The response of the upper ocean to tropical cyclone Viyaru over the Bay of Bengal

Better forecast of tropical cyclone(TC) can help to reduce risk and enhance management. The TC forecast depends on the scientific understanding of oceanic processes, air-sea interaction and finally, the atmospheric process. The TC Viyaru is taken as an example, which is formed at the end of 11 May 2013 and sustains up to 17 May 2013 during pre-monsoon season. Argo data are used to investigate ocean response processes by comparing pre-and post-conditions of the TC. Eight oceanic parameters including the sea surface temperature(SST), the sea surface salinity(SSS), and the barrier layer thickness(BLT), the 26°C isotherm depth in the ocean(D26), the isothermal layer depth(ILD), the mixed layer depth(MLD), the tropical cyclone heat potential(TCHP) and the effective oceanic layer for cyclogenesis(EOLC) are chosen to evaluate the pre-and post-conditions of the TC along the track of Viyaru. The values of the SST, D26, BLT, TCHP and EOLC in the pre-cyclonic condition are higher than the post-cyclonic condition, while the SSS, ILD and MLD in the post-cyclonic condition are higher than the pre-cyclonic condition of the ocean due to strong cyclonic winds and subsurface upwelling. It is interesting that the strong intensity of the TC reduces less SST and vice versa. The satisfied real time Argo data is not available in the northern Bay of Bengal especially in the coastal region. A weather research and forecasting model is employed to hindcast the track of Viyaru, and the satellite data from the National Center Environmental Prediction are used to assess the hindcast.     

热力学效应及斯托克斯漂流对混合层影响的研究

本文通过理想化的外部强迫以及海洋站点实测数据驱动普林斯顿海洋模式来研究海洋热力学效应和斯托克斯漂流对上混合层数值模拟的影响。在Mellor-Yamada湍流闭合方案中,经常出现夏季海表面温度偏暖和混合层深度偏浅的模拟误差。实验表明,斯托克斯漂流在冬季和夏季均能增强湍流动能,加深混合层深度。这种效应可以改善夏季的模拟结果,但与观测数据相比,将增大冬季混合层深度的模拟误差。斯托克斯漂流可以通过增强湍动能来加深混合层深度。结果表明,将斯托克斯漂流与冷皮层和暖层对上部混合层的热效应相结合,可以正确地模拟混合层深度。在夏季,海洋冷皮层和暖层通过“阻挡结构”和双温跃层结构模拟出更真实的上混合层变化。在冬季,海洋热力学效应通过增强上层海洋层结平衡了斯托克斯漂流的影响,并且由斯托克斯漂流引起的过度混合被校正。     

Validation of interannual simulations from the 1/8° global Navy Coastal Ocean Model (NCOM)

A 1/8° global version of the Navy Coastal Ocean Model (NCOM) is used for simulation of upper-ocean quantities on interannual time scales. The model spans the global ocean from 80°S to a complete Arctic cap, and includes 19 terrain-following σ- and 21 fixed z-levels. The global NCOM assimilates three-dimensional (3D) temperature and salinity fields produced by the Modular Ocean Data Assimilation System (MODAS) which generates synthetic temperature and salinity profiles based on ocean surface observations. Model-data intercomparisons are performed to measure the effectiveness of NCOM in predicting upper-ocean quantities such as sea surface temperature (SST), sea surface salinity (SSS) and mixed layer depth (MLD). Subsurface temperature and salinity are evaluated as well. An extensive set of buoy observations is used for this validation. Where possible, the model validation is performed between year-long time series obtained from the model and time series from the buoys. The statistical analyses include the calculation of dimensionless skill scores (SS), which are positive if statistical skill is shown and equal to one for perfect SST simulations. Model SST comparisons with year-long SST time series from all 83 buoys give a median SS value of 0.82. Model subsurface temperature comparisons with the year-long subsurface temperature time series from 24 buoys showed that the model is able to predict temperatures down to 500 m reasonably well, with positive SS values ranging from 0.18 to 0.97. Intercomparisons of MLD reveal that the model MLD is usually shallower than the buoy MLD by an average of about 15 m. Annual mean SSS and subsurface salinity biases between the model and buoy values are small. A comparison of SST between NCOM and a satellite-based Pathfinder data set demonstrates that the model has a root-mean-square (RMS) SST difference of 0.61 °C over the global ocean. Spatial variations of kinetic energy fields from NCOM show agree with historical observations. Based on these results, it is concluded that the global NCOM presented in this paper is able to predict upper-ocean quantities with reasonable accuracy for both coastal and open ocean locations.     

