Possible changes in the structure and seasonal variability of the subtropical ridge may lead to changes in the rainfall’s variability modes over Caribbean region. This generates additional difficulties around water r...Possible changes in the structure and seasonal variability of the subtropical ridge may lead to changes in the rainfall’s variability modes over Caribbean region. This generates additional difficulties around water resource planning, therefore, obtaining seasonal prediction models that allow these variations to be characterized in detail, it’s a concern, specially for island states. This research proposes the construction of statistical-dynamic models based on PCA regression methods. It is used as predictand the monthly precipitation accumulated, while the predictors (6) are extracted from the ECMWF-SEAS5 ensemble mean forecasts with a lag of one month with respect to the target month. In the construction of the models, two sequential training schemes are evaluated, obtaining that only the shorter preserves the seasonal characteristics of the predictand. The evaluation metrics used, where cell-point and dichotomous methodologies are combined, suggest that the predictors related to sea surface temperatures do not adequately represent the seasonal variability of the predictand, however, others such as the temperature at 850 hPa and the Outgoing Longwave Radiation are represented with a good approximation regardless of the model chosen. In this sense, the models built with the nearest neighbor methodology were the most efficient. Using the individual models with the best results, an ensemble is built that allows improving the individual skill of the models selected as members by correcting the underestimation of precipitation in the dynamic model during the wet season, although problems of overestimation persist for thresholds lower than 50 mm.展开更多
The simulation and prediction of the climatology and interannual variability of the East Asia winter monsoon(EAWM),as well as the associated atmospheric circulation,was investigated using the hindcast data from Global...The simulation and prediction of the climatology and interannual variability of the East Asia winter monsoon(EAWM),as well as the associated atmospheric circulation,was investigated using the hindcast data from Global Seasonal Forecast System version 5(GloSea5),with a focus on the evolution of model bias among different forecast lead times.While GloSea5 reproduces the climatological means of large-scale circulation systems related to the EAWM well,systematic biases exist,including a cold bias for most of China’s mainland,especially for North and Northeast China.GloSea5 shows robust skill in predicting the EAWM intensity index two months ahead,which can be attributed to the performance in representing the leading modes of surface air temperature and associated background circulation.GloSea5 realistically reproduces the synergistic effect of El Niño–Southern Oscillation(ENSO)and the Arctic Oscillation(AO)on the EAWM,especially for the western North Pacific anticyclone(WNPAC).Compared with the North Pacific and North America,the representation of circulation anomalies over Eurasia is poor,especially for sea level pressure(SLP),which limits the prediction skill for surface air temperature over East Asia.The representation of SLP anomalies might be associated with the model performance in simulating the interaction between atmospheric circulations and underlying surface conditions.展开更多
The spatial distribution and seasonal variation of the tide-induced Lagrangian Residual Circulations (LRC hereafter), wind-driven LRC, and the coupling dynamic characteristics were simulated using ECOM, given the He...The spatial distribution and seasonal variation of the tide-induced Lagrangian Residual Circulations (LRC hereafter), wind-driven LRC, and the coupling dynamic characteristics were simulated using ECOM, given the Hellerman and Rosenstein global monthly-mean wind stresses. The results showed that the tide-induced LRC of the harmonic constituent M2 bears an identical pattern in four seasons in the Bohai Sea: the surface one is weak with random directions; however, there exist a southeast current from the Bohai Strait to the Laizhou bay, and a weakly anticlockwise gyre in the south of the Bohai Strait for the bottom layer LRC. The magnitude of bottom layer tide-induced LRC is larger than the surface one, and moreover, it contributes significantly to the whole LRC in the Bohai Sea. Unlike the identical structure of the tide-induced LRC, the wind driven LRC varies seasonally under the prevailing monsoon. It forms a distinct gyre under the summer and winter monsoons in July and January respectively, but it seems weak and non-directional in April and September.展开更多
In this study, a regional air quality model system (RAQMS) was applied to investigate the spatial distributions and seasonal variations of atmospheric aerosols in 2006 over East Asia. Model validations demonstrated ...In this study, a regional air quality model system (RAQMS) was applied to investigate the spatial distributions and seasonal variations of atmospheric aerosols in 2006 over East Asia. Model validations demonstrated that RAQMS was able to reproduce the evolution processes of aerosol components reasonably well. Ground-level PM10 (particles with aerodynamic diameter ≤10 μm) concentrations were highest in spring and lowest in summer and were characterized by three maximum centers: the Taklimakan Desert (-1000 μg m^-3), the Gobi Desert (-400 μg m^-3), and the Huabei Plain (- 300 μg m^-3) of China. Vertically, high PM10 concentrations ranging from 100 μg m-3 to 250 μg m-3 occurred from the surface to an altitude of 6000 m at 30°-45°N in spring. In winter, the vertical gradient was so large that most aerosols were restricted in the boundary layer. Both sulfate and ammonium reached their highest concentrations in autumn, while nitrate reached its maximum level in winter. Black carbon and organic carbon aerosol concentrations reached maximums in winter. Soil dust were strongest in spring, whereas sea salt exerted the strongest influence on the coastal regions of eastern China in summer. The estimated burden of anthropogenic aerosols was largest in winter (1621 Gg) and smallest in summer (1040 Gg). The sulfate burden accounted for -42% of the total anthropogenic aerosol burden. The dust burden was about twice the anthropogenic aerosol burden, implying the potentially important impacts of the natural aerosols on air quality and climate over East Asia.展开更多
