nonetheless, few studies have been conducted to investigate the simultaneous occurrence of drought and flood events. Here we explore the spatiotemporal characteristics and the shift pattern of droughts and pluvials over Eastern China from a three‐dimensional perspective, using the self‐calibrated Palmer Drought Severity Index and the Climate Research Unit data set as well as four regional climate model simulations. We find that Eastern China experienced droughts and pluvials simultaneously in different locations during boreal summer, and it is projected to simultaneously experience more frequent and more intense droughts and pluvials under a warming climate. Specifically, we investigate the pattern of more pluvials in Southeast China and more droughts in Northeast China for the historical period of 1975–2004. This pattern dynamically evolves under climate warming: the pluvial‐dominated regime shifts from Southeast to Northeast China, while the drought‐dominated regime shifts from Northeast to Southeast China. The weakening strength of the western Pacific subtropical high and a northward displacement of the monsoon rain belt may both contribute to the pattern of more pluvials in Northeast China and more droughts in Southeast China. These findings provide insights into the development of adaptation strategies and emergency response plans for enhancing society's resilience to the spatial co‐occurrence of dry and wet extremes. Plain Language Summary: The spatial co‐occurrence of drought and flood events has been receiving widespread attention in recent years since the superimposed condition of drought and flood has brought unprecedented challenges to disaster prevention, mitigation, and relief work. Eastern China is prone to droughts and floods, but their spatial interconnections are not yet well understood. Thus, we explore the historical evolution and the future change of simultaneous occurrence of droughts and floods over Eastern China under a warming climate. The spatial co‐occurrence of droughts and floods is projected to affect more land areas and become more frequent as climate warms. Eastern China experienced a pattern of more floods in Southeast China and more droughts in Northeast China during 1975–2004. We find that droughts tend to become more intense in Southeast China and the severity of floods is expected to increase in the northern region of East China, resulting in a shift pattern of more droughts in Southeast China and more floods in Northeast China. The shift pattern may be attributed to the weakening of western Pacific subtropical high strength and a northward displacement of the monsoon rain band in a changing climate. Key Points: Eastern China is projected to experience more frequent and more intense droughts and pluvials simultaneouslyThe spatial pattern of more pluvials in Southeast China and more droughts in Northeast China is expected to become an opposite pattern under a warming climateThe weakening strength of the western Pacific subtropical high and a northward displacement of the monsoon rain belt may contribute to the pattern of more pluvials in Northeast China and more droughts in Southeast China [ABSTRACT FROM AUTHOR]

Climate change impacts ocean nutrient availability and will likely alter the marine food web. While climate models predict decreased average ocean productivity, the extent of these changes, especially in the marginal seas upon which large human populations depend, is not well understood. Here, we reconstructed changes in seawater phosphate concentration and nitrate source over the past 400 years, which reveals a more than 50% decline in residence time of seawater phosphate, and 8%–48% decline in subsurface nitrogen supply following the coldest period of Little Ice Age. Our data indicates a link between surface ocean nutrient supply and the East Asian Summer Monsoon strength in an economically important marginal sea. As climate models predict that the East Asian Summer monsoon will strengthen in the future, our study implies that surface ocean primary productivity may increase in the South China Sea, contrary to the predicted decrease in global average ocean productivity. Plain Language Summary: Global climate models predict that surface ocean nutrient concentrations will significantly decrease over the next 100 years as our climate changes. However, in the world's marginal seas, which human populations depend on most heavily for food security, the surface ocean biogeochemical changes are still difficult to predict with global‐scale models. Here, using coral‐based paleoclimate proxies, we reconstruct changes to surface phosphate concentration and to sources of surface nitrogen over the past four centuries in the South China Sea (SCS). Combined with box model simulations, our data reveal a more than 50% decline in phosphate residence time and an 8%–48% decline in subsurface nitrate supply from the 1600s to present. Such a decline implies a significant decrease in primary productivity and likely a community shift toward nitrogen‐fixing phytoplankton. Importantly, our data indicate that the decrease in nutrient supply was driven by weakened monsoon‐induced upwelling, demonstrating strong ties between nutrient supply and monsoon strength in the SCS. Climate change is predicted to strengthen the East Asian Summer Monsoon, and our results suggest that primary productivity in this economically important region may increase, contrary to the widely predicted decreases in average global ocean productivity. Key Points: Coral skeletal phosphorus content with scattered nitrogen isotopes is reconstructed over the past 400 yearsNutrient supply declined up to 48% since the Little Ice Age in the western South China SeaThe coral record from links nutrient supply to monsoon wind, implying higher productivity under a stronger monsoon in the future [ABSTRACT FROM AUTHOR]

In this study, we focus on the features and predictability of winter 2‐m air temperature (t2m) over China under different intensities of La Niña events. The seasonal and intraseasonal prediction skills of winter t2m over China are examined by four state‐of‐art seasonal climate forecast models. The results show that the China winter t2m anomaly is sensitive to the intensity of La Niña. Strong and moderate (S/M) La Niña events are often accompanied by cold winter over China, while a positive anomaly of mean t2m over China frequently occurs in the weak La Niña events. The intensity difference of the East Asian winter monsoon (EAWM) results in this discrepancy. All models have a slightly higher anomaly correlation coefficient (ACC) for the S/M La Niña than that for the weak La Niña in leading 1 month (LT1). Both individual models and MME exhibit higher skills of anomaly sign consistency rate (ASCR) for the S/M La Niña, which implies that models predict t2m anomaly over China more accurately in the S/M La Niña events. Furthermore, the winter t2m over China presents larger intraseasonal variability for the S/M La Niña than that for the weak La Niña. Models can capture the t2m anomaly over China more accurately when the temperature varies gently with small intraseasonal variability during winter for the S/M La Niña. [ABSTRACT FROM AUTHOR]

Drought is one of the most serious natural disasters exacerbated by climate change. Changes in precipitation and temperature in the future increase the likelihood of drought in China. In this study, a stepwise cluster ensemble downscaling (SCED) model was developed to bias‐correct projections of temperature and precipitation from multiple RCM outputs, and further characterized the drought hazards. The developed SCED model was used to aggregate and correct the results of multiple regional climate models, and its performance was proved to be reliable by comparing with the observed results. The proposed SCED method has been applied for drought projections over the Fujian province, China. The results showed that the changes of precipitation and temperature in Fujian would have obvious spatial heterogeneous characteristics. The temperature in the southeast coastal areas will increase by up to 4°C and the precipitation will decrease by 3.1% in the late 21st century, while the temperature rises and precipitation increases in the southwest. Temperature in inland areas will be lower and precipitation will be less. The drought hazards were also characterized by both SPI and SPEI based on biased‐corrected projections from SCED model. According to the SPI and SPEI indices, although the number of dry months in Fujian province will not change significantly in future, the spatial and temporal heterogeneity may become more explicit. Moreover, the moderate drought (from SPI) may increase while the general drought may decrease (from both SPI and SPEI). For extreme droughts, there would not be visible changes detected by SPI, but an increasing trend characterized since the impact of temperature was included in SPEI. In addition, there would be an increasing trend on drought when increasing temperature and precipitation occurred simultaneously. [ABSTRACT FROM AUTHOR]

Daily climate data are extremely important to drive ecological models, but the outputs of climate models are often deviated from the observations. The bias correction methods mostly highlight the target statistical parameters (e.g., mean and variance) for a target period, but perturb the simulated change trend and variability. In this study, we utilize a trend‐preserving bias correction method that can simultaneously consider the frequency and intensity of climatic variables to adjust the daily maximum and minimum temperature, and precipitation (Tmax, Tmin, and Pre) from CORDEX‐EA regional climate models for the period of 2021–2050 over China. Results show that: (a) the bias correction method greatly improves the spatial patterns of simulated Tmax, Tmin, and Pre since the corrected data has higher correlation and smaller differences across the whole domain. The differences in mean Tmax, Tmin, and Pre between climate models and observations have been reduced from −4.5 ± 6.41°C, −2.06 ± 0.58°C, 177.25 ± 51.55 mm before correction to 0.01 ± 0.02°C, −0.01 ± 0.02°C, −26.22 ± 6.39 mm after correction, respectively. In addition, the simulated change trend and climate variability at all time scales are well preserved. (b) Spatially, the warming rates in the west would be higher than in the east, and they are larger under the most severe future emissions scenario (RCP8.5) relative to the low‐mid emissions scenario (RCP4.5). The Pre change would mainly occur over east China with the significant upward trend. The dataset presented in this article has been published in the Network Common Data Form (NetCDF) File Format at https://doi.org/10.5281/zenodo.5058620. [ABSTRACT FROM AUTHOR]

