Monthly Mean Sea Research Articles

Can We See the Wind? Statistical Downscaling of Historical Sea Surface Winds in the Subarctic Northeast Pacific

The statistical predictability of wintertime (December–February) monthly-mean sea surface winds (both vector wind components and wind speed) in the subarctic northeast Pacific off the west coast of Canada is considered, in the context of surface wind downscaling. Predictor fields (zonal wind, meridional wind, wind speed, and temperature) are shown to carry predictive information on the large scales (both vertical and horizontal) that are well simulated by numerical weather prediction and global climate models. It is found that, in general, the monthly mean vector wind components are more predictable by indices of the large-scale flow than by the monthly mean wind speed, with no systematic vertical variation in predictive skill for either across the depth of the troposphere. The difference in predictive skill between monthly-mean vector wind components and wind speed is interpreted in terms of an idealized model of the vector wind speed probability distribution, which demonstrates that for the conditions in the subarctic northeast Pacific, the sensitivity of mean wind speed to the standard deviations of vector wind component fluctuations (which are not well predicted) is greater than that to the mean vector wind components. It is demonstrated that this sensitivity is state dependent, and it is suggested that monthly mean wind speeds may be inherently more predictable in regions where the sensitivity to the vector wind component means is greater than that to the standard deviations. It is also demonstrated that daily wind fluctuations (both vector wind and wind speed) are generally more predictable than monthly-mean variability, and that monthly averages of the predicted daily winds generally represent the monthly-mean surface winds better than the predictions directly from monthly mean predictors.

Smooth Piecewise Algebraic Approximation as Applied to Large-Scale 2D Scattered Geodetic Data Fitting

We have developed an efficient method, Smooth Piecewise Algebraic Approximation (hereafter SPAA), to automatically compute a smooth approximation of large-scale functional scattered 2D observation points and tilt between them. The area of study is divided into patches and piecewise algebraic surfaces are fitted to the data. When the surfaces are approximated, a set of constraints is imposed in such a way that the resulting function is continuous only in the zero and first derivatives everywhere in the region, which results in a very short computation time. In other word, the surfaces are fitted simultaneously, using the constraints as set-conditions which the parameters of the surfaces must also satisfy. This method does not require a triangulation or quadrangulation of the data points and as such, it is very well suited for extremely large datasets.This method has been successfully applied to the monthly mean sea level and re-levelling data in Canada to thereby compile a map of Vertical Crustal Movements (VCM) in the region. The VCM model obtained using this method accommodates different kinds of scattered geodetic data, while yielding the optimum approximation to them. Enforcing the continuity and smoothness throughout the surfaces, the VCM model of Canada highlights the long wavelength temporal variations of the crust in the region, mainly due to Post Glacial Rebound (PGR). As a result, using the method of SPAA, a more physically meaningful VCM is modelled.

Sea level trends and NAO influences: The Bristol Channel/Severn Estuary

Fifteen years, 1993 (earliest available) to 2007 inclusive of monthly mean and extreme (maximum and minimum) sea level data were assessed for four tide gauges located in the Bristol Channel (Mumbles and Ilfracombe) and Severn Estuary (Newport and Hinkley Point). Results showed decreasing maximum sea level trends and increasing minimum sea level trends, resulting in convergence. However, maximum extreme sea levels on the Welsh shoreline (Mumbles and Newport) were higher than corresponding locations on the English coast (Ilfracombe and Hinkley Point). Analysis showed that from 1995 to 1998 inclusive, maximum extreme sea levels were significantly higher at Mumbles (t = 2.342; df = 10; p < 0.05), Newport (t = 5.034; df = 13; p < 0.01) and Hinkley Point (t = 3.570; df = 13; p < 0.01) and were correlated to increased storm frequencies during these years. However, Ilfracombe (t = 1.472; df = 12; p > 0.05) did not demonstrate similar significance, possibly due to tide gauge location and coastal aspect, while tidal influences became more dominant as the tidal prism moved up the estuary. Actual mean sea levels (MSL) at Newport (t = 2.880; df = 14; p < 0.05) and Hinkley Point (t = 5.282; df = 14; p < 0.01) were significantly higher than predicted; at Mumbles (t = 2.673; df = 11; p < 0.05) they were significantly lower than predicted; while Ilfracombe (t = 1.989; df = 13; p > 0.05) once again showed no significant difference. Mumbles is the only location with off-shore sand waves and analysis suggested these as the cause of opposite trends. Sea level variation was strongly correlated to the North Atlantic Oscillation (NAO) Index, especially for maximum extreme sea levels during positive phases (R 2 = 86%), and higher positive or negative NAO Index values resulted in larger sea level ranges. Further analysis showed a rising Bristol Channel and Severn Estuary MSL trend of 2.4 mm yr − 1 and a 2050 MSL of 0.370 m is projected to inform future management. However, continuous updating and refinement of the sea level datasets will be needed.

