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Melissa S. Bukovsky

Abstract

The skill of six regional climate models (RCMs) in reproducing short-term (24-yr), observed, near-surface temperature trends when driven by reanalysis is examined. The RCMs are part of the North American Regional Climate Change Assessment Program (NARCCAP). If RCMs can reproduce observed temperature trends, then they are, in a way, demonstrating their ability to capture a type of climate change, which may be relevant to their ability to credibly simulate anthropogenic climate changes under future emission scenarios. This study finds that the NARCCAP RCMs can simulate some resolved-scale temperature trends, especially those seen recently in spring and, by and large, in winter. However, results in other seasons suggest that RCM performance in this measure may be dependent on the type and strength of the forcing behind the observed trends.

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Melissa S. Bukovsky
and
David J. Karoly

Abstract

This note examines the sensitivity of simulated U.S. warm-season precipitation in the Weather Research and Forecasting model (WRF), used as a nested regional climate model, to variations in model setup. Numerous options have been tested and a few of the more interesting and unexpected sensitivities are documented here. Specifically, the impacts of changes in convective and land surface parameterizations, nest feedbacks, sea surface temperature, and WRF version on mean precipitation are evaluated in 4-month-long simulations. Running the model over an entire season has brought to light some issues that are not otherwise apparent in shorter, weather forecast–type simulations, emphasizing the need for careful scrutiny of output from any model simulation. After substantial testing, a reasonable model setup was found that produced a definite improvement in the climatological characteristics of precipitation over that from the National Centers for Environmental Prediction–National Center for Atmospheric Research global reanalysis, the dataset used for WRF initial and boundary conditions in this analysis.

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Melissa S. Bukovsky
and
David J. Karoly

Abstract

Several aspects of the precipitation climatology from the North American Regional Reanalysis (NARR) are analyzed and compared with two other reanalyses and one set of gridded observations over a domain encompassing the United States. The spatial distribution, diurnal cycle, and annual cycle of precipitation are explored to establish the reliability of the reanalyses and to judge their usefulness. While the NARR provides a much improved representation of precipitation over that of the other reanalyses examined, some inaccuracies are found and have been highlighted as a warning to potential users of the data.

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Melissa S. Bukovsky
and
David J. Karoly

Abstract

In this study, the Weather Research and Forecasting (WRF) model is employed as a nested regional climate model to dynamically downscale output from the National Center for Atmospheric Research’s (NCAR’s) Community Climate System Model (CCSM) version 3 and the National Centers for Environmental Prediction (NCEP)–NCAR global reanalysis (NNRP). The latter is used for verification of late-twentieth-century climate simulations from the WRF.

This analysis finds that the WRF is able to produce precipitation that is more realistic than that from its driving systems (the CCSM and NNRP). It also diagnoses potential issues with and differences between all of the simulations completed. Specifically, the magnitude of heavy 6-h average precipitation events, the frequency distribution, and the diurnal cycle of precipitation over the central United States are greatly improved. Projections from the WRF for late-twenty-first-century precipitation show decreases in average May–August (MJJA) precipitation, but increases in the intensity of both heavy precipitation events and rain in general when it does fall. A decrease in the number of 6-h periods with rainfall accounts for the overall decrease in average precipitation. The WRF also shows an increase in the frequency of very heavy to extreme 6-h average events, but a decrease in the frequency of all events lighter than those over the central United States. Overall, projections from this study suggest an increase in the frequency of both floods and droughts during the warm season in the central United States.

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Melissa S. Bukovsky
,
John S. Kain
, and
Michael E. Baldwin

Abstract

Bowing, propagating precipitation features that sometimes appear in NCEP's North American Mesoscale model (NAM; formerly called the Eta Model) forecasts are examined. These features are shown to be associated with an unusual convective heating profile generated by the Betts–Miller–Janjić convective parameterization in certain environments. A key component of this profile is a deep layer of cooling in the lower to middle troposphere. This strong cooling tendency induces circulations that favor expansion of parameterized convective activity into nearby grid columns, which can lead to growing, self-perpetuating mesoscale systems under certain conditions. The propagation characteristics of these systems are examined and three contributing mechanisms of propagation are identified. These include a mesoscale downdraft induced by the deep lower-to-middle tropospheric cooling, a convectively induced buoyancy bore, and a boundary layer cold pool that is indirectly produced by the convective scheme in this environment. Each of these mechanisms destabilizes the adjacent atmosphere and decreases convective inhibition in nearby grid columns, promoting new convective development, expansion, and propagation of the larger system. These systems appear to show a poor correspondence with observations of bow echoes on time and space scales that are relevant for regional weather prediction, but they may provide important clues about the propagation mechanisms of real convective systems.

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Melissa S. Bukovsky
,
David J. Gochis
, and
Linda O. Mearns

Abstract

The authors examine 17 dynamically downscaled simulations produced as part of the North American Regional Climate Change Assessment Program (NARCCAP) for their skill in reproducing the North American monsoon system. The focus is on precipitation and the drivers behind the precipitation biases seen in the simulations of the current climate. Thus, a process-based approach to the question of model fidelity is taken in order to help assess confidence in this suite of simulations.

