Canadian Hydrographic Service

The International Bathymetric Chart of the Arctic Ocean (IBCAO) released its first gridded bathymetric compilation in 1999. The IBCAO bathymetric portrayals have since supported a wide range of Arctic science activities, for example, by providing constraint for ocean circulation models and the means to define and formulate hypotheses about the geologic origin of Arctic undersea features. IBCAO Version 3.0 represents the largest improvement since 1999 taking advantage of new data sets collected by the circum‐Arctic nations, opportunistic data collected from fishing vessels, data acquired from US Navy submarines and from research ships of various nations. Built using an improved gridding algorithm, this new grid is on a 500 meter spacing, revealing much greater details of the Arctic seafloor than IBCAO Version 1.0 (2.5 km) and Version 2.0 (2.0 km). The area covered by multibeam surveys has increased from ∼6% in Version 2.0 to ∼11% in Version 3.0.

Winter conditions are rapidly changing in temperate ecosystems, particularly for those that experience periods of snow and ice cover. Relatively little is known of winter ecology in these systems, due to a historical research focus on summer 'growing seasons'. We executed the first global quantitative synthesis on under-ice lake ecology, including 36 abiotic and biotic variables from 42 research groups and 101 lakes, examining seasonal differences and connections as well as how seasonal differences vary with geophysical factors. Plankton were more abundant under ice than expected; mean winter values were 43.2% of summer values for chlorophyll a, 15.8% of summer phytoplankton biovolume and 25.3% of summer zooplankton density. Dissolved nitrogen concentrations were typically higher during winter, and these differences were exaggerated in smaller lakes. Lake size also influenced winter-summer patterns for dissolved organic carbon (DOC), with higher winter DOC in smaller lakes. At coarse levels of taxonomic aggregation, phytoplankton and zooplankton community composition showed few systematic differences between seasons, although literature suggests that seasonal differences are frequently lake-specific, species-specific, or occur at the level of functional group. Within the subset of lakes that had longer time series, winter influenced the subsequent summer for some nutrient variables and zooplankton biomass.

Bathymetry (seafloor depth), is a critical parameter providing the geospatial context for a multitude of marine scientific studies. Since 1997, the International Bathymetric Chart of the Arctic Ocean (IBCAO) has been the authoritative source of bathymetry for the Arctic Ocean. IBCAO has merged its efforts with the Nippon Foundation-GEBCO-Seabed 2030 Project, with the goal of mapping all of the oceans by 2030. Here we present the latest version (IBCAO Ver. 4.0), with more than twice the resolution (200 × 200 m versus 500 × 500 m) and with individual depth soundings constraining three times more area of the Arctic Ocean (∼19.8% versus 6.7%), than the previous IBCAO Ver. 3.0 released in 2012. Modern multibeam bathymetry comprises ∼14.3% in Ver. 4.0 compared to ∼5.4% in Ver. 3.0. Thus, the new IBCAO Ver. 4.0 has substantially more seafloor morphological information that offers new insights into a range of submarine features and processes; for example, the improved portrayal of Greenland fjords better serves predictive modelling of the fate of the Greenland Ice Sheet.

Abstract. Environment Canada has been developing a community environmental modelling system (Modélisation Environmentale Communautaire – MEC), which is designed to facilitate coupling between models focusing on different components of the earth system. The ultimate objective of MEC is to use the coupled models to produce operational forecasts. MESH (MEC – Surface and Hydrology), a configuration of MEC currently under development, is specialized for coupled land-surface and hydrological models. To determine the specific requirements for MESH, its different components were implemented on the Laurentian Great Lakes watershed, situated on the Canada-US border. This experiment showed that MESH can help us better understand the behaviour of different land-surface models, test different schemes for producing ensemble streamflow forecasts, and provide a means of sharing the data, the models and the results with collaborators and end-users. This modelling framework is at the heart of a testbed proposal for the Hydrologic Ensemble Prediction Experiment (HEPEX) which should allow us to make use of the North American Ensemble Forecasting System (NAEFS) to improve streamflow forecasts of the Great Lakes tributaries, and demonstrate how MESH can contribute to a Community Hydrologic Prediction System (CHPS).

