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Kenneth E. Kunkel, David R. Easterling, David A. R. Kristovich, Byron Gleason, Leslie Stoecker, and Rebecca Smith

Abstract

Daily extreme precipitation events, exceeding a threshold for a 1-in-5-yr occurrence, were identified from a network of 935 Cooperative Observer stations for the period of 1908–2009. Each event was assigned a meteorological cause, categorized as extratropical cyclone near a front (FRT), extratropical cyclone near center of low (ETC), tropical cyclone (TC), mesoscale convective system (MCS), air mass (isolated) convection (AMC), North American monsoon (NAM), and upslope flow (USF). The percentage of events ascribed to each cause were 54% for FRT, 24% for ETC, 13% for TC, 5% for MCS, 3% for NAM, 1% for AMC, and 0.1% for USF. On a national scale, there are upward trends in events associated with fronts and tropical cyclones, but no trends for other meteorological causes. On a regional scale, statistically significant upward trends in the frontal category are found in five of the nine regions. For ETCs, there are statistically significant upward trends in the Northeast and east north central. For the NAM category, the trend in the West is upward. The central region has seen an upward trend in events caused by TCs.

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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.

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

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.

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Rajarshi Das Bhowmik, A. Sankarasubramanian, Tushar Sinha, Jason Patskoski, G. Mahinthakumar, and Kenneth E. Kunkel

Abstract

Most of the currently employed procedures for bias correction and statistical downscaling primarily consider a univariate approach by developing a statistical relationship between large-scale precipitation/temperature with the local-scale precipitation/temperature, ignoring the interdependency between the two variables. In this study, a multivariate approach, asynchronous canonical correlation analysis (ACCA), is proposed and applied to global climate model (GCM) historic simulations and hindcasts from phase 5 of the Coupled Model Intercomparison Project (CMIP5) to downscale monthly precipitation and temperature over the conterminous United States. ACCA is first applied to the CNRM-CM5 GCM historical simulations for the period 1950–99 and compared with the bias-corrected dataset based on quantile mapping from the Bureau of Reclamation. ACCA is also applied to CNRM-CM5 hindcasts and compared with univariate asynchronous regression (ASR), which applies regular regression to sorted GCM and observed variables. ACCA performs better than ASR and quantile mapping in preserving the cross correlation at grid points where the observed cross correlations are significant while reducing fractional biases in mean and standard deviation. Results also show that preservation of cross correlation increases the bias in standard deviation slightly, but estimates observed precipitation and temperature with increased likelihood, particularly for months exhibiting significant cross correlation. ACCA also better estimates the joint likelihood of observed precipitation and temperature under hindcasts since hindcasts estimate the observed variability in precipitation better. Implications of preserving cross correlations across climate variables for projecting runoff and other land surface fluxes are also discussed.

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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.

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Ho-Chun Huang, Xin-Zhong Liang, Kenneth E. Kunkel, Michael Caughey, and Allen Williams

Abstract

The impacts of air pollution on the environment and human health could increase as a result of potential climate change. To assess such possible changes, model simulations of pollutant concentrations need to be performed at climatic (seasonal) rather than episodic (days) time scales, using future climate projections from a general circulation model. Such a modeling system was employed here, consisting of a regional climate model (RCM), an emissions model, and an air quality model. To assess overall model performance with one-way coupling, this system was used to simulate tropospheric ozone concentrations in the midwestern and northeastern United States for summer seasons between 1995 and 2000. The RCM meteorological conditions were driven by the National Centers for Environmental Prediction/Department of Energy global reanalysis (R-2) using the same procedure that integrates future climate model projections. Based on analyses for several urban and rural areas and regional domains, fairly good agreement with observations was found for the diurnal cycle and for several multiday periods of high ozone episodes. Even better agreement occurred between monthly and seasonal mean quantities of observed and model-simulated values. This is consistent with an RCM designed primarily to produce good simulations of monthly and seasonal mean statistics of weather systems.

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Xin-Zhong Liang, Jinhong Zhu, Kenneth E. Kunkel, Mingfang Ting, and Julian X. L. Wang

Abstract

This study uses the most recent simulations from all available fully coupled atmosphere–ocean general circulation models (CGCMs) to investigate whether the North American monsoon (NAM) precipitation seasonal–interannual variations are simulated and, if so, whether the key underlying physical mechanisms are correctly represented. This is facilitated by first identifying key centers where observed large-scale circulation fields and sea surface temperatures (SSTs) are significantly correlated with the NAM precipitation averages over the core region (central–northwest Mexico) and then examining if the modeled and observed patterns agree.

Two new findings result from the analysis of observed NAM interannual variations. First, precipitation exhibits significantly high positive (negative) correlations with 200-hPa meridional wind centered to the northwest (southeast) of the core region in June and September (July and August). As such, wet conditions are associated with strong anomalous southerly upper-level flow on the northwest flank during the monsoon onset and retreat, but with anomalous northerly flow on the southeast flank, during the peak of the monsoon. They are often identified with a cyclonic circulation anomaly pattern over the central Great Plains for the July–August peak monsoon and, reversely, an anticyclonic anomaly pattern centered over the northern (southern) Great Plains for the June (September) transition. Second, wet NAM conditions in June and July are also connected with a SST pattern of positive anomalies in the eastern Pacific and negative anomalies in the Gulf of Mexico, acting to reduce the climatological mean gradient between the two oceans. This pattern suggests a possible surface gradient forcing that favors a westward extension of the North Atlantic subtropical ridge. These two observed features connected to the NAM serve as the metric for quantitative evaluation of the model performance in simulating the important NAM precipitation mechanisms.

