Surface flux response to interannual tropical Pacific sea surface temperature variability in AMIP models

 A systematic comparison of observed and modeled atmospheric surface heat and momentum fluxes related to sea surface temperature (SST) variability on interannual time scales in the tropical Pacific is conducted. This is done to examine the ability of atmospheric general circulation models (AGCMs) in the Atmospheric Model Intercomparison Project (AMIP) to simulate the surface fluxes important for driving the ocean on interannual time scales. In order to estimate the model and observed response to such SST variability, various regression calculations are made between a time series representing observed ENSO SST variability in the tropical Pacific and the resulting surface flux anomalies. The models exhibit a range of differences from the observations. Overall the zonal wind stress anomalies are most accurately simulated while the solar radiation anomalies are the least accurately depicted. The deficiencies in the solar radiation are closely related to errors in cloudiness. The total heat flux shows some cancellation of the errors in its components particularly in the central Pacific. The performance of the GCMs in simulating the surface flux anomalies seems to be resolution dependent and low-resolution models tend to exhibit weaker flux responses. The simulated responses in the western Pacific are more variable than those of the central and eastern Pacific but in the west the observed estimates are less robust as well. Further improvements in atmospheric GCM flux simulation through better physical parametrization is clearly required if such models are to be used to their full potential in coupled modeling and climate forecasting. Received: 24 August 1999 / Accepted: 11 September 2000     

Modes of SST variability and the fluctuation of global mean temperature

Annually averaged global mean land air temperature and sea surface temperature (SST) combined, and global mean SST alone share similar fluctuations. We examine contributions by modes of SST variability in the global mean SST based on a new version (version 3) of global sea-ice and SST (GISST3). Besides a trend mode, the dominant modes are El Niño-Southern Oscillation (ENSO), interhemispheric oscillation, and North Pacific oscillation. Statistics over the period of 1880–1997 show that excluding a warming trend the fluctuation on interannual (IA) and decadal-interdecadal (DID) time scales is dominated by IA ENSO and DID ENSO-like variability. However, the contribution by IA ENSO cycles experiences significant fluctuations, and there appears to be strong modulations by ENSO-like variability on DID or longer time scales: during several decade-long periods, when DID ENSO-like variability raises the temperature in the equatorial eastern Pacific, the contribution by IA ENSO cycles weakens to an insignificant level. The latest example of such modulation is the period since about 1980; despite the exceptional strength of El Niño events, the contribution by IA ENSO cycles weakens, suggesting that the exceptional strength is a consequence of superposition of IA El Niño events, a warming phase of DID ENSO-like variability, and possibly an ENSO-like warming trend.     

Interannual to decadal summer drought variability over Europe and its relationship to global sea surface temperature

Interannual to decadal variability of European summer drought and its relationship with global sea surface temperature (SST) is investigated using the newly developed self calibrated Palmer drought severity index (scPDSI) and global sea surface temperature (SST) field for the period 1901–2002. A European drought severity index defined as the average of scPDSI over entire Europe shows quasiperiodic variations in the 2.5–5 year band as well as at 12–13 years suggesting a possible potential predictability of averaged drought conditions over Europe. A Canonical Correlation Analysis between summer scPDSI anomalies over Europe and global SST anomalies reveals the existence of three modes of coupled summer drought scPDSI patterns and winter global SST anomalies. The first scPDSI-SST coupled mode represents the long-term trends in the data which manifest in SST as warming over all oceans. The associated long-term trend in scPDSI suggests increasing drought conditions over the central part of Europe. The second mode is related to the inter-annual ENSO and decadal PDO influence on the European climate and the third one captures mainly the drought pattern associated to Atlantic Multidecadal Oscillation. The lag relationships between winter SST and summer drought conditions established in this study can provide a valuable skill for the prediction of drought conditions over Europe on interannual to decadal time scales.     

Long-term variability of sea surface temperature in Taiwan Strait

Long-term variability of sea surface temperature (SST) in the Taiwan Strait was studied from the U.K. Met Office Hadley Centre climatological data set HadISST1. In 1957–2011, three epochs were identified. The first epoch of cooling SST lasted through 1976. The regime shift of 1976–1977 led to an extremely rapid warming of 2.1 °C in 22 years. Another regime shift occurred in 1998–1999, resulting in a 1.0 °C cooling by 2011. The cross-frontal gradient between the China Coastal Current and offshore Taiwan Strait waters has abruptly decreased in 1992 and remained low through 2011. The long-term warming of SST increased towards the East China Sea, where the SST warming in 1957–2011 was about three times that in the South China Sea. The long-term warming was strongly enhanced in winter, with the maximum warming of 3.8 °C in February. The wintertime amplification of long-term warming has resulted in a decrease of the north–south SST range from 5 to 4 °C and a decrease in the amplitude of seasonal cycle of SST from 11 to 8 °C.     