Winter-to-winter recurrence of sea surface temperature, salinity and mixed layer depth anomalies

The mean seasonal cycle of mixed layer depth (MLD) in the extratropical oceans has the potential to influence temperature, salinity and mixed layer depth anomalies from one winter to the next. Temperature and salinity anomalies that form at the surface and spread throughout the deep winter mixed layer are sequestered beneath the mixed layer when it shoals in spring, and are then re-entrained into the surface layer in the subsequent fall and winter. Here we document this ‘re-emergence mechanism’ in the North Pacific Ocean using observed SSTs, subsurface temperature fields from a data assimilation system, and coupled atmosphere–ocean model simulations. Observations indicate that the dominant large-scale SST anomaly pattern that forms in the North Pacific during winter recurs in the following winter. The model simulation with mixed layer ocean physics reproduced the winter-to-winter recurrence, while model simulations with observed SSTs specified in the tropical Pacific and a 50 m slab in the North Pacific did not. This difference between the model results indicates that the winter-to-winter SST correlations are the result of the re-emergence mechanism, and not of similar atmospheric forcing of the ocean in consecutive winters. The model experiments also indicate that SST anomalies in the tropical Pacific associated with El Niño are not essential for re-emergence to occur.The recurrence of observed SST and simulated SST and SSS anomalies are found in several regions in the central North Pacific, and are quite strong in the northern (>50°N) part of the basin. The winter-to-winter autocorrelation of SSS anomalies exceed those of SST, since only the latter are strongly damped by surface fluxes. The re-emergence mechanism also has a modest influence on MLD through changes in the vertical stratification in the seasonal thermocline.     

The impact of bio-optical heating on the properties of the upper ocean: A sensitivity study using a 3-D circulation model for the Labrador Sea

The impact of bio-optical heating on the properties of the upper Labrador Sea water was investigated by considering changes in light attenuation in water associated with the seasonal change of chlorophyll distribution. The time- and depth-dependent attenuation coefficients were obtained from remotely sensed SeaWiFS ocean-colour data. Sea-surface temperature (SST) and mixed-layer depth (MLD) were computed from a three-dimensional ocean circulation model. The model was integrated from 1999 to 2003 with 6-hourly atmospheric forcing. The changes in SST and MLD attributable to bio-optical heating were determined by comparing the model results using the observed attenuation coefficients (chlorophyll) to those using a weak and constant attenuation (clear water). The model results show that bio-optical heating is controlled mainly by chlorophyll concentration and MLD. The increase in SST is around 1 °C in most parts of the Labrador Sea and the shelves, and up to 2.7 °C in areas of shallow MLD and high chlorophyll concentrations (the Grand Banks and Northeastern Newfoundland Shelf). The increase is much higher than that found in previous studies, which was typically a fraction of a degree. Bio-optical heating also can enhance the stratification of the upper ocean and reduce the MLD by 20–50%.     

Verification of an operational ocean circulation-surface wave coupled forecasting system for the China's seas

An operational ocean circulation-surface wave coupled forecasting system for the seas off China and adjacent areas(OCFS-C) is developed based on parallelized circulation and wave models. It has been in operation since November 1, 2007. In this paper we comprehensively present the simulation and verification of the system, whose distinguishing feature is that the wave-induced mixing is coupled in the circulation model. In particular, with nested technique the resolution in the China's seas has been updated to(1/24)° from the global model with(1/2)°resolution. Besides, daily remote sensing sea surface temperature(SST) data have been assimilated into the model to generate a hot restart field for OCFS-C. Moreover, inter-comparisons between forecasting and independent observational data are performed to evaluate the effectiveness of OCFS-C in upper-ocean quantities predictions, including SST, mixed layer depth(MLD) and subsurface temperature. Except in conventional statistical metrics, non-dimensional skill scores(SS) is also used to evaluate forecast skill. Observations from buoys and Argo profiles are used for lead time and real time validations, which give a large SS value(more than 0.90). Besides, prediction skill for the seasonal variation of SST is confirmed. Comparisons of subsurface temperatures with Argo profiles data indicate that OCFS-C has low skill in predicting subsurface temperatures between 100 m and 150 m. Nevertheless, inter-comparisons of MLD reveal that the MLD from model is shallower than that from Argo profiles by about 12 m, i.e., OCFS-C is successful and steady in MLD predictions. Validation of 1-d, 2-d and 3-d forecasting SST shows that our operational ocean circulation-surface wave coupled forecasting model has reasonable accuracy in the upper ocean.     

