以中尺度非静力WRF模式的格点预报结果作为云模式的初值集合,经云模式的多初值雷暴预报及预报结果的集合分析,建立了雷暴云的集合预报方法。将该方法应用于南京周边地区未来一天雷暴天气的特征预报,并利用南京夏季9个雷暴天气的多普勒雷达资料(SCIT,storm cell identification and tracking)进行预报效果的检验。结果表明,雷暴云的集合预报对研究区域内未来一天雷暴强度、分布预报效果较好,尤其对强雷暴的分布有较强的预警预测能力。此外,雷暴持续时间概率密度分布的集合预报产品,在雷暴影响范围概率预报上的应用,提高了雷达对雷暴的预警监测能力。
Most ocean-atmosphere coupled models have difficulty in predicting the E1 Nifio-Southern Oscillation （ENSO） when starting from the boreal spring season. However, the cause of this spring predictability barrier （SPB） phenomenon remains elusive. We investigated the spatial characteristics of optimal initial errors that cause a significant SPB for E1 Nifio events by using the monthly mean data of the pre-industrial （PI） control runs from several models in CMIP5 experiments. The results indicated that the SPB-related optimal initial errors often present an SST pattern with positive errors in the central-eastern equatorial Pa- cific, and a subsurface temperature pattern with positive errors in the upper layers of the eastern equatorial Pacific, and nega- tive errors in the lower layers of the western equatorial Pacific. The SPB-related optimal initial errors exhibit a typical La Ni- fia-like evolving mode, ultimately causing a large but negative prediction error of the Nifio-3.4 SST anomalies for El Nifio events. The negative prediction errors were found to originate from the lower layers of the western equatorial Pacific and then grow to be large in the eastern equatorial Pacific. It is therefore reasonable to suggest that the E1 Nifio predictions may be most sensitive to the initial errors of temperature in the subsurface layers of the western equatorial Pacific and the Nifio-3.4 region, thus possibly representing sensitive areas for adaptive observation. That is, if additional observations were to be preferentially deployed in these two regions, it might be possible to avoid large prediction errors for E1 Nifio and generate a better forecast than one based on additional observations targeted elsewhere. Moreover, we also confirmed that the SPB-related optimal initial errors bear a strong resemblance to the optimal precursory disturbance for E1 Nifio and La Nifia events. This indicated that im- provement of the observation network by additional observations in the identified sensitive areas would also be
Atlantic thermohaline circulation(THC) is a key component of the Earth Climate System and identification of its changes during the 20th Century is critical to the understanding of its variation characteristics and the corresponding climatic impacts.Previous researches have been inconclusive,with the results varying depending on the approach used to measure THC.The results for the two established approaches for measurement of the phenomenon(direct observation and indirect reconstruction) are contradictive(weakening and non-weakening),and their credibility needs improving.Based on the tight relationship between THC anomaly and "see-saw" intensities of Sea Surface Temperature(SST) and Surface Air Temperature(SAT),we first diagnose their quantitative relationship in the model experiments,which is corresponding to its two possible scenarios,and then reconstruct the changes of THC during the 20th Century respectively with multiple observed datasets of SST and SAT.Model results show that THC anomaly and SST/SAT "see-saw" intensities are well correlated in timescales longer than 10/40 years under scenarios of weakening/non-weakening respectively.Two kinds of reconstructions here are consistent with each other,and we propose that THC has undergone a 2-cycle oscillation with inter-decadal scale since the Industrial Revolution with a magnitude of about 1 Sv.The transformation times of decadal trend are around the mid-1910s,the 1940s,and the mid-1970s.This research further validates the main results of previous reconstructions,and points out that THC does not have a long-term weakening during the 20th Century.
利用第5次耦合模式比较计划(CMIP5)中35个全球气候模式历史模拟与RCP4.5预估结果,通过贝叶斯模型平均(Bayesian Model Averaging,BMA)对中国气温进行多模式集合研究,给出了中国未来气温变化预估及其不确定性的时空分布。结果表明,中国21世纪冬夏将持续升温,且升温具有冬季高于夏季,北方高于南方的特点。初期(2016—2035年)北方有很大可能(>80%)升温超过0.7℃,南方升温相同幅度的概率则超过50%;中期(2046—2065年)北方和南方升温超过1.5℃的概率分别为80%和50%;末期(2081—2100年),北方(南方)有80%(50%)的可能的升温超过2℃。气温预估的不确定性研究发现,无论冬夏,21世纪不同时期升温相对较弱的塔里木盆地、青藏高原南侧和中国东南地区为不确定性低值区,基本低于0.6℃,对应可信度较高,如21世纪初期信噪比超过4;而不确定性的高值区则主要分布在新疆北部、东北平原北部和青藏高原东南侧等升温相对较大的地区,普遍高于1℃,对应可信度较低,如初期信噪比低于2.5。此外,基于信噪比对比发现除青藏高原东部外,其他区域夏季预估的可信度均高于冬季,21世纪末期高于初期,且空间分布特征一致。
An initial conditions （ICs） perturbation method was developed with the aim to improve an operational regional ensemble prediction system （REPS）. Three issues were identified and investigated： （1） the impacts of perturbation scale on the ensemble spread and forecast skill of the REPS; （2） the scale characteristic of the IC perturbations of the REPS; and （3） whether the REPS＇s skill could be improved by adding large-scale information to the IC perturbations. Numerical experiments were conducted to reveal the impact of perturbation scale on the ensemble spread and forecast skill. The scales of IC perturbations from the REPS and an operational global ensemble prediction system （GEPS） were analyzed. A ＂multi-scale blending＂ （MSB） IC perturbation scheme was developed, and the main findings can be summarized as follows： The growth rates of the ensemble spread of the REPS are sensitive to the scale of the IC perturbations; the ensemble forecast skills can benefit from large-scale perturbations; the global ensemble IC perturbations exhibit more power at larger scales, while the regional ensemble IC perturbations contain more power at smaller scales; the MSB method can generate IC perturbations by combining the small-scale component from the REPS and the large-scale component from the GEPS; the energy norm growth of the MSB-generated perturbations can be appropriate at all forecast lead times; and the MSB-based REPS shows higher skill than the original system, as determined by ensemble forecast verification.
Previous studies suggest that the atmospheric precursor of E1 Nifio-Southern Oscillation （ENSO） in the extratropical Southern Hemisphere （SH） might trigger a quadrapole sea surface temperature anomaly （SSTA） in the South Pacific and subsequently influence the following ENSO. Such a quadrapole SSTA is referred to as the South Pacific quadrapole （SPQ）. The present study investigated the relationships between the atmospheric precursor signal of ENSO and leading modes of atmospheric variability in the extratropical SH [including the SH annular mode （SAM）, the first Pacific-South America （PSA1） mode, and the second Pacific-South America （PSA2） mode]. The results showed that the atmospheric precursor signal in the extratropical SH basically exhibits a barotropic wavenumber-3 structure over the South Pacific and is significantly correlated with the SAM and the PSA2 mode during austral summer. Nevertheless, only the PSA2 mode was found to be a precursor for the following ENSO. It leads the SPQ-like SSTA by around one month, while the SAM and the PSA1 mode do not show any obvious linkage with either ENSO or the SPQ. This suggests that the PSA2 mode may provide a bridge between the preceding circulation anomalies over the extratropical SH and the following ENSO through the SPQ-like SSTA.
