This study provides a comprehensive evaluation of historical surface soil moisture simulation(1979-2012)over Eurasia at annual and seasonal time scales between two medium-resolution versions of the Beijing Climate Cen...This study provides a comprehensive evaluation of historical surface soil moisture simulation(1979-2012)over Eurasia at annual and seasonal time scales between two medium-resolution versions of the Beijing Climate Center Climate System Model(BCC-CSM)—one that is currently participating in phase 6 of the Coupled Model Intercomparison Project(CMIP6),i.e.,BCC-CSM2-MR,and the other,BCC-CSM1.1m,which participated in CMIP5.We show that BCC-CSM2-MR is more skillful in reproducing the climate mean states and standard deviations of soil moisture,with pattern correlations increased and biases reduced significantly.BCC-CSM2-MR performs better in capturing the first two primary patterns of soil moisture anomalies,where the period of the corresponding time series is closer to that of reference data.Comparisons show that BCC-CSM2-MR performs at a high level among multiple models of CMIP6 in terms of centered pattern correlation and“amplitude of variation”(relative standard deviation).In general,the centered pattern correlation of BCC-CSM2-MR,ranging from 0.61 to 0.87,is higher than the multi-model mean of CMIP6,and the relative standard deviation is 0.75,which surmounts the overestimations in most of the CMIP6 models.Due to the vital role played by precipitation in land-atmosphere interaction,possible causes of the improvement of soil moisture simulation are further related to precipitation in BCC-CSM2-MR.The results indicate that a better description of the relationship between soil moisture and precipitation and a better reproduction of the climate mean precipitation by the model may result in the improved performance of soil moisture simulation.展开更多
The climate system models from Beijing Climate Center, BCC_CSM1.1 and BCC_CSM1.1-M, are used to carry out most of the CMIP5 experiments. This study gives a general introduction of these two models, and provides main i...The climate system models from Beijing Climate Center, BCC_CSM1.1 and BCC_CSM1.1-M, are used to carry out most of the CMIP5 experiments. This study gives a general introduction of these two models, and provides main information on the experiments including the experiment purpose, design, and the external forcings. The transient climate responses to the CO2 concentration increase at 1% per year are presented in the simulation of the two models. The BCC_CSM1.1-M result is closer to the CMIP5 multiple models ensemble. The two models perform well in simulating the historical evolution of the surface air temperature, globally and averaged for China. Both models overestimate the global warming and underestimate the warming over China in the 20th century. With higher horizontal resolution, the BCC_CSM1.1-M has a better capability in reproducing the annual evolution of surface air temperature over China.展开更多
The second-generation Global Ocean Data Assimilation System of the Beijing Climate Center （BCC_GODAS2.0） has been run daily in a pre-operational mode. It spans the period 1990 to the present day. The goal of this pa...The second-generation Global Ocean Data Assimilation System of the Beijing Climate Center （BCC_GODAS2.0） has been run daily in a pre-operational mode. It spans the period 1990 to the present day. The goal of this paper is to introduce the main components and to evaluate BCC_GODAS2.0 for the user community. BCC_GODAS2.0 consists of an observational data preprocess, ocean data quality control system, a three-dimensional variational （3DVAR） data assimilation, and global ocean circulation model [Modular Ocean Model 4 （MOM4）]. MOM4 is driven by six-hourly fluxes from the National Centers for Environmental Prediction. Satellite altimetry data, SST, and in-situ temperature and salinity data are assimilated in real time. The monthly results from the BCC_GODAS2.0 reanalysis are compared and assessed with observations for 1990-201 I. The climatology of the mixed layer depth of BCC_GODAS2.0 is generally in agreement with that of World Ocean Atlas 2001. The modeled sea level variations in the tropical Pacific are consistent with observations from satellite altimetry on interannual to decadal time scales. Performances in predicting variations in the SST using BCC_GODAS2.0 are evaluated. The standard deviation of the SST in BCC_GODAS2.0 agrees well with observations in the tropical Pacific. BCC_GODAS2.0 is able to capture the main features of E1 Nifio Modoki I and Modoki II, which have different impacts on rainfall in southern China. In addition, the relationships between the Indian Ocean and the two types of E1 Nino Modoki are also reproduced.展开更多
Climate variability modes, usually known as primary climate phenomena, are well recognized as the most impor- tant predictability sources in subseasonal-interarmual climate prediction. This paper begins by reviewing t...Climate variability modes, usually known as primary climate phenomena, are well recognized as the most impor- tant predictability sources in subseasonal-interarmual climate prediction. This paper begins by reviewing the re- search and development carried out, and the recent progress made, at the Beijing Climate Center （BCC） in predicting some primary climate variability modes. These include the El Nifio-Southern Oscillation （ENSO）, Madden-Julian Oscillation （MJO）, and Arctic Oscillation （AO）, on global scales, as well as the sea surface temperature （SST） modes in the Indian Ocean and North Atlantic, western Pacific subtropical high （WPSH）, and the East Asian winter and summer monsoons （EAWM and EASM, respectively）, on regional scales. Based on its latest climate and statistical models, the BCC has established a climate phenomenon prediction system （CPPS） and completed a hindcast experi- ment for the period 1991-2014. The performance of the CPPS in predicting such climate variability modes is system- atically evaluated. The results show that skillful predictions have been made for ENSO, MJO, the Indian Ocean basin mode, the WPSH, and partly for the EASM, whereas less skillful predictions were made for the Indian Ocean Dipole （IOD） and North Atlantic SST Tripole, and no clear skill at all for the AO, subtropical IOD, and EAWM. Improve- ments in the prediction of these climate variability modes with low skill need to be achieved by improving the BCC＇s climate models, developing physically based statistical models as well as correction methods for model predictions. Some of the monitoring/prediction products of the BCC-CPPS are also introduced in this paper.展开更多
The performance of BCC （Beijing Climate Center） AGCM 2.0.1 （Atmospheric General Circulation Model version 2.0.1） in simulating the tropical intraseasonal oscillation （TIO） is examined in this paper.The simulatio...The performance of BCC （Beijing Climate Center） AGCM 2.0.1 （Atmospheric General Circulation Model version 2.0.1） in simulating the tropical intraseasonal oscillation （TIO） is examined in this paper.The simulations are validated against observation and compared with the NCAR CAM3 （Community Atmosphere Model version 3） results.The BCC AGCM2.0.1 is developed based on the original BCC AGCM （version 1） and NCAR CAM3.New reference atmosphere and reference pressure are introduced into the model.Therefore,the original prognostic variables of temperature and surface pressure become their departures from the reference atmosphere.A new Zhang-McFarlane convective parameterization scheme is incorporated into the model with a few modifications.Other modifications include those in the boundary layer process and snow cover calculation.All simulations are run for 52 yr from 1949 to 2001 under the lower boundary conditions of observed monthly SST.The TIOs from the model are analyzed.The comparison shows that the NCAR CAM3 has a poor ability in simulating the TIO.The simulated strength of the TIO is very weak.The energy of the eastward moving waves is similar to that of the westward moving waves in CAM3.While in observation the former is much larger than the latter.The seasonal variation and spatial distribution of the TIO produced by CAM3 are also much different from the observation.The ability of the BCC AGCM2.0.1 in simulating the TIO is significantly better.The simulated TIO is evident.The strength of the TIO produced by the BCC AGCM2.0.1 is close to the observation.The energy of eastward moving.waves is much stronger than that of the westward moving waves,which is consistent with the observation.There is no significant difference in the seasonal variation and spatial distribution of the TIO between the BCC model simulation and the observation.In general,the BCC model performs better than CAM3 in simulating the TIO.展开更多