Coupling a two-way nested primitive equation model and a statistical SST predictor of the Ligurian Sea via data assimilation

A primitive equation model and a statistical predictor are coupled by data assimilation in order to combine the strength of both approaches. In this work, the system of two-way nested models centred in the Ligurian Sea and the satellite-based ocean forecasting (SOFT) system predicting the sea surface temperature (SST) are used. The data assimilation scheme is a simplified reduced order Kalman filter based on a constant error space. The assimilation of predicted SST improves the forecast of the hydrodynamic model compared to the forecast obtained by assimilating past SST observations used by the statistical predictor. This study shows that the SST of the SOFT predictor can be used to correct atmospheric heat fluxes. Traditionally this is done by relaxing the model SST towards the climatological SST. Therefore, the assimilation of SOFT SST and climatological SST are also compared.     

夏季黄海表面冷水对大气边界层及海雾的影响

海表面温度(SST)是海气界面上的1个物理量,受到海洋潮汐、海底地形等因素影响,并对海洋大气边界层有着重要的影响.夏季的黄海,由于黄海冷水团的存在和陆架锋的影响,或是潮汐混合的作用导致海水的垂直混合,使海表面温度的分布产生复杂的结构.通过对卫星观测的海表面温度数据分析,发现在夏季黄海有几个SST冷中心的存在:辽东半岛以及山东半岛的顶端、朝鲜半岛的西侧、山东半岛南侧、江苏外海和黄海南部等.本文利用一系列船舶观测资料、卫星遥感数据、再分析数据分析等,并运用数值模拟研究黄海的冷中心对其上大气的影响.在冷区之上,大气稳定度增加,抑制了近海面大气的垂直混合,使海表面风速减弱.通过对船测数据的分析,在冷区位置有海雾多发区的存在,黄海南部冷区上的海雾发生频率达到15％以上.Weather Research and Forecasting(WRF)模式的数值模拟表明,冷中心降低上空的温度,使海表面风速减弱,形成厚度达500m的逆温层,为海雾的形成创造了有利的条件.与船测数据结果所不同的是黄海南部冷中心之上的海雾发生频率可以达到30％,去掉冷区影响的试验表明冷区较冷的海表面温度最多可以使海雾的发生频率增加15％以上.     

Upper Ocean Four-Dimensional Variational Data Assimilation in the Arabian Sea and Bay of Bengal

A regional ocean circulation model with four-dimensional variational data assimilation scheme is configured to study the ocean state of the Indian Ocean region (65°E–95°E; 5°N–20°N) covering the Arabian Sea (AS) and Bay of Bengal (BoB). The state estimation setup uses 10 km horizontal resolution and 5 m vertical resolution in the upper ocean. The in-situ temperature and salinity, satellite-derived observations of sea surface height, and blended (in-situ and satellite-derived) observations of sea surface temperature alongwith their associated uncertainties are used for data assimilation with the regionally configured ocean model. The ocean state estimation is carried out for 61 days (1 June to 31 July 2013). The assimilated fields are closer to observations compared to other global state estimates. The mixed layer depth (MLD) of the region shows deepening during the period of assimilation with AS showing higher MLD compared to the BoB. An empirical forecast equation is derived for the prediction of MLD using the air–sea forcing variables as predictors. The surface and sub-surface (50 m) heat and salt budget tendencies of the region are also investigated. It is found that at the sub-surface, only the advection and diffusion temperature and salt tendencies are important.     

Simulation of the ocean surface mixed layer under the wave breaking

A one-dimensional mixed-layer model, including a Mellor-Yamada level 2.5 turbulence closure scheme, was implemented to investigate the dynamical and thermal structures of the ocean surface mixed layer in the northern South China Sea. The turbulent kinetic energy released through wave breaking was incorporated into the model as a source of energy at the ocean surface, and the influence of the breaking waves on the mixed layer was studied. The numerical simulations show that the simulated SST is overestimated in summer without the breaking waves. However, the cooler SST is simulated when the effect of the breaking waves is considered, the corresponding discrepancy with the observed data decreases up to 20% and the MLD calculated averagely deepens 3.8 m. Owing to the wave-enhanced turbulence mixing in the summertime, the stratification at the bottom of the mixed layer was modified and the temperature gradient spread throughout the whole thermocline compared with the concentrated distribution without wave breaking.     

