Sea surface temperature predictability in the North Pacific from multi-model seasonal forecast

Sea surface temperature (SST) prediction based on the multi-model seasonal forecast with numerous ensemble members have more useful skills to estimate the possibility of climate events than individual models. Hence, we assessed SST predictability in the North Pacific (NP) from multi-model seasonal forecasts. We used 23 years of hindcast data from three seasonal forecasting systems in the Copernicus Climate Change Service to estimate the prediction skill based on temporal correlation. We evaluated the predictability of the SST from the ensemble members' width spread, and co-variability between the ensemble mean and observation. Our analysis revealed that areas with low prediction skills were related to either the large spread of ensemble members or the ensemble members not capturing the observation within their spread. The large spread of ensemble members reflected the high forecast uncertainty, as exemplified in the Kuroshio–Oyashio Extension region in July. The ensemble members not capturing the observation indicates the model bias; thus, there is room for improvements in model prediction. On the other hand, the high prediction skills of the multi-model were related to the small spread of ensemble members that captures the observation, as in the central NP in January. Such high predictability is linked to El Niño Southern Oscillation (ENSO) via teleconnection.

     

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.     

Distribution,seasonality, lengths,and feeding behaviour of whale sharks (Rhincodon typus) observed in New Zealand waters

Data from 36 whale shark (Rhincodon typus Smith, 1828) sightings off north‐east North Island, New Zealand are summarised. Sightings were concentrated over the outer shelf and shelf break in areas influenced by the East Auckland Current at sea surface temperatures (SST) of 21–24°C. Sightings occurred from late spring to early autumn (November‐April) but were most frequent in midsummer (February) when upwelling along the north‐east shelf is weakest. The data indicate whale sharks occur off north‐east New Zealand most summers, including those when SST is colder than usual. A cluster of sightings and three observations of whale sharks feeding on schools of anchovy (Engraulis australis) near Whale Island, Bay of Plenty, suggest whale sharks may aggregate seasonally in this area. Estimated total lengths (TL) of 26 whale sharks ranged from 3.5 to 15 m, with 73% between 6 and 9 m TL.     

Simulated Heat Content Variability in the Upper Layers of the Tropical Indian Ocean

Ocean General Circulation Model (OGCM) simulations from 1970–2007 are used to study the upper ocean heat content variability in the Tropical Indian Ocean (TIO). Model computed heat contents up to 50 m (denoted by HC50 m hereafter) representing upper ocean heat content and 300 m (HC300 m) representing heat content up to thermocline depth are first compared with heat contents computed from observations of two buoys in the TIO. It is found that there is good agreement between the model and observations. Fourier analysis of heat content is carried out in different regions of TIO. The amplitudes of semi-annual variability for HC50 m and HC300 m are observed to be greater than those for the annual variability in the Bay of Bengal, while in the Arabian Sea there is a mixed result. Heat content tendency is known to be governed by net surface heat flux and horizontal as well as vertical heat transports. For understanding the relative importance of these processes, a detailed analysis of these terms in the tendency equation is carried out. Rossby wave is observed in the annual mode of heat transport while equatorial jet and Kelvin waves are observed in the semi-annual mode of heart transport. Finally, the correlation between heat content and sea surface temperature (SST) and sea level anomaly (SLA), taken one at a time, is computed. It is found that the correlation improves significantly when both these quantities are together taken into account.     

Ocean wave characteristics around New Zealand

Nearly 17 years wave records from deep water and shore‐based stations are used to describe the ocean wave characteristics around New Zealand. The wave environment is dominated by west and southwest swell and storm waves generated in the temperate latitude belt of westerly winds. As a result, the west and south coasts are exposed, high energy shores, the east coast is a high energy lee shore, and the northern coast from North Cape to East Cape is a low energy lee shore sheltered from these winds and waves. South of New Zealand, wave energies are extremely high; the prevailing deep water wave is 3.5–4.5 m high and has a 10–12 s period, with a slight increase in wave heights in winter.

