In this study we introduce a pair of idealized tracers to quantify how changes in physical advection and mixing under climate change affect the nutrient supply, new production, and particulate export rates. The low cost and simplicity of these tracers allows us to explore the sensitivity of the model biogeochemistry, and in particular its response to a changing physical environment, to the choice of model parameters. Using CESM2.1 with active ocean and ice only, at nominal one-degree resolution, under initial conditions and forcing representative of 2000 and 2100, our idealized nutrient and particulate are within the spread of nitrate and export from CMIP5 models. The simple form of the tracers allows us to identify the physical controls on the changing rates of supply, production, and export throughout the year, which together form the different seasonal cycles. We find that the ocean basins with the largest changes in the seasonal cycle over the 21st century are the North Atlantic, the Arctic, and the eastern tropical Pacific. We present results comparing the controls across basins, focusing on shifts in the timing of deepening mixed layers and maximum production rate in the northern North Atlantic through the Arctic, and changes in the spatial and temporal patterns of vertical advective exchange in the tropics and subtropics of the Pacific and Indian Oceans. In both cases we discuss how much these changes depend on the biogeochemical model parameter values.

The advocacy activities necessary to sustain healthy watersheds and improve impaired ones ultimately rely on the democratic process, and therefore depend on a public that values our coastal resources and understands the role that water quality plays in maintaining that value. We contend that an opportunity exists to improve the temporal and spatial density of monitoring by reducing the cost of collecting measurements, while simultaneously fostering an informed and invested public. We envision a distributed water quality monitoring sensor network, composed of low-cost ($1000-$2000) profiling devices we call TideRiders, built and operated by private citizens and local educational organizations and supported by an institution-hosted centralized data and control portal. The TideRider concept engages the public not just in the collection of data but also in the building, deployment, operation, and recovery of these robot sensors. TideRiders will carry a suite of basic water quality instrumentation (temperature, conductivity, and dissolved oxygen), transmit data and accept commands over the cellular network, and can sample surface and bottom waters by surfacing and submerging on a programmable schedule. Operators will harness tidal currents to move their TideRiders deliberately around an embayment, essentially by surfacing in a favorable tide and anchoring on the bottom in an adverse tide. A network of TideRiders deployed in tidally-dominated estuaries like Buzzards Bay and Narragansett Bay could provide basic water quality data at several-hour intervals for weeks at a time by “virtually mooring” in center-bay locations that are otherwise only accessible by boat and therefore typically sampled less frequently than shore stations. We present preliminary field results from a series of prototypes designed and built by students. The prototype devices utilize a novel low-cost semi-passive shallow-water buoyancy engine and were constructed for less than $1000 in parts.

Diurnal tidal currents are the dominate contributors to diapycnal mixing in many regions along the pathways for warm Atlantic Water (AW) circulating within the Arctic Ocean along the continental slope. This mixing diffuses AW heat and salt into the cooler and fresher surroundings, including the upper ocean where ocean heat fluxes play a role in the stability of the ice pack. The strongest diurnal currents are associated with topographically-trapped vorticity waves, which are sensitive to stratification and mean flow. In models, these waves are also sensitive to choices for forcing and geometry. Sensitivity to background conditions implies that tidal currents and mixing will change as the Arctic evolves towards a new climate state. Here, as a first step towards understanding how diurnal tidal currents might change in a future Arctic Ocean, we describe results from a suite of high-resolution (dx=2 km) 2-D and 3-D models for Arctic diurnal tides, focusing on their currents at locations along the AW pathways. We first demonstrate that accurate representation of barotropic diurnal tides requires forcing with both open boundary conditions and the direct potential tide. Next, we use 3-D models with realistic, ocean background stratification and mean flow to describe the annual cycle of depth-averaged diurnal tidal currents. Finally, we investigate the baroclinic structure of diurnally forced waves including the generation of harmonics (semidiurnal and higher) that can contribute to mixing within the water column. Our results show that tides should be explicitly included in ocean and coupled predictive models for the Arctic to represent the feedbacks between tidal energetics and ocean mean state via mixing.