The simulation characteristics of the seasonal evolution of subtropical anticyclones in the Northern Hemisphere are documented for the Flexible Global Ocean-Atmosphere-Land System model, Spectral Version 2 (FGOALS-s2...The simulation characteristics of the seasonal evolution of subtropical anticyclones in the Northern Hemisphere are documented for the Flexible Global Ocean-Atmosphere-Land System model, Spectral Version 2 (FGOALS-s2), developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, the Institute of Atmospheric Physics. An understanding of the seasonal evolution of the subtropical anticyclones is also addressed. Compared with the global analysis established by the European Centre for Medium-Range Forecasts, the ERA-40 global reanalysis data, the general features of subtropical anticyclones and their evolution are simulated well in both winter and summer, while in spring a pronounced bias in the generation of the South Asia Anticyclone(SAA) exists. Its main deviation in geopotential height from the reanalysis is consistent with the bias of temperature in the troposphere. It is found that condensation heating (CO) plays a dominant role in the seasonal development of the SAA and the subtropical anticyclone over the western Pacific (SAWP) in the middle troposphere. The CO biases in the model account for the biases in the establishment of the SAA in spring and the weaker strength of the SAA and the SAWP from spring to summer. CO is persistently overestimated in the central-east tropical Pacific from winter to summer, while it is underestimated over the area from the South China Sea to the western Pacific from spring to summer. Such biases generate an illusive anticyclonic gyre in the upper troposphere above the middle Pacific and delay the generation of the SAA over South Asia in April. In mid- summer, the simulated SAA is located farther north than in the ERA-40 data owing to excessively strong surface sensible heating (SE) to the north of the Tibetan Plateau. Whereas, the two surface subtropical anticyclones in the eastern oceans during spring to summer are controlled mainly by the surface SE over the two continents in the Northern Hemisphere, which are simulated reasonably well, albeit with their centers shifted westwards owing to the weaker longwave radiation cooling in the simulation associated with much weaker local stratiform cloud. Further improvements in the related parameterization of physical processes are therefore identified.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
The seasonal cycle of the climate of 9000 years before present was simulated with the IAP two-level atmospheric general circulation model. The incoming solar radiation was specified from the orbital parameters for 900...The seasonal cycle of the climate of 9000 years before present was simulated with the IAP two-level atmospheric general circulation model. The incoming solar radiation was specified from the orbital parameters for 9000 years ago. The boundary conditions of that time were prescribed to the present value because of the small differences between the two. The change in radiation makes temperature to be higher in summer and lower in winter over large areas of the land; and the increased temperature contrast between the land and the ocean strengthens the summer monsoon circulation and increases the precipitation over there. The asymmetry of temperature change between the Northern Hemisphere and the Southern Hemisphere and between summer and winter still exists, which agrees with that get from the previous perpetual experiments.展开更多
Recently, the National Typhoon Center (NTC) at the Korea Meteorological Administration launched a track-pattern-based model that predicts the horizontal distribution of tropical cyclone (TC) track density from Jun...Recently, the National Typhoon Center (NTC) at the Korea Meteorological Administration launched a track-pattern-based model that predicts the horizontal distribution of tropical cyclone (TC) track density from June to October. This model is the first approach to target seasonal TC track clusters covering the entire western North Pacific (WNP) basin, and may represent a milestone for seasonal TC forecasting, using a simple statistical method that can be applied at weather operation centers. In this note, we describe the procedure of the track-pattern-based model with brief technical background to provide practical information on the use and operation of the model. The model comprises three major steps. First, long-term data of WNP TC tracks reveal seven climatological track clusters. Second, the TC counts for each cluster are predicted using a hybrid statistical-dynamical method, using the seasonal prediction of large-scale environments. Third, the final forecast map of track density is constructed by merging the spatial probabilities of the seven clusters and applying necessary bias corrections. Although the model is developed to issue the seasonal forecast in mid-May, it can be applied to alternative dates and target seasons following the procedure described in this note. Work continues on establishing an automatic system for this model at the NTC.展开更多
In the South China Sea(SCS), the subsurface chlorophyll maximum(SCM) is frequently observed while the mechanisms of SCM occurrence have not been well understood. In this study, a 1-D physical-biochemical coupled model...In the South China Sea(SCS), the subsurface chlorophyll maximum(SCM) is frequently observed while the mechanisms of SCM occurrence have not been well understood. In this study, a 1-D physical-biochemical coupled model was used to study the seasonal variations of vertical profiles of chlorophyll-a(Chl-a) in the SCS. Three parameters(i.e., SCM layer(SCML) depth, thickness, and intensity) were defined to characterize the vertical distribution of Chl-a in SCML and were obtained by fitting the vertical profile of Chl-a in the subsurface layer using a Gaussian function. The seasonal variations of SCMs are reproduced reasonably well compared to the observations. The annual averages of SCML depth, thickness, and intensity are 75 ± 10 m, 31 ± 6.7 m, and 0.37 ± 0.11 mg m-3, respectively. A thick, close to surface SCML together with a higher intensity occurs during the northeastern monsoon. Both the SCML thickness and intensity are sensitive to the changes of surface wind speed in winter and summer, but the surface wind speed exerts a minor influence on the SCML depth; for example, double strengthening of the southwestern monsoon in summer can lead to the thickening of SCML by 46%, the intensity decreasing by 30%, and the shoaling by 6%. This is because part of nutrients are pumped from the upper nutricline to the surface mixed layer by strong vertical mixing. Increasing initial nutrient concentrations by two times will increase the intensity of SCML by over 80% in winter and spring. The sensitivity analysis indicates that light attenuation is critical to the three parameters of SCM. Decreasing background light attenuation by 20% extends the euphotic zone, makes SCML deeper(~20%) and thicker(12% – 41%), and increases the intensity by over 16%. Overall, the depth of SCML is mainly controlled by light attenuation, and the SCML thickness and intensity are closely associated with wind and initial nitrate concentration in the SCS.展开更多
