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Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks (2009)

Chapter: Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena

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Suggested Citation:"Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena." National Research Council. 2009. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. Washington, DC: The National Academies Press. doi: 10.17226/12540.
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Suggested Citation:"Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena." National Research Council. 2009. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. Washington, DC: The National Academies Press. doi: 10.17226/12540.
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Suggested Citation:"Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena." National Research Council. 2009. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. Washington, DC: The National Academies Press. doi: 10.17226/12540.
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Suggested Citation:"Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena." National Research Council. 2009. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. Washington, DC: The National Academies Press. doi: 10.17226/12540.
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Suggested Citation:"Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena." National Research Council. 2009. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. Washington, DC: The National Academies Press. doi: 10.17226/12540.
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Suggested Citation:"Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena." National Research Council. 2009. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. Washington, DC: The National Academies Press. doi: 10.17226/12540.
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Suggested Citation:"Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena." National Research Council. 2009. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. Washington, DC: The National Academies Press. doi: 10.17226/12540.
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Suggested Citation:"Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena." National Research Council. 2009. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. Washington, DC: The National Academies Press. doi: 10.17226/12540.
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Suggested Citation:"Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena." National Research Council. 2009. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. Washington, DC: The National Academies Press. doi: 10.17226/12540.
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Suggested Citation:"Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena." National Research Council. 2009. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. Washington, DC: The National Academies Press. doi: 10.17226/12540.
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Suggested Citation:"Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena." National Research Council. 2009. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. Washington, DC: The National Academies Press. doi: 10.17226/12540.
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Suggested Citation:"Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena." National Research Council. 2009. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. Washington, DC: The National Academies Press. doi: 10.17226/12540.
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Suggested Citation:"Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena." National Research Council. 2009. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. Washington, DC: The National Academies Press. doi: 10.17226/12540.
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Suggested Citation:"Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena." National Research Council. 2009. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. Washington, DC: The National Academies Press. doi: 10.17226/12540.
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Suggested Citation:"Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena." National Research Council. 2009. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. Washington, DC: The National Academies Press. doi: 10.17226/12540.
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Suggested Citation:"Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena." National Research Council. 2009. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. Washington, DC: The National Academies Press. doi: 10.17226/12540.
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Suggested Citation:"Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena." National Research Council. 2009. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. Washington, DC: The National Academies Press. doi: 10.17226/12540.
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Suggested Citation:"Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena." National Research Council. 2009. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. Washington, DC: The National Academies Press. doi: 10.17226/12540.
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Suggested Citation:"Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena." National Research Council. 2009. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. Washington, DC: The National Academies Press. doi: 10.17226/12540.
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Suggested Citation:"Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena." National Research Council. 2009. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. Washington, DC: The National Academies Press. doi: 10.17226/12540.
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Suggested Citation:"Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena." National Research Council. 2009. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. Washington, DC: The National Academies Press. doi: 10.17226/12540.
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Suggested Citation:"Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena." National Research Council. 2009. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. Washington, DC: The National Academies Press. doi: 10.17226/12540.
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Suggested Citation:"Appendix A: A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena." National Research Council. 2009. Observing Weather and Climate from the Ground Up: A Nationwide Network of Networks. Washington, DC: The National Academies Press. doi: 10.17226/12540.
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Appendixes

Appendix A A Rationale for Choosing the Spatial Density and Temporal Frequency of Observations for Various Atmospheric Phenomena The question is perennial: “How many observations do I need, and how dense and how frequent?” The honest answer is “It depends upon the application.” This appendix deals with a single but very important applica- tion: observational support of the national infrastructure for weather and climate monitoring and numerical weather prediction. Even for this single application area, the answer to the question depends upon the phenom- enon: its size and longevity, which governs its predictability, and whether it has any embedded features that cause localized damage. Consideration of the phenomena is roughly in the order of size/longevity. The list is neither definitive nor exhaustive, but it does cover events that cause the greatest disruption, damage, and loss of life. FLOODING FROM LARGE-SCALE STORMS Definition: Steady soaking rains, sometimes with embedded showers and thunderstorms, cause flooding of small streams and larger rivers. Rain fall- ing on melting snow exacerbates the flooding. Size: Typically 300-2000 km across. Duration: half a day to several days Geographic preference: West Coast, Southern Plains, Lower Midwest, A ­ ppalachians. Rapid melting of a heavy snow cover, especially when accom- panied by rainfall, sometimes causes floods in the northern United States, 187

188 APPENDIX A for example, the Red River flood at Grand Forks, North Dakota, in April 1997 or flooding from Ohio to New England during the January thaw of 1996. Floods can create health risks to humans and the local ecology due to the biological and chemical constituents in flood drainage that otherwise would not be present. Because these storms are large, typically 1000 km in diameter, they are rather well observed over land. Those that cause flooding and landslides along the West Coast, as in January to February 2005, are almost always centered offshore. Occasionally, however, a long plume of moisture in southwesterly flow will cause soaking orographic rains along the ­California coastline without the presence of a well-defined cyclonic circulation. In either case, more in-situ observations are needed within a few hundred k ­ ilometers of the coast, especially of temperature, wind, and moisture below 600 mb, to supplement satellite observations. In-situ observations inside of cloud systems within a day or so of reaching the West Coast would also be very helpful. Mesoscale features within the storm circulation often mark the difference between merely soaking rains (say, 0.20 inches per hour) and serious flood- ing (>0.50 inches per hour, prolonged). In many parts of the country, tropo- spheric wind observations, especially within cloudy areas, are too far apart to resolve these details. Moisture observations, especially below 600 mb, where most atmospheric moisture is concentrated, are sparse. For these mesoscale features, lower tropospheric soundings at ∆x=50 km, ∆z=200 m, and ∆t=3 h resolution are appropriate. ∆x refers to horizontal spacing, ∆z to vertical spacing, and ∆t to temporal frequency. For longer forecasts than those considered here, the Winter Storm Recon- naissance Program in the North Pacific Ocean provides targeted aircraft observations. These benefit the entire country but especially the West. NOR’EASTERS Definition: A Nor’easter is a large cyclonic storm occurring from late fall through spring that moves northeastward along the U.S. Atlantic coast or a few hundred kilometers offshore. Sometimes intensifying rapidly, Nor’easters bring strong onshore winds, often from the northeast (hence the name), storm tides, flooding, and heavy precipitation. For practical purposes, a Nor’easter may be considered an Atlantic coastal storm accom- panied by an onshore component of the wind of at least 40 mph for at least 12 hours.