Out of 17 CGCMs, only the Meteorological Research Institute (MRI) model with a medium resolution consistently captures the observed NAM precipitation annual cycle (having a realistic amplitude and no phase shift) as well as interannual covariations with the planetary circulation patterns (having the correct sign and comparably high magnitude of correlation) throughout the summer. For the metric of correlations with 200-hPa meridional wind, there is general agreement among all CGCMs with observations for June and September. This may indicate that large-scale forcings dominate interannual variability for the monsoon onset and retreat, while variability of the peak of the monsoon in July and August may be largely influenced by local processes that are more challenging for CGCMs to resolve. For the metric of correlations with SSTs, good agreement is found only in June. These results suggest that the NAM precipitation interannual variability may likely be determined by large-scale circulation anomalies, while its predictability based on remote signals such as SSTs may not be sufficiently robust to be well captured by current CGCMs, with the exception of the June monsoon onset which is potentially more predictable.

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Xin-Zhong Liang, Min Xu, Kenneth E. Kunkel, Georg A. Grell, and John S. Kain

Abstract

The fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5)-based regional climate model (CMM5) simulations of U.S.–Mexico summer precipitation are quite sensitive to the choice of Grell or Kain–Fritsch convective parameterization. An ensemble based on these two parameterizations provides superior performance because distinct regions exist where each scheme complementarily captures certain observed signals. For the interannual anomaly, the ensemble provides the most significant improvement over the Rockies, Great Plains, and North American monsoon region. For the climate mean, the ensemble has the greatest impact on skill over the southeast United States and North American monsoon region, where CMM5 biases associated with the individual schemes are of opposite sign. Results are very sensitive to the specific methods used to generate the ensemble. While equal weighting of individual solutions provides a more skillful result overall, considerable further improvement is achieved when the weighting of individual solutions is optimized as a function of location.

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Xin-Zhong Liang, Li Li, Kenneth E. Kunkel, Mingfang Ting, and Julian X. L. Wang

Abstract

The fifth-generation PSU–NCAR Mesoscale Model (MM5)-based regional climate model (CMM5) capability in simulating the U.S. precipitation annual cycle is evaluated with a 1982–2002 continuous baseline integration driven by the NCEP–DOE second Atmospheric Model Intercomparison Project (AMIP II) reanalysis. The causes for major model biases (differences from observations) are studied through supplementary seasonal sensitivity experiments with various driving lateral boundary conditions (LBCs) and physics representations. It is demonstrated that the CMM5 has a pronounced rainfall downscaling skill, producing more realistic regional details and overall smaller biases than the driving global reanalysis. The precipitation simulation is most skillful in the Northwest, where orographic forcing dominates throughout the year; in the Midwest, where mesoscale convective complexes prevail in summer; and in the central Great Plains, where nocturnal low-level jet and rainfall peaks occur in summer. The actual model skill, however, is masked by existing large LBC uncertainties over data-poor areas, especially over oceans. For example, winter dry biases in the Gulf States likely result from LBC errors in the south and east buffer zones. On the other hand, several important regional biases are identified with model physics deficiencies. In particular, summer dry biases in the North American monsoon region and along the east coast of the United States can be largely rectified by replacing the Grell with the Kain–Fritsch cumulus scheme. The latter scheme, however, yields excessive rainfall in the Atlantic Ocean but large deficits over the Midwest. The fall dry biases over the lower Mississippi River basin, common to all existing global and regional models, remain unexplained and the search for their responsible physical mechanisms will be challenging. In addition, the representation of cloud–radiation interaction is essential in determining the precipitation distribution and regional water recycling, for which the new scheme implemented in the CMM5 yields significant improvement.

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Kenneth E. Kunkel, Stanley A. Changnon, Beth C. Reinke, and Raymond W. Arritt

A brief but intense heat wave developed in the central and eastern United States in mid-July 1995, causing hundreds of fatalities. The most notable feature of this event was the development of very high dewpoint temperature (T d ) over the southern Great Lakes region and the Upper Mississippi River Basin. At many locations, hourly values of T d set new records. The combination of high air and dewpoint temperatures resulted in daily average apparent temperatures exceeding 36°C over a large area on some days. A comparison with past heat waves shows that this was the most intense short-duration heat wave in at least the last 48 years at some locations in the southern Great Lakes region and Upper Mississippi River Basin. An analysis of historical data for Chicago, where the majority of fatalities occurred, indicates the intensity of this heat wave was exceeded only by a few periods in the 1910s and 1930s. Impacts in the Chicago urban center were exacerbated by an urban heat island that raised nocturnal temperatures by more than 2°C. An analysis of radiosonde data indicates that maximum daytime boundary layer mixing depths were only a few hundred meters in the core region of the heat wave. Simulations using a single-column version of a three-dimensional mesoscale model strongly suggest that this contributed to the very high values of T d since soil moisture in the central United States was near to above average and evapotransporation was likely high, causing a rapid moistening of the shallow boundary layer.

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