North Atlantic coast wave statistics hindcast by the wave spectrum method /

Mode of access: Internet.

Benefits of using a spectral hindcast database for wave power extraction assessment

When considering deployment of wave energy converters at a given site, it is of prime importance from both a technical and an economical point of view to accurately assess the total yearly energy that can be extracted by the given device. Especially, to be considered is the assessment of the efficiency of the device over the widest span of the sea-states spectral bandwidth. Hence, the aim of this study is to assess the biases and errors introduced on extracted power classically computed using spectral data derived from analytical functions such as a JONSWAP spectrum, compared to the power derived using actual wave spectra obtained from a spectral hindcast database.

Estimating present day extreme water level exceedance probabilities around the coastline of Australia : tides, extra-tropical storm surges and mean sea level

The occurrence of extreme water levels along low-lying, highly populated and/or developed coastlines can lead to considerable loss of life and billions of dollars of damage to coastal infrastructure. Therefore it is vitally important that the exceedance probabilities of extreme water levels are accurately evaluated to inform risk-based flood management, engineering and future land-use planning. This ensures the risk of catastrophic structural failures due to under-design or expensive wastes due to over-design are minimised. This paper estimates for the first time present day extreme water level exceedence probabilities around the whole coastline of Australia. A high-resolution depth averaged hydrodynamic model has been configured for the Australian continental shelf region and has been forced with tidal levels from a global tidal model and meteorological fields from a global reanalysis to generate a 61-year hindcast of water levels. Output from this model has been successfully validated against measurements from 30 tide gauge sites. At each numeric coastal grid point, extreme value distributions have been fitted to the derived time series of annual maxima and the several largest water levels each year to estimate exceedence probabilities. This provides a reliable estimate of water level probabilities around southern Australia; a region mainly impacted by extra-tropical cyclones. However, as the meteorological forcing used only weakly includes the effects of tropical cyclones, extreme water level probabilities are underestimated around the western, northern and north-eastern Australian coastline. In a companion paper we build on the work presented here and more accurately include tropical cyclone-induced surges in the estimation of extreme water level. The multi-decadal hindcast generated here has been used primarily to estimate extreme water level exceedance probabilities but could be used more widely in the future for a variety of other research and practical applications.

Estimating present day extreme water level exceedance probabilities around the coastline of Australia : tropical cyclone-induced storm surges

The incidence of major storm surges in the last decade have dramatically emphasized the immense destructive capabilities of extreme water level events, particularly when driven by severe tropical cyclones. Given this risk, it is vitally important that the exceedance probabilities of extreme water levels are accurately evaluated to inform risk-based flood and erosion management, engineering and for future land-use planning and to ensure the risk of catastrophic structural failures due to under-design or expensive wastes due to over-design are minimised. Australia has a long history of coastal flooding from tropical cyclones. Using a novel integration of two modeling techniques, this paper provides the first estimates of present day extreme water level exceedance probabilities around the whole coastline of Australia, and the first estimates that combine the influence of astronomical tides, storm surges generated by both extra-tropical and tropical cyclones, and seasonal and inter-annual variations in mean sea level. Initially, an analysis of tide gauge records has been used to assess the characteristics of tropical cyclone-induced surges around Australia. However, given the dearth (temporal and spatial) of information around much of the coastline, and therefore the inability of these gauge records to adequately describe the regional climatology, an observationally based stochastic tropical cyclone model has been developed to synthetically extend the tropical cyclone record to 10,000 years. Wind and pressure fields derived for these synthetically generated events have then been used to drive a hydrodynamic model of the Australian continental shelf region with annual maximum water levels extracted to estimate exceedance probabilities around the coastline. To validate this methodology, selected historic storm surge events have been simulated and resultant storm surges compared with gauge records. Tropical cyclone induced exceedance probabilities have been combined with estimates derived from a 61-year water level hindcast described in a companion paper to give a single estimate of present day extreme water level probabilities around the whole coastline of Australia. Results of this work are freely available to coastal engineers, managers and researchers via a web-based tool (www.sealevelrise.info). The described methodology could be applied to other regions of the world, like the US east coast, that are subject to both extra-tropical and tropical cyclones.

