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- Author or Editor: K. E. Kunkel x
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Abstract
A manometric type of wind sensor has been developed. This sensor convert the dynamic pressure of the wind into a modulated dynamic pressure signal which can then be sensed using microphones. This permits wind speed measurements to be made with high sensitivity and fast response. The sensor is described in detail. Applications of this sensor vary from the simple measurement of the mean wind speed to the high-frequency measurement of atmospheric turbulence. The sensor is rugged and can operate in environmentally adverse conditions.
Abstract
A manometric type of wind sensor has been developed. This sensor convert the dynamic pressure of the wind into a modulated dynamic pressure signal which can then be sensed using microphones. This permits wind speed measurements to be made with high sensitivity and fast response. The sensor is described in detail. Applications of this sensor vary from the simple measurement of the mean wind speed to the high-frequency measurement of atmospheric turbulence. The sensor is rugged and can operate in environmentally adverse conditions.
Abstract
Monte Carlo techniques are utilized to compute monostatic lidar returns from turbid atmospheres. Examples are evaluated for thick hazes, clouds, fogs and rain. The effects of multiple scattering are significant in the cases considered. Results are compared with those obtained by Eloranta (1972) to describe doubly scattered lidar returns and the agreement is satisfactory, provided that higher orders of multiple scattering are negligible.
Abstract
Monte Carlo techniques are utilized to compute monostatic lidar returns from turbid atmospheres. Examples are evaluated for thick hazes, clouds, fogs and rain. The effects of multiple scattering are significant in the cases considered. Results are compared with those obtained by Eloranta (1972) to describe doubly scattered lidar returns and the agreement is satisfactory, provided that higher orders of multiple scattering are negligible.
Abstract
Measurements of the optical refractive index structure coefficient
Abstract
Measurements of the optical refractive index structure coefficient
Abstract
Procedures are described for the analysis of lidar data to remotely measure 1) spectra of aerosol density fluctuations, 2) radial and transverse components of the mean wind and turbulent fluctuations of the transverse component of the wind velocity in the convective boundary layer, and 3) the kinetic energy dissipation rate. Results were compared with independent data obtained with a bivane anemometer installed at the 70 m level on a tower within the scanning sector of the lidar. Good agreement was obtained whenever the lidar data had adequate signal-to-noise characteristics (i.e., S/ greater than unity).
Abstract
Procedures are described for the analysis of lidar data to remotely measure 1) spectra of aerosol density fluctuations, 2) radial and transverse components of the mean wind and turbulent fluctuations of the transverse component of the wind velocity in the convective boundary layer, and 3) the kinetic energy dissipation rate. Results were compared with independent data obtained with a bivane anemometer installed at the 70 m level on a tower within the scanning sector of the lidar. Good agreement was obtained whenever the lidar data had adequate signal-to-noise characteristics (i.e., S/ greater than unity).
Abstract
A scanning lidar system has been used to observe convection in the atmospheric boundary layer. In particular, cell sizes and geometry have been determined and circulation patterns in and around the cells have been measured.
The lidar data show that the preferred form of convective cells are plumes with roots near the surface. The majority of these plumes have aspects ratios between 0.5 and 1.5. The measurements of circulation patterns show the strongest rising motion on the upwind side of the cell with sinking motion on the downwind side. These observations show that lidar is a powerful tool for observing convection.
Abstract
A scanning lidar system has been used to observe convection in the atmospheric boundary layer. In particular, cell sizes and geometry have been determined and circulation patterns in and around the cells have been measured.
The lidar data show that the preferred form of convective cells are plumes with roots near the surface. The majority of these plumes have aspects ratios between 0.5 and 1.5. The measurements of circulation patterns show the strongest rising motion on the upwind side of the cell with sinking motion on the downwind side. These observations show that lidar is a powerful tool for observing convection.