APPENDIX A 189 Size: Typically 500-2000 km across. Duration: 0.5-4 days Geographical preference: Atlantic Coast, most often between Cape ­Hatteras, North Carolina, and Eastport, Maine. Several Nor’easters typically occur during each cold season. These storms are mentioned separately because the principal form of dam- age is due to coastal flooding and beach erosion resulting from the storm surge. (It is acknowledged that some West Coast storms also cause beach and headland erosion.) Along the Atlantic Coast, the typical beach erosion rate is 1-3 ft per year, but a severe Nor’easter can erode the coast inland 100 ft in just 24 hours (FEMA, 2000, Fig. 1.1 and p. xxvii). That the coast- line can accrete partway back within a decade or so is small consolation to homeowners in the path of the storm surge. Of course, Nor’easters can also produce heavy rains, strong wind, and if the temperature is low enough, blizzards. For a thorough survey of North- east snowstorms, including Nor’easters, see Kocin and Uccellini (2004). The most difficult to predict aspect of these storms is explosive deepening, which can reach 8-10 hPa per hour. Details in the sea-surface temperature in the vicinity of the Gulf Stream, strong latent heating in deep cloud sys- tems, and the movement of potent upper air disturbances seem to govern the deepening (see, for example, Wang and Rogers, 2001 or Mailhot and Chouinard, 1989). Accurate sea-surface temperature within a day of deep- ening at ∆x~10-km, and 3-h sounding data at ∆x=100 km within 500 km of the storm center with ∆z= 0.3 km up to 12 km would probably improve the prediction of these events. SNOWSTORMS AND ICE STORMS Definition: These storms include any storm depositing enough snow or ice to disrupt road or air travel, communications, or the electrical power supply. An ice storm occurs when liquid precipitation falls at surface tem- peratures below freezing. Size: Snowstorms and ice storms cause problems in swaths typically 10 to 200 km wide and 50 to 1000 km long. Duration: 2 hours to 2 days Geographic preference: With the exception of mountainous areas, the great-

190 APPENDIX A est frequency of major snowstorms occurs east of the Rocky Mountains and north of about 35°N. Included here are snowstorms that deliver large liquid water equivalents but also “drier” storms associated with high winds and low temperatures. Also included are lake-effect snowstorms, the best known occurring downwind of the Great Lakes in fall and early winter, that bring crippling amounts of snow in narrow swaths. According to Changnon (2003), the greatest risk of damage and financial loss from ice storms exists in the Northeast U.S. followed by the lower Midwest and the Southern Great Plains. Both snow and ice storms disrupt daily commerce and transportation, but ice storms commonly pose the additional hazard of power outages with all the collateral damage that implies, and damage to the power distribu- tion infrastructure. The cost of major winter storms can be very high. In the March 1993 Superstorm, newspaper estimates of damage ranged from $1 billion to $6 billion and fatalities from 200 to 300. A National Climatic Data Center Report on the January 1996 blizzard and subsequent flood in the mid-Atlantic and northeast states cited insurance losses of nearly $1 billion and 187 fatalities. The key to good forecasts for most of these storms is accurate location of frontal zones in three dimensions and detailed knowledge of the wind, temperature, and moisture fields within the storm, particularly if these suggest the potential for embedded convection. Knowing the altitude of single or multiple freezing levels is critical. If this information is available, there is a much better chance of predicting precipitation type and amount, and the boundaries between snow, sleet, freezing rain, and rain. Forecast errors of just a few tens of kilometers in the position of these boundaries can have serious consequences, especially in heavily populated areas. See, for example, the report on an over-forecast of snow for the Washington, D.C., and Baltimore, Maryland metropolitan areas on December 30, 2000 (Petersen and McQueen, 2001). Lake-effect snowstorms are a special case. Knowledge of lake surface tem- perature, the temperature profile up to 700 mb in the cold air mass advanc- ing across the lake, and the fetch of the wind across the water (wind direction is crucial) is key for a good forecast. Temperature, wind, and moisture soundings up to 500 mb are desirable within and surrounding the precipitation zone at ∆x=30 km, ∆z=100 m, and ∆t=2 h.   See http://www.ncdc.noaa.gov/oa/reports/billionz.html.