The uncertainty of the climatic effect of Black carbon (BC) remains large. One critical uncertainty source that needs to be captured is BC aging. Here we use the Community Atmosphere Model version 6 (CAM6) configured with the four‐mode version of the Modal Aerosol Module (MAM4) to evaluate the modeled BC aging process with recent laboratory and in‐situ measurements over China. As revealed by the comparison of BC aging timescale and number fraction of aged BC against recent measurements, the modeled condensation aging timescale is estimated to be about 0.8 hr (17%) faster than the chamber measurement, and the diurnal variations of modeled BC aging degree are typically higher than observations mainly due to the fast increase in modeled BC aging degree during daytime. Further analysis shows that the condensation aging dominates (>70%) BC aging across China. More specifically, the condensation of secondary organic aerosol (SOA) vapor contributes most to BC aging over China. Slowing down BC aging increases the modeled surface BC concentration over remote Western China and BC burden, but hardly changes surface BC concentration over Eastern China. Our results suggest that BC aging representation in the MAM4 needs to be further improved toward slowing down the BC aging rate, especially the condensation aging by SOA, to improve the BC simulation over remote areas and its impact on BC transport in MAM4. Plain Language Summary: Black carbon (BC) has a warming effect on climate. Currently, significant divergences in simulated BC burden and optical properties have been shown among global climate models (GCMs), and hence BC radiative forcing remains largely uncertain. BC aging is one of the key processes that contribute to uncertainties in BC simulation. In this study, we evaluate the BC aging process in a global climate model with recent laboratory and in‐situ measurements over China. Our study illustrates that BC aging is too fast in the model compared with observations, and the dominant process for modeled BC aging is SOA vapor condensation over China. We further show how different BC aging rates might affect modeled surface BC concentration and BC burden. Our results suggest that further measurements are needed to better understand BC aging mechanism to improve BC aging in GCMs. Key Points: BC aging is too fast in MAM4 compared against measured BC condensation aging timescale and number fraction of aged BCSOA vapor condensation plays a dominant role in modeled BC aging process over ChinaSlowing down BC aging increases surface BC over remote Western China and BC burden, but hardly changes surface BC over Eastern China [ABSTRACT FROM AUTHOR]

Most of China's carbon sink inversion research uses global atmospheric transport models to assimilate natural fluxes, which quantifies the biosphere and ocean carbon budget with a relative coarse spatial resolution and long timescale from a weekly or monthly perspective. Toward high‐resolution inversion of CO2 fluxes, a novel carbon flux forecast model was developed in this study, which was then further used to carry out carbon assimilation based on a regional chemical transport model (CMAQ) at higher spatial (64 × 64 km2) and temporal (1 hr) resolutions. An Ensemble Kalman Smoother was applied as the assimilation algorithm and further extended to assimilate surface CO2 observations. Concentrations and fluxes were simultaneously assimilated as state variables to help reduce the uncertainty in the initial CO2 fields with the joint data assimilation framework (JDAS). In general, the posterior fluxes reproduced the seasonal, daily and hourly variation effectively, demonstrating the ability to fully absorb and utilize observations. Moreover, the influence of the choice of assimilation window on the carbon flux inversion was assessed via sensitivity experiments, revealing 36 hr to be the optimum length. Evaluation of the prior and posterior flux simulations also indicated that JDAS offers reasonable improvements, making it suitable for fine‐scale flux optimization and estimation. In addition, the posterior biosphere estimation in mainland China (−682 TgC yr−1) tends to be the optimal mathematical solution under current sparse observation coverage with daytime photosynthetic uptake, which likely leads to the overestimation of the optimized CO2 sink. This study serves as a basis for future regional and urban assessment. Plain Language Summary: Top‐down methods are used increasingly to constrain the carbon budget under the Monitoring and Verification Support framework by the United Nations Framework Convention on Climate Change. Different to previous attempts to assimilate China's carbon sink from a weekly or monthly perspective, we developed a novel regional carbon inversion system based on Community Multiscale Air Quality (CMAQ) and Ensemble Kalman Smoother with surface observations toward high‐resolution inversion of CO2 fluxes. Besides the forward, fine‐scale simulation by CMAQ, a flux forecast model with diurnal variation capability was also introduced to facilitate illustrating the hourly evolution of ensemble fluxes. The results indicate that our posterior fluxes reproduced the seasonal, daily and hourly variation effectively, which suggests the method provides a promising tool for future monitoring of the effectiveness of progress toward carbon neutrality. Key Points: An Ensemble Kalman Smoother‐based regional carbon data assimilation system was developed with Community Multiscale Air Quality to resolve fine‐scale CO2 flux variabilityThe seasonal, daily and hourly variations of posterior fluxes were reproduced effectivelySensitivity experiments further highlighted the valuable impact of the choice of assimilation window [ABSTRACT FROM AUTHOR]

This study evaluates the ability of 23 climate models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating extreme climate events over China. The multimodel ensemble (MME) performs better than most individual models in reproducing the climatological mean distribution of all extreme indices. The MME can reproduce well the climatological mean distributions of five extreme climate indices over China, including annual total precipitation (PTOT), maximum consecutive 5‐day precipitation (RX5), simple daily intensity (SDII), maximum daily maximum temperature (TXX), and minimum daily minimum temperature (TNN), with Taylor skill scores exceeding 0.7. SDII and TXX are the most skilful precipitation and temperature extreme indices simulated by the MME, respectively. The MME has relatively lower skill in simulating the climatological mean distribution of warm days (TX90P) and cold nights (TN10P) over China. Future projections of these extreme climate indices by the end of the 21st century are explored with the MME under the SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5 scenarios. The PTOT and RX5 in northwestern China are all projected to increase by more than 30% under SSP5‐8.5. R20 is projected to increase by 4–5 days over southeastern China under SSP5‐8.5. There are fewer (more) consecutive dry days over north China (south China), with a change of 5 days under SSP5‐8.5. The extreme temperature indices, including TX90P, TXX, and TNN, all increase with time and higher SSP scenarios. The three indices increase by 40–55%, 4–6°C, and 4–7°C under SSP5‐8.5 over east China, respectively. The TN10P decreases by more than 6% over east China. The changes in these extreme indices under SSP1‐2.6 and SSP2‐4.5 are similar to those under SSP5‐8.5 but with a smaller magnitude. Large uncertainties still exist in the future projections, especially under the high SSP scenarios. [ABSTRACT FROM AUTHOR]

The East Asian summer monsoon (EASM) is unique among monsoon systems that it features meridional evolution of the summer monsoon. In this study, we evaluate the performances of a Variable‐Resolution Community Earth System Model (VR‐CESM) regionally refined over eastern China (14 km) in reproducing the seasonal evolution of EASM precipitation over China. Compared with reference datasets, VR‐CESM shows better performance than the corresponding globally uniform coarse‐resolution model CESM (quasi‐uniform 1°), especially over western China where complex local topography exists. The northward monsoon migration is closely related to low‐level southerly flows and vertical moisture advection, which are more reasonably simulated in VR‐CESM. The four critical timings of the EASM (monsoon onset, withdrawal, peak, and duration) are also better captured in VR‐CESM than in CESM. The corresponding spatial Pearson correlation coefficients of the four critical timings with respect to reference datasets are about 0.1 higher in VR‐CESM than those in CESM. Both models are most accurate in simulating monsoon onset and least accurate at simulating the monsoon peak. The overestimated zonal thermal contrast in CESM is responsible for the earlier monsoon onset and excessive precipitation in September over the Yangtze River valley. Finer resolution in VR‐CESM, especially over the Tibetan Plateau (TP), appears to be a main factor in simulating better zonal thermal contrast and seasonal evolution of the EASM. [ABSTRACT FROM AUTHOR]