Land cover is one of the most basic input elements of land surface and climate models. Currently, the direct and indirect effects of land cover data on climate and climate change are receiving increasing attentions. I...Land cover is one of the most basic input elements of land surface and climate models. Currently, the direct and indirect effects of land cover data on climate and climate change are receiving increasing attentions. In this study, a high resolution(30 m) global land cover dataset(Globe Land30) produced by Chinese scientists was, for the first time, used in the Beijing Climate Center Climate System Model(BCC_CSM) to assess the influences of land cover dataset on land surface and climate simulations. A two-step strategy was designed to use the Globe Land30 data in the model. First, the Globe Land30 data were merged with other satellite remote sensing and climate datasets to regenerate plant functional type(PFT) data fitted for the BCC_CSM. Second, the up-scaling based on an area-weighted approach was used to aggregate the fine-resolution Globe Land30 land cover type and area percentage with the coarser model grid resolutions globally. The Globe Land30-based and the BCC_CSM-based land cover data had generally consistent spatial distribution features, but there were some differences between them. The simulation results of the different land cover type dataset change experiments showed that effects of the new PFT data were larger than those of the new glaciers and water bodies(lakes and wetlands). The maximum value was attained when dataset of all land cover types were changed. The positive bias of precipitation in the mid-high latitude of the northern hemisphere and the negative bias in the Amazon, as well as the negative bias of air temperature in part of the southern hemisphere, were reduced when the Globe Land30-based data were used in the BCC_CSM atmosphere model. The results suggest that the Globe Land30 data are suitable for use in the BCC_CSM component models and can improve the performance of the land and atmosphere simulations.展开更多
Based on the empirical orthogonal function(EOF) analysis, the East Asia–Pacific(EAP) teleconnection is extracted as the leading mode of the subseasonal variability over East Asia in summer, with a meridional tripole ...Based on the empirical orthogonal function(EOF) analysis, the East Asia–Pacific(EAP) teleconnection is extracted as the leading mode of the subseasonal variability over East Asia in summer, with a meridional tripole structure and significant periods of 10–30 and 50–70 days. A two-dimensional phase–space diagram is established for the EAP index and its time tendency so as to monitor the real-time state of EAP events. Based on the phase composite analysis, the general circulation anomalies first occur over the high-latitude area of Europe centered near Novaya Zemlya at the beginning of EAP events. These general circulation anomalies then influence rainfall over Northeast China,North China, and the region south of the Yangtze River valley(YRV) as the phases of EAP event progress. The representation, predictability, and prediction skill of the EAP teleconnection are examined in the two fully coupled subseasonal prediction systems of the Beijing Climate Center(BCC) and UK Met Office(UKMO GloSea5). Both models are able to simulate the EAP meridional tripole over East Asia as the leading mode and its characteristics of evolution as well, except for the weaker precursors over Novaya Zemlya and an inconspicuous influence on precipitation over Northeast China. The actual prediction skill of the EAP teleconnection during May–September(MJJAS) is about 10 days in the BCC model and 15 days in the UKMO model based on correlation measures, but is higher when initialized from the EAP peak phases or when targeted on strong EAP scenarios. However, both of the ensemble prediction systems are under-dispersive and the predictable signals extend to 18 and 30 days in BCC and UKMO models based on signal-to-error metrics, indicating that there may be further scope for enhancing the capability of these models for the EAP teleconnection prediction and the associated impacts studies.展开更多
In the summer of 2024, following a strong El Ni?o event in the preceding winter, the tropical Indian Ocean and tropical North Atlantic recorded their highest SSTs since 1961, along with a significant westward shift an...In the summer of 2024, following a strong El Ni?o event in the preceding winter, the tropical Indian Ocean and tropical North Atlantic recorded their highest SSTs since 1961, along with a significant westward shift and intensification of the western Pacific subtropical high(WPSH). Under these conditions, China experienced its hottest summer since 1961,and was hit by a series of high-impact extreme weather and climate events. From 9 June to 2 July, southern China experienced an unprecedented extreme precipitation event that exceeded the well-known 1998 summer precipitation event in both duration and impact scope, resulting in devastating floods in the Yangtze River basin. Subsequently, in early to midJuly, the Huanghe-Huaihe Basin suffered from a severe drought–flood abrupt alternation event, heavily affecting Henan and Shandong. Meanwhile, southern China underwent a widespread heatwave event lasting 74 days, ranking as the second most intense since 1961. From late July to the end of August, northern China faced unusually frequent heavy precipitation events, with cumulative precipitation reaching the second highest for the same period since 1961, causing floods in many rivers of northern China. This study provides a timely summary and assessment of the characteristics and impacts of these extreme events. It serves as a reference for climate change research, including mechanism analysis, numerical simulation,and climate event attribution, and also offers valuable insights for improving meteorological disaster prevention and mitigation strategies.展开更多
The Three Gorges Region(TGR)of the Yangtze River basin exhibited warm and dry climatic characteristics in 2024.The annual mean temperature in the TGR was 18.6℃,which was 1.2℃above normal and marked the highest level...The Three Gorges Region(TGR)of the Yangtze River basin exhibited warm and dry climatic characteristics in 2024.The annual mean temperature in the TGR was 18.6℃,which was 1.2℃above normal and marked the highest level since 1961.All four seasons were warmer than normal,with spring and autumn both recording their highest temperatures since 1961.Additionally,the TGR recorded 57.2 high-temperature days in 2024,reaching a historic high since 1961 and exceeding the previous record set in 2022 by 2.4 days.Annual rainfall was 11.2%below normal,with spring,summer,and autumn all being drier than normal.However,the number of heavy rain days was slightly higher than normal.The annual mean wind speed in the TGR ranked as the second-highest since 1961,only slightly lower than in 2022.The annual mean relative humidity was below normal and the number of fog days across large areas of the TGR decreased compared to 2023.In 2024,the TGR experienced extreme high-temperature events characterized by exceptional intensity and prolonged duration,accompanied by generally severe meteorological drought conditions.During the year,the TGR also experienced frequent and intense cooling events,an early onset of heavy rainfall(including severe convective weather),and exceptionally extreme rainstorm events.展开更多
The year 2024 witnessed remarkable climatic anomalies across China,characterized by pronounced warm and wet conditions.The annual mean temperature soared to a record high since 1951,with seasonal temperatures in sprin...The year 2024 witnessed remarkable climatic anomalies across China,characterized by pronounced warm and wet conditions.The annual mean temperature soared to a record high since 1951,with seasonal temperatures in spring,summer,and autumn all exceeding historical extremes.Meanwhile,the annual precipitation ranked as the fourth highest on record,with all four seasons experiencing above-average rainfall.Notably,the Yangtze River Basin and Jiangnan region encountered their most intense precipitation event since 1961.Extreme weather events were particularly striking:An unusually early and severe heatwave swept through central and eastern China,becoming the second most intense high-temperature event in recorded history.Autumn typhoon activity also displayed exceptional intensity,with Typhoon Yagi triggering significant impacts in Hainan,Guangdong,and Guangxi.Although drought conditions were generally mild overall,notable seasonal and regional disparities emerged,especially in the winter–spring droughts affecting southwestern China.Conversely,cold outbreaks occurred more frequently than usual,and convective weather events exhibited heightened activity.Moreover,dust storm activity remained relatively limited.展开更多
