Based on an analysis of the relationship between the tropical cyclone genesis frequency and large-scale circulation anomaly in NCEP reanalysis, large-scale atmosphere circulation information forecast by the JAMSTEC SI...Based on an analysis of the relationship between the tropical cyclone genesis frequency and large-scale circulation anomaly in NCEP reanalysis, large-scale atmosphere circulation information forecast by the JAMSTEC SINTEX-F coupled model is used to build a statistical model to predict the cyclogenesis frequency over the South China Sea and the western North Pacific. The SINTEX-F coupled model has relatively good prediction skill for some circulation features associated with the cyclogenesis frequency including sea level pressure, wind vertical shear, Intertropical Convergence Zone and cross-equatorial air flows. Predictors derived from these large-scale circulations have good relationships with the cyclogenesis frequency over the South China Sea and the western North Pacific. A multivariate linear regression(MLR) model is further designed using these predictors. This model shows good prediction skill with the anomaly correlation coefficient reaching, based on the cross validation, 0.71 between the observed and predicted cyclogenesis frequency. However, it also shows relatively large prediction errors in extreme tropical cyclone years(1994 and 1998, for example).展开更多
A new nudging scheme is proposed for the operational prediction system of the National Marine Environmental Forecasting Center(NMEFC)of China,mainly aimed at improving El Niño–Southern Oscillation(ENSO)and India...A new nudging scheme is proposed for the operational prediction system of the National Marine Environmental Forecasting Center(NMEFC)of China,mainly aimed at improving El Niño–Southern Oscillation(ENSO)and Indian Ocean Dipole(IOD)predictions.Compared with the origin nudging scheme of NMEFC,the new scheme adds a nudge assimilation for wind components,and increases the nudging weight at the subsurface.Increasing the nudging weight at the subsurface directly improved the simulation performance of the ocean component,while assimilating low-level wind components not only affected the atmospheric component but also benefited the oceanic simulation.Hindcast experiments showed that the new scheme remarkably improved both ENSO and IOD prediction skills.The skillful prediction lead time of ENSO was up to 11 months,1 month longer than a hindcast using the original nudging scheme.Skillful prediction of IOD could be made 4–5 months ahead by the new scheme,with a 0.2 higher correlation at a 3-month lead time.These prediction skills approach the level of some of the best state-of-the-art coupled general circulation models.Improved ENSO and IOD predictions occurred across all seasons,but mainly for target months in the boreal spring for the ENSO and the boreal spring and summer for the IOD.展开更多
The experience of developing a short-term climate prediction system at the Institute of Atmospheric Science of the Chinese Academy of Sciences is summarized,and some problems to be solved in future are discussed in th...The experience of developing a short-term climate prediction system at the Institute of Atmospheric Science of the Chinese Academy of Sciences is summarized,and some problems to be solved in future are discussed in this paper.It is suggested that a good system for short-term climate prediction should at least consist of (1) well-tested model(s),(2) sufficient data and good methods for the initialization and assimilation,(3) a good system for quantitative corrections,(4) a good ensemble prediction method,and (5) appropriate prediction products,such as mathematical expectation,standard deviation,probability,among others.展开更多
The Argo(Array for Real-time Geostrophic Oceanography) data from 1998 to 2003 were used in the Beijing Climate Center-Global Ocean Data Assimilation System(BCC-GODAS). The results show that the utilization of Argo glo...The Argo(Array for Real-time Geostrophic Oceanography) data from 1998 to 2003 were used in the Beijing Climate Center-Global Ocean Data Assimilation System(BCC-GODAS). The results show that the utilization of Argo global ocean data in BCC-GODAS brings about remarkable improvements in assimilation effects. The assimilated sea surface temperature(SST) of BCC-GODAS can well represent the climatological states of observational data. Comparison experiments based on a global coupled atmosphere-ocean general circulation model(AOCGM) were conducted for exploring the roles of ocean data assimilation system with or without Argo data in improving the climate predictability of rainfall in boreal summer. Firstly, the global ocean data assimilation system BCC-GODAS was used to obtain ocean assimilation data under the conditions with or without Argo data. Then, the global coupled atmosphere-ocean general circulation model(AOCGM) was utilized to do hindcast experiments with the two sets of the assimilation data as initial oceanic fields. The simulated results demonstrate that the seasonal predictability of rainfall in boreal summer, particularly in China, increases greatly when initial oceanic conditions with Argo data are utilized. The distribution of summer rainfall in China hindcast by the AOGCM under the condition when Argo data are used is more in accordance with observation than that when no Agro data are used. The area of positive correlation between hindcast and observation enlarges and the hindcast skill of rainfall over China in summer improves significantly when Argo data are used.展开更多
By consulting the typhoon yearbook and restoring the historical weather chart,technical separation of typhoon precipitation in Yongzhou from July to September of 1981-2015 was conducted.On this basis,climatic characte...By consulting the typhoon yearbook and restoring the historical weather chart,technical separation of typhoon precipitation in Yongzhou from July to September of 1981-2015 was conducted.On this basis,climatic characteristics of typhoon precipitation in midsummer of Yongzhou were analyzed,and climate prediction and diagnostic analysis were carried out.The research results showed that typhoon precipitation was an important component of midsummer precipitation in Yongzhou,but its contribution to total precipitation was not as much as precipitation of the westerly belt system.When the ridge line of the western Pacific subtropical high was northward,typhoon precipitation was more than westerly precipitation in midsummer of Yongzhou;when the subtropical high was southward,there were more patterns of westerly precipitation year;when the subtropical high was normally northward,typhoon precipitation and westerly precipitation were less,with more dry years.In summer,abnormal cold sea surface temperature(SST)in tidal zone and warm pool zone of western Pacific and abnormal warm SST in NinoZ zone(strong El Nino event)were favorable for that the ridge line of the western Pacific subtropical high was southward,and there were more patterns of westerly precipitation year in midsummer of Yongzhou.On the contrary,when subtropical high was northward or normally northerly,there was less westerly precipitation.In non La Nina years when the subtropical high was northward,most of them were typhoon precipitation years.In La Nina years when the subtropical high was northward,most of them were dry years.展开更多
