|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Nonlinear singular vectors and nonlinear singular values显示文摘A novel concept of nonlinear singular vector and nonlinear singular value is introduced, which is a natural generalization of the classical linear singular vector and linear singular value to the nonlinear category. The optimization problem related to the determination of nonlinear singular vectors and singular values is formulated. The general idea of this approach is demonstrated by a simple two-dimensional quasigeostrophic model in the atmospheric and oceanic sciences. The advantage and its applications of the new method to the predictability, ensemble forecast and finite-time nonlinear instability are discussed. This paper makes a necessary preparation for further theoretical and numerical investigations. | 穆穆 | 2000 | Science China Earth Sciences2000，43，4： | 37 |
| 2 | Conditional nonlinear optimal perturbation: Applications to stability, sensitivity, and predictability显示文摘Conditional nonlinear optimal perturbation (CNOP) is a nonlinear generalization of linear singular vector (LSV) and features the largest nonlinear evolution at prediction time for the initial perturbations in a given constraint. It was proposed initially for predicting the limitation of predictability of weather or climate. Then CNOP has been applied to the studies of the problems related to predictability for weather and climate. In this paper, we focus on reviewing the recent advances of CNOP's applications, which involves the ones of CNOP in problems of ENSO amplitude asymmetry, block onset, and the sensitivity analysis of ecosystem and ocean's circulations, etc. Especially, CNOP has been primarily used to construct the initial perturbation fields of ensemble forecasting, and to determine the sensitive area of target observation for precipitations. These works extend CNOP's applications to investigating the nonlinear dynamical behaviors of atmospheric or oceanic systems, even a coupled system, and studying the problem of the transition between the equilibrium states. These contributions not only attack the particular physical problems, but also show the superiority of CNOP to LSV in revealing the effect of nonlinear physical processes. Consequently, CNOP represents the optimal precursors for a weather or climate event; in predictability studies, CNOP stands for the initial error that has the largest negative effect on prediction; and in sensitivity analysis, CNOP is the most unstable (sensitive) mode. In multi-equilibrium state regime, CNOP is the initial perturbation that induces the transition between equilibriums most probably. Furthermore, CNOP has been used to construct ensemble perturbation fields in ensemble forecast studies and to identify sensitive area of target observation. CNOP theory has become more and more substantial. It is expected that CNOP also serves to improve the predictability of the realistic predictions for weather and climate events plays an increasingly important role in exploring the nonlinear dynamics of atmospheric, oceanic and coupled atmosphere-ocean system. | DUAN WanSuo MU Mu | 2009 | Science China Earth Sciences2009，52，7： | 32 |
| 3 | Target observations for improving initialization of high-impact ocean-atmospheric environmental events forecasting显示文摘In this paper, we emphasize the importance of accurate initial conditions in predicting high-impact ocean-atmospheric environmental events, such as El Nin?o-Southern Oscillation(ENSO), Indian Ocean Dipole(IOD), tropical cyclone(TC), and Kuroshio large meander(KLM), by reviewing recent progresses toward target observations for improving the initialization of these events forecasting. Since ield observations are costly and will never be dense enough to fully cover the vast space of these events, it is necessary to develop methodologies that guide the design of eicient and efective observation strategy. Of particular interest is a method called conditional non-linear optimal perturbation(CNOP), which has been shown to be very useful in determining the sensitive areas for target observations applicable to the predictions of ENSO, IOD, TC, and KLM. Further studies are needed to understand the predictability of these events under the inluence of climate change, and to explore the possibility of implementing ield programs of target observations. hese studies are challenging but are crucially important for improving our forecast skill of the high-impact ocean-atmospheric environmental events, and thus for disaster prevention,climate change mitigation, and sustainable socio-economic development. | Mu Mu Wansuo Duan Dake Chen Weidong Yu | 2015 | National Science Review2015，2，2： | 21 |