The present study aimed to evaluate the performance of 46 global climate models (GCMs) from the newly released Coupled Model Intercomparison Project Phase 6 (CMIP6) in the historical simulation of precipitation and temperature, and select the best performing GCMs for future projection across China and three major river basins. This study uses four shared socioeconomic pathways (SSPs), namely SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5 relative to the base period (1961–2014). Initially, 46 models were evaluated across China employing an improved Taylor diagram method. Based on relatively better performance, 10 best‐performing models (TBMs) were selected out of 46 models for further evaluation. The results show that historical temperature was well reproduced by CMIP6 over the study regions with a high correlation coefficient (CC). All the TBMs produced good CC ranging from 0.8 to 0.99 presenting the precipitation and temperature distribution well. Meanwhile, EC‐Earth3 and EC‐Earth3‐Veg well simulated the precipitation and temperature amounts as well as trends over selected three river basins. The multimodel ensemble mean (MME) underestimates temperature over China and selected three basins with bias values of −0.53, −0.21, −0.91, and −0.68°C, respectively. In contrast, MEM overestimated the simulated precipitation with the amount of 27.7, 32.4, 21.0, and 104.6% across China and selected three basins. During future projections, increased precipitation and temperature trends are projected over three selected river basins as well as all across China. The increasing trend of future precipitation over China under SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5 scenarios are 0.65, 0.86, 1.29, and 0.76 mm·a−1, whereas, the increasing trend of temperature is 0.008, 0.028, 0.050, and 0.065°C·a−1, respectively. Comparatively, the greater the radiation force, the higher projected increases in precipitation and temperature across China and three major river basins were observed. The extent of CMIP6 models over the target region and its river basins calls for further deep assessment of the attribution and possible implementation of robust methods that can accurately simulate the observed patterns for future practice. [ABSTRACT FROM AUTHOR]

Global climate change is projected to increase the probability of occurrence and severity of droughts. Increased CO2 concentration drives partial closure of plant stomata and reduces evapotranspiration. However, the impact of reduced evapotranspiration due to CO2 on future droughts characteristics in China is unclear. In this study, we have used the Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate model simulations (GCMs) under historical period, and four shared socioeconomic pathway scenarios (SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5) to estimate drought. We used a widely applicable drought index (i.e., the self‐calibrating Palmer Drought Severity Index [scPDSI]) to evaluate the historical and future drought conditions, using the Penman–Monteith formula with and without the CO2 concentrations. The results show that the increasing trend of scPDSI slows down when the CO2 effect is considered in all scenarios, especially in Heilongjiang, northern Xinjiang, and the Qinghai–Tibet Plateau. The divergence in the slowdown trend among the different scenarios becomes greater after 2030, with higher emission scenarios implying a greater slowdown in the increasing trend of scPDSI. After considering CO2, drought characteristics such as the drought frequency, intensity, and drought area decrease. Increased CO2 concentration on vegetation physiological processes could mitigate future drought. Therefore, the effects of CO2 on plant physiology should be considered in studies of future drought trends to develop more realistic response and adaptation policies to future drought changes. [ABSTRACT FROM AUTHOR]

The Chinese Meteorology Administration chemistry model Chinese Unified Atmospheric Chemistry Environment (CUACE) is online integrated into the mesoscale operational numerical weather prediction (NWP) model (GRAPES_Meso5.1) and aerosol‐cloud‐radiation interaction is achieved to establish the first version (V1) of chemistry‐weather (CW) interacted model GRAPES‐Meso5.1/CUACE CW V1. The most polluted winter 2016–2017 is selected to study the meteorology impacts on haze/fog prediction, the impact of aerosol‐radiation, aerosol‐cloud and CW interaction (ARI, ACI, CWI) on haze/fog prediction and NWP. Single way model without CWI displays reasonable PM2.5 and visibility prediction in general. However, modeled PM2.5 peaks are underestimated and visibility valleys are overestimated during haze/fog pollution, the underestimation of relative humidity (RH) contributes major to this misestimation; CWI model cut the negative bias of PM2.5 peaks and the positive bias of visibility valleys. The improvement of 5 and 3 km low visibility by CWI during severe haze/fog period is more obvious than that of 10 km, which just compensates for the largest deficiency in low visibility prediction related with severe haze/fog by single way model; The NWP including sea level pressures, RH, temperature, wind speed are also improved by CWI from surface to upper troposphere; ARI contributes larger to the predicted PM2.5,visibility and NWP improvement than that of ACI, their relative contributions varies with model vertical height and the overlapping condition of cloud and aerosols. Due to the joint contribution of RH and PM2.5, CWI's improving on visibility is larger than PM2.5. This study illustrates the importance of including CWI in air quality prediction model. Plain Language Summary: Double way atmospheric chemistry model considering complete aerosol‐radiation‐cloud interaction is the hot and difficult issue in climate, weather and air quality (AQ) modeling. Focusing on better prediction of haze/fog pollution in China, the first version (V1) of chemistry‐weather (CW) interacted model GRAPES‐Meso5.1/CUACE CW V1 is established by online coupling the Chinese Meteorology Administration CUACE chemistry model with the updated operational mesoscale weather model GRAPES_Meso5.1 and the further completion of aerosol‐cloud‐radiation interaction in it. The meteorology impacts on haze/fog prediction including PM2.5 and visibility is discussed. The impacts of aerosol‐cloud interaction (ACI), aerosol radiation interaction (ARI) and the both (CWI) on haze/fog prediction and mesoscale NWP is further studied. The study results shows that the important impacts of relative humidity on high PM2.5 and low visibility and the improving of PM2.5, low visibility prediction and NWP by ARI, ACI and CWI during haze/fog episode, indicating the importance of CW model in better AQ prediction and NWP in polluted region. Key Points: An online chemistry‐weather (CW) interacted GRAPES_Meso5.1/Chinese Unified Atmospheric Chemistry Environment CW V1.0 model with aerosol‐radiation‐cloud interaction is establishedSingle way model shows basic reasonable haze/fog prediction including visibility and PM2.5 in most polluted subregions in ChinaCW Interaction improves PM2.5, visibility and numerical weather prediction from surface to upper troposphere to varying degree [ABSTRACT FROM AUTHOR]

The surface air temperature seasonal cycle in China has clearly changed in response to global warming, but its future projection has yet to be studied. Here, we investigate the performance and projection of the temperature seasonal cycle in China in 32 global climate models participating in the Coupled Model Intercomparison Project 6 (CMIP6). The characteristics of the temperature seasonal cycle, as represented by the amplitude and phase, are measured by the Fourier transform. The results show that the CMIP6 models can reasonably capture the observed typical temperature seasonal cycle feature with clear north–south gradients both for amplitude and phase in China. In the twenty‐first century, the models robustly project a delay in the phase across the whole country and a reduction in the amplitude in most of China relative to the reference period. Those changes are similar in the two shared socioeconomic pathway (SSP) scenarios, with overall larger magnitudes in the SSP5‐8.5 scenario than in the SSP2‐4.5 scenario. Projected amplitude changes are mainly linked to surface energy flux changes, especially latent heat flux changes. In response to future global warming, larger increases in the latent heat flux and thus stronger surface evaporative cooling lead to weaker surface warming in summer than in winter, contributing to a decrease in the amplitude of the temperature seasonal cycle in most regions of China. [ABSTRACT FROM AUTHOR]

Within the frameworks of the Coordinated Regional Downscaling Experiment‐East Asia first and second phase (CORDEX‐EA‐I and CORDEX‐EA‐II), the impact of spatial resolution, physical parameterization schemes and spectral nudging (SN) on simulating inland and offshore near‐surface wind speed over China is evaluated. By using WRF and RegCM4 models, the CORDEX‐EA simulations driven by the ERA‐Interim reanalysis data are conducted from 1989 to 2008. The regional climate models (RCMs) have the capacity to simulate the spatial patterns of surface wind, although significant overestimations exist over inland China. The WRF CORDEX‐EA‐II experiments with increasing horizontal resolution perform better in reproducing both inland and offshore wind speed than the CORDEX‐EA‐I experiments. Moreover, the experiments with SN can significantly reduce the positive biases of surface wind speed. For the temporal variation of wind speed, almost all the simulations show larger biases in winter than in summer. Particularly, the simulated wind speed in summer in the RegCM4 experiment with CLM3 land surface model (RCC‐II) is close to the observations. The extreme wind speed can be well reproduced by WRF simulations, and the SN experiments perform better than the experiments without SN (NOSN). In addition, the overestimations of surface wind speed can be partly explained by the overestimations of the wind field at 850 hPa level inherited from ERA‐Interim reanalysis and the increase of temperature gradient between the land and ocean in winter. [ABSTRACT FROM AUTHOR]