The meridional gradient of surface air temperature associated with“Warm Arctic–Cold Eurasia”(GradTAE)is closely related to climate anomalies and weather extremes in the mid-low latitudes.However,the Climate Forecas...The meridional gradient of surface air temperature associated with“Warm Arctic–Cold Eurasia”(GradTAE)is closely related to climate anomalies and weather extremes in the mid-low latitudes.However,the Climate Forecast System Version 2(CFSv2)shows poor capability for GradTAE prediction.Based on the year-to-year increment approach,analysis using a hybrid seasonal prediction model for GradTAE in winter(HMAE)is conducted with observed September sea ice over the Barents–Kara Sea,October sea surface temperature over the North Atlantic,September soil moisture in southern North America,and CFSv2 forecasted winter sea ice over the Baffin Bay,Davis Strait,and Labrador Sea.HMAE demonstrates good capability for predicting GradTAE with a significant correlation coefficient of 0.84,and the percentage of the same sign is 88%in cross-validation during 1983−2015.HMAE also maintains high accuracy and robustness during independent predictions of 2016−20.Meanwhile,HMAE can predict the GradTAE in 2021 well as an experiment of routine operation.Moreover,well-predicted GradTAE is useful in the prediction of the large-scale pattern of“Warm Arctic–Cold Eurasia”and has potential to enhance the skill of surface air temperature occurrences in the east of China.展开更多
Machine learning methods are effective tools for improving short-term climate prediction.However,commonly used methods often carry out classification and regression prediction modeling separately and independently.Suc...Machine learning methods are effective tools for improving short-term climate prediction.However,commonly used methods often carry out classification and regression prediction modeling separately and independently.Such a single modeling approach may obtain inconsistent prediction results in classification and regression and thus may not meet the needs of practical applications well.To address this issue,this study proposes a selective Naive Bayes ensemble model(SENB-EM)by introducing causal effect and voting strategy on Naive Bayes.The new model can not only screen effective predictors but also perform classification and regression prediction simultaneously.After being applied to the area prediction of summer western North Pacific subtropical high(WNPSH)from 2008 to 2021,it is found that the accuracy classification score(a metric to assess the overall classification prediction accuracy)and the time correlation coefficient(TCC)of SENB-EM can reach 1.0 and 0.81,respectively.After integrating the results of different models[including multiple linear regression ensemble model(MLR-EM),SENB-EM,and Chinese Multimodel Ensemble Prediction System(CMME)used by National Climate Center(NCC)]for 2017-2021,the TCC of the ensemble results of SENB-EM and CMME can reach 0.92(the highest result among them).This indicates that the prediction results of the summer WNPSH area provided by SENB-EM have a high reference value for the real-time prediction.It is worth noting that,except for the numerical prediction results,the SENB-EM model can also give the range of numerical prediction intervals and predictions for anomalous degrees of the WNPSH area,thus providing more reference information for meteorological forecasters.Overall,as a new hybrid machine learning model,the SENB-EM has a good prediction ability;the approach of performing classification prediction and regression prediction simultaneously through integration is informative to short-term climate prediction.展开更多
This study investigates the possible causes for the precipitation of Guangdong during dragon-boat rain period(DBRP) in 2022 that is remarkably more than the climate state and reviews the successes and failures of the ...This study investigates the possible causes for the precipitation of Guangdong during dragon-boat rain period(DBRP) in 2022 that is remarkably more than the climate state and reviews the successes and failures of the prediction in2022. Features of atmospheric circulation and sea surface temperature(SST) are analyzed based on several observational datasets for nearly 60 years from meteorological stations and the NCEP/NCAR Global Reanalysis Data. Results show that fluctuation of the 200-h Pa westerly wind as well as the westerly jet is strengthened due to the propagation of wave energy, leading to strong updraft over southern China. Activities of a subtropical high and a shear line provide favorable conditions for the transport of moisture to Guangdong. With the support of powerful southwest winds, extreme precipitation is induced. ENSO is a good indicator of atmospheric circulation at mid-and high-levels during the DBRP in2022 but it performs badly at low levels. During recent years, the influence of ENSO on precipitation during the DBRP has decreased obviously. The SSTA of tropical southeast Atlantic(SEA) in spring may become the key indicator. During the years with warm SEA, wave trains propagate from northwest to southeast over Eurasia with energy enhancing the westerly jet, conducive to updraft over southern China and the occurrence of heavy precipitation. Meanwhile, the Rossby wave is triggered over Maritime Continent by heat sources of southern Atlantic-western Indian Ocean through the Gill response. Thus, strong transport of moisture and heavy rainfall occur.展开更多
In order to explore the climate change in the Dawen River basin,based on the data of six weather stations in the Dawen River basin from 1966 to 2017,Mann-Kendall test and wavelet analysis were used to study the temper...In order to explore the climate change in the Dawen River basin,based on the data of six weather stations in the Dawen River basin from 1966 to 2017,Mann-Kendall test and wavelet analysis were used to study the temperature and precipitation trends,mutations and cycles in the region.In addition,based on the three scenarios of RCP2.6,RCP4.5,and RCP8.5 under the CanESM2 model,SDSM was used to compare and analyze the future climate change of the Dawen River basin.The results revealed that:the annual mean temperature of the Dawen River basin had increased significantly since 1966(p<0.01);in different scenarios,the spatial distribution of the projected maximum temperature,minimum temperature and precipitation will hardly change compared with that in history;the temperature and precipitation in the Dawen River basin will generally increase in the future.The rising trend of maximum and minimum temperature under the three scenarios is in the EP<MP<LP,and June and November was the months with the highest increase;the future precipitation will have the highest increase in July and August.Under the RCP4.5 and RCP8.5 scenarios,the annual maximum and minimum temperatures in the future will increase with the increase in time scale.展开更多
