Search Results

You are looking at 1 - 10 of 12 items for :

  • Author or Editor: Kenneth E. Kunkel x
  • Journal of Applied Meteorology and Climatology x
  • All content x
Clear All Modify Search
Kenneth E. Kunkel

Abstract

Many climatological locations report only maximum and minimum temperatures. However, in certain applications, such as estimation of design temperatures, the frequency distribution of hourly temperatures is required. For this reason, a method is developed for estimating the mathematical form of the upper half of the cumulative probability distribution function (CDF) for hourly temperatures from the CDF for daily maximum temperatures for the summer months of June, July and August. In this method, an exponential function is fitted to the daily maximum CDF. A procedure for estimating the hourly CDF from the daily CDF is presented. This method is used to estimate summer design temperatures for a number of stations in New Mexico.

Full access
Kenneth E. Kunkel

Abstract

An operational soil moisture monitoring capability for the midwestern United States is developed using a multilayer soil water balance model which incorporates daily weather data to calculate precipitation, soil evaporation, plant transpiration, runoff, and drainage through the soil profile. The effects of vegetation on soil evaporation and plant transpiration are incorporated through the use of a model for the growth and development of corn. Data requirements include daily observations of maximum temperature, minimum temperature, and precipitation and hourly observations of cloud cover, humidity, and wind speed; these data are collected in real time and aggregated on a climate division scale. The average characteristics of the dominant soils in each climate division are used as representative of that climate division. Using these weather and soils data, the model makes estimates of the current soil moisture status on a climate division basis updated daily. Historical soil moisture estimates using this same model were generated for the period 1949–89 to provide an historical perspective on current soil moisture estimates. This information is accessible to the public through a dial-up computer information system.

Full access
Steve T. Stegall and Kenneth E. Kunkel

Abstract

A simple index of extreme surface (2 m) monthly temperature was analyzed over the conterminous United States for 13 models from the Coupled Model Intercomparison Project phase 5 (CMIP5) hindcast (1981–2010) and prediction (2006–35) datasets as well as the U.S. climate division dataset, version 2 (nClimDiv), as observations for 1981–2010. Results are analyzed for regions defined in the recent Third U.S. National Climate Assessment. There is good agreement between models and observations for all regions for the annual warm and cold indices except for the warm index in the Northwest. For seasonal values of the temperature index, model simulations generally agree with the sign of the observed seasonal trends in all regions except for the Northwest and a few seasons in the “warming hole” areas of the central and southeastern United States. Most individual ensemble member simulations agree with the sign of the observed trend. However, in all regions and seasons, some simulations, in the range of 10%–40% of all ensemble members, show opposite signs, indicating that even overall skillful projections can have substantial uncertainty. These results indicate that there is potential skill in use of GCMs to provide projections of hot and cold extremes on the 30-yr time scale. However, it is important to note that natural variability is comparable to the forced signal on this time scale and thus introduces uncertainty. Analysis of the future simulations (2006–35) indicates that warm extremes increase rapidly while cold extremes become substantially more rare.

Full access
Steve T. Stegall and Kenneth E. Kunkel

Abstract

The CMIP5 decadal hindcast (“Hindcast”) and prediction (“Predict”) experiment simulations from 11 models were analyzed for the United States with respect to two metrics of extreme precipitation: the 10-yr return level of daily precipitation, derived from the annual maximum series of daily precipitation, and the total precipitation exceeding the 99.5th percentile of daily precipitation. Both Hindcast simulations and observations generally show increases for the 1981–2010 historical period. The multimodel-mean Hindcast trends are statistically significant for all regions while the observed trends are statistically significant for the Northeast, Southeast, and Midwest regions. An analysis of CMIP5 simulations driven by historical natural (“HistoricalNat”) forcings shows that the Hindcast trends are generally within the 5th–95th-percentile range of HistoricalNat trends, but those outside that range are heavily skewed toward exceedances of the 95th-percentile threshold. Future projections for 2006–35 indicate increases in all regions with respect to 1981–2010. While there is good qualitative agreement between the observations and Hindcast simulations regarding the direction of recent trends, the multimodel-mean trends are similar for all regions, while there is considerable regional variability in observed trends. Furthermore, the HistoricalNat simulations suggest that observed historical trends are a combination of natural variability and anthropogenic forcing. Thus, the influence of anthropogenic forcing on the magnitude of near-term future changes could be temporarily masked by natural variability. However, continued observed increases in extreme precipitation in the first decade (2006–15) of the “future” period partially confirm the Predict results, suggesting that incorporation of increases in planning would appear prudent.

Full access
Stanley A. Changnon and Kenneth E. Kunkel

Abstract

A unique rainstorm in northern Illinois produced 43 cm of precipitation in mid-July 1996, the highest 24-h precipitation amount ever recorded officially in the upper Midwest. Rains exceeding 20 cm fell over an area of 4400 km2, creating extremely damaging flash floods in portions of Chicago and its suburbs. Measurements from 496 rain gauges, including 80 recording gauges in the heavy rain area, made it possible to accurately define this storm.