APPENDIX A 191 LANDFALLING HURRICANES AND TROPICAL STORMS Definition: Hurricanes are powerful cyclonic storms that pose multiple threats: high winds (74 mph or greater) causing structural damage, storm surge causing coastal flooding, and excessive rains causing inland flooding after landfall. Tropical storms (winds from 39-73 mph) are less powerful but still cause damage. Size: Gale force winds (>39 mph) have been observed within diameters as small as 100 km and as large as 2000 km. Duration: 1 day to more than a week Geographic preference: On one of its webpages, the Hurricane Research Division of NOAA’s Atlantic Oceanographic and Meteorological Labora- tory maps the probability that the center of a hurricane will approach to within 110 km of a given location within a single hurricane season. The probability appears to be a little less than 10 percent along most of the Gulf Coast and the Atlantic Coast north to Cape Hatteras, with the exception of southern Florida, where the maximum probability is about 16 percent. The probability is lower north of Cape Hatteras. Tropical storms are virtually unknown along the West Coast, though remnants sometimes move north- ward into the southwest United States from the Baja region. Hurricane circulations are large, often 1000 km across, but the diameter of damaging winds is often less than 100 km. Hurricanes last from days to weeks over warm ocean water, but high winds invariably diminish rapidly after landfall. This report deals only with hurricanes and tropical storms close to landfall and with storms making the extratropical transition after landfall, because the hazards are greatest during this time. Hurricane track forecasts have become ever more skillful, but rapid changes in intensity are still very difficult to anticipate. It is likely that changes in the underlying surface (sea-surface temperature and the depth of the 27°C isotherm, subtle changes in the hurricane’s environment, reorganization of the internal structure, or a combination of these govern changes in intensity. Better observations can clarify which mechanisms are the most important. It is noteworthy that dropsondes that enter the hurricane core are not yet assimilated into operational forecast models. Numerical prediction models often become less skillful during the extra-   See http://www.aoml.noaa.gov/hrd/tcfaq/h_prob.gif.

192 APPENDIX A tropical transition, as the tropical cyclone encounters any combination of the following: frontal zones and increased vertical shear, upper-level trough, moisture gradients, gradients in sea-surface temperature, increased surface drag after landfall, increased Coriolis force as the center of circulation moves poleward, and complex topography. See the review paper by Jones et al. (2003) for more details. Aberson (2003) documented substantial improvements in track forecasts out to several days when targeted dropsonde observations were made in regions where sensitivity of the forecast to initial conditions was high. The National Centers for Environmental Prediction determine the targeted area by means of the “breeding” method, which employs an ensemble of forecasts. The targeted area must be well sampled by the dropsondes. The use of additional observations taken outside the targeted area in the initial conditions did not lead to further improvements in the forecast. The foregoing considerations suggest that further improvements in forecasts of track and of the extratropical transition will require targeted sound- ing data throughout the depth of the troposphere at roughly 100-150 km spacing and 6-h frequency. To uncover the mechanisms of tropical cyclone intensification and weakening, it may be necessary to sound the full depth of the hurricane core (nominal radius of 100 km from the eye) at resolu- tions of ∆x=10 km, ∆z=200 m, and ∆t=3 h. The challenge will be to obtain measurements starting from above the cloud shield, which in intense hur- ricanes can reach to 100 hPa and above. AIR POLLUTION Definition: air pollution is the presence of gases or particles in the air, resulting mostly from human activity but sometimes occurring naturally (e.g., pollen), that cause health problems, directly (e.g., difficulty in breath- ing) or indirectly. As an example of an indirect effect, chemical compounds called chlorofluorocarbons were widely used as refrigerants, propellants in aerosol cans, and cleaning solvents. In gaseous form, these substances slowly diffused upward into the stratosphere, where, under conditions of very low temperature and sunlight, they participated in chemical reactions that depleted ozone, especially at high latitudes. Because ozone absorbs ultraviolet radiation from the sun, a reduction in stratospheric ozone allows more ultraviolet radiation to reach the Earth’s surface, thus increasing the incidence of skin cancer—an indirect effect on human health caused by a manufactured gas. Size: Pollution can be a problem within a single, heavily industrialized

APPENDIX A 193 valley on scales of tens of kilometers, and it can be a regional problem on scales exceeding 1000 km, when the sources are widely distributed or the wind mixes the pollutants over a wide area. Duration: hours to several days Geographic preference: Large cities and heavily industrialized areas. Regional pollution is also a problem, especially in the Northeast Urban Corridor and in the southeast United States (mostly summer). Atmospheric pollutants concentrate in stagnant air masses. Persistent inver- sions trap the pollutants close to the ground, where high concentrations pose a health problem. During the day, the pollutants reside in the mixed layer. The depth of this layer is critical: the shallower the mixed layer the greater the potential for high concentrations. At night, pollutants in the residual mixed layer are available for longer-range transport, and winds within this layer contribute strongly to regional pollution in the Northeast. Pollutants emitted at night are confined to the ground-based stable layer, but they interact with the aged pollutants when the boundary layer grows again the next day. Taking inventory of pollution sources and measuring the concentration of each major pollutant are fundamental requirements. Measurements that relate to the dispersion of pollutants are equally important: high-resolution measurements (∆x=5 km, ∆z=50 m, and ∆t=15 min within cities) of wind and temperature are essential for gauging the depth of the mixed layer and tracking the drift of the pollution plume. Outside metropolitan areas, ∆x could probably be relaxed to 20-30 km and ∆t to 30 min, but this may not be sufficient near lakeshores or the seacoast, where the meteorology is com- plicated by land and sea breezes. These requirements pertain to the surface- based stable layer and the deeper mixed layer, where the pollutants reside. The toll in human health from fine-particle air pollution (referred to as PM2.5—particulate matter with a diameter 2.5 micrometers or less) is slowly being realized, and it is potentially staggering. “Hundreds of studies have suggested that breathing fine particles spewed by vehicles, factories, and power plants can trigger heart attacks and worsen respiratory disease in vulnerable people, leading to perhaps 60,000 premature deaths a year in the United States” (Kaiser, 2005, p. 1858). One of these studies (Cifuentes et al., 2001) argued that a reduction in greenhouse gas emissions would result in a corresponding reduction in particulate matter. If greenhouse gas mitigation technologies reduced particulate matter and low-level ozone concentrations by just 10 percent in four large cities (Mexico City, Sao

