太平洋海温与我国大陆降水的EOF分析

该文采用经验正交函数(EOF)对太平洋海温场与我国大陆降水场作相关分析,主要基于探讨海气相互作用对我国大陆降水影响的机制和规律,分析发现:太平洋海温不仅与我国东部降水相关,而且与西部高原降水也相关,降水场存在5个高相关区域,海温场存在4个高敏感区;长江中下游地区汛期降水与赤道西太平洋海温呈负相关,与黑潮海温存正相关;不同时期海温与降水相关的敏感区是不同的。这些对我国气候预测分析特别是旱涝趋势预测具有重要的指导作用。     

两类ENSO事件前期的热带太平洋海温距平场

分析了１９５６年以来两类ＥＮＳＯ事件热带太平洋海温距平场的特征。结果指出,东部型ＥｌＮｉｎｏ事件前期为ＬａＮｉｎａ事件年,热带中东太平洋为强的海温负距平,东部型ＬａＮｉｎａ事件前期为ＥｌＮｉｎｏ事件年,热带中不太平洋为强的海温正距平,中部型ＥｌＮｉｎｏ事件前期热带中西太平洋多为明显的海温正距平,中部型ＬａＮｉｎａ事件前期热带东太平洋多为明显的海渐负距平。两类ＥＮＳＯ事件前期海温距平场特殊基本相反。     

热带太平洋和印度洋海温年际变化的均方差分析

运用1951～1997年热带（20°N～20°S,50°E～80°W）海温（SST）资料求出其各月的均方差,结果表明:太平洋海温变化相对印度洋海温变化要明显,特别是赤道中东太平洋附近 （165～90°W,6°N～6°S）的海温变化比较显著,其海温的变化范围在2～4°C左右,3～4月份海温年际变化小,11～12月海温年际变化大;“暖池”附近洋面海温年际变化也小。而印度洋海域的海温变化范围在1～2°C左右,在印度洋南半球洋面海温变化比北半球洋面海温变化相对较大。同时,根据上述海温变化特征确定了几个海温年际变化最大的关键区。     

热带西太平洋海温变化及其与赤道东太平洋海温变化的关系

利用１９５１－１９８８年１０°Ｓ－５０°Ｎ太平洋的ＳＳＴ资料对热带西太平洋海表温度的变化及其与赤道东太平洋海表温度变化的关系进行了分析，发现热带西太平洋ＳＳＴ存在准两年周期的变化。这种变化与ＥＮＳＯ活动相联系：Ｅｌ Ｎｉｎｏ年的ＳＳＴ距平值位于谷值；反Ｅｌ Ｎｉｎｏ年的ＳＳＴ距平值位于峰值。热带西太平洋与赤道东太平洋的ＳＳＴ变化存在弱的反相关关系。两者间存在位相差，前者的变化比后者超前几个月甚至１     

用北太平洋海温场资料制作月降水量预报

使用东营市1963-1996年逐月降水量资料和1962-1996年北太平洋海温资料，采取滚动式相关分析方法，建立了备选因子集。另外，应用逐步回归、最优子集回归、人工神经元网络、多因子EOF迭代等四种统计方法，分析了东营市月降水量与北太平洋海温场的关系。结果表明：东营市月降水量与北太平洋海温场存在显著相关；采用四种统计方法制作东营市月降水量预报，其预报效果均较好。     

全球变暖背景下热带太平洋海温长期趋势研究

热带太平洋对全球的气候有重要作用。然而,关于全球变暖背景下热带太平洋海温长期趋势的研究,迄今为止仍有争议。本文利用多套海表温度资料和次表层海温资料,基于无参的趋势估计方法（Theil-Sen趋势）,分析了热带太平洋海表温度长期趋势及赤道太平洋次表层海温长期趋势。多套资料的结果均表明在全球变暖背景下,热带太平洋冷舌区为长期冷趋势,而冷舌区之外的热带太平洋区域为长期暖趋势,即似La Ni?a（La Ni?a-like）海温长期趋势。此海温长期趋势是由热带太平洋冷舌模态所引起。当冷舌模态为正位相时,对应热带太平洋冷舌区为冷海温异常,而冷舌区之外的热带太平洋为暖海温异常。冷舌模态时间序列主要为长期趋势,而造成冷舌模态长期趋势的机制是全球变暖强迫下的海洋动力反馈过程。赤道太平洋的表层和次表层海温似La Ni?a型的长期趋势,是冷舌模态在表层海温和次表层海温上的不同体现。     

我国沿海地区降水量与北太平洋海温场的关联

本文利用月降水资料讨论了我国沿海地区降水量的年变化、年际变化以及各地相关性等气侯学特征。分析了各地汛期降水与北太平洋海温场的关联,得出汛期降水与前期海温的相关场的三类代表型式。     

