The Weather Almanac: A Reference Guide to Weather, Climate, and Related Issues in the United States and Its Key Cities

By Steven L. Horstmeyer

The Weather Almanac, 12th Edition is a resource for a variety of climate and meteorological data including both domestic and international weather trends, historical weather patterns dating back 1000 years, natural disasters, and a 20 page glossary of weather terminology. The book is complete with detailed maps, pictures, and tables compiling climate data from a variety of sources, including the National Weather Service and the US Geological Survey.

Separate sections in The Weather Almanac are devoted to tornadoes, hurricanes, thunderstorms, and lightening, flash floods, and winter storms, and they have been edited from official reports by governmental agencies. The new edition has been updated to include recent disasters such as the 2004 Indian Ocean Tsunami that devastated Indonesia as well as 2005’s Hurricane Katrina. These chapters serve as a basic reference for severe weather and extreme conditions, which can assist in preparing for a weather emergency.

• Language: English
• Publisher: Wiley
• Release date: Sep 23, 2011
• ISBN: 9781118015209

Book preview

Preface

Whenever an established work like The Weather Almanac is updated, the primary concern of the editor is to remain true to the traditions established in earlier editions. The editor is faced with retaining some material, updating other material, and saying goodbye to material that has seen better days.

The 12th edition of The Weather Almanac is my best effort at staying true to the hard work of my predecessors, but at the same time move the book in the direction that my 33 years as a broadcast meteorologist, public speaker, and educator tell me is most useful to the user of the book seeking answers to weather questions.

If you are looking at material that contains numbers or maps or graphs, admittedly most of the book, then you are reaping the rewards of the hard work of James Patterson. During the course of this rewrite, James was working full- and part-time jobs, finishing his meteorology degree, buying a house, and starting a family. He always found time to get the job done. He has a great ability to find problem numbers and fix them. Thanks James. James, did I say thanks?

Chapter 1 contains 42 climate maps of the United States and communicate what maps can best the spatial patterns that determine what we call climate. Chapter 2 is all new and a response to a heightened interest in renewable energy. In Chapter 2, you will find detailed information about the solar radiation and wind climates of the United States and many wind roses. They are hard to come by, but there are many here.

I have lumped the many varieties of extreme and record-setting weather into Chapter 3 and dug long and hard to assemble a chapter with some very difficult to find but important weather information. I have stayed with the customary chapters for severe and tropical weather (Chapters 4 and 5, respectively). Chapter 6 covers El Niño/La Niña, perhaps the most important climate discovery of the last half of the 20th century. Chapter 6 is updated with all new easy-to-follow diagrams.

The second entirely new chapter is Chapter 7: Global Warming and Climate Change. As a professional meteorologist deeply concerned with human impact on our environment, I am continually dismayed by the amount of bad information out there about global warming. I have intentionally steered clear of forecasts and hope this chapter clarifies physical principles, research methods, the role of proxy data, and what climate models are and what they are not.

Air Pollution is the topic of Chapter 8 and contains the latest available data that comes primarily from the US Environmental Protection Agency (EPA).

Chapter 9 contains international climate data. I have included more locations (321) and each location has more data. While this does not give a complete look at Earth's climate, most places you can easily go are covered.

In Chapter 10, you will find climate data for 128 US cities in the form of the 2009 Local Climatological Data Annual Summary. There is a great deal of information here on each station, and there are 20 more stations than the last edition. We also graphed the daily high temperatures, low temperatures, and precipitation for 2009 so you can see at a glance what 2009 was like in each city.

Chapter 11 is an annotated time line of human interaction with and knowledge of the atmosphere. As of this writing, there is no other popular reference work with such a listing. History buffs should find this interesting.

I can now answer the question my wife put to me about a week ago. Yes honey, you now get your husband back.

Steven L. Horstmeyer

August 23, 2010

Cincinnati, OH

1

Climate Maps of the United States

WHAT IS CLIMATE?

