Predictability of the western North Pacific summer climate associated with different ENSO phases by ENSEMBLES multi-model seasonal forecasts

Predictability of the western North Pacific (WNP) summer climate associated with different El Niño–Southern Oscillation (ENSO) phases is investigated in this study based on the 1-month lead retrospective forecasts of five state-of-the-art coupled models from ENSEMBLES. During the period from 1960 to 2005, the models well capture the WNP summer climate anomalies during most of years in different ENSO phases except the La Niña decaying summers. In the El Niño developing, El Niño decaying and La Niña developing summers, the prediction skills are high for the WNP summer monsoon index (WNPMI), with the prediction correlation larger than 0.7. The high prediction skills of the lower-tropospheric circulation during these phases are found mainly over the tropical western Pacific Ocean, South China Sea and subtropical WNP. These good predictions correspond well to their close teleconnection with ENSO and the high prediction skills of tropical SSTs. By contrast, for the La Niña decaying summers, the prediction skills are considerably low with the prediction correlation for the WNPMI near to zero and low prediction skills around the Philippines and subtropical WNP. These poor predictions relate to the weak summer anomalies of the WNPMI during the La Niña decaying years and no significant connections between the WNP lower-tropospheric circulation anomalies and the SSTs over the tropical central and eastern Pacific Ocean in observations. However, the models tend to predict an apparent anomalous cyclone over the WNP during the La Niña decaying years, indicating a linearity of the circulation response over WNP in the models prediction in comparison with that during the El Niño decaying years which differs from observations. In addition, the models show considerable capability in describing the WNP summer anomalies during the ENSO neutral summers. These anomalies are related to the positive feedback between the WNP lower-tropospheric circulation and the local SSTs. The models can capture this positive feedback but with some uncertainties from different ensemble members during the ENSO neutral summers.     

How are seasonal prediction skills related to models’ performance on mean state and annual cycle?

Given observed initial conditions, how well do coupled atmosphere–ocean models predict precipitation climatology with 1-month lead forecast? And how do the models’ biases in climatology in turn affect prediction of seasonal anomalies? We address these questions based on analysis of 1-month lead retrospective predictions for 21 years of 1981–2001 made by 13 state-of-the-art coupled climate models and their multi-model ensemble (MME). The evaluation of the precipitation climatology is based on a newly designed metrics that consists of the annual mean, the solstitial mode and equinoctial asymmetric mode of the annual cycle, and the rainy season characteristics. We find that the 1-month lead seasonal prediction made by the 13-model ensemble has skills that are much higher than those in individual model ensemble predictions and approached to those in the ERA-40 and NCEP-2 reanalysis in terms of both the precipitation climatology and seasonal anomalies. We also demonstrate that the skill for individual coupled models in predicting seasonal precipitation anomalies is positively correlated with its performances on prediction of the annual mean and annual cycle of precipitation. In addition, the seasonal prediction skill for the tropical SST anomalies, which are the major predictability source of monsoon precipitation in the current coupled models, is closely link to the models’ ability in simulating the SST mean state. Correction of the inherent bias in the mean state is critical for improving the long-lead seasonal prediction. Most individual coupled models reproduce realistically the long-term annual mean precipitation and the first annual cycle (solstitial mode), but they have difficulty in capturing the second annual (equinoctial asymmetric) mode faithfully, especially over the Indian Ocean (IO) and Western North Pacific (WNP) where the seasonal cycle in SST has significant biases. The coupled models replicate the monsoon rain domains very well except in the East Asian subtropical monsoon and the tropical WNP summer monsoon regions. The models also capture the gross features of the seasonal march of the rainy season including onset and withdraw of the Asian–Australian monsoon system over four major sub-domains, but striking deficiencies in the coupled model predictions are observed over the South China Sea and WNP region, where considerable biases exist in both the amplitude and phase of the annual cycle and the summer precipitation amount and its interannual variability are underestimated.     