The results show that the regional climate models (RCMs) forced with a reanalysis product and atmosphere-only global climate model (AGCM) time-slice simulations perform reasonably well over the core Mexican and southwest United States regions. Some of the dynamically downscaled simulations do, however, have strong dry biases in Arizona that are related to their inability to develop credible monsoon flow structure over the Gulf of California. When forced with different atmosphere–ocean coupled global climate models (AOGCMs) for the current period, the skill of the RCMs subdivides largely by the skill of the forcing or “parent” AOGCM. How the inherited biases affect the RCM simulations is investigated. While it is clear that the AOGCMs have a large influence on the RCMs, the authors also demonstrate where the regional models add value to the simulations and discuss the differential credibility of the six RCMs (17 total simulations), two AGCM time slices, and four AOGCMs examined herein. It is found that in-depth analysis of parent GCM and RCM scenarios can identify a meaningful subset of models that can produce credible simulations of the North American monsoon precipitation.

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Linda O. Mearns
,
Melissa S. Bukovsky
, and
Vanessa J. Schweizer

Abstract

In this brief article, we report the initial results of an expert elicitation with the co-PIs (regional climate modelers) of the North American Regional Climate Change Assessment Program regarding their evaluation of the relative quality of regional climate model simulations focusing on the subregion dominated by the North American monsoon (NAM). We assumed that an expert elicitation framework might reveal interesting beliefs and understanding that would be different from what would be obtained from calculating quantitative metrics associated with model quality.

The simulations considered were of six regional climate models (RCMs) that used NCEP Reanalysis 2 as boundary conditions for the years 1980–2004. The domain covers most of North America and adjacent oceans. The seven participating regional modelers were asked to complete surveys on their background beliefs about model credibility and their judgments regarding the quality of the six models based on a series of plots of variables related to the NAM (e.g., temperature, winds, humidity, moisture flux, precipitation). The specific RCMs were not identified.

We also compared the results of the expert elicitation with those obtained from using a series of metrics developed to evaluate a European collection of climate model simulations. The results proved to be quite different in the two cases.

The results of this exercise proved very enlightening regarding regional modelers’ perceptions of model quality and their beliefs about how this information should or should not be used. Based on these pilot study results, we believe a more complete study is warranted.

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Melissa S. Bukovsky
,
Rachel R. McCrary
,
Anji Seth
, and
Linda O. Mearns

Abstract

Global and regional climate model ensembles project that the annual cycle of rainfall over the southern Great Plains (SGP) will amplify by midcentury. Models indicate that warm-season precipitation will increase during the early spring wet season but shift north earlier in the season, intensifying late summer drying. Regional climate models (RCMs) project larger precipitation changes than their global climate model (GCM) counterparts. This is particularly true during the dry season. The credibility of the RCM projections is established by exploring the larger-scale dynamical and local land–atmosphere feedback processes that drive future changes in the simulations, that is, the responsible mechanisms or processes. In this case, it is found that out of 12 RCM simulations produced for the North American Regional Climate Change Assessment Program (NARCCAP), the majority are mechanistically credible and consistent in the mean changes they are producing in the SGP. Both larger-scale dynamical processes and local land–atmosphere feedbacks drive an earlier end to the spring wet period and deepening of the summer dry season in the SGP. The midlatitude upper-level jet shifts northward, the monsoon anticyclone expands, and the Great Plains low-level jet increases in strength, all supporting a poleward shift in precipitation in the future. This dynamically forced shift causes land–atmosphere coupling to strengthen earlier in the summer, which in turn leads to earlier evaporation of soil moisture in the summer, resulting in extreme drying later in the summer.

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Melissa S. Bukovsky
,
William Gutowski
,
Linda O. Mearns
,
Dominique Paquin
, and
Sara C. Pryor
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Melissa S. Bukovsky
,
Carlos M. Carrillo
,
David J. Gochis
,
Dorit M. Hammerling
,
Rachel R. McCrary
, and
Linda O. Mearns

Abstract

This study presents climate change results from the North American Regional Climate Change Assessment Program (NARCCAP) suite of dynamically downscaled simulations for the North American monsoon system in the southwestern United States and northwestern Mexico. The focus is on changes in precipitation and the processes driving the projected changes from the regional climate simulations and their driving coupled atmosphere–ocean global climate models. The effect of known biases on the projections is also examined. Overall, there is strong ensemble agreement for a large decrease in precipitation during the monsoon season; however, this agreement and the magnitude of the ensemble-mean change is likely deceiving, as the greatest decreases are produced by the simulations that are the most biased in the baseline/current climate. Furthermore, some of the greatest decreases in precipitation are being driven by changes in processes/phenomena that are less credible (e.g., changes in El Niño–Southern Oscillation, when it is initially not simulated well). In other simulations, the processes driving the precipitation change may be plausible, but other biases (e.g., biases in low-level moisture or precipitation intensity) appear to be affecting the magnitude of the projected changes. The most and least credible simulations are clearly identified, while the other simulations are mixed in their abilities to produce projections of value.

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