Weather is the day-to-day, sometimes minute-to-minute, changes in the atmosphere. Everyone has an intuitive idea what weather is. But when the time period is extended to months, seasons, years, decades, and longer, we talk about climate. Climate is the long-term state of the atmosphere. It is how you expect the atmosphere to behave.

The change of seasons is part of what climate is. In the Midwestern United States, residents expect hot, humid summer weather to gradually yield to autumn, characterized by cool mornings and toasty warm afternoons dominated by blue sky. In southern and central California, residents know that the brown hillsides that dominate the landscape from late spring into late autumn will begin to green as seasonal rains replenish soil moisture and plants begin to grow.

In Hawaii there is hardly any seasonal temperature change at all, but there are subtle differences from summer into winter in wind and rain events.

Climate is much more than seasonal change. It has been called the average of all weather, but it is still more. It can also be the daily, weekly, monthly, or annual range of a weather variable. Climate can be the frequency of occurrence of any weather event such as lightning. In addition there are more complex statistical measures, such as standard deviation that measures the variation about the average, that can help define climate.

Climate can be the average relative humidity at a specific hour of the day or the number of days the relative humidity drops below a certain value. The number of days snow fall exceeds a given amount gives you an idea of the frequency of traffic snarls, while the number of hours the average wind exceeds a given value during a year may help decide about the placement of a wind-powered turbine.

Climate can be defined however you need it to be. You decide what weather variables affect your project and develop a climatology that describes what to expect. The average afternoon temperature for a given place may give you an idea of how comfortable the location is but including a humidity variable and wind speed will give you a better idea of the comfort climate.

If you are projecting the heating cost of locating a new office facility, you would want detailed information about lowest temperatures, how long the temperature is colder than a particular value, how sunny the location is, and how windy it is. Each weather variable is part of the natural gas for heating climatology, and each affects the demand for natural gas for heating.

In summer a residential cooling climatology would include the same variables as for heating along with a humidity variable to account for electrical power demand.

Think of it this way: weather is a rainy day, while climate is a rainy place. All US cities have rainy days, but Seattle has a rainy climate. Portland, ME, has occasional hot days, but Orlando, FL, has a hot climate.

THE CLIMATE MAPS

The 42 maps in this chapter represent a detailed picture, a climatology, of what you can expect over the long term in the lower 48 states.

The data were prepared and quality-controlled by the National Climatic Data Center (NCDC) of National Oceanic and Atmospheric Administration (NOAA) for the Climate Maps of the United States (CLIMAPS) database. The maps were redesigned and replotted for grayscale reproduction in this volume.

If you have experience with using or creating contour maps, you may be accustomed to having a fixed data interval between contour lines. That almost never works when creating climate maps because the distribution of climate is not regular and there are many factors that complicate how quickly values change. The contour intervals used here are the intervals chosen by the NCDC.

Figure 1.1 Mean annual minimum dew point temperature.

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Elevation is probably the most difficult complicating factor to deal with. When you examine the maps in this chapter, you will see how small some of the areas can be because of dramatic changes in climate over a short distance in mountainous terrain. For that reason it was decided not to use fill patterns because they can be very confusing when small areas are involved.

For most of the climate maps we opted to use a symmetrical shading scale ranging from white at the minimum value through medium–dark gray back to white at the maximum value. To the unaccustomed this may seem confusing, but it is standard practice in many science publications. There are a few geographical areas where maximum white and minimum white come close together, such as from the Central Valley of California into the Sierra Nevada Mountains. In areas such as this you will need to be careful to interpret the date correctly.

To help guide you in using the climate maps, many have specific values plotted for a contour or an area. Doing this is always problematic because map data can be obscured by the numbers. We carefully considered the placement of each and every number so as to minimize covering fine detail.

Not all the climate maps we prepared are in this chapter; many fit better in chapters on specific topics.

Climate maps covering sunshine, solar radiation, cloud cover, and wind variables are in Chapter 2, covering solar and wind renewable energy-generating technologies.