Abstract
The general applicability of an isonomogram developed by Czys and coauthors to diagnose the position of the geographic boundary between freezing precipitation (freezing rain or freezing drizzle) and ice pellets (sleet or snow grains) was tested using a 25-yr sounding database consisting of 1051 soundings, 581 where stations were reporting freezing drizzle, 391 reporting freezing rain, and 79 reporting ice pellets. Of the 1051 soundings, only 306 clearly had an environmental temperature and moisture profile corresponding to that assumed for the isonomogram. This profile consisted of a three-layer atmosphere with 1) a cold cloud layer aloft that is a source of ice particles, 2) a midlevel layer where the temperature exceeds 0°C and ice particles melt, and 3) a surface layer where T < 0°C. The remaining soundings did not conform to the profile either because 1) the freezing precipitation was associated with the warm rain process or 2) the ice pellets formed due to riming rather than melting and refreezing. For soundings conforming to the profile, the isonomogram showed little diagnostic skill. Freezing rain or freezing drizzle occurred about 50% of the time that ice pellets were expected. Ice pellets occurred in nearly a third of the cases where freezing precipitation was diagnosed. Possible reasons for the poor diagnostic skill of the method are suggested.
Abstract
The general applicability of an isonomogram developed by Czys and coauthors to diagnose the position of the geographic boundary between freezing precipitation (freezing rain or freezing drizzle) and ice pellets (sleet or snow grains) was tested using a 25-yr sounding database consisting of 1051 soundings, 581 where stations were reporting freezing drizzle, 391 reporting freezing rain, and 79 reporting ice pellets. Of the 1051 soundings, only 306 clearly had an environmental temperature and moisture profile corresponding to that assumed for the isonomogram. This profile consisted of a three-layer atmosphere with 1) a cold cloud layer aloft that is a source of ice particles, 2) a midlevel layer where the temperature exceeds 0°C and ice particles melt, and 3) a surface layer where T < 0°C. The remaining soundings did not conform to the profile either because 1) the freezing precipitation was associated with the warm rain process or 2) the ice pellets formed due to riming rather than melting and refreezing. For soundings conforming to the profile, the isonomogram showed little diagnostic skill. Freezing rain or freezing drizzle occurred about 50% of the time that ice pellets were expected. Ice pellets occurred in nearly a third of the cases where freezing precipitation was diagnosed. Possible reasons for the poor diagnostic skill of the method are suggested.
Abstract
The importance of warm rain and melting processes in freezing precipitation events is investigated by analyzing 972 rawinsonde soundings taken during freezing precipitation. The soundings cover regions of the United States east of the Rocky Mountain states for the period 1970–94. The warm rain process was found to be unambiguously responsible for freezing precipitation in 47% of the soundings. In these soundings, the clouds had temperatures entirely below freezing, or had top temperatures that were above freezing. Another 28% of the soundings had cloud top temperatures between 0° and −10°C. Clouds with top temperatures >−10°C also can support an active warm rain process. Considered together, the warm rain process was potentially important in about 75% of the freezing precipitation soundings. This estimate is significantly higher than the estimate of 30% in a previous study by Huffman and Norman. The temperature, moisture, and wind profiles of the soundings, their geographic distribution, and the common occurrence of freezing drizzle at the sounding sites suggest that most of these events were associated with shallow cloud decks forming over arctic cold air masses.
The “classic” freezing rain sounding, with a deep moist layer and a midlevel warm (>0°C) layer, was observed in only 25% of the sample. In these soundings, the depth of the cloud layer implies that melting processes were important to precipitation production. From the geographic distribution, the common occurrence of freezing rain, and the sounding profile, these cases appear to be associated primarily with cold air damming and overrunning along the U.S. East Coast, and with warm-frontal overrunning in the midwestern United States.
