Title: Ensemble Projection of City-Level Temperature Extremes with Stepwise Cluster Analysis
Journal: Climate Dynamics
Abstract: Climate change can cause property damage and deaths in cities. City-scale climate projections are essential for making informed decisions towards climate change mitigation and adaptation at city levels. This study aims at developing ensemble projections of temperature extremes at the city-level and quantifying the contributions of various factors to the resulting uncertainty of the ensemble projections. The city of Toronto will be used here as an example to demonstrate the effectiveness of the proposed research framework. In particular, the stepwise cluster analysis (SCA) model will be used to perform climate downscaling to three GCM datasets (GFDL, IPSL, and MPI) under three emission scenarios (RCP2.6, RCP4.5, and RCP8.5) in order to generate city-level climate projections for the city of Toronto. The SCA model is demonstrated to be capable of capturing the inter- and intra-annual variations of the daily maximum, mean, and minimum temperatures in the studied city. The results suggest that mean temperatures in Toronto are projected to increase at the rate of 0.15 and 0.5 °C/decade under RCP4.5 and RCP8.5, respectively, while no significant warming trend is detected for RCP2.6. In terms of temperature extremes, extreme warm events are projected to increase while extreme cold events decrease under all emission scenarios. The decrease in the heating demand is two to four times larger than the increase in the cooling demand, indicating a decrease in the city’s total energy use. The projected warming might be beneficial for the urban growers because of the significant increases in the growing season length and growing degree days; however, the residents of the city of Toronto are likely to experience simultaneous increases in the intensity, duration, and frequency of heatwave events in future summers. Because of the warming, coldwave events in winters are likely to become less frequent and be shorter in duration, but their intensity is expected to increase significantly. Through decomposition of the resulting uncertainty of the ensemble projections, emission scenario is found to be the dominant factor for the uncertainty associated with urban climate projection.
Title: Vine Copula Ensemble Downscaling for Precipitation Projection Over the Loess Plateau Based on High‐Resolution Multi‐RCM Outputs
Journal: Water Resources Research
Abstract: A vine copula‐based ensemble downscaling (VCED) framework is proposed to jointly downscale the projected precipitation from multiple regional climate models (RCMs). This approach can effectively reduce the biases inherent to precipitation projections from different RCMs and thus provide more reliable ensemble projections. The proposed approach was applied to RCM projections over the Loess Plateau of China, which features complex topography and various climatic zones. Precipitation projections from 7 RCMs were used, and 21 sets of downscaling results were obtained. The performance of the VCED in reproducing historical precipitation across the Loess Plateau was evaluated using mean absolute error (MAE), the Taylor diagram, and the rank histogram (RH). The proposed VCED approach was found to be more effective than quantile mapping and bivariate copula methods in achieving robust precipitation projections. Overall flat RH diagrams indicate that the ensemble prediction and observations have strong consistency in distribution. Future precipitation changes of two 30‐year periods (i.e., the 2050s and 2080s) under two Representative Concentration Pathway (RCP) scenarios (RCP 4.5 and RCP 8.5) over the Loess Plateau were then analyzed after postdownscaling processes. The results show that the average annual precipitation over the Loess Plateau may increase by 8.4%–11.4% under the RCP 4.5 scenario and by 9.3%–17.5% under RCP 8.5. The projected precipitation in the south‐central parts of the Loess Plateau would be significantly reduced whereas those of the other parts be significantly increased.
The following paper about projecting city-level temperature extremes has recently been accepted for publication by Climate Dynamics.
Lu, C., G. Huang, X. Wang, and L. Liu. Ensemble projection of city-level temperature extremes with stepwise cluster analysis. Climate Dynamics, accepted on January 11, 2020.
More details will come soon once the paper is published.
The following paper about future precipitation projection over the Loess Plateau, China has recently been accepted for publication by Water Resources Research.
Sun, C., G. Huang, Y. Fan, X. Zhou, C. Lu, and X. Wang. Vine copula ensemble downscaling for precipitation projection over the Loess Plateau based on high-resolution multi-RCM outputs. Water Resources Research, accepted on December 5, 2020.
More details will come soon once the paper is published.
Title: Spatiotemporal patterns of future temperature and precipitation over China projected by PRECIS under RCPs
Journal: Atmospheric Research
Abstract: In this study, the spatiotemporal patterns of future temperature and precipitation changes over China are explored with the regional climate model PRECIS at two horizontal resolutions (25 km and 50 km). The gauge-based temperature (CN05.1) and precipitation data (APHRODITE) are used to validate the performance of PRECIS. The results show that PRECIS has better performance in reproducing the present climatology in spatial distribution and annual cycle than its driving GCM, particularly in some cold months and the high latitude regions, though the simulation is worse in precipitation over the high-cold Tibet Plateau of China. Compared to the observation, the difference between the simulations at 50 km (R50) and 25 km (R25) resolutions is very small. Projected annual temperature and precipitation will increase gradually with the time over most regions of China, especially in the late of this century. The results from R25 show the mean temperature over China will increase by ~1.3(1.5) °C in the early century, 2.7(3.5) °C in the middle century, and 3.5(5.9) °C in the late century under RCP4.5(8.5), which are all smaller than the values from its driving GCM. Most models project that the temperature will have more increases in cold months (i.e., January to March) while the southeastern region will show smaller changes relative to other sub-regions. Additionally, China will receive more precipitation from the overall trend, but the increased amplitude among different concentration scenarios and models are different obviously. The projections from R25 show more precipitation than the R50 and their driving GCM. For instance, the annual mean precipitation will increase by ~15(22) % for GCM, ~20(33) % for R50 and ~ 22(37) % for R25 in the late of this century over the entire China under RCP4.5(8.5). The annual cycles of precipitation at sub-regions also show a distinct variation. The changes are smaller in October or November than other months for the southeastern and central regions, while the percentage change is larger in the northwest, which will alleviate the pressure of water shortage in this arid region of China.