The climatology of US severe weather is in Chapter 4, with maps of tornado tracks, hail, and lightning occurrence, and the climatic information about Atlantic and eastern Pacific hurricanes is included in Chapter 5. There are maps dealing with specific aspects of past climate (paleoclimate) in Chapter 7. Extensive numerical information about 128 US cities is found in Chapter 10, while weather data for 321 locations outside the United States are found in Chapter 9.

Figure 1.2 Mean annual maximum dew point temperature.

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Figure 1.3 Mean January minimum dew point temperature.

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Figure 1.4 Mean January maximum dew point temperature.

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Figure 1.5 Mean July minimum dew point temperature.

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Figure 1.6 Mean July maximum dew point temperature.

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Dew Point Temperature

Notes: Dew point temperature is one of the many measures of humidity. It is defined as the temperature to which a mass of air must be cooled for condensation to begin or equivalently the temperature at which a relative humidity of 100% occurs when the air is cooled. It is a measure often used by forecasters, and the smaller the difference between dew point temperature and air temperature, the higher the relative humidity. When the dew point temperature equals the ambient air temperature, the relative humidity is 100%.

When the dew point temperature reaches 60°F, nearly everyone feels the humidity, and when the dew point temperature reaches 70°F, nearly everyone says the weather is sticky. Because of that, dew point temperature along with temperature is a primary predictor of energy usage for cooling.

Energy Use for Heating and Cooling

Figure 1.7 Mean annual number of cooling degree days.

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Figure 1.8 Mean annual number of heating degree days.

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Degree Days Maps

Notes: The terms cooling degree days and heating degree days are confusing and it is best to think of them as cooling units and heating units.

Using a base temperature of 65°F as the dividing point between the need for heating and the need for cooling, both heating and cooling degree days are the difference between the average daily temperature and the base temperature of 65°F. If the average temperature is warmer than 65°F, the difference in °F is the number of cooling degree days. If the average temperature is cooler than 65°F, the difference in °F is equal to the number of heating degree days.

Figure 1.9 Mean length of the freeze-free period.

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If the high temperature for a day is 80°F and the low is 66°F, the average for the day is 73°F, which is 8°F warmer than the base temperature of 65°F, so the day adds 8 cooling degree days to the running seasonal total.

The way degree days are calculated can lead to a significant error. For example, if at midnight it is 60°F and the temperature drops to 45°F at 1:00 A.M., then for the next 22 hours, the temperature hovers at 40°F; the average temperature for the day using only the high and low is 50°F, but using the 24-hourly temperatures yields an average of 41°F, an 18% difference. Whenever there is a large temperature change early or late in a day, large errors can occur when using only the daily high and daily low to calculate average temperature. For this reason many private utilities use hourly data in forecasting and tracking electrical loads and natural gas demands.

Figure 1.10 Earliest date of the first autumn freezing temperature.

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Figure 1.11 Mean date of the first autumn freezing temperature.

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Figure 1.12 Latest date of the last spring freezing temperature.

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Figure 1.13 Mean date of the last spring freezing temperature.

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Growing Season/Freeze–Thaw Maps

Notes: Traditionally, the growing season ends with the first-observed frost and begins again after the last frost. Frost can occur when the air temperature at thermometer height is as warm as 35°F–37°F, but because colder air is denser and settles to the ground, the temperature where the frost occurs is freezing or colder.

Figure 1.14 Mean annual number of days with measurable precipitation.

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Instead of the term growing season, freeze-free period is used, and it is defined as the number of days between the last spring freezing temperature and the first autumn freezing temperature. This use prevents confusion between the traditional definition and the one currently in use.

Just because a location reaches 32°F does not mean plant growth has stopped and plant damage has occurred. The length of time the temperature stays at or below a certain temperature threshold is also important. The freeze-free period gives a general indication of the length of the growing season, but crop-specific and site-specific information is required for practical application in agriculture.

Precipitation Maps

Notes: In the United States, measurable precipitation is defined as an amount of 0.01" or more.