Deficiencies and possibilities for long-lead coupled climate prediction of the Western North Pacific-East Asian summer monsoon

Long-lead prediction of waxing and waning of the Western North Pacific (WNP)-East Asian (EA) summer monsoon (WNP-EASM) precipitation is a major challenge in seasonal time-scale climate prediction. In this study, deficiencies and potential for predicting the WNP-EASM precipitation and circulation one or two seasons ahead were examined using retrospective forecast data for the 26-year period of 1981–2006 from two operational couple models which are the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS) and the Bureau of Meteorology Research Center (BMRC) Predictive Ocean–Atmosphere Model for Australia (POAMA). While both coupled models have difficulty in predicting summer mean precipitation anomalies over the region of interest, even for a 0-month lead forecast, they are capable of predicting zonal wind anomalies at 850 hPa several months ahead and, consequently, satisfactorily predict summer monsoon circulation indices for the EA region (EASMI) and for the WNP region (WNPSMI). It should be noted that the two models’ multi-model ensemble (MME) reaches 0.40 of the correlation skill for the EASMI with a January initial condition and 0.75 for the WNPSMI with a February initial condition. Further analysis indicates that prediction reliability of the EASMI is related not only to the preceding El Niño and Southern Oscillation (ENSO) but also to simultaneous local SST variability. On other hand, better prediction of the WNPSMI is accompanied by a more realistic simulation of lead–lag relationship between the index and ENSO. It should also be noted that current coupled models have difficulty in capturing the interannual variability component of the WNP-EASM system which is not correlated with typical ENSO variability. To improve the long-lead seasonal prediction of the WNP-EASM precipitation, a statistical postprocessing was developed based on the multiple linear regression method. The method utilizes the MME prediction of the EASMI and WNPSMI as predictors. It is shown that the statistical postprocessing is able to improve forecast skill for the summer mean precipitation over most of the WNP-EASM region at all forecast leads. It is noteworthy that the MME prediction, after applying statistical postprocessing, shows the best anomaly pattern correlation skill for the EASM precipitation at a 4-month lead (February initial condition) and for the WNPSM precipitation at a 5-month lead (January initial condition), indicating its potential for improving long-lead prediction of the monsoon precipitation.     

冬季和春季印度洋海温异常年际变率模态对中国东部夏季降水的可能影响过程

印度洋热力状况是影响全球气候变化和亚洲季风变异的一个重要的因素,但以往研究更多关注热带印度洋海温的变化,对南印度洋中高纬地区海温变化关注不够,由此限制了我们对印度洋的全面认识.本文研究了年际尺度上整个印度洋海温异常主导模态的特征及其对我国东部地区夏季降水的可能影响过程,以期望为气候变异研究及预测提供理论依据.研究结果表明:全印度洋海温异常年际变率的主导模态特征是在南印度洋副热带地区海温异常呈现西南—东北反向变化的偶极子模态,西极子位于马达加斯加以东南洋面,东极子位于澳大利亚以西洋面;同时,热带印度洋海温异常与东极子一致.当西极子为正的海温异常,东极子、热带印度洋为负异常时定义为正的印度洋海温异常年际变率模态;反之,则为负的印度洋海温异常年际变率模态.从冬至春,印度洋海温异常年际变率模态具有较好的季节持续性;与我国长江中游地区夏季降水显著负相关,而与我国华南地区夏季降水显著正相关.其可能的影响过程为:对于正的冬、春季印度洋海温异常年际变率模态事件,印度洋地区异常纬向风的经向大气遥相关使得热带印度洋盛行西风异常,导致春、夏季海洋性大陆对流减弱,使夏季西太平洋副热带高压强度偏弱、位置偏东偏北,造成华南地区夏季降水增多,长江中游地区降水减少;反之亦然.同时,印度洋海温异常年际变率模态可通过改变印度洋和孟加拉湾向长江中游地区的水汽输送而影响其夏季降水.     

Assessment of the Capability of ENSEMBLES Hindcasts in Predicting Spring Climate in China

Using the hindcasts provided by the Ensemble-Based Predictions of Climate Changes and Their Impacts(ENSEMBLES) project for the period of 1980–2005, the forecast capability of spring climate in China is assessed mainly from the aspects of precipitation, 2-m air temperature, and atmospheric circulations. The ENSEMBELS can reproduce the climatology and dominant empirical orthogonal function(EOF) modes of precipitation and 2-m air temperature, with some differences arising from different initialization months. The multi-model ensemble(MME) forecast of interannual variability is of good performance in some regions such as eastern China with February initialization.The spatial patterns of the MME interannual and inter-member spreads for precipitation and 2-m air temperature are consistent with those of the observed interannual spread, indicating that internal dynamic processes have major impacts on the interannual anomaly of spring climate in China. We have identified two coupled modes between intermember anomalies of the 850-hPa vorticity in spring and sea surface temperature(SST) both in spring and at a lead of 2 months, of which the first mode shows a significant impact on the spring climate in China, with an anomalous anticyclone located over Northwest Pacific and positive precipitation and southwesterly anomalies in eastern China.Our results also suggest that the SST at a lead of two months may be a predictor for the spring climate in eastern China. A better representation of the ocean–atmosphere interaction over the tropical Pacific, Northwest Pacific, and Indian Ocean can improve the forecast skill of the spring climate in eastern China.     

