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Weighting models according to their performance has been used to produce multimodel climate change projections. But the added value of model weighting for future projection is not always examined. Here we apply an imperfect model framework to evaluate the added value of model weighting in projecting summer temperature changes over China. Members of large-ensemble simulations by three climate models of different climate sensitivities are used as pseudo-observations for the past and the future. Performance of the models participating in the phase 6 of the Coupled Model Intercomparison Project (CMIP6) are evaluated against the pseudo-observations based on simulated historical climatology and trends in global, regional, and local temperatures to determine the model weights for future projection. The weighted projections are then compared with the pseudo-observations in the future period. We find that regional trend as a metric of model performance yields generally better skill for future projection, while past climatology as performance metric does not lead to a significant improvement to projection. Trend at the grid-box scale is also not a good performance indicator as small-scale trend is highly uncertain. For the model weighting to be effective, the metric for evaluating the model's performance must be relatable to future changes, with the response signal separable from internal variability. Projected summer warming based on model weighting is similar to that of unweighted projection but the 5th–95th-percentile uncertainty range of the weighted projection is 38% smaller with the reduction mainly in the upper bound, with the largest reduction appearing in southeast China. [ABSTRACT FROM AUTHOR]

In China, the topography, climate, ecology, hydrology, and human environment vary greatly from southeast to northwest, and a typical natural and social environmental transition zone (i.e., comprehensive transition zone) exists near the "Hu Huanyong line," which is a famous demographic dividing line in China, known as the Hu zone. Dry and wet climate changes in the Hu zone can have a significant impact on terrestrial ecosystems and hydrological conditions, ultimately affecting human–land relations. However, there is still a lack of clear understanding of environmental changes in the context of climate change in the Hu zone. Here, a quantitative analysis of climate change and its impacts on terrestrial hydrology and ecosystems from 1951 to 2020 is presented. The results showed that there exists a significant drying trend in the Hu zone and a dramatic decrease in terrestrial water storage (TWS), indicating that the environment has become worse. Conversely, from the perspective of significant greening, the environment has improved. This contradiction is mainly due to climate change dominating the depletion of TWS, while the increase in vegetation greenness is more driven by human activities including agricultural management and ecological restoration, offsetting to some extent the negative impact of water scarcity on vegetation growth. Significance Statement: The Hu zone is a transition zone between southeast and northwest China, which is a sensitive area under climate change as well as key region for coordinated development. The purpose of this study is to reveal the long-term climate change in the Hu zone and its impacts on hydrology and ecology. Our results indicate a significant drying trend in this zone over the last 70 years, which led to a substantial reduction in water storage. However, the vegetation coverage increased due to human activities. This study provides guidance for agricultural structure adjustment and ecological protection in transition zones. Future research should focus more on the assessment and risk management of dry/wet changes in climate transition areas around the world. [ABSTRACT FROM AUTHOR]

Observations and model simulations have confirmed that the higher percentiles of precipitation intensity of all wet days have increased with the local daily dewpoint temperature at the Clausius–Clapeyron (C-C) rate of 7% °C−1 using the binning technique over China. It is uncertain whether the binning scaling rates will remain constant in the future climate. Here, we use daily precipitation and dewpoint temperature (DPT) over China from 20 CMIP6 models to examine and project the change of binning scaling of precipitation extremes. The results of the study suggest that the multimodel ensemble median (MEM) generally captures the spatial distribution of binning scaling rates and binning curves in different climate zones across China. The binning scaling rates have stability in the future but with a large increasing trend (more than 30%) in southeast China in the far future (2061–2100) under the SSP5-8.5 scenario. CMIP6 models project that both the peak of extreme precipitation and the temperature for the plateau mountain zone will increase in the far future under the SSP5-8.5 scenario, implying that the peak structure does not provide an upper limit for future precipitation extremes. Significance Statement: The binning scaling rates describe the relationship between precipitation extremes and temperature based on their day-to-day variations. However, it is still unclear whether the binning scaling rates of daily precipitation extremes with daily temperature will change in the future. We use 20 CMIP6 models to project the scaling rates of precipitation extremes with dewpoint temperature over China in the future. The results show that the sensitivity of precipitation extremes to dewpoint temperature will generally be stable, except that southeast China shows an increasing trend of up to 30%. Moreover, the peak of extreme precipitation and the temperature will increase with warming in the plateau mountain zone. Our results have implications for precipitation prediction and risk assessment. [ABSTRACT FROM AUTHOR]

