Melinda Berman's Presentation:
Understanding the Impact of the Lower Stratospheric Thermodynamic Environment on Observed Overshooting Top Characteristics
Overshooting tops (OTs) are manifestations of deep convective updrafts that extend above the stable layer at the tropopause into the stratosphere. They can result in irreversible transport of aerosols, smoke, water vapor and other mass from the troposphere into the stratosphere. This transport can impact both the chemical composition of the stratosphere and induce dynamic perturbations. Recent work has examined OT characteristics such as area and how this relates to midlevel updraft structure. Other studies have shown how static stability in the lowermost stratosphere impacts other observed features at storm top. A knowledge gap remains, however, in understanding how stability in the lowermost stratosphere (LMS) specifically impacts OT characteristics including area, depth and injection duration. These relationships may be useful in describing mid- and low-level storm dynamics from satellite-observed characteristics of OTs in near real time. Using a combination of reanalysis data, observed rawinsonde data, and geostationary satellite observations, the LMS thermodynamic environment and observed OT characteristics are quantified and compared. OTs are tracked in time and space to derive area, depth and duration values that are compared to the stability of the environment. Results show relationships between multiple measures of atmospheric stability and observed OT characteristics, including a direct relationship between OT depth and LMS temperature lapse rate. Idealized model simulations using the Bryan Cloud Model 1 (CM1) will be used to help interpret these relationships.
Rachel Tam's Presentation:
Different Drivers of Low Cloud Radiative Feedbacks and Their Uncertainty in Historical and Future Simulation
The radiative feedback pattern effect remains a large source of uncertainty for both projections of future climate change, as well as interpretations and attribution of warming trends over the last 40 years. In particular, it remains one of the major sources of poorly quantified and poorly constrained uncertainty for climate sensitivity. Most of the pattern effect, as well as the attendant uncertainty, is attributable to low cloud radiative feedbacks.
Here we use low cloud radiative kernels and cloud controlling factors to disentangle the drivers of the low cloud radiative effect (CRE) and its uncertainty in recent and future time periods, using both AMIP historical and abrupt quadrupling simulations.
We find that over the last forty years (i.e. the satellite record) changes in Estimated Inversion Strength (EIS) is the main driver to low cloud CRE. Conversely, we find that the more uniform Sea Surface Temperature (SST) warming pattern in abrupt4xCO2 simulations leads to SSTs being the primary driver of the CRE. In both the historical period and the future, the model-spread is related to the sensitivity of low clouds to the environmental conditions.
The fact that drivers of the net feedback is expected to change in the future should lead to increased caution when trying to use historical global-mean changes in Earth’s energy budget to place constraints in future warming.
