Shortcomings in climate model simulations of the ENSO-Atlantic hurricane teleconnection

A number of recent studies have used model projections to investigate how the North Atlantic environment in which tropical storms develop, as well as hurricane activity itself, might change in a warming world. However, accurate projection of the North Atlantic environment in the future requires, at a minimum, accurate representation of its mean state and variability in the current climate. Here we examine one metric of Atlantic basin tropical cyclone variability—its well-documented association with the El Ni?o-Southern Oscillation (ENSO)—in reanalyses and Intergovernmental Panel of Climate Change (IPCC) 4th Assessment Report (AR4) twentieth century and Atmospheric Model Intercomparison Project simulations. We find that no individual model provides consistently good representation of ENSO-related variability in the North Atlantic for variables relevant to hurricane activity (e.g. vertical wind shear, genesis potential). Model representation of the ENSO influence is biased due to both inaccurate representation of ENSO itself and inaccurate representation of the response to ENSO within the North Atlantic. Among variables examined, ENSO impacts on vertical wind shear and potential intensity were most poorly simulated. The multi-model ensemble mean representation of North Atlantic environmental response to ENSO is better matched with reanalysis than most individual AR4 models; however, this mean response still possesses some considerable bias. A few models do provide comparable or slightly better simulation of these ENSO-North Atlantic teleconnections than the multi-model ensemble average; however, for both the multi-model mean and the well performing models, good simulation of the ENSO-related variability of genesis potential within portions of the North Atlantic does not stem from accurate representation of the ENSO-related variability of the individual environmental variables that comprise genesis potential (e.g. vertical wind shear, potential intensity).     

The impact of tropical sea surface temperatures on various measures of Atlantic tropical cyclone activity

Summary Since 1995 there has been a resurgence of Atlantic hurricane activity, with 2005 being the most active and destructive hurricane season on record. The influence of sea surface temperatures (SSTs) upon trends in Atlantic hurricane activity is investigated by considering SSTs in the southern tropical North Atlantic, an area known as the main development region (MDR). Significant differences in hurricane activity are observed when comparing the ten coolest and ten warmest years of SSTs in the MDR for the period spanning from 1941 to 2006, with increasing MDR SSTs linked to the increased duration and frequency of tropical cyclones. It is concluded that future increases in SSTs, as climate models project, could result in increased Atlantic basin hurricane activity. Understanding how oceanic processes affecting the MDR may change with climate change could therefore help increase the predictive capability for hurricane activity. Authors’ addresses: Paul A. Steenhof, 50 Hendrick, Chelsea, Quebec, J9B 1M1 Canada; William A. Gough, Department of Physical and Environmental Sciences, University of Toronto at Scarborough, Scarborough, Ontario, Canada     

Evaluation of long-term trends in tropical cyclone intensity forecasts

Summary The National Hurricane Center and Joint Typhoon Warning Center operational tropical cyclone intensity forecasts for the three major northern hemisphere tropical cyclone basins (Atlantic, eastern North Pacific, and western North Pacific) for the past two decades are examined for long-term trends. Results show that there has been some marginal improvement in the mean absolute error at 24 and 48 h for the Atlantic and at 72 h for the east and west Pacific. A new metric that measures the percent variance of the observed intensity changes that is reduced by the forecast (variance reduction, VR) is defined to help account for inter-annual variability in forecast difficulty. Results show that there have been significant improvements in the VR of the official forecasts in the Atlantic, and some marginal improvement in the other two basins. The VR of the intensity guidance models was also examined. The improvement in the VR is due to the implementation of advanced statistical intensity prediction models and the operational version of the GFDL hurricane model in the mid-1990s. The skill of the operational intensity forecasts for the 5-year period ending in 2005 was determined by comparing the errors to those from simple statistical models with input from climatology and persistence. The intensity forecasts had significant skill out to 96 h in the Atlantic and out to 72 h in the east and west Pacific. The intensity forecasts are also compared to the operational track forecasts. The skill was comparable at 12 h, but the track forecasts were 2 to 5 times more skillful by 72 h. The track and intensity forecast error trends for the two-decade period were also compared. Results showed that the percentage track forecast improvement was almost an order of magnitude larger than that for intensity, indicating that intensity forecasting still has much room for improvement.     

