Relationships between large-scale meteorological conditions and surface radiative state in the Arctic

Past studies have demonstrated the existence of distinct radiative states at high latitudes (Persson et al., 1999, Stramler et al., 2010, Morrison et al., 2012). The main factor controlling transitions between "radiatively clear" and "opaquely cloudy" states is the presence (or lack of) liquid-containing clouds. A large fraction of this cloud cover is composed of low-level mixed-phase stratiform clouds. To date, mechanisms controlling the formation and lifetime of these clouds remain a complex problem. Morrison et al. (2012) outlined the need to understand numerous processes occurring simultaneously in order to truly understand mixed-phase cloud lifecycle, including the influence of large-scale meteorology. In this work, we investigate the observed correlation between large-scale meteorological variables (e.g. sea level pressure, lower tropospheric stability, large scale vertical motion) and surface radiative state. Such relationships have previously been investigated for both lower-latitude and Arctic clouds (e.g. Klein and Hartmann, 1993; Wood and Bretherton, 2006). Here we aim to investigate not only the correlations between properties at high latitudes, but also the causation. Based on preliminary analysis, we hypothesize that for Arctic clouds, subsidence and lower tropospheric stability are important controlling mechanisms in the formation and dissipation of these clouds. In our presentation, we will characterize the occurrence of the two radiative states over a long timeseries at multiple locations, expanding upon previous analyses that primarily focus on wintertime at SHEBA. Additionally, we will present statistical analyses of the relationships between suspected driving mechanisms and radiative state. Finally, we will compare and contrast these findings to those previously derived for lower-latitude clouds in an effort to support (or disagree with) the use of general relationships such as these in global climate models.