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).

Climatological surface temperature and humidity variables for China are presented based on 6-hourly data from 196 stations for the period of 1961–90. Seasonal and annual means for daytime, nighttime, and the full day are shown. The seasonal cycle of moisture is primarily controlled by the east Asia monsoon system, with dominant factors of temperature change in northern and western China and of moisture advection associated with monsoon circulations in the southeast. Trends during 1951–94 are estimated for each station and for four regions of the country, with attention paid to the effects of changes in instrumentation, observing time, and station locations. The data show evidence of increases in both temperature and atmospheric moisture content. Temperature and specific humidity trends are larger at nighttime than daytime and larger in winter than summer. Moisture increases are observed over most of China. The increases are several percent per decade for specific humidity, and several tenths of a... Abstract Climatological surface temperature and humidity variables for China are presented based on 6-hourly data from 196 stations for the period of 1961–90. Seasonal and annual means for daytime, nighttime, and the full day are shown. The seasonal cycle of moisture is primarily controlled by the east Asia monsoon system, with dominant factors of temperature change in northern and western China and of moisture advection associated with monsoon circulations in the southeast. Trends during 1951–94 are estimated for each station and for four regions of the country, with attention paid to the effects of changes in instrumentation, observing time, and station locations. The data show evidence of increases in both temperature and atmospheric moisture content. Temperature and specific humidity trends are larger at nighttime than daytime and larger in winter than summer. Moisture increases are observed over most of China. The increases are several percent per decade for specific humidity, and several tenths of a...

The representation of transient air‐sea interactions is critical to the prediction of the sea surface temperature diurnal cycle and daily variability. This study develops a multilevel upper ocean model to more realistically resolve these interactions. The model is based on the one‐dimensional turbulence kinetic energy closure developed by Noh et al. [2011], and incorporates new numerical techniques and improved schemes for model physics. The primary improvements include: (1) a surface momentum flux penetration scheme to better depict velocity shear in the diurnal mixed layer; (2) a solar penetration scheme to improve the penetration of visible and near‐infrared bands of solar radiation into the mixed layer ocean; (3) a scheme to resolve the cool‐skin and warm‐layer effects on sea skin temperature; (4) a vertical grid stretch scheme to achieve higher near‐surface resolution with fewer vertical levels; (5) a trapezoidal time integration scheme for flexible time steps; (6) a relaxation term of the previous daily mean difference between observed and modeled sea surface temperature. According to the numerical experiments based on the TOGA‐COARE IMET mooring buoy data and the validation by observations from the National Data Buoy Center, NOAA, the results indicate that the new upper ocean mixed layer model improves the simulation of the diurnal cycle of SST and sea skin temperature, especially in amplitude.

Although air quality in the United States has improved remarkably in the past decades, ground-level ozone (O₃) often rises in exceedance of the national ambient air quality standard in nonattainment areas, including the Long Island Sound (LIS) and its surrounding areas. Accurate prediction of high-ozone episodes is needed to assist government agencies and the public in mitigating harmful effects of air pollution. In this study, we have developed a suite of potential forecast improvements, including dynamic boundary conditions, rapid emission refresh and chemical data assimilation, in a 3 km resolution Community Multiscale Air Quality (CMAQ) modeling system. The purpose is to evaluate and assess the effectiveness of these forecasting techniques, individually or in combination, in improving forecast guidance for two major air pollutants: surface O₃ and nitrogen dioxide (NO₂). Experiments were conducted for a high-O₃ episode (28–29 August 2018) during the Long Island Sound Tropospheric Ozone Study (LISTOS) field campaign, which provides abundant observations for evaluating model performance. The results show that these forecast system updates are useful in enhancing the capability of this 3 km forecasting model with varying effectiveness for different pollutants. For O₃ prediction, the most significant improvement comes from the dynamic boundary conditions derived from the NOAA operational forecast system, National Air Quality Forecast Capability (NAQFC), which increases the correlation coefficient (R) from 0.81 to 0.93 and reduces the root mean square error (RMSE) from 14.97 to 8.22 ppbv, compared to that with the static boundary conditions (BCs). The NO₂ from all high-resolution simulations outperforms that from the operational 12 km NAQFC simulation, regardless of the BCs used, highlighting the importance of spatially resolved emission and meteorology inputs for the prediction of short-lived pollutants. The effectiveness of improved initial concentrations through optimal interpolation (OI) is shown to be high in urban areas with high emission density. The influence of OI adjustment, however, is maintained for a longer period in rural areas, where emissions and chemical transformation make a smaller contribution to the O₃ budget than that in high-emission areas. Following the assessment of individual updates, the forecasting system is configured with dynamic boundary conditions, optimal interpolation of initial concentrations and emission adjustment, to simulate a high-ozone episode during the 2018 LISTOS field campaign. The newly developed forecasting system significantly reduces the bias of surface NO₂ prediction. When compared with the NASA Langley GeoCAPE Airborne Simulator (GCAS) vertical column density (VCD), this system is able to reproduce the NO₂ VCD with a higher correlation (0.74), lower normalized mean bias (40 %) and normalized mean error (61 %) than NAQFC (0.57, 45 % and 76 %, respectively). The 3 km system captures magnitude and timing of surface O₃ peaks and valleys better. In comparison with lidar, O₃ profile variability of the vertical O₃ is captured better by the new system (correlation coefficient of 0.71) than by NAQFC (correlation coefficient of 0.54). Although the experiments are limited to one pollution episode over the Long Island Sound, this study demonstrates feasible approaches to improve the predictability of high-O₃ episodes in contemporary urban environments.