Multi-year prediction skill of Atlantic hurricane activity in CMIP5 decadal hindcasts

Using a statistical relationship between simulated sea surface temperature and Atlantic hurricane activity, we estimate the skill of a CMIP5 multi-model ensemble at predicting multi-annual level of Atlantic hurricane activity. The series of yearly-initialized hindcasts show positive skill compared to simpler forecasts such as persistence and climatology as well as non-initialized forecasts and return anomaly correlation coefficients of ～0.6 and ～0.8 for five and nine year forecasts, respectively. Some skill is shown to remain in the later years and making use of those later years to create a lagged-ensemble yields, for individual models, results that approach that obtained by the multi-model ensemble. Some of the skill is shown to come from persisting rather than predicting the climate shift that occur in 1994–1995. After accounting for that shift, the anomaly correlation coefficient for five-year forecasts is estimated to drop to 0.4, but remains statistically significant up to lead years 3–7. Most of the skill is shown to come from the ability of the forecast systems at capturing change in Atlantic sea surface temperature, although the failure of most systems at reproducing the observed slow down in warming over the tropics in recent years leads to an underestimation of hurricane activity in the later period.     

Skill of synthetic superensemble hurricane forecasts for the Canadian maritime provinces

Summary From 1994 to 2003, fifty-five tropical cyclones entered the Canadian Hurricane Centre (CHC) Response Zone, or about 42% of all named Atlantic tropical cyclones in this ten-year period, and 2003 was the fourth consecutive year for a tropical cyclone to make landfall in Canada. The CHC forecasts all tropical cyclones that enter the CHC Response Zone and assumes the lead in forecasting once the cyclone enters its area of forecast responsibility. This study acknowledges the challenges of forecasting such tropical cyclones at extratropical latitudes. If a tropical cyclone has been declared extratropical, global models may no longer use vortex bogussing to carry the cyclone, and even if it is modeled, large model errors often result. The purpose of this study is to develop a new version of the Florida State University (FSU) hurricane superensemble with greater skill in tracking tropical cyclones, especially at extratropical latitudes. This has been achieved from the development of the synthetic superensemble, which is similar to the operational version of the multi-model superensemble that is used at FSU. The synthetic superensemble differs in that is has a larger set of member models consisting of regular member models, synthetic versions of these models, and the operational superensemble and its synthetic version. This synthetic superensemble is being used here to forecast hurricane tracks from the 2001, 2002, and 2003 hurricane seasons. The track forecasts from this method have generally less error than those of the member models, the operational superensemble, and the ensemble mean. This study shows that the synthetic superensemble performs consistently well and would be an asset to operational hurricane track forecasting.     

Hurricane intensity changes associated with geomagnetic variation

Recently some indications have appeared that several purely meteorological processes in the terrestrial atmosphere are dependent upon magnetosphere variations. To analyse the possible relationship with North Atlantic hurricane intensification, the authors examine geomagnetic data for ten days prior to all hurricanes over the last 50 years (1950–1999). A significant positive correlation between the averaged Kp index of global geomagnetic activity and hurricane intensity as measured by maximum sustained wind speed is identified for baroclinically-initiated hurricanes. Results are consistent with a mechanism whereby ionization processes trigger glaciation at cloud top which leads to hurricane intensification through upper tropospheric latent heat release.     