According to the abundant studies,the relevant information and comprehensive analysis of the climate changes,several important problems on the climate changes and its studies were proposed.Based on the temporal distri...According to the abundant studies,the relevant information and comprehensive analysis of the climate changes,several important problems on the climate changes and its studies were proposed.Based on the temporal distribution of the meteorological disaster of agriculture,the wave theory was expounded so as to draw people's attention on climate changes and to be objective,just and careful about the study.展开更多
This brief review described spatial-time climate patterns generated by the dynamics and thermodynamics of the Earth’s climate system and methods of identifying these patterns. Specifically, it does discuss the follow...This brief review described spatial-time climate patterns generated by the dynamics and thermodynamics of the Earth’s climate system and methods of identifying these patterns. Specifically, it does discuss the following major climate patterns: El Ni?o-Southern Oscillation (ENSO), Cold Ocean-Warm Land (COWL) pattern, Northern and Southern Annular Patterns (NAM and SAM), Atlantic Multidecadal Oscillation (AMO) and Atlantic Meridional Overturning Circulation (AMOC), Pacific North-American Pattern (PNA) and Pacific Decadal Oscillation Pattern (PDO). In view of an extensive number of publications on some climate patterns, such as the ENSO, which discussed in many hundred of publications, this review is not intended to cover all the details of individual climate patterns but intends only to give a general overview of their structure, mechanisms of their formation and response to external forcing. It is assumed that the climate patterns can be treated as attractors of dynamical systems allowing us to extract and predict some specific features of the patterns such as the origin and evolution of the climate patterns and their role in climate change. Thus the knowledge of patterns allows the climate prediction on long time scales and understanding of how an external forcing affects the frequency of occurrence of climate patterns and their magnitude but not the spatial structure.展开更多
Current dynamical models experience great difficulties providing reliable seasonal forecasts of regional/local rainfall in South China.This study evaluates seasonal forecast skill for precipitation in the first rainy ...Current dynamical models experience great difficulties providing reliable seasonal forecasts of regional/local rainfall in South China.This study evaluates seasonal forecast skill for precipitation in the first rainy season(FRS,i.e.,April–June)over South China from 1982 to 2020 based on the global real-time Climate Forecast System of Nanjing University of Information Science and Technology(NUIST-CFS1.0,previously known as SINTEX-F).The potential predictability and the practical forecast skill of NUIST-CFS1.0 for FRS precipitation remain low in general.But NUIST-CFS1.0 still performs better than the average of nine international models in terms of correlation coefficient skill in predicting the interannual precipitation anomaly and its related circulation index.NUIST-CFS1.0 captures the anomalous Philippines anticyclone,which transports moisture and heat northward to South China,favoring more precipitation in South China during the FRS.By examining the correlations between sea surface temperature(SST)and FRS precipitation and the Philippines anticyclone,we find that the model reasonably captures SST-associated precipitation and circulation anomalies,which partly explains the predictability of FRS precipitation.A dynamical downscaling model with 30-km resolution forced by the large-scale circulations of the NUIST-CFS1.0 predictions could improve forecasts of the climatological states and extreme precipitation events.Our results also reveal interesting interdecadal changes in the predictive skill for FRS precipitation in South China based on the NUIST-CFS1.0 hindcasts.These results help improve the understanding and forecasts for FRS precipitation in South China.展开更多
Most real-world time series have some degree of nonstationarity due to external perturbations of the observed system; external driving forces are the essential reason that leads to the nonstationarity of dynamics syst...Most real-world time series have some degree of nonstationarity due to external perturbations of the observed system; external driving forces are the essential reason that leads to the nonstationarity of dynamics system. In this paper, the authors present a novel technique in which the authors incorporate external forces to predict nonstationary time series. To test the effect, the authors also examined two prediction experiments with an ideal time series from a logistic map and a proxy climate dataset for the past millennium. The preliminary results show that the resulting algorithm has better predictive ability than the one that does not consider the external forces.展开更多
The regional climate model(RegCM3), developed by the Abdus Salam International Centre for Theoretical Physics and nested in one-way mode within the latest version of Community Climate System Model from the National Ce...The regional climate model(RegCM3), developed by the Abdus Salam International Centre for Theoretical Physics and nested in one-way mode within the latest version of Community Climate System Model from the National Center for Atmospheric Research, is used to conduct a set of experiments to examine its capability of climate simulation for the past 50 years and to explore possible changes in extreme precipitation(EP) in the next 100 years under the A1 B scenario. Compared with the observation from the Climate Research Unit at the University of East Anglia and CPC Merged Analysis of Precipitation, RegCM3 reasonably reproduces the spatiotemporal distributions of precipitation and EP in eastern China. Based on the present-day analysis, this study examines the changes in monsoonal precipitation over eastern China in mid- and late-21st century relative to the reference period of 1970-1999. It is found that the precipitation will increase over the middle and lower reaches of the Yangtze River and areas to its north, and decrease over coastal areas to its south, especially in late-21st century. The various indices reflecting extreme events showed that the EP will enhance 10%-15% over the middle and lower reaches of the Yangtze River and areas to its north, and weaken over the areas to its south. The summer monsoon will strengthen and shift northwards under SERS A1 B, bringing more water vapor and energy from the Indian Ocean and South China Sea for precipitation and eventually more precipitation over northern China.展开更多