Seasonal prediction of African precipitation with ECHAM4–T42 ensemble simulations using a multivariate MOS re-calibration scheme

A 15 member ensemble of 20th century simulations using the ECHAM4–T42 atmospheric GCM is utilized to investigate the potential predictability of interannual variations of seasonal rainfall over Africa. Common boundary conditions are the global sea surface temperatures (SST) and sea ice extent. A canonical correlation analysis (CCA) between observed and ensemble mean ECHAM4 precipitation over Africa is applied in order to identify the most predictable anomaly patterns of precipitation and the related SST anomalies. The CCA is then used to formulate a re-calibration approach similar to model output statistics (MOS) and to derive precipitation forecasts over Africa. Predictand is the climate research unit (CRU) gridded precipitation over Africa. As predictor we use observed SST anomalies, ensemble mean precipitation over Africa and a combined vector of mean sea level pressure, streamfunction and velocity potential at 850 hPa. The different forecast approaches are compared. Most skill for African precipitation forecasts is provided by tropical Atlantic (Gulf of Guinea) SST anomalies which mainly affect rainfall over the Guinean coast and Sahel. The El Niño/Southern Oscillation (ENSO) influences southern and East Africa, however with a lower skill. Indian Ocean SST anomalies, partly independent from ENSO, have an impact particularly on East Africa. As suggested by the large agreement between the simulated and observed precipitation, the ECHAM4 rainfall provides a skillful predictor for CRU precipitation over Africa. However, MOS re-calibration is needed in order to provide skillful forecasts. Forecasts using MOS re-calibrated model precipitation are at least as skillful as forecast using dynamical variables from the model or instantaneous SST. In many cases, MOS re-calibrated precipitation forecasts provide more skill. However, differences are not systematic for all regions and seasons, and often small.     

Spring Indian Ocean-western Pacific SST contrast and the East Asian summer rainfall anomaly

studying the relationship between SST in the tropical Indian Ocean （TIO）, tropical western Pacific （TWP）, and tropical eastern Pacific （TEP） and East Asian summer rainfall （EASR）, using data provided by NOAA/OAR/ESRL PSD and the National Climate Center of China for the period 1979-2008, an index, SSTDI, was defined to describe the SST difference between the TIO and TWP. In comparison with the winter ENSO, the spring SST contrast between the TIO and TWP was found to be more significantly associated with summer rainfall in East Asia, especially along the EASR band and in Northeast China. This spring SST contrast can persist into summer, resulting in a more significant meridional teleconnection pattern of lower-tropospheric circulation anomalies over the western North Pacific and East Asia. These circulation anomalies are dynamically consistent with the summer rainfall anomaly along the EASR band. When the SSTDI is higher （lower） than normal, the EASR over the Yangtze River valley, Korea, and central and southern Japan is heavier （less） than normal. The present results suggest that this spring SST contrast can be used as a new and better predictor of EASR anomalies.     

