Climate Analysis: Diagnostic, Theoretical & Modeling Studies
Our research focuses to increase our understanding of atmospheric and climate variability and climate change through parallel development and analysis of observational, assimilated, model-generated and model-forcing datasets; and, by using these datasets for empirical studies, diagnostic analyses, and model experimentation to document comprehensively climate variability, its causes and the processes involved. Further, systematic numerical experimentation using models provides insights and assesses predictability that may allow attribution of observed variability to processes and causes. A crucial question is how well do we simulate the full spectrum of natural variability in models such as CCSM/CESM, and thereby provide a sound basis for future projections? The answer depends on a strong and balanced program in data analysis, theoretical and model application studies.
Did you know that ground-level ozone is a serious pollution problem? Ground-level (“bad”) ozone is toxic to plants and animals – including humans. It is different from the ozone layer (“good” ozone) high in the atmosphere that blocks the Sun’s harmful ultraviolet (UV) rays, even though it is the same chemical in both places. Ground-level ozone is harmful to us because it is in the air we breathe.
Although ozone is invisible, its effects can be observed on the leaves of certain plants. Ozone sensitive plants develop symptoms on their leaves that we can see, telling us when high levels of ozone are present in the air around us. Because they provide this information, they are called bioindicator plants. However, there are still lots of questions when it comes to ozone and plants...
To learn more visit the Ozone Garden Homepage
Simulating the Climate System: Community Model Development & Evaluation
The development and continuous improvement of a comprehensive climate modeling system is at the forefront of international efforts to understand and predict the behavior of the Earth's climate continues to be a high priority of CGD research. This requires strong support of ongoing fundamental research on climate processes operating in the atmosphere, ocean, land and cryosphere. It also requires the continual development of software engineering methods to improve performance and portability, and extensive infrastructure and support for external collaborators and users.