Sahel rainfall and decadal to multi-decadal sea surface temperature variability

Decadal Sahelian rainfall variability was mainly driven by sea surface temperatures (SSTs) during the twentieth century. At the same time SSTs showed a marked long-term global warming (GW) trend. Superimposed on this long-term trend decadal and multi-decadal variability patterns are observed like the Atlantic Multidecadal Oscillation (AMO) and the inter-decadal Pacific Oscillation (IPO). Using an atmospheric general circulation model we investigate the relative contribution of each component to the Sahelian precipitation variability. To take into account the uncertainty related to the use of different SST data sets, we perform the experiments using HadISST1 and ERSSTv3 reconstructed sets. The simulations show that all three SST signals have a significant impact over West Africa: the positive phases of the GW and the IPO lead to drought over the Sahel, while a positive AMO enhances Sahel rainfall. The tropical SST warming is the main cause for the GW impact on Sahel rainfall. Regarding the AMO, the pattern of anomalous precipitation is established by the SSTs in the Atlantic and Mediterranean basins. In turn, the tropical SST anomalies control the impact of the IPO component on West Africa. Our results suggest that the low-frequency evolution of Sahel rainfall can be interpreted as the competition of three factors: the effect of the GW, the AMO and the IPO. Following this interpretation, our results show that 50% of the SST-driven Sahel drought in the 1980s is explained by the change to a negative phase of the AMO, and that the GW contribution was 10%. In addition, the partial recovery of Sahel rainfall in recent years was mainly driven by the AMO.     

Mean seasonal and spatial variability in global surface air temperature

Summary Using terrestrial observations of shelter-height air temperature and shipboard measurements, a global climatology of mean monthly surface air temperature has been compiled. Data were obtained from ten sources, screened for coding errors, and redundant station records were removed. The combined data base consists of 17 986 independent terrestrial station records and 6 955 oceanic grid-point records. These data were then interpolated to a 0.5° of latitude by 0.5° of longitude lattice using a spherically-based interpolation algorithm. Spatial distributions of the annual mean and intra-annual variance are presented along with a harmonic decomposition of the intra-annual variance.With 7 Figures     

Impact of southeast Indian Ocean sea surface temperature anomalies on monsoon-ENSO-dipole variability in a coupled ocean–atmosphere model

Recent studies show that SouthEast Indian Ocean (SEIO) SSTs are a highly significant precursor of transitions of the whole monsoon-El Niño-Southern Oscillation (ENSO) system during recent decades. However, the reasons for this specific interannual variability have not yet been identified unequivocally from the observations. Among these, the possibility of SEIO SST-driven variability in the monsoon-ENSO system is investigated here by inserting positive/negative SEIO temperature anomalies in the February’s restart files of a state-of-the-art coupled General Circulation Model (GCM) for 49 years of a control simulation. For each year of the control simulation, the model was then integrated for a 1-year period in fully coupled mode. These experiments show that Indian Summer Monsoon (ISM) and tropical Indian Ocean Dipole Mode (IODM) events are significantly influenced by the SEIO temperature perturbations inserted in the mixed layer of the coupled GCM several months before. A warm SEIO perturbation, inserted in late boreal winter, slowly propagates northward during the following seasons, implies enhanced ISM rainfall and finally triggers a negative IODM pattern during boreal fall in agreement with observations. A reversed evolution is simulated for a cold SEIO perturbation. It is shown that the life cycle of the simulated SEIO signal is driven by the positive wind-evaporation-SST, coastal upwelling and wind-thermocline-SST feedbacks. Further diagnosis of the sensitivity experiments suggests that stronger ISM and IODM variabilities are generated by excluding the El Niño years of the control simulation or when the initial background state in the SEIO is warmer. This finding confirms that IODM events may be triggered by multiple factors, other than ENSO, including subtropical SEIO SST anomalies. However, the ENSO mode does not react significantly to the SEIO temperature perturbation in the perturbed runs even though the simulated Pacific pattern agrees with the observations during boreal fall. These discrepancies with the observations may be linked to model biases in the Pacific and to the too strong ENSO simulated by this coupled GCM. These modeling evidences confirm that subtropical Indian Ocean SST anomalies generated by Mascarene high pulses during austral summer are a significant precursor of both ISM and IODM events occuring several months later.     

