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Determining cloud thermodynamic phase using infrared satellite observations typically requires a priori assumptions about relationships between cloud phase and cloud temperature. In this study, limitations of an approach using two infrared channels with moderate spectral resolutions are demonstrated, as well as the potential for improvement using channels with higher spectral resolution. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument uses a bispectral infrared cloud phase determination algorithm. MODIS observations during January 2005 show that approximately 23% of cloudy pixels are classified as mixed or unknown cloud phase; this increases to 78% when only cloud-top temperatures between 250 and 265 K are considered. Radiative transfer simulations show that the bispectral algorithm has limited ability to discriminate between water and ice clouds in this temperature range. There is also the potential for thin ice clouds at colder temperatures to be misclassified as water clouds. In addition, sensitivities to cloud particle size and cloud height can be larger than sensitivities to cloud phase. Simulations suggest that phase sensitivity may be higher with hyperspectral observations such as those from the Atmospheric Infrared Sounder (AIRS). The AIRS brightness temperature differences between channels at 8.1 and 10.4 [micro]m show phase sensitivities of at least 0.5 K, regardless of cloud particle size, cloud-top temperature, or cloud height. They also demonstrate reduced sensitivity to atmospheric temperature and water vapor variability. The reduced sensitivity of AIRS radiances to these physical quantities shows that hyperspectral sounders will serve an important role in refining estimates of cloud phase.

A single-layer urban canopy model is incorporated into a simple two-dimensional atmospheric model in order to examine the individual impacts of anthropogenic heating, a large heat capacity, and a small sky-view factor on mesoscale heat island formation. It is confirmed that a nocturnal heat island on a clear, calm summer day results from the difference in atmospheric stability between a city and its surroundings. The difference is caused by anthropogenic heating and the following two effects of urban canyon structure: (i) a larger heat capacity due to the walls and (ii) a smaller sky-view factor. Sensitivity experiments show that the anthropogenic heating increases the surface air temperature though the day. (This factor strongly affects the nocturnal temperature, and the maximum increase of 0.67[degrees]C occurs at 0500 LST.) The larger heat capacity due to the walls decreases the daytime temperature and increases the nocturnal temperature. (The maximum increase of 0.39[degrees]C occurs at 0600 LST.) The smaller sky-view factor increases the temperature though the day, particularly during the first several hours after sunset. (The maximum increase of 0.52[degrees]C occurs at midnight.) In urban areas, this factor results in uniform cooling that occurs at a constant rate. The impact of the canyon structure is shown to be as significant as anthropogenic heating.

This paper makes use of ensemble forecasts to infer the correlation between surface skin temperature [T.sub.s] and air temperature [T.sub.a] model errors. The impact of this correlation in data assimilation is then investigated. In the process of assimilating radiances that are sensitive to the surface skin temperature, the [T.sub.s] - [T.sub.a] error correlation becomes important because it allows statistically optimal corrections to the background temperature profile in the boundary layer, in converse, through this correlation, surface air temperature data can substantially influence the analysis of skin temperature. One difficulty is that the [T.sub.s] - [T.sub.a] correlation depends on the local static stability conditions that link the two variables. Therefore, a correlation estimate based on spatial or temporal averages is not appropriate. Ensembles of forecasts valid at the analysis time provide a novel means to infer the correlation dynamically at each model grid point. Geostationary Operational Environmental Satellite (GOES)-8 and -10 surface-sensitive imager radiances are assimilated with and without the inferred correlations in a 3D variational analysis system. The impact of the correlation on analyses is assessed using independent radiosonde data. The impact on 6-h forecasts is also evaluated using surface synoptic reports. The influence of the correlation extends from the surface to about 1.5 km. Temperature differences in the resulting analyses on the order of 0.3-0.6 K are typical in the boundary layer and may extend over broad regions. These difference patterns persist beyond 6 h into the forecasts.

A Doppler lidar deployed to the center of the Great Salt Lake (GSL) basin during the Vertical Transport and Mixing (VTMX) field campaign in October 2000 found a diurnal cycle of the along-basin winds with northerly up-basin flow during the day and a southerly down-basin low-level jet at night. The emphasis of VTMX was on stable atmospheric processes in the cold-air pool that formed in the basin at night. During the night the jet was fully formed as it entered the GSL basin from the south. Thus, it was a feature of the complex string of basins draining toward the Great Salt Lake, which included at least the Utah Lake basin to the south. The timing of the evening reversal to down-basin flow was sensitive to the larger-scale north-south pressure gradient imposed on the basin complex. On nights when the pressure gradient was not too strong, local drainage flow (slope flows and canyon outflow) was well developed along the Wasatch Range to the east and coexisted with the basin jet. The coexistence of these two types of flow generated localized regions of convergence and divergence, in which regions of vertical motion and transport were focused. Mesoscale numerical simulations captured these features and indicated that updrafts on the order of 5 cm [s.sup.-1] could persist in these localized convergence zones, contributing to vertical displacement of air masses within the basin cold pool.

ABSTRACT Most of the dozens of essential climate variables monitored each year in this report continued to follow their long-term trends in 2014, with several setting new records. Carbon dioxide, [...]