Abstract

Heavy 30-day snowfall amounts were evaluated to identify spatial and temporal characteristics east of the Rocky Mountains in the United States during the period 1900–2016. An extensive data assessment identified 507 stations for use in this long-term climate study. The top 30-day heavy snowfall amount and the average of the top five 30-day heavy snowfall amounts were examined. Both amounts generally increased with latitude; however, much higher amounts were found downwind of the Great Lakes, at higher elevations, or in locations impacted by topographic features (e.g., Rockies, Black Hills, and Appalachians). When compared with the 1981–2010 average winter snowfall, the top 30-day amount was found to be greater than the winter average in most areas of the eastern United States. The number of stations experiencing a top-five 30-day heavy snowfall period in a winter ranged from 1 to 128 (1959/60), with a greater overall occurrence in the second half of the 117-yr period. Six episodes had 10% or more stations experiencing one of the top five 30-day snowfall amounts, with the February–March 1960 episode impacting 124 stations, and these episodes were associated with large negative 500-hPa height anomalies. The northern Great Plains, Great Lakes, Midwest, and Northeast experienced more top-five periods in the second half of the 117-yr period, whereas most of the southern states experienced top-five periods throughout the study’s time frame. Examining extremes at periods beyond the daily event and less than the season contributes to our knowledge of climate and provides useful information to snow-sensitive sectors.

Job opportunities for undergraduate meteorology students are decreasing. An innovative course in applied climatology has been designed and tested to help prepare such students for the career options developing in the private sector. Students are trained to use their meteorological knowledge and analytical skills to work interactively with weather-sensitive users in utilities, agribusinesses, water-resource agencies, recreation firms, and transportation companies. The students develop and test climate relationship-decision models in a real-world environment for these organizations. The models they develop bridge existing information “gaps” between climatologists and weather-sensitive managers who 1) do not understand climate information, and/or 2) do not know how to apply it to their environmental or economic decisions. As a result, students receive applied research experience and important “education-to-career” opportunities; that is, students can apply what is learned through direct and often beneficial interactions with decision makers. These efforts address problems similar to those they likely will encounter after employment. Other long-term objectives of this course are to develop a more effective information flow between climatologists and weather-sensitive users and to assist climatologists by identifying the types of needs for climate information.

Over the past six years, 27 projects were conducted involving weather–climate product development by students working with weather-sensitive decision makers in various institutions. Thirteen of these decision makers were interviewed during 2003 to assess the post-product impacts. This assessment revealed that successful integration of climate-related products and information into the decision process depended on the following four factors: 1) the user's basic knowledge of atmospheric sciences, 2) their ability to manage risks associated with use of uncertain climate information, 3) their access to climate information and expertise in a timely fashion, and 4) demonstrations of value from the use of the project information. These interactive projects, which included a university faculty climatologist, undergraduate meteorology students, and the decision makers, had increased decision makers' awareness of, and interest in, climatological information (data, derived products, seasonal outlooks, etc.). The projects also identified where climate information and expertise could be obtained, and established a continuing dialogue between the climatologist and users. These projects further demonstrated that most decision makers, even those in the same weather-sensitive sector, often face very different issues that require specialized, value-added information that goes well beyond the generalized information produced by government agencies. Because of this ongoing shift in user needs, the atmospheric science community may have to broaden the educational experiences for future students.

Abstract

Uses of climate information have grown considerably in the past 15 years as a wide variety of weather-sensitive businesses sought to deal effectively with their financial losses and manage risks associated with various weather and climate conditions. Availability of both long-term quality climate data and new technologies has facilitated development of climate-related products by private-sector atmospheric scientists and decision makers. Weather derivatives, now widely used in the energy sector, allow companies to select a financially critical seasonal weather threshold, and, for a price paid to a provider, to obtain financial reparation if this threshold is exceeded. Another new product primarily used by the insurance industry is weather-risk models, which define the potential risks of severe-weather losses across a region where few historical insured loss data exist. Firms develop weather-risk models based on historical storm information combined with a target region’s societal, economic, and physical conditions. Examples of the derivatives and weather-risk models and their uses are presented. Atmospheric scientists who want to participate in the development and use of these new risk-management products will need to broaden their educational experience and develop knowledge and skills in fields such as finance, geography, economics, statistics, and information technology.