Seasonal rainfall predictability over the Huaihe River basin is evaluated in this paper on the basis of 23-year(1981-2003) retrospective forecasts by 10 climate models from the Asia-Pacific Economic Cooperation(APEC) ...Seasonal rainfall predictability over the Huaihe River basin is evaluated in this paper on the basis of 23-year(1981-2003) retrospective forecasts by 10 climate models from the Asia-Pacific Economic Cooperation(APEC) Climate Center(APCC) multi-model ensemble(MME) prediction system.It is found that the summer rainfall variance in this basin is largely internal,which leads to lower rainfall predictability for most individual climate models.By dividing the 10 models into three categories according to their sea surface temperature(SST) boundary conditions including observed,predicted,and persistent SSTs,the MME deterministic predictive skill of summer rainfall over Huaihe River basin is investigated.It is shown that the MME is effective for increasing the current seasonal forecast skill.Further analysis shows that the MME averaged over predicted SST models has the highest rainfall prediction skill,which is closely related to model's capability in reproducing the observed dominant modes of the summer rainfall anomalies in Huaihe River basin.This result can be further ascribed to the fact that the predicted SST MME is the most effective model ensemble for capturing the relationship between the summer rainfall anomalies over Huaihe River basin and the SST anomalies(SSTAs) in equatorial oceans.展开更多
Using the seasonal cross-multiplication trend model, monthly precipitation of eight national basic weather stations of Shaanxi Province from 2005 to 2010 was predicted, and the forecast results were verified using the...Using the seasonal cross-multiplication trend model, monthly precipitation of eight national basic weather stations of Shaanxi Province from 2005 to 2010 was predicted, and the forecast results were verified using the rainfall scoring rules of China Meteorological Administration. The verification results show that the average score of annual precipitation prediction in recent six years is higher than that made by a professional forecaster, so this model has a good prospect of application. Moreover, the level of making prediction is steady, and it can be widely used in long-term prediction of rainfall.展开更多
The grey forecasting model has been successfully applied to many fields. However, the precision of GM(1,1) model is not high. In order to remove the seasonal fluctuations in monitoring series before building GM(1,1) m...The grey forecasting model has been successfully applied to many fields. However, the precision of GM(1,1) model is not high. In order to remove the seasonal fluctuations in monitoring series before building GM(1,1) model, the forecasting series of GM(1,1) was built, and an inverse process was used to resume the seasonal fluctuations. Two deseasonalization methods were presented , i.e., seasonal index-based deseasonalization and standard normal distribution-based deseasonalization. They were combined with the GM(1,1) model to form hybrid grey models. A simple but practical method to further improve the forecasting results was also suggested. For comparison, a conventional periodic function model was investigated. The concept and algorithms were tested with four years monthly monitoring data. The results show that on the whole the seasonal index-GM(1,1) model outperform the conventional periodic function model and the conventional periodic function model outperform the SND-GM(1,1) model. The mean Absolute error and mean square error of seasonal index-GM(1,1) are 30.69% and 54.53% smaller than that of conventional periodic function model, respectively. The high accuracy, straightforward and easy implementation natures of the proposed hybrid seasonal index-grey model make it a powerful analysis technique for seasonal monitoring series.展开更多
The conventional zenith tropospheric delay(ZTD)model(known as the Saastamoinen model)does not consider seasonal variations affecting the delay,giving it low accuracy and stability.This may be improved with adjustments...The conventional zenith tropospheric delay(ZTD)model(known as the Saastamoinen model)does not consider seasonal variations affecting the delay,giving it low accuracy and stability.This may be improved with adjustments to account for annual and semi-annual variations.This method uses ZTD data provided by the Global Geodetic Observing System to analyze seasonal variations in the bias of the Saastamoinen model in Asia,and then constructs a model with seasonal variation corrections,denoted as SSA.To overcome the dependence of the model on in-situ meteorological parameters,the SSA+GPT3 model is formed by combining the SSA and GPT3(global pressure-temperature)models.The results show that the introduction of annual and semi-annual variations can substantially improve the Saastamoinen model,yielding small and time-stable variations in bias and root mean square(RMS).In summer and autumn,the bias and RMS are noticeably smaller than those from the Saastamoinen model.In addition,the SSA model performs better in low-latitude and low-altitude areas,and bias and RMS decease with the increase of latitude or altitude.The prediction accuracy of the SSA model is also evaluated for external consistency.The results show that the accuracy of the SSA model(bias:-0.38 cm,RMS:4.43 cm)is better than that of the Saastamoinen model(bias:1.45 cm,RMS:5.16 cm).The proposed method has strong applicability and can therefore be used for predictive ZTD correction across Asia.展开更多
It has been shown by the observed data that during the early 1990′s, the severe disastrous climate occurred in East Asia. In the summer of 1991, severe flood occurred in the Yangtze River and the Huaihe River basin o...It has been shown by the observed data that during the early 1990′s, the severe disastrous climate occurred in East Asia. In the summer of 1991, severe flood occurred in the Yangtze River and the Huaihe River basin of China and in South Korea, and it also appeared in South Korea in the summer of 1993. However, in the summer of 1994, a dry and hot summer was caused in the Huaihe River basin of China and in R. O. K.. In order to investigate the seasonal predictability of the summer droughts and floods during the early 1990′s in East Asia, the seasonal prediction experiments of the summer droughts and floods in the summers of 1991-1994 in East Asia have been made by using the Institute of Atmopsheric Physics-Two-Level General Circulation Model (IAP-L2 AGCM), the IAP-Atmosphere/Ocean Coupled Model (IAP-CGCM) and the IAP-L2 AGCM including a filtering scheme, respectively. Compared with the observational facts, it is shown that the IAP-L2 AGCM or IAP-CGCM has some predictability for the summer droughts and floods during the early 1990′s in East Asia, especially for the severe droughts and floods in China and R. O. K.. In this study, a filtering scheme is used to improve the seasonal prediction experiments of the summer droughts and floods during the early 1990′s in East Asia. The predicted results show that the filtering scheme to remain the planetary-scale disturbances is an effective method for the improvement of the seasonal prediction of the summer droughts and floods in East Asia.展开更多