Adaptive use of research aircraft data sets for hurricane forecasts

Summary This study uses an adaptive observational strategy for hurricane forecasting. It shows the impacts of Lidar Atmospheric Sensing Experiment (LASE) and dropsonde data sets from Convection and Moisture Experiment (CAMEX) field campaigns on hurricane track and intensity forecasts. The following cases are used in this study: Bonnie, Danielle and Georges of 1998 and Erin, Gabrielle and Humberto of 2001. A single model run for each storm is carried out using the Florida State University Global Spectral Model (FSUGSM) with the European Center for Medium Range Weather Forecasts (ECMWF) analysis as initial conditions, in addition to 50 other model runs where the analysis is randomly perturbed for each storm. The centers of maximum variance of the DLM heights are located from the forecast error variance fields at the 84-hr forecast. Back correlations are then performed using the centers of these maximum variances and the fields at the 36-hr forecast. The regions having the highest correlations in the vicinity of the hurricanes are indicative of regions from where the error growth emanates and suggests the need for additional observations. Data sets are next assimilated in those areas that contain high correlations. Forecasts are computed using the new initial conditions for the storm cases, and track and intensity skills are then examined with respect to the control forecast. The adaptive strategy is capable of identifying sensitive areas where additional observations can help in reducing the hurricane track forecast errors. A reduction of position error by approximately 52% for day 3 of forecast (averaged over 7 storm cases) over the control runs is observed. The intensity forecast shows only a slight positive impact due to the model’s coarse resolution. Corresponding author’s address: T. N. Krishnamurti, Department of Meteorology, Florida State University, Tallahassee, FL 32306-4520, USA     

华北及周边地区夏季分区客观降水预报

在降水客观分区的基础上,对华北及周边地区进行夏季降水预报。利用2006—2008年的6—8月T213资料和相应时段的实况资料,通过概率回归降水等级方案建模,对2009年和2010年6—8月进行了试报。结果表明:分区建模的降水预报与单站建模预报相比,TS评分在不同时效、不同量级上均有提高,并且在空报和漏报上有较大改善,特别是大量级降水预报改善明显。从因子分析上看,分区建模较单站建模所选因子更丰富,利用了模式产品的有用信息,因此做出了更好的预报。分区建模与模式降水预报的对比分析表明:分区建模的降水预报效果好于模式直接降水预报,空报现象改善明显。     

Atlantic Basin Hurricanes: Indices of Climatic Changes

Accurate records of basinwide Atlantic and U.S. landfalling hurricanes extend back to the mid 1940s and the turn of the century, respectively, as a result of aircraft reconnaissance and instrumented weather stations along the U.S. coasts. Such long-term records are not exceeded elsewhere in the tropics. The Atlantic hurricanes, U.S. landfalling hurricanes and U.S. normalized damage time series are examined for interannual trends and multidecadal variability. It is found that only weak linear trends can be ascribed to the hurricane activity and that multidecadal variability is more characteristic of the region. Various environmental factors including Caribbean sea level pressures and 200mb zonal winds, the stratospheric Quasi-Biennial Oscillation, the El Niño-Southern Oscillation, African West Sahel rainfall and Atlantic sea surface temperatures, are analyzed for interannual links to the Atlantic hurricane activity. All show significant, concurrent relationships to the frequency, intensity and duration of Atlantic hurricanes. Additionally, variations in the El Niño-Southern Oscillation are significantly linked to changes in U.S. tropical cyclone-caused damages. Finally, much of the multidecadal hurricane activity can be linked to the Atlantic Multidecadal Mode - an empirical orthogonal function pattern derived from a global sea surface temperature record. Such linkages may allow for prediction of Atlantic hurricane activity on a multidecadal basis. These results are placed into the context of climate change and natural hazards policy.     

西北太平洋热带气旋频次的延伸期动力-统计预报方法和评估

介绍了西北太平洋热带气旋(TC)频次的延伸期预报方法,比较了新构建的动力-统计和统计预报模型的预测技巧,并探讨了预报误差来源及改进方向。动力-统计预报模型是基于动力模式预测的热带季节内振荡(ISO)信号及ISO-TC生成的同期统计关系来进行预报;统计预报模型则是基于TC生成的前兆ISO信号建模预报。预报评估结果显示,动力-统计混合预报模型的预报技巧高于统计预报模型,原因在于影响TC次季节变化的前兆信号并不稳定,且随着预报超前时间迅速消散,无法提供有效且稳定的可预报源;相反地,TC生成与同期的ISO背景场显著相关,动力模式对ISO(预报因子)有较好的预报能力,因此动力-统计相结合的预报方法为TC延伸期预报提供了有效途径。虽然目前动力-统计预报模型的预报技巧可达5～6周,但仍有进一步改进和提高的空间。通过对不同类型TC预报技巧检验和误差分析,研究认为年际和年代际背景场对ISO调控TC活动的影响不可忽略,且热带外ISO信号(如罗斯贝波破碎和西风急流强度等)对TC频次和轨迹也有显著影响,这些因子为TC延伸期预报提供了潜在可预报源。     