Estimating present day extreme total water level exceedance probabilities around the Australian coastline

The occurrence of extreme water level events along low-lying, highly populated and/or developed coastlines can lead to devastating impacts on coastal infrastructure. Therefore it is very important that the probabilities of extreme water levels are accurately evaluated to inform flood and coastal management and for future planning. The aim of this study was to provide estimates of present day extreme total water level exceedance probabilities around the whole coastline of Australia, arising from combinations of mean sea level, astronomical tide and storm surges generated by both extra-tropical and tropical storms, but exclusive of surface gravity waves. The study has been undertaken in two main stages. In the first stage, a high-resolution (~10 km along the coast) hydrodynamic depth averaged model has been configured for the whole coastline of Australia using the Danish Hydraulics Institute’s Mike21 modelling suite of tools. The model has been forced with astronomical tidal levels, derived from the TPX07.2 global tidal model, and meteorological fields, from the US National Center for Environmental Prediction’s global reanalysis, to generate a 61-year (1949 to 2009) hindcast of water levels. This model output has been validated against measurements from 30 tide gauge sites around Australia with long records. At each of the model grid points located around the coast, time series of annual maxima and the several highest water levels for each year were derived from the multi-decadal water level hindcast and have been fitted to extreme value distributions to estimate exceedance probabilities. Stage 1 provided a reliable estimate of the present day total water level exceedance probabilities around southern Australia, which is mainly impacted by extra-tropical storms. However, as the meteorological fields used to force the hydrodynamic model only weakly include the effects of tropical cyclones the resultant water levels exceedance probabilities were underestimated around western, northern and north-eastern Australia at higher return periods. Even if the resolution of the meteorological forcing was adequate to represent tropical cyclone-induced surges, multi-decadal periods yielded insufficient instances of tropical cyclones to enable the use of traditional extreme value extrapolation techniques. Therefore, in the second stage of the study, a statistical model of tropical cyclone tracks and central pressures was developed using histroic observations. This model was then used to generate synthetic events that represented 10,000 years of cyclone activity for the Australia region, with characteristics based on the observed tropical cyclones over the last ~40 years. Wind and pressure fields, derived from these synthetic events using analytical profile models, were used to drive the hydrodynamic model to predict the associated storm surge response. A random time period was chosen, during the tropical cyclone season, and astronomical tidal forcing for this period was included to account for non-linear interactions between the tidal and surge components. For each model grid point around the coast, annual maximum total levels for these synthetic events were calculated and these were used to estimate exceedance probabilities. The exceedance probabilities from stages 1 and 2 were then combined to provide a single estimate of present day extreme water level probabilities around the whole coastline of Australia.

Extreme water level exceedance probabilities around Australia

The potential impacts of extreme water level events on our coasts are increasing as populations grow and sea levels rise. To better prepare for the future, coastal engineers and managers need accurate estimates of average exceedance probabilities for extreme water levels. In this paper, we estimate present day probabilities of extreme water levels around the entire coastline of Australia. Tides and storm surges generated by extra-tropical storms were included by creating a 61-year (1949-2009) hindcast of water levels using a high resolution depth averaged hydrodynamic model driven with meteorological data from a global reanalysis. Tropical cyclone-induced surges were included through numerical modelling of a database of synthetic tropical cyclones equivalent to 10,000 years of cyclone activity around Australia. Predicted water level data was analysed using extreme value theory to construct return period curves for both the water level hindcast and synthetic tropical cyclone modelling. These return period curves were then combined by taking the highest water level at each return period.