This study examines the changes in the outer size distribution of landfalling tropical cyclones (TCs) over the Chinese mainland from 1977 to 2020. The period was divided into two epochs: 1977–98 and 1999–2020. The results show that the size distribution of landfalling TCs over South China has no apparent change, while that of landfalling TCs over East China (LTCEC) is narrower in the second epoch, and the difference in the median sizes between East China and South China become more significant. Furthermore, it is found that LTCEC formed over the western part of the western North Pacific (W-WNP) shifted to a larger size range (300–500 km) at landfall, while those formed over the eastern part of the western North Pacific (E-WNP) rarely grew to extremely large size (>500 km). Further investigation revealed that over the W-WNP, the genesis position of LTCEC migrated equatorward during the second epoch, leading to a longer TC lifetime before landfall. Also, the increase of background relative vorticity and moisture associated with the southward migration is conducive to larger initial vortices. For TCs originating from the E-WNP, the change in the active area of TC passages reduced the frequency of TCs affecting the Chinese coast. Moreover, the growth of TC size during the intensification stage was significantly suppressed, lowering the occurrence probability of extremely large TCs. Changes in the large-scale thermodynamic environments between the two epochs were explored. Increased static stability and decreased convective available potential energy are possible factors limiting TC size increase. [ABSTRACT FROM AUTHOR]

Anthropogenic greenhouse gases (GHG) and anthropogenic aerosols (AA) have changed radiation balance and regulated the regional climate at seasonal or longer time scales. Based on station observations, reanalyses, and satellite observations, this study examines how anthropogenic forcings affect surface temperature and strongly regulate the regional climate at a diurnal time scale over the North China plains (NCP) in July and August. As AA cooling is dominant in the daytime over low-lying plains, it leads to a cooler day-warmer night temperature trend that decreases the diurnal temperature range over NCP but increases the thermal contrast between NCP and its west highlands. In response to the daytime cooling, the weakened vertical thermal contrast decreases the boundary layer turbulent mixing in the daytime and reduces friction to low-level winds, which leads to anomalous southerlies at 2000 LST over NCP. In contrast, nighttime warming results in anomalous northerlies at 0200 LST. On the other hand, in response to the enlarged horizontal thermal contrast, the stronger mountain-plain circulation helps to intensify low-level ascent over the plains at 0200 LST. These human-induced changes in the diurnal variation of regional circulations are conducive to the increased moisture convergence at 2000 and 0200 LST over NCP. The nighttime proportion of precipitation accordingly exhibits an increasing trend over NCP, though the seasonal precipitation decreases because of the weakened monsoon background. These findings highlight that the diurnal cycle of regional circulations can express a strong dynamic response to the radiation effect of anthropogenic forcings and thus affect the long-term change in regional climate. [ABSTRACT FROM AUTHOR]

