Ask Question, Ask an Expert

+61-413 786 465

info@mywordsolution.com

Ask Statistics and Probability Expert

Can We Predict the Weather?

If you were in the business of supplying heating oil in the northeastern United States, would it be useful to know if a big winter snowstorm with subzero temperatures was likely to hit Massachusetts the following month? If you were a fi refighter in the backcountry of California and you knew that the odds of intense Santa Anna winds would increase dramatically in three weeks, how would you react? If you were a Home Depot manager, wouldn't you want to have snow shovels in stock if a large snowstorm was approaching? If you worked in the Federal Emergency Management Agency (FEMA), would you want to receive a 30-day advance warning of the next hurricane? Although meteorologists currently make widespread use of satellite imaging and computer modeling, the founders of EarthRisk Technologies (www.earthrisktech.com) maintain it is nearly impossible to use current weather forecasting models to make anything more than the most general predictions about weather more than two weeks into the future.

To address this limitation, EarthRisk has implemented weather forecasting software to estimate the likelihood of extreme weather events 30 to 40 days in advance, which is twice as long as conventional forecasts. EarthRisk draws on 60 years of weather data to identify conditions that could lead to major temperature swings several weeks later. The weather events that precede a hot or cold stretch are like dominoes toppling in sequence. The company's software predicts the probability of each domino falling over, and it sells that information to energy companies that want to lock in fuel prices before demand peaks.

For instance, the U.S. division of Iberdrola Renewables (www .iberdrolausa.com), the Spanish energy company, uses Earth Risk's service to plan its natural gas purchases. In the fall of 2011, the experts' consensus was that the winter of 2012 would be cold, and natural gas prices rose accordingly. But as Earth Risk analyzed the historical data, its projections showed a warming trend in the Midwest and the East. Further, that trend would accelerate as the winter wore on. As Earth Risk predicted, the winter of 2012 had the second-highest number of extreme heat events and the lowest number of extreme cold events since 1948. Natural gas prices dropped, and Iberdrola profited by buying less natural gas, at a lower price.

Earth Risk's next project is to detect Atlantic hurricanes days in advance by analyzing conditions such as ocean temperatures, sea level pressures, and vertical wind shear. The company also wants to make its software intuitive enough to be used by no meteorologists at insurance companies and other businesses. Climate Corporation (www.climate.com) also analyzes weather patterns, but it applies the results of their analyses in a different way than Earth Risk. Climate provides crop insurance to help farmers manage their risk. The company uses analytics to price their insurance products. It analyzes decades of data from the National Weather Service and other sources to derive knowledge of rainfall, temperature, and soil conditions in farmlands across America. The data sets are so fine-tuned that Climate can determine how the average weather at one spot differs from another spot just 2.5 miles away. The firm uses this information, along with historic crop yields, to predict how next year's crop is going to look. For each location, Climate simulates the weather for the next two years, performing this operation10,000 times. This analysis enables the company to customize insurance prices according to each farm's risk factors and to offer protection that supplements federal assistance. Historically, farmers have relied on crop insurance sold by the federal government. Unfortunately, this program suffers from bureaucratic red tape. Farmers must plant their fi elds on a schedule determined by the government and then consent to inspections. To estimate crop value, farmers have to record and turn over years' worth of data pertaining to yields. When disasters strike, claims take months to process, and the payout often covers only costs, not lost profi ts.

Today, farmers can log on to Climate's Web site and input details about their planting plans. An algorithm then produces multiple policy options. Farmers choose the option that best fits their needs. Because Climate's servers are always recording weather data, the company knows when a policy is triggered by, for instance, a drought, and it automatically issues payments to the affected farmers. Climate also makes its data available to its customers, showing them the range of yields and profits they can expect based on likely weather conditions. Consider John Stevens, a farmer who owns 5,300 acres of farmland. Stevens spends much of the winter trying to find the perfect "prescriptions," as he calls them, for his fi elds. Stevens analyzes weather data, takes soil moisture readings, and studies the latest news on seed hybrids, all to maximize his crop yields. During the last few years, however, his meticulous planning has been undermined by severe weather. Heavy rains fell during his brief five-day planting windows.