Figure 1.15 Mean annual number of days with freezing rain or freezing drizzle.

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Figure 1.16 Mean annual total precipitation.

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Figure 1.17 Record annual total precipitation.

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Atmospheric Pressure (Sea Level)

Notes: Atmospheric pressure is always mathematically adjusted to what it would be at sea level the standard reference level in meteorology. Unadjusted pressure values are referred to as station pressure.

Figure 1.18 Mean annual minimum pressure.

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Figure 1.19 Extreme lowest pressure.

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Figure 1.20 Mean annual maximum pressure.

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Figure 1.21 Extreme highest pressure.

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Figure 1.22 Mean annual total snowfall.

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Snowfall Maps

Notes: In the United States, measurable snowfall is defined as a depth of 0.1" or more.

Figure 1.23 Record annual total snowfall.

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Figure 1.24 Mean annual number of days with snowfall of 0.1" or more.

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Figure 1.25 Mean annual number of days with snowfall of 1" or more.

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Figure 1.26 Mean annual number of days with snowfall of 5" or more.

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Figure 1.27 Mean annual number of days with snowfall of 10" or more.

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Figure 1.28 Median date of first measurable (≥0.1") snowfall.

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Figure 1.29 Extreme first date of first measurable snowfall.

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Figure 1.30 Median date of last measurable (0.1") snowfall.

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Figure 1.31 Extreme last date of last measurable snowfall.

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Figure 1.32 Probability of a white Christmas.

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Temperature

Figure 1.33 Mean annual number of days ≥90°.

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Figure 1.34 Mean annual number of days ≤32°.

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Figure 1.35 Mean annual minimum temperature.

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Figure 1.36 Mean annual maximum temperature.

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Figure 1.37 Extreme minimum temperature.

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Figure 1.38 Extreme maximum temperature.

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Figure 1.39 Mean January minimum temperature.

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Figure 1.40 Mean January maximum temperature.

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Figure 1.41 Mean July minimum temperature.

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Figure 1.42 Mean July maximum temperature.

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2

Renewable Energy

INTRODUCTION

The goal of this chapter is to summarize the wind power climate and the solar energy climate of the 48 contiguous states and provide the user with data regarding the feasibility of both solar power energy generation and wind power energy generation.

The material in this chapter could easily have been included in Chapter 1, but because of the specific nature of the information I have treated the wind and solar energy climates of the United States separately.

There are 97 figures, a combination of maps, and 132 graphs, in this chapter covering 44 cities. You will find a combination of annual maps covering the lower 48 states, and detailed wind roses, wind speed histograms, and solar energy graphs for specific locations.

RENEWABLE ENERGY

Of the renewable energy sources available the most well known are solar energy and wind energy. In addition, the US Department of Energy's National Renewable Energy Laboratory (NREL) lists geothermal, hydrogen (including fuel cells), and biomass as sources of renewable energy. Not listed by the NREL is tidal energy as a potential source in the future.

Weather and climate play a part in the utilization of any energy source for heating and cooling because of varying demand. Only wind and solar renewable energies are directly dependent on weather and climate for supply.

Definitions

Renewable energy is produced from natural processes that are replenished constantly. In most cases energy is derived directly from the sun, such as wind, solar, and biomass energy sources. Heat generated deep within the earth is also considered renewable, but it is not a product of solar radiation. Geothermal energy is largely the result of radioactive decay deep within the earth. Hydrogen as a fuel source is earth-based, also because water is its source.

Modern biomass energy production, also called bioenergy, involves processing plant materials to a more readily usable form such as a gas or liquid like ethanol. Directly burning wood continues to be the most common form of bioenergy worldwide.

Geothermal energy has been in use for thousands of years. Rome was famous for hot baths and heating small structures using geothermal heat. The modern approach to geothermal energy production involves generating electricity with turbines turned by steam. Geothermal energy production is growing slowly at 3% per year primarily because under present technologies, generation must take place near the sources that are tectonically active regions of earth. The largest geothermal power plant in the world, The Geysers, is located north of San Francisco in Sonoma and Lake Counties and has a generating capacity of 750 MW.