The west coast wave environment is mixed, and consists of locally generated westerly and southerly storm waves, and swell waves generated to the south. The prevailing wave is t.0–3.0 m and 6–8 s period. There are no strong seasonal rhythms, only shorter period cycles of wave height (5 day) associated with similar quasi‐rhythmic cycles in the weather.

The east coast also has a mixed wave climate with southerly swells, originating in the westerlies south of New Zealand, and locally generated southerly and northerly storm waves. The prevailing wave is 0.5–2.0 m and 7–11 s period. A short period rhythmic cycle, similar to that on the west coast, is superimposed on a weak seasonal cycle. The seasonal, cycle results from an increase in the frequency of local northerly waves in summer.

The prevailing wave on the north coast is a northeasterly, 0.5–1.5 m high and 5–7 s period. Subtropical disturbances and southward‐moving depressions generate a mixed wave environment and a possible seasonally reflecting a winter increase in. storminess.     

FIO-ESM气候模式北太平洋海表温度和降水的季节性预报技巧评估

The seasonal prediction of sea surface temperature(SST) and precipitation in the North Pacific based on the hindcast results of The First Institute of Oceanography Earth System Model(FIO-ESM) is assessed in this study.The Ensemble Adjusted Kalman Filter assimilation scheme is used to generate initial conditions, which are shown to be reliable by comparison with the observations. Based on this comparison, we analyze the FIO-ESM 6-month hindcast results starting from each month of 1993–2013. The model exhibits high SST prediction skills over most of the North Pacific for two seasons in advance. Furthermore, it remains skillful at long lead times for midlatitudes. The reliable prediction of SST can transfer fairly well to precipitation prediction via air-sea interactions.The average skill of the North Pacific variability(NPV) index from 1 to 6 months lead is as high as 0.72(0.55) when El Ni?o-Southern Oscillation and NPV are in phase(out of phase) at initial conditions. The prediction skill of the NPV index of FIO-ESM is improved by 11.6%(23.6%) over the Climate Forecast System, Version 2. For seasonal dependence, the skill of FIO-ESM is higher than the skill of persistence prediction in the later period of prediction.     

OSTIA数据在中国近海业务化环流模型中的同化应用

The prediction of sea surface temperature(SST) is an essential task for an operational ocean circulation model. A sea surface heat flux, an initial temperature field, and boundary conditions directly affect the accuracy of a SST simulation. Here two quick and convenient data assimilation methods are employed to improve the SST simulation in the domain of the Bohai Sea, the Yellow Sea and the East China Sea(BYECS). One is based on a surface net heat flux correction, named as Qcorrection(QC), which nudges the flux correction to the model equation; the other is ensemble optimal interpolation(En OI), which optimizes the model initial field. Based on such two methods, the SST data obtained from the operational SST and sea ice analysis(OSTIA) system are assimilated into an operational circulation model for the coastal seas of China. The results of the simulated SST based on four experiments, in 2011, have been analyzed. By comparing with the OSTIA SST, the domain averaged root mean square error(RMSE) of the four experiments is 1.74, 1.16, 1.30 and 0.91°C, respectively; the improvements of assimilation experiments Exps 2, 3 and 4 are about 33.3%, 25.3%, and 47.7%, respectively.Although both two methods are effective in assimilating the SST, the En OI shows more advantages than the QC,and the best result is achieved when the two methods are combined. Comparing with the observational data from coastal buoy stations, show that assimilating the high-resolution satellite SST products can effectively improve the SST prediction skill in coastal regions.     