Inconsistencies in the Eocene climates of East Asia have been revealed in both geological studies and simulations. Several earlier reconstructions showed an arid zonal band in mid‐latitude China, but others showed a humid climate in the same region. Moreover, previous Eocene modeling studies have demonstrated that climate models can simulate both scenarios in China. Therefore, it is essential to investigate the cause of this model spread. We conducted a series of experiments using Norwegian Earth System Model 1‐F and examined the impact of mountains in Southern China on the simulated Eocene climate. These mountains, including the Gangdese and Southeast Mountains, are located along the main path of water vapor transport to East Asia. Our results reveal that the Southeast Mountains play the dominant role in controlling the simulated precipitation in Eastern China during the Eocene. When the heights of the Southeast Mountains exceed ∼2,000 m, an arid zonal band appears in mid‐latitude China, whereas humid climates appear in Eastern China when the elevation of the Southeast Mountains is relatively low. Key Points: Southeast Mountains control simulated Eocene precipitation in Eastern ChinaWhen the Southeast Mountains are high, an arid zonal band appears in mid‐latitude ChinaThe early Eocene climate in East Asia is not monsoonal climate [ABSTRACT FROM AUTHOR]

To support the implementation of China's carbon neutrality target, this study assesses the impact of future climate change on hydroelectricity production (HP) in China. We developed a hydropower database for mainland China, which covers 92% of the installed capacity indicated by national statistics (352 GW in 2018). An HP model was applied to simulate monthly HP by 3,521 conventional plants at different levels of global warming (1°, 1.5°, 2°, and 3°C above preindustrial) using an ensemble of monthly streamflow time series computed by five global hydrological models (GHMs), where each global hydrological model was driven by four global climate models (GCMs). With a probability of 80%, limiting global warming to 1.5°C will constrain changes of national HP to the range of −1.4%–2.5% as compared to near‐present climate (1°C). In case of a 3°C world, this range more than doubles. HP is projected to likely increase in the two provinces Sichuan and Yunnan that encompass more than half of China's installed capacity. However, with a probability of about 10%, HP may decrease in a 3°C world by more than 15% in five provinces, and 40% of the installed capacity may suffer from an HP decrease of more than 5%. The uncertainty of projected HP changes is mainly due to the GCMs. We found that relative changes in annual HP and streamflow often differ in magnitude and direction as HP depends on seasonal streamflow patterns and installed capacities that determine the maximum flow through the turbines. Key Points: A new hydropower database for mainland China was compliedSignificant reductions due to climate change cannot be precluded for 40% of the installed capacityChanges in annual hydroelectricity production and streamflow often differ in magnitude and direction [ABSTRACT FROM AUTHOR]

The evolution of hydroclimate in East Asia during the Pliocene—a potential analog of the future greenhouse climate—remains highly uncertain. Here we reconstruct changes in the hydroclimate of Northern China during this epoch. Our results reveal previously undocumented severe drought conditions that persisted through the early Pliocene with a significantly greater magnitude than suggested by other records. Using a broad hierarchy of climate simulations, we find that reduction in the Pacific meridional sea surface temperature (SST) gradient has particularly strong impacts on precipitation over Northern China, which suggests its key role in maintaining drought conditions during the early Pliocene. The weaker Pacific meridional SST gradient causes the weakening of the East Asian summer monsoon precipitation over this region via a reduction of atmospheric northward moisture transport from the ocean, which enhances aridity inland. Our results highlight the fundamental control of the tropical ocean on the extra‐tropical hydrological cycle. Plain Language Summary: Understanding East Asian rainfall changes with global warming is an important issue of climate sciences. The Pliocene epoch provides a potential analog to the future greenhouse climate. Here, for the first time we reconstruct high‐resolution aridity changes over the Chinese Loess Plateau (CLP) in northern East Asia during the Pliocene. Our results indicate persistent drought conditions over CLP during the early Pliocene. Analyzing a broad range of climate model simulations, we find that the reduced meridional sea surface temperature gradient is a critical factor in the weakening of the East Asian summer monsoon over Northern China and in maintaining drought conditions during the early Pliocene relative to the late Pliocene. Our results expand the Asian inland paleoclimate records during the Pliocene, providing new information on past Asian monsoon precipitation variations during the warm Pliocene with potential implications for future hydroclimate changes under greenhouse warming in East Asia. Key Points: Severe drought conditions persisted throughout the early Pliocene epoch over Northern ChinaWe link these conditions to the reduced meridional temperature gradient in the Pacific OceanThe reduced Pacific meridional temperature gradient acts to weaken the summer East Asian monsoon precipitation over Northern China [ABSTRACT FROM AUTHOR]

Since 2013, Chinese policies have dramatically reduced emissions of particulates and their gas‐phase precursors, but the implications of these reductions for aerosol‐radiation interactions are unknown. Using a global, coupled chemistry‐climate model, we examine how the radiative impacts of Chinese air pollution in the winter months of 2012 and 2013 affect local meteorology and how these changes may, in turn, influence surface concentrations of PM2.5, particulate matter with diameter <2.5 μm. We then investigate how decreasing emissions through 2016 and 2017 alter this impact. We find that absorbing aerosols aloft in winter 2012 and 2013 heat the middle‐ and lower troposphere by ∼0.5–1 K, reducing cloud liquid water, snowfall, and snow cover. The subsequent decline in surface albedo appears to counteract the ∼15–20 W m−2 decrease in shortwave radiation reaching the surface due to attenuation by aerosols overhead. The net result of this novel cloud‐snowfall‐albedo feedback in winters 2012–2013 is a slight increase in surface temperature of ∼0.5–1 K in some regions and little change elsewhere. The aerosol heating aloft, however, stabilizes the atmosphere and decreases the seasonal mean planetary boundary layer (PBL) height by ∼50 m. In winter 2016 and 2017, the ∼20% decrease in mean PM2.5 weakens the cloud‐snowfall‐albedo feedback, though it is still evident in western China, where the feedback again warms the surface by ∼0.5–1 K. Regardless of emissions, we find that aerosol‐radiation interactions enhance mean surface PM2.5 pollution by 10%–20% across much of China during all four winters examined, mainly though suppression of PBL heights. Plain Language Summary: Particulate matter, also called aerosols, influences climate through the absorption and reflection of solar radiation traveling through the atmosphere. Trends in particulate matter can therefore impact local and regional climate, which may in turn exacerbate particulate pollution. Here we embed a detailed atmospheric chemistry scheme within a global climate model to examine aerosol‐radiation interactions and their impact on particulate pollution over China in winter 2012–2013 and 2016–2017. We find that surface particulates decrease by 20% between the time periods, a result of stricter regulations. In both time periods, aerosol absorption of sunlight heats the atmosphere aloft, leading to more stable conditions. This in turn amplifies the concentration of surface particulate pollution by 10%–20%, again in both time periods. Aerosol heating aloft also diminishes cloud cover, which then reduces snowfall, especially in 2012–2013. The subsequent loss of snow cover allows more sunlight to be absorbed by the surface, apparently counteracting to some extent the surface cooling from reflection of sunlight by aerosols aloft. This work suggests an important role for absorbing aerosols like soot in affecting local climate; it also demonstrates the potential for climate models with detailed chemistry to shed new light on interactions between aerosols and climate. Key Points: GEOS‐Chem aerosols are for the first time coupled to radiation in an Earth System Model to examine aerosol‐radiation interactions in ChinaAbsorbing aerosols aloft may reduce clouds and snowfall, causing more surface absorption of radiation despite aerosol attenuation overheadAerosol‐radiation interactions over China in winter can increase concentrations of particulate matter in surface air by ∼10%–20% [ABSTRACT FROM AUTHOR]