Accurate prediction of the summer precipitation over the middle and lower reaches of the Yangtze River(MLYR)is of urgent demand for the local economic and societal development.This study assesses the seasonal forecast...Accurate prediction of the summer precipitation over the middle and lower reaches of the Yangtze River(MLYR)is of urgent demand for the local economic and societal development.This study assesses the seasonal forecast skill in predicting summer precipitation over the MLYR region based on the global Climate Forecast System of Nanjing University of Information Science and Technology(NUIST-CFS1.0,previously SINTEX-F).The results show that the model can provide moderate skill in predicting the interannual variations of the MLYR rainbands,initialized from 1 March.In addition,the nine-member ensemble mean can realistically reproduce the links between the MLYR precipitation and tropical sea surface temperature(SST)anomalies,but the individual members show great discrepancies,indicating large uncertainty in the forecasts.Furthermore,the NUIST-CFS1.0 can predict five of the seven extreme summer precipitation anomalies over the MLYR during 1982-2020,albeit with underestimated magnitudes.The Weather Forecast and Research(WRF)downscaling hindcast experiments with a finer resolution of 30 km,which are forced by the large-scale information of the NUIST-CFS1.0 predictions with a spectral nudging method,display improved predictions of the extreme summer precipitation anomalies to some extent.However,the performance of the downscaling predictions is highly dependent on the global model forecast skill,suggesting that further improvements on both the global and regional climate models are needed.展开更多
On the basis of a comprehensive literature review and data analysis of global influenza surveillance, a transmission theory based numerical model is developed to understand the causative factors of influenza seasonali...On the basis of a comprehensive literature review and data analysis of global influenza surveillance, a transmission theory based numerical model is developed to understand the causative factors of influenza seasonality and the biodynamical mechanisms of seasonal flu. The model is applied to simulate the seasonality and weekly activity of influenza in different areas across all continents and climate zones around the world. Model solution and the good matches between model output and actual influenza indexes affirm that influenza activity is highly auto-correlative and relies on determinants of a broad spectrum. Internal dynamic resonance; variations of meteorological elements (solar radiation, precipitation and dewpoint); socio-behavioral influences and herd immunity to circulating strains prove to be the critical explanatory factors of the seasonality and weekly activity of influenza. In all climate regions, influenza activity is proportional to the exponential of the number of days with precipitation and to the negative exponential of quarter power of sunny hours. Influenza activity is a negative exponential function of dewpoint in temperate and arctic regions and an exponential function of the absolute deviation of dewpoint from its annual mean in the tropics. Epidemics of seasonal influenza could be deemed as the consequence of the dynamic resonance and interactions of determinants. Early interventions (such as opportune vaccination, prompt social distancing, and maintaining incidence well below a baseline) are key to the control and prevention of seasonal influenza. Moderate amount of sunlight exposure or Vitamin D supplementation during rainy and short-day photoperiod seasons, more outdoor activities, and appropriate indoor dewpoint deserve great attention in influenza prevention. To a considerable degree, the study reveals the mechanism of influenza seasonality, demonstrating a potential for influenza activity projection. The concept and algorithm can be explored for further applications.展开更多
This paper presents seasonal regression models of demand to investigate electricity consumption characteristics. Electricity consumption in commercial areas in Japan is analyzed by using meteorological variables, name...This paper presents seasonal regression models of demand to investigate electricity consumption characteristics. Electricity consumption in commercial areas in Japan is analyzed by using meteorological variables, namely temperature and relative humidity. A dummy variable for holidays is also considered. We have developed models for two levels of period to analyze demand characteristics, that is, half year models and seasonal models. Some options for each model are calculated and validated by statistical tests to obtain better models. As results, half year and seasonal models present explicit information about how the variables affect the demand differently for each period. These specific information help in analyzing characteristics of studied commercial demand.展开更多
文摘Possible changes in the structure and seasonal variability of the subtropical ridge may lead to changes in the rainfall’s variability modes over Caribbean region. This generates additional difficulties around water resource planning, therefore, obtaining seasonal prediction models that allow these variations to be characterized in detail, it’s a concern, specially for island states. This research proposes the construction of statistical-dynamic models based on PCA regression methods. It is used as predictand the monthly precipitation accumulated, while the predictors (6) are extracted from the ECMWF-SEAS5 ensemble mean forecasts with a lag of one month with respect to the target month. In the construction of the models, two sequential training schemes are evaluated, obtaining that only the shorter preserves the seasonal characteristics of the predictand. The evaluation metrics used, where cell-point and dichotomous methodologies are combined, suggest that the predictors related to sea surface temperatures do not adequately represent the seasonal variability of the predictand, however, others such as the temperature at 850 hPa and the Outgoing Longwave Radiation are represented with a good approximation regardless of the model chosen. In this sense, the models built with the nearest neighbor methodology were the most efficient. Using the individual models with the best results, an ensemble is built that allows improving the individual skill of the models selected as members by correcting the underestimation of precipitation in the dynamic model during the wet season, although problems of overestimation persist for thresholds lower than 50 mm.