影响山东热带气旋的频数与太平洋海温的关系

利用1949—2007年热带气旋年鉴资料,对影响山东热带气旋（TC）的频数与太平洋海温的关系进行了分析。结果表明：（1）厄尔尼诺年,影响山东的TC频数较常年明显偏少。厄尔尼诺次年TC频数较常年稍有增加。拉尼娜年影响山东的TC频数较常年显著偏多,增加明显的月份主要是8月和9月,拉尼娜次年,影响山东TC频数偏少。厄尔尼诺事件强度越大,影响山东的TC频数越少。（2）影响山东的TC数和菲律宾以东洋面的海温呈正相关,并具有很好的持续性。（3）影响山东的TC多年,赤道中东太平洋有较强的负距平区;影响山东的TC少年,赤道中东太平洋为正距平区。说明赤道中东太平洋的海温高低对影响山东的TC频数有较好的指示作用。     

夏季热带北大西洋海温异常对西北太平洋热带气旋生成的影响

利用1979—2012年西北太平洋热带气旋最佳路径资料,Hadley中心的海温资料和NCEP/NCAR再分析资料等,研究了夏季(6—10月)热带北大西洋海温异常与西北太平洋热带气旋(Tropical Cyclone,TC)生成的关系及其可能机制。结果表明,夏季热带北大西洋海温异常与同期西北太平洋TC生成频次之间存在显著的负相关关系。热带北大西洋海温的异常增暖可产生一对东—西向分布的偶极型低层异常环流,其中气旋性异常环流位于北大西洋/东太平洋地区,反气旋异常环流位于西北太平洋地区。该反气旋环流异常使得TC主要生成区的对流活动受到抑制、低层涡度正异常、中低层相对湿度负异常、中层下沉气流异常,这些动力/热力条件均不利于TC生成。此外,西北太平洋地区低层涡旋动能负异常,同时来自大尺度环流的涡旋动能的正压转换也受到抑制,不能为TC的生成和发展提供额外能量源。反之亦然。     

基于EOF分解的中期平均气温距平客观预报方法

本文通过将500 hPa高度、850 hPa温度、海平面气压的预报与历史要素场进行EOF分解,并假定EOF分解空间函数(即特征向量)是基本稳定的,建立以EOF分解主分量系列的时间系数、预报站点附近基本要素值的时间序列与预报站点平均气温距平的多元线性逐步回归预报方程,结合ECMWF集合预报数值产品,生成全国范围未来10 d平均气温距平客观预报产品投入业务应用,并采用同号率方法检验。结果表明,客观预报产品在检验时段内,同号率平均值为0.77,明显高于ECMWF集合预报模式2 m温度直接计算得出的同类产品同号率0.63;该客观预报产品不仅在分布范围上,同时在距平幅度上预报效果均较好。此外,相关分析也证明同号率方法在检验中期时效气温距平预报中有其合理性。     

基于ConvLSTM的西北太平洋海表温度中短期预报

尽管海表温度(Sea Surface Temperature,SST)短期变化较小,但这种变化对海洋涡旋、海洋锋以及热带气旋的发生发展仍有着重要的影响,因此短期SST预报意义重大,且对预报精度的要求较高。本文基于ConvLSTM的深度学习模型,利用SST和温度平流双预报因子对西北太平洋划定区域内SST进行7 d的连续预报,将其结果与仅使用SST预报因子ConvLSTM以及混合坐标海洋模型(HYbrid Coordinate Ocean Model,HYCOM)的预报结果分别进行了对比。结果表明,在7 d的预报时效内,温度平流预报因子的加入可使得ConvLSTM模型预报技巧大幅提升,明显优于HYCOM模式。此外,本文将预报时效进一步延长至30 d,对模型在不同季节的预报能力进行了分析,发现ConvLSTM模型在春、秋季(夏、冬季)的预报效果相对较好(差)。     

Blunt ocean dynamical thermostat in response of tropical eastern Pacific SST to global warming