To support future solar energy deployment in China, long‐term changes in solar energy resources over China were investigated based on high‐resolution dynamical downscaling simulations under three emission scenarios. First, an evaluation of model performance was conducted through comparison with station and ERA5 data, which indicated that although consistent overestimation was found, the spatial distribution and intra‐annual variation of solar radiation were captured well by ensemble simulation, showing added value over regions with complex topography as well. Then, the trends of the solar power output from photovoltaic (PV) systems during 2020–2099 were projected, characterized by an increase in east and central China, and a consistent decrease in the solar‐energy‐abundant regions (e.g., northeast China, the Tibetan Plateau, and northwest China) under the three scenarios. Except for under the low emission scenario, the regional averaged trends of PV were projected to decrease consistently over China in all four seasons, with significant magnitude apparent in both spring and winter. In addition, a more intense magnitude of decline was found under the higher emission scenario, with more subregions with a significant trend and higher intra‐annual and inter‐annual variability. However, it seems that the emission scenarios impact the spatial pattern only remarkably in the late century, however strengthened the decreasing magnitude in all future periods. In addition, results indicate decline in the future PV potential over most of subregions of China due to reduced radiation and increased temperature, but for the decrease over Tibetan Plateau the reduced wind speed also act as an important factor. Plain Language Summary: The long‐term goal of carbon neutrality in China involves new requirements for the development and utilization of solar energy. The present study was motivated by supporting future solar energy deployment at local scales. However, due to data limitations, relatively little effort has been made to project long‐term changes in solar energy over different subregions of China. Accordingly, we investigated this based on a set of high‐resolution dynamical downscaling simulations under different climate scenarios, and found that the higher emission scenarios reinforce the magnitude of the decline in solar energy and result in higher inter‐annual variability. These findings suggest an increased need for constraining emissions for the benefit of solar energy. In addition, we found that radiation will likely be the most important factor related to future changes in solar resources over most of subregions under RCP2.6 scenario, however the effect of wind speed should not be ignored over Tibetan Plateau. Key Points: Despite some overestimation, the spatial distribution and intra‐annual variation of solar radiation were captured well, showing added valuesFuture solar power were projected to generally increase in east and central China but decrease in solar‐energy‐abundant regionsRadiation was the most robust factor for future solar energy trend over China, however wind speed can not be ignored over Tibetan Plateau [ABSTRACT FROM AUTHOR]

The impact of soil freezing‐thawing processes on August rainfall in Southern China (SC) during 1979–2008 and related physical mechanisms are investigated using the coupled land‐atmosphere model Grid‐Point Atmospheric Model version 2.0—Community Land Model version 2.0 (GAMIL2.0‐CLM2.0). The moisture‐budget analysis is employed to quantify the contributions of different factors to the change of precipitation in SC. The results indicate that the vertical moisture advection and its dynamic component play an essential role in the long‐term trends of August rainfall. The possible physical mechanism is that the model which includes the supercooled water simulates much higher soil/air temperature in August, especially in the north of 40°N, which is not only weakened the meridional thermal contrast but also induced an anomaly "north high–south low" circulation pattern in the middle and high latitude of Eurasia. Both resulted in the 200 hPa zonal winds weakening, and 850 hpa northerly wind southward moved. Meanwhile, a convergence anomaly cyclone is initiated in the lower troposphere over SC regions, accompanied by enhanced ascending and strong moisture flux convergence, which is beneficial to the increased precipitation. This study provides a new interpretation of the "southern flooding" during 1979–2008 from the point of frozen soil changing. Key Points: The coupled land‐atmosphere model (Grid‐Point Atmospheric Model version 2.0‐Community Land Model version 2.0) with the consideration of supercooled water reproduces the trend of the August rainfall in Southern ChinaThe dynamic processes of the vertical moisture advection play a vital role in the long‐term trend of the August rainfallThe decreasing soil ice content has contributed to the wetter of Southern China in August over 1979–2008 [ABSTRACT FROM AUTHOR]

China supplied 4.1% of the global agro‐food exports in 2019, which is worth $65 billion in sales. The vulnerability of this sector to climatic factors has been growing with climate change that not only affects the costs of primary products but may also affect the costs of processing by reducing input productivity. Existing studies have examined the impacts of a changing climate on yields of major crops, but the sensitivity of the food processing sector to rising temperatures has not been assessed. Here we show, using a rich firm‐level data set of food processing firms and daily weather in China for the 1998–2007 period, that accounting profits of Chinese food processing firms exhibited non‐linear responses to temperature changes, peaking at a daily average temperature of 21–24°C and declining sharply at higher temperatures. Higher temperatures have wide‐ranging effects – raising final‐good inventory levels, hurting innovation activity, and reducing industrial output by decreasing TFP, investment in capital and capital stock, all of which caused the adverse impacts of higher temperatures on profits. If no additional adaptation is undertaken, the total profits and output of Chinese food processing firms are projected to decline annually by 15–25% and 14–22%, respectively, under RCP8.5 of the global climate models HadGEM2‐ES and NorESM1‐M by 2080. [ABSTRACT FROM AUTHOR]

This study presents an analysis of the changes in extreme temperatures over major river basins in China under different shared socioeconomic pathway (SSP) scenarios based on a set of dynamical downscaling over CORDEX East Asia, performed with the regional climate model RegCM4 at a resolution of 25 km, driven by the global climate model FGOALS‐g3. The results indicated that the dynamical downscaling tended to reduce the warm (cold) biases of the present‐day daily maximum (TXx) and minimum temperatures (TNn) simulated by FGOALS‐g3. Under the SSP scenarios, substantial increases in TXx and TNn and the number of warm days and warm nights throughout China were projected by both models. The average increase in TXx in most of the river basins ranged from 1 to 2°C under the SSP1‐2.6 scenario, from 2 to 3°C under the SSP2‐4.5 scenario, and from 3 to 5°C under the SSP5‐8.5 scenario. Reductions in the number of cold days and cold nights were projected across China, but these reductions were smaller than the increases in the number of warm days and warm nights. The interregional variability in the increases in TXx and TNn was more pronounced in the SSP5‐8.5 scenario and the RegCM4 model than in the other SSP scenarios and the FGOALS‐g3 model, respectively. Larger percentages of the land area and population of China would be affected by greater increases in extreme high temperatures and TNn. Under the SSP2‐4.5 (SSP1‐2.6) scenario, 20–65% (50–95%) of the impacts of extreme temperatures under the SSP5‐8.5 scenario could be avoided across most regions in China. The avoided impacts of warm days and warm nights were greater than those of the other extreme temperature indices. More of the impacts of extreme temperatures could be avoided in the Huai River basin, Yellow River basin, Hai River basin, and Northwest Interior River basin than in the other river basins in China. [ABSTRACT FROM AUTHOR]

The Cryogenian Period (717–635 Ma) experienced two low‐latitude "snowball Earth" glaciations, the Sturtian and the Marinoan of contrasting 57 and <16 Myr durations, respectively. A lack of reliable age controls on extensional tectonics and associated magmatic rocks during the Marinoan has hampered an understanding of the deglaciation. Furthermore, although deglaciation is generally assumed to have occurred once ongoing magmatism accumulated enough atmospheric CO2, as suggested by cap carbonates, specific geologic evidence linking volcanic events with deglaciation are lacking. Here, we present high‐precision zircon geochronology with chemical abrasion‐isotope‐dilution isotope ratio mass spectrometry that indicates an extensive and thick sequence of rift‐related magmatic rocks in South Qinling, Central China, erupted 2–6 Myr before the termination of the Marinoan. Climate modeling proposes a scenario explaining why the Marinoan was the shorter snowball and how volcanism may have driven the deglaciation. Plain Language Summary: Volcanic CO2 and dust emissions have been regarded as the major driver for Marinoan deglaciation. Most of CO2 outgassing is associated with seafloor spreading and subduction (arc magmatism), which are ongoing processes on geological timescales. To drastically increase CO2 emissions, there must have been many active rift zones during Marinoan glaciation. We provide age constraints on a previously little‐known major Marinoan rift‐related volcanic suite in South Qinling, which reveals volcanic activity lasting 4 Myr and ending 2 Myr before the termination of the Marinoan snowball Earth. Climate modeling provides constraints for the ice‐age duration deduced from the geological setting. Key Points: Volcanism is dated at 641–637 Ma using chemical abrasion‐isotope‐dilution isotope ratio mass spectrometry techniqueClimate modeling on the volcanism‐related CO2 emission is conductedEnhanced volcanic‐related dust and CO2 emission can shorten the Marinoan snowball Earth by 2–5 Myr [ABSTRACT FROM AUTHOR]