El Niño and decadal effects on sea‐level variability in northern New Zealand: A wavelet analysis

Sea‐level data from two sites in northern New Zealand, along with the Southern Oscillation Index (SOI), are analysed for interannual and decadal variability using wavelets. The analysis shows, using statistically significant wavelet power, there is a significant relationship between mean sea level (MSL) and SOI. However, the relationship is highly variable, both in magnitude and in the range of time‐scales over which it occurs. This non‐stationarity necessitates the use of techniques such as wavelets for analysis. An interdecadal response in MSL around northern New Zealand has been isolated, with shifts occurring in 1950 and the late 1970s. This behaviour in MSL appears to coincide with shifts in the Pacific Decadal Oscillation, thought previously to be largely centred in the North Pacific. A strong correlation between SOI and sea surface temperature (SST) is also demonstrated. This relationship appears to be stable in magnitude (a large change in SOI produces a large change in SST) and to occur over the same range of time‐scales. More SST and MSL data are required for other parts of New Zealand to determine whether these findings apply elsewhere.     

Comparison of AVHRR measurements of sea surface temperature with surface observations around New Zealand

Multi‐channel Advanced Very‐High Resolution Radiometer (AVHRR) images of sea surface temperature (SST) in the New Zealand region have been archived since 1989. A comparison of these data with conductivity‐temperature‐depth (CTD) and expendable bathythermograph (XBT) data shows that the AVHRR temperatures are about 7% too high (when expressed in °C). Once the AVHRR temperatures have been corrected, they measure SST with an uncertainty of about 0.7°C.     

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%.     

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.     

Assimilation of sea surface temperature in the Northwest Pacific Ocean and its marginal seas using the ensemble Kalman filter

Satellite-borne sea surface temperature (SST) data were assimilated with the ensemble Kalman filter (EnKF) in a Northwest Pacific Ocean circulation model to examine the effect of data assimilation. The model domain included the northwestern part of the Pacific Ocean and its marginal seas, such as the Yellow Sea and East/Japan Sea. The performance of the data assimilation was evaluated by comparing the simulated ocean state with that observed. Spatially averaged root-mean-squared errors in the SST and sea surface height (SSH) decreased by 0.44 °C and 4 cm, respectively, by the assimilation. The results of the numerical experiments substantiated the effectiveness of the SST assimilation via the EnKF for all marginal seas, as well as the Kuroshio region. The benefit of the data assimilation depended on the characteristics of each marginal sea. The variation of the SST in the East/Japan Sea and the Kuroshio extension (KE) region were improved 34% and those in the Yellow Sea 12.5%. The variation of the SSH was improved approximately 36% in the KE region. This large improvement was achieved in the deep-water regions because assimilation of SST data corrected the separation point of the western boundary currents, such as the Kuroshio and the East Korea Warm Current, and the associated horizontal surface currents. The SST assimilation via the EnKF also improved the subsurface temperature profiles. The effectiveness of SST assimilation was seasonally dependent, with the improvement being relatively larger in winter than in summer, which was related to the seasonal variation of the vertical mixing and stratification in the ocean surface layer.     

Urban and ocean ensembles for improved meteorological and dispersion modelling of the coastal zone

A high-resolution (1.67 km) ensemble transform (ET)-based meso-scale modelling system utilizing urbanization and sea surface temperature (SST) perturbations is used to examine characteristics of sea breeze/heat island interactions and atmospheric transport and dispersion for Tokyo. The ensemble displays a positive spread–skill relationship, with the addition of urban perturbations enabling the ensemble variance to distinguish a larger range of forecast error variances. Two synoptic regimes are simulated. For a pre-frontal period (stronger synoptic flow), there is less variability among ensemble members in the strength of the urban heat island and its interaction with the sea breeze front. During the post-frontal time period, the sea breeze frontal position is very sensitive to the details of the urban representation, with horizontal frontal variation covering the width of the urban centre (∼30 km) and displaying significant impacts on the development and strength of the heat island. Moreover, the dosage values of a tracer released at offshore and urban sites have considerable variability among ensemble members in response to small-scale features such as coastally upwelled water, enhanced anthropogenic heating and variations in building heights. Realistic variations in SST (i.e. warm Tokyo Bay or local upwelling) produce subtle sea breeze variations that dramatically impact tracer distributions.     

Seasonal variability in the Macroinvertebrate Community Index: Are seasonal correction factors required?

