Possible Sources of Forecast Errors Generated by the Global/Regional Assimilation and Prediction System for Landfalling Tropical Cyclones. Part Ⅱ: Model Uncertainty

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.

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

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.

A Reconstructed Wind Stress Dataset for Climate Research over the Tropical Pacific during a 153-Year Period

There are close relationships between the sea surface temperature (SST) and the surface wind over the tropical Pacific.To study the past climate variability over the tropical Pacific,the long-term monthly wind stress anomalies over the tropical Pacific for the period of 1856–2008 are reconstructed with an SVD (singular value decomposition)-based statistical atmospheric model,where the wind stress anomalies are slave and directly correspond to the SST anomalies.The verification results show that the reconstructed wind stress data have high correlations and a small root mean square (RMS) error with the three reanalysis/simulated surface wind datasets from the last 50 years.In addition,the simulated SST anomalies from an intermediate oceanic model (IOM),which is forced by the reconstructed wind stress,can simulate the realistic interannual and decadal variability of the ENSO (El Nio-Southern Oscillation);this indicates that this new long-term wind stress dataset is useful for various climate studies,especially for the large-scale interannual and decadal variability.

Ocean Response to a Climate Change Heat-Flux Perturbation in an Ocean Model and Its Corresponding Coupled Model

State-of-the-art coupled general circulation models(CGCMs)are used to predict ocean heat uptake(OHU)and sealevel change under global warming.However,the projections of different models vary,resulting in high uncertainty.Much of the inter-model spread is driven by responses to surface heat perturbations.This study mainly focuses on the response of the ocean to a surface heat flux perturbation F,as prescribed by the Flux-Anomaly-Forced Model Intercomparison Project(FAFMIP).The results of ocean model were compared with those of a CGCM with the same ocean component.On the global scale,the changes in global mean temperature,ocean heat content(OHC),and steric sea level(SSL)simulated in the OGCM are generally consistent with CGCM simulations.Differences in changes in ocean temperature,OHC,and SSL between the two models primarily occur in the Arctic and Atlantic Oceans(AA)and the Southern Ocean(SO)basins.In addition to the differences in surface heat flux anomalies between the two models,differences in heat exchange between basins also play an important role in the inconsistencies in ocean climate changes in the AA and SO basins.These discrepancies are largely due to both the larger initial value and the greater weakening change of the Atlantic meridional overturning circulation(AMOC)in CGCM.The greater weakening of the AMOC in the CGCM is associated with the atmosphere–ocean feedback and the lack of a restoring salinity boundary condition.Furthermore,differences in surface salinity boundary conditions between the two models contribute to discrepancies in SSL changes.

Multiscale Combined Action and Disturbance Characteristics of Pre-summer Extreme Precipitation Events over South China

The dominant frequency modes of pre-summer extreme precipitation events(EPEs)over South China(SC)between1998 and 2018 were investigated.The 67 identified EPEs were all characterized by the 3-8-d(synoptic)frequency band.However,multiscale combined modes of the synoptic and three low-frequency bands[10-20-d(quasi-biweekly,QBW);15-40-d(quasi-monthly,QM);and 20-60-d(intraseasonal)]accounted for the majority(63%)of the EPEs,and the precipitation intensity on the peak wet day was larger than that of the single synoptic mode.It was found that EPEs form within strong southwesterly anomalous flows characterized by either lower-level cyclonic circulation over SC or a deep trough over eastern China.Bandpass-filtered disturbances revealed the direct precipitating systems and their life cycles.Synoptic-scale disturbances are dominated by mid-high latitude troughs,and the cyclonic anomalies originate from downstream of the Tibetan Plateau(TP).Given the warm and moist climate state,synoptic-scale northeasterly flows can even induce EPEs.At the QBW and QM scales,the disturbances originate from the tropical Pacific,downstream of the TP,or mid-high latitudes(QBW only).Each is characterized by cyclonic-anticyclonic wave trains and intense southwesterly flows between them within a region of large horizontal pressure gradient.The intraseasonal disturbances are confined to tropical regions and influence SC by marginal southwesterly flows.It is concluded that low-frequency disturbances provide favorable background conditions for EPEs over SC and synoptic-scale disturbances ultimately induce EPEs on the peak wet days.Both should be simultaneously considered for EPE predictions over SC.