Abstract To use the Monte Carlo Independent Column Approximation method for computing domain‐average radiative fluxes in large‐scale atmospheric models (LSAMs), a method is needed for generating cloudy subcolumns within LSAM columns. Here, a stochastic cloud generator is introduced to produce the subcolumns. The generator creates a cloud field on a column‐by‐column basis using information about layer cloud fraction, vertical overlap of cloud fraction and cloud condensate for adjacent layers, and density functions describing horizontal variations in cloud water content. The performance of the generator is assessed using a single day's worth of data from an LSAM simulation that employed a low‐resolution two‐dimensional cloud‐resolving model (CRM) within each LSAM column (a total of ∼59 000 cloudy domains). Statistical characteristics of generated cloud fields are compared against original CRM data, and radiative‐transfer biases associated with the generator are evaluated. When the generator is initialized to the greatest extent possible with information obtained from the CRM fields, overall biases are small. For example, global‐mean total cloud fraction exhibits a bias of −0.004, as compared with −0.024 for maximum‐random overlap (MRO) and 0.047 for random overlap. Biases in radiative fluxes and heating rates are in general ¼ to ½ those for MRO with horizontally homogeneous clouds. Copyright © 2004 Royal Meteorological Society

Abstract New computer software that permits more versatility in the harmonic analysis of tidal time series is described and tested. Specific improvements to traditional methods include the analysis of randomly sampled and/or multiyear data; more accurate nodal correction, inference, and astronomical argument adjustments through direct incorporation in the least squares matrix; multiconstituent inferences from a single reference constituent; correlation matrices and error estimates that facilitate decisions on the selection of constituents for the analysis; and a single program that analyzes one- or two-dimensional time series. This new methodology is evaluated through comparisons with results from old techniques and then applied to two problems that could not have been accurately solved with older software. They are (i) the analysis of ocean station temperature time series spanning 25 yr, and (ii) the analysis of satellite altimetry from a ground track whose proximity to land has led to significant data dropout. This new software is free as part of the Institute of Ocean Sciences (IOS) Tidal Package and can be downloaded, along with sample input data and an explanatory readme file.

This paper presents a photogrammetric model for digital underwater video imagery, which has been mostly applied to qualitative analysis in the marine environment. With this model, quantitative analysis of underwater images is possible, e.g., to locate positions, calculate sizes, and measure shapes of objects from image features. The underwater photogrammetric model is based on a three-dimensional optical ray tracing technique which rigorously models imaging systems with multilens configurations and multiple refractions. The calibration procedure with two independent phases has been proven to be efficient in simplifying the computation and improving the calibration accuracy. With the current imaging system configuration and photogrammetric model, an accuracy of 0.8 cm in lateral directions and 1.2 cm along the depth direction for objects located about 2-3 m from the camera system in the object space is attainable. A PC-based digital underwater photogrammetric prototype system has been developed to implement the underwater photogrammetric model.

Differentiating between first-year ice (FYI) and multi-year ice (MYI) in C-band synthetic aperture radar (SAR) imagery during spring–summer melt, when wet snow and melt ponds mask the underlying ice, is difficult. It has been suggested that the use of L-band SAR may alleviate this concern given increased penetration depths at longer wavelengths; however, this has not been thoroughly assessed. Here the separability of FYI and MYI is compared using horizontally polarized (HH) C-band (RADARSAT-2) and L-band (ALOS/PALSAR) ScanSAR images acquired over landfast sea ice in the Canadian Arctic Archipelago in the spring and summer of 2009. L-band provided enhanced contrast between FYI and MYI during early melt onset and during the drainage phase of advanced melt, while C-band was found to provide enhanced contrast when the wet snowpack was transitioning from the pendular regime to the funicular regime. At the time of the pendular–funicular transition, the backscatter signatures of FYI and MYI reversed at both C- and L-band. This behavior is well established at C-band, but has not been reported previously at L-band. The L-band imagery also provided improved definition of floe boundaries and ridges throughout the melt season. Finally, the L-band data had reduced speckle (equivalent number of looks ~ 12), relative to the C-band data (~ 9 equivalent looks). These results indicate that L-band SAR data acquired during the melt season could be used to enhance operational and scientific sea ice information products that have traditionally been derived from single-frequency C-band SAR data.