Compound extreme climate events may profoundly affect human activity in the Yangtze River Basin.This study analyzed the long-term spatiotemporal distribution characteristics of compound heatwave-drought and heatwave-w...Compound extreme climate events may profoundly affect human activity in the Yangtze River Basin.This study analyzed the long-term spatiotemporal distribution characteristics of compound heatwave-drought and heatwave-waterlogging events in the Yangtze River Basin using multi-period historical observation data and future scenario climate model data.It also examined the changes in population exposure to compound extreme climate events in the basin and their driving factors by combining population statistics and forecast data.The results show that the occurrence days of compound heatwave-drought and heatwave-waterlogging events in the Yangtze River Basin have shown a significant upward trend both in historical periods and future scenarios,accompanied by a marked expansion in the affected areas.Compared to historical periods,population exposure in the Yangtze River Basin under future scenarios is expected to increase by 1.5–2 times,primarily concentrated in the key urban areas of the basin.The main factors driving the changes in population exposure are the increased frequency of extreme climate events and population decline in future scenarios.These findings provide scientific evidence for early mitigation of meteorological disasters in the Yangtze River Basin.展开更多
In recent decades,large ensemble simulation(LENS)or super-large ensemble simulation(SLENS)experiments with climate models,including the simulation of both the historical and future climate,have been increasingly explo...In recent decades,large ensemble simulation(LENS)or super-large ensemble simulation(SLENS)experiments with climate models,including the simulation of both the historical and future climate,have been increasingly exploited in the fields of climate change,climate variability,climate projection,and beyond.This paper provides an overview of LENS in climate systems.It delves into its definition,initialization,significance,and scientific concerns.Additionally,its development history and relevant theories,methods,and primary fields of application are also reviewed.Conclusions obtained from single-model LENS can be more robust compared with those from ensemble simulations with smaller numbers of members.The interactions among model biases,forced responses,and internal variabilities,which serve as the added value in LENS,are highlighted.Finally,we put forward the future trajectory of LENS with climate or Earth system models(ESMs).Super-large ensemble simulation,high-resolution LENS,LENS employing ESMs,and combining LENS with artificial intelligence,will greatly promote the study of climate and related applications.展开更多
The 19th Workshop on Antarctic Meteorology and Climate(WAMC)and the 8th Year of Polar Prediction in the Southern Hemisphere(YOPP-SH)meeting were held in June 2024 at the Byrd Polar and Climate Research Center,The Ohio...The 19th Workshop on Antarctic Meteorology and Climate(WAMC)and the 8th Year of Polar Prediction in the Southern Hemisphere(YOPP-SH)meeting were held in June 2024 at the Byrd Polar and Climate Research Center,The Ohio State University,Columbus,Ohio.These hybrid events convened 79 participants from 15 nations to foster international collaboration on Antarctic meteorology,climate research,and forecasting.The WAMC featured presentations on automatic weather stations,numerical weather prediction,Antarctic sea ice dynamics,and extreme weather events.The YOPP-SH meeting emphasized the positive impacts of enhanced observations during the 2022 Winter Special Observing Period(SOP)on forecast accuracy and addressed the transition toward the Polar Coupled Analysis and Prediction for Services(PCAPS)initiative.The outcomes reflect significant advancements in polar meteorological research and underscore the importance of sustained collaborative efforts,including improved observational networks and advanced modeling systems,to address the unique challenges of Antarctic meteorology.Future workshops will continue to support and expand upon these critical themes.展开更多
Land use in arid and semi-arid regions has a substantial effect on climate,environment,and biodiversity,thereby projecting the spatiotemporal changes in land use and the subsequent effects.This study employed the loca...Land use in arid and semi-arid regions has a substantial effect on climate,environment,and biodiversity,thereby projecting the spatiotemporal changes in land use and the subsequent effects.This study employed the locally calibrated Future Land Use Simulation(FLUS)model,which coupled system dynamics with cellular automata and integrated an artificial neural network algorithm and a roulette wheel selection mechanism.We projected future land use(2020–2100)dynamics of Lanzhou,a typical river valley city in Northwest China,under three different Shared Socioeconomic Pathway(SSP)scenarios(SSP1-2.6,SSP2-4.5,and SSP5-8.5).The simulation results were validated and subsequently reclassified using the International Geosphere Biosphere Programme(IGBP)system to produce a dataset suitable for driving climatic and environmental models.Under the SSP1-2.6 scenario,urban and built-up land expanded consistently,whereas irrigated cropland and pasture as well as grassland contracted continuously.Conversely,the SSP5-8.5 scenario was characterized by a contraction of urban and built-up land,and relative stability of irrigated cropland and pasture as well as grassland.The SSP2-4.5 scenario presented a more complex trade-off,where urban and built-up land and grassland increased first and then decreased,whereas irrigated cropland and pasture followed an opposite trajectory.A significant inverse relationship between urban and built-up land and irrigated cropland and pasture was observed under all scenarios,underscoring the fundamental spatial competition that prevailed in this land-constrained valley city.Furthermore,the negative correlation of grassland with urban and built-up land,coupled with the positive correlation of grassland with irrigated cropland and pasture under both the SSP1-2.6 and SSP5-8.5 scenarios,indicated an evolution from broad confrontation to intricate internal trade-offs within the urban–agricultural–ecological system.This study underscored the critical influence of regional topographic and hydrological constraints on land-use evolution in arid regions,providing guidance for water resource management and ecosystem protection in Lanzhou,with applications for sustainable land-use planning in other arid and semi-arid river valley cities.展开更多
Global land monsoon precipitation(GLMP)is highly sensitive to changes in interhemispheric thermal contrast(ITC).Amplified interhemispheric asymmetries of GLMP due to enhanced ITC driven by high-level anthropogenic emi...Global land monsoon precipitation(GLMP)is highly sensitive to changes in interhemispheric thermal contrast(ITC).Amplified interhemispheric asymmetries of GLMP due to enhanced ITC driven by high-level anthropogenic emissions are expected to simultaneously increase the probability of regional floods and droughts,threatening ecosystems within global terrestrial monsoon regions and the freshwater supply for billions of residents in these areas.In this study,the responses of GLMP to the evolution of ITC toward the carbon neutrality goal are assessed using multimodel outputs from a new model intercomparison project(CovidMIP).The results show that the Northern Hemisphere-Southern Hemisphere(NH-SH)asymmetry of GLMP in boreal summer weakens during the 2040s,as a persistent reduction in well-mixed greenhouse gas(WMGHG)emissions leads to a downward trend in the ITC after 2040.At the same time,the reduction in WMGHG emissions dampens the Eastern Hemisphere-Western Hemisphere(EH-WH)asymmetry of GLMP by inducing La Niña-like cooling and enhancing moisture transport to Inner America.The resulting increases in land monsoon precipitation(LMP)may alleviate drought under the global warming scenario by about 19%-25%and 7%-9%in the WH and SH monsoon regions,respectively.However,a persistent reduction in aerosol emissions in Asia will dominate the increases in LMP in this region until the mid-21st century,and these increases may be approximately 23%-60%of the growth under the global warming scenario.Our results highlight the different rates of response of aerosol and WMGHG concentrations to the carbon neutrality goal,leading to various changes in LMP at global and regional scales.展开更多