Abstract
The importance of warm rain and melting processes in freezing precipitation events is investigated by analyzing 972 rawinsonde soundings taken during freezing precipitation. The soundings cover regions of the United States east of the Rocky Mountain states for the period 1970–94. The warm rain process was found to be unambiguously responsible for freezing precipitation in 47% of the soundings. In these soundings, the clouds had temperatures entirely below freezing, or had top temperatures that were above freezing. Another 28% of the soundings had cloud top temperatures between 0° and −10°C. Clouds with top temperatures >−10°C also can support an active warm rain process. Considered together, the warm rain process was potentially important in about 75% of the freezing precipitation soundings. This estimate is significantly higher than the estimate of 30% in a previous study by Huffman and Norman. The temperature, moisture, and wind profiles of the soundings, their geographic distribution, and the common occurrence of freezing drizzle at the sounding sites suggest that most of these events were associated with shallow cloud decks forming over arctic cold air masses.
The “classic” freezing rain sounding, with a deep moist layer and a midlevel warm (>0°C) layer, was observed in only 25% of the sample. In these soundings, the depth of the cloud layer implies that melting processes were important to precipitation production. From the geographic distribution, the common occurrence of freezing rain, and the sounding profile, these cases appear to be associated primarily with cold air damming and overrunning along the U.S. East Coast, and with warm-frontal overrunning in the midwestern United States.
Abstract
An analysis of 411 winter storms that produced freezing precipitation events in the United States east of the Rocky Mountains over the 25-yr period of 1970–94 is presented to identify specific weather patterns associated with freezing precipitation and to determine their frequency of occurrence. Seven archetypical weather patterns are identified associated with freezing precipitation. Four patterns (arctic fronts, the warm front–occlusion sector of cyclones, cyclone–anticyclone couplets, and the west quadrant of anticyclones) are not associated with specific topographic features. Three patterns (East Coast cold-air damming with an anticyclone, cold-air damming with a coastal cyclone, and cold-air trapping during approaching continental cyclones) are associated with freezing precipitation in and along the Appalachian Mountains. The frequency of occurrence and duration of each of these patterns are presented, and variability within patterns is discussed. In the second part of the paper, the vertical structure of the atmosphere during freezing precipitation events is investigated by analyzing 972 rawinsonde soundings taken during freezing precipitation. The soundings cover regions of the United States east of the Rocky Mountain states for the period of 1970–94. Statistical summaries of soundings from each archetypical weather pattern and from the entire dataset are presented for 1) the depth and minimum temperature of the cold surface layer, 2) the depth and maximum temperature of the warm layer aloft, 3) stability characteristics of air above the inversion, 4) layer thickness for the 1000–500-mb and 1000–850-mb layers, and 5) wind speed and direction at the surface, the 850-mb level, and the 700-mb level.
Abstract
An analysis of 411 winter storms that produced freezing precipitation events in the United States east of the Rocky Mountains over the 25-yr period of 1970–94 is presented to identify specific weather patterns associated with freezing precipitation and to determine their frequency of occurrence. Seven archetypical weather patterns are identified associated with freezing precipitation. Four patterns (arctic fronts, the warm front–occlusion sector of cyclones, cyclone–anticyclone couplets, and the west quadrant of anticyclones) are not associated with specific topographic features. Three patterns (East Coast cold-air damming with an anticyclone, cold-air damming with a coastal cyclone, and cold-air trapping during approaching continental cyclones) are associated with freezing precipitation in and along the Appalachian Mountains. The frequency of occurrence and duration of each of these patterns are presented, and variability within patterns is discussed. In the second part of the paper, the vertical structure of the atmosphere during freezing precipitation events is investigated by analyzing 972 rawinsonde soundings taken during freezing precipitation. The soundings cover regions of the United States east of the Rocky Mountain states for the period of 1970–94. Statistical summaries of soundings from each archetypical weather pattern and from the entire dataset are presented for 1) the depth and minimum temperature of the cold surface layer, 2) the depth and maximum temperature of the warm layer aloft, 3) stability characteristics of air above the inversion, 4) layer thickness for the 1000–500-mb and 1000–850-mb layers, and 5) wind speed and direction at the surface, the 850-mb level, and the 700-mb level.