Distinct modes of winter arctic sea ice motion and their associations with surface wind variability

Using monthly mean sea ice velocity data obtained from the International Arctic Buoy Programme (IABP) for the period of 1979–1998 and the monthly mean NCEP/NCAR re-analysis dataset (1960–2002), we investigated the spatiotemporal evolution of the leading sea ice motion mode (based on a complex correlation matrix constructed of normalized sea ice motion velocity) and their association with sea level pressure (SLP) and the predominant modes of surface wind field variability. The results indicate that the leading winter sea ice motion mode’s spatial evolution is characterized by two alternating and distinct sea ice modes, or their linear combination. One mode (M1) shows a nearly closed cyclonic or anti-cyclonic circulation anomaly in the Arctic Basin and its marginal seas, resembling to a large extent the response of sea ice motion to the Arctic Oscillation (AO), as many previous studies have revealed. The other mode (M2) displays a coherent cyclonic or anti-cyclonic circulation anomaly with its center close to the Laptev Sea, which has not been identified in previous observational studies. In fact, M1 and M2 respectively reflect the responses of sea ice motion to two predominant modes of winter surface wind variability north of 70°N, which well correspond, with slight differences, to the first two modes of EOF analysis of winter monthly mean SLP north of 70°N. These slight differences in SLP anomalies lead to a difference of M2 from the response of sea ice motion to the dipole anomaly. Although the AO significantly influences sea ice motion, it is not crucial for the existence of M1. The new sea ice motion mode (M2) has the largest variance and clearly differs from the response of winter monthly mean sea ice motion to the dipole anomaly in SLP fields, and corresponding SLP anomalies also show differences compared to the dipole anomaly. This study indicates that in the Arctic Basin and its marginal seas, slight differences in SLP anomaly patterns can force distinctly different sea ice motion anomalies.

Anomalous biogeochemical conditions in the northern South China Sea during the El‐Niño events between 1997 and 2003

Anomalous biogeochemical conditions were observed at the SouthEast Asian Time‐series Study (SEATS) station in the northern South China Sea (SCS) during the 1997–98 and 2002–03 El Niño events. The time‐series records showed decreases of monthly mean sea surface chlorophyll‐a (S‐chl) (and integrated primary production, IPP) by 42% (and 42%) and 13% (and 10%), respectively, below the climatological mean in the winter months (DJF) of the two events. The negative anomalies in S‐chl and IPP corresponded to elevated sea surface temperature by 1.2°C and 0.4°C, respectively, above the climatological mean, while the mean wind speed was reduced by about 20% and 11%, respectively. Statistical analysis demonstrated the reduction in S‐chl and IPP during El Niño events was caused by the diminished vertical mixing and strengthened stratification. Regional anomalies in hydrographic and biological conditions in the northern SCS (15–21°N and 112–119°E) were consistent with those found at the SEATS site.

Evidence for tropical SST influence on Antarctic polar atmospheric dynamics

A Singular Value Decomposition analysis is applied to climatological data to determine the modes of variability of monthly mean Sea Surface Temperature (SST) in the tropics coupled with the southern hemisphere stratospheric polar vortex intensity for the 1958 to 2006 period and to identify the tropical region strongly influencing the high latitude stratospheric dynamics. Two subsets of data have been considered by explicitly taking into account the phase of the Pacific Decadal Oscillation (PDO). The study evidences a shift of the tropical region affecting the polar vortex from the Western Pacific to the Indo‐Pacific Ocean, driven by the modulation of the SST pattern, due to the phase of the PDO. The analysis shows in both cases (years with positive/negative PDO phases) a high degree of correlation between an SST related index, calculated from NOAA/ERSST and HadISST datasets, and an index of the polar vortex intensity based on ECMWF data.