| 4 | Theory for Constructing Generalized Synchronization and Applications显示文摘The approaches for constructing directionally coupled generalized synchronization (GS) systems are presented, which are available for the driving system and the respond system that are in GS via a given diffeomorphism transformation. Examples are proposed for illustrating the methods. | Xiaodan Zhang, Lequan Min (Applied Science School, University of Science and Technology Beijing, Beijing 100083, China) | 2000 | International Journal of Minerals,Metallurgy and Materials2000，14，3： | 9 |
| 5 | Progress in ENSO prediction and predictability study显示文摘ENSO is the strongest interannual signal in the global climate system with worldwide climatic, ecological and societal impacts. Over the past decades, the research about ENSO prediction and predictability has attracted broad attention. With the development of coupled models, the improvement in initialization schemes and the progress in theoretical studies, ENSO has become the most predictable climate mode at the time scales from months to seasons. This paper reviews in detail the progress in ENSO predictions and predictability studies achieved in recent years. An emphasis is placed on two fundamental issues: the improvement in practical prediction skills and progress in the theoretical study of the intrinsic predictability limit. The former includes progress in the couple models, data assimilations, ensemble predictions and so on, and the latter focuses on efforts in the study of the optimal error growth and in the estimate of the intrinsic predictability limit. | Youmin Tang Rong-Hua Zhang Ting Liu Wansuo Duan Dejian Yang Fei Zheng Hongli Ren Tao Lian Chuan Gao Dake Chen Mu Mu | 2018 | National Science Review2018，5，6： | 8 |
| 6 | On the Application of a Genetic Algorithm to the Predictability Problems Involving 'On-Off' Switches显示文摘The lower bound of maximum predictable time can be formulated into a constrained nonlinear opti- mization problem, and the traditional solutions to this problem are the filtering method and the conditional nonlinear optimal perturbation (CNOP) method. Usually, the CNOP method is implemented with the help of a gradient descent algorithm based on the adjoint method, which is named the ADJ-CNOP. However, with the increasing improvement of actual prediction models, more and more physical processes are taken into consideration in models in the form of parameterization, thus giving rise to the on-off switch problem, which tremendously affects the effectiveness of the conventional gradient descent algorithm based on the ad- joint method. In this study, we attempted to apply a genetic algorithm (GA) to the CNOP method, named GA-CNOP, to solve the predictability problems involving on-off switches. As the precision of the filtering method depends uniquely on the division of the constraint region, its results were taken as benchmarks, and a series of comparisons between the ADJ-CNOP and the GA-CNOP were performed for the modified Lorenz equation. Results show that the GA-CNOP can always determine the accurate lower bound of maximum predictable time, even in non-smooth cases, while the ADJ-CNOP, owing to the effect of on-off switches, often yields the incorrect lower bound of maximum predictable time. Therefore, in non-smooth cases, using GAs to solve predictability problems is more effective than using the conventional optimization algorithm based on gradients, as long as genetic operators in GAs are properly configured. | 郑琴 戴毅 张露 沙建新 陆小庆 | 2012 | Advances in Atmospheric Sciences2012，29，2： | 5 |
| 7 | The Nature and Predictability of the East Asian Extreme Cold Events of 2020/21显示文摘Three extreme cold events invaded China during the early winter period between December 2020 to mid-January 2021 and caused drastic temperature drops,setting new low-temperature records at many stations during 6−8 January 2021.These cold events occurred under background conditions of low Arctic sea ice extent and a La Niña event.This is somewhat expected since the coupled effect of large Arctic sea ice loss in autumn and sea surface temperature cooling in the tropical Pacific usually favors cold event occurrences in Eurasia.Further diagnosis reveals that the first cold event is related