Statistical decadal predictions for sea surface temperatures: a benchmark for dynamical GCM predictions

Accurate decadal climate predictions could be used to inform adaptation actions to a changing climate. The skill of such predictions from initialised dynamical global climate models (GCMs) may be assessed by comparing with predictions from statistical models which are based solely on historical observations. This paper presents two benchmark statistical models for predicting both the radiatively forced trend and internal variability of annual mean sea surface temperatures (SSTs) on a decadal timescale based on the gridded observation data set HadISST. For both statistical models, the trend related to radiative forcing is modelled using a linear regression of SST time series at each grid box on the time series of equivalent global mean atmospheric CO₂ concentration. The residual internal variability is then modelled by (1) a first-order autoregressive model (AR1) and (2) a constructed analogue model (CA). From the verification of 46 retrospective forecasts with start years from 1960 to 2005, the correlation coefficient for anomaly forecasts using trend with AR1 is greater than 0.7 over parts of extra-tropical North Atlantic, the Indian Ocean and western Pacific. This is primarily related to the prediction of the forced trend. More importantly, both CA and AR1 give skillful predictions of the internal variability of SSTs in the subpolar gyre region over the far North Atlantic for lead time of 2–5 years, with correlation coefficients greater than 0.5. For the subpolar gyre and parts of the South Atlantic, CA is superior to AR1 for lead time of 6–9 years. These statistical forecasts are also compared with ensemble mean retrospective forecasts by DePreSys, an initialised GCM. DePreSys is found to outperform the statistical models over large parts of North Atlantic for lead times of 2–5 years and 6–9 years, however trend with AR1 is generally superior to DePreSys in the North Atlantic Current region, while trend with CA is superior to DePreSys in parts of South Atlantic for lead time of 6–9 years. These findings encourage further development of benchmark statistical decadal prediction models, and methods to combine different predictions.     

Sensitivity studies with the North Atlantic sigma coordinate Princeton Ocean Model

The sigma coordinate, Princeton Ocean Model (POM) has been configured for the North Atlantic Ocean between 5°N and 50°N as part of data assimilation, model predictability and intercomparison studies. The model uses a curvilinear orthogonal grid with higher resolution in the western North Atlantic and lower resolution in the eastern North Atlantic. A series of experiments, each one of a 10-year duration, are performed to evaluate the sensitivity of the ocean mean state and variability to model parameters and model configuration; these experiments include open vs. closed boundary conditions, low vs. high resolution grids, and different choices of diffusion and viscosity. The results show that the use of closed boundaries together with near-boundary buffer zones where temperature and salinity are relaxed towards the observed values give less realistic flows, weaker recirculation gyres and less realistic Gulf Stream separation than do open boundary conditions. The experiments show that the sensitivity of the ocean variability in the model to the choice of the Smagorinsky diffusion and viscosity coefficients significantly differs from one region to another and largely depends on other attributes such as the mean position of the Gulf Stream in each simulation. A 50% change in model resolution in the Gulf Stream region has a larger effect on ocean variability than a change of diffusivity by a factor of 10. In areas where either the high or the low resolution models have sufficient resolution, as in the Gulf of Mexico, they are able to produce variability comparable to that observed from altimeter data; elsewhere, model variability is underestimated.     