Tidal energy uses the power of incoming and outgoing tidal water to power generators. This source has also been used since Roman times to power mills. Tidal energy falls into two broad categories: the capture of the kinetic energy of water moving horizontally under the influence of tides and the capture of potential energy or water lifted in the tidal bulge. Tidal energy is the only energy source relying on the relative motions of the Earth and moon. Tidal energy production is rare because of infrastructure costs, potential environmental damage, and the lack of suitable sites.

Wind energy is the fastest growing of the renewable sources, with capacity in the United States growing at 30% per year. Worldwide generating capacity in 2008 totaled 121,000 MW. The modern approach to wind energy uses air flow to turn a wind turbine, also called an aerogenerator. If the mechanical energy is used directly by machinery for grinding grain or pumping water, for example, the term windmill is used.

Solar energy is the use of sunlight for power. The NREL lists five categories of solar energy production:

1. Concentrating solar power (CSP) technologies use parabolic reflectors to focus sunlight and concentrate the heat to boil water and drive a turbine. CSP technologies are realized as expensive projects that require large investment and therefore designed as large-scale electrical distribution systems in much the same way as traditional coal- or oil-based electrical power generation. Because of the expense CSP facilities are limited to the sunniest parts of the country.

2. Photovoltaic (PV) technology is the most well-known solar energy technology. Sunlight generates electricity using the PV effect, which was discovered in 1954. First-generation solar cells used silicon flat plates and are what most people think of when referring to solar energy production. Second-generation cells involve thin-film technology that can be used to make roof shingles as collectors and thus overcome the esthetic objections to solar panels. Third-generation solar technology uses materials other than silicon alone to more efficiently capture solar energy. Because PV technology is modular and individual modules are relatively inexpensive when compared to CSP technologies, PV technology is well suited for individual residences.

3. Passive solar technology involves building designs that allow or promote daytime heating of walls and spaces through exposure to sunlight.

4. Solar water heating is simple, water exposed directly or within a collector to sunshine is heated and stored for future use in an insulated tank.

5. Solar process heating refers to the use of a variety of technologies in industrial buildings. Some of the technologies are too expensive for residential uses, but solar process heating encompasses the use of PV technology, the primary residential solar energy technology.

SOME HISTORY OF WIND MEASUREMENT

In 1805, before anemometers were invented to measure the wind speed, British Admiral Sir Francis Beaufort created a scale named after him. The first version gave a qualitative description of the effect of the wind on the sails on a man of war. There were 13 classes ranging from just sufficient to give steerage to that which no canvas sails could withstand.

In the 1830s, reporting the Beaufort Scale became standard practice in the British Navy. In the 1850s, the scale was adapted for land use, with scale numbers corresponding to anemometer cup rotations. At this time anemometers did not display wind speed.

As steam power supplanted sails the Beaufort Scale was changed in 1906 to reflect the character of the sea, not the state of the sails. In 1923, anemometer cup rotations were standardized and land-based descriptions were added. In 1946, forces 13–17 were added for special cases such as tropical cyclones. Today the Beaufort Scale has been nearly abandoned for measured units of meters per second, kilometers per hour, nautical miles per hour (knots), and miles per hour. The modern Beaufort Scale is found in Table 2.1.

WIND ENERGY POTENTIAL IN THE UNITED STATES

Wind energy potential is highly variable from place to place and also highly variable in any one place from time to time. The latter is termed the intermittency problem because wind-generated power, even in the most reliable locations, will at times be unavailable. In general, areas with the greatest wind potential are where some factor, often terrain, influences the speed of the wind.

But wind speed is not the only variable that makes a place good or bad for producing wind energy. A place with a reliable, more constant wind may produce more energy than one with higher speeds and less consistency. The suitability of any location for generating wind energy is the product of the complex interaction of many factors that vary at a very small scale. A good location for a wind turbine may not be obvious from casual inspection.