基金This work was jointly supported by the National Natural Science Foundation of China projects[grant numbers 42305178 and U2344224]the National Key Scientific and Technological Infrastructure project“Earth System Numerical Simulation Facility”(EarthLab).
基金supported by the Chinese-Norwegian Collaboration Projects within Climate Systems jointly funded by the National Key Research and Development Program of China[grant number 2022YFE0106800]the National Natural Science Foundation of China[grant number 42088101]+1 种基金a Research Council of Norway funded project(MAPARC)[grant number 328943]the Innovation Group Project of the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)[grant number 311020001].
基金supported by the State Key Program of the National Natural Science of China(Grant No.41730964)the National Key Research and Development Program on Monitoring,Early Warning and Prevention of Major Natural Disaster(2018YFC1506000)+2 种基金the National Natural Science Foundation of China(Grant Nos.41975091 and 42175047)National Basic Research Program of China(2015CB453203)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The simulation and prediction of the climatology and interannual variability of the East Asia winter monsoon(EAWM),as well as the associated atmospheric circulation,was investigated using the hindcast data from Global Seasonal Forecast System version 5(GloSea5),with a focus on the evolution of model bias among different forecast lead times.While GloSea5 reproduces the climatological means of large-scale circulation systems related to the EAWM well,systematic biases exist,including a cold bias for most of China’s mainland,especially for North and Northeast China.GloSea5 shows robust skill in predicting the EAWM intensity index two months ahead,which can be attributed to the performance in representing the leading modes of surface air temperature and associated background circulation.GloSea5 realistically reproduces the synergistic effect of El Niño–Southern Oscillation(ENSO)and the Arctic Oscillation(AO)on the EAWM,especially for the western North Pacific anticyclone(WNPAC).Compared with the North Pacific and North America,the representation of circulation anomalies over Eurasia is poor,especially for sea level pressure(SLP),which limits the prediction skill for surface air temperature over East Asia.The representation of SLP anomalies might be associated with the model performance in simulating the interaction between atmospheric circulations and underlying surface conditions.
基金N ational N atural Science Foundation of China, N o.40271020 K now ledge Innovation Project of the Institute ofG eographic Sciences and N aturalResources Research,CA S,N o.CX IO G -A 04-09
文摘The spatial distribution and seasonal variation of the tide-induced Lagrangian Residual Circulations (LRC hereafter), wind-driven LRC, and the coupling dynamic characteristics were simulated using ECOM, given the Hellerman and Rosenstein global monthly-mean wind stresses. The results showed that the tide-induced LRC of the harmonic constituent M2 bears an identical pattern in four seasons in the Bohai Sea: the surface one is weak with random directions; however, there exist a southeast current from the Bohai Strait to the Laizhou bay, and a weakly anticlockwise gyre in the south of the Bohai Strait for the bottom layer LRC. The magnitude of bottom layer tide-induced LRC is larger than the surface one, and moreover, it contributes significantly to the whole LRC in the Bohai Sea. Unlike the identical structure of the tide-induced LRC, the wind driven LRC varies seasonally under the prevailing monsoon. It forms a distinct gyre under the summer and winter monsoons in July and January respectively, but it seems weak and non-directional in April and September.