Uncertainties of ENSO-related Regional Hadley Circulation Anomalies within Eight Reanalysis Datasets

El Nino-Southern Oscillation(ENSO),the leading mode of global interannual variability,usually intensifies the Hadley Circulation(HC),and meanwhile constrains its meridional extension,leading to an equatorward movement of the jet system.Previous studies have investigated the response of HC to ENSO events using different reanalysis datasets and evaluated their capability in capturing the main features of ENSO-associated HC anomalies.However,these studies mainly focused on the global HC,represented by a zonal-mean mass stream function(MSF).Comparatively fewer studies have evaluated HC responses from a regional perspective,partly due to the prerequisite of the Stokes MSF,which prevents us from integrating a regional HC.In this study,we adopt a recently developed technique to construct the three-dimensional structure of HC and evaluate the capability of eight state-of-the-art reanalyses in reproducing the regional HC response to ENSO events.Results show that all eight reanalyses reproduce the spatial structure of HC responses well,with an intensified HC around the central-eastern Pacific but weakened circulations around the Indo-Pacific warm pool and tropical Atlantic.The spatial correlation coefficient of the three-dimensional HC anomalies among the different datasets is always larger than 0.93.However,these datasets may not capture the amplitudes of the HC responses well.This uncertainty is especially large for ENSO-associated equatorially asymmetric HC anomalies,with the maximum amplitude in Climate Forecast System Reanalysis(CFSR)being about 2.7 times the minimum value in the Twentieth Century Reanalysis(20CR).One should be careful when using reanalysis data to evaluate the intensity of ENSO-associated HC anomalies.

Will the Globe Encounter the Warmest Winter after the Hottest Summer in 2023?

In the boreal summer and autumn of 2023,the globe experienced an extremely hot period across both oceans and continents.The consecutive record-breaking mean surface temperature has caused many to speculate upon how the global temperature will evolve in the coming 2023/24 boreal winter.In this report,as shown in the multi-model ensemble mean(MME)prediction released by the Institute of Atmospheric Physics at the Chinese Academy of Sciences,a medium-to-strong eastern Pacific El Niño event will reach its mature phase in the following 2−3 months,which tends to excite an anomalous anticyclone over the western North Pacific and the Pacific-North American teleconnection,thus serving to modulate the winter climate in East Asia and North America.Despite some uncertainty due to unpredictable internal atmospheric variability,the global mean surface temperature(GMST)in the 2023/24 winter will likely be the warmest in recorded history as a consequence of both the El Niño event and the long-term global warming trend.Specifically,the middle and low latitudes of Eurasia are expected to experience an anomalously warm winter,and the surface air temperature anomaly in China will likely exceed 2.4 standard deviations above climatology and subsequently be recorded as the warmest winter since 1991.Moreover,the necessary early warnings are still reliable in the timely updated mediumterm numerical weather forecasts and sub-seasonal-to-seasonal prediction.

The Relationship between the East Asian Subtropical Westerly Jet and Summer Precipitation over East Asia as Simulated by the IAP AGCM4.0

Based on a 30-year Atmospheric Model Intercomparison Project(AMIP) simulation using IAP AGCM4.0, the relationship between the East Asian subtropical westerly jet(EASWJ) and summer precipitation over East Asia has been investigated, and compared with observation. It was found the meridional displacement of the EASWJ has a closer relationship with the precipitation over East Asia both from model simulation and observation, with an anomalous southward shift of EASWJ being conducive to rainfall over the Yangtze-Huaihe River Valley(YHRV), and an anomalous northward shift resulting in less rainfall over the YHRV. However, the simulated precipitation anomalies were found to be weaker than observed from the composite analysis, and this would be related to the weakly reproduced mid-upper-level convergence in the mid-high latitudes and ascending motion in the lower latitudes.