194 APPENDIX A Paulo, Santiago, and New York City—combined population 45 million), the authors estimated that 64,000 premature deaths and 65,000 chronic bronchitis cases could be avoided from 2001 through 2020. Improving the air quality by reducing emissions is one way to avoid the health costs of air pollution. Reducing exposure to existing pollutants is another, and that is possible through enhanced observations and improved forecasts of air quality. FOG AND LOW CLOUDS Definition: By the time cloud base descends to 500 ft or fog lowers surface visibility to 1 mile, restrictions on air traffic into and out of most airports have already been imposed. Conditions this bad or worse are the focus of discussion here. Size: Highly variable, typically from tens to hundreds of kilometers. Duration: most common from early to mid-morning, typically lasting from an hour to more than a day Geographic preference: No part of the United States is immune from fog, but the most persistent fog occurs during the wintertime in basins (e.g., central valley of California, Salt Lake Valley). Fog and marine stratus are also common in coastal regions, where large population centers exist. Limited surface visibility can be a significant hazard to all forms of trans- portation including automobile traffic, the trucking industry, rail traffic, and marine interests, and to aircraft landings and takeoffs. In the 1980s alone, there were more than 6000 highway deaths attributed to fog (source: U.S. Department of Transportation). In addition, low ceilings impede ­traffic flow into and out of major airports by curtailing side-by-side landings when parallel runways are within 2500 ft of each other. This is the case in San Francisco, where marine stratus can cut landings by 50 percent when ceil- ings are below 3000 ft. It is just as important to predict the onset of dense fog (visibility less than ¼ mile for surface-based operations and less than 1 mile for marine interests) as to predict the dissipation. It is critical to know the height of the inversion layer and the strength of the inversion in order to predict dense fog or the height of a low cloud base. To predict dissipation, it is also important to know the thickness of the fog bank or lower cloud layer, and whether higher cloud layers are present.

APPENDIX A 195 Temperature and moisture measurements are required up to 2000 m above ground at ∆x=25 km, ∆z=30 m, and ∆t=15 min to resolve mesoscale varia- tions in inversion depth and strength especially in complex terrain. It is important to know cloud cover above 2000 m. THUNDERSTORMS The multiple hazards posed by thunderstorms are discussed separately below. Unlike phenomena discussed so far, thunderstorms have short life- times (almost always less than 6 h for a given cell and sometimes less than 30 min), they can merge into clusters, and their outflows can interact with each other or with terrain to spawn new thunderstorms. With high- resolution measurements, some classes of thunderstorms, those with strong dynamical forcing, can be accurately predicted. Thunderstorms resulting from gust-front interactions in the boundary layer, along stationary low- level convergence zones, or within horizontal convective rolls are much less predictable, even with good measurements. See, for example, Weckwerth (2000) or Wilson et al. (1998). Lightning Definition: Lightning is a transfer of electrical charge through often branch- ing channels in the atmosphere that causes a bright flash of light. The primary concern is with cloud-to-ground lightning, which causes the most damage. Size: The lightning stroke itself is a few centimeters in diameter and often kilometers long, but emphasis here is on the aggregate of strokes produced by a thunderstorm cell. Thus, the horizontal dimensions of interest are roughly from 1-20 km. Duration: the duration of a single stroke is less than 0.1 millisecond, but the main threat from multiple strokes within a single thunderstorm typically lasts from a few minutes to nearly an hour Geographic preference: Anywhere thunderstorms occur, but see map (Orville and Huffines, 2001) giving the number of cloud-to-ground strikes per square kilometer across the country 1989-1998. The greatest strike density is in the southeast quadrant of the United States. Cloud-to-ground lightning is a clear threat to life and property, not to mention that it starts many forest fires. In fact, huge economic losses occur when “dry” lightning starts forest fires in the West and Alaska. In

196 APPENDIX A one 5-year period, 66,000 lightning-caused fires burned over 20 million acres. Property damage from lightning is also significant. State Farm Insur- ance alone processes more than 300,000 lightning-related claims annually, amounting to loss reimbursements of over $300 million. A number of commercial lightning detection systems are available, but they give warning only after the first stroke has occurred. Avoiding the lightning hazard entirely depends upon an accurate prediction of thunderstorm devel- opment, and that, in turn, depends upon mesoscale observations of wind, temperature, and moisture, especially in the boundary layer. For short-term prediction of thunderstorm initiation, observations of wind, temperature, and moisture are needed at ∆x~2 km, ∆z~100 m from the surface to the top of the boundary layer, and ∆t~15 min. The top of the boundary layer (also called the well-mixed layer) is itself defined by high- resolution temperature or refractivity measurements. Flash Floods Definition: A flash flood is a sudden rise in water, often in places where deep or rushing water is unexpected, caused by excessive rainfall. The flooding occurs within 6 hours of the causative rainfall. Size: The area of excessive rainfall is often only a few kilometers wide, but the flood can propagate downstream for tens of kilometers. Duration: 30 min to several hours Geographical preference: Flash floods favor steep terrain, especially where the ground is relatively impermeable or the soil is already saturated. How- ever, rainfall of several inches within an hour can cause flooding almost anywhere. Some flash floods are caused when a thunderstorm becomes anchored to the terrain. Others occur when cells within a line of storms move parallel to the line itself, and this happens most often within a nearly stationary zone of low-level convergence. Still others occur in connection with “mesoscale convective systems,” clusters of thunderstorms that form more often at   Derived from the Fire and Aviation Management Web Applications Database in ­Kansas City, Missouri, by Heath Hockenberry in Predictive Services, National Interagency Fire Center.   See http://www.lightningsafety.com/nlsi_lls/nlsi_annual_usa_losses.htm.