基金supported by the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No. KZCX2-YW-Q11-03)the "Strategic Priority Research Program" of the Chinese Academy of Sciences (Grant No. XDA05100502)+2 种基金the National 973 Project of China (Grant No. 2010CB950804)the National Natural Science Foundation of China (GrantNo. 41075106)the Hundred Talents Program of the Chinese Academy of Sciences
文摘In this study, a regional air quality model system (RAQMS) was applied to investigate the spatial distributions and seasonal variations of atmospheric aerosols in 2006 over East Asia. Model validations demonstrated that RAQMS was able to reproduce the evolution processes of aerosol components reasonably well. Ground-level PM10 (particles with aerodynamic diameter ≤10 μm) concentrations were highest in spring and lowest in summer and were characterized by three maximum centers: the Taklimakan Desert (-1000 μg m^-3), the Gobi Desert (-400 μg m^-3), and the Huabei Plain (- 300 μg m^-3) of China. Vertically, high PM10 concentrations ranging from 100 μg m-3 to 250 μg m-3 occurred from the surface to an altitude of 6000 m at 30°-45°N in spring. In winter, the vertical gradient was so large that most aerosols were restricted in the boundary layer. Both sulfate and ammonium reached their highest concentrations in autumn, while nitrate reached its maximum level in winter. Black carbon and organic carbon aerosol concentrations reached maximums in winter. Soil dust were strongest in spring, whereas sea salt exerted the strongest influence on the coastal regions of eastern China in summer. The estimated burden of anthropogenic aerosols was largest in winter (1621 Gg) and smallest in summer (1040 Gg). The sulfate burden accounted for -42% of the total anthropogenic aerosol burden. The dust burden was about twice the anthropogenic aerosol burden, implying the potentially important impacts of the natural aerosols on air quality and climate over East Asia.
基金supported by the National Natural Science Foundation of China(Grant No.40925015)the CAS Strategic Priority Research Program(Grant No.XDA01020303)the National Program on Key Basic Research Project(Grant No.2010CB950400)
文摘The simulation characteristics of the seasonal evolution of subtropical anticyclones in the Northern Hemisphere are documented for the Flexible Global Ocean-Atmosphere-Land System model, Spectral Version 2 (FGOALS-s2), developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, the Institute of Atmospheric Physics. An understanding of the seasonal evolution of the subtropical anticyclones is also addressed. Compared with the global analysis established by the European Centre for Medium-Range Forecasts, the ERA-40 global reanalysis data, the general features of subtropical anticyclones and their evolution are simulated well in both winter and summer, while in spring a pronounced bias in the generation of the South Asia Anticyclone(SAA) exists. Its main deviation in geopotential height from the reanalysis is consistent with the bias of temperature in the troposphere. It is found that condensation heating (CO) plays a dominant role in the seasonal development of the SAA and the subtropical anticyclone over the western Pacific (SAWP) in the middle troposphere. The CO biases in the model account for the biases in the establishment of the SAA in spring and the weaker strength of the SAA and the SAWP from spring to summer. CO is persistently overestimated in the central-east tropical Pacific from winter to summer, while it is underestimated over the area from the South China Sea to the western Pacific from spring to summer. Such biases generate an illusive anticyclonic gyre in the upper troposphere above the middle Pacific and delay the generation of the SAA over South Asia in April. In mid- summer, the simulated SAA is located farther north than in the ERA-40 data owing to excessively strong surface sensible heating (SE) to the north of the Tibetan Plateau. Whereas, the two surface subtropical anticyclones in the eastern oceans during spring to summer are controlled mainly by the surface SE over the two continents in the Northern Hemisphere, which are simulated reasonably well, albeit with their centers shifted westwards owing to the weaker longwave radiation cooling in the simulation associated with much weaker local stratiform cloud. Further improvements in the related parameterization of physical processes are therefore identified.
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.
文摘The seasonal cycle of the climate of 9000 years before present was simulated with the IAP two-level atmospheric general circulation model. The incoming solar radiation was specified from the orbital parameters for 9000 years ago. The boundary conditions of that time were prescribed to the present value because of the small differences between the two. The change in radiation makes temperature to be higher in summer and lower in winter over large areas of the land; and the increased temperature contrast between the land and the ocean strengthens the summer monsoon circulation and increases the precipitation over there. The asymmetry of temperature change between the Northern Hemisphere and the Southern Hemisphere and between summer and winter still exists, which agrees with that get from the previous perpetual experiments.
基金funded by the Korea Meteorological Administration Research and Development Program under Grant CATER 2012-2040supported by the BK21 project of the Korean government
文摘Recently, the National Typhoon Center (NTC) at the Korea Meteorological Administration launched a track-pattern-based model that predicts the horizontal distribution of tropical cyclone (TC) track density from June to October. This model is the first approach to target seasonal TC track clusters covering the entire western North Pacific (WNP) basin, and may represent a milestone for seasonal TC forecasting, using a simple statistical method that can be applied at weather operation centers. In this note, we describe the procedure of the track-pattern-based model with brief technical background to provide practical information on the use and operation of the model. The model comprises three major steps. First, long-term data of WNP TC tracks reveal seven climatological track clusters. Second, the TC counts for each cluster are predicted using a hybrid statistical-dynamical method, using the seasonal prediction of large-scale environments. Third, the final forecast map of track density is constructed by merging the spatial probabilities of the seven clusters and applying necessary bias corrections. Although the model is developed to issue the seasonal forecast in mid-May, it can be applied to alternative dates and target seasons following the procedure described in this note. Work continues on establishing an automatic system for this model at the NTC.