Improvement of short-termforecasting in the northwest Pacific through assimilating Argo data into initial fields

The impact of assimilating Argo data into an initial field on the short-term forecasting accuracy of temper- ature and salinity is quantitatively estimated by using a forecasting system of the western North Pacific, on the base of the Princeton ocean model with a generalized coordinate system （POMgcs）. This system uses a sequential multigrid three-dimensional variational （3DVAR） analysis scheme to assimilate observation da- ta. Two numerical experiments were conducted with and without Argo temperature and salinity profile data besides conventional temperature and salinity profile data and sea surface height anomaly （SSHa） and sea surface temperature （SST） in the process of assimilating data into the initial fields. The forecast errors are estimated by using independent temperature and salinity profiles during the forecasting period, including the vertical distributions of the horizontally averaged root mean square errors （H-RMSEs） and the horizontal distributions of the vertically averaged mean errors （MEs） and the temporal variation of spatially averaged root mean square errors （S-RMSEs）. Comparison between the two experiments shows that the assimila- tion of Argo data significantly improves the forecast accuracy, with 24% reduction of H-RMSE maximum for the temperature, and the salinity forecasts are improved more obviously, averagely dropping of 50% for H-RMSEs in depth shallower than 300 m. Such improvement is caused by relatively uniform sampling of both temperature and salinity from the Argo drifters in time and space.     

基于回归模型的热带气旋条件下的海表降温参数化方案设计

Combining a linear regression and a temperature budget formula, a multivariate regression model is proposed to parameterize and estimate sea surface temperature(SST) cooling induced by tropical cyclones(TCs). Three major dynamic and thermodynamic processes governing the TC-induced SST cooling(SSTC), vertical mixing, upwelling and heat flux, are parameterized empirically using a combination of multiple atmospheric and oceanic variables:sea surface height(SSH), wind speed, wind curl, TC translation speed and surface net heat flux. The regression model fits reasonably well with 10-year statistical observations/reanalysis data obtained from 100 selected TCs in the northwestern Pacific during 2001–2010, with an averaged fitting error of 0.07 and a mean absolute error of 0.72°C between diagnostic and observed SST cooling. The results reveal that the vertical mixing is overall the pre dominant process producing ocean SST cooling, accounting for 55% of the total cooling. The upwelling accounts for 18% of the total cooling and its maximum occurs near the TC center, associated with TC-induced Ekman pumping. The surface heat flux accounts for 26% of the total cooling, and its contribution increases towards the tropics and the continental shelf. The ocean thermal structures, represented by the SSH in the regression model,plays an important role in modulating the SST cooling pattern. The concept of the regression model can be applicable in TC weather prediction models to improve SST parameterization schemes.     

Long-term variability of winter mixed layer depth and temperature along the Kuroshio jet in a high-resolution ocean general circulation model

To explore the causes of the winter shallow mixed layer and high sea surface temperature (SST) along the strong Kuroshio jet from the East China Sea to the upstream Kuroshio extension (25.5°N–150°E) during 1988–1994 when the Japanese sardine stocks collapsed, high-resolution ocean general circulation model (OGCM) hindcast data are analyzed with a bulk mixed layer model which traces particles at the mixed layer base. The shallow mixed layer and high SST along the Kuroshio jet are mainly caused by the acceleration of the Kuroshio current velocity and the reduction of the surface cooling. Because the acceleration reduces the time during which the mixed layer is exposed to wintertime cooling, deepening and cooling of the winter mixed layer are restricted. The weaker surface cooling due to less severe meteorological forcing also causes the shallow mixed layer and the high SST. The impact of the strong heat transport along the Kuroshio extends to the southern recirculation gyre of the Kuroshio/Kuroshio extension regions; previous indications that the Japanese sardine recruitment is correlated with the winter SST and the mixed layer depth (MLD) in the Kuroshio extension recirculation region could be related to the velocity, SST, and MLD near the Kuroshio axis which also could affect the variability of North Pacific subtropical water.     