Subsurface mooring allows researchers to measure the ocean properties such as water temperature,salinity,and velocity at several depths of the water column for a long period.Traditional subsurface mooring can release ...Subsurface mooring allows researchers to measure the ocean properties such as water temperature,salinity,and velocity at several depths of the water column for a long period.Traditional subsurface mooring can release data only after recovered,which constrains the usage of the subsurface and deep layer data in the ocean and climate predictions.Recently,we developed a new real-time subsurface mooring(RTSM).Velocity profiles over upper 1000 m depth and layered data from sensors up to 5000 m depth can be realtime transmitted to the small surface buoy through underwater acoustic communication and then to the office through Beidou or Iridium satellite.To verify and refine their design and data transmission process,we deployed more than 30 sets of RTSMs in the western Pacific to do a 1-year continuous run during 2016–2018.The continuous running period of RTSM in a 1-year cycle can reach more than 260 days on average,and more than 95%of observed data can be successfully transmitted back to the office.Compared to the widely-used inductive coupling communication,wireless acoustic communication has been shown more applicable to the underwater sensor network with large depth intervals and long transmission distance to the surface.展开更多
Climate variability modes, usually known as primary climate phenomena, are well recognized as the most important predictability sources in subseasonal–interannual climate prediction. This paper begins by reviewing th...Climate variability modes, usually known as primary climate phenomena, are well recognized as the most important predictability sources in subseasonal–interannual climate prediction. This paper begins by reviewing the research 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 Ni?o–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 experiment for the period 1991–2014. The performance of the CPPS in predicting such climate variability modes is systematically 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. Improvements 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 efficiencies and effectiveness of water resource management are inextricably linked to climate services. This study demonstrates a climate information service for Danjiangkou Reservoir, which is the largest artifi...The efficiencies and effectiveness of water resource management are inextricably linked to climate services. This study demonstrates a climate information service for Danjiangkou Reservoir, which is the largest artificial lake in Asia, facing mounting challenges for flood control, water storage, and water diversion. Unlike traditional water resource management on the basis of short-term weather forecast and runoff monitoring, subseasonal to seasonal(S2S)and annual climate predictions as well as long-term climate change projections were well used to support the decision makers in Danjiangkou Reservoir. The National Climate Center(NCC) has projected the changes of future climate and extreme events by dynamically downscaling the Coupled Model Intercomparison Project phase 5(CMIP5)projections to 25-km resolution for the long-term planning of water resource management in Danjiangkou Reservoir.Real-time climate predictions based on climate models and downscaling interpretation and application methods at different timescales were also provided to meet the specific needs of earlier predictions and spatial refinement for the short-term diversion of the reservoir. Our results show that such climate services facilitated the Diversion Center of Danjiangkou Reservoir(DCDR) to reasonably control the operational water level, increased the ecological water supply to the northern portion of China by 844 million m^(3), and reduced as much as 1.67 billion m^(3) of abandoned water in 2019. In the future, it is necessary to develop climate prediction methods to increase spatial and temporal resolutions and prediction skills, and enhance interactions between providers and users.展开更多
Subseasonal to seasonal(S2S)variability represents the atmospheric disturbance on the 10–90-day timescale,which is an important bridge linking weather and climate.In 2015,China Meteorological Administration(CMA)liste...Subseasonal to seasonal(S2S)variability represents the atmospheric disturbance on the 10–90-day timescale,which is an important bridge linking weather and climate.In 2015,China Meteorological Administration(CMA)listed the S2S prediction project that was initiated by WMO programs three years ago as one of its key tasks.After five years of research,significant progress has been made on the mechanisms of the East Asian monsoon(EAM)S2S variability,related impact of climate change,as well as the predictability on the S2S timescale of numerical models.The S2S variability of the EAM is closely linked to extreme persistent climate events in China and is an important target for seasonal climate prediction.However,under the influence of global warming and the interactions among climate systems,the S2S variability of the EAM is so complex that its prediction remains a great challenge.This paper reviews the past achievement and summarizes the recent progress in research of the EAM S2S variability and prediction,including characteristics of the main S2S modes of the EAM,their impact on the extreme events in China,effects of external and internal forcing on the S2S variability,as well as uncertainties of climate models in predicting the S2S variability,with a focus on the progress achieved by the S2S research team of the Chinese Academy of Meteorological Sciences.The present bottlenecks,future directions,and critical research recommendations are also analyzed and presented.展开更多
基金Specialized Science and Technology Project for Public Welfare Industry(GYHY200906015)National Basic Research Program of China(973 Program,2010CB428606)Key Technologies R&D Program of China(2009BAC51B05)
文摘Based on an analysis of the relationship between the tropical cyclone genesis frequency and large-scale circulation anomaly in NCEP reanalysis, large-scale atmosphere circulation information forecast by the JAMSTEC SINTEX-F coupled model is used to build a statistical model to predict the cyclogenesis frequency over the South China Sea and the western North Pacific. The SINTEX-F coupled model has relatively good prediction skill for some circulation features associated with the cyclogenesis frequency including sea level pressure, wind vertical shear, Intertropical Convergence Zone and cross-equatorial air flows. Predictors derived from these large-scale circulations have good relationships with the cyclogenesis frequency over the South China Sea and the western North Pacific. A multivariate linear regression(MLR) model is further designed using these predictors. This model shows good prediction skill with the anomaly correlation coefficient reaching, based on the cross validation, 0.71 between the observed and predicted cyclogenesis frequency. However, it also shows relatively large prediction errors in extreme tropical cyclone years(1994 and 1998, for example).