Indian Ocean Dipole: Processes and impacts

Equatorial Indian Ocean is warmer in the east, has a deeper thermocline and mixed layer, and supports a more convective atmosphere than in the west. During certain years, the eastern Indian Ocean becomes unusually cold, anomalous winds blow from east to west along the equator and southeastward off the coast of Sumatra, thermocline and mixed layer lift up and the atmospheric convection gets suppressed. At the same time, western Indian Ocean becomes warmer and enhances atmospheric convection. This coupled ocean-atmospheric phenomenon in which convection, winds, sea surface temperature (SST) and thermocline take part actively is known as the Indian Ocean Dipole (IOD). Propagation of baroclinic Kelvin and Rossby waves excited by anomalous winds, play an important role in the development of SST anomalies associated with the IOD. Since mean thermocline in the Indian Ocean is deep compared to the Pacific, it was believed for a long time that the Indian Ocean is passive and merely responds to the atmospheric forcing. Discovery of the IOD and studies that followed demonstrate that the Indian Ocean can sustain its own intrinsic coupled ocean-atmosphere processes. About 50% percent of the IOD events in the past 100 years have co-occurred with El Nino Southern Oscillation (ENSO) and the other half independently. Coupled models have been able to reproduce IOD events and process experiments by such models – switching ENSO on and off – support the hypothesis based on observations that IOD events develop either in the presence or absence of ENSO. There is a general consensus among different coupled models as well as analysis of data that IOD events co-occurring during the ENSO are forced by a zonal shift in the descending branch of Walker cell over to the eastern Indian Ocean. Processes that initiate the IOD in the absence of ENSO are not clear, although several studies suggest that anomalies of Hadley circulation are the most probable forcing function. Impact of the IOD is felt in the vicinity of Indian Ocean as well as in remote regions. During IOD events, biological productivity of the eastern Indian Ocean increases and this in turn leads to death of corals over a large area.Moreover, the IOD affects rainfall over the maritime continent, Indian subcontinent, Australia and eastern Africa. The maritime continent and Australia suffer from deficit rainfall whereas India and east Africa receive excess. Despite the successful hindcast of the 2006 IOD by a coupled model, forecasting IOD events and their implications to rainfall variability remains a major challenge as understanding reasons behind an increase in frequency of IOD events in recent decades.

A novel neural network design for long range prediction of rainfall pattern

The importance of long-range prediction of rainfall pattern for devising and planning agricultural strategies cannot be overemphasized. However, the prediction of rainfall pattern remains a difficult problem and the desired level of accuracy has not been reached. The conventional methods for prediction of rainfall use either dynamical or statistical modelling. In this article we report the results of a new modelling technique using artificial neural networks. Artificial neural networks are especially useful where the dynamical processes and their interrelations for a given phenomenon are not known with sufficient accuracy. Since conventional neural networks were found to be unsuitable for simulating and predicting rainfall patterns, a generalized structure of a neural network was then explored and found to provide consistent prediction (hindcast) of all-India annual mean rainfall with good accuracy. Performance and consistency of this network are evaluated and compared with those of other (conventional) neural networks. It is shown that the generalized network can make consistently good prediction of annual mean rainfall. Immediate application and potential of such a prediction system are discussed.

Recovery and status of shortnose sturgeon in the Hudson River

Shortnose sturgeon (Acipenser brevirostrum), an endangered species, has experienced a several-fold increase in abundance in the Hudson River in recent decades. This population growth followed a substantial improvement in water quality during the 1970s to a large portion (c. 40%) of the species' summertime nursery area. Age structure and growth were investigated to evaluate the hypothesis that improvements in water quality stimulated population recovery through increased survival of young of the year juveniles. Specimens were captured using gill nets bi-monthly from November 2003 to November 2004 (n = 596). Annuli in fin spine sections were used to generate estimates of sturgeon age. Based upon a marginal increment analysis, annuli were determined to form at an annual rate. Age determinations yielded a catch composed of age 5-30 years for sizes 49-105cm Total Length (n = 554). Individual growth rate (von Bertalanffy coefficients: TL, = 1045mm, K = 0.07) for the population was similar to previous growth estimates within the Hudson River as well as proximal estuaries. Hindcast year-class strengths, based upon a recent stock assessment (Bain et al. 2000) and corrected for gill net mesh selectivity and cumulative mortality indicated high recruitments (28,000-43,000 yearlings)during 1986-1992, which were preceded and succeeded by c.5-year periods of lower recruitment (5,000-1 5,000 yearlings). Recruitment patterns were corroborated by trends in shortnose sturgeon bycatch from a Hudson utilities-sponsored monitoring program. Results indicated that Hudson River shortnose sturgeon abundance increased due to the formation of several strong year-classes occurring about five years subsequent to improved water quality in important nursery and forage habitats in the upper Hudson River estuary. (PDF contains 108 pages.)