Reproductive cycle and gonad development of the Northern Argentinean Mesodesma mactroides (Bivalvia: Mesodesmatidae)

The reproductive cycle and gonad development of the yellow clam Mesodesma mactroides was studied over a period of 24 months (January 2005–December 2006) at the Argentinean sandy beach Santa Teresita. Histological examination of gonadal tissue revealed that sex ratios did not significantly deviate from the proportion of 1:1 and no case of hermaphroditism was found. The reproductive cycle of M. mactroides followed an annual cyclicality, which was significantly correlated to monthly mean sea surface temperatures (SST). Oocytes showed highest abundance in winter, indicating a process of gonadal development and sexual maturation. The mean oocyte size decreased significantly during spring. Modal oocyte sizes decreased significantly during winter and late spring of each year, suggesting spawning events. The condition index was not useful in describing the annual reproductive cycle of M. mactroides. Ash-free, shell-free dry mass was chosen to detect the condition of the specimens, and this significantly correlated with monthly mean SST and the gametogenic cycle. Annual recruitment patterns during summer–autumn indicated a 3-month-long planktonic phase of M. mactroides. The reproduction cycle and gonad development of M. mactroides showed only weak differences between data from the present study and those collected 40 years ago.

Reconsideration of the True versus Apparent Arctic Oscillation

Abstract The physical reality of the Arctic Oscillation (AO; or northern annular mode) is considered. The data used are mainly the monthly mean sea level pressure (SLP). A schematic figure is first presented to illustrate the relationship between the North Atlantic Oscillation (NAO)–Pacific–North American Oscillation (PNA) system and the AO–negative correlation mode between the Atlantic and the Pacific (AO–NCM) system. Although the NAO–PNA (apparent AO–NCM) and true AO–NCM systems give rise to the same EOFs, the probability density functions for the time coefficients of the two leading modes are different. Therefore, the discrimination of the two systems is possible. Several pieces of evidence indicate that, in the real world, the NAO–PNA and the AO–NCM are located on almost the same plane in phase space. This means that the NAO–PNA and AO–NCM systems have the same variations on the plane in common, implying that when the NAO–PNA system is real, the AO–NCM is unlikely to be real. Simple independent component analysis is carried out to distinguish between the true and apparent AO–NCM systems, indicating that the NAO and PNA are independent oscillations, that is, true ones. The analysis is extended to the winter mean SLP field, for which the EOF shows the NAO–PNA but not the AO–NCM. This may be due to the fact that the winter mean NAO and PNA patterns have little spatial correlation. Calculations using randomly selected samples also indicate that when the NAO and PNA patterns have little spatial correlation, the AO never appears as EOF1. All the preceding results show that almost all characteristics of the AO–NCM can be explained from those of the NAO–PNA. Hence it is concluded that the AO, which is extracted by EOF analysis from the temporarily independent but spatially overlapping variations of the NAO and PNA, is almost apparent.

Upper ocean response of the Mesoamerican Barrier Reef System to Hurricane Mitch and coastal freshwater inputs: A study using Sea‐viewing Wide Field‐of‐view Sensor (SeaWiFS) ocean color data and a nested‐grid ocean circulation model

The passage of category‐5 Hurricane Mitch through the Mesoamerican Barrier Reef System (MBRS) in October 1998 was an extreme event with the potential to create unusual patterns of reef connectivity. The impact of this hurricane on the upper ocean of the MBRS is investigated using a triply nested grid ocean circulation modeling system. The model results are validated with contemporaneous ocean color data from the Sea‐viewing Wide Field‐of‐view Sensor (SeaWiFS) satellite and oceanographic measurements in the MBRS. The nested grid system is forced by 6‐hourly National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) winds for the first 294 days prior to the arrival of the hurricane in the MBRS, and then by the combination of the NCEP/NCAR wind‐forcing and an idealized vortex representative of Mitch for the following 20 days. The system is also forced by the monthly mean sea surface heat and freshwater fluxes and buoyancy forcing associated with major river discharges and storm‐induced precipitation in the western Caribbean Sea. The simulated upper ocean circulation during Mitch is characterized by strong and divergent currents under the storm and intense near‐inertial currents and sea surface temperature cooling behind the storm. The nested grid system also reproduces the buoyant estuarine plumes extending from the coast off Honduras as inferred from SeaWiFS satellite data and detected in field measurements at Gladden Spit in Belize shortly after the passage of Hurricane Mitch. The present model results suggest that populations of site‐attached organisms associated with nearshore and offshore reef features that are dynamically isolated in normal conditions experienced greater potential for ecological connection under Mitch's extreme conditions.

