[1] A modified zonal index (ZI) for the Northern Hemisphere (NH) general circulation is defined as the normalized difference in zonal-averaged sea level pressure anomalies between 35°N and 65°N. The ZI is a measure of hemispheric-wide fluctuations in air mass between two annular belts of action (ABAs) over middle and high latitudes, centered near 35°N and 65°N, respectively. The spatial structure of the NH general circulation represented by the ZI is a zonally symmetric pattern, similar to the NH annular mode. Some physical features associated with the ZI are discussed and summarized as a concept model, and the analysis indicates that the Ferrel cell stands out as a dominant signal in the zonal-mean circulation anomalies related to the ZI, implying a strong dynamical property of the general circulation in the mid-high latitudes.INDEX TERMS: 3309

Climate models have consistently projected a drying trend in the southwestern United States, aiding speculation of increasing dust storms in this region. Long‐term climatology is essential to documenting the dust trend and its response to climate variability. We have reconstructed long‐term dust climatology in the western United States, based on a comprehensive dust identification method and continuous aerosol observations from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network. We report here direct evidence of rapid intensification of dust storm activity over American deserts in the past decades (1988–2011), in contrast to reported decreasing trends in Asia and Africa. The frequency of windblown dust storms has increased 240% from 1990s to 2000s. This dust trend is associated with large‐scale variations of sea surface temperature in the Pacific Ocean, with the strongest correlation with the Pacific Decadal Oscillation. We further investigate the relationship between dust and Valley fever, a fast‐rising infectious disease caused by inhaling soil‐dwelling fungus (Coccidioides immitis and C. posadasii) in the southwestern United States. The frequency of dust storms is found to be correlated with Valley fever incidences, with a coefficient (r) comparable to or stronger than that with other factors believed to control the disease in two endemic centers (Maricopa and Pima County, Arizona).

The CWRF is developed as a climate extension of the Weather Research and Forecasting model (WRF) by incorporating numerous improvements in the representation of physical processes and integration of external (top, surface, lateral) forcings that are crucial to climate scales, including interactions between land, atmosphere, and ocean; convection and microphysics; and cloud, aerosol, and radiation; and system consistency throughout all process modules. This extension inherits all WRF functionalities for numerical weather prediction while enhancing the capability for climate modeling. As such, CWRF can be applied seamlessly to weather forecast and climate prediction. The CWRF is built with a comprehensive ensemble of alternative parameterization schemes for each of the key physical processes, including surface (land, ocean), planetary boundary layer, cumulus (deep, shallow), microphysics, cloud, aerosol, and radiation, and their interactions. This facilitates the use of an optimized physics ensemble approach to improve weather or climate prediction along with a reliable uncertainty estimate. The CWRF also emphasizes the societal service capability to provide impactrelevant information by coupling with detailed models of terrestrial hydrology, coastal ocean, crop growth, air quality, and a recently expanded interactive water quality and ecosystem model. This study provides a general CWRF description and basic skill evaluation based on a continuous integration for the period 1979– 2009 as compared with that of WRF, using a 30-km grid spacing over a domain that includes the contiguous United States plus southern Canada and northern Mexico. In addition to advantages of greater application capability, CWRF improves performance in radiation and terrestrial hydrology over WRF and other regional models. Precipitation simulation, however, remains a challenge for all of the tested models.

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