King-Fai Li

PhD Candidate

Division of Geological and Planetary Sciences

California Institute of Technology

Email: kfl @ gps.caltech.edu

Advisor: Prof. Yuk Yung

Education

Research Interests

Atmospheric Transport of Carbon Dioxide

Carbon dioxide (CO2) is the most important anthropogenic greenhouse gas in the present-day climate. Most of the community focuses on its long-term (decadal to centennial) behaviors that are relevant to climate change, but there are relatively few discussions of its higher-frequency forms of variability, and none regarding its subseasonal distribution. Recently, the ENSO impact on CO2 mixing ratios in the middle troposphere (~5-10 km) have been revealed [Jiang et al., 2010] in the observations by NASA's Atmospheric Infrared Sounder (AIRS). This implies that convection and other large-scale motions may regulate CO2 in subseasonal time-scales. This is the first observation of "an intraseasonal breath our climate system" in terms of mid-tropospheric variations of CO2. These variations derive from the systematic influence of the so-called Madden-Julian Oscillation (MJO) that drives the signal through vertical and horizontal winds that transport CO2 and that influence its transfer between the surface and the atmosphere.
    The annual breathing of the climate system (e.g., agriculture, forests, biomass burning) and the associated signal in atmospheric CO2 is well known with a magnitude of about 1% (i.e. ~ 3 ppm). This observation of upper tropospheric CO2 variations is new and much faster in time - on the order of 2-4 weeks with a similar size magnitude for typical MJO events. However, due to their stochastic weather-like nature, the influence of the MJO may vary significantly from event to event, much the same way no two storms are alike but they have common features. Therefore, each atmospheric CO2 variation due to the MJO is unique and only through sophisticated averaging on a large sample of satellite measurements and over a number of MJO events can we construct a typical picture of the effects of the MJO on CO2. In this case, each individual MJO event may produce variations in CO2 on the order of 1% - comparable to the annual cycle - with the composite event exhibiting a magnitude of about 0.3%. About 9 millions AIRS satellite retrievals are used for this analysis. This highlights the importance of having spaceborne measurements with high spatial resolutions.
    There is still limited information on how CO2 is vertically distributed as in-situ profiling (e.g. balloons and aircraft) measurements are still sparse in time and space. Because the MJO phenomena we are examining involves convection and thus upward mixing of air from the surface into the middle and upper troposphere (where AIRS measures CO2) and compensating downward motions, we can examine how the CO2 measurements change between these upward and downward moving areas and infer that the typical vertical structure of CO2 over the tropical atmosphere decreases with height from the surface up to the middle and upper troposphere.
    Coupled carbon-climate models, which will be more thoroughly utilized in the climate simulations/projections for the next IPCC Assessment Report, are still undergoing continued development and are in sore need of as many observational constraints for evaluation and validation. Documenting the spatial-temporal variation of CO2 on intraseasonal time scales associated with the MJO will provide an important contribution in this area.
    A paper related to this research is Li et al. (2010), Tropical mid-tropospheric CO2 variability driven by the Madden-Julian oscillation, Proc. Nat. Acad. Sci. - USA.

Solar cycles and Stratospheric Changess

Whether the solar cycle has important influence on the current climate remains a controversial issue. Nonetheless, it is sometimes used to test the climate sensitivity of general circulation models. Since most of the solar cycle variations occur in the shortwave region (~120-300 nm), any solar-cycle effects on climate are expected to be enhanced in the middle atmosphere via solar heating due to stratospheric ozone absorption. Take the 11-year solar cycle as an example. The variation in total solar irradiance is only ~ 0.08%. Therefore it is extremely hard to either measure or simulate the solar cycle effects in climate models. Furthermore, other difficulties often arise from the fact that atmospheric processes such as the El Niño Southern-Oscillation, the quasi-biennial oscillation and even volcanic effects, may interact with or contaminate the signal from the 11-year solar cycle. The recently released EOS MLS version 2.2 products have been studied to verify further the presence of the 27-day cycle in temperature in the middle atmosphere. The noise-assisted or the Monte-Carlo Empirical Mode Decomposition (MCEMD), where the statistical significance of the IMFs can be tested, is employed. The filtered data are further expanded into a linear combination of spatial and temporal functions by a new technique, the Composite Mean Difference (CMD). This allows the examination of the latitudinal-height pattern of the 27-day solar cycle response in temperature. A paper related to this research is Li et al. (2011), A 27-day solar cycle in the middle atmosphere from MLS/Aura measurements, in preparation.

Clouds and Climate Change

It is well known that clouds are a principal source of uncertainty in current climate models. The climate sensitivity, defined as the surface temperature increase caused by a doubling of CO2, is strongly dependent on the cloud feedback. Goody et al. [1998] pointed out the advantages of using spectrally resolved radiance for validating climate models since it has signatures of both forcing (e.g., changes of greenhouse gases) and the responses to the forcing (e.g., temperature, water vapor, and clouds). In addition, the higher the spectral resolution, the more information we can obtain about the vertical profiles of temperature, moisture and clouds, which help diagnose model shortcomings and point the way to model improvements (see, e.g., Huang et al. [2007]). Haskins et al. [1999] and Huang and Yung [2005] used the principal component analysis (PCA) on monthly averaged infrared spectra. Both studies concluded that clouds are the major source of the infrared spectral variability, accounting for more than 90% of the variances. Since atmospheric radiation, specifically with regards to the hydrological cycle (e.g., cloudiness), is a non-linear process, it is important to consider the consequence of this averaging on the results. For example, consider an atmosphere that is the superposition of cloudy and clear scenes. Upon averaging, all scenes can become smeared into one mixed scene. Likewise, synoptically, clouds can occur as isolated low clouds and then separately as high clouds, each with their own signature on the spectra. However, upon averaging, an unnatural cloud scene could be produced. to provide a more robust radiative description of tropical cloud systems, it is necessary to include temporal information in the principle mode calculations. A paper related to this work is Li et al. (2011), Principal Modes of High-Resolution Spectral Variability in Tropical Cloud Systems, in preparation.