The 2020/21 Extremely Cold Winter in China Influenced by the Synergistic Effect of La Niña and Warm Arctic

In the first half of winter 2020/21,China has experienced an extremely cold period across both northern and southern regions,with record-breaking low temperatures set in many stations of China.Meanwhile,a moderate La Niña event which exceeded both oceanic and atmospheric thresholds began in August 2020 and in a few months developed into its mature phase,just prior to the 2020/21 winter.In this report,the mid−high-latitude large-scale atmospheric circulation anomalies in the Northern Hemisphere,which were forced by the negative phase of Arctic Oscillation,a strengthened Siberian High,an intensified Ural High and a deepened East Asian Trough,are considered to be the direct reason for the frequent cold surges in winter 2020/21.At the same time,the synergistic effect of the warm Arctic and the cold tropical Pacific(La Niña)provided an indispensable background,at a hemispheric scale,to intensify the atmospheric circulation anomalies in middle-to-high latitudes.In the end,a most recent La Niña prediction is provided and the on-coming evolution of climate is discussed for the remaining part of the 2020/21 winter for the purpose of future decision-making and early warning.

Global Upper Ocean Heat Content Estimation: Recent Progress and the Remaining Challenges

Ocean heat content(OHC)change contributes substantially to global sea level rise,so it is a vital task for the climate research community to estimate historical OHC.While there are large uncertainties regarding its value,in this study,the authors discuss recent progress to reduce the errors in OHC estimates,including corrections to the systematic biases in expendable bathythermograph(XBT)data,filling gaps in the data,and choosing a proper climatology.These improvements lead to a better reconstruction of historical upper(0–700 m)OHC change,which is presented in this study as the Institute of Atmospheric Physics(IAP)version of historical upper OHC assessment.Challenges still remain;for example,there is still no general consensus on mapping methods.Furthermore,we show that Coupled Model Intercomparison Project,Phase 5(CMIP5)simulations have limited ability in capturing the interannual and decadal variability of historical upper OHC changes during the past 45 years.

Effect of Decadal Changes in Air-Sea Interaction on the Climate Mean State over the Tropical Pacific

Collaboration of interannual variabilities and the climate mean state determines the type of El Nio. Recent studies highlight the impact of a La Nia-like mean state change, which acts to suppress the convection and low-level convergence over the central Pacific, on the predominance of central Pacific(CP) El Nio in the most recent decade. However, how interannual variabilities affect the climate mean state has been less thoroughly investigated. Using a linear shallow-water model, the effect of decadal changes of air-sea interaction on the two types of El Nio and the climate mean state over the tropical Pacific is examined. It is demonstrated that the predominance of the eastern Pacific(EP) and CP El Nio is dominated mainly by relationships between anomalous wind stresses and sea surface temperature(SST). Furthermore, changes between air-sea interactions from 1980–98 to 1999–2011 prompted the generation of the La Nialike pattern, which is similar to the background change in the most recent decade.

Simulating Eastern-and Central-Pacific Type ENSO Using a Simple Coupled Model

Severe biases exist in state-of-the-art general circulation models（GCMs） in capturing realistic central-Pacific（CP） El Nino structures. At the same time, many observational analyses have emphasized that thermocline（TH） feedback and zonal advective（ZA） feedback play dominant roles in the development of eastern-Pacific（EP） and CP El Nino-Southern Oscillation（ENSO）, respectively. In this work, a simple linear air-sea coupled model, which can accurately depict the strength distribution of the TH and ZA feedbacks in the equatorial Pacific, is used to investigate these two types of El Nino. The results indicate that the model can reproduce the main characteristics of CP ENSO if the TH feedback is switched off and the ZA feedback is retained as the only positive feedback, confirming the dominant role played by ZA feedback in the development of CP ENSO. Further experiments indicate that, through a simple nonlinear control approach, many ENSO characteristics,including the existence of both CP and EP El Nino and the asymmetries between El Nino and La Nina, can be successfully captured using the simple linear air-sea coupled model. These analyses indicate that an accurate depiction of the climatological sea surface temperature distribution and the related ZA feedback, which are the subject of severe biases in GCMs, is very important in simulating a realistic CP El Nino.