to the southward movement of the polar vortex and the second one is related to a continent-wide ridge,while both the southward polar vortex and the Asian blocking are crucial for the third event.Here,we evaluate the forecast skill for these three events utilizing the operational forecasts from the ECMWF model.We find that the third event had the highest predictability since it achieves the best skill in forecasting the East Asian cooling among the three events.Therefore,the predictability of these cold events,as well as their relationships with the atmospheric initial conditions,Arctic sea ice,and La Niña deserve further investigation. | Guokun DAI Chunxiang LI Zhe HAN Dehai LUO Yao YAO | 2022 | Advances in Atmospheric Sciences2022，39，4： | 4 |
| 8 | An Examination of the Predictability of Tropical Cyclone Genesis in High-Resolution Coupled Models with Dynamically Downscaled Coupled Data Assimilation Initialization显示文摘Predicting tropical cyclone(TC)genesis is of great societal importance but scientifically challenging.It requires fineresolution coupled models that properly represent air−sea interactions in the atmospheric responses to local warm sea surface temperatures and feedbacks,with aid from coherent coupled initialization.This study uses three sets of highresolution regional coupled models(RCMs)covering the Asia−Pacific(AP)region initialized with local observations and dynamically downscaled coupled data assimilation to evaluate the predictability of TC genesis in the West Pacific.The APRCMs consist of three sets of high-resolution configurations of the Weather Research and Forecasting−Regional Ocean Model System(WRF-ROMS):27-km WRF with 9-km ROMS,and 9-km WRF with 3-km ROMS.In this study,a 9-km WRF with 9-km ROMS coupled model system is also used in a case test for the predictability of TC genesis.Since the local sea surface temperatures and wind shear conditions that favor TC formation are better resolved,the enhanced-resolution coupled model tends to improve the predictability of TC genesis,which could be further improved by improving planetary boundary layer physics,thus resolving better air−sea and air−land interactions. | Mingkui LI Shaoqing ZHANG Lixin WU Xiaopei LIN Ping CHANG Gohkan DANABASOGLU Zhiqiang WEI Xiaolin YU Huiqin HU Xiaohui MA Weiwei MA Haoran ZHAO Dongning JIA Xin LIU Kai MAO Youwei MA Yingjing JIANG Xue WANG Guangliang LIU Yuhu CHEN | 2020 | Advances in Atmospheric Sciences2020，37，9： | 4 |
| 9 | The Interannual Variability and Predictability in a Global Climate Model显示文摘TheInterannualVariabilityandPredictabilityinaGlobalClimateModel①WangHuijun(王会军),XueFeng(薛峰)andBiXunqiang(毕训强)LASG,Instituteof... | 王会军 薛峰 毕训强 | 1997 | Advances in Atmospheric Sciences1997，14，4： | 3 |
| 10 | Insights into Convective-scale Predictability in East China: Error Growth Dynamics and Associated Impact on Precipitation of Warm-Season Convective Events显示文摘This study investigated the regime-dependent predictability using convective-scale ensemble forecasts initialized with different initial condition perturbations in the Yangtze and Huai River basin(YHRB)of East China.The scale-dependent error growth(ensemble variability)and associated impact on precipitation forecasts(precipitation uncertainties)were quantitatively explored for 13 warm-season convective events that were categorized in terms of strong forcing and weak forcing.The forecast error growth in the strong-forcing regime shows a stepwise increase with increasing spatial scale,while the error growth shows a larger temporal variability with an afternoon peak appearing at smaller scales under weak forcing.This leads to the dissimilarity of precipitation uncertainty and shows a strong correlation between error growth and precipitation across spatial scales.The lateral boundary condition errors exert a quasi-linear increase on error growth with time at the larger scale,suggesting that the large-scale flow could govern the magnitude of error growth and associated precipitation uncertainties,especially for the strong-forcing regime.Further comparisons between scale-based initial error sensitivity experiments show evident scale interaction including upscale transfer of small-scale errors and downscale cascade of larger-scale errors.Specifically,small-scale errors are found to be more sensitive in the weak-forcing regime than those under strong forcing.Meanwhile,larger-scale initial errors are responsible for the error growth after 4 h and produce the precipitation uncertainties at the meso-β-scale.Consequently,these results can be used to explain underdispersion issues in convective-scale ensemble forecasts and provide feedback for ensemble design over the YHRB. | Xiaoran ZHUANG Jinzhong MIN Liu ZHANG Shizhang WANG Naigeng WU Haonan ZHU | 2020 | Advances in Atmospheric Sciences2020，37，8： | 3 |