Decadal prediction skill in the GEOS-5 forecast system

A suite of decadal predictions has been conducted with the NASA Global Modeling and Assimilation Office’s (GMAO’s) GEOS-5 Atmosphere–Ocean general circulation model. The hind casts are initialized every December 1st from 1959 to 2010, following the CMIP5 experimental protocol for decadal predictions. The initial conditions are from a multi-variate ensemble optimal interpolation ocean and sea-ice reanalysis, and from GMAO’s atmospheric reanalysis, the modern-era retrospective analysis for research and applications. The mean forecast skill of a three-member-ensemble is compared to that of an experiment without initialization but also forced with observed greenhouse gases. The results show that initialization increases the forecast skill of North Atlantic sea surface temperature compared to the uninitialized runs, with the increase in skill maintained for almost a decade over the subtropical and mid-latitude Atlantic. On the other hand, the initialization reduces the skill in predicting the warming trend over some regions outside the Atlantic. The annual-mean atlantic meridional overturning circulation index, which is defined here as the maximum of the zonally-integrated overturning stream function at mid-latitude, is predictable up to a 4-year lead time, consistent with the predictable signal in upper ocean heat content over the North Atlantic. While the 6- to 9-year forecast skill measured by mean squared skill score shows 50 % improvement in the upper ocean heat content over the subtropical and mid-latitude Atlantic, prediction skill is relatively low in the subpolar gyre. This low skill is due in part to features in the spatial pattern of the dominant simulated decadal mode in upper ocean heat content over this region that differ from observations. An analysis of the large-scale temperature budget shows that this is the result of a model bias, implying that realistic simulation of the climatological fields is crucial for skillful decadal forecasts.     

A multi-model comparison of Atlantic multidecadal variability

A multi-model analysis of Atlantic multidecadal variability is performed with the following aims: to investigate the similarities to observations; to assess the strength and relative importance of the different elements of the mechanism proposed by Delworth et al. (J Clim 6:1993–2011, 1993) (hereafter D93) among coupled general circulation models (CGCMs); and to relate model differences to mean systematic error. The analysis is performed with long control simulations from ten CGCMs, with lengths ranging between 500 and 3600 years. In most models the variations of sea surface temperature (SST) averaged over North Atlantic show considerable power on multidecadal time scales, but with different periodicity. The SST variations are largest in the mid-latitude region, consistent with the short instrumental record. Despite large differences in model configurations, we find quite some consistency among the models in terms of processes. In eight of the ten models the mid-latitude SST variations are significantly correlated with fluctuations in the Atlantic meridional overturning circulation (AMOC), suggesting a link to northward heat transport changes. Consistent with this link, the three models with the weakest AMOC have the largest cold SST bias in the North Atlantic. There is no linear relationship on decadal timescales between AMOC and North Atlantic Oscillation in the models. Analysis of the key elements of the D93 mechanisms revealed the following: Most models present strong evidence that high-latitude winter mixing precede AMOC changes. However, the regions of wintertime convection differ among models. In most models salinity-induced density anomalies in the convective region tend to lead AMOC, while temperature-induced density anomalies lead AMOC only in one model. However, analysis shows that salinity may play an overly important role in most models, because of cold temperature biases in their relevant convective regions. In most models subpolar gyre variations tend to lead AMOC changes, and this relation is strong in more than half of the models.     

Impact of the configuration of stretching and ocean–atmosphere coupling on tropical cyclone activity in the variable-resolution GCM ARPEGE