Increasing extent and duration of seasonally ice-free area in the western Arctic Ocean suggests increased air-sea coupling, specifically fluxes of momentum and heat between the lower atmosphere and the upper ocean. The dependence of these fluxes on ice concentration and its dynamical characteristics is still uncertain. As part of the Stratified Ocean Dynamics of the Arctic (SODA) project, year-long time series of upper-ocean velocity profiles were obtained across a range of ice conditions and are used to infer momentum fluxes. We consider the structure of observed current profiles as a function of sea state and ice cover. During the summer and in open water with minimal stratification, the wind forcing is in local equilibrium with surface gravity waves, and there is a direct transfer of momentum from the atmosphere to the upper ocean. The presence of ice modifies the momentum budget through both the inclusion of ice-atmosphere and ice-ocean stresses, and by damping short surface gravity waves and thus changing the surface roughness that the atmosphere acts upon. Ice presence is also associated with increased near-surface stratification, which can act to decouple the sub-surface ocean from atmospheric forcing. Our observations show frequent decoupling of a thin surface layer (<10 m depth), including case studies in which the relatively fresh surface waters formed by “ice puddles” have entirely different motion from the relatively salty water a few meters below. Ice formation in the fall affects both the ocean stratification and the ice characteristics, leading to competing effects affecting momentum transfer. Initial results across the annual cycle are presented.

Eddies have two distinct properties known as eddy advection (K_GM ) and eddy diffusion (K_iso). These are parameterized by Gent-McWilliams [1990] (K_GM ) and Redi [1982] (K_iso), respectively, in low to moderate resolution global ocean models. Both processes play an active part in the uptake of tracers such as CO_2 and CFCs. The advective role of eddies is associated with slumping of isopycnals, whereas the diffusive role is associated with the down-gradient diffusion [Lee et al., 2007]. In this work we investigate, for the first-time, which eddy process plays a dominant role in controlling tracer distribution in models. The model (pyOM2) used in this work is a coarse-resolution (2°x 2°) global ocean model [Eden et al., 2014]. We use a suite of nine different experiments, each with different K_GM and K_iso values. An idealised passive tracer is introduced at the surface of the ocean after the model is well equilibrated and it evolves for 100 years. We found on decadal time scales eddy diffusion and eddy advection both play equally important roles in controlling tracer distribution. However, on the time scale of hundred years or more eddy advection dominates over eddy diffusion. Small K_GM values set the isopycnal slopes to be steep, which allows the tracer to easily penetrate the deep ocean along isopycnals. On the contrary, large K_GM values flatten the isopycnals and therefore tracer only weakly penetrates the deep ocean. Near Antarctica, large values of K_iso exert strong control over the tracer distribution and brings tracer rich water to depth.

Accurate forecasts of total water level (i.e., a combination of tides, surge, wave and freshwater components) is imperative for stakeholders and federal agencies to adopt strategies for potential flooding hazards in a timely-manner. In that regard, the National Water Center in partnership with several federal agencies have been providing forecast services to the United States since 2017. However, the complex interaction of dynamical forcing conditions among other factors (e.g., anthropogenic activities, land cover change, etc.) reduce the National Water Model’s (NWM) ability to provide accurate Total Water Level (TWL) prediction in Coastal Transition Zones (CTZs). In this study, we use an existing inland to coastal model coupling framework (i.e., NWM, HWRF, Delft3D-FM and ADCIRC) to analyze the influence of dynamical forcing conditions (e.g., local wind, surge and river discharge) on TWL prediction in Delaware Bay, USA. In addition, we quantify the contribution of each component in TWL for Hurricanes Isabel and Sandy based on a systematic set of scenarios generated in Delft3D-FM. It is revealed that in both hurricanes, storm surge-induced water level is the main contributor to TWL followed by astronomical tides. River discharge induced-water level is rather small compared to the other components. Analyses of spatial variation of TWL as well as temporal variation of error in prediction suggest that wind forcing plays a key role in TWL prediction followed by river discharge. Moreover, our results suggest that the wind module of Delft3D-FM greatly improves the model performance at TWL peak when compared to the other forcing.