| 11 | A Preliminary Study on the Polar Climate Predictability显示文摘Studies have revealed that predictability of the atmospheric general circulation is generally high in thetropics throughout the year and that there is some predictability in the Northern extra-tropical winter atmospheric circulation through some patterns of tele connection. Predictability of the general circulation atthe polar regions has still remained as a’ cold’ topic and little has been known about this question. Based ona preliminary study on the predictability by using the institute of Atmospheric Physics (IAP) general circulation model, it is found that the SST-related predictability of the Southern winter lower atmospheric circulation in Antarctica is reasonably high and that there is some pledictability in the 500 hpa and 200 hpageopotential height fields over Europe and the Okhotsk Sea region during the Northern winter. It is suggested that more researches on this issue based on data analysis and model simulations are needed to obtainbetter understanding. | 王会军 | 1999 | Advances in Atmospheric Sciences1999，16，3： | 2 |
| 12 | INTELLIGENT ALGORITHMS FOR SOLVING CNOP AND THEIR APPLICATIONS IN ENSO PREDICTABILITY AND TROPICAL CYCLONE ADAPTIVE OBSERVATIONS显示文摘Some intelligent algorithms(IAs) proposed by us, including swarm IAs and single individual IAs, have been applied to the Zebiak-Cane(ZC) model to solve conditional nonlinear optimal perturbation(CNOP) for studying El Ni?o-Southern Oscillation(ENSO) predictability. Compared to the adjoint-based method(the ADJ-method), which is referred to as a benchmark, these IAs can achieve approximate CNOP results in terms of magnitudes and patterns.Using IAs to solve CNOP can avoid the use of an adjoint model and widen the application of CNOP in numerical climate and weather modeling. Of the proposed swarm IAs, PCA-based particle swarm optimization(PPSO) obtains CNOPs with the best patterns and the best stability. Of the proposed single individual IAs, continuous tabu search algorithm with sine maps and staged strategy(CTS-SS) has the highest efficiency. In this paper, we compare the validity, stability and efficiency of parallel PPSO and CTS-SS using these two IAs to solve CNOP in the ZC model for studying ENSO predictability. The experimental results show that CTS-SS outperforms parallel PPSO except with respect to stability. At the same time, we are also concerned with whether these two IAs can effectively solve CNOP when applied to more complicated models. Taking the sensitive areas identification of tropical cyclone adaptive observations as an example and using the fifth-generation mesoscale model(MM5), we design some experiments. The experimental results demonstrate that each of these two IAs can effectively solve CNOP and that parallel PPSO has a higher efficiency than CTS-SS. We also provide some suggestions on how to choose a suitable IA to solve CNOP for different models. | 穆斌 张琳琳 袁时金 钱一闻 温仕成 颜景豪 周菲凡 | 2019 | Journal of Tropical Meteorology2019，25，1： | 2 |
| 13 | Predictability of the Western North Pacific Subtropical High Associated with Different ENSO Phases in GloSea5显示文摘The western North Pacific subtropical high(WNPSH) dominates the summer climate over East Asia. The intensity,position, and shape of WNPSH influence the spatiotemporal distributions of precipitation, temperature, and tropical cyclone activities in this region. This paper intends to investigate the performance of the UK Met Office Global Seasonal forecast system version 5(GloSea5) in simulation/prediction of the WNPSH based on a hindcast dataset. Analyses of the hindcast data show a systematic bias in the mean circulation over West Pacific, with negative geopotential height anomalies over the western North Pacific(WNP) and cyclonic anomalies in the 850-hPa winds and water vapor transport, indicating a weakening and eastward shift of the WNPSH. Despite the model’s bias in the climatology, it well captured the interannual variability of the monthly and seasonal-mean intensity of the WNPSH and the position of its ridge line in boreal summer from 1993 to 2015. The seasonal hindcasts indicate that there is significant