基金The National Natural Science Foundation of China under contract No.41690124the Scientific Research Fund of the Second Institute of Oceanography,Ministry of Natural Resources under contract No.JG2007+1 种基金the National Natural Science Foundation of China under contract Nos 42006034,41690120 and 41530961the Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)under contract No.311021009.
文摘A new nudging scheme is proposed for the operational prediction system of the National Marine Environmental Forecasting Center(NMEFC)of China,mainly aimed at improving El Niño–Southern Oscillation(ENSO)and Indian Ocean Dipole(IOD)predictions.Compared with the origin nudging scheme of NMEFC,the new scheme adds a nudge assimilation for wind components,and increases the nudging weight at the subsurface.Increasing the nudging weight at the subsurface directly improved the simulation performance of the ocean component,while assimilating low-level wind components not only affected the atmospheric component but also benefited the oceanic simulation.Hindcast experiments showed that the new scheme remarkably improved both ENSO and IOD prediction skills.The skillful prediction lead time of ENSO was up to 11 months,1 month longer than a hindcast using the original nudging scheme.Skillful prediction of IOD could be made 4–5 months ahead by the new scheme,with a 0.2 higher correlation at a 3-month lead time.These prediction skills approach the level of some of the best state-of-the-art coupled general circulation models.Improved ENSO and IOD predictions occurred across all seasons,but mainly for target months in the boreal spring for the ENSO and the boreal spring and summer for the IOD.
文摘The experience of developing a short-term climate prediction system at the Institute of Atmospheric Science of the Chinese Academy of Sciences is summarized,and some problems to be solved in future are discussed in this paper.It is suggested that a good system for short-term climate prediction should at least consist of (1) well-tested model(s),(2) sufficient data and good methods for the initialization and assimilation,(3) a good system for quantitative corrections,(4) a good ensemble prediction method,and (5) appropriate prediction products,such as mathematical expectation,standard deviation,probability,among others.
基金National Program on Key Basic Research Project of China(2012CB955203,2013CB430202)National Natural Science Foundation of China(40231014,41175065)+1 种基金China Meteorological Administration R&D Special Fund for Public Welfare(meteorology)(GYHY201306021)National High Technology Research and Development Program of China(2010AA012404)
文摘The Argo(Array for Real-time Geostrophic Oceanography) data from 1998 to 2003 were used in the Beijing Climate Center-Global Ocean Data Assimilation System(BCC-GODAS). The results show that the utilization of Argo global ocean data in BCC-GODAS brings about remarkable improvements in assimilation effects. The assimilated sea surface temperature(SST) of BCC-GODAS can well represent the climatological states of observational data. Comparison experiments based on a global coupled atmosphere-ocean general circulation model(AOCGM) were conducted for exploring the roles of ocean data assimilation system with or without Argo data in improving the climate predictability of rainfall in boreal summer. Firstly, the global ocean data assimilation system BCC-GODAS was used to obtain ocean assimilation data under the conditions with or without Argo data. Then, the global coupled atmosphere-ocean general circulation model(AOCGM) was utilized to do hindcast experiments with the two sets of the assimilation data as initial oceanic fields. The simulated results demonstrate that the seasonal predictability of rainfall in boreal summer, particularly in China, increases greatly when initial oceanic conditions with Argo data are utilized. The distribution of summer rainfall in China hindcast by the AOGCM under the condition when Argo data are used is more in accordance with observation than that when no Agro data are used. The area of positive correlation between hindcast and observation enlarges and the hindcast skill of rainfall over China in summer improves significantly when Argo data are used.