North Atlantic climate variability from a self‐organizing map perspective

North Atlantic variability in general, and the North Atlantic Oscillation (NAO) in particular, is a long‐studied, very important but still not well‐understood problem in climatology. The recent trend to a higher wintertime NAO index was accompanied by an additional increase in the Azores High not coupled to changes in the Icelandic Low, as shown by a self‐organizing maps (SOMs) analysis of monthly mean DJF mean sea level pressure data from 1957 to 2002. SOMs are a nonlinear tool to optimally extract a user‐specified number of patterns or icons from an input data set and to uniquely relate any input data field to an icon, allowing analyses of occurrence frequencies and transitions complementary to principal component analysis (PCA). SOMs analysis of ERA‐40 data finds a North Atlantic “monopole” roughly colocated with the mean position of the Azores High, as well as the well‐known NAO dipole involving the Icelandic Low and the subtropical high. Little trend is shown in December, but the Azores High increased along with the NAO in January and February over the study interval, with implications for storminess in northwestern Europe. In short, our SOM‐based analyses of winter MSLP have both confirmed prior knowledge and expanded it through the relative ease of use and power with nonlinear systems of the SOM‐based approach to climatological analysis.

Arctic or North Atlantic Oscillation? Arguments based on the principal component analysis methodology

The Arctic Oscillation (AO) appears as the leading unrotated mode of principal component analysis (PCA) of monthly mean sea level pressure anomalies, whereas the North Atlantic Oscillation (NAO) results from rotated PCA, regardless of the number of PCs rotated. Three criteria are employed to decide whether the interpretation in terms of the NAO or AO should be preferred: the degree of simple structure, the similarity between the PC loadings and correlation/covariance maps, and the sensitivity to spatial subsampling. All these criteria favour, to a different extent, the interpretation in terms of the NAO. This is further supported by more general arguments. Therefore, the statistical arguments suggest that in interpreting the Northern Hemisphere circulation variability, the sectorial view, i.e. the NAO, should be preferred to the hemispheric view, i.e. the AO. Our analysis supports the idea expressed in other studies that the AO is rather a statistical artifact.

Demographic variation in the New Zealand abalone Haliotis iris

Growth data for the New Zealand abalone Haliotis iris were collected from 30 sites around the New Zealand coast by tag–recapture methods. Most data were collected to provide input into abalone stock assessments within discrete management areas, but had not been examined to determine the nature or extent of any large-scale patterns that might be useful to fishery managers. Sites spanned more than 10° of latitude and were subject to a large range of wave energies and temperatures. Mean monthly sea surface temperature (SST) and wave energy were estimated for each site and a generalised linear regression model was used to examine the relationship between variables. Size-at-maturity was also examined at ten sites. Initial length of abalone explained 35% of the variation in incremental growth, and a further 19% was explained by maximum SST, which also explained 60% of the variation in asymptotic length. Fastest growth was generally in areas with lower mean monthly maximum SST, and sites with the slowest growth had the highest mean monthly maximum SST. Size-at-maturity decreased with increasing temperature. The implications of these broad patterns upon abalone fisheries management strategies are discussed.