prediction skill at up to three-month lead time for both the intensity and position of the WNPSH ridge line. The relationship between the WNPSH and different phases of the El Nino–Southern Oscillation(ENSO) in both the observational data and GloSea5 hindcasts was then investigated. The model captured the summer WNPSH anomalies well during most of the ENSO phases, except in the La Nina decaying and neutral summers. The intensity of the anticyclone in the WNP is weak in the decaying phase of El Nino in the GloSea5 hindcasts compared with the reanalysis data. GloSea5 is capable of representing the lagged teleconnection between El Nino events in the previous winter and the intensity of the WNPSH in the following summer. Regression analysis reveals weakened negative sea surface temperature anomalies(SSTAs) over the WNP in GloSea5, which reduced the gradient between the tropical western Pacific and the tropical Indian Ocean, resulting in a weaker easterly anomaly and stronger westerly anomaly, contributing to the weak anomalous anticyclone over the WNP and the weakened WNPSH relative to the reanalysis data. | Daquan ZHANG Gill M.MARTIN Jose MRODRIGUEZ Zongjian KE Lijuan CHEN | 2020 | Journal of Meteorological Research2020，34，5： | 2 |
| 14 | Possible Sources of Forecast Errors Generated by the Global/Regional Assimilation and Prediction System for Landfalling Tropical Cyclones. Part Ⅱ: Model Uncertainty显示文摘This paper investigates the possible sources of errors associated with tropical cyclone(TC) tracks forecasted using the Global/Regional Assimilation and Prediction System(GRAPES). In Part I, it is shown that the model error of GRAPES may be the main cause of poor forecasts of landfalling TCs. Thus, a further examination of the model error is the focus of Part II.Considering model error as a type of forcing, the model error can be represented by the combination of good forecasts and bad forecasts. Results show that there are systematic model errors. The model error of the geopotential height component has periodic features, with a period of 24 h and a global pattern of wavenumber 2 from west to east located between 60?S and 60?N. This periodic model error presents similar features as the atmospheric semidiurnal tide, which reflect signals from tropical diabatic heating, indicating that the parameter errors related to the tropical diabatic heating may be the source of the periodic model error. The above model errors are subtracted from the forecast equation and a series of new forecasts are made. The average forecasting capability using the rectified model is improved compared to simply improving the initial conditions of the original GRAPES model. This confirms the strong impact of the periodic model error on landfalling TC track forecasts. Besides, if the model error used to rectify the model is obtained from an examination of additional TCs, the forecasting capabilities of the corresponding rectified model will be improved. | Feifan ZHOU Wansuo DUAN He ZHANG Munehiko YAMAGUCHI | 2018 | Advances in Atmospheric Sciences2018，35，10： | 2 |
| 15 | Investigating the Initial Errors that Cause Predictability Barriers for Indian Ocean Dipole Events Using CMIP5 Model Outputs显示文摘By analyzing the outputs of the pre-industrial control runs of four models within phase 5 of the Coupled Model Intercomparison Project, the effects of initial sea temperature errors on the predictability of Indian Ocean Dipole events were identified. The initial errors cause a significant winter predictability barrier(WPB) or summer predictability barrier(SPB).The WPB is closely related with the initial errors in the tropical Indian Ocean, where two types of WPB-related initial errors display opposite patterns and a west–east dipole. In contrast, the occurrence of the SPB is mainly caused by initial errors in the tropical Pacific Ocean, where two types of SPB-related initial errors exhibit opposite patterns, with one pole in the subsurface western Pacific Ocean and the other in the upper eastern Pacific Ocean. Both of the WPB-related initial errors grow the fastest in winter, because the coupled system is at its weakest, and finally cause a significant WPB. The SPB-related initial errors develop into a La Ni ?na–like mode in the Pacific Ocean. The negative SST errors in the Pacific Ocean induce westerly wind anomalies in the Indian Ocean by modulating the Walker circulation in the tropical oceans. The westerly wind anomalies first cool the sea surface water in the eastern Indian Ocean. When the climatological wind direction reverses in summer, the wind anomalies in turn warm the sea surface water, finally causing a significant SPB. Therefore, in addition to the spatial patterns of the initial errors, the climatological conditions also play an important role in causing a significant predictability barrier. | Rong FENG Wansuo DUAN | 2018 | Advances in Atmospheric Sciences2018，35，10： | 2 |
