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Kenneth E. Kunkel, David R. Easterling, Kenneth Hubbard, Kelly Redmond, Karen Andsager, Michael C. Kruk, and Michael L. Spinar

Abstract

A recent comprehensive effort to digitize U.S. daily temperature and precipitation data observed prior to 1948 has resulted in a major enhancement in the computer database of the records of the National Weather Service’s cooperative observer network. Previous digitization efforts had been selective, concentrating on state or regional areas. Special quality control procedures were applied to these data to enhance their value for climatological analysis. The procedures involved a two-step process. In the first step, each individual temperature and precipitation data value was evaluated against a set of objective screening criteria to flag outliers. These criteria included extreme limits and spatial comparisons with nearby stations. The following data were automatically flagged: 1) all precipitation values exceeding 254 mm (10 in.) and 2) all temperature values whose anomaly from the monthly mean for that station exceeded five standard deviations. Additional values were flagged based on differences with nearby stations; in this case, metrics were used to rank outliers so that the limited resources were concentrated on those values most likely to be invalid. In the second step, each outlier was manually assessed by climatologists and assigned one of the four following flags: valid, plausible, questionable, or invalid. In excess of 22 400 values were manually assessed, of which about 48% were judged to be invalid. Although additional manual assessment of outliers might further improve the quality of the database, the procedures applied in this study appear to have been successful in identifying the most flagrant errors.

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Kenneth E. Kunkel, Michael A. Palecki, Leslie Ensor, David Easterling, Kenneth G. Hubbard, David Robinson, and Kelly Redmond

Abstract

Temporal variability in the occurrence of the most extreme snowfall years, both those with abundant snowfall amounts and those lacking snowfall, was examined using a set of 440 quality-controlled, homogenous U.S. snowfall records. The frequencies with which winter-centered annual snowfall totals exceeded the 90th and 10th percentile thresholds at individual stations were calculated from 1900–01 to 2006–07 for the conterminous United States, and for 9 standard climate regions. The area-weighted conterminous U.S. results do not show a statistically significant trend in the occurrence of either high or low snowfall years for the 107-yr period, but there are regional trends. Large decreases in the frequency of low-extreme snowfall years in the west north-central and east north-central United States are balanced by large increases in the frequency of low-extreme snowfall years in the Northeast, Southeast, and Northwest. During the latter portion of the period, from 1950–51 to 2006–07, trends are much more consistent, with the United States as a whole and the central and northwest U.S. regions in particular showing significant declines in high-extreme snowfall years, and four regions showing significant increases in the frequency of low-extreme snowfall years (i.e., Northeast, Southeast, south, and Northwest).

In almost all regions of the United States, temperature during November–March is more highly correlated than precipitation to the occurrence of extreme snowfall years. El Niño events are strongly associated with an increase in low-extreme snowfall years over the United States as a whole, and in the northwest, northeast, and central regions. A reduction in low-extreme snowfall years in the Southwest is also associated with El Niño. The impacts of La Niña events are strongest in the south and Southeast, favoring fewer high-extreme snowfall years, and, in the case of the south, more low-extreme snowfall years occur. The Northwest also has a significant reduction in the chance of a low-extreme snowfall year during La Niña. A combination of trends in temperature in the United States and changes in the frequency of ENSO modes influences the frequency of extreme snowfall years in the United States.

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Kenneth E. Kunkel, Michael A. Palecki, Kenneth G. Hubbard, David A. Robinson, Kelly T. Redmond, and David R. Easterling

Abstract

There is an increasing interest in examining long-term trends in measures of snow climatology. An examination of the U.S. daily snowfall records for 1900–2004 revealed numerous apparent inconsistencies. For example, long-term snowfall trends among neighboring lake-effect stations differ greatly from insignificant to +100% century−1. Internal inconsistencies in the snow records, such as a lack of upward trends in maximum seasonal snow depth at stations with large upward trends in snowfall, point to inhomogeneities. Nationwide, the frequency of daily observations with a 10:1 snowfall-to-liquid-equivalent ratio declined from 30% in the 1930s to a current value of around 10%, a change that is clearly due to observational practice. There then must be biases in cold-season liquid-equivalent precipitation, or snowfall, or both. An empirical adjustment of snow-event, liquid-equivalent precipitation indicates that the potential biases can be statistically significant.