Predicting Western Pacific Subtropical High Using a Combined Tropical Indian Ocean Sea Surface Temperature Forecast

Weather and climate in East China are closely related to the variability of the western Pacific subtropical high(WPSH), which is an important part of the Asian monsoon system. The WPSH prediction in spring and summer is a critical component of rainfall forecasting during the summer flood season in China. Although many attempts have been made to predict WPSH variability, its predictability remains limited in practice due to the complexity of the WPSH evolution. Many studies have indicated that the sea surface temperature(SST) over the tropical Indian Ocean has a significant effect on WPSH variability. In this paper, a statistical model is developed to forecast the monthly variation in the WPSH during the spring and summer seasons on the basis of its relationship with SST over the tropical Indian Ocean. The forecasted SST over the tropical Indian Ocean is the predictor in this model, which differs significantly from other WPSH prediction methods. A 26-year independent hindcast experiment from 1983 to 2008 is conducted and validated in which the WPSH prediction driven by the combined forecasted SST is compared with that driven by the persisted SST. Results indicate that the skill score of the WPSH prediction driven by the combined forecasted SST is substantial.

Preliminary Studies on Predicting the Tropical Indian Ocean Sea Surface Temperature through Combined Statistical Methods and Dynamic ENSO Prediction

The sea surface temperature(SST) in the Indian Ocean affects the regional climate over the Asian continent mostly through a modulation of the monsoon system.It is still difficult to provide an a priori indication of the seasonal variability over the Indian Ocean.It is widely recognized that the warm and cold events of SST over the tropical Indian Ocean are strongly linked to those of the equatorial eastern Pacific.In this study,a statistical prediction model has been developed to predict the monthly SST over the tropical Indian Ocean.This model is a linear regression model based on the lag relationship between the SST over the tropical Indian Ocean and the Ni o3.4(5°S-5°N,170°W-120°W) SST Index.The predictor(i.e.,Ni o3.4 SST Index) has been operationally predicted by a large size ensemble El Ni o and the Southern Oscillation(ENSO) forecast system with coupled data assimilation(Leefs_CDA),which achieves a high predictive skill of up to a 24-month lead time for the equatorial eastern Pacific SST.As a result,the prediction skill of the present statistical model over the tropical Indian Ocean is better than that of persistence prediction for January 1982 through December 2009.

Analysis of the interannual variations and influencing factors of wind speed anomalies over the Beijing–Tianjin–Hebei region

风场对京津冀地区雾霾的产生和消散起着决定性作用。本文利用站点观测数据,研究了京津冀地区冬季风场的年际变化及其影响因素。研究表明,京津冀地区的冬季平均风速为2.0 m s^(-1),每年降幅为0.01 m s^(-1)。大多数情况下,强风年对应热带太平洋东部的负海温异常,而弱风年份相反。此外,京津冀地区冬季风场的年际变化还受到包括北半球中高纬度气压梯度、欧亚大陆地表温度、菲律宾东部热带太平洋海面温度等多重因素的影响。

Application of a Coupled Land Surface-Hydrological Model to Flood Simulation in the Huaihe River Basin of China

A hydrological simulation in the Huaihe River Basin(HRB) was investigated using two different models: a coupled land surface hydrological model(CLHMS), and a large-scale hydrological model(LSX-HMS). The NCEP-NCAR reanalysis dataset and observed precipitation data were used as meteorological inputs. The simulation results from both models were compared in terms of flood processes forecasting during high flow periods in the summers of 2003 and 2007, and partial high flow periods in 2000. The comparison results showed that the simulated streamflow by CLHMS model agreed well with the observations with Nash-Sutcliffe coefficients larger than 0.76, in both periods of 2000 at Lutaizi and Bengbu stations in the HRB, while the skill of the LSX-HMS model was relatively poor. The simulation results for the high flow periods in 2003 and 2007 suggested that the CLHMS model can simulate both the peak time and intensity of the hydrological processes, while the LSX-HMS model provides a delayed flood peak. These results demonstrated the importance of considering the coupling between the land surface and hydrological module in achieving better predictions for hydrological processes, and CLHMS was proven to be a promising model for future applications in flood simulation and forecasting.