夏季亚洲对流层中上层温度年际变率的预测水平评估及其在我国东部降水预测中的应用

夏季亚洲对流层温度异常与中国东部夏季降水紧密相关并可能作为降水的有效预报因子。基于欧盟ENSEMBLES计划的季节预测试验耦合模式每年5月1日开始的回报试验，分析了其对1960～2005年夏季亚洲对流层中上层温度（以200～500 hPa厚度替代，简称对流层温度）年际变率的预测结果，发现模式集合平均对夏季亚洲对流层温度年际变率具有较高的预报技巧，可以合理回报其前两个EOF（Empirical Orthogonal Function）主导模态（EOF1、EOF2），只是未能回报出EOF2高纬度的温度异常，模式集合平均预测的第一模态主成分（PC1）和第二模态主成分（PC2）与再分析资料的时间相关系数分别达到0.63和0.77。再分析资料中前两个EOF模态分别由ENSO（El Ni?o–Southern Oscillation）发展年印度夏季降水异常所激发的丝绸之路遥相关波列和ENSO衰减年西北太平洋夏季降水异常对应的太平洋—日本遥相关波列导致。ENSEMBLES计划可以合理预测出相应的海温异常及遥相关波列，进而合理预测出前两个EOF模态。对流层温度PC1和PC2分别表征了欧亚大陆与周围海洋之间的纬向和经向热力对比异常，模式对由PC1的预报技巧远高于前人定义的纬向热力对比的东亚夏季风指数，对前人定义的经向热力对比指数的预测技巧与PC2相当。将PC1和前人定义的经向热力对比指数作为预报因子，建立了中国夏季降水的动力—统计降尺度预测模型，交叉检验的结果表明该预报模型显著提高了东北和长江流域上游夏季降水的预报技巧。本文提出的亚洲对流层温度年际变率的EOF1及PC1，既能较好表征纬向热力对比与中国东部夏季降水显著相关，又能被模式合理预测，可以作为我国中高纬度地区，特别是东北地区降水的重要预测因子之一。     

Statistical Downscaling for Multi-Model Ensemble Prediction of Summer Monsoon Rainfall in the Asia-Pacific Region Using Geopotential Height Field

The 21-yr ensemble predictions of model precipitation and circulation in the East Asian and western North Pacific （Asia-Pacific） summer monsoon region （0°-50°N, 100° 150°E） were evaluated in nine different AGCM, used in the Asia-Pacific Economic Cooperation Climate Center （APCC） multi-model ensemble seasonal prediction system. The analysis indicates that the precipitation anomaly patterns of model ensemble predictions are substantially different from the observed counterparts in this region, but the summer monsoon circulations are reasonably predicted. For example, all models can well produce the interannual variability of the western North Pacific monsoon index （WNPMI） defined by 850 hPa winds, but they failed to predict the relationship between WNPMI and precipitation anomalies. The interannual variability of the 500 hPa geopotential height （GPH） can be well predicted by the models in contrast to precipitation anomalies. On the basis of such model performances and the relationship between the interannual variations of 500 hPa GPH and precipitation anomalies, we developed a statistical scheme used to downscale the summer monsoon precipitation anomaly on the basis of EOF and singular value decomposition （SVD）. In this scheme, the three leading EOF modes of 500 hPa GPH anomaly fields predicted by the models are firstly corrected by the linear regression between the principal components in each model and observation, respectively. Then, the corrected model GPH is chosen as the predictor to downscale the precipitation anomaly field, which is assembled by the forecasted expansion coefficients of model 500 hPa GPH and the three leading SVD modes of observed precipitation anomaly corresponding to the prediction of model 500 hPa GPH during a 19-year training period. The cross-validated forecasts suggest that this downscaling scheme may have a potential to improve the forecast skill of the precipitation anomaly in the South China Sea, western North Pacific and the East Asia Pacific regions, wh     

Interdecadal shift in the relationship between the East Asian summer monsoon and the tropical Indian Ocean

In this work, the authors investigate changes in the interannual relationship between the East Asian summer monsoon (EASM) and the tropical Indian Ocean (IO) in the late 1970s. By contrasting the correlations of the EASM index (EASMI) with the summer IO sea surface temperature anomaly (SSTA) between 1953–1975 and 1978–2000, a pronounced different correlation pattern is found in the tropical IO. The SSTA pattern similar to the positive Indian Ocean Dipole (IOD) shows a strongly positive correlation with the EASMI in 1953–1975. But in 1978–2000, significant negative correlation appears in the northern IO and the IOD-like correlation pattern disappears. It is indicated that the summer strong IOD events in 1953–1975 can cause a weaker-than-normal western North Pacific (WNP) subtropical high, which tends to favor a strong EASM. In 1978–2000, the connection between the summer IOD and the WNP circulation is disrupted by the climate shift. Instead, the northern IO shows a close connection with the WNP circulation in 1978–2000. The warming over the northern IO is associated with the significant enhanced 500 hPa geopotential height and an anomalous anticyclone over the WNP. The change in the IO–EASM relationship is attributed to the interdecadal change of the background state of the ocean–atmosphere system and the interaction between the ENSO and IO. In recent decades, the tropical IO and tropical Pacific have a warmer mean SST, which has likely strengthened (weakened) the influence of the northern IO (IOD) on the EASM. In addition, due to the increase in the ENSO variability along with the higher mean equatorial eastern Pacific SST in 1978–2000, the influence of ENSO on the East Asian summer circulation experiences a significant strengthening after the late 1970s. Because the warming over the northern IO is associated with the significant warming in the equatorial eastern Pacific, the strengthened ENSO–EASM relationship has likely also contributed to the strengthened relationship between the northern IO and the EASM in 1978–2000.     