Abstract Using an optimal detection technique and climate change simulations produced with two versions of two GCMs, we have assessed the causes of twentieth-century temperature changes from global to regional scales. Our analysis is conducted in nine spatial domains: 1) the globe; 2) the Northern Hemisphere; four large regions in the Northern Hemispheric midlatitudes covering 30°–70°N including 3) Eurasia, 4) North America, 5) Northern Hemispheric land only, 6) the entire 30°–70°N belt; and three smaller regions over 7) southern Canada, 8) southern Europe, and 9) China. We find that the effect of anthropogenic forcing on climate is clearly detectable at global through regional scales. The effect of combined greenhouse gases and sulfate aerosol forcing is detectable in all nine domains in annual and seasonal mean temperatures observed during the second half of the twentieth century. The effect of greenhouse gases can also be separated from that of sulfate aerosols over this period at continental and regional scales. Uncertainty in these results is larger in the smaller spatial domains. Detection is improved when an ensemble of models is used to estimate the response to anthropogenic forcing and the underlying internal variability of the climate system. Our detection results hold after removal of North Atlantic Oscillation (NAO)-related variability in temperature observations—variability that may or may not be associated with anthropogenic forcing. They also continue to hold when our estimates of natural internal climate variability are doubled.

Approximately 1000 Canadian Hydrographic Service (CHS) charts cover Canada’s oceans and navigable waters. Many charts use information collected with techniques that predate the more advanced technologies available to Hydrographic Offices (HOs) today. Furthermore, gaps in survey data, particularly in the Canadian Arctic where only 6% of waters are surveyed to modern standards, are also problematic. Through a Canadian Space Agency (CSA) Government Related Initiatives Program (GRIP) project, CHS is exploring remote sensing techniques to assist with the improvement of Canadian navigational charts. Projects exploring optical/Synthetic Aperture Radar (SAR) shoreline extraction and change detection, as well as optical Satellite-Derived Bathymetry (SDB), are currently underway. This paper focuses on SDB extracted from high-resolution optical imagery, highlighting current results as well as the challenges and opportunities CHS will encounter when implementing SDB within its operational chart production process. SDB is of particular interest to CHS due to its ability to supplement depths derived from traditional hydrographic surveys. This is of great importance in shallow and/or remote Canadian waters where achieving wide-area depth coverage through traditional surveys is costly, time-consuming and a safety risk to survey operators. With an accuracy of around 1 m, SDB could be used by CHS to fill gaps in survey data and to provide valuable information in dynamic areas.

A method for classifying synoptic-scale maps into discrete groups is introduced. Tree-based recursive partitioning models are used to develop mappings between synoptic-scale circulation fields and the leading linear and nonlinear principal components (PCs) of weather elements observed at a surface station. Statistically unique but climatically insignificant patterns are avoided by identifying map patterns based on their association with indices related to local weather conditions. The method requires few user-adjustable parameters and includes an algorithm that provides objective guidance for determining the appropriate number of map patterns to retain. The classification method is demonstrated using daily sea level pressure and 500-hPa geopotential height maps from a domain covering British Columbia and the northeastern Pacific Ocean. The linear and nonlinear weather element PCs are derived from daily measurements of surface temperature, dewpoint temperature, cloud opacity, and u and υ wind components taken at Vancouver, British Columbia. Classification performance is tested by applying the method to precipitation and air quality scenarios. Results are compared with those from unsupervised map-pattern classifications based on the k-means clustering algorithm. Results from recursive partitioning models using linear weather element PCs as targets were better than those from the k-means algorithm. Recursive partitioning trees using nonlinear PCs as targets performed slightly worse than those using linear PCs as targets. Interestingly, trees using gridpoint circulation data as inputs outperformed models that used truncated PCs of the circulation data as inputs. Poorer results were found not to result from loss of information due to truncation of the PCs. Instead, the way information is encoded in principal component analysis (PCA) may be responsible for the poor classification performance in the recursive partitioning models using circulation PCs as inputs.

The paper describes the system developed and used by the United States Hydrographic Office for selecting the optimum track for transoceanic crossings by applying long-range predictions of wind, waves and currents to a knowledge of how the routed vessel reacts to these variables. Over a period of two years, over 1000 optimum ship routes were provided to one authority, with an average reduction in travel time of 14 hours.