The frequency of large-scale anomalous precipitation events over China has increased during 1961–2018. However, it remains challenging to understand the mechanisms associated with these anomalous events showing different spatial patterns. Here, we applied an autoencoder technique to identify large-scale anomalous precipitation events for both observations and model simulations, which were then classified into several patterns through a self-organizing map method. The synoptic behavior and atmospheric circulation background of different anomalous patterns were also analyzed using simultaneous composite analyses. Results show that occurrences of different anomalous precipitation patterns have increased significantly, except those centered in North China, Northeast China, and the Yangtze River basin. The anomalous precipitation patterns manifest various intraseasonal distributions, which are linked to zonal oscillations of the western North Pacific subtropical high (WNPSH) and meridional displacements of East Asia westerly jet (EAJ). Accompanied by the westward movement of WNPSH, anticyclonic systems transport warm moist air from the Indian Ocean and the South China Sea to converge with the cold air caused by anomalous cyclones over the northwest flank of the WNPSH, leading to large-scale anomalous precipitation in these regions. Besides WNPSH, the northward and southward displacements of EAJ also favor the occurrence of anomalous precipitation events in northern and southern China, respectively. Our study also illustrates that the occurrence frequency of anomalous precipitation events is projected to increase remarkably under the Shared Socioeconomic Pathway 5–8.5 (SSP585) scenario by rates of twofold to fourfold. [ABSTRACT FROM AUTHOR]

Using the multimodel simulations from phase 6 of the Coupled Model Intercomparison Project (CMIP6), we investigate the aridity changes in China and the associated mechanisms during the three geological periods of the Last Interglacial (LIG), Last Glacial Maximum (LGM), and mid-Holocene (MH), as well as the three future scenarios of the shared socioeconomic pathways of SSP1-2.6, SSP2-4.5, and SSP5-8.5. The aridity index is used to measure terrestrial moisture, which combines the effects of both precipitation and potential evapotranspiration (PET), with the latter representing the amount of water consumed by the atmosphere. The results show that relative to the preindustrial period, the total dryland area in China varies by −15%, 6%, and −13% during the LIG, LGM, and MH, respectively, and slightly varies in the three future scenarios. Over China, LGM dryland expansion and future dryland contraction are mainly attributed to precipitation changes, MH dryland contraction is mainly caused by PET changes, and LIG dryland contraction is comparably caused by PET and precipitation changes. For the LGM and three future scenarios, temperature is the leading factor of PET changes, while during the MH and LIG, the change in relative humidity is the main factor. In comparison, the simulated aridity changes in China are generally consistent with the reconstructed moisture changes for the three past periods, although uncertainties exist in reconstructions during the LGM and MH. [ABSTRACT FROM AUTHOR]

The East Asian summer monsoon (EASM) and associated summer precipitation patterns over eastern China have exhibited interannual and interdecadal variations in recent decades, but whether the precipitation modes vary with climate conditions remains unclear. In this study, we investigate the changes in summer precipitation modes over eastern China and associated mechanisms in simulated past and future warm periods, namely, the last interglacial (LIG), mid-Holocene, and the twenty-first century under the Shared Socioeconomic Pathway (SSP) based on representative concentration pathway 8.5 (SSP5–8.5) scenario, using Coupled Model Intercomparison Project Phase 6 (CMIP6) models. The model evaluation indicates that only one out of nine CMIP6 models, specifically the Community Earth System Model, version 2 (CESM2), can well reproduce the observed summer precipitation modes at the present. The empirical orthogonal function (EOF) analyses of the CESM2 simulations reveal that during the warm periods induced by either orbital parameters or greenhouse gas concentrations, the first leading mode of summer precipitation switches from its present meridional tripolar structure to a dipole pattern, and the second leading mode is generally a meridional tripolar mode that differs from the present dipole pattern. This summer precipitation regime interchange in the warm intervals is associated with the formation of the dipole and tripolar circulation patterns. The large-scale circulation changes responsible for the altered precipitation modes are attributed to the enhanced EASM and relevant southerly winds due to intensified land–sea thermal contrast, although the external forcings and the magnitude of EASM enhancement are different in the interglacial and future periods. [ABSTRACT FROM AUTHOR]