The variance of sea surface temperature and projected changes with global warming

Based on the surface energy budget, the sea surface temperature (SST) variance is related to the product of three factors: the sum of the variances of surface radiative and turbulent energy fluxes and of ocean heat transport, an efficiency factor depending on the covariances among them, and a transfer factor involving the persistence of surface temperature via its lagged autocorrelation. These quantities are analyzed for current climate conditions based on results from the NCEP/NCAR reanalyses and a simulation with the CCCma coupled climate model. Potential changes with climate change are considered based on two quasi-equilibrium climate change integrations for which the forcing has been stabilized at years 2050 and 2100 values of the IS92a forcing scenario. The surface energy fluxes, which contribute to the variance of SST, are similar in the modelled and reanalyzed atmosphere but modelled temperature variance is conditioned on the thickness of the upper ocean model layer. Changes of SST variance with global warming show broad scale patterns with decreases in the tropical central-eastern Pacific and the northern extra-tropical Pacific, and increases in both the sub-tropical Pacific and mid-latitudes of the North Atlantic. The changes in SST variance are not associated only with changes in the variances of surface energy fluxes/transports but also with changes in the covariances among them and by changes in the temperature autocorrelation structure.     

Storm track sensitivity to sea surface temperature resolution in a regional atmosphere model

A high resolution regional atmosphere model is used to investigate the sensitivity of the North Atlantic storm track to the spatial and temporal resolution of the sea surface temperature (SST) data used as a lower boundary condition. The model is run over an unusually large domain covering all of the North Atlantic and Europe, and is shown to produce a very good simulation of the observed storm track structure. The model is forced at the lateral boundaries with 15–20 years of data from the ERA-40 reanalysis, and at the lower boundary by SST data of differing resolution. The impacts of increasing spatial and temporal resolution are assessed separately, and in both cases increasing the resolution leads to subtle, but significant changes in the storm track. In some, but not all cases these changes act to reduce the small storm track biases seen in the model when it is forced with low-resolution SSTs. In addition there are several clear mesoscale responses to increased spatial SST resolution, with surface heat fluxes and convective precipitation increasing by 10–20% along the Gulf Stream SST gradient.     

Can local linear stochastic theory explain sea surface temperature and salinity variability?

 Sea surface temperature (SST) and salinity (SSS) time series from four ocean weather stations and data from an integration of the GFDL coupled ocean-atmosphere model are analyzed to test the applicability of local linear stochastic theory to the mixed-layer ocean. According to this theory, mixed-layer variability away from coasts and fronts can be explained as a ‘red noise’ response to the ‘white noise’ forcing by atmospheric disturbances. At one weather station, Papa (northeast Pacific), this stochastic theory can be applied to both salinity and temperature, explaining the relative redness of the SSS spectrum. Similar results hold for a model grid point adjacent to Papa, where the relationships between atmospheric energy and water fluxes and actual changes in SST and SSS are what is expected from local linear stochastic theory. At the other weather stations, this theory cannot adequately explain mixed-layer variability. Two oceanic processes must be taken into account: at Panulirus (near Bermuda), mososcale eddies enhance the observed variability at high frequencies. At Mike and India (North Atlantic), variations in SST and SSS advection, indicated by the coherence and equal persistence of SST and SSS anomalies, contribute to much of the low frequency variability in the model and observations. To achieve a global perspective, TOPEX altimeter data and model results are used to identify regions of the ocean where these mechanisms of variability are important. Where mesoscale eddies are as energetic as at Panulirus, indicated by the TOPEX global distribution of sea level variability, one would expect enhanced variability on short time scales. In regions exhibiting signatures of variability similar to Mike and India, variations in SST and SSS advection should dominate at low frequencies. According to the model, this mode of variability is found in the circumpolar ocean and the northern North Atlantic, where it is associated with the irregular oscillations of the model’s thermohaline circulation. Received: 11 March 1996 / Accepted: 6 September 1996     

Predictability of Mediterranean climate variables from oceanic variability. Part I: Sea surface temperature regimes

The determination of specific sea surface temperature (SST) patterns from large-scale gridded SST-fields has widely been done. Often principal component analysis (PCA) is used to condense the SST-data to major patterns of variability. In the present study SST-fields for the period 1950?C2003 from the area 20°S to 60°N are analysed with respect to SST-regimes being defined as large-scale oceanic patterns with a regular and at least seasonal occurrence. This has been done in context of investigations on seasonal predictability of Mediterranean regional climate with large-scale SST-regimes as intended predictors in statistical model relationships. The SST-regimes are derived by means of a particular technique including multiple applications of s-mode PCA. Altogether 17 stationary regimes can be identified, eight for the Pacific Ocean, five for the Atlantic Ocean, two for the Indian Ocean, and two regimes which show a distinct co-variability within different ocean basins. Some regimes exist, with varying strength and spatial extent, throughout the whole year, whereas other regimes are only characteristic for a particular season. Several regimes show dominant variability modes, like the regimes associated with El Ni?o, with the Pacific Decadal Oscillation or with the North Atlantic Tripole, whereas other regimes describe little-known patterns of large-scale SST variability. The determined SST-regimes are subsequently used as predictors for monthly precipitation and temperature in the Mediterranean area. This subject is addressed in Part II of this paper.     