| 16 | Causes and Predictability of the 2021 Spring Southwestern China Severe Drought显示文摘In the spring of 2021,southwestern China(SWC)experienced extreme drought,accompanied by the highest seasonal-mean temperature record since 1961.This drought event occurred in the decaying phase of a La Niña event with negative geopotential height anomalies over the Philippine Sea,which is distinct from the historical perspective.Historically,spring drought over SWC is often linked to El Niño and strong western North Pacific subtropical high.Here,we show that the extreme drought in the spring of 2021 may be mainly driven by the atmospheric internal variability and amplified by the warming trend.Specifically,the evaporation increase due to the high temperature accounts for about 30%of drought severity,with the contributions of its linear trend portion being nearly 20%and the interannual variability portion being about 10%.Since the sea surface temperature forcing from the tropical central and eastern Pacific played a minor role in the occurrence of drought,it is a challenge for a climate model to capture the 2021 SWC drought beyond one-month lead times. | Yunyun LIU Zeng-Zhen HU Renguang WU Xing YUAN | 2022 | Advances in Atmospheric Sciences2022，39，10： | 2 |
| 17 | Optimal Initial Error Growth in the Prediction of the Kuroshio Large Meander Based on a High-resolution Regional Ocean Model显示文摘Based on the high-resolution Regional Ocean Modeling System(ROMS) and the conditional nonlinear optimal perturbation(CNOP) method, this study explored the effects of optimal initial errors on the prediction of the Kuroshio large meander(LM) path, and the growth mechanism of optimal initial errors was revealed. For each LM event, two types of initial error(denoted as CNOP1 and CNOP2) were obtained. Their large amplitudes were found located mainly in the upper 2500 m in the upstream region of the LM, i.e., southeast of Kyushu. Furthermore, we analyzed the patterns and nonlinear evolution of the two types of CNOP. We found CNOP1 tends to strengthen the LM path through southwestward extension. Conversely,CNOP2 has almost the opposite pattern to CNOP1, and it tends to weaken the LM path through northeastward contraction.The growth mechanism of optimal initial errors was clarified through eddy-energetics analysis. The results indicated that energy from the background field is transferred to the error field because of barotropic and baroclinic instabilities. Thus, it is inferred that both barotropic and baroclinic processes play important roles in the growth of CNOP-type optimal initial errors. | Xia LIU Qiang WANG Mu MU | 2018 | Advances in Atmospheric Sciences2018，35，11： | 2 |
| 18 | The Predictability of Ocean Environments that Contributed to the 2020/21 Extreme Cold Events in China:2020/21 La Niña and 2020 Arctic Sea Ice Loss显示文摘Several consecutive extreme cold events impacted China during the first half of winter 2020/21,breaking the low-temperature records in many cities.How to make accurate climate predictions of extreme cold events is still an urgent issue.The synergistic effect of the warm Arctic and cold tropical Pacific has been demonstrated to intensify the intrusions of cold air from polar regions into middle-high latitudes,further influencing the cold conditions in China.However,climate models failed to predict these two ocean environments at expected lead times.Most seasonal climate forecasts only predicted the 2020/21 La Niña after the signal had already become apparent and significantly underestimated the observed Arctic sea ice loss in autumn 2020 with a 1-2 month advancement.In this work,the corresponding physical factors that may help improve the accuracy of seasonal climate predictions are further explored.For the 2020/21 La Niña prediction,through sensitivity experiments involving different atmospheric-oceanic initial conditions,the predominant southeasterly wind anomalies over the equatorial Pacific in spring of 2020 are diagnosed to play an irreplaceable role in triggering this cold event.A reasonable inclusion of atmospheric surface winds into the initialization will help the model predict La Niña development from the early spring of 2020.For predicting the Arctic sea ice loss in autumn 2020,an anomalously cyclonic circulation from the central Arctic Ocean predicted by the model,which swept abnormally hot air over Siberia into the Arctic Ocean,is recognized as an important contributor to successfully predicting the minimum Arctic sea ice extent. | Fei ZHENG Ji-Ping LIU Xiang-Hui FANG Mi-Rong SONG Chao-Yuan YANG Yuan YUAN Ke-Xin LI Ji WANG Jiang ZHU | 2022 | Advances in Atmospheric Sciences2022，39，4： | 2 |