Human influence on regional warming since 1901 has received little attention because of limited data during the early period. This study investigates the relative contribution of different external forcings to observed annual, summer, and winter warming in China over the period 1901–2018. First, four observational datasets were compared to validate data representativeness, particularly during the early twentieth century. Observed temperature changes were then compared with outputs from phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6) based on an optimal fingerprinting method. Generally, both generations of climate models were able to reliably reproduce long-term warming in China over the period 1901–2018; however, they slightly underestimate the amplitude of annual and winter temperature increases. The observed annual warming of 1.54°C from 1901 to 2018 was more rapid than the global mean and was mostly attributable to the anthropogenic forcing signal. The three-signal detection analyses, including greenhouse gas (GHG), anthropogenic aerosol (AA), and natural external (NAT) forcings, indicated the detectable and distinct influence of GHG and AA signals on annual, summer, and winter temperatures during 1901–2018. For annual mean temperature, the GHG and AA contributed to 2.06°C (from 1.58° to 2.54°C) and −0.45°C (from −0.17° to −0.73°C) of observed change, respectively. The GHG signal was detectable from individual CMIP6 models and thus was indicative of the robustness of this influence. While during 1951–2018, GHG and AA were simultaneously detected in the summer temperatures based on the CMIP6 models; here, the AA cooling effects offset approximately 25% of GHG-induced warming. [ABSTRACT FROM AUTHOR]

Future changes in spatiotemporal features of the mean wind speed over China have been extensively reported, but future changes in the maximum wind speed, such as the daily maximum wind speed (DMWS), were rarely estimated. In this study, the performance of Coupled Model Intercomparison Project phase 6 (CMIP6) models in simulating the DMWS changes across China is evaluated, based on which the projection on DMWS is carried out under different shared socioeconomic pathways (SSPs). The observed DMWS shows a significant reduction during all four seasons, with the strongest decrease in spring and the weakest decrease in autumn. The DMWS increases from January to April and decreases from April to August. The spatiotemporal characteristics of the DMWS are captured by the multimodel ensemble of CMIP6; however, the reduction of DMWS in CMIP6 is weaker than those in observations. The performance of CMIP6 in simulating the future DMWS changes over China shows regional and seasonal discrepancies. The projected DMWS exhibits a reduction for all SSPs from 2021 to 2100, and the decreasing trend is increased accompanied by the strength in the forcing scenario. The lower-emission scenario likely avoids the long-term weakening of the DMWS. The effects of strength in forcing scenarios on the trends of DMWS are more significant than the DMWS climate state. The seasonal cycle of the projected DMWS under the different SSPs is consistent with the historical DMWS; however, the strength in the forcing scenario could induce enhanced variability in the month-to-month DMWS difference. [ABSTRACT FROM AUTHOR]

Heavy precipitation (HP) events can be preceded by moist heatwaves (HWs; i.e., hot and humid weather), and both can be intensified by urbanization. However, the effect of moist HWs on increasing urban HP remains unknown. Based on statistical analyses of daily weather observations and ERA5 reanalysis data, we herein investigate the effect of moist HWs on urban-intensified HP by dividing summer HP events into NoHW- and HW-preceded events in the Yangtze River delta (YRD) urban agglomeration of China. During the period 1961–2019, the YRD has experienced more frequent, longer-lasting, and stronger intense HP events in the summer season (i.e., June–August), and urbanization has contributed to these increases (by 22.66%–37.50%). In contrast, urban effects on HP are almost absent if we remove HW-preceded HP events from all HP events. Our results show that urbanization-induced increases in HP are associated with, and magnified by, moist HWs in urban areas of the YRD region. Moist HWs are conducive to an unstable atmosphere and stormy weather, and they also enhance urban heat island intensity, driving increases in HP over urban areas. Significance Statement: The contribution of urbanization to increases in heavy precipitation has been widely reported in previous studies. HP events can be preceded by moist heatwaves (hot and humid extremes); however, it is unknown whether moist HWs enhance urban effects on HP. We choose the Yangtze River delta urban agglomeration to explore this question and find that urbanization contributes to the increasing frequency, duration, maximum intensity, and cumulative intensity of HP events in the summer season. However, this urban signal is not detectable if we remove HW-preceded events from all HP events. In other words, moist HWs play a key role in magnifying urbanization-induced increases in HP. Given that urban areas are projected to continue expanding and moist HWs are projected to occur with increasing frequency and intensity in the future, the role of HWs in the urban water cycle merits further investigation. [ABSTRACT FROM AUTHOR]