Diversity of the Coupling Wheels in the East Asian Summer Monsoon on the Interannual Time Scale: Challenge of Summer Rainfall Forecasting in China

Two types of three-dimensional circulation of the East Asian summer monsoon(EASM) act as the coupling wheels determining the seasonal rainfall anomalies in China during 1979–2015. The first coupling mode features the interaction between the Mongolian cyclone over North Asia and the South Asian high(SAH) anomalies over the Tibetan Plateau at 200 hPa. The second mode presents the coupling between the anomalous low-level western Pacific anticyclone and upperlevel SAH via the meridional flow over Southeast Asia. These two modes are responsible for the summer rainfall anomalies over China in 24 and 7 out of 37 years, respectively. However, the dominant SST anomalies in the tropical Pacific, the Indian Ocean, and the North Atlantic Ocean fail to account for the first coupling wheel's interannual variability, illustrating the challenges in forecasting summer rainfall over China.     

Toward Understanding the Extreme Floods over Yangtze River Valley in June?July 2020: Role of Tropical Oceans※

The extreme floods in the Middle/Lower Yangtze River Valley (MLYRV) during June?July 2020 caused more than 170 billion Chinese Yuan direct economic losses. Here, we examine the key features related to this extreme event and explore relative contributions of SST anomalies in different tropical oceans. Our results reveal that the extreme floods over the MLYRV were tightly related to a strong anomalous anticyclone persisting over the western North Pacific, which brought tropical warm moisture northward that converged over the MLYRV. In addition, despite the absence of a strong El Ni?o in 2019/2020 winter, the mean SST anomaly in the tropical Indian Ocean during June?July 2020 reached its highest value over the last 40 years, and 43％ (57％) of it is attributed to the multi-decadal warming trend (interannual variability). Based on the NUIST CFS1.0 model that successfully predicted the wet conditions over the MLYRV in summer 2020 initiated from 1 March 2020 (albeit the magnitude of the predicted precipitation was only about one-seventh of the observed), sensitivity experiment results suggest that the warm SST condition in the Indian Ocean played a dominant role in generating the extreme floods, compared to the contributions of SST anomalies in the Maritime Continent, central and eastern equatorial Pacific, and North Atlantic. Furthermore, both the multi-decadal warming trend and the interannual variability of the Indian Ocean SSTs had positive impacts on the extreme floods. Our results imply that the strong multi-decadal warming trend in the Indian Ocean needs to be taken into consideration for the prediction/projection of summer extreme floods over the MLYRV in the future.     

西南季风期间斯里兰卡降水的年代际、年际变化及其与热带印度洋的联系

本文主要研究了1979—2016期间斯里兰卡在西南季风期间降水的年代际、年际变化以及与印度洋海温的联系.首先用经验正交的方法分析了斯里兰卡以及周边地区降水的时空分布,发现前两个模态能够解释超过70%的方差.其中第一模态为均一模态,且其PC1以及斯里兰卡7 a滑动平均降水序列都有年代际变化,降水异常在2000年前后异常偏多和偏少.通过合成分析发现2000年之后降水的异常减少与热带西部、中部印度洋的暖海温异常有关.暖海温异常通过调整经向环流引起了斯里兰卡上空的下沉运动,抑制了降水.在第二模态中,负的信号出现在斯里兰卡大部分地区,只有在斯里兰卡北部海角很小地区出现了正的信号.PC2表现出了年际变化,且与热带东南印度洋海温异常有显著的关系.通过Gill-Matsuno响应,热带东南印度洋海温异常造成热带北印度洋上空的气旋性环流异常,引起了水汽的辐合,从而利于降水.     