This study starts by investigating the impact of the configuration of the variable-resolution atmospheric grid on tropical cyclone (TC) activity. The French atmospheric general circulation model ARPEGE, the grid of which is rotated and stretched over the North Atlantic basin, was used with prescribed sea surface temperatures. The study clearly shows that changing the position of the stretching pole strongly modifies the representation of TC activity over the North Atlantic basin. A pole in the centre of the North Atlantic basin provides the best representation of the TC activity for this region. In a second part, the variable-resolution climate model ARPEGE is coupled with the European oceanic global climate model NEMO in order to study the impact of ocean–atmosphere coupling on TC activity over the North Atlantic basin. Two pre-industrial runs, a coupled simulation and a simulation forced by the sea surface temperatures from the coupled one, are compared. The results show that the coupled simulation is more active in the Caribbean Sea and the Gulf of Mexico while the forced simulation is more active over eastern Florida and the eastern Atlantic. The difference in the distribution of TC activity is certainly linked with the location of TC genesis. In the forced simulation, tropical cyclogenesis is closer to the west African coast than in the coupled simulation. Moreover, the difference in TC activity over the eastern Atlantic seems to be related to two different mechanisms: the difference in African easterly wave activity over the west of Africa and the cooling produced, in the coupled simulation, by African easterly waves over the eastern Atlantic. Finally, the last part studies the impact of changing the frequency of ocean–atmosphere coupling on Atlantic TC activity. Increasing the frequency of coupling decreases the density of TC activity over the North Atlantic basin. However, it does not modify the spatial distribution of the TC activity. TC rainfalls are decreased by 8?% in the high frequency coupled run.     

An evaluation of the role of hurricane Olga (2001) in an extreme rainy event in Israel using dynamic tropopause maps

Summary During the period from end of November to early December 2001, a sequence of extremely intense synoptic developments occurred over the area from the Atlantic to Mediterranean. These included the formation of hurricane Olga, an intensification of the Icelandic Low, strengthening of the subtropical westerly jet stream (STJ) over North Africa, formation of the Red Sea Trough (RST) and Cyprus Low cyclones, which resulted in torrential rains in Israel on December 4–5. The evolution of the synoptic processes over a large area from the Atlantic to Western Europe and the Mediterranean region during November 25–December 2 is investigated here with the help of dynamic tropopause patterns calculated based on reanalysis data. It is shown that the chain of extreme weather events was triggered by the acceleration of a coherent tropopause disturbance (CTD) over the Labrador Sea. Two branches of the process may be distinguished, southern and northern. The southern one was associated with the transformation of a tropical storm into hurricane Olga, strengthening of the STJ and eventually the formation of the RST cyclone. The RST contributed to the intensification of the transport of moist air masses from equatorial Africa to the Mediterranean region. The northern branch was determined by an eastward drift of the CTD, moist air mass transport from the area of the hurricane to the North Atlantic and the European-Mediterranean region, strengthening of the Icelandic Low and formation of an upper troposphere potential vorticity-streamer system over western Scandinavia. Displacement of the streamer to the Mediterranean region and its interaction with the RST system played a major role in the development of the powerful Cyprus Low cyclone over the northeastern Mediterranean region.     

Development of statistical prediction models for Changma precipitation: An ensemble approach

An ensemble statistical forecast scheme with a one-month lead is developed to predict year-to-year variations of Changma rainfall over the Korean peninsula. Spring sea surface temperature (SST) anomalies over the North Atlantic, the North Pacific and the tropical Pacific Ocean have been proposed as useful predictors in a previous study. Through a forward-stepwise regression method, four additional springtime predictors are selected: the northern Indian Ocean (NIO) SST, the North Atlantic SST change (NAC), the snow cover anomaly over the Eurasian continent (EUSC), and the western North Pacific outgoing longwave radiation anomaly (WNP (OLR)). Using these, three new prediction models are developed. A simple arithmetic ensemble mean produces much improved forecast skills compared to the original prediction model of Lee and Seo (2013). Skill scores measured by temporal correlation and MSSS (mean square error skill score) are improved by about 9% and 17%, respectively. The GMSS (Gerrity skill score) and hit rate based on a tercile prediction validation scheme are also enhanced by about 19% and 13%, respectively. The reversed NIO, reversed WNP (OLR), and reversed NAC are all related to the enhancement of a cyclonic circulation anomaly to the south or southwest of the Korean peninsula, which induces southeasterly moisture flux into the peninsula and increasing Changma precipitation. The EUSC predictor induces an enhancement of the Okhotsk Sea high downstream and thus strengthening of Changma front.     