Freshwater macroinvertebrate data collected from streams in Taranaki, New Zealand (1981–2006) were used to examine seasonality of biological indices including taxon richness, %EPT (Ephemeroptera, Plecoptera, and Trichoptera) richness, and the hard‐ and soft‐bottomed (‐sb) stream versions of the Macroinvertebrate Community Index (MCI). All indices tested showed modest but statistically significant seasonal variation in hard‐bottomed streams. Seasonal means for the MCI were within ±3.0% of the annual mean. The Semi‐Quantitative MCI (SQMCI) (±4.3%), %EPT richness (±7.4%) and taxon richness (±7.7%) showed greater seasonal variability than the MCI. MCI, SQMCI, and %EPT richness were significantly higher in spring and winter compared with autumn and summer. Taxon richness was lower in winter than in other seasons. In soft‐bottomed streams, SQMCI‐sb showed least seasonality (within ±3.6% of the annual mean, nonsignificant), followed by MCI‐sb and taxon richness (±4.7%), and %EPT richness (±11.2%). Spring and winter MCI‐sb and SQMCI‐sb values tended to be significantly higher than those calculated from summer or autumn samples, although most values were within 5% of the annual site means. Examination of seasonal variation in species traits and their relationships to observed seasonal patterns of biotic indices did not support the suggestion that seasonal variations in life histories of aquatic macroinvertebrates affect index values. Rather, seasons with higher biotic index values were associated with a greater frequency of flow disturbance, which is consistent with the view that the character of New Zealand's stream macroinvertebrate communities with their poorly‐synchronised life histories, has been shaped by the unpredictable physical environment. We recommend the MCI and MCI‐sb for State of Environment reporting in New Zealand for cost‐effectiveness and because data requirements and seasonal variation were less than for quantitative alternative indices. We suggest that seasonal variability is unlikely to confound interpretation, and does not need to be considered.     

Planktonic stages of Maurolicus muelleri (Teleostei Sternoptychidae) in New Zealand waters

The seasonality and distribution, abundance, and hydrological affinities of the planktonic stages of the sternoptychid Maurolicus muelleri (Grnelin, 1788) are described for the New Zealand region. Spawning occurred from August to March, and the planktonic stages were widespread around New Zealand. Spawning probably takes place around midday at depths greater than 250 m. Eggs and larval stages were present over temperature ranges of 9.0–15.5°c and 13–22°c respectively.     

集合同化方法在黄海海域海表面温度同化中的应用

The effects of sea surface temperature(SST) data assimilation in two regional ocean modeling systems were examined for the Yellow Sea(YS). The SST data from the Operational Sea Surface Temperature and Sea Ice Analysis(OSTIA) were assimilated. The National Marine Environmental Forecasting Center(NMEFC) modeling system uses the ensemble optimal interpolation method for ocean data assimilation and the Kunsan National University(KNU) modeling system uses the ensemble Kalman filter. Without data assimilation, the NMEFC modeling system was better in simulating the subsurface temperature while the KNU modeling system was better in simulating SST. The disparity between both modeling systems might be related to differences in calculating the surface heat flux, horizontal grid spacing, and atmospheric forcing data. The data assimilation reduced the root mean square error(RMSE) of the SST from 1.78°C(1.46°C) to 1.30°C(1.21°C) for the NMEFC(KNU) modeling system when the simulated temperature was compared to Optimum Interpolation Sea Surface Temperature(OISST) SST dataset. A comparison with the buoy SST data indicated a 41%(31%) decrease in the SST error for the NMEFC(KNU) modeling system by the data assimilation. In both data assimilative systems, the RMSE of the temperature was less than 1.5°C in the upper 20 m and approximately 3.1°C in the lower layer in October. In contrast, it was less than 1.0°C throughout the water column in February. This study suggests that assimilations of the observed temperature profiles are necessary in order to correct the lower layer temperature during the stratified season and an ocean modeling system with small grid spacing and optimal data assimilation method is preferable to ensure accurate predictions of the coastal ocean in the YS.     