Interannual horizontal heat advection in the surface mixed layer over the equatorial Pacific Ocean: assimilation versus TAO analysis

The interannual anomalies of horizontal heat advection in the surface mixed layer over the equatorial Pacific Ocean in an assimilation experiment are studied and compared with existing observational analyses. The assimilation builds upon a hindcast study that has produced a good simulation of the observed equatorial currents and optimizes the simulation of the Reynolds sea surface temperature (SST) data. The comparison suggests that the assimilation has improved the simulation of the interannual horizontal heat advection of the surface mixed layer significantly. During periods of interrupted current measurements, the assimilation is shown to produce more meaningful anomalies of the heat advection than the interpolation of the observational data does. The assimilation also shows that the eddy heat flux due to the correlation between high-frequency current and SST variations, which is largely overlooked by the existing observational analyses, is important for the interannual SST balance over the equatorial Pacific. The interannual horizontal heat advection anomalies are found to be sensitive to SST errors where oceanic currents are strong, which is a challenge for ENSO prediction. The study further suggests that the observational analyses of the tropical SST balance based on the TAO and the Reynolds SST data contain significant errors due to the large gradient errors in the Reynolds SST data, which are amplified into the advection anomalies by the large equatorial currents.

Analysis of the sea-level variability along the Chinese coast and estimation of the impact of a CO2-perturbed atmospheric circulation

The relationship between monthly sea-level data measured at stations located along the Chinese coast and concurrent large-scale atmospheric forcing in the period 1960-1990 is examined. It is found that sea-level varies quite coherently along the whole coast, despite the geographical extension of the station set. A canonical correlation analysis between sea-level and sea-level pressure (SLP) indicates that a great part of the sea-level variability can be explained by the action of the wind stress on the ocean surface. The relationship between sea-level and sea-level pressure is analyzed separately for the summer and winter half-years. In winter, one factor affecting sea-level variability at all stations is the SLP contrast between the continent and the Pacific Ocean, hence the intensity of the winter Monsoon circulation. Another factor that affects coherently all stations is the intensity of the zonal circulation at mid-latitudes. In the summer half year, on the other hand, the influence of SLP on sea-level is spatially less coherent: the stations in the Yellow Sea are affected by a more localized circulation anomaly pattern, whereas the rest of the stations is more directly connected to the intensity of the zonal circulation. Based on this analysis, statistical models (different for summer and winter) to hindcast coastal sealevel anomalies from the large-scale SLP field are formulated. These models have been tested by fitting their internal parameters in a test period and reproducing reasonably the sea-level evolution in an independent period. These statistical models are also used to estimate the contribution of the changes of the atmospheric circulation on sea-level along the Chinese coast in an altered climate. For this purpose the ouput of 150 year-long experiment with the coupled ocean-atmosphere model ECHAM1-LSG has been analyzed, in which the atmospheric concentration of greenhouse gases was continuously increased from 1940 until 2090, according to the Scenario A projection of the Intergovermental Panel on Climate Change. In this experiment the meridional (zonal) circulation relevant for sea-level tends to become weaker (stronger) in the winter half year and stronger (weaker) in summer. The estimated contribution of this atmospheric circulation changes to coastal sea-level is of the order of a few centimeters at the end of the integration, being in winter negative in the Yellow Sea and positive in the China Sea with opposite signs in the summer half-year.

How should sparse marine in situ measurements be compared to a continuous model: an example

This work demonstrates an example of the importance of an adequate method to sub-sample model results when comparing with in situ measurements. A test of model skill was performed by employing a point-to-point method to compare a multi-decadal hindcast against a sparse, unevenly distributed historic in situ dataset. The point-to-point method masked out all hindcast cells that did not have a corresponding in situ measurement in order to match each in situ measurement against its most similar cell from the model. The application of the point-to-point method showed that the model was successful at reproducing the inter-annual variability of the in situ datasets. Furthermore, this success was not immediately apparent when the measurements were aggregated to regional averages. Time series, data density and target diagrams were employed to illustrate the impact of switching from the regional average method to the point-to-point method. The comparison based on regional averages gave significantly different and sometimes contradicting results that could lead to erroneous conclusions on the model performance. Furthermore, the point-to-point technique is a more correct method to exploit sparse uneven in situ data while compensating for the variability of its sampling. We therefore recommend that researchers take into account for the limitations of the in situ datasets and process the model to resemble the data as much as possible.