季节预测模式对东亚夏季环流的预测能力及其对热带海洋的响应分析

东亚夏季环流变化对中国夏季降水的年际变化有重要影响,因此需要进一步理解季节预测模式对东亚夏季环流的预测能力。利用1991~2013年美国国家环境预测中心（NCEP）、中国气象局国家气候中心（NCC）和日本东京气候中心（TCC）的三个季节预测模式（CFS V2、BCC_CSM V2和MRI-CGCM）以及NCEP/NCAR再分析资料,定量评估了模式对东亚夏季风（EASM）和夏季西太平洋副热带高压（WPSH）强度的预测能力。在此基础上,分析了模式预测的EASM和WPSH对热带海温异常的响应能力,以及ENSO事件对EASM和WPSH预测的影响,阐述了预测误差产生的原因。结果表明:整体而言,三个模式对EASM和WPSH的预测技巧较高,但TCC模式对WPSH的预测技巧相对较低。三个模式预测的850 hPa风场在西北太平洋存在一个异常气旋,使得预测的EASM偏强和WPSH偏弱。同时,二者的年际变率整体比观测小。三个模式预测的EASM和WPSH对热带海洋海温异常的响应随季节演变特征与观测比较接近,但NCEP模式和TCC模式预测的EASM对前期热带太平洋和前期、同期热带印度洋的海温异常响应要强于观测,NCC模式预测的EASM对前期和同期的热带太平洋的海温异常响应明显比观测强。此外,三个模式预测的WPSH对前期和同期的热带太平洋、热带印度洋和热带大西洋的海温异常响应明显强于观测。三个模式预测的EASM和WPSH在ENSO年的平均绝对误差（MAE）整体而言要比正常年的小很多,NCEP模式和NCC模式预测的EASM和WPSH的MAE在La Ni?a年和El Ni?o年差别不大,而TCC模式预测的EASM和WPSH的MAE在El Ni?o年比在La Ni?a年大很多,表明ENSO事件是东亚夏季环流重要的可预报源。     

Simulated decadal oscillations of the Atlantic meridional overturning circulation in a cold climate state

The significance of the Atlantic meridional overturning circulation (MOC) for regional and hemispheric climate change requires a complete understanding using fully coupled climate models. Here we present a persistent, decadal oscillation in a coupled atmosphere–ocean general circulation model. While the present study is limited by the lack of comparisons with paleo-proxy records, the purpose is to reveal a new theoretically interesting solution found in the fully-coupled climate model. The model exhibits two multi-century-long stable states with one dominated by decadal MOC oscillations. The oscillations involve an interaction between anomalous advective transport of salt and surface density in the North Atlantic subpolar gyre. Their time scale is fundamentally determined by the advection. In addition, there is a link between the MOC oscillations and North Atlantic Oscillation (NAO)-like sea level pressure anomalies. The analysis suggests an interaction between the NAO and an anomalous subpolar gyre circulation in which sea ice near and south of the Labrador Sea plays an important role in generating a large local thermal anomaly and a meridional temperature gradient. The latter induces a positive feedback via synoptic eddy activity in the atmosphere. In addition, the oscillation only appears when the Nordic Sea is completely covered by sea ice in winter, and deep convection is active only near the Irminger Sea. Such conditions are provided by a substantially colder North Atlantic climate than today.     

基于机器学习的数值天气预报风速订正研究

对风速进行准确预测是精细化天气预报服务(如风能发电、冬季奥运会赛场条件保障等)的重要环节。本文基于三种机器学习算法(LASSO回归、随机森林和深度学习),对数值天气预报模式ECMWF预测的华北地区近地面10 m风速进行订正。首先利用LASSO回归算法提取对10 m风速有重要影响的气象要素特征集,将其作为三种机器学习算法的输入,建立相应模型对ECMWF预测的风速进行订正。用提取后的气象要素特征集建模有助于减少计算量和存储开销,并减小模型的复杂性,从而提高模型的泛化能力。将订正结果与传统订正方法模式输出统计(model output statistics,MOS)得到的订正结果进行对比。结果表明,三种机器学习算法的订正效果均好于MOS方法,显示了机器学习方法在改善局地精准气象预报方面的潜力。