Examples from this study show that there are nonclimatic issues that complicate the identification of and significantly change the trends in snow variables. Thus, great care should be taken in interpretation of time series of snow-related variables from the Cooperative Observer Program (COOP) network. Furthermore, full documentation of optional practices should be required of network observers so that future users of these data can properly account for such practices.

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Kenneth E. Kunkel, Stanley A. Changnon, Steven E. Hollinger, Beth C. Reinke, Wayne M. Wendland, and James R. Angel

Effective responses by government agencies, businesses, and private industry to climate disasters such as the disastrous Mississippi River flood of 1993 hinge on the regional availability of diverse up-to-date weather, climate, and water information. In addition to the obvious need for accurate forecasts and warnings of severe weather and floods, other types of meteorologically based information can contribute to effective responses. Some examples of information requested during and after the 1993 flood include 1) hydroclimatic assessments of the magnitude of the event, 2) agricultural assessments of the impacts of heavy rains and flooding on corn and soybean production, and 3) probabilistic outlooks of the recurrence of flooding based on soil moisture conditions. Quick responses to these climate information needs necessitate 1) a real-time climate monitoring system, 2) physical models to assess effects and impacts, and 3) scientific expertise to address complex issues.

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Kenneth E. Kunkel, Thomas R. Karl, Michael F. Squires, Xungang Yin, Steve T. Stegall, and David R. Easterling

Abstract

Trends of extreme precipitation (EP) using various combinations of average return intervals (ARIs) of 1, 2, 5, 10, and 20 years with durations of 1, 2, 5, 10, 20, and 30 days were calculated regionally across the contiguous United States. Changes in the sign of the trend of EP vary by region as well as by ARI and duration, despite the statistically significant upward trends for all combinations of EP thresholds when area averaged across the contiguous United States. Spatially, there is a pronounced east-to-west gradient in the trends of the EP with strong upward trends east of the Rocky Mountains. In general, upward trends are larger and more significant for longer ARIs, but the contribution to the trend in total seasonal and annual precipitation is significantly larger for shorter ARIs because they occur more frequently. Across much of the contiguous United States, upward trends of warm-season EP are substantially larger than those for the cold season and have a substantially greater effect on the annual trend in total precipitation. This result occurs even in areas where the total precipitation is nearly evenly divided between the cold and warm seasons. When compared with short-duration events, long-duration events—for example, 30 days—contribute the most to annual trends. Coincident statistically significant upward trends of EP and precipitable water (PW) occur in many regions, especially during the warm season. Increases in PW are likely to be one of several factors responsible for the increase in EP (and average total precipitation) observed in many areas across the contiguous United States.

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James P. Kossin, Thomas R. Karl, Thomas R. Knutson, Kerry A. Emanuel, Kenneth E. Kunkel, and James J. O’Brien
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Kenneth E. Kunkel, Karen Andsager, Xin-Zhong Liang, Raymond W. Arritt, Eugene S. Takle, William J. Gutowski Jr., and Zaitao Pan