Then, unusually high temperatures suffocated his crops. To protect his operation, Stevens now purchases crop insurance from Climate. He appreciates the additional peace of mind that Climate provides. Each year he spends hundreds of thousands of dollars during the planting season. If a weather event damages his crops in May, Climate will pay him quickly enough to buy more seed and replant.

Questions

1. What impact will Earth Risk and/or Climate Corporation have on the business model of The Weather Channel? If you were a Weather Channel executive, what would you do to counter the threat from these two companies?

2. Provide examples of other organizations to whom long-range weather forecasts would be valuable.

Statistics and Probability, Statistics

  • Category:- Statistics and Probability
  • Reference No.:- M91764875

Have any Question?


Related Questions in Statistics and Probability

An important part of the customer service responsibilities

An important part of the customer service responsibilities of a cable company relates to the speed with which trouble in service can be repaired. Historically, the data show that the likelihood is 0.75 that troubles in a ...

Acme airlines flies airplanes that seat 20 passengers from

Acme Airlines flies airplanes that seat 20 passengers. From experience, they have learned that, on average, 85% of the passengers holding reservations for a particular flight actually show up for the flight. If they book ...

An oil company determines it costs 25000 to sink a test

An oil company determines it costs $25,000 to sink a test well, an oil hit yields a net revenue of $475,000($500,000 gross-$25,000costs), and a natural gas hit yields $125,000 net revenue ($150,000 gross-$25,000 costs). ...

In a production process a product is assembled by using

In a production process, a product is assembled by using four independent parts (A, B, C, and D). In order for the part to operate properly, each part must be free of defects. The probability that the parts are defect-fr ...

A researcher wants to determine if there is an association

A researcher wants to determine if there is an association between religious affiliation (e.g., Christian, Muslim, Jewish. Buddhist, Unaffiliated, etc.) and ethnicity (African American, Asian, American Indian, Whte, Othe ...

In a random sample of 100 college student 60 were females

In a random sample of 100 college student 60 were females, 65 were under 21 years of age and 15 males were 21 years of age or older, a student is selected at random from the sample. What is the probability that a female ...

Suppose a firm uses sales teams to market their products

Suppose a firm uses sales teams to market their products. For example, a construction equipment manufacturer may assign three sales agents to a team so each team member can specialize in particular product functions (e.g ...

A sample of 175 randomly selected students found that the

A sample of 175 randomly selected students, found that the proportion of students planning to travel home for thanksgiving is 0.64 What is the standard deviation of the sampling distribution.

You are the foreman of the bar-s cattle ranch in colorado a

You are the foreman of the Bar-S cattle ranch in Colorado. A neighboring ranch has calves for sale, and you are going to buy some calves to add to the Bar-S herd. How much should a healthy calf weigh? Let  x  be the age ...

Folgers has specified that the average amount of coffee

Folgers has specified that the average amount of coffee that goes into one of their small coffee cans is not to exceed 13.24 ounces. A quality control inspector for Folgers takes a random sample of 16 cans and found the ...

  • 4,153,160 Questions Asked
  • 13,132 Experts
  • 2,558,936 Questions Answered

Ask Experts for help!!

Looking for Assignment Help?

Start excelling in your Courses, Get help with Assignment

Write us your full requirement for evaluation and you will receive response within 20 minutes turnaround time.

Ask Now Help with Problems, Get a Best Answer

Why might a bank avoid the use of interest rate swaps even

Why might a bank avoid the use of interest rate swaps, even when the institution is exposed to significant interest rate

Describe the difference between zero coupon bonds and

Describe the difference between zero coupon bonds and coupon bonds. Under what conditions will a coupon bond sell at a p

Compute the present value of an annuity of 880 per year

Compute the present value of an annuity of $ 880 per year for 16 years, given a discount rate of 6 percent per annum. As

Compute the present value of an 1150 payment made in ten

Compute the present value of an $1,150 payment made in ten years when the discount rate is 12 percent. (Do not round int

Compute the present value of an annuity of 699 per year

Compute the present value of an annuity of $ 699 per year for 19 years, given a discount rate of 6 percent per annum. As