Previous studies show that volcanic eruptions can intensify and extend drought events triggered by internal variability over Eastern China. However, it has remained unclear whether volcanic eruptions occurring in different drought phases have different impacts. Here, based on multiple reconstructions, simulations, as well as volcanic sensitivity experiments with volcanic forcing imposed in the early and late phases of droughts, we propose a nonlinear effect of volcanic eruptions on drought events. Late‐phase volcanic eruptions exert greater impact on drought persistence and intensity while early‐phase volcanic eruptions induce modest and weaker impacts. The evolutions of drought differ substantially from the typical volcanic‐only influence or the linear combination of the drought triggered by internal variability and volcanic‐only influences, which are hypothesized to be associated with positive feedbacks of soil moisture to precipitation, as well as its interaction with the evolution of the East Asia Summer monsoon. Plain Language Summary: The effects of volcanic eruptions on precipitation changes are usually considered only on short timescales, however, recent studies have found that volcanic eruptions can influence decadal mega‐drought when superposed on drought events triggered by internal variability in the climate system (Ning et al., 2019; F. Chen et al., 2020). Our modeling and observational studies further show that the response of droughts to volcanic eruptions also depends significantly on the timing of the eruption. A volcanic eruption occurs in the late‐phase of a drought intensify the drought and extends the drought the most, and this impact decreases when the followed eruptions occur toward the early‐phase. These nonlinear responses may be explained by the nonlinear feedbacks of local soil moisture to precipitation and nonlinear changes of East Asia Summer Monsoon after volcanic eruptions. Key Points: Droughts over eastern China responds nonlinearly to volcanic eruptions at different phases of droughts induced by internal variabilityThis nonlinear response can be attributed to the nonlinear influences of volcanic eruptions on EASMThe positive feedbacks between local soil moisture and precipitation can also contribute to this nonlinear response [ABSTRACT FROM AUTHOR]

Bias‐corrected monthly precipitation and surface temperature datasets are constructed for the monsoon transitional zone (MTZ) in China during 1965–2100 based on 21 coupled climate models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) using the equi‐ratio and equidistant cumulative distribution function quantile‐based mapping methods (equi‐ratio cumulative distribution function [ERCDF] and equidistant cumulative distribution function [EDCDF]), respectively. The efficiencies of the two methods are verified via cross‐validation by the jack‐knife method, and the biases are remarkably reduced compared to those of the raw model outputs. Then, the bias‐corrected model outputs are applied to future projections of precipitation, surface temperatures and drought events under the medium (SSP2‐4.5) and high (SSP5‐8.5) shared socioeconomic pathway scenarios. The obtained results present pronounced increases in both the projected annual mean precipitation and temperature fields for the model ensemble mean. In accompany, the MTZ is predicted to become drier in the three future periods; this result was attributed to the dramatic increases in semiarid events and to the decreases in humid events. The drought tension showed more rapid development under SSP585 than under the other scenario, with comparable occurrence frequencies of relatively wet and dry events in the long‐term period, posing a serious threat to regional sustainable development. [ABSTRACT FROM AUTHOR]

Hindcasts during 1991–2010 are analysed to investigate the forecast skills for summer precipitation in northeast China (NEC) and circulations in northeast Asia with a leading time of 1‐month in three operational climate models and their equally weighted mean. It is found that the precipitation prediction ability of all the models and their combinations are much low in NEC. However, both the single model and their averages can well reproduce the basic summer circulation characteristics over Northeast Asia, especially the northeast China cold vortex (NECV) that directly affects precipitation in NEC. Observed precipitation is significantly correlated with the forecasted vorticities in each model and their combinations, particularly in the ensemble mean of the models (MME). Furthermore, the interannual variability of the NECV in MME agrees well with the observations. Linear regression between the simulated NECV and the precipitation in NEC is established for each model and their averages. The root‐mean‐square errors (RMSEs) of precipitation forecast from the regression of NECV are much lower than the direct outputs in above models, while the correlation coefficients (CCs) are much higher. The CC between observation and forecasts by the regression method based on the NECV in MME is the highest (0.5), closest to the value of 0.58 in observation, and the RMSE is the smallest (0.54), decreased by 13% compared with MME direct outputs. The cross‐validation during the 20 years can provide better prediction skills with a CC of 0.37, higher than that for the single‐model outputs, the averages of random two models and the MME. Independent forecasts also provide higher prediction skills than the official forecast of China Meteorological Administration in 4 years during 2013–2018, especially the extreme flood summer of 2013. The results indicate it might be a feasible approach to improve the prediction skill of summer precipitation in NEC. [ABSTRACT FROM AUTHOR]

A global model formulation for unified weather‐climate forecast is evaluated, with emphasis on the climate simulations at typical hydrostatic resolutions. The internal sensitivity is explored by considering different dynamical configurations (resolution, solver type, transport scheme). After a basic assessment of the global mean climate, a detailed analysis of precipitation characteristics is extended to East Asia. The model shows a reasonable mean state, seasonal variation, frequency–intensity structure, and diurnal phase time. The artificial rainfall around the steep slopes of the Tibetan Plateau can be improved through choices in the dynamical configuration. The regional features characterized by "afternoon versus nocturnal‐to‐early‐morning peaks" are properly distinguished. The hourly climatic features are comparable to super‐parameterized CAM5. Different dynamical configurations demonstrate unique sensitivities related to underling physical mechanisms, which are studied from the perspective of the diurnal cycle for three representative regions. Over South China, the higher‐resolution models decrease the weak‐precipitation while increase intense rainfall, thus reducing the dry biases. This is contributed by enhanced grid and sub‐grid scale motions associated with daytime convection progression. Over central western China, the variable‐resolution model better simulates the eastward propagating episodes characterized by a transition from convective to stratiform rainfall along the eastern slope of the Plateau. This reduces the positive biases at the high topography of the Plateau and alleviates the negative biases at the lower foot. Over central eastern China, the model replicates the dominant role of large‐scale governing factors in regulating the early morning rainfall peaks, and produces stratiform heating patterns. Plain Language Summary: We examine the statistical simulation of a model developed within the Global‐to‐Regional Integrated forecast SysTem, using Atmospheric Model Intercomparison Project style integration. This is among an effort in exploring a unified system for weather and climate modeling. Because of the evolutionary nature of model development, the absolute model performance can change. Thus, special attention is paid to the model sensitivity related to dynamical configurations, which helps to gain understanding that can support continuous research and development. Precipitation is one of the most important variables in a general circulation model as it encapsulates the synergistic effects of resolvable and non‐resolvable processes, the hydrological cycle, and radiative balance. Simulating precipitation faces the challenges in representing the moist physics and its interaction with dynamics. We use precipitation as performance metrics for a better understanding of the model behavior, focusing on a unique region–East Asia. The diurnal cycle is given particular emphasis because it reveals the direct physical mechanism of precipitation, and can help to disentangle the interactions between model dynamics and physics. We show that the models produce hourly rainfall features that are comparable to a global multiscale modeling framework that has two interactive dynamical solvers, and support some beneficial sensitivity. Key Points: To evaluate a model formulation for unified weather‐climate forecast using the Atmospheric Model Intercomparison Project‐style experimentTo understand model precipitation characteristics over East Asia by analyzing hourly scale apparent sources/sinks and grid‐scale tendenciesTo understand model sensitivity related to dynamical configurations, including grid resolution, moisture transport scheme and solver type [ABSTRACT FROM AUTHOR]

Climate change has affected the dynamics of the water cycle and its consequent effects on water resources in many regions. The Buyuan River, the largest tributary of the Upper Mekong River, is one of the regions with the strongest climate change in the Mekong River Basin, and its cross‐border impact on water resources has received increasing attention. However, few studies have focused on the runoff responses to future climate change in the Buyuan River Basin (BRB). In this study, the MIKE SHE model was applied to estimate the runoff of the BRB, based on climate‐change scenarios from the Beijing Climate Center Climate System Model (BCC‐CSM1‐1) under two Representative Concentration Pathways (RCPs). The simulations predicted a slight decrease in the mean annual runoff of the BRB under the RCP4.5 and RCP8.5 scenarios (2020–2049) compared with the reference period (1959–2012), with an increase in the magnitude of inter‐annual variation, leading to increased deficit and surplus during dry and wet years. The simulations predicted the earlier maximum monthly runoff and a more evenly distributed annual distribution of the runoff under RCP4.5 and RCP8.5 scenarios as compared to the reference period. The arrival of the flood season in the BRB was advanced by a month under future climate‐change scenarios. The results showed that the average annual runoff of the BRB does not change significantly under future climate‐change scenarios. However, there are obvious changes in the inter‐annual and intra‐annual distribution of the runoff. [ABSTRACT FROM AUTHOR]