Northeast China serves as an important crop production region.Accurately forecasting summer precipitation in Northeast China(NEC-PR)has been a challenge due to its wide range of time scales influenced by varying clima...Northeast China serves as an important crop production region.Accurately forecasting summer precipitation in Northeast China(NEC-PR)has been a challenge due to its wide range of time scales influenced by varying climatic conditions.This study presents a scale separation hybrid statistical model with recurrent neural network(SS-RNN)to predict the summer monthly NEC-PR.The SS-RNN model decomposes the multiple scales of the NEC-PR into several spatiotemporal intrinsic mode functions covering annual to decadal time scales.This strategy provides a way to derive appropriate predictors and establish predictive models for the primary spatial modes of the NEC-PR at various time scales.Our results demonstrate substantial improvements by the SS-RNN model in predicting the summer monthly NEC-PR as compared with dynamic models,particularly in predicting the spatial pattern of the NEC-PR.In this paper we take August,the month of the highest NEC-PR,to assess our model skill.Independent forecasts of the August NEC-PR over the period 2021–24 achieve significant spatial anomaly correlation coefficients,reaching a maximum value of 0.83.Additional verifications by station observations show that the model hits most station anomalies,achieving a mean predictive skill score of 90.展开更多
Since the initiation of the subseasonal-to-seasonal prediction project by the World Meteorological Organization,the accuracy of model forecasts has improved notably.However,substantial discrepancies have been observed...Since the initiation of the subseasonal-to-seasonal prediction project by the World Meteorological Organization,the accuracy of model forecasts has improved notably.However,substantial discrepancies have been observed among forecast results produced by different ensemble members when applied to South China.To enhance the accuracy of sub-seasonal forecasts in this region,it is essential to develop new methods that can effectively leverage multiple predictive models.This study introduces a weighted ensemble forecasting method based on online learning to improve forecast accuracy.We utilized ensemble forecasts from three models:the Integrated Forecasting System model from the European Centre for Medium-Range Weather Forecasts,the Climate Forecast System Version 2 model from the National Centers for Environmental Prediction,and the Beijing Climate Center-Climate Prediction System version 3 model from the China Meteorological Administration.The ensemble weights are trained using an online learning approach.The results indicate that the forecasts obtained through online learning outperform those of the original dynamical models.Compared to the simple ensemble results of the three models,the weighted ensemble model showed a stronger capability to capture temperature and precipitation patterns in South China.Therefore,this method has the potential to improve the accuracy of sub-seasonal forecasts in this region.展开更多
The Zebiak–Cane(ZC) model, renowned as a coupled ocean-atmosphere model specifically designed to simulate and predict El Niño-Southern Oscillation(ENSO), is an indispensable tool for ENSO studies. However, the o...The Zebiak–Cane(ZC) model, renowned as a coupled ocean-atmosphere model specifically designed to simulate and predict El Niño-Southern Oscillation(ENSO), is an indispensable tool for ENSO studies. However, the original ZC model exhibits certain biases in reproducing the ENSO–related sea surface temperature anomalies and heating anomalies, limiting its broader applicability. To improve the accuracy of ENSO simulation, we propose a modified ZC model based on Xie et al.(2015), named the MZC_XJH model, through refining the heating parameterization scheme. The performance in simulating the nonlinear SST–precipitation relationship in the MZC_XJH model is firstly elaborated. Then, we investigate the impacts of three key atmospheric parameters on ENSO simulation by conducting experiments with the MZC_XJH model. Through assessing the performance in simulating five fundamental ENSO metrics(amplitude, periodicity,seasonality, diversity, and skewness), we uncover that the sensitivities of simulated ENSO behaviors to different parameters are distinct. Moreover, we explain why a particular parameter greatly affects some simulated ENSO behaviors while others exert minor influence. We also reveal that the nonlinear effect due to the covariation of multi-parameters on ENSO simulation warrants careful consideration when tuning multi-parameters synchronously. Lastly, we present an updated version of the MZC_XJH model, in which some biases have been mitigated but some remain obvious. Although there are no universally optimal parameters that would ensure flawless performance in simulating every aspect of ENSO, this study provides a valuable reference for tuning atmospheric parameters in the MZC_XJH model, rendering the MZC_XJH model applicable to some research objectives.展开更多
The root-to-shoot(R/S)ratio is a critical indicator of the balance between root biomass and shoot biomass,representing the ecological strategies and adaptive responses of plants to environmental conditions.However,the...The root-to-shoot(R/S)ratio is a critical indicator of the balance between root biomass and shoot biomass,representing the ecological strategies and adaptive responses of plants to environmental conditions.However,the patterns of change in community R/S ratios during forest succession and their response to moisture levels across broad geographic gradients remains unclear.Based on forest biomass data from a national field inventory of 5,825 plots conducted across China between 2011 and 2015,this study looked into allocating biomass shoots and roots at the early,middle,and late stages of growth in plantations and succession in natural forests,and evaluated how moisture availability influences this allocation.The results revealed a significant decline in R/S ratios from early to late stages for both plantations and natural forests.Shoot and root biomass in plantations grew isometrically during the early and middle succession stages but shifted to allometric growth in the late stage,with the slope of the log-transformed shoot-root biomass relationship differing significantly across growth stages.Natural forests,in contrast,maintained isometric growth across successional stages,showing no significant variation in the slope of the log-transformed shoot-root biomass relationship.Environmental factors,particularly moisture levels,strongly influenced R/S ratios.Moisture levels significantly affected size-corrected R/S ratios,particularly in the middle stage of plantations and the early and middle stages of natural forests,supporting the hypothesis of optimal allocation.These findings suggest that in water-limited regions,forest management should prioritize drought-tolerant,deep-rooted native species,encourage mixed-species planting in the early stage,and reduce logging intensity in mature plantations.Conserving natural forests to maintain successional dynamics is essential for long-term ecological resilience.These findings emphasize the importance of balancing productivity with ecological sustainability by adapting practices to specific environments and forest types under climate change.展开更多
Both natural and human-induced disturbances affect the normal functioning and services of mangrove ecosystems.To address the consequences of intense human and climatic disturbances on sedimentation and carbon burial,s...Both natural and human-induced disturbances affect the normal functioning and services of mangrove ecosystems.To address the consequences of intense human and climatic disturbances on sedimentation and carbon burial,sediment cores from the last remaining mangrove Kandelia obovata forest and an adjacent mudflat in the densely populated and typhoon-prone Zhujiang(Pearl)River estuary of China,were analyzed using methods including^(210)Pb dating andδ^(13)C analysis.Results indicate that after damming in the 1950s,during 1960-1980,the natural establishment of K.obovata forests initiated the insitu sedimentation.As these forests matured during 1980-1990,they significantly boosted siltation in the region on mudflat.During 1990-2015,the invasion of Spartina alterniflora and land reclamation for aquaculture caused infiltration of coarse sediments and the impacts of typhoons were recorded within the K.obovata forest,while no clear typhoon record was observed on the mudflat.Since 2015,reforestation efforts with S.apetala that began in 1999 have reversed the effects of earlier deforestation.Over time,mangroves established a rapid autochthonous carbon burial that grew as the forests age,potentially surpassing the influx of allochthonous carbon due to deforestation.The reforestation also immediately improved carbon burial on the mudflat,which stabilized after a decade due to the rapid growth and high biomass of S.apetala.Overall,the K.obovata forest demonstrated a stronger sedimentation and carbon burial capabilities than the mudflat,with a surplus of 35.2 Mg C/hm^(2)in soil organic carbon stock and 1.0 Mg C/(hm^(2)·a)in burial rate.Organic matter dissolved in soil was mainly humus-like components,and mangrove inputs likely increased the degree of humification.This study offered direct evidence regarding the impact of multiple disturbances on local and regional sedimentation and carbon burial,and future management strategies.展开更多
基金supported by the National Key Research and Development Program of China(Grant Nos.2018YFC1506004 and 2016YFA0602602).
