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Application of lake models coupled within earth-system prediction models, especially for predictions from days to weeks, requires accurate initialization of lake temperatures. Commonly used methods to initialize lake temperatures include interpolation of global sea-surface temperature (SST) analyses to inland lakes, daily satellite-based observations, or model-based reanalyses. However, each of these methods have limitations in capturing the temporal characteristics of lake temperatures (e.g., effects of anomalously warm or cold weather) for all lakes within a geographic region and/or during extended cloudy periods. An alternative lake-initialization method was developed which uses two-way-coupled cycling of a small-lake model within an hourly data assimilation system of a weather prediction model. The lake model simulated lake temperatures were compared with other estimates from satellite and in situ observations and interpolated-SST data for a multi-month period in 2021. The lake cycling initialization, now applied to two operational US NOAA weather models, was found to decrease errors in lake surface temperature from as much as 5–10 K vs. interpolated-SST data to about 1–2 K compared to available in situ and satellite observations.

Application of lake models coupled within earth-system prediction models, especially for short-term predictions from days to weeks, requires accurate initialization of lake temperatures. Here, we describe a lake initialization method by cycling within an hourly updated weather prediction model to constrain lake temperature evolution. We compare these simulated lake temperature values with other estimates from satellite and in situ and interpolated-SST data sets for a multi-month period in 2021. The lake cycling initialization, now applied to two operational US NOAA weather models, was found to decrease errors in lake temperature from as much as 5–10 K (using interpolated-SST data) to about 1–2 K (comparing with available in situ and satellite observations.

NOAA technical memorandum NOS CS ; 48

A tool to estimate the ray-tracing component of the surveyed depth uncertainty was created and made publicly available through Web services and a Web geographic information system. The estimation is based on a spatial variability analysis at the time of validity of two popular, global-scope sources of oceanographic environmental data. The tool has potential applications in all the phases of ocean mapping, from survey planning to data collection and processing.

Despite recent technological advances in seafloor mapping systems, the resulting products and the overall operational efficiency of surveys are often affected by poor awareness of the oceanographic environment in which the surveys are conducted. Increasingly reliable ocean nowcast and forecast model predictions of key environmental variables – from local to global scales – are publicly available, but they are often not used by ocean mappers. With the intention of rectifying this situation, this work evaluates some possible ocean mapping applications for commonly available oceanographic predictions by focusing on one of the available regional models: NOAA’s Gulf of Maine Operational Forecast System. The study explores two main use cases: the use of predicted oceanographic variability in the water column to enhance and extend (or even substitute) the data collected on-site by sound speed profilers during survey data acquisition; and, the uncertainty estimation of oceanographic variability as a meaningful input to estimate the optimal time between sound speed casts. After having described the techniques adopted for each use case and their implementation as an extension of publicly-available ocean mapping tools, this work provides evidence that the adoption of these techniques has the potential to improve efficiency in survey operations as well as the quality of the resulting ocean mapping products.

Ice Cover in the Great Lakes has significant impacts on regional weather, economy, lake ecology, and human safety. However, forecast guidance for the lakes is largely focused on the ice-free season and associated state variables (currents, water temperatures, etc.) A coupled lake-ice model is proposed with potential to provide valuable information to stakeholders and society at large about the current and near-future state of Great Lakes Ice. The model is run for three of the five Great Lakes for prior years and the modeled ice cover is compared to observations via several skill metrics. Model hindcasts of ice conditions reveal reasonable simulation of year-to-year variability of ice extent, ice season duration, and spatial distribution, though some years appear to be prone to higher error. This modeling framework will serve as the basis for NOAA&rsquo, s next-generation Great Lakes Operational Forecast System (GLOFS), a set of 3-D lake circulation forecast modeling systems which provides forecast guidance out to 120 h.

Considerable effort has gone into building numerical weather and ocean prediction models during the past 50 years. Less effort has gone into the visual representation of output from those forecast models and many of the techniques used are known to be ineffective. The effectiveness of a data display depends on how well critical patterns can be perceived. This paper outlines a set of perceptual principles for what makes a good representation of a 2D vector field and shows how these principles can be used for the portrayal of currents, winds, and waves. Examples are given from a series of evaluation studies that examine the optimal representation of these variables. The results suggest that for static graphic presentations, equally spaced streamlines may be optimal. If wind barbs are curved to follow streamlines, perception of local wind speed and direction as well as the overall pattern is improved. For animated portrayals of model output, animated streamlets can perceptually separate layers of information...