Abstract

Hail-day occurrences during a 100-yr period, 1896–1995, derived from carefully screened records of 66 first-order stations distributed across the United States, were assessed for temporal fluctuations and trends. Shorter-term (5- and 10-yr) fluctuations varied greatly and were often dissimilar between adjacent stations reflecting localized differences in hailstorm activity, making temporal interpretations difficult. But temporal fluctuations based on 20-yr and longer periods exhibited regional coherence reflecting the control of large-scale synoptic hail-producing systems on the point distributions over broader areas. Classification of station fluctuations based on 20-yr periods revealed five types of distributions existed across most of the nation. One present in the Midwest had a peak in hail activity in 1916–35 followed by a general decline to 1976–95. Another distribution had a midcentury peak and was found at stations in three areas: the central high plains, northern Rockies, and East Coast. The third distribution peaked during 1956–75 and was found at stations in the northern and south-central high plains. The fourth temporal distribution showed a steady increase during the 100-yr period, peaking in 1976–95, and was found in an area from the Pacific Northwest to the central Rockies and southern plains. The fifth distribution found at stations in the eastern Gulf Coast had a maximum at the beginning of the century and declined thereafter. The 100-yr linear trends defined four regions across the United States with significant up trends in the high plains, central Rockies, and southeast, but with decreasing trends elsewhere in the nation. These up trends have occurred in areas where hail damage is greatest, and the trends matched well with those defined by crop-hail insurance losses and those found in studies of thunderstorm trends. The national average based on all station hail values formed a bell-shaped 100-yr distribution with hail occurrences peaking in midcentury. Thunderstorm data from the 66 stations, also based on screening to ensure quality data, revealed a bell-shaped distribution similar to the hail-day distribution, and national hail insurance loss values have declined since the 1950s, also agreeing with the hail-day decrease since midcentury. The national distribution differs markedly from certain regional distributions illustrating the importance of using regional analysis to assess temporal fluctuations in severe weather conditions.

Abstract

Crop-hail insurance loss data for 1948–94 are useful as measures of the historical variability of damaging hail in those 26 states where most crop damages occur. However, longer records are needed for various scientific and business applications, as well as information on potential losses in United States’ areas without crop insurance. The long-term (1901 to present) data on hail-day incidences, as derived from National Weather Service historical station records, were investigated to determine if some form of a hail-day expression related well to the insurance losses. The areal extent of insured areas of Illinois, Texas, and Nebraska experiencing growing season frequencies of hail days matching or exceeding the once in 10-yr frequencies was found to have the best relationship with insured loss values. The computed correlation coefficients were +0.97 for Illinois, +0.73 for Texas, and +0.91 for Nebraska. These values appear to be a useful surrogate for 1) estimating pre-1948 loss values, 2) estimating loss values in areas with no insurance, and 3) further research involving other states with different crop and hail conditions.

Abstract

Teleconnections were used to link three El Niño–Southern Oscillation (ENSO) parameters to winter (December–February) cyclone frequencies over the United States during the 1949–96 period. Since each ENSO event is not exactly the same, small subsets of ENSO events were examined in addition to the more common composite ENSO event. Mean winter cyclone frequencies, derived by counting cyclones passing through 30, 5° latitude equal-area circles located in a grid from 70° to 120°W and 30° to 50°N were determined for classes of El Niños and La Niñas based on 1) the intensity of the equatorial Pacific sea surface temperature anomaly, 2) the intensity of the Tahiti–Darwin sea level pressure anomaly, and 3) the location of the 28°C isotherm. The average cyclone count for each class of El Niño and La Niña was compared to the average count for winters when no ENSO event occurred.

Expected differences in cyclone frequency patterns when comparing an average of all El Niño winters to all La Niña winters were found; however, large pattern differences were also determined when comparing winters with strong El Niños to moderate–weak El Niños and similarly for La Niñas. Significant differences in number of cyclones were found in 8 of 30 circles located in the Pacific Northwest, the Great Lakes, New England, and the Southeast. The differences found in the cyclone frequency patterns for El Niños and La Niñas of different intensities and locations indicated that using a composite of all El Niños or La Niñas may provide misleading information while examination of each of these parameters independently may assist in the preparation of long-range climate predictions.