文摘This study provides a comprehensive evaluation of historical surface soil moisture simulation(1979-2012)over Eurasia at annual and seasonal time scales between two medium-resolution versions of the Beijing Climate Center Climate System Model(BCC-CSM)—one that is currently participating in phase 6 of the Coupled Model Intercomparison Project(CMIP6),i.e.,BCC-CSM2-MR,and the other,BCC-CSM1.1m,which participated in CMIP5.We show that BCC-CSM2-MR is more skillful in reproducing the climate mean states and standard deviations of soil moisture,with pattern correlations increased and biases reduced significantly.BCC-CSM2-MR performs better in capturing the first two primary patterns of soil moisture anomalies,where the period of the corresponding time series is closer to that of reference data.Comparisons show that BCC-CSM2-MR performs at a high level among multiple models of CMIP6 in terms of centered pattern correlation and“amplitude of variation”(relative standard deviation).In general,the centered pattern correlation of BCC-CSM2-MR,ranging from 0.61 to 0.87,is higher than the multi-model mean of CMIP6,and the relative standard deviation is 0.75,which surmounts the overestimations in most of the CMIP6 models.Due to the vital role played by precipitation in land-atmosphere interaction,possible causes of the improvement of soil moisture simulation are further related to precipitation in BCC-CSM2-MR.The results indicate that a better description of the relationship between soil moisture and precipitation and a better reproduction of the climate mean precipitation by the model may result in the improved performance of soil moisture simulation.
基金supported by the National Basic Research Program of China (973 Program) under No. 2010CB951903the National Science Foundation of China under Grant No. 41105054, 41205043the China Meteorological Administration under Grant No.GYHY201106022, GYHY201306048, CMAYBY2012-001
文摘The climate system models from Beijing Climate Center, BCC_CSM1.1 and BCC_CSM1.1-M, are used to carry out most of the CMIP5 experiments. This study gives a general introduction of these two models, and provides main information on the experiments including the experiment purpose, design, and the external forcings. The transient climate responses to the CO2 concentration increase at 1% per year are presented in the simulation of the two models. The BCC_CSM1.1-M result is closer to the CMIP5 multiple models ensemble. The two models perform well in simulating the historical evolution of the surface air temperature, globally and averaged for China. Both models overestimate the global warming and underestimate the warming over China in the 20th century. With higher horizontal resolution, the BCC_CSM1.1-M has a better capability in reproducing the annual evolution of surface air temperature over China.
基金supported by the National Natural Science Foundation of China (Grant No. 41306005)the National Basic Research Program of China (Grant No. 2012CB955903)the CAS/SAFEA International Partnership Program for Creative Research Teams
文摘The second-generation Global Ocean Data Assimilation System of the Beijing Climate Center （BCC_GODAS2.0） has been run daily in a pre-operational mode. It spans the period 1990 to the present day. The goal of this paper is to introduce the main components and to evaluate BCC_GODAS2.0 for the user community. BCC_GODAS2.0 consists of an observational data preprocess, ocean data quality control system, a three-dimensional variational （3DVAR） data assimilation, and global ocean circulation model [Modular Ocean Model 4 （MOM4）]. MOM4 is driven by six-hourly fluxes from the National Centers for Environmental Prediction. Satellite altimetry data, SST, and in-situ temperature and salinity data are assimilated in real time. The monthly results from the BCC_GODAS2.0 reanalysis are compared and assessed with observations for 1990-201 I. The climatology of the mixed layer depth of BCC_GODAS2.0 is generally in agreement with that of World Ocean Atlas 2001. The modeled sea level variations in the tropical Pacific are consistent with observations from satellite altimetry on interannual to decadal time scales. Performances in predicting variations in the SST using BCC_GODAS2.0 are evaluated. The standard deviation of the SST in BCC_GODAS2.0 agrees well with observations in the tropical Pacific. BCC_GODAS2.0 is able to capture the main features of E1 Nifio Modoki I and Modoki II, which have different impacts on rainfall in southern China. In addition, the relationships between the Indian Ocean and the two types of E1 Nino Modoki are also reproduced.
基金Supported by the National(Key)Basic Research and Development(973)Program of China(2015CB453203)China Meteorological Administration Special Public Welfare Research Fund(GYHY201506013 and GYHY201406022)+3 种基金National Natural Science Foundation of China(41205058,41375062,41405080,41505065,41606019,and 41605116)US National Science Foundation(AGS-1406601)US Department of Energy(DOE)(DE-SC000511)the UK–China Research&Innovation Partnership Fund through the Met Office Climate Science for Service Partnership(CSSP) China as part of the Newton Fund
文摘Climate variability modes, usually known as primary climate phenomena, are well recognized as the most impor- tant predictability sources in subseasonal-interarmual climate prediction. This paper begins by reviewing the re- search and development carried out, and the recent progress made, at the Beijing Climate Center （BCC） in predicting some primary climate variability modes. These include the El Nifio-Southern Oscillation （ENSO）, Madden-Julian Oscillation （MJO）, and Arctic Oscillation （AO）, on global scales, as well as the sea surface temperature （SST） modes in the Indian Ocean and North Atlantic, western Pacific subtropical high （WPSH）, and the East Asian winter and summer monsoons （EAWM and EASM, respectively）, on regional scales. Based on its latest climate and statistical models, the BCC has established a climate phenomenon prediction system （CPPS） and completed a hindcast experi- ment for the period 1991-2014. The performance of the CPPS in predicting such climate variability modes is system- atically evaluated. The results show that skillful predictions have been made for ENSO, MJO, the Indian Ocean basin mode, the WPSH, and partly for the EASM, whereas less skillful predictions were made for the Indian Ocean Dipole （IOD） and North Atlantic SST Tripole, and no clear skill at all for the AO, subtropical IOD, and EAWM. Improve- ments in the prediction of these climate variability modes with low skill need to be achieved by improving the BCC＇s climate models, developing physically based statistical models as well as correction methods for model predictions. Some of the monitoring/prediction products of the BCC-CPPS are also introduced in this paper.
基金Supported by the Key Basic Research Project of the National "973" Program of China under Grant No.2010CB951902
文摘The performance of BCC （Beijing Climate Center） AGCM 2.0.1 （Atmospheric General Circulation Model version 2.0.1） in simulating the tropical intraseasonal oscillation （TIO） is examined in this paper.The simulations are validated against observation and compared with the NCAR CAM3 （Community Atmosphere Model version 3） results.The BCC AGCM2.0.1 is developed based on the original BCC AGCM （version 1） and NCAR CAM3.New reference atmosphere and reference pressure are introduced into the model.Therefore,the original prognostic variables of temperature and surface pressure become their departures from the reference atmosphere.A new Zhang-McFarlane convective parameterization scheme is incorporated into the model with a few modifications.Other modifications include those in the boundary layer process and snow cover calculation.All simulations are run for 52 yr from 1949 to 2001 under the lower boundary conditions of observed monthly SST.The TIOs from the model are analyzed.The comparison shows that the NCAR CAM3 has a poor ability in simulating the TIO.The simulated strength of the TIO is very weak.The energy of the eastward moving waves is similar to that of the westward moving waves in CAM3.While in observation the former is much larger than the latter.The seasonal variation and spatial distribution of the TIO produced by CAM3 are also much different from the observation.The ability of the BCC AGCM2.0.1 in simulating the TIO is significantly better.The simulated TIO is evident.The strength of the TIO produced by the BCC AGCM2.0.1 is close to the observation.The energy of eastward moving.waves is much stronger than that of the westward moving waves,which is consistent with the observation.There is no significant difference in the seasonal variation and spatial distribution of the TIO between the BCC model simulation and the observation.In general,the BCC model performs better than CAM3 in simulating the TIO.