APPENDIX A 197 night than during the day. Flash floods cause more deaths per year in the United States than any other convective storm phenomenon. One predictor of heavy rainfall is vertically Integrated Precipitable Water (IPW), but flooding rains often deliver more than the amount of IPW even within 1 hour. The flux of vapor into the thunderstorm and the rate of condensation within the updraft control the amount of precipitation, and this, in turn, depends upon atmospheric instability, the strength of the wind importing moisture laterally toward the storm, and the amount of water vapor it carries. Good predictions of excessive convective precipitation thus depend upon • temperature and moisture profiles within an hour of storm forma- tion and approximately within the same air mass as the storm forms (as a measure of the potential instability). Resolution: ∆x=50 km, ∆z=200 m at least up to 200 mb, ∆t=60 min, and detailed terrain elevation measurements (easy to obtain down to 1-km resolution). • wind and moisture measurements in the sub-cloud layer. Except in the case of elevated thunderstorms (seldom a cause of flash flooding), most of the air participating in the updraft is drawn from the sub-cloud layer. In flash-flood situations, the cloud base is usually lower than the climatologi- cal normal; in fact, it is often lower than 1500 m. A cloud base temperature of 10°C or higher is an indicator of high precipitation efficiency; the consid- erable depth of cloud below the freezing level aids the “warm rain” process (formation of many large drops by collision and coalescence) (Davis, 2001, p. 491). Nominal resolutions for wind and moisture measurements in the sub-cloud layer are: ∆x=20 km, ∆z=100 m, ∆t=15 min. This requirement holds only in the inflow region of the storm, probably not beyond 100 km out. A common element in many excessive rainfall events is the “low-level” jet, a ribbon of high-speed air 100-200 km wide and 1-2 km deep bring- ing moisture-laden air, most often from the Gulf of Mexico but sometimes from the Pacific or Atlantic Oceans, either into the storm genesis region or the storms themselves, once formed. A sub-class of the low-level jet is the “nocturnal jet,” which forms at night over the gently sloping terrain of the southern and central Great Plains. The horizontal and vertical dimensions of the low-level jet demand measurements at ∆x=30 km in the direction perpendicular to the jet but only 100 km along the jet. A ∆z of 200 m up to 3 km and a ∆t of 2 h is probably sufficient.   NOAA Natural Hazard Statistics, http://www.nws.noaa.gov/om/hazstats.shtml.

198 APPENDIX A Hailstorms Definition: Hail is a ball of ice that develops and is suspended within a thunderstorm updraft that contains both liquid and frozen particles at tem- peratures below freezing. A hailstorm is a fall of hail that causes damage or injury on the ground. Size: Hailstorms typically range from 0.5 to 10.0 km in size. Duration: hailstorms typically last from a couple of minutes to tens of minutes Geographical preference: The greatest incidence of hail lies near the west- ern edge of the Great Plains from Wyoming to New Mexico. Winter hail, invariably small, is also frequent along the Pacific Northwest Coast, but hail volume and hail size is a much better indicator of hail losses than hail frequency. Changnon (2001, p.70) maps the “loss cost” due to hail across the United States, which is the dollar amount of crop losses over a speci- fied period divided by the dollar amount of insured liability, multiplied by $100. The maximum ($6-$9) stretches from southeast Montana southward through eastern Wyoming, eastern Colorado, and eastern New Mexico. A secondary maximum is in South Carolina, where tobacco is grown. Tobacco is very easily damaged, even by relatively small hail. Large hail causes property damage (in individual storms up to hundreds of millions of dollars) though very seldom loss of life. The greatest incidence of 2-inch hail is in the central Great Plains from South Dakota to Texas. The greatest risk of property damage from hail is in roughly the same area (Changnon, 1999). Hail forms in thunderstorms whenever liquid and ice are present within a cloud volume at sub-freezing temperatures. Whenever an ice particle cap- tures a cloud or rain droplet, the liquid freezes to the ice particle, making it larger. The updraft suspends the hail within the cloud while the hailstone grows. Since large hail falls faster than small hail, stronger updrafts are necessary for the generation of larger hail. Radars are good at detecting hail within a storm, but there is little skill in predicting whether a given thunderstorm will produce large hail, even when conditions seem favorable. What combination of cloud physics and dynamics controls hail growth is still mostly a mystery (Knight and Knight, 2001), but it is clear that convective available potential energy, a measure of atmospheric instability that is correlated with maximum updraft speed, and vertical wind shear, which governs whether or not the precipitation shaft

APPENDIX A 199 chokes the updraft, are important. Given this situation, the requirements given in the two bullets of the section on flash flooding seem appropriate. One exception to this is hail two inches or larger, almost always associated with supercell thunderstorms. For very large hail, the resolution criteria suggested for tornadoes (later in this appendix) are appropriate. The height of the minus 20°C isotherm and the level at which the wet bulb temperature is 0°C may be diagnosed from the sounding data. These parameters are related to the probability that hail will reach the ground before melting. Straight-Line Damaging Winds Definition: In this section, we restrict attention to two specific types of damaging straight-line winds that accompany thunderstorms: (1) those associated with a bow echo, an echo on a display of radar reflectivity that bulges out ahead of other echoes within a line of echoes and (2) a derecho, a thunderstorm producing a long path of damage caused by strong straight- line winds. Size: The damage swath is usually just a few kilometers wide but ranges from a few to more than 100 km long. Duration: a few minutes to more than an hour Geographical preference: A 4-year climatology of cold-season bow echoes over the continental United States shows them confined to east of the Rocky Mountains and south of 45°N (Burke and Schultz, 2004). A longer climatology of derechos covering all seasons from 1986 to 2001 (Coniglio and Stensrud, 2004) shows a corridor of high frequency from the upper Mississippi River valley to Ohio in the warm season. The bow echoes responsible for damaging winds most often form in an environment of strong low-level shear in association with a convective line. Not infrequently, counter-rotating vortices appear at either end of the bow, both helping to accelerate the air forward in the bow itself. Low-level instability tends to be moderate in cases strongly forced by atmospheric dynamics but high in weakly forced cases. An elevated rear-inflow jet of dry air is often present in lines that produce bow echoes. The hodograph associated with bow echoes (and squall lines more generally) is usually straighter (the shear is closer to unidirectional) than the hodograph associ- ated with supercells. These generalizations suggest what features to look for in the pre- t ­ hunderstorm environment, but trying to predict even an hour in advance