Possible astrobiological signatures on exoplanets

Currently the only method for detection of extraterrestrial life is by remote sensing. A recent discovery of water vapor, methane and carbon dioxide on an exoplanet [Tinetti et al., 2007; Swain et al., 2008 & 2009] by NASA's Spitzer Space Telescope strongly suggests that habitable exoplanets might be very common in the universe. The remaining question is whether these exoplanets might have life. According to Drake's equation, the probability of detecting an extraterrestrial civilization is directly proportional to the duration over which they broadcast (e.g. in electromagnetic waves). Such duration is obviously bounded by the life span of their biosphere. In Gaia Hypothesis, the Earth's biosphere, through the regulation of the global surface temperature (in geological time scales) by the carbonate-silicate cycle around the evolving Sun, can last only for ~ 1 Ga more from present. Most likely, higher forms of life like humans would extinct well before this limit as the environment becomes more extreme. Thus, given that intelligent life has only existed for ~ 10 ka on Earth, extraterrestrial civilizations (if any) must be able to make use of this 1-Ga window in order to receive our broadcast. Hence the probability of having an extraterrestrial communication would be greatly enhanced if there are ways to extend the life span of the terrestrial biosphere. Recently, it has been suggested that the global surface temperature may also be regulated by the atmospheric pressure. This would potentially extend the life span of the biosphere to ~ 2 Ga, doubling the chance of humans being detected by extraterrestrial intelligence. A paper related to this research is Li et al. (2009), Atmospheric Pressure as a Natural Climate Regulator of a Terrestrial Planet with a Biosphere, Proc. Nat. Acad. Sci. - USA .

Publication

Wang, S., K.-F. Li, X. Jiang, M.-C. Liang, and Y. L. Yung (2012), Atmospheric OH Response to the 11-year Solar Cycle -- Could the gap between model and observations be filled by SORCE measurements? Proc. N. Acad. Sci. - USA, under review.

Li, K.-F., M.-C. Liang, C. D. Camp, Y. L. Yung (2012), A 27-day solar cycle in the middle atmosphere from MLS/Aura measurements, in preparation.

Li, K.-F., B. Tian, D. E. Waliser and Y. L. Yung (2012), Principal Modes of High-Resolution Spectral Variability in Tropical Cloud Systems, in preparation.

Li, K.-F., X. Jiang, M.-C. Liang, and Y. L. Yung (2012), Impacts of SORCE Irradiance on the Simulation of 11-year Solar-Cycle in Total Column Ozone, Atmos. Chem. Phys. Discuss., 12, 1867-1893, doi: 10.5194/acpd-12-1867-2012.

Li, K.-F., B. Tian, D. E. Waliser, M. J. Schwartz, J. L. Neu, J. R. Worden, and Y. L. Yung (2012), Vertical structure of MJO-related subtropical ozone variations from MLS, TES, and SHADOZ data, Atmos. Chem. Phys., 12, 425-436.

Jiang, X., D. E. Waliser, W. S. Olson, W.-K. Tao, T. S. L'Ecuyer, S. Shige, K.-F. Li, Y. L. Yung, S. Lang, and Y. N. Takayabu (2011), Vertical diabatic heating structure of the MJO: Intercomparison between recent reanalyses and TRMM estimates, Mon. Wea. Rev., 139, 32083223.

Li, K.-F., B. Tian, D. E. Waliser, Y. L. Yung (2010), Tropical mid-tropospheric CO2 variability driven by the Madden-Julian oscillation, Proc. Nat. Acad. Sci. - USA, 107(45), 19171-19175.

Li, K.-F., K. Pahlevan, J. L. Kirschvink, Y. L. Yung (2009), Atmospheric Pressure as a Natural Climate Regulator of a Terrestrial Planet with a Biosphere, Proc. Nat. Acad. Sci. - USA, 106(24), 9576-9579. WiredScience; ScienceNews; Nature Highlights; Caltech Press Releases; Environmental Research Web; TIME Magazine

Natraj, V., K.-F. Li and Y. L. Yung (2009), Rayleigh Scattering in Planetary Atmospheres: Corrected Tables Through Accurate Computation of X and Y Functions, Astrophys. J., 691, 1909.

Liang, M.-C., K.-F. Li, R.-L. Shia, and Y. L. Yung (2008), Short-period solar cycle signals in the ionosphere observed by FORMOSAT-3/COSMIC, Geophys. Res. Lett., 35, L15818, doi:10.1029/2008GL034433.

Cheung, R., K. F. Li, S. Wang, T. J. Pongetti, R. P. Cageao, S. P. Sander, and Y. L. Yung (2008), Atmospheric hydroxyl radical (OH) abundances from ground-based ultraviolet solar spectra: an improved retrieval method, Appl. Opt., 47(33), 6277-6284, doi:10.1364/AO.47.006277.

Li, K.-F., R. P. Cageao, E. M. Karpilovsky, F. P. Mills, Y. L. Yung, J. S. Margolis, and S. P. Sander (2005), OH column abundance over Table Mountain Facility, California: AM-PM diurnal asymmetry, Geophys. Res. Lett., 32, L13813, doi:10.1029/2005GL022521.

Li, K. F. (2006). Possible observational effects of extra forces in extra dimensional models. Thesis (Master of Philosophy). The Chinese University of Hong Kong, Hong Kong.