基金supported by the National High Technology Research and Development Program of China (Grant No. 2009AA122005)the Public Welfare Meteorology Research Project of China (Grant Nos. 201506023, 201306048)the National Natural Science Foundation of China (Grant Nos. 41275076, 40905046)
文摘Land cover is one of the most basic input elements of land surface and climate models. Currently, the direct and indirect effects of land cover data on climate and climate change are receiving increasing attentions. In this study, a high resolution(30 m) global land cover dataset(Globe Land30) produced by Chinese scientists was, for the first time, used in the Beijing Climate Center Climate System Model(BCC_CSM) to assess the influences of land cover dataset on land surface and climate simulations. A two-step strategy was designed to use the Globe Land30 data in the model. First, the Globe Land30 data were merged with other satellite remote sensing and climate datasets to regenerate plant functional type(PFT) data fitted for the BCC_CSM. Second, the up-scaling based on an area-weighted approach was used to aggregate the fine-resolution Globe Land30 land cover type and area percentage with the coarser model grid resolutions globally. The Globe Land30-based and the BCC_CSM-based land cover data had generally consistent spatial distribution features, but there were some differences between them. The simulation results of the different land cover type dataset change experiments showed that effects of the new PFT data were larger than those of the new glaciers and water bodies(lakes and wetlands). The maximum value was attained when dataset of all land cover types were changed. The positive bias of precipitation in the mid-high latitude of the northern hemisphere and the negative bias in the Amazon, as well as the negative bias of air temperature in part of the southern hemisphere, were reduced when the Globe Land30-based data were used in the BCC_CSM atmosphere model. The results suggest that the Globe Land30 data are suitable for use in the BCC_CSM component models and can improve the performance of the land and atmosphere simulations.
基金Supported by the National Key Research and Development Program of China(2018YFC1505906)National Natural Science Foundation of China(41905067 and 41775066)+1 种基金National(Key)Basic Research and Development(973)Program of China(2015CB453203)UK–China Research and Innovation Partnership Fund through the Met Office Climate Science for Service Partnership(CSSP)China as part of the Newton Fund。
文摘Based on the empirical orthogonal function(EOF) analysis, the East Asia–Pacific(EAP) teleconnection is extracted as the leading mode of the subseasonal variability over East Asia in summer, with a meridional tripole structure and significant periods of 10–30 and 50–70 days. A two-dimensional phase–space diagram is established for the EAP index and its time tendency so as to monitor the real-time state of EAP events. Based on the phase composite analysis, the general circulation anomalies first occur over the high-latitude area of Europe centered near Novaya Zemlya at the beginning of EAP events. These general circulation anomalies then influence rainfall over Northeast China,North China, and the region south of the Yangtze River valley(YRV) as the phases of EAP event progress. The representation, predictability, and prediction skill of the EAP teleconnection are examined in the two fully coupled subseasonal prediction systems of the Beijing Climate Center(BCC) and UK Met Office(UKMO GloSea5). Both models are able to simulate the EAP meridional tripole over East Asia as the leading mode and its characteristics of evolution as well, except for the weaker precursors over Novaya Zemlya and an inconspicuous influence on precipitation over Northeast China. The actual prediction skill of the EAP teleconnection during May–September(MJJAS) is about 10 days in the BCC model and 15 days in the UKMO model based on correlation measures, but is higher when initialized from the EAP peak phases or when targeted on strong EAP scenarios. However, both of the ensemble prediction systems are under-dispersive and the predictable signals extend to 18 and 30 days in BCC and UKMO models based on signal-to-error metrics, indicating that there may be further scope for enhancing the capability of these models for the EAP teleconnection prediction and the associated impacts studies.
基金supported by the National Natural Science Foundation of China (Grant Nos.42005029 and 41701103)the China Meteorological Administration Special Foundation for Innovation and Development (Grant No.CXFZ2024Q007)。
文摘In the summer of 2024, following a strong El Ni?o event in the preceding winter, the tropical Indian Ocean and tropical North Atlantic recorded their highest SSTs since 1961, along with a significant westward shift and intensification of the western Pacific subtropical high(WPSH). Under these conditions, China experienced its hottest summer since 1961,and was hit by a series of high-impact extreme weather and climate events. From 9 June to 2 July, southern China experienced an unprecedented extreme precipitation event that exceeded the well-known 1998 summer precipitation event in both duration and impact scope, resulting in devastating floods in the Yangtze River basin. Subsequently, in early to midJuly, the Huanghe-Huaihe Basin suffered from a severe drought–flood abrupt alternation event, heavily affecting Henan and Shandong. Meanwhile, southern China underwent a widespread heatwave event lasting 74 days, ranking as the second most intense since 1961. From late July to the end of August, northern China faced unusually frequent heavy precipitation events, with cumulative precipitation reaching the second highest for the same period since 1961, causing floods in many rivers of northern China. This study provides a timely summary and assessment of the characteristics and impacts of these extreme events. It serves as a reference for climate change research, including mechanism analysis, numerical simulation,and climate event attribution, and also offers valuable insights for improving meteorological disaster prevention and mitigation strategies.
基金supported by the Innovation and Development Special Project of the China Meteorological Administration[grant number CXFZ2024J071]the National Key Research and Development Program of China[grant number 2023YFC3206001].
文摘The Three Gorges Region(TGR)of the Yangtze River basin exhibited warm and dry climatic characteristics in 2024.The annual mean temperature in the TGR was 18.6℃,which was 1.2℃above normal and marked the highest level since 1961.All four seasons were warmer than normal,with spring and autumn both recording their highest temperatures since 1961.Additionally,the TGR recorded 57.2 high-temperature days in 2024,reaching a historic high since 1961 and exceeding the previous record set in 2022 by 2.4 days.Annual rainfall was 11.2%below normal,with spring,summer,and autumn all being drier than normal.However,the number of heavy rain days was slightly higher than normal.The annual mean wind speed in the TGR ranked as the second-highest since 1961,only slightly lower than in 2022.The annual mean relative humidity was below normal and the number of fog days across large areas of the TGR decreased compared to 2023.In 2024,the TGR experienced extreme high-temperature events characterized by exceptional intensity and prolonged duration,accompanied by generally severe meteorological drought conditions.During the year,the TGR also experienced frequent and intense cooling events,an early onset of heavy rainfall(including severe convective weather),and exceptionally extreme rainstorm events.
文摘The year 2024 witnessed remarkable climatic anomalies across China,characterized by pronounced warm and wet conditions.The annual mean temperature soared to a record high since 1951,with seasonal temperatures in spring,summer,and autumn all exceeding historical extremes.Meanwhile,the annual precipitation ranked as the fourth highest on record,with all four seasons experiencing above-average rainfall.Notably,the Yangtze River Basin and Jiangnan region encountered their most intense precipitation event since 1961.Extreme weather events were particularly striking:An unusually early and severe heatwave swept through central and eastern China,becoming the second most intense high-temperature event in recorded history.Autumn typhoon activity also displayed exceptional intensity,with Typhoon Yagi triggering significant impacts in Hainan,Guangdong,and Guangxi.Although drought conditions were generally mild overall,notable seasonal and regional disparities emerged,especially in the winter–spring droughts affecting southwestern China.Conversely,cold outbreaks occurred more frequently than usual,and convective weather events exhibited heightened activity.Moreover,dust storm activity remained relatively limited.
基金supported by the National Natural Science Foundation of China(Nos.42301029,42371354)the Scientific Research Start-up Fund for New Young Faculty,China University of Geosciences,Wuhan(No.CUGXQN2307)China Meteorological Administration Innovation and Development Project(No.CXFZ2023J051).