Responses of summer precipitation in China to global 1.5°C warming with transient and stabilized pathways are investigated through the analysis of the Common Earth System Model climate simulations. Precipitation increases more significantly in southeast China in the stabilized scenario compared with the transient one. The difference is primarily attributable to dynamic factors related to circulation changes and driven by differences of land‐ocean thermal contrast between the two scenarios. The stabilized warming favors conditions of larger ocean warming and smaller land warming, leads to enhanced meridional temperature gradient and ultimately speeds up the jet stream over East Asia. Ageostrophic wind at the entrance of the accelerated jet strengthens ascending motion and precipitation along the coast of Asia from southeast China to India. The enhanced heating over India further induces a Kelvin‐wave response with an anomalous anticyclone that contributes to the enhanced westward shifted of the western North Pacific Subtropical High. Southerly winds at the west flank of the anticyclone transport moisture northward from tropical oceans, and strengthen precipitation in southeast China. Plain Language Summary: This study deals with the issue of regional precipitation response to 1.5°C global warming in accordance to the Paris Agreement on Climate Change for two different pathways, either transient or stabilized. Compared with the transient warming scenario, summer precipitation increases more significantly in southeast China in the stabilized one. This feature of distinctive precipitation responses, with strong implications for policy making in terms of regional climate mitigation and adaptation, is furthermore explored through a moisture budget analysis. Dynamic effect in relation to changes of atmospheric circulation is found to be the major contributor to the difference. The cause of the significant difference in precipitation in South China is attributed to changes of land‐ocean thermal contrast, leading to a series of atmospheric circulation adjustments. Results presented here satisfactorily addressed, for the first time, the long‐standing issue on global warming, namely, how the atmosphere responds distinctively under the transient and stabilized anthropogenic forcing pathways which show however an identical global warming level. Key Points: The summer precipitation increases more significantly in southeast China in the stabilized warming scenario compared with the transient oneThe dynamic effect in relation to changes of atmospheric circulation constitutes the major factor of distinctive precipitation responsesThe differential meridional thermal gradient related to a contrasted land‐ocean warming leads to dynamic changes [ABSTRACT FROM AUTHOR]

The arid and semi‐arid regions are highly vulnerable to climate change and variability. Agricultural production in these regions is particularly vulnerable because of its heavy dependence on climate conditions. Therefore, it is important to improve the projections of future agro‐climatic conditions. This study investigates the changes in agroclimatic conditions for growing Chinese Medicinal Yam (CMY) in the semi‐arid North China during 2031–2050 under the Representative Concentration Pathway (RCP) 4.5 and 8.5 emission scenarios. It employs high‐resolution climate data provided by the regional climate model (RCM) of Providing Regional Climates for Impacts Studies (PRECIS‐2.0). The changes in CMY yield and producing area under future climate change are simulated by the Agro‐Ecological Zone model. The simulations are based on newly calibrated cultivar parameters. The results show that the high‐resolution RCM simulation corresponds better with the observations of precipitation and temperature than the general circulation model (GCM). Because of the increased temperature and precipitation, the agroclimatic conditions for CMY are going to improve. While the traditional yam production area will maintain suitable for CMY production, the CMY production areas will further expand northward in the future. The average yield will increase by 1,196 and 1,336 kg DM/ha under RCP 4.5 and 8.5 emission scenarios, respectively. Key Points: Improving the projections of future agro‐climatic conditions in the semi‐arid North ChinaThe high‐resolution Providing Regional Climates for Impacts Studies projections correspond better with the observationsThe Chinese Medicinal Yam production areas will expand northward in the future, the average yield will increase by 1196–1336 kg DM/ha in the future [ABSTRACT FROM AUTHOR]

Projections of future drought conditions under climate change are an important step in formulating the long‐term climate adaptation strategies. It is therefore valuable to predict the drought conditions in China following the release of the CMIP6 (the phase six of the Coupled Model Inter‐comparison Project). Thus, based on 20 global climate model simulations from CMIP6, we project China's drought conditions and its socioeconomic impacts using the self‐calibrated Palmer Drought Severity Index (scPDSI). Four scenarios are considered in this analysis: SSP1‐2.6 (the low‐level development scenario), SSP2‐4.5 (the middle‐level development scenario), SSP3‐7.0 (the medium to high‐level development scenario) and SSP5‐8.5 (the high‐level development scenario). Under SSP1‐2.6, we observed wetting trends over large areas of China except the arid region during 2020–2099; however, under SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5, significant drying trends are detected in the humid and temperate semi‐humid region, while in other areas there are significant wetting trends. The projected drought conditions are likely to be severe with more frequent monthly occurrences and higher probability of extreme drying conditions, especially in these humid and temperate semi‐humid regions under SSP3‐7.0 and SSP5‐8.5. Consequently, the population exposure to drought in most climatic regions will increase initially up to 2040s and gradually decrease under all the scenarios except SSP3‐7.0; and the humid region will be a future hotspot where the impact of climate on population exposure to drought will be more significant. The economic exposure to drought will increase over the whole China under all four scenarios, especially in the humid and semi‐humid region. Our results have important implications for future drought projections and provide a scientific evidence for developing climate change adaptation strategies and disaster prevention. [ABSTRACT FROM AUTHOR]

Using the dynamical downscaling by the regional climate model RegCM4 from four global climate models, future changes in heat waves (HWs) over China under the RCP4.5 scenario are projected in terms of frequency and magnitude. The magnitude combines the duration and intensity together to characterize HW severity. The ensemble of RegCM4 downscaling simulations indicates a substantial increase in the frequency and magnitude of HWs over China toward the end of the 21st century relative to the current climate (1986–2005). The considerable changes occur in Southwest, South, North, and Northeast China for the frequency and in South, Southwest, East, and Central China for the magnitude. The prolonged HW duration plays a leading role in the enhancement of HW severity. In particular, an accelerated aggravation of the risk of extreme HWs is anticipated. Unusual HWs that never occurred in the current climate are expected to be usual phenomenon. For instance, by the end of the 21st century, the risks of the occurrence of extreme HWs (above the 99th percentile) in Southwest and South China are 64 and 53 times of the current, respectively, while the projected risks of the occurrence of mild HWs (below the 60th percentile) are much smaller and comparable in China. The HW frequency above the maximum of the current would appear once almost every year, and South, Central, and East China (North and Northeast China) would experience more severe HWs than the most extreme of the present every 1–2 (2–4) years. [ABSTRACT FROM AUTHOR]

The traditional paleoclimatological view suggests that monsoonal China was overall wetter when the East Asian summer monsoon (EASM) was strong. However, this view is at odds with the understanding of modern climate, which demonstrates an analogous "tripole precipitation pattern" in monsoonal China. Little is known about the spatial pattern of paleo‐precipitation in monsoonal China, particularly during the past glacial‐interglacial cycles. Here, we provide evidence for a potential tripole precipitation pattern in monsoonal China over the past 425 ka using climate modeling, and compare the results with paleoclimate records available from China. Our simulations illustrate that more (less) precipitation in North China and South China, and less (more) precipitation in the Central‐East China during strong (weak) EASM periods associated with high (low) boreal summer insolation. Our results agree with the present understanding of modern East Asian climate, and furthermore confirm that the boreal summer insolation is the dominant forcing for the intensity of EASM and the response of subtropical high pressures is fundamental in modulating the precipitation pattern in monsoonal China on orbital timescales. This temporal and spatial variability of precipitation, as revealed in our simulations, shows the potential high complexities in hydroclimatic conditions in monsoonal China throughout the past glacial‐interglacial cycles. Nevertheless, whether the tripole precipitation pattern in monsoonal China over the past 425 ka is robust enough still should be tested, preferable by taking advantage of existing and new well‐dated and explicit indicative precipitation archives in Central‐East China. Key Points: Our simulations suggest that the tripolar precipitation pattern in monsoonal China likely occurs on orbital timescalesThe boreal summer insolation is the dominant forcing for the intensity of East Asian summer monsoon on orbital time scalesThis study emphasizes the high complexities in hydroclimatic conditions in monsoonal China throughout the past glacial‐interglacial cycles [ABSTRACT FROM AUTHOR]