Glacier mass balance in southern norway modelled by circulation indices and spring‐summer temperatures ad 1781–2000

By stepwise regression analysis the accumulation, ablation, and equilibrium line altitude (ELA) were modelled by circulation indices and spring‐summer temperature on six Norwegian glaciers (Ålfotbreen, Nigardsbreen, Rembesdalsskåka, Storbreen, Hellstugubreen and Gråsubreen). The circulation indices were derived from a gridded monthly mean sea level pressure (MSLP) data set, whereas temperature series were derived from instrumental and proxy data.Analyses showed that accumulation on the western glaciers was strongly related to western airflow perpendicular to the main mountain range releasing precipitation on the glaciers. No other airflow variable significantly improved the regression. For the continental glaciers, circulating air in connection with low pressure systems was also found to be important. This may explain the lack of synchronicity in the glaciers' development in southern Norway during the Holocene. Accumulation was better modelled using the MSLP data set than by using the North Atlantic Oscillation (NAO) index as predictor.The decadal variations of accumulation, ablation, and ELA were analysed by a Gaussian low pass filter. The well‐known abundant accumulation on Norwegian glaciers during the early 1990s turned out to be unprecedented during the entire series (since 1781), whereas the accumulation of the 1960s has not been lower since the early 19th century according to model results. Ablation increased significantly from the mid‐19th century to the 1930s. The ablation maximum during the 1930s has not yet been exceeded. Also the 1930s show extremely high ELA values.

Predicting the Onset of Australian Winter Rainfall by Nonlinear Classification

Abstract A method for predicting the timing of winter rains is presented, making no assumptions about the functional form of any relationships that may exist. Ideas built on classification and regression trees and machine learning are used to develop robust predictive rules. These methods are applied in a case study to predict the timing of winter rain in five farming towns in the southwest of Western Australia. The variables used to construct the model are mean monthly sea surface temperatures (SSTs) over a 72-cell grid in the Indian Ocean, Perth monthly mean sea level pressure (MSLP), and monthly values of the Southern Oscillation index (SOI). A predictive model is constructed from data over the period 1949–99. This model correctly classifies the onset of the winter rains approximately 80% of the time with SST variables proving to be the most important in deriving the predictions. Further analysis indicates a change point in the mid-1970s, a well-known phenomenon in the region. The prediction rates are significantly worse after 1975. Furthermore, the important region of the Indian Ocean, in terms of SSTs for prediction, moves from the Tropics down toward the Southern Ocean after this date.

How Does Solar Attenuation Depth Affect the Ocean Mixed Layer? Water Turbidity and Atmospheric Forcing Impacts on the Simulation of Seasonal Mixed Layer Variability in the Turbid Black Sea*

Abstract A fine-resolution (≈3.2 km) Hybrid Coordinate Ocean Model (HYCOM) is used to investigate the impact of solar radiation attenuation with depth on the predictions of monthly mean sea surface height (SSH), mixed layer depth (MLD), buoyancy and heat fluxes, and near-sea surface circulation as well. The model uses spatially and temporally varying attenuation of photosynthetically available radiation (kPAR) climatologies as processed from the remotely sensed Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) to take water turbidity into account in the Black Sea. An examination of the kPAR climatology reveals a strong seasonal cycle in the water turbidity, with a basin-averaged annual climatological mean value of 0.19 m−1 over the Black Sea. Climatologically forced HYCOM simulations demonstrate that shortwave radiation below the mixed layer can be quite different based on the water turbidity, thereby affecting prediction of upper-ocean quantities in the Black Sea. The clear water constant solar attenuation depth assumption results in relatively deeper MLD (e.g., ≈+15 m in winter) in comparison to standard simulations due to the unrealistically large amount of shortwave radiation below the mixed layer, up to 100 W m−2 during April to October. Such unrealistic sub–mixed layer heating causes weaker stratification at the base of the mixed layer. The buoyancy gain associated with high solar heating in summer effectively stabilizes the upper ocean producing shallow mixed layers and elevated SSH over the most of the Black Sea. In particular, the increased stability resulting from the water turbidity reduces vertical mixing in the upper ocean and causes changes in surface-layer currents, especially in the easternmost part of the Black Sea. Monthly mean SSH anomalies from the climatologically forced HYCOM simulations were evaluated against a monthly mean SSH anomaly climatology, which was constructed using satellite altimeter data from TOPEX/ Poseidon (T/P), Geosat Follow-On (GFO), and the Earth Remote Sensing Satellite-2 (ERS-2) over 1993–2002. Model–data comparisons show that the basin-averaged root-mean-square (rms) difference is ≈4 cm between the satellite-based SSH climatology and that obtained from HYCOM simulations using spatial and temporal kPAR fields. In contrast, when all solar radiation is absorbed at the sea surface or clear water constant solar attenuation depth values of 16.7 m are used in the model simulations, the basin-averaged SSH rms difference with respect to the climatology is ≈6 cm (≈50% more). This demonstrates positive impact from using monthly varying solar attenuation depths in simulating upper-ocean quantities in the Black Sea. The monthly mean kPAR and SSH anomaly climatologies presented in this paper can also be used for other Black Sea studies.