Using an intermediate ocean–atmosphere coupled model (ICM) for the tropical Pacific, we investigated the role of the ocean dynamical thermostat (ODT) in regulating the tropical eastern Pacific sea surface temperature (SST) under global warming conditions. The external, uniformly distributed surface heating results in the cooling of the tropical eastern Pacific “cold tongue,” and the amplitude of the cooling increases as more heat is added but not simply linearly. Furthermore, an upper bound for the influence of the equatorially symmetric surface heating on the cold tongue cooling exists. The additional heating beyond the upper bound does not cool the cold tongue in a systematic manner. The heat budget analysis suggests that the zonal advection is the primary factor that contributes to such nonlinear SST response. The radiative heating due to the greenhouse effect (hereafter, RHG) that is obtained from the multi-model ensemble of the Climate Model Intercomparison Project Phase III (CMIP3) was externally given to ICM. The RHG obtained from the twentieth century simulation intensified the cold tongue cooling and the subtropical warming, which were further intensified by the RHG from the doubled CO₂ concentration simulation. However, the cold tongue cooling was significantly reduced and the negative SST response region was shrunken toward the equator by the RHG from the quadrupled CO₂ concentration simulation, while the subtropical warming increased further. A systematic RHG forced experiment having the same spatial pattern of RHG from doubled CO₂ concentration simulation with different amplitude of forcing revealed that the ocean dynamical response to global warming tended to enhance the cooling in the tropical eastern Pacific by virtue of meridional advection and upwelling; however, these cooling effects could not fully compensate a given RHG warming as the external forcing becomes larger. Moreover, the feedback by the zonal thermal advection actually exerted the warming over the equatorial region. Therefore, as the global warming is intensified, the cooling over the eastern tropical Pacific by ODT and the negative SST response area are reduced.     

数值模式的热带气旋强度预报订正及其集成应用

提供热带气旋强度预报产品的业务数值天气预报模式有很多,并已表现出一定的预报技巧,为提高对模式热带气旋强度预报产品的定量应用能力,分析2010—2012年7个业务数值模式的西北太平洋热带气旋强度预报,发现预报误差不仅受到模式热带气旋初始强度误差的显著影响,还与热带气旋及其所处环境的初始状况有密切关系,包括热带气旋初始强度、尺度、移速、环境气压、环境风切变、热带气旋发展潜势等。根据这些因子与各模式热带气旋强度预报误差之间的相关性,采用逐步回归方法建立热带气旋强度预报误差的统计预估模型,并通过逐个热带气旋滚动式建模来进行独立样本检验。检验结果表明,基于误差预估的模式订正预报比模式直接输出的热带气旋强度预报有显著改进,在此基础上建立的热带气旋强度多模式集成预报方案相对气候持续性预报方法在12 h有28%的正技巧,在24—72 h则稳定在15%—20%,具有业务参考价值。     

Decadal change in relationship between western North Pacific tropical cyclone frequency and the tropical Pacific SST

In this study, we examine the relationship between the number of tropical cyclones (TCs) in the western North Pacific and the tropical Pacific sea surface temperature (SST) during the main TC season (July–November) for the period of 1965–2006. Results show that there are periods when TC frequency and the tropical Pacific SST are well correlated and periods when the relationship breaks down. Therefore, decadal variation is readily apparent in the relationship between the TC frequency and the SST variations in the tropical Pacific. We further examine the oceanic and atmospheric states in the two periods (i.e., 1979–1989 vs. 1990–2000) when the marked contrast in the correlation between the TC frequency and the tropical Pacific SST is observed. Before 1990, the analysis indicates that oceanic conditions largely influenced anomalous TC frequency, whereas atmospheric conditions had little impact. After 1990, there the reverse appears to be the case, i.e., atmospheric conditions drive anomalous TC frequency and oceanic conditions are relatively unimportant. A role of atmosphere and ocean in relation to the TC development in the western North Pacific changes, which is consistent with the change of the correlations between the TC frequency and the tropical Pacific SST.     

Skill of western North Pacific tropical cyclone intensity forecast guidance relative to Weighted-Analog technique

The accuracy of the western North Pacific tropical cyclone intensity forecast guidance products available at the Joint Typhoon Warning Center (JTWC) is evaluated relative to a new skill metric called Weighted Analog Intensity Pacific (WAIP) that includes knowledge of the JTWC official track forecast and the current intensity, which is information that is available at the time the intensity forecast is generated. An intensity consensus technique called S5XX that includes statistical-dynamic intensity forecasts plus other dynamic and thermodynamic prediction techniques has statistically significant smaller errors than WAIP at 24 h and 48 h and has similar accuracy through 120 h. While the track consensus CONW is a critical input to the JTWC official track forecast, it has no skill relative to WAIP as an intensity forecast. Three regional numerical models also have no skill relative to WAIP, and especially at forecast intervals beyond 72 h because their mean absolute errors are statistically significantly larger than for WAIP. Furthermore, these regional models have statistically significant positive or negative intensity biases relative to the verifying intensities. However, an experimental consensus technique called CMES that includes these three regional models has small accuracy relative to WAIP in the 24 h to 72 h forecast intervals. Geographical-based comparisons of the intensity guidance products with the WAIP indicate almost all of the products are more accurate than WAIP over the South China Sea region. The statistical-dynamic consensus technique S5XX does have skill through 72 h for landfalling situations along the coasts of China and Southeast Asia. At 120 h, the WAIP has superior performance over the guidance products over most areas of the western North Pacific, but again the S5XX is more accurate than WAIP for landfalling tropical cyclones on the Philippine Islands, Southeast Asia, South China, and northeastern Japan. This information will be useful to the forecaster in deciding when and where (or how much) to rely on each guidance product in preparing the five-day intensity forecast once the official track forecast has been established.     

