[세미나] Dr. Greg McFarquhar

In-situ measurements of cloud properties: how, what, where, when and why

Dr. Greg McFarquhar

2023년 9월 12일 (화) 16:00

과학관 B102호

Abstract

The most fundamental and complex problems in understanding climate and weather are our poor understanding of basic cloud properties and an inability to quantify the many effects cloud processes have on weather and climate. For example, clouds have a net impact on Earth’s radiation budget of 20 W m^2, meaning they reflect more solar radiation than they absorb infrared radiation. However, if the distribution of cloud heights and microphysical properties changes in response to increases in greenhouse gases and aerosols, associated changes in cloud radiative impact could feed back on Earth’s climate.

For weather, forecasts of quantitative precipitation amount and type, as well as rapid intensification of hurricanes, are subject to large errors and high uncertainties. Representations of cloud microphysical processes (e.g., radiative scattering, particle sedimentation, riming, evaporation, and aggregation) are needed for global climate and numerical weather prediction models that predict these effects. Algorithms retrieving cloud information from ground and satellite-based sensors also require assumptions about cloud microphysical properties. To develop such representations, accurate observations of cloud particle sizes, shapes, phases, and concentrations are needed. Such observations are obtained by aircraft cloud probes.

An overview of how aircraft cloud probes operate is presented. Sources of error in the observations (statistical counting errors, variability in cloud properties, measurement errors induced by influencing the cloud) are described using data collected in boundary layer clouds over the Southern Ocean, and in convective clouds over the tropical oceans near Australia and South America, and over the continental United States. It is shown how data from cloud probes are used to inform the understanding of processes occurring in clouds and to develop representations of cloud properties and processes as required by weather and climate models. An example application of a stochastic cloud parameterization scheme in a model of a mid-latitude convective anvil is shown. New projects underway and planned to better characterize cloud properties and processes are reviewed.