PICES Press, Vol. 17, No. 1, January 2009

Major Outcomes from the 2008 PICES Annual Meeting: A Note from the Chairman (pdf, 0.1 Mb) PICES Science – 2008 (pdf, 0.1 Mb) 2008 PICES Awards (pdf, 0.3 Mb) Charles B. Miller – A Selective Biography (pdf, 0.4 Mb) Latest and Upcoming PICES Publications (pdf, 0.1 Mb) 2008 OECOS Workshop in Dalian (pdf, 0.2 Mb) PICES Calendar (pdf, 0.1 Mb) 2008 PICES Workshop on “Climate Scenarios for Ecosystem Modeling (II)” (pdf, 0.1 Mb) PICES/ESSAS Workshop on “Marine Ecosystem Model Inter-Comparisons” (pdf, 0.2 Mb) Highlights of the PICES Seventeenth Annual Meeting (pdf, 0.5 Mb) 2008 PICES Summer School on “Ecosystem-Based Management” (pdf, 0.3 Mb) 4th PICES Workshop on “The Okhotsk Sea and Adjacent Areas” (pdf, 0.2 Mb) PICES WG 21 Rapid Assessment Surveys (pdf, 0.4 Mb) PICES Interns (pdf, 0.3 Mb) PICES @ Oceans in a High CO2 World (pdf, 0.1 Mb) Coping with Global Change in Marine Social–Ecological Systems: An International Symposium (pdf, 0.1 Mb) The State of the Western North Pacific in the First Half of 2008 (pdf, 1.3 Mb) State of the Northeast Pacific through 2008 (pdf, 0.3 Mb) The Bering Sea: Current Status and Recent Events (pdf, 0.2 Mb) An Opinion Born of Years of Observing Timeseries Observations (pdf, 0.1 Mb) New Chairman for the PICES Fishery Science Committee (pdf, 0.1 Mb

Rule Based Forecasting [RBF] - Improving Efficacy of Judgmental Forecasts Using Simplified Expert Rules

Rule-based Forecasting (RBF) has emerged to be an effective forecasting model compared to well-accepted benchmarks. However, the original RBF model, introduced in1992, incorporates 99 production rules and is, therefore, difficult to apply judgmentally. In this research study, we present a core rule-set from RBF that can be used to inform both judgmental forecasting practice and pedagogy. The simplified rule-set, called coreRBF, is validated by asking forecasters to judgmentally apply the rules to time series forecasting tasks. Results demonstrate that forecasting accuracy from judgmental use of coreRBF is not statistically different from that reported from similar applications of RBF. Further, we benchmarked these coreRBF forecasts against forecasts from (a) untrained forecasters, (b) an expert system based on RBF, and (c) the original 1992 RBF study. Forecast accuracies were in the hypothesized direction, arguing for the generalizability and validity of the coreRBF rules

Assessing the Impact of Game Day Schedule and Opponents on Travel Patterns and Route Choice using Big Data Analytics

The transportation system is crucial for transferring people and goods from point A to point B. However, its reliability can be decreased by unanticipated congestion resulting from planned special events. For example, sporting events collect large crowds of people at specific venues on game days and disrupt normal traffic patterns. The goal of this study was to understand issues related to road traffic management during major sporting events by using widely available INRIX data to compare travel patterns and behaviors on game days against those on normal days. A comprehensive analysis was conducted on the impact of all Nebraska Cornhuskers football games over five years on traffic congestion on five major routes in Nebraska. We attempted to identify hotspots, the unusually high-risk zones in a spatiotemporal space containing traffic congestion that occur on almost all game days. For hotspot detection, we utilized a method called Multi-EigenSpot, which is able to detect multiple hotspots in a spatiotemporal space. With this algorithm, we were able to detect traffic hotspot clusters on the five chosen routes in Nebraska. After detecting the hotspots, we identified the factors affecting the sizes of hotspots and other parameters. The start time of the game and the Cornhuskers’ opponent for a given game are two important factors affecting the number of people coming to Lincoln, Nebraska, on game days. Finally, the Dynamic Bayesian Networks (DBN) approach was applied to forecast the start times and locations of hotspot clusters in 2018 with a weighted mean absolute percentage error (WMAPE) of 13.8%

Principal Component Analysis of Crop Yield Response to Climate Change

The objective of this study is to compare the effects of climate change on crop yields across different regions. A Principal Component Regression (PCR) model is developed to estimate the historical relationships between weather and crop yields for corn, soybeans, cotton, and peanuts for several northern and southern U.S. states. Climate change projection data from three climate models are applied to the estimated PCR model to forecast crop yield response. Instead of directly using weather variables as predictor variables, the PCR model uses weather indices transformed from original weather variables by the Principal Component Analysis (PCA) approach. A climate change impact index (CCII) is developed to compare climate change effects across different regions. The key contribution of our study is in identifying a different climate change effects in crop yields in different U.S. states. Specifically, our results indicate that future warmer weather will have a negative impact for southern U.S. counties, while it has insignificant impact for northern U.S. counties in the next four decades.Principal component regression, Crop yield response, Climate change., Crop Production/Industries,

Scenario of the organic food market in Europe

Scenario analysis is a qualitative tool for strategic policy analysis that enables researchers and policymakers to support decision making, and a systemic analysis of the main determinants of a business or sector. In this study, a scenario analysis is developed regarding the future development of the market of organic food products in Europe. The scenario follows a participatory approach, exploiting potential interactions among the relevant driving forces, as selected by experts. Network analysis is used to identify the roles of driving forces in the different scenarios, and the results are discussed in comparison with the main findings from existing scenarios on the future development of the organic sector

An Assessment of PIER Electric Grid Research 2003-2014 White Paper

This white paper describes the circumstances in California around the turn of the 21st century that led the California Energy Commission (CEC) to direct additional Public Interest Energy Research funds to address critical electric grid issues, especially those arising from integrating high penetrations of variable renewable generation with the electric grid. It contains an assessment of the beneficial science and technology advances of the resultant portfolio of electric grid research projects administered under the direction of the CEC by a competitively selected contractor, the University of California’s California Institute for Energy and the Environment, from 2003-2014

The International Workshop on Wave Hindcasting and Forecasting and the Coastal Hazards Symposium

Following the 13th International Workshop on Wave Hindcasting and Forecasting and 4th Coastal Hazards Symposium in October 2013 in Banff, Canada, a topical collection has appeared in recent issues of Ocean Dynamics. Here we give a brief overview of the history of the conference since its inception in 1986 and of the progress made in the fields of wind-generated ocean waves and the modelling of coastal hazards before we summarize the main results of the papers that have appeared in the topical collection