Davis Weather Station Protocol

This resource provides instructions on how to log atmosphere data using a Davis weather station. A weather station is setup to measure and record atmospheric measurements at 15-minute intervals and can be transferred to the GLOBE program via email. Students can view data for their school that are continuous and show variations within a day. The data collected includes wind speed and direction and pressure thereby supporting a more complete study of meteorology using GLOBE. Students pursue a more extensive set of research investigations. Educational levels: Middle school, High school

Weathering the storm- Fair weather versus stormy-weather governance in the euro area

Jean Pisani-Ferry and André Sapir believe that the euro has proved attractive as a fair-weather currency for countries and investors well beyond its borders. But it still remains to be seen if its governance is strong enough for it to succeed as a stormy-weather currency. The authors already detect, howevever, that the crisis shows the euro-area governance system lacks some crucial properties: speed of reaction, policy discretion and centralised decision-making.

Weathering and Erosion: Simulating Rock Attack in the Lab

These activities examine the ways in which water can weather rocks. Simulations of erosion by running water, solution, freeze‑thaw and by wind are investigated. Several class laboratory and demonstration activities simulate some of the processes occurring in weathering and erosion. They include a look at the effect of pouring water onto brown sugar to simulate the effect of water on soluble rock, observing the residue left after water samples have evaporated to show that water can dissolve minerals, showing that water expands on freezing by placing a sealed jar of water in the freezer overnight, and inspection of the effect of freezing on a water-soaked sample of porous rock. In addition, an activity simulates the effect of water impact on rocks by pouring water on sand and another uses a hair dryer to simulate wind erosion by sandblasting copper sulfate crystals. Educational levels: Middle school

Weather Forecasting for Weather Derivatives

We take a simple time-series approach to modeling and forecasting daily average temperature in U.S. cities, and we inquire systematically as to whether it may prove useful from the vantage point of participants in the weather derivatives market. The answer is, perhaps surprisingly, yes. Time-series modeling reveals conditional mean dynamics, and crucially, strong conditional variance dynamics, in daily average temperature, and it reveals sharp differences between the distribution of temperature and the distribution of temperature surprises. As we argue, it also holds promise for producing the long-horizon predictive densities crucial for pricing weather derivatives, so that additional inquiry into time-series weather forecasting methods will likely prove useful in weather derivatives contexts.Risk management; hedging; insurance; seasonality; temperature; financial derivatives

Incorporating weather information into real-time speed estimates: comparison of alternative models

Weather information is frequently requested by travelers. Prior literature indicates that inclement weather is one of the most important factors contributing to traffic congestion and crashes. In this paper, we propose a methodology to use real-time weather information to predict future speeds. The reason for doing so is to ultimately have the capability to disseminate weather-responsive travel time estimates to those requesting information. Using a stratified sampling technique, we select cases with different weather conditions (precipitation levels) and use a linear regression model (called the base model) and a statistical learning model (using Support Vector Machines for Regression) to predict 30-minute ahead speeds. One of the major inputs into a weather-responsive short-term speed prediction method is weather forecasts; however, weather forecasts may themselves be inaccurate. We assess the effects of such inaccuracies by means of simulations. The predictive accuracy of the SVR models show that statistical learning methods may be useful in bringing together streaming forecasted weather data and real-time information on downstream traffic conditions to enable travelers to make informed choices