Ngar-Cheung (Gabriel) LauPhone Number: (609)-452-6524 Postal address: Geophysical Fluid Dynamics Laboratory/NOAA Princeton University P.O. Box 308 Princeton, NJ 08542 |
Lead Scientist of the Climate Diagnostics Group
at the Geophysical Fluid Dynamics Laboratory which is part of the U.S. Federal government's Office of Atmospheric and Oceanic Research, National Oceanic and Atmospheric Administration, U.S. Department of Commerce.
Lecturer with rank of Professor
of the Program in Atmospheric and Oceanic Sciences, the Department of Geosciences, at Princeton University.
Other Responsibilities
- Scientific Advisor, Hong Kong Observatory
- Associate Editor, Advances in Atmospheric Sciences
- Editorial Board, World Scientific Series on Meteorology of East Asia
- Co-Chair, Expert Team on Climate Impacts on Monsoon Weather, WMO World Weather Research Program
- Advisory Board, Climate Forecast System High-Resolution Reanalysis Project, US Climate Prediction Center
Education
1970: St. Francis Xavier's School, Hong Kong
1974: B.Sc. (Physics), Chinese University of Hong Kong, Hong Kong
1978: Ph.D. (Atmospheric Sciences), University of Washington, Seattle
Awards and Honors
1990: Clarence Leroy Meisinger Award, American Meteorological Society,
- for `Outstanding Studies
of Low-Frequency Variability in the Atmosphere by a Synthesis of Modeling and Diagnostics'
1991: Unusually Outstanding Performance Award, National Oceanic and Atmospheric Administration, U.S. Department of Commerce
1993: Chen-Ning Yang Visiting Fellow, Chinese University of Hong Kong, Hong Kong
2003: Hong Kong Observatory 120th Anniversary Distinguished Meteorologist
2008: Distinguished Lecturer, Department of Atmospheric Sciences, Peking University
2009: Guest Professor, Peking University
Courses taught at Princeton University
- GEO 427: Introduction to Terrestrial and Planetary Atmospheres
- AOS 577: Weather and Climate Dynamics
- AOS 580: Special Topics
Research Interests
- Observational and modeling studies of the atmospheric general circulation
- Impact of large-scale air-sea interaction on atmospheric variability
- Properties of tropical circulation systems
- Analysis of atmospheric phenomena simulated by high-resolution numerical models
Summary of research activities
- I hold a long-standing interest in the origin of atmospheric variability on time scales ranging from several days to a few years, and the dynamical interactions between observed atmospheric phenomena residing in different parts of the frequency spectrum. I have demonstrated that month-to-month changes in the preferred trajectory and intensity of synoptic-scale disturbances are closely related to the pattern of the quasi-stationary flow field.
- I also take advantage of the extensive datasets resulting from multi-year general circulation model (GCM) at the Geophysical Fluid Dynamics Laboratory. I am intrigued by the role of sea surface temperature (SST) anomalies in altering the atmospheric circulation. The model diagnoses have led to insights on the influences of the El Nino-Southern Oscillation phenomenon on atmospheric variability in both tropical and midlatitude regions. These atmospheric perturbations can in turn lead to changes in the near-surface oceanic conditions in many parts of the globe.
Typical sea surface temperature anomaly patterns in the World Oceans during El Nino events, based on observational data (upper panel) and simulation with an atmospheric GCM coupled to an oceanic mixed-layer model outside the tropical eastern/central Pacific (lower panel).
- My investigation on tropical circulation features is mainly concerned with weather systems in the East Asian monsoon region (such as the Plum Rain or Meiyu-Baiu phenomenon in the warm season and cold air outbreaks in the cold season), the structure and propagation characteristics of synoptic-scale and intraseasonal disturbances in the tropical zone, the space-time evolution of monsoon circulation, and the modulation of various tropical phenomena by El Nino events.
- I have analyzed the output from several simulations based on atmospheric GCMs with spatial resolution in the 25-50 km range, and have compared the model results with available observations of comparable resolution, such as datasets based on satellite measurements. Particular attention has been devoted to regional details of the diurnal cycle, and fine-structure of mesoscale meteorological systems.