The NOAA National Ocean Service’s (NOS) Northern Gulf of Mexico Operational Forecast System (NGOFS) became operational in March 2012. Implemented with the Finite Volume Coastal Ocean Model (FVCOM) as its core three-dimensional oceanographic circulation model, NGOFS produces a real-time nowcast (−6 h to zero) and six-hourly, two-day forecast guidance for water levels and three-dimensional currents, water temperature and salinity over the northern Gulf of Mexico continental shelf. Designed as a regional scale prediction system, NGOFS lacks sufficient spatial coverage and/or resolution to fully resolve hydrodynamic features in critical seaports and estuaries. To overcome this shortcoming and better support the needs of marine navigation, emergency response, and environmental management, two FVCOM-based, high-resolution, estuary-scale nested forecast modeling systems, namely the Northwest and Northeast Gulf of Mexico Operational Forecast Systems (NWGOFS and NEGOFS), have been developed through one-way nesting in NGOFS. Using the atmospheric forecast guidance from the NOAA (National Oceanic and Atmospheric Administration)/NWS (National Weather Services)’ North American Mesoscale (NAM) Forecast System, US Geological Survey (USGS) river discharge observations, and the NGOFS water level, current, water temperature and salinity as the surface, river, and open ocean boundary forcing, respectively, a six-month model hindcast for the period October 2010–March 2011 has been conducted. Modeled water levels, currents, salinity and water temperature are compared with observations using the NOS standard skill assessment software. Skill assessment scores indicated that NWGOFS and NEGOFS demonstrate improvement over NGOFS. The NWGOFS and NEGOFS are under real-time nowcast/forecast test and evaluation by NOS’s Center for Operational Oceanographic Products and Services (CO-OPS). The forecast systems are scheduled to be implemented operational on NOAA Weather & Climate Operational Supercomputing System (WCOSS) in June 2014.

The real-time, three-dimensional, limited-area Coastal Ocean Forecast System (COFS) has been developed for the northwestern Atlantic Ocean and implemented at the National Centers for Environmental Prediction. COFS generates a daily nowcast and 1-day forecast of water level, temperature, salinity, and currents. Surface forcing is provided by 3-h forecasts from the National Weather Service's Eta Model, a mesoscale atmospheric prediction model. Lateral oceanic boundary conditions are based on climatic data. COFS assimilates in situ sea surface temperature (SST) observations and multichannel satellite SST retrievals for the past 48 h. SST predictions from the assimilating and nonassimilating versions of COFS were compared with independent observations and a 14-km-resolution multichannel SST analysis. The assimilation of SST data reduced the magnitude and the geographic extent of COFS's characteristic positive temperature bias north of the Gulf Stream. The root-mean-square SST differences between the ...

A one-way coupled atmospheric‐lake modeling system was developed to generate short-term, mesoscale lake circulation, water level, and temperature forecasts for Lake Erie. The coupled system consisted of the semioperational versions of the Pennsylvania State University‐National Center for Atmospheric Research threedimensional, mesoscale meteorological model (MM4), and the three-dimensional lake circulation model of the Great Lakes Forecasting System (GLFS). The coupled system was tested using archived MM4 36-h forecasts for three cases during 1992 and 1993. The cases were chosen to demonstrate and evaluate the forecasts produced by the coupled system during severe lake conditions and at different stages in the lake’s annual thermal cycle. For each case, the lake model was run for 36 h using surface heat and momentum fluxes derived from MM4’s hourly meteorological forecasts and surface water temperatures from the lake model. Evaluations of the lake forecasts were conducted by comparing forecasts to observations and lake model hindcasts. Lake temperatures were generally predicted well by the coupled system. Below the surface, the forecasts depicted the evolution of the lake’s thermal structure, although not as rapidly as in the hindcasts. The greatest shortcomings were in the predictions of peak water levels and times of occurrence. The deficiencies in the lake forecasts were related primarily to wind direction errors and underestimation of surface wind speeds by the atmospheric model. The three cases demonstrated both the potential and limitations of daily high-resolution lake forecasts for the Great Lakes. Twice daily or more frequent lake forecasts are now feasible for Lake Erie with the operational implementation of mesoscale atmospheric models such as the U.S. National Weather Service’s Eta Model and Rapid Update Cycle.

A better understanding of growth and developmental processes of rice (Oryza sativa L.) seedlings is necessary for crop management and modeling perspectives. This experiment was conducted to identify preautotrophic phases of rice seedlings, quantify seed dry matter mobilization and utilization, characterize dry matter partitioning during early growth, and observe if these processes are affected by cultivar and seed size. Seeds of two cultivars, each separated into two seed sizes, were sown in a greenhouse using field soil, and observations on seed weight loss and seedling weight gain were recorded daily for 27 d. The durations of heterotrophic and transition phases were determined as 74 and 247 thermal units (base temperature 9°C), respectively. Seeds lost 0.79 ± 0.010 g g -1 during the preautotrophic phases, while 0.42 ± 0.023 g g -1 seed weight accumulated in the seedling. Partitioning of dry matter was equal between root and shoot up to 37 thermal units, then allocation to root reduced curvilinearly until a constant root-to-shoot ratio (15:85) was reached at 148 thermal units and maintained thereafter. Shoot dry matter partitioning between culm and leaf was almost equal throughout the experiment except for the initial 37 thermal units when all dry matter accumulated in the culm. Early developmental processes in rice seedlings were independent of cultivar and seed size in this study. Although seed dry matter loss in proportion to the initial seed dry matter was significantly higher for larger seeds, the utilization pattern remained unaffected by seed size. This indicates that larger seeds were less efficient than smaller seeds in the utilization of reserves.