Impacts of the leading modes of tropical Indian Ocean sea surface temperature anomaly on sub-seasonal evolution of the circulation and rainfall over East Asia during boreal spring and summer

The two leading modes of the interannual variability of the tropical Indian Ocean (TIO) sea surface temperature (SST) anomaly are the Indian Ocean basin mode (IOBM) and the Indian Ocean dipole mode (IODM) from March to August. In this paper, the relationship between the TIO SST anomaly and the sub-seasonal evolution of the circulation and rainfall over East Asia during boreal spring and summer is investigated by using correlation analysis and composite analysis based on multi-source observation data from 1979 to 2013, together with numerical simulations from an atmospheric general circulation model. The results indicate that the impacts of the IOBM on the circulation and rainfall over East Asia vary remarkably from spring to summer. The anomalous anticyclone over the tropical Northwest Pacific induced by the warm IOBM is closely linked with the Pacific–Japan or East Asia–Pacific teleconnection pattern, which persists from March to August. In the upper troposphere over East Asia, the warm phase of the IOBM generates a significant anticyclonic response from March to May. In June and July, however, the circulation response is characterized by enhanced subtropical westerly flow. A distinct anomalous cyclone is found in August. Overall, the IOBM can exert significant influence on the western North Pacific subtropical high, the South Asian high, and the East Asian jet, which collectively modulate the precipitation anomaly over East Asia. In contrast, the effects of the IODM on the climate anomaly over East Asia are relatively weak in boreal spring and summer. Therefore, studying the impacts of the TIO SST anomaly on the climate anomaly in East Asia should take full account of the different sub-seasonal response during boreal spring and summer.     

Interannual variability of summertime outgoing longwave radiation over the Maritime Continent in relation to East Asian summer monsoon anomalies

The Maritime Continent (MC) is under influences of both the tropical Pacific and the Indian Ocean. Anomalous convective activities over the MC have significant impacts on the East Asian summer monsoon (EASM) and climate in China. In the present study, the variation in convective activity over the MC in boreal summer and its relationship to EASM anomalies are investigated based on regression analysis of NCEP–NCAR reanalysis and CMAP [Climate Prediction Center (CPC) Merged Analysis of Precipitation] data, with a focus on the impacts of ENSO and the Indian Ocean Dipole (IOD). The most significant interannual variability of convective activity is found over 10°S–10°N, 95°–145°E, which can be roughly defined as the key area of the MC (hereafter, KMC). Outgoing longwave radiation anomaly (OLRA) exhibits 3- to 7-yr periodicities over the KMC, and around 70% of the OLRA variance can be explained by the ENSO signal. However, distinct convection and precipitation anomalies still exist over this region after the ENSO and IOD signals are removed. Abnormally low precipitation always corresponds to positive OLRA over the KMC when negative diabatic heating anomalies and anomalous cooling of the atmospheric column lead to abnormal descending motion over this region. Correspondingly, abnormal divergence occurs in the lower troposphere while convergence occurs in the upper troposphere, triggering an East Asia–Pacific/Pacific–Japan (EAP/PJ)-like anomalous wave train that propagates northeastward and leads to a significant positive precipitation anomaly from the Yangtze River valley in China to the islands of Japan. This EAP/PJ-like wave pattern becomes even clearer after the removal of the ENSO signal and the combined effects of ENSO and IOD, suggesting that convective anomalies over the KMC have an important impact on EASM anomalies. The above results provide important clues for the prediction of EASM anomalies and associated summer precipitation anomalies in China.     

The Summer Snow Cover Anomaly over the Tibetan Plateau and Its Association with Simultaneous Precipitation over the Mei-yu–Baiu region