Tropical cyclone (TC) translation distance, proportional to its duration and translation speed, basically determines the spatial extent of TC-impacted marine and terrestrial areas. Although a long-term slowdown of TCs has recently been reported, changes in translation distance of TCs over the western North Pacific (WNP) and their driving mechanisms remain poorly understood. Using multiple TC datasets, here we find that the trends are opposite in overland translation distance of landfall WNP TCs over China and excluding China, with the number of landfalls in the two groups being almost the same. However, the increase in overland translation distance of landfall TCs over China is offset by a greater decrease in that excluding China, with the result that the overland translation distance of TCs over the WNP has declined (−4.0% decade−1). The oversea translation distance of TCs over the WNP also shows a decreasing trend (−2.4% decade−1), and thus the genesis-to-demise translation distance of TCs over the WNP has significantly decreased (by 17.7%) during 1961–2019. The shorter duration and reduced translation speed of TCs directly and jointly contribute (by 76.9% and 23.1%, respectively) to their shortened translation distance. The gradual increase in westerly and northerly winds and weaker moisture transport during the days following TC generation tend to inhibit long-distance travel after TC genesis. Declining TC translation distance is likely associated with the long-term increases in genesis potential index and an anomalous cyclonic steering flow over the WNP. Our findings suggest that these changes in TC translation distance may alter regional patterns of TC-related drying and wetting of the WNP. Significance Statement: The spatial extent affected by a tropical cyclone (TC) is largely determined by TC translation distance. For example, TCs passing through marine areas could cool sea surface temperature and modulate local air–sea heat fluxes exchange; TCs with longer translation distances over land are more likely to trigger widespread flooding or terminate droughts in inland areas. Over the western North Pacific (WNP), we find that observational evidence supports opposite trends in overland translation distance of landfall TCs over China and excluding China. Nevertheless, the genesis-to-demise translation distance of TCs shows a significant decline over the WNP during the past six decades. Understanding the impacts of changes in TC translation distance has particular importance given the extensive footprint of TC-related drying and wetting of the marine and terrestrial areas. [ABSTRACT FROM AUTHOR]

The diurnal temperature range (DTR) as measured by the difference between daily maximum (Tmax) and minimum (Tmin) temperatures is of great importance to human health, ecology, and agriculture. The link of its long-term change to anthropogenic forcing is still unclear. This study shows evidence of human influence on long-term changes in DTR over the globe, five continents, and China during the past century (1901–2014). Using multiple observational datasets, we find a general decrease in the DTR over most of the global land since 1901, especially after the mid-1950s. Changes in DTR are due to different warming rates of Tmax and Tmin in response to external forcings. The climate models that participated in phase 6 of the Coupled Model Intercomparison Project Phase 6 (CMIP6) generally reproduce most of the changes in DTR, along with those in Tmax and Tmin. The models have underestimated the observed changes in DTR, however. A formal detection and attribution analysis shows that the anthropogenic forcing signal, including both greenhouse gas and aerosol emissions but dominated by the greenhouse gas emissions, is the main driver for these changes. The anthropogenic aerosol signal can be detected in Tmax and Tmin but not in DTR during the period of 1901–2014 over the globe and most continents. These indicate the observed decrease in DTR is not a simple response to anthropogenic aerosol emission. The natural signal is negligible in almost all the cases. Globally, anthropogenic influence is estimated to explain more than 90% of the observed changes in the three variables. In China, human influence is also clearly detected, although model simulated results on the regional scale have larger deviation. Significance Statement: The diurnal temperature range (DTR) is of great importance in many areas. We compare multiple observational datasets with the simulations by climate models that participated in the latest phase (phase 6) of the Coupled Model Intercomparison Project (CMIP6), finding evidence of human influence on long-term changes in DTR over the past century (1901–2014) and robust evidence for the period since the early 1950s. The decrease in DTR as seen in the observational dataset is caused by different warming rates of daily maximum and daily minimum temperature in response to anthropogenic forcing, including both greenhouse gases and aerosols. [ABSTRACT FROM AUTHOR]