Abstract

The insurance industry, insurance regulatory bodies, and scientists investigating climate change all desire long records of hail losses. Existing loss records for some states cover the 1948–present period; this span is helpful but is not long enough to define trends, possible fluctuations, and extremes adequately. The only other hail data with much longer records are the frequencies of hail days collected at National Weather Service stations since 1901, and a newly developed database for the major hail-loss states that contains hail-day data for 910 cooperative stations for 1901–94. This study tested two methods for estimating the historical loss values using hail-day data; one method produced modified hail-day values found to relate closely to loss values in the nation’s 21 primary hail-loss states. The method involved modifying a station’s hail-day values for each of the crop-season months using insurance-derived monthly hail intensity indices, resulting in an annual hail-intensity-weighted value. These weighted values of each year were combined using all stations in the crop regions of a state. The state-weighted annual indices were compared with the insurance loss values and yielded correlation coefficients of +0.60 or higher in 18 of 21 states; the resulting regression equations were used to estimate the loss values for the 1901–47 period. The temporal fluctuations and trends in the state hail intensity and loss values for 1901–94 showed major regional differences. States in the High Plains had increasing losses and greater variability with time, whereas states near the Great Lakes exhibited decreasing hail losses and variability with time. The approach can also be used to estimate loss values for areas for which historical loss values do not exist.

The uses and potential applications of climate forecasts for electric and gas utilities were assessed 1) to discern needs for improving climate forecasts and guiding future research, and 2) to assist utilities in making wise use of forecasts. In-depth structured interviews were conducted with 56 decision makers in six utilities to assess existing and potential uses of climate forecasts. Only 3 of the 56 use forecasts. Eighty percent of those sampled envisioned applications of climate forecasts, given certain changes and additional information. Primary applications exist in power trading, load forecasting, fuel acquisition, and systems planning, with slight differences in interests between utilities. Utility staff understand probability-based forecasts but desire climatological information related to forecasted outcomes, including analogs similar to the forecasts, and explanations of the forecasts. Desired lead times vary from a week to three months, along with forecasts of up to four seasons ahead. The new NOAA forecasts initiated in 1995 provide the lead times and longer-term forecasts desired. Major hindrances to use of forecasts are hard-to-understand formats, lack of corporate acceptance, and lack of access to expertise. Recent changes in government regulations altered the utility industry, leading to a more competitive world wherein information about future weather conditions assumes much more value. Outreach efforts by government forecast agencies appear valuable to help achieve the appropriate and enhanced use of climate forecasts by the utility industry. An opportunity for service exists also for the private weather sector.

Abstract

The 241 largest snowstorms over the eastern two-thirds of the United States during 1950–2000 exhibited considerable temporal variability ranging from 1 storm in three winters to 10 storms in 1993/94. The peak decadal frequency was 55 storms (1950s), and the minimum was 45 storms (1970s and 1980s). The east–north-central region experienced the greatest number of large snowstorms (148) followed by the west–north-central (136) and central (133) regions. Regional trends were different. Assessment of surface cyclone tracks associated with the large snowstorms identified three primary tracks: one was located from the leeward side of the south-central Rocky Mountains east-northeast toward the Great Lakes; a second was from the lower Mississippi River basin northeastward toward the Great Lakes; and a third was along the coastal mid-Atlantic region northeast toward Maine. Temporal differences in the frequency of certain surface cyclone tracks were related to the decadal trends in regional large snowstorm occurrence. The minimum surface pressure associated with these storms ranged from 959 to 1013 hPa with more than 67% of all storms having a minimum surface pressure between 980 and 999 hPa. The average orthogonal distance from the storm track to the heavy snow region was 201 km. The average rate of cyclone movement ranged from less than 483 to more than 1930 km day⁻¹, with more than 57% of storms moving between 805 and 1287 km day⁻¹.