基金supported by the National Natural Science Foundation of China (Nos. 41106007, 41210008)the China Postdoctoral Science Foundation (No. 2013M 541958)the International Cooperation Project of China (No. 2010DFA91350)
文摘In the South China Sea(SCS), the subsurface chlorophyll maximum(SCM) is frequently observed while the mechanisms of SCM occurrence have not been well understood. In this study, a 1-D physical-biochemical coupled model was used to study the seasonal variations of vertical profiles of chlorophyll-a(Chl-a) in the SCS. Three parameters(i.e., SCM layer(SCML) depth, thickness, and intensity) were defined to characterize the vertical distribution of Chl-a in SCML and were obtained by fitting the vertical profile of Chl-a in the subsurface layer using a Gaussian function. The seasonal variations of SCMs are reproduced reasonably well compared to the observations. The annual averages of SCML depth, thickness, and intensity are 75 ± 10 m, 31 ± 6.7 m, and 0.37 ± 0.11 mg m-3, respectively. A thick, close to surface SCML together with a higher intensity occurs during the northeastern monsoon. Both the SCML thickness and intensity are sensitive to the changes of surface wind speed in winter and summer, but the surface wind speed exerts a minor influence on the SCML depth; for example, double strengthening of the southwestern monsoon in summer can lead to the thickening of SCML by 46%, the intensity decreasing by 30%, and the shoaling by 6%. This is because part of nutrients are pumped from the upper nutricline to the surface mixed layer by strong vertical mixing. Increasing initial nutrient concentrations by two times will increase the intensity of SCML by over 80% in winter and spring. The sensitivity analysis indicates that light attenuation is critical to the three parameters of SCM. Decreasing background light attenuation by 20% extends the euphotic zone, makes SCML deeper(~20%) and thicker(12% – 41%), and increases the intensity by over 16%. Overall, the depth of SCML is mainly controlled by light attenuation, and the SCML thickness and intensity are closely associated with wind and initial nitrate concentration in the SCS.
基金supported by the National Natural Science Foundation of China (41175073)the National Science Foundation of China (NSFC)-Yunnan Province Joint Grant (U1133603)+1 种基金the National Basic Research Program of China (2010CB428403 and 2009CB421406)the NOAA Climate Program Office and Michigan State University (NA10OAR4310246 and NA12OAR 4310081)
文摘Seasonal rainfall predictability over the Huaihe River basin is evaluated in this paper on the basis of 23-year(1981-2003) retrospective forecasts by 10 climate models from the Asia-Pacific Economic Cooperation(APEC) Climate Center(APCC) multi-model ensemble(MME) prediction system.It is found that the summer rainfall variance in this basin is largely internal,which leads to lower rainfall predictability for most individual climate models.By dividing the 10 models into three categories according to their sea surface temperature(SST) boundary conditions including observed,predicted,and persistent SSTs,the MME deterministic predictive skill of summer rainfall over Huaihe River basin is investigated.It is shown that the MME is effective for increasing the current seasonal forecast skill.Further analysis shows that the MME averaged over predicted SST models has the highest rainfall prediction skill,which is closely related to model's capability in reproducing the observed dominant modes of the summer rainfall anomalies in Huaihe River basin.This result can be further ascribed to the fact that the predicted SST MME is the most effective model ensemble for capturing the relationship between the summer rainfall anomalies over Huaihe River basin and the SST anomalies(SSTAs) in equatorial oceans.
基金Supported by the Major State Basic Research Development Program("973"Program)(2012CB956204)Special Project for Climate Change of China Meteorological Administration(CCSF2011-4)
文摘Using the seasonal cross-multiplication trend model, monthly precipitation of eight national basic weather stations of Shaanxi Province from 2005 to 2010 was predicted, and the forecast results were verified using the rainfall scoring rules of China Meteorological Administration. The verification results show that the average score of annual precipitation prediction in recent six years is higher than that made by a professional forecaster, so this model has a good prospect of application. Moreover, the level of making prediction is steady, and it can be widely used in long-term prediction of rainfall.
文摘The grey forecasting model has been successfully applied to many fields. However, the precision of GM(1,1) model is not high. In order to remove the seasonal fluctuations in monitoring series before building GM(1,1) model, the forecasting series of GM(1,1) was built, and an inverse process was used to resume the seasonal fluctuations. Two deseasonalization methods were presented , i.e., seasonal index-based deseasonalization and standard normal distribution-based deseasonalization. They were combined with the GM(1,1) model to form hybrid grey models. A simple but practical method to further improve the forecasting results was also suggested. For comparison, a conventional periodic function model was investigated. The concept and algorithms were tested with four years monthly monitoring data. The results show that on the whole the seasonal index-GM(1,1) model outperform the conventional periodic function model and the conventional periodic function model outperform the SND-GM(1,1) model. The mean Absolute error and mean square error of seasonal index-GM(1,1) are 30.69% and 54.53% smaller than that of conventional periodic function model, respectively. The high accuracy, straightforward and easy implementation natures of the proposed hybrid seasonal index-grey model make it a powerful analysis technique for seasonal monitoring series.
基金This work was supported by the Basic Science Research Program of Shaanxi Province(2023-JC-YB-057 and 2022JM-031).
文摘The conventional zenith tropospheric delay(ZTD)model(known as the Saastamoinen model)does not consider seasonal variations affecting the delay,giving it low accuracy and stability.This may be improved with adjustments to account for annual and semi-annual variations.This method uses ZTD data provided by the Global Geodetic Observing System to analyze seasonal variations in the bias of the Saastamoinen model in Asia,and then constructs a model with seasonal variation corrections,denoted as SSA.To overcome the dependence of the model on in-situ meteorological parameters,the SSA+GPT3 model is formed by combining the SSA and GPT3(global pressure-temperature)models.The results show that the introduction of annual and semi-annual variations can substantially improve the Saastamoinen model,yielding small and time-stable variations in bias and root mean square(RMS).In summer and autumn,the bias and RMS are noticeably smaller than those from the Saastamoinen model.In addition,the SSA model performs better in low-latitude and low-altitude areas,and bias and RMS decease with the increase of latitude or altitude.The prediction accuracy of the SSA model is also evaluated for external consistency.The results show that the accuracy of the SSA model(bias:-0.38 cm,RMS:4.43 cm)is better than that of the Saastamoinen model(bias:1.45 cm,RMS:5.16 cm).The proposed method has strong applicability and can therefore be used for predictive ZTD correction across Asia.