文摘By consulting the typhoon yearbook and restoring the historical weather chart,technical separation of typhoon precipitation in Yongzhou from July to September of 1981-2015 was conducted.On this basis,climatic characteristics of typhoon precipitation in midsummer of Yongzhou were analyzed,and climate prediction and diagnostic analysis were carried out.The research results showed that typhoon precipitation was an important component of midsummer precipitation in Yongzhou,but its contribution to total precipitation was not as much as precipitation of the westerly belt system.When the ridge line of the western Pacific subtropical high was northward,typhoon precipitation was more than westerly precipitation in midsummer of Yongzhou;when the subtropical high was southward,there were more patterns of westerly precipitation year;when the subtropical high was normally northward,typhoon precipitation and westerly precipitation were less,with more dry years.In summer,abnormal cold sea surface temperature(SST)in tidal zone and warm pool zone of western Pacific and abnormal warm SST in NinoZ zone(strong El Nino event)were favorable for that the ridge line of the western Pacific subtropical high was southward,and there were more patterns of westerly precipitation year in midsummer of Yongzhou.On the contrary,when subtropical high was northward or normally northerly,there was less westerly precipitation.In non La Nina years when the subtropical high was northward,most of them were typhoon precipitation years.In La Nina years when the subtropical high was northward,most of them were dry years.
基金This research is supported by the National Key R&D Program of China(Grant No.2022YFF0801604).
文摘The meridional gradient of surface air temperature associated with“Warm Arctic–Cold Eurasia”(GradTAE)is closely related to climate anomalies and weather extremes in the mid-low latitudes.However,the Climate Forecast System Version 2(CFSv2)shows poor capability for GradTAE prediction.Based on the year-to-year increment approach,analysis using a hybrid seasonal prediction model for GradTAE in winter(HMAE)is conducted with observed September sea ice over the Barents–Kara Sea,October sea surface temperature over the North Atlantic,September soil moisture in southern North America,and CFSv2 forecasted winter sea ice over the Baffin Bay,Davis Strait,and Labrador Sea.HMAE demonstrates good capability for predicting GradTAE with a significant correlation coefficient of 0.84,and the percentage of the same sign is 88%in cross-validation during 1983−2015.HMAE also maintains high accuracy and robustness during independent predictions of 2016−20.Meanwhile,HMAE can predict the GradTAE in 2021 well as an experiment of routine operation.Moreover,well-predicted GradTAE is useful in the prediction of the large-scale pattern of“Warm Arctic–Cold Eurasia”and has potential to enhance the skill of surface air temperature occurrences in the east of China.
基金Supported by the National Natural Science Foundation of China (42130610,41975076,and 42175067)National Key Research and Development Program of China (2019YFA0607104)。
文摘Machine learning methods are effective tools for improving short-term climate prediction.However,commonly used methods often carry out classification and regression prediction modeling separately and independently.Such a single modeling approach may obtain inconsistent prediction results in classification and regression and thus may not meet the needs of practical applications well.To address this issue,this study proposes a selective Naive Bayes ensemble model(SENB-EM)by introducing causal effect and voting strategy on Naive Bayes.The new model can not only screen effective predictors but also perform classification and regression prediction simultaneously.After being applied to the area prediction of summer western North Pacific subtropical high(WNPSH)from 2008 to 2021,it is found that the accuracy classification score(a metric to assess the overall classification prediction accuracy)and the time correlation coefficient(TCC)of SENB-EM can reach 1.0 and 0.81,respectively.After integrating the results of different models[including multiple linear regression ensemble model(MLR-EM),SENB-EM,and Chinese Multimodel Ensemble Prediction System(CMME)used by National Climate Center(NCC)]for 2017-2021,the TCC of the ensemble results of SENB-EM and CMME can reach 0.92(the highest result among them).This indicates that the prediction results of the summer WNPSH area provided by SENB-EM have a high reference value for the real-time prediction.It is worth noting that,except for the numerical prediction results,the SENB-EM model can also give the range of numerical prediction intervals and predictions for anomalous degrees of the WNPSH area,thus providing more reference information for meteorological forecasters.Overall,as a new hybrid machine learning model,the SENB-EM has a good prediction ability;the approach of performing classification prediction and regression prediction simultaneously through integration is informative to short-term climate prediction.
基金National Natural Science Foundation of China Meteorological Joint Fund(U2142205)National Key Research and Development Program of China(2018YFA0606203)+2 种基金Guangdong Major Project of Basic and Applied Basic Research(2020B0301030004)Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies(2020B1212060025)Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(311021001)。
文摘This study investigates the possible causes for the precipitation of Guangdong during dragon-boat rain period(DBRP) in 2022 that is remarkably more than the climate state and reviews the successes and failures of the prediction in2022. Features of atmospheric circulation and sea surface temperature(SST) are analyzed based on several observational datasets for nearly 60 years from meteorological stations and the NCEP/NCAR Global Reanalysis Data. Results show that fluctuation of the 200-h Pa westerly wind as well as the westerly jet is strengthened due to the propagation of wave energy, leading to strong updraft over southern China. Activities of a subtropical high and a shear line provide favorable conditions for the transport of moisture to Guangdong. With the support of powerful southwest winds, extreme precipitation is induced. ENSO is a good indicator of atmospheric circulation at mid-and high-levels during the DBRP in2022 but it performs badly at low levels. During recent years, the influence of ENSO on precipitation during the DBRP has decreased obviously. The SSTA of tropical southeast Atlantic(SEA) in spring may become the key indicator. During the years with warm SEA, wave trains propagate from northwest to southeast over Eurasia with energy enhancing the westerly jet, conducive to updraft over southern China and the occurrence of heavy precipitation. Meanwhile, the Rossby wave is triggered over Maritime Continent by heat sources of southern Atlantic-western Indian Ocean through the Gill response. Thus, strong transport of moisture and heavy rainfall occur.