Towards an integrated forecasting system for pelagic fisheries

First results of a coupled modeling and forecasting system for the pelagic fisheries are being presented. The system consists currently of three mathematically fundamentally different model subsystems: POLCOMS-ERSEM providing the physical-biogeochemical environment implemented in the domain of the North-West European shelf and the SPAM model which describes sandeel stocks in the North Sea. The third component, the SLAM model, connects POLCOMS-ERSEM and SPAM by computing the physical-biological interaction. Our major experience by the coupling model subsystems is that well-defined and generic model interfaces are very important for a successful and extendable coupled model framework. The integrated approach, simulating ecosystem dynamics from physics to fish, allows for analysis of the pathways in the ecosystem to investigate the propagation of changes in the ocean climate and lower trophic levels to quantify the impacts on the higher trophic level, in this case the sandeel population, demonstrated here on the base of hindcast data. The coupled forecasting system is tested for some typical scientific questions appearing in spatial fish stock management and marine spatial planning, including determination of local and basin scale maximum sustainable yield, stock connectivity and source/sink structure. Our presented simulations indicate that sandeels stocks are currently exploited close to the maximum sustainable yield, but large uncertainty is associated with determining stock maximum sustainable yield due to stock eigen dynamics and climatic variability. Our statistical ensemble simulations indicates that the predictive horizon set by climate interannual variability is 2–6 yr, after which only an asymptotic probability distribution of stock properties, like biomass, are predictable.

Decadal variability in biogeochemical models: Comparison with a 50-year ocean colour dataset

Assessing the skill of biogeochemical models to hindcast past variability is challenging, yet vital in order to assess their ability to predict biogeochemical change. However, the validation of decadal variability is limited by the sparsity of consistent, long-term biological datasets. The Phytoplankton Colour Index (PCI) product from the Continuous Plankton Recorder survey, which has been sampling the North Atlantic since 1948, is an example of such a dataset. Converting the PCI to chlorophyll values using SeaWiFS data allows a direct comparison with model output. Here we validate decadal variability in chlorophyll from the GFDL TOPAZ model. The model demonstrates skill at reproducing interannual variability, but cannot simulate the regime shifts evident in the PCI data. Comparison of the model output, data and climate indices highlights under-represented processes that it may be necessary to include in future biogeochemical models in order to accurately simulate decadal variability in ocean ecosystems.

Modelling the Influence of Major Baltic Inflows on Near-Bottom Conditions at the Entrance of the Gulf of Finland

A coupled hydrodynamic-biogeochemical model was implemented in order to estimate the effects of Major Baltic Inflows on the near-bottom hydrophysical and biogeochemical conditions in the northern Baltic Proper and the western Gulf of Finland during the period 1991�2009. We compared results of a realistic reference run to the results of an experimental run where Major Baltic Inflows were suppressed. Further to the expected overall decrease in bottom salinity, this modelling experiment confirms that in the absence of strong saltwater inflows the deep areas of the Baltic Proper would become more anoxic, while in the shallower areas (western Gulf of Finland) near-bottom average conditions improve. Our experiment revealed that typical estuarine circulation results in the sporadic emergence of short-lasting events of near-bottom anoxia in the western Gulf of Finland due to transport of water masses from the Baltic Proper. Extrapolating our results beyond the modelled period, we speculate that the further deepening of the halocline in the Baltic Proper is likely to prevent inflows of anoxic water to the Gulf of Finland and in the longer term would lead to improvement in near-bottom conditions in the Baltic Proper. Our results reaffirm the importance of accurate representation of salinity dynamics in coupled Baltic Sea models serving as a basis for credible hindcast and future projection simulations of biogeochemical conditions.