The Center for Prototype Climate Modeling (CPCM) is a new unit of the NYUAD Institute, thanks to generous funding approved by the Institute's advisory board. The primary mission of the Center is to bridge the gap between climate theory, modeling, and observation with the goal of improving our ability to predict future climate. Its goals are to explore, test, and implement cutting-edge ideas in climate prediction, and to provide a new link between the academic and modeling communities. A major focus of the Center is on improving our understanding of and ability to predict climate in the tropics and subtropics, changes which will have tremendous impact on Abu Dhabi and the Middle East.
The Center currently consists of its founders, Professor Andrew Majda (Principal Investigator), Professors Olivier Pauluis, and Shafer Smith (Co-Principal Investigators), all from the Center for Atmosphere Ocean Science, Courant Institute of Mathematical Sciences, NYU. The Center is managed by Asma Kamal, who is located at NYUAD. Over the next two years, the Center will hire scientists, support scientists and postdoctoral researchers. In addition, funds are available to support graduate and undergraduate research, mentored by the investigators and senior scientists. The primary tool of investigation will be the Institute's High Performance Computing Cluster. The Center will hold annual workshops on cutting-edge topics in climate science, and perform outreach activities for the benefit of the NYU and Abu Dhabi communities.
The main purpose of the Center for Prototype Climate Modeling is to drive and enable innovations in climate prediction by blending modern applied mathematics, climate theory, observations, and modeling, yielding concrete improvements in climate forecasting. The Center will provide a valuable and unique link between individual university researchers — who often do not have the resources to run large climate models — and large modeling centers — which cannot devote sufficient time to fundamental research. We envision that the research will be a joint effort between scientists at the Center, faculty members in CAOS at NYUNY, and collaborators at major universities and modeling centers. Core research projects will likely run for periods of three to ﬁve years. The four research topics below, which are ripe for broader testing and implementation, would be the focus of the ﬁrst round of research.
Core Research Topics
Multi-Scale Modeling and Superparameterization
Atmospheric and oceanic ﬂows involve a vast range of interacting scales that cannot all be explicitly simulated, even by the most powerful computers, and so the unresolved dynamics that interact with the resolved ﬂow must be parametrized. 'Superparameterization' indicates the use of a series of fast numerical processes to represent the effects of the unresolved dynamics on the resolved ﬂow. Recent mathematical developments by the Principle Investigator have pointed toward a powerful new way to address the parametrization problem, which generalizes superparameterization and is based on a three-step process:
- The development of a systematic multiscale model of the physical problem
- The use of a periodic approximation for the ﬂuctuations
- Exploitation of intermittency to replace ﬂuctuating dynamics with reduced models that may be solved by either inexpensive numerical methods or by analytic solutions
This technology is ideally suited to remedy some of the most vexing issues in climate modeling: the representation of unresolved convective cells in the atmosphere, and of unresolved submesoscale dynamics in the ocean. A major focus of the Center will be to develop, implement, and evaluate new multi-scale models of atmospheric and oceanic ﬂows and superparametrization approaches for solving the models.
Data Assimilation and Filtering of Turbulent Signals
Data assimilation — the procedure required to incorporate observations from hundreds of weather stations around the globe to determine the current state of the atmosphere — is a crucial component of weather forecasting. The tropical regions pose a particular problem for weather forecasting due to the fact that deep convection in these regions introduces a signiﬁcant amount of high frequency variability. New techniques, speciﬁcally designed to remove the noise introduced by these disturbances, have been proposed by the Principle Investigator and will be tested within realistic atmospheric models at the Center.
Tropical and Extra-Tropical Interactions
Most of the Earth's deserts are located in the subtropics. This is the result of a combination of two key aspects of the global circulations: the tropical Hadley circulation that dries the subtropics by bringing down dry air from the upper troposphere, and the midlatitude weather systems that continuously extract water vapor from the subtropical regions. The co-Principle Investigator (Pauluis) has recently revisited the global atmospheric circulation, by showing that moist subtropical air is the primary 'fuel' for the midlatitudes weather systems, and accounts for approximately half of the global circulation. The dryness of the subtropical regions is thus the result of a complex interplay between the tropics and extra-tropics. A better understanding of how the tropics and extra-tropics interact could improve our ability to predict severe droughts in the subtropics, and this will be a key focus of the Center.
Fluctuation-Dissipation Theorem and Climate Response
The ﬂuctuation-dissipation theorem (FDT) in statistical physics makes it possible to determine the response of a physical system by studying its ﬂuctuations near an equilibrium state. The application of FDT to real-world climate data, ﬁrst proposed three decades ago, may make it possible to determine the response of the climate system to external forcing — such as the ongoing increase in greenhouse gas concentration — by analyzing only past ﬂuctuations, i.e., without the need for numerical climate simulations. While conceptually elegant, practical applications of FDT have been hindered by the intrinsic complexity of Earth's climate. Recent advances in the application of FDT to complex data by the Principle Investigator and collaborators, however, can be used to circumvent these difﬁculties. Implementing the FDT to determine climate response will be one of the key tasks of the Center.