200 APPENDIX A which cells will develop bow echoes is largely fruitless. To understand the internal circulations that lead to bow echoes would require observations on the scale of ∆x=1 km, ∆z=100 m, and ∆t=5 min. Tornadoes Definition: A tornado is a violently rotating column of air that makes a connection between a convective cloud and the ground. A funnel-shaped cloud usually (but not always) accompanies the tornado. Tornado strength is rated on a scale originally proposed by Tetsuya Fujita and named after him. An Enhanced Fujita (EF) scale was formulated by a team of meteo- rologists and wind engineers and introduced by the U.S. National Weather Service on February 1, 2007. The scale ranges from EF0 (causing minor damage) to EF5 (causing almost total destruction). Size: Typically from tens of meters to more than a kilometer in diameter. Duration: from less than a minute to more than an hour Geographical preference: Concannon et al. (2000) present a U.S. map showing the mean number of days per century with at least one tornado, F2 intensity or greater, touching down in a grid box 80 km on a side. The maximum of 40 days exists just southeast of Oklahoma City, but the 25-day contour includes most of Oklahoma, the eastern two-thirds of Kansas, southeast Nebraska, southwest Iowa, northwest Missouri and west central Arkansas. Few F2 or greater tornadoes occur west of the Rocky Mountains or east of the Appalachians. Two classes of tornadoes are distinguished here: supercell and non-supercell. Supercell thunderstorms have strongly rotating updrafts. The probability that a supercell thunderstorm will spawn a tornado is probably no more than 20 percent, and yet it is true that most strong or violent tornadoes (F2 or greater) originate in this way. Weisman and Klemp (1984) defined a Bulk Richardson Number (a mea- sure of atmospheric instability divided by a measure of vertical shear from the surface to 6 km) that distinguished rather well between thunderstorm types in a storm-scale model. This number is easily calculated from sound- ing data. Values between 15 and 45 favor supercell thunderstorms. Other good predictors of supercells are the wind shear in the lowest 6 km and the   The map is on the Web at http://www.nssl.noaa.gov/users/brooks/public_html/­concannon/.

APPENDIX A 201 low-level helicity (higher values favor strong rotating updrafts). Tornadoes spawned by supercell thunderstorms descend earthward from the rotating updraft. It is important to sample the pre-storm environment in which supercells form. Since the shear can change rapidly, within 2 or 3 hours, the sampling rate must be rather high. Suggested resolution: ∆x=50 km, ∆z=200 m up to 6 km, ∆t=1 h. Though multiple storms may form in this environment, it is very difficult to say in advance which ones will acquire supercell charac- teristics. If a supercell forms and the shear in the lowest kilometer is high, tornadogenesis is more likely than when the shear is distributed over a deeper layer. Radar detection of mesocyclones (a signature for large rotating updrafts) within supercells is reliable within a range of 100 km or so. Non-supercell tornadoes (Wakimoto and Wilson, 1989) are most ­common in environments that are not strongly sheared. The initial rotation is near the surface, concentrated by persistent low-level convergence. If a thunder- storm forms over the convergence zone, the low-level vorticity (a measure of spin or rotation in the wind flow) is drawn into the updraft and verti- cally stretched. The rotation intensifies. If a tornado forms, it develops from the ground up. Tornadoes formed in this way are called landspouts or ­gustnadoes. They are almost always weaker than their supercell counter- parts, but, because they are not so strongly forced by atmospheric ­dynamics, they are much more difficult to predict. Though Doppler radars can easily detect mesocyclones within supercell thunderstorms, they cannot often see the tornado vortex, unless it is at least several hundred meters wide and at close range. Non-supercell tornadoes, being generally smaller, are even more difficult to detect. To anticipate a non-supercell tornado, one would have to monitor the sub-cloud wind, temperature, and moisture field at ∆x=500 m, ∆z=100m, and ∆t=5 min. One would also have to know whether a growing cell were positioned above the center of rotation. WINDSTORMS WITHOUT PRECIPITATION Downslope Windstorms Definition: Downslope windstorms are usually localized in the lee of moun- tain barriers. Wind blowing across a mountain barrier causes waves to form in the flow, similar to water waves in a stream when it flows across a rock in the streambed. When the cross-mountain flow is strong and the mountains are high, strong surface winds can occur at the base of the wave,