The heavy rains were the result of two massive mesoscale convective systems, one in the afternoon and one at night. These systems formed to the north of a nearby stationary warm front. Several factors contributed to the excessive rainfall. Excessive moisture was present to the southwest of the warm front over Iowa and western Illinois; atmospheric moisture content was enhanced by surface evaporation from a very wet surface created by heavy rains the previous day, creating a conditionally unstable atmosphere. A cool air mass transported by easterly winds off Lake Michigan strengthened and slowed the movement of the warm front. A low-level jet oriented perpendicular to the warm front resulted in rising motion north of the warm front. These factors (instability, moisture availability, lifting mechanism) combined to form intense storms. This paper, the first of a three-part series, describes the storm in detail, including its morphology and causes, and the resulting rainfall distributions.

Full access
Nancy E. Westcott, Steven E. Hollinger, and Kenneth E. Kunkel

Abstract

This study evaluated the suitability of rain estimates based on the National Weather Service (NWS) Weather Surveillance Radar-1988 Doppler (WSR-88D) network to estimate yield response to rainfall on a county scale and to provide real-time information related to crop stress resulting from deficient or excessive precipitation throughout the summer. The relationship between normalized corn yield and rainfall was examined for nine states in the central United States for 1997–99 and 2001–02. Monthly rainfall estimates were computed employing multisensor precipitation estimate (MPE) data from the National Centers for Environmental Prediction and quality-controlled (QC_Coop) and real-time (RT_Coop) NWS cooperative gauge data. In-season MPE rain estimates were found to be of comparable quality to the postseason QC_Coop estimates for predicting county corn yields. Both MPE and QC_Coop estimates were better related to corn yield than were RT_Coop estimates, presumably because of the lower density of RT_Coop gauges. Large corn yields typically resulted when May rain was less than 125 mm and July rain was greater than 50 mm. Low yields often occurred when July rainfall was less than 100 mm. For moderate July rains (50–100 mm), positive and negative normalized yields resulted. Parameterization of heat stress (number of July days > 32.2°C) improved the correlation between rainfall and normalized corn yield, particularly for years with the poorest yield-vs-rain relationship (1998 and 1999). For the combined analysis years, the multiple regression correlation coefficient was 0.56, incorporating May and July rainfall and July heat stress and explaining 31% of the variance of normalized corn yield. Results show that MPE rainfall estimates provide timely yield projections within the growing season.

Full access
Mary Schoen Petersen, Peter J. Lamb, and Kenneth E. Kunkel

Abstract

A semiphysical solar radiation (SR) model is implemented to generate a new historical daily SR database for 53 locations in nine Midwestern and six adjacent states (available from the Midwestern Climate Center). This model estimates daily SR using standard hourly meteorological observations (surface atmospheric pressure and dewpoint temperature; cloud height and fractional sky cover by layer) as well as time of day, day of year, latitude/longitude, and the daily presence/absence of snow cover as input. Because of an extensive effort to interpolate for missing input (especially cloud) data, the daily SR dataset generated is 92% complete for all 53 stations for 1948–91, and 99% complete for the 43 stations with continuous hourly meteorological observations that commenced during 1945–50 and extended through 1991. Consistent with previous work, the model validates favorably against sets of daily SR measurements from (three) contrasting parts of the study region, and so its output is used here without adjustment.

Analyses of the dataset document the basic Midwestern spatial and temporal SR variability since the mid-to late 1940s. The spatial variation of calendar monthly mean SR is dominated by a near-meridional (north-eastward) decrease in fall and winter. This fundamental pattern is substantially perturbed from midspring through summer by subregional-to-mesoscale variability around and across the Great Lakes. Time series of individual monthly station mean SR values exhibit a pronounced, regionwide 1945–91 downtrend for August–November. This decline is strongest (∼12%) and most statistically significant (>99% level) for October in a belt extending east-southeastward from west-central Wisconsin across southern lake Michigan and western Lake Erie to western Pennsylvania. The SR trends for December–July are largely positive but of lesser spatial coherence, temporal consistency, and statistical significance.

Full access
Jared Rennie, Jesse E. Bell, Kenneth E. Kunkel, Stephanie Herring, Heidi Cullen, and Azar M. Abadi

Abstract

Land surface air temperature products have been essential for monitoring the evolution of the climate system. Before a temperature dataset is included in such analyses, it is important that nonclimatic influences be removed or changed so that the dataset is considered to be homogenous. These inhomogeneities include changes in station location, instrumentation, and observing practices. Many homogenized products exist on the monthly time scale, but few daily and weekly products exist. Recently, a submonthly homogenized dataset has been developed using data and software from NOAA’s National Centers for Environmental Information. Homogeneous daily data are useful for identification and attribution of extreme heat events. Projections of increasing temperatures are expected to result in corresponding increases in the frequency, duration, and intensity of such events. It is also established that heat events can have significant public health impacts, including increases in mortality and morbidity. The method to identify extreme heat events using daily homogeneous temperature data is described and used to develop a climatology of heat event onset, length, and severity. This climatology encompasses nearly 3000 extreme maximum and minimum temperature events across the United States since 1901. A sizeable number of events occurred during the Dust Bowl period of the 1930s; however, trend analysis shows an increase in heat event number and length since 1951. Overnight extreme minimum temperature events are increasing more than daytime maximum temperatures, and regional analysis shows that events are becoming much more prevalent in the western and southeastern parts of the United States.

Free access
Robert M. Rauber, Larry S. Olthoff, Mohan K. Ramamurthy, Dianne Miller, and Kenneth E. Kunkel

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.

Full access
Robert M. Rauber, Larry S. Olthoff, Mohan K. Ramamurthy, and Kenneth E. Kunkel

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.

Full access