On the Relationship between Stratiform Low Cloud Cover and Lower-Tropospheric Stability

Abstract

Observations in subtropical regions show that stratiform low cloud cover is well correlated with the lower-troposphere stability (LTS), defined as the difference in potential temperature θ between the 700-hPa level and the surface. The LTS can be regarded as a measure of the strength of the inversion that caps the planetary boundary layer (PBL). A stronger inversion is more effective at trapping moisture within the marine boundary layer (MBL), permitting greater cloud cover. This paper presents a new formulation, called the estimated inversion strength (EIS), to estimate the strength of the PBL inversion given the temperatures at 700 hPa and at the surface. The EIS accounts for the general observation that the free-tropospheric temperature profile is often close to a moist adiabat and its lapse rate is strongly temperature dependent. Therefore, for a given LTS, the EIS is greater at colder temperatures. It is demonstrated that while the seasonal cycles of LTS and low cloud cover fraction (CF) are strongly correlated in many regions, no single relationship between LTS and CF can be found that encompasses the wide range of temperatures occurring in the Tropics, subtropics, and midlatitudes. However, a single linear relationship between CF and EIS explains 83% of the regional/seasonal variance in stratus cloud amount, suggesting that EIS is a more regime-independent predictor of stratus cloud amount than is LTS under a wide range of climatological conditions. The result has some potentially important implications for how low clouds might behave in a changed climate. In contrast to Miller’s thermostat hypothesis that a reduction in the lapse rate (Clausius–Clapeyron) will lead to increased LTS and increased tropical low cloud cover in a warmer climate, the results here suggest that low clouds may be much less sensitive to changes in the temperature profile if the vertical profile of tropospheric warming follows a moist adiabat.

The Diversity of Cloud Responses to Twentieth Century Sea Surface Temperatures

“…Previous studies have shown lower tropospheric stability (LTS) to be a useful diagnostic tool that connects low-cloud changes to the characteristics of the large-scale environment, especially within traditionally defined stratocumulus regions (Klein & Hartmann, 1993;Medeiros et al, 2008;Webb et al, 2015;Wood & Bretherton, 2006). We analyze the EIS, which can be thought of as a correction to the LTS based on the moist adiabatic profile.…”

“…The LTS used by Klein and Hartmann (1993) was defined as LTS = 700 hPa − sfc , where is the potential temperature and the subscript indicates the level at which the values are taken. For EIS we use the approximation made by Wood and Bretherton (2006): 1925 and 1955 (1975 and 2005). SST fields are from AMIP boundary conditions, PCMDI-AMIP (Taylor et al, 2000).…”

“…Recently, Qu et al (2014Qu et al ( , 2015 provided a thorough examination of the dependencies between low-cloud cover, the estimated inversion strength (EIS), and surface temperature in both observations, and an ensemble of models from CMIP3 and CMIP5. They, as did most previous studies (e.g., Klein & Hartmann, 1993;Wood & Bretherton, 2006), focused on five oceanic regions which are important for stratocumulus decks of radiatively active lowlevel clouds. Only recently have the fields of stability, low-level clouds, and low-level temperature begun to be investigated over larger swaths of the globe (Grise & Medeiros, 2016;Rose & Rayborn, 2016;Webb et al, 2015;Zhou et al, 2016).…”

Low-Cloud Feedbacks from Cloud-Controlling Factors: A Review

“…Although low clouds result from the interactions of inherently nonlinear processes, there is ample evidence that a linear approach can explain cloud variations at spatial scales greater than 100 km and time-scales longer than a few days. For example, observations show that a linear relationship with inversion strength can explain over 80% of the variance in the seasonal cycle of tropical and extra-tropical marine low clouds (Klein and Hartmann 1993;Wood and Bretherton 2006). Over decadal time-scales, Seethala et al (2015) find that observed tropical low-cloud changes can be well explained with a linear model using SST, EIS, and horizontal temperature advection as cloud-controlling factors.…”

Geographically versus dynamically defined boundary layer cloud regimes and their use to evaluate general circulation model cloud parameterizations

“…[3] Low-level clouds are oftentimes identified according to the large-scale dynamics [Klein and Hartmann, 1993;Bony et al, 2004;Wood and Bretherton, 2006;Medeiros and Stevens, 2011]. Other times, geographical regions are used as a proxy for studying the representations of a cloud regime [Webb et al, 2001;Chepfer et al, 2010].…”