Decreasing grid spacing in mesoscale models to less than 10-15 km generally improves the realism of the results but does not necessarily significantly improve the objectively scored accuracy of the forecasts. A major question confronting the meteorological community regards the benefits of increasing horizontal resolution in short-range (1-3 day) numerical weather prediction models. As computer power has increased, operational model resolution has followed-from a horizontal grid spacing of 381 km in the National Meteorological Center barotropic model in the late 1950s to 12 km in the current version of the National Centers for

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In part III of a three-part study on North American climate in phase 5 of the Coupled Model Intercomparison Project (CMIP5) models, the authors examine projections of twenty-first-century climate in the representative concentration pathway 8.5 (RCP8.5) emission experiments. This paper summarizes and synthesizes results from several coordinated studies by the authors. Aspects of North American climate change that are examined include changes in continental-scale temperature and the hydrologic cycle, extremes events, and storm tracks, as well as regional manifestations of these climate variables. The authors also examine changes in the eastern North Pacific and North Atlantic tropical cyclone activity and North American intraseasonal to decadal variability, including changes in teleconnections to other regions of the globe. Projected changes are generally consistent with those previously published for CMIP3, although CMIP5 model projections differ importantly from those of CMIP3 in some aspects, including CMIP5 model agreement on increased central California precipitation. The paper also highlights uncertainties and limitations based on current results as priorities for further research. Although many projected changes in North American climate are consistent across CMIP5 models, substantial intermodel disagreement exists in other aspects. Areas of disagreement include projections of changes in snow water equivalent on a regional basis, summer Arctic sea ice extent, the magnitude and sign of regional precipitation changes, extreme heat events across the northern United States, and Atlantic and east Pacific tropical cyclone activity.

(includes mixed phase and graupel) explicit scheme and MRF PBL (with no heat/moisture surface fluxes). Klemp and Durran's (1983) upper-radiative boundary condition and a sponge layer were applied in order to prevent gravity waves from being reflected off the model top. The 2-D runs included rotational effects (f ~10-4 s-1), therefore terrain-normal flow can develop when a pressure gradient exists in the x-direction. Below are how the parameters were varied: U = 5, 10, 15, 20, 25, and 30 m s-1. h m = 500, 1000, 1500, 2000, and 2500 m. N m = 0.005 and 0.01 s-1. L = 50 and 25 km. FL = slightly below surface (sea-level temperature = 270 o K, FLSFC), at 750 mb (FL750), and at 500 mb (FL500). 3. ROLE OF THE MOUNTAIN CIRCULATION For the first set of experiments both L and FL were fixed at 50 km and 750 mb, respectively. Figure 1 shows the accumulated 6-12 h precipitation across the barrier for a fixed ambient wind speed but slowly increasing mountain height. As a result, the variations in Froude number are determined by changes in barrier height. For the simulations using U =10 m s-1 and N m ,=0.01 s-1 (Fig. 1a), the precipitation distribution is broad and decreases Figure 1. Accumulated precipitation (6-12 h) as a function of terrain height (see inset box) for (a) 10 m s-1 , N m = 0.01 s-1 and (b) 20 m s-1 , N m = 0.01 s-1. (c) and (d) Same as (a) and (b) except for N m = 0.005 s-1. The thick gray line is the mountain location.

This is the first part of a three-part paper on North American climate in phase 5 of the Coupled Model Intercomparison Project (CMIP5) that evaluates the historical simulations of continental and regional climatology with a focus on a core set of 17 models. The authors evaluate the models for a set of basic surface climate and hydrological variables and their extremes for the continent. This is supplemented by evaluations for selected regional climate processes relevant to North American climate, including cool season western Atlantic cyclones, the North American monsoon, the U.S. Great Plains low-level jet, and Arctic sea ice. In general, the multimodel ensemble mean represents the observed spatial patterns of basic climate and hydrological variables but with large variability across models and regions in the magnitude and sign of errors. No single model stands out as being particularly better or worse across all analyses, although some models consistently outperform the others for certain variables across most regions and seasons and higher-resolution models tend to perform better for regional processes. The CMIP5 multimodel ensemble shows a slight improvement relative to CMIP3 models in representing basic climate variables, in terms of the mean and spread, although performance has decreased for some models. Improvements in CMIP5 model performance are noticeable for some regional climate processes analyzed, such as the timing of the North American monsoon. The results of this paper have implications for the robustness of future projections of climate and its associated impacts, which are examined in the third part of the paper.

Extratropical cyclone track density, genesis frequency, deepening rate, and maximum intensity distributions over eastern North America and the western North Atlantic were analyzed for 15 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) for the historical period (1979–2004) and three future periods (2009–38, 2039–68, and 2069–98). The cyclones were identified using an automated tracking algorithm applied to sea level pressure every 6 h. The CMIP5 results for the historical period were evaluated using the Climate Forecast System Reanalysis (CFSR). The CMIP5 models were ranked given their track density, intensity, and overall performance for the historical period. It was found that six of the top seven CMIP5 models with the highest spatial resolution were ranked the best overall. These models had less underprediction of cyclone track density, more realistic distribution of intense cyclones along the U.S. East Coast, and more realistic cyclogenesis and deepening rates. The best seven models were used to determine projected future changes in cyclones, which included a 10%–30% decrease in cyclone track density and weakening of cyclones over the western Atlantic storm track, while in contrast there is a 10%–20% increase in cyclone track density over the eastern United States, including 10%–40% more intense (<980 hPa) cyclones and 20%–40% more rapid deepening rates just inland of the U.S. East Coast. Some of the reasons for these CMIP5 model differences were explored for the selected models based on model generated Eady growth rate, upper-level jet, surface baroclinicity, and precipitation.

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Despite continual increases in numerical model resolution and significant improvements in the forecasting of many meteorological parameters, progress in quantitative precipitation forecasting (QPF) has been slow. This is attributable in part to deficiencies in the bulk microphysical parameterization (BMP) schemes used in mesoscale models to simulate cloud and precipitation processes. These deficiencies have become more apparent as model resolution has increased. To address these problems requires comprehensive data that can be used to isolate errors in QPF due to BMP schemes from those due to other sources. These same data can then be used to evaluate and improve the microphysical processes and hydrometeor fields simulated by BMP schemes. In response to the need for such data, a group of researchers is collaborating on a study titled the Improvement of Microphysical Parameterization through Observational Verification Experiment (IMPROVE). IMPROVE has included two field campaigns carried out in the Pacific Northwest: an offshore frontal precipitation study off the Washington coast in January–February 2001, and an orographic precipitation study in the Oregon Cascade Mountains in November–December 2001. Twenty-eight intensive observation periods yielded a uniquely comprehensive dataset that includes in situ airborne observations of cloud and precipitation microphysical parameters; remotely sensed reflectivity, dual-Doppler, and polarimetric quantities; upper-air wind, temperature, and humidity data; and a wide variety of surface-based meteorological, precipitation, and microphysical data. These data are being used to test mesoscale model simulations of the observed storm systems and, in particular, to evaluate and improve the BMP schemes used in such models. These studies should lead to improved QPF in operational forecast models.