This study analyzes the spatiotemporal distributions and climate trends of tropical cyclone (TC)-induced extreme hourly precipitation (EXHP) in the warm season (May–September) during 1975–2018 over China and the involved mechanisms. Each TC is classified as a high-, mid-, and low-EXHP TC according to the total amount of EXHP it produces over China during its lifetime. Results show that low-EXHP TCs have a greater contribution to the total TC-induced EXHP over southern and southwestern China, whereas high-EXHP TCs make greater contributions over eastern and northeastern China as they tend to move northwestward after making landfall. It is shown that, although the total frequency of EXHP-producing TCs displays a decreasing trend, the total frequency of TC-induced EXHP over China shows a significant increasing trend, which is largely contributed by the high-EXHP TCs. To explore the possible mechanisms responsible for the different characteristics in EXHP-producing TC groups, we further analyze the large-scale environmental conditions with respect to three groups by composite analysis. The cooperation of large-scale environmental fields between high and low levels provides favorable conditions for the intensification of TCs and the enhancement of the TC-induced precipitation for the high-EXHP group, such as stronger divergence at high levels, weaker vertical wind shear, more sufficient water vapor, and more conducive steering airflow over the southeastern and eastern area of mainland China. The westward and northward movement of western North Pacific subtropical high is conducive to the northward shift of TC tracks, thus contributing to the high frequency of TC-induced EXHP over the eastern area of mainland China. [ABSTRACT FROM AUTHOR]

Climate change can lead to variations in the probability distribution of precipitation. In this study, quantile regression (QR) is undertaken to identify the quantile trends in precipitation over China and to examine the quantile effects of various climate oscillations on precipitation. The results show that the quantile trends show apparent seasonal variations, with a greater number of stations showing trends in winter (especially at quantile levels ≥ 0.5), and larger average magnitudes of trends at nearly all quantile levels in summer. The effects of El Niño–Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), and Pacific decadal oscillation (PDO) exhibit evident variations with respect to the quantile level. Spatial clusters are subsequently identified based on the quantile trends, and the individual and combined effects from the teleconnection patterns are further investigated from the perspective of moisture budget. Seven spatial clusters with distinct seasonal quantile trends can be identified; three of them are located in southeastern China and are characterized by increasing trends in summer and winter precipitation. Summer precipitation over this region is positively influenced by ENSO and negatively influenced by NAO, with the former affecting both the dynamic and thermodynamic components of vertically integrated moisture divergence and the latter affecting only the dynamic component. The interaction effect of ENSO and NAO on summer precipitation anomalies in months that are extremely wetter than normal is statistically significant. In comparison, winter precipitation in this region is under the positive influence of ENSO and NAO and the negative influence of PDO; the effect of ENSO on moisture convergence can be mainly attributed to its dynamic component. [ABSTRACT FROM AUTHOR]

Vegetation activity and phenology are significantly affected by climate change, and changes in vegetation activity and phenology can in turn affect regional or global climate patterns. As one of the world’s great biomes, temperate grasslands have undergone remarkable changes in recent decades, but the connections between vegetation activity and phenology changes and regional climate there have remained unclear. Using the observation minus reanalysis (OMR) method, this study investigated the possible effects of vegetation activity and vegetation growing season changes on air temperatures in temperate grasslands of China. The results showed that average NDVI of the temperate grassland significantly increased by 0.011 decade21 for the growing season during 1982–2015. The growing season started earlier and ended later, resulting in an extension. Increased vegetation activity during spring and autumn significantly warmed spring and autumn air temperatures by reducing albedo. By contrast, summer greening had no significant effect on summer temperature, due to the opposing effects of decreased albedo and enhanced evapotranspiration on temperature. The earlier start and later end of the growing season contributed to warmer spring and autumn air temperatures. As phenological changes had no significant effect on summer temperature, the extended growing season warmed air temperature. Our results suggest that the climate change–induced increasing vegetation activity and extended growing seasons can further aggravate regional warming in temperate grasslands of China, implying that the effects of vegetation activity and phenology changes on regional climate should be considered in climate models for accurately simulating climate change in temperate grasslands. [ABSTRACT FROM AUTHOR]

