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Kenneth E. Kunkel

Abstract

A series of simple procedures are presented for extrapolating climatic averages of humidity variables from a reference location with long-term humidity measurements to nearby higher elevation locations. The extrapolation of monthly average dewpoint temperature is accomplished by using an exponential function for the height decrease of water vapor pressure. This procedure results in a lapse rate of dewpoint temperature which is to a first approximation a constant. lie root-mean-square (rms) error in estimating dewpoint temperature at nine higher elevation locations averaged 1.I°C. Summer wet-bulb design temperatures are estimated using a region-wide lapse rate of 4.4°C km−1. The rms error in estimating 1%, 2.5%, and 5% wet-bulb design temperatures at 12 higher elevation locations was 0.9°C. Three-hour monthly average wet-bulb temperatures and relative humidity are estimated from the 3-hour monthly average dewpoint temperature and the 3-hour monthly average air temperature at the reference location with the following procedure. An estimate of the 3-hour monthly average air temperature at the desired location is obtained using an average lapse rate calculated from the monthly mean maximum and minimum temperatures at the two locations. An estimate of 3-hour monthly average dewpoint temperature is obtained using the same procedure that was developed for monthly average dewpoint temperature. Estimates of 3-hour monthly average wet-bulb temperature and relative humidity are then calculated from the estimated air and dewpoint temperatures. A test of this procedure for two station pairs resulted in good agreement for 3-hour monthly average air and wet-bulb temperatures with rms values of 0.8°C and 0.7°C, respectively. The rms error for 3-hour monthly average relative humidity was 5%, however, with some individual errors around 10%.

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Kenneth E. Kunkel and Xin-Zhong Liang

Abstract

A diagnostic analysis of relationships between central U.S. climate characteristics and various flow and scalar fields was used to evaluate nine global coupled ocean–atmosphere general circulation models (CGCMs) participating in the Coupled Model Intercomparison Project (CMIP). To facilitate identification of physical mechanisms causing biases, data from 21 models participating in the Atmospheric Model Intercomparison Project (AMIP) were also used for certain key analyses.

Most models reproduce basic features of the circulation, temperature, and precipitation patterns in the central United States, although no model exhibits small differences from the observationally based data for all characteristics in all seasons. Model ensemble means generally produce better agreement with the observationally based data than any single model. A fall precipitation deficiency, found in all AMIP and CMIP models except the third-generation Hadley Centre CGCM (HadCM3), appears to be related in part to slight biases in the flow on the western flank of the Atlantic subtropical ridge. In the model mean, the ridge at 850 hPa is displaced slightly to the north and to the west, resulting in weaker southerly flow into the central United States.

The CMIP doubled-CO2 transient runs show warming (1°–5°C) for all models and seasons and variable precipitation changes over the central United States. Temperature (precipitation) changes are larger (mostly less) than the variations that are observed in the twentieth century and the model variations in the control simulations.

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Kenneth E. Kunkel, Karen Andsager, and David R. Easterling

Abstract

This paper describes the results of an analysis of trends in short duration (1–7 days) extreme precipitation events that have a recurrence interval of 1 yr or longer for stations in the United States and Canada. This definition of extreme precipitation was chosen because such events are highly correlated with hydrologic flooding in some U.S. regions. The dominant temporal characteristic of a national event composite index is significant low-frequency variability. There were lengthy periods of a below-average number of events in the 1930s and 1950s and an above-average number of events in the early 1940s, early 1980s, and 1990s. Regional variations often differ substantially from the national composite. A simple linear analysis indicates that the overall trend covering the period 1931–96 has been upward at a highly statistically significant rate over the southwest United States and in a broad region from the central Great Plains across the middle Mississippi River and southern Great Lakes basins. The national trend for the United States is upward at a rate of 3% decade−1 for the period 1931–96. While the annual trend for Canada is upward for the period 1951–93, it is not statistically significant. Although the high statistical significance of the results is partially a consequence of the low frequency during the 1930s and 1950s located in the first half of the record, the latter half of the record exhibits an upward trend nearly identical to the entire record. However, an analysis of a 101-yr record of midwestern stations shows that heavy precipitation event frequencies around the turn of the twentieth century (1896–1906) were higher than for other periods of comparable length, except for 1986–96. Although data were not available in digital form to extend the analysis back to 1896 for the entire United States, the midwestern analysis shows that interpretation of the recent upward trends must account for the possibility of significant natural forcing of variability on century timescales.