Because wind speed generally increases with height above the surface, wind energy potential is calculated above the surface. Common values used to estimate wind power density are 10 m (33 feet), 30 m (98 feet), and 50 m (164 feet) above ground level.

Because most wind measurements are made near the surface, wind power density estimates apply a rule of thumb called the wind profile power law or the one-seventh power law. This relationship works well over unobstructed ground in stable atmospheric conditions, but over open water/very rough ground or over areas with numerous obstructions to low-level air flow, the error can be substantial.

Better estimates can be made using the log wind profile equation that includes input for surface roughness and stability. When these are missing, which is quite often, the wind profile power law is used.

Table 2.2 shows the wind power density in watts per square meter at 10, 30, and 50 m above ground level. The associated wind speeds in both meters per second and miles per hour calculated (estimated) from the wind profile power law are listed. They are classified using the US Department of Energy's wind potential classification.

Superb potential for wind power generation (800–1600 W/m−2) at 50 m above ground level is hard to find. Superb potential is most often found in isolated areas of the Great Plains, coastal areas, and high mountain passes. Electricity from wind can be generated at other areas, but it may not be economically feasible on a large scale. Most of the Great Plains and foothills of the Rocky Mountains are rated as having good or better potential.

The maps and tables in this chapter present a general wind climatology of the contiguous 48 states. Wind roses and wind speed frequency histograms are included for 33 cities along with annual national maps of average wind speed, the occurrence of peak gusts at three limits, and the fastest mile of wind.

The wind speed climatology of a place is also important as input in building and structure design, including towers for capturing wind energy. Modern standards are moving away from the fastest mile as a building standard and toward the 3-s wind gust with a 2% annual occurrence, the same as a 50-year recurrence interval.

Table 2.1 The Modern Beaufort Wind Scale

Table 2.2 Estimates of Power Density and wind Speed at Three Altitudes Above Ground Level Using the Wind Profile Power Law.

The fastest mile of wind is measured in miles per hour and is the fastest average wind speed during the period of 1 min that is observed during the time period required for the air to travel 1 mile past the anemometer. The fastest mile is always slower than the 3-s wind gust.

Table 2.3 provides the approximate conversion from fastest mile to 3-s wind gust according to the International Building Code.

Figure 2.1 shows the wind energy potential at 50 m above ground level of the United States as estimated by the US Department of Energy. Notice how large parts of the country, especially the east and south, have little potential as sites for generation of wind energy.

Figures 2.2–2.6 are maps that show the wind climate of the United States using traditional measures. Figure 2.2 shows the average wind speed in miles per hour; Figures 2.3–2.5 show the occurrences of wind gusts exceeding 30, 40, and 50 mph, respectively; and Figure 2.6 shows the fastest mile of wind for the 48 lower states. Notice the similarities between Figure 2.1 and Figures 2.2–2.6.

Included in this chapter are wind roses and wind speed frequency bar graphs (histograms) for 44 locations in the lower 48 states (Figures 2.7–2.50). It is important to realize two factors when using this information: (1) most of these are near-surface velocities, so wind speed at turbine level will be faster, and (2) local variations in exposure and topography can drastically alter the availability of wind power.

Table 2.3 Conversion from Fastest-Mile Wind Data to 3-Second Gust Wind Data

Figure 2.1 National wind parameter map.

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Figure 2.2 National wind parameter map.

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Figure 2.3 National wind parameter map.

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Figure 2.4 National wind parameter map.

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Figure 2.5 National wind parameter map.

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Figure 2.6 National wind parameter map.

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Figure 2.7 City wind roses and wind speed frequency histogram.

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Figure 2.8 City wind roses and wind speed frequency histogram.

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Figure 2.9 City wind roses and wind speed frequency histogram.

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Figure 2.10 City wind roses and wind speed frequency histogram.

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Figure 2.11 City wind roses and wind speed frequency histogram.

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Figure 2.12