Based on hourly temperature data collected from 2,307 meteorological stations over China and two sets of climate change simulations over East Asia using the regional climate model version 4.4 (RegCM4.4) driven by the global models of HadGEM2‐ES and MPI‐ESM‐MR, future changes of heating and cooling degree‐hours (HDH and CDH) at the end of the 21st century under RCP4.5 scenario are investigated. Compared against the observation, the spatial distribution, magnitude and annual cycle of present‐day HDH and CDH at different times, as well as the diurnal cycle of them can be realistically simulated by the model. Meanwhile, some bias can also be found and it varies with the times, especially for CDH. At the end of the century, significant decrease of HDH can be found over the Tibetan Plateau, the northern part of Northeast China, and Northwest China at each times while increase of CDH are observed at all the times except some parts of the Tibetan Plateau where the CDH remains zero due to the cold climate there. But for different times, some differences are found in HDH decrease and CDH increase. For example, the changes of HDH at the fifth to the seventh times present a weaker decrease in the northwestern basins compared to other times and the CDH increase are more significant at the fifth and the sixth times. The regional mean changes of HDH and CDH over China in the 21st century (2006–2098) also diverge among different times, which indicates the degree‐hours is needed to precisely calculate the hourly heating and cooling energy demand and then the heating and cooling degree days. [ABSTRACT FROM AUTHOR]

South‐East China usually experiences mild winter temperatures but can also be impacted by large‐scale and long‐lasting cold events. Here, we investigate how this category of events has changed during the past 6 decades and why, using both observation and climate model ensembles. We first show that models can reproduce the observed largescale dynamics associated with cold events. A dynamical advection of cold air is mostly responsible not only to trigger cold surges but also we found strong feedback from shortwave radiation, decreasing due to enhanced cloud cover. Recent trends are more difficult to evaluate. Models show a large internal variability and intermodel spread, while observation also indicates large uncertainties in its trend due to high internal variability. Our analysis indicates that even if cold events are likely to have been reduced due to greenhouse gases, trends cannot be attributed with high confidence to any anthropogenic signal alone. However, in the next few decades, the frequency of long‐lasting cold events are expected to quickly reduce due to the emerging greenhouse gases signal and possibly weakening aerosol effect over South‐East China. We also found that most of the trends are due to the change in the mean temperature. Thus, indirectly, there is no clear evidence that the change in cold event frequency is due to a change in the circulation. Key Points: Change in the frequency of cold waves over South‐East China during the past decades is not detectable yetCMIP5 and CMIP6 models can reproduce the observed dynamics of these eventsCold waves are expected to decrease due to the dominant impact of greenhouse gases in the next decades [ABSTRACT FROM AUTHOR]

Measurement‐model comparisons for various atmospheric species have been widely used for evaluating the reliability of model simulations, yet such comparisons are quite limited for atmospheric isoprene due to the lack of systematic observations over a large scale. Here, we collected ambient air samples concurrently at 20 sites in China during 2012–2014 and compared the observed isoprene mixing ratios with those simulated by coupling MEGAN v2.1 with the 3‐D Regional chEmical trAnsport Model. The observed average isoprene concentration for all 1,731 samples is 0.35 ± 0.03 ppbv, 13% higher than the model simulated average of 0.31 ± 0.02 ppbv; while during the growing season, the simulated average (0.53 ± 0.05 ppbv) is almost the same as the observed average (0.52 ± 0.04 ppbv). The observed isoprene average level in the north (0.35 ppbv) is similar to that in the south (0.37 ppbv). However, the model simulated average in the south (0.53 ppbv) is ∼4 times that in the north (0.14 ppbv). The model overestimated the observations at most southern sites but underestimated at most northern sites in the growing season, which might be resulted from inadequate characterization of isoprene‐emitting land vegetation with fast afforestation in the north and rapid urbanization in the south. Compared to the model simulation, the observations revealed abnormally high isoprene levels in winter at some northern sites, largely due to nonbiogenic emissions, as evidenced by the enhancements of measured combustion tracers concurrent with the abnormally elevated isoprene levels. Plain Language Summary: Isoprene alone accounts for approximately one‐third of global emission of volatile organic compounds from both nature and human activities, yet in many parts of the world biogenic isoprene emission estimates have large uncertainties (reported isoprene emission estimates span 4–29 TgC y−1 in China), and narrowing these uncertainties is a challenging task. Here we collected ambient air samples concurrently at 20 sites over China during 2012–2014, and made measurement‐model comparison to check the emission estimates for isoprene, and found that although overall observed and predicted average isoprene levels matched well particularly during growing seasons, there exists a south‐north discrepancy that model simulated averages in the south were much higher than the north while their observed averages were quite near each other. Modeled values overestimated at most southern sites but underestimated at most northern sites, probably the fast afforestation in the north and rapid urbanization in the southeast were inadequately characterized in the model. Abnormally higher isoprene levels were observed in winter at some northern sites probably due to contribution from nonbiogenic sources. Our results highlight that high‐resolution PFT/LAI, field campaigns with higher spatial and temporal resolutions, as well as biomass burning activity data, are necessary for better observation‐model comparison. Key Points: Ambient isoprene mixing ratios observed at 20 sites across China during 2012–2014 are compared with the MEGAN‐REAM model simulationThe model simulated averages in the south were much higher than those in north, while the observed averages were much more similarAbnormally high isoprene levels were observed in winter at some northern sites probably due to contributions from nonbiogenic sources [ABSTRACT FROM AUTHOR]

In early summer 2020, the Meiyu‐Baiu rainfall was markedly enhanced, triggering devastating floods in Japan and central China. We examined the underlying processes using a climate model and analysis. The enhanced Meiyu‐Baiu rainfall was reasonably predicted by the climate model initialized at the end of April. The sensitivity experiment indicated that Indian Ocean (IO) warming enhanced the Meiyu‐Baiu rainfall. Moreover, we found that the warm IO condition can be traced back to the super Indian Ocean Dipole (IOD) in 2019. The IO warmth was influenced by successive processes: record strong downwelling Rossby waves excited by the IOD and tripole sea surface temperature anomalies in the tropical IO‐western Pacific, their arrival to the southwestern IO in spring, and associated modulation of monsoon flow. The results suggest that the seasonal predictability of the Meiyu‐Baiu rainfall in 2020 originated from the super IOD. Plain Language Summary: In early summer 2020, Japan and central China suffered from serious floods due to torrential rainfall associated with the intensified Meiyu‐Baiu front, which extends from central China to southern Japan. The results of climate model simulations indicated that a warm condition of the Indian Ocean (IO) was an underlying condition for the enhanced rainfall. We found that the warm IO condition can be traced back to the strong Indian Ocean Dipole (IOD) episode in 2019, which featured a pair of colder‐than‐normal and warmer‐than‐normal ocean temperatures west of the Sumatra coast and in the western IO, respectively. This IOD contributed to the IO warming in the following seasons through oceanic dynamics and monsoon modulation. Key Points: The markedly enhanced rainfall in the Meiyu‐Baiu frontal zone in early summer 2020 was associated with the warm IO conditionThe warm IO condition can be traced back to the super IOD event in 2019Ocean dynamics and associated modulation of monsoon flow in the IO sector facilitated IO warming [ABSTRACT FROM AUTHOR]

We implemented a subgrid terrain radiative forcing (STRF) scheme into the International Centre for Theoretical Physics, Italy, Regional Climate Model Version 4.1 (RegCM4.1) and evaluated its impacts on the summer precipitation simulation over China by comparing the model results from the experiments with and without the STRF scheme. The RegCM4.1 without the STRF scheme simulates strong East Asian summer monsoon and overestimates the summer precipitation over China. Adopting the STRF scheme in the RegCM4.1 improves the representation of surface radiation process over complex terrains, by reducing the net gain of the surface radiation energy over the Tibetan Plateau (TP). As a result, the heat released from the surface to the overlying air column decreases, thus suppressing the development of local convection over the TP. In addition, the weakened TP thermal forcing due to the STRF effect reduces the land‐sea thermal contrast, resulting in a weakened East Asian summer monsoon that produces less transport of water vapor from tropical oceans and hence weakens summer precipitation over China. Our analysis indicates that such improvement in the precipitation simulation induced by the STRF effect is mainly due to the improved simulation of precipitation intensity, particularly that associated with the moderate and heavy precipitation events, and convective processes. Key Points: A subgrid terrain radiative forcing (STRF) scheme was developedRegCM4.1 model with considering the STRF effect improved the summer precipitation simulation over China [ABSTRACT FROM AUTHOR]