In this study we introduce a pair of idealized tracers to quantify how changes in physical advection and mixing under climate change affect the nutrient supply, new production, and particulate export rates. The low cost and simplicity of these tracers allows us to explore the sensitivity of the model biogeochemistry, and in particular its response to a changing physical environment, to the choice of model parameters. Using CESM2.1 with active ocean and ice only, at nominal one-degree resolution, under initial conditions and forcing representative of 2000 and 2100, our idealized nutrient and particulate are within the spread of nitrate and export from CMIP5 models. The simple form of the tracers allows us to identify the physical controls on the changing rates of supply, production, and export throughout the year, which together form the different seasonal cycles. We find that the ocean basins with the largest changes in the seasonal cycle over the 21st century are the North Atlantic, the Arctic, and the eastern tropical Pacific. We present results comparing the controls across basins, focusing on shifts in the timing of deepening mixed layers and maximum production rate in the northern North Atlantic through the Arctic, and changes in the spatial and temporal patterns of vertical advective exchange in the tropics and subtropics of the Pacific and Indian Oceans. In both cases we discuss how much these changes depend on the biogeochemical model parameter values.

Journals, funding agencies, and researchers are more frequently expecting manuscripts to include links to shared research data. Effective data sharing requires that data be findable, accessible, interoperable, and reusable (FAIR), and is thus predicated on establishing a common understanding on how to communicate: data exchange standards, common data formats, controlled vocabularies, and a communal data repository. When conducting research, we still communicate in shorthand that is effective for everyone on the team who understands our context, but is lost when data is shared in the absence of that context. “Water temperature” means only one thing to my research team, yet can mean dozens of things outside of that context. Data sharing is thus an exercise in sharing not just the data, which is typically readily available, but also the context of that data, which requires additional effort. This effort is one of the barriers to sharing data. We’ll describe an alternative model for accepting data to a repository: the immediate ingestion of data regardless of its metadata quality, then behavioural nudges and crowd-sourcing features that ensure this data meets appropriate standards prior to publication. We’ll show a work-in-progress prototype software tool that supports this alternative model, capable of accepting and standardizing a research data set to use CF conventions and ISO 8601 dates.

Ocean processes in the Southwest North Atlantic (SWNA) play an important role in long-term earth and ocean climate change. This region is also a resource-rich coastal zone with abundant fisheries and other material assets. Combined, the previously released NCEI Northwest Atlantic (NWA) regional climatology (RC) and newly developed SWNA RC provide complete coverage of the Gulf Stream system, which is the critical element of northward heat transport and the Atlantic Meridional Overturning Circulation. The SWNA RC is a collection of high-resolution quality-controlled temperature and salinity fields on standard depth levels from the sea surface to 4,900 m depth. This RC is based on temperature and salinity observations from the 2018 release of the World Ocean Database. The coverage includes the years 1955 to 2017 by annual, seasonal, and monthly fields for the entire period, as well as for each of the six decades. All fields computed on three horizontal grids: 1°x1°, 1/4°x1/4°, and 1/10°x1/10° degree. The SWNA RC is instrumental for assessing ocean climate changes in this region of the North Atlantic Ocean over the 1955-2017 time period and can be used in various climate studies, environmental research projects, and related applications.

Zooplankton and micronekton are key links in tropical Pacific food webs, which include tuna as top-level predators. Zooplankton and micronekton vertically migrate to deeper depths to avoid visual predators, including tuna, during the day and then return to shallower depths to feed at night. Vertical migration depths vary spatially in the tropical Pacific and are correlated with oxygen, light, and temperature. El Niño-Southern Oscillation (ENSO) causes vertical shifts in the thermocline and oxycline. The accessibility of prey during the day should therefore vary interannually depending on the ENSO phase. We use available acoustic doppler current profiler (ADCP) data from cruises within the tropical Pacific between 1990 and 2019 to investigate the timescales and potential drivers of variability in zooplankton and micronekton vertical distributions in this region. Preliminary results suggest that ENSO-associated variations in vertical migration depths differ across the Exclusive Economic Zones (EEZs) of small island nations in the tropical Pacific. These variations are compared to temperature and oxygen-driven tuna vertical habitat variability to assess potential impacts on tuna.