A Simplified Linear Framework for Interpreting Patterns of Northern Hemisphere Wintertime Climate Variability

Abstract The principal patterns of variability of the extratropical Northern Hemisphere (NH) wintertime circulation are examined, based on 42 yr of data from the NCAR–NCEP reanalyses. The two-dimensional phase space defined by the two leading PCs of the monthly mean sea level pressure (SLP) field poleward of 20°N is used as a basis for surveying the structure of the geopotential height and surface air temperature (SAT) fields. Together these two patterns account for roughly half the variance of SLP on interannual time scales and longer, and virtually all the planetary-scale SLP trends over the 42-yr period of record. The leading EOF corresponds to the NH annular mode (NAM), and the second EOF resembles the Pacific–North America (PNA) pattern. The leading EOF of the monthly mean geopotential height field at various levels throughout the troposphere and lower stratosphere is well represented by linear combinations of these two SLP patterns, as are the intraseasonal and interannual SLP fields, the NAM, the N...

Long-Range Statistical Forecasting of Ice Severity in the Beaufort–Chukchi Sea

Abstract Interannual variations in Beaufort Sea summer ice conditions influence a wide range of socioeconomic activities, including merchant shipping in the Beaufort Sea and subsistence lifestyles on the Alaskan North Slope. Each year, the National Ice Center quantifies Beaufort Sea summer ice conditions based on the Barnett severity index (BSI), which is based on distances from Point Barrow, Alaska, to the sea ice edge, as well as characteristics of the shipping season from Prudhoe Bay to the Bering Sea. Long-range forecasts (monthly to seasonal) of the BSI would be valuable for the above-mentioned users, provided that the forecasts are communicated effectively and used properly. Utilizing mean monthly sea ice and atmospheric data from 1979 through 2000, multiple linear regression models are developed here to forecast the BSI at monthly intervals from October of the previous year through to July of the prediction year. The final models retain between three and five variables, with decreased multiyear sea...

Climatological SST and MLD Predictions from a Global Layered Ocean Model with an Embedded Mixed Layer*

The Naval Research Laboratory (NRL) Layered Ocean Model (NLOM) with an embedded mixed layer submodel is used to predict the climatological monthly mean sea surface temperature (SST) and surface ocean mixed layer depth (MLD) over the global ocean. The thermodynamic model simulations presented in this paper are performed using six dynamical layers plus the embedded mixed layer at 1/28 resolution in latitude and 0.7031258 in longitude, globally spanning from 728 St o 658N. These model simulations use climatological wind and thermal forcing and include no assimilation of SST or MLD data. To measure the effectiveness of the NLOM mixed layer, the annual mean and seasonal cycle of SST and MLD obtained from the model simulations are compared to those from different climatological datasets at each grid point over the global ocean. Analysis of the global error maps shows that the embedded mixed layer in NLOM gives accurate SST with atmospheric forcing even with no SST relaxation/assimilation. In this case the model gives a global root-mean-square (rms) difference of 0.378C for the annual mean and 0.598C over the seasonal cycle over the global ocean. The mean global correlation coefficient (R) is 0.91 for the seasonal cycle of the SST. NLOM predicts SST with an annual mean error of ,0.58C in most of the North Atlantic and North Pacific Oceans. For the MLD the model gave a global rms difference of 34 m for the annual mean and 63 m over the seasonal cycle over the global ocean in comparison to the NRL MLD climatology (NMLD). The mean global R value is 0.62 for the seasonal cycle of the MLD. Additional model‐data comparisons use climatological monthly mean SST time series from 18 National Oceanic Data Center (NODC) buoys and 11 ocean weather station (OWS) hydrographic locations in the North Pacific Ocean. The median rms difference between the NLOM SSTs and SSTs at these 29 locations is 0.498C for the seasonal cycle. Deepening and shallowing of the MLD at the all OWS locations in the northeast Pacific are captured by the model with an rms difference of ,20 m and an R value of .0.85 for the seasonal cycle. Using several statistical measures and climatologies of SST and MLD we have demonstrated that NLOM with an embedded mixed layer is able to simulate with substantial skill the climatological SST and MLD when using accurate and computationally efficient surface heat flux and solar radiation attenuation parameterizations over the global ocean. Further, this was accomplished using a model with only seven layers in the vertical, including the embedded mixed layer. Success of climatological predictions from the NLOM with an embedded mixed layer is a prerequisite for simulations using interannual atmospheric forcing with high temporal resolution. NLOM gives accurate upper-ocean quantities with atmospheric forcing even with no SST relaxation or assimilation, a strong indication that the model is a good candidate for assimilation of SST data. Finally, the techniques and datasets used here can be applied to evaluation of other ocean models in predicting the SST and MLD.