The summer snow anomalies over the Tibetan Plateau （TP） and their effects on climate variability are often overlooked,possibly due to the fact that some datasets cannot properly capture summer snow cover over high terrain.The satellite-derived Equal-Area Scalable Earth grid （EASE-grid） dataset shows that snow still exists in summer in the western part and along the southem flank of the TP.Analysis demonstrates that the summer snow cover area proportion （SCAP） over the TP has a significant positive correlation with simultaneous precipitation over the mei-yu-baiu （MB） region on the interannual time scale.The close relationship between the summer SCAP and summer precipitation over the MB region could not be simply considered as a simultaneous response to the Silk Road pattern and the SST anomalies in the tropical Indian Ocean and tropical central-eastern Pacific.The SCAP anomaly has an independent effect and may directly modulate the land surface heating and,consequently,vertical motion over the western TP,and concurrently induce anomalous vertical motion over the North Indian Ocean via a meridional vertical circulation.Through a zonal vertical circulation over the tropics and a Kelvin wave-type response,anomalous vertical motion over the North Indian Ocean may result in an anomalous high over the western North Pacific and modulate the convective activity in the western Pacific warm pool,which stimulates the East Asia-Pacific （EAP） pattern and eventually affects summer precipitation over the MB region.     

Relationships between the East Asian-western north pacific monsoon and ENSO simulated by FGOALS-s2

The relationships between ENSO and the East Asian-western North Pacific monsoon simulated by the Flexible Global Ocean-Atmosphere-Land System model, Spectral Version 2 (FGOALS-s2), a state-of-the-art coupled general circulation model (CGCM), are evaluated. For El Nio developing summers, FGOALS-s2 reproduces the anomalous cyclone over the western North Pacific (WNP) and associated negative precipitation anomalies in situ. In the observation, the anomalous cyclone is transformed to an anomalous anticyclone over the WNP (WNPAC) during El Nio mature winters. The model reproduces the WNPAC and associated positive precipitation anomalies over southeastern China during winter. However, the model fails to simulate the asymmetry of the wintertime circulation anomalies over the WNP between El Nio and La Nia. The simulated anomalous cyclone over the WNP (WNPC) associated with La Nia is generally symmetric about the WNPAC associated with El Nio, rather than shifted westward as that in the observation. The discrepancy can partially explain why simulated La Nin a events decay much faster than observed. In the observation, the WNPAC maintains throughout the El Nio decaying summer under the combined effects of local forcing of the WNP cold sea surface temperature anomaly (SSTA) and remote forcing from basinwide warming in the tropical Indian Ocean. FGOALS-s2 captures the two mechanisms and reproduces the WNPAC throughout the summer. However, owing to biases in the mean state, the precipitation anomalies over East Asia, especially those of the Meiyu rain belt, are much weaker than that in the observation.     

Advance and prospectus of seasonal prediction: assessment of the APCC/CliPAS 14-model ensemble retrospective seasonal prediction (1980–2004)

We assessed current status of multi-model ensemble (MME) deterministic and probabilistic seasonal prediction based on 25-year (1980–2004) retrospective forecasts performed by 14 climate model systems (7 one-tier and 7 two-tier systems) that participate in the Climate Prediction and its Application to Society (CliPAS) project sponsored by the Asian-Pacific Economic Cooperation Climate Center (APCC). We also evaluated seven DEMETER models’ MME for the period of 1981–2001 for comparison. Based on the assessment, future direction for improvement of seasonal prediction is discussed. We found that two measures of probabilistic forecast skill, the Brier Skill Score (BSS) and Area under the Relative Operating Characteristic curve (AROC), display similar spatial patterns as those represented by temporal correlation coefficient (TCC) score of deterministic MME forecast. A TCC score of 0.6 corresponds approximately to a BSS of 0.1 and an AROC of 0.7 and beyond these critical threshold values, they are almost linearly correlated. The MME method is demonstrated to be a valuable approach for reducing errors and quantifying forecast uncertainty due to model formulation. The MME prediction skill is substantially better than the averaged skill of all individual models. For instance, the TCC score of CliPAS one-tier MME forecast of Niño 3.4 index at a 6-month lead initiated from 1 May is 0.77, which is significantly higher than the corresponding averaged skill of seven individual coupled models (0.63). The MME made by using 14 coupled models from both DEMETER and CliPAS shows an even higher TCC score of 0.87. Effectiveness of MME depends on the averaged skill of individual models and their mutual independency. For probabilistic forecast the CliPAS MME gains considerable skill from increased forecast reliability as the number of model being used increases; the forecast resolution also increases for 2 m temperature but slightly decreases for precipitation. Equatorial Sea Surface Temperature (SST) anomalies are primary sources of atmospheric climate variability worldwide. The MME 1-month lead hindcast can predict, with high fidelity, the spatial–temporal structures of the first two leading empirical orthogonal modes of the equatorial SST anomalies for both boreal summer (JJA) and winter (DJF), which account for about 80–90% of the total variance. The major bias is a westward shift of SST anomaly between the dateline and 120°E, which may potentially degrade global teleconnection associated with it. The TCC score for SST predictions over the equatorial eastern Indian Ocean reaches about 0.68 with a 6-month lead forecast. However, the TCC score for Indian Ocean Dipole (IOD) index drops below 0.40 at a 3-month lead for both the May and November initial conditions due to the prediction barriers across July, and January, respectively. The MME prediction skills are well correlated with the amplitude of Niño 3.4 SST variation. The forecasts for 2 m air temperature are better in El Niño years than in La Niña years. The precipitation and circulation are predicted better in ENSO-decaying JJA than in ENSO-developing JJA. There is virtually no skill in ENSO-neutral years. Continuing improvement of the one-tier climate model’s slow coupled dynamics in reproducing realistic amplitude, spatial patterns, and temporal evolution of ENSO cycle is a key for long-lead seasonal forecast. Forecast of monsoon precipitation remains a major challenge. The seasonal rainfall predictions over land and during local summer have little skill, especially over tropical Africa. The differences in forecast skills over land areas between the CliPAS and DEMETER MMEs indicate potentials for further improvement of prediction over land. There is an urgent need to assess impacts of land surface initialization on the skill of seasonal and monthly forecast using a multi-model framework.     

