Browsing by Author "Lu, Chen"

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Open Access
Projecting Regional Climate Change through Statistical and Dynamical Downscaling Techniques
(Faculty of Graduate Studies and Research, University of Regina, 2017-08) Lu, Chen; Huang, Guo (Gordon); An, Chunjiang; wu, Peng; Zeng, Fanhua
Climate change has comprehensive and profound influences on every aspect of the natural and human systems such as the hydrological systems, ecosystems, food systems, infrastructure, human health and livelihoods. Not only are the impacts diverse in expressions, they are also geographically heterogeneous. In order to manage and reduce the risk of climate change impacts with the consideration of its heterogeneity, region-specific mitigation and adaptation strategies needs to be taken. The foundation of regional climate impact studies and the subsequent design of regional mitigation and adaption strategies is the projection of future regional or local climate. To this end, this study focuses on exploring how the regional or local climate is affected in the context of global warming, using both statistical and dynamical downscaling techniques. Specifically, (1) the stepwise cluster analysis (SCA) is used for downscaling of the local climate of the City of Toronto, and (2) the RegCM is used for the dynamical downscaling of the regional climate over China. From the statistical downscaling study of the temperature of the City of Toronto, the capability of the SCA for capturing the relationship between the global atmospheric variables and the local surface variables is demonstrated. Geophysical Fluid Dynamics Laboratory (GFDL) data of the historical period, representative concentration pathways (RCP4.5 and RCP8.5) is used for the projection of the future local climate. The results show that the future daily maximum, mean and minimum temperature (Tmax, Tmean, and Tmin) of the City of Toronto is likely to increase, with the speed of increase higher under RCP8.5 than under RCP4.5. The Tmin is projected to have a slightly larger increase than the Tmax. Significant increasing trend can be found under both scenarios for the entire 80- year future periods for Tmax, Tmean, and Tmin. In terms of the seasonal variations, large temperature increase happens in summer under RCP4.5, while it happens in both summer and winter under RCP8.5. In terms of the extreme climate, the occurrence of extreme cold weather will decrease and extreme warm weather increase, whether the index is percentile-based or value-based. The diurnal temperature range will decrease, which is consistent with the aforementioned conclusions. Potentially beneficial for the agriculture, the growing season length is projected to increase for the City of Toronto. For the dynamical downscaling study of the regional climate over China, the results indicate that RegCM is capable of reproducing the spatial distributions of temperature and precipitation over China. Particularly, the high temperature centers in the Tarim Basin and the Sichuan Basin, which GFDL fails to capture, are reasonably represented by RegCM. RegCM also demonstrates good performance in eliminating the unrealistic high-precipitation center between the Tibetan Plateau and the Sichuan Basin produced by GFDL. Future projections from RegCM suggest that an increase of 2 °C in mean temperature is expected in China by the end of the twenty-first century under RCP4.5 while an increase of 4 °C would be seen under RCP8.5. The Tibetan Plateau is likely to expect the largest increase in temperature in China. The magnitude of increase in minimum temperature is apparently higher than that of mean and maximum temperature. In comparison, the annual total precipitation over China is projected to increase by 7% by the end of the twenty-first century under RCP4.5 and by 9% under RCP8.5. The projected changes in precipitation show apparent spatial variability due to the influences of local topography and land cover/use.
Open Access
Spatiotemporal heterogeneity in precipitation and moisture transport over China and their connections with anthropogenic emissions and natural variability
(Faculty of Graduate Studies and Research, University of Regina, 2022-09) Lu, Chen; Huang, Guo (Gordon); Zhu, Hua; Ng, Kelvin Tsun Wai; Deng, Dianliang; Chen, Zhi
In this dissertation research, the following scientific questions are explored: (i) Has the probability distribution of precipitation over China undergone variations since the midtwentieth century? (ii) How are the above changes related to the modes of climate variability? (iii) Can these changes be attributed to anthropogenic behaviors? (iv) What are the mechanisms for these changes in terms of moisture transport and recycling? Specifically, through quantile regression, the quantile trends in monthly precipitation anomalies over China, as well as the individual and combined quantile effects of teleconnection patterns, are examined. The results show that the quantile trends exhibit apparent seasonal variations, with a greater number of stations showing trends in winter, and larger average magnitudes of trends at nearly all quantile levels in summer. The effects of El Niño–Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), and Pacific Decadal Oscillation (PDO) exhibit evident variations with respect to the quantile level. Spatial clusters are subsequently identified based on the quantile trends, and the individual and combined effects from the teleconnection patterns are further investigated from the perspective of moisture budget. Seven spatial clusters with distinct seasonal quantile trends can be identified; three of them are located in southeastern China and are characterized by increasing trends in summer and winter precipitation. Summer precipitation over this region is positively influenced by ENSO and negatively influenced by NAO, with the former affecting both the dynamic and thermodynamic components of vertically integrated moisture divergence and the latter affecting only the dynamic component. The interaction effect of ENSO and NAO on summer precipitation anomalies in extremely-wetter-than-normal months is statistically significant. The influences of anthropogenic greenhouse gas and aerosol emissions on the probability distribution of daily precipitation over China are explored through a formal detection and attribution analysis. It is found that the increasing trends in winter precipitation at high and extremely high quantile levels, as well as that in spring precipitation at all quantile levels, can be attributed to the effects of historical (ALL) or anthropogenic (ANT) forcing. The effect of anthropogenic greenhouse gas forcing (GHG) is evident over the domain, to which the increasing precipitation trends at all quantile levels in all seasons can be attributed; this effect can be separated from that of anthropogenic aerosol forcing (AER) for winter precipitation trends at high and extremely high quantile levels, and for spring, summer, and autumn trends at low quantile levels. Through integrating detection and attribution analysis and moisture tracking into one framework, the anthropogenic influence on the moisture source-receptor relationship over China is investigated. The subdomains of China can be grouped into 3 categories according to the major moisture sources, which are regions mainly dependent on (a) oceanic sources, (b) external terrestrial sources, and (c) local recycling. It is found that the GHG forcing, in general, favor reduced moisture contributions from oceanic sources to the west of the domain in winter and enhanced those from the ones to the east of the domain in both winter and summer for regions in the first category. Under the GHG scenario, moisture contributions from external terrestrial sources are reduced in summer for subdomains in the first category and show a shift from the north to the south for other regions; under the AER scenario, the opposite case can be observed. Local recycling is generally enhanced in summer under both GHG and AER scenarios, with an exception for the regions in the first category, which exhibit reduced local recycling under the GHG forcing.