Mixed layer variability in Northern Arabian Sea as detected by an Argo float

Seasonal evolution of surface mixed layer in the Northern Arabian Sea (NAS) between 17° N–20.5° N and 59° E-69° E was observed by using Argo float daily data for about 9 months, from April 2002 through December 2002. Results showed that during April - May mixed layer shoaled due to light winds, clear sky and intense solar insolation. Sea surface temperature (SST) rose by 2.3 °C and ocean gained an average of 99.8 Wm⁻². Mixed layer reached maximum depth of about 71 m during June - September owing to strong winds and cloudy skies. Ocean gained abnormally low ∼18 Wm⁻² and SST dropped by 3.4 °C. During the inter monsoon period, October, mixed layer shoaled and maintained a depth of 20 to 30 m. November - December was accompanied by moderate winds, dropping of SST by 1.5 °C and ocean lost an average of 52.5 Wm⁻². Mixed layer deepened gradually reaching a maximum of 62 m in December. Analysis of surface fluxes and winds suggested that winds and fluxes are the dominating factors causing deepening of mixed layer during summer and winter monsoon periods respectively. Relatively high correlation between MLD, net heat flux and wind speed revealed that short term variability of MLD coincided well with short term variability of surface forcing.     

Ocean temperature responses to Typhoon Mstsa in the East China Sea

The MASNUM wave-tide-circulation coupled model, with 21 layers in the vertical and （1/8） °horizontal resolution, was employed to investigate the oceanic responses to Typhoon Mstsa which traversed the East China Sea （ECS） during the period of 4 - 6 August, 2005. Numerical experiment results are analyzed and compared with observation. The responses of the sea surface temperature （SST）, in a focused area of （27° -29°N, 121° - 124°E）, include heating and cooling stages. The heating is mainly due to warm Kuroshio water transportation and downwelling due to the water accumulation. In the cooling stage, the amplitude of the simulated cold wake （ -3℃ ）, located on the right side of this typhoon track, is compared quite well with that of the satellite observed SST data. The wave-induced mixing（Bv） plays a key role for the SST cooling. Bv still plays a leading role, which accounts for 36%, for the ocean temperature drop in the upper ocean of 0 - 40 m, while the upwelling is responsible for 84% of the cooling for the lower layer of 40 - 70 m. The mixed layer depth （MLD） increased quickly from 28 to 50 m in the typhoon period. However, the simulated MLD without the wave-induced vertical mixing, evolution from 13 to 32 m, was seriously underestimated. The surface wave is too important to be ignored for the ocean responses to a typhoon.     

Seasonal variability of the mixed layer in the central Bay of Bengal and associated changes in nutrients and chlorophyll

Hydrographic data from National Oceanographic Data Center (NODC) and Responsible National Oceanographic Data Centre (RNODC) were used to study the seasonal variability of the mixed layer in the central Bay of Bengal (8–20°N and 87–91°E), while meteorological data from Comprehensive Ocean Atmosphere Data Set (COADS) were used to explore atmospheric forcing responsible for the variability. The observed changes in the mixed-layer depth (MLD) clearly demarcated a distinct north–south regime with 15°N as the limiting latitude. North of this latitude MLD remained shallow (∼20 m) for most of the year without showing any appreciable seasonality. Lack of seasonality suggests that the low-salinity water, which is perennially present in the northern Bay, controls the stability and MLD. The observed winter freshening is driven by the winter rainfall and associated river discharge, which is advected offshore under the prevailing circulation. The resulting stratification was so strong that even a 4 °C cooling in sea-surface temperature (SST) during winter was unable to initiate convective mixing. In contrast, the southern region showed a strong semi-annual variability with deep MLD during summer and winter and a shallow MLD during spring and fall intermonsoons. The shallow MLD in spring and fall results from primary and secondary heating associated with increased incoming solar radiation and lighter winds during this period. The deep mixed layer during summer results from two processes: the increased wind forcing and the intrusion of high-salinity waters of Arabian Sea origin. The high winds associated with summer monsoon initiate greater wind-driven mixing, while the intrusion of high-salinity waters erodes the halocline and weakens the upper-layer stratification of the water column and aids in vertical mixing. The deep MLD in the south during winter was driven by wind-mixing, when the upper water column was comparatively less stable. The deep MLD between 15 and 17°N during March–May cannot be explained in the context of local atmospheric forcing. We show that this is associated with the propagation of Rossby waves from the eastern Bay. We also show that the nitrate and chlorophyll distribution in the upper ocean during spring intermonsoon is strongly coupled to the MLD, whereas during summer river runoff and cold-core eddies appear to play a major role in regulating the nutrients and chlorophyll.     