Potential habitat models have become an increasingly used method for characterizing fish larval habitat. Describing the potential habitat of fish larvae can yield insight into distribution patterns over temporal and spatial scales that cannot be easily characterized w discrete ichthyoplankton surveys, as well as setting a reference against which to assess the impact of anthropogenic and natural disturbances. Potential habitats are defined based on larval distribution and the environmental conditions that are suitable for development and survival. In the central Gulf of México (GoM), mesoscale circulation is dominated by the Loop Current (LC), LC-derived anticyclonic eddies that are transported westward and cyclonic eddies; these features influence productivity and water column characteristics and hence larval habitat. A semi-permanent cyclonic eddy in the Bay of Campeche (southern GoM) and other processes such as regional upwelling and offshore transport can also influence larval potential habitat. Between 2011-2017 nine oceanographic cruises covering the Mexican EEZ were conducted and fish larvae were collected using a bongo net sampler. Five taxa with different life history strategies, abundance and distribution patterns, spawning seasonality, and of varying economic importance were selected for the characterization of their potential habitat (Auxis spp., Benthosema suborbitale, Bregmaceros atlanticus, Caranx crysos and Cubiceps pauciradiatus). Their potential habitat will be characterized using generalized additive models correlating larval distribution with environmental parameters derived from in situ CTD and satellite-based measurements. The results of this study will yield insight into the potential larval habitat of representative fish species throughout the central and southern Gulf of Mexico.

Biological connectivity studies are crucial for explaining the structure of marine populations of species with a pelagic larval stage. Numerical modelling is a powerful tool for evaluating marine dispersal pathways of planktonic organisms. The high-resolution numerical circulation model HYCOM (HYbrid Coordinate Ocean Model) has been used to examine fish connectivity patterns in the Gulf of Mexico (GoM), but without biological validation. We examined the connectivity of fish larvae caught in the northwestern GoM by coupling ichthyoplankton surveys with numerical modelling and particle backtracking experiments. Fish larvae were collected with 200 m oblique bongo tows along two parallel transects extending from the edge of the shelf to deep waters of the Perdido region in the northwestern GoM (24°N to 26°N and 94.5°W to 97°W) during four cruises (June and October 2016, April and November 2017). Larvae of coastal and shelf-spawning species were used to infer offshore transport. In order to explore their dispersal pathways, the real-time HYCOM 1/25° model hourly output with the Navy Coupled Ocean Data Assimilation (NCODA) was used to simulate Lagrangian trajectories for each cruise and transect. Particles were seeded at sampling stations and the circulation model was run backward in time to infer larval origin. Patterns of spatial distribution and abundance of the coastal and shelf larvae caught in oceanic stations among cruises exhibited a reasonable agreement with the results of modelling exercises, and indicate the shelves of Tamaulipas and Texas were the main source of larvae to Perdido’s deepwater region. Our results suggest the combined use of ichthyoplankton surveys and ocean circulation models can yield insight into the dispersal pathways of larvae of neritic fish species to deep waters regions in the GoM. Likewise, these results imply that fish larval distributions are a useful tool for evaluating the reliability of using 2-D velocity fields from circulation models to infer larval transport at time scales of several weeks.

In high-latitude environments such as the Arctic Ocean, phytoplankton growth is strongly constrained by light availability. Because light penetration into the upper ocean is attenuated by snow and ice cover, it was generally believed until recently that phytoplankton growth was limited to areas of open water, with negligible growth under the ice. However, under-ice phytoplankton blooms have been reported multiple times over the past several decades [e.g. Fukuchi et al. (1989); Legendre, Ingram, and Poulin (1989)]. In July 2011, Arrigo et al. (2012) observed a massive phytoplankton bloom beneath sea ice in the Chukchi Sea. Observational evidence suggests that this bloom was not an isolated case, and that under-ice blooms maybe widespread on Arctic continental shelves (Arrigo et al., 2014; Lowry, van Dijken, & Arrigo, 2014). Arrigo and van Dijken (2011) estimate the total primary production north of the Arctic Circle to be 438 +/- 21.5 Tg C yr -1. However, due to observational limitations, this estimate did not include under sea ice production. Therefore, an open question remains: How important are under-ice phytoplankton blooms to the total Arctic primary production? RASM is a high-resolution, fully-coupled, regional model with a domain encompassing the entire marine cryosphere of the Northern Hemisphere, including the major inflow and outflow pathways, with extensions into North Pacific and Atlantic oceans. The components of RASM include: atmosphere, sea ice, ocean, biogeochemical, and land hydrology (Maslowski et al. 2012, Roberts et al. 2015, DuVivier et al. 2016, Hamman et al. 2016, Hamman et al. 2017, Cassano et al. 2017). The ocean BGC component in RASM is a medium-complexity Nutrients-Phytoplankton-Zoo-plankton-Detritus (NPZD) model (Jin et al. 2018). The model has three phytoplankton categories: diatoms, small phytoplankton and diazotrophs. RASM results show that under-ice pelagic chl-a and primary production values can at times be very high, particularly during the spring and early summer. Our numerical model results produce a mean of 495 Tg C yr -1 north of the Arctic Circle during 1980-1998 (and 507 Tg C yr -1 during 1980-2018). We also see an increase in primary production over the last several decades. This increase is attributed to the reduced sea ice cover, which increases light availability to the upper ocean. We conclude that under-sea-ice pelagic primary production makes up a large fraction of the total production and cannot be considered negligible.