The impact of atmospheric initialisation on seasonal prediction of tropical Pacific SST

The impact of realistic atmospheric initialisation on the seasonal prediction of tropical Pacific sea surface temperatures is explored with the Predictive Ocean–Atmosphere Model for Australia (POAMA) dynamical seasonal forecast system. Previous versions of POAMA used data from an Atmospheric Model Intercomparison Project (AMIP)-style simulation to initialise the atmosphere for the hindcast simulations. The initial conditions for the hindcasts did not, therefore, capture the true intra-seasonal atmospheric state. The most recent version of POAMA has a new Atmosphere and Land Initialisation scheme (ALI), which captures the observed intra-seasonal atmospheric state. We present the ALI scheme and then compare the forecast skill of two hindcast datasets, one with AMIP-type initialisation and one with realistic initial conditions from ALI, focussing on the prediction of El Niño. For eastern Pacific (Niño3) sea surface temperature anomalies (SSTAs), both experiments beat persistence and have useful SSTA prediction skill (anomaly correlations above 0.6) at all lead times (forecasts are 9 months duration). However, the experiment with realistic atmospheric initial conditions from ALI is an improvement over the AMIP-type initialisation experiment out to about 6 months lead time. The improvements in skill are related to improved initial atmospheric anomalies rather than an improved initial mean state (the forecast drift is worse in the ALI hindcast dataset). Since we are dealing with a coupled system, initial atmospheric errors (or differences between experiments) are amplified though coupled processes which can then lead to long lasting errors (or differences).     

Diagnosing southeast tropical Atlantic SST and ocean circulation biases in the CMIP5 ensemble

Warm sea-surface temperature (SST) biases in the southeastern tropical Atlantic (SETA), which is defined by a region from 5°E to the west coast of southern Africa and from 10°S to 30°S, are a common problem in many current and previous generation climate models. The Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble provides a useful framework to tackle the complex issues concerning causes of the SST bias. In this study, we tested a number of previously proposed mechanisms responsible for the SETA SST bias and found the following results. First, the multi-model ensemble mean shows a positive shortwave radiation bias of ~20 W m^?2, consistent with models’ deficiency in simulating low-level clouds. This shortwave radiation error, however, is overwhelmed by larger errors in the simulated surface turbulent heat and longwave radiation fluxes, resulting in excessive heat loss from the ocean. The result holds for atmosphere-only model simulations from the same multi-model ensemble, where the effect of SST biases on surface heat fluxes is removed, and is not sensitive to whether the analysis region is chosen to coincide with the maximum warm SST bias along the coast or with the main SETA stratocumulus deck away from the coast. This combined with the fact that there is no statistically significant relationship between simulated SST biases and surface heat flux biases among CMIP5 models suggests that the shortwave radiation bias caused by poorly simulated low-level clouds is not the leading cause of the warm SST bias. Second, the majority of CMIP5 models underestimate upwelling strength along the Benguela coast, which is linked to the unrealistically weak alongshore wind stress simulated by the models. However, a correlation analysis between the model simulated vertical velocities and SST biases does not reveal a statistically significant relationship between the two, suggesting that the deficient coastal upwelling in the models is not simply related to the warm SST bias via vertical heat advection. Third, SETA SST biases in CMIP5 models are correlated with surface and subsurface ocean temperature biases in the equatorial region, suggesting that the equatorial temperature bias remotely contributes to the SETA SST bias. Finally, we found that all CMIP5 models simulate a southward displaced Angola–Benguela front (ABF), which in many models is more than 10° south of its observed location. Furthermore, SETA SST biases are most significantly correlated with ABF latitude, which suggests that the inability of CMIP5 models to accurately simulate the ABF is a leading cause of the SETA SST bias. This is supported by simulations with the oceanic component of one of the CMIP5 models, which is forced with observationally derived surface fluxes. The results show that even with the observationally derived surface atmospheric forcing, the ocean model generates a significant warm SST bias near the ABF, underlining the important role of ocean dynamics in SETA SST bias problem. Further model simulations were conducted to address the impact of the SETA SST biases. The results indicate a significant remote influence of the SETA SST bias on global model simulations of tropical climate, underscoring the importance and urgency to reduce the SETA SST bias in global climate models.     

Inter-annual variability and skill of tropical rainfall and SST in APCC seasonal forecast models

Climate Dynamics - The present study explored the performance of the current coupled models obtained from the Asia Pacific Economic Cooperation (APEC) Climate Centre (APCC) in representing the...