基金National Natural Science Foundation of China(41471160)。
文摘In order to explore the climate change in the Dawen River basin,based on the data of six weather stations in the Dawen River basin from 1966 to 2017,Mann-Kendall test and wavelet analysis were used to study the temperature and precipitation trends,mutations and cycles in the region.In addition,based on the three scenarios of RCP2.6,RCP4.5,and RCP8.5 under the CanESM2 model,SDSM was used to compare and analyze the future climate change of the Dawen River basin.The results revealed that:the annual mean temperature of the Dawen River basin had increased significantly since 1966(p<0.01);in different scenarios,the spatial distribution of the projected maximum temperature,minimum temperature and precipitation will hardly change compared with that in history;the temperature and precipitation in the Dawen River basin will generally increase in the future.The rising trend of maximum and minimum temperature under the three scenarios is in the EP<MP<LP,and June and November was the months with the highest increase;the future precipitation will have the highest increase in July and August.Under the RCP4.5 and RCP8.5 scenarios,the annual maximum and minimum temperatures in the future will increase with the increase in time scale.
文摘According to the abundant studies,the relevant information and comprehensive analysis of the climate changes,several important problems on the climate changes and its studies were proposed.Based on the temporal distribution of the meteorological disaster of agriculture,the wave theory was expounded so as to draw people's attention on climate changes and to be objective,just and careful about the study.
文摘This brief review described spatial-time climate patterns generated by the dynamics and thermodynamics of the Earth’s climate system and methods of identifying these patterns. Specifically, it does discuss the following major climate patterns: El Ni?o-Southern Oscillation (ENSO), Cold Ocean-Warm Land (COWL) pattern, Northern and Southern Annular Patterns (NAM and SAM), Atlantic Multidecadal Oscillation (AMO) and Atlantic Meridional Overturning Circulation (AMOC), Pacific North-American Pattern (PNA) and Pacific Decadal Oscillation Pattern (PDO). In view of an extensive number of publications on some climate patterns, such as the ENSO, which discussed in many hundred of publications, this review is not intended to cover all the details of individual climate patterns but intends only to give a general overview of their structure, mechanisms of their formation and response to external forcing. It is assumed that the climate patterns can be treated as attractors of dynamical systems allowing us to extract and predict some specific features of the patterns such as the origin and evolution of the climate patterns and their role in climate change. Thus the knowledge of patterns allows the climate prediction on long time scales and understanding of how an external forcing affects the frequency of occurrence of climate patterns and their magnitude but not the spatial structure.
基金supported by National Natural Science Foundation of China(Grant Nos.42088101 and 42030605)National Key R&D Program of China(Grant No.2020YFA0608000)。
文摘Current dynamical models experience great difficulties providing reliable seasonal forecasts of regional/local rainfall in South China.This study evaluates seasonal forecast skill for precipitation in the first rainy season(FRS,i.e.,April–June)over South China from 1982 to 2020 based on the global real-time Climate Forecast System of Nanjing University of Information Science and Technology(NUIST-CFS1.0,previously known as SINTEX-F).The potential predictability and the practical forecast skill of NUIST-CFS1.0 for FRS precipitation remain low in general.But NUIST-CFS1.0 still performs better than the average of nine international models in terms of correlation coefficient skill in predicting the interannual precipitation anomaly and its related circulation index.NUIST-CFS1.0 captures the anomalous Philippines anticyclone,which transports moisture and heat northward to South China,favoring more precipitation in South China during the FRS.By examining the correlations between sea surface temperature(SST)and FRS precipitation and the Philippines anticyclone,we find that the model reasonably captures SST-associated precipitation and circulation anomalies,which partly explains the predictability of FRS precipitation.A dynamical downscaling model with 30-km resolution forced by the large-scale circulations of the NUIST-CFS1.0 predictions could improve forecasts of the climatological states and extreme precipitation events.Our results also reveal interesting interdecadal changes in the predictive skill for FRS precipitation in South China based on the NUIST-CFS1.0 hindcasts.These results help improve the understanding and forecasts for FRS precipitation in South China.
基金supported by the National Natural Science Foundation of China (Grant Nos. 40940023, 41075061 and 40890052)
文摘Most real-world time series have some degree of nonstationarity due to external perturbations of the observed system; external driving forces are the essential reason that leads to the nonstationarity of dynamics system. In this paper, the authors present a novel technique in which the authors incorporate external forces to predict nonstationary time series. To test the effect, the authors also examined two prediction experiments with an ideal time series from a logistic map and a proxy climate dataset for the past millennium. The preliminary results show that the resulting algorithm has better predictive ability than the one that does not consider the external forces.
基金Strategic Priority Research Program of the Chinese Academy of Sciences(XDB03020601)National Basic Research Program of China(2010CB833406)National Science Foundation of China(41290255)
文摘The regional climate model(RegCM3), developed by the Abdus Salam International Centre for Theoretical Physics and nested in one-way mode within the latest version of Community Climate System Model from the National Center for Atmospheric Research, is used to conduct a set of experiments to examine its capability of climate simulation for the past 50 years and to explore possible changes in extreme precipitation(EP) in the next 100 years under the A1 B scenario. Compared with the observation from the Climate Research Unit at the University of East Anglia and CPC Merged Analysis of Precipitation, RegCM3 reasonably reproduces the spatiotemporal distributions of precipitation and EP in eastern China. Based on the present-day analysis, this study examines the changes in monsoonal precipitation over eastern China in mid- and late-21st century relative to the reference period of 1970-1999. It is found that the precipitation will increase over the middle and lower reaches of the Yangtze River and areas to its north, and decrease over coastal areas to its south, especially in late-21st century. The various indices reflecting extreme events showed that the EP will enhance 10%-15% over the middle and lower reaches of the Yangtze River and areas to its north, and weaken over the areas to its south. The summer monsoon will strengthen and shift northwards under SERS A1 B, bringing more water vapor and energy from the Indian Ocean and South China Sea for precipitation and eventually more precipitation over northern China.