202 APPENDIX A which goes by the name mountain wave. Occasionally a single windstorm will cause property damage in the millions of dollars, or it will cause even greater collateral damage by fanning the flames of a wildfire. Size: Downslope windstorms are fairly localized, affecting areas from the edge of the foothills to 20 km downwind. Duration: downslope windstorms typically last from one to several hours. Two or more episodes may occur within a single day Geographical preference: Downslope windstorms frequent the east slopes of the Colorado Front Range from Fort Collins to Colorado Springs and the west slopes of the Wasatch Range near Salt Lake City, Utah. They also occur near Albuquerque, New Mexico. They are called Santa Ana winds in southern California, Sundowner winds near Santa Barbara, California, and Taku winds in southeast Alaska, especially Juneau. Most downslope windstorms are caused by mountain wave activity and breaking gravity waves (similar to water waves breaking in the ocean) in the upper troposphere and lower stratosphere (Durran, 2003a,b). They are characterized by strong leeside winds at low levels near the base of the mountain wave and severe clear air turbulence over and near the moun- tains. Forecasters look for strong cross-mountain winds, a stable layer near mountain-top level, often near 600 hPa along the Front Range of the Rocky Mountains in Colorado, and a lack of strong shear in the mid- and upper troposphere. The strong surface winds typically last for a few hours at a time and can be extremely gusty. Ground-based lidar measurements during downslope windstorms have demonstrated extreme local variability (Neiman et al., 1988). When and where the strong winds surface seems to be sensitive to terrain features on a scale of less than 1 km and small changes in atmospheric wind and temperature profiles. To diagnose conditions favorable for a downslope windstorm, tropospheric soundings at ∆x=100 km, ∆z=200m, and ∆t=3 h are appropriate from the location of the mountains to 500 km upstream. To understand local variability within a windstorm, suitable resolutions are ∆x=1 km, ∆z=100 m, and ∆t=15 min. Terrain data at ∆x=0.5 km are probably necessary. Pressure-Gradient Windstorms Definition: Pressure-gradient windstorms arise around the periphery of low- pressure systems, when strong differences in pressure over short distances

APPENDIX A 203 induce strong winds, without precipitation. Blowing dust has caused many fatal traffic accidents. Strong winds in connection with precipitation (e.g., blizzards, Nor’easters, hurricanes, or convective storms) are covered in other sections. Size: Pressure-gradient windstorms affect larger areas than downslope windstorms, often hundreds of kilometers across. Duration: pressure-gradient winds typically last from 2-12 hours Pressure-gradient windstorms without precipitation are most frequent in winter and spring north of 40°N latitude, merely because low-pressure s ­ ystems tend to be more energetic there than in the southern United States. The strong winds sometimes occur in the warm sector of an intense low- pressure system but also frequently on the west side of the low after cold- front passage. Prediction of the strong winds 24 h in advance is probably adequate. For this purpose, full-tropospheric temperature and wind sound- ings within the broad region including the low are necessary at resolutions of ∆x=100 km, ∆z=0.5 km, and ∆t=6 h. FIRE WEATHER Definition: Fire weather refers to conditions that favor the rapid spread of brush or forest fires, whether a fire is in progress or not. Size: The area of interest usually ranges from 10 to 100 km across. Duration: typically a few hours to a few days Geographical preference: Most common from the Rocky Mountains to the West Coast in forested areas during the dry season. Many fires are started by cloud-to-ground lightning in “dry” thunderstorms. Half the wildfires in the U.S. West are lightning-caused. In total there are about 10,000 such fires, costing the Bureau of Land Management approximately $100 million annually. Many other wildfires are caused by human carelessness. Lightning-caused wildfires have already been mentioned in the section on lightning. These fires play a role in the natural evolution of the forest. Whenever forest fires or brush fires threaten life or property, however, they must be brought under control.   See http://www.lightningsafety.com/nlsi_lls/nlsi_annual_usa_losses.htm.

204 APPENDIX A Weather information is important for determining not only when the fire danger will be high but also how quickly a fire will spread and how dan- gerous conditions will be for the firefighting crews. Antecedent surface conditions (precipitation, temperature, wind, and humidity) signal how dry the fuel on the forest floor has become, but surface conditions alone are inadequate for determining how fast a fire will spread. For example, the lower-tropospheric lapse rate controls how easily stronger winds aloft can mix down to the surface. As another example, the presence or absence of clouds modulates the development of the daytime mixed layer. The observing requirements when wildfires are in progress are similar to those for downslope windstorms (previous section), except that the atmospheric soundings probably do not need to go higher than 500 hPa. Looking at least 500 km upstream gives adequate forewarning of changes in wind direction or speed in the boundary layer. At the fire site, wind measurements are the most important, followed by relative humidity and temperature. HAZARDS TO AIRCRAFT Aside from thunderstorms, several meteorological phenomena pose specific hazardous to those who fly: icing, downbursts, and turbulence. Clear-air turbulence is potentially more dangerous than other kinds of turbulence, because there is no visual cue of its presence and sometimes no forewarning (e.g., from planes recently flying through the same airspace). In-Cloud Icing Definition: Ice accumulates on the airframe as the pilot flies through a cloud containing liquid water at temperatures below freezing. Size: Supercooled clouds blanket areas from tens to hundreds of kilometers across. Duration: typically from half an hour to half a day Geographic preference: None. Any supercooled cloud can produce aircraft icing. A supercooled cloud contains liquid water at temperatures below 0°C. An aircraft flying through such a cloud will accrete ice on the wings and other surfaces, sometimes faster than it can be shed, resulting in decreased lift. The larger the droplets in a supercooled cloud, the faster the ice accumu-