中国近海沿岸海温多时间尺度变率及影响其变化的天气气候因素

本文通过对中国近海13个海洋站1959年～2003年逐日日平均海表温度及其相关数据的处理分析,结合中国近海多年逐日天气实况,研究了中国近海水温的短时（1d）、过程、旬、月、年际变率以及海温的长期趋势变化,并在此基础上详细讨论了影响中国近海各时间尺度水温变化的天气气候因素.     

Response of the mixed layer depth and subduction rate in the subtropical Northeast Pacific to global warming

The response of the mixed layer depth(MLD) and subduction rate in the subtropical Northeast Pacific to global warming is investigated based on 9 CMIP5 models. Compared with the present climate in the 9 models, the response of the MLD in the subtropical Northeast Pacific to the increased radiation forcing is spatially nonuniform, with the maximum shoaling about 50 m in the ensemble mean result. The inter-model differences of MLD change are non-negligible, which depend on the various dominated mechanisms. On the north of the MLD front, MLD shallows largely and is influenced by Ekman pumping, heat flux, and upper-ocean cold advection changes. On the south of the MLD front, MLD changes a little in the warmer climate, which is mainly due to the upper-ocean warm advection change. As a result, the MLD front intensity weakens obviously from 0.24 m/km to0.15 m/km(about 33.9%) in the ensemble mean, not only due to the maximum of MLD shoaling but also dependent on the MLD non-uniform spatial variability. The spatially non-uniform decrease of the subduction rate is primarily dominated by the lateral induction reduction(about 85% in ensemble mean) due to the significant weakening of the MLD front. This research indicates that the ocean advection change impacts the MLD spatially non-uniform change greatly, and then plays an important role in the response of the MLD front and the subduction process to global warming.     

Mixed layer depth front and subduction of low potential vorticity water under seasonal forcings in an idealized OGCM

The mixed layer depth (MLD) front and subduction under seasonal variability are investigated using an idealized ocean general circulation model (OGCM) with simple seasonal forcings. A sharp MLD front develops and subduction occurs at the front from late winter to early spring. The position of the MLD front agrees with the curve where \({\rm D}T_{\rm s}/{\rm D}t = \partial T_{\rm s} /\partial t + {\user2{u}}_{\rm g} \cdot \nabla T_{\rm s} = 0\) is satisfied (t is time, \({\user2{u}}_{\rm g}\) is the upper-ocean geostrophic velocity, \(T_{\rm s}\) is the sea surface temperature (SST), and \(\nabla\) is the horizontal gradient operator), indicating that thick mixed-layer water is subducted there parallel to the SST contour. This is a generalization of the past result that the MLD front coincides with the curve \({\user2{u}}_{\rm g} \cdot \nabla T_{\rm s} = 0\) when the forcing is steady. Irreversible subduction at the MLD front is limited to about 1 month, where the beginning of the irreversible subduction period agrees with the first coincidence of the MLD front and \({\rm D}T_{\rm s}/{\rm D}t =0\) in late winter, and the end of the period roughly corresponds to the disappearance of the MLD front in early spring. Subduction volume at the MLD front during this period is similar to that during 1 year in the steady-forcing model. Since the cooling of the deep mixed-layer water occurs only in winter and SST can not fully catch up with the seasonally varying reference temperature of restoring, the cooling rate of SST is reduced and the zonal gradient of the SST in the northwestern subtropical gyre is a little altered in the seasonal-forcing case. These effects result in slightly lower densities of subducted water and the eastward shift of the MLD front.     

海气相互作用的随机-动力理论

在长期天气过程和气候形成的理论中,海洋起着重要的作用。但是海洋是一种缓慢流动的介质,比热也远比大气的比热大,从大范围运动角度来看,大气运动特别大尺度天气过程,相对说来比较活跃和变化速度较快,这种较快的天气起伏,将影响海水的潜热和感热输送,使海温发生变化,然而海温的气候变化是一个缓慢过程,而且是一个大范围现象,因此可以将天气过程的起伏看成一种随机强迫,从这一观点出发,Frankignoul and Hasselman采用简单的随机模型,探讨了海温异常的成因与变化,得到了引人注目。