文摘It has been shown by the observed data that during the early 1990′s, the severe disastrous climate occurred in East Asia. In the summer of 1991, severe flood occurred in the Yangtze River and the Huaihe River basin of China and in South Korea, and it also appeared in South Korea in the summer of 1993. However, in the summer of 1994, a dry and hot summer was caused in the Huaihe River basin of China and in R. O. K.. In order to investigate the seasonal predictability of the summer droughts and floods during the early 1990′s in East Asia, the seasonal prediction experiments of the summer droughts and floods in the summers of 1991-1994 in East Asia have been made by using the Institute of Atmopsheric Physics-Two-Level General Circulation Model (IAP-L2 AGCM), the IAP-Atmosphere/Ocean Coupled Model (IAP-CGCM) and the IAP-L2 AGCM including a filtering scheme, respectively. Compared with the observational facts, it is shown that the IAP-L2 AGCM or IAP-CGCM has some predictability for the summer droughts and floods during the early 1990′s in East Asia, especially for the severe droughts and floods in China and R. O. K.. In this study, a filtering scheme is used to improve the seasonal prediction experiments of the summer droughts and floods during the early 1990′s in East Asia. The predicted results show that the filtering scheme to remain the planetary-scale disturbances is an effective method for the improvement of the seasonal prediction of the summer droughts and floods in East Asia.
基金National Natu-ral Science Foundation of China(Grant Nos.42030605 and 42088101)National Key R&D Program of China(Grant No.2020YFA0608004).
文摘Accurate prediction of the summer precipitation over the middle and lower reaches of the Yangtze River(MLYR)is of urgent demand for the local economic and societal development.This study assesses the seasonal forecast skill in predicting summer precipitation over the MLYR region based on the global Climate Forecast System of Nanjing University of Information Science and Technology(NUIST-CFS1.0,previously SINTEX-F).The results show that the model can provide moderate skill in predicting the interannual variations of the MLYR rainbands,initialized from 1 March.In addition,the nine-member ensemble mean can realistically reproduce the links between the MLYR precipitation and tropical sea surface temperature(SST)anomalies,but the individual members show great discrepancies,indicating large uncertainty in the forecasts.Furthermore,the NUIST-CFS1.0 can predict five of the seven extreme summer precipitation anomalies over the MLYR during 1982-2020,albeit with underestimated magnitudes.The Weather Forecast and Research(WRF)downscaling hindcast experiments with a finer resolution of 30 km,which are forced by the large-scale information of the NUIST-CFS1.0 predictions with a spectral nudging method,display improved predictions of the extreme summer precipitation anomalies to some extent.However,the performance of the downscaling predictions is highly dependent on the global model forecast skill,suggesting that further improvements on both the global and regional climate models are needed.
文摘On the basis of a comprehensive literature review and data analysis of global influenza surveillance, a transmission theory based numerical model is developed to understand the causative factors of influenza seasonality and the biodynamical mechanisms of seasonal flu. The model is applied to simulate the seasonality and weekly activity of influenza in different areas across all continents and climate zones around the world. Model solution and the good matches between model output and actual influenza indexes affirm that influenza activity is highly auto-correlative and relies on determinants of a broad spectrum. Internal dynamic resonance; variations of meteorological elements (solar radiation, precipitation and dewpoint); socio-behavioral influences and herd immunity to circulating strains prove to be the critical explanatory factors of the seasonality and weekly activity of influenza. In all climate regions, influenza activity is proportional to the exponential of the number of days with precipitation and to the negative exponential of quarter power of sunny hours. Influenza activity is a negative exponential function of dewpoint in temperate and arctic regions and an exponential function of the absolute deviation of dewpoint from its annual mean in the tropics. Epidemics of seasonal influenza could be deemed as the consequence of the dynamic resonance and interactions of determinants. Early interventions (such as opportune vaccination, prompt social distancing, and maintaining incidence well below a baseline) are key to the control and prevention of seasonal influenza. Moderate amount of sunlight exposure or Vitamin D supplementation during rainy and short-day photoperiod seasons, more outdoor activities, and appropriate indoor dewpoint deserve great attention in influenza prevention. To a considerable degree, the study reveals the mechanism of influenza seasonality, demonstrating a potential for influenza activity projection. The concept and algorithm can be explored for further applications.
文摘This paper presents seasonal regression models of demand to investigate electricity consumption characteristics. Electricity consumption in commercial areas in Japan is analyzed by using meteorological variables, namely temperature and relative humidity. A dummy variable for holidays is also considered. We have developed models for two levels of period to analyze demand characteristics, that is, half year models and seasonal models. Some options for each model are calculated and validated by statistical tests to obtain better models. As results, half year and seasonal models present explicit information about how the variables affect the demand differently for each period. These specific information help in analyzing characteristics of studied commercial demand.