In the past 30 years, Cook Inlet, Alaska (CI) has experienced significant changes in environmental conditions from anthropogenic and atmospheric events including the Exxon Valdez Oil spill, multiple ENSO cycles, and the recent 2014-2016 Pacific marine heatwave known as “the Blob”. The latter event coincided with the appearance of several well-documented marine species (e.g. ocean sunfish, skipjack tuna, and several species of copepods) common along the coasts of California to Washington in the Gulf of Alaska, and CI. As part of the Gulf Watch Alaska long-term monitoring program, CI zooplankton were collected to understand how these disturbances affect ecological patterns in zooplankton associated with the nearshore marine system. From 2012 to 2017, zooplankton were collected monthly along five nearshore transects across CI with a 0.6 m bongo net (333 µm mesh) towed vertically from 50m to the surface (n = 396). Tows were subsampled and microscopically enumerated for species composition and abundance. GAMs showed that abundance peaked mid-June (2533.70±189.64 no. m-3) and gradually declined to a low in January (9.40±224.80 no. m-3). Of the 237 species identified, 77 of the most abundant species (>5% presence) were used in an indicator species analysis (ISA) to show seasonal shifts in community composition. In early spring, the community was comprised of Neocalanus spp. copepods and ichthyoplankton (e.g. Clupea pallasi). Progressing into late spring, the community switched to a larvae (barnacles, polychaetes, euphausiids) dominated structure that also included copepods common to the region (Pseudocalanus spp. and Calanus marshallae). In the late summer through early fall, communities were comprised of gelatinous zooplankton. A year after the marine heatwave dissipated (2017), the community dominated by large copepods and ichthyoplankton was replaced by a community comprised of the larvae and smaller common copepods. Beginning in 2016, the last year of heatwave, a fall community characterized warm-water associated copepods (Paracalanus parvus and Corycaeus anglicus) increased significantly (9 events 2012-2015; 20 events in 2016) and continued to dominate the communities in the fall of 2017 (12 events), suggesting effects of anomalously warm-waters may persist after the marine heatwave dissipated.

Mean residence time of the seawater in the shelf region, τ, has been studied in several closed bays and inland seas around Japan. From previous estimates of 0.69 months in the Ise Bay and 6.4-14.7 months in the Seto Inland Sea, τ is expected to vary depending on area, but there is no research that reveals the whole picture of the spatiotemporal variation of τ around Japan. As the first step, we estimate τ for the entire coastal regions using the 2-km resolution Japanese coastal model “MRI.COM-JPN” that we developed for a JMA operational system. The model reproduces well tides, river inflows and many coastal currents around Japan, which are necessary to simulate the basic physical processes of coastal-offshore water exchange. In order to estimate τ, an experiment was conducted to run an “age tracer” that takes an age while existing in the shelf region and then resets the age to zero offshore. The tracer value can be regarded as the mean residence time τ of the seawater flowing into the shelf region. The model was driven for 9 years, and the results from the last 7 years were used for the analysis. Results showed that in many coastal areas, τ ranged from 20 to 100 days. In eight closed areas such as the Tokyo Bay and the Seto Inland Sea, τ reached 100-450 days. In addition, τ was as long as 100-200 days in the downstream of the two coastal currents originating from continental shelves, the Tsushima Warm Current and the East Sakhalin Current. On the other hand, τ on the Pacific side, including the southern coast of Japan where the Kuroshio Current flows offshore, was as short as several to 20 days. At presentation, we will also discuss results of a particle tracking experiment.