APPENDIX A 205 lates. Larger drops can in fact roll off the de-icing boots and freeze on the wings, severely degrading performance and lift within just a few minutes of entering the supercooled cloud. Airframe icing has caused 583 accidents and more than 800 fatalities in the United States from 1982 through 2000 (Petty and Floyd, 2004). Less than one-quarter of these accidents resulted from airframe icing on the ground before takeoff. Successful prediction of icing depends upon successful prediction of cloud location and in-cloud temperatures. Cloud top temperatures between –10° and 0°C usually provide the greatest potential for aircraft icing due to the lack of natural ice. (At lower temperatures, ice particles are more probable. These grow at the expense of supercooled droplets when both are present, and they collect the droplets through collisions, causing them to freeze. Thus ice particles act to deplete the supercooled water.) Supercooled clouds whose tops are no colder than –10°C are common in post-frontal stratocumulus clouds. Models have moderate skill in predicting cloud cover and cloud altitude, marginal skill in predicting cloud properties, and little skill in predicting the location of individual clouds. In one way, the prediction of clouds is more difficult than the prediction of precipita- tion, because the spatial, temporal, and physical variability of clouds is greater. The specification of cloud fields as observed from the ground and remotely from satellites is an aid to progress, but more detailed measure- ments of wind and water vapor concentration would more directly address the need for accurate vapor fluxes, which in turn would lead to better pre- dictions of vertical motion and clouds. Prediction of the freezing level is much less a problem than the prediction of liquid water at sub-freezing temperatures. The detection of icing requires observation of clouds positioned between the 0°C and minus 20°C isotherms at ∆x=5 km, ∆z=100 m, and ∆t=1 h. Measurements of temperature and hydrometeor type are necessary in this layer. Infrared measurements from space and ceilometer measurements from the ground will not detect supercooled clouds unless the cloud base or cloud top lies within the critical temperature layer. Downbursts Definition: A downburst is a strong downrush of air from a convective cloud that strikes the ground. Also called a microburst. Size: Typically from 100 to 2000 m across.

206 APPENDIX A Duration: typically from 1 to 10 minutes Geographic preference: Downbursts can accompany any convective storm. The most dangerous to aircraft are those with low reflectivity, little or no precipitation at the ground, and no lightning, because they offer few visual cues. Such “dry” downbursts occur most often in summer from early after- noon until early evening in the dry climates of the western Great Plains and the Intermountain West (Caracena et al., 1989). Downbursts pose a serious risk to an aircraft on takeoff roll or one about to land. An aircraft first experiences the downburst as a sudden headwind. Once past its nearest approach to the center of the downburst, it experi- ences a sudden tailwind. The loss of lift can cause departing aircraft to roll off the end of the runway and landing aircraft to crash short of the runway. Wet downbursts are associated with a descending core of heavy precipitation, perhaps mixed with unsaturated air from mid-levels. These downbursts look menacing, at least in the daytime, and are reliably detected by radar. They are not difficult to avoid. Dry downbursts are more sinister. They are caused by the evaporation of droplets falling into a deep layer of fairly dry air below a high cloud base in the presence of a steep lapse rate (rapid decrease of temperature with height, about 1°C for each 100 m of altitude). If the droplets are numerous and small, but do not completely evaporate until reaching the ground, the downrushing air can accelerate enough to produce radial outflows exceed- ing 30 m s–1. Sometimes the only visual cue is a circular ring of blowing dust at the ground. Early afternoon soundings would aid in the prediction of downbursts. Moist air in mid-troposphere to support high-based thunderstorms and a steep lapse rate below cloud base are the hallmarks of downburst condi- tions (Wakimoto, 1985). Mid-tropospheric winds of 20 m s–1 or so will strengthen the downburst if momentum at this level is incorporated in the descending precipitation. A single sounding such as a rawinsonde would suffice in the vicinity of the airport. Once convective showers form, monitoring from the surface to 400 hPa (within the convective cloud) becomes critical. Given that most down- bursts last for only a few minutes and affect small areas (on the order of 10 km2), the appropriate sampling resolution is ∆x=1 km, ∆z=200 m, and ∆t=1 min.   See, for example, http://www-das.uwyo.edu/~geerts/cwx/notes/chap08/microburst.html.

APPENDIX A 207 Aircraft Turbulence Definition: Frequent fliers invariably experience turbulence, differential air motions that shake the aircraft and its passengers. Size: Turbulence that affects aircraft occurs on scales of tens to hundreds of meters. Duration: Though individual bumps last about a second, the eddies in the air flow that cause the bumps probably last tens of seconds; some flights experience turbulence for many minutes at a time. Geographic preference: None. Clear-air turbulence is most common in the vicinity of upper air fronts, which are associated with strong three- d ­ imensional wind shears. Clear-air turbulence is also common, and may be severe, in mountain wave situations. Turbulence in convective clouds is taken for granted because of the up-and-down air motions, but pilots try to avoid thunderstorms. Turbulence is the leading cause of non-fatal injury to flight attendants and passengers. Under the Federal Aviation Administration’s (FAA’s) Safer Skies Program, the Commercial Aviation Safety Team commissioned the Turbu- lence Joint Safety Analysis Team to study the increasing rate of air carrier turbulence incidents and accidents from 1987 to 2000. The average annual cost of the rare fatality and all non-fatal injuries combined for all airlines is approximately $26 million. Because of the ephemeral nature of turbulence, its existence is almost always inferred and predicted from the larger-scale wind field. Aircraft experiencing turbulence routinely inform following aircraft about what to expect. Measurements in clear and cloudy air on the scale of tens to hundreds of meters every few seconds are needed to detect aircraft turbulence. If this is ever to become a practical reality, it may have to be done from the aircraft itself. The prediction of aircraft turbulence will be based on parameter- izations (approximations in computer models that account for physical processes too small to be captured on the grid of points where model computations occur) for many years to come. It has yet to be shown that observations of turbulence can lead to better predictions of turbulence in models.

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Detailed weather observations on local and regional levels are essential to a range of needs from forecasting tornadoes to making decisions that affect energy security, public health and safety, transportation, agriculture and all of our economic interests. As technological capabilities have become increasingly affordable, businesses, state and local governments, and individual weather enthusiasts have set up observing systems throughout the United States. However, because there is no national network tying many of these systems together, data collection methods are inconsistent and public accessibility is limited. This book identifies short-term and long-term goals for federal government sponsors and other public and private partners in establishing a coordinated nationwide "network of networks" of weather and climate observations.

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