南京信息工程大学气候预测系统1.0版简介

南京信息工程大学气候预测系统1.0版(NUIST CFS1.0)是基于日本海洋科学技术开发机构(JAMSTEC)的SINTEX-F模式发展而来,可以实现对全球气候异常的季节-年际预测。对过去近40 a的集合历史回报预测试验结果的评估发现,该预测系统对热带太平洋和印度洋海温异常具有良好的预测技巧,并且该系统能提前1.5~2 a对ENSO(Nino3.4指数)做出有技巧的预测(即相关系数达0.5),同时也可以提前1~2个季节对印度洋偶极子(IOD)做出有较高技巧的预测,展现了对主要热带气候信号的良好预测技巧。但是与国内外所有动力模式预测系统类似,该系统对东亚地区的气候异常预测还存在较大的不足。考虑到ENSO对东亚地区气候异常的强烈影响,本文尝试去除与ENSO预测相关的系统偏差来初步订正东亚地区夏季温度异常和降水距平百分率的预测结果。对比订正前后的结果表明,这一简单的订正方法有助于提高我国气候异常的预测准确率。同时选取2019年夏季气温异常和降水距平百分率的实时预测结果作为个例进行分析,发现订正能够提供一定的技巧改善,但与观测结果相比仍存在较大偏差,需要在今后的工作中不断改进完善。此外,本文也初步评估了NUIST CFS1.0对我国冬春季的气候预测技巧,并提供了经简单订正后的2019/2020年冬季和2020年春季的实时预测结果。     

Predictability of the summer East Asian upper-tropospheric westerly jet in ENSEMBLES multi-model forecasts

The interannual variation of the East Asian upper-tropospheric westerly jet(EAJ) significantly affects East Asian climate in summer. Identifying its performance in model prediction may provide us another viewpoint,from the perspective of uppertropospheric circulation,to understand the predictability of summer climate anomalies in East Asia. This study presents a comprehensive assessment of year-to-year variability of the EAJ based on retrospective seasonal forecasts,initiated from1 May,in the five state-of-the-art coupled models from ENSEMBLES during 1960–2005. It is found that the coupled models show certain capability in describing the interannual meridional displacement of the EAJ,which reflects the models' performance in the first leading empirical orthogonal function(EOF) mode. This capability is mainly shown over the region south of the EAJ axis. Additionally,the models generally capture well the main features of atmospheric circulation and SST anomalies related to the interannual meridional displacement of the EAJ. Further analysis suggests that the predicted warm SST anomalies in the concurrent summer over the tropical eastern Pacific and northern Indian Ocean are the two main sources of the potential prediction skill of the southward shift of the EAJ. In contrast,the models are powerless in describing the variation over the region north of the EAJ axis,associated with the meridional displacement,and interannual intensity change of the EAJ,the second leading EOF mode,meaning it still remains a challenge to better predict the EAJ and,subsequently,summer climate in East Asia,using current coupled models.