The coastal waters off Newport, Oregon are part of a naturally dynamic ecosystem influenced by the California Current. In additional to highly variable interannual and decadal processes, recent environmental monitoring has indicated instances of persistent warm water masses in the region. One method of assessing long standing shifts in the ecology of this coastal and offshore environment is to associate physical oceanographic variables with the presence of indicator species such as marine mammals. Using cross-platform oceanographic and spatial data sources, we evaluated prey habitat suitability and marine mammal distribution across three years. The Ocean Observatories Initiative (OOI) maintains a series of coastal and offshore monitoring platforms and data systems that include cabled sensors and gliders. Since 2016, this conglomeration of resources has continuously collected information such as temperature, dissolved oxygen, pH, pCO2, chlorophyll and nitrate from the continental shelf near Newport out to the Axial Seamount along the Juan de Fuca Ridge. Gliders travel along five east-west transect lines from a depth of 0-1,000 m, contributing greater spatial resolution of these variables. Approximately 10 species of marine mammals inhabit the waters off Oregon, several of which feed within the region of interest. To obtain marine mammal distribution data within a 1,000 km2 area surrounding the OOI cabled and glider instruments, we queried the Ocean Biogeographic Information System (OBIS) database for observations of killer whales, sperm whales and pacific white-sided dolphins. We used physical oceanographic variables from moorings just below the surface and at depth to characterize the seasonal prey habitat of these three species of marine mammals. Although we did not have data to support an assessment of the region prior to the warm water mass of 2014-2015, the years following this event from 2016-2018 were explored for seasonal ecosystem trends.

Wave energy has received significant attention in both academic and industrial areas during the past few decades. Among all of Wave Energy Devices (WEC) devices, many researchers focus on modeling the point absorber since it can provide a large amount of power in a small simple device when compared with other technologies. In this present work, we developed an efficient Structured Adaptive Mesh Refinement (SAMR) framework to model the interactions between the wave and pointer absorber by directly solving the Naiver-Stokes equation in a conservative manner. In particular, the level set function is used to capture the air-water interface, and re-initialization across different levels is applied. The Discrete Immersed Boundary Method (DIBM) is applied to describe geometry of the pointer absorber and include its effects on the incoming wave, which is generated in the inlet and absorbed by using a sponger layer closed to the outlet. To save computational cost, meshes are only refined near the air-water interface and surface of point absorber. Specially, both non-subcycling, where a uniform time step is employed for all variables on composite levels, and subcycling, in which variables on different levels advance via different time steps, are embedded in the SAMR framework. Cases about wave generation and fluid-structure interaction are obtained to validate the above proposed algorithm. Results show that subcycling takes significantly less CPU hours than non-subcycling to model the wave and pointer absorber interaction. Heave motions under different wave inputs are compared with previous experiments as well as results from potential flow theory, which shows viscous effects are important in this process. Future work including coupling AMR with Turbulent Models (e.g. RANS or LES) are also listed as an extension.

The Dungeness crab (Metacarcinus magister) fishery is one of the highest value fisheries in the US Pacific Northwest, but its catch size fluctuates widely across years. Although the underlying causes of this variability are not well understood, the abundance of M. magister megalopae has been linked to recruitment into the adult fishery four years later. These pelagic megalopae are exposed to a range of ocean conditions during their dispersal period, which may drive their occurrence patterns. Environmental exposure history has been found to be important for some pelagic organisms, so we hypothesized that inclusion of environmental exposure history would improve our ability to predict M. magister megalopae occurrence patterns compared to using ‘in situ’ conditions alone. We combined local observations of M. magister megalopae and regional simulations of ocean conditions to model megalopae occurrence using a generalized linear model (GLM) framework. The modeled ocean conditions were extracted from J-SCOPE, a high-resolution coupled physical-biogeochemical model. The analysis included variables from J-SCOPE identified in the literature as important for larval crab occurrence: temperature, salinity, dissolved oxygen concentration, nitrate concentration, phytoplankton concentration, aragonite and calcite saturation state, and pH. GLMs were developed with either in situ ocean conditions or environmental exposure histories generated using particle tracking experiments. We found that inclusion of exposure history improved the ability of the GLMs to predict megalopae occurrence. Of the five swimming behaviors used to simulate megalopae dispersal, several behaviors generated GLMs with superior fits to the observations, so a biological ensemble of these models was constructed. Our results highlight the importance of including exposure history in larval occurrence modeling and help provide a method for predicting pelagic megalopae occurrence. This work is a step towards developing a forecast product to support management of the fishery.