Possible thermodynamic effects of global warming on the landfalling typhoons that affect South China and their associated storm surges over Pearl River Delta region are investigated, using the Weather Research and Forecasting (WRF) Model and the Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model based on the pseudo–global warming (PGW) technique. Twenty intense historical TCs that brought extreme storm surges to Hong Kong since the 1960s are selected and replicated by the 3-km WRF Model, with the outputs to drive the SLOSH model in storm surge simulation. The tracks, intensities, storm structure, and induced storm surges are well simulated. The PGW technique is then used to build a warmer background climate for the 20 selected TCs in the period of 2075–99 under the RCP8.5 scenario. To obtain a better adjusted warming environment, a pre-PGW adjustment method is developed. Comparing the same TCs in PGW experiments and historical runs, the TC lifetime peak (landfall) intensity can be intensified by about 9% 6 8% (12% 6 13%), with a ∼3% increase of TC peak intensity per degree of SST warming being inferred. The TCs are projected to be more compact, with the radius of maximum wind (RMW) reduced by ∼7% 6 10%. TC precipitation is also expected to increase, with the extreme precipitation within the eyewall strengthened by 22% 6 12%. All the above characters have passed the Student’s t test at 0.05 significance level. Finally, the projected induced storm surges near the Hong Kong waters are not significantly tested, although a weak storm surge height increase tendency is revealed. [ABSTRACT FROM AUTHOR]

Precipitation in China is controlled by a combination of multiple weather systems and is susceptible to their spatiotemporal variability under climate warming. Based on the daily precipitation dataset developed by the China Meteorological Administration and ERA5 6-hourly data from 1979 to 2018, we detected tropical cyclones, extratropical cyclones, and fronts affecting mainland China of an altitude less than 1500 m using objective methods and identified their individually associated precipitation. We quantified climatological characteristics of precipitation associated with these three meteorological causes and their proportion of precipitation totals, and evaluated their relative contribution to change in precipitation. Results show that precipitation associated with tropical cyclones (TCP), extratropical cyclones (ETCP), and fronts (FRTP) accounted for 3.0%, 21.2%, and 20.4% of the total precipitation in China, and constituted the largest percentage in August, June, and January, respectively. The total proportion of these three types of precipitation exceeded 50% in more than 55% of China's regions. The high-value regions of corresponding precipitation were directly related to the locations of frequent occurrences of these weather systems. TCP and FRTP increased over the past four decades, while ETCP decreased. The western part of Northeast China and the middle and upper reaches of the Yangtze River show precipitation decreases, 37.8% of which is contributed by ETCP decreases. Precipitation increased in most regions of China during the dry season, 34.1% of which is contributed by FRTP increases. Among them, Northeast (Northwest) China significantly increased it precipitation by 14.4% decade−1 (21.8% decade−1), 33.6% (51.3%) of which is contributed by FRTP increases. [ABSTRACT FROM AUTHOR]

