Master of Science (MS)
Meteorology and Climate Science
Global cloud coverage has a substantial impact on local and global radiative budgets. It is necessary to correctly represent clouds in numerical weather models to improve both weather and climate predictions. This study evaluates in situ airborne observations of cloud microphysical properties and compares results with the Weather Research and Forecasting model (WRF) and Community Atmosphere Model version 5 (CAM5). Dynamical conditions producing supersaturated conditions with respect to ice at high altitudes in regions diagnosed by convective activity are explored using observations taken from the Deep Convective Clouds and Chemistry (DC3) campaign, and results are compared with simulated data from WRF. The WRF analysis tests multiple cloud microphysics schemes and finds the model requires much stronger updrafts to initiate large magnitudes of ice supersaturation (ISS) relative to observations. This is primarily due to the microphysics schemes over-predicting ice particle number concentrations (Ncice), which rapidly deplete the available water vapor. The frequency of different cloud phases and the distribution of relative humidity (RH) over the Southern Ocean is explored using in situ airborne observations taken from the O2/N2 Ratio and CO2 Airborne Southern Ocean Study (ORCAS) and compared with simulated data from CAM5. The CAM5 simulations produce comparable distributions of RH in clear-sky conditions at warmer temperatures (>-20°C). However, simulations fail to capture high frequencies of clear-sky ISS at colder temperatures (< 40°C). In addition, CAM5 underestimates the frequency of subsaturated conditions within ice phase clouds from -40°‒0°C.
D'Alessandro, John, "Cloud Microphysical Properties based on Airborne In Situ Observations and Evaluation of a Weather Forecasting Model and a Global Climate Model" (2018). Master's Theses. 4935.