GCM experiments on changes in atmospheric predictability associated with the PNA pattern and tropical SST anomalies

Based on results from a simple three-level quasi-geostrophic model, Lin and Derome suggested that atmospheric predictability is influenced by the Pacific/North American (PNA) pattern. In the present study, predictability experiments are conducted with the Canadian Centre for Climate Modelling and Analysis general circulation model (CCCma GCM). A 47-yr integration of the GCM with specified sea surface temperature (SST) for the years 1948–94 is first performed. Forecasts are initiated whenever the PNA pattern is in a strong positive or strong negative phase during this simulation. For each forecast, an ensemble of six initial conditions is generated with small random perturbations. Forecasts initiated when the PNA is in its positive phase have smaller growth rates of ensemble standard deviation than forecasts initiated when the PNA is in its negative phase. Regional characteristics of the prediction spread are also examined. Similar experiments are conducted to determine the relationship between atmospheric predictability and SST anomalies in the tropical Pacific. Forecasts initiated when tropical SST anomalies are positive have smaller growth rates of ensemble standard deviation than forecasts initiated when tropical SST anomalies are negative. However, cases with positive tropical SST anomalies but without a strong PNA pattern show a similar prediction spread to cases with negative SST anomalies. The results suggest that, in comparison to the PNA pattern, the influence of tropical SST anomalies is only secondary. A set of three-layer diagnostic equations is used to analyze the GCM results. It is speculated that the transient eddies have a stronger influence on the circulation anomalies (and therefore reduce the atmospheric predictability more) in the negative PNA phase than in the positive PNA phase.     

The other 93%: trophic cascades,stressors and managing coastlines in non-marine protected areas

Abstract

This paper reviews interactions involving stands of macroalgae on rocky reefs, and presents new data on changing sea surface temperatures (SSTs), as a contribution to the celebration of the fiftieth anniversary of the Leigh Marine Laboratory (LML) of the University of Auckland. The focus is on trophic interactions involving predators, sea urchins and large brown algae, particularly trophic cascades. Of the 369 publications arising from work at LML, 40 have been on key aspects of these trophic interactions. Quantitative investigations of the structure of kelp bed communities and mechanistic studies involving manipulative field-based experiments, essentially a bottom-up perspective based on habitats and key species, dominated the research through the 1980s. From the mid-1990s onwards, the focus was more on marine reserves and a hierarchical, top-down perspective of community structure, with a particular focus on the role of predatory fish, and marine reserves as a tool of management. I discuss these models of community structure of kelp beds within the wider context of the New Zealand nearshore zone, the varying biogeographic regimes around the coastline, diffuse stressors and the changing nearshore climate. I show there appears to have been a significant warming trend in SST in northeast and northwest New Zealand over the past 30 years. I conclude that a trophic effects model is unlikely to apply to much of the coastline of New Zealand, and that a model involving multiple effects, including bottom-up forces, environmental and climatic influences, species' demographics, and catchment-derived sedimentation is more appropriate for kelp communities over most of the country. New management models are needed to safeguard marine resources and the services they provide.     

Ocean temperature change around New Zealand over the last 36 years

Ocean temperature changes around New Zealand are estimated from satellite sea surface temperature (SST) products since 1981, two high resolution expendable bathythermograph transects (HRXBT) since 1986 and 1991, and Argo data since 2006. The datasets agree well where they overlap. Significant surface warming is found in subtropical waters. Greatest warming is east of Australia and in the central Pacific. All NZ coastal waters are warming, with strongest warming east of Wairarapa and weakest between East Cape and North Cape. Temperature changes are surface intensified, extending to ～200 m in the northeast and at least 850 m in the eastern Tasman. Significant interannual variability is coherent over a large area of ocean north of the Subtropical Front and modulates extreme events. NZ air temperatures are highly correlated at interannual timescales with SSTs over a broad region of ocean north of the Subtropical Front from the eastern Tasman to east of the dateline.