Variations and trends in extreme climate events have only recently received much attention. Exponentially increasing economic losses, coupled with an increase in deaths due to these events, have focused attention on the possibility that these events are increasing in frequency. One of the major problems in examining the climate record for changes in extremes is a lack of high-quality, long-term data. In some areas of the world increases in extreme events are apparent, while in others there appears to be a decline. Based on this information increased ability to monitor and detect multidecadal variations and trends is critical to begin to detect any observed changes and understand their origins.
Variations and trends in extreme climate events have only recently received much attention. Exponentially increasing economic losses, coupled with an increase in deaths due to these events, have focused attention on the possibility that these events are increasing in frequency. One of the major problems in examining the climate record for changes in extremes is a lack of high-quality, long-term data. In some areas of the world increases in extreme events are apparent, while in others there appears to be a decline. Based on this information increased ability to monitor and detect multidecadal variations and trends is critical to begin to detect any observed changes and understand their origins.
In the midwestern United States, the summertime rise in infection rate by the West Nile virus is associated with a seasonal shift in the abundance of two mosquito populations, Culex restuans and Culex pipiens. This seasonal shift usually precedes the time of the peak infection rate in mosquitoes by 2–3 weeks and generally occurs earlier in the summer with above normal temperatures and later in the summer with below-normal temperatures. Two empirical models were developed to predict this seasonal shift in mosquito species, or the “crossover,” and have been run operationally since 2004 by the Midwestern Regional Climate Center located at the Illinois State Water Survey. These models are based on daily temperature data and have been verified by use of a unique dataset of daily records of mosquito species abundance collected by the Illinois Natural History Survey. An unfortunate characteristic of the original temperature models was that the crossover date often was reached with little or no lead time. In 2009, the models were modified to incorporate National Weather Service (NWS) model output statistics (MOS) 10-day temperature forecasts. This paper evaluates the effectiveness of these models to predict the crossover date and thus the period of increased risk of West Nile virus in the Midwest.
For the 8-yr period from 2002 to 2009, 6 yr had at least one model predicting the crossover within one week of the actual crossover date, and for 7 yr at least one of the model predictions was within 2 weeks of the actual crossover date. Incorporation of MOS temperature forecasts for a 10-day period, although not substantially changing the predicted crossover date, greatly improved the forecast lead time by about 9 days. From a disease management point of view, this improvement in advanced notice is significant. In 2009, there was an unprecedented early crossover date and a failed forecast. The poor forecast was likely caused by an unusually early summer prolonged and intense heat wave, followed immediately by a record cold July.
In the midwestern United States, the summertime rise in infection rate by the West Nile virus is associated with a seasonal shift in the abundance of two mosquito populations, Culex restuans and Culex pipiens. This seasonal shift usually precedes the time of the peak infection rate in mosquitoes by 2–3 weeks and generally occurs earlier in the summer with above normal temperatures and later in the summer with below-normal temperatures. Two empirical models were developed to predict this seasonal shift in mosquito species, or the “crossover,” and have been run operationally since 2004 by the Midwestern Regional Climate Center located at the Illinois State Water Survey. These models are based on daily temperature data and have been verified by use of a unique dataset of daily records of mosquito species abundance collected by the Illinois Natural History Survey. An unfortunate characteristic of the original temperature models was that the crossover date often was reached with little or no lead time. In 2009, the models were modified to incorporate National Weather Service (NWS) model output statistics (MOS) 10-day temperature forecasts. This paper evaluates the effectiveness of these models to predict the crossover date and thus the period of increased risk of West Nile virus in the Midwest.
For the 8-yr period from 2002 to 2009, 6 yr had at least one model predicting the crossover within one week of the actual crossover date, and for 7 yr at least one of the model predictions was within 2 weeks of the actual crossover date. Incorporation of MOS temperature forecasts for a 10-day period, although not substantially changing the predicted crossover date, greatly improved the forecast lead time by about 9 days. From a disease management point of view, this improvement in advanced notice is significant. In 2009, there was an unprecedented early crossover date and a failed forecast. The poor forecast was likely caused by an unusually early summer prolonged and intense heat wave, followed immediately by a record cold July.