Mean position and variability of the sea surface temperature front east of the grand banks

Abstract

Three years of weekly sea surface temperature maps were analysed to determine the mean position and standard deviation of the front separating the Mixed Water from the North Atlantic Current water to the east of the Grand Banks between 40–50°N and 40–50°W. The front was found to lie along the path of the North Atlantic Current proposed by Dietrich et al. (1975) and to have a standard deviation ranging from 100 to 200 km. The dominant mode of movement at periods of 6 months and longer consisted of a nearly uniform translation. The trajectories of satellite‐tracked drifting buoys were analysed to create a map of the eddy kinetic energy for the region. The high energy ridge of the map generally corresponded to the mean position of the sea surface temperature front.     

The Dynamical Influence of Land－Sea Contrast and Sea Surface Temperature on Intraseasonal Oscillation in Tropical Atmosphere

An equatorial β-plane model which includes realistic non-uniform land-sea contrast and the underlying surface temperature distribution is used to simulate the 30-60 day oscillation (LFO) processes in tropical atmosphere, with emphasis on its longitude-dependent evolution and convective seesaw between Indian and the western Pacific oceans.The model simulated the twice-amplification of the disturbances over Indian and the western Pacific oceans while they are travelling eastward. It reproduced the dipole structure caused by the out-of-phase oscillation of the active centres in these two areas and the periodical transition between the phases of LFO. It is suggested that the convective seesaw is the result of interaction of the internal dynamics of tropical atmosphere with the zonally non-uniform thermal forcing from underlying surface. The convective activities are suppressed over Indonesia mari-time continents whilst they are favoured over the Indian Ocean and western Pacific warm waters, so there formed two active oscillation centres. The feedback of convection with large-scale flow slows down the propagation of disturb-ances when they are intensifying over these two areas, therefore they manifest a kind of quasi-stationary component to favor the ‘dipole’ structure. Whereas the disturbances weaken and speed up over the eastern Pacific cold water re-gion due to the interaction of sensible heating and evaporation with perturbational wind. Therefore the two major centers just show out-of-phase oscillation during onecycle around the latitudinal beltBy introducing the SST anomalies in El Ni?o and La Ni?a years into the surface temperature, we also show that they have significant influence on LFO processes. In an anomalously warm year, the LFO disturbances dissipate more slowly over the central-eastern Pacific region and can travel farther eastward; whilst in an anomalously cold year, the opposite is true.     

GCM response of the mean zonal surface heat and water budgets to a global sea surface temperature anomaly

Two sets of sensitivity experiments are presented. The first set consists of three 100-day integrations with perpetual January conditions: a reference integration, an integration with a uniform +2 K sea surface temperature (SST) anomaly, and an integration with an anomaly of reverse sign. The second set is similar, but with perpetual July conditions. The zonal mean components of the water and heat budgets at the surface are studied over ocean and over land separately.The values of the reference integration are very close to those obtained when the model is run with annual cycle conditions, and reasonably close to observed values over 60° N−40° S ocean. The SST anomalies produce generally a stronger response in July than in January. This response is linear for the averages over ocean, but if we consider the zonal distribution, only the longwave radiation, latent and sensible heat exhibit a linear response. The model response to temperature increase consists of an enhancement of the water cycle over ocean, and a heat transfer from the ocean, through the latent heat, to the continent. In January, we observe also a water transfer from the ocean to the continent. As a consequence of the heat transfer, the land surface temperature increases by the same magnitude as the SST.     

BCC_CSM对全球海表温度和混合层深度的模拟评估

为了定量评估北京气候中心(BCC)发展的BCC_CSM对当代全球海表温度和混合层深度的模拟能力,以WOA09(World Ocean Atlas 2009)观测资料作为检验模式的气候态实况场,提取包括BCC_CSM在内的CMIP5中的17个海气耦合模式的模拟结果,评估BCC_CSM模拟的全球海表温度和混合层深度的气候平均态并分析造成偏差的可能原因。结果表明:BCC_CSM模拟的海表温度在北半球中高纬的误差较大,而在其余纬度的模拟性能较佳。偏差的产生主要归因于海洋环流偏差。BCC_CSM模拟的最深混合层在北半球中高纬和南半球高纬地区的误差较大,同时这些区域也是多模式模拟差异最大的区域;其模拟的最浅混合层在南半球中高纬的偏差较大。冬季大西洋经向翻转环流的模拟在北大西洋下沉的位置偏南导致北半球高纬地区海表温度偏冷。由此认为包括BCC_CSM在内的许多海气耦合模式需重点改进对南、北半球深对流海域物理过程的描述,以提高气候预测的可信度。