Abstract

A regional climate model simulation of the period of 1979–88 over the contiguous United States, driven by lateral boundary conditions from the National Centers for Environmental Prediction–National Center for Atmospheric Research reanalysis, was analyzed to assess the ability of the model to simulate heavy precipitation events and seasonal precipitation anomalies. Heavy events were defined by precipitation totals that exceed the threshold value for a specified return period and duration. The model magnitudes of the thresholds for 1-day heavy precipitation events were in good agreement with observed thresholds for much of the central United States. Model thresholds were greater than observed for the eastern and intermountain western portions of the region and were smaller than observed for the lower Mississippi River basin. For 7-day events, model thresholds were in good agreement with observed thresholds for the eastern United States and Great Plains, were less than observed for the most of the Mississippi River valley, and were greater than observed for the intermountain western region. The interannual variability in frequency of heavy events in the model simulation exhibited similar behavior to that of the observed variability in the South, Southwest, West, and North-Central study regions. The agreement was poorer for the Midwest and Northeast, although the magnitude of variability was similar for both model and observations. There was good agreement between the model and observational data in the seasonal distribution of extreme events for the West and North-Central study regions; in the Southwest, Midwest, and Northeast, there were general similarities but some differences in the details of the distributions. The most notable differences occurred for the southern Gulf Coast region, for which the model produced a summer peak that is not present in the observational data. There was not a very high correlation in the timing of individual heavy events between the model and observations, reflecting differences between model and observations in the speed and path of many of the synoptic-scale events triggering the precipitation.

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Xin-Zhong Liang, Hyun I. Choi, Kenneth E. Kunkel, Yongjiu Dai, Everette Joseph, Julian X. L. Wang, and Praveen Kumar

Abstract

This paper utilizes the best available quality data from multiple sources to develop consistent surface boundary conditions (SBCs) for mesoscale regional climate model (RCM) applications. The primary SBCs include 1) fields of soil characteristic (bedrock depth, and sand and clay fraction profiles), which for the first time have been consistently introduced to define 3D soil properties; 2) fields of vegetation characteristic fields (land-cover category, and static fractional vegetation cover and varying leaf-plus-stem-area indices) to represent spatial and temporal variations of vegetation with improved data coherence and physical realism; and 3) daily sea surface temperature variations based on the most appropriate data currently available or other value-added alternatives. For each field, multiple data sources are compared to quantify uncertainties for selecting the best one or merged to create a consistent and complete spatial and temporal coverage. The SBCs so developed can be readily incorporated into any RCM suitable for U.S. climate and hydrology modeling studies, while the data processing and validation procedures can be more generally applied to construct SBCs for any specific domain over the globe.

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Kenneth E. Kunkel, Karen Andsager, Glen Conner, Wayne L. Decker, Harry J. Hillaker Jr., Pam Naber Knox, Fred V. Nurnberger, Jeffrey C. Rogers, Kenneth Scheeringa, Wayne M. Wendland, James Zandlo, and James R. Angel

Daily observations of precipitation and maximum and minimum temperature from the National Weather Service's cooperative observer network collected prior to 1948 were keyed into a digital database. This database includes stations in the nine midwestern states of Illinois, Indiana, Iowa, Kentucky, Michigan, Minnesota, Missouri, Ohio, and Wisconsin. The primary source used in this project was the publication Climatological Data, which began in 1896. This database provides a substantial enhancement to the National Climatic Data Center's TD-3200 Summary of the Day database, which includes little data prior to 1948. Approximately 2 × 107 data values were keyed, increasing the amount of pre- 1948 digital data by about a factor of 3 and substantially improving its spatial uniformity. The data were subjected to an extensive set of quality control procedures. It is expected that these data will find their greatest value in applications requiring very long historical records, such as assessments of the risks of extreme events.

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Gerald A. Meehl, Thomas Karl, David R. Easterling, Stanley Changnon, Roger Pielke Jr., David Changnon, Jenni Evans, Pavel Ya. Groisman, Thomas R. Knutson, Kenneth E. Kunkel, Linda O. Mearns, Camille Parmesan, Roger Pulwarty, Terry Root, Richard T. Sylves, Peter Whetton, and Francis Zwiers

Weather and climatic extremes can have serious and damaging effects on human society and infrastructure as well as on ecosystems and wildlife. Thus, they are usually the main focus of attention of the news media in reports on climate. There are some indications from observations concerning how climatic extremes may have changed in the past. Climate models show how they could change in the future either due to natural climate fluctuations or under conditions of greenhouse gas-induced warming. These observed and modeled changes relate directly to the understanding of socioeconomic and ecological impacts related to extremes.

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