The reported decreasing trend of the annual tropical cyclone (TC) landfalls in southern China and increasing trend in southeastern China in recent decades are confirmed to be an abrupt shift occurring at the end of the twentieth century, based on a statistical analysis. The opposite trends in the two adjacent regions are often considered to be a result of tropical cyclone landfalls in southern China being deflected northward. However, it is demonstrated in this study that they are phenomenally independent. In fact, the abrupt decrease of TC landfalls in southern China occurs as a result of an abrupt decrease of the westward events in the postpeak season (October–December), which in turn is a consequence of a significant decrease of the TC genesis frequency in the southeastern part of the western North Pacific (WNP) Ocean basin. On the other hand, the abrupt increase of TC landfalls in southeastern China occurs because of an abrupt increase of the northwest events in the peak season (July–September), as the consequence of a statistically westward shift of TC genesis. The relevant variations of TC genesis are shown to be mainly caused by decreased relative vorticity and increased vertical wind shear, which, however, are intrinsically related to the accelerated zonal atmospheric circulation driven by a La Niña–like sea surface warming pattern over the WNP that developed after the end of twentieth century. [ABSTRACT FROM AUTHOR]

The planetary boundary layer (PBL) plays an essential role in climate and air quality simulations. Nevertheless, large uncertainties remain in understanding the drivers for long-termtrends of PBL height (PBLH) and its simulation. Herewe combine the radiosonde data and reanalysis datasets to analyze PBLHlong-termtrends over China, and to further explore the performance of CMIP6 climate models in simulating these trends. Results show that the observed long-term "positive-tonegative" trend shift of PBLH is related to the variation in the surface upward sensible heat flux (SHFLX), and the SHFLX is further controlled by the synergistic effect of low cloud cover (LCC) and soil moisture (SM) changes. Variabilities in LCC and SM directly influence the energy balance via surface net downward shortwave flux (SWF) and the latent heat flux (LHFLX), respectively. The CMIP6 climate models, however, cannot reproduce the observed PBLH long-term trend shift over China. The CMIP6 results illustrate an overwhelming continuous downward PBLH trend during the 1979-2014 period, which is largely caused by the poor capability in simulating long-term variations of cloud radiative effect. Our results reveal that the long-term cloud radiative effect simulation is critical for CMIP6 models in reproducing the long-term trend of PBLH. This study highlights the importance of processes associated with LCC and SM in modulating PBLH long-term variations and calls attention to improve these processes in climate models in order to improve the PBLH long-term trend simulations. SIGNIFICANCE STATEMENT: Investigating the long-term variations of the planetary boundary layer height (PBLH) is of great importance in understanding the complicated interactions between climate change and the planetary boundary layer. The availability of long-term radiosonde observations, along with reanalysis data and data from phase 6 of the Coupled Model Intercomparison Project, provides an excellent opportunity for us to analyze the long-term variability of PBLH and explore the capability of global climate models in reproducing the observed trend of PBLH. We argue that variations of cloud cover and soil moisture dominate the long-term variability of PBLH over China, given their key role in modifying the surface energy partition and balance. More importantly, whether cloud processes can be well simulated or not is key to reproducing the observed PBLH variations in global climate models, which merits further process-based observation in the future. [ABSTRACT FROM AUTHOR]

Projections of future sea level changes are usually based on global climate models (GCMs). However, the changes in shallow coastal regions, like the marginal seas near China, cannot be fully resolved in GCMs. To improve regional sea level simulations, a high-resolution (~8 km) regional ocean model is set up for the marginal seas near China for both the historical (1994–2015) and future (2079–2100) periods under representative concentration pathways (RCPs) 4.5 and 8.5. The historical ocean simulations are evaluated at different spatiotemporal scales, and the model is then integrated for the future period, driven by projected monthly climatological climate change signals from eight GCMs individually via both surface and open boundary conditions. The downscaled ocean changes derived by comparing historical and future experiments reveal greater spatial details than those from GCMs, such as a low dynamic sea level (DSL) center of -0.15min the middle of the South China Sea (SCS).As a novel test, the downscaled results driven by the ensemble mean forcings are almost identical with the ensemble average results from individually downscaled cases. Forcing of the DSL change and increased cyclonic circulation in the SCS are dominated by the climate change signals from the Pacific, while the DSL change in the East China marginal seas is caused by both local atmosphere forcing and signals from the Pacific. The method of downscaling developed in this study is a useful modeling protocol for adaptation and mitigation planning for future oceanic climate changes. [ABSTRACT FROM AUTHOR]