Abstract Similar nonsteady‐state automated chamber systems were used to measure and partition soil CO 2 efflux in contrasting deciduous (trembling aspen) and coniferous (black spruce and jack pine) stands located within 100 km of each other near the southern edge of the Boreal forest in Canada. The stands were exposed to similar climate forcing in 2003, including marked seasonal variations in soil water availability, which provided a unique opportunity to investigate the influence of climate and stand characteristics on soil CO 2 efflux and to quantify its contribution to the net ecosystem CO 2 exchange (NEE) as measured with the eddy‐covariance technique. Partitioning of soil CO 2 efflux between soil respiration (including forest‐floor vegetation) and forest‐floor photosynthesis showed that short‐ and long‐term temporal variations of soil CO 2 efflux were related to the influence of (1) soil temperature and water content on soil respiration and (2) below‐canopy light availability, plant water status and forest‐floor plant species composition on forest‐floor photosynthesis. Overall, the three stands were weak to moderate sinks for CO 2 in 2003 (NEE of −103, −80 and −28 g C m −2 yr −1 for aspen, black spruce and jack pine, respectively). Forest‐floor respiration accounted for 86%, 73% and 75% of annual ecosystem respiration, in the three respective stands, while forest‐floor photosynthesis contributed to 11% and 14% of annual gross ecosystem photosynthesis in the black spruce and jack pine stands, respectively. The results emphasize the need to perform concomitant measurements of NEE and soil CO 2 efflux at longer time scales in different ecosystems in order to better understand the impacts of future interannual climate variability and vegetation dynamics associated with climate change on each component of the carbon balance.

Observations, numerical modeling, and theoretical calculations show how the 18.6-year modulation of the main lunar semidiurnal tide in the Bay of Fundy and Gulf of Maine is reduced from its astronomical value of 3.7 percent to 2.4 percent by the effects of friction and resonance. The agreement of the three approaches increases confidence in model predictions of widespread changes in the tidal regime resulting from development of tidal power.

Abstract A form of sensitivity analysis is described that illustrates the effects that inputs have on outputs of statistical models. The strength and sign of relationships, the types of nonlinearity, and the presence of interactions between inputs can be diagnosed using this technique. Intended for interpreting flexible nonlinear models, the graphical sensitivity analysis is applied to artificial neural networks (ANNs) in this study. As ANNs are increasingly being used for climate prediction, the discussion focuses on specific problems associated with their use in this context. The technique is illustrated using a real‐world, long‐range climate prediction example. Principal components (PCs) of circulation fields prior to the Indian summer monsoon are related to rainfall during monsoon months for the 1958–98 period. The skill of multiple linear regression and ensemble ANNs are compared using a resampling procedure. Interpretation of the models is then conducted using traditional diagnostic tools and graphical sensitivity analysis. This provides an improved investigation of precursor circulation field–summer monsoon rainfall relationships identified in a previous modelling study. The relatively stable, linear relationship identified between the May 200 hPa geopotential height field and summer monsoon rainfall is confirmed. Correlations previously identified between 850 hPa geopotential heights during January and rainfall by ANNs are shown to be the result of a weakly nonlinear, interactive relationship involving the first and second PCs of this field. An analysis of out‐of‐sample model predictions suggests that this relationship does not persist over the entire study period. This may result from a modulation of the strength of the circulation–rainfall relationship by El Niño–southern oscillation. Stratification of the results also reveals a relatively strong, nearly linear relationship with monsoon strength during years exhibiting positive scores of the second PC. On extending the analysis to longer lead‐times, the surface pressure and 850 hPa geopotential height fields during November show relatively strong, persistent precursor relationships with summer monsoon rainfall. Sensitivity analyses suggest a mildly nonlinear relationship that is common to both fields. Copyright © 2002 Environment Canada. Published by John Wiley & Sons, Ltd.

Under physically isolated conditions, net community production (NCP) can be accurately estimated from the rate of oxygen evasion to the atmosphere derived from local mixed layer oxygen/argon measurements. We use a simple box model to demonstrate that, when physical inputs are negligible, the sea‐to‐air flux of biological oxygen (bioflux) represents the average NCP exponentially weighted over the past several residence times of oxygen in the mixed layer. This new weighting scheme shows that there is no apparent lag between bioflux and exponentially weighted time‐averaged NCP. Furthermore, a strict steady state assumption is unnecessary to this relationship. However, this widely used O 2 /Ar method is not effective in dynamic coastal zones where low oxygen water upwells to the surface. Yet these zones are highly productive and their episodic productivity needs to be quantified. We use a quasi‐2‐D version of the Regional Ocean Modeling System, including oxygen and argon as prognostic variables, to explore the application of this method and the relationship between NCP and bioflux in a coastal upwelling system. We show that bioflux is an accurate measure of NCP over large regions of time and space. Bioflux is most biased near the shore following upwelling favorable winds, where bioflux is sometimes negative (flux from the atmosphere to the ocean) and even positive bioflux values can severely underestimate NCP. Assessing a range of model variables that are easily observed in the field, we show that sea surface temperature is the most effective at identifying bioflux measurements that are likely to be biased.