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Kenneth E. Kunkel, Xin-Zhong Liang, Jinhong Zhu, and Yiruo Lin

Abstract

The observed lack of twentieth-century warming in the central United States (CUS), denoted here as the “warming hole,” was examined in 55 simulations driven by external historical forcings and in 19 preindustrial control (unforced) simulations from 18 coupled general circulation models (CGCMs). Twentieth-century CUS trends were positive for the great majority of simulations, but were negative, as observed, for seven simulations. Only a few simulations exhibited the observed rapid rate of warming (cooling) during 1901–40 (1940–79). Those models with multiple runs (identical forcing but different initial conditions) showed considerable intramodel variability with trends varying by up to 1.8°C century−1, suggesting that internal dynamic variability played a major role at the regional scale. The wide range of trend outcomes, particularly for those models with multiple runs, and the small number of simulations similar to observations in both the forced and unforced experiments suggest that the warming hole is not a robust response of contemporary CGCMs to the estimated external forcings. A more likely explanation based on these models is that the observed warming hole involves external forcings combined with internal dynamic variability that is much larger than typically simulated.

The observed CUS temperature variations are positively correlated with North Atlantic (NA) sea surface temperatures (SSTs), and both NA SSTs and CUS temperature are negatively correlated with central equatorial Pacific (CEP) SSTs. Most models simulate rather well the connection between CUS temperature and NA SSTs. However, the teleconnections between NA and CEP SSTS and between CEP SSTs and CUS temperature are poorly simulated and the models produce substantially less NA SST variability than observed, perhaps hampering their ability to reproduce the warming hole.

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Xin-Zhong Liang, Kenneth E. Kunkel, and Arthur N. Samel

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A regional climate model (RCM) is being developed for U.S. Midwest applications on the basis of the newly released Pennsylvania State University–NCAR Fifth-Generation Mesoscale Model (MM5), version 3.3. This study determines the optimal RCM domain and effective data assimilation technique to accurately integrate lateral boundary conditions (LBCs) across the buffer zones. The LBCs are constructed from both the NCEP–NCAR and ECMWF reanalyses to depict forcing uncertainties. The RCM domain was chosen to correctly represent the governing physical processes while minimizing LBC errors. Sensitivity experiments are conducted for the Midwest 1993 summer flood to investigate buffer zone treatment impacts on RCM performance.

The results demonstrate the superiority of the buffer zone treatment that consists of the physically based domain choice and revised assimilation technique. Given this treatment, the RCM realistically simulates both temporal variations and spatial distributions in the major flood area (MFA). This success is identified with the accurate representation of both the midlatitude upper-level jet stream and Great Plains low-level jet (LLJ). The RCM reproduces different climate regimes, where observed rainfall was identified with the periodic (5 day) passage of midlatitude cyclones in June and persistent synoptic circulations in July. The model also correctly simulates the MFA rainfall diurnal cycle (with the peak amount at 0900 UTC), which follows the LLJ cycle by approximately 3 h. On the other hand, RCM performance is substantially reduced when the southern buffer zone extends to the Tropics, where large forcing errors exist. In particular, the RCM generates a weaker LLJ and, as a consequence, a decreased amount and delayed diurnal cycle of the MFA rainfall. In addition, the MM5 default LBC data assimilation technique produces considerable model biases, whereas the revised technique improves overall RCM performance and reduces sensitivity to domain size.

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Kenneth E. Kunkel, Xin-Zhong Liang, and Jinhong Zhu

Abstract

Regional climate model (RCM) simulations, driven by low and high climate-sensitivity coupled general circulation models (CGCMs) under various future emissions scenarios, were compared to projected changes in heat wave characteristics. The RCM downscaling reduces the CGCM biases in heat wave threshold temperature by a factor of 2, suggesting a higher credibility in the future projections. All of the RCM simulations suggest that there is a high probability of heat waves of unprecedented severity by the end of the twenty-first century if a high emissions path is followed. In particular, the annual 3-day heat wave temperature increases generally by 3°–8°C; the number of heat wave days increases by 30–60 day yr−1 over much of the western and southern United States with slightly smaller increases elsewhere; the variance spectra for intermediate, 3–7 days (prolonged, 7–14 days), temperature extremes increase (decrease) in the central (western) United States. If a lower emissions path is followed, then the outcomes range from quite small changes to substantial increases. In all cases, the mean temperature climatological shift is the dominant change in heat wave characteristics, suggesting that adaptation and acclimatization could reduce effects.

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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, 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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