Dr. Hongyu Liu

One of the goals of the Global Modeling Initiative (GMI) activity is to improve assessments of anthropogenic perturbations to the Earth system. To achieve this goal, the GMI has developed and utilized atmospheric models which facilitate the testing of model sensitivities and uncertainties, and subjected the models to extensive evaluation against observations of atmospheric composition. One of the features of the GMI CTM is the ability to run the model with several sets of meteorological data [e.g., Considine et al., 2005]. This capability enables evaluation of the sensitivity of model simulations to differences in the meteorological data sets alone. Previous studies have illustrated that the GMI framework is very useful for characterizing and helping reduce uncertainties in the processes in the meteorological fields used to drive the models. In this project, we aim to improve our understanding of uncertainties in model predictions due to the use of different input meteorological fields by incorporating output from GFDL AM3 GCM into the GMI modeling framework. In particular, we will assess the AM3 meteorological fields through intercomparison with those from other major global climate models or data assimilation systems. Eventually we will use the GMI CTM to study the regional and long-range transport of Asian pollution as well as the effect of climate change. This work is led by postdoctoral research associate Hyun-Deok Choi. Collaborators: Larry Horowitz, Arlene Fiore, Vaishali Naik (NOAA GFDL); David Considine, Jim Crawford (NASA LaRC).

We are analyzing an extensive ozonesonde dataset obtained over East/South China during spring using GEOS-Chem and GMI CTMs. This work is led by visiting graduate student Yiqiang Zhang. Collaborators: Jim Crawford, David Considine (NASA LaRC); Zunyu Chen (John Chan, Sun Yat-sen University, China).

Clouds exert an important influence on tropospheric photochemistry through modification of solar radiation which determines photolysis rates (J-values). Enhanced photolysis rates have been found above and in the upper levels of clouds, while reduced rates have been found below optically thick clouds and absorbing aerosols. The objective of this study was to assess the radiative impact of clouds on global tropospheric chemistry including the effect of cloud overlap, using a state-of-the-art three-dimensional tropospheric chemistry and transport model (GEOS-CHEM). This work was published in JGR-Atmospheres [Liu et al., 2006]. Collaborators: Jim Crawford (LaRC), Brad Pierce (LaRC, now at NOAA), Peter Norris (GSFC/UMBC), Steve Platnick (GSFC), and Daniel Jacob's group (Harvard). Also see my GEOS-CHEM Activities page.

Previous estimates of the radiative impact of clouds on global tropospheric chemistry were based on chemistry transport models (CTMs) driven by different meteorology that contained different cloud fields, either from general circulation models (GCMs) or from data assimilation systems. The representation of clouds in current climate models is still a challenging task because cloud processes typically take place on scales that are not adequately resolved by these models and have to be parameterized. The uncertainty in simulated clouds (and relevant radiative processes) has been recognized as a large limiting factor in current assessments of climate change. As a follow-up study to our recent assessment of the radiative effect of clouds on tropospheric chemistry, this study evaluates the importance of cloud vertical distributions and optical properties with the use of GEOS-CHEM. We drive GEOS-Chem with a series of meteorological archives from the Goddard Earth Observing System data assimilation system (GEOS DAS) at the NASA Global Modeling and Assimilation Office (GMAO), which are characterized by distinctly different cloud fields, in particular cloud vertical distributions and cloud optical depths. This work was published on JGR-Atmospheres [Liu et al., 2009]. Collaborators: Jim Crawford (LaRC), David Considine (LaRC), Peter Norris (GSFC/UMBC), Steve Platnick (GSFC), and Daniel Jacob's group (Harvard). Also see my GEOS-CHEM Activities page.

Improved understanding of the impact of convection and associated lightning activity on reactive nitrogen and ozone chemistry in the upper troposphere is essential for predicting anthropogenic perturbations to upper tropospheric composition, in particular ozone. Satellite platforms could offer a unique opportunity to monitor convective and lightning influences on the upper troposphere from space. We are conducting regional modeling and observation-based studies to examine the ability of Aura and other satellites to provide constraints on the impact of convection and lightning on upper tropospheric chemistry, in particular NO_x and O₃. A regional chemistry transport model (RAQMS_N) [Pierce et al., 2003], the regional component of the NASA Langley Research Center (LaRC) and University of Wisconsin Regional Air Quality Modeling System (RAQMS), is used to link satellite observations with in-situ measurements in a physically consistent manner. We have recently focused on RAQMS_N simulations of the 2004 phase of the Intercontinental Chemical Transport Experiment-North America (INTEX-A) aircraft mission and model evaluations with satellite, aircraft, sonde and surface observations. Collaborators: Brad Pierce (LaRC, now at NOAA), Jim Crawford , and Jassim Al-Saadi (LaRC).

The stratosphere-troposphere exchange (STE) flux of ozone plays an important role in the tropospheric ozone budget. Representing this flux in global models is critical to quantitatively understanding the tropospheric ozone budget. Beryllium-7 (⁷Be), a radionuclide produced cosmogenically in the stratosphere and upper troposphere, has long been used to determine the stratospheric origin of tropospheric air. In this study, we use the Global Modeling Initiative (GMI) modeling framework to assess the utility of ⁷Be for evaluating STE in global models [Liu et al., manuscript to be submitted to JGR, 2010]. GMI is a NASA-led activity to develop and maintain a state-of-the-art modular three-dimensional chemistry and transport model that can be used for assessment of the impacts of anthropogenic and natural perturbations on atmospheric composition and chemistry. The GMI model can be driven by a variety of meteorological archives such as GEOS DAS, fvGCM, ECMWF, CCM3 and GISS II'. Collaborators: David Considine (LaRC), and the GMI core team (GSFC).

The aerosol absorption is enhanced when clouds are located below the aerosols. This synergy was found to be strong when clouds are located below the absorbing aerosols [Yang and Levy, 2004]. We are using the GEOS-Chem model to compare the radiative effects of aerosols [Martin et al., 2003] versus clouds [Liu et al., 2006] on tropospheric photochemistry and to assess the synergistic impact of aerosols and clouds on global and regional tropospheric photochemistry. Collaborators: Mian Chin (GSFC), David Considine (LaRC), Jim Crawford (LaRC), Siyang Hu (Sun Yat-sen University, China), and the GMI core team (GSFC).