基金the Wenhai Program(No.SQ2017WHZZB0502)the Scientific and Technological Innovation Project(Nos.2016ASKJ12,2017ASKJ01)+2 种基金the Marine S&T Fund of Shandong Province(No.2018SDKJ0101)of Pilot National Laboratory for Marine Science and Technology(Qingdao)the Scientific Instrument Developing Project of the Chinese Academy of Sciences(Nos.YJKYYQ20170038,YJKYYQ20180057)the National Program on Global Change and Air-Sea Interaction(No.GASI-IPOVAI-01-01)。
文摘Subsurface mooring allows researchers to measure the ocean properties such as water temperature,salinity,and velocity at several depths of the water column for a long period.Traditional subsurface mooring can release data only after recovered,which constrains the usage of the subsurface and deep layer data in the ocean and climate predictions.Recently,we developed a new real-time subsurface mooring(RTSM).Velocity profiles over upper 1000 m depth and layered data from sensors up to 5000 m depth can be realtime transmitted to the small surface buoy through underwater acoustic communication and then to the office through Beidou or Iridium satellite.To verify and refine their design and data transmission process,we deployed more than 30 sets of RTSMs in the western Pacific to do a 1-year continuous run during 2016–2018.The continuous running period of RTSM in a 1-year cycle can reach more than 260 days on average,and more than 95%of observed data can be successfully transmitted back to the office.Compared to the widely-used inductive coupling communication,wireless acoustic communication has been shown more applicable to the underwater sensor network with large depth intervals and long transmission distance to the surface.
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 important predictability sources in subseasonal–interannual climate prediction. This paper begins by reviewing the research 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 Ni?o–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 experiment for the period 1991–2014. The performance of the CPPS in predicting such climate variability modes is systematically 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. Improvements 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 National Key Research and Development Program of China (2018YFA0606302)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The efficiencies and effectiveness of water resource management are inextricably linked to climate services. This study demonstrates a climate information service for Danjiangkou Reservoir, which is the largest artificial lake in Asia, facing mounting challenges for flood control, water storage, and water diversion. Unlike traditional water resource management on the basis of short-term weather forecast and runoff monitoring, subseasonal to seasonal(S2S)and annual climate predictions as well as long-term climate change projections were well used to support the decision makers in Danjiangkou Reservoir. The National Climate Center(NCC) has projected the changes of future climate and extreme events by dynamically downscaling the Coupled Model Intercomparison Project phase 5(CMIP5)projections to 25-km resolution for the long-term planning of water resource management in Danjiangkou Reservoir.Real-time climate predictions based on climate models and downscaling interpretation and application methods at different timescales were also provided to meet the specific needs of earlier predictions and spatial refinement for the short-term diversion of the reservoir. Our results show that such climate services facilitated the Diversion Center of Danjiangkou Reservoir(DCDR) to reasonably control the operational water level, increased the ecological water supply to the northern portion of China by 844 million m^(3), and reduced as much as 1.67 billion m^(3) of abandoned water in 2019. In the future, it is necessary to develop climate prediction methods to increase spatial and temporal resolutions and prediction skills, and enhance interactions between providers and users.
基金Supported by the National Natural Science Foundation of China(41830969)the Second Tibetan Plateau Scientific Expedition and Research(STEP)Program(2019QZKK0105)+2 种基金National Natural Science Foundation of China(42005131)Basic Scientific Research and Operation Fund of the Chinese Academy of Meteorological Sciences(CAMS)(2021Z004)Science and Technology Development Fund of CAMS(2020KJ009 and 2020KJ012)。
文摘Subseasonal to seasonal(S2S)variability represents the atmospheric disturbance on the 10–90-day timescale,which is an important bridge linking weather and climate.In 2015,China Meteorological Administration(CMA)listed the S2S prediction project that was initiated by WMO programs three years ago as one of its key tasks.After five years of research,significant progress has been made on the mechanisms of the East Asian monsoon(EAM)S2S variability,related impact of climate change,as well as the predictability on the S2S timescale of numerical models.The S2S variability of the EAM is closely linked to extreme persistent climate events in China and is an important target for seasonal climate prediction.However,under the influence of global warming and the interactions among climate systems,the S2S variability of the EAM is so complex that its prediction remains a great challenge.This paper reviews the past achievement and summarizes the recent progress in research of the EAM S2S variability and prediction,including characteristics of the main S2S modes of the EAM,their impact on the extreme events in China,effects of external and internal forcing on the S2S variability,as well as uncertainties of climate models in predicting the S2S variability,with a focus on the progress achieved by the S2S research team of the Chinese Academy of Meteorological Sciences.The present bottlenecks,future directions,and critical research recommendations are also analyzed and presented.