文摘Compound extreme climate events may profoundly affect human activity in the Yangtze River Basin.This study analyzed the long-term spatiotemporal distribution characteristics of compound heatwave-drought and heatwave-waterlogging events in the Yangtze River Basin using multi-period historical observation data and future scenario climate model data.It also examined the changes in population exposure to compound extreme climate events in the basin and their driving factors by combining population statistics and forecast data.The results show that the occurrence days of compound heatwave-drought and heatwave-waterlogging events in the Yangtze River Basin have shown a significant upward trend both in historical periods and future scenarios,accompanied by a marked expansion in the affected areas.Compared to historical periods,population exposure in the Yangtze River Basin under future scenarios is expected to increase by 1.5–2 times,primarily concentrated in the key urban areas of the basin.The main factors driving the changes in population exposure are the increased frequency of extreme climate events and population decline in future scenarios.These findings provide scientific evidence for early mitigation of meteorological disasters in the Yangtze River Basin.
基金This study was supported by the National Natural Science Foundation of China(Grant No.U2342228)the National Key Program for Developing Basic Sciences(Grant No.2020YFA0608902)+1 种基金the National Natural Science Foundation of China(Grant Nos.92358302,and 42242018)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB0500303).
文摘In recent decades,large ensemble simulation(LENS)or super-large ensemble simulation(SLENS)experiments with climate models,including the simulation of both the historical and future climate,have been increasingly exploited in the fields of climate change,climate variability,climate projection,and beyond.This paper provides an overview of LENS in climate systems.It delves into its definition,initialization,significance,and scientific concerns.Additionally,its development history and relevant theories,methods,and primary fields of application are also reviewed.Conclusions obtained from single-model LENS can be more robust compared with those from ensemble simulations with smaller numbers of members.The interactions among model biases,forced responses,and internal variabilities,which serve as the added value in LENS,are highlighted.Finally,we put forward the future trajectory of LENS with climate or Earth system models(ESMs).Super-large ensemble simulation,high-resolution LENS,LENS employing ESMs,and combining LENS with artificial intelligence,will greatly promote the study of climate and related applications.
基金support from the Office of Polar Programs of the National Science Foundation(Grant Nos.2205398,2233182,1951720,1951603,2301362).
文摘The 19th Workshop on Antarctic Meteorology and Climate(WAMC)and the 8th Year of Polar Prediction in the Southern Hemisphere(YOPP-SH)meeting were held in June 2024 at the Byrd Polar and Climate Research Center,The Ohio State University,Columbus,Ohio.These hybrid events convened 79 participants from 15 nations to foster international collaboration on Antarctic meteorology,climate research,and forecasting.The WAMC featured presentations on automatic weather stations,numerical weather prediction,Antarctic sea ice dynamics,and extreme weather events.The YOPP-SH meeting emphasized the positive impacts of enhanced observations during the 2022 Winter Special Observing Period(SOP)on forecast accuracy and addressed the transition toward the Polar Coupled Analysis and Prediction for Services(PCAPS)initiative.The outcomes reflect significant advancements in polar meteorological research and underscore the importance of sustained collaborative efforts,including improved observational networks and advanced modeling systems,to address the unique challenges of Antarctic meteorology.Future workshops will continue to support and expand upon these critical themes.
基金supported by the Soft Science Special Project of Gansu Basic Research Plan(25JRZA206)the Longyuan Youth Talent Project of Gansu Province(ZHU Rong)+1 种基金the Innovation Development Special Project of China Meteorological Administration(CXFZ2025J036)the Program of the State Key Laboratory of Cryospheric Science and Frozen Soil Engineering,Chinese Academy of Sciences(CSFSE-KF-2402).
文摘Land use in arid and semi-arid regions has a substantial effect on climate,environment,and biodiversity,thereby projecting the spatiotemporal changes in land use and the subsequent effects.This study employed the locally calibrated Future Land Use Simulation(FLUS)model,which coupled system dynamics with cellular automata and integrated an artificial neural network algorithm and a roulette wheel selection mechanism.We projected future land use(2020–2100)dynamics of Lanzhou,a typical river valley city in Northwest China,under three different Shared Socioeconomic Pathway(SSP)scenarios(SSP1-2.6,SSP2-4.5,and SSP5-8.5).The simulation results were validated and subsequently reclassified using the International Geosphere Biosphere Programme(IGBP)system to produce a dataset suitable for driving climatic and environmental models.Under the SSP1-2.6 scenario,urban and built-up land expanded consistently,whereas irrigated cropland and pasture as well as grassland contracted continuously.Conversely,the SSP5-8.5 scenario was characterized by a contraction of urban and built-up land,and relative stability of irrigated cropland and pasture as well as grassland.The SSP2-4.5 scenario presented a more complex trade-off,where urban and built-up land and grassland increased first and then decreased,whereas irrigated cropland and pasture followed an opposite trajectory.A significant inverse relationship between urban and built-up land and irrigated cropland and pasture was observed under all scenarios,underscoring the fundamental spatial competition that prevailed in this land-constrained valley city.Furthermore,the negative correlation of grassland with urban and built-up land,coupled with the positive correlation of grassland with irrigated cropland and pasture under both the SSP1-2.6 and SSP5-8.5 scenarios,indicated an evolution from broad confrontation to intricate internal trade-offs within the urban–agricultural–ecological system.This study underscored the critical influence of regional topographic and hydrological constraints on land-use evolution in arid regions,providing guidance for water resource management and ecosystem protection in Lanzhou,with applications for sustainable land-use planning in other arid and semi-arid river valley cities.
基金funded by the National Natural Science Foundation of China(Grant No.42275039)the Meteorological Joint Fund by NSF and CMA(Grant No.U2342224)+1 种基金the National Key R&D Program of China(Grant No.2022YFC3701202)the S&T Development Fund of CAMS(Grant No.2024KJ019)。
文摘Global land monsoon precipitation(GLMP)is highly sensitive to changes in interhemispheric thermal contrast(ITC).Amplified interhemispheric asymmetries of GLMP due to enhanced ITC driven by high-level anthropogenic emissions are expected to simultaneously increase the probability of regional floods and droughts,threatening ecosystems within global terrestrial monsoon regions and the freshwater supply for billions of residents in these areas.In this study,the responses of GLMP to the evolution of ITC toward the carbon neutrality goal are assessed using multimodel outputs from a new model intercomparison project(CovidMIP).The results show that the Northern Hemisphere-Southern Hemisphere(NH-SH)asymmetry of GLMP in boreal summer weakens during the 2040s,as a persistent reduction in well-mixed greenhouse gas(WMGHG)emissions leads to a downward trend in the ITC after 2040.At the same time,the reduction in WMGHG emissions dampens the Eastern Hemisphere-Western Hemisphere(EH-WH)asymmetry of GLMP by inducing La Niña-like cooling and enhancing moisture transport to Inner America.The resulting increases in land monsoon precipitation(LMP)may alleviate drought under the global warming scenario by about 19%-25%and 7%-9%in the WH and SH monsoon regions,respectively.However,a persistent reduction in aerosol emissions in Asia will dominate the increases in LMP in this region until the mid-21st century,and these increases may be approximately 23%-60%of the growth under the global warming scenario.Our results highlight the different rates of response of aerosol and WMGHG concentrations to the carbon neutrality goal,leading to various changes in LMP at global and regional scales.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFC3002803)the National Key Research and Development Program of China(Grant No.2024YFF0808402)the National Natural Science Foundation of China(Grant No.42375169)。
文摘Northeast China serves as an important crop production region.Accurately forecasting summer precipitation in Northeast China(NEC-PR)has been a challenge due to its wide range of time scales influenced by varying climatic conditions.This study presents a scale separation hybrid statistical model with recurrent neural network(SS-RNN)to predict the summer monthly NEC-PR.The SS-RNN model decomposes the multiple scales of the NEC-PR into several spatiotemporal intrinsic mode functions covering annual to decadal time scales.This strategy provides a way to derive appropriate predictors and establish predictive models for the primary spatial modes of the NEC-PR at various time scales.Our results demonstrate substantial improvements by the SS-RNN model in predicting the summer monthly NEC-PR as compared with dynamic models,particularly in predicting the spatial pattern of the NEC-PR.In this paper we take August,the month of the highest NEC-PR,to assess our model skill.Independent forecasts of the August NEC-PR over the period 2021–24 achieve significant spatial anomaly correlation coefficients,reaching a maximum value of 0.83.Additional verifications by station observations show that the model hits most station anomalies,achieving a mean predictive skill score of 90.