The performance of atmospheric component model R42L9 of GOALS/LASG

This paper examines the performance of an atmospheric general circulation model (AGCM) developed at the State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics (LASG/IAP). It is a spectral model truncated at R42(2.8125°long×1.66°lat) resolution and with nine vertical levels, and referred to as R42L9/LASG hereafter. It is also the new version of atmospheric component model R15L9 of the global ocean-atmosphere-land system (GOALS/LASG). A 40-year simulation in which the model is forced with the climatological monthly mean sea surface temperature is compared with the 40-year (1958–97) U.S. National Center for Environmental Prediction (NCEP) global reanalysis and the 22-year (1979–2000) Xie-Arkin monthly precipitation climatology. The mean DJF and JJA geographical distributions of precipitation, sea level pressure, 500-hPa geopotential height, 850-hPa and 200-hPa zonal wind, and other fields averaged for the last 30-year integration of the R42L9 model are analyzed. Results show that the model reproduces well the observed basic patterns, particularly precipitation over the East Asian region. Comparing the new model with R15L9/LASG, the old version with coarse resolution (nearly 7.5°long×4.5°lat), shows an obvious improvement in the simulation of regional climate, especially precipitation. The weaknesses in simulation and future improvements of the model are also discussed.

Spawning patterns of four species of predominantly temperate pelagic fishes in the sub-tropical waters of southern Queensland

The diverse pelagic fish assemblage of sub-tropical southern Queensland includes fishes with predominantly temperate distributions, such as tailor Pomatomus saltatrix, sardine Sardinops sagax, round herring Etrumeus teres, and Australian anchovy Engraulis australis. The peak spawning seasons of P. saltatrix, S. sagax and E. teres occur during late winter and early spring (June–October). Eggs and larvae of these three species are widely distributed in shelf waters and comprise >50% of the ichthyoplankton assemblage during this period. Mean monthly sea surface temperatures (SSTs) during late winter and early spring range from 21 to 23 °C, and are thus similar to those recorded in southern Australia during summer and autumn, which is the spawning season of these three species in those temperate waters. E. australis eggs occur mainly in inshore waters, and comprise >50% of fish eggs collected during summer and autumn when mean monthly SSTs in southern Queensland exceed 27 °C. E. australis also spawns mainly during summer and autumn in temperate Australia. Hence, water temperature may be less important as a determinant of the spawning season of E. australis than it is for the other three species. The suitability of southern Queensland for spawning by predominantly temperate species during late winter and early spring may contribute to the high diversity of the region's pelagic fish assemblage. Adult P. saltatrix, S. sagax and E. teres appear to migrate northwards into southern Queensland during early winter to spawn, and larvae may be transported southwards into temperate waters by the East Australian Current. This dispersal-migration pattern is similar to those observed for several species, including P. saltatrix, in the western boundary current systems off the east coasts of North America and Africa. Hence, pelagic fishes in ecosystems off the east coast of three continents migrate into sub-tropical waters to spawn, and larvae are transported back into temperate nursery areas by the prevailing current.