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During the Dynamics of the MJO (DYNAMO) field campaign, radiosonde launches were regularly conducted from three small islands/atolls (Malé and Gan, Maldives, and Diego Garcia, British Indian Ocean Territory) as part of a large-scale sounding network. Comparison of island upsondes with nearby and near-contemporaneous dropsondes over the ocean provides evidence for the magnitude and scope of the islands' influence on the surrounding atmosphere and on the island upsonde profiles. The island's impact on the upsonde data is most prominent in the lowest 200 m. Noting that the vertical gradients of temperature, moisture, and winds over the ocean are generally constant in the lowest 0.5 km of dropsondes, a simple procedure was constructed to adjust the upsonde profiles in the lowest few hundred meters to resemble the atmospheric structures over the open ocean. This procedure was applied to the soundings from the three islands mentioned above for the October–December 2011 period of DYNAMO. As a result of this procedure, the adjusted diurnal cycle amplitude of surface temperature is reduced fivefold, resembling that over the ocean, and low-level wind speeds are increased in ~90% of the island soundings. Examination of the impact of these sounding adjustments shows that dynamical and budget fields are primarily affected by adjustments to the wind field, whereas convective parameters are sensitive to the adjustments in thermodynamic fields. Although the impact of the adjustments is generally small (on the order of a few percent), intraseasonal wind regime changes result in some systematic variations in divergence and vertical motion over the sounding arrays. [ABSTRACT FROM AUTHOR]

Blowing snow is a frequent and widespread phenomenon over most of Antarctica. The transport and sublimation of blowing snow are important for the mass balance of the Antarctic ice sheet, and the latter is a major contributor to the hydrological cycle in high-latitude regions. Although much is known about blowing snow from surface observations, knowledge of the thermodynamic structure of deep (>50 m) blowing-snow layers is lacking. Here, dropsonde measurements are used to investigate the temperature, moisture, and wind structure of deep blowing-snow layers over Antarctica. The temperature lapse rate within the blowing-snow layer is at times close to dry adiabatic and is on average between dry and moist adiabatic. Initiation of blowing snow causes the surface temperature to increase to a degree proportional to the depth of the blowing-snow layer. The relative humidity with respect to ice is generally largest near the surface (but less than 100%) and decreases with height, reaching a minimum near the top of the layer. These findings are at odds with the generally accepted theory that blowing-snow sublimation will cool and eventually saturate the layer. The observations support the conclusion that high levels of wind-shear-induced turbulence cause mixing and entrainment of warmer air from above the blowing-snow layer, which suppresses humidity and produces the observed well-mixed temperature structure within the layer. The results may have important consequences for understanding the mass balance of the Antarctic ice sheet and the moisture budget of the atmosphere in high latitudes. [ABSTRACT FROM AUTHOR]

Fields of atmospheric motion vectors (AMVs) are routinely derived by tracking features in sequential geostationary satellite infrared, water vapor, and visible-channel imagery. While AMVs produced operationally by global data centers are routinely evaluated against rawinsondes, there is a relative dearth of validation opportunities over the tropical oceans-in particular, in the vicinity of tropical disturbances when anomalous flow fields and strongly sheared environments commonly exist. A field experiment in 2010 called Pre-Depression Investigation of Cloud-Systems in the Tropics (PREDICT) was conducted in the tropical west Atlantic Ocean and provides an opportunity to evaluate the quality of tropical AMVs and analyses derived from them. The importance of such a verification is threefold: 1) AMVs often provide the only input data for numerical weather prediction (NWP) over cloudy areas of the tropical oceans, 2) NWP data assimilation methods are increasingly reliant on accurate flow-dependent observation-error characteristics, and 3) global tropical analysis and forecast centers often rely on analyses and diagnostic products derived from the AMV fields. In this paper, the authors utilize dropsonde information from high-flying PREDICT aircraft to identify AMV characteristics and to better understand their errors in tropical-disturbance situations. It is found that, in general, the AMV observation errors are close to those identified in global validation studies. However, some distinct characteristics are uncovered in certain regimes associated with tropical disturbances. High-resolution analyses derived from the AMV fields are also examined and are found to be more reflective of anomalous flow fields than the respective Global Forecast System global model analyses. [ABSTRACT FROM AUTHOR]