基金Science and Technology Development Program of the“Taihu Light”(K20231023)CMA Numerical Weather Prediction R&D Project(TCYF2024QH007)+1 种基金“Qing Lan”Project of Jiangsu Province for C.H.LUWuxi University Research Start-up Fund for Introduced Talents(2023r037)。
文摘Since the initiation of the subseasonal-to-seasonal prediction project by the World Meteorological Organization,the accuracy of model forecasts has improved notably.However,substantial discrepancies have been observed among forecast results produced by different ensemble members when applied to South China.To enhance the accuracy of sub-seasonal forecasts in this region,it is essential to develop new methods that can effectively leverage multiple predictive models.This study introduces a weighted ensemble forecasting method based on online learning to improve forecast accuracy.We utilized ensemble forecasts from three models:the Integrated Forecasting System model from the European Centre for Medium-Range Weather Forecasts,the Climate Forecast System Version 2 model from the National Centers for Environmental Prediction,and the Beijing Climate Center-Climate Prediction System version 3 model from the China Meteorological Administration.The ensemble weights are trained using an online learning approach.The results indicate that the forecasts obtained through online learning outperform those of the original dynamical models.Compared to the simple ensemble results of the three models,the weighted ensemble model showed a stronger capability to capture temperature and precipitation patterns in South China.Therefore,this method has the potential to improve the accuracy of sub-seasonal forecasts in this region.
基金supported by the National Key Research and Development Program of China (Grant No.2022YFF0802004)the Excellent Youth Natural Science Foundation of Jiangsu Province (BK20230061)+1 种基金the Joint Open Project of KLME&CIC-FEMD (Grant No.KLME202501)Jiangsu Innovation Research Group (Grant No.JSSCTD 202346)。
文摘The Zebiak–Cane(ZC) model, renowned as a coupled ocean-atmosphere model specifically designed to simulate and predict El Niño-Southern Oscillation(ENSO), is an indispensable tool for ENSO studies. However, the original ZC model exhibits certain biases in reproducing the ENSO–related sea surface temperature anomalies and heating anomalies, limiting its broader applicability. To improve the accuracy of ENSO simulation, we propose a modified ZC model based on Xie et al.(2015), named the MZC_XJH model, through refining the heating parameterization scheme. The performance in simulating the nonlinear SST–precipitation relationship in the MZC_XJH model is firstly elaborated. Then, we investigate the impacts of three key atmospheric parameters on ENSO simulation by conducting experiments with the MZC_XJH model. Through assessing the performance in simulating five fundamental ENSO metrics(amplitude, periodicity,seasonality, diversity, and skewness), we uncover that the sensitivities of simulated ENSO behaviors to different parameters are distinct. Moreover, we explain why a particular parameter greatly affects some simulated ENSO behaviors while others exert minor influence. We also reveal that the nonlinear effect due to the covariation of multi-parameters on ENSO simulation warrants careful consideration when tuning multi-parameters synchronously. Lastly, we present an updated version of the MZC_XJH model, in which some biases have been mitigated but some remain obvious. Although there are no universally optimal parameters that would ensure flawless performance in simulating every aspect of ENSO, this study provides a valuable reference for tuning atmospheric parameters in the MZC_XJH model, rendering the MZC_XJH model applicable to some research objectives.
基金supported by the China National Science Foundation(No.42130506,42071031)the Special Technology Innovation Fund of Carbon Peak and Carbon Neutrality in Jiangsu Province(BK20231515)+1 种基金the Spanish Government grant PID2022-140808NB-I00 funded by MICIU/AEI/https://doi.org/10.13039/501100011033the Catalan Government grants SGR 2021-1333 and AGAUR2023 CLIMA 00118.
文摘The root-to-shoot(R/S)ratio is a critical indicator of the balance between root biomass and shoot biomass,representing the ecological strategies and adaptive responses of plants to environmental conditions.However,the patterns of change in community R/S ratios during forest succession and their response to moisture levels across broad geographic gradients remains unclear.Based on forest biomass data from a national field inventory of 5,825 plots conducted across China between 2011 and 2015,this study looked into allocating biomass shoots and roots at the early,middle,and late stages of growth in plantations and succession in natural forests,and evaluated how moisture availability influences this allocation.The results revealed a significant decline in R/S ratios from early to late stages for both plantations and natural forests.Shoot and root biomass in plantations grew isometrically during the early and middle succession stages but shifted to allometric growth in the late stage,with the slope of the log-transformed shoot-root biomass relationship differing significantly across growth stages.Natural forests,in contrast,maintained isometric growth across successional stages,showing no significant variation in the slope of the log-transformed shoot-root biomass relationship.Environmental factors,particularly moisture levels,strongly influenced R/S ratios.Moisture levels significantly affected size-corrected R/S ratios,particularly in the middle stage of plantations and the early and middle stages of natural forests,supporting the hypothesis of optimal allocation.These findings suggest that in water-limited regions,forest management should prioritize drought-tolerant,deep-rooted native species,encourage mixed-species planting in the early stage,and reduce logging intensity in mature plantations.Conserving natural forests to maintain successional dynamics is essential for long-term ecological resilience.These findings emphasize the importance of balancing productivity with ecological sustainability by adapting practices to specific environments and forest types under climate change.
基金Supported by the National Natural Science Foundation of China(No.U21A6001)the Guangdong Natural Science Foundation Youth Enhancement Program(No.2024A1515030206)the China Meteorological Administration Climate Change Special Program(No.QBZ202301)。
文摘Both natural and human-induced disturbances affect the normal functioning and services of mangrove ecosystems.To address the consequences of intense human and climatic disturbances on sedimentation and carbon burial,sediment cores from the last remaining mangrove Kandelia obovata forest and an adjacent mudflat in the densely populated and typhoon-prone Zhujiang(Pearl)River estuary of China,were analyzed using methods including^(210)Pb dating andδ^(13)C analysis.Results indicate that after damming in the 1950s,during 1960-1980,the natural establishment of K.obovata forests initiated the insitu sedimentation.As these forests matured during 1980-1990,they significantly boosted siltation in the region on mudflat.During 1990-2015,the invasion of Spartina alterniflora and land reclamation for aquaculture caused infiltration of coarse sediments and the impacts of typhoons were recorded within the K.obovata forest,while no clear typhoon record was observed on the mudflat.Since 2015,reforestation efforts with S.apetala that began in 1999 have reversed the effects of earlier deforestation.Over time,mangroves established a rapid autochthonous carbon burial that grew as the forests age,potentially surpassing the influx of allochthonous carbon due to deforestation.The reforestation also immediately improved carbon burial on the mudflat,which stabilized after a decade due to the rapid growth and high biomass of S.apetala.Overall,the K.obovata forest demonstrated a stronger sedimentation and carbon burial capabilities than the mudflat,with a surplus of 35.2 Mg C/hm^(2)in soil organic carbon stock and 1.0 Mg C/(hm^(2)·a)in burial rate.Organic matter dissolved in soil was mainly humus-like components,and mangrove inputs likely increased the degree of humification.This study offered direct evidence regarding the impact of multiple disturbances on local and regional sedimentation and carbon burial,and future management strategies.