| 19 | Determination of the Backward Predictability Limit and Its Relationship with the Forward Predictability Limit显示文摘In this work, two types of predictability are proposed—forward and backward predictability—and then applied in the nonlinear local Lyapunov exponent approach to the Lorenz63 and Lorenz96 models to quantitatively estimate the local forward and backward predictability limits of states in phase space. The forward predictability mainly focuses on the forward evolution of initial errors superposed on the initial state over time, while the backward predictability is mainly concerned with when the given state can be predicted before this state happens. From the results, there is a negative correlation between the local forward and backward predictability limits. That is, the forward predictability limits are higher when the backward predictability limits are lower, and vice versa. We also find that the sum of forward and backward predictability limits of each state tends to fluctuate around the average value of sums of the forward and backward predictability limits of sufficient states.Furthermore, the average value is constant when the states are sufficient. For different chaotic systems, the average value is dependent on the chaotic systems and more complex chaotic systems get a lower average value. For a single chaotic system,the average value depends on the magnitude of initial perturbations. The average values decrease as the magnitudes of initial perturbations increase. | Xuan LI Ruiqiang DING Jianping LI | 2019 | Advances in Atmospheric Sciences2019，36，6： | 1 |
| 20 | Uncertainties and error growth in forecasting the record-breaking rainfall in Zhengzhou,Henan on 19–20 July 2021显示文摘This study explores the controlling factors of the uncertainties and error growth at different spatial and temporal scales in forecasting the high-impact extremely heavy rainfall event that occurred in Zhengzhou,Henan Province China on 19−20 July 2021 with a record-breaking hourly rainfall exceeding 200 mm and a 24-h rainfall exceeding 600 mm.Results show that the strengths of the mid-level low-pressure system,the upper-level divergence,and the low-level jet determine both the amount of the extreme 24-h accumulated and hourly rainfall at 0800 UTC.The forecast uncertainties of the accumulated rainfall are insensitive to the magnitude and the spatial structure of the tiny,unobservable errors in the initial conditions of the ensemble forecasts generated with Global Ensemble Forecast System(GEFS)or sub-grid-scale perturbations,suggesting that the predictability of this event is intrinsically limited.The dominance of upscale rather than upamplitude error growth is demonstrated under the regime of k^(−5/3) power spectra by revealing the inability of large-scale errors to grow until the amplitude of small-scale errors has increased to an adequate amplitude,and an apparent transfer of the fastest growing scale from smaller to larger scales with a slower growth rate at larger scales.Moist convective activities play a critical role in enhancing the overall error growth rate with a larger error growth rate at smaller scales.In addition,initial perturbations with different structures have different error growth features at larger scales in different variables in a regime transitioning from the k^(−5/3) to k^(−3) power law.Error growth with conditional nonlinear optimal perturbation(CNOP)tends to be more upamplitude relative to the GEFS or sub-grid-scale perturbations possibly owing to the inherited error growth feature of CNOP,the inability of convective parameterization scheme to rebuild the k^(−5/3) power spectra at the mesoscales,and different error growth characteristics in the k^(−5/3) and k^(−3) regimes. | Yunji ZHANG Huizhen YU Murong ZHANG Yawen YANG Zhiyong MENG | 2022 | Science China Earth Sciences2022，65，10： | 1 |
您所在的机构暂未开通此部分的功能，请联系管理员