We review the results of several studies of significance to the question of future shipping conditions the Canada's Northwest Passage. As shown, these studies raise significant questions around the estimation of the impacts of predicted lighter ice seasons from Global Climate Models and introduce further plausible scenarios that should be considered as well when planning adaptation strategies for marine transportation in the Canadian Arctic.

Abstract Hydro peaking causes an important environmental impact on running water ecosystems. Many affected rivers have a poor ecological status. In rivers affected by hydro peaking, the flow conditions are highly complex and difficult to grasp. To develop a general framework for detecting and characterizing sub‐daily flow fluctuations, we analysed more than 500 Austrian hydrographs, covering the whole range from unimpacted to heavily impacted rivers. Different fluctuation types could be identified according to the potential source: e.g. sub‐daily flow fluctuations caused by hydro peaking, rainfall or snow and glacier melt. Additionally, the term ‘hydro fibrillation’ was established, to indicate frequently occurring artificial fluctuations with comparably low intensities. An automatic procedure was used to detect frequency and intensity of each flow fluctuation. Using variables based on duration curves of flow fluctuation rates (ramping rates), amplitudes, flow ratios, durations and daily numbers of fluctuations, a predictive model (linear discriminant analysis) was fitted to classify hydrographs into predominant fluctuation regimes. This is the basis for a detailed investigation of present sub‐daily flow regimes and to analyse the differences between the regimes. Based on the results, we finally propose a general framework that enables a standardized assessment of flow fluctuations regarding event intensities and/or event timing. The proposed framework offers a standardized selection of particular flow fluctuations referring to increase and decrease events separately. The selection of specific flow fluctuations can be defined with respect to several research questions (e.g. ecologically relevant fluctuations), which offers a wide range of applications. Copyright © 2015 John Wiley & Sons, Ltd.

Abstract The concept of the Northern Marine Transportation Corridors (NMTC) initiative was developed under the Government of Canada World‐Class Tanker Safety System Initiative (WCTSS). The NMTC is an interdepartmental Arctic initiative within the Department of Fisheries and Oceans Canada (DFO), through the Canadian Coast Guard (CCG) and the Canadian Hydrographic Service (CHS), in collaboration with Transport Canada (TC). The NMTC initiative was developed to strengthen the safety of marine navigation in the Arctic, and to offer an efficient planning guide for present and future Arctic investments. Transportation corridors identified through this initiative will provide the Government of Canada the framework needed to better prioritize and deliver on its programs and services, including: nautical charts and products; aids to navigation; icebreaking services; and marine safety regulations. The corridors were generated and analyzed with a Geographic Information System (GIS) using two main data sources: the Automated Identification System (AIS) and CHS's nautical charts and publications. The geographic extent of the NMTC is defined as the Northern Canada Vessel Traffic Service Zone (NORDREG Zone) and the Mackenzie River. With close to 4 million km 2 of water in the Arctic and 162,000 km of coastline, surveying the Arctic to modern standards represents an enormous challenge to CHS. By adopting a corridor‐based approach, CHS and other government programs can prioritize their efforts on 12% of the Canadian Arctic waters. CHS currently has 32% of the NMTC adequately surveyed, with an additional 3% surveyed to modern standards.

Knowledge about seafloor depth, or bathymetry, is crucial for various marine activities, including scientific research, offshore industry, safety of navigation, and ocean exploration. Mapping the central Arctic Ocean is challenging due to the presence of perennial sea ice, which limits data collection to icebreakers, submarines, and drifting ice stations. The International Bathymetric Chart of the Arctic Ocean (IBCAO) was initiated in 1997 with the goal of updating the Arctic Ocean bathymetric portrayal. The project team has since released four versions, each improving resolution and accuracy. Here, we present IBCAO Version 5.0, which offers a resolution four times as high as Version 4.0, with 100 × 100 m grid cells compared to 200 × 200 m. Over 25% of the Arctic Ocean is now mapped with individual depth soundings, based on a criterion that considers water depth. Version 5.0 also represents significant advancements in data compilation and computing techniques. Despite these improvements, challenges such as sea-ice cover and political dynamics still hinder comprehensive mapping.