Analysis of Nonstationary Wind Fluctuations Using the Hilbert-Huang Transform

Climatological patterns in wind fluctuations on time scales of 1–10 h are analyzed at a meteorological mast at the Yangmeishan wind farm, Yunnan Province,China, using a 2-yr time series of 10-min wind speed observations. For analyzing the spectral properties of nonstationary wind fluctuations in mountain terrain, the Hilbert-Huang transform(HHT) is applied to investigate climatological patterns between wind variability and several variables including time of year, time of day, wind direction, and pressure tendency. Compared with that for offshore sites, the wind variability at Yangmeishan wind farm has a more distinct diurnal cycle, but the seasonal discrepancies and the differences according to directions are not distinct, and the synoptic influences on wind variability are weaker. There is enhanced variability in spring and winter compared with summer and autumn. For flow from the main direction sector, the maximum wind variability is observed in spring. And the severe wind fluctuations are more common when the pressure tendency is rising.

Interdecadal and Interannnual Variabilities of the Antarctic Oscillation Simulated by CAM3

Based on four sets of numerical simulations prescribed with atmospheric radiative forcing and sea surface temperature(SST) forcing in the Community Atmospheric Model version 3(CAM3), the interannual and interdecadal variabilities of the Antarctic oscillation(AAO) during austral summer were studied. It was found that the interannual variability is mainly driven by SST forcing. On the other hand, atmospheric radiative forcing plays a major role in the interdecadal variability. A cooling trend was found in the high latitudes of the Southern Hemisphere(SH) when atmospheric radiative forcing was specified in the model. This cooling trend tended to enhance the temperature gradient between the mid and high latitudes in the SH, inducing a transition of the AAO from a negative to a positive phase on the interdecadal timescale. The cooling trend was also partly weakened by the SST forcing, leading to a better simulation compared with the purely atmospheric radiative forcing run. Therefore, SST forcing cannot be ignored, although it is not as important as atmospheric radiative forcing.

The Cold Vortex Circulation over Northeastern China and Regional Rainstorm Events

In this study,regional rainstorm events (RREs) in northeastern China associated with the activity of the Northeastern China Cold Vortex (NCCV) were investigated on a medium-range time scale.The RREs occurring in northeastern China could be categorized into three groups according to the distribution of heavy rainfall.The largest cluster is characterized by the rainstorm events that occur on the northwestern side of the Changbai Mountains along a southwest-northeast axis.These events occur most frequently during the post-meiyu period.The authors place particular emphasis on the RREs that belong to the largest cluster and are closely associated with the activity of the NCCV.These RREs were preconditioned by the transportation of substantial amounts of water vapor to which the anomalous western Pacific subtropical high (WPSH) contributed.The attendant anomalous WPSH was primarily driven by the anomalous transient eddy feedback forcing the nearby East Asian jet.The development of the NCCV circulation was concurrent with the RREs and acted as their primary causative factor.A perspective based on low-frequency dynamics indicates that Rossby wave packets emanated from the blocking-type circulation over northeastern Asia led to the development of the NCCV activity.

A Multivariate Empirical Orthogonal Function-Based Scheme for the Balanced Initial Ensemble Generation of an Ensemble Kalman Filter

The initial ensemble perturbations for an ensemble data assimilation system are expected to reasonably sample model uncertainty at the time of analysis to further reduce analysis uncertainty. Therefore, the careful choice of an initial ensemble perturbation method that dynamically cycles ensemble perturbations is required for the optimal performance of the system. Based on the multivariate empirical orthogonal function (MEOF) method, a new ensemble initialization scheme is developed to generate balanced initial perturbations for the ensemble Kalman filter (EnKF) data assimilation, with a reasonable consideration of the physical relationships between different model variables. The scheme is applied in assimilation experiments with a global spectral atmospheric model and with real observations. The proposed perturbation method is compared to the commonly used method of spatially-correlated random perturbations. The comparisons show that the model uncertainties prior to the first analysis time, which are forecasted from the balanced ensemble initial fields, maintain a much more reasonable spread and a more accurate forecast error covariance than those from the randomly perturbed initial fields. The analysis results are further improved by the balanced ensemble initialization scheme due to more accurate background information. Also, a 20-day continuous assimilation experiment shows that the ensemble spreads for each model variable are still retained in reasonable ranges without considering additional perturbations or inflations during the assimilation cycles, while the ensemble spreads from the randomly perturbed initialization scheme decrease and collapse rapidly.