Electric vehicle production is expected to increase dramatically over the next 10 years. DC motors are used exclusively at present but the change to AC brings advantages in weight and efficiency providing improved range. Because it is readily available, the induction motor is being used for the next generation of electric vehicles but the brushless DC motor has the lightest weight and highest efficiency and is expected to be used within the next 10 years. The switched reluctance motor also has merits for special applications. The author compares the different types of motor for weight, efficiency, cost and other factors. The author also discusses generators for hybrid electric vehicles.

The objective of the Coastal and Inland Flooding Observation and Warning (CI-FLOW) project is to prototype new hydrometeorologic techniques to address a critical NOAA service gap: routine total water level predictions for tidally influenced watersheds. Since February 2000, the project has focused on developing a coupled modeling system to accurately account for water at all locations in a coastal watershed by exchanging data between atmospheric, hydrologic, and hydrodynamic models. These simulations account for the quantity of water associated with waves, tides, storm surge, rivers, and rainfall, including interactions at the tidal/surge interface. Within this project, CI-FLOW addresses the following goals: i) apply advanced weather and oceanographic monitoring and prediction techniques to the coastal environment; ii) prototype an automated hydrometeorologic data collection and prediction system; iii) facilitate interdisciplinary and multiorganizational collaborations; and iv) enhance techniques and techn...

Mesoscale weather data was input to a gypsy moth, Lymantria dispar L., phenological model to provide a landscape description of gypsy moth phenology. Mesoscale climatological (30-yr average) and single-season (1990) data were spatially interpolated by regressing station temperature as a function of geophysical data (longitude, latitude, and elevation). The interpolated, high-resolution (1 by 1 km pixels) minimum and maximum temperatures were input into a previously developed gypsy moth phenology model to predict egg hatch dates for a single season and for an average season as defined by climatological data. The single-season and climatological predictions were compared statistically to observed egg hatch dates at 15 sites in two states. The single-season predictions and the observed dates were only 2.1 ± 0.2 (mean (± SE) d apart when averaged over all sites, indicating that mesoscale data can successfully be used as input into gypsy moth phenology models. Although the results of the single-year simulation were mostly accurate, the mesoscale climatic predictions of egg hatch averaged 24.3 ± 0.7 d after the observed date in the field. This difference was caused by the unusually warm spring in 1990 compared with a climatological (average) season. The comparison of the singleseason and climatic predictions in 1990 indicate the importance of using mesoscale data from a current season to update the phenological predictions used in long-range planning.

Optimizing complex displays is difficult because there are many alternative ways of mapping the data to its graphical representation. In this paper we report on a study employing a method we call “interactive design space hill climbing”. This involves first parameterizing the mapping from data to display. Next, using an interactive interface, designers and domain experts attempt to construct good designs by interactively changing parameters settings based on a random starting point. In our study we applied this method to the problem of 2D flow visualization: users adjusted 22 different sliders under each of 11 mappings to try to create an optimal display of a flow field from an ocean flow model. The results suggest that some variables should have settings in a narrow range. We conclude that employing designers with a human in the loop hill climbing interface can be a good overall solution for complex visual display designs in cases where a relatively simple parameterization is possible.

NOAA’s Local Analysis and Prediction System (LAPS) was implemented for the Narragansett Bay region to provide surface forcing for an oceanographic forecast model for the bay and adjacent coastal waters. The forecast model used by LAPS was the Pennsylvania State University/National Center for Atmospheric Research (NCAR) mesoscale model (MM5). The Narragansett Bay, with its complex shoreline and numerous islands, provided a difficult challenge for an atmospheric model in properly forecasting mesoscale phenomena such as sea and land breezes. MM5 forecasts (primarily its surface wind predictions) will be evaluated using observations from a variety of different federal, state, university, and cooperative networks. When considered together, these networks provide a dense coverage of observations essential for evaluating mesoscale forecasts in the coastal zone.

An upper UHF band for hospital radio telemetry use has been evaluated. Signal strength measurements show good agreement with the Rayleigh distribution over non-LOS paths. The channel can accommodate wide band data transmission and provide an adequate output signal-to-noise ratio with a +10 dBm source.

A 1999–2000 National Ocean Partnership Project (NOPP) has demonstrated highly accurate predictions of ocean temperatures, currents, and surface elevation through a model that integrates the state of the ocean to routinely produce real-time nowcasts and forecasts. The success is attributed to a new technology for model-assimilation of satellite-derived surface observations with observations from in situ equipment. Because the Chesapeake Bay and the northwestern Atlantic boarding the east coast of the United States is an area of intense ocean harvest, recreational boating, and major shipping —activities that depend on near-term prediction of near-surface conditions of the waters off the eastern coast—it served as the test-bed for the “Coastal Marine Demonstration Project”