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
DOI: https://doi.org/10.1016/j.atmosres.2020.105303
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.
The following paper about the spatiotemporal patterns of future temperature and precipitation over China has recently been accepted for publication by Atmospheric Research.
Wu, Y., J. Guo, H. Lin, J. Bai, and X. Wang. Spatiotemporal patterns of future temperature and precipitation over China projected by PRECIS under RCPs. Atmospheric Research, accepted on October 6, 2020.
More details will come soon once the paper is published.
Title: Factorial Sensitivity Analysis of Physical Schemes and Their Interactions in RegCM
Journal: Journal of Geophysical Research: Atmospheres
DOI: https://doi.org/10.1029/2020JD032501
Abstract: It is well known that the choices of physical schemes in Regional Climate Models (RCMs) can cause considerable uncertainties in future climate projections. In this study, a factorial sensitivity analysis method has been proposed to screen out statistically significant schemes and interactions, which assists in selecting the optimized physical scheme combination from a long‐term perspective with affordable computational costs. The Regional Climate Model (RegCM) is used as an example to illustrate how the approach works. In detail, all schemes are fully tested through 120 experimental runs based on a factorial design; the contributions and statistical significance (P value) of individual schemes and their interactions to temperature, precipitation, wind speed, and wind direction are then quantified. The performance of the proposed approach is then demonstrated through a case study of Canada. The results indicate that there exist considerable spatial and temporal simulated variations associated with different scheme combinations. It is also suggested that individual physical schemes have dominant influences on simulated variations, but some effects explained by their interactions are statistically significant and thus cannot be neglected. In particular, the planetary boundary layer (PBL) scheme, moisture scheme, and land surface model are found to be the dominant factors affecting the uncertainties of temperature, precipitation, and wind speed in future climate projections over Canada, respectively. Furthermore, the potential relationships between the vegetation cover conditions and the sensitivity of physical schemes are explored. The proposed approach is an attempt to analyze the sensitivity influenced by not only individual physical schemes and also their multilevel interactions.