John G. W. Kelley

Generation of Three-Dimensional Lake Model Forecasts for Lake Erie*

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.

Mesoscale forecasts generated from operational numerical weather-prediction model output

A technique called Model Output Enhancement (MOE) has been developed for the generation and display of mesoscale weather forecasts. The MOE technique derives mesoscale or high-resolution (order of 1 km) weather forecasts from synoptic-scale numerical weather-prediction models by modifying model output with geophysical and land-cover data. Mesoscale forecasts generated by the MOE technique are displayed as color-class maps overlaid on perspective plots of terrain. The MOE technique has been demonstrated in the generation of mesoscale maximum-temperature and minimum-temperature forecasts for case-study days of clear-sky conditions over the Commonwealth of Pennsylvania. The generated forecasts were evaluated using data from selected climatological stations.

The CI-Flow Project: A System for Total Water Level Prediction from the Summit to the Sea

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...

Assimilation of SST Data into a Real-Time Coastal Ocean Forecast System for the U.S. East Coast*

Abstract 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 Services 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 COFSs characteristic positive temperature bias north of the Gulf Stream. The root-mean-square SST differences between the ...

Improving the Display of Wind Patterns and Ocean Currents

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...

Investigating flow visualizations using interactive design space hill climbing

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 with and appropriate 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. Designers were better at producing good results than nondesigners. 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. Keywords—flow visualization, oceanography, vector fieldsOptimizing 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.

A Ray-Tracing Uncertainty Estimation Tool for Ocean Mapping

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.